Assessment of Rangeland Ecosystem Conditions in 

Grand Canyon-Parashant National Monument, Arizona

Open-File Report 2020–1040

U.S. Department of the Interior

U.S. Geological Survey
Cover. Photograph of the southern part of Whitmore Canyon, Grand Canyon-Parashant National Monument, Arizona. 

Photograph by E.C. Palmquist.
Assessment of Rangeland Ecosystem Conditions in 

Grand Canyon-Parashant National Monument, Arizona

By Michael C. Duniway and Emily C. Palmquist

Open-File Report 2020–1040

U.S. Department of the Interior

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

DAVID BERNHARDT, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2020

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Suggested citation:

Duniway, M.C., and Palmquist, E.C., 2020, Assessment of rangeland ecosystem conditions in Grand Canyon-Parashant 

National Monument, Arizona: U.S. Geological Survey Open-File Report 2020–1040, 42 p., https://doi.org/10.3133/

ofr20201040. 

Associated data for this publication:

Duniway, M.C., and Palmquist, E.C., 2020, Vegetation and soils data from an assessment of rangeland ecosystem 

conditions in Grand Canyon-Parashant National Monument, Arizona. U.S. Geological Survey data release, 

https://doi.org/10.5066/P9SJSJHT.

ISSN 2331-1258 (online)
iii

Acknowledgments

We would like to acknowledge the advice and support provided to us by the National Park 

Service and Bureau of Land Management staff, specifically Brandon Boshell and Jennifer Fox. 

Additionally, we had outstanding field assistance on this project from Erika Geiger, Lauren 

Mitchell, Henry Grover, Nick Kainrath, John Kao, Austin Rutherford, Paige Stuart, and Nora 

Talkington. 

We would also like to thank Mark Miller for initiating this important project and providing early 

input into the design. Thanks also to Walt Fertig for assistance with plant identification. This 

work was funded by the Grand Canyon-Parashant National Monument and the U.S. Geological 

Survey Ecosystems Mission Area. 
iv

Contents

Acknowledgments........................................................................................................................................iii

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

Introduction.....................................................................................................................................................2

Materials and Methods.................................................................................................................................4

Study Location.......................................................................................................................................4

Site and Plot Selection.........................................................................................................................6

Vegetation and Soil Assessments......................................................................................................8

Data Analyses......................................................................................................................................10

Results ...........................................................................................................................................................12

Soils, Ecological Sites, and Vegetation Communities Sampled..................................................12

Trends Across Elevation ...................................................................................................................16

Cattle Use.............................................................................................................................................19

Low Desert...........................................................................................................................................20

Landscape Setting, Soils, and Rangeland Indicators..........................................................20

Ordinations..................................................................................................................................23

Middle Desert......................................................................................................................................24

Landscape Setting, Soils, and Rangeland Indicators..........................................................24

Ordinations..................................................................................................................................27

High Desert and Forest and Savanna .............................................................................................28

Landscape Setting, Soils, and Rangeland Indicators..........................................................28

Ordinations..................................................................................................................................32

Discussion.....................................................................................................................................................34

Patterns in Rangeland Health Indicators........................................................................................34

Invasive Species.................................................................................................................................34

Soils, Topography, and Ecosystems.................................................................................................34

Evidence of Cattle Impacts ...............................................................................................................35

Conclusion.....................................................................................................................................................36

Appendix 1. Identification of Hydrologically Enhanced Areas.............................................................43
v

Figures

1. Map showing the study area in the Grand Canyon-Parashant National Monument in 

the southwestern United States.................................................................................................3

2. Plots showing the study area average monthly climatic conditions and weather 

 deviation from normal for 2011–14.............................................................................................5

3. Maps of topographic-geomorphic units showing allotment and study 

 area boundaries............................................................................................................................6

4. Maps of soil-geomorphic strata used for locating plots in the study area.........................7

5. Maps showing example variable probability surfaces created for the eastern 

 allotments in the study area.............................................................................................................9

6. Maps showing the distribution of identified ecological site groups..................................11

7. Maps showing the spatial distribution of community clusters...........................................16

8. Plots showing trends in indicators of soil and site stability and hydrologic function

 with elevation ..............................................................................................................................17

9. Plots showing trends in indicators of biotic integrity with elevation.................................18

10. Plots showing the relation between observed cow dung frequency and 

 cost-distance to water, predicted forage production, and plot ruggedness index.........19

11. Plots characterizing the low desert ecological site groups................................................21

12. Plots showing fractional cover of the low desert ecological site groups ........................22

13. Plot showing correlations between rangeland health indicators, ordination axes, 

 and landscape setting, soil, and cattle factors for low desert settings ............................23

14. Plots characterizing the middle desert ecological site groups ..........................................25

15. Plots showing fractional cover of the middle desert ecological site groups...................26

16. Plot showing correlations among rangeland health indicators, ordination axes, 

 and landscape setting, soil, and cattle factors for middle desert settings.......................27

17. Plots characterizing the high desert and forest and savanna ecological

 site groups ...................................................................................................................................29

18. Plots showing fractional cover of the high desert and forest and savanna 

 ecological site groups................................................................................................................30

19. Plots showing correlations between rangeland health indicators, ordination axes, 

 and landscape setting, soil, and cattle factors for high desert and forest and 

 savanna settings.........................................................................................................................31
vi

Tables

1. Indicators of rangeland health, association with attributes, and brief description..........2

2. Study area allotments, size, permitted stocking rates, and season of use ........................5

3. Topographic classes and geologic parent material used in stratified random 

 sampling design and extent mapped in study area ...............................................................7

4. Final distribution of plots sampled by allotment and topographic-geologic grouping .....8

5. Landscape setting, soil, and cattle use variables hypothesized to control indicators 

 of rangeland health and community ordinations...................................................................11

6. Ecological site groups identified in the study area...............................................................13

7. Floristic groups identified in the study area...........................................................................14

8. Cross tabulation of ecological site groups and cluster analysis floristic groups............17

9. Richness and diversity indices for climate zones and floristic groups within .................18

10. Parameter estimates from multiple quantile regression estimating the 90-percent 

 quantile of cattle dung frequency in active grazing allotments..........................................21

11. Floristic groups in the low desert climate zone identified by cluster analysis and 

 indicator species analysis.........................................................................................................24

12. Floristic groups in the middle desert climate zone identified by cluster analysis and 

indicator species analysis.........................................................................................................28

13. Floristic groups in the high desert climate zone identified by cluster analysis and 

 indicator species analysis.........................................................................................................32

14. Floristic groups in the forest and savanna climate zone identified by cluster 

 analysis and indicator species analysis .................................................................................33
vii

Conversion Factors

U.S. customary units to International System of Units

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

acre 4,047 square meter (m2)

acre 0.4047 hectare (ha)

acre 0.4047 square hectometer (hm2) 

acre 0.004047 square kilometer (km2)

square foot (ft2) 929.0 square centimeter (cm2)

square foot (ft2) 0.09290 square meter (m2)

square inch (in2) 6.452 square centimeter (cm2)

square mile (mi2) 259.0 hectare (ha)

square mile (mi2) 2.590 square kilometer (km2) 

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

 °F = (1.8 × °C) + 32.

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

°C = (°F – 32) / 1.8.
viii

Abbreviations

BLM Bureau of Land Management

ca. circa

cm centimeters

CRA Conservation Resource Area

DEM Digital Elevation Model

DIMA Database for Inventory, Monitoring, and Assessments

ESD ecological site description

ESG ecological site groups

GMP/RMP Joint NPS Grazing Management Plan/BLM Resource Management Plan

GPS Global Positioning System

GRTS general randomized tessellation stratification 

ha hectares

LPI line point intercept

m meters

mm millimeters

MLRA Major Land Resource Area

N number

NMS nonmetric multidimensional scaling 

NPS National Park Service

NRCS Natural Resources Conservation Service

p probability value

r correlation coefficient

spp. species

TWI topographic wetness index

USDA U.S. Department of Agriculture

USGS U.S. Geological Survey
Assessment of Rangeland Ecosystem Conditions in 

Grand Canyon-Parashant National Monument, Arizona

By Michael C. Duniway and Emily C. Palmquist

Abstract

Sustainability of dryland ecosystems depends on 

the functionality of soil-vegetation feedbacks that affect 

ecosystem processes, such as nutrient cycling, water 

capture and retention, soil erosion and deposition, and plant 

establishment and reproduction. Indicators that represent 

these fundamental processes are central to many approaches 

for ecosystem assessment and monitoring in drylands—

collectively they are referred to as “rangeland health.” 

Evaluation of rangeland health relies on describing the 

condition and sustainability of these individual, measurable, 

or observable indicators that are linked to important 

ecosystem processes. Useful, common indicators can provide 

information on soil and site stability, hydrologic function, 

and biotic integrity. Quantitative approaches to rangeland 

health evaluations allow for robust and reliable evaluations 

of trends through time (that is, monitoring) and serve as the 

basis for several national rangeland monitoring programs. 

However, management-relevant interpretations of rangeland 

health assessments require contextual information on how 

soils, landscape, and climate setting are shaping ecosystem 

qualities and some estimate of what constitutes target values 

of a healthy system. 

The approximately one-million-acre Grand CanyonParashant National Monument is located in the northwest 

corner of Arizona and co-managed by the Bureau of Land 

Management (BLM) and National Park Service (NPS). 

This report focuses on the circa (ca.) 200,000 acres of NPSadministered lands in the monument—one of the largest NPS 

units where livestock grazing is a permitted land-use activity. 

Many ecosystems in the monument are characterized by a 

low degree of resilience to improper grazing because of low 

and variable precipitation. Grand Canyon-Parashant National 

Monument is marked by a high degree of environmental 

heterogeneity, including a large elevation gradient, widely 

differing precipitation patterns, a diversity of geologic 

substrates, and unique combinations of plant species. 

The objective of this report is to (1) increase our 

understanding of the underlying landscape, soil, and climate 

setting factors that affect Grand Canyon-Parashant National 

Monument dryland ecosystem structure and function (also 

referred to as land potential) and (2) characterize the condition 

of Grand Canyon-Parashant National Monument ecosystems 

in relation to management concepts, such as rangeland health. 

The results discussed here on ecosystem condition, coupled 

with the increased understanding of soil-geomorphic controls 

on vegetation distribution within Grand Canyon-Parashant 

National Monument, provide information to help managers 

develop appropriate livestock management strategies. 

Locations for rangeland assessments were selected using 

a stratified, spatially balanced random sampling method based 

on allotment, soil type, slope, distance to cattle water locations, 

and accessibility. A total of 155 plots were established and 

sampled between March and November of 2012 and 2013. 

Data collection at each plot included soil-geomorphic setting 

descriptions, plant and soil cover, and soil aggregate stability. 

Data were analyzed by elevation zone using both univariate 

and multivariate approaches. Survey results document the high 

level of diversity within the study area, including 15 unique 

soil taxa (to great group level) and 271 species of plants. We 

collected three new plant species for Grand Canyon-Parashant 

National Monument and 17 new species for the NPS portion of 

Grand Canyon-Parashant National Monument. 

Results also document a strong association between 

rangeland health indicators and elevation, topographic setting, 

and soils. Soil factors found to explain important variation 

across plots include the amount of exposed bedrock, soil 

rockiness, soil texture (and associated hydrologic properties), 

and soil depth. We also found that dominant species turnover 

across elevation may represent species’ differences in 

adaptation to climates, including Larrea tridentata, Coleogyne 

ramosissima, and Artemisia spp. Bromus rubens is the most 

common invasive species of concern recorded in this study, 

but other common invasive species are Bromus tectorum, 

Erodium cicutarium, and Schismus arabicus. Correlations 

between an index of cattle use and indicators of rangeland 

health suggest that areas with high cattle use have increased 

bare ground, decreased ground cover, increased frequency 

of Schismus arabicus, decreased cover of Coleogyne 

ramosissima and Ephedra spp., and increased cover of 

Gutierrezia spp. The few strong correlations observed between 

indicators of vascular plant community cover or abundance 

and indicators of cattle activity support rangeland assessment 

and monitoring strategies that do not rely solely on plantbased indicators are needed. 
2 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

This work supports management of dryland ecosystems, 

including Grand Canyon-Parashant National Monument, 

using concepts of land potential. Land-potential-based 

classification systems use climate, soils, and topographic 

properties to classify landscapes based on potential 

productivity, composition, and response to climate and 

management. We conclude the report with recommendations 

on improving existing land-potential-based classification 

systems, associated interpretations, and methods for moving 

forward with a Grand Canyon-Parashant National Monument 

rangeland monitoring program. 

Introduction

Sustainability of dryland ecosystems, including 

ecosystem resilience to climate disturbances and 

anthropogenic stressors, depends on ecosystem capacity 

for capturing and retaining scarce resources (Whitford, 

2002). This capacity is largely controlled by soil-vegetation 

feedbacks that affect ecosystem processes, such as nutrient 

cycling, water capture and retention, and soil erosion and 

deposition, as well as plant demographic processes, such 

as establishment and reproduction (Tongway and Ludwig, 

1997; Whitford, 2002). Because of their importance for the 

functionality and dynamics of dryland ecosystems, as well 

as their sensitivity to land-use impacts (Tongway and others, 

2003; Neff and others, 2005), indicators of these processes 

are central to many approaches for ecosystem assessment 

and monitoring in drylands and collectively referred to as 

“rangeland health” (National Research Council, 1994; Pyke 

and others, 2002; Tongway and Hindley, 2004; Herrick and 

others, 2005; Pellant and others, 2005).

Evaluation of rangeland health does not rely on one 

single response variable, but rather a suite of fundamental 

attributes that describe the condition and sustainability of 

drylands. Three attributes are increasingly recognized as 

fundamental to condition and sustainability: soil and site 

stability, hydrologic function, and biotic integrity (National 

Research Council, 1994; Pyke and others, 2002). Soil 

and site stability refers to the capacity of a plot or area to 

minimize redistribution and otherwise retain soil resources 

against the erosive forces of wind and water. Hydrologic 

function pertains to a plot or area’s ability to capture, store, 

and safely release incoming precipitation or overland flow. 

Biotic integrity refers to a plot or an area’s biotic community, 

including plants, animals, insects, and soil biota, and its ability 

to support ecological processes and recover these processes 

when disturbed. Assessment of rangeland health attributes 

uses individual, measurable indicators that are linked to 

important ecosystem processes, such as amount of foliar cover 

or exposed bare ground. Evaluation of the three attributes of 

rangeland health utilizes both qualitative assessments (Pyke 

and others, 2002; Herrick and others, 2010) and quantitative 

approaches (Herrick and others, 2005; Duniway, Herrick, and 

others, 2010; Duniway and Herrick, 2013) (table 1). 

Quantitative approaches to rangeland health evaluations 

allow for robust and reliable evaluation of trends through time 

(monitoring) and serve as the basis for several national and 

regional rangeland monitoring programs (Nusser and Goebel, 

Table 1. Indicators of rangeland health, association with attributes, and brief description (adapted from Pellant and others [2005] and 

Duniway, Herrick, and others [2010]).

[SSS, soil and site stability; HF, hydrologic function; BI, biotic integrity; cm, centimeters; mm, millimeters; m2, square meters]

Quantitative indicator Expected 

correlation1

Attribute

Description SSS HF BI

Basal gaps >200 cm − ● ● Fraction of plot in basal gaps >200 cm

Canopy gaps >100 cm − ● ● Fraction of plot in canopy gaps >100 cm

Bare ground − ● ● Fraction of plot with no foliar, litter, or soil cover

Ground cover + ● Fraction of plot with ground cover (biological soil crust, litter, rock, basal)

Biological soil crust + ● Summed cover of dark cyanobacteria, lichen, and moss

Lichen + ● ● Fractional soil cover of lichens

Moss + ● ● Fractional soil cover of mosses

Soil surface (top few mm) 

resistance to erosion

+ ● ● ● Average soil aggregate stability index (1–6) measure of water stable 

aggregates 

Functional/structural groups +/− ● ● Fractional cover by plant life form and duration

Species cover +/− ● Species diversity and fractional cover of important native species

Litter cover + ● ● Fractional cover of litter (herbaceous or woody)

Total foliar cover + ● Total fraction of plot with foliar cover

Invasive species − ● Rooted frequency (1 m2 quadrat) of species of concern

1

Expected correlation (positive, negative, or both) with indicators of rangeland health.
Introduction 3

1997; Toevs and others, 2011; National Park Service, 2016), 

though this type of approach can be difficult to implement for 

some soil and site stability and hydrologic function indicators 

(Duniway, Herrick, and others, 2010). Standard methods for 

collecting rangeland data that allow for quantitative estimates 

of rangeland health indicators are now well established 

(Herrick and others, 2005; Toevs and others, 2011) and widely 

used. These quantitatively derived indicators can be then 

used for management-relevant interpretations, such as datadriven state-and-transition models (Miller and others, 2011), 

evaluating risk of accelerated erosion (Webb and others, 

2014), and detection of leading indicators of state change 

(Bestelmeyer and others, 2013). However, interpretation of 

indicator values and meaningful assessment of rangeland 

health attributes requires contextual information on how soils, 

landscape, and climate setting are shaping ecosystem qualities 

and some estimate of what constitutes target values of a 

healthy system.

Risks of persistent, undesirable changes in ecosystem 

structure and function are dependent on inherent properties 

that confer resistance and resilience to drivers of change, 

as well as the degree of exposure to drivers (for example, 

livestock grazing; Archer and Stokes, 2000; Herrick and 

others, 2006). Whereas ecosystem resistance and resilience 

can change in relation to varying climatic conditions and 

dynamic ecosystem properties affected by climate, land use, 

and management (Bestelmeyer and others, 2015), they are also 

strongly controlled by ecosystem properties that are generally 

stable through time. Inherent soil properties (for example, rock 

content, texture, depth, mineralogy) and geomorphic setting 

are among the most important factors controlling ecosystem 

resistance and resilience to land-use activities (Duniway, 

Bestelmeyer, and others, 2010), but specific relations between 

soil-geomorphic properties and ecosystem dynamics are poorly 

understood on a regional basis (Duniway and others, 2016). 

The Grand Canyon-Parashant National Monument is 

one of the largest National Park Service (NPS) units where 

livestock grazing is a permitted land-use activity (fig. 1). The 

Bureau of Land Management (BLM), which co-manages 

the monument, administers nine allotments on the NPS 

portion of the monument, some of which are closed to 

grazing and some of which are actively grazed. Like many 

arid regions globally, some ecosystems in Grand CanyonParashant National Monument are characterized by a low 

degree of resilience to improper grazing. Unique to Grand 

Canyon-Parashant National Monument is the high degree 

of environmental heterogeneity encompassed by these nine 

allotments. Situated on the northwestern edge of the Grand 

Canyon, these allotments contain a large elevation gradient, 

widely differing precipitation patterns, a diversity of geologic 

substrates, and unique combinations of plant species. This 

area is also remote and difficult to travel in. Combined, 

these ecosystem characteristics make this area particularly 

complex to understand and therefore manage. Despite the 

broad spatial extent of grazing activity in Grand CanyonParashant National Monument, and the sensitivity of dryland 

ecosystems to associated impacts, monument managers 

have little information regarding effects of past and current 

livestock grazing on the condition of rangeland resources 

within the monument. 

Rigorous scientific information documenting the current 

condition of rangeland ecosystems in relation to land use 

and climate is needed to make progress towards achieving 

resource protection goals (for example, those identified in the 

2008 joint NPS General Management Plan/BLM Resource 

Management Plan for the monument [GMP/RMP]). One goal 

specifically called for in the GMP/RMP is the identification 

of “vital signs” (indicators and attributes of ecosystem 

health) and the implementation of a long-term program to 

monitor vital signs as a means of evaluating grazing effects 

on vegetation, soil, and watershed conditions. The GMP/RMP 

prescribes an adaptive management approach to grazing, 

whereby monitoring results are evaluated against applicable 

indicators and associated standards and are used to refine 

NPS and BLM grazing management. Refinement may include 

changes to season of use or timing, rest, grazing intensity, 

more active herd management within pastures, deferment, 

or other actions. Adaptive management would be aimed 

at retaining or restoring ecosystem resilience and resource 

sustainability while minimizing risks of impairment to 

resources or ecological processes. 

This project focuses on two scientific issues: (1) 

understanding the underlying landscape, soil, and climate 

setting factors that affect Grand Canyon-Parashant National 

Figure 1. Map showing the study area in the Grand CanyonParashant National Monument in the southwestern United States. 

The monument is outlined in dark green. Land management 

agency boundaries are shown in light green. Natural Resources 

Conservation Service (NRCS) Major Land Resource Areas and 

Land Resource Units within the study area are shown by various 

colors (Lindsay and others, 2003; Natural Resources Conservation 

Service, 2006); land resource codes are defined in table 3. Black 

dots indicate weather station locations. NRA, National Recreation 

Area; NP, National Park; km, kilometers.
4 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

Monument dryland ecosystem structure and function (also 

referred to as land potential) and (2) characterizing ecosystem 

condition in relation to management concepts, such as 

rangeland health. This assessment project aims to provide 

information required to facilitate prioritization for restoration, 

monitoring, or other activities that support resource protection 

goals and thereby allow for further evaluation of the adequacy 

of current grazing management practices on NPS lands. The 

specific objectives of this work were to collect rangeland 

ecological condition inventory data from the nine allotments 

within the NPS-managed portion of the monument, provide 

interpretations on these results as they pertain to monument 

management, and include some suggestions for the next steps. 

The results included here on ecosystem condition, coupled 

with the increased understanding of soil-geomorphic controls 

on vegetation distribution within Grand Canyon-Parashant 

National Monument, will enable managers to develop 

appropriate livestock management strategies. 

Materials and Methods

Study Location

Field studies were conducted on NPS-administered 

lands within Grand Canyon-Parashant National Monument 

(fig. 1). This area comprises more than 200,000 acres 

(80,937 hectares [ha]) of the approximately 1,000,000-acre 

(404,686 ha) monument located in the northwest corner 

of Arizona. This area is bordered on the south and east 

by Grand Canyon National Park, to the north by BLMadministered lands of Grand Canyon-Parashant National 

Monument, and to the west by the BLM’s Southern Nevada 

District and Lake Mead National Recreation Area. Elevation 

ranges from approximately 400 to more than 2,000 meters 

(m). The low-elevation western side of the study area is 

characterized by Mojave Desert flora (Major Land Resource 

Area [MLRA] 030, Mohave Basin and Range; Natural 

Resources Conservation Service, 2006). The eastern side of 

the study area is dominated by large canyon benches with 

diverse vegetation communities because of the influence of 

the Mojave Desert, the Great Basin, and the Sonoran Desert, 

and to a lesser degree the Colorado Plateau (MLRA 035). The 

high-elevation parts in the center of the study area are largely 

pinyon-juniper stands with some ponderosa pine occurring in 

patches. Of the 1,095plant species recorded in Grand CanyonParashant National Monument to date, 681species are listed 

for the NPS-managed land, of which 135 only occur on NPSmanaged lands, and new species records are regularly reported 

(Hildebrand and Fertig, 2012). Climate regimes vary from 

arid in the low reaches to mesic at high elevations. Average 

annual precipitation ranges from 204 to 405 millimeters (mm). 

Low elevation areas are warm to hot (monthly average ranges 

from a low of 8 °C in December to a high of 32 °C in July) 

and higher reaches of Grand Canyon-Parashant National 

Monument are cool to cold (monthly average ranges from a 

low of −1.4 °C in December to a high of 21 °C in July) with 

significant snow accumulation in some winters (fig. 2).

The monument straddles the Colorado Plateau and 

Great Basin physiographical provinces, separated by the 

Grand Wash Cliffs (Billingsley and others, 2004). Eastern 

Grand Canyon-Parashant National Monument falls within 

the Colorado Plateau (the Sanup and Shivwits Plateaus) and 

is dominated by structural benches and mesas formed from 

Paleozoic limestones, sandstones, and gypsiferous mudstones. 

Soils in these settings are formed from residuum, colluvium, 

and alluvium of varying geologic sources. To the west of the 

Grand Wash Cliffs lies the lower Basin and Range Province 

(Grand Wash trough), which is dominated by Tertiary and 

Quaternary sedimentary deposits (Billingsley and others, 

2004). There are several prominent Tertiary-aged basalt flows 

that occur in both the western and eastern parts of the study 

area (Billingsley and others, 2004). The diversity of climatic 

conditions and variety of geologic substrate of Grand CanyonParashant National Monument together have produced a wide 

range of soil types. The most recent soil survey (Lindsay and 

others, 2003), though done at a coarse scale (1:24,000 scale 

mapping), includes 65 unique soil map unit components in the 

study area. 

As in much of the western United States, grazing in this 

area has been an important land-use activity since the 1880s 

(Rider and Paulsen, 1985; Godfrey, 2008) with likely profound 

ecosystem impacts (Fleischner, 1994). Prior to the Taylor 

Grazing Act of 1934, grazing across the western United States 

was largely unregulated, with stocking rates generally higher 

than sustainable (Godfrey, 2008). After the establishment 

of the BLM and subsequent grazing management, stocking 

rates have generally been reduced. Grazing in low-elevation 

areas on the west side of Grand Canyon-Parashant National 

Monument is typically permitted year round, and, because of 

low forage availability, at fairly low intensities. In the midelevation areas, grazing occurs during the winter and into 

early summer. High elevation reaches were used historically 

in the summer (table 2). The study area is currently divided 

into nine allotments, some of which are separated into 

pastures for grazing management. There are several allotments 

where grazing does not currently occur. These include the 

Tassi allotment on the western edge, in which cattle use was 

disallowed in 2001 because of endangered species concerns 

(Gopherus agassizii; fig. 3). There were several wild burro and 

trespassing cattle in the Tassi allotment, but most cattle were 

rounded up in 2013. In the eastern study area, one allotment 

(Lone Mountain) has not experienced appreciable grazing by 

domestic livestock because of inaccessibility, however we 

were not able to collect field data from this allotment. Finally, 

there has been no domestic grazing in the Home Ranch 

allotment since 2003. 
Materials and Methods 5

Figure 2. Plots showing the study area average monthly climatic conditions (A and B) and weather deviation from normal 

for 2011–14 (C and D). Weather deviation is shown for one year prior to and during the two-year sampling period (sample 

periods indicated by gray fill). Plots A and C show data from a low-elevation weather station (884 meters; Olaf Knolls in 

fig. 1). Plots B and D show data from a high-elevation weather station (1,878 meters; Yellow John in fig. 1). Data from the 

Western Regional Climate Center (http://www.wrcc.dri.edu); long-term average based on the record period from 1985 to 

2016. mm, millimeters; °C, degrees Celsius.

Table 2. Study area allotments, size, permitted stocking rates, and season of use.

[Data from Bureau of Land Management Rangeland Administration System Reports, accessed June 25, 2019, at https://reports.blm.gov/reports/RAS. Billed 

animal unit months (AUMs) are averaged for 1990 to 2014; data accessed October 15, 2015, at https://reports.blm.gov/reports/RAS. NA, not applicable]

Allotment Area, in hectares1 AUMs2 Billed AUMs3 Season of use

Big Spring Pipeline 23,358 2,789 1,266 Year round4

Dripping Spring 4,690 448 323 Nov.–May

Home Ranch 30,890 - 1,152 NA

Mt. Trumbull 13,463 1,825 1,175 Year round

Mule Canyon 7,022 585 338 Nov.–May5

Pa’s Pocket 3,518 479 276 Dec.–Apr.6

Red Pond 22,280 2,508 1,144 Year round

Tassi 45,150 - 1,024 NA

1

Hectares totaled within allotment corresponding to AUMs from Rangeland Administration System Reports. 

2

Animal unit months, based on authorized use as of June 25, 2019. 

3

Dripping Spring data missing 2003–2005, Pa’s Pocket data only available 2001–2014, Home Ranch data ends in 2003, and Tassi data ends in 2000.

4

Numbers reduced by about one-third for Oct.–Feb.

5

Numbers reduced by about one-third for Mar.–May.

6

Numbers reduced by about one-third for Mar.–Apr.
6 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

Figure 3. Maps of topographic-geomorphic units showing allotment and study area boundaries. Soil-geomorphic units 

based on soil survey map unit descriptions (Lindsay and others, 2003). Map inset shows the part of the Grand CanyonParashant National Monument that the National Park System administers (outlined in green). km, kilometers.

Site and Plot Selection

To account for the high degree of heterogeneity 

imposed by abiotic factors in the study area, we employed 

a stratified random sampling scheme based on climate, soil, 

and topographic factors. We first attempted to use Natural 

Resources Conservation Service (NRCS) ecological site 

descriptions (ESDs), which are assigned to soil survey 

map unit components (Lindsay and others, 2003; Duniway, 

Bestelmeyer, and others, 2010). However, there were too 

many unique ESDs in the study area to use as strata (N >60). 

Given the importance of soil parent material and topographic 

setting in controlling dryland ecosystem dynamics, we used 

geologic parent material groups and topographic setting as 

soil-geomorphic strata. We used the soil parent material data 

(as described in the soil survey map units; Lindsay and others, 

2003), to create three geologic groups (table 3). Given the 

importance of slope in governing plant community dynamics 

and cattle distribution, we further subdivided soil map units by 

slope (into three groups). Slope and other terrain derivatives 

were calculated using Spatial Analyst in Esri’s ArcGIS ver. 

10.1 and a 10-m digital elevation model (DEM) from the 

U.S. Geological Survey (USGS) National Elevation Dataset 

(https://nationalmap.gov). 

To capture areas that are likely more productive, and 

therefore important from a livestock forage perspective, we 

used a simple supervised classification approach to pick out 

shallow slope areas (<8°) that likely accumulate overland 

flow from the surrounding landscape (“run-in”) (Rango and 

others, 2006). Methods used to map these hydrologically 

enhanced areas are described in appendix 1. To further reduce 

the number of strata, we did not cross slope and topographic 

setting with parent material for the run-in and steep-slope 

strata (fig. 3). For both run-in and steep-slope locations, we 

anticipated that the influence of topographic setting would 

most often overwhelm that of surficial geology. 

To ensure an adequate number of study plots in each 

livestock management unit, we further stratified our sampling 

by Grand Canyon-Parashant National Monument allotment. 

Two allotments spanned large precipitation gradients (Big 

Spring Pipeline and Pa’s Pocket) and for these two allotments 

we further divided the strata by zones identified in the soil 

survey (Common Resource Areas [CRAs] precipitation 

zones: 6–10, 10–14, 13–17, and 17–25 inches annually; 

fig.1). Sample draws were done for each strata within eac

allotment separately using the general randomized tessellation 

stratification (GRTS) method to generate random, spatially 

balanced plot locations (Stevens and Olsen, 2004) with the 

geostatistical analysis tools in ArcGIS ver. 10.1. Not all strata 

occurred in each allotment, resulting in a variable number of 

strata in each allotment (fig. 4). We allocated more sampling 

effort to large allotments and landscape settings likely to 

receive high use by livestock (run-in and other shallow-slope 

sites; table 4). The GRTS approach provides a random order of 

selection for each sample draw, allowing users to not sample 

all selected points either because of predefined rejection 

criteria or inadequate time. 

We used a variable probability surface with a 10-m pixel 

size (snapped to the DEM) within each allotment and strata 

to increase the probability of obtaining a grazing gradient in 
Materials and Methods 7

Table 3. Topographic classes and geologic parent material used in stratified random sampling design and extent mapped in study area 

(in hectares).

Topographic class Geologic parent 

material 030X1 035C2 035E3 035F4 035H5 Total

Shallow slopes (<8°) 2,951 3,581 8,298 24,145 2,039 45,905

Run-in 2,325 719 2,202 4,992 966 11,204

Mixed geology 212 5,104

Basalt 51 219 954 11,722 12,946

Gypsiferous 518 1,756 2,274

Sedimentary 58 2,644 3,173 7,430 1,073 14,377

Medium slopes (8° to 19.5°) 11,589 6,580 14,938 5,344 43 38,495

Mixed geology 6,993 6,993

Basalt 53 586 902 1,880 3,422

Gypsiferous 476 543 1,019

Sedimentary 349 1,815 6,194 2,288 39 10,685

Steep slopes (>19.5°) 3,718 4,178 7,299 1,176 4 16,375

Total 19,432 10,161 23,236 29,489 2,082 84,400

1

030X, Mohave Basin and Range, elevations range from 400 to 3,000 feet and precipitation averages 6 to 10 inches per year.

2

035C, Colorado Plateau, elevations range from 4,500 to 6,000 feet and precipitation averages 10 to 14 inches.

3

035E, Colorado Plateau, elevations range from 1,600 to 4,500 feet and precipitation averages 6 to 10 inches per year.

4

035F, Colorado Plateau, elevations range from 5,500 to 7,000 feet and precipitation averages 13 to 17 inches per year.

5

035H, Colorado Plateau, elevations range from 6,800 to 8,500 feet and precipitation averages 17 to 25 inches per year. 

Figure 4. Maps of soil-geomorphic strata used for locating plots in the study area (locations sampled indicated by black 

dots). The geologic parent material classes were based on soil map unit descriptions and terrain subdivisions based 

on digital elevation model analyses. Map inset shows the part of the Grand Canyon-Parashant National Monument, 

northwestern Arizona, that the National Park System administers (outlined in green). km, kilometers.
8 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

Table 4. Final distribution of plots sampled by allotment and topographic-geologic grouping.

Topographic class Geologic parent 

material

Big Spring 

Pipeline

Home 

Ranch Mt. Trumbull Mule Canyon

Pa’s 

Pocket

Red 

Pond Tassi Total

Shallow slopes (<8°) 18 26 9 2 15 9 18 97

Run-in 7 10 4 5 4 8 38

Basalt 8 4 12

Gypsiferous 3 3

Mixed 11 3 7 21

Sedimentary 8 5 2 3 5 23

Medium slopes (8° to 19.5°) 7 5 3 1 8 4 6 34

Basalt 2 2 4

Mixed 7 3 6 16

Sedimentary 3 3 1 3 4 14

Steep slopes (>19.5°) 2 1 2 2 2 2 11

Mixed slopes 7 6 13

Basalt 3 3

Gypsiferous 4 2 6

Middle bench 4 4

Total 27 32 21 3 25 15 32 155

our sample and to increase efficiency of field work. This was 

done because of the large size of each allotment (table 2) and 

the importance of landscape features and distance to water 

for governing cattle distribution in arid rangelands (Bailey 

and others, 1996). Distance to water was used as a proxy for 

likely grazing intensity and distance to accessible roads was 

used to estimate field sampling costs. For both distance to 

water and distance to roads, we created a cost-distance model 

that considered impassible cliffs and terrain steepness using 

the Spatial Analyst extension in ArcGIS. Cliffs were defined 

using a ruggedness index (Riley and others, 1999) where cells 

with ruggedness >2.3 were defined as impassible; for distance 

to water, allotment fence lines were defined as impassible. 

The monument is characterized by remote and rugged terrain. 

To increase efficiency of field work, we used the same travelcost surface as used for grazing intensity to calculate distance 

from roads for field sampling. For each strata within each 

study area allotment, we created one variable probability 

surface based on these two cost-distance models. The goal 

of the livestock cost-distance to water model was to increase 

the likelihood of obtaining samples from varying distances 

to water (even if those distances are not evenly represented 

on the landscape). This was achieved by binning the data 

for each strata and then making the selection probability 

inversely proportional to the area represented by each 

bin (scaled from >0 to <1). For the distance from roads 

probability, we scaled the cost-distance values for each strata 

from near zero (very far from roads) to near 1 (very near 

roads). These two probability surfaces were then averaged, 

and the final probability sampling surface represents a 

compromise between obtaining a grazing gradient and 

increasing field work efficiency (fig. 5).

Vegetation and Soil Assessments

A total of 155 plots were established and sampled 

between March and November of 2012 and 2013 (table4, 

fig. 4). Mojave Desert sites were sampled in the early 

spring (March and April), high-elevation pinyon-juniper 

and ponderosa sites were sampled May through July, and 

the eastern canyon benches were sampled between August 

and October. Each 50×50-m plot consists of three parallel 

50-m transects spaced 25 m apart. Transects were placed so 

that they followed the topography, with transects following 

topographic contours rather than running up or down slope. 

Plots were marked with blue painted rebar at each end of the 

center transect. The locations of all transect ends and the plot 

centers were recorded by Global Positioning System (GPS; 

Garmin eTrex, Vista HCx, accuracy 3 m). Six plots intended 

for sampling were not established because the slopes were too 

steep to work on safely (four plots) or they were inaccessible 

(two plots). Only three plots were established in Parashant 

Canyon and no plots were established in Andrus Canyon 

and the surrounding benches (Mule Canyon and Dripping 

Spring allotments) because of extensive road damage during 

the sampling period in both 2012 and 2013. No plots were 

established in Lone Mountain owing to inaccessibility. 

At each study plot, the NRCS soil map unit component 

was determined using soil properties and geomorphic setting 

(Lindsay and others, 2003). At a representative location near 

the plot center, a small soil pit or auger hole was excavated to a 

depth of at least 50 centimeters (cm) in rocky soils and 100 cm 

in nonrocky soils or until a restrictive layer was reached. Soil 

pedogenic horizons were identified and described following 

Schoeneberger and others (2012). Soil properties descriptions 
Materials and Methods 9

include soil textural class, clay percentage, effervescence in 

response to 1 normal HCl, coarse fragment content (percentage 

by volume), and carbonate stage. Structure (shape, grade, and 

size) was added in 2013 for horizons occurring within ~30 cm 

Figure 5. Maps showing example variable probability surfaces 

created for the eastern allotments in the study area in Grand 

Canyon-Parashant National Monument, northwestern Arizona,for 

(A) distance to livestock water sources, (B) distance from roads, 

and (C) the final combined probability surface used in plot selection.

of the soil surface. Plot parent material, landform, elevation, 

slope, slope shape, and aspect were also recorded. Additionally, 

digital photographs were taken at both ends of each transect 

following Herrick and others (2005) methods for a total of six 

photographs per plot. Each photograph contains a photograph 

board with the allotment, plot name, date, transect number, and 

direction of image.

We used soil and landscape property data, along with 

climate zone, and plot photographs to assign each plot to a soil 

map unit component (Lindsay and others, 2003). We did not 

restrict possible soils to those described for the map unit in 

which the plot occurred but included surrounding map units as 

well. We then identified the plot ecological site using the map 

unit component-ESD correlation provided in the NRCS soil 

survey database (Lindsay and others, 2003).

To assess plot ecological condition, we collected data 

on soil and site stability, hydrologic function, and plant 

community cover and composition. Foliar cover by species, 

ground cover, and plant composition were assessed using the 

line-point intercept method (LPI; Herrick and others, 2005) 

with a point spacing of 1 m, for a total of 150 points per plot. 

Plant species frequency was assessed using a nested frequency 

frame containing a 10×10 cm and 40×40 cm quadrat (rooted 

frequency for herbaceous species and canopy frequency for 

woody species). Frames were placed every 5 m along each 

transect, resulting in 30 frames per plot. Potential for wind 

and water erosion, run-off, and perennial community structure 

were assessed on each transect using the perennial plant 

canopy and basal gap intercept method (Herrick and others, 

2005). Surface soil aggregate stability was measured using 

a soil stability test, which ranks stability from 1 to 6, with 

6 being the most stable (Herrick and others, 2001; Herrick 

and others, 2005). Six soil surface samples were collected at 

randomly selected points along each transect (18 per plot). 

Relative cattle use was assessed using frequency of dung. The 

presence or absence of cattle dung was recorded for ten 1×1-m 

quadrats per transect (placed every 5 m, 30 total per plot). It 

is not possible to use cattle dung frequency counts to estimate 

absolute use (Fuller, 1991), but dung counts have been used 

in many studies as an index of relative use (Augustine, 2003; 

Veblen, 2012; Kimuyu and others, 2017). 

All soil and vegetation data were entered into the Database 

for Inventory, Monitoring, and Assessment (DIMA; Courtright 

and Van Zee, 2011) either directly using a field computer (LPI, 

canopy and basal gap) or afterward (soil stability, frequency, 

and soil pedon descriptions). Basic summary reports were 

generated in DIMA for further data analysis. Dung frequency 

data were entered and stored separately.

Data Analyses

We used four general approaches to data analysis. First, 

we provide general descriptions and summaries of soils, plants, 

and cattle activity across the Grand Canyon-Parashant National 

Monument. Second, we summarized quantitative indicators 

of rangeland health (table 1) by generalized ecological site 

type and then conducted analyses for differences in indictors 
10 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

between these soil groups. Third, within the four climate zones, 

we conducted community-scale analyses using multivariate 

approaches to understand how plot soil and plant composition 

vary across the landscape, looking for natural floristic groups. 

Fourth, we examined the univariate and multivariate data for 

the relations among indicators of rangeland health, abiotic 

gradients, and indicators of cattle activity. 

Plot-level averages of species foliar cover, soil cover, 

plant canopy and basal gap distribution, and other indicators 

of rangeland health were derived using the reporting functions 

provided by DIMA (table 1; Courtright and Van Zee, 2011). 

Plant species were categorized in three ways: growth form 

(tree, shrub, grass, or forb), woody or herbaceous, and 

perennial or annual. Category determinations follow the U.S. 

Department of Agriculture PLANTS database. For species that 

can take on multiple growth forms (for example, can either be 

a forb or subshrub), the form that was most commonly seen in 

the study area was used. These categories were used to broadly 

describe plant structure. Although frequency was collected 

for all plant species, we only analyzed frequency of exotic 

species here. Species lists with associated classifications and all 

frequency data is available in Duniway and Palmquist (2020). 

Trends in rangeland ecosystem indicators with elevation 

were examined using cubic local regression (SAS software 

ver. 9.4, LOESS procedure). Relations between cattle dung 

frequency and environmental covariates were examined using 

a quantile regression approach (QUANTREG procedure). 

Quantile regression provides an approach for examining 

relations between independent and dependent variables that 

is robust to outliers (Cade and Noon, 2003). A final index 

of relative cattle use was developed based on a multiple 

quantile regression using frequency of cattle dung (dependent 

variable) and a suite of environmental covariates (independent 

variables). Environmental covariates examined included 

cost-distance to water (as described in the survey design), plot 

ruggedness (using the ruggedness index described above), and 

soil survey estimated forage production (representative value) 

for the correlated soil map unit component. Forage production 

is an attribute in NRCS soil surveys based on soil profile 

properties and climate that can be used to estimate appropriate 

stocking rates. 

We created site climate zones based on NRCS 

precipitation groups and natural elevation breaks and grouped 

ESDs in each climate zone into generalized ecological site 

groups (ESGs) based on similarity in soil properties and (or) 

soil parent materials (fig. 6; Duniway and others, 2016). 

Descriptive statistics of plant and soil communities were done 

using SAS ver. 9.4 (MEANS procedure) and examination of 

differences in indicators was done using a mixed model with 

ESGs as fixed effects (MIXED procedure). 

To conduct multivariate analyses, two data matrices 

were created from plot data in each of the four climate 

zones, one containing the foliar and ground cover data and 

the other environmental and cattle use variables. The foliar 

and ground cover data matrices were used for the cluster 

and multivariate analyses, and the environmental and cattle 

use matrices were used to examine correlations. The foliar 

and ground cover matrices consisted of the cover values for 

each plant species, biological soil crust, litter, and bare soil, 

as well as frequency values instead of LPI cover values for 

Bromus rubens, Bromus tectorum, Erodium cicutarium, and 

Schimus arabicus. Frequency values were used for these four 

nonnative invasive species because their cover values were 

commonly low but their presence or absence was considered 

an important indicator of ecosystem change. The correlation 

matrices consisted of the physical characteristics of the plot 

(slope, aspect, and elevation), characteristics of the soil 

(parent material, percentage of cover by rock fragments on 

the surface, percentage of rock by volume of the first horizon, 

surface texture, and percentage of sand and silt estimates), 

cattle dung frequency, the cattle use index, and distance to the 

nearest road (table 5).

Multivariate analyses, richness, and diversity measures 

(Simpson’s diversity index and Shannon’s diversity index) 

were generated using PC-ORD ver. 6.08 (McCune and 

Mefford, 2011). Both measures of diversity are reported 

here to facilitate comparisons across geographic regions and 

studies. Prior to multivariate analysis, species that occurred 

in less than 5 percent of plots were removed (McCune and 

Grace, 2002). Cover values were converted to compositional 

cover (cover of species within the total foliar cover) for 

all species other than the four nonnative species listed 

above. Data was otherwise untransformed, except where 

transformation clarified relations. In the one case where data 

transformation improved analyses (middle desert), a square 

root transformation was applied to all columns. Two plots 

were removed from analyses for which outlier analysis using 

the Sørensen distance measure indicated that they fell more 

than two standard deviations from the mean and including 

these outliers obscured further interpretation of data. One 

of these outliers occurs in a burned ponderosa forest, which 

now has very little living ponderosa overstory and has high 

amounts of very large woody material owing to dead and 

downed ponderosa. The other outlier occurs in a drainage 

through bedrock with very little soil and consequently very 

little foliar cover.

Plots were classified using hierarchical cluster analysis 

(flexible beta [β = −0.25] linkage and a Sørensen distance 

matrix) and indicator species analysis (9,999 randomizations 

and quantitative response). The number of clusters that 

generated the highest indicator values and had a reasonable 

amount of information remaining was chosen to define floristic 

groups. Those groups were also cross-checked with plot 

photographs to make sure the communities were recognizable.

Nonmetric multidimensional scaling (NMS) using the 

Sørensen distance measure was used to illustrate variability 

within climate zones and correlations between floristic 

groups and explanatory variables (environmental and land 

use factors). The “slow and thorough” method in autopilot 

was chosen, which uses a random starting configuration, 250 

runs of real and randomized data with a maximum of 500 

iterations, and an instability criterion of 0.0000001. The best 
Materials and Methods 11

Figure 6. Maps showing the distribution of identified ecological site groups (table 6). Map inset shows the part of the 

Grand Canyon-Parashant National Monument, northwestern Arizona, that the National Park System administers (outlined in 

green). km, kilometers.

Table 5. Landscape setting, soil, and cattle use variables hypothesized to control indicators of rangeland health and community 

ordinations in the Grand Canyon-Parashant National Monument, northwestern Arizona.

[m2, square meters; Wm−2, watts per square meter]

Variable Description Source1

Landscape setting

Elevation Plot elevation, in meters DEM

TWI Topographic wetness index (Sörensen and others, 2006) DEM

Flow accumulation Contributing area, measure of hydrologic connectivity (log transformed) DEM

Slope Plot average slope (degrees) DEM

Curvature Plot compound curvature DEM

Solar insolation Plot annual solar insolation (in Wm−2) DEM

Soil surface properties

Bedrock Cover of exposed bedrock LPI

Cobble Cover of surface cobbles LPI

Gravel Cover of surface gravels LPI

All Rock Total rock cover LPI

A-horizon fragment Rock fragments in surface soil horizon A Soil

Sand Estimated sand content of surface horizon Soil

Clay Estimated clay content of surface horizon Soil

Saturated conductivity Saturated conductivity of surface horizon based on texture Soil

AWC Available water capacity of surface horizon based on texture Soil

Field cap. Field capacity of surface horizon based on texture Soil
12 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

Table 5. Landscape setting, soil, and cattle use variables hypothesized to control indicators of rangeland health and community 

ordinations in the Grand Canyon-Parashant National Monument, northwestern Arizona.—Continued.

Variable Description Source1

Cattle

Cow dung Frequency of cow dung in 1-m2 quadrats Freq.

Distance to water Cost-distance to water source (log transformed) Derived

Cattle index Cattle index based on multiple quantile regression Derived

Soil classes

Depth Generalized soil depth class (very shallow, shallow, and moderately deep or deeper) Soil

Texture Generalized soil textural class Soil

Soil taxonomy Generalized soil taxonomic class Soil

1

DEM, calculated from 10-meter digital elevation model; LPI, line-point intercept model; Soil, data from soil pedon observation or derived soil variable 

(using pedotransfer function or soil survey; Schapp and others, 2001); Freq., quadrat frequency data; Derived, variable calculated using multiple sources

(see Materials and Methods section).

number of dimensions was assessed by substantial reductions 

in stress and a Monte Carlo test (McCune and Grace, 2002). 

Pearson’s r was used to analyze correlations between axis 

scores and explanatory variables.

To examine for structure in the cross-tabulation of ESGs 

and floristic groups, chi-square tests were done by climate 

zone (SAS ver. 9.4; FREQ procedure). Analysis of association 

between rangeland health indicators, NMS axis, and edaphic 

explanatory variables were done by climate zone using 

correlation for continuous variables (SAS ver. 9.4; CORR 

procedure) and mixed model analysis of variance for class 

variables (MIXED procedure). Edaphic variables included 

DEM-derived landscape setting indices, surface soil rockiness 

indicators, soil texture, and estimates of soil hydrologic 

properties (table 5; Schaap and others, 2001). The various 

field data as well as new data generated using geographic 

information systems and statistical analysis are available in 

Duniway and Palmquist (2020).

Results

Soils, Ecological Sites, and Vegetation 

Communities Sampled

In the 155 plots, we sampled 15 unique soil taxa (to 

great group level) and 52 unique soil map units components 

(table 6). Soil taxa represented in the plot data are dominated 

by aridisols but include mollisols and alfisols at high 

elevations, entisols in active alluvial settings, and some 

vertisols in locations dominated by shrink-swell clays. These 

52 soil map unit components were correlated to 31 unique 

ecological sites in the soil survey (Lindsay and others, 2003). 

We used the NRCS MLRA and CRA classifications (primarily 

delineated by elevation breaks) as an initial ecologicalsite 

grouping factor. We then looked within these groups for 

similarities in soil parent material, slope, and texture to develop 

potential soil-geomorphic units that will share commonalities 

in soil-plant relations. This resulted in a total of ten ESGs that 

were distributed among four climate zones (table 6); three in 

the low desert, four in the middle desert, two in the high desert, 

and one in the forest and savanna climate zones (fig. 6).

A total of 271 species were recorded in the study area 

(based on nested frequency and LPI). This includes new 

vouchered collections of three species for Grand CanyonParashant National Monument and 17 species for the NPSadministered part of the monument. All collections are 

located at the Grand Canyon-Parashant National Monument 

Herbarium. The new species recorded and vouchered for 

Grand Canyon-Parashant National Monument are Eriastrum 

sparsiflorum, Thlaspi montanum, and Trichoptilium incisum. 

Cluster analysis and indicator species analysis identified a 

total of 11 different floristic groups (table 7) distributed among 

the four climate zones (fig. 7). Details of cluster analysis and 

ordination results are provided by climate zone below. 

Cross tabulation of plot tallies by the ESGs assigned 

a priori and data-driven cluster analysis of vegetation 

composition suggests a strong concordance between the two 

approaches in most instances (table 8), indicating close links 

between soils and vegetation. Notable exceptions include the 

splitting of the Mojave shrub, desert grassland, and blackbrush 

floristic groups into two primary ESGs and some significant 

spread among floristic groups within the deep basalt, shallow 

limestone, and shallow loam ESGs. Details of the underlying 

properties driving these results are given by climate zone.
Results 13

Table 6. Ecological site groups identified in the study area.[ft, feet; in., inches; LRU, Land Resource Unit; m, meters; MLRA, Major Land Resource Area; N, number of plots sampled; NRCS, Natural Resources Conservation Service; %, percent]

Ecological 

site group Description N NRCS ecological sites Elevation range (m) Slope range (%) Soil taxonomy Allotment

Low desert (MLRA 030)

H

Shallow limestone.—Ecological sites with 6–9 in. 

precipitation, limestone parent material, shallow soils, elevations of 1,500–3,200 ft, and sandy soil textures.

12 R030XB212AZ, R030XB214AZ 432–695 9–37 Petrocalcids, haplocambids, haplocalcids Tassi

G

Deep mixed.—Ecological sites with a mix of limestone, 

basalt, and granite parent materials, deep soils, shallow to moderate slopes, elevations of 400–3,000 ft, and sandy soil textures

12

R030XA109AZ,R030XA115AZ,R030XB215AZ,R030XB218AZ,R030XB221AZ

430–623 1–7

Torriorthents, 

haplocalcids, torripsamments Tassi

C

Gypsum.—Ecological sites with gypsum parent material, 

deep soils, elevations of 1,600–3,400 ft, and sandy loam to loamy soil textures.

4 R030XB222AZ 590–630 6–44 Torriorthents Tassi

Middle desert (MLRA 035, LRU E)

I

Shallow mixed.—Limestone and sandstone parent material, 

shallow soils, typically moderate to steep slopes, elevations of 3,500–5,000 ft, and sandy to loamy soil textures.

16

R035XE503AZ,R035XE505AZ,R035XE517AZ,R035XE519AZ

1,067–1,463 1–45

Petrocalcids, 

haplocalcids, haplogypsids, torriorthents

Big Spring Pipeline, Mt. 

Trumbull, Pa’s Pocket, Tassi

J

Deep limestone.—Mostly limestone (some sandstone) 

parent material, deep soils, typically shallow to moderate slopes, elevations of 3,500–5,000 ft, and sandy to loamy soil textures.

18

R035XE511AZ,R035XE514AZ,R035XE518AZ

1,022–1,574 3–30

Haplocalcids, 

calcigypsids, torriorthents

Big Spring Pipeline, 

Mt. Trumbull, Mule Canyon, Pa’s Pocket

A

Deep basalt.—Primarily basalt parent material, moderately 

deep to deep soils, elevations between 2,800–5,000 ft, and loamy to clayey loam soil textures.

22 R035XE501AZ, R035XE520AZ 874–1,537 3–47 Haplargids, calciargids, argigypsids Big Spring Pipeline, Mt. Trumbull, Pa’s Pocket

E

Shallow sandstone.—Sandstone parent material, shallow 

soils, shallow slopes, elevations of 1,600–4,600 ft, and sandy loam and loamy sand soil textures.

8 R035XE510AZ 1,021–1,230 2–23 Torriorthents Mt. Trumbull

High desert (MLRA 035, LRU C and F)

D

Deep basalt.—Primarily basalt parent material, generally 

shallow to moderate slopes, moderately deep to deep soils, elevations of 5,000–6,600 ft, and loamy to clayey loam soil textures.

18

F035XF611AZ,R035XC301AZR035XC303AZ,R035XF604AZ

1,437–1,953 1–24

Paleustolls, 

argiustolls, haplusterts, haplargids, haplocambids, haplustalfs

Big Spring Pipeline, 

Home Ranch
14 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona Table 6. Ecological site groups identified in the study area.—Continued Ecological site group Description

N NRCS ecological sites Elevation range (m) Slope range (%) Soil taxonomy Allotment

High desert (MLRA 035, LRU C and F)—Continued

F

Shallow limestone.—Primarily limestone parent material, 

mostly shallow to moderate slopes, shallow soils, elevations of 4,500–6,000 ft, and loamy to clayey soil textures.

24

R035XC302AZ,R035XC319AZ,R035XC331AZ_1,R035XC350AZ

1,523–1,724 0–63

Haplocalcids, 

torriorthents, petrocalcids, haplustalfs

Big Spring Pipeline, Red 

Pond

Forest and savanna (MLRA 035, LRU F and H)

B

Shallow loam.—Shallow soils, elevations of 5,500–7,500 ft, 

and loamy to clayey soil textures. Typically, Pinus edulis/Juniperus osteosperma or Pinus ponderosa sites.

21

F035XF613AZ,F035XF620AZ,F035XF624AZ,F035XH805AZ

1,718–1,977 1–40

Argiustolls, 

calciustolls haplustalfs, haplusterts, paleustolls

Big Spring Pipeline, 

Home Ranch

Table 7. Floristic groups identified in the study area.[m, meters; N, number of plots sampled; NRCS, Natural Resources Conservation Service; %, percent]

Floristic group Description

N NRCS ecological sites Elevation range (m) Slope range (%) Allotment

Low desert

Mojave shrub

Characterized by Ambrosia dumosa and Schimus arabicus, 

typically low plant cover, and a high proportion of annual species cover. Graminoid cover is low, particularly perennial grasses. Generally shallow slopes.

25

R030XA115AZ,

R030XB221AZ,R030XB215AZ,R030XB218AZ,

R030XA109AZ,

R030XB212AZ,R030XB222AZ,R030XB214AZ,

430–695 1–37 Tassi

Mojave gypsum

Characterized primarily by very low foliar cover and high 

biological soil crust cover and development. Lycium

andersonii and Mentzelia affinis are low cover and frequency indicator species. Restricted to gypsiferous soils.

3 R030XB222AZ 590–609 6–44 Tassi

Middle desert

Desert grassland

Characterized by typically high grass cover and all grass 

indicator species: Hilaria rigida, Muhlenbergia porteri, 

Bouteloua eriopoda, Sporobolus cryptandrus, and Tridens muticus. Total foliar cover is variable but tends to be higher than other groups. Mostly occurs on shallow slopes (gradients <20%).

32

R035XE518AZ,R035XE514AZ,R035XE501AZ,

R035XE511AZ,

R035XE505AZ,R035XE520AZ,

R035XE517AZ

985–1,574 3–47 Big Spring Pipeliine, Mt. Trumbull, Mule Canyon, Pa’s Pocket
Results 15

Table 7. Floristic groups identified in the study area.—Continued

Floristic group Description

N NRCS ecological sites Elevation range (m) Slope range (%) Allotment

Middle desert—Continued

Blackbrush 

shrubland

A mix of grasses and shrubs characterized by Coleogyne 

ramosissima and Mortonia utahensis. Shares many species with low and high desert groups, which have affiliations with the Mojave Desert and the Colorado Plateau. Mostly on shallow slopes (gradients <20%).

26

R035XE520AZ,R035XE517AZ,R035XE510AZ,R035XE519AZ,R035XE503AZ,R035XE505AZ,R035XE501AZ,

R035XE514AZ

1,021–1,418 1–45 Big Spring Pipeline, Mt. Trumbull, Pa’s Pocket, Tassi

Creosote slopes

Primarily woody shrubs with little understory or an understory 

of annual, nonnative grass. Larrea tridentata is the primary 

indicator species and Pectis papposa is a weak indicator. Mostly on shallow slopes (gradients <15%).

6

R035XE514AZ,R035XE501AZ,R035XE520AZ,

R035XE519AZ

874–1,191 3–35 Mt. Trumbull, Pa’s Pocket

High desert

Mixed shrublands

Bromus rubens, Atriplex canescens, Ephedra viridis, and Yucca baccata characterize this group. Shrubs are the primary 

cover, but grass cover can also be codominant. Strongly correlated with steep slopes and high amounts of surface rock. At lower elevations than the pinyon-juniper woodlands.

7

R035XC331AZ,R035XC302AZ,R035XC303AZ,

R035XC319AZ

1,437–1,704 7–63 Big Spring Pipieline, Pa’s Pocket, Red Pond

Sagebrush shrublands

Characterized by Artemisia tridentata, Bromus tectorum, and 

Sphaeralcea grossularifolia. Foliar cover primarily from shrubs; some annual grasses. Mostly on shallow slopes (gradients <25%) and lower elevation than the pinyon-juniper woodlands.

16

R035XC319AZ,

R035XC331AZ_1,

R035XC301AZ,R035XC302AZ,

R035XC350AZ

1,523–1,790 0–51 Big Spring Pipeline, Red Pond

Pinyon-juniper 

woodland

Characterized by tree cover from Juniperus osteosperma, 

Pinus monophylla, and Pinus edulis and low amounts of Eriogonum umbellatum. Low covers of perennial grass are present. Mostly above 1,800 m in elevation on very shallow slopes (gradients <10%).

19

F035XF611AZ,

R035XC302AZ,

R035XF604AZ,

R035XC350AZ,

R035XC319AZ

1,658–1,953 1–21 Big Spring Pipeline, Home Ranch, Red Pond

Forest and savanna

Pinyon woodland

Primarily characterized by tree cover from Pinus edulis, with 

some Artemisia tridentata. Very low amounts of understory cover. Strongly correlated with surface rock fragments.

4 F035XF620AZ, F035XF624AZ 1,718–1,977 3–36 Big Spring Pipeline

Juniper woodland

Characterized by Juniperus osteosperma, little shrub understory, and Elymus elymoides. Understory cover is low, 

particularly annual species. Positively correlated with high cattle index values. Occurs on shallow slopes.

11

F035XF613AZ,F035XF620AZ,

F035XF624AZ

1,815–1,955 1–10 Home Ranch

Forest shrubland

Highest foliar cover of all groups, mostly a mix of tree and 

shrub cover. Poa fendleriana, Garrya flavescens, Quercus 

turbinella, and Purshia stansburiana are characteristic. Annual cover is almost zero. Typically on steep slopes (gradients >25%).

4 F035XF620AZ, F035XF613AZ 1,788–1,871 3–40 Home Ranch
16 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

Trends Across Elevation 

Indicators of soil and site stability and hydrologic 

function show contrasting trends with elevation (fig. 8). 

Vegetation gap indicators signify increasing stability and 

function (decrease in cover of large basal and canopy gaps and 

increase in protective litter cover) with increasing elevation, 

and total amount of exposed bare soil is generally unchanged 

across elevations (fig. 8A). There is a large increase in litter 

cover between 1,700 and 1,800 m, likely associated with an 

increase in tree cover (fig. 8A). Soil surface biologic indicators 

(biological soil crusts and soil aggregate stability) show a 

decrease with elevation whereas rock cover increases slightly 

to a peak between 1,400 and 1,500 m before reaching lower 

values at higher elevations (fig. 8B). The average aggregate 

soil stability index is highest in the low elevations (ca. 4), 

with a pronounced dip in soil aggregate stability to minimum 

smoothed index value of ca. 2 near 1,700 m. Total biological 

soil crust cover decreases between the low-elevation Tassi 

allotment and the next elevation zone with data (1,100 m). 

Trends in indicators of biotic integrity demonstrate the 

importance of elevation (and associated climates) on plant 

communities in Grand Canyon-Parashant National Monument 

(fig. 9). Plant diversity is highest in the lower and upper 

reaches of the study area (table 9), with an evident dip in 

the local regression line and many field plots that have very 

low diversity between 1,000 and 1,400 m elevation (fig. 9A). 

Average total foliar cover increases with increasing elevation; 

the lowest cover value is for the low desert zone (ca. 0.2) 

and the highest is for the forest and savanna zone (ca. 0.5). 

Understory herbaceous and shrub cover peaks at the boundary 

between the low and high desert elevations (1,400–1,500 m), 

which coincides with marked increase in tree cover (starting 

at ca. 1,600 m; fig. 9A). Trends in dominant woody species 

cover with elevation show both elevation distinction and 

overlap among species (fig. 9B). Ambrosia dumosa and Larrea 

tridentata are both dominants in the lowest elevations and 

L. tridentata occurs at high cover values as high as about 

1,200 m, whereas A. dumosa is limited to elevations below 

700 m. Coleogyne ramosissima and Ephedra spp. overlap 

in elevation with L. tridentata, with average cover peaking 

at ca. 1,400 and 1,500 m, respectively. Artemisia spp. cover 

begins at ca. 1,400m, peaks at ca. 1,600 m, and decreases at 

higher elevations. For the common tree species, Juniperus spp. 

and pinyon, cover starts at 1,500 and 1,600 m, respectively. 

Juniperus spp. are the dominant species at high elevations, 

with a sharp increase in cover between 1,700 and 1,800 m. 

Occurrence of invasive species is an important part of 

biotic integrity, and frequency of invasive species of concern 

shows strong trends with elevation (fig. 9C). The annual 

grass Bromus rubens is the most common invasive species at 

most elevations. Schismus arabicus, also an annual grass, has 

similar, if not higher, frequency in the lowest elevations but 

observations of this species were infrequent above 700 m. The 

biennial forb Erodium cicutarium, a nonnative weed, occurs 

at low to mid-elevations (500–1,600 m). Average frequencies 

are low (local area regression line), but there are several plots 

across elevations that have high frequency. Bromus tectorum, 

another regionally important annual invasive grass, is also 

prevalent in the high elevation sites (1,400 to 1,900 m).

Figure 7. Maps showing the spatial distribution of identified floristic groups (table 7). Map inset shows the part of the 

Grand Canyon-Parashant National Monument, northwestern Arizona, that the National Park System administers (outlined in 

green). km, kilometers.
Results 17

Table 8. Cross tabulation of ecological site groups (ESGs) (fig. 6) and cluster analysis floristic groups (fig. 7).

[Values are number of plots in each combination of ESGs and floristic groups. ESG and cluster groups show significant association (chi-square test for 

independence in all climate zones except forest and savanna, where there is only one ESG). Low desert p = 0.001, middle desert p < 0.001, and high 

desert p < 0.001]

Cluster analysis floristic groups

Low desert Middle desert High desert Forest and 

savanna

C G H A E I J D F B

Mojave shrub 1 12 12

Mojave gypsum 3

Desert grassland 14 2 16

Blackbrush shrubland 4 8 13 1

Creosote slopes 4 1 1

Mixed shrublands 1 6

Sagebrush shrublands 1 15

Pinyon-juniper woodland 16 3

Pinyon woodland 4

Juniper woodland 11

Forest shrubland 4

Outliers 2

Figure 8. Plots showing trends in indicators of (A) soil and site stability and (B) hydrologic function with elevation (in 

meters [m]). Dots are observations, lines are loess cubic fit (SAS ver. 9.4, LOESS procedure). Plot A shows cover of bare 

soil, proportion of large basal (>200 centimeters [cm]) and canopy (>100 cm) gaps, and cover of litter (herbaceous and 

woody). Plot B shows indicators of soil cover, total biological crust cover (BSC), lichen cover, moss cover, rock cover, and 

soil aggregate stability.
18 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

Figure 9. Plots showing trends in indicators of biotic integrity with elevation (in meters [m]). Dots are observations, lines are loess 

cubic fit (SAS ver. 9.4, LOESS procedure). A, Shrub cover, tree cover, annual cover, perennial grass cover, perennial forb cover, and 

Simpson’s diversity index. B, Cover of dominant woody species. C, Frequency of invasive species (using a 0.16 square meter frame).

Table 9. Richness and diversity indices for climate zones and floristic groups within. 

Floristic group Avg. number of 

species per plot

Total number of species 

recorded

Avg. Simpson’s 

diversity index

Avg. Shannon’s 

diversity index

Low desert 10.3 62 0.78 1.85

Mojave shrub 10.6 56 0.78 1.87

Mojave gypsum 7.7 17 0.76 1.68

Middle desert 11.1 107 0.75 1.81

Desert grassland 13.2 84 0.81 2.03

Blackbrush shrubland 9.5 65 0.74 1.70

Creosote slopes 6.8 19 0.52 1.12

High desert 11.0 82 0.70 1.68

Mixed shrublands 15.7 52 0.84 2.25

Sagebrush shrublands 10.6 37 0.74 1.74

Pinyon-juniper woodland 9.7 41 0.62 1.42
Results 19

Table 9. Richness and diversity indices for climate zones and floristic groups within.—Continued

Floristic group Avg. number of 

species per plot

Total number of species 

recorded

Avg. Simpson’s 

diversity index

Avg. Shannon’s 

diversity index

Forest and savanna 10.9 51 0.69 1.61

Pinyon woodland 7.2 14 0.65 1.36

Juniper woodland 11.2 36 0.64 1.50

Forest shrubland 12.2 22 0.82 1.97

Cattle Use

Comparison of cow dung frequency to cost-distance 

from water in active grazing allotments indicates factors other 

than distance to water are also important for determining 

cattle distribution within NPS-managed allotments in 

Grand Canyon-Parashant National Monument (fig. 10A). 

Looking at the relation between cattle dung frequency and 

cost-distance to water, we observed a generally better fit 

to the upper quantiles of the dung frequency distribution 

(log-linear; p = 0.003; 90th percentile better than 75th or 

50th), which suggests that the cost-distance to water variable 

provides a robust estimate of the upper bound on cattle 

dung frequency and is less suited to predicting more central 

tendencies or lower bounds of the distribution (fig. 10A). 

The 90th quantile of dung distribution also has a significant 

positive relation with estimated forage production (based on 

soil survey data; fig. 10B; p = 0.029) and negative relation 

with plot ruggedness index (DEM-derived ruggedness 

index; fig. 10C; p = 0.023). The model fit was improved by 

conducting a multiple-90th-quantile regression that includes 

all three independent variables (log cost-distance, potential 

forage production, plot ruggedness, and an interaction of 

plot potential forage production and ruggedness; table 10, 

fig. 10D). Such multiple predictor models have been used in 

other cattle distribution studies (Senft and others, 1983; Wade 

and others, 1998; Brock and Owensby, 2000; Ganskopp and 

Bohnert, 2009). The results presented here suggest a quantile 

regression approach may be more suited to estimating 

potential cattle use than a least-squares approach. 

Figure 10. Plots showing the relation 

between observed cow dung frequency 

and (A) cost-distance to water, (B) 

predicted forage production based on 

correlated soil map unit component (in 

pounds per acre), (C) plot ruggedness 

index, and (D) a multiple regression of 

all three explanatory variables. Data for 

each allotment are shown. Black line 

depicts a 90-percent quantile regression 

fit. km, kilometers.
20 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

Low Desert 

Landscape Setting, Soils, and Rangeland 

Indicators 

Ecological site groups in the low desert are primarily 

distinguished by soil parent material, soil depth, soil horizons, 

slope, and landscape position (table 6, fig. 11). The four plots 

established in the gypsum hill area of the Tassi allotment were 

all classified to the same ESD and were placed in one ESG 

(gypsum). The other two groups (shallow limestone and deep 

mixed) are distinguished primarily by soil depth, soil horizon 

development, rock fragments, and landscape setting (slope 

and topographic wetness index [TWI]; fig. 11). The shallow 

limestone group is generally sloping with shallow soils and 

includes ESDs with these as the primary descriptor. The deep 

mixed group includes a variety of ESDs because of the range 

of soils included, however most plots in this group had little 

soil horizon development (entisols). Very little cattle dung was 

observed in this allotment (fig. 11G), however, plots in the 

shallow-slope and low-rock-content deep mixed group had the 

highest occurrence. This is expected since this allotment was 

officially closed to grazing at the time of this study and only 

trespassing cattle were present.

These differences in soils and topography among groups 

created few significant differences in indicators of site 

stability, hydrologic function, and plant functional groups 

(fig. 12). The deep mixed group has the highest bare ground 

and lowest soil aggregate stability, likely caused by low 

biological soil crust and rock cover (fig. 12A). The gypsum 

group has significantly higher biological soil crust cover 

(cyanobacteria, lichens, and mosses). Examination of plant 

functional group cover shows that the deep mixed group 

has a high cover of perennials, driven by high woody cover 

(fig. 12B). Looking at individual species, Ambrosia dumosa

and Larrea tridentata occur across all groups with some 

among-group trends evident but no significant differences 

detected. The deep mixed sites had a high frequency of the 

invasive annual grass Schismus arabicus (fig. 12C). 

Indicators of site stability and hydrologic function in 

the low desert show strongest correlation with measures of 

plot topographic setting and plot rockiness (fig. 13). Run-in 

areas (high TWI, high flow accumulation, and shallow slope) 

have high bare ground and low ground cover, potentially 

because of less protective rock cover. There is also a trend 

of high bare ground and low ground cover on warm aspects 

(high solar insolation). Soil aggregate stability followed 

similar trends. Total biological soil crust cover and cover of 

lichens was positively correlated with amount of exposed 

bedrock but negatively correlated with surface rockiness. 

Only proportion of large canopy gaps and soil aggregate 

stability showed correlation with soil texture variables, with 

more large gaps but also greater soil stability on fine-textured 

soils characterized by high water retention at field capacity. 

Though there is no cattle use currently permitted in the low 

desert (Tassi allotment), there is still a significant correlation 

with distance to water, which suggests areas more accessible 

to water sources have higher bare ground and lower ground 

cover than more distant parts of the Tassi allotment. This could 

be caused by historic cattle use, feral cattle and wild burro use 

(animals were present when field data was collected), or both.

Indicators of biotic integrity in the low desert show high 

correlation with soil texture and soil depth (fig. 13). Areas with 

high curvature (run-off location, hill tops, and shoulders) have 

low cover of woody vegetation, low cover of all perennial 

species, and low plant diversity. Areas with less exposed 

bedrock and deep soils tended to have more total cover, and 

areas with less exposed bedrock, few rocks in the soil profile, 

and deep soils tended to have high woody and shrub cover. 

Perennial species in general, and woody species in particular, 

show a positive correlation with coarse, well-drained surface 

soil textures. Though cover of perennial grasses and forbs is 

generally not very high in the low desert, there is significantly 

high cover of these functional groups in the shallow soil sites. 

There is surprisingly little correlation among the two 

dominant shrubs of the low desert (Ambrosia dumosa and 

Larrea tridentata) and the suite of edaphic variables (fig. 13). 

There are no significant relations detected for A. dumosa. L. 

tridentata tends to occur on soils with high gravel cover and 

soil types that demonstrate some weak level of development 

(not entisols). Frequency of the two invasive annual species 

of concern show more correlation with soil and landscape 

variables. Bromus rubens is correlated with high elevations 

and deep soils. Schismus arabicus occurs at low elevations 

and is more common in areas that receive run-in moisture 

(high TWI) and have coarse surface textures. There is also 

a significant negative correlation between S. arabicus and 

distance to water sources, suggesting areas that historically 

have had high cattle use have high frequency of S. arabicus.

Ordinations

Only two floristic groups were identified for the low 

desert in the cluster analysis: the Mojave shrub and the Mojave 

gypsum (table 11). The final NMS has three axes, stress of 

9.61, and instability of 0.00000. Cover in the Mojave shrub 

group is a mix of annual and woody species, characterized 

by Ambrosia dumosa and Schismus arabicus. Annual grasses 

compose the bulk of the graminoid cover in this group. 

Average richness is moderate (10.6), as is Simpson’s diversity 

(0.78). The Mojave gypsum group is identifiable by its very 

well developed biological soil crust and sparse vegetation. 

It supports few species (average richness = 7.7, Simpson’s 

diversity = 0.76) and low foliar cover (average total foliar 

cover = 0.13), but Lycium andersonii and Mentzelia affinis are 

indicators. Sparse vegetation leads to low indicator values and 

low average richness since no species occur regularly. 
Results 21

Table 10. Parameter estimates from multiple quantile regression estimating the 90-percent quantile of cattle dung frequency in active 

grazing allotments.

[Each estimate has 1 degree of freedom. %, percent]

Parameter Estimate Standard error 90-percent quantile p-value

Min. Max.

Intercept 0.6699 0.1689 0.3891 0.9507 <0.001

Log cost-distance to water −0.1969 −0.2787 −0.1151 −4.00 <0.001

Soil survey perennial grass production 0.0079 0.0023 0.0040 0.0118 0.001

Ruggedness 0.0737 0.0755 −0.0518 0.1992 0.332

Ruggedness × perennial grass production −0.0044 0.0020 −0.0078 −0.0011 0.029

Figure 11. Plots characterizing the low desert ecological site groups. See figure 6 and table 6 for 

more information. Plots show the frequency of (A) surface soil texture class (L, loam; LSa, loamy 

sand; SaL, sandy loam), (B) soil depth class, (C) soil taxonomy, (D) elevation (in meters [m]), (E) 

slope, (F) topographic wetness index (TWI), (G) observed cow dung, (H) log cost-distance to water, 

and (I) surface rock cover. Box and whisker plots are shown for continuous variables, denoting 

25th, 50th, and 75th quantiles (boxes); 10th and 90th quantiles (whiskers); and outliers (dots).
22 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

Figure 12. Plots showing fractional cover of the low desert ecological site groups. See figure 6 and table 6 for more 

information. A, Soil and hydrologic function indicators; B, plant community functional group cover; and C, dominant species 

cover and invasive species frequency. * indicates p<0.10; ** indicates p<0.05 for ecological site group differences from 

mixed model analysis of variance. Where analysis of variance detected differences among ecological site groups, bars 

with the same letter (a or b) do not differ. BSC, biological soil crust; per., perennial; AMDU, Ambrosia dumosa; LATR, Larrea 

tridentata; SCAR, Schismus arabicus; BRRU, Bromus rubens.
Results 23

Figure 13. Plot showing correlations between rangeland health indicators, ordination axes (nonmetric multidimensional 

scaling [NMS]), and landscape setting, soil, and cattle factors for low desert settings. See table 1 for descriptions of 

rangeland health indicators (left column) and table 5 for descriptions of edaphic factors (top row). Cell values are Pearson 

correlation coefficients (for continuous variables; bold values indicate p-values <0.05) or p-values from ANOVA tests (for 

soil classes). Cell color shading provides further emphasis on correlation strength (dark green, strong positive; yellow, near 

zero; and dark red, strong negative) or ANOVA p-value strength (dark green is strong and white is weak).

Table 11. Floristic groups in the low desert climate zone identified by cluster analysis and indicator species analysis.

[In addition to functional indicators, species with statistically significant (p <0.05) indicator values are listed, followed by indicator value in parentheses. SD, 

standard deviation; N, number] 

Indicator Mean (SD) Min. Max.

Mojave shrub (N = 25)

Total foliar cover 0.29 (0.09) 0.12 0.43

Woody cover 0.12 (0.05) 0.03 0.23

Graminoid cover 0.10 (0.08) 0.00 0.30

Annual cover 0.19 (0.09) 0.08 0.40

Avg. soil stability 4.22 (0.84) 2.83 5.67

Ambrosia dumosa (84) 0.03 (0.03) 0.00 0.08

Schimus arabicus (82) 0.03 (0.04) 0.00 0.13

Bare soil (75) 0.14 (0.11) 0.01 0.39

Indicator Mean (SD) Min. Max.

Mojave gypsum (N = 3)

Total foliar cover 0.13 (0.09) 0.07 0.24

Woody cover 0.06 (0.05) 0.00 0.11

Graminoid cover 0.04 (0.07) 0.00 0.12

Annual cover 0.08 (0.07) 0.03 0.15

Avg. soil stability 5.49 (0.36) 5.07 5.72

Biological soil crust (82) 0.69 (0.09) 0.59 0.76

Lycium andersonii (67) 0.01 (0.01) 0.00 0.02

Mentzelia affinis (67) 0.00 (0.00) 0.00 0.01
24 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

There is evidence for the importance of landscape and 

soil setting as controlling factors for indicators of plant 

community composition. There is strong agreement between 

Mojave gypsum floristic group and the gypsum ESG, whereas 

the Mojave shrub group was evenly split between the deep 

mixed and shallow limestone ESGs (table 8). Examination of 

relations among diversity, NMS axes, and edaphic gradients 

suggests local topographic setting (TWI, flow accumulation, 

slope, and curvature) plays an important role in controlling 

the primary axis of community composition (axis-1; fig.13). 

Proportion of exposed bedrock, A-horizon rockiness, 

properties associated with soil texture, and soil depth are all 

also significantly correlated with the primary axis. The other 

two axes identified in the NMS (axis-2 and axis-3), show less 

correlation with measured landscape and soil factors, with 

significant correlations only observed for elevation (for both 

axes) and sand percentage (for axis-3). 

Middle Desert 

Landscape Setting, Soils, and Rangeland 

Indicators 

The four ESGs of the middle desert are distinguished 

primarily by parent material (basalt, sandstone, and limestone), 

soil depth (shallow to deep), and slope (table 6, fig. 14). There 

are two ESGs that are characterized by shallow soils but have 

contrasting soil diagnostic horizons (and taxonomy; fig. 14C). 

Shallow limestone plots are all torriorthents, which are soils 

that have very little soil development, whereas shallow mixed 

plots generally are in taxonomic classes that require calcic 

horizon development. The other two ESGs are moderately deep 

to deep and generally not steeply sloping but have contrasting 

parent materials and resulting texture and mineralogy. 

Deep basalt plots are generally finer in texture than deep 

limestone plots, though deep limestone plots tend to be more 

hydrologically enhanced (high TWI; fig. 14F). Cattle dung 

frequency is highest in the deep limestone plots (fig.14G).

Groups in the middle desert exhibit large and consistent 

differences in ecosystem indicators of site stability and 

hydrologic function (fig. 15A) and plant functional and 

species occurrence (fig. 15B, C). The deep limestone group 

has lower cover of large basal (>200 cm) and canopy (>100 

cm) gaps than other ESGs. The shallow sandstone group has 

the highest biological soil crust cover and the deep basalt 

and deep limestone groups have the lowest. Soil aggregate 

stability is highest in the shallow mixed and deep limestone 

groups, shallow sandstone groups have an intermediate level 

of aggregation, and the deep basalt group has the lowest 

aggregate stability. ESG plant functional group and species 

cover indicate differences in basal and canopy gaps are driven 

by very high perennial grass cover in the deep limestone 

group. The shallow mixed group has significantly higher cover 

of Coleogyne ramosissima, leading to an overall higher cover 

of shrubs, than the other ESGs, whereas the shallow sandstone 

group has intermediate cover. Gutierrezia spp. cover is also 

high in the deep limestone group. Bromus rubens frequency 

shows some specificity to ESGs, with the deep limestone 

group having the lowest and deep basalt and shallow mixed 

both showing similarly common occurrence. Frequency of the 

invasive species Erodium cicutarium was highest in the deep 

limestone group and lowest in the deep basalt group.

In the middle desert, site stability and hydrologic function 

indicators associated with soil cover (bare ground, ground 

cover, and biological soil crusts) show the most correlation 

with landscape and soil setting variables (fig. 16). Sites with 

high TWI, shallow slopes, and low rock cover tend to have 

more bare ground and less ground cover. Total cover of 

biological soil crusts as well as cover of lichens and mosses 

are significantly positively correlated with proportion of 

exposed bedrock, negatively correlated with most rock cover 

indicators, and positively correlated with coarse soil textures. 

Together, these suggest that biological soil crusts are most 

prevalent on shallow, sandy soil settings. Soil stability and 

biological soil crust cover both showed decreasing trends 

with elevation. Moss cover and soil stability are negatively 

correlated with solar insolation, indicating they are high in the 

cool aspects. Correlations with cow dung frequency, distance 

to water, and the cattle index suggest areas with high cattle 

activity have high bare ground and low ground cover. 

There are fewer associations among biotic integrity 

indicators, landscape, and soil setting variables in the 

middle desert than in indicators of soil and site stability and 

hydrologic function (fig. 16). There is less total cover in sites 

with high amounts of exposed bedrock and less cover of 

herbaceous and annual functional types on coarse well-drained 

soils. Similarly, few correlations were detected between 

functional group cover and the three measures of cattle use. 

There is some evidence of high shrub cover where cattle use 

is low (cow dung correlation) and high tree and annual cover 

where cattle use is low, but the lack of consistent trends among 

other functional group indicators suggests these correlations 

may be spurious. 

Cover of dominant species and species of concern 

demonstrate more correlation with landscape and soil 

factors than functional group cover in the middle desert 

(fig. 16). Ephedra spp. cover is positively correlated and 

Larrea tridentata cover is negatively correlated with 

elevation. Ephedra cover is also positively correlated with 

steep slope and negatively correlated with run-in positions 

(TWI). Ephedra is the only dominant species that shows any 

correlation with soil properties, preferring soils with high 

rock cover but that are not excessively drained (negative 

correlation with soil conductivity). Bromus rubens frequency 

is also positively correlated with soil rockiness (rock cover as 

well as A-horizon rock content) and soil textures that afford 

high water retention (high clay, low conductivity, and high 
Results 25

Figure 14. Plots characterizing the middle desert ecological site groups. See figure 6 and table 6 for more 

information. Plots show the frequency of (A) surface soil texture class (L, loam; LSa, loamy sand; SaL, sandy 

loam), (B) soil depth class, (C) soil taxonomy, (D) elevation (in meters [m]), (E) slope, (F) topographic wetness 

index (TWI), (G) observed cow dung, (H) log cost-distance to water, and (I) surface rock cover. Box and 

whisker plots are shown for continuous variables, denoting 25th, 50th, and 75th quantiles (boxes); 10th and 90th 

quantiles (whiskers); and outliers (dots).
26 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

Figure 15. Plots showing fractional cover of the middle desert ecological site groups. See figure 6 and table 6 

for more information. A, soil and hydrologic function indicators; B, plant community functional group cover; and C, 

dominant species cover and invasive species frequency. * indicates p<0.10; ** indicates p<0.05 for ecological site 

group differences from mixed model analysis of variance. Where analysis of variance detected differences among 

ecological site groups, bars with the same letter (a, b, or c) do not differ. BSC, biological soil crust; per., perennial; 

CORA, Coleogyne ramosissima; LATR, Larrea tridentata, BRRU, Bromus rubens, ERCI, Eragrostis cilianensis.
Results 27

Figure 16. Plot showing correlations among rangeland health indicators, ordination axes (nonmetric multidimensional 

scaling [NMS]), and landscape setting, soil, and cattle factors for middle desert settings. See table 1 for descriptions of 

rangeland health indicators (left column) and table 5 for descriptions of edaphic factors (top row). Cell values are Pearson 

correlation coefficients (for continuous variables; bold values indicate p-values <0.05) or p-values from ANOVA tests (for 

soil classes). Cell color shading provides further emphasis on correlation strength (dark green, strong positive; yellow, near 

zero; and dark red, strong negative) or ANOVA p-value strength (dark green is strong and white is weak).

available water capacity). There are some significant trends 

in dominant shrub cover relative to cattle variables. Both

Coleogyne ramosissima and Ephedra appear to have high 

cover in locations that receive low cattle pressure. Conversely, 

Gutierrezia spp. has high cover in locations with high dung 

frequency, close water sources, and where the cattle index 

predicts high use. B. rubens frequency is negatively correlated 

with the cattle index.

Ordinations

The middle desert contains three floristic groups 

identified in the cluster analysis: one dominated by grasses 

(desert grassland), one that is largely characterized by C. 

ramosissima and a mix of shrubs (blackbrush shrubland), and 

one that is characterized by L. tridentata (creosote slopes; 

table 12). The final NMS has three axes, stress of 18.03, and 

instability of 0.00000. 

The desert grasslands have the highest average graminoid cover (0.30) and the highest maximum graminoid cover 

(0.73) for the study area, whereas woody cover is generally 

low (0.18; table 12). The species with the highest indicator 

values are all native perennial grasses, but the composition 

of those grasses within plots is variable. Simpson’s diversity 

within this group is high (0.81) and average species richness 

is second highest of the eleven floristic groups (13.2). Many 

of the species that occur within this group occur in different 

combinations across the landscape and overlap with either the 

low desert or the high desert floristic groups. It is a transitional 

community and has a combination of species that are typically 

found in the Mojave Desert and on the Colorado Plateau.

Blackbrush shrublands are generally less vegetated 

than the desert grasslands but are comparable in cover to the 

creosote slopes (table 12). This group has a mix of woody 

and graminoid cover, where the woody cover is composed 

almost entirely of shrubs rather than trees (0.21 versus 0.01). 
28 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

Table 12. Floristic groups in the middle desert climate zone 

identified by cluster analysis and indicator species analysis.

[In addition to functional groups, species with statistically significant

(p <0.05) indicator values are listed, followed by indicator value in 

parentheses. SD, standard deviation; N, number] 

Indicator Mean (SD) Min. Max.

Desert grassland (N = 32)

Total foliar cover 0.46 (0.16) 0.07 0.88

Woody cover 0.18 (0.09) 0.00 0.31

Annual cover 0.19 (0.10) 0.03 0.54

Graminoid cover 0.30 (0.14) 0.05 0.73

Avg. soil stability 3.88 (0.92) 2.11 5.67

Hilaria rigida (67) 0.05 (0.06) 0.00 0.24

Muhlenbergia porteri (61) 0.03 (0.03) 0.00 0.10

Bouteloua eriopoda (44) 0.03 (0.04) 0.00 0.18

Sporobolus cryptandrus

(39) 0.04 (0.09) 0.00 0.40

Tridens muticus (25) 0.01 (0.01) 0.00 0.03

Blackbrush shrubland (N =26)

Total foliar cover 0.32 (0.11) 0.15 0.62

Woody cover 0.22 (0.10) 0.05 0.47

Graminoid cover 0.14 (0.11) 0.00 0.38

Annual cover 0.15 (0.11) 0.00 0.35

Avg. soil stability 3.86 (0.90) 2.22 5.29

Coleogyne ramosissima

(64) 0.08 (0.10) 0.00 0.35

Biological soil crust (49) 0.01 (0.04) 0.00 0.19

Bare soil (40) 0.16 (0.11) 0.05 0.47

Mortonia utahensis (35) 0.02 (0.03) 0.00 0.11

Creosote slopes (N = 6)

Total foliar cover 0.34 (0.15) 0.21 0.57

Woody cover 0.19 (0.05) 0.11 0.27

Graminoid cover 0.17 (0.17) 0.02 0.39

Annual cover 0.20 (0.20) 0.02 0.49

Avg. soil stability 3.72 (0.65) 2.44 4.20

Larrea tridentata (83) 0.16 (0.07) 0.08 0.26

Pectis papposa (43) 0.04 (0.06) 0.00 0.15

The species with the highest indicator values, although 

weak, are both native and uncommon in the study area. 

Mortonia utahensis occurs only in this floristic group, albeit 

sporadically. Coleogyne ramosissima occurs sporadically 

across the study range, but more consistently in this floristic 

group. M. utahensis is typically found in the Mojave Desert, 

whereas C. ramosissima occurs on the Colorado Plateau and 

into the Mojave. The low indicator values and somewhat low 

average richness (9.5) are due to the variable composition 

of the plots. This variability in composition and the mix of 

species with Mojave Desert and Colorado Plateau affiliations 

illustrate that this group is also a transitional community. Like 

the desert grasslands group, this group shares many species 

with low desert and high desert floristic groups. Soil stability 

ranges from instable to stable (2.22–5.29), and the average is 

moderately stable (3.86).

Creosote slopes have moderate levels of average 

total foliar cover (0.34), of which the woody component 

is consistent (0.19) and composed of shrubs (table 12). 

Graminoid and annual covers are variable, but high annual 

covers correspond with high graminoid covers, indicating the 

primary driver of graminoid cover is the annual nonnative 

species Bromus rubens. Since forbs are negligible (0.05), this 

group is characterized by woody shrubs with little understory 

or an understory of an annual nonnative grass. Larrea 

tridentata is the primary shrub in this group, which is reflected 

in a high indicator value (83). This group has the lowest 

average richness (6.8) and the lowest diversity (0.52).

Soils and plant community data suggest the middle desert 

climate zone has a higher diversity in soils and landscapes as 

well as associated plant communities than any other climate 

zone (four ESGs and three floristic groups; table 8, fig. 16). 

Desert grassland floristic groups were evenly split between 

the deep basalt and shallow limestone ESGs. Blackbrush 

shrublands occur in all ESGs but are most common in the 

shallow mixed group, and creosote slopes are most common 

in the deep basalt group. Correlations between axis scores and 

environmental variables were strongest with axis-1, which is 

positively correlated with contributing area (flow accumulation; 

fig. 16); negatively correlated with amount of exposed bedrock; 

and positively correlated with A-horizon rockiness, surface 

soil sand content (and associated soil hydrologic properties), 

and soil depth. Axis-2 shows no trends with landscape and soil 

variables and axis-3 is correlated with sites that have low TWI, 

steep slopes, and high exposed bedrock.

High Desert and Forest and Savanna 

Landscape Setting, Soils, and Rangeland 

Indicators 

In the results presented here, we lump the high desert 

and forest and savanna ESGs, because there is only one ESG 

identified in the forest and savanna zone and there is high 

overlap in elevations and associated climates between the 

two zones (table 6; fig. 17D). The two high desert ESGs are 

distinguished by both parent material and soil depth. The deep 

basalt and shallow limestone groups both have shallow to 

moderate slopes, however, as the names indicate, they have 

differing parent materials and dominant depths (fig. 17B). 

The high desert basalt group is also generally deeper and finer 

textured than the high desert shallow limestone group. The 

shallow loam group in the forest and savanna has a similar 

elevation range as the high desert basalt group. The shallow 

loam group is generally shallower and coarser in texture than 
Results 29

Figure 17. Plots characterizing the 

high desert and forest and savanna 

ecological site groups. See figure 6 

and table 6 for more information. Plots 

show the frequency of (A) surface 

soil texture class (CL, clay loam; L, 

loam; SaCL, sandy clay loam, SaL, 

sandy loam), (B) soil depth class, 

(C) soil taxonomy, (D) elevation (in 

meters [m]), (E) slope, (F) topographic 

wetness index (TWI), (G) observed 

cow dung, (H) log cost-distance to 

water, and (I) surface rock cover. 

Box and whisker plots are shown for 

continuous variables, denoting 25th, 

50th, and 75th quantiles (boxes); 10th 

and 90th quantiles (whiskers); and 

outliers (dots).

the high desert basalt ESG. Cattle use, as indicated by dung 

frequency, is absent on the high desert basalt group and forest 

and savanna shallow loam because these ESGs are restricted 

to the Home Ranch allotment (fig. 6), which has not been 

grazed by livestock since 2003. Cattle dung was observed in 

the high desert shallow limestone group, but frequencies were 

generally low (fig. 17G). 

Indicators of soil and site stability, hydrologic function, 

and plant functional group differed among the three ESGs 

(fig. 18A, B). There were no differences in cover of large 

basal gaps, however, canopy gaps were lower in the forest and 

savanna shallow loam than the high desert shallow limestone 

ESG. Bare ground was significantly lower in the forest and 

savanna ESG than the high desert ESGs. Biological soil crust 

cover was greatest in the shallow limestone group, potentially 

because of soil differences and low foliar and litter cover. 

These trends in gaps, bare ground, and litter are explained in 

part by trends in vascular plant cover. There were significant 

differences among all ESGs in indicators of biotic integrity. 

Total, perennial, and woody cover differed, with cover lowest 

in the shallow limestone group and highest in the shallow 

loam group. However, cover of annual grasses, Artemsia spp., 

and Gutierrezia spp. were significantly higher in the shallow 

limestone group than other groups (fig. 18C). The two high 

elevation ESGs had similar high cover of trees (primarily 

juniper with some pinyon). The two species of the invasive 

Bromus annual grasses (B. rubens and B. tectorum) were 

significantly more frequent in the shallow limestone ESG. 

Across the high desert and forest and savanna ESGs, 

there are a number of significant correlations between the 

soil and site stability and hydrologic function indicators and 

landscape and soil setting properties (fig. 19). The proportion 

of canopy gaps is high at low elevations and in landscape 

settings with high curvatures (more convex). Both ground 

cover and litter increase with elevation. Unexpectedly, the 

proportion of bare ground increases with degree of hydrologic 

enhancement (high TWI, high flow accumulation, and 

shallow slopes) but also increases in warm aspects (high 

solar insolation). Rocky areas have low bare ground and 

high ground cover. Litter cover is also reduced in areas with 

high bedrock exposure and coarse surface soils. There is no 

association between cost-distance to cattle water sources and 

indicators of soil and site stability and hydrologic function. 

Indicators of biotic integrity show some association with 

landscape setting variables and many associations with soil 

properties (fig. 19). High elevations tend to have high total and 
30 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

Figure 18. Plots showing fractional cover of the high desert and forest and savanna ecological 

site groups. See figure 6 and table 6 for more information. A, Soil and hydrologic function 

indicators; B, plant community functional group cover; and C, dominant species cover and 

invasive species frequency. * indicates p<0.10; ** indicates p<0.05 for ecological site group 

differences from mixed model analysis of variance. Where analysis of variance detected 

differences among ecological site groups, bars with the same letter (a, b, or c) do not differ. 

BSC, biological soil crust; per., perennial; BRRU, Bromus rubens; BRTE, Bromus tectorum.
Results 31

Figure 19. Plots showing correlations between rangeland health indicators, ordination axes (nonmetric multidimensional 

scaling [NMS]), and landscape setting, soil, and cattle factors for high desert and forest and savanna settings. See table 1 for 

descriptions of rangeland health indicators (left column) and table 5 for descriptions of edaphic factors (top row). Cell values 

are Pearson correlation coefficients (for continuous variables; bold values indicate p-values <0.05) or p-values from ANOVA 

tests (for soil classes). Cell color shading provides further emphasis on correlation strength (dark green, strong positive; 

yellow, near zero; and dark red, strong negative) or ANOVA p-value strength (dark green is strong and white is weak).

woody (tree) cover. Low elevations have a large proportion 

of shrubs and herbaceous species (except perennial grasses). 

There is also a tendency for high tree cover in hydrologically 

enhanced areas (high TWI and flow accumulation; more 

concave), whereas shrubs and herbaceous species occupy 

less-enhanced, more sloping locations. Woody and tree cover 

are also positively correlated with high solar gain (high solar 

insolation) whereas shrubs and herbaceous functional types 

(annuals, perennial grasses, and so on) tend to occur on 

cool aspects. The amount of exposed bedrock and soil depth 

are significantly associated with tree and herbaceous plant 

cover, but soil rockiness is not. High tree cover is associated 

with less exposed bedrock and deeper soils, whereas more 

bedrock and shallow soils favor herbaceous functional groups, 

including annual forbs and grasses. High surface sand content 

and associated hydrologic properties favor high tree cover, 

whereas shrubs show negative correlation with surface clay 

content and water retention at field capacity. 

Dominant species and species of concern also show 

strong association with landscape position, soil properties, and 

soil taxonomy (fig. 19). There is high cover of Artemisia spp. 

and Gutierrezia spp. and high frequency of Bromus rubens

and Bromus tectorum at low elevations, whereas juniper, 

pinyon, and Quercus spp. have high cover at high elevations. 

Gutierrezia spp. cover and B. rubens frequency are associated 

with landscape settings that shed water (low TWI and flow 
32 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

accumulation; high curvature) whereas juniper species are 

associated with run-in, shallow slope areas. Both Artemisia

spp. and Gutierrezia spp. have high cover on cool aspects (low 

solar insolation), as does B. rubens. Gutierrezia spp. cover 

is high in locations with more exposed bedrock and sandier 

soils with low available water holding capacity. Juniperus

spp. cover is negatively correlated with exposed bedrock and 

soil rockiness and positively correlated with clay content and 

associated hydrologic properties. Pinus spp. have a similar 

association with soil texture but are also positively correlated 

with cobble content. B. rubens is more common in sites with 

high exposed bedrock and high rockiness. The species level 

of association with soil taxonomy was notably strong in the 

high desert and forest and savanna climates. Artemisia and 

Gutierrezia spp. were most abundant on haploargids and 

haplocalids, respectively. Juniperus and Pinus spp. were most 

abundant on the various taxa characterized by mollic epipedons 

(argiustolls, calciustolls, and paleustolls) and Quercus spp. 

were most abundant on calcareous soils with a mollic epipedon 

(calciustolls). B. rubens was most frequent on torriorthents. 

Ordinations

The cluster analysis identified three floristic groups in 

the high desert, two of which are characterized by shrubs 

(mixed shrublands and sagebrush shrublands) and one that is 

characterized by trees (pinyon-juniper woodlands; table13). 

The final NMS has three dimensions, stress of 9.81, and 

instability of 0.00000. 

The mixed shrublands have the highest average richness 

(15.7) and the highest diversity (Simpson’s diversity index 

of 0.84) of all the floristic groups, despite the small sample 

size (N = 7). Woody cover is dominant (0.25), but graminoid 

cover also composes a large portion of the cover in places (as 

much as 0.29). The woody cover is predominantly composed 

of shrubs (0.23), rather than trees (0.2). The graminoid cover 

is due in part to cover of the nonnative annual grasses Bromus 

rubens and Bromus tectorum. This group is characterized by 

B. rubens, and the native shrubs Atriplex canescens, Ephedra viridis, and Yucca baccata. Soil stability is generally low 

(2.12), with only two of the seven plots averaging higher than 

category 2. 

The sagebrush shrublands have a moderate average 

richness (10.6) and diversity (0.74), and more variability in 

the amount of total foliar cover (0.19 to 0.58) than the mixed 

shrublands (table 13). This cover is largely woody cover (0.26) 

as shrubs (0.23), but graminoid cover in the form of mostly 

B. tectorum and B. rubens is also a large component in some 

areas (ranges from 0.01 to 0.44). Artemisia tridentata is the 

primary shrub and primary indicator for this group. Additionally, B. tectorum and Sphaeralcea grossularifolia are weak 

indicators. Average soil stability is low to moderate with an 

average of 2.47.

Pinyon-juniper woodlands have a moderate average 

richness (9.7), but low diversity (0.621; table 13). This 

floristic group has high average total foliar cover (0.46) but is 

somewhat variable. Most of the total foliar cover is accounted 

for by woody tree cover (0.37), as shrub (0.09), graminoid 

(0.04), and forb (0.02) cover are all low. Though low in cover, 

graminoid cover is composed of perennial grasses rather 

than annual nonnatives. Tree cover consists of Juniperus 

osteosperma and two species of pinyon (Pinus monophylla

and Pinus edulis), which are also the strongest indicator 

species. The forb Eriogonum umbellatum, though low in 

cover, was primarily found with this plant assemblage and is 

therefore a moderate indicator.

In the high desert, we observed strong concordance 

between ESGs and floristic groups (table 8) and NMS axes 

Table 13. Floristic groups in the high desert climate zone 

identified by cluster analysis and indicator species analysis.

[In addition to functional groups, species with statistically significant

(p <0.05) indicator values are listed, followed by indicator value in 

parentheses. SD, standard deviation; N, number] 

Indicator Mean (SD) Min. Max.

Mixed shrublands (N = 7)

Total foliar cover 0.41 (0.07) 0.31 0.47

Woody cover 0.25 (0.08) 0.15 0.35

Graminoid cover 0.16 (0.08) 0.04 0.29

Annual cover 0.13 (0.09) 0.01 0.25

Avg. soil stability 2.12 (1.24) 1.06 4.28

Bromus rubens (74) 0.08 (0.09) 0.00 0.25

Atriplex canescens (58) 0.02 (0.01) 0.00 0.04

Ephedra viridis (55) 0.03 (0.02) 0.00 0.07

Yucca baccata (53) 0.02 (0.01) 0.00 0.04

Sagebrush shrublands (N = 16)

Total foliar cover 0.38 (0.13) 0.19 0.58

Woody cover 0.26 (0.08) 0.15 0.41

Graminoid cover 0.16 (0.13) 0.01 0.44

Annual cover 0.11 (0.13) 0.00 0.41

Avg. soil stability 2.47 (0.93) 1.17 4.29

Artemisia tridentata (84) 0.14 (0.08) 0.03 0.34

Bromus tectorum (49) 0.07 (0.08) 0.00 0.24

Sphaeralcea grossularifolia

(41) 0.01 (0.02) 0.00 0.05

Pinyon-juniper woodland (N = 19)

Total foliar cover 0.46 (0.11) 0.25 0.71

Woody cover 0.43 (0.11) 0.25 0.71

Graminoid cover 0.04 (0.05) 0.00 0.17

Annual cover 0.00 (0.00) 0.00 0.01

Avg. soil stability 2.60 (0.96) 1.33 4.94

Juniperus osteosperma (80) 0.30 (0.10) 0.10 0.43

Pinus monophylla (79) 0.06 (0.07) 0.00 0.27

Pinus edulis (63) 0.05 (0.06) 0.00 0.26

Eriogonum umbellatum (53) 0.00 (0.01) 0.00 0.02
Results 33

(fig.19). The deep basalt ESG was almost exclusively classified 

by the cluster analysis as a pinyon-juniper woodland. The 

shallow limestone ESG has both the mixed shrubland and 

sagebrush shrubland clusters (table 8). Several landscape and 

soil factors were strongly correlated with the first NMS axis but 

fewer significant correlations were found with the second and 

third axes (fig. 19). Axis-1 is positively correlated with high 

elevations, run-in topographic settings (high TWI and flow 

accumulation, shallow slope and curvature), and warm aspects 

(high solar insolation). Axis-1 is also negatively correlated with 

soil rockiness (amount of exposed bedrock, gravel cover, and 

all rock cover) and positively correlated with soil clay content. 

Axis-2 shows no correlation with landscape metrics but, like 

axis-1, is negatively correlated with rockiness (gravel cover 

and all rock cover). Axis-3 is also positively correlated with 

elevation and solar insolation but negatively correlated with 

surface sand content and available water capacity. 

Three groups were identified within the forest and 

savanna climate zone (table 14). Two of the groups are 

typified by different tree species with little understory (pinyon 

woodlands and juniper woodlands), whereas the third has a 

dense shrubby understory (forest shrublands). The final NMS 

has two dimensions, stress of 11.86, and instability of 0.00000. 

The pinyon woodlands have low average richness 

(7.2) and low diversity (0.65), similar to the pinyon-juniper 

woodlands. The high average total foliar cover (0.50) is 

composed mostly of woody cover (0.47), especially trees 

(0.37). This group does have some shrub cover (0.14), 

particularly Artemisia tridentata. Annual cover is negligible 

(0.01), so most of the graminoid cover (0.04) is attributable 

to perennial grasses. Pinus edulis and A. tridentata are strong 

indicators of this group, but Juniperus osteosperma and 

other shrubs do occur in smaller amounts. Soil stability is 

moderately stable (3.70).

The juniper woodlands have a moderate average species 

richness (11.2), but low diversity (0.64), similar to the 

pinyon-juniper woodlands and the pinyon woodlands. The 

high average total foliar cover (0.52) is also composed mostly 

of woody vegetation (0.48), particularly trees (0.40). This 

group, however, generally has very little shrub understory 

(0.09) and is characterized by J. osteosperma. Although Pinus 

monophylla and P. edulis occur, they are in much smaller 

amounts than in the pinyon-juniper woodlands and in the 

pinyon woodlands. Graminoid cover (0.07) is predominantly 

composed of the perennial Elymus elymoides. Soil stability is 

unstable to moderately stable (2.51), and only four of eleven 

plots have an average soil stability of 3 or more.

The forest shrublands, in contrast to the juniper woodlands 

and pinyon woodlands, have high average species richness 

(12.2) and diversity (0.82), despite the small sample size (N 

= 4). This group also has the highest average and overall total 

foliar cover of all eleven groups (0.62, ranging from 0.52 to 

0.73). Woody cover is the dominant type (0.53), but shrub and 

tree cover are generally balanced (0.26 and 0.33, respectively). 

Average graminoid cover is also higher than pinyon woodlands 

or juniper woodlands (0.22) and is composed mostly of 

perennial grasses. This group is characterized by the native 

perennial grass Poa fendleriana and the native shrubs Garrya 

flavescens, Quercus turbinella, and Purshia stansburiana. Soil 

stability is generally moderately stable (>3), but one plot had 

very low average stability (1.6).

Fewer landscape and soil factors were correlated with 

NMS axes in the forest and shrublands than in other climate 

zones (fig. 19), likely partly because only one ESG is 

identified in this climate zone (table 8). Axis-1 is negatively 

correlated with run-in positions (TWI), incoming solar gain 

(solar insolation), and soil rockiness (cobbles and total rock 

cover). Axis-2 is negatively correlated with run-in position 

(TWI) but is positively correlated with soil rockiness (total 

rock cover). 

Across the high desert and forest and savanna field 

plots, there is no association between plant diversity and 

soil variables measured and very little association between 

Table 14. Floristic groups in the forest and savanna climate zone 

identified by cluster analysis and indicator species analysis.

[In addition to functional groups, species with statistically significant 

(p <0.05) indicator values are listed, followed by indicator value in 

parentheses. SD, standard deviation; N, number] 

Indicator Mean (SD) Min. Max.

Pinyon woodlands (N = 4)

Total foliar cover 0.50 (0.06) 0.44 0.56

Woody cover 0.47 (0.06) 0.43 0.56

Graminoid cover 0.04 (0.07) 0.00 0.15

Annual cover 0.01 (0.02) 0.00 0.03

Avg. soil stability 3.70 (1.17) 2.13 4.61

Pinus edulis (80) 0.24 (0.11) 0.09 0.33

Artemisia tridentata (77) 0.05 (0.05) 0.01 0.11

Juniper woodlands (N = 11)

Total foliar cover 0.52 (0.08) 0.39 0.67

Woody cover 0.48 (0.09) 0.31 0.63

Graminoid cover 0.07 (0.05) 0.00 0.13

Annual cover 0.01 (0.01) 0.00 0.03

Avg. soil stability 2.51 (0.91) 1.12 4.28

Elymus elymoides (75) 0.02 (0.02) 0.00 0.07

Juniperus osteosperma (52) 0.34 (0.08) 0.19 0.50

Forest shrubland (N = 4)

Total foliar cover 0.62 (0.09) 0.52 0.73

Woody cover 0.53 (0.10) 0.41 0.65

Graminoid cover 0.22 (0.04) 0.17 0.27

Annual cover 0.00 (0.01) 0.00 0.01

Avg. soil stability 3.33 (1.24) 1.56 4.33

Poa fendleriana (79) 0.19 (0.07) 0.13 0.27

Garrya flavescens (72) 0.04 (0.04) 0.00 0.09

Quercus turbinella (67) 0.13 (0.05) 0.09 0.21

Purshia stansburiana (59) 0.04 (0.02) 0.02 0.07
34 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

diversity and landscape factors (fig. 19). The only significant 

correlation detected suggest locations that are hydrologically 

enhanced (high TWI and flow accumulation) are characterized 

by low diversity. 

Discussion

Patterns in Rangeland Health Indicators

The results presented here contribute to regional- and 

national-scale efforts aimed at developing robust conceptual 

models regarding the role soil, topographic, and climate 

properties play in controlling ecosystem resilience and 

vulnerability to land use and climate change (Steele and 

others, 2012; Bestelmeyer and others, 2016; Williamson and 

others, 2016). Organizing landscapes based on contextual 

information that (1) is generally static under managementrelevant time frames and (2) groups landscape units based on 

ecosystem response to management and climate provides a 

useful framework for management actions, policy decisions, 

as well as ecological investigations (Duniway, Bestelmeyer, 

and others, 2010). 

In the NPS-managed portions of the Grand CanyonParashant National Monument surveyed here (fig. 1), elevation 

gradients explain much of the broad-scale variation in soil 

and vegetation indicators, and associated rangeland health 

interpretations. Broad trends suggest a decrease in erosion risk 

with increasing elevation because of increasing vegetation 

cover, including a strong linear decrease in the cover of large 

canopy gaps and increase in litter cover (fig. 8A; Okin, 2008). 

However, other indicators that are important for soil and site 

stability and hydrologic function (table 1) either do not have 

strong elevational trends (for example, bare ground) or have 

trends that suggest decreasing function with elevation (for 

example, soil stability; Pellant and others, 2005). 

There are few strong associations between plant 

functional groups and elevation (with trees being the 

exception; fig. 9A), but there are strong species-level 

climate associations. This suggests that species turnover 

across elevation zones may represent species differences in 

adaptation to climates (fig. 9B). For example, there is a shift 

in the dominant shrub from Ambrosia dumosa in the low 

elevations to Coleogyne ramosissima in the middle elevations 

to Artemisia spp. in the high elevations. Upper limits for 

Larrea tridentata and C. ramosissima are likely attributable 

to temperature limits and freeze sensitivity (Beatley, 1974; 

Meyer and Pendleton, 2005), whereas the lower elevation 

boundaries for both C. ramosissima and Artemisia spp. likely 

represent a low aridity tolerance (Meyer and Pendleton, 2005; 

Schlaepfer and others, 2011). Similarly, the lower limit for 

Juniperus spp. is also likely governed by aridity. The upper 

limits of Artemisia spp. observed here are below known 

elevation and climate limits of Artemisia spp., which can 

likely be attributed to the increase of Juniperus spp. Increases 

in juniper and pinyon species cover into historic sagebrush 

shrublands and consequent decrease in other species is a 

common phenomenon observed across the western United 

States (McArthur and Plummer, 1978). Several of the plots 

recorded here, particularly in the pinyon-juniper woodland, 

pinyon woodland, and juniper woodland floristic groups 

likely represent some level of tree encroachment (table 7; van 

Auken, 2000).

Invasive Species

Invasive Bromus species are of great management concern 

in the intermountain west, primarily because of the increase 

in fire frequency associated with Bromus invasions (Beatley, 

1966; Balch and others, 2013). However, distributions of 

these species are likely to shift in response to climate change 

(Abatzoglou and Kolden, 2011). In particular, Bromus rubens

is likely to move up-slope, into areas where its distribution 

has been historically cold limited (Bradley and others, 2016). 

B. rubens is the most frequent invasive species of concern 

recorded in this study (fig. 9C), with a clear upper elevation 

limit (strong negative correlation with elevation in the high 

desert and forest and savanna climate zones; fig. 19). Forecasts 

for increasing temperatures in the southwestern United 

States (Garfin, 2014) suggest B. rubens may move to higher 

elevations of Grand Canyon-Parashant National Monument 

in coming decades. Soil associations from the middle desert 

suggest areas with higher risk of B. rubens are rocky soils with 

fine textures of the nonrock soil fraction (fig.16).

Schismus arabicus and Erodium cicutarium are also 

nonnative species of concern because of altered fire regimes 

and competition with native species (Brooks, 1999a, 2000; 

Steers and Allen, 2010). In this study, S. arabicus was 

more abundant in the low elevations with a strong negative 

correlation with elevation and an affinity for run-in locations, 

sites close to livestock water sources, and coarse soils 

(figs. 9C, 16), which agrees with observations in previous 

studies (Brooks, 1999b). E. cicutarium was found in both the 

low and middle deserts (fig. 9C) but showed little association 

with soil or landscape properties (figs. 16, 19). Similar to 

concerns regarding B. rubens, it is likely that S. arabicus will 

increase in frequency at high elevations as temperatures warm. 

Soils, Topography, and Ecosystems

The effect of the combination of climate, topography, 

and soils on ecosystem properties and processes, including 

resistance and resilience to drivers of change, is referred to as 

“ecological potential” or “land potential” (Caudle and others, 

2013; Bestelmeyer and others, 2015). The NRCS ecological 

site system is a land classification system based on concepts 

of ecological potential. Sites are differentiated primarily by 

climate, soil depth, soil rockiness, soil texture, soil mineralogy, 
Discussion 35

and site topographic setting (Duniway, Bestelmeyer, and 

others, 2010). Spatial information on ecological sites 

is provided through soil survey map units (Duniway, 

Bestelmeyer, and others, 2010). However, ecological site 

information is not yet standardized and available for all lands, 

leading to efforts to standardize methodologies (Caudle and 

others, 2013). Many ecological site descriptions (ESDs) with 

associated state-and-transition models are not yet complete 

for soil units in Grand Canyon-Parashant National Monument 

(Lindsay and others, 2003; Natural Resources Conservation 

Service, 2018). A proposed approach to streamline 

development of robust and data-driven ESDs is to create 

more generalized groups that fit within hierarchical classes 

(Bestelmeyer and others, 2016; Duniway and others, 2016; 

Salley and others, 2016). Indeed, it is fairly common to group 

ecological sites when using them to understand impacts of 

management on large heterogeneous landscapes (Duniway and 

Herrick, 2013; Munson and others, 2016). 

Here, we organized the 31 ecological sites we 

encountered into 10 ecological site groups (ESGs; table 6). 

These aggregations of ESDs (1–5 ESDs per group) explain 

important variability in the distribution of plant communities 

(strong correlation between ESGs and floristic groups; table 

8) and many indicators of rangeland health were found to 

vary systematically among ESGs (figs. 12, 15, 18), although 

the amount of indicator variation explained by ESGs 

varies greatly across climate zones. In the low desert, little 

differentiation in floristic groups was identified between 

the two non-gypsiferous ESGs (table 8). In the middle and 

high desert zones, there was generally strong concordance 

between ESGs and floristic groups. The two shallow ESGs 

were dominated by blackbrush shrublands floristic groups and 

the majority of plots in the two deep ESGs were classified as 

desert grasslands in the ordination. This pattern of shallow 

soils supporting shrubland communities and deeper soils 

supporting perennial grasslands follows patterns observed 

in other areas of the Colorado Plateau (Duniway and others, 

2016). We also see a pattern of shrublands (sagebrush and 

mixed shrubland) in the shallow ESGs in the high desert, 

however, in contrast to the middle desert, deep soil settings 

in the high desert support pinyon-juniper woodlands (table8). 

In some areas of the Colorado Plateau, sites with deep soil 

dominated by pinyon-juniper woodlands indicate woody 

expansion and departure from reference conditions (van 

Auken, 2000; Duniway and others, 2016).

In addition to concordance of ecosystem condition and 

ESGs, individual soil and landscape properties were also 

shown to have a strong control on plant communities and 

rangeland condition in many instances (McAuliffe, 1994; 

Duniway, Bestelmeyer, and others, 2010; Munson and 

others, 2015). The soil and landscape variables found to be 

important in governing rangeland conditions are consistent 

with other dryland plant-soil relations frameworks (Duniway, 

Bestelmeyer, and others, 2010): elevation, topographic setting 

(run-in/run-off characteristics, slope, aspect), amount of 

exposed bedrock, soil rockiness, soil texture (and associated 

hydrologic properties), and soil depth (figs. 13, 16, 19). There 

is variation in the relative importance of soil and landscape 

properties among climate zones and attributes of rangeland 

health. For example, landscape setting variables are less 

correlated with the ordination axis scores in the middle 

desert (fig. 16) than any of the other climate zones (figs. 

13, 19), suggesting a low importance of topographic setting 

in the middle desert. Similarly, associations between plant 

functional group cover and soil and landscape properties 

varied between climate zones, with woody species showing 

strong associations in the low desert, high desert, and forest 

and savanna zones and primarily herbaceous functional groups 

displaying significant correlations in the middle desert. 

Interestingly, cover of woody species displayed 

essentially opposite associations with soil texture in the lower 

than higher climate zones, with woody cover greater on welldrained sandy soils in the low desert versus finer textured and 

higher water-holding-capacity soils in the upper elevations. 

This inverse association of texture along an aridity gradient 

has been demonstrated in other studies (Sala and others, 

1988) and is thought to be due to the shifting importance of 

evaporative loss from the soil surface between arid and more 

mesic climates. Tree species cover, primarily Juniperus spp., 

was also high in run-in locations in the high desert and forest 

and savanna climate zones (fig. 19). Other work assessing 

topographic relations and woody encroachment has found 

that areas with high TWI were more susceptible to woody 

encroachment (Ben Wu and Archer, 2005). However, more 

work is needed in the Grand Canyon-Parashant National 

Monument pinyon-juniper woodlands to establish which 

woodlands are near reference condition and which represent 

an alternative state of a shrubland or more open savanna 

(Archer and others, 2017).

Evidence of Cattle Impacts

Grazing by domestic livestock is one of the most 

widespread land-use types in the region (Copeland and others, 

2017) and has been shown to affect dryland ecosystems both 

directly, through selective herbivory and hoof impacts, and 

indirectly via feedbacks with ecosystem processes, such 

as plant competition and plant-soil feedbacks (Branson 

and others, 1981; Warren and others, 1986; Fleischner, 

1994). Observations from this study support previous work 

demonstrating that grazing in drylands can lead to increases 

in bare ground and decreases in ground cover (Turner, 1971; 

Miller, 2008; Duniway and others, 2018). Here, we observed 

more bare ground and less ground cover in areas with high 

evidence of cattle use (figs. 13, 16, 19), suggesting reduced 

hydrologic function and soil and site stability with increased 

cattle activity (Pellant and others, 2005), including increased 

run-off and water erosion (Lusby, 1970; Branson and others, 

1981). Of added concern with loss of protective vegetative 

and ground cover in arid rangeland is risk of accelerated wind 
36 Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona

erosion and consequent dust emissions, which has been shown 

to increase in areas with heavy livestock use (Nauman and 

others, 2018). 

In general, improper grazing reduces overall vegetative 

cover and can alter vegetation composition, favoring 

unpalatable species and introduction of invasive species 

(Fleischner, 1994). In the survey results presented here, 

correlations between biotic integrity indicators and likely 

cattle use provide some evidence of these negative cattle 

impacts on Grand Canyon-Parashant National Monument 

allotments. The biotic integrity indicators that are of concern 

are Schismus arabicus in the low desert (increased frequency 

close to livestock water sources; fig. 13); decreases in 

Coleogyne ramosissima and Ephedra spp. with indicators 

of cattle use in the middle desert (fig. 16); and increases in 

Gutierrezia spp. (a species that commonly increases with 

livestock grazing pressure) with cattle indicators in all of 

the high-elevation areas (figs. 16, 19). Similar to what was 

observed here, Schismus arabicus has been shown to be more 

abundant in more disturbed areas in the western Mojave 

Desert (Brooks, 1999b). Evaluation of C. ramosissima

communities across a grazing gradient east of the study area 

(in and around Glen Canyon National Recreation Area) also 

showed decreases in C. ramosissima with increased grazing 

(Jeffries and Klopatek, 1987). However, the correlations 

between distance to water and C. ramosissima cover observed 

here are potentially confounded by the strong affinity of C. 

ramosissima for the shallow mixed ESG (fig. 14), which tends 

to occur farther from water (fig. 13). However, reduction 

of shrubs in winter-use shrub-dominated allotments has 

been observed in the region (Munson and others, 2016) and 

livestock are known to browse on shrubs to meet nutrient 

demands (Cook and others, 1954). 

It is noteworthy that we did not find evidence of cattle 

impacts on perennial grasses, given their importance as 

livestock forage. We attribute this to (1) generally low cover 

of perennial grasses in the study area (except for the deep 

limestone ESG in the middle desert; fig. 15), (2) winter use in 

many of the allotments where grazing is most prevalent (table 

2); and (3) stocking rates well below what is permitted (in 

most instances; table 2). Indeed, correlations between dung 

frequency and perennial grass within the deep limestone ESG 

suggests a negative trend (r = −0.45, p = 0.058). 

The dung frequency and distance from water approach 

used here to examine cattle impacts on Grand CanyonParashant National Monument allotments is essentially 

evaluating the role livestock distribution within pastures 

may play in allotment rangeland conditions, and the results 

described above suggest that cattle distribution in Grand 

Canyon-Parashant National Monument allotments could be 

better managed. Careful livestock distribution is one of the 

primary mechanisms for improving the health of western 

rangelands (Bailey and Rittenhouse, 1989). Several methods 

have been suggested for obtaining a more uniform distribution. 

Creating smaller pastures can help with achieving a more even 

distribution (Hart and others, 1993), though this may not be 

feasible given the remote and rugged nature of Grand CanyonParashant National Monument and the requirement of frequent 

movement of herds between pastures. Use of supplements has 

been shown to be successful to increase use of underutilized 

areas in large and rugged pastures in Montana (as much as 

600m from supplements; Derek and others, 2001), though 

other studies using salting stations did not find success in 

addressing serious livestock distribution problems in large 

pastures of an arid rangeland (Ganskopp, 2001). A potential 

long-term solution could be a breed change. Heritage breeds 

of cattle (for example, Raramuri Criollo cattle; Anderson and 

others, 2015) have been shown to have better distribution 

in large arid pastures when compared to the English breeds 

typically used by ranchers in the United States, with the largest 

differences observed where green forage is scarce (Peinetti 

and others, 2011; Spiegal and others, 2019).

Warming and drying predicted for the Desert Southwest 

will likely further decrease vegetative cover and exacerbate 

risk to rangeland ecosystems (Seager and others, 2007; 

Munson and others, 2011; Hoover and others, 2015). 

Furthermore, increased aridity and severity of drought 

will heighten risks of improper livestock management, 

particularly risk to wind erosion (Duniway and others, 2019). 

The results presented here suggest some improvements 

to livestock distribution are needed in the Grand CanyonParashant National Monument. However, our study did 

not include evaluation of areas without grazing (long-term 

exclosures), which can provide a valuable reference for better 

understanding rangeland condition in the absence of livestock 

(for example, Duniway and others, 2018). Additionally, our 

study relied on coarse proxies of cattle use (dung frequency 

and cost-distance to water). Better understanding of how 

cattle are distributed and their behaviors in different areas 

(that is, trailing versus grazing) would greatly increase our 

understanding of their impacts on Grand Canyon-Parashant 

National Monument allotments, such as the types of data 

available from modern GPS tracking collars (Ungar and 

others, 2005). Finally, these results support rangeland 

monitoring and assessment programs that collect indicators of 

soil and site stability (bare ground and ground cover) and do 

not rely solely on vegetation composition indicators to assess 

livestock management (Pellant and others, 2005; Toevs and 

others, 2011). 

Conclusion

The Grand Canyon-Parashant National Monument was 

established on January 11, 2000, to preserve the monument’s 

biologically diversity, “impressive landscape,” and an “array 

of scientific and historic objects.” In this survey of 155 

plots across the NPS-managed portions of the monument, 

we document a wide array of soils types, plant species, and 

communities, including 15 unique soil taxa (to great group 

level) and 271 plant species. We collected three new plant 

species for Grand Canyon-Parashant National Monument 
References Cited 37

and 17 new species for the NPS portion of the monument. 

We also demonstrate strong association between rangeland 

health indicators and plant community types with elevation, 

topographic setting, and soils. These results support the 

management of Grand Canyon-Parashant National Monument 

lands using land classifications based on concepts of land 

potential, such as NRCS ecological sites. However, given 

the tremendous size of Grand Canyon-Parashant National 

Monument and large number of ESDs present (based on the 

soil survey), we also suggest using groups of ecological sites 

for broad management questions, as was done here. There are 

existing efforts to formalize ecological site groups regionally 

that may facilitate Grand Canyon-Parashant National 

Monument management (Bestelmeyer and others, 2016; 

Duniway and others, 2016). Additionally, recent improvements 

in digital soil mapping may allow improved maps of ESGs 

for the monument (Maynard and Karl, 2017; Ramcharan and 

others, 2018; Maynard and others, 2019). 

The large area, rugged terrain, and remote nature of the 

Grand Canyon-Parashant National Monument makes access 

for field sampling of rangeland health indicators challenging 

and costly. Developments in satellite-based remote sensing of 

indicators may improve the efficiency of monitoring in Grand 

Canyon-Parashant National Monument (Jones and others, 

2018; Poitras and others, 2018), particularly if monitoring 

methods employed are compatible with other national-level 

programs (as was done here). Additionally, classification of 

field plots into ecological sites that are linked to state-andtransition models (Miller and others, 2011) can then be used 

to train remote-sensing-based classifications of landscapes 

into putative ecological states (Poitras and others, 2018). Such 

maps, coupled with ecological site (or group) maps, can then 

be used for landscape-scale management actions (Steele and 

others, 2012) or to understand climate sensitivities (Bunting 

and others, 2017; Thoma and others, 2018).

Based on the above, the next steps for a rangeland health 

monitoring program for the Grand Canyon-Parashant National 

Monument are: (1) integrate the ecological site groups 

developed here with regional grouping efforts and use these as 

a basis for monitoring; (2) leverage new digital soil mapping 

workflows and products to create more precise and accurate 

spatial depiction of ESGs; (3) develop a rangeland health 

monitoring strategy that leverages field and remote-sensingbased measures; and (4) utilize decision frameworks, such 

as state-and-transition models, for interpreting monitoring 

results and guiding management objectives. In this project, 

developing the ecological site groups for analysis and 

developing new themes and maps for sample design required 

significant expertise and resources. Completing steps 1 and 

2 above would streamline this for future assessments. Our 

ability to address study objectives was also limited by the 

high travel costs and difficult access for field work in Grand 

Canyon-Parashant National Monument. Incorporating remote 

sensing indicators (step 3) to expand sampling to remote areas 

(such as Lone Mountain) in future assessments will represent a 

substantial improvement. Finally, contextualizing assessments 

relative to known ecological processes and management goals 

is necessary for using rangeland assessments in decisionmaking processes. Development of group-level state-andtransition models (step 4) is one approach for translating 

assessment results into management decisions. Importantly, 

the data and interpretations from the 155 plots presented here 

are a valuable resource for achieving these next steps and will 

help Grand Canyon-Parashant National Monument staff better 

address potential threats to monument resources, including 

invasive species, unsustainable grazing by domestic livestock, 

and climate change. 

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42 

Appendix 1. Identification of Hydrologically Enhanced Areas

The identification of hydrologically enhanced areas was 

done using the maximum likelihood classification tool in the 

Spatial Analyst extension of ArcGIS (ver. 10.1). More than 

3,000 training polygons were manually digitized through 

examination of contemporary 1-meter color aerial imagery in 

the study area. Observers visually inspected aerial photographs 

with overlaid shaded-relief layers and created circular polygon 

features that either had (1) evidence of increased productivity 

or water accumulation (coded as “1”) or (2) were clearly 

upland areas without significant run-in (coded as “2”). These 

polygons were then used to create a supervised classification 

within shallow-slope soil-geologic strata (table 3) and, based 

on multiple terrain derivatives (table 1.1), signatures extracted 

and classified. Cells classified as hydrologically enhanced and 

with slopes less than 8° were then put into the “run-in” strata. 

This was accomplished using the model builder in ArcCatalog. 

Table 1.1. Raster input layers for the supervised classification of hydrologically enhanced areas used in the study sample design. 

[Derivatives were calculated using Spatial Analyst (ArcMap ver. 10.1) and a 10-meter digital elevation model (DEM) from the U.S. Geological Survey National 

Elevation Dataset (https://nationalmap.gov). m, meters] 

DEM-derived layer Description

Relative elevation Difference in elevation between local mean (0–20 m from cell center) and annular ring at 70 –80 m 

distance

Flow accumulation Mean of 1og10-flow accumulation in a 30 m radius around the target pixel

Distance to stream or other drainage Horizontal distance to stream or other drainage (identified using flow accumulation raster) based on 

water-flow patterns (using cost distance tool)

Height above stream or other drainage Elevation (in meters) above closest stream or drainage
Moffet Field Publishing Service Center, California 

Manuscript approved for publication April 27, 2020

Edited by Monica Edman

Layout and design by Kimber Petersen
Duniway and Palmquist—Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona—Open-File Report 2020–1040

ISSN 2331-1258 (online)

https://doi.org/10.3133/ofr20201040