Impacts of development in the Coachella Valley on Fringe-Toed Lizards and the related implications to Joshua Tree National Park
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Impacts of development in the Coachella Valley
on Fringe-Toed Lizards and the related
implications to Joshua Tree National Park
Final Report submitted to
Joshua Tree National Park
February 21, 2002
Mary E. Cablk, Ph.D.
Desert Research Institute
Division of Earth and Ecosystem Sciences
2215 Raggio Parkway
Reno, NV 89512
(775) 673-7371
(775) 674-7557 fax
mcablk@dri.eduTable of Contents
Introduction 2
Desert Habitat Description 4
Coachella Valley Fringe Toed Lizard (Uma inornata) 5
Demographics – Riverside County 7
Project Objectives 8
Methodology 9
Results 14
Discussion 15
Implications for Joshua Tree National Park 19
Conclusions 22
Literature Cited 24
Appendix I 26
Appendix II 29
Appendix III 30Introduction
Joshua Tree National Park lies in the southernmost extent of the Mojave Desert of
California (Figure 1). Established originally as a National Monument in 1936, a Biosphere
Reserve in 1984, and finally a National Park in 1994, Joshua Tree harbors fantastic arrays of
Mojave and Colorado Desert vegetation and wildlife. Geomorphologically, Joshua Tree’s
mountainous terrain is amassed with enormous boulders and extensive bajadas dissected by
sandy washes. The geologic landscape features that creates a unique environment draws visitors
to the park throughout the year. The geology of the park formed 100 million years ago when
monzogranite formed as plutonic intrusions on the earth’s surface. The monzogranite developed
a system of directional rectangular joints. Groundwater percolated down through these joint
fractures transforming hard mineral grains into soft clay, while grains resistant to solution were
washed away. Flash floods eroded the surface of the landscape away from these granite
formations exposing them as the huge boulders and rock piles visitors enjoy and marvel at today.
Figure 1. Joshua Tree National Park in Southern California.
Kern Joshua Tree National Park
San Bernardino
Los
Angeles
Legend
River side California
Orange
Park boundary
N
San Di ego Imperial W E
S
scale 1:2 6508 78
The flora and fauna of Joshua Tree National Park (JOTR) are well adapted to their desert
existence. Miller and Stebbins (1964) outlined essentially five categories of stresses that desert
biota uniquely face: 1) water availability; 2) water abundance; 3) extreme diurnal temperature
differences; 4) available cover and other habitat features; and 5) dust storms. Fauna in particular
-2 -evolved and have become well adapted to exploit water from unexpected sources such as
vegetation, moist animal matter such as insects, and metabolic water. Other adaptations
involving conserving water, or minimizing water loss, such as expending dried feces, are also
unique adaptations of desert fauna.
Reptiles, being ectothermic, are well adapted for desert existence. They rely on external
temperatures and heat sources to maintain their body temperature. Desert reptiles use behavior to
thermoregulate body temperature, such as moving to shade or burrowing under the sand in
excessive heat. Fringe-toed lizards for example have the capability of burrowing beneath the
sand when surface temperatures rise dangerously hot. They also utilize rodent burrows to escape
heat. In cold months lizards remain below the surface where they will not freeze. Fringe-toed
lizards, like many reptiles, have also mastered concealment. They exhibit coloration and mottling
so similar to their sandy dune habitat that they are fairly indistinguishable from the background
substrate. Fringe-toed lizards also have developed the scale fringes that are their namesake for
mobility purposes. The advantage of these fringes serve to allow effective and expedient
locomotion across loose sand, useful for escaping predators, for burrowing under the surface for
thermoregulation, and for moving to cooler locations either on the surface or in rodent burrows
also for heat regulation (Miller and Stebbins, 1964).
Although the fauna and flora of the desert have evolved with the extremes of their
environment, these species face other challenges that they cannot in many instances overcome
nor adapt to. These insurmountable factors include human encroachment into habitat and direct
and indirect loss of habitat from development. These factors occur on very short time scales such
as a few years, certainly not the requisite time frames over which adaptation and evolution occur.
Species such as the fringe-toed lizard which have evolved to exploit a particular niche and are
relative specialists, suffer enormous pressure and population losses with the reduction of habitat
from human encroachment.
Visitation to Joshua Tree National Park has increased over the past decade and in 1999
the park hosted 1,316,340 visitors. As more people become aware of the unique beauty and other
intangible resources this park affords, the demand for a [relatively] pristine desert experience
increases. New roads, expanded parking areas, and upgraded facilities have been required to
accommodate the increase in public usage and concurrent access demands by park visitors.
-3 -Joshua Tree National Park, like all public lands, faces natural resource management
challenges. In addition to pressure from the public for access and services, Joshua Tree faces
physical challenges to management due to its juxtaposition with urban development on adjacent
private lands. The city of Twenty-nine Palms to the north, the Morongo Valley to the west, and
the conglomerate of cities to the southwest in the Coachella Valley are expanding (Cablk, in
review, Cablk et al., 1999). As urban and suburban development increases the biota that can be
displaced are. Those species that are immobile, such as plants, or fauna which require specific
conditions to exist and lose those conditions, cease to exist. Some species find refuge within the
political safehaven of the park’s boundaries. Immobile species or those which lack acceptable or
accessible corridors to Joshua Tree, end up with diminished or relict populations that are found
in disjunct areas or exclusively within park boundaries. The Coachella Valley Fringe-Toed lizard
may become such a species if efforts are not taken to preserve their last remaining habitat outside
of Joshua Tree’s boundaries.
Desert Habitat Description
South of Joshua Tree National Park lies the Coachella Valley which is the northwestern
extent of Sonoran Desert (Mayhew, 1965). This region is referred to as Colorado Desert and is
considered transitional to the Mojave Desert that lies to the north. The dominant vegetation are
creosote bush (Larrea tridentata) and burro bush (Franseria dumosa) which together comprise
90-100 percent of the vegetative cover (Mares, 1999). Other common vegetation species are
brittlebush (Encelia farinosa), teddy bear cholla (Opuntia bigelovii) and catclaw (Acacia
greggii). Compared to the Mojave Desert to the north, the Colorado Desert has lower overall
biotic diversity despite having a greater arborescent component (Mares, 1999). In the Mojave to
the north, Creosote Bush and White Bursage (Ambrosia dumosa), comprises only 70% of the
vegetation cover, rather than nearly all of it as in the Colorado Desert (Rowlands, 1995).
Physiographically the Coachella Valley is bordered to the north by Joshua Tree National
Park and to the northwest by the San Bernardino Mountains. The San Jacinto Range borders the
Coachella Valley to the south and is the highest range in California south of the Sierra Nevada,
supporting a wide range of climate zones. Snow often persists on the 11,000 foot peaks until
June, when the temperature 10 miles away on the valley floor may be well over 37.8° C (100° F).
The mix of abrupt mountains and lowlands creates microhabitats such as oases at Little Morongo
-4 -Canyon and Indian Wells. Another rare but biologically important habitat is the desert grassland.
These grasslands occur where sinks, or low areas, in the landscape floor fill with water after
heavy rainfall. Although creating ephemeral pools, these events are enough to preclude growth
of shrubs and permit growth of annuals. In 1964 Miller and Stebbins reported the best desert
grassland habitat in Pleasant Valley.
Dune habitat is of critical importance to the Coachella Valley Fringe-toed lizard.
Sand dune habitat for this species is discussed below.
Coachella Valley Fringe Toed Lizard (Uma inornata)
The Coachella Valley Fringe-toed lizard, U. inornata, hereafter referred to as FTL, is
described as a medium sized Uma found only in aeolian (windblown) sand dunes of the
Coachella Valley and San Gorgonio Pass in Riverside County, California (Pough, 1973, Turner
et al., 1984). This sand dwelling lizard is active from April through September (Durtsche, 1992).
Appropriate dune habitat for U. inornata is unstable, supports little plant life, and consists of
very small particles consistently between 0.5mm and 2mm (Stebbins, 1944). The range of
particle size has been reported in the literature between 1.0 and 0.1mm (Barrows, 1997). These
conditions are prerequisite to allow U. inornata to burrow or “swim” underneath the surface. The
reason for such behavior is to avoid predation and to regulate temperature. For this reason sand
compaction is an important factor for differentiating between what is suitable and what is
unsuitable U. inornata habitat (Turner et al., 1994; Barrows, 1997). Roadrunners (Geococcyx
californianus) and badgers (Taxidea taxus berlandieri) are known predators. Other bird and
snake species as well as coyote also likely feed on U. inornata (Stebbins, 1944; Miller and
Stebbins, 1964). This omnivorous lizard consumes flowers, leaves, plant-dwelling arthropods,
ants, and ground arthropods. Prey varies with availability and seasonal abundance (Durtsche,
1995). U. inornata gets most of its water from its diet (Stebbins, 1944; Durtsche, 1995). Due to
dramatic reductions in habitat, U. inornata was listed as endangered by the state of California in
June 1980, and Federally listed as threatened by the US Fish and Wildlife Service in September
1980 (Federal Register, 1980).
Sand dune habitat has been reduced in the Coachella Valley from both direct and indirect
activities (Durtsche, 1995). Urban development such as houses, shopping centers, and public
utilities serve to directly reduce available habitat. What is somewhat more difficult to measure
-5 -are the indirect effects of development and off-road vehicle activity that serve to reduce the
influx of sand, required to maintain aeolian formations. Wind farms, for example, change wind
patterns resulting in a reduction of available, mobile source sand. As a result, downwind dunes
experience a gradual coarsening and stabilization of surface sands. The result has been
elimination of suitable habitat for U. inornata (Turner et al., 1984; Barrows, 1997). As a result of
reduction of habitat, a preserve system was established to conserve and maintain the remaining
sand dune remnants (Barrows, 1997). The following table describes the remaining aeolian dune
habitat within the Coachella Valley.
Descriptor Hectares Acres
Area 285.75 706.1
Number of dunes 19870 19870
Mean dune size 0.01 0.03
Maximum dune size 43.37 107.17
Minimum dune size 0.001 0.003
The current extent of active aeolian dunes in the Coachella Valley is shown in Figure 2.
Populations of FTL are reported to be doing “good” by officials at the Center for Lands
Management in Thousand Palms, California. This does not imply, however, that these dunes are
preserved against development nor is there any implication that they will not suffer from
reduction of source sand in the future.
Figure 3. Population growth in Riverside County between 1990 and
2000
1600000
1550000
1500000
1450000
1400000
1350000
1300000
1250000
1200000
1150000
1100000
90
91
92
93
94
95
96
97
98
99
00
19
19
19
19
19
19
19
19
19
19
20
-6 -Demographics – Riverside County
California is the most populous state in the US, containing 12 percent of the US
population in 2000. California’s population is expected to increase, and the state is expected to
have 15 percent of the Nation's population by the year 2020. Riverside County is of particular
concern to the park because of the rapid rate of development and projected population increase.
Nearly five percent of California’s population resides in Riverside County. Figure 3, above,
shows the increase in population for Riverside County between 1990 and 2000, which increased
from 1,170,413 people in 1990 to 1,545,387 people in 2000. This represents an approximate 32%
increase in the number of people living there in the last decade and follows the trend of the
previous decade, shown in Figure 4. Between 1980 and 1990 the population in Riverside County
grew from 663,199 in 1980 to 1,170,413 in 1990.
Within Riverside County, the Coachella Valley (Figure 5) is a destination resort
comprised of nine incorporated cities. Figure 6 shows the breakdown of population by each of
these nine cities, which total 255,790 people or 17% of Riverside County’s entire population.
Figure 4. Population growth in Riverside County between 1980 and
1990.
1300000
1200000
1100000
1000000
900000
800000
700000
600000
500000
80
81
82
83
84
85
86
87
88
89
90
90
19
19
19
19
19
19
19
19
19
19
19
19
Perhaps the best known city within the Coachella Valley is the resort destination of Palm
Springs. Palm Springs is located near the San Andreas Fault, which passes through the middle of
the Coachella Valley. North of the San Gorgonia pass, which brings traffic into the Coachella
Valley from Los Angeles and other metropolitan areas, are the San Bernardino Mountains, a
popular destination for hiking, camping, fishing and skiing during winter. The San Bernardino
-7 -Figure 6. Population by city within the Coachella Valley.
50000
40000
30000
20000
10000
0
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Sp a
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range, which reaches heights of 10,000 feet, is the easterly extension of the San Gabriel
Mountains. Because this pass channels and intensifies the prevailing westerly winds at the head
of the Coachella Valley, it has been populated with hundreds of large wind generators.
Project Objectives
Due to the projected population increases over the next 20 years and the expected
development that must accompany such increases, Joshua Tree National Park will face
increasing pressure from outside forces. The reduction of habitat for U. inornata in areas
adjacent to the park could result in loss of this species. Although U. inornata is not known to
occur within park boundaries, other species may suffer habitat loss and come to occur only
within park boundaries. This would result in heavy stewardship demands on park officials and
managers.
In an effort to begin proactive measures to work with neighboring land managers and
owners, two projections of potential future development were modeled based on existing patterns
of development and projected population increases. The impacts of these scenarios, which are
but two of a suite of potential futures, were evaluated on the existing habitat of Federally and
state listed Coachella Valley Fringe-Toed Lizard. The results of this analysis include maps of
development at specific time intervals in the last few decades, maps of projected development,
-8 -tabular data summarizing population growth between 1980 and 2000, projected growth to the
year 2020, and an analysis of potential habitat loss by U. inornata.
Methodology
The analysis presented here was based on work in the Mojave Desert funded by the
Department of Defense Strategic Environmental Research and Development Program (SERDP)
(Cablk et al., 1999; Gonzalez, 2000). Although the same variables used in this study for the
Coachella Valley as were developed in the Mojave, the specific probability models were
developed based on Coachella Valley data. For this reason, other variables may be cited for
incorporation into this analysis at a future date, but were not acquired for the purposes of this
study.
Landsat Multispectral Scanner (MSS) data were acquired from the North American Land
Characterization (NALC) Program. The NALC program was funded by the US Environmental
Protection Agency (EPA) Office of Research and Development's Global Warming Research
Program (GWRP) and the USGS Earth Resources Observation Systems (EROS) Data Center.
The objectives of the NALC project are to develop standardized remotely sensed data sets (e.g.,
NALC triplicates) for change detection analyses. NALC satellite data are referred to as
triplicates, three sets of satellite data acquired in the early 1970s, mid-1980s and early to mid-
1990s, respectively. Original MSS data have a nominal spatial resolution of 79m but the NALC
data are resampled to a nominal spatial resolution of 60m. The MSS instrument has detectors
sensitive in four discrete regions of the electromagnetic spectrum from visible green to near
infrared. These bands are optimal for detecting vegetation and other biotic landscape features as
well as abiotic features such as bare soil, water, or impervious surfaces. While the spatial
resolution is somewhat coarse relative to other commercially available satellite data (down to 1m
panchromatic) the spatial, spectral, and temporal resolutions of MSS data were appropriate for
our large study area and for detecting urbanization in the desert (from
http://eosims.cr.usgs.gov:5725/CAMPAIGN_DOCS/nalc_proj_camp.html).
Three scenes of MSS data provide complete coverage of the California Mojave Desert.
The following table identifies each scene (path and row) and the corresponding image acquisition
dates.
-9 -1970
Path Row Date
39 36 7 Aug 72 & 13 Sep 72
39 37 23 May 73 & 9 Jun 73
40 36 29 Jun 73 & 23 Jun 74
1980
Path Row Date
39 36 10 Sep 86
39 37 6 Jun 86
40 36 10 Jun 85
1990
Path Row Date
39 36 10 Sep 93
39 37 30 Jun 93
40 36 21 Jun 93
The set of three scenes (not three dates) was pieced together into one large, seamless file
that covered the study area. This mosaic was first masked to the project study area to exclude
regions outside the scope of the project and then masked again to include only privately owned
lands, as federally managed public lands, state, and certain other lands are not available for
development. This process generated three seamless images for the entire study area for the mid-
1980s and early 1990s, which included pixel data for private lands only, or those lands available
for future development. These two data sets were interpreted for extent of urban or other
anthropogenic development using spectral and spatial pattern recognition techniques. The 1986
and 1993 scenes were digitized on-screen with a resulting binary classification of two classes:
urban and non-urban. The 1970’s data were not interpreted due to poor image quality. The
minimum mapping unit was one pixel, or 60m. The resulting urban layers were used in the
development of models to predict future development to the year 2020. Past and current (i.e.
1990s) development was derived from NALC satellite imagery.
Future development was modeled to the year 2020 based on past patterns of development
between 1986 and 1993, population projections from the US Census bureau, distance to existing
urban areas, political boundaries, natural landscape features and infrastructure. Population
growth between 1986 and 1993 was used over the greater time period of 1973 and 1993 to better
capture population growth trends of recent times. Population in Riverside County nearly doubled
between 1980 and 1990, but saw only a 32% increase in the last decade.
The resulting model was spatially explicit and resulted in a raster output that retains the
original geographical coordinates of the input data. Population predictions, which have no spatial
- 10 -component, were applied uniformly throughout the landscape. Population growth was an
estimated density increase of 12.3 people/ha, calculated by dividing the number of people living
in urban areas of the Coachella Valley in the early 1990s (224,357 people) by the number of
developed hectares in 1993 (18270.7 ha). The number of developed hectares in the Coachella
Valley was extrapolated based on proportional area of incorporated cities inside the valley
relative to the greater Riverside County. Of the entire county, the cities in the Coachella Valley
comprise 16.78% of what is developed. Therefore the number of people living in the Coachella
Valley in 1986 and 1993 were calculated based on corresponding percentages. For example, in
1993 the total population of Riverside County was 1,321,304. To calculate the proportional
population in the Coachella Valley, this figure was multiplied by 0.1678. The population was
assumed to increase in the Coachella Valley at the current rate. The population of Coachella
Valley cities was 198,800 in 1990 while the total Riverside population for 1990 was 1,170,413.
This means the Coachella Valley population is 16.98% of the whole county by area. Using this
percentage, the following was estimates:
Total area developed in 1986 = 89574834.234 m2 = 8957.5 ha
Population in 1986 = 871209
Proportional population = 871209 * 0.1698 = 147931.3
People/ha in 1986 = 16.5148
Total area developed in 1993 = 182706814 m2 = 18270.7 ha
Population in 1993 = 1321304
Proportional Population = 1321304 * 0. 1698 = 224357.4
People/ha in 1993 = 12.27963
These calculations assume all development within urban boundaries (>50k people).
Based on these calculations, population densities for the future were estimated as follows:
18270.7 ha in 1993 minus 8957.5 ha in 1986 = 9313.2 new ha of development
Population change between 1986 and 1993 = 76426.1 new people
76426.1 / 9313.2 = 8.2 new people per ha were added to the CV between 1986 and 1993.
The projected population for Riverside County in 2020 is 2,773,431 based on the US Census
figures. The proportional projected population for the Coachella Valley is 470,929. Based on this
information, the basis for two scenarios, based on past rates of population growth and actual per
capita population growth were calculated:
- 11 -1. Trend rate = 8.2 people/ha:
Projected growth = 2020 population minus 1993 population
470,929 – 224,357 = 246,572 people
Settlement density of 8.2/ha gives an additional 30,070 ha of new development.
2. Growth = 12.28 people/ha:
Projected growth = 2020 population minus 1993 population
470,929 - 224,357 = 246,572 people
Settlement density of 12.28 people/ha gives an additional 20,079 ha of new development.
Although census results for 2000 are available, 1993 population values must be used
because the population is tied to the developed lands. Development is available for 1993 only,
not for 2000. Predicted development was modeled based on the methods of Landis et al. (1998).
A detailed description of the modeling process used in the Mojave Desert study, on which this
analysis is based, is detailed in Gonzalez (2000).
Spatial data used to model projected development are listed in the following table. All
data, including NALC data listed above, have a 60 m cell size in UTM projection, zone 11
(NAD83). Acquired data layers are those data that were acquired either from direct interpretation
of remotely sensed imagery or were obtained from another source. Derived data are products that
were created from one or more combinations of acquired data. For example, “Change in
development (93-86)” was derived by subtracting development in 1986 from development in
1993.
Acquired data Derived data
1
1986 development Change in development (93-86)
1
1993 development Distance to 1986 development
2
city boundaries Percent development
3
roads Slope
4
DEM Distance to roads
4
private land City boundaries
The baseline data were masked to include only private lands in the Coachella Valley using the
same method as for the NALC data, discussed above. Pixel size for this data layer was 60 m2 .
The resulting development layer for the year 2020 was resampled to 60m2 using a nearest
neighbor algorithm to allow comparison of results with NALC derived urban data. Projected
1
Interpreted from NALC satellite imagery
2
Source: ESRI
3
Aerial photograph interpretation and interpreted SPOT imagery
4
Source: Mojave Desert Ecosystem Program (MDEP)
- 12 -development was then modeled based on the existing probabilities and patterns of development
that occurred between 1986 and 1993.
Differences between the Mojave Desert methodology exist as scale (60m here rather than
100m grid cells) reduced masking because of integration of products using ENVI software rather
than ESRI software, and roads were masked from all files. The rationale for masking out roads
was that development does not physically occur on roads, whether the road is existing or new.
Development can occur only adjacent to a road. The intent was to eliminate populating roads or
counting roads as having population living on them. Also, this method does not produce
“missing” values, as occurred with the original methodology. Finally, all roads were treated as
equal, rather than categorizing roads to primary and secondary. In the California desert region
people are just as likely to build on a dirt or otherwise unimproved road than on a paved road.
This is not the case everywhere in the United States.
The modeling process involved acquiring existing data, deriving secondary data products,
eliminating areas excluded from development, developing a statistical model to quantify the
relationship between these variables and patterns of development, and finally, projecting
potential future development based on past development history. The code written and original
documentation are provided in Appendix I. Following the Mojave protocol, the following
variables were used to develop the predictive model: percent of existing development (pctdev),
slope (slope), distance to existing development (devdist), within or outside of city boundaries
(citybnds), and distance to roads (roaddist). All spatial layers first had undevelopable lands,
specifically public lands, masked out. Those lands in the public sector were not included in the
analysis. The variable pctdev was derived using a 20x20 moving window on 1986 and 1993
development data, respectively. Slope was calculated based on the DEM. The variable devdist
was calculated using euclidean distance on each of the development data layers, 1986 and 1993,
respectively. Pixels were either within or outside of city boundaries and as such citybnds was
binary. The roaddist variable was calculated using euclidean distance, in the same fashion as
devdist was created but using roads as the input feature.
The difference between 1986 development and 1993 development (newdev) was the
response variable, or Y, for the statistical analysis. All of the data layers described above and the
variable newdev were exported into Splus statistical package for model development. The model
was developed using logistic regression and a generalized linear model (GLM) was developed.
- 13 -The model was developed with 90% of the data, randomly selected, and validated with the
remaining 10%. Because drop in deviance is not necessarily the best way to evaluate the
goodness-of-fit in logistic regression, Analysis of Variance (ANOVA) using a Chi-squared test
was also conducted.
Once the final model was derived, it was applied to the 1993 development layer using the
corresponding coefficients and data layers to create the probability of development surface. This
surface was populated with 8.2 people/ha and 12.28 people/ha, respectively, as calculated above.
A confusion matrix was generated to evaluate the accuracy of the resulting probability surface
with probability greater than 30.
A spatial coverage of current Fringe-toed lizard distribution was acquired from Cameron
Barrows of the Coachella Valley Nature Preserve as previously described. This Fringe-toed
lizard habitat coverage was compared with the predicted development coverage to quantify the
extent to which existing habitat would be impacted from potential future development under the
current scenario.
Results
The existing development in 1986 and 1993 are shown in Appendices II and III,
respectively. The data used to develop the probability surface are shown in Figures 7-13,
respectively. The probability surface is shown in Figure 14. The final model used to generate the
probability of development surface was:
Pr(development) ~ -2.203 + (0.038*pctdevelop93) + (-0.120 * slopepct93) + (-0.004 *
devdist93) + (0.758 * citybnds93) + (-0.008 * roaddist93)
Results from the Chi-squared analysis are shown in the following table.
Variable Df Deviance Resid. Df Resid. Deviance Pr(Chi)
NULL 27055 37507.58
Pctdev 1 6450.761 27054 31056.82 0
Slope 1 4523.35 27053 26533.47 0
Devdist 1 7299.930 27052 19233.54 0
Citybnds 1 389.342 27051 18844.2 0
Roaddist 1 2308.165 27050 16536.03 0
Results from the accuracy assessment of the probability surface indicated an overall accuracy of
93.35% with a Kappa coefficient of 0.033. The total number of hectares required to populate the
Coachella Valley with a density of 8.2 people/ha and 12.28 people/ha is approximately 30,070 ha
- 14 -and 20,079 ha, respectively. The highest probability was assigned 0.81 and the lowest probability
was assigned 0.01. Based on the model prediction, the total number of hectares that are
candidates for development equal a total of 49,584. Figure 15 shows the intersection of Fringe-
toed lizard habitat with projected development at a density of 8.2 people/ha and Figure 16 shows
the same intersection with the higher density of 12.28 people/ha.
When existing suitable habitat for Fringe-toed lizards is compared with modeled
development, 65 ha of dunes are directly lost from development at low density projections. At
high density population projections 36 ha of dune habitat is directly lost. The total area of dune
habitat for Fringe-toed lizards is 285.8 ha. These areas are shown in Figures 17 and 18,
respectively. The following table summarizes the statistics describing the existing dune habitat
and the dune habitat lost under two potential development scenarios. Sum is the sum total of the
perimeter (edge) or area of dune features. Mean is the average perimeter length or average area
size of each dune feature. Count is the number of dune features analyzed.
Sum Mean Count
Existing dunes
Perimeter (m) 761227.99 38.3 19870
Area (ha) 285.75 0.014 19870
High density scenario (12.28 people/ha)
Perimeter (m) 105036.16 43.58 2410
Area (ha) 36.20 0.015 2410
Low density scenario (8.2 people/ha)
Perimeter (m) 179132.68 44.72 4006
Area (ha) 64.96 0.016 4006
Discussion
The Coachella Valley is growing, although the rate of growth over the past 30 years is
slowing. County wide, the US Census reported an 87% occupancy rate of all housing units.
Within the Coachella Valley that figure ranges between 52% (Indian Wells) and 96%
(Coachella). This data is given in the following table, from the 2000 US Census.
- 15 -City Population Total Housing Occupied % occupied
(2000) units housing housing
Riverside County 1,545,387 584,674 506,218 86.6
Cathedral City 42647 17893 14027 78.4
Coachella 22724 5024 4807 95.7
Desert Hot Springs 16582 7032 5859 83.3
Indian Wells 3816 3843 1982 51.6
Indio 49116 16909 13871 82.0
La Quinta 23694 11812 8445 71.5
Palm Desert 41155 28021 19182 68.5
Palm Springs 42807 30823 20516 66.6
Rancho Mirage 13249 11816 6813 57.7
Total 255790 133173 95502
Riverside County 1,545,387 584,674 506,218
Study area 17% 23% 19%
percentages
Although growth rates have slowed over the past two decades, there is positive growth
and it continues to push towards Joshua Tree National Park, in the direction of the critical dune
habitat that remains in the Coachella Valley.
The model developed here is empirical and deterministic. It predicts potential future
development based on historical, documented trends in development. That is, the model does not
incorporate knowledge or preferences from sources such as planners or land managers, rather the
model was developed based on statistical relationships between certain variables and the areas
where development actually occurred in the past. There are trends in development that exist and
those trends can be quantified. For example, development and the presence of roads are related.
Roads must be built to allow development to occur, whether simple dirt roads or paved, public
roads. At the same time, if an infrastructure exists and access is readily available, development
may more readily occur. While this does not always hold true, there was a significant statistical
relationship between roads and development over time in this analysis. Distance to roads and
development hold an inverse relationship, meaning the closer a location is to a road, the more
likely it is to become developed. The probability of development decreases with distance from a
road.
The variables used to develop the model for the Coachella Valley were limited to the
same variables that were found to be significant in the Mojave Desert of California. For the
Coachella Valley, these variables were also found to be significant. Development is positively
- 16 -related to existing development and incorporated city boundaries. The more urban features that
exist already, the more likely a location is to be developed. Likewise, if an area is within city
boundaries, it is more likely of being developed than a location outside incorporated city
boundaries. These variables relate to existing infrastructure and while not explicit about such
features as power, water, or other services, the two variables can be considered to represent such
features at an aggregate level.
Development was negatively related to slope and distance to existing development.
Urbanization is more likely to occur where the landscape is relatively flat as opposed to steeper
slopes. Slope ranged between 0 and 71 percent in this study, although most of the valley floor is
relatively flat. Coupled with percent development is the variable that describes distance to
existing development. The closer a parcel is to existing development, the higher the probability
that it will be developed, hence the negative sign of the regression equation. Both the distance to
existing development and the amount of existing development nearby are significant. The
correlation coefficient (0.396) of these two variables also supports this.
Other variables might be considered for similar future analyses that were not considered
in the Mojave Desert might be significant specifically to the Coachella Valley. Distance to golf
courses for example or proximity to mountains are variables that might influence development.
These features are highly desirable in the Coachella Valley but in the case of golf courses, are
not necessarily common features elsewhere in the Mojave Desert. Because the Coachella Valley
does not harbor any military installations and because of the prevalence of golf courses,
development trends and sociodemographics vary between the two desert regions (Mojave and
Coachella). The inclusion of such variables might result in a slightly different model.
There are an infinite number of development scenarios that might occur in the Coachella
Valley. If development were to occur in the manner predicted by the model, loss of dune habitat
for existing populations of Fringe-toed lizards would occur. These losses would vary with
settlement density and the figures presented in this report represent minimum area losses, not
absolute. If a relatively low density settlement (8.2 people/ha), which was the actual density of
people in the Coachella Valley in 1986, occurs between 1993 and 2020, approximately 20% of
the existing Fringe-toed lizard habitat will be lost at a minimum. Under the scenario of 12.28
people/ha, a more dense population settlement trend that had occurred by 1993, 12% of the
Fringe-toed lizard habitat will be lost by 2020 at a minimum. Although statistically a higher
- 17 -settlement density results in only half the dune loss of a lower settlement density, there are other
externalities associated with population growth to consider. In each scenario, the same total
number of people were “added” to the landscape, but the densities were different. Regardless of
the density, more people in the Coachella Valley means just that – more people. With more
people, there will be greater pressure for access to undeveloped areas to hike, ride off-road
vehicles, camp, bird watch, and otherwise visit open space, nature preserves, and Joshua Tree
National Park. More services will be needed to accommodate the greater number of people, such
as grocery stores, schools, medical services, and infrastructure. Existing services will have to be
expanded or further developed to meet the population growth and demand, regardless of how
many people move to the Coachella Valley or the density of their placement.
While variations in total population growth were not examined, the impacts from
different settlement densities were. Density does have an impact on the direct and indirect loss of
what is considered “natural” lands, including active sand dunes, due to the number of structures
built on the landscape. Physical construction changes the vegetation and other characteristics of
the landscape to directly impact habitat. Indirect impacts also result from construction and
expansion of existing development, primarily in the form of fragmentation. Fragmentation may
result in sand dune habitat that is too small (area wise) to sustain fauna and may interfere with
sand transport critical for sustaining aeolian dunes. The results of the analysis indicate that
fragmentation will occur under the two development scenarios. Given the low density scenario,
almost 2500 dune features would be lost, and those features will average around 44 ha in size.
This is a loss of approximately 20% of the current dunes. Under a high density scenario only
2410 dunes would be lost, or approximately 12%. Larger dunes would be lost under the
projected low density scenario, likely the result of an overall greater loss in the number or extent
of existing dunes. These numbers do not indicate whether or not remaining dunes are the original
dunes in whole, or are also inclusive of dune fragments from larger features.
Fragmentation and interference with aeolian deposition are the two reasons why the
impacts of development on dunes are reported above as minimum values. Over time, without
sand transport from suitable upwind sources, dunes diminish in size and become too hard, or
sustain only large sand particles, thus rendering them unsuitable for Fringe-toed lizards.
Therefore, although there may be a certain number of dunes remaining, those dunes may not be
suitable size in the year 2020, and their longevity beyond 2020 is unknown. Regardless, under
- 18 -either of the modeled scenarios, there will be loss of sand dune habitat for Fringe-toed lizards.
The populations will suffer from direct loss of amount of habitat, from fragmentation, and from
quality of dune habitat associated with increased usage by people and reduction in sand
transport.
The Coachella Valley Association of Governments is in the process of drafting a plan that
to this date is neither complete nor available. However, when released, this plan will provide an
alternative growth pattern based on concerns for the perpetuation of Fringe-toed lizard
populations. It is expected that this plan will result in very different growth patterns on the
landscape and would potentially alter the bleak statistics under the scenarios modeled here.
Implications for Joshua Tree National Park
Clearly, the population figures alone indicate that development pressure and an
increasing population are inevitable in the area surrounding Joshua Tree National Park. This
study focused on the Coachella Valley, but results from other work in the Mojave Desert indicate
that development is expected to the north, particularly in the Morongo and Yucca Valleys and 29
Palms area. The report to SERDP for 2000 is included as a supplemental document at the end of
this report. Based on these modeling and analysis efforts, the Morongo Valley and vicinity,
including the 29 Palms area, are expected to expand. The results from both the Mojave Desert
Analysis and analysis presented here indicate that Joshua Tree National Park is and will become
more ecologically isolated due to development that is occurring to the north, southwest, and
southern edges of the park.
Joshua Tree NP is unique in that it encompasses ecotones between desert types. The
variety of flora and fauna that can be seen and enjoyed within a relatively small area are found
nowhere else in southern California. Desert ecosystems are fragile and their undisturbed surfaces
are alive with cryptogamic bacteria, opportunistic organisms that assist in maintaining the
integrity of the desert floor. These crusts are extremely susceptible to disturbance such as foot,
horse, dog, cattle, or mechanized vehicle traffic. Joshua Tree becomes more available to visitors
as people move closer to the park’s boundaries. The park becomes more accessible in terms of
legal entry points and unofficial entry points across roadless park boundaries.
At least one development may impact the park. A new planned development project
would cover 7,200 acres on the southern edge of Joshua Tree National Park. The site would abut
- 19 -the north side of the Coachella Valley Preserve, span Dillon Road, and abut the southern edge of
the park. The Desert Sun (2/8/02) reported the following:
"We’re talking no manufacturing and no pollutants of any kind,"
said Eve Fromberg, an attorney who spoke on behalf of partners in
the…investment group, who have yet to come forward. "Just brain-
trust stuff."
From a Fringe-toed lizard habitat perspective, the development would eliminate little, if any
existing dune habitat. However, there would be other significant impacts on the park, not unlike
those experienced by military installations to the north, in the Mojave Desert. These impacts
include illegal entry by civilians, illegal actions such as theft and vandalism by civilians,
reduction of habitat, poaching, and threats to wildlife and people by feral dogs, among others.
While Joshua Tree National Park does not engage in the same type of operations as a military
base, the Department of Interior does have an entry fee collection system in place. For this
reason, park patrons are expected to enter the park through an official station and pay appropriate
fees. While no paved roads would be built that allowed legal access to the park adjacent to this
complex, opportunities for entrance into the park would be more readily available with the
development of the proposed complex. The closer people can get to an undeveloped area, the
farther into that area they push. Vandalism and other misuse of natural areas are, sadly, intrinsic
attributes that go hand in hand with unsupervised public access. Red Rocks, Nevada, for
example, lies only a few miles from the city of Las Vegas. It is a Bureau of Land Management
managed wilderness area that requires an entrance fee and has controlled entry points. The
beautiful red canyons and ancient varnished surfaces of this protected area become increasingly
scarred with carvings from modern day visitors with each passing year. Joshua Tree is not
immune to the same forces. Because Joshua Tree administrative offices are in the north side of
the park, far from the proposed development complex, there can be little supervision or law
enforcement in the proposed development area. There is an existing road “corridor” that links the
park’s existing Geology Tour Road with the federal road system that would feed into the
proposed development. This is shown in Figure 19.
Poaching and other illegal activities occur when people have uncontrolled, if not
unsupervised, access to natural areas. As development closes the gap between the park and area
outside its boundary, Joshua Tree will experience the effects of having people in close proximity
- 20 -to a relatively pristine area without law enforcement or mitigative educational opportunities.
Education and law enforcement, while at opposite ends of the range of facilitation, are an added
expense to an already tight allocated budget. Finally, feral dogs may become a problem, if not
already so, in the park. To the north, feral dogs are known to run in packs and wreak havoc on
wildlife as reported by Edwards AFB and the Marine Corps Base at 29 Palms. These dogs pose a
danger to people as well.
In short, there are no less significant impacts to the park’s natural integrity regardless of
whether or not a “pollution-free” industry is built on its boundary. The very presence of
development and the addition of people to the landscape will impart direct and indirect impacts
on the desert.
Wildlife will also feel the impacts of increasing development. While some species are
known to adapt somewhat to urbanization, such as raven and coyote, other species that are less
mobile and require more specialized habitat may not be able to endure future development.
There are but a few options for wildlife when their respective habitat is altered from its natural
state to that of urban structures. Those species that can adapt may do so, at the risk of human-
wildlife interactions and the potentially negative consequences of those interactions. Highways,
for example, are deadly to fauna. Likewise, people kill animals they view as a threat to their pets
and children, such as coyote. Non-native toxic vegetation planted as landscaping, such as
oleander, also kills native fauna such as desert bighorn sheep. With few roads and no housing
developments, the park offers the last remnants of undisturbed habitat.
Species that cannot adapt to co-existence with humans will either go extinct, locally, or
will remain only in relict populations where development has yet to occur. Joshua Tree National
Park is therefore one of the few remaining refuges in southern California for Colorado Desert
species that cannot adapt to human development. The park also provides refuge for those species
that can adapt, but prefer suitable habitat in the park rather than marginal habitat in developed
areas. This results in tremendous pressure on the managers of the park. The demands of the
public are to have a certain type of experience and the public has a range of expectations of the
National Park System. The challenge for park officials is to provide the experience expected by
the public, facilitate appropriate access in accordance with federal and state laws, and
simultaneously maintain the park ecology, geology, cultural and other natural features in pristine
conditions. If the park ends up being the sole refuge of certain species, particularly threatened
- 21 -and endangered species, the management challenges balancing visitor use and maintaining
natural conditions increase in expense, difficulty, and complexity. The increase in expense,
difficulty, and complexity occurs with an unknown function, and may not necessarily be
proportional or additive. It can be, however, quantified in terms of user days, operational costs,
and litigation as well as biologically through surveys. This is not an insignificant challenge.
Conclusions
Results from this study indicate that development in the Coachella Valley will continue
to occur and will be fueled by an increasing population that is expected to nearly double between
the years 2000 and 2020. If development follows past trends since the mid-1980s in terms of
where it may occur and if no efforts are undertaken to prevent suitable dune habitat loss, the
Coachella Valley Fringe-Toed lizard will face significant reduction of habitat. Faced with the
loss of more than 20% of existing suitable dune habitat, this Uma may be forced into extinction
in the Coachella Valley.
The implications of this are significant to Joshua Tree National Park, which faces
development pressure not only from the south in the Coachella Valley, but also from the Mojave
Desert region to the north and west. If U. inornata is extirpated from the Coachella Valley, then
any individuals that occur within Joshua Tree National Park will require tremendous and
intensive management from a habitat perspective. It is noted that they are not known to occur at
this time in the park. Efforts to maintain suitable dune habitat would be the last hope for survival
of this species, assuming the genetics would allow perpetuity of the population or remaining
meta populations.
The park also faces other pressures from development that threatens to abut directly
against its political boundaries. Like military installations in the Mojave Desert to the north, the
park is one of the last remaining areas that are representative of undisturbed desert conditions.
Harboring the ecotone between desert types, Joshua Tree is perhaps more fragile because of its
unique mix of flora, fauna, and the variety of geological features coupled with climate, that exist
in the southern California region. Based on the Department of Defense’s experience at
installations across the country with regards to the impacts of development right up to
boundaries, the effects of such development on Joshua Tree National Park should be considered
a threat to the natural integrity of the park. The prospect of having urban development in any
- 22 -form along a park boundary should be taken very seriously as a threat to the landscape and its
fauna and flora, particularly when coupled with diminishing open space and large human
population influxes. The impacts from such development are first direct in the form of loss of
habitat and fragmentation, and second indirect in the form of enabling human access and the
negative externalities that accompany rural, urban, and suburban development.
When the Coachella Valley Association of Governments publishes its report that outlines
plans for development in the Coachella Valley, taking into consideration Fringe-toed lizard
habitat, Joshua Tree National Park officials may elect to become active in approving or assisting
in the final planning and implementation process as legally possible. A proactive approach to
working with planners and government officials in the Coachella Valley will aid the park by
reducing the chances of becoming sole stewards of threatened or endangered species.
Minimizing development along park boundaries through proactive planning measures will also
be a critical task for the park in the next 20 years.
- 23 -Literature Cited
Barrows, C.W. 1997. Habitat relationships of the Coachella Valley Fringe-Toed Lizard (Uma
inornata). The Southwestern Naturalist. 42:218-223.
Cablk, M.E. in review. Quantifying urban development using historical satellite imagery:
Implications for military installations in the California Mojave Desert. in C. Lee, D. Morofka,
and B. Prigge, Eds. Special Issue: Monitoring and Mitigating the Environmental Impacts of
Military Training at the National Training Center, Ft. Irwin, CA. Journal of Arid Environments.
Cablk, M.E., J.S. Heaton, R.J. Lilieholm, M.de J. Gonzalez, M. Stevenson, and D. Mouat.
Military Ecology: The role of the Defense Department in protecting and preserving our biotic
resources and challenges for civilian researchers in this realm. In D. Brunkhorst, ed., Landscape
Futures: An international symposium on advances in research for natural resource planning and
management across regional landscapes. Armidale, NSW, Australia. 22-25 September 1999.
ISBN 1 8639 664 3.
Durtsche, R. D. 1995. Feeding time strategies of the fringe-toed lizard, Uma inornata, during
breeding and non-breeding seasons. Oecologia. 89:85-89.
Durtsche, R. D. 1995. Foraging ecology of the Fringe-Toed Lizard, Uma inornata, during
periods of high and low food abundance. Copeia. 4:915-926.
Federal Register. 1980. Reproposal of critical habitat for the Coachella Valley fringe-toesd
lizard. Red. Reg. 45:36038-36041.
Gonzalez, M. 2000. Futures Scenarios of Land Use in the California Mojave Desert. Ph. D.
Dissertation. Department of Forest Resources, Utah State University. Logan, Utah.
Landis, J. J.P. Monzon, M. Reilly, and C. Cogan. 1998. Development & Pilot Application of the
California Urban & Biodiversity Analysis (CURBA) Model.
Mares, M.A. 1999. Encyclopedia of Deserts. University of Oklahoma Press. Norman, OK.
Mayhew, W. W. 1965. Reproduction in the sand-dwelling lizard Uma inornata. Herpetologica
21:39-55.
Miller, A. H., and R. C. Stebbins. 1964. The lives of desert animals in Joshua Tree National
Monument. Univ. California Press, Berkeley. 452pp.
Pough, F. H. 1973. Uma inornata. Cat. Am. Amphibians and Reptiles 126.1-126.2.
Rowlands, P. G. 1995. Vegetation attributes of the California Desert Conservation Area. In:
Latting, J. a. P. G. R. (Ed.), The California Desert: An introduction to natural resources and
man's impact Volume I. Riverside, CA, June Latting Books: 135-183.
- 24 -Stebbins, R.C. 1944. Some aspects of the ecoogy of the iguanid genus Uma. Ecological
Monographs. 14:311-332.
Turner, F.B., D.C. Weaver, and J.C. Rorabaugh. 1984. Effects of reduction in windblown sand
on the abundance of the Fringe-Toed lizard (Uma inornata) in the Coachella Valley, California.
Copeia. 2:370-378.
- 25 -Appendix I. Documentation of model development process.
Model procedure modified from Matt Stevenson’s revised CURBA model (2000). Differences here exist as
scale (60m rather than 100m grid cells), reduced masking because of integration of ENVI products, and roads
were masked from all files. The rationale for masking out roads is that development does not occur on roads,
whether existing or new. The intent was to eliminate populating roads or counting roads as having population
living on them. Also, this method does not produce “missing” values, as occurred with the original
methodology. Finally, all roads were treated as equal, rather than categorizing roads to primary and secondary.
The rationale for this is from personal knowledge of the CA desert regions. People are just as likely to build on
a dirt or otherwise unimproved road than on a paved road.
All of the work, including following arc command code, was written and performed by Dr. Mary Cablk at the
Desert Research Institute (fall 2000).
Model process:
Create the mask(s)
• Set non-private land to nodata mask86_priv2 = setnull(mask86_priv == 0, mask86_priv)
• Set background 0’s to nodata for 1986 u86sub_mask2 = setnull(u86sub_mask == 0, u86sub_mask)
• Set background 0’s to nodata for change chdev2 = setnull(changedevmask == 0, changedevmask)
• convert nodata in roads to “1” roads2 = con(roads == nodata, 1, roads)
• Create final mask with no roads/86
development/only in private land setmask u86submask2
mask86_priv2a = selectmask(mask86_priv2, u86submask2)
setmask roads2
mask86_priv3 = selectmask(mask86_priv2, roads2)
setmask off
Distance to development
• Create distance to development for 1986 devdist86 = eucdistance(u86sub_mask2)
• Mask out private land and 86 urban setmask mask86_priv3
devdist86b = selectmask(devdist86, mask86_priv3)
• convert to integer devdist86i2 = int(devdist86b)
• turn off the mask setmask off
• build the vat buildvat devdist86i2
• kill interim products kill devdist86
kill devdist86b
rename devdist86i2 devdist86
Percent existing development
• create % surrounding development
grid for 1986 w/20x20 window pctdev86 = focalmean(u86sub_mask, rectangle, 20,20)
• mask it out setmask mask86_priv3
pctdev86b = selectmask(pctdev86, mask86_priv3)
setmask off
• convert to integer do this in arcview and *100 for pctdevelop
City boundaries, in or out
• recode cities to 2 and all else to 1 cities2 = con(cities == 1, 2, cities)
cities3 = con(cities2 == 0, 1, cities2)
• mask it out setmask mask86_priv3
cities4 = selectmask(cities3, mask86_priv3)
- 26 -setmask off
kill cities2
kill cities3
• recode cities to binary 0, 1 cities5 = con(cities4 == 1, 0, cities4)
cities6 = con(cities5 == 2, 1, cities5)
kill cities4
kill cities5
rename cities6 citybnds
Slope
• mask slope grid setmask mask86_priv3
slopepct = selectmask(slopesubmask, mask86_priv3)
setmask off
Roads
• Create distance to roads do this in arcview for roaddist
• convert to integer roaddist_int = int(roaddist)
• build the vat buildvat roaddist_int
• mask it out setmask mask86_priv3
roaddist4 = selectmask(roaddist_int, mask86_priv3)
setmask off
New development (dependent variable)
• Mask new development-change grid setmask mask86_priv3
chdev3 = selectmask(chdev2, mask86_priv3)
• create binary for develop/non-developed chdev4 = con(isnull(chdev3), 0, chdev3)
setmask off
Dump to statistical program
• create the input for stats regress.txt = sample(chdev4, pctdevelop, slopepct, devdist86,
citybnds, roaddist4)
Do preparations on 1993 data
• Set background 0’s to nodata for 1993 setmask priv_mask
mask93_priv = selectmask(u93sub_mask, mask93_priv)
setmask off
mask93_priv5 = setnull(mask93_priv4 == 0, mask93_priv4)
# recall this : convert nodata in roads to “1” roads2 = con(roads == nodata, 1, roads)
• Create final mask with no roads/93
development/only in private land setmask roads2
mask93_priv3 = selectmask(mask93_priv2, roads2)
setmask off
dump to ENVI for mask93_priv5
Distance to development
calculate distance to 1993 development in arcview for devdist93a
• Mask out private land and 93 urban setmask mask93_priv5
devdist93b = selectmask(devdist93a, mask94_priv5)
• convert to integer devdist93int = int(devdist93b)
• turn off the mask setmask off
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