economic feasibility of redberry juniper a thesis in
TRANSCRIPT
ECONOMIC FEASIBILITY OF REDBERRY JUNIPER
CONTROL USING INDIVIDUAL TREE TREATMENTS
by
JEFFREY A. SORELLE, B.S.
A THESIS
IN
AGRICULTURAL AND APPLIED ECONOMICS
Submitted to the Graduate Faculty of Texas Tech University in
Partial Fulfillment of the Requirements for
the Degree of
MASTER OF SCIENCE
Approved
Accepted
May, 2000
Ac
f3 ACKNOWEDGEMENTS Ary\ Li ^W^
r ^ T. I would like to thank Dr. Phil Johnson and Dr. Darrell Ueckert for their time
assisting me with their expertise and to write and edit this thesis. I would like to thank
Dr. Billy G. Freeman for recruiting me into the Agricultural and Applied Economics
program and supporting me with his friendship and guidance. I would also like to thank
Professors Carlton Britton and Don Ethridge for their advice and support during the
writing of this thesis. Also I would like to thank Brent Racher for his allowing me to
participate in the data collection, and thanks to David Echels and Jarrod Depew for their
help collecting the field data. Much gratitude also goes to my wife, Elizabeth SoRelle,
without whose patience, encouragement, support, and seemingly endless love I would
have never finished the project.
u
TABLE OF CONTENTS
ACKNOWLEDGEMENTS ii
LIST OF TABLES v
LIST OF FIGURES vi
CHAPTER
I. INTRODUCTION 1
Specific Problem 4
Statement of Objectives 5
II. LITERATURE REVIEW 6
Physiology 6
Invasion and Establishment 8
Control Methods 14
Economics of Brush Control 18
III. CONCEPTUAL FRAMEWORK 23
Biological Relationships 23
Economic Relationships 32
IV. METHODS AND PROCEDURES 37
The Study Area and Data Collection 37
Calculations and Conversions 44
Estimation of Additional Revenues from Livestock Production 45
Estimation of Additional Revenues Using Lease Income 48
Estimation of Net Present Value 49
111
Baseline Conditions 51
Estimationof Terminal Land Value 57
V. RESULTS 39
Forage as a Function of Canopy Cover 59
Relationship Between Individual Tree Treatment Costs and Canopy Cover 63
Individual Tree Treatment as the Initial and Maintenance
Control Methods 65
Individual Tree Treatment with Initial Mechanical Control 70
Total Net Present Value and Land Values 77
VI. SUMMARY AND CONCLUSIONS 80
Conclusions 83
Limitations and Recommendations 85
REFERENCES 87
APPENDICES
A. MARKETABLE ANIMAL UNIT 92
B. 30 m SUMMARIZED CANOPY COVERS AND FORAGE PRODUCTION DATA 93
C. 60 M SUMMARIZED CANOPY COVERS AND FORAGE PRODUCTION DATA 96
D. SUMMARIZED HERBICIDE TREATMENT DATA 98
IV
LIST OF TABLES
4.1. Componentsof Added Variable Cost. 47
4.2. Low, Baseline, and High Variable Values Used for Analysis with Individual Tree Treatment as Initial Control Method. 52
4.3. Low, Baseline, and High Variable Values Used for Analysis with
Mechanical Control as Initial Control Method. 53
4.4. Average Height an Average Number of Trees ha'' at Each Location. 56
5.1. Mean, Range, and Standard Deviation for Individual Tree Treatment Data. 64 5.2. Net Present Value and Optimum Treatment Cycles for Baseline and
All Variations using Livestock Method. Individual Tree Treatment with Hexazinone for Initial and Maintenance Treatments. 67
5.3. Baseline Solution: 16-Year Optimum Interval Maintenance Control Cycle using Hexazinone as the Initial Control. 68
5.4. Net Present Value and Optimum Treatment Cycles for Baseline and All Variations using Lease Land Method. Individual Tree Treatment With Hexazinone for Initial and Maintenance Treatments. 71
5.5. Net Present Value and Optimum Treatment Cycles for Baseline and All Variations using Livestock Method with Initial Mechanical Control. 73
5.6. Net Present Value and Optimum Treatment Cycles for Baseline and All Variations using Lease Land Method with Initial Mechanical Control. 74
5.7. Baseline Solution: 16-Year Optimum Interval Maintenance Control Cycle
Using Mechanical Control as the Initial Treatment. 75
5.8. Land Values and Optimum Treatment Cycles for Baseline. 79
B. 1. Summarized Data for 30-m Long Transects. 94
C. 1. Summarized Data for 60-m Long Transects 97
D. 1. Summarized Herbicide Treatment Data for 30-m Transects 99
LIST OF FIGURES
3.1. Juniper Canopy Cover Over Time. 24
3.2. Redberry Juniper Canopy Cover With and Without Treatment Using an
Initial Mechanical Control Method. 26
3.3. Redberry Juniper Canopy Cover With and Without Treatment Scenario . 28
3.4. Redberry Juniper Canopy Cover and Forage Production. 29
3.5. Production Function for Grass Production as a
Function of Environmental Inputs. 31
3.6. Forage and Cattle Production following Brush Treatment. 33
3.7. Total Cost Total Revenue Curves. 34
4.1. Map of Texas and Study Site Locations. 38
5.1. Estimated Relationship between Canopy Cover and Forage Production in the Rolling Plains and Edwards Plateau Region. 62
VI
CHAPTER I
INTRODUCTION
Texas rangelands are a vital part of the state's economy, contributing $5.9 billion
in 1998 from the production of cattle and calves, sheep, wool, and mohair (Texas
Agricultural Statistics Service, 1998). Rangeland is defined as uncultivated land that
provides the necessities of life for grazing and browsing animals (Holecheck, Pieper and
Herbel, 1989). In the state of Texas, 38.5 million ha or 61% of the total surface area is
rangeland (Texas Soil and Water Conservation Board, 1991).
The Natural Resources Conservation Service stated in 1964 that brush infestation
was the major problem on Texas rangelands (U.S. Department of Agriculture, 1964).
Osbom and Witkowski (1974) reported that undesirable woody plants infested 82% of
the rangeland in the state. Furthermore, 25% of the state's grasslands had less than half
of the desirable forage plants they once supported, and 30-35% of the state's grasslands
only had a quarter of the usable forage that existed there originally. The loss in income to
ranchers was estimated at $26.2 million aimually from the decreased carrying capacity of
the rangeland due to the reduction of grazable forage. This reduction in rangeland
livestock production not only has reduced income for ranchers, but also has been felt by
suppliers of ranch inputs.
In 1987, the five most common rangeland-invading plants were mesquite
(Prosopis glandulosa), prickly pear (Opuntia spp.), blackbrush acacia {Acacia rigidula),
live oak (Quercus virginiana), and redberry juniper (Juniperus pinchotii) (Texas Soil and
Water Conservation Board, 1991). Several techniques have been used to control these
noxious plants, including the use of mechanical methods, prescribed fire, and herbicides
(Scifres, 1980). Mechanical methods are categorized into two broad groups: top removal
and removal of the entire plant from the ground. Prescribed fire is often used to kill or
suppress woody plants and prickly pear and to bum debris following mechanical brush
treatments. Herbicide treatments are used to control large areas or to treat individual
plants.
Mechanical methods of control are very popular with producers because of their
success rate, immediate results, feasibility, and equipment availability. Often the
equipment used in mechanical brush control is a large crawler tractor with heavy-duty
implements. Mechanical methods include shredding, chaining, grubbing, root plowing,
and bulldozing. Mechanical control methods have some substantial disadvantages
compared to prescribed fire and chemical control. The first disadvantage is the cost. The
cost per hectare to treat redberry juniper with two-way chaining was estimated at $37.58
to $45.10 ha"' (Johnson et al., 1999) and grubbing or root plowing would cost $148 to
$173 ha' . Also, when using a mechanical method of control, such as root plowing,
environmental problems such as soil erosion and destruction of a high percentage of the
perennial grasses and desirable browse plants may occur (Scifres, 1980). According to
Scifres, mechanical control methods remain one of the most important control techniques
used on brush because in many cases they may be the only solution (Scifres, 1980).
The use of prescribed fire is less expensive than mechanical control. Johnson et
al. (1999) reported that the cost to bum redberry juniper is $8.73 to $10.47 ha''.
Prescribed fire is often used after a mechanical treatment to eliminate downed debris or to
maintain treated rangeland. Prescribed fire is most often used to re-treat rangeland
subsequent to mechanical or chemical treatment to extend the treatment life of the
expensive, initial treatments and to maintain productivity. Johnson et al. (1999)
suggested that rangeland infested with redberry juniper in the Texas Rolling Plains
should be rebumed every 7 years to maintain the benefits realized by the mechanical
treatment of two-way chaining. However, there are several disadvantages to prescribed
fire, the most obvious being safety, liability, and suitable livestock grazing management.
Although prescribed fire is an effective way to suppress or control some bmsh species, its
disadvantages compared to other methods of treatment have limited its widespread use.
Herbicidal treatment of bmsh is also an effective control technique. According to
Scifres (1980), the herbicides currently available are highly selective and systemic in
action, with only small amounts required for control. Other important advantages of
herbicides are their safety to humans if used correctly, ease of application, and relative
inexpense as compared to mechanical methods. Also, it is not necessary to defer grazing
from a pasture before or after treatment. However, there are some disadvantages to
herbicide treatments, the most notable of which is availability of labor. Some commonly
used herbicides to control bmsh on Texas rangelands include: clopyralid 3,6-dichloro-2-
pyridinecarboxylic acid, tebuthiuronN-[5-(l,l-dimethylethyl)-l,3,4-thiadiazol-2-yl]-
N,N'-dimethylurea, hexazinone 3-cyclohexyl-6-(dimethylamino)-1 -methyl-1,3,5-triazine-
2,4(1 H,3H)-dione, 2,4-D (2,4-dichlorophenoxy)acetic acid, dicamba 3,6-dichloro-2-
methoxybenzoic acid, 2,4-D plus picloram4-amino-3,5,6-trichloro-2-pyridinecarboxilic
acid, and triclopyr [(3,5,6-trichloro-2-pyridinyl)oxy]acetic acid.
Specific Problem
Redberry juniper is one of the most common undesirable plants on Texas
rangelands. Redberry juniper is an evergreen conifer found mainly in westem Texas.
Oklahoma, New Mexico, and Arizona (Smith, Wright, and Schuster, 1975). Redberry
juniper grows to about 7.6 m tall with lower branches occurring close to the ground
(Correll and Johnston, 1970). According to Scifres (1980), redberry juniper occurs most
frequently on rough rangeland on shallow soils in the Rolling Plains and Edwards Plateau
Region of Texas. Cedar (redberry juniper) is a resprouter, with its bud zone often located
beneath the soil surface (Dye, Ueckert, and Whisenant, 1995).
Redberry juniper infestations have plagued rangelands since the early twentieth
century because of overgrazing, periodic droughts, climatic conditions and atmospheric
CO2 concentration more favorable for woody plants, and the absence of natural fires. In
the last 50 years, however, infestations have increased. Redberry juniper infestations
have increased from 2.5 million ha in 1948 to 4.1 million ha in 1982 in a 65-county area
in northwestem Texas (Ansley, Pinchak, and Ueckert, 1995). The National Resources
Inventory estimated in 1987 that moderate-to-dense infestations of cedar in northwest
Texas had increased by 16% from 1982 to 1987 (USDA, 1990). This increase in
redberry juniper poses threats to the economic potential of rangeland in the Rolling Plains
and Edwards Plateau regions of Texas.
Although much research has been conducted on techniques and approaches to
control redberry juniper, limited research has been done to evaluate the economic
feasibility of the various control practices. This study evaluated the economic feasibility
of individual tree hexazinone applications as an initial method of redberry juniper control
and as a maintenance treatment following mechanical methods.
Objectives
The general objective of this study was to determine the economic feasibility of
individual tree treatment with hexazinone for control of redberry juniper in the Rolling
Plains and Edwards Plateau of Texas. Specific objectives were to:
1. estimate the relationship between forage production and redberry juniper
canopy cover;
2. estimate the additional forage production following treatment of redberry
juniper;
3. determine the additional revenues following treatment of redberry juniper; and
4. determine the net present value of the bmsh control practice and optimum
individual tree treatment intervals under various environmental, economic, and
managerial conditions.
CHAPTER II
LITERATURE REVIEW
An overview of the literature relevant to redberry juniper and related noxious
plants is presented in this section. The section is divided into four subsections:
physiology, invasion and estabUshment, control methods, and economics of control.
Physiology
Redberry juniper is classified as a Gymnosperm, which is a flowering tree or
shmb that has seeds not enclosed in an ovary (Correll and Johnston, 1970). Other
gymnosperms include pines, firs, bald cypress, and junipers.
Redberry juniper is a basal-sprouting evergreen conifer that has multiple stems
originating from its base to form a dense clump. The bark of redberry junipers is thin,
ash-gray and shaped like scales (Correll and Johnston, 1970). The trees have a white sap
wood with light brown or reddish heartwood. Redberry juniper inhabits gravely, rocky
limestone or gypsum soils on open flats or dry hills (Correll and Johnston, 1970). Also,
redberry juniper can be found on deep, fertile soils on lowland sites, as well as in
canyons, on caprocks, and in arroyos.
Smith, Wright, and Schuster (1975) described the reproduction of redberry
juniper. In their study, redberry juniper germination did not appear to be an interaction
between soil moisture levels and soil temperature; however, both environmental
conditions measured independently did affect germination. The authors found that as soil
moisture declines, seed germination declines, with optimum moisture levels being 0 to
0.4 MPa. They concluded that the optimum soil temperature for redberry juniper
germination was 18 degrees Celsius, which implies that mild, moist conditions are
optimal for germination. Smith, Wright, and Schuster (1975) flirther stated that
germination and emergence were greatest in wet springs and autumn seasons.
Following seed germination, environmental conditions must be favorable for
seedling establishment. According to McPherson and Wright (1990a), above-average
cool-season precipitation in two consecutive years may be the dominant factor for
accelerated redberry juniper establishment in rangelands. However, even if redberry
juniper can estabhsh, it is a weak competitor compared to grasses. Smith, Wright, and
Schuster (1975) found that after emergence and in the following two months, clipping the
seedlings above the cotyledonary node killed about 58% of the seedlings; however,
clipping at ground level killed all of the seedlings and saplings until they grew to 8 years
of age.
A major problem with redberry juniper is its aggressive resprouting if the top of
the tree is removed above the bud zone. If the aerial portion of the tree is killed, the
resulting sprouts grow faster than the undamaged plant (McPherson and Wright, 1989).
A primary reason for the faster growth rate following top kill is the massive resources the
plant can use for resprouting from extensive root systems that provide food reserves and
water. Also, unlike saplings, which are poor competitors with grasses (Smith, Wright,
and Schuster, 1975), redberry juniper resprouts are not affected by adjacent shmbs or
herbaceous plants (McPherson and Wright, 1990a).
7
Invasion and Establishment
Phillips (1999) determined the rate of change of redberry juniper canopy cover
from the mid 1950s through the late 1990s on undisturbed and adjacent mechanically
treated rangeland at 5 sites in westem Texas. Using aerial photographs taken an average
of 13.4 years apart, he determined that on undisturbed sites, average redberry juniper
canopy cover increased an average of 0.37 percentage unit year'' (range 0.12 to 0.59).
On sites where mechanical control practices had occurred, redberry juniper canopy cover
increased 1.00 percentage unit year'' (range 0.72 to 1.21). Canopy cover changes within
shorter periods ranged from -0.44 to 1.08 percentage unit year'' on undisturbed sites, and
from 0.50 to 1.73 percentage unit year'' following mechanical control. Phillips states that
following mechanical control, juniper canopy cover recovered to pre-treatment levels in
an average of 20.6 years. He also found that annual herbage production on undisturbed
rangeland declines in three stages. In the first stage, herbage production declines slowly
as redberry juniper canopy cover initially reaches 12 to 18%. As redberry juniper canopy
cover increases from 19%o up to 29%, herbage production decreases rapidly. After
redberry juniper canopy cover exceeds 29%, herbage production again declines slowly.
He recommended initial and maintenance control techniques should be installed before
redberry juniper canopy cover exceeds 12 to 18%.
Racher (1998) estimated aerial phytomass production with varying levels of
redberry-juniper-dominated canopy cover, density and canopy volume on four sites in the
Rolling Plains and Edward's Plateau resource areas of Texas. He estimated equations for
each of the four study sites using ordinary least squares (OLS). The first location, located
8
in northeastern Borden County, Texas, was a deep hardland range site. He estimated the
following equation for this site:
Y = 2530 - 133.660 X + 4.8658 X^ - 0.0592 X^ (2.1)
where Y was aerial phytomass yield in kg ha'', and X was redberry juniper dominated
canopy cover estimated on line transects. He reported an R = 0.88 for the model.
Racher stated that forage yield would decline 55% as canopy cover increased from 0 to
40%.
Like the first location, the second was a deep hardland range site. The site was
located in Ford and Hardeman Counties, Texas. Racher's (1998) estimated relationship
between aerial phytomass production and redberry-dominated canopy cover for this site
was:
Y = 2024 - 68.785 X + 1.6580 X^ - 0.014704 X^, (2.2)
where Y and X are defined above with a R = 0.88. At this location it was estimated that
after canopy cover increased to 63%, the herbaceous yield potential would decline 71%.
The third study area was located in Dickens County, Texas, on a mixland range
site. Racher estimated the following cubic equation for this site:
Y = 2651 - 50.342 X + 1.2519 X^ -0.019177 X^, (2.3)
where Y and X are defmed above with a R = 0.71. He stated that at this location the
highest rate of yield reduction occurred when canopy cover was at 0 to 10% and above
35%). The equation predicted that yield would be reduced by 54% from the potential
production when redberry juniper dominated canopy cover reached 44%.
The fourth and last location was a clay loam range site located in Tom Green
County, Texas. The estimated equation for this site was as follows:
Y = 1639 -2.715 X -1.0519 X^ +0.015517 X^, (2.4)
where Y was aerial phytomass yield in kg ha"', and X was the redberry juniper dominated
canopy cover with an R = 0.82. At this site, Racher predicted that aerial phytomass was
reduced 51%) from the potential production when redberry juniper canopy cover
increased to 48%). He further estimated that at a 20% canopy cover, herbaceous yield
would decline 21%.
Racher also estimated a combination equation using dummy variables as intercept
shifters for each of the four locations. He estimated the following equation:
Y = 1959 - 55.836 X + 1.51 X^ - 0.009679 X^ + 280.876 Bi
+ 670.834 B2 - 22.809 B3, (2.5)
where Y was aerial phytomass yield in kg ha'', and X was the redberry juniper dominated
canopy cover, and Bi, B2, and B3 were location variables. He reported an R^ = 0.82 for
the model. He stated that forage yield rapidly decreased as redberry-juniper-dominated
canopy cover increased from 0 to 35%. He further stated that the largest decrease in
yield occurred as canopy increased from 0 to 15%. He concluded that redberry juniper
control should be initiated at low levels of canopy cover on deep soils where production
potentials are high.
Jameson (1967) developed non-linear equations to study the effects of trees on
understory vegetation. He used three sets of data, two from Pearson (1964) and one from
Arnold et al. (1964). Pearson collected data on ponderosa pine (Pinus ponderosa) basal
area, canopy cover, and herbage production in northem Arizona. Amold et al. (1964)
collected data in northem and central Arizona on pinyon-juniper (Pinus edulis, Juniperus
10
spp.) canopy cover and herbage production. Jameson estimated three relationships from
these data sets using the following fiinction form:
Y = H + A(l -e-^^^-^^)^" ' , (2.6)
where X is the independent variable, Y is the estimated value of the dependent variable,
and H and A are the upper and lower asymptotes, respectively. Jameson stated that B
provides the necessary curvature, M adjusts the inflection point, and G adjusts the value
of X so that X-G = 0 when Y=H.
Using this functional form and the three sets of data, Jameson estimated three
non-linear equations. The first equation was the relationship between ponderosa pine
basal area and herbage production:
Y = 6 7 2 - 6 2 8 ( l - e - ' ' ^ ' ' ) ' ' \ (2.7)
where Y is the herbage production in kg ha'' and X is the pine basal area in square meters
ha''. The second equation estimated was the relationship between ponderosa pine canopy
cover and herbage production:
Y = 682-643(l-e-° ' ' ' ' ' ) ' , (2.8)
where Y is the herbage production in kg ha"' and X is the pine canopy cover. The last
equation estimated by Jameson was the relationship between pinyon-juniper canopy
cover and herbage production:
Y = 597-527(l-e- '° ' ' ' ' ) ' , (2.9)
where Y is the herbage production in kg ha"' and X in the pinyon-juniper canopy cover.
11
Jameson stated that relationships between tree measurements and herbage
production are "clearly curvilmear." He reported that other mathematical models that
had been pubUshed included log y = a +bx, y =a +b log(x +1), y = a + bx + cx^, and y = a
+ bx + ex + dx . Jameson estimated all of these functional forms using the three sets of
Arizona data and none of the forms gave a "good fit." He stated that the simpler models
generally gave a "poor fit," especially as X approached zero and that the polynomial
models were "illogical when computed lines were extended beyond the limits of the data"
(p. 247). He concluded that his 5-parameter transition sigmoid growth curve should be
used as a general model for overstory-understory relationships; however, he did report
that his first equation was the only one that was sigmoidal.
McPherson and Wright (1990a) studied the establishment of redberry juniper in
westem Texas. They found that over the 30-year period from 1950 to 1979, the
establishment rate was approximately twice as high in the second year of a 2-year period
of above-average cool-season precipitation as compared to periods that had normal to
be low-normal precipitation. They concluded that the occurrence of consecutive wet
years was the key to redberry juniper establishment. The first year facilitated seed
germination and the second facilitated plant establishment.
McPherson and Wright (1990b) described the effects of cattle grazing and
redberry juniper canopy cover on herb cover and production in westem Texas. They
found an inverse relationship between juniper canopy cover and grass production. This
relationship was linear on ungrazed sites and logarithmic on grazed sites, which led them
to conclude that grazing shifts the competitive advantage toward juniper because of
decreased competition for resources.
12
Along with the two studies mentioned above, McPherson and Wright (1989)
studied the direct effects of competition on individual juniper plants. They found that
large plants with buried basal caudexes or well-developed root systems were independent
of competition. They also stated that even after top removal, there was no competition
between juniper regrowth and forage plants. In addition, herbaceous plants and shmbs
were unable to exclude the junipers from the resources. They found that the growth rate
after top removal was mainly dependent on the mean ambient temperature and total
precipitation. They suggested that competition from neighboring species was more
detrimental to growth of redberry juniper seedhngs than adult trees.
McPherson, Wright and Wester (1988) studied the patterns of shmb invasion in
semi-arid Texas grasslands. They found that the rate of redberry juniper encroachment
on shallow sites was facilitated by the presence of honey mesquite and cattle grazing.
The authors stated that accelerated invasion of grasslands by junipers was a function of
the removal of herbaceous competitors and the exposure of bare ground. The rate of
invasion of juniper in areas where mesquite was present was higher than on sites where
mesquite was absent because mesquite serves as a nurse tree for the saplings. They
suggested that mesquite can change the microclimate and soil around the tree to facilitate
establishment of other species including algerita (Berberis trifoliolata), redberry juniper,
littleleaf sumac (Rhus microphylla), and catclaw mimosa (Mimosa biuncifera). They
found that with mesquite present and no large junipers in the area, the mean density of
jumper ranged from 100 to 1250 plants ha"'. On similar soils but without mesquite, the
mean density of juniper was less than 100 to 150 plants ha''. They also concluded that
13
grazing by livestock exposed more bare ground for redberry juniper to establish and
reduce competition with other forages.
Control Methods
Mechanical Control
The most widely used mechanical control method is chaining, which is the felling
of trees by an anchor chain pulled between two large tractors or bulldozing, which is
removing the roots of trees from the soil. Skousen, Davis, and Brotherson (1986)
sampled two adjacent big game winter range sites located in central Utah in 1981 that had
been double chained in 1965 and selectively bulldozed in 1957. They found that double
chaining and bulldozing had significantly reduced the tree and litter cover, had increased
grass production, and had increased browse species densities compared to a nearby-
untreated site. The untreated site had 35.5% juniper cover and 0.46% grass cover,
whereas the two-way chained treated area had a 4.1% juniper cover and 8.31% grass
cover. On the bulldozed site juniper cover was 1.42% and a grass cover of 13.68%).
They concluded that because tree density was 42% greater on the two-way chained site
than on the bulldozed site, that bulldozing was "probably" more effective; however, they
further concluded that the ineffectiveness of the two-way chaining may have been due to
the relatively young age of the stand and that it was comprised of small, flexible trees at
the time of treatment.
14
Prescribed Fire
Although prescribed fire is not an effective primary control technique on mature
stands of redberry juniper due to the absence of adequate fme fiiel to carry intense fires, it
is an effective tool in maintaining a rangeland subsequent to mechanical treatment has
been applied (Rasmussen, McPherson, and Wright, 1986). Steuter (1982) found that
spring burning slows the growth of redberry juniper. He also found that although
perennial grass yields were reduced the fu-st season after a prescribed fu-e event, yields
were similar to those on unbumed areas the second year. He also determined that above-
normal rainfall the year following a bum produced grass yields equal to untreated areas
and chained areas. However, in dry years following a burn, the recovery time to reach
grass yields similar to those on untreated areas was 2 years. Despite an initial reduction
in grass yields, Steuter found that prescribed fu-e not only killed some redberry juniper,
but also killed other undesirablegrasses and forbs. These species included threeawn
(Aristida spp.) and common broomweed (Amphiachyris amoena). Furthermore, Steuter
stated that because of the high mortality rate of young redberry juniper, slow regrowth,
and delayed reproduction of the redberry junipers, a 15-year interval between
maintenance burns may be possible. He also suggested that burning juniper stands before
green-up when soil moisture reserves are favorable might minimize losses in grass yields.
Steuter and Britton (1983) found that the mortality of redberry juniper with fire
treatment was directly related to the location of the bud zone, plant size, site conditions,
and growing conditions. They found that buming on shallow rocky sites with trees less
than 13 years old resulted in mortality rate between 33% and 100%. This large variation
was dependent upon tree size and growing season conditions. They found that trees
15
growing in deep soils with bud zones covered with soil only had a 13%) mortality rate.
During a year of above-average precipitation, the mortality redberry juniper averaged
70%). However, this mortality rate was not universal; trees with the bud zone below the
soil surface had only a 3% mortality rate.
Chemical Controls
The most commonly used herbicide treatment for redberry juniper control is
picloram. Scifres (1972) applied picloram pellets by hand to redberry junipers in
northwest Texas. The pellets were applied to the trunk bases at rates from 0.93 to 7.44
grams a.i. m' of canopy diameter. The average density of the stands of redberry juniper
was 124 trees ha'' and the trees averaged 2.68 m tall. He reported that 95% of fohage
was killed after 1 year and that 100%) of the foliage was killed after 2 years when rates
were 3.81 to 7.44 grams a.i. of picloram were applied. He also found that there was no
grass damage from the picloram treatments but that some other woody species close to
the redberry junipers were damaged or killed.
Schuster (1976) also studied the control of redberry juniper with picloram. The
trees were up to 3.65 m tall, with canopy diameters ranging from 0.3048 to 4.57 m. The
herbicide was applied with a sprayer each month from April to October to completely
saturate the foliage of the trees at a rate of 0.23 kg per 378.5 liters of water. Two
treatment mixtures were appHed in diesel fuel-water emulsions: picloram at 0.227 kg per
378.5 liters in an oil-water emulsion carrier, and picloram + 2,4,5-T at a 1:1 ratio at 0.454
kg per 378.5 I of carrier. The effectiveness of the treatments was evaluated at the end of
the second growing season following treatment. Schuster used soil-applied picloram as
16
10%) pellets at rates equivalent to 0.227, 0.454, 0.908, and 1.816 kg ha''. He concluded
that 2.24 kg a.i. ha'' was the optimum rate to control redberry juniper using dry form
picloram applied as 10%) pellets.
The foliar spray treatments reduced redberry juniper canopies by at least 95%)
after the second growing season, except when applied in the months of October and
August. The reduction in canopy was 74% in October and 82% in August. Schuster
reported that a 2.24 kg a.i. ha'' broadcast rate of picloram resulted in a 94%) reduction in
canopies and a 76%) plant kill. He fiirther stated that picloram rates less than 2.24 kg ha"'
were not as effective and that rates over 2.24 kg ha'' did not improve control.
McGinty et al. (1998) recommended the application of undiluted hexazinone to
the soil surface within 0.9 m of the stems of redberry juniper for control of this species.
The recommended dose is 2 ml 0.9 m'' of canopy height or diameter (whichever is
greater). This treatment normally kills 76 to 100%) of the plants treated. In a 1997
experiment, this treatment killed 48% of the mature redberry junipers treated and reduced
juniper canopy volume by 91% (D.N. Ueckert, unpublished data). The same treatment
applied to the juniper stem bases killed 65% of the mature junipers and reduced live
juniper canopy volume by 98%. In five large-plot experiments installed in 1996, the 2 ml
dose of undiluted hexazinone 0.9 m'' of plant height or diameter killed an average 93% of
the immature redberry junipers treated, compared to 91% mortality of immature junipers
treated with a leaf spray containing 1% picloram (Tordon 22k) (D.N. Ueckert and W.A.
McGinty, unpublished data).
17
Economics of Bmsh Control
Ethridge, Weddle, Bowman, and Wright (1991) estimated the labor savings from
controlling bmsh in the Texas Rolling Plains. The study focused on three noxious plant
species: honey mesquite, redberry juniper, and prickly pear. They found that by using
bmsh control, ranchers could benefit in three ways: increased stocking capacity, reduced
permanent ranch working crew, and reduced round-up labor. They estimated that both
permanent ranch labor and round-up labor could be reduced by 50 to 60%. They also
determined that bmsh control, regardless of method, increased carrying capacity of
rangeland by 40 to 50%). The economic impact of this increase was the reduction of fixed
cost per animal due to the increase in animal numbers.
Osbom and Withowski (1974) estimated the economic impact of honey mesquite
encroachment in Texas. They stated that the encroachment of mesquite had not only
reduced the livestock carrying capacity of the rangeland, but had also increased costs to
ranchers for supplemental feed. It was estimated that because of mesquite encroachment,
the total reduction in usable forage was 0.924 to 1.8 million Cow Producing Units (CPU).
The estimate total output of range livestock could be increased by 12 to 23% if mesquite
were not present. The authors stated that this decrease in production from rangelands had
affected private investment and public policy. Private investment had been delayed or
discontinued, which has resulted in a regressive attitude toward the ranching business.
Also, the decline in ranch values has affected the tax base for local governments. This
decrease in tax base has caused problems for local governments because of long-term
fmance projects, including refinancing and selling of long-term bonds.
18
Economic Evaluations of Other Noxious Species
Carpenter, Ethridge, and Sosebee (1991) studied the economics of broom
snakeweed (Gutierrezia sarothrae) control on the Southem Plains. The authors used
three general steps to determine economic feasibility of investing in herbicidal control of
broom snakeweed. The first step was to estimate the biological response of snakeweed
and the corresponding forage yield using multiple regression techniques. They used the
regression model to estimate forage production over the life of the treatment. The second
step was to estimate cow-calf efficiency gains. These gains were estimated for various
levels of snakeweed infestation. The last step was to determine the total economic
benefits of snakeweed control. The economic benefits were calculated by combining the
value of the additional beef produced as a result of the treatment due to increased
carrying capacity and the value of the additional beef produced due to the suppression of
the poisoning effect of broom snakeweed. The authors estimated the profitablitiy of
broom snakeweed control at various livestock price levels and discount rates. They
concluded that at all levels of cattle prices and discount rates, it was economically
feasible to control snakeweed except for areas with light infestations under normal
environmental and economic conditions. The authors also found that when broom
snakewood infestations were moderate to heavy, there was a substantial economic impact
on animal efficiency; however, when infestations were light, there was no impact on
animal efficiency and revenue animal unit'' . They concluded that snakeweed-free
pastures had 22%) more revenue per cow producing unit than pastures that were
moderately to heavily infested.
19
Ethridge, Dahl, and Sosebee (1984) evaluated the economics of chemical honey
mesquite control using 2,4,5-T [(2,4,5-trichlorophenoxy)acetic acid]. They estunated the
net present value of added grass production over the life of the treatment. The gross
value of herbicidal mesquite control was estimated using different combinations of
livestock prices, percent top kill, percent canopy cover, and discount rate. They reported
net present values of mesquite control ranging from $22 ha'' to over $73 ha"'.
Ethridge, Pettit, Neal, and Jones (1987) estimated the net returns from the control
of sand shinnery oak (Quercus havardii) using tebuthiuron. They determined that
tebuthiuron at a rate of 0.56 kg a.i. ha"' was more profitable than higher tebuthiuron rates.
The authors suggested that many factors affected the returns from treating shiimery oak,
including herbicide rate, livestock prices, discount rates, rainfall, and cost of tebuthiuron.
The payback period for treatment with tebuthiuron ranged from 3 to 6 years, and the
stocking rates could possibly double or triple after treatment.
Economic Evaluations of Juniper Control
Reinecke, Conner and Thurow (1997) studied the economic considerations in
ashe juniper (Juniperus ashei) control. They reported that bmsh management practices
produced a significant increase in forage production. They used grazing lease revenues
and costs for the management technique. The authors estimated the stocking rates for
different levels of ashe juniper canopy cover and discovered that controlling junipers on
areas with low ashe juniper canopy cover showed the highest net cash flow at $138.70 ha"
' using rotational grazing, compared to a $121.06 ha'' using a continuous grazing system.
The intemal rate of retum to ashe juniper control for the same scenarios was -11.75% and
20
-22.56%), respectively. Other scenarios evaluated ranged from 15 to 75% initial canopy
cover. The net cash flow for these scenarios ranged from $105.42 ha'' to $44.06 ha'' for
continuous grazing. They suggested that neglecting or postponing ashe juniper control
has significant negative fmancial impacts for producers.
Johnson, GerboUni, Ethridge, Britton, and Ueckert (1999) described the
economics of redberry juniper control in the Rolling Plains. The authors stated that
redberry juniper control should be considered as a long-term investment with cost and
benefits being evaluated over a 30-year period. The management system evaluated was
an initial treatment of two-way chaining followed by periodic maintenance burns. A
forage production function relative to percent juniper canopy cover was estimated by the
equation:
T r p _ 7.1626024-0.000441'CCf ^^ . ^x
where HPt is the production of herbage in kg ha'' at time t, e ' ^ " is the amount of
herbage produced at zero canopy cover, and CCt is the percent redberry juniper canopy
cover. The forage production function showed that as juniper canopy cover increased to
33.67%, forage production decreased at an increasing rate. After 33.67% canopy cover,
forage production continued to decrease but at a decreasing rate.
Johnson et al. used several variables to determine the economic feasibility of
redberry juniper control, including initial percent canopy cover, increase in canopy cover
year', price of livestock, real discount rate, and treatment cost. The authors determined
that under all conditions tested, the net present value of the treatment was positive and
that the optimum period between maintenance bums was 7 years. However, this
21
optimum burn interval was dependent upon the reinfestation rate. A higher rate of
reinfestation decreased the optimum bum interval; likewise, a slow reinfestation rate
increased the bum interval. The authors also determined that the pay-back period under
baseline conditions was 8 years. The authors suggested that with the capitalization rate
for the Rolling Plains rangeland at approximately 3%, producers should consider
investment in redberry juniper rather than ranch expansion because the estimated intemal
rate of retum of 27% for bmsh control was much greater than the retum from investment
in additional rangeland.
^1
CHAPTER m
CONCEPTUAL FRAMEWORK
The economic evaluation of redberry juniper control may be approached from a
capital budgeting perspective. As a long-term range improvement, costs of the treatments
are realized at the time of the range improvement, whereas benefits of the improvement
are realized for several years following treatment. In this analysis, two bmsh control
treatments were assumed: the first was individual tree treatment with hexazinone both as
the initial control technique and the follow-up maintenance treatments; the second was an
initial mechanical control technique (two-way chaining) followed by individual plant
treatments with hexazinone as a maintenance practice. The major assumption of this
analysis was that added revenue occurs from increased livestock production following
both the initial treatment and maintenance treatments due to increased forage production.
No added revenue was assumed to accme due to improvement of wildlife habitat
resulting from treatments. The economic feasibility of the bmsh control investment was
determined by whether or not the present value of added revenues exceeded the present
value of added costs.
Biological Relationships
Redberry Juniper Response
Conceptually, three different infestation zones of redberry juniper canopy levels
and time can be identified. The first zone, labeled Zone A in Figure 3.1, is where the
canopy cover of the redberry juniper is increasing at an increasing rate over time. Zone B
23
Juniper Canopy Cover
Figure 3.1. Juniper Canopy Cover Over Time.
Time
24
is the period after the canopy cover reaches an inflection point and is increasing at a
decreasing rate. Zone C is the period in which the canopy cover has reached equilibrium
with the environment and is nearing a maximum level.
With this hypothesized relationship between canopy cover and time and the
identification of three infestation zones, there are two possible control response scenarios.
The first control response is the scenario in which the canopy cover of redberry juniper is
too great (Zone C) for individual tree treatment to be feasible; therefore, a mechanical
control technique must be employed for the initial control. The second response scenario
is where the canopy cover is not so high (Zones A and B) and where individual tree
treatment may be feasible not only as a maintenance treatment practice, but also as the
initial control treatment. It is assumed for this study that redberry juniper is the bmsh
species that is the target of the initial control treatment and follow-up treatment, and that
it will be the dominant reinvading species subsequent to the initial and maintenance
control treatments.
Figure 3.2 describes the response of juniper canopy cover over time using an
initial mechanical control method and individual tree treatment as maintenance control.
A mechanical control technique would be used because of the high initial canopy cover in
Zone C of Figure 3.1. The curve labeled CCw/o represents the level of redberry juniper
canopy cover through time without treatment. The curves labeled CCs show the re-
establishment of the junipers following each treatment. The shorter curve labeled CCi in
Figure 3.2 represents the canopy after the initial treatment at time t l . No matter which
mechanical control method is used, the initial treatment has a limited life due to seedling
25
JUniper Canopy Cover
CCi
CCw/o
CCs CCs
t1 t2 t3 Time
Figure 3.2. Redberry Juniper Canopy Cover With and Without Treatment Using an Initial Mechanical Control Method.
26
establishment and rapid regrowth of trees that were not uprooted. Therefore,
maintenance treatments are needed to kill the surviving junipers and newly established
junipers following the initial treatment. However, because individual tree treatments are
highly effective, successive maintenance treatments after the initial treatment should
occur further apart.
If the juniper canopy cover is not too great and the trees are relatively small, the
initial mechanical control method may be foregone. Figure 3.3 shows this altemative
scenario. The curve CCw/o represents the percent canopy cover of the juniper but the
curve is increasing at a steeper rate because the initial control is when the juniper
infestation is in Zone A or B near the vertical axis. In Figure 3.2, the canopy has reached
a closed canopy; therefore, no new trees are established and the trees are reaching their
maximum size. The curves labeled CCs in Figure 3.3 show the juniper canopy cover after
the individual plant treatments. The interval between each successive follow-up
treatment grows farther and farther apart, due to the high level of effectiveness of the
control method when applied to trees less than 1.8 m tall.
Forage Response from Juniper Control
Juniper canopy cover and forage production are inversely related. As juniper
canopy cover increases, the amount of forage produced decreases because juniper
competes aggressively for light, nutrients and water. As the canopy cover increases and
the trees get older and mature, yield, cover, and diversity of forage plants decrease.
Figure 3.4 illustrates that as juniper canopy cover increases, forage production decreases
27
JUni per Canopy Cover
A / B
CCw/o
CCs CCs
t1 12 Time
Figure 3.3. Redberry Juniper Canopy Cover With and Without Treatment Scenario.
28
Redberry Junlp«r Canopy Cover
Figure 3.4. Redberry Juniper Canopy Cover and Forage Production.
29
until it approaches a production output close to zero. It is conjectured that actual forage
production never reaches zero, yet the ability of livestock to utilize the little forage
produced may be severely limited due to the dense bmsh stands.
The relationship between forage production and inputs can also be represented by
a traditional production function as illustrated in Figure 3.5. The vertical axis represents
forage production, and the horizontal axis represents variable environmental inputs. For
example, as the amount of rainfall increases while holding all other environmental inputs
constant, the forage production increases. This relationship is represented by the curve
TPPw/o- However, if the control of juniper is implemented, the production function shifts
upward due to the decrease in juniper canopy cover. The same amount of inputs
produces more forage due to less competition between junipers and forage species. TPPx,
represents this relationship between forage production and inputs with juniper control.
The additional forage production can be calculated by:
AFP = (FPi - FP2), (3.1)
where AFP is the additional forage production produced as a result of from the treatment,
FPi is the quantity of forage production with juniper control, and FP2 is the quantity of
forage production without control.
Through time, redberry juniper canopy cover will increase, and because of its
inverse relationship to grass production, the curve TPPw will shift downward to its
original pretreatment level (TPPw/o )• Thus, forage production will diminish due to
increased competition for resources.
30
Forage
FPl
TPPw
FP2
X* Inputs
Figure 3.5. Production Function for Forage Production as a Function of Environmental Inputs.
31
Livestock Response
Range improvements such as juniper control increase the amount of grazable
forage ha" . As the amount of usable forage increases, the producer makes adjustments in
the stocking rate of the ranch. Assuming that the land is at the correct stocking rate
before treatment, the producer may increase the stocking rate at some time after
treatment. Additional benefits to juniper control are that livestock producers may realize
greater rates of gain due to less stress on the animals, easier access to forage, and greater
diversity of herbaceous forage plants.
The response of livestock production is similar to the response of forage
production to juniper control. As forage production increases, so does livestock
production. Figure 3.6 shows the relationship between forage production, cattle
production, and time after bmsh control. After the initial treatment, forage and cattle
production increase to levels above pretreatment levels. Over time, the redberry juniper
reestabhshes and livestock production declines. Forage production increases after
application of a maintenance control treatment, then over time it again decreases as the
juniper re-establishes and begins to compete.
Economic Relationships
The cost for bmsh treatment depends on the treatments used in the long-term
bmsh management system, while the revenues are dependent on forage production. For
this analysis, the different levels of livestock production on improved and unimproved
rangeland are shown using a static model for total revenue and total cost. In Figure 3.7,
there are two total cost curves: the curve labeled TCw/o represents the total cost of the
32
Forage/ cattle production
0 Initial Spray Spray Time
Figure 3,6. Forage and Cattle Production following Bmsh Treatment.
33
Revenue/tost
P^w/b P*b p*w Cattle Production
Figure 3.7. Total Cost and Total Revenues Curves.
34
producer who does not control juniper, and the curve labeled TCw represents the total cost
curve of the producer who controls juniper. The added cost of treatment can be
conceptualized by viewing the total fixed cost curves TFCw. The cost of treatment is
added to the fixed cost of the producer (TFCw/o) because it is a long-term cost and is not
dependent on the number of animals the producer is currently carrying. The curve TCw/o
is shifted up and to the right to reflect this increase in cost due to the bmsh control
operations and is labeled TCw Also shown in Figure 3.7 is the total revenue curve. The
total revenue curve is the same for both situations because it is independent of the cost
curves and is determined by market livestock prices.
If the goal of the producer is to maximize profit, the producer will produce at
points P*w/o and P*w depending on whether the producer has controlled the redberry
juniper. The points P*w/o and P*w are the profit maximizing points where the marginal
cost equals the marginal revenue. Producers who treat redberry juniper will maximize
profits at P*w and producers who do not treat redberry juniper will maximize profits at
p* w/o-
After the bmsh treatment, the percent canopy cover of redberry juniper will
increase each year with reinfestation. As juniper canopy cover increases, grass
production will begin to decline. This decrease in grass production in tum will decrease
cattle production, which will decrease total cost. Therefore, it is expected that through
time, the TCw curve will shift back down and to the left to curve TCtw, which will in tum
shift the profit maximizing level of cattle production to the left to P*b, becoming closer to
the original untreated livestock production level at P*w/o-
35
The feasibility of the range improvement investment may be determined as the net
present value of the treatment which is the discounted cash flow at the firm's discount
rate. The net present value for the treatment is:
JL AT? n AC
MPV=y-^^-f^^^, (3.2)
t ^ d + O' i^od + i)'
where NPV is the net present value of the treatment, AR is the added revenue from the
treatment in year t. AC is the added cost of the treatment in year /, t is years, and / is the
discount rate. The discount rate is the ranch's opportunity cost of the capital. For the
redberry juniper treatment to be feasible, the NPV of the treatment must be greater than
or equal to zero. If the NPV is equal to zero, then the compound rate of retum is equal to
the discount rate used. If NPV is greater than zero, then the compound rate of retum is
greater than the discount rate used.
36
CHAPTER IV
METHODS AND PROCEDURES
The objectives of this study included the following: estimation of the relationship
between forage production and redberry juniper canopy cover: estimation of the
additional forage production after brush control treatments; estimation of additional
revenues attributable to redberry juniper control; and the determination of the net present
value and optimum follow-up treatment intervals for various environmental, economic,
and managerial conditions. Environmental, economic, and managerial baseline
assumptions were made to approximate observed conditions. Economic feasibility of
redberry juniper control was evaluated with regard to the baseline conditions and
variations from these values. This research evaluated the conditions under which an
investment in individual tree treatment as a brush control method was economically
feasible.
The Study Area and Data Collection
The study area for the project was in the Rolling Plains and Edward's Plateau of
Texas covering an area from Paducah, Texas to San Angelo, Texas (see Figure 4.1).
Sites were selected on deep hardland, mixedland, and clay loam range sites where cattle
grazing was either not occurring or grazing was limited due to the restriction that sites be
at least 1.60 km from a permanent water source and no less than 0.80 km from a seasonal
watering source. The data were collected on the following sites:
• Texas Tech Experimental Ranch near Justiceburg, Texas;
37
• Tnangle Ranch Study Site • Pitchfork Ranch Study Site • Texas Tech Ej^erimental Ranch Study Site • Stone Ranch Study Site
Figure 4.1. Map of Texas and Study Site Locations.
38
• Triangle Ranch in Foard and Hardeman Counties near Paducah. Texas:
• Pitchfork Ranch in Dickens County near Girard, Texas;
• Hugh Stone Ranch in Tom Green County near San Angelo. Texas.
Texas Tech Experimental Ranch
The Texas Tech Experimental Ranch study site is predominantly located in Garza
County, Texas: however, the area utilized is located in northeastem Borden County,
Texas upon the Texas High Plains. Soil and range site descriptions were taken from the
Soil Survey of Borden County, Texas (Dixon, 1975). This site is classified as a deep
hardland range site producing short to mid-grasses with expected forage yields when the
range is in excellent condition of 1,500 to 2,700 kg ha"' in favorable years. No livestock
had been grazing in the study area since 1982.
This deep hardland range site is described as nearly level to gently sloping. The
soil is an Olton clay loam with 0 to 1% slopes. The Olton soil is well-drained, and runoff
and intemal drainage are slow. Permeability is moderately slow. The climax forage
species includes blue grama (Bouteloua gracilis), buffalograss (Buchloe dactyloides),
sideoats grama (Bouteloua curtipendula), vine mesquite (Panicum obtusum), westem
wheatgrass (Elytrigia smithii), silver bluestem (Bothriochloa laguroides), tobosagrass
(Hilaria mutica), and Texas wintergrass (Stipa leucotricha). Invaders, including forage
species and non-forage species in pastures that are in less than good condition, include
the following: perennial three-awn (Aristida spp.), pricklypear, redberry juniper, and
mesquite (Dixon, 1975).
39
Triangle Ranch
The Triangle Ranch study site in Foard and Hardeman Counties is also classified
as a deep hardland range site. This study area was in the Dripping Springs Pasture and
although the site had been used for grazing, all livestock were removed 9 weeks before
sampling.
The following description of soil and range site is from the Soil Survey of
Hardeman County, Texas (Loften et al., 1972). Soils on this site are Tillman clay loams
with a 1 to 3% slope. In this study, soil areas were irregular and ranged in size from 6 to
several hundred ha. The original vegetation was made up mostly of blue grama. Other
species that could be present included westem wheatgrass, vinemesquite, sideoats grama,
buffalograss, and silver bluestem. This site produced mid to short grasses and was
capable of producing 3100 kg ha"' of forage in favorable years.
Pitchfork Ranch
The third study location was the Pitchfork Ranch in eastem Dickens County,
Texas on a mixedland range site. Study sites were located in the southwest comer of the
T-41 Pasture. The area had historically and was currently being used for grazing. Forage
production potential was 3300 kg ha"' in favorable years on excellent condition sites.
This site is described as producing predominantly short grasses with some mid-grasses
(Girdner and Richardson, 1970).
In excellent condition, this site would support blue grama, sideoats grama.
Arizona cottontop, westem wheatgrass, and vinemesquite. The major increasers are
buffalograss, hairy grama {Bouteloua hirsuta), silver bluestem, and perermial three-awn.
40
Stone Ranch
Soil and range site descriptions were taken from the Soil Survey, Tom Green
County, Texas (Wiedenfeld and Flores,1976). The soil is an Angelo clay loam with 1 to
3% slopes. The site is a clay loam range site with the dominant forage species including
sideoats grama, buffalograss, cane bluestem (Bothriochloa barbinodis), tobosagrass,
vinemesquite, and perennial three-awn. Expected annual air-dry herbage production
ranged from 1700 to 4900 kg ha"' depending on range condition and precipitation. The
Angelo clay loam has moderately slow permeability and high available-water capacity.
The pasture in which the study site was located had been historically grazed but livestock
were removed early in the growing season prior to measurements being taken. Also, the
area is greater than 1.6 km from the nearest watering point. The study site had few
mesquites and numerous redberry juniper seedlings (< 50 cm tall) under the mature
redberry juniper canopy.
Data Collection
Data collected were in conjunction with a study to determine the relationship
between redberry juniper canopy cover and forage production in West Texas (Racher,
1998). Data collected included tree densities, line-intercept canopy cover before
treatment, canopy area before treatment, treatment cost ha"', and forage production ha" .
Ten random points were selected at each study site. These points were selected within
varying amounts of juniper canopy cover that was estimated visually. The points were
marked by a steel t-post so that in the future these sites can be revisited for additional
study.
41
Canopy Cover
Canopy cover was estimated by the line intercept method (Canfield, 1941). From
each of the 10 steel t-posts, a 30-m line was extended compass north and compass south
for each of the ten random points at each site. Extending two 30-m lines from a single
point in opposite directions allowed for analyzing of 2 transect lengths, 30 m and 60 m.
Canopy intercept was measured to the nearest centimeter by species. Sample sizes were
twenty, 30-m line transects, or ten, 60-m line transects for each of the four study sites.
Belt Transect Canopy Area
Canopy area per unit area were estimated by setting up two belt transects, running
compass north and compass south from each steel post. These belt transects were 10 m
wide with the line intercept cable (described above) being the mid point. A 5-m rope was
moved along each side of the intercept line to delineate the margins of the belt transect.
All non-forage species with their main trunk inside the belt were measured by recording
the species, length of the major and minor axes, and height. Canopy area was calculated
as if the canopy was an ellipse. The formula used to calculate canopy area was as
follows:
canopy area = (1/4) * 71 * x * y, (4.1)
where canopy area is the area of one tree in cm , x is to the major axis in cm. y is to the
minor axis in cm, and n is to the constant 3.14159. The formula used to calculate total
canopy area was as follows:
TA = 2 ] (canopy area) 10,000, (4.2)
42
where TA is the total canopy area for the belt in m and canopy area is defined above.
Canopy cover can then be calculated by the following equation:
CC = (TA / 300 m ) * 100, (4.3)
where CC is percent canopy cover for belt transect and TA is defmed above.
Forage Production
Forage production was estimated during peak standing crop, which was assumed
to be after the spring rains in mid-June through August. Ten 0.25-m^ quadrats were
sampled randomly under the 30-m line intercept cable. All herbaceous vegetation within
each quadrat was clipped to 1-cm stubble height and placed in paper bags for drying. In
addition to these quadrats, an additional 20 quadrats were selectively placed and clipped
at areas no closer than 3 m from the drip line canopy edge of any redberry juniper tree.
The forage in the quadrat was separated into three components: grass, forbs, and litter.
The bags were oven dried for 48 hr at 60° C. The contents of each bag were then
weighed and recorded.
Herbicide Application
At the Stone Ranch and Triangle Ranch study sites, the liquid formulation of
hexazinone (Velpar® L) was used to individually treat the redberry juniper trees in all belt
transects. The herbicide was applied undiluted to the soil beneath junipers with an exact
delivery handgun set to release a volume of 2 ml. Junipers taller than 0.91 m within the
belts were treated at the recommended dosage of 2 ml for each 0.91 m of plant height or
every 0.91 m of plant canopy diameter, whichever was greater (McGinty et al., 1998).
43
The amount of herbicide, the time required to treat each belt transect, and the number of
redberry junipers treated in the belt were recorded. Cost for treatment was broken down
into two categories. These categories were herbicide costs ($19.43 liter"'), and labor
($5.15 hr' ). The cost of labor was increased by an efficiency factor of 25% which
included an adjustment for equipment breakdown, inexperienced applicator, breaks,
lunch, travel time to and from the treatment location, and down time. Cost per ha were
calculated using the following equation:
TC = (HC /1000 * HU + TT* EF * RT) / 0.03 ha, (4.4)
where TC is the total cost of hexazinone treatment $ ha"', HC is the cost of herbicide in $
liter"', HU is the amount of herbicide used in ml, TT the time to treat the redberry
junipers in the belt in hours, EF is the labor efficiency factor constant of 1.25% and RT is
the hourly wage rate in $ hr"'.
Calculations and Conversions
Additional Forage Production
The additional forage production associated with treatment is the difference
between the estimated forage production following treatment and forage production
without treatment on the same land. This difference is expressed as:
AFPt = FPwt - FPt. (4.5)
where AFPt is the additional forage production in kg ha"' in year t, FPwt is the forage
production following treatment in kg ha"' in year t, and FP, is the forage production
without treatment in kg ha"' in year t.
44
Added Livestock Production
The additional forage production can be converted into additional livestock
production (ALP) by multiplying AFP by a constant (K) that represents the kg of
livestock production kg"' of forage produced. K was defmed as 0.0136068 under
baseline conditions, which assumes that an animal unit would require 11.97 kg of dry-
matter forage day" or 4371 kg of forage year"', and an assumed management practice of
25% utilization of standing forage (Ethridge et al., 1985). K is calculated by the
following equation:
K = MAU / [(11.97 kg day"' AU"' * 365) / URate], (4.6)
where K is the forage conversion constant, URate is the forage utilization rate, and MAU
is a marketable animal unit in kg (237.8943 kg). See Appendix A for calculations and
references on MAU. The equation for additional livestock production is expressed as
ALPt = K * AFPt, (4.7)
where ALPt is the additional livestock production in kg ha"' in year t. K is the forage
conversion constant, and AFPt is as defined previously.
Estimation of Additional Revenues from Livestock Production
Increased livestock production revenues from increased forage production
following bmsh control treatment may be calculated as follows:
ARt = [ALPt * (PL - AVC)] + LS, (4.8)
where ARt is the value in $ ha"' of additional revenues produced in year t, PL is the
weighted price of livestock in $ kg"', estimated by weighting average prices of steers,
heifers, and cull cows, AVC is the added variable production cost in $ kg" incurred with
45
producing an additional marketable animal unit, LS is the labor savings per ha realized
from the bmsh control treatment, and ALPt is as defined previously.
The price of livestock was defmed as the weighted price of heifer calves, steer
calves, and cull cows. Each was weighted according to the contribution to a marketable
animal unit. The calculation was as follows:
PL = (WH * %H / MAU * PH) + (WS * %S
/ MAU * PS) + (WC * %C / MAU * PC), (4.9)
where PL is the weighted price of livestock in $ kg"', WH is the weaning weight of a
heifer calf in kg, %H is the percent of a heifer sold animal unit"', WS is the weaning
weight of a steer calf in kg, %S is the percent of a steer sold animal unit"', WC is the
weight in kg of a cull cow, %C is the percent of a cull cow sold animal unit"', PH, PS,
and PC are the prices ($ kg"') of heifer calves, steers calves, and cull cows, and MAU is
as previously defined.
Labor savings were estimated by Ethridge, Weddle, Bowman, and Wright (1991)
to be between 50 and 60% when bmsh control was used as a management tool. Labor
savings for this study were estimated to be $0.62 ha"'. This estimation was calculated
assuming a labor savings of 50% with a labor cost of $13.37 animal unif' (Bevers, 1999)
and a stocking rate of 10.77 ha exposed female" (McGraim, 1995). The labor savings
estimation was calculated by dividing the savings animal unif' of $6,685 ($13.37 * 0.50)
by the number of ha required to support an exposed female (10.77).
Added variable costs incurred with producing an additional kg of marketable
animal unit were estimated by dividing the summation of input costs (see Table 4.1) by
46
Table 4.1. Components of Added Variable Cost.
Item $ AU" Bam 0.04
Fence 2.91
Interest - Eamed -0.63
Interest - OC Borrowed 5.5
Other direct Cost $30.00
Pickup Truck 3/4 Ton $28.55
Salt and mineral $5.40
Shed $0.02
Sprayer $0.07
Supplemental feed $61.25
Trailer $0.48
Vet medicine cow-calf $14.32
Water $0.18
Working Pens $0.04
Total $148.13
Source: Bevers, S.l 1999. Texas Enterprise Budgets, Rolling Plains region; projected for 1999. Texas Agricultural Extension Service. B-1241 (C03).
47
the weight of a marketable animal unit. Added variable cost in $ kg"' of marketable
animal unit was as follows:
AVC = (Z input cost $ [AU]"' ) / MAU , (4.10)
where the AVC is the added variable cost in $ kg"' of marketable animal unit, AU is an
animal unit, and MAU us defmed previously. Equation 4.7 can be re-written as
AVC = 148.13/237.8943 (4.11)
AVC = $0.62. (4.12)
The added cost of producing an additional kilogram of marketable livestock was $0.62.
Estimation of Additional Revenues Using Lease Income
Another means of calculating revenues from rangeland is from a grazing lease.
This method addresses the variability in livestock market prices and the diversity in the
species of animals raised in the Rolling Plains including sheep, goats, and cattle. Not
only does using grazing lease revenues provide flexibility, it also makes the study more
applicable due to the prevalence of rangeland leasing.
The first step is to calculate the stocking rate for the rangeland and convert it
through a series of additional calculations into additional revenues. The stocking rate is
calculated as follows:
RDt = (TPt * URatCt) / DFR^, (4.13)
where RDt is the number of required days needed to support one AU ha"' in days ha"'
AU"', TPt is the total forage production of 1 ha annually in kg ha"'. URate is the forage
utilization rate, and DFRt is the daily forage requirement for one AU in kg day"'. Hence.
SRt = ( 365 days year"' ) / RDt. (4.14)
48
where SR, is the stocking rate in ha AU"' year"' in year t and RDt is defmed as above.
After the stocking rate has been determined, lease revenue can be calculated as
LRt = (LNP) / SR,, (4.15)
where LR, is the lease revenue in $ ha"' year"' in year t, and SRt is defmed as above.
LNP was the average leased native pasture cost animal unit"' year"' which was assumed
as $100 AU"' year"' (Ueckert, 1998). Additional revenues from bmsh control treatment
can then be calculated as
ARt= LRwt-LR,, (4.16)
where ARt is the additional revenue in $ ha"' year"', LRwt is the lease revenues on a
treated site, and LR is the lease revenue on the same site without treatment.
Estimation of Net Present Value
Added costs of the brush control treatments were estimated using the cash
outflows realized from the treatment. Because the individual tree treatment and two-way
chaining do not include range deferment costs, the added cost was equal to the following:
ACt = TCtw-TCt, (4.17)
where ACt is the additional cost in $ ha"' in year t, TCt is the total cost on untreated sites
in $ ha"' in year t, and TCwt is the total cost in $ ha"' with treatment on treated sites in
year t. The total cost is defined only as the cost incurred when using individual tree
treatment as an initial control technique or as a maintenance brush control technique, or
as the cost incurred when using 2-way chaining as the initial control technique and
individual plant treatment as the maintenance redberry juniper control technique. The
present value of the additional revenue realized by the landowner was calculated as the
49
yearly added revenues discounted to t=0. The present value of the additional revenue in
year t is equal to:
PVARt = AR,/( 1+i)', (4.18)
where PVAR, is the present value of the added revenues in $ ha"' in year t, and i is the
discount rate. The present value of the additional cost realized by the producer was
calculated as the yearly added costs discounted to t=0. The present value of added cost in
year t is the following:
PVACt = ACt/( \+i)\ (4.19)
where PVACt is the present value of the added cost in $ ha"' in year t, ACt is added cost
in year t, and i is again the discount rate.
A 30-year planning horizon was used to evaluate the net present value of the
initial treatment and maintenance treatments. A 30-year planning horizon allows for one
or more maintenance control treatments to be performed.
The net present value was estimated by the following equation:
NPV = (PVAR,-PVAC,) , (4.20) t=0
where NPV is the net present value in $ ha"', PVARt is the present value of the added
revenues in $ ha"' in year t, and PVAC, is the present value of the added cost in $ ha"' in
year t. The NPV was used to determine the economic feasibility of using hexazinone
individual tree treatments to control redberry juniper, and the optimal number of years
between maintenance treatments. Also the NPV was used to determine the economic
feasibility of using 2-way chaining as the initial treatment with hexazinone individual
50
plant treatments for the maintenance control, and the optimal number of years between
maintenance treatments.
Baseline Conditions
Baseline conditions for the physical and economic variables were obtained from
prior research and discussions with range ecologist Dr. Darrell Ueckert at the Texas
Agricultural Experiment Station in San Angelo (Ueckert, 1999) and Dr. Carlton Britton at
Texas Tech Univeristy in Lubbock, Texas (Britton, 1999). The baseline condition
variables were categorized into three groups: environmental, economic and managerial.
Tables 4.2 and 4.3 show the baseline values for the environmental, economic, and
managerial variables with individual tree treatment as the initial control method and with
mechanical control as the initial control method, respectively. The baseline initial canopy
cover (CCt=o) was defmed as 20% when individual tree treatment was used as the initial
control technique; however, a 30% CCt=o was used when two-way chaining was used as
the initial treatment followed by maintenance control using individual tree treatment.
The increase from 20 to 30% for initial canopy cover was due to there being two possible
scenarios that a producer may encounter. The first scenario was one in which individual
tree treatment could be used as the initial control method when the trees are still
relatively small, widely spaced, and easily maneuvered through by ground crews. The
second scenario was when the trees are larger and walking through a stand becomes
difficult. Also when using hexazinone, there are label restrictions as to the amount of
chemical that can be applied ha"' yr"' (3,118 ml ha"' yr"' or 1/3 gal acre"' yr"').
51
Table 4.2. Low, Baseline, and High Variable Values Used for Analysis with Individual Tree Treatment as Initial Control Method.
Variables
r' in %
Rr'' in %
CCVo in %
RC' t v=o in %
i' in %
URate^ in %
PL^ in $ kg"'
Density* trees ha"'
Low
0.12
0.5
10
0.5
5
20
1.20
<600
Baseline
0.37
1.0
20
2.5
7.91
25
1.38
>600
High
1.08
1.73
30
6
10
40
1.90
NA
r is the rate of redberry juniper infestation.
'Hr is the rate of redberry juniper re-infestation after treatment.
''CC is the initial canopy cover of redberry juniper.
' RC is the residual redberry canopy cover after treatment.
i is the real discount rate.
^IJRate is the forage utilization rate.
=PL is the weighted price of livestock.
•"Density is the average redberry juniper tree density.
52
Table 4.3. Low, Baseline, and High Variable Values Used for Analysis with Mechanical Control as Initial Control Method.
Variables
r' in %
Rr in %
CC%o in %
RC' t.v=o in %
i' in %
URate^in%
PL^ in $ kg"'
Density trees ha'
Low
0.12
0.5
20
1
5
20
1.20
<600
Baseline
0.37
1.0
30
2.5
7.91
25
1.38
>600
High
1.08
1.73
55
6
10
40
1.90
NA
r is the rate of redberry juniper infestation.
•TRJ is the rate of redberry juniper re-infestation after treatment.
' CC is the initial canopy cover of redberry juniper.
' RC is the residual redberry canopy cover after treatment.
i is the real discount rate.
URate is the forage utilization rate.
^PL is the weighted price of livestock.
•"Density is the average redberry juniper tree density.
53
The infestation rate (r) and re-infestation (Rr) were assumed to have baseline
values of 0.37 and 1.0% yr"', respectively, with r and Rr being defined as the increase in
redberry juniper canopy cover yr"' in percentage units. These estimates were again based
on prior research and personal communications (Phillips, 1999; Ueckert, 1998). Residual
reberry juniper canopy cover (RCwt=o) was assumed to be 2.5%. Residual canopy cover
after treatment was not assumed to be 0% because prior research by Scifres (1972)
Schuster (1976), indicated < 100% canopy reduction after herbicide control techniques
were applied to redberry juniper.
The real discount rate (i) of 7.91% was calculated by using by the following
formula:
i = } ^ - l , (4.21)
1 + v
where x] was the average intermediate-term fixed-loan rate reported on a quarterly basis
(from the first quarter in 1994 to the fu-st quarter in 1999) and estimated at 10.347%
(Federal Reserve Bank of Dallas, 1999), and v is the estimated expected inflation rate of
2.25% yr' estimated by taking the average of the percentage increase in the consumer
price index from 1994 to 1999 (U.S. Dept. of Labor, 1999).
A forage utilization rate (URate) of 25% was assumed for baseline conditions per
the recommendation of Range Specialists with the Texas Agricultural Extension Service.
White and McGinty (1992) proposed that "the principle governing stocking rate decisions
is to 'take half and leave half" (p. 5). They stated that half of the total forage produced
should remain ungrazed. Of the remaining 50% of useable forage, only half can be used
54
to feed livestock because the other half will be lost to insects, weathering, trampling,
other animals, and decomposition.
The baseline price of livestock (PL) of $1.38 kg"' was calculated using equation
4.9,
P L = ( W H * % H / M A U * P H baseline)
+ ( W S * % S / M A U * P S baseline)
+ ( W C * % C / M A U * P C baseline), ( 4 . 2 2 )
where PL is the weighted price of livestock in $ kg"', WH is the weaning weight of a
heifer calf in kg, %H is the percent of a heifer sold animal unit"', WS is the weaning
weight of a steer calf in kg, %)S is the percent of the steer sold animal unit"', WC is the
weight in kg of a cull cow, %C is the percent of a cull cow sold animal unit"'. Equation
4.19 can then be rewritten as follows:
P L baseline = ( 2 4 4 . 7 6 k g * 2 7 . 1 3 5 % / M A U * P H baseline)
+ ( 2 6 2 . 4 9 k g * 4 1 . 1 3 5 % / M A U * P S baseline)
+ (453.6kg * 14.00% / MAU * PC baseline), (4.23)
where PH baseline was $1.48/kg, PS baseline was $1.66, and PC baseline was $0.92 kg"' (Davis,
1998). MAU was 237.8943 kg of marketable livestock and is defmed and calculated in
Appendix A.
Tree density and tree height are important factors in determining the cost of
individual tree treatment. It was determined that the two sites selected for treatments
were different in height of trees and number of trees ha"' (Table 4.4). The Stone Ranch
location had a significantly lower cost of treatment ha"' than the Triangle Ranch location
because of a lower tree density and smaller tree size; therefore, the Stone Ranch location
3D
Table 4.4. Average Height and Average Number of Trees ha" at Each Location.
Site Average height Trees > 0.914 m in height
Stone Ranch 2.04 m 471 ha"'
Triangle Ranch 2.20 m 1168 ha"'
56
(Density-low) was more representative of a re-treatment scenario with fewer residual
trees ha"'. The Triangle Ranch location (Densitybaseiine) was more representative of sites
being treated initially with individual tree treatment because of the higher tree density.
Two cost equations were developed to represent each of the scenarios. Economic
feasibility was determined by using the predicted initial treatment cost with the Triangle
Ranch location cost equation (Densitybaseiine) and re-treatment cost was estimated by
using a Stone Ranch location cost equation (Density-low). Sensitivity analysis was done
by estimating initial treatment cost with the Density-low equation.
Estimation of the Terminal Land Value
To obtain a thorough understanding of the economic feasibility of individual tree
treatment for redberry juniper control, the effect of bmsh treatment on rangeland values
should be taken into consideration. The terminal land value as used in this study is the
value of the land at the end of the 30-year planning horizon. The terminal land value was
based on the level of forage production, which was converted to a stocking rate then to
leasing revenue. The lease revenue equation is as follows:
LR, = LNP / SRt, (4.24)
where LRt is the lease revenue in $ ha"' in year t which represents the retum to land, SRt
is the stocking rate in ha AU"' yr"' in year t, and LNP is defined above (Equation 4.15).
The value of the land was estimated using the income capitalization method (Appraisal of
Rural Properties, 1993). The income capitalization formula is:
value = income / capitalization rate, (4.25)
57
where income was the lease revenue (LRt), and the capitalization rate was 3% (Gilliland,
1995). Expected rates of retum for rangeland, or the capitalization rates, have been
historically low compared to other types of agricultural lands and other non-farm real
estate. Possible reasons for these low capitalization rates include: the under valuing of
the resource; the use of rangeland for activities other than livestock production: and not
including revenues from hunting activities on the ranch. Using the income capitalization
method, a land value was calculated:
LVt = LRt / CAPR, (4.26)
where LVt is the land value in $ ha"' in time t, CAPR is the capitalization rate, and LRt is
as defined above. Additional land value from bmsh treatment is the difference between
the land value where bmsh control was performed and the land value without treatment.
Additional land value from using individual tree treatment can then be estimated as:
ALVt = LV^ - LVt, (4.27)
where ALVt is the additional land value from bmsh control in $ ha"' in time t, LV^t is the
land value of rangeland that has been treated in $ ha"', and LVt is the land value of
rangeland that has not been treated in $ ha"'. The present value of additional land value
in year t is equal to:
PVALVt = ALVt / (1+i)', (4.28)
where PVALVt is the present value of the additional land value in $ ha"', ALVt is defined
above, and i is the discount rate.
58
CHAPTER V
RESULTS
The results of this thesis are presented in six sections. The first section presents
the relationship between total forage production and redberry juniper canopy cover as
canopy cover increases over time. The second section describes the relationship between
the cost of treating rangeland infested with redberry juniper with hexazinone and canopy
cover. Section three presents the net present values of treatment of redberry juniper and
the optimum maintenance control intervals using individual tree treatment as the initial
and maintenance treatment methods. The fourth section presents the net present values of
treatment of redberry juniper and the optimum maintenance control intervals with a
mechanical control used as the initial control method and individual tree treatment as the
maintenance control method. The last section presents the net present values of treatment
of redberry juniper when land values are taken into consideration.
Forage as a Function of Canopy Cover
Canopy cover at each of the range sites was primarily comprised of redberry
juniper, mesquite, and prickly pear cactus. Average composition of the canopy cover
over all range sites was as follows: 25.2% redberry juniper, 0.6% mesquite, 0.2% prickly
pear, and 0.7% yucca. A forage production relationship was estimated as a function of
redberry juniper canopy cover.
Models were estimated using ordinary least squares (OLS) with the dependent
variable being total forage production and the independent variables being canopy cover
59
of the various bmsh species. Trial models were estimated using various functional forms
with independent variables being squared, cubed, or subject to log transformations. The
following functional form was selected to estimate the canopy cover-forage production
relationship:
InTP = BO + BI * TJCC + B2 * TTU + B3
*TA + B4*PF, (5.1)
where InTP is the natural logarithm of total forage production in kg ha"', TJCC is
redberry juniper canopy cover from 60-m line transects, BO is the intercept, and BI, B2,
B3, and B4 are the estimated coefficients for the respective independent variables.
Variables TTU, TA, and PF are weighted location dummy variables, where PF is the
Pitchfork Ranch location, TTU is the Justiceburg location, and TA is the Triangle Ranch
Location. The fourth range site location (the base) was the Stone Ranch. Note that
mesquite, prickly pear, and yucca are not in the flmctional form because their canopy
covers were not statistically significant.
The model was selected based on goodness of fit using the adjusted R value, F
value, prior research, prior conceptual expectations, and flmctional form analysis
procedures. The functional form analysis procedure described by Brown and Ethridge
(1995) was used to test model stmcture. The variables and the variables squared were
regressed against the residuals of the model. The regression statistics for the variables
and variables squared were zero and not significant, thus indicating that the functional
form was correct. Equation 5.1 can be rewritten with the estimated coefficients and
location values as:
60
InTP = 7.506950576 - 0.019075873 * TJCC f0.076948^ rO.OO 19948)
+ 0.191037334 * TTU- 0.064058134 * TA <0.074772) (0.0736875)
+ 0.402739539 * PF, (5.2) (0.074742)
where hiTP, TJCC, TTU, TA, and PF are as previously defined. Adjusted R is 0.79879
and the F value (4,39) is 43.6778. Numbers in parentheses are standard errors of the
coefficients and intercept.
Equation 5.1 can be rewritten to estimate the total forage production versus
canopy cover relationship in the Rolling Plains region by weighting each of the location
variables by their proportion of the data, which was one fourth, thus resulting in the
following equation:
lnTP = BO' + Bl *TJCC, (5.3)
where hiTP is the natural log of total forage production in kg ha"' at the average location
and TJCC as previously defined. BO' is the sum of the intercept and location coefficients
times the weighting factors. Therefore,
BO' = 7.506950576 + 0.191037334 * 0.25 - 0.064058134
* 0.25 + 0.402739539 * 0.25. (5.4)
Equation 5.4 can be flirther reduced to the following:
y p _ (763938-0.019075873*TJCC) (S S')
where TP is the total forage production in kg ha"', e is a constant (2.71828182845904),
and TJCC is as defmed above. The relationship, as shown in Figure 5.1, shows that
forage production decreases at a decreasing rate as redberry juniper canopy
61
3000 1
2500
_ 2000 ( a
e
3 1500 •a o k_ Q.
• 5 o "• 1000
500
0
C
) N.
o o
A
A A
A X A
X >y^
O ^ » ^ X X
o ^ o ^ ^ X o o
o
o
o
0
0
^—Estimated Relationship
X Texas Tech Ranch Location
A Pitchfork Ranch Location
o Triangle Ranch Location
o Stone Ranch Location
- p p _ (7.63938-0,019075873*TJCC)
/?'=0.79879
o * " ^ ^ , ^
o ^ ^ ' ' ^ ^ ^ - — ^
1 1 1 1 i 1
10 20 30 40 50 60
Juniper Canopy Cover (%)
70 80 90 100
Figure 5.1. Estimated Relationship between Canopy Cover and Forage Production in the Rolling Plains and Edwards Plateau Region.
62
cover increases. The estimated level of forage production at a 0% canopy cover is 2,078
kg ha"'. Forage production decreases to 687 kg ha"' at 58% canopy cover.
Relationship Between Individual Tree Treatment Costs and Canopy Cover
Individual tree treatment cost data were collected on two sites, the Stone Ranch
and the Triangle Ranch. These sites gave an indication of the relative cost for individual
tree treatment in older stands of redberry juniper. Plots treated were comprised of mature
trees over 1.8 m tall with smaller seedlings under many of the trees. The average total
redberry juniper canopy cover for both sites was 39.71% with an average treatment cost
of$66.73 ha'(Table 5.1).
A cost equation was estimated using OLS to predict the cost of individual tree
treatment as a fiinction of redberry juniper canopy cover. The following flmctional form
best explained the variation in cost ha"' of individual tree treatment:
hiCPH = BO + BI * InJCC + B2 * InTR, (5.6)
where hiCPH is the natural logarithm of treatment cost in $ ha"', hiJCC is the natural
logarithm of redberry juniper canopy cover from 30-m belt transect data, and InTR is the
natural logarithm of the percent redberry juniper canopy cover at the Triangle Ranch
location variable. BO is the intercept and BI and B2 are the estimated coefficients for the
respective independent variables. Equation 5.6 can be rewritten with its estimated
coefficients as:
InCPH = 2.1163 + 0.473858793 * hiJCC
(0.26028) (0.074627)
+ 0.168641078* InTR, (5.7) (0,035219)
63
Table 5.1. Mean, Range, and Standard Deviation for Individual Tree Treatment Data.
Description
Treatment Cost $ ha"'
Herbicide liter ha"'
Density trees ha"'
Man hours hrs ha"'
Mean
66.73
2.88 1
748
2.11
Range
5.19 to 167.64
0.266 to 7.66
66 to 2166
0.002 to 5.326
Std.
39.24
1.79
538
1.06
64
where hiCPH, InJCC, and InTR as defmed previously and the numbers in parentheses are
the standard error of the coefficients. Adjusted R is 0.6625 and F value (2,36) of 38.312.
The equation can then be re-written as follows:
CPH=8.30*JCC'' ' ' ' ' ' ' ' *TR o'^'o^«, (5.8)
where CPH, JCC, and TR are as previously defined.
Individual Tree Treatment as the Initial and Maintenance Control Methods
Net present value (NPV) was calculated for the redberry juniper control method
of individual tree treatment using hexazinone as the initial and maintenance treatments.
Two methods were used to estimate the revenues from increased forage production
resulting from redberry juniper control treatments. The first method used additional
livestock production and the second method used the land lease price to calculate the
additional revenues. Net present values were calculated over the 30-year planning
horizon with re-treatment of the range evaluated at various periods to determine the
optimal interval for maintenance control (OIMC).
For all scenarios, the NPV increased as the maintenance interval increased and
reached a peak at an OIMC. Less frequent sprayings than the OIMC produced less
additional revenues and lower additional costs, where more frequent sprayings than the
OIMC produced both additional revenues and additional costs resulting in a lower NPV.
For all scenarios the additional livestock method of estimating revenues had a shorter
OIMC than under the same conditions for the land lease method.
65
Baseline Conditions for the Additional Livestock Method
As shown in Table 5.2, the NPV of brush treatment using the additional livestock
method under baseUne conditions was a -$5.47 ha"' with an OIMC of 16 years. The
negative NPV indicated that it was not economically feasible to treat redberry juniper
using individual tree treatment under the additional livestock method. Under baseline
conditions and re-treating at the OIMC of 16 years, the canopy cover reached 17.5%
before re-treatment. The Intemal Rate of Retum (IRR), which is the rate of retum that an
investment earns, was not reported because the estimate was not reliable and resulted in
multiple rates of retum. These multiple rates of retum were estimated due to multiple
cash flow sign changes, and by Descartes' mle, with every sign change, there may be a
new positive, real root estimated (Copeland and Weston, 1988).
The present value payback period (PVPP) was estimated, which is the number of
years necessary for the present value of benefits to become positive. Under baseline
conditions, using the cumulative total net present value (CTNPV) does not become
positive during the 30-year planning horizon (see Table 5.3).
Variations from Baseline Conditions for the Additional Livestock Method
Table 5.2 shows the results as the various physical and economic factors were
varied from baseline conditions. For example, when the real discount rate is reduced
from 7.9% to 5.0% while all other factors are held at baseline values, the NPV increases
from -$5.47 ha"' to $10.95 ha"'. Of the 15 scenarios evaluated, the five factors that
caused significant deviation from the baseline NPV were the initial infestation rate (r).
66
Table 5.2. Net Present Value and Optimum Treatment Intervals for Baseline and All Variations using Livestock Method. Individual Tree Treatment wdth Hexazinone for Initial and Maintenance Treatments.
Conditions
Baseline
r in % high
r in % low
Rr in % high
Rr in % low
CCt in % high
CCt in % low
RCtw in % high
RCtw in % low
i in % high
i in % low
URate high
URate low
PL high
PL low
Density low
NPV"
$ha"'
-5.47
13.14
-13.00
-21.55
7.92
4.47
-17.54
-19.81
3.46
-13.19
10.95
30.08
-16.20
35.64
-18.22
17.09
PVLV"
$ha"'
7.73
15.18
4.3
8.25
11.70
11.61
3.04
5.79
12.69
4.35
17.56
20.30
6.19
12.69
7.76
7.73
OIMC
Years
16
16
16
11
16
16
16
16
11
16
16
8
16
8
16
16
CCwt
%
17.5
17.5
17.5
19.8
10.0
17.5
17.5
21
10.5
17.5
17.5
9.5
17.5
9.5
17.5
17.5
^NPV is the net present value of the treatment.
'T'VLV is the present value of the difference in terminal land values at the end of the 30 year planning horizon.
' OIMC is the optimal interval of maintenance control.
' CCwt is the redberry juniper canopy cover at retreatment in time t.
67
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re-infestation rate (Rr), discount rate (i), forage utilization rate (URate), and price of
livestock (PL).
When the infestation rate was low (r-low=0.12% year"'), NPV became a -$13.00
ha' . This change from the baseline value exists because the canopy cover when left
untreated was only increasing at a rate of 0.37% year"', whereas the re-infestation (Rr)
after treatment at baseline was increasing at 1.0% rate year"'. This difference among
infestation rates (r and Rr) reduced the net revenues over the 30-year period. The
opposite holds tme for the high infestation rate (r-high=1.08% year"') because the
untreated site's canopy cover was increasing faster than the canopy cover after treatment
with a Rr-baseline of 1.0% year"' giving a NPV of $13.14. Because r-high was greater
than Rr-baseline, the net revenues increased because total forage production on the
untreated site was going dovm faster than total production on the treated site, thereby
increasing the additional forage produced.
The initial canopy cover before treatment affected NPV in much the same way as
the infestation rate. When initial canopy cover was high (CCt-high=30%), the net
revenues after treatment increased substantially more than under baseline conditions.
This increase in net revenues increased the NPV to $4.47 ha"'. However, when initial
canopy cover was low, (CCt-low=10%) there was no benefit to the producer to treat
(NPV=-$ 17.54) because the reduction in canopy cover after treatment did not have as
great an impact on net revenues because total forage production had not been increased
substantially.
69
Baseline Conditions for the Land Lease Price Method
Unlike the additional livestock method discussed above, the lease land method
failed to produce positive NPV estunates. At baseline conditions the NPV was -$36.32
ha"' with an OIMC of 18 years (Table 5.4). With NPV being negative at baseline
condition, the CTNPV never reached zero, with the highest CTNPV(-$34.97, data not
shown) in year 18. Even though it was not economically feasible to use individual tree
treatment wdth the land lease method, the OIMC of 18 years did indicate that the
optimum canopy cover for apphcation of follow-up herbicide treatment was 19.5%.
Variations from Baseline Conditions for the Land Lease Price Method
Like the additional livestock method discussed above, variations from the
baseline conditions were evaluated using the land lease method of estimating revenues.
As shown on Table 5.4, the NPV ranged from a low of-$46.99 ha"' to a high of-$13.76
ha"'. The land lease method of calculating revenues failed to make individual tree
treatment an attractive investment for all variations from baseline conditions.
Individual Tree Treatment with Initial Mechanical Control
Within the scope of this study, two initial treatment scenarios were evaluated for
economic feasibility. The fu-st was individual tree treatment with hexazinone as the
initial treatment method, and the second was two-way chaining used on rangelands that
had initial canopy cover too high to effectively use individual tree treatment as the initial
control technique. For the second scenario, which included the use of two-way chaining
as the initial control technique, the baseline initial canopy cover (CCt) was increased
70
Table 5.4. Net Present Value and Optimum Treatment Cycles for Baseline and All Variations using Lease Land Method. Individual Tree Treatment with Hexazinone for Initial and Maintenance Treatments.
Conditions
Baseline
r in % high
r in % low
Rr in % high
Rr in % low
CCt in % high
CCt in % low
RCtw in % high
RCtw in % low
i in % high
i in % low
URate high
URate low
Density low
NPV"
$ha"'
-36.32
-25.99
-40.50
-46.99
-27.49
-38.34
-33.92
-44.33
-31.33
-35.60
-25.79
-18.51
-41.99
-13.76
PVLV"
$ha"'
8.90
16.35
5.47
2.76
14.05
12.78
4.21
8.60
8.90
6.58
19.54
12.37
8.59
8.90
OIMC"
Years
18
18
18
16
23
18
18
21
16
21
16
16
21
18
CCwt
%
19.5
19.5
19.5
28.5 .
13.5
19.5
19.5
26
15.5
22.5
17.5
17.5
22.5
19.5
*NPV is the net present value of the treatment.
^VLV is the present value of the difference in terminal land values at the end of the 30 year planning horizon.
" OIMC is the optimal interval of maintenance control.
' CCwt is the redberry juniper canopy cover at retreatment in time t.
71
from 20%) to 30%). This mcrease reflected the situation of canopy cover reaching a point
where individual tree treatment could not be used effectively either due to economic or to
physical constraints. For this scenario, NPV was estimated using two-way chaining as
the initial treatment with maintenance bmsh control using individual tree treatment with
hexazinone.
The additional livestock produced and land lease price methods of calculating
revenues were evaluated. As shown in Tables 5.5 and 5.6, for all conditions the NPV
reached a peak at an optimal interval for maintenance control (OIMC). Less frequent
sprayings than the OIMC produced less additional revenues and lower additional costs,
whereas more frequent sprayings than the OIMC produced both more additional revenues
and additional costs resulting in a lower NPV. In all cases evaluated, the additional
livestock method of calculating revenues gave a shorter OIMC than under the same
conditions using the lease land method.
Baseline Conditions for the Additional Livestock Method
The additional livestock method produced a positive NPV for all conditions as
shown in Table 5.5. Under baseline conditions the OIMC was 16 years with an NPV of
$40.70 ha"'. The PVPP occurred in year 6 with a CTNPV of $L23 ha"' (Table 5.7). This
shorter PVPP was due to the increased initial canopy cover, which for this scenario was
increased from 20% to 30%. The greater initial canopy cover for this scenario allowed
the additional livestock production in time t (ALPt) to increase after treatment more than
ALPt when initial canopy cover was assumed to be 20%. The optimum canopy cover for
retreatment was 17.5%.
72
Table 5.5. Net Present Value and Optimum Treatment Cycles for Baseline and All Variations using Livestock Method with Initial Mechanical Control.
Conditions
Baseline
r in % high
r in % low
Rr in % high
Rr in % low
CCt in % high
CCt in % low
RCtw in % high
RCtw in % low
i in % high
i in % low
URate high
URate low
PL high
PL low
NPV"
$ha"'
40.70
55.81
34.48
24.62
54.09
89.19
13.84
26.36
47.16
28.58
66.20
91.94
24.47
100.26
21.57
PVLV'
$ha"'
11.61
18.34
8.77
12.12
15.57
18.60
7.73
9.67
12.48
6.53
26.36
24.40
9.75
16.56
11.61
OIMC
Years
16
17
16
11
16
16
16
16
16
16
16
11
17
8
16
CCwt
%
17.5
18.5
17.5
19.8
10.0
17.5
17.5
21.0
16.0
17.5
17.5
12.5
18.5
9.5
17.5
"NPV is the net present value of the treatment.
'I^VLV is the present value of the difference in terminal land values at the end of the 30 year plarming horizon.
"OIMC is the optimal interval of maintenance control.
" CCwt is the redberry juniper canopy cover at retreatment in time t.
73
Table 5.6. Net Present Value and Optimum Treatment Cycles for Baseline and All Variations using Lease Land Method with Initial Mechanical Control.
Conditions
Baseline
r in % high
r in % low
Rr in % high
Rr in % low
CCt in % high
CCt in % low
RCtw in % high
RCtw in % low
i in % high
i in % low
URate high
URate low
NPV"
$ha"'
-2.11
6.43
-5.56
-12.78
6.73
24.81
-17.02
-10.12
1.60
-6.73
8.34
24.65
-10.76
PVLV'
$ha"'
12.78
18.93
9.94
6.63
17.92
19.77
8.90
12.48
12.48
8.58
26.37
18.57
11.69
OIMC"
Years
18
18
18
16
23
18
18
21
16
22
16
16
21
CCwt
%
19.5
19.5
19.5
28.5
13.5
19.5
19.5
26.0
16.0
23.5
17.5
17.5
22.5
"NPV is the net present value of the treatment.
'T'VLV is the present value of the difference in terminal land values at the end of the 30 year planning horizon.
''OIMC is the optimal interval of maintenance control.
' CCwt is the redberry juniper canopy cover at retreatment in time t.
74
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75
Variations from Baseline Conditions for the Additional Livestock Method
Although two-way chaining was the initial treatment in this scenario, the
additional livestock method of estimating net revenues produced positive NPV for all 14
variations from baseline (see Table 5.5). The additional livestock method had four
variations, the discount rate (i), the initial canopy cover (CCt), the utilization rate
(URate), and the price of livestock (PL) that had a noticeably different NPV than the
baseline. Like the scenario without mechanical control, the most dramatic shift in NPV
was due to a high livestock price (PL-high=$l .90 kg"'). Also, a high initial canopy cover
(CCt-high=55%) shifted the NPV to $89.19 ha"'. As the initial canopy cover increased,
the difference between the forage production on an untreated site and a treated site
became larger. Hence, even though the cost of initial treatment was higher because of the
chaining cost, the net revenues more than made up the difference.
Baseline Conditions for the Land Lease Price Method
The effects of two-way chaining and increased initial canopy cover had an effect
on the baseline's NPV using the land lease method of calculating revenues. The NPV was
negative with an estimated value of-$2.11 ha"' (see Table 5.6). The method of two-way
chaining followed by individual tree treatment wdth an OIMC of 18 years using land lease
revenues was not economically feasible under baseline conditions.
Variations from Baseline Conditions for the Land Lease Price Method
There were 12 conditions evaluated for economical feasibility. The PL-low and
PL-high were dropped because they were not applicable in the land lease method. Unlike
76
the land lease method without an initial mechanical control, there was a noticeable
improvement under six of the conditions in this scenario. The six variations included low
re-infestation rate (Rr-low=0.5%), high initial canopy cover (CCt-high=55%), high
infestation rate (r-high=1.08% year"'), low discount rate (i-low=5.0%), and a high forage
utilization rate (URate-high=40%). Each were estimated with positive NPV ranging from
$6.43 ha"' to $24.81 ha' (see Table 5.6).
Total Net Present Value and Land Values
In order to obtain a thorough evaluation of the economic feasibility of individual
tree treatment of redberry juniper, the value of the rangeland should be taken into
consideration. When the producer allows redberry juniper infestations to increase, forage
production declines and the value of the land reflects the resulting decrease in forage
production for livestock and wildlife. If the landowner controls the juniper, forage
production increases, thereby increasing livestock and wildlife production. This added
livestock and wildUfe production potential should give juniper-free rangeland a higher
value than rangeland that is infested with redberry juniper.
In this study, land values at the end of the 30-year planning period were estimated
using the income capitalization method. The present value of the difference in terminal
land values for treated and untreated rangelands (PVLV) are shown in Tables 5.2, 5.4,
5.5, and 5.6. In all cases, terminal land values were greater with redberry juniper
treatments than land values from rangeland that had not been treated. Under baseline
conditions using the livestock method of calculating additional revenues and using
hexazinone as the initial control treatment, the present value of the difference in terminal
77
land values (PVLV) was $7.73 ha' (Table 5.2). PVLV is the difference between the
present value of land that has been treated and land that has not been treated. For
example, the estimated terminal value of land that has been treated under baseline
conditions using the additional livestock method with individual treatment as the initial
control method to calculate additional revenues was $294.84 ha"' which has a present
value of $30.04 ha"'. The estimated terminal value of land that has not been treated was
$218.95 ha"' which has a present value of $22.31 ha"'. The resulting PVLV was $7.73
ha' . PVLV land under baseline conditions with an initial two-way chaining treatment
was estimated at $11.61 ha" (Table 5.5).
When taking into consideration terminal values of the land, the use of individual
tree treatment with or without an initial mechanical control in most cases was
economically feasible using the lease land method (see Tables 5.4 and 5.6). For example,
under baseline conditions without an initial mechanical control, the NPV for the
additional livestock method was -$5.47 ha"'; however, if the difference in land values was
considered, the NPV became a positive $2.26 ha"' (Table 5.8). Another example was the
baseline conditions with two-way chaining being used as the initial control technique
using the lease land method to calculate the additional revenues. Without the land value
factored into the NPV, the NPV for this scenario was estimated to be a -$2.11 ha"', but if
terminal land value was taken into consideration, the NPV became $10.76 ha"' (Table
5.8). When using the lease land method with an initial mechanical control and herbicide
treatment as the maintenance control treatment, taking into consideration the terminal
value to calculate the NPV, all but 2 of the 13 variations tested became economically
feasible (Table 5.6).
78
Table 5.8. Land Values and Optimum Treatment Cycles for Baseline.
Method OIMC" ALVt" NPV," PVLVt NPVt+PVLVt
Years
16
18
16
18
$ha"'
75.89
87.35
113.92
125.38
$ha-'
-5.47
-36.32
40.70
-2.11
$ha-'
7.73
8.90
11.61
12.78
$ha"'
2.26
-27.42
52.31
10.76
Additional Livestock
Land Lease
Additional Livestock with Chaining
Land Lease with Chaining
"OIMC is the optimal maintenance interval control.
^ALV is the additional land value.
TSTPV is the net present value of the treatment.
' PVLV is the present value of the difference in terminal land values at the end of the 30-year plaiming horizon.
79
CHAPTER VI
SUMMARY AND CONCLUSIONS
This study estimated the economic feasibility of individual tree treatment with
hexazinone for redberry juniper control in the Rolling Plains and Edwards Plateau
regions of Texas. Texas rangelands are a vital part of the Texas economy; however,
increasing infestation levels of redberry juniper pose real threats to the economic
potential of rangeland in these regions. The loss in income from decreased carrying
capacity of the rangeland due to the reduction of grazable forage not only affects the
economic and financial situation of ranchers, but also the suppliers of ranch inputs.
Although some research has been done on techniques and approaches of
controlling redberry juniper, limited research has been conducted to evaluate the
economic feasibility of the various control practices. This study evaluated the economic
feasibility of individual tree herbicide application as a method of redberry juniper control
and as a maintenance treatment following a mechanical control method, two-way
chaining.
Investment in redberry juniper control using the additional livestock production
method to calculate additional revenues proved to be economically feasible under most
conditions evaluated. However, investment in redberry juniper control was economically
feasible only under certain conditions when using a combination of two-way chaining
and herbicide maintenance treatment and the land lease method. The use of mechanical
control as the initial brush control method in redberry juniper infestations that are too
dense for individual tree treatment was found to be economically feasible under all
80
conditions when the livestock method was used. It was found that the inclusion of the
impacts on terminal land values from the application of redberry juniper control increased
the economic feasibility under most situations analyzed.
The economic feasibility of controlling redberry juniper with individual tree
treatment using a herbicide depends on environmental, economic, and managerial
variables. The economic variables considered were the real discount rate and the price of
livestock. Both had a substantial impact on the feasibility of the investment decision.
Among the envirormiental variables which affected the economic feasibility associated
with redberry juniper control are initial canopy cover, rate of infestation, rate of re
infestation after treatment, the residual canopy cover after treatment, and tree density. Of
these variables, a high rate of infestation, a high rate of re-infestation and initial canopy
cover showed the greatest influence on the economic feasibility of redberry juniper
control.
The managerial variable that producers or landowners can directly control is the
forage utilization rate. Under both methods of estimating additional revenues, the forage
utilization rate had a substantial impact on the NPV or the decision to invest in redberry
juniper control. Under three of the four situations considered when forage utilization was
40%, the redberry juniper control practice was an acceptable investment; however, a low
forage utilization rate of 20% resulted in negative NPV in three out of the four situations.
In this thesis, landowners were categorized into two groups when considering the
use of individual tree treatment as a method of controlling redberry juniper. For the
landowner who raises livestock, redberry juniper control using individual tree treatment
was economically feasible under most conditions considered. In contrast, for the
81
landowner who leases the land to others for grazing, redberry juniper control was not
economically feasible except when two-way chaining was the initial control treatment
and even then under very limited conditions. These conditions include a high initial
canopy cover, a low discount rate, a high infestation rate, a low residual canopy cover, a
low re-infestation rate, and a high forage utilization rate greater than the recommended
25%. This is important because as more rangeland resources are being leased with
landovmers dependent on lease income rather than livestock production, it is less likely
that there will be an increase in the amount of redberry juniper control.
When evaluating the economic feasibility of redberry juniper control, the effect
on the fliture value of the land should be taken into consideration. The benefit of brush
control is two-fold. The first benefit is the increase in livestock production or lease
income. The second benefit is improvement to the land that will be reflected in its fliture
value. In this study, terminal land values were estimated using the income capitalization
approach which relates the value of land to its income-producing potential for grazing
livestock. If the difference in land values for rangelands where redberry juniper
infestations have been controlled and rangelands where redberry juniper has been
allowed to continue to increase are considered, the economic feasibility of redberry
juniper control is enhanced. The present value of the difference in land values increased
the attractiveness of the brush control investment. This was particularly important for the
situation where revenues from redberry juniper control were calculated using the land
lease method. The investment in redberry juniper control by landowners who rely on
lease income was not economically feasible under most conditions evaluated, except
when the future value of the land was considered.
82
Conclusions
The conclusions of this study only apply to the Rolling Plains and Edward's
Plateau regions of Texas. The results show that under certain environmental, economic,
and managerial factors individual tree treatment with herbicide is economically feasible.
Individual plant treatment is most attractive when used in combination with two-way
chaining and least attractive when used as the initial and maintenance control technique
when revenues are generated with lease income. Only under limited and very specific
situations does individual tree treatment become economically feasible when the
landowner is dependent on lease income. One of these situations is when forage
utilization is increased above the recommended 25%. This has implications regarding
possible overgrazing following redberry juniper control to justify the investment. A
higher than reconmiended utilization rate of the range resource has other impacts on the
land that may nullify any short-term increase in production due to decreased competition
from redberry juniper. Some of these impacts include increased soil erosion, decrease in
nutrient rich climax grass species, increase in other non-controlled brush species such as
prickly pear or mesquite, and an increase in less desirable grass and forb species and
reduced competition between forage plants and juniper seedlings.
Controlling redberry juniper has a positive impact on rangeland values.
Landowners who consider the fiiture value of their rangelands may be more inclined to
imdertake brush control practices. The consideration of land values is of particular
importance for those landowners who rely on lease income because the terminal land
values contribute significantly to the economic feasibility of redberry juniper control.
83
Governmental policies to assist landowners in controlling brush could improve
the attractiveness of chemical individual tree treatment to the landowners who rely on
lease income as well as those who produce livestock and wildhfe. In 1999, the Texas
Legislature established a cost share program for brush control in the North Concho River
Watershed (Dandy Kothmaim, 2000). The program is administered through the Tom
Green County Soil and Water Conservation District. The program requires landowners
to develop a conservation plan and agree to a 10-year brush control maintenance
agreement to quahfy for a cost share program which pays 70% of the actual cost of brush
control up to a maximum dollar amount. For normal juniper infested areas (9 to 19%
canopy cover), the maximum dollar amount that would be paid by the state for chemical
individual tree treatment would be $69.19 ha"'. On heavily infested areas (20% canopy
cover and greater), the maximum dollar amount that would be paid by the state for
chemical individual tree treatment would be $103.78 ha"'. If the landowner preferred the
combination technique of two-way chaining followed by maintenance individual tree
treatment, the state would cost share up to $24.21 ha"' for the initial two-way chaining.
This cost share program would improve the attractiveness of all the situations evaluated
in this study because the initial cash outlay required by the landovmer would be reduced
by up to 70% depending on the control cost. This reduction in initial cost would not only
increase the returns but would possibly shorten the interval between follow-up
treatments.
In this study the optimal interval maintenance cycle (OIMC) ranged from as short
as 8 years to as long as 23 years. The OIMC was based solely on the economics of
redberry juniper control. In all cases evaluated, the optimum canopy cover to retreat was
84
between 9 and 29%. Other factors that may be considered when individual tree treatment
with hexazinone is used to control redberry juniper include both biological and physical
factors, such as not allowing young trees to mature and become reproductive, optimum
wildlife habitat m the form of thermal cover and food, water erosion from loss of grass
cover due to increased competition with mature redberry juniper trees, ease of
retreatment, and availability of labor for treatment applications. An additional factor that
could play a role in the decision to retreat at shorter time intervals is the aesthetic value of
the land.
Limitations and Recommendations
A limiting factor of this study was the lack of distinction between grass types in
estimating forage production. This lack of distinction resulted in variability in grass
production data due to variable production potential between study sites with short, mid,
and tall grasses and among plots at each site rather than variability in grass production
due to redberry juniper canopy cover. An additional limitation was the absence of grass
production data at higher and lower levels of canopy cover.
As with the juniper canopy cover and forage production relationship, the
estimation of the cost relationship would have been improved if data had been available
for lower and higher extremes of redberry juniper canopy cover. Also, retreament costs
could have been better estimated if data had been available for a retreatment type
situation. In this study the treatment cost relationship was estimated to be non-linear with
the cost ha"' being dependent on redberry juniper canopy cover; however, the estimate of
cost as a ftinction of canopy cover may not be the most accurate predictor of the cost
85
because cost ha"' is more dependent on tree density and size of the trees. Data on costs
for treating larger spray plots and large variations in canopy cover on sites could aid in
further refining the treatment cost relationship.
It is reconmiended that follow-up clipping and canopy measurements be done on
the treated sites. These follow-up measurements would provide additional data to
estimate the relationship between canopy cover and forage production as well as provide
mortality data when using individual tree treatment as a control technique for redberry
juniper.
With the growing importance of wildhfe and the emergence of nature tourism as
supplemental ranch income, empirical relationships need to be estimated to determine
how these non-traditional ranch revenues sources affect when, how much, and how to
control brush species. Because wildlife is part of the ranch animal community, a better
understanding between forage composition, production, and juniper canopy cover is
needed so managers can make informed decisions on optimal redberry juniper canopy
cover levels. Another Umitation is the need to know the impacts of various levels of
juniper control (i.e. the percent of the land cleared or how many redberry junipers to
leave ha"') on wildlife populations (quail, turkey, deer) and on the value of the rangeland
for recreational hunting.
86
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90
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91
APPENDIX A
MARKETABLE ANIMAL UNIT
A marketable animal unit is calculated as follows:
MAU = (WH) (%H) + (WS) (%S) + (WC) (%C), (A. 1)
where MAU is the marketable animal unit in kg, WH is the weaning weight of a heifer calf
in kg, %H is the percent of a heifer marketed animal unit"', WS is the weaning weight of a
steer calf in kg, %S is the percent of the steer marketed animal unit"', WC is the weight in
kg of a cull cow, %C is the percent of a cull cow marketed animal unif'.
Assuming a 50% chance of giving birth to a heifer or a bull calf and a weaning
percentage of 82.27, a rate of 14% for cull cows, and all replacement heifers come from
the herd, the percent of animals for sale is as follows animal unif': heifer calves 27.135%,
steer calves 41.35%, and cull cows 14.0%. Assuming the weights of a steer calves and
heifer calves at weaning are 262.488 kg and 244.761 kg, respectively, and that a cull
cow's weight is 453.6 kg (Kermedy, 1970; McGrann, 1995), equation A.I can then be re
written as
MAU = (244.761 * .27135) + ( 262.488 * .4135)
+ (453.6 * .14) = 237.8943 kg. (A.2)
92
APPENDIX B
30 m SUMMARIZED CANOPY COVERS AND FORAGE PRODUCTION DATA
For complete data set see Racher (1998).
Key
Location: 1 - Texas Tech Experimental Ranch Study Site 2 - Triangle Ranch Study Site 3 - Stone Ranch Study Site 4 - Pitchfork Ranch Study Site
Rep: Random point number (one through ten). Rep zero (0) signifies potential yield data with no canopy cover present. Transects were extended from each random point.
Plot: Division of two transects extended from each random point. 1 - 3 0 - m transect extended north 2 - 30 - m transect extended south 0 - Potential yield with no canopy cover
JUPI Line Canopy: Line intercept redberry juniper canopy cover data in percent (%).
PRGL Line Canopy: Line intercept mesquite canopy cover data in percent (%).
PEAR Line Canopy: Line intercept prickly pear canopy cover data in percent (%).
YUCC Line Canopy Cover: Line intercept yucca canopy cover data in percent (%).
Grass Yield: Transect mean aerial phytomass yield of grass species clipped to 1-cm stubble height (kg ha').
Forb Yield: Transect mean aerial phytomass yield of forb species clipped to 1-cm stubble height (kg ha"').
Grass + Forb: Transect mean of total aerial phytomass yield (kg ha').
93
Table B. 1. Summarized Data for 30-m Long Transects.
Location
2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
Rep
1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 0
Plot
1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2
1 2 1 2 1 2 1 2 I 2 1 2 1 2 1 2 1 2 1 2
JUPI Line
Canopy (%)
33.13 25.27
6.03 30.30
9.10 4.47
20.83 42.20 16.03 30.73 31.27 32.43 16.17 16.20 9.63
42.37 10.23 39.73 43.13 25.23
0.00 66.63 42.63 18.73 54.73 52.37 62.60 13.77 6.17
30.37 27.87 29.83 20.37 12.93 2.57
68.93 33.43 23.17 11.47 17.43 28.40
0.00
PRGL Line
Canopy (%)
0.00 0.47 0.70 0.00 0.00 0.00 0.37 0.20 0.00 1.30 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.17 3.63 1.47 0.00 0.00 0.00 1.43 0.00 0.00 0.00 0.53 0.80 0.00 0.00 0.00 3.07 4.37 4.47 0.13 0.00
PEAR Line
Canopy (%)
0.00 2.93 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.97 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
YUCC Line
Canopy (%)
0.00 2.97 0.00 4.47 1.50 0.00 2.87 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Grass Yield
(kg ha-')
1167.28 676.2
1073.64 505.8
1221.08 1304.96 662.89
1024.32 1053.48 701.28
1004.36 999.76
1142.72 787.88
2042.04 860.44 1255.8
1324.52 846.48 957.36
1812.86 569.76 551.68
1047.44 902.16
311.2 457.64
1173.24 1743.4
1078.76 741.36 714.68
1557.32 1303.92 900.44 746.28 549.44 817.24 971.16 476.48 921.68
1750.34
Forb Yield
(kg ha ' )
326.28 286.64 361.04
112.4 507
527.6 488.52 170.08 413.24 498.04 139.08 575.04 374.72 544.12 604.32 122.48
191.8 392.16 288.88 282.08 719.14
19.84 89.12
173.88 84.68 24.08 21.84
54.2 138.92 143.68
92.4 36.2
65.16 355.8 339.2 41.64 51.68 29.56
329.92 0.00
270.28 221.88
Grass + Forb Yield
(kg ha ')
1493.56 962.84
1434.68 618.2
1728.08 1832.56 1151.41
1194.4 1466.72 1199.32 1143.44
1574.8 1517.44
1332 2646.36
982.92 1447.6
1716.68 1135.36 1239.44
2532 589.6 640.8
1221.32 986.84 335.28 479.48
1227.44 1882.32 1222.44 833.76 750.88
1622.48 1659.72 1239.64 787.92 601.12
846.8 1301.08 476.48
1191.96 1972.22
94
Table B.l. Continued.
Location
3 3 3 3 3 3 3 3 3 3 3
3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
Rep
1 1 2 2 3 -> J
4 4 5 5 6 6 7 7 8 8 9 9 10 10 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 0
Plot
1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2
1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2
JUPI Line
Canopy (%)
18.90 56.03 65.83 28.07 40.00 16.47 35.77
5.27 14.87 51.03 57.03 15.30 43.97 25.00 15.90 59.80 11.20 23.17 30.73 10.13 0.00
26.73 37.20
8.90 23.00 33.30 22.60 25.73 15.27 38.23 10.63 9.77
26.53 13.57 31.73 26.90 22.30 12.17 41.70 15.00 45.20
0.00
PRGL Line
Canopy (%)
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.63 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.93 8.40 0.00 0.00 0.00 1.87 0.00 0.00 0.00 0.10 1.47 0.00 0.00 0.00 0.00 1.27 3.77 0.00 0.43 0.93 0.00
PEAR Line
Canopy
(%)
0.00 0.00 0.00 0.00 0.00 2.17 0.00 0.00 0.00 0.00 0.00 0.00 3.93 0.60 0.00 0.00 0.00 2.93 0.00 0.00 0.00 0.13 0.00 0.13 4.03 0.00 0.00 0.13 0.87 0.00 3.23 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
YUCC Line
Canopy (%)
2.07 1.47 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.37 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.03 4.33 0.00 4.40 0.00 2.43 1.17 0.00 0.00 0.00
18.67 5.23 6.40 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Grass Yield
(kg ha-')
733.72 441.28 694.64 435.24 801.88 1155.2 492.08
1011.44 712.48 286.64 443.36 877.16 386.44 612.72
1265.52 363.04 1032.2
1046 260.72 998.92 1138.9
1192.44 968.6
2269.92 1228.6
1408.16 1859
1667.56 1867.52
1791 1981.72 1296.84 2286.12 1698.32
1279.8 1167.68 2489.8
1568.68 1602.68
1715.4 675.2
2542.56
Forb Yield
(kg ha-')
642.36 255.12 128.24 325.36
56 155.36 287.88
679.4 446.88
367.6 59.92
361.92 139.56 208.28 610.16 303.16 482.72
450.8 445.4
360.28 494.24 285.32
54.04 91.08 49.04
13.4 177.16 38.24
371.82 26.58
153.92 616.68 181.08 27.24
169.88 153.08
83.6 75.4
18.64 195.12
41 111.4
Grass + Forb Yield
(kg ha" ')
1376.08 696.4
822.88 760.6
857.88 1310.56 779.96
1690.84 1159.36 654.24 503.28
1239.08 526 821
1875.68 666.2
1514.92 1496.8 706.12 1359.2
1633.14 1477.76 1022.64
2361 1277.64 1421.56 2036.16
1705.8 2239.34 1817.58 2135.64 1913.52 2467.2
1725.56 1449.68 1320.76 2573.4
1644.08 1621.32 1910.52
716.2 2653.96
95
APPENDIX C
60 m SUMMARIZED CANOPY COVERS AND FORAGE PRODUCTION DATA
For complete data set see Racher (1998).
Key
Location: 1 - Texas Tech Experimental Ranch Study Site 2 - Triangle Ranch Study Site 3 - Stone Ranch Study Site 4 - Pitchfork Ranch Study Site
Rep: Random point number (one through ten). Rep zero (0) signifies potential yield data with no canopy cover present. Transects were extended from each random point.
Plot: Division of two transects extended from each random point. 0 - Potential yield with no canopy cover
JUPI Line Canopy: Line intercept redberry juniper canopy cover data in percent (%).
PRGL Line Canopy: Line intercept mesquite canopy cover data in percent (%).
PEAR Line Canopy: Line intercept prickly pear canopy cover data in percent (%).
YUCC Line Canopy Cover: Line intercept yucca canopy cover data in percent (%).
Grass Yield: Transect mean aerial phytomass yield of grass species clipped to 1-cm stubble height (kg ha"').
Forb Yield: Transect mean aerial phytomass yield of forb species clipped to 1-cm stubble height (kg ha').
Grass + Forb: Transect mean of total aerial phytomass yield (kg ha"').
96
Table C 1 . Summarized Data for 60-m Long Transects.
Location
2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4
Rep
1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 0
JUPI Line
Canopy (%)
29.2 18.17 6.78
31.52 23.38 31.85 16.18
26 24.98 34.18
0.00 54.63 36.73 57.48
9.97 29.12
25.1 7.75
51.18 17.32 22.92
0.00 37.47 46.95 28.23 20.52 32.95 36.17 34.48 37.85 17.18 20.43
0.00 31.97 15.95 27.95
20.5 24.43 18.15 22.65
24.6 26.93
30.1 0.00
PRGL Line
Canopy (%)
0.23 0.35 0.00 0.28 0.65 0.00 0.00 0.00 0.00 0.00 0.00 0.58 2.55 0.00 0.72 0.00 0.27 0.40 0.00 3.72 2.30 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.82 0.00 0.00 0.00 0.00 7.17 0.00 0.93 0.00 0.05 0.73 0.00 0.63 1.88 0.68 0.00
PEAR Line
Canopy (%)
1.47 0.00 0.00 0.00 0.00 0.00 0.00 1.78 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.48 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.08 0.00 0.00 0.00 2.27 0.00 1.47 0.00 0.00 0.07 2.08 0.00
0.5 1.62 0.00 0.00 0.00 0.00 0.00 0.00
YUCC Line
Canopy (%)
1.48 2.23 0.75 1.43 0.00 0.00 0.00 1.58 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.77 0.00 0.00 0.00 0.00 0.00 1.18 0.00 0.00 0.00 0.00 4.68
2.2 1.22 0.58 0.00
11.95 3.2
0.00 0.00 0.00 0.00
Grass Yield
(kg ha-')
921.74 789.72
1263.02 843.6
877.38 1002.06
965.3 1451.24 1290.16 901.92
1812.86 560.72 974.8
384.42 1458.32 910.06
1136 1102.18 647.86
894.2 699.08
1750.34 587.5
564.94 978.54 751.76 499.56 660.26 499.58 814.28 1039.1 629.82 1138.9
1080.52 1749.26 1633.58 1767.54 1886.36 1791.48 1489.06 1828.74 1585.68 1195.3
2542.56
Forb Yield
(kg ha-')
306.46 236.72
517.3 329.3
455.64 357.06 459.42
363.4 291.98 285.48 719.14
54.48 129.28 22.96 96.56
118.04 50.68 347.5 46.66
179.74 135.14 221.88 448.74
226.8 105.68 483.64 407.24 210.92 173.92 456.66 466.76 402.84 494.24 169.68 70.06 95.28
205.03 90.25
398.88 98.56
118.34 47.02
118.06 111.4
Grass + Forb Yield
(kgha-')
1228.2 1026.44 1780.32
1172.9 1333.02 1359.12 1424.72 1814.64 1582.14
1187.4 2532
615 1104 407
1555 1028 1187 1450 695
1074 834
1972 1036.24 791.74
1084.22 1235.4 906.8
871.18 673.5
1270.94 1505.86 1032.66 1633.14
1250.2 1819.32 1728.86 1972.57 1976.61 2190.36 1587.62 1947.08
1632.7 1313.36 2653.96
97
APPENDIX D
SUMMARIZED HERBICIDE TREATMENT DATA
Key
Location: 1 - Stone Ranch Study Site 2 - Triangle Ranch Study Site
Rep: Random point number (one through ten). Transects were extended from each random point.
Plot: Division of two transects extended from each random point. 1 - 3 0 - m transect extended north 2 - 30 - transect extended south
Trees: Number of trees over 0.91 m in height within belt transect(300 m ).
Dose: Number of milliliters applied to belt transect.
Time: The amount of time to treat belt transect in hours.
Height: Average height of redberry juniper trees (m) within belt transect (Racher, 1998).
Belt Canopy: Belt transect redberry juniper canopy cover in percent (%) (Racher, 1998).
98
Table D. 1. Summarized Herbicide Treatment Data for 30-m Transects.
Location
2 2 2 2 2 2 2 2 2 2 2 2 2
2 2 2 2 2 2
2
Rep
1
1 2 9
3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10
Plot
1
2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2
Trees
(300 m^)"' 9 10 11 14 7 10 9 10 25 17 15 14 25 11 11 5 7 14 9 7 31 60 31 22 55 29 33 22 43 38 18 35 2 9
65 20 52 25 46
Dose
(ml) 42 44 56 98 22 64 36 50 104 104 80 108 106 56 54 24 48 44 38 34 108 230 154 90 212 128 98 72 116 98 58 88 8 38
230 56 172 118 80
Time
(hrs)
0.0531 0.0587 0.0811 0.0591 0.0636 0.0269 0.0271 0.0353 0.0962 0.0573 0.0469 0.0373 0.0553 0.0869 0.0227 0.0387 0.0344 0.0407 0.0240 0.0282 0.1278 0.0431 0.0429 0.0598 0.0642 0.1116 0.0458 0.0540 0.0533 0.0520 0.0498 0.0311 0.0149 0.0001
0.0871 0.0544 0.0273 0.0418 0.0360
Height
(m) 2.42 1.98 3.02 1.63 2.70 1.58 1.78 1.60 2.29 2.01 2.56 1.57 3.48 2.37 1.79 2.71 1.15 2.05 2.10 1.63 2.74 1.72 0.87 1.60 2.00 2.24 1.44 1.33 1.34 1.05 1.17 1.14 1.25 1.37
1 22 0.82 1.83 1.27 1.38
Belt Canopy (%)
40.64 50.65 89.79 50.58 69.11 20.83 24.29 31.86 43.74 56.88 66.92 37.53 60.83 53.46 15.55 51.81 10.42 16.34 34.03 13.09 80.26 35.33 3.96 37.81 62.20 88.52 47.27 23.68 39.15 33.31 34.83 20.51 6.07 1.38
53.51 29.39 23.43 30.65 59.20
99
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