Soil Compaction Vulnerability at Organ Pipe Cactus

National Monument, Southwestern Arizona

U.S. Department of the Interior

U.S. Geological Survey

Open-File Report 2014–1048

Soil Compaction Vulnerability at Organ Pipe Cactus 

National Monument, Southwestern Arizona

By Robert H. Webb, Kenneth E. Nussear, Shinji Carmichael, and Todd C. Esque

Open-File Report 2014–1048

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2014

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Suggested citation:

Webb, R.H, Nussear, K.E., Carmichael, Shinji, and Esque, T.C., 2014, Soil compaction vulnerability at Organ Pipe 

Cactus National Monument, Arizona: U.S. Geological Survey Open-File Report 2014-1048, 24 p., 

http://dx.doi.org/10.3133/ofr20141048.

ISSN 2331-1258 (online)

Any use of trade, product, or firm names is for descriptive purposes only and does not imply 

endorsement by the U.S. Government.

Although this report is in the public domain, permission must be secured from the individual 

copyright owners to reproduce any copyrighted material contained within this report.
iii

Contents

Abstract ......................................................................................................................................................................... 1

Introduction.................................................................................................................................................................... 1

Setting........................................................................................................................................................................ 5

Climate....................................................................................................................................................................... 5

Geology and Soils...................................................................................................................................................... 5

Methods......................................................................................................................................................................... 6

Experimental Design.................................................................................................................................................. 6

Field Measurements .................................................................................................................................................. 6

Laboratory Measurements ......................................................................................................................................... 7

Results..........................................................................................................................................................................10

Qualitative Assessment of Soil Compaction Vulnerability .........................................................................................10

Particle-Size Distributions and Sorting......................................................................................................................11

Undisturbed Bulk Density and Laboratory Compaction Measurements ....................................................................12

Quantitative Assessment of Soil Compaction Vulnerability .......................................................................................15

Discussion and Conclusions.........................................................................................................................................19

Acknowledgments ........................................................................................................................................................20

References Cited..........................................................................................................................................................21

Figures

Figure 1. Map showing spatial distribution of soils by vulnerability classifications and the locations of 

soil sampling points, Organ Pipe Cactus National Monument, southwestern Arizona................................................... 3

Figure 2. Three examples of Proctor compaction curves illustrating low, medium, and high vulnerability to soil 

compaction at Organ Pipe Cactus National Monument, southwestern Arizona............................................................. 8

Figure 3. Proctor curves illustrating some of the characteristics used to calculate soil vulnerability to compaction .... 8

Figure 4. Ternary diagram showing particle-size distributions for 48 soil samples analyzed for compaction 

vulnerability at Organ Pipe Cactus National Monument, southwestern Arizona .......................................................... 11

Figure 5. Histogram showing Folk sorting coefficients for soil samples from Organ Pipe Cactus 

National Monument, southwestern Arizona ................................................................................................................. 12

Figure 6. Histograms showing Proctor compaction curves (see fig. 3) for (A) maximum bulk density minus 

undisturbed bulk density (Dmax–Dud), (B) maximum minus minimum bulk density (Dmax–Dmin), (C) water content at 

maximum density, and (D) water content at minimum density, with the scoring system for compaction vulnerability 

shown in groups delineated with dashed lines............................................................................................................. 14

Figure 7. Graphs showing maximum soil strength compared to (A) moisture content, (B) bulk density, and

(C) Folk sorting coefficient, σi. ..................................................................................................................................... 16

Figure 8. Map showing soil vulnerability to soil compaction based on laboratory measurements, 

Organ Pipe Cactus National Monument, southwestern Arizona .................................................................................. 17

Figure 9. Map showing changes in classifications of soil compaction vulnerability from qualitative (fig. 1) to 

quantitative (fig. 8) assessments, Organ Pipe Cactus National Monument, southwestern Arizona............................. 18
iv

Tables

Table 1. Soil vulnerability classifications of Organ Pipe Cactus National Monument .................................................... 4

Table 2. Vulnerability scores for selected laboratory measurements of compaction of soils at Organ Pipe Cactus 

National Monument, southwestern Arizona ................................................................................................................. 10

Table 3. Undisturbed dry bulk densities for soils at Organ Pipe Cactus National Monument, 

southwestern Arizona .................................................................................................................................................. 13

Conversion Factors and Datums

Conversion Factors

SI to Inch/Pound

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

Area

hectare (ha) 2.471 acre

Volume

cubic centimeter (cm3) 0.06102 cubic inch (in3) 

Density

kilogram per cubic meter (kg/m3) 0.06242 pound per cubic foot (lb/ft3) 

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32.

Datums

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 (NAVD 88).

Horizontal information in geographic coordinates is referenced to the World Geodetic System 1984 (WGS 84).

Elevation, as used in this report, refers to distance above the vertical datum.
1

Soil Compaction Vulnerability at Organ Pipe Cactus 

National Monument, Southwestern Arizona

By Robert H. Webb, Kenneth E. Nussear, Shinji Carmichael, and Todd C. Esque

Abstract

Compaction vulnerability of different types of soils by hikers and vehicles is poorly known, 

particularly for soils of arid and semiarid regions. Engineering analyses have long shown that poorly 

sorted soils (for example, sandy loams) compact to high densities, whereas well-sorted soils (for example, 

eolian sand) do not compact, and high gravel content may reduce compaction. Organ Pipe Cactus National 

Monument (ORPI) in southwestern Arizona, is affected greatly by illicit activities associated with the 

United States–Mexico border, and has many soils that resource managers consider to be highly vulnerable 

to compaction. Using geospatial soils data for ORPI, compaction vulnerability was estimated qualitatively 

based on the amount of gravel and the degree of sorting of sand and finer particles. To test this qualitative 

assessment, soil samples were collected from 48 sites across all soil map units, and undisturbed bulk 

densities were measured. A scoring system was used to create a vulnerability index for soils on the basis 

of particle-size sorting, soil properties derived from Proctor compaction analyses, and the field 

undisturbed bulk densities. The results of the laboratory analyses indicated that the qualitative assessments 

of soil compaction vulnerability underestimated the area of high vulnerability soils by 73 percent. The

results showed that compaction vulnerability of desert soils, such as those at ORPI, can be quantified 

using laboratory tests and evaluated using geographic information system analyses, providing a 

management tool that managers potentially could use to inform decisions about activities that reduce this 

type of soil disruption in protected areas.

Introduction

Land uses in the North American deserts that cause soil disruption are widespread and increasing 

on public lands (Lovich and Bainbridge, 1999; Leu and others, 2008), particularly on vehicle roads and 

tracks (Vogel and Hughson, 2009) and unauthorized trails attributed to immigration, drug smuggling, and 

interdiction by federal authorities near the United States–Mexico borderlands (U.S. Fish and Wildlife 

Service, 2011). An understanding of the spatial variability of soil vulnerability to compaction could 

contribute to land management that minimizes the adverse effects of these uses (Jones and others, 2003). 

Compaction and its effects on soil properties are recognized widely in agricultural (Vorhees and others,

1978) and engineering practices (Fredlund and Rahardjo, 1993), as well as off-road vehicle use (Webb,

1983; Webb and others, 2013), livestock grazing (Brooks and others, 2006; Chen and others, 2012), 

human trampling (Liddle, 1975; Liddle and Grieg-Smith, 1975; Weaver and Dale, 1978), and construction 

of utility corridors (Vasek and others, 1975). Military exercises involving extensive vehicle use, in 

particular, cause substantial soil compaction and surface disruption (Krzysik, 1985; McCarthy, 1996; 

Prose and Wilshire, 2000). 
2

Soil compaction has negative environmental effects that may persist for decades to centuries 

(Webb, 2002). Compaction decreases infiltration rates and increases runoff, thus accelerating soil erosion 

(Snyder and others, 1976; Iverson, 1980; Iverson and others, 1981) and increasing dust production and 

wind erosion (Campbell, 1972; Goossens and Buck, 2009, 2011), all of which may retard plant 

establishment (Adams and others, 1982; Prose and others, 1987). Minimizing soil compaction, therefore,

is a priority for management of natural areas, particularly national parks (National Park Service, 2006), 

and the ability to predict the vulnerability of different soils to soil compaction is important in the 

development of management plans where soil properties may be threatened by adverse land uses. 

Vulnerability of soils to compaction is known from studies of engineered fill, where the objective 

is to maximally compact fill to support roadways or building foundations (Fredlund and Rahardjo, 1993). 

The magnitude of the increase in density has been shown to depend on the soil moisture content, texture, 

and the compacting load (Williams and McLean, 1950; Bodman and Constantin, 1965; Webb, 1983). 

Vehicles moving across soil surfaces cause deformation as normal and shear stresses are applied beneath 

tires (Muro and O’Brien, 2004). Compaction results when normal and shear stresses applied to a soil 

surface are greater than soil strength, and this results in deformation of soil structure, particularly 

decreased pore volume and increased bulk density. If normal stress from surface disturbances is repeated 

sufficiently, soils compact to a maximum density for that applied stress. Poorly sorted soils, such as loamy 

sands and sandy loams, compact more readily than well-sorted soils, such as eolian sand or playa surfaces 

(Webb, 1983). Increasing amounts of gravel may decrease compaction, even though additional gravel

makes the soil more poorly sorted (Webb, 1983); when gravel content is greater than about 30 percent, the 

larger particles interact, absorbing applied stress. 

Soils compact the most when stresses are applied at water contents slightly less than field capacity 

(water content that a saturated soil drains to after about 24 hours; Webb, 2002). At water contents 

approaching zero, pore-water pressures are high, increasing the resistance to applied pressure (Greacen,

1960; Webb, 1983), whereas at water contents near saturation, volume decreases can be attained only by 

forcing water from the soil, and drainage rates become the limiting factor. Low vulnerability soils do not 

show a large variation over the range in moisture contents, have minima at a moisture content of 0, and 

(or) have maximum density at a relatively high moisture content that may create drainage problems. Soils 

that are waterlogged generally deform rather than compact.

The purpose of this paper is to quantify compaction vulnerability for desert soils at Organ Pipe 

Cactus National Monument (ORPI), southwestern Arizona (fig. 1). Immigration, smuggling, border 

security interdiction, and visitor usage have caused a mosaic of soil compaction and disruption in an area 

managed for conservation and wilderness (T.C. Esque and others, U.S. Geological Survey, unpub. data, 

2010; Webb and others, 2013), and we demonstrate how assessment of compaction vulnerability might be

useful for resource assessments and management of disturbances at ORPI, as well as for other arid and 

semiarid landscapes. Geospatial National Resources Conservation Service (NRCS) Soil Survey 

Geographic (SSURGO) data were used (termed the National Cooperative Soil Survey [NCSS] data 

[NRCS, n.d.]) to qualitatively rank soil vulnerability on the basis of particle-size sorting (poor 

sorting=many different sizes of particles in the soil) and gravel content (more large particles=less 

vulnerable) (table 1). Soil samples then were analyzed for compaction properties and scoring system was 

developed for assessing soil vulnerability to compaction from laboratory data. The qualitative and 

quantitative assessments were compared to show why quantitative analyses are important to the evaluation 

of compaction vulnerability.
3

Figure 1. Map showing spatial distribution of soils by vulnerability classifications and the locations of soil sampling 

points, Organ Pipe Cactus National Monument, southwestern Arizona. Distribution of soils is from Soil Survey 

Geographic data and qualitative vulnerability classifications (table 1). NWR, National Wildlife Refuge. 
4

Table 1. Soil vulnerability classifications of Organ Pipe Cactus National Monument, southwestern Arizona.

[Soil map unit: SSURGO data for ORPI: http://soildatamart.nrcs.usda.gov/Metadata.aspx?Survey=AZ646&UseState=AZ, 

accessed July 15, 2012. Abbreviations: ORPI, Organ Pipe Cactus National Monument; SSURGO, Soil Survey Geographic; nd, 

not determined]

Soil map unit Hectares

Extent 

(percent)

Qualitative

vulnerability 

classification Samples

Laboratory

vulnerability

classification

Ajo very cobbly sandy loam 1,300 1.0 High 3 High

Ajo very gravelly loam 4,040 3.0 Medium 4 High

Antho fine sandy loam 5,849 4.4 High 3 High

Antho soils, very gravelly variant 618 0.5 High 3 High

Cherioni gravelly very fine sandy loam 5,044 3.8 High 4 High

Cipriano gravelly loam 3,911 2.9 Medium 3 Medium

Gachado very cobbly loam 621 0.5 Medium 1 High

Gilman very fine sandy loam 10,917 8.2 High 3 Medium

Gilman very fine sandy loam, saline 561 0.4 High 2 High

Growler-Antho Complex 6,761 5.1 High 3 High

Gunsight very gravelly loam 4,091 3.1 Medium 0 nd

Gunsight very gravelly loam 24,824 18.6 Medium 3 High

Harqua very gravelly loam 213 0.2 Medium 0 nd

Harqua very cobbly loam 260 0.2 High 1 Medium

Harqua-Gunsight Complex 13,652 10.2 Medium 2 High

Laveen loam 723 0.5 High 3 Medium

Lomitas very stony loam 13,303 9.9 Medium 0 nd

Perryville very cobbly fine sandy loam 774 0.6 High 2 Medium

Rillito gravelly sandy loam 8,070 6.0 High 4 Medium

Rock land 11,739 8.8 Low 1 High

Rock outcrop 1,556 1.2 Low 0 nd

Stony land- Rock outcrop association 9,124 6.8 Low 0 nd

Torrifluvents 5,862 4.4 High 3 High

Totals 133,813 100.0 48
5

Setting

Organ Pipe Cactus National Monument (ORPI), a unit of the National Park Service (NPS), was

established in 1933. ORPI contains 133,800 ha of Sonoran Desert landscape on the United States–Mexico 

border in southwestern Arizona, sharing a 47.9-km boundary with Mexico (fig. 1). ORPI also shares 

boundaries with Cabeza Prieta National Wildlife Refuge on the west, the Tohono O’odham Reservation 

on the east, and a combination of Bureau of Land Management and private lands on the north. Elevations

of ORPI range from 297 m at the United States–Mexico border in the southwestern part of ORPI, to 1,465 

m at the top of Mount Ajo in the Ajo Mountains (fig. 1).

Climate

The National Park Service (2008) provides details on climate stations and the climate of ORPI. 

Based on records from the NPS headquarters from 1948 to 2011 (at an elevation of 501 m), the mean 

annual precipitation was 236 mm, July air temperatures averaged 31.5 °C, January air temperatures

averaged 12.1 °C, 14.1 freezing days occurred per year, and 84 days per year exceeded a maximum air 

temperature of 37.7° C. Monthly precipitation was highest in August (49.5 mm) and about one-half of the 

precipitation occurred from June through September as monsoonal thunderstorms. For the Bull Pasture 

climate station at an elevation of 947 m in the Ajo Mountains, mean annual precipitation was 290 mm, 

July air temperatures averaged 29.1 °C, and December air temperatures averaged 11.8 °C. In contrast, for 

the Growler Wash climate station at an elevation of 370 m, mean annual precipitation was 209 mm, July 

high air temperature was 39.4 °C, and December air temperatures averaged a low of 4.76 ° C.

Geology and Soils

The geology of ORPI is dominated by Tertiary volcanic and older granitic mountain ranges and 

Cenozoic alluvial plains (National Park Service, 2010). Using remote sensing, Nauman (2009) showed 

that the alluvial plains of ORPI could be distinguished based on their source lithologies. Geospatial 

geologic data (National Park Service, 2010) indicates that 74 percent of the land area of ORPI is alluvial 

deposits. Surficial geology has been mapped for 41 percent of the area of ORPI (Pearthree and others,

2011; Youberg and Pearthree, 2011; Young and Pearthree, 2011). About 40 percent of the mapped 

surficial deposits are alluvial deposits of Middle to Late Pleistocene age with moderate to strong soil 

development, and another 30 percent are surfaces and active channels of Latest Pleistocene to Holocene 

age with weak soil development. Most of the surficial deposits of the alluvial plains at ORPI do not have 

desert pavement, but many surfaces, particularly regolith overlying bedrock, have lag gravel armoring the 

surface. 

The soils have been described and mapped for the 133,813-ha area of ORPI (Chamberlain, 1972). 

Nauman (2009) used remotely sensed data to verify the Chamberlain (1972) map units and added 

information on lithologic source materials and active fluvial systems, neither of which are important to 

these analyses. The Natural Resources Conservation Service (NRCS) Soil Survey Geographic (SSURGO)

database, the digital equivalent of the Chamberlain (1972) soils maps, provides polygon coverages for all 

soil-map units and provides a variety of data on each soil map unit, particularly surficial soil particle-size 

distributions (Natural Resources Conservation Service [n.d.]). The areas given in Chamberlain (1972) 

differ from the more recent SSURGO data by about 1–2 percent. The SSURGO soil units and areas for 

ORPI are shown in table 1. A total of 22,419 ha (17 percent) of ORPI are mapped as bedrock or weathered 

regolith, and the remaining 83 percent of the land area is composed of relatively deep soils on alluvial fans 

and plains.
6

Methods

Experimental Design

The SSURGO surficial soil particle-size distributions were used to qualitatively rank the soils of 

ORPI by vulnerability classifications of high, medium, and low. Integer scores of 3, 2, and 1 were used 

strictly for convenience to denote the vulnerability classifications of high, medium, and low, respectively. 

High vulnerability soils (score=3) are poorly sorted with gravel content of less than 30 percent, and 

generally are categorized as sandy loams or loamy sands (table 1). Medium vulnerability soils (score=2) 

are better sorted in the less-than-2-mm fraction (for example, loams) but also have high gravel content 

(>30 percent), which presumably would decrease the amount of compaction from surface stresses. 

Bedrock outcrops, weathered regolith, and very rocky soils were considered to have a low vulnerability 

for soil compaction (score=1).

Soil samples for laboratory analysis were collected as part of a larger study on human impacts at 

ORPI (T.C. Esque and others, U.S. Geological Survey, unpub. data, 2010). The samples were collected 

using a random stratified experimental design of 211 points distributed evenly between undisturbed and 

disturbed desert upland sites that were at least 50 m from xeroriparian channels greater than or equal to 25 

cm deep and (or) 2 m wide. Random sample points near polygon boundaries were rejected. The study 

plots were distributed among soil polygons of the three qualitative vulnerability classifications. Field 

teams located study plots using hand-held GPS units, typically with an accuracy of ±3 m. A total of 48 

bulk soil samples were collected from a 75×75 cm by 10 cm deep excavation at the center of each plot. 

These samples typically weighed about 20 kg and were composed of all material less than 16 mm in size,

as determined with a sieve; most were bulk soil samples containing all particles in the upper 10 cm of the 

sampled point. 

Because of access restrictions due to safety concerns and difficult topography, we were unable to 

sample soils by these relative percentages. Instead, 34 soil samples were collected from high vulnerability 

soils (71 percent of samples), 13 samples were collected from medium vulnerability soils (27 percent of 

samples), and only 1 sample was collected from a low vulnerability soil (fig. 1). Therefore, our analyses 

better illustrate the properties of highly vulnerable soils in laboratory analyses instead of a true test of the 

range in field compaction vulnerability.

Field Measurements

A Troxler® 3440 Moisture Density Gauge was used to measure undisturbed bulk density and 

moisture content of soils at ORPI using the American Society for Testing and Materials Standard (ASTM 

D6938-10). The Troxler® 3440 uses a dual source of cesium-137 (

137Cs) for high-energy gamma rays 

(density) and americium-241/beryllium (241Am/Be) for fast neutrons (moisture content). A list of random 

sampling points for each SSURGO soil unit were generated and sites for sampling were selected from the 

list on the basis of access availability, both in terms of security related to illegal border activities and to 

minimize the carrying distance from roads. At each site, 10 sampling points were selected randomly in 

undisturbed soil. After a standard count to calibrate to the test environment, a stake was driven 50 mm into 

the ground to create a measurement hole, the gauge was placed over the hole with as much contact 

between the base of the gauge and soil surface without moving surficial rock fragments, the probe was 

inserted, and the radiation returns were counted for 1 minute. The volume of soil sampled was not 

constant because of variation in density and moisture content, but was about 100 cm3

. The gauge 

calculated wet and dry density as well as moisture content, and only the dry bulk density was used in the

analyses.
7

Laboratory Measurements

The 48 bulk density samples were air-dried and an approximately 300-g subsample was removed 

using a sample splitter to determine the particle-size distribution. Soil particle-size diameters (D) are 

measured in millimeters, and D generally is defined as the intermediate, or b-axis, diameter of a particle.

Particle-size distributions typically are expressed in phi (φ) units, which are defined as:

D=φ -2. (1)

This subsample was sieved using 1φ intervals from -4φ (16 mm) to 4φ (0.063 mm), with the 4φ

interval considered to be the break between sand and the silt plus clay fraction. The silt plus clay fraction 

then was analyzed to separate silt and clay content using the hydrometer technique (Gee and Bauder,

1986). 

Many sorting coefficients have been developed, particularly from analyses of hydrodynamic 

interpretations of sediments and stratigraphy (Bunte and Abt, 2001). Among the many possible sorting 

coefficients, the Folk sorting coefficient σi (Folk, 1974) was used to measure the degree of sorting for soil 

particles. The Folk sorting coefficient reflects the slope of the particle-size distribution (Bunte and Abt,

2001), where

σi=(φ84.1 + φ50 + φ15.9)/3. (2)

This sorting coefficient uses a scale from about 0.25<σi<4, where well-sorted soils have σi<0.35 

and poorly sorted soils have σi >2. Thus, compaction vulnerability increases with increasing Folk sorting 

coefficients. The Folk sorting coefficients were scored according to the vulnerability classifications of 

poorly sorted, σi<2.0 (score=2); very poorly sorted, 2≤σi ≤3 (score=2.5); and extremely poorly sorted, σi>3 

(score=3.0).

Proctor compaction analyses were used, combined with particle-size analyses, to develop a 

quantitative index of compaction vulnerability for soils at ORPI. Proctor compaction tests involve use of a 

device to apply repeated, standardized pressures to the surface of a disturbed sample to achieve maximum 

compaction (Bradford and Gupta, 1986). The test consists of compacting soils over a range of moisture 

contents by applying a standardized normal stress and documents the optimal moisture content for 

achieving maximum soil compaction (fig. 2). Proctor compaction curves vary with different soil particlesize distributions, but each soil has a lowest maximum density with a corresponding moisture content as 

well as a high maximum density and moisture content (fig. 3). This allows calculation of several metrics 

of soil compaction, particularly the differences between these two densities, the water content at maximum 

and minimum densities, and the difference between maximum compacted and undisturbed densities 

(fig. 3).
8

Figure 2. Three examples of Proctor compaction curves illustrating low, medium, and high vulnerability to soil 

compaction at Organ Pipe Cactus National Monument, southwestern Arizona.

Figure 3. Proctor curves illustrating some of the characteristics used to calculate soil vulnerability to compaction. D, 

bulk density, and θ, moisture content, at various states as determined using Proctor compaction analyses; Dmax= 

maximum bulk density, Dmin=minimum bulk density, DUD=undisturbed bulk density, θmin=moisture content at Dmin; 

θmax=moisture content at Dmax. See text and table 3.
9

The 48 soil samples from ORPI were compacted to high bulk densities over a range of soil 

moisture contents using a Ploog Engineering Co., Inc., automatic soil compactor. The standard method 

outlined in the ASTM standards (ASTMD 698-00a, D2168-02a) was followed. A total of 7 water contents, 

ranging from 0–16 percent by weight, were measured using a standard mold and 3 lifts with 25 blows per 

lift. The resulting curve shows minima at a relatively low soil-water content (typically 2–3 percent) and 

maxima at or near field capacity (8–15 percent). These empirical data typically fit a 3–4 parameter 

polynomial equation, which typically would allow statistical assessments of compaction vulnerability 

based on the coefficients. However, the polynomial fit did not adequately represent the Proctor 

compaction curves, so a cubic-spline curve-fitting routine was used to fit the data and to develop methods 

for statistically comparing these empirical curves.

The maximum bulk density, especially when compared with the undisturbed bulk density, shows 

the magnitude of change that occurs with applied surface pressures; the greater the deviation between 

maximum and undisturbed bulk densities, the more vulnerable the soil to compaction. The differences

between the maximum and minimum bulk densities, as well as the moisture contents of these two values, 

are important measures of compaction vulnerability. This approach was used to develop a scoring system 

of low, medium, and high vulnerability, as used in the qualitative determinations (table 2). 

The difference between maximum and undisturbed densities was scored as:

• 2.0 for (Dmax – DUD)<250 kg/m3

, 

• 2.5 for 250≤(<( Dmax – DUD) ≤)<400 kg/m3, and 

• 3.0 for (Dmax – DUD)>400 kg/m3.

None of the soils sampled had low vulnerability characteristics. Similarly, the difference between 

maximum and minimum bulk densities (Dmax–Dmin) were scored as:

• for (Dmax–Dmin)<18 kg/m3

, 

• 1.5 for 18≤ (<(Dmax–Dmin) ≤)<33 kg/m3, 

• for 33≤ (<(Dmax–Dmin) ≤)<66 kg/m3

, 

• 2.5 for 66≤(<(Dmax–Dmin)<100 kg/m3, and 

• for (Dmax – Dmin)>100 kg/m3

. 

Water content at maximum bulk density (θmax) were scored as:

• for θmax <6% and θmax >16%, 

• for 6< θmax <8% and 14< θmax <16%, and 

• for 8< θmax <14%, and 14< θmax<16%. 

Water content at minimum compaction (θmin) were scored as:

• for θmin <0.5, 

• for 0.5< θmin <1, and 

• for θmin >1%. 

These five scores then were averaged for each sample to obtain a vulnerability rating for each sample, and 

each sample was averaged according to soil map unit to obtain a final vulnerability rating.

For each maximally compacted sample still in the Proctor molds, soil penetration resistance was 

measured using a U.S. Army Corps of Engineers cone penetrometer (Bradford, 1986), model H-4120. 

This hand-held penetrometer measures the pressure required to push the cone 25.41 mm into the 

compacted soil at a constant rate of 3 cm/s (Bradford, 1986). A total of 4 measurements were made for 

each sample at each water content-bulk density pair, and these data were averaged to produce one value of 

penetration resistance. 
10

Table 2. Vulnerability scores for selected laboratory measurements of compaction of soils at Organ Pipe Cactus 

National Monument, southwestern Arizona.

[Abbreviations: kg/m3

, kilogram per cubic meter; =, equals; <, less than; >,greater than; %, percent; –, Dmin=minimum bulk 

density, DUD=undisturbed bulk density, θmin=moisture content at Dmin; θmax=moisture content at Dmax]

Laboratory 

measurement

Low 

vulnerability 

(score=1) (score=1.5)

Medium 

vulnerability 

(score=2.0) (score=2.5)

High 

vulnerability 

(score=3.0)

Folk sorting 

coefficient, σi

<2 – 2–3 – >3

Maximumundisturbed bulk 

density difference 

(Dmax – DUD), 

kg/m3

<250 – 250–400 – >400

Maximumminimum bulk 

density difference 

(Dmax – Dmin), 

kg/m3

<18 18-33 33-63 63-100 >100

Moisture content at 

maximum bulk

density (θmax), %

<6, >16 – 6-8, 14–16 – 8–14

Moisture content at 

minimum bulk 

density (θmin), %

<0.5 – 0.5–1.0 – >1.0

Results

Qualitative Assessment of Soil Compaction Vulnerability

The qualitative assessment of soil compaction vulnerability, based on the SSURGO particle-size 

distributions and the criteria outlined in the section, “Methods,” is shown in table 1 and figure 1. A land 

area of 46,739 ha (35 percent) within ORPI was determined to be highly vulnerable to soil compaction, 

whereas a land area of 64,654 ha (48 percent) was determined to have medium vulnerability to soil 

compaction (table 1).
11

Particle-Size Distributions and Sorting

Most soils that were measured at ORPI were poorly sorted, containing a range of particle sizes. 

The standard soil-texture ternary diagram is inappropriate for these soils because it provides little 

differentiation given the high sand content and low silt-and-clay content of most soils; instead, a ternary 

diagram was used, showing gravel, sand, and silt plus clay to display the particle-size distributions (fig. 4). 

Even with this diagram, most of the ORPI soils plot in the upper part of the diagram, showing more

variation in particle-size distribution among the sites. Folk sorting coefficients (σi) show that soils sampled 

at ORPI are very poorly sorted to extremely poorly sorted with only five poorly sorted samples (fig. 5), 

although more than one-half of the samples were extremely poorly sorted (fig. 5). The particle-size 

distributions suggest that most soils would have high vulnerability to soil compaction in the absence of 

large rocks that might absorb surface pressure.

Figure 4. Ternary diagram showing particle-size distributions for 48 soil samples analyzed for compaction 

vulnerability at Organ Pipe Cactus National Monument, southwestern Arizona.
12

Figure 5. Histogram showing Folk sorting coefficients for soil samples from Organ Pipe Cactus National Monument, 

southwestern Arizona.

Undisturbed Bulk Density and Laboratory Compaction Measurements

All SSURGO soil units present at ORPI were sampled for undisturbed bulk density at ORPI 

(table 3). Bulk densities of undisturbed soils ranged from 1,305 to 1,662 kg/m3, which is the expected 

range for these poorly sorted soils with high gravel content. Some of the lowest bulk densities were 

measured on rocky soils with significant void space at or near the surface because rocks were not cleared 

from the surface prior to measurements. Most of the soils with low gravel contents had undisturbed bulk 

densities of near 1,500 kg/m3

, as expected.

The Proctor compaction analyses resulted in maximum densities ranging from 1,657 to 2,039 

kg/m3 (typical density of rock is 2,650 kg/m3), and minimum densities ranging from 1,528 to 1,969 kg/m3

for 48 soil samples (fig. 6). Moisture contents ranged from 4.3 to 17.3 percent for maximum bulk density, 

and from 0 to 4.8 percent for minimum bulk density. Histograms were created of the differences between 

maximum and undisturbed (Dmax–DUD) and maximum and minimum bulk densities (Dmax–Dmin) (figs. 6A,

B), as well as histograms of maximum and minimum moisture contents (figs. 6C, D). The scoring criteria 

then was applied to rate each soil. Four soils—Antho soils (very gravelly variant), Gachado very cobbly 

loam, Gilman very fine sandy loam (saline), and Torrifluvents—rated a consistent high vulnerability; all 

other soils had various scores ranging from medium to high, but the average score for all high

vulnerability soils was greater than 2.5. 
13

Table 3. Undisturbed dry bulk densities for soils at Organ Pipe Cactus National Monument, southwestern Arizona.

[kg/m3

, kilograms per cubic meter, n = 10 measurements]

Soil map unit

Mean dry bulk 

density

(kg/m3)

Standard 

deviation

Ajo very cobbly sandy loam 1,352 71

Ajo very gravelly loam 1,305 68

Antho fine sandy loam 1,595 53

Antho soils, very gravelly variant 1,556 31

Cherioni gravelly very fine sandy loam 1,548 108

Cipriano gravelly loam 1,362 31

Gachado very cobbly loam 1,486 90

Gilman very fine sandy loam 1,403 66

Gilman very fine sandy loam, saline 1,408 73

Growler-Antho Complex 1,476 49

Gunsight very gravelly loam 1,622 24

Gunsight very gravelly loam 1,388 51

Harqua very gravelly loam 1,662 55

Harqua very cobbly loam 1,491 116

Harqua-Gunsight Complex 1,452 96

Laveen loam 1,507 44

Lomitas very stony loam 1,524 115

Perryville very cobbly fine sandy loam 1,429 83

Perryville very cobbly fine sandy loam 1,407 50

Rillito gravelly sandy loam 1,579 76

Rock land 1,523 73

Rock outcrop 1,406 69

Stony land- Rock outcrop association 1,597 39

Torrifluvents 1,435 160
14

Figure 6. Histograms showing Proctor compaction curves (see fig. 3) for (A) maximum bulk density minus 

undisturbed bulk density (Dmax–Dud), (B) maximum minus minimum bulk density (Dmax–Dmin), (C) water content at 

maximum density, and (D) water content at minimum density, with the scoring system for compaction vulnerability 

shown in groups delineated with dashed lines.
15

Penetration-resistance tests show some problems with using penetrometers to assess soil 

compaction (fig. 7). The maximum penetration resistance typically occurred at low water contents and 

bulk densities than the maximum compaction, indicating interactions among penetration resistance, bulk 

density, and moisture content for each soil particle-size distribution. The average water content for 

maximum penetration resistance was 10.7±2.4 percent (mean ±1 standard deviation), and the moisture 

content for maximum bulk density averaged 11.0±2.0 percent; the paired-sample t-test shows these values 

are not significantly different (df = 47, t = 1.516, p = 0.136). Because penetration resistance is a function 

of particle-size distribution, moisture content, and bulk density, it introduced greater variability when 

compared to bulk density alone. 

A multiple linear regression was done using maximum penetration resistance as the dependent 

variable and Folk sorting coefficient, and bulk density at the maximum resistance and moisture content at 

the maximum resistance as the independent variables. This analysis resulted in the equation:

P=-3.742 – 2.191 ∙ θmin - 0.186 ∙ θmax -0.002 ∙ (Dmax–DUD) +0.082 ∙ (Dmax–Dmin) + 9.689 ∙ σi (3)

with a multiple R2 = 0.244 (df = 44, t = -0.233, p = 0.817). Although this linear regression is not 

significant, it suggests that sorting, as reflected by the Folk σi, has the largest effect on penetration 

resistance.

Quantitative Assessment of Soil Compaction Vulnerability

We averaged the scores by soil for each of the five laboratory results used to reflect compaction 

vulnerability (table 1; figs. 5, 6), resulting in a vulnerability score for each of the 48 soil samples. The 

resulting map (fig. 8) differs significantly from the qualitative assessment of vulnerability (fig. 1) in 

several ways (fig. 9). First, most of the bedrock surfaces, qualitatively rated as low vulnerability, were not 

sampled and could not be scored based on laboratory tests. Second, the vulnerability classifications of 

several soil units shifted as a result of the laboratory analyses; four soils changed from medium to high 

vulnerability, five soils changed from high to medium vulnerability, and one soil changed from low to 

high vulnerability (table 1). 

On the basis of these analyses (fig. 8), 80,870 ha (60 percent) of the 133,800 ha at ORPI has a high 

vulnerability to compaction compared with the 24,655 ha (18.4 percent) determined from qualitative 

assessment (laboratory analyses were not performed on the remaining 21 percent of area with soils). The 

area of high vulnerability soils increased 73 percent from the 46,740 ha assessed qualitatively (table 1). 

The analyses determined that the area of medium vulnerability was 24,655 ha, a decrease from 64,654 ha 

determined qualitatively. Only one low vulnerability soil was sampled, thus precluding statistical analysis. 

Soils over an area of 28,297 ha were not sampled, and two soils qualitatively rated as low vulnerability 

soils were present in this area.
16

Figure 7. Graphs showing maximum soil strength compared to (A) moisture content, (B) bulk density, and (C) Folk 

sorting coefficient, σi.
17

Figure 8. Map showing soil vulnerability to soil compaction based on laboratory measurements, Organ Pipe Cactus 

National Monument, southwestern Arizona.
18

Figure 9. Map showing changes in classifications of soil compaction vulnerability from qualitative (fig. 1) to 

quantitative (fig. 8) assessments, Organ Pipe Cactus National Monument, southwestern Arizona.
19

Discussion and Conclusions

Field and laboratory measurements were used to assess soil vulnerability to compaction from 

applied surface pressure for soils at Organ Pipe Cactus National Monument (ORPI) in southwestern 

Arizona. Our analyses determined that 60 percent of ORPI had soils highly vulnerable to compaction, 18

percent had soils of medium vulnerability, and no areas had low vulnerability, although soils covering 21

percent of the national park unit were not sampled owing to access restrictions or difficult terrain. Results 

from the field and laboratory measurements differed significantly from qualitative assessments of 

vulnerability based on widely available digital soils data (Soil Survey Geographic, or SSURGO), which 

suggests that the easily performed qualitative assessments, although potentially useful as guides for land 

managers, should be tested with quantitative measures. For ORPI, this is underscored by comparing the 

qualitative assessment with the quantitative analysis for Gunsight very gravelly loam, which covers 

24,824 ha (18.6 percent) and changed from a qualitative rating of medium vulnerability to a rating of high

vulnerability on the basis of laboratory analyses (table 1).

Four soils consistently scored as highly vulnerable to compaction in the analyses. Antho soils (very 

gravelly variant), Gilman very fine sandy loam (saline), and Torrifluvents were rated as highly vulnerable, 

both on the qualitative and quantitative assessments. These soils occupy an area of 7,040 ha at ORPI. 

However, the Gachado very cobbly loam, which qualitatively was rated with medium vulnerability, 

became highly vulnerable, but this soil only occupies 621 ha at ORPI. Only one soil—Cipriano gravelly 

loam—was qualitatively and quantitatively rated with medium vulnerability, which shows that field 

variability in compaction characteristics is too high to be assessed with SSURGO data alone.

The SSURGO database—which contains generalized particle-size data in a geospatial framework 

and is available for most of Arizona and much of the continental United States—is both useful and 

problematic in assessing compaction vulnerability. SSURGO provides data averaged over map areas 

(polygons), some of which are very large, and, as a result, these data cannot account for continuous spatial 

variability in surficial soil properties, which can be extreme in desert landscapes. Although as many as

four samples were obtained from a soil at ORPI (table 1), laboratory tests from only one sample typically 

were used to characterize the compaction vulnerability of a soil. The analyses indicate that SSURGO data 

alone are of insufficient resolution to differentiate medium levels from high levels of compaction 

vulnerability. Because of the soils present at ORPI, as well as our ability to sample, we could not reliably

determine if the soils mapped as either well sorted or very rocky within the SSURGO database would rate 

as low vulnerability from field and laboratory data.

The high content of particles greater than 16 mm, (otherwise referred to here as coarse gravel) is

another problem with laboratory assessment of soil vulnerability for coarse desert soils. ASTM testing 

standards require that particles greater than 16 mm b-axis diameter be removed from samples prior to 

Proctor analyses because they have problematic interactions with the compacting hammer in the Proctor 

molds. High concentrations of these particles, however, are expected to reduce compaction vulnerability 

by absorbing applied stress in particle-to-particle contacts instead of pore-space reductions. The change in 

the Gachado very cobbly loam from medium to high vulnerability may be an example of the problems 

experienced with removal of large particles prior to Proctor analyses. Experimental work with soils in the 

field (Webb and others, 2013) may be the solution to this problem, but this type of work is more expensive 

and time consuming than the laboratory analyses described in this paper.
20

Our map showing soil vulnerability to compaction does not consider other adverse effects of 

applied surface pressures. It is unclear whether soils that are highly vulnerable to soil compaction also are 

highly vulnerable to other environmental problems as well, particularly soil-erosion potential. Gilman very 

fine sandy loam, which occurs in northern ORPI, provides a good example. Although laboratory analyses 

indicated it has medium vulnerability to soil compaction, it is the most wind- and water-eroded soil at 

ORPI as a result of long-term grazing, human trampling, and vehicle disturbance (P. Holm, National Park 

Service, written commun., 2012). On the western boundary of ORPI, experimental work conducted in 

2010 found extensive rutting and disruption in this soil while dry (Webb and others, 2013). Rutman (1996) 

found that severe erosion problems occurred in Gilman very fine sandy loam (saline) at several sites in the 

northern part of ORPI, and this saline variant is highly vulnerable to compaction. Further work is required 

to establish if any quantitative connection exists between compaction and erosion vulnerability.

Desert soils have important subsurface properties that must be considered when assessing 

compaction vulnerabilities using laboratory analyses of non-intact soil samples. In the upper 10 

centimeters of their profiles, most intact (uneroded) desert soils have Av (vesicular A) horizons (either 

underlying desert pavement or at the surface) that vary in texture from sandy to silty loams. The vesicles 

in this horizon are macropores that applied surface pressure can easily collapse, particularly when wet, 

creating a dense platy horizon with low infiltration capacity. Mixed with gravel or sand, this zone can be 

highly vulnerable to compaction and differs from soils of more mesic regions. This fine structure cannot 

be preserved for laboratory analyses, and vulnerability to soil compaction must be assessed using field 

experiments.

Management practices designed to minimize adverse environmental effects of surface disturbances 

should consider soil compaction vulnerability analyses as one part of an overall strategy to protect natural 

resources, to plan for their use, and to monitor for potential adverse responses. The biggest problem with 

the approach of this study was the low resolution of geospatial data on soil physical properties as 

illustrated with our experience with SSURGO data at ORPI. High-resolution data on surficial particle-size 

distributions would help to improve geospatial analyses of soil vulnerability to disturbances. 

Acknowledgments

The National Park Service and the U.S. Geological Survey provided funding for this research. We 

thank Sarah M.S. Howard, Ed M. Kuklinski, and Justine L. McCune for their collection of samples at 

ORPI. Helen Raichle helped with field work and provided the geographic information system analyses, 

and Trevor Birt and Margaret Snyder helped with laboratory analyses. Peter Holm provided climate data 

and other background material on Organ Pipe Cactus National Monument. This manuscript was critically 

reviewed by Peter Holm, Jayne Belnap, and three anonymous reviewers.
21

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