COMMUNITY RESPONSE TO USE OF
PRESCRIBED GRAZING AND TEBUTHIURON HERBICIDE
FOR RESTORATION OF SAND SHINNERY OAK COMMUNITIES
by
JENNIFER ZAVALETA, B. A.
A THESIS
IN
WILDLIFE SCIENCE
Submitted to the Graduate Faculty
of Texas Tech University in
Partial Fulfillment of the Requirements
for the Degree of
MASTER OF SCIENCE
Approved
Clint Boal
Chair of Committee
David Haukos
Robert Cox
Gad Perry
Peggy Miller
Interim Dean of Graduate School
May, 2012
Copyright 2012
Jennifer Zavaleta
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Texas Tech University, Jennifer Zavaleta, May 2012
ACKNOWLEDGMENTS
I would like to acknowledge Dr. Dave Haukos for taking a risk and asking me to be
his graduate student even though my background was nontraditional. It also speaks highly of
a mentor who can foster a relationship and coach me through a thesis from a distance. Thank
you for being amenable to dinner-time phone calls and late-night text messages.
Dr. Clint Boal, thank you for accepting me into your lab and affording me
opportunities to go to conferences and present my research. Thank you also for your
mentorship and sending funny emails to keep us all sane. Dr. Cox, thank you for being
available to talk to me and help me when I was in a pinch and frustrated with analysis. Dr.
Perry, thank you for encouraging me to come to Texas Tech and serving on my committee.
I would also like to acknowledge the folks at Weaver Ranch for facilitating this study,
especially, Jim Weaver, Willard Heck, and Charles Dixon. Your leadership and commitment
to restoring shinnery oak habitat is admirable. This was a lengthy project that took dedication
and the help of many field technicians including Apple Wood, Tish McDaniel, and Robert
Martin.
None of this research would be possible without the financial and logistical support of
these funding institutions: Grasslands Charitable Trust, Great Plains Landscape Conservation
Cooperative, The Nature Conservancy, New Mexico Game and Fish, Texas Parks and
Wildlife, Texas Tech Department of Natural Resources Management, US Fish and Wildlife,
and USGeological Survey.
On a more personal note, I would like to thank my labmates, especially Blake
Grisham and Matt VanLandeghem for their incredible patience, brilliant intellect, and
passion for data analysis. I would like to thank my Lubbock-support network, Chris Cheek
and Matthew Trawick, for encouraging me when I was frustrated and never distracting me
from working on my thesis. Finally, I would like to thank my family for always supporting
me and being proud of who I am.
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Texas Tech University, Jennifer Zavaleta, May 2012
TABLE OF CONTENTS
ACKNOWLEDGMENTS………………………………………………………………...…iii
ABSTRACT…………………………………………………………………………….……vi
LIST OF TABLES……………………………………………………………………………ix
LIST OF FIGURES…………………………………………………………………………xiv
I. A LITERATURE REVIEW
Introduction………………………………………………………………………....…1
Literature Cited…………………………………………………………………...….16
Tables ………………………………………………………………………………..20
Figures……………………………………………………………………………......22
II. EFFECTS OF TEBUTHIURON HERBICIDE AND GRAZING TREATMENTS ON
SOIL MOISTURE, PLANT COMPOSITION, PLANT STRUCTURE. AND PLANT AND
SEED PRODUCTION
Introduction………………………………………………………………………..…24
Methods………………………………………………………………………………28
Results……………………………………………………………………………......35
Discussion……………………………………………………………………………42
Literature Cited………………………………………………………………….…...53
Tables………………………………………………………………………………...57
Figures………………………………………………………………………………..70
III. EFFECTS OF TEBUTHIURON HERBICIDE AND GRAZING TREATMENTS ON
MAMMAL, HERPTILE, AND INVERTEBRATE COMMUNITIES
Introduction…………………………………………………………………………..95
Methods………………………………………………………………………………98
Results………………………………………………………………………………103
Discussion…………………………………………………………………………..111
Literature Cited…………………………………………………………………......121
Tables ……………………………………………………………………………....124
Figures………………………………………………………………………………140
IV. TEBUTHIURON HERBICIDE AND GRAZING AS A MEANS OF RESTORING
SHINNERY OAK GRASSLANDS
Introduction………………………………………………………………………....156
Methods……………………………………………………………………………..160
Results………………………………………………………………………………163
Discussion…………………………………………………………………………..165
Literature Cited……………………………………………………………………..168
Tables ………………………………………………………………………………170
Figures……………………………………………………………………………....182
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Texas Tech University, Jennifer Zavaleta, May 2012
APPENDICES
$LIST OF PLANTS FOUND IN ROOSEVELT COUNTY, NM ACCORDING TO
ECOLOGICAL SITE DESCRIPTION………………..…………………….188
%LIST OF ALL SPECIES FOUND IN THE STUDY TESTING THE EFFECTS OF
TEBUTHIURON AND GRAZING IN ROOSEVELT COUNTY,
NM………………………………………………..………………………….190
&LIST OF REPTILES AND AMPHIBIANS FOUND FROM 2002-2010 IN A STUDY
TESTING THE EFFECTS OF TEBUTHIURON AND GRAZING IN
ROOSEVELT COUNTY, NM………………………………………………192
'LIST OF MAMMALS FOUND FROM 2002-2010 IN A STUDY TESTING THE
EFFECTS OF TEBUTHIURON AND GRAZING IN ROOSEVELT
COUNTY, NM……….……………………………………………………...193
(LIST OF INVERTEBRATES FOUND FROM 2003-2011 IN A STUDY TESTING
THE EFFECTS OF TEBUTHIURON AND GRAZING IN ROOSEVELT
COUNTY, NM …………………………...................................................…194
F. CHAPTER II VARIABLES DESCRIBED IN TERMS OF MEANS AND SE FOR
TREATED-GRAZED, TREATED-NON-GRAZED, NOT TREATEDGRAZED, AND NOT TREATED-NON-GRAZED PLOTS………….....…200
G. CHAPTER III VARIABLES DESCRIBED IN TERMS OF MEANS AND SE FOR
TREATED-GRAZED, TREATED-NON-GRAZED, NOT TREATEDGRAZED, AND NOT TREATED-NON-GRAZED PLOTS…………….…210
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Texas Tech University, Jennifer Zavaleta, May 2012
ABSTRACT
The sand shinnery oak (Quercus havardii) mixed-grass community is an isolated,
relict habitat located within short-grass prairie of the Southern High Plains. With the
introduction of center-pivot agriculture, unmanaged grazing, oil and gas exploration and
suppression of the natural fire regime, the vegetation composition of the shinnery oak
community has changed during the past century. While some areas have become dominated
by a monoculture of shinnery oak, the absolute amount of shinnery oak has been drastically
reduced. This is particularly disconcerting not only because native biodiversity is lost, but
also because this area is home to a number of species of conservation concern including the
lesser prairie-chicken (Tympanuchuspallidicinctus), sand dunes lizard (Sceloporus
arenicolus), and Cassin’s sparrow (Aimophia cassinii).
Land managers have used herbicides (e.g., tebuthiuron) and a variety of grazing
systems as tools to manage shinnery oak. However, very little research has been done to test
how these tools can be used to restore an altered shinnery oak-grass community to presettlement standards of species composition. This thesis tests the community response in
terms of abiotic factors; plant composition, structure and production; and mammal, herptile,
and invertebrate community responses in terms of abundance, dominance, and diversity to a
designed restoration effort from 2000-2011. The primary objectives were to (1) determine the
variable response to tebuthiuron and grazing treatments, (2) assess the temporal response of
the variables to the use of four treatment combinations over a 12-year period, and (3)
compare resultant vegetation composition to historical standards.
In Roosevelt Co, New Mexico, on the Southern High Plains, 532 ha of private land
were treated with tebuthiuron (rate of 0.60 kg/ha with dune avoidance) in 2000. The state of
New Mexico owned 518 ha of adjacent land, representing extant shinnery oak community
(experimental control). This application rate was approximately 50% of previously
recommended rates because the goal was to reduce shinnery oak to historical levels, not to
eliminate it. A moderate grazing treatment was designed to take a maximum of 50% of the
annual herbaceous production. To allow for inference beyond the study site, the experimental
design was a combined completely randomized design with a systematic application of
treatments following random assignment of initial treatment combination. The four
treatments were treated/grazed, treated/not grazed, not treated/grazed, and not treated/not
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Texas Tech University, Jennifer Zavaleta, May 2012
grazed. There were four replicates for the four treatments, totaling 16 plots. To remove the
variation of year-to-year precipitation on the effect of tebuthiuron and grazing, I first ranked
precipitation variables (based on two winter, growing and annual precipitation indices) and
then used an analysis of variance with precipitation as a covariate.
Plant and abiotic variables include soil moisture; line intercept data that was used for
percent composition of shrubs, grasses, forbs, litter, bare ground, percent shinnery oak and
sand bluestem (Andropogongerardii) grass; Robel pole heights to measure visual obstruction;
angle of obstruction to measure overhead obstruction; herbaceous production; and seed
production for dropseed species (Sporobolus spp.), bluestems (Andropogon spp.), sand
paspalum (Paspalummaritimum), and gramas (Bouteloua spp.). Small mammals and herptiles
were trapped from May to September with 800 trap nights and 960 trap nights per plot per
year from 2002-2010. Mammals were trapped with Sherman live traps and herptiles were
trapped with pitfall and funnel traps. Abundance, dominance, diversity and the three most
abundant mammals - kangaroo rat (Dipidomis ordii), spotted ground squirrel (Spermophilus
spilosoma), and pocket mouse species (Perognathus spp.) - and herptiles (prairie lizard
(Sceloporus lecontei), Great Plains skink (Eumeces obsoletus), and coachwhip (Masticophis
flagellum)) were variables used in analyses. Invertebrates were collected in April and June
with a terrestrial vacuum sampler. Invertebrate abundance, biomass, and number of
taxonomic families as well as biomass of the three most abundant (grasshoppers (Acrididae),
treehoppers (Acrididae), and caterpillars (Lepidoptera larvae) were variables used in
analysis.
My results show that at relatively low levels of tebuthiuron (0.60 kg/ha) and
subsequent moderate grazing system, sand shinnery oak can be reduced and maintained at
near historical levels without reapplying tebuthiuron because the tested management
approach allowed grasses to remain competitive in the system. Over the ten years, there was
91% less shinnery oak in untreated areas.The removal of shinnery oak made environmental
soil moisture more available for grasses and forbs to germinate and grow. Indeed, grasses
increased by 149% and forbs increased by 257% in treated areas as compared to untreated
areas throughout the study period. In terms of visual obstruction, there was both an herbicide
and grazing effect in April such that visual obstruction increased by 30% in treated areas as
compared to untreated and decreased by 6.5% in grazed areas as compared to non-grazed
areas. Similarly, there was an herbicide and grazing interaction effect such that treated areas
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Texas Tech University, Jennifer Zavaleta, May 2012
had a 14% decrease in overhead obstruction in grazed areas and non-treated areas had only
10% less in grazed areas as compared to non-grazed areas. These changes in plant
composition and structure increase biodiversity such that there are more available niches to
fill. The results from mammal, herptile, and invertebrate data indicated that species react on
an individual basis to herbicide and grazing combinations, so the treatments yielded mixed
results.
I found no significant herbicide effect of overall abundance of small mammals.
However, there was a significant grazing effect such that there was 23% more abundance of
small mammals in grazed areas as compared to non-grazed areas, which was likely driven by
kangaroo rats. In terms of herptile abundance, there was an interaction effect such that more
lizards were found in treated/non-grazed and not treated/grazed areas. This mixed result
indicates that species act individually in response to herbicide and grazing. Invertebrates, for
the most part, responded positively to herbicide treatment and negligibly in terms of grazing,
presumably due to increases in forbs.
Areas that were treated with tebuthiuron and had moderate grazing statistically
reached historical standards only during one year, but showed trends that were comparable to
historical standards throughout the study compared to other treatment combinations. The
largest difference between treated areas and historical standards was that treated areas had
more forbs. This may not necessarily be interpreted as a bad thing because increase in
invertebrates due to forb presence indicates good habitat quality and increases food sources
for animals higher on the food chain.
With low rates of tebuthiuron (0.60 kg/ha) and moderate levels of grazing, shinnery
oak communities can approach historical. With moderate levels of grazing, shinnery oak will
not need to be re-treated as grasses remain competitive in the system. With the removal of
shinnery oak, there is increased soil moisture such that grasses and forbs can establish. The
change from a shrub monoculture to a mixed-grass prairie changes the plant composition and
structure and provides more niches for invertebrates, mammals and herptiles to fill.
Treatment with tebuthiuron at low doses is the first step in managing shinnery oak
communities; however, given the incredible, absolute loss of shinnery oak managers should
be cautious about treating all shinnery-oak dominated areas.
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Texas Tech University, Jennifer Zavaleta, May 2012
/,672)7$%/(6
1.1 Vegetation composition and cover means from control and tebuthiuron-treated
area vegetation transects in Roosevelt County, New Mexico, before and
after 2000 tebuthiuron application. Pre-application data were collected in
2000; post-application data were collected in 2001………………………..20
1.2 2001 grass seed production on control and treatment areas in eastern New
Mexico, after tebuthiuron application……………………………………...21
2.1 List of top ranked AIC models for precipitation, W, precipitation effect’s F and P values, r2, and trend of precipitation regression for soil moisture, plant
composition, plant structure, and plant and seed production. Data were
collected in 16 experimental plots consisting of the combinations of (1)
tebuthiron (herbicide) treated – grazed, (2) tebuthiron treated – non-grazed,
(3) nontebuthiron treated – grazed, and (4) non tebuthiron treated – nongrazed in eastern New Mexico from 2000-2010…………………………...57
2.2 List of ranked AIC models for precipitation, AICc, Δ AIC, and W for soil
moisture in April and June. Data were collected in 16 experimental plots
consisting of the combinations of (1) tebuthiron (herbicide) treated – grazed,
(2) tebuthiron treated – non-grazed, (3) nontebuthiron treated – grazed, and
(4) non tebuthiron treated – non-grazed in eastern New Mexico from 20002010………………………………………………………………………...58
2.3 List of herbicide, grazing, and interaction effect for soil moisture in April and
June that were collected in 16 experimental plots consisting of the
combinations of (1) tebuthiron (herbicide) treated – grazed, (2) tebuthiron
treated – non-grazed, (3) nontebuthiron treated – grazed, and (4) non
tebuthiron treated – non-grazed in eastern New Mexico from 2001-2010...59
2.4. Summary of percent cover variables (grass, shrub, forb, litter, and bare
ground) and their relationship with winter precipitation index, which was
selected for the MANOVA following the trends of other plant variables.
Data are from 16 experimental plots consisting of the combinations of (1)
tebuthiron (herbicide) treated – grazed, (2) tebuthiron treated – non-grazed,
(3) nontebuthiron treated – grazed, and (4) non tebuthiron treated – nongrazed in eastern New Mexico from 2002-2010…………………………...60
2.5 Overall MANCOVA results for percent cover and individual ANCOVA
results for percent cover with associated F and P values. Data are from 16
experimental plots consisting of the combinations of (1) tebuthiron
(herbicide) treated – grazed, (2) tebuthiron treated – non-grazed, (3)
nontebuthiron treated – grazed, and (4) non tebuthiron treated – non-grazed
in eastern New Mexico from 2001-2010…………………………………..61
2.6. List of ranked AIC models for precipitation, AICc, Δ AIC, and W for
presence of shinnery oak and bluestem species. Data were collected in 16
experimental plots consisting of the combinations of (1) tebuthiron
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Texas Tech University, Jennifer Zavaleta, May 2012
(herbicide) treated – grazed, (2) tebuthiron treated – non-grazed, (3)
nontebuthiron treated – grazed, and (4) non tebuthiron treated – non-grazed
in eastern New Mexico from 2000-2010………………………………….62
2.7 List of herbicide, grazing, and interaction effect for presence of shinnery oak
and sand bluestem that were collected in 16 experimental plots consisting of
the combinations of (1) tebuthiron (herbicide) treated – grazed, (2)
tebuthiron treated – non-grazed, (3) nontebuthiron treated – grazed, and (4)
non tebuthiron treated – non-grazed in eastern New Mexico from 20012010…….…………………………………………………………………..63
2.8. List of ranked AIC models for precipitation, AICc, Δ AIC, and W for visual
and overhead obstruction in April and June. Data were collected in 16
experimental plots consisting of the combinations of (1) tebuthiron
(herbicide) treated – grazed, (2) tebuthiron treated – non-grazed, (3)
nontebuthiron treated – grazed, and (4) non tebuthiron treated – non-grazed
in eastern New Mexico from 2000-2010…………………………………..64
2.9. List of herbicide, grazing, and interaction effect for measures of visual and
overhead obstruction in April and June in 16 experimental plots consisting
of the combinations of (1) tebuthiron (herbicide) treated – grazed, (2)
tebuthiron treated – non-grazed, (3) nontebuthiron treated – grazed, and (4)
non tebuthiron treated – non-grazed in eastern New Mexico from 20002010………………………………………………………………………...65
2.10 List of ranked AIC models for precipitation, AICc, Δ AIC, and W for
herbaceous and seed production. Data were collected in 16 experimental
plots consisting of the combinations of (1) tebuthiron (herbicide) treated –
grazed, (2) tebuthiron treated – non-grazed, (3) nontebuthiron treated –
grazed, and (4) non tebuthiron treated – non-grazed in eastern New Mexico
from 20002010………………………………………………………………………...66
2.11 List of herbicide, grazing, and interaction effect for measures of herbaceous
and seed production, specifically sand dropseed, bluestem, sand paspalum,
and blue grama seed production. Herbaceous production measurements were
taken from 2002-2010 and seed production was taken from 2004-2009. Data
were collected in 16 experimental plots consisting of the combinations of (1)
tebuthiron (herbicide) treated – grazed, (2) tebuthiron treated – non-grazed,
(3) nontebuthiron treated – grazed, and (4) non tebuthiron treated – nongrazed in eastern New
Mexico…………………………………………………………………….67
2.12 List of ranked AIC models for precipitation, AICc, Δ AIC, and W for seed
production of sand dropseed, bluestem, sand paspalum, and blue grama.
Data were collected in 16 experimental plots consisting of the combinations
of (1) tebuthiron (herbicide) treated – grazed, (2) tebuthiron treated – nonix
Texas Tech University, Jennifer Zavaleta, May 2012
grazed, (3) nontebuthiron treated – grazed, and (4) non tebuthiron treated –
non-grazed in eastern New Mexico from 2000-2010……………………...68
3.1 Number of captured mammals during 800 trap nights each year from June to
September from 2002-2010 (with 600 trap nights in 2005 and 2010) in 16
experimental plots consisting of the combinations of (1) tebuthiuron
(herbicide) treated – grazed, (2) tebuthiuron treated – non-grazed, (3) nontebuthiuron treated – grazed, and (4) non-tebuthiuron treated – non-grazed
in eastern New Mexico…………………………………………………...124
3.2 Number of herptile species trapped for 960 trap nights a year from June to
September from 2002-2010 (with 480 trap nights in 2005 and 2010) in 16
experimental plots consisting of the combinations of (1) tebuthiuron
(herbicide) treated – grazed, (2) tebuthiuron treated – non-grazed, (3) nontebuthiuron treated – grazed, and (4) non-tebuthiuron treated – non-grazed
in eastern New Mexico…………………………………………………...125
3.3 Number of collected invertebrates by taxon group from five, 0.5 by 0.5m
samples per plot as a dependent variable in models testing of herbicide and
grazing treatments on sand shinnery oak grass communities in eastern New
Mexico from 2003-2010……………………………………………….…126
3.4 List of top ranked AIC models for precipitation, W, r2 with associated F and
P, and trend of precipitation regression for mammal data. Data were
collected in 16 experimental plots consisting of the combinations of (1)
tebuthiuron (herbicide) treated – grazed, (2) tebuthiuron treated – nongrazed, (3) non-tebuthiuron treated – grazed, and (4) non-tebuthiuron treated
– non-grazed in eastern New Mexico from 2002-2010………………..…128
3.5 List of ranked AIC models for precipitation, AICc, Δ AIC, and W for
mammal abundance, dominance (1-Simpson’s index) and diversity (Shannon’s index) that were collected in 16 experimental plots consisting of
the combinations of (1) tebuthiuron (herbicide) treated – grazed, (2)
tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated – grazed, and
(4) non-tebuthiuron treated – non-grazed in eastern New Mexico from 20022010……………………………………………………………………….129
3.6 List of herbicide, grazing, and interaction effect for measures of mammal
abundance, dominance, diversity and three most abundant species (Ord’s kangaroo rat, ground squirrel, and pocket mouse) that were captured in 16
experimental plots consisting of the combinations of (1) tebuthiuron
(herbicide) treated – grazed, (2) tebuthiuron treated – non-grazed, (3) nontebuthiuron treated – grazed, and (4) non-tebuthiuron treated – non-grazed
in eastern New Mexico from 2002-2010…………………………………130
3.7 List of ranked AIC models for precipitation, AICc, Δ AIC, and W for the three
most abundant mammals, Ord’s kangaroo rat, ground squirrel, and pocket x
Texas Tech University, Jennifer Zavaleta, May 2012
mouse. Data were collected in 16 experimental plots consisting of the
combinations of (1) tebuthiuron (herbicide) treated – grazed, (2) tebuthiuron
treated – non-grazed, (3) non-tebuthiuron treated – grazed, and (4) nontebuthiuron treated – non-grazed in eastern New Mexico from 20022010……………………………………………………………………….131
3.8 List of top ranked AIC models for precipitation, W, precipitation effect’s F and P values, r2, and trend of precipitation regression for herptile data. Data
were collected in 16 experimental plots consisting of the combinations of (1)
tebuthiuron (herbicide) treated – grazed, (2) tebuthiuron treated – nongrazed, (3) non-tebuthiuron treated – grazed, and (4) non-tebuthiuron treated
– non-grazed in eastern New Mexico from 2002-2010…………………..132
3.9 List of ranked AIC models for precipitation, AICc, Δ AIC, and W for herptile
abundance, dominance (1-Simpson’s index) and diversity (Shannon’s index)
that were collected in 16 experimental plots consisting of the combinations
of (1) tebuthiuron (herbicide) treated – grazed, (2) tebuthiuron treated – nongrazed, (3) non-tebuthiuron treated – grazed, and (4) non-tebuthiuron treated
– non-grazed in eastern New Mexico from 2002-2010…………………..133
3.10 List of herbicide, grazing, and interaction effect for measures of herptile
abundance, dominance, diversity and three most abundant species (prairie
lizard, skink, and coachwhip). There were 960 trap nights per plot per year
(in 2005 and 2010 there were only 480 trap nights. Data were from 16
experimental plots consisting of the combinations of (1) tebuthiuron
(herbicide) treated – grazed, (2) tebuthiuron treated – non-grazed, (3) nontebuthiuron treated – grazed, and (4) non-tebuthiuron treated – non-grazed
in eastern New Mexico from 2002-2010……………………………….134
3.11 List of ranked AIC models for precipitation, AICc, Δ AIC, and W for the
most abundant herptiles, which were prairie lizard, Great Plains skink, and
coachwhip. Data were collected in 16 experimental plots consisting of the
combinations of (1) tebuthiuron (herbicide) treated – grazed, (2) tebuthiuron
treated – non-grazed, (3) non-tebuthiuron treated – grazed, and (4) nontebuthiuron treated – non-grazed in eastern New Mexico from 20022010……………………………………………………………………….135
3.12 List of top ranked AIC models for precipitation, W, r2 with associated F and
P, and trend of precipitation regression for invert data. Data were collected
in 16 experimental plots consisting of the combinations of (1) tebuthiuron
(herbicide) treated – grazed, (2) tebuthiuron treated – non-grazed, (3) nontebuthiuron treated – grazed, and (4) non-tebuthiuron treated – non-grazed
in eastern New Mexico from 2003-2011……………………………..…136
3.13 List of ranked AIC models for precipitation, AICc, Δ AIC, and W for total
number of invertebrates, biomass of invertebrates, and number of
invertebrate taxonomic groups that were collected in 16 experimental plots
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Texas Tech University, Jennifer Zavaleta, May 2012
consisting of the combinations of (1) tebuthiuron (herbicide) treated –
grazed, (2) tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated –
grazed, and (4) non-tebuthiuron treated – non-grazed in eastern New Mexico
from 2003-2011…………………………………………………………..137
3.14 List of herbicide, grazing, and interaction effect for measures of invertebrate
abundance, number of invertebrate taxonomic groups, and invertebrate
biomass and the three species with the most cumulative biomass, which
were treehoppers, grasshoppers, and caterpillar larvae. Data were from a 16
experimental plots consisting of the combinations of (1) tebuthiuron
(herbicide) treated – grazed, (2) tebuthiuron treated – non-grazed, (3) nontebuthiuron treated – grazed, and (4) non-tebuthiuron treated – non-grazed
in eastern New Mexico from 2003-2011…………………………………138
3.15 List of ranked AIC models for precipitation, AICc, Δ AIC, and W for the
invertebrates with the most biomass, treehopper, grasshopper, and caterpillar
larvae. Data were collected in 16 experimental plots consisting of the
combinations of (1) tebuthiuron (herbicide) treated – grazed, (2) tebuthiuron
treated – non-grazed, (3) non-tebuthiuron treated – grazed, and (4) nontebuthiuron treated – non-grazed in eastern New Mexico from 20032011……………………………………………………………………….139
4.1 Chi-square values for comparing percent cover shrub, grass, and forb for each
plot every year to historical standards of shrub (15%), grass (80%), and forb
(5%). Data were collected in 16 experimental plots consisting of the
combinations of (1) tebuthiron (herbicide) treated – grazed, (2) tebuthiron
treated – non-grazed, (3) nontebuthiron treated – grazed, and (4) non
tebuthiron treated – non-grazed in eastern New Mexico from 2002-2010.
The critical value for a significant chi-squared test with 2 degrees of
freedom is 5.991. So values less than 5.999 indicate there is no difference
with historical standards………………………………………………….170
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Texas Tech University, Jennifer Zavaleta, May 2012
LIST OF FIGURES
1.1.Current range of shinnery oak grassland across the southwest from Peterson
and Boyd 1998……………………………………………………………..22
1.2 Study area in sand shinnery oak habitats of eastern New Mexico, showing
application of tebuthiuron and grazing treatments that were applied in an
assessment of restoration of habitats during 2000-2012…………………...23
2.1 Regression of June and April soil moisture and winter precipitation from a
study of sand shinnery oak grass communities in eastern New Mexico from
2002-2010………………………………………………………………….69
2.2 Soil moisture in April as a dependent variable in models testing the effect of
herbicide and grazing treatments in sand shinnery oak grass communities in
eastern New Mexico from 2001-2010 (missing data 2002)……………..…70
2.3. Soil moisture in June as a dependent variable in models testing the effect of
herbicide and grazing treatments in sand shinnery oak grass communities in
eastern New Mexico from 2001-2010 (missing data 2002 and 2008)……..71
2.4 Percent composition of shrubs as a dependent variable in models testing the
effect of herbicide and grazing treatments in sand shinnery oak grass
communities in eastern New Mexico from 2002-2010…………………….72
2.5 Percent composition of grass as a dependent variable in models testing the
effect of herbicide and grazing treatments in sand shinnery oak grass
communities in eastern New Mexico from 2002-2010…………………….73
2.6 Percent composition of forbs as a dependent variable in models testing the
effect of herbicide and grazing treatments in sand shinnery oak grass
communities in eastern New Mexico from 2002-2010…………………….76
2.7 Percent composition of litter as a dependent variable in models testing the
effect of herbicide and grazing treatments in sand shinnery oak grass
communities in eastern New Mexico from 2002-2010…………………….77
2.8 Percent composition of bare ground as a dependent variable in models testing
the effect of herbicide and grazing treatments in sand shinnery oak grass
communities in eastern New Mexico from 2002-2010…………………….78
2.9 Regression of shinnery oak and sand bluestem presence and winter
precipitation from a study of sand shinnery oak grass communities in eastern
New Mexico from 2002-2010……………………………………………...79
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2.10 Abundance of shinnery oak, in terms of percent composition, as a dependent
variable in models testing the effect of herbicide and grazing treatments in
sand shinnery oak grass communities in eastern New Mexico from 20022010………………………………………………………………………...78
2.11 Abundance of sand bluestem, in terms of percent composition, as a
dependent variable in models testing the effect of herbicide and grazing
treatments in sand shinnery oak grass communities in eastern New Mexico
from 2002-2010……………………………………………………………79
2.12 Regression of visual and overhead obstruction in April and June and winter
precipitation from a study of sand shinnery oak grass communities in eastern
New Mexico from 2002-2010……………………………………………..80
2.13 Visual obstruction in April, as measured by Robel pole, as a dependent
variable in models testing the effect of herbicide and grazing treatments in
sand shinnery oak grass communities in eastern New Mexico from 20022010………………………………………………………………………..81
2.14 Visual obstruction in June, as measured by Robel pole, as a dependent
variable in models testing the effect of herbicide and grazing treatments in
sand shinnery oak grass communities in eastern New Mexico from 20022010………………………………………………………………………...82
2.15 Overhead obstruction in April, as measured by angle of obstruction, as a
dependent variable in models testing the effect of herbicide and grazing
treatments in sand shinnery oak grass communities in eastern New Mexico
from 2002-2010……………………………………………………………83
2.16 Overhead obstruction in June, as measured by angle of obstruction, as a
dependent variable in models testing the effect of herbicide and grazing
treatments in sand shinnery oak grass communities in eastern New Mexico
from 2002-2010……………………………………………………………84
2.17 Regression of herbaceous production, total seed production, dropseed species
seed production, sand paspalum species seed production, grama species seed
production, and bluestem species seed production and winter precipitation
from a study of sand shinnery oak grass communities in eastern New
Mexico from 2002-2010 for herbaceous production and 2004-2009 for seed
production………………………………………………………………….85
2.18 Annual herbaceous production, measured in dry weight (kg/ha) with 100
samples of 1 by 0.25m2 quadrats in each plot every year, as a dependent
variable in models testing the effect of herbicide and grazing treatments on
sand shinnery oak communities in eastern New Mexico from 20022010...............................................................................................................86
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2.19 Total seed production, measured in dry weight (kg/ha) with 100 samples of 1
by 0.25m2 quadrats in each plot every year, as a dependent variable in
models testing the effect of herbicide and grazing treatments on sand
shinnery oak communities in eastern New Mexico from 2004-2009…...…87
2.20 Sand dropseedseed production, measured in dry weight (kg/ha) with 100
samples of 1 by 0.25m2 quadrats in each plot every year, as a dependent
variable in models testing the effect of herbicide and grazing treatments on
sand shinnery oak communities in eastern New Mexico from 2004-2009.
The presence of * indicates that the mean values differ (P<0.05)…………88
2.21 Bluestem seed production, measured in dry weight (kg/ha) with 100 samples
of 1 by 0.25m2 quadrats in each plot every year, as a dependent variable in
models testing the effect of herbicide and grazing treatments on sand
shinnery oak communities in eastern New Mexico from 2004-2009……...89
2.22Paspalum species seed production, measured in dry weight (kg/ha) with 100
samples of 1 by 0.25m2 quadrats in each plot every year, as a dependent
variable in models testing the effect of herbicide and grazing treatments on
sand shinnery oak communities in eastern New Mexico from 2004-2009.
The presence of * indicates that the mean values differ (P<0.05)…………90
2.23Gramaseed production, measured in dry weight (kg/ha) with 100 samples of 1
by 0.25m2 quadrats in each plot every year, as a dependent variable in
models testing the effect of herbicide and grazing treatments on sand
shinnery oak communities in eastern New Mexico from 2004-2009. The
presence of * indicates that the mean values differ (P<0.05)……………...91
2.24 Bluestem species seed production and winter precipitation from a study of
sand shinnery oak-grass communities in eastern New Mexico from 20042009…………………………………………………………………….......92
2.25Paspalum species seed production and winter precipitation from a study of
sand shinnery oak-grass communities in eastern New Mexico from 20042009………………………………………………………………………...93
2.26Grama species seed production and winter precipitation from a study of sand
shinnery oak-grass communities in eastern New Mexico from 20042009………………………………………………………………………...94
2.27 Total seed production and winter precipitation from a study of sand shinnery
oak-grass communities in eastern New Mexico from 2004-2009…………95
3.1 Regression of mammal abundance, diversity, and dominance and winter
precipitation as well as kangaroo rat, pocket mouse and ground squirrel (800
trap nights per plot per year except 600 trap nights in 2005 and 2010) and
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winter precipitation from a study of sand shinnery oak grass communities in
eastern New Mexico from 2002-2010…………………………………..140
3.2 Mammal abundance with 800 trap nights per plot per year as a dependent
variable in models testing the effect of herbicide and grazing treatments on
sand shinnery oak grass communities in New Mexico from 2002-2010 (600
trap nights in 2005 and 2010)……………………………………………141
3.3 Mammal dominance based on the Simpson’s index of diversity with 800 trap nights per plot each year as a dependent variable in models testing of
herbicide and grazing treatments on sand shinnery oak grass communities in
eastern New Mexico from 2002-2010 (600 trap nights in 2005 and
2010)……………………………………………………………………...142
3.4 Mammal diversity based on the Shannon index of diversity with 800 trap
nights per plot each year as a dependent variable in models testing of
herbicide and grazing treatments on sand shinnery oak grass communities in
eastern New Mexico from 2002-2010 (missing data June 2002)……….143
3.5 Kangaroo rat abundance with 800 trap nights per plot each year as a
dependent variable in models testing of herbicide and grazing treatments on
sand shinnery oak grass communities in eastern New Mexico from 20022010 (600 trap nights in 2005 and 2010)…………………………………144
3.6 Ground squirrel abundance with 800 trap nights per plot each year as a
dependent variable in models testing of herbicide and grazing treatments on
sand shinnery oak grass communities in eastern New Mexico from 20022010 (600 trap nights in 2005 and 2010)………………………………....145
3.7 Pocket mouse species abundance with 800 trap nights per plot each year as a
dependent variable in models testing of herbicide and grazing treatments on
sand shinnery oak grass communities in eastern New Mexico from 20022010 (600 trap nights in 2005 and 2010)…………………………………146
3.8 Regression of herptile abundance, diversity, and dominance and winter
precipitation as well as prairie lizard, Great Plains skink, and coachwhip
(960 trap nights per plot per year except 480 trap nights in 2005 and 2010)
and winter precipitation from a study of sand shinnery oak grass
communities in eastern New Mexico from 2002-2010………………...…147
3.9 Herptile abundance with 960 trap nights per plot per year (480 trap nights in
2005 and 2010) as a dependent variable in models testing the effect of
herbicide and grazing treatments on sand shinnery oak grass communities in
New Mexico from 2002-2010…………………………………………….148
3.10 Herptile dominance based on the Simpson’s index of diversity with 960 trap
nights per plot per year (480 trap nights in 2005 and 2010) as a dependent
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Texas Tech University, Jennifer Zavaleta, May 2012
variable in models testing of herbicide and grazing treatments on sand
shinnery oak grass communities in eastern New Mexico from 20022010……………………………………………………………………….149
3.11 Herptile diversity based on the Shannon index of diversity with 960 trap
nights per plot per year (480 trap nights in 2005 and 2010) as a dependent
variable in models testing of herbicide and grazing treatments on sand
shinnery oak grass communities in eastern New Mexico from 20022010…………………………………………………………………….…150
3.12 Prairie lizard abundance with 960 trap nights per plot per year (480 trap
nights in 2005 and 2010) as a dependent variable in models testing of
herbicide and grazing treatments on sand shinnery oak grass communities in
eastern New Mexico from 2002-2010……………………………………151
3.13 Great Plains skink abundance with 960 trap nights per plot per year (480 trap
nights in 2005 and 2010) as a dependent variable in models testing of
herbicide and grazing treatments on sand shinnery oak grass communities in
eastern New Mexico from 2002-2010……………………………………152
3.14 Coachwhip abundance with 960 trap nights per plot per year (480 trap nights
in 2005 and 2010) as a dependent variable in models testing of herbicide and
grazing treatments on sand shinnery oak grass communities in eastern New
Mexico from 2002-2010………………………………………………….153
3.15 Regression of invertebrate abundance, biomass, and number of families and
winter precipitation as well as regressions of grasshopper, treehopper, and
caterpilars and winter precipitation from a study of sand shinnery oak grass
communities in eastern New Mexico from 2003-2010…………………...154
3.16 Total invertebrate abundance from five, 0.5 by 0.5m samples per plot as a
dependent variable in models testing of herbicide and grazing treatments on
sand shinnery oak grass communities in eastern New Mexico from 20032010……………………………………………………………………….155
3.17 Number of invertebrate taxonomic groups from five, 0.5 by 0.5m samples
per plot as a dependent variable in models testing of herbicide and grazing
treatments on sand shinnery oak grass communities in eastern New Mexico
from 2003-2010…………………………………………………………..156
3.18 Invertebrate biomass from five, 0.5 by 0.5m samples per plot as a dependent
variable in models testing of herbicide and grazing treatments on sand
shinnery oak grass communities in eastern New Mexico from 20032010……………………………………………………………………….157
3.19 Grasshopper abundance from five, 0.5 by 0.5m samples per plot as a
dependent variable in models testing of herbicide and grazing treatments on
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Texas Tech University, Jennifer Zavaleta, May 2012
sand shinnery oak grass communities in eastern New Mexico from 20032010………………………………………………………………………158
3.20 Treehopper abundance from five, 0.5 by 0.5m samples per plot as a
dependent variable in models testing of herbicide and grazing treatments on
sand shinnery oak grass communities in eastern New Mexico from 20032010………………………………………………………………………159
3.21 Caterpillar abundance from five, 0.5 by 0.5m samples per plot as a
dependent variable in models testing of herbicide and grazing treatments on
sand shinnery oak grass communities in eastern New Mexico from 20032010……………………………………………………………………….160
4.1 Annual precipitation (cm) on study site in eastern New Mexico…………...171
4.2 Summary across 2002-2010 for percent composition of shrub, grass, and forb
for treated- grazed plots in an experiment designed to examine the effects of
tebuthiuron and grazing in the shinnery oak community of eastern New
Mexico…………………………………………………………………....172
4.3 Summary across 2002-2010 for percent composition of shrub, grass, and forb
for treated- non-grazed plots in an experiment designed to examine the
effects of tebuthiuron and grazing in the shinnery oak community of eastern
New Mexico………………………………………………………………173
4.4 Summary across 2002-2010 for percent composition of shrub, grass, and forb
for untreated- grazed plots in an experiment designed to examine the effects
of tebuthiuron and grazing in the shinnery oak community of eastern New
Mexico……………………………………………………………………174
4.5 Summary across 2002-2010 for percent composition of shrub, grass, and forb
for untreated- non-grazed plots in an experiment designed to examine the
effects of tebuthiuron and grazing in the shinnery oak community of eastern
New Mexico………………………………………………………………175
4.6 Percent composition of shrub, grass, and forb for treated-grazed plots in an
experiment designed to examine the effects of tebuthiuron and grazing in the
shinnery oak community of eastern New Mexico from 2002-2010……...176
4.7 Percent composition of shrub, grass, and forb for treated-non-grazed plots in
an experiment designed to examine the effects of tebuthiuron and grazing in
the shinnery oak community of eastern New Mexico from 2002-2010….177
4.8 Percent composition of shrub, grass, and forb for untreated-grazed plots in an
experiment designed to examine the effects of tebuthiuron and grazing in the
shinnery oak community of eastern New Mexico from 2002-2010……...178
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Texas Tech University, Jennifer Zavaleta, May 2012
4.9 Percent composition of shrub, grass, and forb for untreated-non-grazed plots
in an experiment designed to examine the effects of tebuthiuron and grazing
in the shinnery oak community of eastern New Mexico from 20022010………………………………………………………………………179
4.10 Percent composition of shrub, grass, forb, bare ground and litter for treatedgrazed plots in a study looking at the effect of tebuthiuron and grazing in
sand shinnery oak-grass communities in eastern New Mexico from 20022010……………………………….…………………………………….180
4.11 Percent composition of shrub, grass, forb, bare ground and litter for treatednon-grazed plots in a study looking at the effect of tebuthiuron and grazing
in sand shinnery oak-grass communities in eastern New Mexico from 20022010……………………………….…………………………..…………181
4.12 Percent composition of shrub, grass, forb, bare ground and litter for
untreated-grazed plots in a study looking at the effect of tebuthiuron and
grazing in sand shinnery oak-grass communities in eastern New Mexico
from 2002-2010……………………………….………………………….182
4.13 Percent composition of shrub, grass, forb, bare ground and litter for
untreated-non-grazed plots in a study looking at the effect of tebuthiuron
and grazing in sand shinnery oak-grass communities in eastern New Mexico
from 2002-2010……………………………….………………………….183
4.14 Percent composition of shrub, grass, forb, bare ground and litter for
tebuthiuron treated plots in sand shinnery oak-grass communities in eastern
New Mexico from 2002-2010……………………………….……………184
4.15 Percent composition of shrub, grass, forb, bare ground and litter for untreated
plots in a study looking at the effect of tebuthiuron and grazing in sand
shinnery oak-grass communities in eastern New Mexico from 20022010……………………………….………………………………………185
4.16 Percent composition of shrub, grass, forb, bare ground and litter for grazed
plots in a study looking at the effect of tebuthiuron and grazing in sand
shinnery oak-grass communities in eastern New Mexico from 20022010……………………………………………………………………….186
4.17 Percent composition of shrub, grass, forb, bare ground and litter for nongrazed plots in a study looking at the effect of tebuthiuron and grazing in
sand shinnery oak-grass communities in eastern New Mexico from 20022010……………………………….…………………………………….187
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Texas Tech University, Jennifer Zavaleta, May 2012
CHAPTER I
A LITERATURE REVIEW
Introduction
Sand shinnery oak (Quercus havardii) communities occur across the Southern Great
Plains from western Oklahoma and northern Texas, southward to southeastern New Mexico
(Fig. 1.1). Sand shinnery oak communities comprise the nation’s largest stand of oak,
occupying 2-3 million hectares (Peterson and Boyd 1998). The oak forest is about a meter
tall and made up of ancient plants, most of which are hundreds or thousands of years old.
Historically, sand shinnery oak co-dominated the plant community in association with midand tall grasses that typically grew higher than the sand shinnery oak (Peterson and Boyd
1998). These plant communities are considered isolated relict communities surrounded by
short-grass prairie of the High Plains (Smythe and Haukos 2009).
Sand shinnery oak grasslands are ecologically important to providing habitat for
many species of conservation concern. In particular, numerous grassland bird species with
declining population trends (Peterjohn and Sauer 1999) occupy sand shinnery oak grassland
communities. Perhaps best known among these is the lesser prairie-chicken (Tympanuchus
pallidicinctus), considered an indicator species for the region and also a candidate for
protection under the Endangered Species Act (Smythe and Haukos 2009; Federal Register
2010). Conservation efforts for the lesser prairie-chicken and other grassland birds are
largely contingent on the ability to restore historical habitats.
The current landscape in eastern New Mexico has dramatically changed during the
past 100 years; habitat loss has occurred through degradation and fragmentation with the
introduction of row-crop agriculture, fire suppression, and oil and gas exploration.
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Texas Tech University, Jennifer Zavaleta, May 2012
Furthermore, unmanaged, continuous livestock grazing has replaced the historical ecological
drivers of seasonal grazing by bison (Bison bison) and recurrent fire. These changes in land
use have increased the proportion of shrubs in plant communities and reduced the total area
of the shinnery oak grassland, but not the absolute area of shrubs across much of the region
(Peterson and Boyd 1998). In many areas, due to anthropogenic impacts, sand shinnery oak
has become a monoculture, which has led to a decline of floral and faunal diversity.
Although sand shinnery oak is not considered an invasive plant, it is an effective water
gatherer and has the potential to out-compete native grasses in unmanaged, continuous
grazing systems (Peterson and Boyd 1998).
Historical accounts indicate that there may have been as much as 607,000 hectares of
shinnery oak in New Mexico (Peterson and Boyd 1998). However, with much of the
historical range being converted to monoculture grassland and croplands, Baily and Painter
(1994) considered sand shinnery oak habitat highly threatened in eastern New Mexico. To
restore and conserve the shinnery oak community in eastern New Mexico, land should be
restored to historical proportions of tall- and mid-grasses, shrubs, and forbs in these
communities. Weaver and Clements (1938) considered the sand shinnery oak forest as a postclimax community, meaning that it is no longer in a state of equilibrium. By implementing
combinations of herbicide and grazing, managers can potentially restore land to historical
standards and manage for both wildlife conservation and cattle production.
Tebuthiuron is a dry pelleted herbicide that has been used to eradicate sand shinnery
oak since 1974. Several studies have examined the application of tebuthiuron and its effects
on controlling sand shinnery oak. Researchers have also documented effects of grazing and
stocking rates in sand shinnery oak communities. However, there is no research on how the
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Texas Tech University, Jennifer Zavaleta, May 2012
herbicide treatment and grazing interact to affect the plant composition or native wildlife
species. The goal of my research was to evaluate the use of grazing management and
tebuthiuron application to restore plant assemblages to pre-settlement conditions, and the
influence of these treatments on biodiversity in sand shinnery oak grasslands. This thesis will
report the results of a twelve-year data set documenting the community response to the use of
tebuthiuron and grazing to restore the sand shinnery oak grassland of eastern New Mexico.
Objectives
Restoring sand shinnery oak communities to historical vegetation composition levels
with the use of tebuthiuron and grazing management is a relatively new approach. Shrub
control and grazing greatly affect overhead and horizontal vegetation structure, so it is
important to consider both when designing and evaluating restoration and management plans.
Livestock grazing is an important economic resource for ranchers in the area and will
continue in the future. As such, understanding how grazing and shrub control affect the
composition and structure of plant communities is essential for management
recommendations to restore and then maintain restored communities in this relict ecosystem.
My goal was to assess the effects of two treatments with two levels: tebuthiuron
(treated and not treated) and grazing (grazed and non-grazed). The variables of interest
include vegetation composition, diversity, structure, and production, and also the diversity
and relative abundance of small mammals, reptiles, amphibians, and invertebrates.
Specifically, my first objective was to compare the vegetation response from 2002-2010
herbicide and grazing treatments in terms of plant diversity, percent vertical and overhead
obstruction, seed production, and plant biomass. The second objective was to compare
relative abundance, diversity of common species of mammals, reptile, amphibian, and
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Texas Tech University, Jennifer Zavaleta, May 2012
invertebrates among treatments. My third objective was to assess the influence of herbicide
and grazing treatments on restoring the community historical standards.
Hypotheses
1. Low levels of tebuthiuron and subsequent grazing management will restore sand shinnery
oak grasslands to historical composition.
2. Restoration of sand shinnery oak grasslands will increase grass species occurrence,
biomass, and biodiversity.
3. Due to increased habitat heterogeneity, small mammals, reptiles, amphibians, and
invertebrates will increase in abundance and diversity in treated and non-grazed plots.
Historical accounts of sand shinnery oak communities
The absolute amount and proportion of shinnery oak is widely debated throughout the
literature. Garrison and McDaniel (1982) estimated 1,068,370 hectares in New Mexico.
However, this seems to be a liberal estimate considering Peterson and Boyd’s (1998) subsequent conclusionfollowing an extensive literature review of 607,000 hectares in the
entire shinnery oak range. What remains clear is that the absolute amount of shinnery oak
communities has been decreasing due to conversion into cropland and monotypic grassland.
In the last 100 years, greater than 500,000 ha of sand shinnery oak communities have been
converted in Texas and New Mexico (Peterson and Boyd 1998). The shinnery oak
community has become one of the most imperiled vegetation community types in the world
(Baily and Painter 1994, Bell et al. 2010).
Historically, USDA Soil Conservation Service (now Natural Resources Conservation
Service [NRCS]) surveys indicate that shinnery oak made up 5% to 25% of plant
composition in the pre-settlement plant community (Conner et al. 1974, Hodson et al. 1980).
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Texas Tech University, Jennifer Zavaleta, May 2012
However, other researchers claim that, historically, shinnery oak may have constituted 80%
to 90% of plant mass or ground cover in the community (Peterson and Boyd 1998). Under
grazing pressure, USDA defines shinnery oak in historical soil surveys as an “increaser,” which at the time was defined as a species that increased in percentage composition of the
community although it could be decreasing in absolute amount.
Lenfesty (1983) found that shinnery oak increased in absolute amount under grazing
pressure, which is the current definition of “increaser” (Society for Range Management 1995). However, the NRCS has not been able to support this claim with data. Moreover,
there are no data to support that shinnery oak is limited by competition with grasses, so
shinnery oak may not be increasing in absolute terms.
The NRCS and others (Herbel 1979, Herndon 1981, Lenfesty 1983, York and DickPeddie 1979) claim that shinnery oak invades over-grazed rangeland (Peterson and Boyd
1998). However, this is disputed given the stable existence of shinnery oak for hundreds of
years and the fact that shinnery oak expands slowly with rhizomes and rarely by seed (acorn)
germination. The assumption that shinnery oak was not a significant part of the historical
community has influenced the Bureau of Land Management (BLM) to treat 40,500 hectares
in New Mexico with herbicide (Peterson and Boyd 1998, USDI BLM 1979, BLM Roswell
District Manager letter to the Sierra Club September 24, 1991). It is reasonable to consider
that with the loss of historical ecological drivers, the increase of cattle production, and the
consequent depletion of grass production, there may be an appearance of a greater proportion
of sand shinnery oak than before in extant communities.
Weaver and Clements (1938) considered shinnery oak forests as a post-climax
community (Peterson and Boyd 1998). They attributed the extension of mid- and tallgrass
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Texas Tech University, Jennifer Zavaleta, May 2012
prairie in the region to previously wetter climates. The survival of sand shinnery oak may be
in part due to deep sands that developed during the Pleistocene drying of the Southern Great
Plains (Peterson and Boyd 1998). The environment can be harsh, with an average, though
highly variable, annual precipitation at 45.9 cm, and with average high and low temperatures
ranging from 37.4°C to 13.3°C in July and from 22.9°C to -13.1°C in January (C. Dixon,
Wildlife Plus Consulting, unpubl. data). Those species that are deep-rooted, soil-stabilizing,
and drought-tolerant are the most suited to thrive in these abiotic conditions (NRCS 2011).
The assumed historic climax plant community was a mixture of tall grasses (50%),
mid-grasses (25%), short grasses (5%), shrubs (15%), and perennial forbs (5%) (NRCS
2011). See Appendix A for the common and scientific names of grasses, forbs and shrubs
that are found in Roosevelt County and Appendix B for plants found on the study site. The
amount of annual forbs found was dependent on the soil moisture in a given year (NRCS
2011). Proportions of grasses and forbs declined somewhat in dryer years, and in wet years
forb growth was profuse (NRCS 2011). The woody shrubs were more stable across years as
they are more tolerant of climatic extremes. It is, therefore, evident that shrubs were a major
component in historic plant communities (NRCS 2011).
Sand shinnery oak, yucca (Yucca glauca), purple three-awn (Aristida purpurea), fall
witchgrass (Digitaria cognata), and sand dropseed (Sporobolus contractus) made up 80% of
149 10-by-20 m, survey plots across four counties in New Mexico (Martin 1990). The
remaining 20% was comprised of fifteen additional species. Based on this, Martin (1990)
classified eight distinct vegetation communities within the region, expanding on Ahlborn’s (1980) three classifications following changes in ecological drivers of bison and fire.
Sand Shinnery Oak
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Texas Tech University, Jennifer Zavaleta, May 2012
Sand shinnery oak is a slowly reproducing, short shrub with up to 100 or more aerial
shoots in shallow and deep root systems (Pettit 1986). The shrub spreads via rhizomes and
rarely by seed (acorn) germination in natural settings (Peterson and Boyd 1988). The lateral
stems can spread to form plants 3-15 m across (Muller 1951). Sears (1982) found that 73%
by weight of the roots were found in the first 30 cm of soil. However, the vertical root
system can reach depths of 4.5-6 m below the soil surface (McIlivan 1954). This root
structure makes sand shinnery oak effective at both obtaining and storing water and
preventing wind induced soil erosion (Peterson and Boyd 1998).
Water availability is a limiting factor for plant growth in sand shinnery oak
communities, but sand shinnery oak does not use more water than grasses and forbs
(Peterson and Boyd 1998). However, it begins spring growth two weeks earlier than
competing vegetation (Jones and Pettit 1980), which provides several advantages and some
disadvantages. The early spring growth means that shinnery oak has access to water earlier
so it has longer to grow roots. Another advantage is that it is a more effective light gatherer
because it develops leaves and shoots first. However, shinnery oak must deal with colder
temperatures and less predictable moisture.
Sand shinnery oak rhizomes absorb much water during wet periods, with up to 50%
of their mass being water (Peterson and Boyd 1998). Thus, the effects of drought are more
severe for grasses than on shinnery oak, which can store water and carbohydrates, has an
extensive root system and does not leaf out or can drop leaves during drought conditions to
conserve water (Galbraith 1983).
The poisonous buds of sand shinnery oak make it undesirable for livestock grazing
during spring. The phenolic compounds responsible for the toxicity in shinnery oak can lead
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Texas Tech University, Jennifer Zavaleta, May 2012
to malaise, reduced conception rates, lower weight gains, and occasional death (Jones and
Pettit 1984). This and the desire for increased grass forage for cattle production has
encouraged land managers to eradicate sand shinnery oak for the benefit of grass production.
Herbicides
Sand shinnery oak is most commonly eradicated with herbicides. Early attempts at
eradication were done with phenoxy herbicides including 2, 4-D and 2, 4, 5-T and Silvex (2(2,4,5-T) propionic acid), benzoic acids, including dicamba, and a picolenic acid, picloram
(Tordon) (Peterson and Boyd 1998). However, these herbicides usually only resulted in
temporary top kill of sand shinnery oak (Pettit 1979). In addition, the high application rates
used to kill sand shinnery oak also reduced associated grasses and forbs.
Tebuthiuron (N-[5-(1,-dimehylethyl)-1,3,4-thiadiazol-2-yl]-N,N’-dimehylurea) is a
dry pelleted herbicide currently used to control mesquite (Prosopis spp.), whitebrush
(Aloysia lyciodes), and oak (Quercus spp.). Tebuthiuron attacks the root systems of the
woody stems (Peterson and Boyd 1988). Tebuthiuron has the distinct advantages of relative
nontoxicity to non-target species, requires only one application (Scifres et al. 1981), and does
not result in an overspray, which is characteristic of liquid herbicides (Peterson and Boyd
1998). The half-life of tebuthiuron is about 360 days (U.S. Department of Energy-Bonneville
Power Administration 2000).
In a completely randomized design, Pettit (1979) applied picloram and tebuthiuron
pellets to 20 m² plots at rates of 1, 3, 5, and 7 kg/ha with three replications of each treatment.
Results from the study indicated that the herbicide rate of 7 kg/ha was much greater than
required to effectively kill oak. Pettit (1979) also concluded that herbicide application
changed species composition. Applications of tebuthiuron at 1kg/ha killed most of the sand
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Texas Tech University, Jennifer Zavaleta, May 2012
shinnery oak. However, rates greater than 1 kg/ha killed some of the better forage plants,
allowing false buffalo grass (Munroa squarrosa), an undesirable annual, to become
dominate. Picloram pellets were not as detrimental to the plant community as the tebuthiuron
at similar application rates. Plots treated with ≥3 kg/ha of picloram killed all sand shinnery oak, but did not kill all forbs and grasses were less injured. Pettit (1979) ultimately concluded
that 1-2 kg/ha of tebuthiuron could eradicate sand shinnery oak without permanently
affecting other plant species in the community.
Jones and Pettit (1984) conducted experiments with lower rates of tebuthiuron.
Tebuthiuron was applied in 0.2 kg increments from 0.2 to 1.0 kg/ha. They concluded that
treatments of >0.40 kg/ha reduced oak canopy 98% and standing crop at least 90%, while
grasses were unaffected the first year. Therefore, above-ground grass increased from 420 to
690 kg/ha as compared to the control of 140 kg/ha. Also, during drought, grasses on
untreated plots became quiescent up to 6 weeks earlier than on treated areas.
The BLM has used tebuthiuron as a management technique to eradicate shrubs. The
agency treated 40,469 hectares of shinnery oak in New Mexico with tebuthiuron in the 1980s
and early 1990s (Peterson and Boyd 1998). However, complete eradication of shrubs is
nowconsidered detrimental to biodiversity and landscape heterogeneity of the region.
Therefore, the NRCS has more recently proposed reducing shinnery oak canopy cover to less
than 40% to increase grass production with no loss of biodiversity. As such, it has
encouraged and cost-shared ranchers in eastern New Mexico to apply 0.56-0.84 kg/ha of
tebuthiuron (USDA NRCS 2000).
Tebuthiuron and Prairie Chickens
9
Texas Tech University, Jennifer Zavaleta, May 2012
Although tebuthiuron is the most effective and economically feasible way to control
sand shinnery oak (Ethridge et al. 1987), some question the ecological effectiveness of
control. Bell et al. (2010) found that tebuthiuron increased basal and canopy cover contacts
for grasses and decreased canopy cover and stem density of sand shinnery oak. They also
found direct evidence supporting thermal selection and the dependency of lesser prairiechicken broods on shinnery oak. Even though prairie-chickens selected habitat that was
treated with tebuthiuron to avoid extreme temperatures, they selected for greater amounts of
oak, irrespective of thermal cover, suggesting that sand shinnery oak is a preferred habitat.
However, other research indicates that prairie-chickens select grass to nest in, even if
the surrounding area is shinnery oak. Haukos and Smith (1989) found that of the measured
vegetation characteristics, vertical screening cover and percent overhead cover were the most
important features of selected nest sites. Of 10 female prairie-chickens radio collared in
treated areas, eight were nesting in untreated sand shinnery oak, and all nests were found in
residual grasses. Purple three-awn was the dominant vegetation species at the majority of
nest sites, followed by little bluestem (Schizachyrium scoparium) and sand bluestem
(Andropogonhallii).
After comparing successful and unsuccessful nesting sites for the lesser prairiechicken in eastern New Mexico, Riley et al. (1992) determined that female prairie-chickens
primarily used bluestem grasses as nesting cover because it commonly formed tall, wide
clumps with spreading stems that concealed nesting females from fround and overhead
predators. Basal composition of sand bluestem was greater and taller than unsuccessful nests.
Areas with >25% in composition of tall sand bluestem may offer relief from high
temperatures, strong winds, low relative humidity, and intense solar radiation common in
10
Texas Tech University, Jennifer Zavaleta, May 2012
eastern New Mexico during nesting season. Riley et al. (1992) suggested that grazing
utilization levels should be set at <25% of annual growth to allow for key forage species like
sand bluestem and little bluestem to grow tall enough to provide nesting cover. They also
suggested that nesting habitats would be improved by increasing the composition and height
of sand bluestem within potential nesting habitats.
After using radio telemetry on adults, Patten et al. (2005) also found that microhabitat
features and physiognomy, more so than floristic composition, were important for adult
survivorship of the lesser prairie-chicken. Within the shinnery oak community, occupied sites
were characterized by greater cover and density of shrubs and a higher proportion of shrubs.
On average, prairie-chickens avoided areas that were hotter, drier, and more exposed to the
wind, suggesting they perceive their habitat as patchy with regard to microclimate. So while
prairie-chickens were found in shrub heavy areas, they also need grass for nesting.
Grazing
Livestock grazing is an important factor in determining grass response to shrub
control. The shinnery oak communities coevolved with grazing of large mammals like
pronghorn (Antilocapra americana), bison, elk (Cervus canadensis), mule deer (Odocoileus
hemionus), and white-tailed deer (O. virginianus) (Peterson and Boyd 1998). Today, grazing
is predominantly by cattle, and grazing intensity is much greater than historical standards.
Historically, grazing was by roaming herds of ungulates; now ranchers often implement
continuous grazing by cattle. High stocking densities with heavy or moderate continuous
grazing have transformed much of the shinnery community. The most palatable plants are
pressured more severely and consequently, the tall grass-oak communities change away from
historic climax community to short grass-oak or predominately sand shinnery oak
11
Texas Tech University, Jennifer Zavaleta, May 2012
communities (NCRS 2011). Heavy disturbance by hoof action to the soil surface results in
increases in annual grasses and forbs at the expense of perennial grasses (NCRS 2011).
Moreover, grazed areas have more bare ground, which increases wind erosion (Peterson and
Boyd 1998).
Grazing impacts the total production and composition of residual grass cover (Wolfe
1978, Sullivan 1980, Holland 1994). Uneven grazing under season- and year-long continuous
grazing creates a mixture of short grasses, bare ground, and tall, lightly-grazed bunches of
undesirable grass (Peterson and Boyd 1998). Unmanaged grazing typically results in a
decrease of species richness, with a few species tending to dominate. Non-grazed pastures
are mostly perennial grasses, whereas grazed areas have shifted toward annual forbs and
annual grasses (Peterson and Boyd 1998). Areas that are used primarily for livestock grazing
have reduced herbaceous production and require careful management to prevent soil erosion
(Sears et al. 1986).
Grazing also influences vegetation in terms of vertical and horizontal cover. Knopf et
al. (1988) argued that grazing greatly influenced nongame habitat because it alters the
horizontal patterning of the lower vegetation layers. Structural diversity provides critical
habitat features—travel lanes for broods, abundant access to seeds and insects, and close
escape cover (Boyd et al. 2001; Smythe and Haukos 2009, Smythe and Haukos 2010). There
is a need to develop and test grazing systems in sand shinnery oak communities that mimic
historical patterns to determine how to best restore the community to historical standards.
New Mexico Partners in Flight (2003) have identified unmanaged grazing and
eradication of shrubs as the two factors that most influence species using shinnery oak in
eastern New Mexico. Rangelands with light to moderate livestock stocking rates and patch
12
Texas Tech University, Jennifer Zavaleta, May 2012
grazing produce more food (seeds and insects) for prairie-chickens than non-grazed or
heavily grazed areas (Boyd et al. 2001). The composition of the plant community (including
the types of plants, biomass of plants, as well as vertical and horizontal cover of plants)
directly influences reproductive success of the lesser prairie-chicken and other grassland
birds (Smythe and Haukos 2009). Height and density of grass are “Clearly more important to the prairie chickens than species composition”(Hamerstrom et al 1957: 12). Riley et al.
(1992) determined that nest success for lesser prairie-chickens was greater in taller
vegetation. They concluded that the tall, wide clumps of vegetation provide better overhead
and lateral concealment of nesting birds from predators. Haukos and Smith (1989) explained
that lesser prairie-chickens use of sand shinnery oak increased as stocking rates increased
because vertical screening cover and percent overhead cover are the most important features
of lesser prairie-chicken nest sites.
Study Site
The study site for this project was a 1,040 ha area south of Portales, New Mexico.
The study site included 518 ha of private land on the Weaver Ranch and 518 adjacent ha on
the North Bluit Prairie Chicken Area owned by the New Mexico State Game Commission
(Fig. 1.2).
The area was characterized by gentling undulating plains with sandy and loamy soils
that range from shallow to deep (NRCS 2011). The soils on the study site were very deep
soils formed in sandy eolian materials (NCRS 2011). The landform for Sand Hills is dunes
and sheets. Shinnery oak soils are generally permeable and water erosion is low (Peterson
and Boyd 1998). Native vegetation includes short-medium grasses and sandy sites support
tall grasses with shinnery oak. Currently, the predominant land use is livestock grazing,
13
Texas Tech University, Jennifer Zavaleta, May 2012
although irrigated croplands and oil and gas production are becoming more prevalent (NRCS
2011).
Climatic Features
The climate is characterized by large variation in the magnitude of ranges in daily
temperature extremes, low relative humidity, and irregularly spaced rainfall of moderate
amounts. The climate regime is also known for being semi-arid with mild winters (NRCS
2011). From 2001-2010, the average annual precipitation on mystudy site in eastern New
Mexico was 42 cm, but ranged from 21 cm to 82 cm. Droughts occur often, although there
are some years with relatively large rain events (NRCS 2011). Precipitation during spring
and summer months results in increased annual production, even if the remainder of the year
is relatively dry. April through June are generally dry and July through September is
relatively wet (Peterson and Boyd 1998).
The winters are typically mild but cold fronts with strong winds are common (NRCS
2011). While the winter brings little snow and precipitation, dust storms that leave dust
lingering for several days afterward occur in late winter and early spring. Daytime
temperatures in July are an average of 24.5°C with highs and lows ranging from 22.9°C to
4.0°C and January averages are at 4°C with highs and lows ranging from 23°C to -13°C (C.
Dixon, Wildlife Plus Consulting, unpubl. Data).
Initial Assessment of Plant Composition
In the summer of 2000, line point and line intercept methods were used to measure
the vegetative composition prior to application of treatments. Three 100-m transects were
placed randomly within each of the 12 plots. Line point transects were conducted to
determine percent composition of bare ground, litter, and species of rooted plants every
14
Texas Tech University, Jennifer Zavaleta, May 2012
meter for 100 m (Heady et al. 1959). The line intercept method was also employed (Canfield
1941) within a randomly selected 50-m portion of each 100-m transect. The length of
individual plant species that intercepted the line was recorded and converted to percent
composition. Surveys concluded that vegetative composition was homogeneous across the
study area (F15, 11 =0.65, P=0.24 for point transect, F9, 14=0.66, P=0.74 for line transects)
(Smythe 2006).
Smythe (2006) determined that there were significant differences between control and
treated areas after spraying, the details of which are the crux of this investigation. These
differences were significant (F10,5 =46.21, P=0.0003 for point transects, F8,7 =17.68, P=0.006
for line transects; Table 1.1). There was also a 6.5-fold increase in the herbaceous
production and a 29-fold difference in seed production in the treated versus untreated areas
one year after application (Table 1.2).
15
Texas Tech University, Jennifer Zavaleta, May 2012
Literature Cited
Ahlborn, C. G. 1980. Brood-rearing habitat and fall-winter movements of lesser prairie
chickens in eastern New Mexico. Master of Science thesis, New Mexico State
University, Las Cruces. 73 pp.
Baily, J. and C. Painter. 1994. What good is this lizard? New Mexico Wildlife 39 (4): 22-33.
Bell, L. A., S. D. Fuhlendorf, M. A. Patten, D. H.Wolfe, and S. K. Sherrod. 2010. Lesser
prairie-chicken hen and brood habitat use on sand shinnery oak. Rangeland Ecology
and Management 63:478-486.
Boyd, C. S. and T. G. Bidwell. 2001. Influence of prescribed fire on lesser prairie-chicken
habitat in shinnery oak communities in western Oklahoma. Wildlife Society Bulletin
29: 938-947.
Canfield, R. H. 1941. Application of the Line Interception Method in Sampling Range
Vegetation. Journal of Forestry 39(4): 388-394.
Conner, N. R., H. W. Hyde, andH. R. Stoner 1974. Soil survey Andrews County, Texas.
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+maps.
Davis, C. A., T. Z.Riley, H. R. Suminski, and M. J. Wisdom. 1979. Habitat evaluation of
lesser prairie chickens in eastern Chaves County, New Mexico. Final Report to
Bureau of Land Management, Rosewell, Contract YA-512-CT6-61. Las Cruces: New
Mexico State University, Department of Fishery and Wildlife Sciences. 142pp.
Dickerson, R. J., Jr. 1985. Short duration versus continuous grazing on sand shinnery oak
range. Master of Science thesis, Texas Tech University, Lubbock. 88pp.
Ethridge, D. E., R. D. Pettit, T. J. Neal, and V. E. Jones.1987. Economic returns from treating
sand shinnery oak with tebuthiuron in West Texas. Journal of Range Management
40(4) 346-348.
Federal Register. November 10, 2010. Proposed Rules Vol 75, No 217, pg 69222.
Galbraith, J. M. 1983. Plant and soil water relationships following sand shin-oak control.
Master of Science thesis, Texas Tech University, Lubbock. 81pp.
Garrison, G. L. and K. C. McDaniel. 1982. New Mexico brush inventory. Special Report
No.1. Las Cruces, NM: New State University and New Mexico Department of
Agriculture, Forest Service. 68 pp.+maps.
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Hamerstrom, F. N., Jr.,O. E. Mattson, and F. Hamerstrom. 1957. A guide to prairie chicken
management. Wisconsin Conservation Department of Technology, Wildlife Bulletin,
15. 128 pp.
Haukos, D. A. and L. M. Smith. 1989. Lesser prairie-chicken nest site selection and
vegetation characteristic in tebuthiuron-treated and untreated sand shinnery oak in
Texas. Great Basin Naturalist 49: 624-626.
Heady, H. F., R. P. Gibbens, and R. W. Powell. 1959. A comparison of the charting line
intercept, and line point methods of sampling shrub types of vegetation. Rangeland
Management 12: 180-188.
Hodson, M. V., T. E. Calhoun, C. L. Chastain, L. W. Hacker, W. G. Henerson, and C.
R.Seagraves. 1980. Soil survey of Chaves County, New Mexico, southern part.
Washington, DC: USDA Soil Conservation Service. 148 pp. + maps.
Holland, M. 1994. Disturbance, environmental heterogeneity, and plant community structure
in sand shinnery oak community. Master of Science thesis, Texas Tech University,
Lubbock, TX. 112 pp.
Jones, V. E. and R. D. Pettit. 1980. Soil water in Graslan® and untreated oak plots. Research
Highlights 1979 Noxious Brush and Weed Control. Range, Wildlife, and Fisheries
Management 10:31. Texas Tech University, College of Agricultural Sciences and
Natural Resource Management, Lubbock, Texas.
Jones, V. E. and R. D. Pettit. 1984. Low rates of tebuthiuron for control of sand shinnery oak.
Journal of Range Management 37: 488-490.
Knopf, F. L., J. A. Sedgwick, and R. W. Cannon. 1998. Guild structure of riparian avaifauna
relative to seasonal cattle grazing. Journal of Wildlife Management 52: 280-290.
Lenfesty, C. D. 1983. Soil survey of Chaves County, New Mexico, northern part.
Washington, DC: USDA, Soil Conservation Service. 224pp. + maps.
Martin, B. H. 1990. Avian and vegetation research in the shinnery oak ecosystem of
southeastern New Mexico. Master of Science Thesis, New Mexico State University,
Las Cruces, New Mexico, USA.
McIlivan, E. H. 1954. Interim report on shinnery oak control studies in the southern Great
Plains. Proceedings,Eleventh Annual Meeting, North Central Weed Control
Conference, December 6-9, 1954, Fargo, ND. pp. 96.
Muller, C. H. 1951. The significance of vegetative reproduction in Quercus. Madroño
11:129-137.
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New Mexico Partners in Flight. 2003. Draft Land Bird Conservation Plan for the State of
New Mexico. Christopher Rustay, compiler. Albuquerque, New Mexico, USA.
Patten, M. A.,D. H. Wolfe, E. Shochat, and S. K. Sherrod. 2005. Effects of microhabitat and
microclimate selection on adult survivorship of the lesser prairie-chicken. Journal of
Wildlife Management 69 (3): 1270-1278.
Peterjohn, B. G. and J. R. Sauer. 1999. Population status of North American grassland birds
from the North American Breeding Bird Survey, 1966-1996. Studies in Avian
Biology 19: 27-44.
Peterson, R. S. and C. S. Boyd. 1998. Ecology and management of sand shinnery
communities: a literature review. General Technical Report RMRS-GTR-16. United
States Forest Service, Rocky Mountain Research Station, Fort Collins, Colorado,
USA.
Pettit, R. D. 1979. Effects of picloram and tebuthiuron pellets on sand shinnery oak
communities. Journal of Range and Management 32:196-200.
Pettit, R. D. 1986. Sand shinnery oak. pp. 106. In: T. N. Shiflet, editor, Rangeland Cover
Types of the United States. SRM 730. Denver: Society for Range and Wildlife
Management. 5 pp.
Riley, T. Z., C. A. Davis, M. Ortiz, and M. J. Wisdom. 1992. Vegetative characteristics of
successful and unsuccessful nests of lesser prairie chickens. Journal of Wildlife
Management 56 (2): 383-387.
Scifres, C. J., J. W. Smith, and R. W. Bovey. 1981. Control of oaks (Quercus spp.) and
associated woody species on rangeland with tebuthiuron. Weed Science 29: 270-275.
Sears, W. E.,C. M. Britton, D. B. Wester, and R. D.Pettit. 1986. Herbicide conversion of
sand shinnery oak (Quercus havardii) community: effects of nitrogen. Journal of
Range Management 39: 403-407.
Sears, W. E. 1982. Biomass and nitrogen dynamics of herbicide converted sand shinnery oak
community. Master of Science Thesis, Texas Tech University, Lubbock. 105 pp.
Smythe, L.A. 2006. Response of nesting grassland birds to sand shinnery oak communities
treated with tebuthiuron and grazing in eastern New Mexico. Thesis, Texas Tech
University, Lubbock.
Smythe, L. A. and D. A Haukos. 2009. Nesting success of grassland birds in shinnery oak
communities treated with tebuthiuron and grazing in eastern New Mexico. The
Southwestern Naturalist 54(2): 136-145.
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Texas Tech University, Jennifer Zavaleta, May 2012
Society for Range Management. 1995. New concepts for assessment of rangeland condition.
Journal of Rangeland Management 48:271-282.
Sullivan, J. C. 1980. Differentiation of sand shinnery oak communities in west Texas. Master
of Science thesis, Texas Tech University, Lubbock. 100 pp.
U.S. Department of Energy-Bonneville Power Administration. March 2000.Tebuthiuron fact
sheet. Accessed April 11, 2012:
efw.bpa.gov/environmental_services/Document.../Tebuthiuron.pdf
Weaver, J. E. and F. E. Clements. 1938. Plant ecology, New York McGraw-Hill 599 pp.
Western Region Climate Center. 2010. Period of Record Monthly Climate Summary from 1/
1/1905 to 1/31/2012. http://www.wrcc.dri.edu/cgi-bin/cliMAIN.pl?nm7008
Accessed February 1, 2012.
Wolfe, H. G., editor. 1978. An environmental baseline study on the Los Medaños Waster
Isolation pilot Plant (WIPP) project area of New Mexico: a progress report. Sandia
Laboratory Studies SAND 77-7017. Albuquerque: U. S. Department of Energy. 112
pp.
York, J. C. and W. A. Dick-Peddie. 1969. Vegetation changes in southern New Mexico
during the past hundred years. pp. 157. In: W. G. McGinnies and B. J. Goldman,
editors, Arid Lands in Perspective. Tucson: University of Arizona Press.
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Texas Tech University, Jennifer Zavaleta, May 2012
Table 1.1. Vegetation composition and cover means from control and tebuthiuron-treated
area vegetation transects in Roosevelt County, New Mexico, before and after 2000
tebuthiuron application. Pre-application data were collected in 2000; post-application data
were collected in 2001.1
Vegetation Type
Shinnery
oak
Other
shrubs
Before Application
Control
Treatment
22.9
23.1
4.5
5.1
18.5
16.5
1.2
0.9
52.7
54.3
After Application
Control
Treatment
14.7
0.3
1.4
1.0
11.6
47.5
0.9
0.7
71.7
50.3
Before Application
Control
Treatment
42.2
39.6
9.4
6.8
41.3
48.4
3.6
4.8
0
0
After Application
Control
Treatment
38.4
0.5
3.7
1.8
53.3
96.0
4.3
1.6
0
0
Line Transect (%)
Before Application
Control
Treatment
25.6
25.4
3.4
8.0
36.0
35.4
1.8
1.2
0
0
After Application
Control
Treatment
14.3
0.1
2.9
2.2
29.0
63.9
1.9
1.4
0
0
25.6
25.7
7.1
5.2
33.4
25.5
1.2
0.7
41.6
45.4
After Application
Control
21.5
4.9
26.5
Treatment
0.5
2.5
67.6
1
Source: C. Dixon, Wildlife Plus Consulting, unpubl. data.
1.6
1.3
80.5
65.8
Community Measure
Point Transects (%)
Grasses
Forbs
Non-plant
Nearest Plant (%)
Quadrat Estimate (%)
Before Application
Control
Treatment
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Texas Tech University, Jennifer Zavaleta, May 2012
Table 1.2. 2001 grass seed production on control and treatment areas in eastern New Mexico
after tebuthiuron application.1
Seed Production (kg/ha)
Sand
Gramas
Total
Paspalum Dropseed Bluestem
Community Measure
Control
1.06
0.71
1.50
1.06
(no tebuthiuron applied)
Treatment
6.06
16.84
42.55
61.08
(tebuthiuron applied)
1
Source: Smythe 2006 and C. Dixon, Wildlife Plus Consulting, unpubl. data.
21
4.83
126.53
associated with this community. Although occurring in other regions of the United States,
sand shinnery oak likely has the greatest ecological influence in the sandy soils of the
southwestern Southern High Plains (Peterson & Boyd, 1998; Fig. 2). The natural form of
Tech University,
100 or greater
short, aerialJennifer Zavaleta, May 2012
sand shinnery oak in this region is that of a low shrub with up to Texas
shoots from a massive underground stem and root system (Peterson & Boyd, 1998; Pettit,
1986). The underground root system is the primary reproductive structure for sand shinnery
oak.
Figure 1.1. Range of shinnery oak grassland across the southwest.
Fig. 2. Distribution of sand shinnery in New Mexico, Texas, and Oklahoma (Peterson &
Boyd, 1989).
22
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 1.2. Study area in sand shinnery oak habitats of eastern New Mexico, showing
application of tebuthiuron and grazing treatments that were applied in an assessment of
restoration of habitats during 2000-2012.
23
Texas Tech University, Jennifer Zavaleta, May 2012
CHAPTER II
EFFECTS OF TEBUTHIURON HERBICIDE AND GRAZING TREATMENTS ON SOIL
MOISTURE, PLANT COMPOSITION, PLANT STRUCTURE, AND PLANT AND SEED
PRODUCTION
Introduction
The sand shinnery oak (Quercus havardii) (hereafter shinnery oak) community is an
important part of the southwestern High Plains (Haukos 2011). Based on evidence for arid to
semi-arid or sub-humid environments, the Southern High Plains have likely existed as a
grassland for about 11 million years (Holliday 1990, Haukos 2011). The sandy soils of the
High Plains of eastern New Mexico and northwestern Texas create a distinct ecosystem from
surrounding short-grass prairie. Dune fields and sandy soils were formed during the
Altithermal periods (Holliday 1989) along with more than 20,000 ephemeral playa lakes, and
40 saline lakes (many of which are now dry with the advent of irrigation technology and the
expansion of farming; Haukos 2011). These deep, sandy soils have always supported a
mixed-grass prairie with a co-dominant shrub component (USDA NRCS 2010).
Expanding from southeastern New Mexico, northward through the Texas panhandle,
and into southwest Oklahoma, the shinnery oak community is an isolated, relict vegetation
community. Pettit (1979) recognized the significance of this community, and stated, “These lands are perhaps the most fragile of all ecosystems on the Southern High Plains of Texas
and the landowners cannot afford to abuse it” (Haukos 2011: 106). With continuous, unmanaged grazing, suppression of periodic natural fire, and other anthropogenic impacts,
the composition of the shinnery oak-grassland community has changed dramatically during
the past 100 years (Peterson and Boyd 1998, Haukos 2011). Due to these factors along with
24
Texas Tech University, Jennifer Zavaleta, May 2012
its capacity as an effective water gatherer, the density of shinnery oak has increased and, in
many areas, monotypic stands have developed.
Although shinnery oak has frequently been accused of being invasive and increasing
under grazing pressure, its presence for over 3,000 years as evidenced through pollen profiles
(Gross and Dick Peddie 1979) and its slow growth through rhizomes negates this claim. In
fact, due to habitat fragmentation through oil and gas exploration, urban development, and
row-crop agriculture, shinnery oak habitat has declined in absolute terms. While the
historical acreage of the shinnery oak community is disputed, Peterson and Boyd (1998)
estimated that the species historically covered 405,000 ha in Oklahoma, 607,000 in New
Mexico and 1.4 million in Texas. It was estimated that Texas had converted at least 200,000
hectares by 1972. With expansion of center-pivot irrigation and advancements in the
technology of herbicides, shinnery oak has been lost from at least half of its historical range.
However, there is an important need for conservation and restoration of this relicthabitat to a
species composition representative of pre-settlement conditions; it provides the primary
habitat for a number of species of conservation concern including the lesser prairie-chicken
(Tympanuchus pallidicintus), dune sagebrush lizard (a.k.a. sand dunes lizard Sceloporus
arenicolus), and Cassin’s sparrow (Aimophia cassinii).
Similar to short-grass prairie, the important historical ecological drivers in the region
were herbivory, natural fire, and precipitation. However, there was probably less frequent
grazing and fire because the sandy soils were more difficult for bison(Bison bison) to traverse
and more fuel load would need to accumulate for fire to travel across patchy vegetation
(Haukos 2011). Annual precipitation is highly variable in the region, and is a limiting factor
in this semi-arid grassland community (Peterson and Boyd 1988). For example, from 2001-
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Texas Tech University, Jennifer Zavaleta, May 2012
2010 the average annual precipitation on mystudy site in eastern New Mexico was 42 cm, but
ranged from 21 cm to 82 cm.
There are several potential precipitation measures that may be related to plant
community response. These include measures of seasonal, annual, and growing season
moisture. It is important for land managers to know which precipitation index has the
greatest influence on the shinnery oak-grassland ecosystem. For example, recharge of soil
moisture is primarily the result of winter and early spring precipitation (Inouye 2005). As
such, winter precipitation can predict, to a certain extent, annual production, which is
essential to plan stocking rates for the following year.
With a lack of other historical drivers like grazing and fire, the shinnery oak
community has changed in composition from a mixed-grass prairie to monotypic stands with
dense shrubs. Tebuthiuron (N-[5-(1,-dimehylethyl)-1,3,4-thiadiazol-2-yl]-N,N’-dimehylurea)
is an herbicide that attacks the root systems of the woody stems and has been used to
eradicate shrubs (Peterson and Boyd 1988). Thehalf-life of tebuthiuron is about 360 days
(U.S. Department of Energy-Bonneville Power Administration 2000). As a dry-pelleted
herbicide, tebuthiuron has the distinct advantages of relative nontoxicity to non-target
species, requires only one application (Scifres et al. 1981), and does not result in an
overspray characteristic of liquid herbicides (Peterson and Boyd 1998).
In the 1980s and early 1990s, the U.S. Bureau of Land Management (BLM) treated
40,469 hectares of shinnery oak in New Mexico with tebuthiuron under the assumption that
shinnery oak was not a part of the historic composition (Peterson and Boyd 1998). BLM
treated shinnery oak with the goal of eradication for the benefit of grass production in order
to eradicate it to increase grass and because shinnery oak’s buds can be toxic to cattle in the 26
Texas Tech University, Jennifer Zavaleta, May 2012
spring. A complete eradication should be avoided because elimination of vegetation roots,
including shinnery oak, can cause the sandy soils tobecome severely eroded (Grover 1990,
Haukos 2011). It is now recognized that complete eradication of shrubs is considered
detrimental to biodiversity and landscape heterogeneity in the region. Therefore, the Natural
Resources Conservation Service (NRCS) has more recently proposed reducing shinnery oak
canopy cover to less than 40% to increase grass production with no loss of biodiversity. As
such, NRCS has encouraged and cost-shared ranchers in eastern New Mexico to apply 0.560.84 kg/ha of tebuthiuron (USDA NRCS 2000).
Numerous studies have addressed the effects of tebuthiuron application in shinnery
oak communities. This study is the first to evaluate the potential use of the herbicide and
grazing as tools for restoration of the historical vegetation community, which is particularly
important because much of the land in the region is managed for cattle production. This study
is also unique in that it evaluates restoration with 12 years of data, allowing inference
regarding temporal responses.
My goal was to measure attributes of shinnery oak grasslands during an effort to
restore a historical shinnery oak-mixed-grass prairie. Specific objectives were to measure the
(1) abiotic response of soil moisture, (2) changes in the plant community composition,(3)
changes in community structure, and (4) impacts to plant production in terms of total aboveground biomass and seed production. The focus of this chapter is an assessment of the
treatments without regard to annual variation in precipitation. Therefore, for each objective,
several indices of precipitation were tested to determine the measure of precipitation that
explained the most variation within each dependent variable. The selected precipitation index
was used to remove the variation due to annual precipitation levels to focus on the treatment
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Texas Tech University, Jennifer Zavaleta, May 2012
effects of herbicide treatment and grazing management. Knowing more about the effects of
herbicide coupled with grazing will offer better insight as to how the community can be
restored with techniques that are already prevalent in the region.
Methods
Experimental Design
Before beginning the experiment, initial surveys were conducted in the summer of
2000 to test homogeneity of the study site. Three 100 meter (m) transects were placed
randomly within each of the 12 plots. The line intercept method was employed (Canfield
1941) within randomly selected 50 m portion of each 100 m transect. The individual plant
species that intercepted the line was recorded and converted to percent composition. Surveys
concluded that vegetative composition was homogeneous across the study area (F 9, 14=0.66,
P=0.74 for line transects) (Smythe 2006) (Tables 1.1 and 1.2). After initial surveys, another
replicate for each treatment was added for statistical power.
In Roosevelt County, New Mexico, on the Southern High Plains, 532 ha of private
land were treated with tebuthiuron (rate of 0.60 kg/ha with dune avoidance) in 2000. This
application rate was approximately 50% of previously recommended rates because the goal
was to reduce shinnery oak, not to eliminate it.
The state of New Mexico owned 523 ha of adjacent land, representing an extant
shinnery oak community serving as an experimental control. This herbicide control area had
not been grazed for 7 years before the study and the private land was grazed immediately
prior to the herbicide treatment; neither area was grazed until two growing seasons following
herbicide treatment. A moderate grazing treatment was designed to take a maximum of 50%
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Texas Tech University, Jennifer Zavaleta, May 2012
of the annual herbaceous production between two grazing seasons in the growing and
dormant seasons in July and January, respectively, starting in December 2002. Due to
logistical constraints, there was no growing season grazing in 2009 or 2010. Because grass
production differed substantially between the tebuthiuron-treated and control plots, cattle
grazed for approximately 300 animal-days per plot on the control areas and 2,000 animaldays per plot of the tebuthiuron-treated areas to achieve similar grazing intensity within each
treatment combination.
To allow for inference beyond the study site, the experimental design was a combined
completely randomized design with a systematic application of treatments following random
assignment of initial treatment combination (Cochran and Cox 1957, Smythe and Haukos
2009). My independent variables were herbicide treatment (two levels of treated and
untreated) and grazing (two levels of grazed and non-grazed). These were considered fixed
effects and the replicates of the treatments were treated as random effects. There were four
replicates for the four treatments, totaling 16 plots each 1 hectare across (Fig. 1.2).
Historical Climax Plant Community
Using the ecological site description, I created an index of the historical percentage of
plant occurrence in terms of tallgrasses, midgrasses, shortgrasses, shrubs, and forbs
(http://esis.sc.egov.usda.gov, site ID R077DY045TX). I then used the index to compare the
historic plant community to that in each of the four treatments to determine which treatment
combination best approaches a restored sand shinnery oak grass community.
Field Methods
To evaluate the community response to the treatments, abiotic and vegetation
characteristics were measured at each treatment plot. Abiotic variables were precipitation and
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Texas Tech University, Jennifer Zavaleta, May 2012
soil moisture. Vegetation data were partitioned into categories of composition, structure, and
production. Composition included percent composition of grass, shrub, forb, bare ground and
litter. In addition, I separated out shinnery oak and bluestem (Andropogon spp.) for
additional analyses. Visual and horizontal obstruction, measured with the Robel pole and
angle of obstruction respectively, were measured to assess vegetation structure. Because
lesser prairie-chickens and other avian species utilizing these communities may respond
differently to vegetation structure during nesting and brooding seasons, these variables, along
with soil moisture, were recorded in April and June. Plant production was measured in terms
of end-of-growing-season standing crop of total herbaceous production and seed production
separated by bluestem species (Andropogon spp.), grama species (Bouteloua spp.), sand
paspalum (Paspalum maritimum), and dropseed species (Sporobolusspp.).
Weather Data
A digital recording rain gauge (Rainwise, Inc.) was established in the study area to
monitor precipitation. In addition, a weather station was placed near the site to monitor daily
weather conditions, including monthly precipitation (cm). Becauseprecipitation in semi arid
regions is widely recognized as being low and highly variable (Sala and Lauenroth 1982,
Noy-Meir 1973), it was an important to retain in the model as a covariate. Potential
precipitation variables for each year were calculated as winter I (November to March), winter
II (October to March), growing season (April to October), and annual season (April to
March).
Environmental Soil Moisture
Plant growth is largely determined by soil moisture; thus, it was important to measure
the effect of treatments on environmental soil moisture. From 2001-2010, soil moisture was
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Texas Tech University, Jennifer Zavaleta, May 2012
measured April and June with quick draw soil moisture meter (Aquaterr model 200), with the
exception of April 2002 and in June 2002 and 2008). In each of the 16 plots, the probe was
placed 15 cm into the soil at 10-m intervals along three 100-m line transects in a randomly
selected direction from a permanently marked t-post. Soil moisture was recorded in centibars
(cb).
Vegetative Composition
Each September from 2001–2010, vegetative surveys were conducted to monitor
vegetation response to treatments. A pre-vegetation survey conducted in 2000 found that the
study area was homogenous prior to application of the herbicide treatment (Table 1.1).
Within each replicate, percent composition of grass, shrub, forb, bare ground and litter were
measured based on occurrence every meter along three, 10-m transects (Heady et al. 1959).
Percent composition of grass, shrub, forb, bare ground and litter within each replication was
estimated by dividing the number of points at which each occurred by the total number of
points sampled. Also, shinnery oak presence and sand bluestem (Andropogon hallii), an
example of desirable grass, were analyzed.
Visual Obstruction
Visual obstruction was measured each April and June from 2001-2010 (excluding
June 2003) using a Robel pole (Robel et al. 1970) placed 4 m to the right of a point every 10
m along each of the three 100-m transects within each replicate. An observer estimated the
lowest visible decimeter of the pole that was visible from the transect line at an eye-level of 1
m.
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Texas Tech University, Jennifer Zavaleta, May 2012
Overhead Obstruction
Overhead obstruction was measured with angle of obstruction each April and June
from 2001-2010 (excluding June 2002). The angle of obstruction is a function of plant height
and the ground distance of the plant from a point in space, indicating that it is a direct
mathematical integration of vertical and horizontal dimensions of habitat structure (Harrell et
al. 2002). A digital level was attached to a pole that was lowered down until it came into
contact with a plant (Kopp et al. 1998). Angular readings (degrees) were recorded in each
cardinal direction at 10 intervals on three 100-m transects within each plot.
Herbaceous Production
Herbaceous production was measured each October from 2002-2010 to estimate
available above-ground standing crop, which was an index of residual cover for wintering
wildlife and nesting birds. Clip plots were used to measure above-ground production. A 0.25
by 1 m quadrat frame was placed at 10-m intervals in a randomly selected direction. Five
such samples were collected within each replicate of all four treatments. All herbaceous
growth was clipped at ground level, dried at 40°C with a 2002 Cabela's Commercial Food
Dehydrator (160 liter 89 cm x 44 cm x 60 cm) to a constant mass, and then weighed on a
2002 ChargeMaster 1500 scale to the nearest 0.01 g. Above-ground standing crop was
recorded as kg/ha.
Seed Production
Seeds production was estimated for the most abundant grass species during
September from 2004-2009. A 0.25 by 1 m quadrat frame was placed at 10-m intervals in a
randomly selected direction from a randomly selected point. Five samples were taken from
each plot. Seeds were stripped from Andropogon species, Bouteloua species, Paspalum
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Texas Tech University, Jennifer Zavaleta, May 2012
maritimum, and Sporobolus species. Seeds from the same species were grouped and dried at
40°C with a 2002 Cabela's Commercial Food Dehydrator (160 liter-89 cm x 44 cm x 60 cm)
to a constant mass, and then weighed on a 2002 ChargeMaster 1500 scale to the nearest
0.01g. Seed production was recorded as kg/ha.
Statistical Methods
Soil moisture exerts a relative influence on each measured dependent variable
included in this study. Thus, determination of a relevant precipitation index for each
dependent variable was necessary to create a covariate that removed the maximum amount of
variation due to annual precipitation. This enabled me to test the relative effects of the
treatments while minimizing the effect of annual precipitation, which varied from 21-82 cm
during the study (Fig. 4.1).
For each dependent variable, I tested four potential indices of precipitation that are
potentially biologically relevant, using 1 April and 1 October as the start and end of the
growing season, respectively. These four indices are previous annual precipitation (1 April to
31 March), spring/summer precipitation (1 April to 30 September), and two measures of
winter precipitation (1 October to 31 March and 1 November to 31 March). Historically,
from 1981-2010, the average precipitation from April to March was 42.45 cm, from April to
October was 36.3 cm, from October to March was 9.77 cm, and from November to March
was 6.16 cm (WRCC, 2010). I chose two different indices of winter precipitation as it has
been used as a predictor variable for topographic features in the region (Brown et al. 2002). I
tested growing-season precipitation because plant structure may be related to growth during
the previous growing season. I also tested annual precipitation, which is a combination of
spring and winter precipitation.
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Texas Tech University, Jennifer Zavaleta, May 2012
Precipitation was treated as a continuous annual fixed effect. For each dependent
variable, I used Akaike Information Criterion for small samples (AICc) to rank the models
containing the 4 precipitation indices to determine the index with the greatest influence on
each dependent variables (Anderson and Burham 1997). The resultant precipitation measure
from the highest ranked model was then used as a covariate in an analysis of covariance
(ANCOVA), removing the effect of variation in annual precipitation prior to testing the main
effects of herbicide treatment (treated vs. untreated) and grazing (grazing vs. non-grazed) as
well as the their interaction. Data were tested for normality (Shapiro-Wilk Test) and
homogeneity of variance (Levene’s Test and Welch’s Test) (Cochran and Cox 1957). Independence was assumed, as the samples were randomly selected. The Satterthwaite
approximation was used to pool variances, if the variance estimates among the independent
variables of herbicide treatment, grazing, and herbicide*grazing were homogeneous (Zar
2009). If the precipitation covariate was significant (P< 0.05), I used simple linear
regression to evaluate the strength of the influence of the precipitation measure on the
dependent variable. I performed statistical analyses using PROCMIX in SAS 9.2 (SAS
Institute, Cary, North Carolina, USA).
A similar process was used for percent composition, but I initially used a multivariate
analysis of covariance (MANCOVA) to simultaneously test the effects of herbicide treatment
and grazing for all plant species composition variables. Plant species composition was
categorized into groups of vegetation types (grass, shrub, and forb) as well as variables for
bare ground and litter. Following a statistically significant MANCOVA (Wilks’ lambda), univariate mixed effects analysis of variance (ANCOVA) was used to test each dependent
variable in the same study design. For all statistical tests, I set α = 0.05.
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Texas Tech University, Jennifer Zavaleta, May 2012
Results
Precipitation covariate
The highest-ranking index for all precipitation indices was winter precipitation from
either October or November to March, except for overhead obstruction in April. In that case,
growing season (April to March) best explained the variation (Table 2.1, Figs. 2.24-2.28).
The effect of precipitation was statistically significant on all considered variables, except for
annual seed production and blue grama seed production. The linear relationship between
dependent variables and precipitation was marginally biologically relevant as all
relationships had low r2 values. The trends of these relationships were negative with the
exception of herbaceous production, dropseed production, and sand paspalum.
Soil Moisture in April
Winter precipitation from October to March was the highest ranked precipitation
measure for soil moisture in April (Table 2.2). Winter precipitation had a significant effect in
the ANCOVA (F8, 396=541.91, P<0.0001). However, even though the slope for winter
precipitation was statistically significant, it offered little ecological explanatory ability (r2 =
0.12; F1, 430 =59.36, P=0.0001; Fig. 2.1). Plots treated with tebuthiuron had 16% more soil
moisture in April than those that were not treated (F1, 396=105.04, P<0.0001; Table 2.3; Fig.
2.2). There was also a grazing effect (F1, 396=7.67, P=0.006; Fig. 2.2) such that soil moisture
increased by 4% in grazed areas as compared to non-grazed areas. There was no herbicide
and grazing interaction effect (F1, 428=0.16, P=0.69).
Soil Moisture in June
Winter precipitation from November to March was the highest ranked precipitation
measure for soil moisture in June (Table 2.2). Winter precipitation was a significant factor in
the ANCOVA (F8, 360=503.30, P<0.0001). The slope between winter precipitation and soil
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Texas Tech University, Jennifer Zavaleta, May 2012
moisture in June was statistically significant, but there was little explanatory power in the
relationship (r2 =0.01; F1, 391=3.97, P=0.05; Fig. 2.1). Soil moisture in June was 17% greater
in plots treated with tebuthiuron (F1, 360=71.89, P<0.0001; Table 2.3; Fig. 2.3). There was no
grazing effect (F1, 360=1.72, P=0.19), nor was there an herbicide and grazing interaction
effect (F1, 360=1.03, P=0.32) for June soil moisture.
Percent Composition
The winter precipitation from November to March was used in the MANCOVA
model for community composition (Wilks’ lambda= 0.78, F1,120 =6.63, P<0.0001). However,
for each dependent variable, the winter precipitation index did not have a significant effect:
grass - r2=0.007, F1,120 =1.01, P=0.32; shrub - r2=0.008, F1,120 =1.22, P=0.27; forb - r2
=0.0002, F1,120 =0.04, P=0.85; litter - r2 =0.005, F1,120 =0.68, P=0.41; and bare ground - r2
=0.0001, F1,120 =0.01, P=0.91 (Table 2.4).
The overall MANCOVA had significant herbicide effect (Wilks’ lambda=0.081, F 5,124 =282.2, P<0.0001) and grazing effects (Wilks’ lambda=0.69, F 5,124 =11.14,
P<0.0001),
but no interaction effect (Wilks’ lambda=0.99, F 5,124 =0.33, P=0.89). Recognizing this, I
tested herbicide and grazing treatments for each dependent variable using individual
ANCOVAs (Table 2.5). Herbicide effect was found for percent cover of shrub (Fig. 2.4),
grass (Fig. 2.5), forb (Fig. 2.6), and litter (Fig. 2.7). Grazing had an effect on litter and bare
ground (Fig. 2.8). Shrubs were 117% lower in treated areas as compared to untreated areas.
Consequently, grasses increased by 149% and forbs increased by 257% in treated areas
compared to untreated areas. Litter decreased by 17% in treated areas as compared to
untreated areas. There was 13% more litter and 28% more bare ground in grazed than nongrazed pastures.
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Texas Tech University, Jennifer Zavaleta, May 2012
Presence of Shinnery Oak
Winter precipitation from October to March was the highest ranked precipitation
index relative to the occurrence of sand shinnery oak (Table 2.6). There was a significant
precipitation effect on presence of shinnery oak (F3, 144 =4.60, P=0.004). However, despite a
significant slope in the relationship between shinnery oak occurrence and precipitation index
was weak (r2=0.03; F1, 158=5.46, P=0.02; Fig. 2.9). Treated areas had 91% less shinnery oak
than untreated areas (F1, 12=744.68, P<0.0001; Fig. 2.10; Table 2.7). There was no grazing
effect (F1, 12=0.23, P=0.64). There was a marginal herbicide and grazing interaction effect
(F1, 12=4.33, P=0.06) on the occurrence of shinnery oak.
Presence of Sand Bluestem
Winter precipitation from October to March was the highest ranked covariate for the
occurrence of sand bluestem (Table 2.6). This precipitation index had a significant effect on
the occurrence of sand bluestem (F9, 108=39.25, P<0.0001). However, it was had a significant
slope in regression (r2=0.06; F1,158 =9.24, P=0.003; Fig. 2.9). There was an herbicide effect
(F1, 156=29.28, P<0.0001; Fig. 2.11; Table 2.7) such that the treated pastures had 118% more
sand bluestem than those that were not treated. There was no grazing effect (F1, 156=0.03,
P=0.87), nor herbicide and grazing interaction effect (F1, 156=0.47, P=0.49).
Visual Obstruction in April
Winter precipitation from November to March was the highest ranked precipitation
index for visual obstruction in April (Table 2.8). In the subsequent ANCOVA, this
precipitation index had a significant effect (F9, 439=59.79, P<0.0001). Although there was a
statistically significant slope in the regression, the index had low predictive ability for visual
obstruction in April (r2=0.023; F1, 477=14.07, P=0.0002; Fig. 2.12). There were significant
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Texas Tech University, Jennifer Zavaleta, May 2012
main effects of herbicide (F1, 439 =187.27, P<0.0001; Fig. 2.13; Table 2.9) and grazing (F1, 439
=12.50, P=0.0004; Fig.2.13). Treated plots had 30% more visual obstruction, or taller
vegetation, than untreated plots. Grazed plots had 6.5% less visual obstruction than nongrazed plots. There was no herbicide and grazing interaction effect (F1, 439 =3.01, P=0.08).
Visual Obstruction in June
Winter precipitation from November to March best explained the variation of visual
obstruction in June (Table 2.8). There was significant precipitation index effect (F8,
388=13.47,
P<0.0001). However, using regression, the relationship between winter
precipitation and visual obstruction in June was not predictive and had a non-significant
slope (r2=0.005; F1, 430 =3.14, P=0.08; Fig. 2.12). Visual obstruction was 50% greater in
treated areas as compared to untreated areas (F1, 8 =155.63, P<0.0001; Fig. 2.14; Table 2.9).
There was no grazing effect (F1, 8=1.15, P=0.31), nor herbicide and grazing interaction (F1,
8=.92,
P=0.33) effects.
Overhead Obstruction in April
Growing season precipitation from April to October was the highest ranked
precipitation for overhead obstruction in April, which deviated from the trend of other
dependent variables that were primarily associated with winter precipitation (Table 2.8).
Overall growing season precipitation had an effect on the model (F8, 396=125.07, P<0.0001).
The relationship between overhead obstruction in April and this precipitation index had a
significant slope (r2=0.12; F1, 430=60.27, P<0.0001; Fig. 2.12). There was a significant
herbicide effect (F1, 396=239.18, P<0.0001; Fig. 2.15; Table 2.9). There was also a main
effect of grazing (F1, 396=218.37, P<0.0001). There was an herbicide and grazing effect
interaction effect (F1, 396=12.36 P=0.0005; Fig. 2.15). In treated areas, overhead obstruction
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Texas Tech University, Jennifer Zavaleta, May 2012
decreased by 14% in grazed areas as compared to non-grazed areas. Non-treated areas had
only 10% less overhead obstruction in grazed areas as compared to non-grazed areas. In
grazed areas, there was 11% increase in overhead obstruction in treated areas. In non-grazed
areas, there was 14% more overhead obstruction in treated areas as compared to untreated
areas.
Overhead Obstruction in June
Winter precipitation from November to March was the highest ranked precipitation
index for overhead obstruction in June (Table 2.8). There was a winter precipitation effect
(F8, 356=49.19, P<0.0001) and its relationship with overhead obstruction was significant
(r2=0.09; F1, 387=56.31, P<0.0001; Fig. 2.12). There was a main effect of herbicide (F1,
356=97.62,
P<0.0001; Fig. 2.16; Table 2.9) and grazing (F1, 356=40.44, P<0.0001; Fig. 2.16).
There was an herbicide and grazing interaction effect (F1, 356=5.10, P=0.025; Fig. 2.16). In
treated areas, overhead obstruction decreased 7% in grazed areas as compared to non-grazed
areas. In untreated areas, overhead obstruction decreased by 4% in grazed areas. In grazed
areas, overhead obstruction increased by 7.5% in treated areas compared to untreated areas.
However, in non-grazed areas, overhead obstruction increased by 11% in treated areas
compared to untreated areas.
Annual Herbaceous Production
Precipitation from November to March was the top ranked precipitation index related
to annual herbaceous production (Table 2.10). Precipitation had an effect on the overall
ANCOVA (F8, 108 =6.47, P<0.0001). The relationship between winter precipitation and
herbaceous production was not predictive (r2=0.002; F1, 142=0.25, P=0.62, Fig. 2.17).
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Texas Tech University, Jennifer Zavaleta, May 2012
There was 212% more herbaceous production in treated areas than in non-treated
areas (F1, 108 =385.65, P<0.0001; Fig. 2.18; Table 2.11). There was also a grazing effect
(F1,108 =4.64, P=0.03; Fig. 2.18) such that there was 11% less herbaceous production in areas
that had been grazed as compared to non-grazed areas. There was no herbicide and grazing
interaction effect (F1,108 =0.0, P=0.98).
Total Seed Production
Winter precipitation from November to March was the precipitation index that was
the highest ranked of tested precipitation measures tested for influence on total seed
production (Table 2.10). However, that particular precipitation index did not have an
influence on the total production of seeds (F1, 40 =1.76, P=0.19; Fig. 2.17). Neither of the
main effects of herbicide (F1, 40 =1.22, P=0.28; Table 2.11; Fig. 2.19) or grazing (F1, 40 =1.36,
P=0.25) affected seed production. There was not an herbicide effect and grazing interaction
(F1, 40 =0.31, P=0.58).
Sand Dropseed Seed Production
Winter precipitation from November to March was the highest ranked precipitation
index for sand dropseed seed production (Table 2.12). This effect was significant in the
ANCOVA (F1, 41 =6.85, P=0.01). The influence of precipitation on sand dropseed seed
production was statistically significant (r2=0.08; F1, 47 =4.14, P=0.05; Fig. 2.17). There was
an herbicide effect (F1, 41 =15.38, P=0.0003; Table 2.10; Fig. 2.20) such that there were 273%
more seeds produced on treated areas as compared to untreated areas. There was no effect of
grazing (F1, 41 =0.41, P=0.56), nor was there an herbicide and grazing interaction effect (F1, 41
=0.86, P=0.36).
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Texas Tech University, Jennifer Zavaleta, May 2012
Bluestem Seed Production
Winter precipitation from November to March was the highest ranked precipitation
index for production of bluestem seeds (Table 2.12). However, this index was not significant
in the ANCOVA (F1, 41 =3.69; P=0.06; Fig. 2.17). Seed production of bluestem species was
not effected by herbicide treatment (F1, 41 =0.35, P=0.56; Table 2.10, Fig. 2.21). There was
no grazing effect (F1, 41 =0.78, P=0.38), nor was there an herbicide and grazing interaction
effect (F1, 41 =0.62, P=0.43).
Sand Paspalum Seed Production
Winter precipitation from November to March was the precipitation index that ranked
highest for sand paspalum seed production (Table 2.12). There was a precipitation effect in
the ANCOVA (F1, 41 =4.03, P=0.05). However, this precipitation index was not predictive of
sand paspalum seed production (r2= 0.03; F1, 47 =1.53, P=0.22; Fig. 2.17). There was an
effect of herbicide (F1, 41 =14.47, P=0.0005; Fig. 2.20; Table 2.10; Fig. 2.22). Sand paspalum
increased by 1698% in treated areas as compared to untreated areas. There was no effect of
grazing (F1, 41 =0.54, P=0.47), nor was there an herbicide and grazing interaction effect (F1, 41
=0.57, P=0.45) for seed production of sand paspalum.
Grama Seed Production
Winter precipitation from November to March was the highest ranked precipitation
index for grama seed production (Table 2.12). However, when tested in the ANCOVA,
precipitation did not have a significant effect (F1, 41 =1.12, P=0.30; Fig. 2.17). There was no
herbicide effect (F1, 41 =0.07, P=0.80; Table 2.10; 2.23), grazing effect (F1, 41 =3.40, P=0.07),
nor an herbicide and grazing interaction effect (F1, 41 =0.43, P=0.52) on seed production of
grama
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Texas Tech University, Jennifer Zavaleta, May 2012
Discussion
When a nearly monotypic shinnery oak site was treated with 0.60 kg/ha of
tebuthiuron, shinnery oak was reduced by 94% in treated areas that were not grazed and 88%
in treated areas that were grazed throughout a ten-year period. Moreover, when coupled with
a grazing system that removes a maximum of 50% herbaceous production, shinnery oak did
not increase in density following herbicide treatment (Chapter IV). Because shinnery oak is
an effective water gatherer, control to levels conducted in this study increased soil moisture
that becomes available for other plants. With increased soil moisture, there was more
biomass of herbaceous production.
Abiotic Factors
The highest-ranking precipitation models for soil moisture in April and June included
winter precipitation. This is consistent with the literature. Inouye (2005) found that the
recharge of soil moisture was primarily the result of winter and early spring precipitation,
with soil moisture declining during spring and summer growing season as evaporation and
transpiration increased.
Soil moisture increased by 16 and 17% in treated areas compared to untreated areas in
April and July, respectively. Inouye (2005) found that soil moisture was greater at depths
from 120-180 cm in areas that had shrub removal. She did not find significant differences at
more shallow depths. However, four of the five years of her study were drought years, which
may have affected shallow soil moisture measurements. Also, her study was in Idaho, which
has a different soil type than the deep sands of New Mexico. Similar results have been found
in semi-arid shrub-grassland plant communities. In the Chaparral of California, brush control
through the use of 2,4-D, fire, and hand clearing was found to decrease soil moisture stress,
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Texas Tech University, Jennifer Zavaleta, May 2012
which improved the chance of establishment of perennial grass (Test 1972). Similarly, in
Nevada, Robertson (1947) found that removal of big sagebrush increased available water for
grass production.
Soil moisture dynamics affects not only overall production, but what types of plants
can grow. The limiting influence of soil moisture is accentuated in semi-arid environments.
Pettit (1979) explained that shinnery oak does not require more water than grasses. Instead,
shinnery oak is able to outcompete grasses in dry years because it starts spring growth two
weeks earlier. This is confirmed in the literature; the pattern of recharge and depletion of soil
moisture favors plants that can quickly extract soil moisture early in the growing season
(Inouye 2005).
In periods of drought, shinnery oak has an advantage over grass because it stores up
to 50% of its weight as water. However, when water is available, grasses extract more deep
soil water (Jones and Pettit 1980). With the removal of shinnery oak, more water is available
to support herbaceous production, which may mitigate grass loss during drought to a certain
extent.
Rates of Tebuthiuron
It has been argued that herbicides, at a low rate, only offer temporary increases in
herbaceous production and must be reapplied for 2 and 3 consecutive years (Scrifres 1972,
Pettit 1979); this contention is not supported by these data. My results show that when there
is moderate grazing, shinnery oak will not redevelop to pre-treatment levels because grasses
remain competitive under this grazing pressure. In fact, shinnery oak decreased by 88% and
94% in grazed areas and non-grazed areas, respectively, over ten years.
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Texas Tech University, Jennifer Zavaleta, May 2012
Other research indicates that lower application rates (<0.5 kg/ha) of tebuthiuron can
achieve a significant reduction in plant counts of shinnery oak. Jacoby et al. (1983) found
that mortality of sand shinnery oak, based on stem counts, was estimated at 42% and 94%
with application rates of 0.5 kg/ha and 1.0 kg/ha rates of tebuthiuron, respectively, 18 months
following treatment. Jones and Pettit (1989) found that at a rate of 0.4 kg/ha sand shinnery
oak was reduced by 95% after three years. This is consistent with my research, where, at a
rate of 0.60 kg/ha, there was a significant herbicide effect.
I used the examples of shinnery oak and sand bluestemto illustrate the relationship
between shrub removal and forgeable grass growth. Both were significantly influenced by
treatment such that shinnery oak was 91% less and bluestem was 118% more in treated areas
as compared to untreated areas. It is, therefore, reasonable to assume land managers could
use comparable tebuthiuron rates to achieve historical standards of 15% of total shrub
composition (USDA NRCS 2010, Chapter IV). The goal of treatment should not be to
eliminate the shinnery oak completely in favor of grass production and instead should be to
restore it to historical standards. Some land managers have recognized this paradigm shift
and since about 2000 land managers have reduced tebuthiuron application rates to less than
1.0 kg/ha and deliberately avoided dune areas (Haukos 2011).
Changes in composition
Even at low doses, tebuthiuron treatment resulted in changes to the plant composition
of the community. There was a significant herbicide effect for the proportions of grass,
shrub, forb, and litter, but not for bare ground. Litter and bare ground were the only variables
that were significantly affected by grazing. Grasses increased by 149%, shrubs decreased by
79%, and forbs by 257% in treated areas compared to untreated areas. Litter decreased by
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Texas Tech University, Jennifer Zavaleta, May 2012
17% in treated areas compared to untreated areas and decreased by 13% in grazed areas
compared to non-grazed areas. However, grazed plots had 28% more bare ground than nongrazed plots.
Many studies have tested the effect of tebuthiuron not only on shrub control, but also
on grass production. Depending on the rate of tebuthiuron, grass production and the types of
grasses that grow will change. In my study, the percent cover of grasses was substantially
changed such that it increased 149% in treated areas as compared to untreated areas. This is
comparable to the literature. In a study with tebuthiuron rates between 0.4-1.0 (kg/ha), the
highest grass yield was four times as much as control at a rate of 0.8 (kg/ha), but even at a
rate of 0.4 (kg/ha) grass production increased 2.5 times the control after three years (Jones
and Pettit 1984). Doerr (1980) found that grass production increased 88-130%, with bunch
grasses increasing 12-32%, when application rates were between 0.2 and 1.0 kg/ha.
While there is a relationship between increasing grass production with greater rates of
tebuthiuron, it is important to realize that this is not a linear relationship. At application
levels greater than 1.0 kg/ha the increased benefit of grass production becomes muted. At a
rate of >3 kg/ha non-target grasses and forbs are killed. Based on research in Jayton, Texas,
Jacoby et al. (1983) reported that at a rate of 1.1 kg/ha grass yields only doubled in treated as
compared to untreated plots. Furthermore, it is important to note that the quality of grass
production is also affected by high rates of tebuthiuron. At high application rates, most of the
production is of annuals and undesirable species (Haukos 2011).
Much like grass production, forb production is benefited by tebuthiuron treatment. In
mystudy, forbs increased nearly three-fold in treated areas as compared to untreated areas.
Forbs generally increase in diversity and production 2 years after application (Doerr and
45
Texas Tech University, Jennifer Zavaleta, May 2012
Guthery 1983, Haukos 2011). Similar to grass production, there is a threshold in which
tebuthiuron application is no longer beneficial. Doerr (1980) found that forb densities were
decreased in plots with 0.8 and 1.0 kg/ha. Scifres and Mutz (1978) found that most forb
species were killed at application rates of 2.0 and 3.0 kg/ha.
Percent litter was affected by both treatment and grazing such that litter decreased by
17% in treated areas and 12% in grazed areas. This is consistent with the literature;Sears et
al. (1986) found that litter decreased 32% in treated plots as compared to control six years
after treatment. Treated areas have more rooted herbaceous production so there is less litter
compared to untreated areas.
In my study, tebuthiuron did not affect the amount of bare ground, but bare ground
increased by 28% in grazed as compared to non-grazed treatments. Grazed areas are more
likely to have bare ground because of herbaceous production removal by cattle. This is
different than other studies where untreated plots contained almost twice as much bare
ground as compared to treated plots (Jacoby et al. 1983). Differences in our results is likely
due to the higher tebuthiuron application rate (1.0 kg/ha) than our study (0.6 kg/ha)
Grazing
In arid systems, livestock grazing can significantly alter changes in soil properties and
vegetative structure complexity (Castellano 2006). However, the magnitude of these changes
depends on the stocking rate and the level of grazing. In my study, grasses and forbs were
able to persist because they remained a competitive part of the system. Litter and bare ground
were the most affected by grazing with each increasing 13% and 28%, respectively. The
increase in litter and bare ground provides more heterogeneity of the habitat, which may be
beneficial for some types of rodents and herptiles (Chapter III). It is also important to note
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Texas Tech University, Jennifer Zavaleta, May 2012
that the regime of grazing also included deferment of cattle two years after tebuthiuron
spraying. This lag gave grasses and forbs time to establish before grazing or herbaceous
removal ensued.
Plant Structure
In terms of visual obstruction, there was both an herbicide and grazing effect in April
such that visual obstruction increased by 30% in treated areas compared to untreated,
decreased by 6.5% in grazed areas compared to non-grazed areas. However, there was only
an herbicide effect in June such that visual obstruction increased by 50% in treated areas as
compared to untreated areas.
After tebuthiuron treatment, the bunch grasses that grew back were often taller than
shinnery oak. My findings about plant structure are consistent with the literature. Depending
on the rate of application, vertical screening is reduced immediately following application as
shrubs die. When bunch grasses grow back they can be taller than the shinnery oak and will
provide more vertical screening (Doerr and Guthery 1983, Haukos 2011).
During grazing the herbaceous production is removed, which affects the structure or
height of the herbaceous production. It is, therefore, not surprising that there was a grazing
effect. There no grazing effect in June because it was the last month before grazing in July
and production height is based on the growth from the year before.
In terms of overhead obstruction, there was an herbicide and grazing interaction
effect in April and June. In April, treated areas had a 14% decrease in overhead obstruction
in grazed areas and non-treated areas had only 10% less overhead obstruction in grazed areas
as compared to non-grazed areas. This indicates grazed areas have more horizontal
obstruction in untreated than in treated areas. In grazed areas, there was 11% increase in
47
Texas Tech University, Jennifer Zavaleta, May 2012
overhead obstruction in treated areas. In non-grazed areas, there is 14% more overhead
obstruction in treated areas as compared to untreated areas. This indicates that in treated
areas, there is more overhead obstruction in non-grazed areas.
In June, treated areas had 7% less overhead obstruction and similarly untreated areas
had 4% less overhead obstruction in grazed areas as compared to non-grazed areas. In grazed
areas, overhead obstruction increased by 7.5% in treated areas and in non-grazed areas,
overhead obstruction increased by 11% in treated areas as compared to untreated areas. This
indicates that in treated areas, non-grazed areas provide more overhead obstruction.
Plant structure is particularly important for management of lesser prairie-chickens.
Microhabitat selection by prairie chickens is driven more by physiognomy than by floristic
composition (Patten et al. 2005). Given that prairie chickens have declined precipitously
with about 90% of their population and range lost (Taylor and Guthrey 1980), it is important
to know which land management practices are most beneficial. There is conflicting
information about how herbicide treatment and removal of shinnery oak affect prairie
chickens directly. However, structural characteristics of nest sites are important. Haukos
(2011) found that composition and structure were both important for nest selection.
Specifically, vertical screening and percent overhead cover were found to be the most
important features of selected nest sites in New Mexico. Riley et al. (1992) determined plant
height around nests provides concealment from predators and protects the nest from extreme
temperature, wind, and solar radiation.
The best management strategy for prairie chickens would be to treat at low levels of
tebuthiuron such that grasses can grow taller than the shrubs offering more visual and
48
Texas Tech University, Jennifer Zavaleta, May 2012
overhead obstruction. Grazing at moderate levels could also be beneficial to prairie chickens
as it prevents grass from getting too thick.
Olawsky and Smith (1991) found that prairie chicken densities were similar in treated
and untreated areas even though grass and shrubs were greater and shrubs were less in treated
areas. They recommended that cover in tebuthiuron-treated pastures provided better
concealment than untreated pastures, especially in the winter after oak leaves had dropped.
Grasses may therefore be preferred areas for loafing and roosting during cool seasons as they
continue to provide cover throughout the winter (Taylor and Guthery 1980, Olawksy and
Smith 1991).
Herbaceous Production
Herbaceous production is also influenced by herbicide and grazing, especially in light
of shrub removal and consequent increases in soil moisture. One of the most important
benefits of increased soil moisture is an increase in herbaceous production (Inouye 2005).
Sears et al. (1986) concluded that annual fluctuations in biomass primarily occurred as a
function of precipitation. Herbaceous production did not seem to be influenced specifically
by previous winter precipitation, indicating that the relationship between precipitation and
herbaceous production is complex.
There was 212% more herbaceous production in treated areas than untreated areas.
There was a grazing effect such that 11% of herbaceous production was removed in grazed
areas as compared to non-grazed areas. Because grazing, by definition, is the removal of
herbaceous production, the small grazing effect demonstrates how this plant community
responds to managed grazing compared to the traditional, continuous grazing. It is important
to note that grazing did not occur in this study until two years after herbicide treatment and
49
Texas Tech University, Jennifer Zavaleta, May 2012
the grazing system had an objective to use only 50% of available standing crop.
Incorporating managed grazing should replace the traditional system of continuous,
unmanaged grazing.
Thus, while inference can be made beyond the study site, one must recognize the
distinct difference of how this land was grazed as compared to other ranchers in the area. It
is, therefore, recommended that land managers implement a grazing regime that takes about
50% of herbaceous production in discrete grazing sessions. Under these circumstances, the
historical driver of grazing by roaming ungulates like bison can be mimicked. If grazing is
not deferred for a few years or if it is continuously grazed, these potential benefits will be
muted and application of herbicides will once again be necessary within a few years. When
grazing levels remain low to moderate, the benefit of increased herbaceous production is
sustainable. The combination of low rates of tebuthiuron and moderate grazing can restore a
mixed-grass prairie (Chapter IV).
Similarly, Sears et al. (1986) determined that following 0.6 kg/ha of tebuthiuron
application in the shinnery oak system in Yoakum County, Texas, the physiognomy changed
from a shinnery oak shrubland to mixed-grass prairie with a shrub component. They found
above-ground herbaceous material increased approximately 6-fold on treated sites as
compared to untreated sites 3 and 6 years after treatment. This is slightly greater than our
results but my data includes more growing seasons and precipitation levels, including
immediately after treatment. Earlier years when grass was being reestablished it was shorter
and may be disproportionately affect the observed effect size.
Other studies indicate that higher rates of tebuthiuron (1.0-2.0 kg/ha) are required to
increase herbaceous production. Scifres and Mutz (1978) found that herbaceous production
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Texas Tech University, Jennifer Zavaleta, May 2012
increased 1, 2, and 3 years after application of tebuthiuron at rates of 2.24 kg/ha. They found
that lower rates (1.12 kg/ha) did not increase grass standing crop compared to treated and
untreated areas, regardless of year of evaluation. However, they concluded that 1 to 2 kg/ha
was required for range improvement relative to increasing grass standing crop. This conflicts
with myfindings. Scifres and Mutz (1978) only measured production for 1, 2, and 3 years
after treatment, which may not be enough time for grasses to reestablish in the area,
especially when dosed with a large amount of herbicide. Also, they had a much smaller
sample size with only two 0.25 by 0.25-m2 quadrat samples taken from each plot. We had
100 1 by 0.25-m2 samples for each treatment every year. It remains that low doses of
tebuthiuron (0.6 kg/ha) can achieve the benefits of increased herbaceous production.
Seed production
With the exception of blue grama species and total seed production, the highest
ranked precipitation index for all variables was a form of winter precipitation (either from
October to March or November to March).
For gramaspecies, winter precipitation did not explain the variation in seed
production. Sala and Lauenroth (1982) explained that grama species is adapted to the region
takes advantage of small precipitation events (<5 mm). Because the wet season is typically
between July and September (Peterson and Boyd 1998), it could be that gramaseed
production variation is better explained by intermittent rain events during the current growing
season.
Sand dropseedand sand paspalum species were the only species that had a significant
herbicide effect in terms of seed production. The increase in seed production is likely a
product of more of those plants being present in treated areas and thus more plants available
51
Texas Tech University, Jennifer Zavaleta, May 2012
to produce seeds. Similarly, Doerr (1980) found that seed production increased in plots
treated with 0.2, 0.4, and 0.6 (kg/ha). The lack of herbicide effect in other species could be
due to high variance and small sample sizes of seeds. So while there may be an effect with
other species, five quadrats per plot may not have been a big enough sample size to detect
differences.
Conclusion
These data show that at relatively low levels of tebuthiuron (0.60 kg/ha) and moderate
grazing regimes, shinnery oak can be kept at bay without reapplication, and that grasses
remain competitive in the system. With the removal of shinnery oak there is more
environmental soil moisture available for grasses and forbs to grow. Sand dropseedand sand
paspalum seed production is dramatically increased in treated areas. This increase in
herbaceous production affects the vegetation structure such that there is more visual and
overhead obstruction, which may be beneficial for roosting prairie chickens. The effects of
grazing, when designed to take only 50% of herbaceous production, are statistically
significant, but not deleterious. This is best noted by the lack of grazing effect on visual
obstruction in June and decrease of only 11% in grazed areas as compared to non-grazed
areas. When low levels of tebuthiuron and moderate grazing are used, mixed-grass prairie
can be established such that there is more diversity in terms of percent composition, more
visual and overhead obstruction, and more herbaceous production.
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Texas Tech University, Jennifer Zavaleta, May 2012
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Texas Tech University, Jennifer Zavaleta, May 2012
Table 2.1. List of top ranked AIC models for precipitation, W, precipitation effect’s F and P values, r2, and trend of precipitation
regression for soil moisture, plant composition, plant structure, and plant and seed production. Data were collected in 16
experimental plots consisting of the combinations of (1) tebuthiron (herbicide) treated – grazed, (2) tebuthiron treated – nongrazed, (3) nontebuthiron treated – grazed, and (4) non tebuthiron treated – non-grazed in eastern New Mexico from 2000-2010.
Visual obstruction in April
Presence of bluestem species
Growing season
Winter I
Winter I
Winter II
0.780
0.569
0.996
0.824
0.986
0.646
0.987
0.578
1
W
F8, 356=49.19
F8, 396=125.07
F8, 388=13.47
F9, 439=59.79
F9, 108=39.25
F3, 144 =4.60
F8, 360=503.30
F8, 396=541.91
F
P<0.0001
P<0.0001
P<0.0001
P<0.0001
P<0.0001
P<0.0001
P=0.004
P<0.0001
P<0.0001
P
0.002
0.09
0.12
0.005
023
0.06
0.03
.01
0.12
r2
+
-
-
-
-
-
-
-
-
Trend2
Top ranked
model
Winter II1
Visual obstruction in June
Winter I
0.520
F1, 41 =6.85
F1, 40 =1.76
P=0.06
P=0.01
P=0.19
0.03
-
0.08
-
Winter II
Winter I
Overhead obstruction in April
Winter I
Soil moisture in April
Soil moisture in June
Overhead obstruction in June
0.666
F1, 41 =3.69
P=0.05
Presence of shinnery oak
Herbaceous production
0.768
F1, 41 =4.03
-
+
+
F8, 108 =6.47
Winter I
0.908
P=0.30
Winter I
Winter I
F1, 41 =1.12
Winter I
Bluestem seed production
0.619
Annual seed production
Sand paspalum seed production
Winter I
Sand dropseed seed production
Blue grama seed production
1
Winter II is October to March
Winter I is November to March
Growing season is April to March
Trend of precipitation regression
2
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Texas Tech University, Jennifer Zavaleta, May 2012
2
1
4
3
2
1
Model Rank
Growing season
Winter II
Winter I
Annual season4
Growing season3
Winter I2
Winter II1
Precipitation Index
4
4
4
4
4
4
4
4
K
3503.5
3497.9
3491.2
3490.5
3798.4
3792.6
3751.6
3733.3
AICc
-13
-7.4
-0.7
0
-65.1
-59.3
-18.3
0
Δ AIC
0.001
0.014
0.407
0.578
0
0
0
1
W
Table 2.2. List of ranked AIC models for precipitation, AICc, Δ AIC, and W for soil moisture in April and June. Data were
collected in 16 experimental plots consisting of the combinations of (1) tebuthiron (herbicide) treated – grazed, (2) tebuthiron
treated – non-grazed, (3) nontebuthiron treated – grazed, and (4) non tebuthiron treated – non-grazed in eastern New Mexico from
2000-2010.
3
Annual season
Soil moisture in June
Soil moisture in April
4
1
Winter
II is October- March
2
Winter
I is November-March
3
Growing season is April- October
Annual season is April- March
4
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Texas Tech University, Jennifer Zavaleta, May 2012
Soil moisture in April
F1, 360=71.89, P<0.0001
F1, 396=105.04, P<0.0001
F, P
Herbicide effect
F1, 360=1.72, P=0.19
F1, 396=7.67, P=0.006
F, P
Grazing effect
F1, 360=1.03, P=0.32
F1, 428=0.16, P=0.69
F, P
Interaction effect
Table 2.3. List of herbicide, grazing, and interaction effect for soil moisture in April and June that were collected in 16
experimental plots consisting of the combinations of (1) tebuthiron (herbicide) treated – grazed, (2) tebuthiron treated – nongrazed, (3) nontebuthiron treated – grazed, and (4) non tebuthiron treated – non-grazed in eastern New Mexico from 2001-2010.
Soil moisture in June
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Texas Tech University, Jennifer Zavaleta, May 2012
grass
F1,120 =1.22
F1,120 =1.01
F1,120 =6.63
F
P=0.41
P=0.8511
P=0.2722
P=0.3168
P<0.0001
P
0.0001
0.0048
0.0002
0.0085
0.0071
+
trend
Table 2.4. Summary of percent cover variables (grass, shrub, forb, litter, and bare ground) and their relationship with winter
precipitation index, which was selected for the MANOVA following the trends of other plant variables. Data are from 16
experimental plots consisting of the combinations of (1) tebuthiron (herbicide) treated – grazed, (2) tebuthiron treated – nongrazed, (3) nontebuthiron treated – grazed, and (4) non tebuthiron treated – non-grazed in eastern New Mexico from 2002-2010.
shrub
F1,120 =0.04
P=0.91
r2
forb
F1,120 =0.68
Top rank
precipitation
index
Winter II*
litter
F1,120 =0.01
Overall Percent cover
bare ground
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Texas Tech University, Jennifer Zavaleta, May 2012
F
235.91
238.75
64.38
17.92
2.42
Wilks’ Lambda
0.081
0.69
0.99
Herbicide
P
<0.0001
<0.0001
<0.0001
<0.0001
0.14
F (df)
282.2 (5, 124)
11.14 (5, 124)
0.33 (5,124)
F
0.05
0.44
0.0
7.28
24.59
Grazed
P
0.83
0.51
0.96
0.0078
0.0003
P
<0.0001
<0.0001
0.89
Table 2.5. Overall MANCOVA results for percent cover and individual ANCOVA results for percent cover with associated F and
P values. Data are from 16 experimental plots consisting of the combinations of (1) tebuthiron (herbicide) treated – grazed, (2)
tebuthiron treated – non-grazed, (3) nontebuthiron treated – grazed, and (4) non tebuthiron treated – non-grazed in eastern New
Mexico from 2001-2010.
Herbicide
Grazing
Herbicide*Grazing
Percent Cover
Grass
Shrub
Forb
Litter
Bare ground
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Texas Tech University, Jennifer Zavaleta, May 2012
Table 2.6. List of ranked AIC models for precipitation, AICc, Δ AIC, and W for presence of shinnery oak and bluestem species.
Data were collected in 16 experimental plots consisting of the combinations of (1) tebuthiron (herbicide) treated – grazed, (2)
tebuthiron treated – non-grazed, (3) nontebuthiron treated – grazed, and (4) non tebuthiron treated – non-grazed in eastern New
Mexico from 2000-2010.
2
1
Annual season4
Growing season
Winter I1
Winter II
Model
4
4
4
4
4
K
949.1
947.2
1392.2
1390.3
1387.9
1378.6
AICc
-4
-1.9
0
-13.6
-11.7
-9.3
0
Δ AIC
0.017
0.087
0.25
0.646
0.001
0.003
0.009
0.987
W
Model
Rank
3
Winter II
4
951.2
-7.3
4
Presence of bluestem species
Presence of shinnery oak
1
Winter I
4
954.5
1
2
Growing season3
4
2
3
3
Annual season4
1
4
1
Winter II is October- March
2
Winter I is November-March
3
Growing season is April- October
Annual season is April- March
4
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Texas Tech University, Jennifer Zavaleta, May 2012
Presence of shinnery oak
F1, 156=29.28, P<0.0001
F1, 12=744.68, P<0.0001
F, P
Herbicide effect
F1, 156=0.03, P=0.87
F1, 12=0.23, P=0.64
F, P
Grazing effect
F1, 156=0.47, P=0.49
F1, 12=4.33, P=0.06
F, P
Interaction effect
Table 2.7. List of herbicide, grazing, and interaction effect for presence of shinnery oak and sand bluestem that were collected in
16 experimental plots consisting of the combinations of (1) tebuthiron (herbicide) treated – grazed, (2) tebuthiron treated – nongrazed, (3) nontebuthiron treated – grazed, and (4) non tebuthiron treated – non-grazed in eastern New Mexico from 2001-2010.
Presence of sand bluestem
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Texas Tech University, Jennifer Zavaleta, May 2012
Precipitation
Index
Winter I
Annual season
Winter II
Growing season
Winter I
Winter II
Growing season
Annual season
Growing season
Annual season
Winter I
Winter II
Winter I
Annual season
Growing season
Winter II
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
K
2770.1
2771.4
2773
2810.1
3190.6
3201.5
3233.3
3263.7
1991.3
1994.5
2000.9
2003.1
1980.7
1989.3
1998.7
1998.7
AICc
0
-1.3
-2.9
-40
0
-10.9
-42.7
-73.1
0
-3.2
-9.6
-11.8
0
-8.6
-18
-18
Δ AIC
0.569
0.297
0.134
0
0.996
0.004
0
0
0.824
0.166
0.007
0.002
0.986
0.013
0
0
W
Table 2.8. List of ranked AIC models for precipitation, AICc, Δ AIC, and W for visual and overhead obstruction in April and June.
Data were collected in 16 experimental plots consisting of the combinations of (1) tebuthiron (herbicide) treated – grazed, (2)
tebuthiron treated – non-grazed, (3) nontebuthiron treated – grazed, and (4) non tebuthiron treated – non-grazed in eastern New
Mexico from 2000-2010
Model Rank
Visual obstruction in April
1
2
3
4
Visual obstruction in June
1
2
3
4
Overhead obstruction in April
1
2
3
4
Overhead obstruction in June
1
2
3
4
1
Winter
I is November-March
2
Winter
II is October- March
3
Growing season is April- October
Annual season is April- March
4
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Overhead obstruction April
Visual obstruction in June
Visual obstruction in April
F1, 356=97.62, P<0.0001
F1, 396=239.18, P<0.0001
F1, 8 =155.63, P<0.0001
F1, 439 =187.27, P<0.0001
F, P
Herbicide effect
F1, 356=5.10, P=0.025
F1, 396=218.37, P<0.0001
F1, 8=.92, P=0.33
F1, 439 =12.5, P=0.0004
F, P
Grazing effect
F1, 356=5.10, P=0.025
F1, 396=12.36 P=0.0005
F1, 145=3.48, P=0.10
F1, 439 =3.01, P=0.08
F, P
Interaction effect
Table 2.9. List of herbicide, grazing, and interaction effect for measures of visual and overhead obstruction in April and June in 16
experimental plots consisting of the combinations of (1) tebuthiron (herbicide) treated – grazed, (2) tebuthiron treated – nongrazed, (3) nontebuthiron treated – grazed, and (4) non tebuthiron treated – non-grazed in eastern New Mexico from 2000-2010.
Overhead obstruction in June
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Texas Tech University, Jennifer Zavaleta, May 2012
2
1
4
3
2
1
Model Rank
Growing season
Winter II
Winter I
Annual season4
Growing season3
Winter II2
Winter I1
Precipitation Index
4
4
4
4
4
4
4
4
K
315
312.4
306
305.7
1691.4
1690.2
1689.1
1685.3
AICc
9.3
6.7
0.3
0
6.1
4.9
3.8
0
Δ AIC
0.0005
0.020
0.450
0.520
0.037
0.07
0.120
0.780
W
Table 2.10. List of ranked AIC models for precipitation, AICc, Δ AIC, and W for herbaceous and seed production. Data were
collected in 16 experimental plots consisting of the combinations of (1) tebuthiron (herbicide) treated – grazed, (2) tebuthiron
treated – non-grazed, (3) nontebuthiron treated – grazed, and (4) non tebuthiron treated – non-grazed in eastern New Mexico from
2000-2010.
3
Annual season
Seed production
Herbaceous production
4
11
Winter
II is October- March
2
Winter
I is November-March
3
Growing season is April- October
Annual season is April- March
4
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Herbaceous production
F1, 41 =0.35, P=0.56
F1, 41 =15.38, P=0.0003
F1, 40 =1.22, P=0.28
F1, 108 =385.65, P<0.0001
F, P
Herbicide effect
F1, 41 =0.54, P=0.47
F1, 41 =0.78, P=0.38
F1, 41 =0.41, P=0.56
F1, 40 =1.36, P=0.25
F1,108 =4.64, P=0.033
F, P
Grazing effect
F1, 41 =0.43, P=0.52
F1, 41 =0.57, P=0.45
F1, 41 =0.62, P=0.43
F1, 41 =0.86, P=0.36
F1, 40 =0.31, P=0.58
F1,108 =0.0, P=0.98
F, P
Interaction effect
Table 2.11. List of herbicide, grazing, and interaction effect for measures of herbaceous and seed production, specifically sand
dropseed, bluestem, sand paspalum, and blue grama seed production. Herbaceous production measurements were taken from
2002-2010 and seed production was taken from 2004-2009. Data were collected in 16 experimental plots consisting of the
combinations of (1) tebuthiron (herbicide) treated – grazed, (2) tebuthiron treated – non-grazed, (3) nontebuthiron treated – grazed,
and (4) non tebuthiron treated – non-grazed in eastern New Mexico.
Total seed production
F1, 41 =14.47, P=0.0005
F1, 41 =3.40, P=0.0723
Sand paspalum seed production
Bluestem seed production
Sand dropseed seed production
F1, 41 =0.07, P=0.80
Blue grama seed production
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Texas Tech University, Jennifer Zavaleta, May 2012
Winter I
Winter II
Growing season
Annual season
Winter I
Winter II
Growing season
Annual season
Winter I
Winter II
Growing season
Annual season
Winter I1
Winter II2
Growing season3
Annual season4
Model
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
K
166.5
167.5
176.8
178.7
175.6
180.3
186.8
188.1
305.7
309.2
310.2
313.2
130.7
129.3
141.1
143
AICc
0
1
10.3
12.2
0
4.7
11.2
12.5
0
3.5
4.5
7.5
0
1.4
11.8
13.7
Δ AIC
0.619
0.376
0.004
0.001
0.908
0.087
0.003
0.002
0.768
0.133
0.081
0.018
0.666
0.331
0.002
0.001
W
Table 2.12. List of ranked AIC models for precipitation, AICc, Δ AIC, and W for seed production of sand dropseed, bluestem,
sand paspalum, and blue grama. Data were collected in 16 experimental plots consisting of the combinations of (1) tebuthiron
(herbicide) treated – grazed, (2) tebuthiron treated – non-grazed, (3) nontebuthiron treated – grazed, and (4) non tebuthiron treated
– non-grazed in eastern New Mexico from 2000-2010.
Model Rank
Sand dropseed seed production
1
2
3
4
Bluestem seed production
1
2
3
4
Sand paspalum seed production
1
2
3
4
Blue grama seed production
1
2
3
4
1
Winter II is October- March
2
Winter I is November-March
3
Growing season is April- October
Annual season is April- March
4
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.1. Regression of environmental moisture and winter precipitation for April and June from a study of sand shinnery oakgrass communities in eastern New Mexico from 2002-2010.
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.2. Soil moisture in April as a dependent variable in models testing the effect of herbicide and grazing treatments in sand
shinnery oak grass communities in eastern New Mexico from 2001-2010 (missing data 2002)
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.3. Soil moisture in June as a dependent variable in models testing the effect of herbicide and grazing treatments in sand
shinnery oak grass communities in eastern New Mexico from 2001-2010 (missing data 2002 and 2008). The presence of *
indicates that the mean values differ (P<0.05).
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.4 .Percent composition of shrubs as a dependent variable in models testing the effect of herbicide and grazing treatments
in sand shinnery oak grass communities in eastern New Mexico from 2002-2010. The presence of * indicates that the mean values
differ (P<0.05).
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.5. Percent composition of grass as a dependent variable in models testing the effect of herbicide and grazing treatments in
sand shinnery oak grass communities in eastern New Mexico from 2002-2010.The presence of * indicates that the mean values
differ (P<0.05).
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.6. Percent composition of forbs as a dependent variable in models testing the effect of herbicide and grazing treatments in
sand shinnery oak grass communities in eastern New Mexico from 2002-2010. The presence of * indicates that the mean values
differ (P<0.05).
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.7. Percent composition of litter as a dependent variable in models testing the effect of herbicide and grazing treatments in
sand shinnery oak grass communities in eastern New Mexico from 2002-2010. The presence of * indicates that the mean values
differ (P<0.05).
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.8. Percent composition of bare ground as a dependent variable in models testing the effect of herbicide and grazing
treatments in sand shinnery oak grass communities in eastern New Mexico from 2002-2010. The presence of * indicates that the
mean values differ (P<0.05).
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.9. Regression of shinnery oak and sand bluestem presence and winter precipitation from a study of sand shinnery oak
grass communities in eastern New Mexico from 2002-2010
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.10. Abundance of shinnery oak, in terms of percent composition, as a dependent variable in models testing the effect of
herbicide and grazing treatments in sand shinnery oak grass communities in eastern New Mexico from 2002-2010. The presence
of * indicates that the mean values differ (P<0.05).
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.11. Abundance of sand bluestem, in terms of percent composition, as a dependent variable in models testing the effect of
herbicide and grazing treatments in sand shinnery oak grass communities in eastern New Mexico from 2002-2010. The presence
of * indicates that the mean values differ (P<0.05).
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.12. Regression of visual and overhead obstruction in April and June and winter precipitation from a study of sand
shinnery oak grass communities in eastern New Mexico from 2002-2010
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.13. Visual obstruction in April, as measured by Robel pole, as a dependent variable in models testing the effect of
herbicide and grazing treatments in sand shinnery oak grass communities in eastern New Mexico from 2002-2010. The presence
of * indicates that the mean values differ (P<0.05).
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.14. Visual obstruction in June, as measured by Robel pole, as a dependent variable in models testing the effect of
herbicide and grazing treatments in sand shinnery oak grass communities in eastern New Mexico from 2002-2010. The presence
of * indicates that the mean values differ (P<0.05).
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.15. Overhead obstruction in April, as measured by angle of obstruction, as a dependent variable in models testing the
effect of herbicide and grazing treatments in sand shinnery oak grass communities in eastern New Mexico from 2002-2010. The
presence of * indicates that the mean values differ (P<0.05).
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.16. Overhead obstruction in June, as measured by angle of obstruction, as a dependent variable in models testing the
effect of herbicide and grazing treatments in sand shinnery oak grass communities in eastern New Mexico from 2002-2010. The
presence of * indicates that the mean values differ (P<0.05).
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.17. Regression of herbaceous production, total seed production, dropseed species seed production, sand paspalum species
seed production, grama species seed production, and bluestem species seed production and winter precipitation from a study of
sand shinnery oak grass communities in eastern New Mexico from 2002-2010 for herbaceous production and 2004-2009 for seed
production.
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.18. Annual herbaceous production, measured in dry weight (kg/ha) with 100 samples of 1 by 0.25m2 quadrats in each plot
every year, as a dependent variable in models testing the effect of herbicide and grazing treatments on sand shinnery oak
communities in eastern New Mexico from 2002-2010. The presence of * indicates that the mean values differ (P<0.05).
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.19. Total seed production, measured in dry weight (kg/ha) with 100 samples of 1 by 0.25m2 quadrats in each plot every
year, as a dependent variable in models testing the effect of herbicide and grazing treatments on sand shinnery oak communities in
eastern New Mexico from 2004-2009
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.20. Sand dropseed seed production, measured in dry weight (kg/ha) with 100 samples of 1 by 0.25m2 quadrats in each
plot every year, as a dependent variable in models testing the effect of herbicide and grazing treatments on sand shinnery oak
communities in eastern New Mexico from 2004-2009. The presence of * indicates that the mean values differ (P<0.05).
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.21. Bluestem seed production, measured in dry weight (kg/ha) with 100 samples of 1 by 0.25m2 quadrats in each plot
every year, as a dependent variable in models testing the effect of herbicide and grazing treatments on sand shinnery oak
communities in eastern New Mexico from 2004-2009
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.22. Paspalum species seed production, measured in dry weight (kg/ha) with 100 samples of 1 by 0.25m2 quadrats in each
plot every year, as a dependent variable in models testing the effect of herbicide and grazing treatments on sand shinnery oak
communities in eastern New Mexico from 2004-2009. The presence of * indicates that the mean values differ (P<0.05).
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Texas Tech University, Jennifer Zavaleta, May 2012
Figure 2.23. Grama seed production, measured in dry weight (kg/ha) with 100 samples of 1 by 0.25m2 quadrats in each plot every
year, as a dependent variable in models testing the effect of herbicide and grazing treatments on sand shinnery oak communities in
eastern New Mexico from 2004-2009. The presence of * indicates that the mean values differ (P<0.05).
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Texas Tech University, Jennifer Zavaleta, May 2012
50
40
30
20
10
0
2004
2005
2006
2007
Year
2008
2009
16
14
12
10
8
6
4
2
0
Precipitation (cm)
92
Figure 2.24. Bluestem species seed production and winter precipitation from a study of sand shinnery oak-grass communities in
eastern New Mexico from 2004-2009.
Bluestem spp seed production
(g)
Texas Tech University, Jennifer Zavaleta, May 2012
50
40
30
20
10
0
2004
2005
2006
2007
Year
2008
2009
16
14
12
10
8
6
4
2
0
Precipitation (cm)
93
Figure 2.25. Paspalum species seed production and winter precipitation from a study of sand shinnery oak-grass communities in
eastern New Mexico from 2004-2009
Paspalum spp seed production
(g)
Texas Tech University, Jennifer Zavaleta, May 2012
50
40
30
20
10
0
2004
2005
2006
2007
Year
2008
2009
16
14
12
10
8
6
4
2
0
Precipitation (cm)
94
Figure 2.26. Grama species seed production and winter precipitation from a study of sand shinnery oak-grass communities in
eastern New Mexico from 2004-2009
Grama spp seed production (g)
Texas Tech University, Jennifer Zavaleta, May 2012
100
90
80
70
60
50
40
30
20
10
0
2004
2005
2006
2007
Year
2008
2009
16
14
12
10
8
6
4
2
0
Precipitation (cm)
95
Figure 2.27. Total seed production and winter precipitation from a study of sand shinnery oak-grass communities in eastern New
Mexico from 2004-2009
Total Seed Production (g)
Texas Tech University, Jennifer Zavaleta, May 2012
CHAPTER III
EFFECTS OF TEBUTHIURON HERBICIDE AND GRAZING TREATMENTS ON
MAMMAL, HERPTILE, AND INVERTEBRATE COMMUNITIES
Introduction
Expanding from southeastern New Mexico, northward through the Texas panhandle,
and into southwest Oklahoma, the sand shinnery oak (scientific name; hereafter shinnery
oak) community is an isolated, relict vegetation community. Pettit (1979) recognized the
significance of this community, and stated “These lands are perhaps the most fragile of all ecosystems on the Southern High Plains of Texas and the landowners cannot afford to abuse
it” (Haukos 2011: 106). With continuous, unmanaged grazing, suppression of periodic
natural fire, and other anthropogenic impacts, the composition of the shinnery oak-grassland
community has changed dramatically during the past 100 years (Peterson and Boyd 1998,
Haukos 2011). Due to these factors along with its capacity as an effective water gatherer, the
density of shinnery oak has increased and, in many areas, monotypic stands have developed.
Because habitat characteristics, including vegetation structure and composition, affect
mammal, herptile, and invertebrate communities, it is imperative to study the effects of
tebuthiuron and grazing on these communities.
The need for restoration is magnified when one considers how fragmented the habitat
has become. Due to habitat fragmentation through oil and gas exploration, urban
development, and row-crop agriculture, shinnery oak habitat has declined in absolute terms.
While the historical acreage of the shinnery oak community is disputed, Peterson and Boyd
(1998) estimated that the species historically covered 405,000 ha in Oklahoma, 607,000 in
New Mexico and 1.4 million in Texas. It was estimated that Texas had converted at least
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Texas Tech University, Jennifer Zavaleta, May 2012
200,000 hectares by 1972. With expansion of center-pivot irrigation and advancements in the
technology of herbicides, shinnery oak has been lost from at least half of its historical range.
However, there is an important need for conservation and restoration of this relict habitat to
a species composition representative of pre-settlement conditions; it provides the primary
habitat for a number of species of conservation concern including the lesser prairie-chicken
(Tympanuchus pallidicintus), dune sagebrush lizard (a.k.a. sand dunes lizard Sceloporus
arenicolus), and Cassin’s sparrow (Aimophia cassinii).
Similar to short-grass prairie, the important historical ecological drivers in the region
were herbivory, natural fire, and precipitation. However, there was probably less frequent
grazing and fire because the sandy soils were more difficult for bison (Bison bison) to
traverse and more fuel load would need to accumulate for fire to travel across patchy
vegetation (Haukos 2011). Annual precipitation is highly variable in the region, and is a
limiting factor in this semi-arid grassland community (Peterson and Boyd 1988). For
example , from 2001-2010 the average annual precipitation on my study site in eastern New
Mexico was 42 cm, but ranged from 21 cm to 82 cm.
There are several potential precipitation measures that may be related to plant
community response. These include measures of seasonal, annual, and growing season
moisture. It is important for land managers to know which precipitation index has the
greatest influence on the shinnery oak-grassland ecosystem. For example, recharge of soil
moisture is primarily the result of winter and early spring precipitation (Inouye 2005). As
such, winter precipitation can predict, to a certain extent, annual production, which is
essential to planning stocking rates for the following year.
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Texas Tech University, Jennifer Zavaleta, May 2012
With a lack of other historical drivers like grazing and fire, the shinnery oak
community has changed in composition from a mixed-grass prairie to monotypic stands with
dense shrubs. Tebuthiuron (N-[5-(1,-dimehylethyl)-1,3,4-thiadiazol-2-yl]-N,N’-dimehylurea)
is an herbicide that attacks the root systems of the woody stems and has been used to
eradicate shrubs (Peterson and Boyd 1988). As a dry-pelleted herbicide, tebuthiuron has the
distinct advantages of relative nontoxicity to non-target species, requires only one application
(Scifres et al. 1981), and does not result in an overspray characteristic of liquid herbicides
(Peterson and Boyd 1998). A complete eradication should be avoided because elimination of
vegetation roots, including shinnery oak, can cause the sandy soils to become severely
eroded (Grover 1990, Haukos 2011). It is now recognized that complete eradication of shrubs
is considered detrimental to biodiversity and landscape heterogeneity of the region.
There have been numerous studies addressing the effects of tebuthiuron application in
shinnery oak communities. This study is, however, the first to evaluate the potential use of
the herbicide as a tool for restoration of the historical community in conjunction with
managed grazing designed to sustain the restoration effort. This is particularly important
because much of the land in the region is managed for cattle production. This study is also
unique in that it evaluates restoration with 12 years of data and allows inference regarding
temporal responses. However, the scope of this chapter is to test the effects of using an
herbicide and subsequent grazing management as potential conservation strategies to restore
a degraded shinnery oak grassland community in terms of mammal, herptile, and invertebrate
communities.
The overarching goal of this project was to restore the historical composition of
shinnery oak grasslands. Specific objectives of my research associated with this project, and
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Texas Tech University, Jennifer Zavaleta, May 2012
presented here, were to measure the (1) abundance of mammals, herptiles and invertebrates;
(2) dominance in terms of Simpson’s index and diversity in terms of Shannon’s indices for mammals and herptiles; and (3) abundance of the three most abundant mammals, herptiles
and invertebrates in response to two primary treatments (treated with herbicide and managed
grazing) in four combinations. The focus of this chapter is an assessment of the treatments
without regard to annual variation in precipitation. Therefore, for each objective, several
indices of precipitation will be tested to determine the measure of precipitation that had the
greatest influence on each dependent variable. The selected precipitation index will then be
used to control the variation due to annual precipitation levels to focus on the treatment
effects of herbicide treatment and grazing management.
Methods
Experimental Design
This study was conducted on private and public lands in Roosevelt Co, New Mexico.
The soils in the area include the Brownfield and Tivoli series, and are characterized by deep,
loose, light colored, neutral sandy soils and deep, loose, light colored sands that occur as
dunes that are two to five meters high and have slopes as much as 30 percent, respectively
(Newman 1964). The landscape is comprised of a matrix of rangeland, cropland, and gently
undulating sandhills and dominated by shinnery oak and sand sagebrush (Artemisia filifolia)
with mixed grasses and forbs. The major land use for ranches not included in the study was
cattle production.
In 2000, 532 ha of private land were treated with tebuthiuron (rate of 0.60 kg/ha with
dune avoidance). This application rate was approximately 50% of previously recommended
rates because the goal was to reduce shinnery oak, not to eliminate it. Adjacent to the private
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Texas Tech University, Jennifer Zavaleta, May 2012
land was 518 ha of New Mexico state land. The public land consisted of extant shinnery oak
community and was used as an experimental control in relation to herbicide treatment on the
private lands.
The herbicide control had not been grazed for 7 years before the study and the private
land was grazed immediately prior to the herbicide treatment and neither was grazed until 2
growing seasons following herbicide treatment. A moderate grazing treatment was designed
to take a maximum of 50% of the annual herbaceous production between two grazing
seasons in the growing and dormant seasons in July and January, respectively, starting in
January 2002. Due to logistical constraints, there was no growing season grazing in 2009 or
2010. Because grass production differed substantially between the tebuthiuron-treated and
control plots, cattle grazed for approximately 300 animal-days per plot on the control areas
and 2,000 animal-days per plot of the tebuthiuron-treated areas to achieve similar grazing
intensity within each treatment combination.
To allow for inference beyond the study site, the experimental design was a combined
completely randomized design with a systematic application of treatments following random
assignment of initial treatment combination (Cochran and Cox 1957, Smythe and Haukos
2009). The four treatments were treated/grazed, treated/not grazed, not treated/grazed, and
not treated/not grazed, with the latter serving as an experimental control. My independent
variables were herbicide treatment (two levels of treated and untreated) and grazing (two
levels of grazed and non-grazed). These were considered fixed effects and the replicates of
the treatments were treated as random effect. There were four replicates for each treatment,
totaling 16 plots in the study (Fig. 1.2).
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Mammals
Small mammals were sampled monthly from June through September with 800 trap
nights per plot per year (except for 2005 and 2010 when there were only 600 trap nights).
Sherman live traps (7.6 x 7.6 x 22.9 cm) were used on each study plot. Four plots, one from
each treatment combination, were trapped at the same time. Within each study plot, forty
traps were placed 25.4 cm apart in each cardinal direction. A trapping period was five nights
with traps baited near dusk and checked in the early morning to minimize mortality
associated with capture. Mammals were identified, individually marked, and released. Traps
were baited with rolled oats dampened to make a paste (2001-2006) and pelleted horse feed
(2007-2010) (Cramer et al. 2002). Sites were surveyed in random order, with all sites being
surveyed once before any other was surveyed a second time. All small mammals captured
were identified to species.
Herptiles
Reptiles and amphibians were trapped from May to September with 960 trap nights
per plot per year (except 2005 and 2010 had 480 trap nights). Reptiles and amphibians were
captured with pitfall and funnel traps that were checked each morning, identified by species,
individually marked, and released. Four 7.62 m silt erosion drift fences were placed in each
cardinal direction with a 15.4 m gap between fences. Pitfall traps were 7.51 l jugs buried at
the end of each line of drift fence. Funnel traps were placed in the middle and on both sides
of the drift fence, for a total of eight traps on each study area. Wooden boards (20.32 by
40.64 cm and 40.64 by 60.96 cm) were placed in traps to provide shade and reduce heat
stress of captives. All captured individuals were identified to species.
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Invertebrates
Invertebrate samples were collected in April, during avian nest initiation, and June,
when avian broods become active. Samples were collected in each study plot with a
terrestrial vacuum sampler (Harper and Guynn 1998). Five samples were collected from each
study plot with a 0.5 by 0.5 m box placed at 10-m intervals in a randomly selected direction.
All samples were sorted into taxonomic orders and dried at 40°C for 48 hours with a 2002
Cabela's Commercial Food Dehydrator (160 liter-89 cm x 44 cm x 60 cm) to a constant mass,
and then weighed on a 2002 ChargeMaster 1500 scale to the nearest 0.01 g. Invertebrates
were identified to the order and production was recorded as kg/ha.
Statistical Methods
In order to evaluate the mammal and herptile community’s response to herbicide and grazing, I calculated dominance (1- Simpson’s index) and diversity as measured with Shannon’s indices (Magurran 1988). Dominance measures are weighted toward the
abundances of the commonest species and diversity increases as dominance increases.
Simpson’s index specifically measures the probability that any two individuals drawn at
random from an infinitely large community will belong to different species. Shannon’s index is weighted toward more rare species and looks at the evenness of the abundances of species.
To examine how individual species may be affected by herbicide and grazing, I
focused analysis on community and species-specific variables that were dependent variables
in the model. The community variables were abundance, dominance, and diversity of
mammals and herptiles as well as number of invertebrate taxonomic groups. I also
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considered the three most abundant mammals and herptiles as well as the most abundant
invertebrates in terms of biomass and total number of invertebrates.
Because soil moisture exerts a relative influence for each dependent variable,
determination of a relevant precipitation index for each dependent variable was necessary to
create a covariate that removed the maximum amount of variation due to annual
precipitation. This enabled me to test the relative effects of the treatments while minimizing
the effect of annual precipitation, which varied from 21-82 cm during the study (Fig. 4.1).
For each dependent variable, I tested four indices of precipitation that are potentially
biologically relevant, using 1 April and 1 October as the start and end of the growing season,
respectively. These four indices were previous 12-month precipitation (1 April to 31 March),
spring/summer precipitation (1 April to 30 September), and two measures of winter
precipitation (1 October to 31 March and 1 November to 31 March). Historically, from 19812010, the average precipitation from April to March was 42.45 cm, from April to October
was 36.3 cm, from October to March was 9.77 cm, and from November to March was 6.16
cm (WRCC, 2010). I chose two different indices of winter precipitation as it has been used as
a predictor variable for topographic features in the region (Brown et al. 2002). I tested
growing-season precipitation because plant structure may be related to growth during the
previous growing season. I also tested annual precipitation, which is a combination of spring
and winter precipitation.
Precipitation was treated as a continuous annual fixed effect. For each dependent
variable, I used Akaike Information Criterion for small samples (AICc) to rank the models
containing the 4 precipitation indices to determine the index with the greatest influence in the
models (Anderson and Burham 1997). The resultant precipitation measure from the highest
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ranked model was then used as a covariate in an analysis of covariance (ANCOVA) to
remove the effect of variation in annual precipitation prior to testing the main effects of
herbicide treatment (treated vs. untreated) and grazing (grazing vs. non-grazed) as well as the
their interaction. Data were tested for normality (Shapiro-Wilk Test) and homogeneity of
variance (Levene’s Test and Welch’s Test) (Cochran and Cox 1957). Independence was assumed, as the samples were randomly selected. The Satterthwaite approximation was used
to pool variances, if the variance estimates among the independent variables of herbicide
treatment, grazing, and herbicide*grazing were homogeneous (Zar 2009). If the precipitation
covariate was significant (P< 0.05), I used simple linear regression to evaluate the strength of
the influence of the precipitation measure on the dependent variable. I performed statistical
analyses using PROCMIX in SAS 9.2 (SAS Institute, Cary, North Carolina, USA).
Results
When assessing the data collected over a ten year period, 14 mammal species were
detected, but occurred inconsistently across treatments (Table 3.1), 21 herptile species with
the most found in treated/grazed areas (Table 3.2), and 45 taxonomic groups of invertebrates
(Table 3.3). It is important to note that some Perognathusspp. could not be identified to
species, so were pooled into genus in 2009 and 2010. There were no trends that fit all species
and most reactions to herbicide and grazing were species-specific. The most abundant
mammals were Ord’s kangaroo rat (Dipidomis ordii), spotted ground squirrel (Spermophilus
spilosoma), and pocket mouse species (Perognathus spp.). The most abundant herptiles were
prairie lizard (Sceloporus lecontei), Great Plains skink (Eumeces obsoletus), and coachwhip
(Masticophis flagellum). The most abundant invertebrate taxonomic groups were
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grasshoppers (Acrididae), treehoppers (Acrididae), and caterpillars (Lepidoptera larvae).
Mammal abundance
Winter precipitation from October to March was the highest ranked precipitation
measure and used as the covariate in the analysis of abundance of small mammals (Tables
3.4 and 3.5). The effect of precipitation was significant in the ANCOVA (F7, 83=19.26,
P<0.0001). Winter precipitation had weak predictive power for variation in small mammal
abundance (r2 =0.11; F1, 125=15.54, P =0.001; Fig. 3.2). There was no herbicide effect (F1,
95=0.0,
P =0.99; Table 3.6) on abundance, but there was a significant grazing effect (F1,
95=3.94,
P =0.05) such that mammal abundance increased by 23% on grazed areas compared
to non-grazed areas. There was no herbicide and grazing interaction effect (F1, 95=0.06, P
=0.82).
Dominance of mammals (1-Simpson’s index)
Winter precipitation from November to March was the highest ranked precipitation
measure and used as the covariate in the analysis of Simpson’s index for mammals in the model (Tables 3.4 and 3.5). However, it offered little explanatory power because there was
no apparent precipitation effect in the ANCOVA (F 7, 88=0.88, P =0.53). There was not an
herbicide (F1, 88=0.23, P =0.63; Table 3.6) or grazing effect (F1, 88=0.06, P =0.81) on patterns
of species dominance. There was no herbicide and grazing interaction effect (F1, 88=0.57, P
=0.45) on the Simpson’s index for small mammals.
Diversity of mammals (Shannon’s index)
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Winter precipitation from November to March was the highest ranked precipitation
measure and used as the covariate in the analysis of Shannon’s index for mammals in the model (Tables 3.4 and 3.5). There was little explanatory power because of the marginally
significant precipitation effect in the ANCOVA (F 7, 95 =1.95, P =0.07). There was no
significant effect of herbicide (F1, 95=0.18, P =0.67; Table 3.6), or grazing (F 1, 95=1.17, P
=0.28) on diversity. There was a marginal herbicide and grazing interaction (F1, 95=3.26, P
=0.07) on the Shannon’s index for small mammals. In herbicide-treated areas, mammal
diversity increased by 13% in grazed areas compared to non-grazed. However, in untreated
areas, diversity decreased by 39% in grazed areas relative to non-grazed. In grazed areas,
mammal diversity increased by 50% in treated areas compared to untreated. On the other
hand, non-grazed areas had 18% less mammal diversity in treated areas as compared to
untreated areas. This indicates that there was the most mammal diversity in treated and
grazed areas.
Ord’s kangaroo rat (Dipidomis ordii) abundance
Winter precipitation from October to March was the top ranked precipitation index
for kangaroo rat abundance (Tables 3.4 and 3.7). There was a significant effect of
precipitation index in the ANCOVA (F8, 108=6.23, P<0.0001). The precipitation index had a
statistically significant slope (r2 =0.07; F1,142=10.51, P =0.002; Fig. 3.1). There was no
herbicide effect (F1,108=0.00, P =0.95; Table 3.6). There was a significant grazing effect
(F1,108=4.44, P=0.04) such that kangaroo rat abundance increased 35% in grazed areas as
compared to non-grazed areas (Fig. 3.5). There was no herbicide and grazing interaction
effect (F1, 108=0.08 P =0.89)
Ground squirrel (Spermophilus spilosomoa) abundance
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Winter precipitation from October to March was the highest ranked precipitation
index relative to ground squirrel abundance (Tables 3.4 and 3.7). The winter precipitation
index was significant in the ANCOVA (F8, 108=3.75, P=0.0007). However, the selected
precipitation index was a weak predictor of ground squirrel abundance despite a significant
slope (r2=0.06; F1,142=8.76, P =0.004; Fig. 3.6). There was a herbicide effect (F1, 108=4.44,
P=0.037; Table 3.6), such that the abundance of ground squirrels increased by 49% in treated
areas as compared to untreated areas. There was no grazing effect (F1, 108=0.77, P=0.38), nor
was there an herbicide and grazing interaction effect (F1, 108=0.0, P=0.96).
Pocket mouse species (Perognathus sp.) abundance
Winter precipitation from October to March was highest ranked index for pocket
mouse species abundance (Table 3.7 and Table 3.4). Precipitation was significant in the
ANCOVA (F8, 108=23.77, P<0.0001). Despite a significant slope, winter precipitation was a
weak predictive variable of pocket mouse species abundance (r2=0.06; F1,142=9.42, P
=0.003). There was an herbicide effect (F8, 108=3.48, P=0.06; Fig. 3.7; Table 3.10), such that
pocket mouse abundance was 42% greater in treated areas as opposed to untreated areas.
There was no grazing effect (F1, 108=0.48, P=0.49), nor herbicide and grazing interaction
effect (F1, 108=0.79, P=0.38).
Herptile abundance
Winter precipitation from October to March was the highest ranked precipitation
index for the abundance of herptiles (Table 3.8 and 3.9). The effect of precipitation index
was significant in the ANCOVA (F7, 32=10.10, P<0.0001). This index had predictive power
for herptile abundance (r2=0.20; F1, 62=15.54, P =0.002; Fig. 3.8). There was no herbicide
effect (F1, 32=0.25, P =0.62; Table 3.10), nor was there a grazing effect (F1, 60=0.34, P=0.56).
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There was a marginal herbicide and grazing interaction effect (F 1, 32=3.72, P =0.06; Fig.
3.9). In treated areas, herptile abundance decreased by 8% in grazed areas as compared to
non-grazed areas. However, in untreated areas, herptile abundance increased by 27% in
grazed areas compared to non-grazed areas. In grazed areas, herptile abundance decreased by
13% in treated areas relative to untreated areas. Non-grazed areas had 20% more herptile
abundance in treated areas as compared to untreated areas. This indicates that herptile
abundance was greatest in treated and grazed areas.
Herptile dominance (1-Simpson’s index)
Winter precipitation from October to March was the highest ranked precipitation
index in the analysis of the Simpson’s diversity index for herptiles (Tables 3.8 and 3.9). The
effect of winter precipitation was only marginally significant in the ANCOVA (F7, 32=2.20, P
=0.06). Furthermore, precipitation was not predictive for Simpson’s index for herptiles (r2
=0.027; F1, 62 =1.75, P =0.19; Fig. 3.8). There was an herbicide effect (F1, 32=4.91, P =0.03;
Table 3.10). Herptile diversity, measured by the Simpson’s index, increased by 7% in treated areas as compared to untreated areas (Fig. 3.10). There was no grazing effect (F1, 32=0.77, P
=0.39), nor was there an herbicide and grazing interaction effect (F1, 32 =1.81, P =0.19).
Herptile diversity (Shannon’s index)
Winter precipitation from November to March was the highest ranked precipitation
index for Shannon’s index for herptiles (Table 3.8 and 3.9). However, there was not a
significant effect of precipitation in the ANCOVA (F7, 32 =0.87, P=0.54). There was no
herbicide effect (F1, 32 =2.43, P=0.13; Table 3.10), grazing effect (F1, 32 =1.12, P=0.30), nor
an herbicide and grazing interaction (F1, 32 =1.01, P=0.32) for Shannon’s index (Fig. 3.11).
Prairie lizard (Sceloporus lecontei) abundance
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Winter precipitation from October to March was the highest ranked precipitation
index for prairie lizard abundance (Tables 3.8 and 3.11). There was a significant precipitation
effect in the ANCOVA (F8, 36=15.88, P<0.0001). Winter precipitation was statistically
significant for prairie lizard abundance (r2=0.12; F1, 70 =9.43, P =0.003; Fig. 3.8). There was
a significant herbicide effect (F1, 36=4.80, P=0.03; Table 3.10) such that there were 23%
fewer prairie lizards treated areas than in untreated areas (Fig. 3.12). There was no grazing
effect (F1, 36=2.32, P=0.14), nor was there a herbicide and grazing interaction (F1, 68=0.03,
P=0.85).
Great Plains Skink (Eumeces obsoletus)abundance
Winter precipitation from November to March was the highest ranked precipitation
index for skink abundance (F8, 25=6.22, P<0.0001; Tables 3.8 and 3.11). However, the
precipitation index did not have predictive power despite a significant regression model
(r2=0.01; F1, 62=7.73, P =0.007; Fig. 3.8). There was a significant herbicide effect (F1,
36=5.31,
P=0.027; Table 3.10), a significant grazing effect (F1, 36=8.90, P=0.005), and a
significant herbicide and grazing interaction effect (F1, 36=4.32, P=0.04). In treated areas,
skink abundance increased by 93% in grazed areas as compared to non-grazed areas. In
untreated areas, skink abundance increased by only 18% in grazed areas. In grazed areas,
skink abundance increased by 71% in treated areas as compared to untreated areas. In nongrazed areas skink abundance only increased by 4% in treated areas. This indicates that the
most skinks were found in areas that were both treated with herbicide and grazed.
Coachwhip (Masticophis flagellum) abundance
Winter precipitation from November to March was the highest ranked precipitation
index for coachwhip abundance (Table 3.11 and Table 3.8). However, the winter
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precipitation index was not a significant covariate in the ANCOVA (F1, 68=1.33, P=0.26).
There was no herbicide effect (F1, 36=2.35, P=0.13; Table 3.10), grazing effect (F1, 36=1.45,
P=0.24), nor an herbicide and grazing interaction effect (F1, 36=2.02, P=0.16) for coachwhip
abundance.
Invertebrate abundance
Winter precipitation from October to March was highest ranked precipitation index
for the abundance of invertebrates (Table 3.13). There was an effect of precipitation in the
ANCOVA (F7, 96=15.57, P<0.0001). The winter precipitation index was significant for
invertebrate abundance (r2=0.28; F7, 84=50.09, P<0.0001; Fig. 3.15). There was a significant
herbicide effect (F 1,96=9.94, P =0.002; Fig. 3.16) such that the total number of invertebrates
increased by 54% in treated areas as compared to untreated areas. There was no grazing
effect (F1, 96=1.53, P =0.22), nor was there a herbicide and grazing interaction effect (F1,
96=0.04,
P =0.86).
Number of invertebrate taxonomic groups
Winter precipitation from October to March was the highest ranked precipitation
index for the number of invertebrate taxonomic groups. There was a significant precipitation
effect in the ANCOVA (F8, 105=29.23, P<0.0001). The relationship between number of
taxonomic groups and precipitation was biologically relevant (r2=0.34; F1, 139=71.06,
P<0.0001; Fig. 3.15). There was a significant herbicide effect (F1,105=33.33, P<0.0001) such
that the number of invertebrate taxonomic groups increased 25% in treated areas as
compared to untreated areas. There was no grazing effect (F1, 105=0.02, P =0.88), nor was
there a herbicide and grazing interaction effect (F1, 105=1.01, P=0.31).
Invertebrate biomass
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Winter precipitation from October to March was the highest ranked precipitation
index for in invertebrate biomass (Table 3.13). Winter precipitation index was a significant
covariant in the ANCOVA (F7, 84=8.17, P<0.0001). This precipitation index explained a
marginal amount of variation in invertebrate biomass (r2=0.17; F1, 126=25.60, P<0.0001; Fig.
3.15). There was not a significant herbicide (F1, 96=2.71, P=0.10) or grazing effect (F1,
96=1.12,
P=0.29). There was no herbicide and grazing interaction effect (F1, 96=0.44, P =0.51)
(Fig. 3.18).
Grasshopper (Acrididae)
Winter precipitation from November to March was the highest ranked precipitation
index for grasshopper biomass (Table 3.15). Winter precipitation was a significant covariate
(F7, 96=13.30, P<0.0001). However, this precipitation index explained little variation in
grasshopper biomass (r2=0.0004; F1, 126=0.05, P=0.82; Fig. 3.15). There was a significant
herbicide effect (F1, 96=13.17, P=0.0005), such that grasshoppers increased by 200% in
treated areas as compared to untreated areas. There was no grazing effect (F1, 96=2.08,
P=0.15), nor was there a herbicide and grazing interaction effect (F1, 96=1.93, P =0.17) (Fig.
3.19).
Treehopper (Acrididae)
Winter precipitation from October to March was the highest ranked precipitation
index for treehopper biomass (Table 3.15). Winter precipitation was significant (F7, 96=13.35,
P<0.0001). This precipitation index explained a marginal amount of variation in treehopper
biomass (r2=0.15; F1, 126=23.50, P<0.0001; Fig. 3.15). There was not a significant herbicide
(F1, 96=1.1, P=0.30) or grazing (F1, 96=0.02, P=0.90) effect. There was no herbicide and
grazing interaction effect (F1, 96=0.24, P =0.63) (Fig. 3.20).
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Caterpillars (Lepid)
Winter precipitation from November to March was the highest ranked precipitation
index for caterpillar biomass (Table 3.15). Winter precipitation was significant as a covariate
(F7, 96=4.72, P<0.0001). This precipitation index did not explain variation in caterpillar
biomass (r2=0.004; F1, 126=0.47, P=0.49; Fig. 3.12). There was a significant herbicide effect
(F1, 96=13.53, P=0.0005), such that caterpillars decreased by 92% in treated areas as
compared to untreated areas. There was no grazing effect (F1, 96=0.16, P=0.69), nor was there
a herbicide and grazing interaction effect (F1, 96=0.01, P =0.93) (Fig. 3.21).
Discussion
Mammals
There were fourteen species of small mammals captured on our study site. It is
important to note that the capture techniques with Sherman live traps prevented capture of
species past a certain size. So, larger mammals such as western cottontail rabbits (Svlvilagus
auduboni) and blacktail jackrabbits (Lepus californicus) were excluded. Shrews (Sorex
araneus) were also excluded from trapping because they are carnivorous and, therefore,
unlikely to go into a grain-baited Sherman trap.
Another study that tested the effects of shrub removal with similar rates of
tebuthiuron in shinnery oak communities in Yoakum County, Texas, Colbert (1986) found 16
mammals of all sizes, seven of which were also found in our study. Similarly in the same
area, Johnson (2002) found 7 species that overlapped with our study site, some of which
were not found by Colbert (1986).
Precipitation from October or November to March had the strongest influence on the
mammalian species parameters assessed, with the exception of mammal dominance and
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diversity. Willig (1993) found that mammal abundance was related to behavioral responses
to temperature and precipitation. Munger et al. (1983) determined that increases in rodent
abundance are due to annual plant growth, especially of annuals, that follow favorable rains.
However, Mathis (2006) recognized that desert rodents have a complex, yet undeniable
relationship with precipitation, which may explain why all variables were not more
influenced by winter precipitation.
I found no significant herbicide effect of overall abundance of small mammals.
However, there was 23% greater abundance of small mammals in grazed areas compared to
non-grazed areas. This phenomenon was likely driven by the abundance of Ord’s kangaroo rats, which made up 52% of all mammals, and also had a significant grazing effect. Although
there was no apparent effect of the herbicide treatment when all mammals were combined,
pocket mice and ground squirrels, which made up 21% and 17% of total abundance, appear
to have responded positively to changes due to herbicide treatment, such that they increased
in treated areas by 42% and 49%, respectively.
These results are consistent with the literature that indicates that vegetative structure,
whether manipulated by grazing or shrub removal, is important to rodent abundance and
distribution. Vegetation is a source of cover and food for rodent populations (Paramenter
and MacMahon 1983). Johnson and Hansen (1969) found that herbicide treatment affected
rodent populations through changes in the availability of food. Cover is also a main factor
affecting rodent populations in arid and semi-arid environments (Rosenzweig and Winakur
1969, Parmenter and MacMahon 1983, Willig 1993). Hafner (1977) believed that desert
rodent species do not respond to a particular parameter because even animals of the same
species are influenced by different environmental factors. It is reasonable to assume that
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small mammals in the region will respond to grazing differently based on any of the
aforementioned factors.
Grazing regimes have marked effects on the shaping of vegetation in arid regions
(Eccard 2000). Munger (1983) found that physiognomy, or vegetation structure, is an
important factor of desert rodent distribution. I found that there was 23% greater abundance
of all mammals combined in grazed areas. At the same stocking rate, which was designed to
remove 50% of available production, Mathis et al. (2006) found that there was no difference
in species richness between grazed and non-grazed areas 1-3 years after grazing commenced
in Las Cruces, New Mexico. However, Mathis et al. (2006) did not include an element of
shrub removal, which drastically increases the amount of grasses and changes the plant
composition and structure of the community (Chapter II).
Tebuthiuron drastically alters the habitat by changing cover, food resources, foliage
height diversity, and water availability to other plants (Willig 1993). Studies that tested the
effect of shrub removal on rodent populations have had mixed results. Using 0.56 kg/ha
tebuthiuron, Willig (1993) found that rodent diversity was greater in treated areas that
exhibited greater canopy cover and vertical height in Yoakum County, Texas, 2 to 3 years
after treatment. Although the grasshopper mouse was more common in untreated areas, this
was largely driven by more than double the number of detections among grazed plots
compared to non-grazed plots. These results indicate that, not surprisingly, the effects of
herbicide treatments are species-specific and, depending on the time of year of trapping,
different animals will be more abundant (Willig 1993). Similarly, Johnson and Hansen
(1969) found that responses to herbicide were species-specific when using 1-1.5 kg/ha in the
shrub-grass range of western Colorado. In their study, deer mice (Peromyscus maniculatus)
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were not affected by herbicide whereas pocket gophers (Thomomys talpoides) and
chipmunks (Eutamias minimus) decreased in treated areas.
Kangaroo rats are generalist species (Willig 1993) and have been characterized as a
“superior competitor” (Parmenter and MacMahon 1983, Muenger 1983). Kangaroo rats
avoid areas with thick cover and are associated more frequently with sparse vegetation
(Willig 1993). Rosenzweig (1973) found that shrub removal permitted increased use of the
cleared areas by kangaroo rats. Similarly, our study found that kangaroo rats were more
abundant in areas with increased bare ground. There was 28% more bare ground in grazed
plots in our study, which may explain why there are more kangaroo rats in grazed areas.
There were 42% more pocket mice in treated areas than untreated areas. This is
likely because pocket mouse species tend to inhabit areas of high vegetation and coarse
substrate types, while kangaroo rats tend to inhabit more open microhabitats and finer
substrates (Munger et al. 1983). Parmenter and MacMahon (1983) found that the presence of
kangaroo rats in open areas evidently precludes pocket mice from foraging there
simultaneously. They found that shrubs can function as a mediating variable in interspecific
competition among rodents. While the interspecific competition between rodents is beyond
the scope of this thesis, it may offer insights as to why kangaroo rats and pocket mice
respond differently to grazing and herbicide treatments.
Similar to pocket mice, ground squirrels were 49% more abundant in treated areas
with few shrubs as compared to untreated areas this a high density of shrubs. Parmenter and
MacMahon (1983) found that while pocket mice and ground squirrels will climb shrubs to
forage, they do not require it. Their study in southwest Wyoming was based on sampling
before, and one year after, hand-shrub removal. However, they report that density and
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percent cover in shrubs was essentially the same in treated and untreated plots, so it follows
that there were no effects of shrub removal evident in rodent abundance.
Herptiles
Winter precipitation had the strongest influence on the herptile species parameters
assessed, with the exception of overall herptile diversity and coachwhip abundance. All
significant relationships were positively associated with winter precipitation such that
herptile abundance increased with precipitation.
The three most abundant species, prairie lizard, Great Plains skink, and coachwhip,
reacted differently to herbicide and grazing treatments. The result of herbicide treatment
appears to have influenced the vegetation community such that lizards were 22% less
abundant in treated areas. Skinks were influenced by an interaction effect and were more
abundant in treated/non-grazed and not treated/grazed areas. Coachwhip snakes were not
affected by either treatment. While each species reacted differently toward herbicide and
grazing treatment, they are likely reacting to changes in vegetation (Jones 1981). Complexity
of vegetation may affect predation risk, food abundance, or thermoregulatory functions
(Daryanto et al. 2012, Castellano 2006). Thus, it is difficult to discern why species are
reacting toward treatments differently.
The prairie lizard and Great Plains skink were the two most abundant species,
accounting for 28% and 26%, respectively, of all herptiles captured. The prairie lizard was
found mostly in not treated/non-grazed areas, with 22% less abundance in treated areas.
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Texas Tech University, Jennifer Zavaleta, May 2012
Prairie lizards are a generalist species that can be found in all treatments, but perhaps prefer
untreated areas.
I found that Great Plains skink was most abundant in treated-grazed areas, which had
a composition of mainly grasses with some shrubs and forbs, and was most similar to
historical standards (Chapter IV). A similar response was also found in relative lizard
abundance in Arizona. Castellano (2006) found that changes in vegetation structure
complexity and perennial grass cover were positively correlated with lizard relative
abundance. When describing the habitat of skinks, Fitch (1955) found that skinks favored
vegetation types and conditions that were created by the combination of burning and heavy
grazing. Though not exactly the same as burning and grazing, herbicide treated and grazed
areas may create similar vegetation composition. However, he noted, in xeric conditions
where vegetation is sparse because of severe burning or overgrazing, the skinks will be
sparse. This indicates that there is a threshold of grazing, and perhaps also tebuthiuron. When
these treatments are overused, they will no longer benefit skink abundance.
The coachwhip snakes were not influenced by either herbicide or grazing. This is
unsurprising since coachwhip snakes are widely foraging, diurnal predators that “cruise through habitat searching for active and sedentary prey” (Secor 1995). Similarly, Castellano (2006) found that widely foraging species may benefit from increased vegetative structure
complexity to a lesser extent than opportunistic or “sit and wait” predators. It is important to recognize that species have individual responses to herbicide and
grazing when designing management strategies. One theme that has been consistent in the
literature is that lizard abundance and diversity is reduced in heavily grazed sites because of
changes in vegetative structure (Jones 1981, Castellano 2006). Jones (1981) thought it was
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Texas Tech University, Jennifer Zavaleta, May 2012
due primarily loss of low-height vegetation and Castellano(2006) suspected it was due to a
lack of forbs and lessened perennial grass cover. Thus, it is important to maintain moderate
grazing even if the effects of herbicide and grazing appear mixed.
Invertebrates
Although many animals use invertebrates as a food source, little is known about the
ecology of invertebrates in shinnery oak communities (Haukos and McDaniel 2011). I found
> 47 taxonomic groups in the data. This is a substantive increase from the 23 families
reported in the shinnery oak community by Haukos and McDaniel (2011) likely because we
sampled for 10 years.
The highest-ranking precipitation model for all invertebrate variables was winter
precipitation from either October or November until March. Also, the linear relationship
between winter precipitation and invertebrate abundance and number of families explained a
moderate amount of variation, which was among the highest relationships for all fauna.
Biomass and tree hopper abundance was explained only slightly by varying precipitation.
Because many invertebrates require water for their life cycle, it is unsurprising that
precipitation is linked to abundance and biomass. What is surprising about this relationship,
however, is that the relationship is negative, which is not intuitive. Similarly, Haukos and
McDaniel (2011) found that overall biomass fluctuations were not related to annual
precipitation. Joern (2004) found that weather significantly contributed to grasshopper
population dynamics. These mixed results indicate that the relationship between precipitation
and biomass and abundance of invertebrates is complicated.
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Texas Tech University, Jennifer Zavaleta, May 2012
There was a significant herbicide effect on both invertebrate abundance and the
number of families such that each increased by 54% and 25% in treated areas compared to
untreated areas, respectively. This is slightly different from Doerr and Guthery (1983), who
studied the effects on invertebrate biomass and diversity immediately and a year after plots
had been treated with 5 rates of tebuthiuron (0.2, 0.4, 0.6, 0.8, 1.0 kg/ha). They found that the
abundance and diversity of insects were slightly, positively affected by tebuthiuron
treatments when using sweep nets. When using pitfall traps, they found that total insects as
well as grasshoppers were positively affected by treatment. They noted that more samples
were needed given the high variation. The high variation may be due to the timing of Doerr
and Guthery’s (1983) experiment. It is possible that not enough time had elapsed between
treatment and the data collection for the subsequent changes in plant composition and
structure to be taken into account.
Invertebrate abundance is highly patchy and dependent on herbaceous cover and
structure (Hagen et al. 2005, Baines et al. 1996). Jamison (2002) suggests that invertebrate
biomass varies with the composition and structure of vegetation. A positive relationship
between invertebrate biomass and forb presence has also been established (Boyd and Bidwell
2001, Jamison 2002, Hagen 2005). My study is consistent with these earlier reports. Treated
areas had 257% greater abundance of forbs than untreated areas and invertebrate abundance
and number of invertebrate taxonomic groups increased 54% and 25%, respectively.
Similarly, Jamison (2002) found that of all composition variables, forbs had the strongest
association with invertebrate biomass. In the case of prescribed fire, Boyd and Bidwell
(2001) reported concurrent increases in forb cover and grasshopper densities. Doerr and
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Texas Tech University, Jennifer Zavaleta, May 2012
Guthery (1983) found a positive but statistically insignificant trend of forbs and invertebrate
biomass, which as discussed may be due to the short sampling time after treatment.
With regression modeling, Jamison (2002) determined that shrubs were the least
important determinants of invertebrate biomass. This indicates that the consequent forb and
grass production, either in what it provides physiologically or in terms of structure, is more
important to the invertebrate community than the immediate removal of shrubs. Baines
(1996) found that taller vegetation yielded more invertebrates in the United Kingdom. Our
results support this because visual obstruction, measured with a Robel pole, was 30 and 50%
higher in treated areas than in untreated areas in April and June, respectively.
Individual invertebrate taxonomic groups reacted differently to treatment.
Grasshoppers increased 200% and caterpillar larvae decreased by 92% in treated areas as
compared to untreated areas, while treehoppers seemed to not be affected at all. The increase
of grasshoppers in treated areas is positively associated with grass growth in treated areas.
There were 200% more grasshoppers in treated areas that had 149% more grass than
untreated areas. Conclusions about grasshopper abundance are supported by Hagen (2005)
who found that sand sage density was the best linear predictor of grasshopper biomass, with
lower densities of tebuthiuron (0.2-0.4 k/ha) having the most grasshopper biomass. While
there is a correlation between grasshoppers and grass, areas that were managed to maximize
grass cover usually led to reductions in invertebrate biomass (Baines 1996, Hagen 2005).
Understanding the habitats in which invertebrates flourish is important for wildlife
management. It has been found that prairie chicken nesting areas, for example, have higher
invertebrate biomass than associated random points (Hagen 2005, Jamison 2002). Parmenter
and MacMahon (1983) found that insects were also important for rodent community and
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Texas Tech University, Jennifer Zavaleta, May 2012
structure. Though directly influencing the numbers and types of invertebrates is challenging,
vegetation can be managed such that it is conducive to supporting complex invertebrate
communities. This would be facilitated by establishing mixed-grass prairies that have a forb
component because invertebrates are correlated with forb abundance. It is also important to
apply herbicide in low doses (0.2-0.6 kg/ha) as there was more invertebrate biomass
associated with lower rates of tebuthiuron (Doerr and Guthery 1983, Hagen 2005). The lower
rate is suggested not because it is less toxic during application, but because the long-term
benefits of mixed-grass prairie are more apparent with lower doses.
Conclusions
This study provides a comprehensive list of mammals, herptiles, and invertebrates
that can be found in sand shinnery oak community in eastern New Mexico. Mammal
abundance was influenced positively by a grazing effect, herptile diversity was negatively
affected by herbicide effect, and the abundance and biomass of invertebrates was positively
associated with herbicide. It is important to note that while many of the overall variables that
combined species into one category like abundance, dominance and diversity were not
significant. However, when parsed out to a species-level examination, it becomes clear that
species respond differently to herbicide and grazing treatments. Mammals, herptiles and
invertebrates reaction is likely associated with changes in vegetation composition and
structure that result from herbicide and grazing. This indicates that further investigation on
the species-level will be necessary to make more informed management decisions. It is also
important that to note that management of mammals, herptiles, and invertebrates may be best
administered through changes in plant composition and structure.
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Texas Tech University, Jennifer Zavaleta, May 2012
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tetrix and Capercaillie Tetrao urgogallus and distribution of insect food for the chicks.
Ibis 138: 181-187.
Boyd, C. S. and T. G. Bidwell. 2001. Influence of prescribed fire on lesser prairie-chicken
habitat in shinnery oak communities in western Oklahoma. Wildlife Society Bulletin
29: 938-947.
Brown, J. H. and Z. Zongyong. 1989. Comparative population ecology of eleven species of
rodents in the Chihahuan Desert. Ecological Society of America 70 (5):1507-1525
Castellano, M. J. and T. J. Valone. 2006. Effects of livestock removal and perennial grass
recovery on the lizards of a desertified arid grassland. Journal of Arid Environments
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Colbert, R. L. 1986. The effect of the shrub component on small mammal populations in a
sand shinnery oak ecosystem. Thesis, Texas Tech University, Lubbock pp. 57.
Daryanto, S. and D. J. Eldridge. 2012. Shrub hummocks as foci for small animal disturbances
in an encroached shrubland. Journal of Arid Environments 80: 35-39.
Doerr T. B. and F. S. Guthery. 1983. Effects of tebuthiuron on lesser prairie chicken habitat
and food. Journal of Wildlife Management 47:1138-1142.
Eccard, J. A., R. B. Walther, and S. J. Milton. 2000. How livestock grazing affects vegetation
structures and small mammal distribution in the semi-arid Karoo. Journal of Arid
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Fitch, H. S. 1955. Habitats and adaptations of the Great Plains skink (Eumeces obsoletus).
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Hafner, M. S. 1977. Density and diversity in Mojave Desert rodent and shrub communities.
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Hagen, C. A, G. C. Salter, J. C. Pitman, R. J. Robel, and R. D. Applegate. 2005. Lesser
prairie-chicken brood habitat in sand sagebrush: invertebrate biomass and vegetation.
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Haukos, D. A. 2011. Use of tebuthiuron to restore sand shinnery oak grasslands of the
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and mode of action (103-124). Rijeka, Croatia.
Haukos, D. A., andP. McDaniel. (2011). Results of long-term monitoring of lesser prairiechicken habitat on the Milnesand Prairie Preserve, The Nature Conservancy of New
Mexico. The Nature Conservancy, Santa Fe, New Mexico.
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Jamison, B. E., R. J. Robel, J. S. Pontius, and R. D. Applegate. 2002. Invertebrate biomass:
associations with lesser prairie-chicken habitat use and sand sagebrush density in
southwestern Kansas. Wildlife Society Bulletin 30: 517-526.
Joern, A. 2005. Disturbance by fire frequency and bison grazing modulate grasshopper
assemblages in tallgrass prairie. Ecology 86: 861-873.
Johnson, D. R. and R. M. Hansen. 1969. Effects of range treatment with 2, 4-D on rodent
populations. The Journal of Wildlife Management 33: 125-132.
Jones, K. B. 1981. Effects of grazing on lizard abundance and diversity in western Arizona.
Southwestern Association of Naturalists 26 (2): 107-115.
Parmenter, R. R. and J. A. MacMahon. 1983. Factors determining the abundance and
distribution of rodents in a shrub-steppe ecosystem: the role of shrubs. Oecologia 59:
145-156.
Mathis, V. L., W. G. Whitford, F. R. Kay, and P. U. Alkon. 2005. Effects of grazing and
shrub removal on small mammals populations in southern New Mexico, USA.
Journal of Arid Environments 66: 76-86.
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affecting abundance, distribution and genetic structure. Great Basin Naturalist
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Rosenzweig, M. L. and J. Winakur. 1969. Population ecology of desert rodent communities:
habitats and environmental complexity. Ecology 50: 558-572.
Rosenzweig, M. L. 1973. Habitat selection experiments with a pair of coexisting heteromyid
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Secor, S. M. 1995. Ecological aspects of foraging mode for the snakes Crotalus cerastes and
Masticophis flagellum. Herpetologsts’ League. 9: 169-186.
Smythe, L. A. and Haukos D. A. 2009. Nesting success of grassland birds in shinnery oak
communities treated with tebuthiuron and grazing in eastern New Mexico. The
Southwestern Naturalist 54(2): 136-145.
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1/1905 to 1/31/2012. http://www.wrcc.dri.edu/cgi-bin/cliMAIN.pl?nm7008 Accessed
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Willig, M. R., R. L Colbert, R. D. Pettit, and R. D. Stevens. 1993. Response of small
mammals to conversion of a sand shinnery oak woodland into mixed-grass prairie.
The Texas Journal of Science 4.
123
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Scientific name
Chaetodipus hispidus
Dipidomis ordii
Geomys bursarius
Neotoma albigula
Neotoma micropus
Onychomysleucogaste
r
Perognathusflavescens
Perognathusmerriami
Perognathus sp.
Peromyscusleucopus
Reithrodontomysmegal
otis
Reithrodontomysmont
anus
Sigmodonhirsutus
Plains harvest mouse
Western harvest mouse
Common name
Hispid pocket mouse
Ord's kangaroo rat
Plains pocket mouse
White throated wood rat
Southern Plains woodrat
Northern grasshopper
mouse
Plains pocket gopher
Merriam's pocket mouse
Perognathus species
White footed mouse
0
0
0
3
21
82
0
16
47
0
5
1
0
24
57
1
16
448
94
2
1
0
0
8
47
0
44
345
71
1
0
0
0
18
66
0
12
1598
275
3
6
1
3
71
252
1
96
Total
11
833
23
4
16
Southern cotton rat
63
348
No Tebuthiuron
Grazed
Non-grazed
1
2
245
157
2
7
0
3
1
0
Spotted ground squirrel
457
Total
In 2009 and 2010 Perognathus species (Pocket mice) were identified to the genus.
Spermophilus
spilosoma
Tebuthiuron
Grazed
Non-grazed
0
8
254
177
7
7
0
1
11
4
Table 3.1. Number of captured mammals during 800 trap nights each year from June to September from 2002-2010 (with 600 trap
nights in 2005 and 2010) in 16 experimental plots consisting of the combinations of (1) tebuthiuron (herbicide) treated – grazed, (2)
tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated – grazed, and (4) non-tebuthiuron treated – non-grazed in eastern New
Mexico.
1
Table 3.2. Number of herptile species trapped for 960 trap nights a year from June to September from 2002-2010 (with 480 trap
nights in 2005 and 2010) in 16 experimental plots consisting of the combinations of (1) tebuthiuron (herbicide) treated – grazed, (2)
124
Texas Tech University, Jennifer Zavaleta, May 2012
2
0
10
25
0
0
6
7
18
0
2
6
0
68
14
8
4
1
73
4
7
2
121
12
2
2
15
373
5
30
2
2
1
3
401
44
27
19
8
253
14
24
23
425
53
12
14
43
1537
40
100
4
4
23
3
Glossy snake
27
10
1
81
9
5
4
1
53
6
2
5
111
11
4
4
16
347
Untreated
Grazed
Non-grazed
1
0
Great Plains toad
Woodhouse's toad
18
1
82
9
6
3
0
57
1
8
9
97
16
3
6
4
344
Treated
Non-grazed
1
Six-lined racerunner
1
170
12
8
8
6
70
3
7
7
96
14
3
2
8
473
Grazed
1
Western (prairie)
rattlesnake
Ringneck snake
Great Plains skink
Western ognosed snake
Lesser earless lizard
Milk snake
Texas blind snake
Coachwhip
Texas horned lizard
Gopher snake
Long nosed snake
Prairie lizard
Masassauga
Plains spadefoot
Plains black headed snake
Ornate box turtle
Total
Tiger salamander
tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated – grazed, and (4) non-tebuthiuron treated – non-grazed in eastern New
Mexico.
Total
Ambystomatigrinum
Arizona
elegansarenicola
Bufocognatus
Bufowoodhousei
Cnemidophorussexlineat
us
Crotalusviridis
Diadophispuctatus
Eumeces obsoletus
HeterodonNasicus
Holbrookiamaculata
Lampropeltistriangulum
Leptotyphlopsdulis
Masticophis flagellum
Phrynosomacornutum
Pituophismelanoleucus
Rhinocheiluslecontei
Sceloporus lecontei
Sistruruscatenatus
Speabombifrons
TantillaNigriceps
Tertapeneornata
125
Texas Tech University, Jennifer Zavaleta, May 2012
Grams
0.453
8.500
Abundance
6.306
0.000
0.345
0.000
0.006
0.001
0.000
0.002
0.061
0.004
0.002
0.017
0.000
0.017
0.002
0.004
0.004
0.008
0.006
0.002
0.005
0.055
0.005
1.151
0.299
Grams
0.519
0.056
2.667
0.000
1.389
0.306
0.250
0.167
2.361
1.586
0.056
2.917
0.000
3.306
0.139
0.972
0.690
1.350
3.172
0.389
0.276
12.944
0.150
25.500
7.778
0.000
0.045
0.000
0.017
0.001
0.000
0.003
0.033
0.008
0.002
0.021
0.000
0.009
0.001
0.003
0.009
0.005
0.006
0.002
0.003
0.121
0.007
2.336
0.513
0.035
2.319
0.021
0.861
0.278
0.236
0.250
1.660
0.841
0.028
2.167
0.038
3.042
0.306
0.715
0.416
1.203
1.752
0.375
0.265
10.389
0.101
23.114
5.514
0.001
0.106
0.001
0.012
0.001
0.001
0.002
0.037
0.004
0.002
0.012
0.000
0.010
0.003
0.002
0.005
0.004
0.004
0.001
0.003
0.070
0.003
1.448
0.270
Total
Grams
Abundance
5.556
0.134
0.028
2.583
0.000
0.806
0.389
0.306
0.333
2.278
0.821
0.028
3.000
0.000
4.611
0.222
1.111
0.429
2.300
2.250
0.417
0.429
9.778
0.200
30.000
Untreated-Grazed
Grams
0.483
2.722
0.001
0.021
0.001
0.012
0.002
0.000
0.002
0.035
0.002
0.000
0.004
0.000
0.005
0.006
0.000
0.005
0.002
0.002
0.001
0.003
0.053
0.000
0.996
Treated-Non-Grazed
Abundance
5.583
0.133
0.028
1.917
0.042
0.583
0.222
0.139
0.167
1.083
0.500
0.000
1.278
0.050
1.694
0.444
0.167
0.357
0.550
0.679
0.194
0.179
11.472
0.050
18.450
Treated-Grazed
3.056
0.002
0.012
0.001
0.013
0.000
0.003
0.002
0.019
0.003
0.004
0.007
0.000
0.008
0.005
0.002
0.002
0.003
0.001
0.001
0.003
0.051
0.000
1.300
0.505
0.028
2.111
0.042
0.667
0.194
0.250
0.333
0.917
0.429
0.028
1.472
0.105
2.556
0.417
0.611
0.179
0.579
0.857
0.500
0.179
7.361
0.000
18.263
Untreated-NonTotal
Grazed
Abundance
Abundance Grams
5.750
0.563
5.799
Table 3.3. Number of invertebrate taxonomic from vacuum sampler in May and June 2002-2010 in 16 experimental plots consisting
of the combinations of (1) tebuthiuron (herbicide) treated – grazed, (2) tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated –
grazed, and (4) non-tebuthiuron treated – non-grazed in eastern New Mexico.
Acrididae (Forb)
Acrididae
(Grass)
Apidae
Arachnids
Asilidae
Blattidae
Braconidae
Bruchidae
Buprestidae
Carabidae
Cercopidae
Chilopoda
Chrysomellidae
Chrysopidae
Cicadellidae
Coccinellidae
Corimelaenidae
Curculionidae
Cydnidae
Dictyopharidae
Diptera
Elateriidae
Formicidae
Gryllidae
Halictidae
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Texas Tech University, Jennifer Zavaleta, May 2012
Grams
0.000
0.002
0.448
0.002
0.001
0.000
0.017
0.001
0.180
0.000
0.001
0.002
0.000
0.002
0.000
0.001
0.000
0.001
0.017
0.016
0.001
0.053
Treated-Grazed
Abundance
0.000
0.393
0.778
1.000
0.111
0.000
3.056
0.357
245.403
0.211
0.053
0.107
0.036
0.107
0.028
0.111
0.028
0.083
0.472
0.361
0.056
7.237
Table 3.3. Continued
Largidae
Lepid adult
Lepid Larva
Lygaeidae
Mantidae
Meloidae
Membracidae
Miridae
Misc. Parts
Mordellidae
Mutillidae
Myrmeleontidae
Nabidae
Pentatomidae
Phasmatidae
Reduviidae
Scarabaeidae
Scutelleridae
Tenebrionidae
Tettigoniidae
Vespidae
Grand Total
Grams
0.012
0.001
0.415
0.005
0.004
0.000
0.013
0.000
0.177
0.000
0.000
0.002
0.000
0.004
0.001
0.001
0.001
0.001
0.025
0.009
0.000
0.049
Treated-Non-Grazed
Abundance
0.250
0.321
0.472
2.139
0.139
0.000
3.056
0.036
230.944
0.150
0.000
0.036
0.036
0.107
0.028
0.111
0.083
0.083
0.611
0.139
0.000
6.912
127
Grams
0.000
0.000
0.060
0.003
0.003
0.002
0.001
0.001
0.165
0.000
0.000
0.003
0.001
0.003
0.009
0.002
0.000
0.005
0.019
0.024
0.003
0.057
Untreated-Grazed
Abundance
0.000
0.143
0.250
1.250
0.194
0.083
0.333
0.321
201.361
0.200
0.000
0.250
0.071
0.107
0.194
0.194
0.000
0.639
0.389
0.167
0.083
6.654
Untreated-NonTotal
Grazed
Abundance
Abundance Grams
0.050
0.000
0.076
0.207
0.001
0.265
0.250
0.006
0.438
2.694
0.005
1.771
0.222
0.004
0.167
0.028
0.000
0.028
0.556
0.001
1.750
0.552
0.002
0.319
202.056
0.176
219.941
0.300
0.000
0.215
0.000
0.000
0.013
0.379
0.004
0.195
0.552
0.002
0.177
0.345
0.006
0.168
0.194
0.006
0.111
0.167
0.004
0.146
0.111
0.007
0.056
0.583
0.004
0.347
0.611
0.029
0.521
0.111
0.078
0.194
0.083
0.001
0.056
6.684
0.074
6.871
Total
Grams
0.003
0.001
0.232
0.004
0.003
0.001
0.008
0.001
0.174
0.000
0.000
0.003
0.001
0.004
0.004
0.002
0.002
0.002
0.022
0.032
0.001
0.058
Texas Tech University, Jennifer Zavaleta, May 2012
Ord's 1dance
Mammal diversity
Mammal dominance
Mammal abundance
Winter II
Winter II
Winter I
Winter I
Top ranked
model
1
Winter II
0.449
0.437
0.985
0.921
0.61
0.993
W
F8, 108=23.77
F8, 108=3.75
F8, 108=6.23,
F 7, 95 =1.95
F 7, 88=0.88
F7, 83=19.26
F
P<0.0001
P=0.0007
P<0.0001
P =0.07
P =0.53
P<0.0001
P
0.06
0.06
0.07
-
-
0.11
r2
+
+
+
-
-
+
Trend2
Table 3.4. List of top ranked AIC models for precipitation, W, r2 with associated F and P, and trend of precipitation regression for
mammal data. Data were collected in 16 experimental plots consisting of the combinations of (1) tebuthiuron (herbicide) treated –
grazed, (2) tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated – grazed, and (4) non-tebuthiuron treated – non-grazed in
eastern New Mexico from 2002-2010.
Ground squirrel abundance
Winter II
2
Pocket mouse abundance
1
Winter II is October- March, Winter I is November-March
Trend of precipitation regression
2
128
Texas Tech University, Jennifer Zavaleta, May 2012
1
2
3
4
4
3
1
2
Model Rank
Winter I
Winter II
Growing season
Annual season
Winter I
Winter II
Growing season
Annual season
Annual season 4
Growing season3
Winter II 1
Winter I 2
Model
4
4
4
4
4
4
4
4
4
4
4
4
K
294.7
300
303.4
306.9
47.5
48.5
55.3
56.1
1017
1014.2
995
1005
AICc
0
5.3
8.7
12.2
0
1
7.8
8.6
22
19.2
0
10
Δ AIC
0.921
0.065
0.012
0.002
0.61
0.37
0.012
0.008
0
0
0.993
0.007
W
Table 3.5. List of ranked AIC models for precipitation, AICc, Δ AIC, and W for mammal abundance, dominance (1-Simpson’s index) and diversity (Shannon’s index) that were collected in 16 experimental plots consisting of the combinations of (1) tebuthiuron
(herbicide) treated – grazed, (2) tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated – grazed, and (4) non-tebuthiuron
treated – non-grazed in eastern New Mexico from 2002-2010.
Mammal abundance
Mammal dominance
Mammal diversity
1
2
3
4
1
Winter
II is October- March
2
Winter I is November-March
3
Growing season is April- October
Annual season is April- March
4
129
Texas Tech University, Jennifer Zavaleta, May 2012
Ground squirrel abundance
Ord’s kangaroo rat abundance
Diversity of mammals
Dominance of mammals
Mammal abundance
F8,108=3.48, P=0.06
F1,108=4.44, P=0.037
F1,108=0.0, P =0.95
F1, 95=0.18, P =0.67
F1, 88=0.23, P =0.63
F1, 95=0.0, P =0.99
F, P
Herbicide effect
F1, 108=0.48, P=0.49
F1, 108=0.77, P=0.38
F1,108=4.44, P=0.04
F 1, 95=1.17, P =0.28
F1, 88=0.06, P =0.81
F1, 95=3.94, P =0.05
F, P
Grazing effect
F1, 108=0.79, P=0.38
F1, 108=0.0, P=0.96
F1, 108=0.08 P =0.89
F1, 95=3.26, P =0.07
F1, 88=0.57, P =0.4
F1, 95=0.06, P =0.82
F, P
Interaction effect
Table 3.6. List of herbicide, grazing, and interaction effect for measures of mammal abundance, dominance, diversity and three most
abundant species (Ord’s kangaroo rat, ground squirrel, and pocket mouse) that were captured in 16 experimental plots consisting of
the combinations of (1) tebuthiuron (herbicide) treated – grazed, (2) tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated –
grazed, and (4) non-tebuthiuron treated – non-grazed in eastern New Mexico from 2002-2010.
Pocket mouse abundance
130
Texas Tech University, Jennifer Zavaleta, May 2012
Winter II
Winter I
Growing season
Annual season
Winter II
Winter I
Growing season
Annual season
Winter II
Winter I
Growing season
Annual season
Model
4
4
4
4
4
4
4
4
4
4
4
4
K
808.4
812.8
821.2
823.1
657.6
661.5
671.1
673
891.3
899.7
908.2
911.6
AICc
0
4.4
12.8
14.7
0
3.9
13.5
15.4
0
8.4
16.9
20.3
Δ AIC
0.449
0.05
0.001
0
0.437
0.062
0.001
0
0.985
0.015
0
0
W
Table 3.7. List of ranked AIC models for precipitation, AICc, Δ AIC, and W for the three most abundant mammals, Ord’s kangaroo rat, ground squirrel, and pocket mouse. Data were collected in 16 experimental plots consisting of the combinations of (1) tebuthiuron
(herbicide) treated – grazed, (2) tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated – grazed, and (4) non-tebuthiuron
treated – non-grazed in eastern New Mexico from 2002-2010.
Model
Organism
Rank
Ord’s kangaroo rat abundance
1
2
3
4
Ground squirrel abundance
1
2
3
4
Pocket mouse abundance
1
2
3
4
1
Winter I is November-March
2
Winter II is October- March
3
Growing season is April- October
Annual season is April- March
4
131
Texas Tech University, Jennifer Zavaleta, May 2012
Great Plains skink abundance
Prairie lizard abundance
Herptile diversity
Herptile dominance
Herptile abundance
Winter II
Winter I
Winter I
Winter I
Winter II
Winter II1
Top ranked
model
0.466
0.371
0.402
0.808
0.608
0.904
W
F1, 68=1.33
F8, 25=6.22
F8, 36=15.88
F7, 32 =0.87
F7, 32=2.20
F7, 32=10.10
F
P=0.26
P<0.0001
P<0.0001
P=0.54
P =0.06
P<0.0001
P
-
0.01
0.12
-
0.027
0.20
r2
+
+
+
+
-
+
Trend2
Table 3.8. List of top ranked AIC models for precipitation, W, precipitation effect’s F and P values, r2, and trend of precipitation
regression for herptile data. Data were collected in 16 experimental plots consisting of the combinations of (1) tebuthiuron (herbicide)
treated – grazed, (2) tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated – grazed, and (4) non-tebuthiuron treated – nongrazed in eastern New Mexico from 2002-2010.
Coachwhip abundance
1
Winter II is October- March, Winter I is November-March
Trend of precipitation regression
2
132
Texas Tech University, Jennifer Zavaleta, May 2012
Annual season
Winter II
Winter I
Growing season
Winter II
Winter I2
Growing season3
4
Annual season
Model
4
4
4
4
4
4
4
4
4
4
4
4
K
132.1
135.1
141.1
143.2
-65.8
-78.6
-77.7
-67.9
502.2
506.7
518.7
520
AICc
0
3
9
11.1
12.8
0
0.9
10.7
0
4.5
16.5
17.8
Δ AIC
0.808
0.18
0.009
0.003
0.001
0.608
0.388
0.003
0.904
0.095
0
0
W
Table 3.9. List of ranked AIC models for precipitation, AICc, Δ AIC, and W for herptile abundance, dominance (1-Simpson’s index) and diversity (Shannon’s index) that were collected in 16 experimental plots consisting of the combinations of (1) tebuthiuron
(herbicide) treated – grazed, (2) tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated – grazed, and (4) non-tebuthiuron
treated – non-grazed in eastern New Mexico from 2002-2010.
Model
Rank
Herptile abundance
1
2
3
4
Herptile dominance
1
2
3
Winter I
Winter II
Growing season
Annual season
1
4
Herptiles diversity
1
2
3
4
1
Winter
II is October- March
2
Winter
I is November-March
3
Growing season is April- October
Annual season is April- March
4
133
Texas Tech University, Jennifer Zavaleta, May 2012
Skink abundance
Prairie lizard abundance
Diversity of herptiles
Dominance of herptiles
Herptile abundance
F1, 36=2.35, P=0.13
F1, 36=5.31, P=0.027
F1, 36=4.80, P=0.03
F1, 32 =2.43, P=0.13
F1, 32=4.91, P =0.03
F1, 32=0.25, P =0.62
F, P
Herbicide effect
F1, 36=1.45, P=0.24
F1, 36=8.90, P=0.005
F1, 36=2.32, P=0.14
F1, 32 =1.12, P=0.30
F1, 32=0.77, P =0.39
F1, 60=0.34, P =0.56
F, P
Grazing effect
F1, 36=2.02, P=0.16
F1, 36=4.32, P=0.04
F1, 68=0.03, P=0.85
F1, 32 =1.01, P=0.32
F1, 32 =1.81, P =0.19
F 1, 32=3.72, P =0.06
F, P
Interaction effect
Table 3.10. List of herbicide, grazing, and interaction effect for measures of herptile abundance, dominance, diversity and three most
abundant species (prairie lizard, skink, and coachwhip). There were 960 trap nights per plot per year (in 2005 and 2010 there were
only 480 trap nights. Data were from 16 experimental plots consisting of the combinations of (1) tebuthiuron (herbicide) treated –
grazed, (2) tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated – grazed, and (4) non-tebuthiuron treated – non-grazed in
eastern New Mexico from 2002-2010.
Coachwip abundance
134
Texas Tech University, Jennifer Zavaleta, May 2012
4
3
2
3
2
1
Winter I
Annual season4
Growing season3
Winter II
Winter I
Annual season
Growing season
Winter I
Winter II
Model
4
4
4
4
4
4
4
4
4
4
K
317.4
318.3
314
414.4
411.6
408.5
405.2
443.6
440.4
432.1
426.8
AICc
6.1
3.4
4.3
0
9.2
6.4
3.3
0
16.8
13.6
5.3
0
Δ AIC
0.018
0.068
0.043
0.371
0.004
0.016
0.077
0.402
0
0.001
0.033
0.466
W
Table 3.11. List of ranked AIC models for precipitation, AICc, Δ AIC, and W for the most abundant herptiles, which were prairie
lizard, Great Plains skink, and coachwhip. Data were collected in 16 experimental plots consisting of the combinations of (1)
tebuthiuron (herbicide) treated – grazed, (2) tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated – grazed, and (4) nontebuthiuron treated – non-grazed in eastern New Mexico from 2002-2010
1
Winter II
4
320.1
Organism
Model Rank
Prairie lizard abundance
2
Growing season
4
Coachwhip abundance
2
1
3
Annual season
4
Great Plains skink abundance
1
4
1
Winter I is November-March
2
Winter II is October- March
3
Growing season is April- October
Annual season is April- March
4
135
Texas Tech University, Jennifer Zavaleta, May 2012
Treehopper biomass
Invertebrate number of families
Invertebrate biomass
Invertebrate abundance
Winter I
Winter II
Winter II
Winter II
Winter II
Top ranked
model
0.719
0.795
0.987
1
0.987
1
W
F7, 96=4.72
F8, 108=3.75
F7, 96=13.35
F8, 105=29.23
F7, 84=8.17
F7, 96=15.57
F
P<0.0001
P=0.0007
P<0.0001
P<0.0001
P<0.0001
P<0.0001
P
0.004
0.0004
0.15
0.34
0.17
0.28
r2
-
+
-
-
-
-
Trend2
Table 3.12. List of top ranked AIC models for precipitation, W, r2 with associated F and P, and trend of precipitation regression for
invert data. Data were collected in 16 experimental plots consisting of the combinations of (1) tebuthiuron (herbicide) treated –
grazed, (2) tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated – grazed, and (4) non-tebuthiuron treated – non-grazed in
eastern New Mexico from 2003-2011.
Grasshopper biomass
Winter I
1
Caterpillar larvae biomass
1
Winter II is October- March, Winter I is November-March
Trend of precipitation regression
2
136
Texas Tech University, Jennifer Zavaleta, May 2012
Table 3.13. List of ranked AIC models for precipitation, AICc, Δ AIC, and W for total number of invertebrates, biomass of
invertebrates, and number of invertebrate taxonomic groups that were collected in 16 experimental plots consisting of the
combinations of (1) tebuthiuron (herbicide) treated – grazed, (2) tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated –
grazed, and (4) non-tebuthiuron treated – non-grazed in eastern New Mexico from 2003-2011.
Winter II1
Winter I2
3
Annual season
Model
4
4
4
4
4
4
4
4
K
755.4
773.4
809.1
665.4
645.4
654.1
665.2
803.5
755.4
773.4
809.1
AICc
48.1
0
18
53.7
20
0
8.7
19.8
48.1
0
18
53.7
Δ AIC
0
1
0
0
0
0.987
0.013
0
0
1
0
0
W
Model
Rank
Invertebrate abundance
1
2
3
4
4
4
803.5
Winter II
Winter I
Annual season
4
4
Growing season
4
Growing season
Number of invertebrate taxonomic groups
1
Winter II
2
Winter I
3
Annual season
4
Biomass of invertebrates
1
2
3
Growing season
4
1
Winter II is October- March
2
Winter
I is November-March
3
Growing season is April- October
Annual season is April- March
4
137
Texas Tech University, Jennifer Zavaleta, May 2012
Grasshopper
Treehopper
Invertebrate biomass
Number of invertebrate taxonomic groups
Invertebrate abundance
F1, 96=13.53, P=0.0005
F1, 96=13.17, P=0.0005
F1, 96=1.1, P=0.30
F1, 96=2.71, P=0.10
F1,105=33.33, P<0.0001
F 1,96=9.94, P =0.002
F, P
Herbicide effect
F1, 96=0.16, P=0.69
F1, 96=2.08, P=0.15
F1, 96=0.02, P=0.90
F1, 96=1.12, P=0.29
F1, 105=0.02, P =0.88
F1, 96=1.53, P =0.22
F, P
Grazing effect
F1, 96=0.01, P =0.93
F1, 96=1.93, P =0.17
F1, 96=0.24, P =0.63
F1, 96=0.44, P =0.51
F1, 105=1.01, P=0.31
F1, 96=0.04, P =0.86
F, P
Interaction effect
Table 3.14. List of herbicide, grazing, and interaction effect for measures of invertebrate abundance, number of invertebrate
taxonomic groups, and invertebrate biomass and the three species with the most cumulative biomass, which were treehoppers,
grasshoppers, and caterpillar larvae. Data were from a 16 experimental plots consisting of the combinations of (1) tebuthiuron
(herbicide) treated – grazed, (2) tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated – grazed, and (4) non-tebuthiuron
treated – non-grazed in eastern New Mexico from 2003-2011.
Caterpillar larvae
138
Texas Tech University, Jennifer Zavaleta, May 2012
Winter I
Winter II
Growing season
Annual season
Winter I
Winter II
Growing season
Annual season
Winter II
Winter I
Growing season
Annual season
Model
4
4
4
4
4
4
4
4
4
4
4
4
K
342.4
344.4
350.5
352.7
281.3
284.3
288.6
290.9
256.9
265.6
279.2
281.8
AICc
0
2
8.1
10.3
0
3
7.3
9.6
0
8.7
22.3
24.9
Δ AIC
0.719
0.264
0.013
0.004
0.795
0.177
0.021
0.007
0.987
0.013
0
0
W
Table 3.15. List of ranked AIC models for precipitation, AICc, Δ AIC, and W for the invertebrates with the most biomass, treehopper,
grasshopper, and caterpillar. Data were collected in 16 experimental plots consisting of the combinations of (1) tebuthiuron (herbicide)
treated – grazed, (2) tebuthiuron treated – non-grazed, (3) non-tebuthiuron treated – grazed, and (4) non-tebuthiuron treated – nongrazed in eastern New Mexico from 2003-2011.
Model
Rank
Treehopper biomass
1
2
3
4
Grasshopper biomass
1
2
3
4
Caterpillar biomass
1
2
3
4
139
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.1. Regression of mammal abundance, diversity, and dominance and winter precipitation as well as kangaroo rat, pocket
mouse and ground squirrel (800 trap nights per plot per year except 600 trap nights in 2005 and 2010) and winter precipitation from a
study of sand shinnery oak grass communities in eastern New Mexico from 2002-2010.
140
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.2.Mean small mammal abundance (SE) with 800 trap nights per plot per year as a dependent variable in models testing the
effect of herbicide and grazing treatments on sand shinnery oak grass communities in New Mexico from 2002-2010 (600 trap nights in
2005 and 2010). The presence of * indicates that the mean values differ (P<0.05).
141
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.3. Mean small mammal dominance (SE) based on the Simpson’s index of diversity with 800 trap nights per plot each year as
a dependent variable in models testing of herbicide and grazing treatments on sand shinnery oak grass communities in eastern New
Mexico from 2002-2010 (600 trap nights in 2005 and 2010)
142
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.4. Mean small mammal diversity (SE) based on the Shannon index of diversity with 800 trap nights per plot each year as a
dependent variable in models testing of herbicide and grazing treatments on sand shinnery oak grass communities in eastern New
Mexico from 2002-2010 (missing data June 2002)
143
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.5.Mean kangaroo rat abundance (SE) with 800 trap nights per plot each year as a dependent variable in models testing of
herbicide and grazing treatments on sand shinnery oak grass communities in eastern New Mexico from 2002-2010 (600 trap nights in
2005 and 2010). The presence of * indicates that the means differ (P<0.05).
144
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.6. Ground squirrel abundance with 800 trap nights per plot each year as a dependent variable in models testing of herbicide
and grazing treatments on sand shinnery oak grass communities in eastern New Mexico from 2002-2010 (600 trap nights in 2005 and
2010).The presence of * indicates that the mean values differ (P<0.05).
145
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.7. Pocket mouse species abundance with 800 trap nights per plot each year as a dependent variable in models testing of
herbicide and grazing treatments on sand shinnery oak grass communities in eastern New Mexico from 2002-2010 (600 trap nights in
2005 and 2010).The presence of * indicates that the mean values differ (P<0.05).
146
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.8. Regression of herptile abundance, diversity, and dominance and winter precipitation as well as prairie lizard, Great Plains
skink, and coachwhip (960 trap nights per plot per year except 480 trap nights in 2005 and 2010) and winter precipitation from a study
of sand shinnery oak grass communities in eastern New Mexico from 2002-2010
147
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.9. Herptile abundance with 960 trap nights per plot per year (480 trap nights in 2005 and 2010) as a dependent variable in
models testing the effect of herbicide and grazing treatments on sand shinnery oak grass communities in New Mexico from 2002-2010
148
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.10. Herptile dominance based on the Simpson’s index of diversity with 960 trap nights per plot per year (480 trap nights in 2005 and 2010) as a dependent variable in models testing of herbicide and grazing treatments on sand shinnery oak grass communities
in eastern New Mexico from 2002-2010.The presence of * indicates that the mean values differ (P<0.05).
149
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.11. Herptile diversity based on the Shannon index of diversity with 960 trap nights per plot per year (480 trap nights in 2005
and 2010) as a dependent variable in models testing of herbicide and grazing treatments on sand shinnery oak grass communities in
eastern New Mexico from 2002-2010
150
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.12. Prairie lizard abundance with 960 trap nights per plot per year (480 trap nights in 2005 and 2010) as a dependent variable
in models testing of herbicide and grazing treatments on sand shinnery oak grass communities in eastern New Mexico from 20022010.The presence of * indicates that the mean values differ (P<0.05).
151
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.13. Great Plains skink abundance with 960 trap nights per plot per year (480 trap nights in 2005 and 2010) as a dependent
variable in models testing of herbicide and grazing treatments on sand shinnery oak grass communities in eastern New Mexico from
2002-2010 The presence of * indicates that the mean values differ (P<0.05).
152
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.14. Coachwhip abundance with 960 trap nights per plot per year (480 trap nights in 2005 and 2010) as a dependent variable
in models testing of herbicide and grazing treatments on sand shinnery oak grass communities in eastern New Mexico from 20022010
153
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.15. Regression of invertebrate abundance, biomass, and number of families and winter precipitation as well as regressions of
grasshopper, treehopper, and caterpilars and winter precipitation from a study of sand shinnery oak grass communities in eastern New
Mexico from 2003-2010
154
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.16. Total invertebrate abundance from five, 0.5 by 0.5m samples per plot as a dependent variable in models testing of
herbicide and grazing treatments on sand shinnery oak grass communities in eastern New Mexico from 2003-2010. The presence of *
indicates that the mean values differ (P<0.05).
155
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.17. Number of invertebrate taxonomic groups from five, 0.5 by 0.5m samples per plot as a dependent variable in models
testing of herbicide and grazing treatments on sand shinnery oak grass communities in eastern New Mexico from 2003-2010The
presence of * indicates that the mean values differ (P<0.05).
156
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.18. Invertebrate biomass from five, 0.5 by 0.5m samples per plot as a dependent variable in models testing of herbicide and
grazing treatments on sand shinnery oak grass communities in eastern New Mexico from 2003-2010
157
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.19. Grasshopper abundance from five, 0.5 by 0.5m samples per plot as a dependent variable in models testing of herbicide
and grazing treatments on sand shinnery oak grass communities in eastern New Mexico from 2003-2010The presence of * indicates
that the mean values differ (P<0.05).
158
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.20. Treehopper abundance from five, 0.5 by 0.5m samples per plot as a dependent variable in models testing of herbicide and
grazing treatments on sand shinnery oak grass communities in eastern New Mexico from 2003-2010The presence of * indicates that
the mean values differ (P<0.05).
159
Texas Tech University, Jennifer Zavaleta, May 2012
Figure 3.21. Caterpillar abundance from five, 0.5 by 0.5m samples per plot as a dependent variable in models testing of herbicide and
grazing treatments on sand shinnery oak grass communities in eastern New Mexico from 2003-2010 The presence of * indicates that
the mean values differ (P<0.05).
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CHAPTER IV
TEBUTHIURON HERBICIDE AND GRAZING AS A MEANS OF RESTORING
SHINNERY OAK GRASSLANDS
Introduction
The sand shinnery oak (Quercus havardii) (hereafter shinnery oak) community is an
important part of the southwestern High Plains (Haukos 2011). Based on evidence for arid to
semi-arid or sub-humid environment, the Southern High Plains have likely existed as a
grassland for about 11 million years (Holliday 1990, Haukos 2011). The sandy soils of the
Southern High Plains of eastern New Mexico and northwestern Texas create a distinct
ecosystem from surrounding short-grass prairie. Dune fields and sandy soils were formed
during the Altithermal periods (Holliday 1989) along with more than 20,000 ephemeral playa
lakes, and 40 saline lakes (many of which are now dry with the advent of irrigation
technology and the expansion of farming) (Haukos 2011). These deep, sandy soils have
always supported a mixed-grass prairie with a co-dominant shrub component (USDA NRCS
2010)
Expanding from southeastern New Mexico, through the Texas panhandle, and into
southwest Oklahoma, the shinnery oak community is recognized as an isolated, relict
community. Pettit (1979) recognized the significance of this community, and stated “These lands are perhaps the most fragile of all ecosystems on the Southern High Plains of Texas
and the landowners cannot afford to abuse it.” With continuous, unmanaged grazing,
suppression of periodic natural fire, and other anthropogenic impacts, the composition of the
shinnery oak-grassland community has changed dramatically during the past 100 years
(Peterson Boyd 1998, Haukos 2011). Due to these factors along with its life-history strategy
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as an effective water gatherer, the density of shinnery oak has increased and, in many areas,
monotypic stands have developed.
Shinnery oak has frequently been accused of being invasive and an increaser under
grazing pressure, but its presence for over 3,000 years as evident with pollen profiles (Gross
and Dick Peddie 1979) and slow growth from rhizomes negates these postulations. In fact,
due to habitat fragmentation through oil and gas exploration, urban development, and rowcrop agriculture, shinnery oak habitat has declined in absolute terms. While the historical
acreage of the shinnery oak community is disputed, Peterson and Boyd (1998) estimated that
the species historically covered 405,000 ha in Oklahoma, 607,000 ha in New Mexico and 1.4
million ha in Texas (Garrison and McDaniel 1982). It was estimated that Texas had
converted at least 200,000 ha by 1972. With expansion of center-pivot irrigation and
advancements in the technology of herbicides at least half of its historical range has been
lost. There is an important need to restore this relict habitat to a species composition
representative of pre-settlement because it provides the primary habitat for a number of
species of conservation concern including the lesser prairie-chicken (Tympanuchus
pallidicintus), dune sagebrush lizard (a.k.a. sand dunes lizard Sceloporus arenicolus), and
Cassin’s sparrow (Aimophia cassinii).
Similar to short-grass prairie, the important historical ecological drivers in the region
were herbivory, natural fire, and precipitation. However, there was probably less frequent
grazing and fire because the sandy soils were more difficult for bison (Bison bison) to
traverse and more fuel load would need to accumulate for fire to travel across patchy
vegetation (Haukos 2011). Annual precipitation is highly variable in the region, and is a
limiting factor in this semi-arid grassland community (Peterson and Boyd 1988). For
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example, from 2001-2010 the average annual precipitation on my study site in eastern New
Mexico was 42 cm, but ranged from 21 cm to 82 cm.
Herbicides, like tebuthiuron, are one tool to restore a shinnery oak community by
limiting the amount of shrub cover. Tebuthiuron (N-[5-(1,-dimehylethyl)-1,3,4-thiadiazol-2yl]-N,N’-dimehylurea) is an herbicide that attacks the root systems of the woody stems and
has been used to eradicate shrubs (Peterson and Boyd 1988). As a dry-pelleted herbicide,
tebuthiuron has the distinct advantages of relative nontoxicity to non-target species, requires
only one application (Scifres et al. 1981), and does not result in an overspray, which is
characteristic of liquid herbicides (Peterson and Boyd 1998).
In the 1980s and early 1990s, the U.S. Bureau of Land Management (BLM) treated
40,469 hectares of shinnery oak in New Mexico with tebuthiuron (Peterson and Boyd 1998).
The BLM treated shinnery oak in order to eradicate it to increase grass and because shinnery
oak’s buds can be toxic to cattle in the spring. A complete eradication should be avoided because elimination of vegetation roots, including shinnery oak, can cause the sandy soils to
become severely eroded (Grover 1990, Haukos 2011). It is now recognized that complete
eradication of shrubs is considered detrimental to biodiversity and landscape heterogeneity of
the region.
In the last decade a paradigm shift has occurred. Reduction of shinnery oak, as
opposed to complete eradication, is preferred land practice. The Natural Resources
Conservation Service (NRCS) has more recently proposed reducing shinnery oak canopy
cover to less than 40% to increase grass production with the assumption of no loss of
biodiversity. As such, it has encouraged and cost-shared ranchers in eastern New Mexico to
apply 0.56-0.84 kg/ha of tebuthiuron and deliberate avoid dune areas (USDA NRCS 2000).
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It is important to restore sand shinnery oak to historical standards to conserve this
relict ecosystem. Restoration efforts can be judged through a number of criteria. In this case,
restoring ecological function of biomass production, maximizing the biodiversity of native
species, and connecting fragmented patches of sand shinnery oak grassland habitats are
approaches to evaluating the restoration of the mixed-grass community.
While there have been numerous studies about the effects of tebuthiuron application
in shinnery oak communities, this is the first study to evaluate the potential use of the
herbicide to restore the historical vegetation community in conjunction with a component of
managed grazing designed to sustain the restoration effort. This is particularly important
because much of the land in the region is managed for cattle production. Knowing more
about the effects of herbicide coupled with a sustainable managed grazing system will offer
better insight in how the community can be restored using techniques prevalent in the region.
Because the goal of my project was to restore shinnery oak-grassland community, it was
necessary to monitor the full impact of the restoration effort and collect data on plant
composition, structure, and production as well as mammals, herptiles, and invertebrates
across a number of years (Chapters II, III).
This study is also unique in that it evaluates restoration with 12 years of data and
allows inference regarding the temporal response. My goal was to measure composition of
shrubs, grasses, and forbs under different treatments during an effort to restore a community
to a historical shinnery oak-mixed-grass prairie. Specific objectives were to test the
hypothesis that herbicide application and grazing management can be used to successfully
restore a sand shinnery oak grassland and determine if achieving historical standards are a
realistic goal for restoration.
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Methods
Experimental Design
Data on community response to tebuthiuron and grazing in the shinnery oakgrassland community were collected as part of a ten-year data set starting in 2000. The study
was a completely randomized design with two levels of two treatments such that replicated
plots were either tebuthiuron treated or not treated and either grazed or non-grazed. The goal
was to determine which treatment combination and at what point in the restoration effort
most closely restored shinnery oak grasslands to historical standards.
In Roosevelt County, New Mexico, on the Southern High Plains, 532 ha of private
land were treated with tebuthiuron (rate of 0.60 kg/ha with dune avoidance) in 2000. The
state of New Mexico owned 518 ha of adjacent land, representing an extant shinnery oak
community serving as an experimental control. This application rate was approximately 50%
of previously recommended rates because the goal was to reduce shinnery oak, not to
eliminate it.
Before beginning the experiment, initial surveys were conducted in the summer of
2000 to test homogeneity of the study site. Three 100-m transects were placed randomly
within each of the 12 plots. The line intercept method was employed (Canfield 1941) within
a randomly selected 50-m portion of each 100-m transect. The individual plant species that
intercepted the line was recorded and converted to percent composition. Survey results
indicated that vegetative composition was homogeneous across the study area (F 9, 14=0.66,
P=0.74 for line transects) (Smythe 2006) (Table 1.1). After initial surveys, another replicate
for each treatment was added for statistical power.
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The herbicide control had not been grazed for 7 years before the study and the private
land was grazed immediately prior to the herbicide treatment and neither was grazed until 2
growing seasons following herbicide treatment. A moderate grazing treatment was designed
to take a maximum of 50% of the annual herbaceous production between two grazing
seasons in the growing and dormant seasons in July and January, respectively, starting in
January 2002. Due to logistical constraints, there was no growing season grazing in 2009 or
2010. Because grass production differed substantially between the tebuthiuron-treated and
control plots, cattle grazed for approximately 300 animal-days per plot on the control areas
and 2,000 animal-days per plot of the tebuthiuron-treated areas to achieve similar grazing
intensity within each treatment combination.
To allow for inference beyond the study site, the experimental design was a combined
completely randomized design with a systematic application of treatments following random
assignment of initial treatment combination (Cochran and Cox 1957, Smythe and Haukos
2009). The four treatment combinations were treated/grazed (T-G), treated/not grazed (TNG), not treated/grazed (NT-G), and not treated/not grazed (NT-NG). There were four
replicates for the four treatments, totaling 16 plots (Fig. 1.1).
Historical Climax Plant Community
According to the U.S. Department of Agriculture, NRCS ecological site description,
pre-settlement standards were 80% grasses, 15% shrubs and 5% forbs
(http://esis.sc.egov.usda.gov, site ID R077DY045TX). Ecological site descriptions (ESD) are
prepared by the NRCS and seek to identify the site characteristics, plant communities, site
interpretations, and supporting information. The goal of the site description is to provide
information to managers about the individual sites and their interrelationships to one another
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on the landscape. They also provide information on the climax community or a biological
community of plants that has reached a steady state through the process of ecological
succession. This information is important while restoring the landscape to an equilibrium in
which the species in the community are adapted to average conditions in that area. This semiarid environment is characterized by marked fluctuations about average conditions,
especially in regard to precipitation (NRCS 2011). I will compare historic plant community
to that in each of the four treatments to determine which treatment combination best
approaches a restored sand shinnery oak-grass community.
Vegetative Composition
Each September from 2001–2010, vegetative surveys were conducted to monitor
vegetation response to treatments. A pre-vegetation survey conducted in 2000 found that the
study area was homogenous prior to application of the herbicide treatment (Table 1.1).
Within each replicate, percent composition of grass, shrub, forb, bare ground and litter were
measured based on occurrence every meter along three, 10-m transects (Heady et al. 1959).
Percent composition of grass, shrub, forb, bare ground and litter within each replication was
estimated by dividing the number of points at which each occurred by the total number of
points sampled.
Statistical Analysis
I used a 3 by 2 chi-square test to determine if and when historical standards were
reached based on percent composition of shrubs, grasses, and forbs. The assumptions for a
chi-square test are that the samples are random and independent, the sample size is
sufficiently large, and there are at least five observations in each cover type.
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Results
Overall, untreated areas were dominated by shrubs with a moderate amount of grasses
and few forbs (Fig. 4.2, 4.3). Treated areas, on the other hand, were dominated by grasses
with more forbs than shrubs in years with greater than average precipitation, but there were
more shrubs than forbs in dryer years (Fig. 4.4, 4.5). The historical standard of grasses
(80%), shrubs (15%), and forbs (5%) was statistically met only in treated/grazed plots in
2009; this was the year that had less than the usual treatment of grazing because of logistical
constraints of land managers. However, most often the treated/grazed plots were the closest
to historical standards compared to untreated areas due to substantially more grass in treated
areas (Chapter II). Treated areas often did not achieve historical standards because the
percent of forbs was greater than historical standards. The composition of shrubs, grasses and
forbs fluctuated from year to year, presumably due to changes in amount and timing of
precipitation among years.
Treated-grazed plots
Across the study, treated-grazed (T-G) plots were the most comparable to historical
standards with 20.2% shrub, 69.7% grass, and 10.2% forb (Fig. 4.2). These results were
relatively consistent over time with percent forbs and grass fluctuating from year to year
(Fig. 4.6). T-G areas had twice as many forbs and, on average, slightly too many shrubs to
meet historical standards. Also, the grass cover was high, but fell short of historical
standards.
Treated-non-grazed plots
Treated-non-grazed (T-NG) plots were also relatively comparable to historical
standards with 20.2% shinnery oak, 67.3% grass, and 12.6% forb (Fig. 4.3). Similar to T-G
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areas, year-to-year variations were due to changes in grasses and forbs (Fig. 4.7). In general,
there was a slight increase of forbs in non-grazed areas as compared to grazed areas in treated
sites. When compared to historical standards, the shrub component was slightly lower and
forbs were slightly higher. Also, there was too little grass to strictly meet historical standards,
although there was little difference in grass coverage between T-G and T-NG.
Untreated-grazed areas
Untreated-grazed (UT-G) plots had 60.7% shrub, 32.4% grass, and 6.6% forbs (Fig.
4.4). Without herbicide treatment, the shrub component was much too large and
consequently grass coverage was too low to reach historical standards. The forb component,
however, was only slightly greater than historical standards. There were about half as many
forbs in untreated plots as treated plots. Over time there were year-to-year fluctuations in
shrubs, grasses, and forbs (Fig. 4.8). The relative year-to-year changes of shinnery oak were
greater in untreated plots than treated plots.
Untreated-non-grazed plots
Untreated-non-grazed (UT-NG) plots had 61.1% shrubs, 33.2% grass and 5.6% forbs
(Fig. 4.5). Similar to UT-G, UT-NG did not approach historical standards because of high
shrub coverage and low grass coverage. UT-NG, however, came closest to historical
standards in terms of percent forb, which was the lowest of all plots. There were year-to-year
fluctuations and, like UT-G, relative shrub abundance changed more between years in
untreated plots than in treated plots (Fig. 4.9).
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Discussion
Over the last century the American southwest has suffered an encroachment of shrubs
with a corresponding decrease in grass cover due to overgrazing by domestic livestock, fire
suppression, and periods of severe drought (Grover and Musick 1990). Restoration to
historical proportions of grass, shrub and forb requires retarding growth of monotypic
shinnery oak to allow development of stable herbaceous growth (Haukos 2011). The
ecological site description indicates that in the southwestern part of the Southern High Plains,
pre-settlement standards were 80% grasses, 15% shrubs, and 5% forbs. My data indicates
that when treatment of shinnery oak is combined with moderate grazing, long-term
restoration is possible.
The plot type that was treated with low levels of tebuthiuron and exposed to light to
moderate grazing (plot T-G) came closest to the ecological site description. However, T-G
only statistically achieved the ESD in 2009, nine years after treatment. Before discussing
why plot T-G was able to reach ESD standards, it is important to discuss why other plots did
not. The untreated plots, whether grazed or not, had much greater percentages of shrubs.
This, along with the consequently low percent cover of grasses inhibited untreated plots from
ever reaching historical standards. The plot that was treated but not grazed also came close to
historical standards but never achieved it mainly due to the abundance of forbs. So, it seems
reasonable that herbicide treatment at low levels is the first step in reestablishing historical
standards.
Although T-G plots achieved the same proportions as the ESD in 2009 a trend,
consistent with the ESD has emerged. The ESD provides a static target for a dynamic
environment. So natural variation from year to year may not exactly meet the ESD. The trend
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is important since historically standards may not have been exactly the ESD but varied
around the target. Given that we are trying to achieve trends, it is worth noting T-NG areas
were comparable in their composition, although there were more forbs in T-NG areas.
With herbicide treatment and consequent reduction of shrubs followed by a managed,
moderate grazing system, grasses can establish, grow, and remain competitive in the system.
Perhaps with more time, the forb component may also decline in treated plots because of
replacement of grasses. If this is the case, then T-G plots may come closer to historical
standards. The main difference between what we observed in treated areas and the historical
standard is that there are more forbs than there may have been historically. However, this is
not necessarily a negative. Forbs are important not only for increasing biodiversity of the
flora, but also for providing new niches for mammals, herptiles, and invertebrates (Chapter
III).
Invertebrates are especially important when managing for the lesser prairie- chickens.
Jamison (2002) warned against practices, like intensive herbicide treatment, aimed at
reducing cover of native forbs because it may negatively influence habitat quality by
reducing standing crops of important invertebrate and plant food taxa. Similarly, Doerr and
Guthery (1983) recommended lower rates of tebuthiuron to improve the availability of forbs
and that forb diversity should be a goal of habitat management of prairie chickens. Moreover,
Hagen (2005) found that broods have increased survival rates in areas with greater forb and
invertebrate abundance.
Beyond prairie chickens, managing for diversity of vegetation provides more
opportunities and niches for other animals to fill. Mechanisms behind this relationship may
include niche separation, variation in prey abundance and variation in predation risk
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(Castellano 2006). Community diversity and abundance in arid and semi-arid lands are
greatest in vegetation associations that are a mix of grasses and shrubs (Peterson and Boyd
1998, Castellano 2006, Haukos 2011). Management decisions that emphasize diversity are
also important given that many species react differently to herbicide and grazing treatments
(Chapter III).
The trend in increased diversity remains a theme in treated areas throughout the
twelve-year study. However, there was tremendous annual variation in the relative
proportions of shrubs, grasses, and forbs. Grasses and forbs were particularly susceptible to
changes during above average precipitation events. For example, 2004 was almost twice the
average precipitation with 82 cm. In that year, forbs increased substantially, even in untreated
areas. Annual fluctuations indicate perhaps that historical standards should serve as a guide
for management as opposed to a goal for restoration.
Historical standards provide managers with a framework to make management
decisions but should not be a criterion to evaluate success. Instead, success of a restoration
project should be based on maximizing native biodiversity and conserving species of
concern. The treatment that best achieves this is the one that was treated with low levels of
tebuthiuron (0.60 kg/ha) and light to moderate grazing system. However, managers should be
wary of converting too much shrub community into mixed grass prairie in this fragile
ecosystem.
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Literature Cited
Canfield, R. H. 1941. Application of the Line Interception Method in Sampling Range
Vegetation. Journal of Forestry. 39(4): 388-394.
Castellano, M. J. and T. J. Valone. 2006. Effects of livestock removal and perennial grass
recovery on the lizards of a desertified arid grassland. Journal of Arid Environments
66: 87-95.
Cochran, W. G. and G. M. Cox. 1957. Experimental designs. John Wiley and Sons, New
York, New York, USA.
Deering, D. W. and R. D. Pettit. 1972. Sand shinnery oak acreage survey. Research
Highlights Noxious Brush and Weed Control; Range, Wildlife, and Fisheries
Management 2: 14. Lubbock: Texas Tech University, College of Agricultural
Sciences and Natural Resources.
Doerr, T. B.and F. S. Guthery. 1983. Effects of tebuthiuron on lesser prairie-chicken habitat
and foods. Journal of Wildlife Management 47:1138-1142.
Gross, F. A. and W. Dick-Peddie. A. 1979. A map of primeval vegetation in New Mexico.
Southwestern Naturalist 24: 115-122.
Grover, H. D. and H. B. Musick. 1990. Shrubland encroachment in southern New Mexico,
U.S.A: an analysis of desertification processes in the American Southwest. Climate
Change 17: 305-330.
Hagen, C. A, G. C. Salter, J. C. Pitman, R. J. Robel, and R. D. Applegate. 2005. Lesser
prairie-chicken brood habitat in sand sagebrush: invertebrate biomass and vegetation.
Wildlife Society Bulletin 33(3): 1080-1091.
Haukos, D. A. 2011. Use of tebuthiuron to restore sand shinnery oak grasslands of the
Southern High Plains. M. N. A El-Ghany Hasanee (Ed.) In Herbicides: Mechanisms
and mode of action (103-124). Rijeka, Croatia.
Heady, H. F., R. P. Gibbens, and R. W. Powell. 1959. A comparison of the charting line
intercept, and line point methods of sampling shrub types of vegetation. Rangeland
Management 12: 180-188.
Holliday, V. (1989). Middle Holocene drought on the Southern High Plains. Quaternary
Research 31:74-82.
Holliday, V. (1990). Soils and landscape evolution of eolian plains: the Southern High Plains
of Texas and New Mexico. Geomorphology 3:489-515.
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Jamison, B. E., R. J. Robel, J. S. Pontius, and R. D. Applegate. 2002. Invertebrate biomass:
associations with lesser prairie-chicken habitat use and sand sagebrush density in
southwestern Kansas. Wildlife Society Bulletin 30: 517-526.
Peterson, R. S. and C. S. Boyd. 1998. Ecology and management of sand shinnery
communities: a literature review. General Technical Report RMRS-GTR-16. United
States Forest Service, Rocky Mountain Research Station, Fort Collins, Colorado,
USA.
Pettit, R. D. 1979. Effects of picloram and tebuthiuron pellets on sand shinnery oak
communities. Journal of Range Management. 32 (3): 196-200
Scifres, C. J., J. W. Smith, and R. W. Bovey. 1981. Control of oaks (Quercus spp.) and
associated woody species on rangeland with tebuthiuron. Weed Science 29: 270-275.
Smythe, L.A. 2006. Response of nesting grassland birds to sand shinnery oak communities
treated with tebuthiuron and grazing in eastern New Mexico. Thesis, Texas Tech
University, Lubbock.
Smythe, L. A. and Haukos D. A. 2009. Nesting success of grassland birds in shinnery oak
communities treated with tebuthiuron and grazing in eastern New Mexico. The
Southwestern Naturalist 54(2): 136-145.
United States Department of Agriculture, Natural Resources Conservation Service (USDA
NRCS). 2011. Ecological Site Description for R077DY045TX.
http://esis.sc.egov.usda.gov/esdreport/fsReport.aspx?id=R077DY045TX&rptLevel=al
l&approved=yes
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Treated/
grazed
14.60
26.68
289.58
84.85
43.88
133.45
30.20
3.52
60.98
Treated/
non-grazed
16.00
57.21
177.98
31.65
38.07
147.52
85.78
17.72
60.88
Not treated/
grazed
113.58
138.81
191.80
211.65
300.12
180.32
130.58
151.88
189.07
Not treated/
non-grazed
145.08
151.92
173.27
243.08
273.48
138.07
135.98
145.07
166.58
Table 4.1 .Chi-square values for comparing percent cover shrub, grass, and forb for each plot every year to historical standards of
shrub (15%), grass (80%), and forb (5%). Data were collected in 16 experimental plots consisting of the combinations of (1)
tebuthiron (herbicide) treated – grazed, (2) tebuthiron treated – non-grazed, (3) non-tebuthiron treated – grazed, and (4) non tebuthiron
treated – non-grazed in eastern New Mexico from 2002-2010. The critical value for a significant chi-squared test with 2 degrees of
freedom is 5.991. So values less than 5.999 indicate there is no difference with historical standards.
Year
2002
2003
2004
2005
2006
2007
2008
2009
2010
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Figure 4.1. Annual precipitation (cm) on study site in eastern New Mexico. The dashed line is the 10-year average.
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Figure 4.2. Summary across 2002-2010 for percent composition of shrub, grass, and forb for treated- grazed plots in an experiment
designed to examine the effects of tebuthiuron and grazing in the shinnery oak community of eastern New Mexico
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Figure 4.3. Summary across 2002-2010 for percent composition of shrub, grass, and forb for treated- non-grazed plots in an
experiment designed to examine the effects of tebuthiuron and grazing in the shinnery oak community of eastern New Mexico
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Figure 4.4. Summary across 2002-2010 for percent composition of shrub, grass, and forb for untreated- grazed plots in an experiment
designed to examine the effects of tebuthiuron and grazing in the shinnery oak community of eastern New Mexico
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Figure 4.5. Summary across 2002-2010 for percent composition of shrub, grass, and forb for untreated- non-grazed plots in an
experiment designed to examine the effects of tebuthiuron and grazing in the shinnery oak community of eastern New Mexico.
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Figure 4.6. Percent composition of shrub, grass, and forb for treated-grazed plots in an experiment designed to examine the effects of
tebuthiuron and grazing in the shinnery oak community of eastern New Mexico from 2002-2010
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Figure 4.7. Percent composition of shrub, grass, and forb for treated-non-grazed plots in an experiment designed to examine the
effects of tebuthiuron and grazing in the shinnery oak community of eastern New Mexico from 2002-2010
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Figure 4.8. Percent composition of shrub, grass, and forb for untreated-grazed plots in an experiment designed to examine the effects
of tebuthiuron and grazing in the shinnery oak community of eastern New Mexico from 2002-2010
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Figure 4.9. Percent composition of shrub, grass, and forb for untreated-non-grazed plots in an experiment designed to examine the
effects of tebuthiuron and grazing in the shinnery oak community of eastern New Mexico from 2002-2010
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100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Year
Litter
Bare ground
Forb
Grass
Shrub
185
Figure 4.10. Percent composition of shrub, grass, forb, bare ground and litter for treated-grazed plots in a study looking at the effect of
tebuthiuron and grazing in sand shinnery oak-grass communities in eastern New Mexico from 2002-2010.
Percent composition for
treated-grazed plots
Texas Tech University, Jennifer Zavaleta, May 2012
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Year
Litter
Bare ground
Forb
Grass
Shrub
186
Figure 4.11. Percent composition of shrub, grass, forb, bare ground and litter for treated-non-grazed plots in a study looking at the
effect of tebuthiuron and grazing in sand shinnery oak-grass communities in eastern New Mexico from 2002-2010
Percent composition for
treated-non-grazed plots
Texas Tech University, Jennifer Zavaleta, May 2012
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Year
Litter
Bare ground
Forb
Grass
Shrub
187
Figure 4.12. Percent composition of shrub, grass, forb, bare ground and litter for untreated-grazed plots in a study looking at the effect
of tebuthiuron and grazing in sand shinnery oak-grass communities in eastern New Mexico from 2002-2010
Percent composition of
untreated-grazed plots
Texas Tech University, Jennifer Zavaleta, May 2012
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Year
Litter
Bare ground
Forb
Grass
Shrub
188
Figure 4.13. Percent composition of shrub, grass, forb, bare ground and litter for untreated-non-grazed plots in a study looking at the
effect of tebuthiuron and grazing in sand shinnery oak-grass communities in eastern New Mexico from 2002-2010
Percent composition for
untreated-non-grazed plots
Texas Tech University, Jennifer Zavaleta, May 2012
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Year
Litter
Bare ground
Forb
Grass
Shrub
189
Figure 4.14. Percent composition of shrub, grass, forb, bare ground and litter for tebuthiuron treated plots in sand shinnery oak-grass
communities in eastern New Mexico from 2002-2010
Percent composition for
treated plots
Texas Tech University, Jennifer Zavaleta, May 2012
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
2002
2003
2004
2005
Year
2006
2007
2008
2009
2010
Litter
Bare ground
Forb
Grass
Shrub
190
Figure 4.15. Percent composition of shrub, grass, forb, bare ground and litter for untreated plots in a study looking at the effect of
tebuthiuron and grazing in sand shinnery oak-grass communities in eastern New Mexico from 2002-2010
Percent composition for
untreated plots
Texas Tech University, Jennifer Zavaleta, May 2012
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Year
Litter
Bare ground
Forb
Grass
Shrub
191
Figure 4.16. Percent composition of shrub, grass, forb, bare ground and litter for grazed plots in a study looking at the effect of
tebuthiuron and grazing in sand shinnery oak-grass communities in eastern New Mexico from 2002-2010
Percent composition for
non-grazed plots
Texas Tech University, Jennifer Zavaleta, May 2012
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Year
Litter
Bare ground
Forb
Grass
Shrub
192
Figure 4.17. Percent composition of shrub, grass, forb, bare ground and litter for non-grazed plots in a study looking at the effect of
tebuthiuron and grazing in sand shinnery oak-grass communities in eastern New Mexico from 2002-2
Percent composition for
grazed plots
Texas Tech University, Jennifer Zavaleta, May 2012
APPENDIX A
LIST OF PLANTS FOUND IN ROOSEVELT COUNTY, NM ACCORDING TO
ECOLOGICAL SITEDESCRIPTION
Group
Group
Name
Scientific Name
Common Name
Grasses
Shrubs
Forbs
Tallgrasses Andropogon hallii
Calamovilfa gigantea
Panicum havardii
Schizachyriumscoparium
Sporobolusgiganteus
Midgrass
Bothriochloabarbinodis
Boutelouacurtipendula
Sporoboluscontractus
Sporoboluscryptandrus
Sporobolusflexuosus
Aristida purpurea
Shortgrass
var.wrightii
Chloriscucullata
Digitaria cognata
Paspalumsetaceum
Artemisia campestris
Artemisia filifolia
Calylophusserrulatus
Chrysothamnuspulchellus
Quercus havardii
Eriogonumannuum
Gaura
Hesperostipacomata
Hymenopappusfilifolius
Kramerialanceolata
Liatrispunctata
Mentzeliadecapetala
Oenothera spp.
Penstemonambiguus
Yucca glauca
193
sand bluestem
giant sandreed
Havard’s panigrass
little bluestem
giant dropseed
cane bluestem
sideoatsgrama
spike dropseed
sand dropseed
mesa dropseed
wright threeawn
hooded windmillgrass
fall witchgrass
fringeleafpaspalum
field stagewort
sand sagebrush
halfshrubsundrop
southwest rabbitbrush
sand shinoak
annual wildbuckwheat
gaura sp.
needle and thread
fineleafhymenopappus
trailing ratany
dotted gayfeather
tenpetalmentzelia
evening primrose
giliapenstemon
small soapweed
Texas Tech University, Jennifer Zavaleta, May 2012
APPENDIX B
LIST OF ALL PLANT SPECIES FOUND IN THE STUDY TESTING THE EFFECTS OF
TEBUTHIURON AND GRAZING IN ROOSEVELT COUNTY, NM
Andropogonscoparius
little bluestem
Grasses
Andropogon hallii
big bluestem
Andropogongerardii
sand bluestem
Aristida sp.
Threeawn
Boutelouacurtipendula
Sideoatsgrama
Boutelouaeriopoda
black grama
Boutelouagracilis
blue grama
Boutelouahirsuta
hairy grama
Bothrichloasaccharoides
silver bluestem
Cenchruspauciflorus
field sandbur
Chloris Sw.
windmill grass
Eragrostis sp.
lovegrass
Leptplomacognatum
fall witchgrass
Lycurusphleoides
wolftail
Munroa squarrosa
false buffalograss
Paspalumstramineum
sand paspalum
Setarialeucopila
Plains bristlegrass
Sporobolus sp.
sand dropseed
Stipa sp.
stipa
Shrubs
Artemisiafilifolia
Chrysothamnuspulchellus
Gutierreziasarothrae
Opuntia
Prosopisglandulosa
Quercus havardii
Yucca glauca
sand sagebrush
southwest rabbitbrush
broom snakeweed
pricklypear cactus
mesquite
shinnery oak
soapweed yucca
Forbs
Amaranthusalbus
Ambrosia sp.
Artemisia campestris
Asclepias sp.
Symphyotrichum patens
Symphyotrichumporteri
Eastwoodiaelegans
Conyzacanadensis
Commelina sp.
Croton sp.
Dimorphacarpawislizenii
Erogonumanuum
tumble pigweed
ragweed
common sagewort
Milkweed
late purple aster
white aster
yellow aster
horseweed
widows teer
croton species
tourist plant
wild buckwheat
194
Texas Tech University, Jennifer Zavaleta, May 2012
Euforbiaprostrata
Euforbiaserpyllifolia
Froelichiafloridiana
Gauravillosa
Helianthus annuus
Hoffmanseggiaglauca
Krameria sp.
Liatrispunctata
Linum sp.
Mentzelia sp.
Parenchyrajamesii
Schrankiaoccidentalus
Senecioflaccicus
Senecio sp.
Silenescouleria
Stellaria media
prostrate euforb
upright euforb
snake cotton
woolly gaura
sunflower
hog potato
ratany
dotted blazingstar
flax
stickyleaf forb
stickleaf yellow forb
western sensitive briar
threadleafand Riddell's groundsel
butterweed
sleepy catchfly
common chickweed
195
Texas Tech University, Jennifer Zavaleta, May 2012
APPENDIX C
LIST OF REPTILES AND AMPHIBIANS FOUND FROM 2002-2010 IN A STUDY TESTING
THE EFFECTS OF TEBUTHIURON AND GRAZING IN ROOSEVELT COUNTY, NM
Ambystomatigrinum
tiger salamander
Anaxyrusdebilis
green toad
Arizona elegans
glossy snake
Bufocognatus
Great Plains toad
Bufowoodhousii
Woodhouse's toad
Cnemidophorussexlineatus
six-lined racerunner
Crotalusviridis
prairie rattler
Crotaphytuscollaris
collard lizard
Diadophispuctatus
ringneck snake
Eumeces obsoletus
Great Plains skink
Heterodonnasicus
western hognose snake
Holbrookiamaculata
lesser earless lizard
Lampropeltistriangulum
milk snake
Leptotyphlopsdulis
Texas blind snake
Masticophis flagellum
coachwhip
Phrynosomacornutum
Texas horned toad
Pituophiscatenifersayi
bull snake
Pituophismelanoleucus
gopher snake
Rhinocheiluslecontei
long nosed snake
Sceloporus lecontei
prairie lizard
Sistruruscatenatus
masassauga
Speabombifrons
Plains spadefoot
Tantillanigriceps
Plains black headed snake
Terrapeneornataluteola
desert box turtle
Tertapeneornata
ornate box turtle
196
Texas Tech University, Jennifer Zavaleta, May 2012
APPENDIX D
LIST OF MAMMALS FOUND FROM 2002-2010 IN A STUDY TESTING THE EFFECTS OF
TEBUTHIURON AND GRAZING IN ROOSEVELT COUNTY, NM
Chaetodipus hispidus
Cratogeomyscastanops
Dipidomis ordii
Geomys bursarius
Geomys sp.
Ictidomysmexicanus
Neotoma albigula
Neotoma micropus
Onychomysleucogaster
Onychomystorridus
Perognathusflavescens
Perognathusmerriami
Perognathus sp.
Peromyscusleucopus
Reithrodontomysmegalotis
Reithrodontomysmontanus
Sigmodonhispidus
Spermophilus spilosoma
Spermophilustridecemlineatus
Sylvilagusaudubonii
Sylvilagusfloridanus
hispid pocket mouse
yellow-faced pocket gopher
Ord's kangaroo rat
Plains pocket gopher
pocket gopher species
Mexican ground squirrel
white throated woodrat
Southern Plains woodrat
northern grasshopper mouse
grasshopper mouse
Plains pocket mouse
Merriam's pocket mouse
pocket mouse sp.
white footed mouse
western harvest mouse
Plains harvest mouse
hispid cotton rat
spotted ground squirrel
thirteen-lined ground squirrel
desert cottontail
eastern cottontail
197
Texas Tech University, Jennifer Zavaleta, May 2012
APPENDIX E
LIST OF INVERTEBRATES FOUND FROM 2003-2011 IN A STUDY TESTING THE
EFFECTS OF TEBUTHIURON AND GRAZING IN ROOSEVELT COUNTY, NM
Acrididae (Forb)
Acrididae (Grass)
Apidae
Arachnids
Asilidae
Blattidae
Braconidae
Bruchidae
Buprestidae
Carabidae
Cercopidae
Chilopoda
Chrysomellidae
Chrysopidae
Cicadellidae
Coccinellidae
Corimelaenidae
Curculionidae
Cydnidae
Dictyopharidae
Diptera
Elateridae
Formicidae
Gryllidae
Halictidae
Largidae
Lepid adult
Lepid Larva
Lygaeidae
Mantidae
Meloidae
Miridae
Mordellidae
Myrmeleontidae
Nabidae
Pentatomidae
Phasmatidae
Reduviidae
Scarabaeidae
Scutelleridae
treehopper
grasshopper
bee
spider
robber fly
cockroach
braconid wasp
seed beetle
jewel beetle
ground beetle
froghopper
centipede
leaf beetle
lacewing
leafhopper
ladybird beetle
negro bug
snout and bark beetle
burrowing bug
planthopper
fly
click beetle
ant
true cricket
sweat bee
bordered plant bug
butterfly and moth
butterfly and moth larva
seed bug
praying mantis
blister beetle
capsid bug
tumbling flower beetle
antlion
damsel bug
stink bug
walking stick
assassin bug
June beetle
shield backed bug
198
Texas Tech University, Jennifer Zavaleta, May 2012
Tenebrionidae
Tettigoniidae
Vespidae
darkling beetle
katydid
vespid wasps
199
Texas Tech University, Jennifer Zavaleta, May 2012
APPENDIX F
CHAPTER II VARIABLES DESCRIBED IN TERMS OF MEANS AND SE FOR TREATED-GRAZED, TREATED-NONGRAZED, NOT TREATED-GRAZED, AND NOT TREATED-NON-GRAZED PLOTS
200
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201
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202
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203
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204
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205
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206
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207
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208
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209
Texas Tech University, Jennifer Zavaleta, May 2012
APPENDIX G
CHAPTER III VARIABLES DESCRIBED IN TERMS OF MEANS AND SE FOR TREATED-GRAZED, TREATED-NONGRAZED, NOT TREATED-GRAZED, AND NOT TREATED-NON-GRAZED PLOTS
210
Texas Tech University, Jennifer Zavaleta, May 2012
211
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212
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213
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214
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215
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216
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217
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218
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219