Prepared in cooperation with The University of Arizona, School of Natural Resources and the 

Environment, Naval Facilities Engineering Command, Nauman Geospatial, National Park 

Service, and the U.S. Marine Corps 

An Inventory and Monitoring Plan for a Sonoran Desert 

Ecosystem: Barry M. Goldwater Range–West

Open-File Report 2011–1232

U.S. Department of the Interior

U.S. Geological Survey
 

Cover: Photograph of the Tinajas Altas Mountains partially obscured by dust during a high-wind event, October 

27, 2009. Photograph by Miguel L. Villarreal.
An Inventory and Monitoring Plan for a Sonoran Desert 

Ecosystem: Barry M. Goldwater Range–West

By Miguel L. Villarreal, Charles van Riper III, Robert E. Lovich, Robert L. Palmer, Travis Nauman, Sarah E. Studd, 

Sam Drake, Abigail S. Rosenberg, Jim Malusa, and Ronald L. Pearce

Prepared in cooperation with The University of Arizona, School of Natural Resources and the 

Environment, Naval Facilities Engineering Command, Nauman Geospatial, National Park 

Service, and the U.S. Marine Corps 

Open-File Report 2011–1232

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2011

For product and ordering information:

World Wide Web: http://www.usgs.gov/pubprod

Telephone: 1-888-ASK-USGS

For more information on the USGS—the Federal source for science about the Earth,

its natural and living resources, natural hazards, and the environment:

World Wide Web: http://www.usgs.gov

Telephone: 1-888-ASK-USGS

Suggested citation:

Villarreal, M.L., van Riper, Charles, III, Lovich, R.E., Palmer, R.L., Nauman, Travis, Studd, S.E., Drake, Sam, 

Rosenberg, A.S., Malusa, Jim, and Pearce, R.L., 2011, An inventory and monitoring plan for a Sonoran Desert 

ecosystem; Barry M. Goldwater Range–West: U.S. Geological Survey Open-File Report 2011–1232, 103 p., 

available at http://pubs.usgs.gov/of/2011/1232/.

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

endorsement by the U.S. Government.

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

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

Contents

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

Purpose and Scope ....................................................................................................................................................... 2

1.0 Introduction and Background................................................................................................................................... 3

1.1 Introduction .......................................................................................................................................................... 3

1.1.1 Barry M. Goldwater Range: Environmental Setting ....................................................................................... 3

1.1.2 Land Management .......................................................................................................................................13

1.1.3 Review of Range Status, Stressors and Drivers...........................................................................................14

1.2 Inventory and Monitoring Program Goals and Objectives ...................................................................................15

1.2.1 Inventory, Monitoring, and Adaptive Management .......................................................................................15

1.2.2 Inventory and Monitoring Program Goals and Objectives ............................................................................16

BMGR Management Policy Goals .....................................................................................................................17

BMGR Resource Management Goals ...............................................................................................................17

BMGR–West Management and Monitoring Objectives......................................................................................19

1.2.3 Sonoran Desert Regional Monitoring Partnerships.......................................................................................20

Barry M. Goldwater Range Executive Committee and Interagency Executive Committee ................................20

Barry M. Goldwater Range–East .......................................................................................................................21

National Park Service Sonoran Desert Network Inventory and Monitoring Program.........................................21

Organ Pipe Cactus National Monument ............................................................................................................21

Cabeza Prieta National Wildlife Refuge.............................................................................................................21

Sonoran Desert National Monument..................................................................................................................22

Yuma Proving Ground .......................................................................................................................................22

2.0 Methods..................................................................................................................................................................23

2.1 Workshop and Surveys.......................................................................................................................................23

2.2 Review of Existing Protocols and Protocol Development....................................................................................24

2.3 Monitoring Priority Matrix ....................................................................................................................................24

2.4 Sampling Design Considerations for the Inventory and Monitoring Program......................................................26

2.5 Monitoring Databases .........................................................................................................................................26

3.0 Background Information on Monitoring Protocols for the Inventory and Monitoring Plan........................................28

3.1 Vegetation, Soils, Water, and Climate.................................................................................................................28

3.1.1 Vegetation Inventory and Mapping...............................................................................................................28

Plant Inventory and Species Checklist...............................................................................................................29

Regional Monitoring Status................................................................................................................................30

3.1.2 Invasive Species ..........................................................................................................................................30

Regional Monitoring Status................................................................................................................................33

3.1.3 Vegetation Community and Soils .................................................................................................................33

Regional Monitoring Status................................................................................................................................34

3.1.4 Soil Inventory and Upland Erosion Monitoring..............................................................................................34

Regional Monitoring Status................................................................................................................................36

3.1.5 Stream-Channel Erosion Monitoring.............................................................................................................36

Regional Monitoring Status................................................................................................................................37

3.1.6 Tinajas, Tanks, and Developed Waters........................................................................................................37

Regional Monitoring Status................................................................................................................................39

3.1.7 Climate .........................................................................................................................................................39

Regional Monitoring Status................................................................................................................................41

3.2 Birds, Mammals, Amphibians and Reptiles.........................................................................................................42

3.2.1 Bird Monitoring .............................................................................................................................................42
iv

Regional Monitoring Status................................................................................................................................43

3.2.2 Small Mammals and Nocturnal Rodents ......................................................................................................43

Regional Monitoring Status................................................................................................................................43

3.2.3 Sonoran Pronghorn and Desert Bighorn Sheep ...........................................................................................44

Regional Monitoring Status................................................................................................................................46

3.2.4 Bat Guild.......................................................................................................................................................46

Regional Monitoring Status................................................................................................................................48

3.2.5 Amphibian and Reptile Surveys ...................................................................................................................48

Flat-Tailed Horned Lizard ..................................................................................................................................48

Cowles Fringe-Toed Lizard................................................................................................................................48

Desert Tortoise ..................................................................................................................................................50

General Herpetological Monitoring Approach ....................................................................................................50

Regional Monitoring Status................................................................................................................................52

3.3 Anthropogenic Impacts .......................................................................................................................................52

3.3.1 Transportation Corridors...............................................................................................................................52

Acquiring Aerial Imagery....................................................................................................................................52

Conducting Road Inventory ...............................................................................................................................54

Unauthorized Roads..........................................................................................................................................54

Road and Trail Erosion Monitoring ....................................................................................................................55

3.3.2 Visitor Use....................................................................................................................................................56

Visitor Permit Monitoring....................................................................................................................................56

Campsite Monitoring..........................................................................................................................................57

4.0 Data Management ..................................................................................................................................................58

4.1 Data Entry, Metadata, and Archiving...................................................................................................................58

4.2 Geospatial Data Management ............................................................................................................................58

4.3 Monitoring Data Repository: Location and Oversight..........................................................................................59

5.0 Management Actions as a Result of Inventory and Monitoring...............................................................................60

6.0 Programmatic Review of Monitoring and Management Activities ...........................................................................61

Acknowledgments ........................................................................................................................................................62

References Cited..........................................................................................................................................................62

Appendix A. Vegetation Inventory and Mapping Protocol.............................................................................................71

Appendix B. Invasive Species Monitoring Protocol.......................................................................................................73

Appendix C. Soil Inventory and Erosion Monitoring Protocol........................................................................................77

Appendix D. Small Mammals and Nocturnal Rodents Monitoring Protocol ..................................................................82

Appendix E. Bat Guild Monitoring Protocol...................................................................................................................87

Appendix F. Visitor Use Monitoring Protocol ................................................................................................................95

Appendix G. BMGR–West Workshop Participants, Followup Survey, and Survey Results ..........................................97

Figures

1.1. Map depicting the location of the Barry M. Goldwater Range within the Sonoran Desert Ecoregion, adjacent land 

management units, and natural features of the area........................................ ...................................................... 4 

1.2. Map depicting Barry M. Goldwater Range and adjacent land ownership................................................................ 6 

3.1. Completed and planned vegetation maps of southwestern Arizona ............................................................29 

3.2. Preliminary digital soils map of Barry M. Goldwater Range–West.........................................................................35

3.3. Developed waters of Barry M. Goldwater Range-West .........................................................................................38

3.4. Distribution of Remote Automated Weather Stations and other weather stations in areas surrounding Barry M. 

Goldwater Range-West ................................................................................................................................................40

3.5. The current Sonoran pronghorn range. .................................................................................................................44
v

3.6. Location of Arizona Game and Fish Department Bat Monitoring Sites on Barry M. Goldwater Range–West........47

3.7. Flat-tailed horned lizard Management Area, including plot locations, survey points and observation locations.....49

5.1. The relationship between an ecological monitoring program and management activities......................................60

Tables 

1.1. Natural vegetation community types of the Barry M. Goldwater Range.................................................................. 9 

1.2. Resource-specific management goals for Barry M. Goldwater Range ..................................................................18

1.3. Natural resource management objectives for the Barry M. Goldwater Range .......................................................20

2.1. Monitoring matrix showing monitoring elements by priority that was designed to help prioritize monitoring efforts

.....................................................................................................................................................................................25

3.1. Existing and potential invasive plant species located on Barry M. Goldwater Range lands...................................32

A.1. Percent cover system for vegetation mapping.......................................................................................................71

D.1 Small mammals and nocturnal rodents monitoring equipment list .........................................................................85

E.1. Bat guild monitoring equipment list........................................................................................................................90

E.2. Bat species codes .................................................................................................................................................91
vi

List of Acronyms

ABCI Arizona Bird Conservation Initiative

ACEC Areas of Critical Environmental Concern 

AKN Avian Knowledge Network

AMT Above Mean Terrain

ARIA Arizona Regional Image Archive

ARMI Amphibian Research and Monitoring Initiative

ARSC Arizona Remote Sensing Center

ASPRS American Society of Photogrammetry and Remote Sensing

AZGFD Arizona Game and Fish Department

BBS Breeding Bird Survey

BEC Barry M. Goldwater Range Executive Committee

BLM Bureau of Land Management

BMGR Barry M. Goldwater Range

CBP Customs and Border Protection 

CDC Center for Disease Control

CEDES Commission of Ecology and Sustainable Development for the State of Sonora (Mexico)

CEMML Center for Ecological Management of Military Lands

CONANP National Commission for Protected Natural Areas (Mexico)

CPNWR Cabeza Prieta National Wildlife Refuge 

DEM Digital Elevation Model

DHS Department of Homeland Security

DOD Department of Defense

DOI Department of the Interior

DOQ Digital Orthophoto Quadrangle 

DPS Distinct Population Segment

ECE Environmental Compliance Evaluations

EIS Environmental Impact Statement

EMP Ecological Monitoring Program

EMS Environmental Management System

EROS Earth Resources Observation Systems

ESA Endangered Species Act

FGDC Federal Geographic Data Committee

FSA Farm Service Agency

FTHL Flat-Tailed Horned Lizard (Phrynosoma mcallii) 

GBAFAF Gila Bend Air Force Auxiliary Field

GIS Geographic Information Systems

GPS Global Positioning System

GRS Geodetic Reference System

GRTS Generalized Random Tessellation Stratified 

GSD Ground Sample Distance 

HDMS Heritage Data Management System

HQMC Headquarters Marine Corps

I&M Inventory and Monitoring 
vii

IEC Interagency Executive Committee 

INRMP Integrated Natural Resources Management Plan

LAFB Luke Air Force Base

LIDAR Light Detection and Ranging

MA Management Area

MCAS-Yuma Marine Corps Air Station Yuma

MLWA Military Lands Withdrawal Act 

MMDM Mean Maximum Distance Moved

MODIS Moderate Resolution Imaging Spectroradiometer

MP Management Policy

MSCP Multiple Species Conservation Plan

NAD83 North American Datum 1983

NAIP National Agriculture Imagery Program

NAWMA North American Weed Management Association 

NDVI Normalized Difference Vegetation Index

NOAA National Oceanic and Atmospheric Administration

NPS National Park Service

NRCS Natural Resources Conservation Service 

NVCS National Vegetation Classification System

NWR National Wildlife Refuge

OALS Office of Arid Lands Studies

OCPO Outside Count-Period Observation

OPCNM Organ Pipe Cactus National Monument 

PMO Provost Marshal's Office 

QA/QC Quality Assurance and Quality Control

RAWS Remote Automated Weather Stations

RGB Red, Green, Blue

RMBO Rocky Mountain Bird Observatory

RMO Range Management Office

RMSE Root Mean Square Error

RUSLE Revised Universal Soil Loss Equation 

RWEQ Revised Wind Equation

SDNHM San Diego Natural History Museum

SDNM Sonoran Desert National Monument

SDRS Sonoran Desert Research Station

SEINet Southwest Environmental Information Network

SNM Saguaro National Monument

SODN Sonoran Desert Network

SOP Standard Operating Procedure

SPH Sonoran Pronghorn (Antilocapra americana sonoriensis)

SRMA Special Recreation Management Area 

SSURGO Soil Survey Geographic Database 

TON Tohono O’odham Nation

UA University of Arizona

UA-SNRE University of Arizona-School of Natural Resources and Environment
viii

UDA Undocumented Aliens

USAF U.S. Air Force

USBP U.S. Border Patrol

USDA U.S. Department of Agriculture

USFS U.S. Forest Service

USFWS U.S. Fish and Wildlife Service 

USGS U.S. Geological Survey

USMC U.S. Marine Corps

USNG U.S. National Grid 

USPED Unit Stream Power based Erosion and Deposition 

UTM Universal Transverse Mercator

WEQ Wind Erosion Equation 

WGS World Geodetic System

WGS84 World Geodetic System 1984

WRCC Western Regional Climate Center

YPG Yuma Proving Ground
1

An Inventory and Monitoring Plan for a Sonoran Desert 

Ecosystem: Barry M. Goldwater Range–West

By Miguel L. Villarreal,1 Charles van Riper III,2 Robert E. Lovich,3 Robert L. Palmer,

3 Travis Nauman,4 Sarah E.

Studd,5 Sam Drake,6 Abigail S. Rosenberg,7 Jim Malusa,1 and Ronald L. Pearce7

Abstract

Marine Corps Air Station Yuma manages the Barry M. Goldwater Range–West, which 

encompasses approximately 2,800 square kilometers of Sonoran Desert habitat in southwestern Arizona. 

The Barry M. Goldwater Range is a major U.S. military installation designed as an air combat training 

location for the U.S. Marine Corps and U.S. Air Force, but it also includes some of the most pristine 

desert habitat in the United States. In an effort to ensure the long-term viability of this unique natural 

resource, the U.S. Geological Survey (USGS) has developed an Integrated Natural Resources 

Management Plan and Inventory and Monitoring Plan to guide natural resource management of the 

Barry M. Goldwater Range–West. This Inventory and Monitoring Plan provides a framework for longterm ecosystem monitoring on Barry M. Goldwater Range–West lands by identifying existing and 

potential threats to ecosystem function, prioritizing resources for monitoring, and providing information 

and protocols necessary to initiate a long-term ecosystem monitoring program. The Inventory and 

Monitoring Plan and related protocols were developed through extensive review of existing Sonoran 

Desert monitoring programs and monitoring literature and through a 2-day workshop with resource 

managers, monitoring experts, and other stakeholders. The Barry M. Goldwater Range–West Inventory 

and Monitoring Plan stresses the importance of regional monitoring partnerships and protocol 

standardization for understanding landscape-scale ecosystem changes in the Sonoran Desert; 

information and protocols contained within the plan may also be of interest to land managers engaged in 

large-scale ecosystem monitoring and adaptive management of other arid regions. 

Key Words: Inventory and Monitoring, Ecosystem Monitoring, Sonoran Desert, Marine Corps, Barry 

M. Goldwater Range, Adaptive Management

 

1

 University of Arizona, School of Natural Resources and the Environment, Tucson, AZ, 85721 

2

 U.S. Geological Survey, Sonoran Desert Research Station, Tucson, AZ, 85721 

3

 Naval Facilities Engineering Command (NAVFAC) Southwest, San Diego, CA, 92132 

4 Nauman Geospatial, Flagstaff, AZ, 86001 

5

 National Park Service, Sonoran Desert Network, Tucson, AZ, 85710 

6

 University of Arizona, Office of Arid Lands Studies, Tucson, AZ, 85719 

7

 Marine Corps Air Station, Yuma, AZ, 85369 
2

Purpose and Scope

The purpose of this report is to provide background information to facilitate long-term 

ecosystem monitoring of Sonoran Desert ecosystems, specifically the natural resources of the Barry M. 

Goldwater Range–West. The report includes information on existing monitoring efforts in the Sonoran 

Desert, cooperative monitoring activities, and background information on key natural resources, and it 

reviews monitoring techniques and monitoring protocols. 
3

1.0 Introduction and Background 

1.1 Introduction

The Barry M. Goldwater Range (BMGR) in southwestern Arizona is a major U.S. military 

installation, encompassing 7,050 square kilometers (km2

) of land designated as an air combat training 

location for the U.S. Marine Corps (USMC) and the U.S. Air Force (USAF). The Range is separated 

into two components: BMGR–West (~2,800 km2) managed by Marine Corps Air Station Yuma 

(MCAS-Yuma) and BMGR–East (~4,250 km2) managed by Luke Air Force Base (LAFB). While the 

primary mission of MCAS-Yuma and LAFB is to train military aircrews to fly combat missions, the 

range occupies a significant area of Federal lands recognized for their diverse natural resources, cultural 

resources, and outdoor recreation opportunities. A requirement of both the Sikes Act of 1960 and the 

Military Lands Withdrawal Act (MLWA) of 1999 was the development and implementation of an 

Integrated Natural Resources Management Plan (INRMP) (Integrated Natural Resources Management 

Plan, 2007) to facilitate a program that provides for the conservation and rehabilitation of natural 

resources and the sustainable multipurpose use of the resources. In compliance with the INRMP, 

MCAS-Yuma entered into a cooperative agreement with the U.S. Geological Survey (USGS) Sonoran 

Desert Research Station (SDRS) to develop an Inventory and Monitoring (I&M) Plan for the BMGR–

West. To facilitate the management of natural resources on the BMGR–West , a long-term natural 

resources inventory and monitoring plan was developed based on the management objectives of the 

BMGR–West and through the input of natural resource experts, cooperators, and stakeholders. This plan 

addresses the major environmental and conservation concerns of the BMGR–West and presents a set of 

monitoring protocols to inventory natural resources and to identify and track changes in these resources 

over time. Furthermore, the I&M Plan provides a compendium of existing monitoring efforts within the 

Sonoran Desert region and a discussion of their relevance to monitoring and management of natural 

resources across the BMGR–West. 

1.1.1 Barry M. Goldwater Range: Environmental Setting

The BMGR is located in southwestern Arizona, within the Lower Colorado River Valley 

Subdivision of the Sonoran Desert Ecoregion (fig. 1.1). The area is part of the basin and range province 

characterized by long, thin mountain ranges separated by wide alluvial valleys. Elevation within the 

BMGR ranges from <61 m in the alluvial valleys to 1,220 m at the Sand Tank Mountains. 

The BMGR and surrounding areas are characterized by extreme aridity and high temperatures, 

particularly during the summer months. Temperature of the area ranges from an average high of 106.1°F 

in July to an average low of 39.1°F in January (http://www.wrcc.dri.edu/; Yuma Citrus Station, 1920–

2005). The area received an average annual precipitation of 87 mm during 1920–2005 

(http://www.wrcc.dri.edu/; Yuma Citrus Station).
4

Figure 1.1. Map depicting the location of the Barry M. Goldwater Range within the Sonoran Desert Ecoregion, 

adjacent land management units, and natural features of the area.
5

Because of the lack of precipitation, surface water is extremely limited on the 

BMGR. There are no perennial streams; however, ephemeral streams flow in response to 

large precipitation events during the summer monsoon (July–August). The main surfacewater resources on the BMGR are natural tanks, or “tinajas,” rock catchments that store 

small amounts of runoff following precipitation events. The U.S. Fish and Wildlife Service 

(USFWS) and Arizona Game and Fish Department (AZGFD) maintain several water 

sources to support wildlife populations, particularly the endangered Sonoran pronghorn 

(Antilocapra americana sonoriensis) and the desert bighorn sheep (Ovis canadensis 

mexicana). 

The BMGR is nationally significant as a major component of the largest remaining 

tract of relatively unfragmented Sonoran Desert in the United States that, with the 

exception of State Route 85 (fig. 1.2), is free of major developments that may disrupt 

ecological connectivity. The tract currently totals about 12,950 km2

 and, in addition to the 

BMGR, includes the adjacent, ecologically linked areas of Organ Pipe Cactus National 

Monument (OPCNM), Cabeza Prieta National Wildlife Refuge (CPNWR), Sonoran Desert 

National Monument (SDNM), Tohono O’odham Nation (TON), and other lands 

administered by the Bureau of Land Management (BLM; fig. 1.2). Additional protected 

areas surrounding BMGR that are separated by constructed barriers include El Pinacate y 

El Gran Desierto Biosphere Reserve in Mexico (which shares approximately 60 km of the 

U.S.-Mexican border with BMGR–West ), Kofa National Wildlife Refuge, and the U.S. 

Army Yuma Proving Ground (YPG) north of Interstate 8 (fig.1.2).
6

Figure 1.2. Map depicting Barry M. Goldwater Range and adjacent land ownership.
7

The BMGR’s extensive east-west land base includes a wide range of soils, geology, 

landforms, and vegetation types that are typical of the Sonoran Desert Ecoregion. Fifteen 

mountain ranges exist on the BMGR and are composed of igneous, metamorphic, and 

sedimentary rock types. The western section of BMGR falls within the Gran Desierto dune 

system, which extends to the west and south into Mexico. The Mohawk dune system of 

BMGR–West, located in the center of the range, is smaller and independent of the Gran 

Desierto dune system. Hall and others (2001) described and coarsely mapped the native 

vegetation communities, which include the Valley Bottom Floodplain Complex, Valley 

Xeroriparian Scrub, Mountain Xeroriparian Scrub, Dune Complex and Dune Endemics, 

Creosotebush-Bursage Desert Scrub, Creosotebush-Big Galleta Scrub, Paloverde-Mixed 

Cacti-Mixed Scrub, Sand Tank Mountains Uplands, Elephant Tree-Limberbush on Xeric 

Rocky Slopes, Desert Playa, and Salt Desert Scrub (table 1.1). These vegetation 

communities provide habitat for a number of rare, threatened, or endangered species, 

including the Sonoran pronghorn, desert bighorn sheep, Le Conte’s thrasher (Toxostoma 

lecontei), Cowles fringe-toed lizard (Uma rufopunctata), flat-tailed horned lizard 

(Phrynosoma mcallii), desert tortoise (Gopherus agassizii), crucifixion thorn (Castela 

emoryi), and harwood milk-vetch (Astragalus insularis var. harwoodii) (Hall and others, 

2001). 
8

This page intentionally left blank
9

Table 1.1. Natural vegetation community types of the Barry M. Goldwater Range (Hall and others, 2001).

Natural community Composition Spatial pattern and distribution Comments

Valley Bottom

Floodplain Complex

 

 

 

Characteristic vegetation includes

creosotebush, triangle-leaf bursage, white 

bursage, acacias, paloverdes, mesquites, and 

annual and perennial grasses.

Linear/large patch system that

is likely endemic to the

Sonoran Desert Ecoregion

 

Linear xeroriparian areas may be embedded within the 

complex. As a community type that is characterized by 

a shifting mosaic of vegetation patches spread across a 

floodplain, it also can be considered a large patch 

system.

Valley Xeroriparian

Scrub

Characteristic vegetation is highly

variable and includes blue paloverde, 

ironwood, mesquite, foothill paloverde, 

herbaceous and woody perennial vines, and 

sparse annual grasses and forbs.

Linear system that is likely to

be distributed throughout the

Sonoran Desert and Mojave

Desert Ecoregions.

Mesquite bosques (Prosopis spp.) can be associated 

with this community. Significant examples of bosques 

on the BMGR need to be documented. See comment 

below in regard to Mountain Xeroriparian Scrub.

Mountain

Xeroriparian Scrub

 

 

Characteristic vegetation is highly

variable but typically consists of

paloverdes, ironwood, mesquites, and 

succulents.

Linear system that is likely to

be distributed throughout the

Sonoran Desert and Mojave

Desert Ecoregions.

Although its spatial pattern is characterized as linear, it 

may create a mosaic pattern with associated matrix and 

large-patch communities that is repeated frequently 

across the landscape.

Dune Complex and

Dune Endemics

 

 

 

 

 

 

 

 

 

 

 

Complex is generally sparsely vegetated by 

scattered forbs and grasses. May include 

shrubs and

dwarf-shrubs such as white

bursage. Stabilized dunes may

support creosotebush and

mesquites while active dune fields

may lack vegetation.

 

Large patch system that

occurs throughout the

Sonoran and Mojave Desert

Ecoregions.

 

Sonoran Desert endemic (E)/limited (L) plants that 

demonstrate a strong association with the dune 

complex are included within this element’s description. 

These plants include:

Astragalus insularis var. harwoodii (E)

Astragalus magdalenae var. peirsonii (E)

Croton wigginsii (L)

Cryptantha ganderi (E)

Eriogonum deserticola (E)

Euphorbia (= Chamaesyce) platysperma (E)

Helianthus niveus (L)

Pholisma sonorae (E)

Stephanomeria schottii (E)

Triteleiopsis palmeri (E).1
10

Table 1.1. Natural Vegetation Community Types of the Barry M. Goldwater Range (Hall and others, 2001).—Continued

Natural community Composition Spatial pattern and distribution Comments

CreosotebushBursage Desert

Scrub

 

 

 

 

 

Vegetation is primarily dominated by 

creosotebush. Woody and nonwoody cacti 

and rosette succulents commonly occur on 

rocky slopes.

Seasonally present perennial

grasses with some perennial forbs dominate 

the sparse herbaceous layer.

Matrix-forming system that

occurs throughout the Sonoran 

and Mojave Desert Ecoregions.

 

None

 

Creosotebush-Big

Galleta Scrub

 

 

 

Dominant shrub is creosotebush.

Big galleta is the sole or dominant grass in the 

herbaceous layer.

White or triangle-leaf bursage can be a codominant.

Large patch system that occurs in 

the Sonoran Desert and also may 

occur in the Mojave Desert.

 

None

 

Paloverde-Mixed

Cacti-Mixed Scrub

on Bajadas

 

 

 

 

 

 

 

 

Vegetation has a conspicuous but relatively 

sparse layer of saguaro cactus. A sparse to 

moderately

dense short tree/tall shrub canopy

is also present consisting of

paloverde and creosotebush, along with 

ironwood and ocotillo in lesser prominence. A 

sparse herbaceous layer dominated by 

perennial grasses and forbs with seasonal 

annuals is present.

Matrix-forming system that 

occurs only within the Sonoran 

Desert.

 

None

 

Paloverde-Mixed

Cacti-Mixed Scrub

on Rocky Slopes

 

 

 

This community is of similar

composition to that of the

Paloverde-Mixed Cacti-Mixed

Scrub on Bajadas, but contains

additional associates such as

Opuntia bigelovia. 

Large patch system that occurs 

throughout the Sonoran Desert.

 

None

 
11

Table 1.1. Natural Vegetation Community Types of the Barry M. Goldwater Range (Hall and others, 2001).—Continued

Natural community Composition Spatial pattern and distribution Comments

Sand Tank

Mountains Uplands

 

 

 

 

 

 

 

 

 

Vegetation in this complex

includes saguaro cactus and a

sparse to moderately dense short

tree/tall shrub canopy consisting of

paloverde and creosotebush.

Typical associates include

crucifixion thorn and Vaquelinea

californica sonorensis. Also

present is a sparse herbaceous layer 

dominated by perennial grasses and forbs.

Large patch system that occurs in 

the Sonoran Desert; in addition 

to the Sand Tank

Mountains, limited in 

distribution to a few highelevation mountain ranges 

throughout the Sonoran Desert; 

includes an unusual combination 

of plant species.

 

Unusual combination of plants that occur only at high 

elevations are included within this element’s 

description. These plants include:

Canotia holocantha

Juniperus coahuilensis

Vaquelinia californica sonorensis.

2

 

Elephant TreeLimberbush on

Xeric Rocky Slopes

 

 

 

 

 

 

 

The composition of this community is similar 

to that of the Paloverde-Mixed Cacti-Mixed 

Scrub system, but is characterized by 

additional associates. Elephant tree, 

limberbush, Nolina bigelovii, and Rhus 

kearnyi are dominant in a mixed canopy. 

Vegetation of this system may differ with 

substrate.

Large patch system that occurs in 

arid mountain ranges within the 

Lower Colorado Valley, Central 

Gulf Coast, and Arizona Uplands 

subdivisions of the Sonoran 

Desert. On the BMGR it occurs 

on the western mountain ranges 

(Cabeza Prieta, Copper, Gila, 

and Tinajas Altas Mountains).

None

 

Desert Playa

 

 

 

 

 

 

 

Generally desert playas in the central Sonoran 

Desert are sparsely vegetated, with periodic 

emergence of ephemeral species. Large 

playas in the Sonoran Desert may have 

surrounding rings of vegetation. 

Characteristic vegetation differs between 

playas and unpredictable annuals may 

emerge.

Large patch system that occurs 

throughout the Sonoran Desert 

and may occur in the Mojave 

Desert.

None
12

Table 1.1. Natural Vegetation Community Types of the Barry M. Goldwater Range (Hall and others, 2001).—Continued

Natural community Composition Spatial pattern and distribution Comments

Desert Tinaja/Spring

 

 

 

 

Tinajas are typically small aquatic ecosystems 

formed through water accumulation in 

bedrock depressions. Vegetation is typically 

absent or present as a few individual plants.

Small patch system that occurs 

throughout the desert southwest.

None

Salt Desert Scrub

 

 

 

 

 

 

 

 

 

 

 

 

 

Two main types of saltbush communities 

occur. Saltbush communities found along 

major riverine systems typically have been 

converted to agriculture. The drier upland 

type is associated with creosotebush and 

numerous cactus species. The community is 

dominated by the xeromorphic shrub Atriplex 

polycarpa. The sparse to moderately dense 

graminoid layer may be dominated by warm 

season medium-tall and short grasses. Forb 

cover is generally sparse.

Large patch system that occurs 

throughout the desert southwest.

Specific occurrences still need to be mapped on the 

BMGR. 

1

The occurrence of each of these species on the BMGR is documented as follows: Astragalus insularis var. harwoodii, Mohawk Dunes (Felger and others, 1997) 

and Yuma Dunes (Center for Ecological Management of Military Lands [CEMML] unpublished data); Astragalus madgalenae var. peirsonii, Yuma Desert 

northwest of Yuma Dunes (unpublished data; collected by D. Turner and identified by R. Felger); Croton wigginsii, Yuma Dunes (Felger and others, 1997; Warren 

and Laurenzi, 1987); Cryptantha ganderi, Mohawk Dunes (Felger, 2000, Felger and others, 1998); Eriogonum deserticola, Yuma Dunes (CEMML, Felger and 

others, 1997, Warren and Laurenzi, 1987); Euphorbia (= Chamaesyce) platysperma, Yuma Dunes (CEMML, Warren and Laurenzi, 1987); Helianthus niveus, 

Yuma Dunes (CEMML, Warren and Laurenzi, 1987); Pholisma sonorae, Yuma Dunes (CEMML, Felger and others, 1997, Warren and Laurenzi, 1987); 

Stephanomeria schottii, Mohawk Dunes (Felger and others, 1997, Warren and Laurenzi, 1987) and Yuma Dunes (CEMML, Warren and Laurenzi, 1987); 

Triteleiopsis palmeri, Yuma Dunes (CEMML, Felger and others, 1997, Warren and Laurenzi, 1987).

2

The occurrence of each of these species on the BMGR is documented in Felger and others (1997).
13

1.1.2 Land Management 

The BMGR INRMP identifies the protection of natural resources and sustainable public 

use as fundamental goals of the range management, provided that management and use are 

consistent with military purposes of the range. Three Federal agencies and one State agency 

(USAF, USMC, USFWS, and AZGFD) share responsibilities for natural resource management 

within the BMGR. A fifth agency, BLM, has reserve oversight roles but no direct resource 

management responsibilities. The USAF and USMC have primary surface management 

responsibility for BMGR lands and related natural and cultural resources. The Secretaries of the 

Navy, Air Force, and Interior jointly prepared the INRMP, and the Secretary of the Interior 

remains involved in the management of natural and, to a lesser extent, cultural resources within 

the BMGR. The Secretary of the Interior acts through the Director of the USFWS when 

participating in the preparation and implementation of INRMPs. Furthermore, USFWS maintains 

responsibilities for administering compliance with the Endangered Species Act of 1973 and 

Migratory Bird Treaty Act of 1918 within the BMGR. 

The MLWA of 1999 designates BMGR land as (1) an armament and high-hazard testing 

area, (2) an area for training for aerial gunnery, rocketry, electronic warfare, and tactical 

maneuvering and air support, and (3) an area for other defense-related purposes. The impacts on 

natural resources from military training and weapons testing are estimated to be minimal and 

generally contained within relatively small and discrete areas. Only a small percentage (~3 

percent) of soil and vegetation resources has been highly disturbed by military training activities 

(Integrated Natural Resources Management Plan, 2007. A majority of BMGR–West lands have 

received no disturbance or low disturbance from military training activities over the past six 

decades and have been preserved and protected in a relatively natural state (Integrated Natural 

Resources Management Plan, 2007). 

The commitment of the USMC to resource conservation has helped to limit degradation 

of much of the BMGR environment. The ecological integrity of the BMGR has been maintained 

over the past 60 years because (1) most land uses that are known to have negative ecological 

effects (for example, urban development and infrastructure, cattle grazing, unmanaged and 

poorly enforced recreation) have been excluded from the range in order to effectively carry out 

military training operations, and (2) only a small percentage of the restricted land area is 

physically disturbed by military training activities. Operational or other safety requirements 

restrict both habitation and economic development of the range and specify that recreational uses 

be controlled by MCAS-Yuma. Land-use activities such as livestock grazing, mining, 

agriculture, and residential/commercial development have been legally excluded from the range 

since the 1940s (Integrated Natural Resources Management Plan, 2007). 

The State of Arizona has primary jurisdiction over resident wildlife management within 

the BMGR, and the AZGFD implements this jurisdiction on behalf of the State. The AZGFD’s 

mission is to “conserve, enhance, and restore Arizona’s diverse wildlife resources and habitats 

through aggressive protection and management programs, and to provide wildlife resources and 

safe watercraft and off-highway vehicle recreation for the enjoyment, appreciation, and use by 

present and future generations.” 

Approximately 80 percent of all range areas open to general public access is located 

within BMGR–West. The area of BMGR–West usually open to public access encompasses about 
14

75 percent of the BMGR–West land area (about 2,100 km2). Portions of this area are at times 

closed to public access to support regularly scheduled activities that present safety hazards or 

have security requirements. Beginning in 2001, a portion east of the Copper Mountains (fig. 1.1) 

has been closed to public access each year for the fawning season of the Sonoran pronghorn, a 

Federally-listed endangered species. The fawning season is from March 15 to July 15 and 

represents the period of greatest sensitivity to animal disturbance. The road network approved for 

public use within affected areas includes 790 km of roads. 

Within the BMGR–West, the AZGFD is responsible for three major monitoring and 

management activities:

• Hunting: issuing hunting permits and enforcing hunting regulations. Establishing game limits 

for hunting, trapping, and non-game species collection;

• Wildlife management: developing and maintaining habitat assessment/evaluation, protection, 

management, and enhancement projects (for example, artificial water developments and 

Sonoran pronghorn food plots). Conducting wildlife population surveys and managing 

wildlife predators and endangered species/special status species (management of Federally 

listed endangered species is a responsibility shared with the USFWS); and 

• Recreation: managing off-highway vehicles in terms of habitat protection and user 

opportunities. 

Specific AZGFD management activities on the BMGR include conducting annual 

bighorn sheep and golden eagle (Aquila chrysaetos) surveys and maintaining wildlife watering 

holes. 

1.1.3 Review of Range Status, Stressors and Drivers

There are a number of anthropogenic stressors and natural environmental drivers 

affecting Sonoran Desert ecosystems that may result in various degrees and types of habitat 

degradation. Such phenomena can lead to species extirpation or extinction. Biota of the Sonoran 

Desert Ecoregion evolved to survive and reproduce under extreme environmental conditions and 

with limited resources. However, these biotas can become stressed when scarce resources are 

further limited or degraded by competition with hardier nonnative species or through 

anthropogenically induced physical degradation. Disturbed vegetation and soils in arid 

environments tend to have long recovery times, and many restoration and revegetation efforts 

have low success rates (Lovich and Bainbridge, 1999; Webb and others, 2009). Anthropogenic 

stressors and natural ecosystem drivers with potential to impact ecosystem function at the 

BMGR–West include invasive plants and animals, human population growth, adjacent 

agricultural land use, off-highway vehicle and recreation impacts, military and U.S. Border 

Patrol (USBP) activities, prolonged drought, disease, wildfire, and others. The following is a 

short list and description of the chief stressors and drivers with potential to compromise 

ecosystem integrity of BMGR–West:

Invasive Plants and Animals.—Invasive plants and animals are of great concern to land 

managers throughout the Sonoran and Mojave Deserts (Tellman, 2002; Brooks and others, 

2004). If left undetected, unmonitored, and unmanaged, nonnative herbaceous species—for 

example, Sahara mustard (Brassica tournefortii), buffelgrass (Pennisetum ciliare), and red 

brome (Bromus rubens)—could fundamentally alter BMGR’s ecosystem structure through 

competition with native species, reduction of species diversity and enhancing the spread of 
15

wildfires. Nonnative animals also threaten ecosystem function—the European starling (Sturnus 

vulgaris), which has been identified on the BMGR, is associated with urban 

development/encroachment and is known to compete for resources with native cavity-nesting 

birds. Invasive animal species pose an even more insidious threat, in that they have been 

documented to harbor parasites and diseases from their native species ranges, sometimes even 

from other continents (Warburton and others, 2002; Kuperman and others, 2004). 

Roads, Trails and Off-highway Vehicles.—The creation of new roads and the continued 

use of existing roads can affect ecosystem function in numerous ways: roads function as 

corridors for the spread of invasive species (Rutman and Dickson, 2002), are directly associated 

with native species mortality, can restrict species range through habitat fragmentation and direct 

disturbance (Forman and Alexander, 1998; Duncan and others, 2010), and can alter the 

hydrological functions of a given area. In general, roads affect soil cover by displacing, adding 

to, or changing its physical and compositional structure. Alterations of soil conditions and 

hydrological function in turn influence water availability to native vegetation. 

Regional Population Growth and Recreation.—Urban growth and rural development in 

areas surrounding the BMGR have direct and indirect effects on ecosystem function. Air 

pollution, water pollution, water use, and habitat fragmentation outside of the range boundary 

can profoundly impact ecosystem function and dynamics inside the management area. Local and 

regional population growth may lead to increased visitor and recreation uses, thus intensifying 

pressures on BMGR natural resources through the creation of trails and roads, vegetation 

trampling, and soil compaction, and from possible resource extraction activities such as hunting, 

collecting (for example, rocks, reptiles, and others), or even poaching. 

Military Training Operations.—Military training activities, including live ordnance 

jettison, air combat training flights, and large vehicle maneuvers, are known to affect ecosystem 

function directly (that is, soil compaction) or indirectly (that is, aircraft noise levels) (Prose and 

Wilshire, 2000; Webb, 2002). Training activities are part of the BMGR’s primary military 

mission and are restricted to designated areas of the range (see section 1.1.2). 

Drought and Climate Change.—Drought and climate change are regional and global 

drivers of ecosystem change that land managers rarely have control over at their management 

scale. However, land managers can implement management strategies that help to minimize 

climate impacts on resident biota. Knowledge about drought, and climate patterns and forecasts, 

can help managers prepare for alternate future scenarios. The American Southwest has 

experienced drought for the past decade, and some climate models predict a continued drought 

under climatic warming (Seager and others, 2007). Increased temperatures and variable 

precipitation events related to drought and climate change will likely affect BMGR–West by 

decreasing soil moisture, increasing drought stress, and decreasing the availability of surfacewater resources.

1.2 Inventory and Monitoring Program Goals and Objectives

1.2.1 Inventory, Monitoring, and Adaptive Management

A typical Inventory and Monitoring program commences with an extensive inventory of 

resources followed by systematic, long-term monitoring. An Inventory is a point-in-time 

collection of information describing the occurrence, spatial distribution, and condition of a given 
16

resource. Inventories are typically designed to locate populations of species, locate all species 

within a specific area, describe the habitat of a species or assess ages, sizes, and conditions of 

individuals within a population. As a point-in-time collection, an inventory often becomes the 

starting point for a monitoring program. The two may be decoupled in time, however, if prior 

work only included disjunct inventories, or rapid assessments, without the follow-up of a 

monitoring component as the next step. Monitoring is a means to detect trends in a resource over 

time and is typically accomplished by measuring resources at the same locations over time. 

Elzinga and others (2001) define monitoring as “the collection and analysis of repeated 

observations or measurements to evaluate changes in condition and progress toward meeting a 

management objective.” 

A statistically sound and robust monitoring program is a prerequisite for management 

activities aimed at restoring or maintaining ecosystem function. Adaptive management is a 

systematic and iterative learning process whereby management objectives are informed by 

management outcomes. Adaptive management is designed to reduce management uncertainties, 

to better understand how ecological systems function, and to provide information required to 

achieve desired management outcomes. The following is a working definition of adaptive 

management proposed by the National Resource Council and adopted as a standard definition by 

the Department of the Interior ( Williams and others, 2009): 

Adaptive management is a decision process that promotes flexible decision making that can 

be adjusted in the face of uncertainties as outcomes from management actions and other 

events become better understood. Careful monitoring of these outcomes both advances 

scientific understanding and helps adjust policies or operations as part of an iterative 

learning process. Adaptive management also recognizes the importance of natural variability 

in contributing to ecological resilience and productivity. It is not a “trial and error” process, 

but rather emphasizes learning while doing. Adaptive management does not represent an end 

in itself, but rather a means to more effective decisions and enhanced benefits. Its true 

measure is in how well it helps meet environmental, social, and economic goals, increases 

scientific knowledge, and reduces tensions among stakeholders. 

It is suggested that adaptive management be considered once a monitoring program is 

initiated and change in a monitoring parameter is detected (established by means of a threshold 

value determined beforehand). Adaptive management decisions may not be initiated based on 

monitoring data alone but may require additional, well designed, and targeted scientific research. 

In such a case, monitoring data serve as guidance for identifying potential hypotheses for 

changing conditions and to inform the design of additional research. It is the aim of the 

investigators to employ a strategy of adaptive management based on the outcome of the 

inventory and monitoring efforts and resulting data and analyses. 

1.2.2 Inventory and Monitoring Program Goals and Objectives 

Successful monitoring programs are structured around clear management objectives. 

Objective-based monitoring programs support adaptive management by establishing desired 

conditions for specific resources (Elzinga and others, 2001). In addition to supporting 

management activities, the success of a monitoring plan can only be evaluated relative to goals 

and objectives stated beforehand. BMGR goals and objectives for natural resource monitoring 

and management were established during the INRMP planning process (Integrated Natural 
17

Resources Management Plan, 2007). Goals and objectives specific to BMGR–West were 

explicated further by monitoring experts and stakeholders during the monitoring protocol 

development workshop facilitated by the USGS and University of Arizona (UA). 

BMGR Management Policy Goals

Resource management goals were developed to guide the INRMP in accordance with 

BMGR legal requirements (that is, MLWA and Sikes Act) to address military mission 

requirements of the range and interests of other stakeholders (that is, USFWS, AZGFD, USBP 

and selected Native American tribes). Five non-resource-specific management policy (MP) goals 

established during the INRMP planning process were: 

1. MP1—Maintain and enhance the natural resources to ensure that these resources are 

sustained in a healthy condition for compatible uses (for example, low-impact recreation) by 

future generations, while supporting the existing and future military purposes of the BMGR. 

2. MP2—Manage cultural resources in accordance with the BMGR Integrated Cultural 

Resources Management Plan.

3. MP3—Allow for public access to BMGR resources for sustainable multipurpose uses that are 

consistent with the military purposes (that is, security and safety requirements) and 

ecosystem sustainability.

4. MP4—Apply ecosystem management principles through a goal- and objective-driven 

approach that recognizes social and economic values; is adaptable to complex, changing 

requirements; and is realized through effective partnerships among private, local, State, 

Tribal, and Federal interests.

5. MP5—Meet or exceed the statutory requirements of the MLWA of 1999, Sikes Act, and 

other applicable resource management regulatory requirements.

BMGR Resource Management Goals

Eleven resource-specific goals were specified further to guide the INRMP process that 

address soil, water, vegetation, wildlife, visual resources, transportation, recreation, Native 

American access, nonmilitary and perimeter land use, and special natural/interest areas (table 

1.2). 
18

Table 1.2. Resource-specific management goals for Barry M. Goldwater Range (adapted from Integrated 

Natural Resources Management Plan, 2007).

Resource Management Goal(s)

Soil resources • Implement best management practices to control and prevent excessive soil erosion, 

implement soil conservation measures, and restore or rehabilitate degraded 

landscapes wherever practicable, subject to budgetary constraints.

Water resources • Manage water resources to protect, maintain, and improve water quality; water 

conservation to prevent aquifer depletion; and ensure regulatory compliance while 

maintaining unrestricted access for military purposes.

Vegetation

resources

• Protect and conserve plant communities and species diversity.

• Identify, protect, conserve, manage, and ensure regulatory compliance for 

threatened and endangered plant species or otherwise important or sensitive plant 

species.

• Inventory exotic plant species occurrence and distribution and implement 

management measures for their removal or control.

• Restore or rehabilitate altered or degraded plant communities wherever practicable, 

subject to budgetary constraints.

• Incorporate the principles of ecosystem management and promote biodiversity.

Wildlife

resources

• Protect and conserve wildlife habitat, species diversity, and viable populations.

• Identify, protect, conserve, manage, and comply with regulatory requirements for 

federally threatened and endangered wildlife species or otherwise significant or 

sensitive species.

• Restore or rehabilitate human-altered or degraded wildlife habitats wherever 

practicable, subject to budgetary constraints.

• Incorporate the principles of ecosystem management and promote biodiversity.

• Control trespass livestock, or other nonnative species.

Visual resources • Protect or enhance the integrity and diversity of visual resources (that is, scenic 

landscape qualities) on the BMGR.

Transportation • Develop a BMGR transportation plan that addresses continued land-based access 

for military training and testing; provide access for wildlife research and wildlife 

habitat management, land management, and law enforcement by Federal and State 

agencies; and provide public access for wildlife-oriented recreation and sustainable 

multipurpose use.

• Establish policies and provide procedures that ensure vehicle use on the BMGR is 

controlled and directed to protect resources, promote safety, and minimize multi-use 

conflicts.

Recreation • Provide public access and use of natural resources for sustainable multi-purposes 

when such activities are compatible with mission activities and other considerations 

such as security, safety, and resource sensitivity.

• Assess the continuing applicability of Special Recreation Management Area 

(SRMA) designations in consideration of their incompatibility with military 

operations.

• Manage all activities in accordance with the INRMP for the BMGR.
19

Table 1.2. Resource-specific management goals for Barry M. Goldwater Range (adapted from Integrated 

Natural Resources Management Plan, 2007).—Continued

Resource Management Goal(s)

Native American

access

• Provide for Native American access to Traditional Cultural Places and sacred sites, 

consistent with the military mission and natural resource management goals.

Non-military

land use

• Develop a program for addressing rights-of-way on the BMGR.

• Participate in local initiatives to advance ecoregional planning and biodiversity 

goals.

Perimeter land

use

• Cooperate with land managers of adjoining property for conservation, public 

relations, and compliance benefits.

• Develop strategies, in coordination with ranchers when feasible, to reduce trespass 

livestock occurrences.

Special

natural/interest

areas

• Recognize and review existing special resource management areas, such as Areas of 

Critical Environmental Concern (ACEC) and the backcountry byway, and assess the 

continuing applicability of special management provisions for the protection of these 

areas.

BMGR–West Management and Monitoring Objectives

During the August 26, 2009, workshop held at the University of Arizona, participants 

assisted in refining the BMGR–West natural resource management objectives and developing 

basic monitoring strategies to guide I&M Plan development. Table 1.3 contains the original 

management objectives and modified objectives created to specifically guide the monitoring 

process. 
20

Table 1.3. Natural resource management objectives for the Barry M. Goldwater Range. 

Original management objectives Modified management objectives

Manage to control invasive species Identify (location, source and transmission), assess, eradicate, 

reduce, mitigate, and/or minimize problematic invasive species

Minimize erosion (wind, water, and others) Identify (natural events), avoid, and control problematic erosive and 

deleterious landscape impacts

Maximize partnerships, including international 

partnerships, and engage public/demonstrate 

stewardship

Expand and integrate with local, regional, and international 

partnerships to enhance resource management. Enhance public 

outreach and recognition of military operations and stewardship

Ensure that the base functions as a wildlife 

preserve without compromising military 

activities

Ensure that the base functions to conserve plant and animal 

communities without compromising military activities. 

Improve base resource management through 

sound science

Apply natural resource management and protections using sound 

scientific principles and data acquisition

Regional comparability of information/data Integrate and/or enhance regional inventory and monitoring data 

throughout the Sonoran Desert ecosystem

Meet regulatory requirements under the law Exceed and/or meet natural resource inventory and monitoring 

regulatory requirements

Rehabilitate where needed Identify, restore and/or enhance degraded or impacted habitats

Track basic ecosystem functions Identify and monitor ecosystem functions 

Responsive/compatible with adaptive 

management

Implement adaptive resource management

1.2.3 Sonoran Desert Regional Monitoring Partnerships

There are several active monitoring programs in the Sonoran Desert Ecoregion, and one 

objective of the BMGR–West I&M Plan is to facilitate integration of regional monitoring 

programs through protocol standardization and establishment of a central data repository. This 

section describes the organizations responsible for existing monitoring programs in the region 

and the resources monitored, as well as committees and partnerships fostering collaborative 

management.

Barry M. Goldwater Range Executive Committee and Interagency Executive Committee 

The Barry M. Goldwater Range Executive Committee (BEC) was formed in August 1997 

to provide a forum for collaborative management of BMGR lands, resources, and their uses. As a 

result of the MLWA of 1999, land management of the BMGR was transferred from the BLM to 

the LAFB and MCAS-Yuma commanders. LAFB and MCAS-Yuma manage BMGR resources 

through collaborative processes with several agencies that have a vested legal interest in the 

lands, including BLM, USFWS, AZGFD, USBP, and directors for the adjacent SDNM, 

OPCNM, and CPNWR. Together, these entities form the BEC and provide oversight of 

management activities on the range. The BEC is chaired by the Director of the 56th Fighter 

Wing Range Management Office, LAFB, Ariz. The BEC addresses resource management issues 

and conflicts arising from land uses on the BMGR or affected by the BMGR with the intention 
21

of resolving those issues and conflicts. Past subcommittees include: Pronghorn, Public Relations, 

Law Enforcement, Transportation, Natural Resources, and Cultural Resources. Membership was 

limited to agencies with direct responsibility for lands or resources on the BMGR or directly 

affected by military or other activities on the BMGR. 

The Interagency Executive Committee (IEC), as mandated by the MLWA of 1999, is a 

public outreach forum with the purpose of exchanging views, information, and advice related to 

the management of the natural and cultural resources of the BMGR lands. 

Barry M. Goldwater Range–East

The 1.05-million-acre BMGR–East, managed by LAFB, borders BMGR–West, CPNWR, 

TON, and SDNM. In August 2007, the BMGR–East, 56th Range Management Office published 

an Inventory and Monitoring Plan: Barry M. Goldwater Range–East, and it has since 

implemented several components of the plan, including vegetation, bird, and climate monitoring. 

The BMGR–East plan adopted several protocols from existing regional monitoring programs, 

allowing for integration of BMGR–West and BMGR–East monitoring efforts, collaboration, and 

data sharing. 

National Park Service Sonoran Desert Network Inventory and Monitoring Program

The Sonoran Desert Network (SODN) is 1 of 32 National Park Service (NPS) inventory 

and monitoring networks implementing “vital signs” monitoring to assess the condition of park 

resources. Specifically, NPS-SODN is implementing an integrated natural resource monitoring 

program for 11 national park units (10 in Arizona and 1 in New Mexico). Of the 11 park units 

monitored by SODN, 2 are of particular interest for BMGR monitoring partnerships: OPCNM 

and Saguaro National Monument (SNM). Both parks are biologically representative of the 

Sonoran Desert Ecoregion, sharing similar climate, landform, biological, and vegetation 

elements with BMGR. The network began monitoring landbirds and streams in 2005, air quality 

in 2006, and vegetation and soils in 2007. 

Organ Pipe Cactus National Monument

Organ Pipe Cactus National Monument (OPCNM) was established in 1937 under the 

Antiquities Act to preserve a representative portion of the Sonoran Desert ecosystem as well as 

its namesake, the organ pipe cactus (Stenocereus thurberi). The 1,335-km2 park developed an 

extensive in-house ecosystem monitoring program before the establishment of the NPS-SODN 

I&M program. Monitoring activities at OPCNM date back to the 1970s, and many monitoring 

projects were formalized and integrated in 1994 with the development of an Ecological 

Monitoring Program (EMP) (Organ Pipe Cactus National Monument, 2006). OPCNM’s EMP 

was integrated with other SODN parks beginning in 2001 with the establishment of the SODN 

I&M program. Current monitoring protocols at OPCNM relevant to BMGR monitoring include 

those related to vegetation and soils, amphibians, reptiles, climate, small mammals, bats, and 

anthropogenic impacts. 

Cabeza Prieta National Wildlife Refuge 

Cabeza Prieta National Wildlife Refuge (CPNWR) was established as a Wildlife Refuge 

in 1939 “for the conservation and development of natural wildlife resources.” Since the 
22

Endangered Species Act of 1973, CPNWR has become central in the recovery and protection of 

the endangered Sonoran pronghorn. CPNWR staff have conducted general inventories of birds, 

plants, mammals, and herpetofauna and developed a vegetation map of Sonoran pronghorn 

habitat for an NPS cooperative project supported by OPCNM and the BLM, Yuma Office. The 

vegetation map includes the distribution of 20 plant associations and subassociations (Malusa, 

2003). CPNWR staff have been actively monitoring border-related anthropogenic impacts, 

mapping roads, and monitoring change in road networks across the refuge. CPNWR staff are 

currently (2011) in the process of developing a more comprehensive I&M plan. 

Sonoran Desert National Monument

The Sonoran Desert National Monument (SDNM) has been managed by the BLM 

Phoenix Field Office since its designation by President Clinton in 2001. Before 2001, the area 

was part of BMGR–East and managed by LAFB. This relatively new National Monument has no 

monitoring program is yet in place; however, a draft biological resource inventory compiled 

from literature searches and direct observation is available online at 

http://aznps.com/Floras/sdnm.pdf (Turner and others, 2000). 

Yuma Proving Ground 

The U.S. Army Yuma Proving Grounds (YPG) encompasses approximately 3,390 km2 of 

the Sonoran Desert in southwestern Arizona. The YPG is the Army's center for desert natural 

environment testing and artillery; target acquisition equipment and armament, vehicles, a variety 

of munitions, personnel and supply parachute systems, and other specialized equipment are 

tested at YPG. The YPG supports more than 320 species of plants, 33 species of reptiles and 

amphibians, and 47 species of mammals native to the Sonoran Desert (Yuma Proving Ground, 

2010). One hundred thirty-seven native bird species have been documented on the installation, of 

which 49 species breed on YPG (YPG, 2010). 

No plants or resident animal species with protection under the Endangered Species Act 

are known to occur on YPG, with the possible exception of the endangered Nichol's Turk's head 

cactus (Echinocactus horizonthalonius var. nicholii) and the threatened Sonoran Desert Distinct 

Population Segment (DPS) of the bald eagle (Haliaeetus leucocephalus).
23

2.0 Methods

Development of this long-term natural resources I&M plan was based on the needs and 

objectives of the MCAS-Yuma and goals specified in the INRMP. The I&M Plan addresses the 

major environmental and conservation concerns of the BMGR–West and is organized to include 

an inventory and monitoring priority matrix and associated monitoring protocols. The four main 

objectives specified in the I&M Plan are to: 

1. Identify the natural resources on the BMGR–West that are sensitive to changing land use, 

climate, and biological conditions. 

2. Identify and resolve gaps in the current BMGR–West inventorying and monitoring 

efforts. 

3. Prioritize inventory and monitoring efforts on BMGR–West.

4. Identify regionwide monitoring efforts and standardize inventory and monitoring 

protocols for regional stakeholders. 

In addition to input from stakeholders and local experts, development of the I&M Plan 

for BMGR–West was guided by a comprehensive review of relevant research, monitoring, and 

natural history literature. Methods include four main components: (1) surveys of monitoring 

experts and facilitation of a monitoring workshop to identify sensitive resources and monitoring 

approaches, (2) development of a comprehensive plan based on relevant literature and existing 

monitoring protocols, (3) development of a monitoring priority matrix, and (4) development of 

monitoring databases based on proposed data parameters described in the protocols. 

2.1 Workshop and Surveys

The U.S. Geological Survey facilitated a monitoring workshop (August 26-27, 2009) 

designed to gather input from cooperators and local stakeholders. Workshop participants 

included representatives from AZGFD, CPNWR, NPS SODN, LAFB, OPCNM, Pima County, 

San Diego Natural History Museum (SDNHM), San Diego Zoo, UA, USFWS, USMC, U.S. 

Navy, USGS, and YPG. Before the workshop, a monitoring questionnaire was emailed to 15 

scientists and resource managers. The questionnaire was designed to identify key protocols, 

methods, and parameters used for monitoring natural resources in Sonoran Desert ecosystems 

and gather recommendations for BMGR–West monitoring efforts (appendix G). 

Workshop coordinators compiled and presented a list of target resources and monitoring 

approaches identified by both questionnaire respondents and the BMGR INRMP. The first 

workshop component was a series of presentations describing monitoring efforts and resource 

issues facing Sonoran Desert land managers, which included land managers and researchers from 

BMGR–West , Pima County Sonoran Desert Conservation Plan, NPS SODN I&M Program, 

USGS, and UA. The remainder of the workshop consisted of a series of group and subgroup 

exercises meant to refine resource lists, provide information on available data sources, review 

monitoring methods, and provide general direction for the monitoring program. 

A workshop follow-up survey (hosted online, September 21–28, 2009) was designed to 

help prioritize monitoring efforts and develop a monitoring priority matrix. The survey consisted 

of 10 questions, 1 related to general resources and 9 related to specific resources monitoring. 
24

Respondents were asked to rank the elements in each question in terms of monitoring priority for 

the BMGR–West. Each survey question had a blank field for additional comments. A link to an 

online survey was emailed to all 26 workshop participants, and 22 participants completed the 

survey. Survey questions and results are provided in appendix G. 

2.2 Review of Existing Protocols and Protocol Development

The plan and associated protocol documents were developed by examining and reviewing 

existing monitoring programs and protocols in the Sonoran Desert and other arid regions. 

Existing protocols were identified during the monitoring workshop or identified by reviewing 

pertinent monitoring and scientific literature. Included, with little revision, are several welldeveloped and tested protocols implemented on other public lands in the region (for example, 

protocols for Vegetation Community and Soils, and Birds). In some cases protocols were 

compiled from multiple sources and tailored to BMGR–West resources (for example, protocols 

for Small Mammals and Nocturnal Rodents, and Bat Guild). In cases where existing monitoring 

programs are currently (2011) in progress on BMGR–West lands, relevant protocols and 

information were excerpted, or references to the protocol and monitoring agencies were included 

(for example, protocols for flat-tailed horned lizard, and Sonoran pronghorn and desert bighorn 

sheep). In cases where no protocol existed or where existing protocols seemed inappropriate, a 

basic monitoring strategy was proposed that addresses management needs but requires additional 

on-site research and development before implementation. These special-case protocols deal 

primarily with monitoring disturbances and stressors specific to BMGR–West environs (for 

example, invasive plants, transportation corridors, and soil erosion), as opposed to monitoring 

natural communities or individual species. 

2.3 Monitoring Priority Matrix

A monitoring matrix (table 2.1) was designed to prioritize and facilitate annual 

monitoring efforts by ranking the relative importance of each natural resource element based on 

survey responses from cooperators and stakeholders (appendix G). The matrix consists of a 

series of natural resources with assigned monitoring priorities of high, medium, or low based on 

the conservation status of the resource, the current monitoring effort, and the potential impact to 

resources from military training and public use. The protocols included in this document are for 

all high-priority resources. Protocols for some medium- and low-priority resources are included 

if they were covered under the protocols for high-priority resources (for example, Water Quality 

monitoring within Seeps, Springs and Tinajas), if the resources are subject to compliance 

monitoring under the ESA (for example, Sonoran pronghorn), or if the resources have been 

monitored historically at BMGR–West as rare or threatened species of concern (for example, 

flat-tailed horned lizard). Each priority element of the matrix is assigned a monitoring protocol 

based on the best available information. These protocols are meant to provide natural resource 

managers of MCAS-Yuma with sufficient information and appropriate citations to implement 

monitoring of the resources on the BMGR–West.
25

Table 2.1. Monitoring matrix showing monitoring elements by priority that was designed to help prioritize 

monitoring efforts.

Sub-element Priority Protocol(s) in document Referemces

Vegetation (high priority)

Invasive species High Invasive Species (3.1.2) North American Weed Management 

Association, 2002

Vegetation communities High Vegetation Community and 

Soils (3.1.3)

Harrick and others, 2005a,b; Hubbard and 

others, 2009; Malusa 2009

Climate (high priority)

Precipitation High Climate (3.1.7) World Meteorological Organization, 

1983

Temperature Medium Climate (3.1.7) World Meteorological Organization, 

1983

Anthropogenic impacts (high priority) 

Transportation corridors High Transportation Corridors (3.3.1) Drake and others, 2004

Visitor use High Visitor Permit and Campsite 

(3.3.2) 

Cole, 1986

Military Medium Transportation Corridors (3.3.1) Drake and others, 2004

Water resources (high priority)

Seeps, springs, and tinajas High Tinajas, Tanks and Developed 

Waters (3.1.6)

Broyles 1997

Birds (medium priority)

General Bird surveys High Bird Monitoring (3.3.1) Powell and others, 2007

Mammals (medium priority)

Bat guild High Bat Guild (3.2.4) Petrysyzn, 1994; Arizona Game and Fish 

Department, 1997

Sonoran pronghorn High Sonoran Pronghorn Survey 

(3.2.3)

Arizona Game and Fish Department, 2006

Nocturnal and small 

mammals

High Small Mammals and Nocturnal 

Rodents (3.2.2)

Organ Pipe Cactus National Monument, 

2006; Powell and others, 2007

Desert bighorn sheep Medium Desert Bighorn Sheep Survey 

(3.2.3)

Arizona Game and Fish Department, 2006

Amphibians (medium proiority) 

General smphibians High Amphibian and Reptile Surveys 

(3.2.5)

Heyer and others, 1994

Reptiles (medium priority) 

Flat-tailed horned lizard High Flat-tailed Horned lizard (3.2.5) Flat-tailed Horned Lizard Interagency 

Coordinating Committee, 2003

Reptile inventory High Amphibian and Reptile Surveys 

(3.2.5)

Heyer, 1994

Desert tortoise Low Desert Tortoise (3.2.5) Averill-Murray, 2000; Arizona Game and 

Fish Department, 2007

Soil (medium priority)

Channel change/washes High Stream-Channel Erosion (3.1.5) Wiberg and Smith, 1989

Soil erosion (roads and 

other infrastructure)

High Soil Inventory and Upland 

Erosion Monitoring (3.1.4)

Mitasova and Mitas,1999
26

2.4 Sampling Design Considerations for the Inventory and Monitoring Program

The purpose of sampling is to make statistical inferences about a population without 

conducting a complete census of the population, which often is prohibitively expensive and time 

consuming. The number of sample units (sample size), spatial distribution of sampling units, and 

sample frequency vary according to monitoring objective and particular protocol. The aim of a 

sound sampling design is to provide scientifically defensible monitoring data which can be used 

to make general inferences beyond the sites sampled. The sample size and sampling frequency 

required to detect changes in a monitoring parameter are affected by many factors. Below are 

several important considerations: 

1. What are the monitoring objectives? 

2. What precision is required in change or trend? 

3. What is the likely variability of monitoring data (based on collected data or literature 

review)?

4. How will the data be analyzed?

5. How many years of data are required to detect a trend?

6. How many times a year will sampling occur?

7. What is the availability of resources and manpower? 

The spatial distribution of sampling locations typically follows a randomized approach, 

with the exception of resources with discrete locations and small areal coverage, such as tinajas. 

“Judgment-based” or “representative” sampling sites chosen by experts can introduce bias into 

the data, may come under criticism, and would be best avoided, if possible. However, additional, 

targeted sampling of special interest areas (for example, Mohawk dunes) or increased sampling 

at certain locations of interest (for example, soil erosion monitoring near highly disturbed areas) 

is appropriate once a randomized sample design is in place. Simple random sampling is, in most 

cases, not ideal for landscapes like BMGR–West with rugged terrain and few major roads. 

Therefore, to minimize travel time to a sample location, and to maximize field safety and data 

collection, it may be necessary to restrict sampling to areas within a pre-set distance from roads 

and/or by not sampling areas of dangerous or extreme topography. Discussions on randomized, 

spatially balanced sample designs can be found in Stevens and Olsen (2004). Co-location of 

monitoring sites (for example, vegetation, soils, and climate stations) may also reduce costs and 

has the added benefit of providing additional ecological information to guide management 

decisions. For more information about sampling designs and statistical techniques for analyzing 

monitoring data see Schreuder and others (2004) and Elzinga and others (2001). Elzinga and 

others (2001) provide a good general discussion on the importance of power analysis of data 

collected in monitoring programs, and Cohen (1988) details power analysis techniques for the 

most common statistical tests and includes power tables.

2.5 Monitoring Databases

Monitoring databases were developed to manage and store data collected for each 

monitoring/survey protocol on the BMGR–West. When possible, databases were constructed to 

be compatible with existing I&M databases utilized by land managers of the Sonoran Desert. 

Databases developed for the I&M Plan described in this report use Microsoft Excel, Microsoft 
27

Access or ESRI Geodatabases, depending on the spatial requirements and relational complexity 

of the monitoring variables collected (see section 4.1). 

Spatial data collected for USMC are stored in GEOfidelis Geodatabase format. 

GEOfidelis is a common database infrastructure that supports inter-operability across the USMC, 

allowing for integration of monitoring data with existing spatial data sets (see section 4.2).
28

3.0 Background Information on Monitoring Protocols for the Inventory and 

Monitoring Plan 

The background sections below provide the following general summaries of (1) the 

protocol for each variable to be monitored, including general techniques and key information to 

be collected, (2) the authors and organizations that developed the protocol, (3) organizations in 

the region currently (2011) implementing the protocol, and (4) caveats and suggestions for 

tailoring the protocols to the BMGR–West environment. Where applicable, protocols, standard 

operating procedures (SOPs), and data sheets are shown in appendixes. 

3.1 Vegetation, Soils, Water, and Climate

3.1.1 Vegetation Inventory and Mapping

An inventory map describing the vegetation of the BMGR–West is under development 

and expected to be completed by 2014 (fig. 3.1; Malusa, 2009). The purpose of the mapping 

effort is to develop a comprehensive vegetation map and GIS database for the BMGR–West to 

enable management of the vegetation communities and also provide a baseline for ecosystem 

management. In addition to mapping, it is suggested that all plant species previously 

undocumented at the BMGR–West be described or collected and delivered to the Installation 

Representative for an herbarium collection.
29

Figure 3.1. Completed and planned vegetation maps of southwestern Arizona (Malusa, 2009).

Plant Inventory and Species Checklist

The vegetation mapping field team collects and presses plant specimens of any 

previously unrecorded species on the BMGR–West (Malusa, 2009). Herbarium species 

collections consist of three sets of specimens, two mounted sets and one laminated set, with one 

of the mounted sets stored in an archival container. All new plant species are documented with 

photographs and location coordinates and added to the GIS vegetation database (Malusa, 2009). 

A floristic inventory of the BMGR–East was published in 1996 and may provide a draft 

checklist and plant inventory for the BMGR–West (Arnett and Douglas, 1996). Additional plant 

collections from the BMGR–West are available at the Southwest Environmental Information 

Network (SEINet) database at http://swbiodiversity.org/seinet/. SEINet hosts data for a large 

number of specimens collected on the BMGR–West that were submitted and verified by UA 

Herbarium, Arizona State Vascular Plant Herbarium, Northern Arizona University Deaver 

Herbarium, Herbario de la Universidad de Sonora, Desert Botanical Garden Herbarium 

Collection, University of California Riverside Plant Herbarium, and New York Botanical 
30

Garden. Some of the species vouchers date back to the 1930s, but a large number were collected 

in recent decades by Felger and VanDevender. SEINet records contain information on species 

collected and verified, collector’s name, collection date and location (written description and 

approximate coordinates), and general species information. 

Regional Monitoring Status

The eastern half of CPNWR and portions of BMGR–East were mapped using the 

protocols and classification system described in appendix A (Malusa, 2003, 2009). The 

classification system was designed to be cross-walked with the USGS/NPS National Vegetation 

Classification System (NVCS) currently (2011) used for vegetation mapping at SODN park units 

(see Drake and others, 2009) as well as the Brown, Lowe, and Pase system used for earlier NPS 

maps (see Warren and others, 1981). The existing, 30-year-old vegetation map of OPCNM 

(Warren and others, 1981) will be updated in 2012 by SODN as part of the NPS I&M Vegetation 

Mapping Program. CPNWR (Cabeza Prieta National Wildlife Refuge, 1995), BMGR–East 

(Arnett and Douglas, 1996), OPCNM (Schmidt and others, 2006) and SDNM (Turner and others, 

2000) all have some level of plant inventory. 

3.1.2 Invasive Species

Human-induced and natural biological invasions into new regions, whether accidental or 

deliberate, have increased at unprecedented rates in the past few hundred years (D’Antonio and 

Vitousek, 1992). Once established, nonnative plant species introductions often lead to changes in 

ecosystem processes (such as fire frequency, size, and intensity, or altered nutrient levels) that 

are self-maintaining and evolving, leading to functional as well as compositional ecosystem 

change (Brooks and others, 2004). Invasive nonnative species are estimated to cause more than 

$100 billion in economic damage annually in the United States alone (Pimentel and others, 

1999). In addition to competing with and displacing native species, these introduced species can 

hybridize with native species and alter conditions to promote the establishment and spread of 

other nonnative species. They also bring their respective pathogens and parasites (Warburton and 

others, 2002; Kuperman and others, 2004). Several studies have pointed to various 

environmental and climatic variables as potential drivers for sustaining or increasing nonnative 

plant dominance in semiarid ecosystems (Shinneman and Baker, 2009). Especially in the arid 

southwest, historical and current land-management practices, such as livestock grazing and fire 

suppression, are thought to have contributed to the susceptibility of arid lands to nonnative plant 

invasion and subsequent loss of native species and decreased biodiversity (Brown and Archer, 

1999; Brooks and Berry, 2006). Reduced species richness and biological soil cover are indicative 

of communities degraded by grazing, and these factors have been linked to invasion by 

nonnative grasses in place of native species not adapted to such pressures (Shinneman and 

Baker, 2009). Nonnative species often garner a foothold over native species due to their ability to 

thrive under harsher conditions with fewer resources and their ability to be prolific reproducers. 

The BMGR–West and monitoring workshop specialists identified invasive nonnative 

plants as a high priority for monitoring. Furthermore, Executive Order 13112 requires Federal 

agencies to (1) identify actions that may affect invasive species, (2) use relevant programs to 

prevent introduction of invasive species, (3) detect, respond, and control such species, (4) 

monitor invasive species populations, (5) provide for restoration of native species, (6) conduct 
31

research on invasive species, and (7) promote public education (Executive Order 13112, 1999). 

Acquiring reliable baseline data on the presence and abundance of invasive nonnative species is 

a priority in the development of a comprehensive invasive plant monitoring program. This is 

necessary to accomplish two goals: (1) identify which exotic species are not yet present at 

BMGR–West but may require early detection monitoring and (2) map the location, abundance, 

and distribution of established nonnative species (trend assessment). This baseline information 

allows managers to track the spread of known populations and identify new infestations with the 

ultimate result of allowing the evaluation of effectiveness of the management actions or 

treatments. Early detection of new species or infestations enables managers to employ a rapid 

management response while the populations are still small and manageable. Because most 

invasive plants of concern at BMGR–West are annual species, monitoring should be conducted 

during the active growing season, which is slightly variable but typically March-April for winter 

annuals and July-September for summer annuals. 

The BMGR INRMP identified 11 invasive plant species of concern for range 

management (table 3.1). Of the 11 species of concern, several are currently (2011) found on 

BMGR–West, including Sahara mustard, red brome, Lehmann lovegrass (Eragrostis 

lehmanniana), Arabian grass (Schismus spp.), Russian thistle (Salsola tragus), and buffelgrass. 

Observations by Malusa (2009) indicate that Sahara mustard is actively invading large swaths of 

the BMGR–West. As part of the ongoing vegetation mapping (Malusa, 2009), field crews 

identify and map the location of Sahara mustard using handheld GPS receivers. 

 Potential invasive animal species include European starlings, Rio Grande leopard frogs 

(Lithobates berlandieri), and others. 

Mapping efforts may be focused on areas known to be at high risk of invasion (see 

Brooks and Berry, 2006), including 

• roads, trails, campsites and wash corridors; 

• areas in proximity to other nonnative plant populations; 

• recently or continually disturbed areas; and 

• areas of high management priority and protection (sensitive or endangered species 

communities). 

A well-designed spatial database will make data entry and analysis efficient and easy to 

manage. Surveys can be expensive and time consuming and so it is imperative to document 

where they have occurred, even if no species were found (North American Weed Management 

Association, 2002). The construction of a spatially explicit database with invasive vegetation 

information allows managers to visualize the extents and distribution patterns of areas where 

invasive species are still absent. 
32

Table 3.1. Existing and potential invasive plant species located on Barry M. Goldwater Range lands.

Species Common name

Monitoring

priority Comments

Brassica 

tournefortii

 

 

Sahara mustard High Already widespread on the BMGR, Sahara mustard 

may pose a risk to sensitive areas by competing with 

and excluding native plants. Management in limited 

areas may be desirable.

Bromus rubens

 

 

 

Red brome High Red brome has ecosystem modifying abilities and 

increases fire frequency.

It is widespread on the BMGR and its control is 

difficult.

Management may be necessary in sensitive areas.

Eragrostis 

lehmanniana

 

Lehmann

lovegrass

High Lehmann lovegrass has ecosystem-modifying abilities 

and increases fire frequency. On the BMGR, 

populations are still relatively small and localized. 

Pennisetum 

ciliare

Buffelgrass High Buffelgrass increases fire frequency and has 

ecosystem-modifying ability.

Pennisetum 

setaceum

 

 

Fountain grass High Fountain grass may eventually be found on the 

BMGR.

This grass increases fire frequency and has ecosystemmodifying ability. 

Tamarix 

ramosissima

 

Saltcedar High Saltcedar is closely associated with water features, and 

its potential to despoil these scarce resources on the 

BMGR makes control important.

Schismus 

arabicus

 

 

Arabian grass Moderate Arabian grass is abundant and range-wide; further

study is needed to clarify its importance on the 

BMGR. Control efforts, if deemed necessary, would 

be best limited to local sensitive areas such as the 

Mohawk Dunes.

Cynodon 

dactylon

 

Bermuda grass Low to

Moderate

Bermuda grass is generally a problem only in moist 

places. Managers may elect to control it in sensitive 

areas when these efforts do not affect other species 

adversely.

Salsola tragus

 

Russian thistle Low Spot control of Russian thistle may be desirable 

because of fire concerns; it is limited to highly 

disturbed soils.

Centaurea 

melitensis

 

Malta 

Starthistle

Unknown Malta Starthistle is currently not found on the BMGR. 

Occurrence can be monitored and managed to prevent 

its widespread establishment on the BMGR–West.

Hordeum 

murinum 

Smooth barley Unknown A species of concern that may be monitored, its future 

importance to the BMGR is not well understood.
33

Regional Monitoring Status

 OPCNM actively monitors and controls buffelgrass. Various research and management 

activities involving Sahara mustard have been implemented at BMGR, OPCNM, CPNWR, and 

Kofa NWR.

3.1.3 Vegetation Community and Soils

Vegetation communities are commonly monitored in long-term ecological monitoring 

programs, because vegetation often responds conspicuously to climate patterns, land-use 

practices, and natural disturbances. Vegetation is often synonymous with habitat, and thus 

changes in vegetation can be linked to the management of species of concern (for example, 

Sonoran pronghorn). 

Vegetation Community and Soils Monitoring procedures follow the “Terrestrial 

Vegetation and Soils Monitoring Protocol” developed for NPS Sonoran Desert Network park 

units (Hubbard and others, 2009). The protocol is based on well-tested monitoring techniques 

developed for vegetation and soils monitoring by Herrick and others (2005a,b). The NPS 

protocol recognizes the relationship between vegetation and local edaphic factors (for example, 

soil texture, mineralogy, depth, and landform type) and co-locates spatial and temporal sampling 

of both. The protocol uses plot-based sampling to determine status and detect trends in (1) 

vegetation cover (percent) of common plants, (2) frequency (percent) of uncommon plants, and 

(3) soil cover and stability. 

Plot-based measurement of vegetative cover of common perennial species is an effective 

and traditional approach for monitoring plant populations (Elzinga and others, 2001). Cover is 

commonly used as a measure of community composition primarily because it is intuitive and the 

measure is easily equated with biomass or annual production. Measurement of percent cover 

facilitates status and trend monitoring for a single species of interest, especially “indicator” 

species and species of management concern. Determining the cover of all common perennial 

species allows management to retrospectively analyze status and trends of any species, even if 

they are not currently a species of concern. 

For tracking dynamic soil function, the protocol calls for monitoring status and trends of 

factors that influence soil movement. The protocol focuses on monitoring the (1) cover of soil by 

biological soil crusts, vegetation, organic litter, and abiotic materials and (2) the stability of 

surface soil aggregates. Specifically, soils monitoring involves determining the status and 

detecting trends in soil surface cover (percentage by substrate type) and biological soil crusts 

cover and frequency (percentage by lichen species and morphological group for cyanobacteria 

and bryophytes). Surface cover is the percentage of mineral soil surface covered by substrate 

class (Herrick and others, 2005b), providing an absolute and relative measure of these objects 

that influence erosion resistance. Bryophytes and cyanobacteria serve profoundly different 

ecological functions but are difficult to identify in the field. Therefore, they would be best 

identified to the morphological group level. 

Measurements of surface soil aggregate stability (by stability category, 1–6) allow for 

detection of status and trends in soil degradation resistance (Herrick and others, 2005b). Soil 

aggregate stability is both an indicator of disturbance and site resistance to soil erosion. In 

addition, it provides insights into soil water-holding capacity and infiltration rates. For detailed 
34

information regarding laboratory methods for soil surveys consult the NRCS Soil survey 

laboratory methods manual (Burt, 2004). 

The exact number of plots and the design of spatial sampling should be determined by 

vegetation monitoring experts, using a statistical sampling approach and considering the 

potential benefits of co-locating with other resource monitoring efforts. In general, the locations 

of vegetation community and soils monitoring plots should be stratified by vegetation type, 

specifically the NVCS vegetation associations identified and mapped during the vegetation 

mapping of the BMGR–West (Malusa, 2009). 

Regional Monitoring Status

 Staff from OPCNM and other SODN park units monitor vegetation and soils using the 

protocol described above. BMGR–East staff monitor vegetation with a similar 20 × 50 m plot 

adapted from the OPCNM EMP (Lowe and others, 1995). 

3.1.4 Soil Inventory and Upland Erosion Monitoring

Soil resources are a key concern on the BMGR. Currently BMGR–West has no 

completed and verified soil map, thus reducing our knowledge about the basic characteristics of 

the local soils that can have large implications for the soil ecology, vulnerability to erosion, 

compaction, and hydrologic degradation under different management decisions. Of particular 

concern are soil particle size distribution, mineralogy, and horizon development—common static 

features that are described in soil surveys. Creation of a suitable soil map would involve a onetime field sampling effort to create a map and associated database and report, which would be 

used for many future management issues (fig. 3.2). Many new digital tools can be used to 

efficiently create soil maps (McBratney and others, 2003; Scull and others, 2003; See appendix 

C for methodology details). 
35

Figure 3.2. Preliminary digital soils map of Barry M. Goldwater Range–West (Created by Nauman 

Geospatial for Arizona Game and Fish Department, 2009).

Soil loss to wind and water erosion can be monitored by a variety of both quantitative and 

qualitative means. It is important to include wind and water erosion monitoring in rangewide 

monitoring efforts, because erosion can cause problems in many areas of the ecology and causes 

negative feedback loops (for example, more erosion causes more vegetation loss, which leads to 

more erosion). Soil-erosion monitoring, as described in this section, is different from the soil 

quality measures described in section 3.1.3 in that once an area is significantly eroding, soil loss 

tends to reset the ecology of a site, and only stabilizing soil loss will allow vegetation and 

organisms to return to a site and begin rebuilding the fertility and resilience of a site. Thus, soil 

erosion has to be tracked by different methods from the soil-quality parameters presented in 

section 3.1.3 in order to determine if erosion is increasing or decreasing in areas where it occurs.

Because BMGR–West covers a large area, it is helpful to have some method for 

narrowing down potential sampling locations for monitoring erosion. Because methods for soils 

and vegetation monitoring presented in section 3.1.3 locate plots based on statistical inference, 

vegetation and soils plots would be good candidates for potential co-locations of terrestrial 
36

erosion monitoring. Also, having co-located erosion, vegetation, and soil-quality measures offers

valuable insight into surface dynamics once researchers begin to analyze monitoring data. 

Another tool to help identify areas prone to erosion that might be overlooked in plot 

placement is GIS models. Theory derived from the Revised Universal Soil Loss Equation 

(Renard and others, 1997) and Revised Wind Erosion Equation (Fryrear and others, 2001) can be 

modeled in GIS to create erosion-potential-index maps to help focus monitoring efforts (see 

appendix C). A good baseline soil map greatly increases the accuracy of such modeling, but 

topography and satellite data can also be used independently for rougher approximations. 

Once plots are prioritized for monitoring, a variety of erosion monitoring tools can be 

implemented based on the location status and resources available. Erosion manifests in visible 

forms identifiable in the field (for example, sheet, rill, or gully erosion). At the very least, field 

technicians need to record the presence or absence and general abundance of these features at 

monitoring sites (part of the protocol by Hubbard and others, 2009). At sites where these features 

are found in abundance, more quantitative methods should be considered. Appropriate field 

methods would include base-level pin surveys and both wind and water sediment traps. Pin 

surveys simply quantify the depth and dimensions of soil erosion features to help approximate 

soil loss, and sediment traps actually capture sediments for direct measurement of soil loss on the 

plot. These methods are costly and should be allocated only to areas where erosion features are 

visually observed, unless resources are available to implement more detailed erosion rate 

monitoring (see appendix C for method details). 

Regional Monitoring Status

A complete NRCS soils map is available for OPCNM. A draft digital soils map, 

contracted by AZGFD for Sonoran pronghorn monitoring, exists for the entire BMGR, but has 

not been ground-truthed (Nauman, 2009). Various soils and erosion monitoring projects are in 

progress at OPCNM. 

3.1.5 Stream-Channel Erosion Monitoring

Cross-sectional analysis of washes and gullies should be used along with GIS watershed 

analysis to estimate greater watershed and stream-channel erosion rates. Cross-section locations 

should be randomly selected while weighting sampling towards higher Strahler orders (Strahler, 

1952, 1957) and watersheds with higher average estimated erosion potential. Points along 

washes should be allocated using the spatially balanced Generalized Random Tessellation 

Stratified (GRTS) approach (Hubbard and others, 2009; Stevens and Olsen, 2004), which gives 

flexibility in adding or subtracting points if resource availability for monitoring changes. 

Cross sections can be implemented to measure elevation profiles and capture diagnostic 

features (for example, thalweg and terraces) across channels, along with general substrate size 

and vegetation cover. Cross-section sites should be equipped with pressure transducers or other 

gauges with data loggers to log flow-event depths. From these data, the elevation profile and 

flow events recorded can be related to calculate basin erosion or denudation rates. This is done 

using known relationships among channel profile, slope, flow depths, streambed particle size, 

streambed gradient, and watershed area using Manning’s Equation and sediment transport theory 

(Wiberg and Smith, 1989; Ritter and others, 2002). Steam-channel downcutting and aggradation 

rates also can be monitored with these data by simply calculating changes to cross-section area, 
37

leading to estimates of actual channel sediment loss for washes within the GRTS sampling 

framework. 

By subtracting erosion rates calculated from vegetation and soils plots (section 3.1.3) and 

Transportation Corridor monitoring (section 3.3.1) from overall basin erosion rates derived from 

channel cross sections, the effects of specific land-use-driven erosion processes may be 

determined. Sometimes lags or accelerations of sediment pulses from hillslopes or roads in a 

watershed might cause discrepancies between cross-section stream channel erosion rates and 

stream channel erosion rates calculated by subtracting other rates of erosion from the basin 

erosion rate. These dynamics of erosion can be monitored by integrating the different approaches 

of erosion measurement.

Regional Monitoring Status 

A stream monitoring protocol has been implemented as part of the SODN to monitor 

stream channel morphology. 

3.1.6 Tinajas, Tanks, and Developed Waters

Tinajas (rain-fed rock tanks) are an important source of seasonal waters for wildlife 

within BMGR–West. Many natural tinajas in BMGR–West have been developed further to 

provide water for wildlife, especially Sonoran pronghorn and desert bighorn sheep (Broyles, 

1997). Typical wildlife water-developments in southwestern Arizona include constructed 

catchments or “guzzlers,” natural tinajas developed to increase water retention, windmillpowered wells, and developed springs. There is some concern that developed waters may 

provide habitat for pathogens and disease vectors, potentially harming wildlife. This is especially 

true for amphibians, and waters should be regularly tested using developed disease-testing 

protocols. However, recent water quality assessments of developed waters at YPG and Kofa 

NWR found no evidence of the water-borne pathogen Trichomonas gallinae and inconclusive 

evidence of hemorrhagic disease vectors (Rosenstock and others, 2004). Waters of the BMGR–

West have yet to be tested for the global pathogen Batrachochytrium dendrobatidis that is 

causing widespread extinctions and extirpations of amphibians (Wake and Vredenburg, 2008), 

and has also been shown to occur in extremely arid and hot locations (Lovich and others, 2008). 

Before monitoring, it would be helpful to inquire with AZGFD for spatial data on the 

location of tinajas, tanks, and developed water on BMGR–West lands (fig. 3.3). Broyles (1997) 

compiled information on locations and some general inventory parameters (depth, volume, 

duration, and animal usage) of water holes throughout BMGR and CPNWR. 
38

Figure 3.3. Developed waters of Barry M. Goldwater Range–West.
39

It is suggested that monitoring efforts focus on tinaja water quantity (water depth) and 

other basic water quality parameters, and that monitoring be conducted on a yearly basis, 

preferably multiple times per year in order to assess seasonal variations. In general, three seasons 

are identified as important for tinaja sampling: (1) after winter rains, (2) in late spring after many 

tinajas have dried up and water is concentrated at a few important wildlife sites, and (3) after 

summer monsoon rains. 

A multiparameter water quality sonde (http://www.ysi.com/index.php) such as the 

Yellow Springs Incorporated (YSI) 6820 sonde Multiprobe has been recommended by Sprouse 

and others (2005) for monitoring water quality in Sonoran Desert parks. Monitoring parameters 

include: 

• water depth

• air and water temperature

• dissolved-oxygen concentrations 

• specific conductance

• pH 

• reduction-oxidation potential 

• alkalinity

To allow for consistent monitoring protocols throughout the study area, it is suggested 

that all monitoring be conducted according to the methods described in the USGS National Field 

Manual for the Collection of Water-Quality Data (hereafter referred to as the National Field

Manual; U.S. Geological Survey, 2009). This manual provides guidelines and standard 

procedures for assessing the quality of surface-water and groundwater resources. Chapter A6 of 

the National Field Manual presents procedures and guidelines for the collection of data on air 

and water temperature and on dissolved-oxygen concentrations, specific electrical conductance, 

pH, reduction-oxidation potential, alkalinity, and turbidity in water. 

Regional Monitoring Status

OPCNM staff monitors water quality of various springs and tinajas. The AZGFD 

monitors water resources for BMGR–East, YPG, and CPNWR. 

3.1.7 Climate 

Climate plays a central role in natural systems; the spatial distribution of solar radiation, 

temperature, precipitation, and wind controls the distribution and physical character of soils and 

biota over the landscape. This relationship makes climate an integrating factor in ecosystem 

monitoring programs and provides an important variable for understanding short- and long-term 

changes in resources. 

There are no weather stations currently (2011) operating in the BMGR–West, and limited 

weather and climate data are available for adjacent areas in the lower Sonoran Desert of Arizona 

(fig. 3.4). This lack of data is due to the remoteness and ruggedness of the area, and to the fact 

that much of the southwestern climate network infrastructure was developed as a tool for wildfire 

monitoring and is distributed in fire-prone areas (for example, interagency Remote Automated 

Weather Stations (RAWS)). A network of weather stations with locations distributed over 

BMGR–West and adjacent land management units, covering various vegetation communities, 

soil types, landforms, and elevation gradients, would provide a high-resolution dataset describing 
40

regional climate patterns. Using these data, researchers and managers could develop models for 

high-resolution interpolation of precipitation, temperature, and other variables that would aid 

ecosystem research, monitoring, and management. These data and associated models would 

equip managers with a better understanding of local weather and climate patterns within a 

regional and global context. 

Figure 3.4. Distribution of Remote Automated Weather Stations and other weather stations in areas 

surrounding Barry M. Goldwater Range-West. Note the scarcity of stations in southwestern Arizona.
41

A number of weather stations are commercially available, all of which record similar 

information. By definition, weather stations are self-contained instrument packages used to 

automatically record, store, and communicate weather and climate data from remote sites. 

Stations are independently powered by a solar panel and battery. The weather station model used 

to record information on the BMGR–West would not be as important as the number and location 

of these stations and the type and amount of data collected. It is suggested that a weather station 

be included in at least every major vegetation type and co-located near permanent vegetation 

monitoring plots. 

Climate/weather variables that would be useful for monitoring purposes include: 

• air temperature

• relative humidity

• precipitation

• barometric pressure

• solar radiation (300-1,100 nm) 

• photosynthetically active radiation (400-700 nm) 

• wind speed 

• wind direction 

• soil moisture (10-cm depth)

• soil temperature (10-cm depth).

To ensure standardized datasets, it is suggested that each variable be monitored in 

compliance with World Meteorological Organization (WMO) standards (World Meteorological 

Organization, 1983). Weather stations typically collect data for most variables at 1-hour intervals 

or less and consequently produce large amounts of raw data. Collected weather data would be 

downloaded as comma-delimited files with date/time (yy/mm/dd/hr/min/sec) and variable values 

that can be imported into most databases and spreadsheets. Preventative maintenance of the 

station instrumentation is essential to collecting accurate data, and it is suggested that stations be 

inspected quarterly. During these quarterly visits, the weather station data could be compared to 

data measured with a separate set of laboratory-standard sensors. Wind speed and solar sensors 

would be removed and recalibrated annually. The temperature and humidity sensors would be 

calibrated every two years. MCAS-Yuma would partner with other institutions to make BMGR–

West climate-station data available to researchers and the general public through an appropriate 

online climate network (for example, Western Regional Climate Center (WRCC), 

http://www.wrcc.dri.edu/; MesoWest, http://mesowest.utah.edu/; or The Arizona Meteorological 

Association, http://ag.arizona.edu/azmet/).

Regional Monitoring Status

A number of weather stations are currently in operation at OPCNM, Kofa NWR, YPG, 

and BMGR–East. OPCNM staff have been collecting climate data since 1987, and data are 

housed at the WRCC. Other existing stations with published information include MCAS-Yuma, 

Yuma Valley, Yuma South, Roll (Tacna), Paloma, and Gila Bend Air Force Auxiliary Field 

(MesoWest, http://mesowest.utah.edu/; The Arizona Meteorological Association, 

http://ag.arizona.edu/azmet/).
42

3.2 Birds, Mammals, Amphibians and Reptiles

3.2.1 Bird Monitoring

Bird monitoring follows the “Landbird monitoring protocol for the Sonoran Desert 

Network” designed by Powell and others (2007) 

(http://science.nature.nps.gov/im/monitor/protocols/SODN_Landbird.pdf). The protocol uses 

point-transect survey methods to estimate population size and abundance of species on a yearly 

basis and is designed to track changes in relative indices of these parameters over time 

(Buckland and others, 2001). The approach in this protocol focuses on assessing population 

changes of common species—because of low detection probabilities, uncommon or threatened 

species (such as Le Conte’s thrasher) need to be monitored using targeted surveys. 

The protocol focuses on collecting data to monitor and track changes in three population 

variables: density, relative abundance, and occupancy. All three variables can be estimated using 

one set of field methods; however, data are analyzed using different statistical tools and 

approaches. The first variable, density, provides managers with estimates of total population 

change with error estimates. The approach described in this protocol allows detection of 2-

percent annual decline in density over a 30-year period, with an 80-percent probability and a 10-

percent Type I error rate. Over a 30-year monitoring period, a 2-percent annual decline would 

equal a 45-percent overall population decline. Density is estimated using the point-transect 

distance-sampling method at fixed points, and the subsequent analysis is conducted using the 

Distance Program (Thomas and others, 2005; Burnham and Anderson, 2002). 

The second variable, relative abundance, is an estimate of the ratio of overall population 

change among species and years. This ratio is a count of the species of interest divided by the 

total count of the most abundant species within the survey area (van Riper, 1982; Sogge and 

others, 1989). Relative abundance is only appropriate for monitoring changes in population size 

if the ratio of the index count to the actual parameter of interest (for example, population size) 

does not vary systematically over time and if detectability does not change over time (van Riper 

and others, 1988). Because of this limitation, relative abundance is a robust measurement for 

trends, but often it is a secondary measure when density estimates are incalculable (Powell and 

others, 2007. 

The third variable, occupancy, is a measure of presence/absence within sampling units 

and is a coarse metric that can be used to describe changes in the distribution of a species over 

time. As with density, techniques for estimating occupancy explicitly account for variation in 

detectability, thereby adjusting estimates for individuals that are present yet undetected during 

surveys (Williams and others, 2002; Mackenzie and Royle, 2005). All three measurement 

techniques are useful, depending on the level of accuracy and detail land managers desire in their 

monitoring of avian communities. 

Although this protocol provides methods to document community dynamics, certain bird 

species of concern to BMGR–West may require targeted survey efforts (such as Le Conte’s 

thrasher and gray vireo (Vireo vicinior)) or nest-occupancy surveys (such as golden eagle and

peregrine falcon (Falco peregrinus)). Other species may be more easily detected during fall or 

winter, when general community monitoring is not ideal. 
43

BMGR–West may consider making the bird community monitoring data available for 

regionwide analysis by providing data to the Avian Knowledge Network (AKN) or Rocky 

Mountain Bird Observatory (RMBO) Avian Data Center. 

Regional Monitoring Status

The Landbird monitoring protocol is currently used by NPS at OPCNM, and a modified 

version is used by LAFB at BMGR–East. The Arizona Bird Conservation Initiative (ABCI) is 

developing a strategy to increase coordination of bird monitoring activities across the region 

through the development of a coordinated monitoring framework that would provide data to help 

understand regional status and trends of Sonoran Desert species. 

3.2.2 Small Mammals and Nocturnal Rodents 

Small mammals and rodents are an important component of the trophic system; they are 

primary consumers and are the main prey source for many larger mammals and raptors. As 

primary consumers, small mammal populations often provide information about resource 

conditions and can be viewed as indicators of ecosystem productivity. 

Live trapping is an effective and usually nonlethal method for monitoring small mammals 

and rodent populations. Capture provides information on species richness, abundance, diversity, 

and mean species biomass, the last of which can only be collected using capture or trapping 

techniques. There are many different mammal capture techniques; the most appropriate depends 

on the objective of the monitoring program (see Jones and others, 1996; Wilson and others, 

1996). The general process for small mammal and nocturnal rodent monitoring, as adapted for 

this I&M Plan, requires establishing a 7 × 7 (or greater) trap grid of baited live traps. Traps are 

set just before dusk and checked again at midnight and first thing in the morning. Monitoring 

would occur annually for two or three consecutive nights during the summer season. A minimum 

of 500 trap nights (the number of traps multiplied by the number of trapping periods) is 

suggested for the initial inventory (Jones and others, 1996). 

The protocol for small mammal monitoring was adapted from many general monitoring 

sources (appendix D). The number of traps, grid size, sampling season, and frequency were 

adapted from OPCNM EMP monitoring documents (Petryszyn and Russ, 1996; Organ Pipe 

Cactus National Monument, 2006) and meant to provide data consistent with OPCNM long-term 

monitoring efforts. Long-term (1991–2006) rodent monitoring data from the OPCNM EMP were 

recently analyzed for trends and statistical power (Flesch, 2008). The power analysis results 

suggest that the 7 × 7 array and annual monitoring provided adequate power for the monitoring 

program, and reducing the sampling time frame from once per year to every 2 years would 

greatly reduce the power to detect changes (Flesch, 2008). However, the array size necessary to 

detect changes in BMGR–West mammal populations over time may be larger (that is, 10 × 10) 

than what is currently used at OPCNM (Jones and others, 1996). Therefore, we suggest power 

analysis and species accumulation curves be conducted on BMGR–West data once sufficient 

data have been collected.

Regional Monitoring Status

OPCNM staff has monitored small mammals since 1991.
44

3.2.3 Sonoran Pronghorn and Desert Bighorn Sheep

Sonoran pronghorn is a desert subspecies of the American pronghorn. The Sonoran 

pronghorn was listed as a Federally endangered in 1967. Currently, there are at least 68 Sonoran 

pronghorn in the wild and 73 in a captive-breeding pen. Their current distribution is limited to a 

7,122-km2 area that includes CPNWR, BMGR and OPCNM (fig 3.5). A draft Environmental 

Assessment to reestablish a pronghorn population in other protected areas was released in 

October 2009. 

Figure 3.5. The current (2011) Sonoran pronghorn range.

The Sonoran Pronghorn Recovery Plan (Plan) (U.S. Fish and Wildlife Service, 1994) was 

produced by a recovery team comprising representatives from the AZGFD, CPNWR, BLM, 

OPCNM, Commission of Ecology and Sustainable Development for the State of Sonora 

(CEDES), and National Commission for Protected Natural Areas (CONANP) and revised in 

1994, 1998, and 2002. Major recovery actions include (1) enhance present populations of 
45

Sonoran pronghorn by providing supplemental forage and/or water, (2) determine habitat needs 

and protect present range, (3) investigate and address potential barriers to expansion of presently 

used range and investigate, evaluate, and prioritize present and potential future reintroduction 

sites within the historical range, (4) establish and monitor a new, separate herd(s) to guard 

against catastrophes decimating the core population, (5) continue monitoring populations and 

maintain a protocol for a repeatable and comparable survey technique, and (6) examine 

additional specimen evidence to assist in verification of taxonomic status (U.S. Fish and Wildlife 

Service, 1994). 

After the drought-induced die-off of Sonoran pronghorn in 2002, the USFWS, AZGFD, 

and BMGR worked to rebuild populations using the following tactics: (1) in 2003, a semicaptive 

breeding facility was constructed in Childs Valley, Cabeza Prieta NWR, and stocked with wild 

Sonoran pronghorn, (2) forage enhancement plots were created and irrigated to produce forage 

for pronghorn, and (3) emergency water sources (six on CPNWR, one on OPCNM, and two on 

BMGR–West) were constructed.

Monitoring is currently conducted by the USFWS and AZGFD using aerial line-transect 

surveys. For additional information, see USFWS and AZGFD monitoring protocols and reports 

(U.S. Fish and Wildlife Service, 1994; Bright and others, 1999, 2001 2002). 

The desert bighorn sheep is a subspecies of Bighorn sheep that occurs in the southwest 

desert regions of the United States and northern Mexico. One key adaptation that has set the 

desert bighorn sheep apart from other sheep species is its ability to go without water for extended 

periods of time. Although current populations are low, the overall trends since the 1960s show 

population increases. Currently (2011), managers are working to address several issues that 

might limit sheep numbers, such as water availability, disease, human disturbance, and 

predation. AZGFD is the primary managing agency for the desert bighorn sheep. MCAS-Yuma 

has assisted in the past with water developments and with other projects, as needed. Future 

projects include development of several new water catchments and upgrades of existing water 

developments. Every 3 years, the AZGFD conducts aerial helicopter surveys during the months 

of October and November to monitor sheep populations. 

Desert bighorn sheep are currently (2011) surveyed in the Mohawk, Copper, Gila, and 

Tinajas Altas mountain ranges on BMGR–West. The surveys in the Mohawk Mountains, Copper 

Mountains, and Tinajas Altas Mountains cover the entire habitat of BMGR–West and represent 

the population well; the survey in the Gila Mountains is a partial survey, because of funding 

limitations, so the sheep population there is likely larger than estimates indicate. Bighorn sheep 

numbers have remained relatively stable within these mountain ranges from 2008 to 2010, with 

some population fluctuation but no drastic population declines (Arizona Game and Fish 

Department, 2010; http://www.azgfd.gov/h_f/hunting_units_40b.shtml). The current (2011) 

population estimate in this area is about 250 sheep. When the Gila and Tinajas Altas Mountains 

were surveyed in November 2009, population estimates were as follows: ram to ewe ratio was 

94:100, lamb to ewe ratio was 19:100, and yearling to ewe ratio was 11:100. When the Mohawk 

and Copper Mountains were surveyed in October 2007, population estimates were as follows: 

ram to ewe ratio was 87:100, lamb to ewe ratio was 13:100, and yearling to ewe ratio was 

13:100. The AZGFD has a regulated hunt in these mountain ranges for the desert bighorn sheep; 

the current harvest recommendations are six rams per year. The hunts are allowed in three areas: 

the Gila Mountains north of Cipriano Pass, the Tinajas Altas Mountains south of Cipriano Pass, 

and the Mohawk and Copper Mountains. 
46

Regional Monitoring Status

 Sonoran pronghorn monitoring is conducted at CPNWR, BMGR–West, and BMGR–

East, and desert bighorn sheep monitoring is conducted at BMGR, Kofa NWR, and other 

locations.

3.2.4 Bat Guild 

Bat Guild protocol was adapted primarily from a mist-netting protocol developed in 

1993–94 by Yar Petrysyzn (University of Arizona) for the OPCNM. There are, however, other 

bat monitoring protocols that would be helpful in regional monitoring efforts. The Arizona Game 

and Fish Department (1997) protocol, in particular, was designed to standardize methods across 

all four of the department’s regional jurisdictions. AZGFD bat monitoring protocol is primarily 

mist-netting, but also includes a protocol for roost monitoring. It would be helpful to include 

roost monitoring as part of the BMGR–West monitoring efforts. The mist-netting protocol for 

BMGR–West is based on OPCNM and AZGFD (1997) monitoring protocols, and the roost 

monitoring is based on AZGFD procedures. It is useful to review both OPCNM and AZGFD 

protocols and other bat monitoring protocols (for example, Jones and others, 1996) before 

implementing a bat monitoring program.

A 2006 internal review of the OPCNM EMP suggests that the original bat monitoring 

protocol could be improved in various ways (Pate, 2006). One suggestion is the use of an Anabat 

ultrasonic detector/recording system to identify individual species through echolocation 

reference libraries (O’Farrell and others, 1999; Kuenzi and Morrison, 2003). One advantage of 

the ultrasonic detector approach is that it is nonobtrusive, and a comparative study in southeast 

Arizona by Kuenzi and Morrison (2003) suggests that this approach is as effective for bat 

monitoring as mist-netting, although specimens detected cannot be visually verified and no 

voucher data can be obtained (for example, blood, tissue, health status, disease detection, and 

other data). A second recommendation made by Pate (2006) and based on the review of the 

OPCNM bat monitoring program was to sample during spring/summer as opposed to late 

summer/fall (postmonsoon). Although there is often more available water and forage after the 

monsoon, the variability in precipitation is too great and may result in poor monitoring data 

(Pate, 2006). Finally, environmental conditions (temperature, moonlight, barometric pressure, 

and wind) can greatly influence the effectiveness and comparability of mist-net data, and 

minimizing variation in these conditions from one monitoring year to the next increases the 

accurate identification or long-term trends (Pate, 2006). 

Even though there is a scarcity of available surface water at BMGR–West, limiting 

potential monitoring locations, the mist-netting protocol requires that monitoring be repeated at 

the exact same locations on an annual basis. It may be efficient to select and co-locate water 

sampling/survey locations with other sampling/monitoring locations (for example, amphibians, 

tinajas), but ultimately site selection is based on the biologist and resource manager’s knowledge 

of local bat and water resources (fig. 3.6). The AZGFD bat monitoring protocol suggests that 

each netting location be surveyed for small terrestrial mammals concurrently with each bat 

survey. 

The goal of roost monitoring is to focus monitoring on selected bat roosts/populations, 

especially roosts of high-priority species, in order to assess variability in annual and seasonal 

roost use. Measurements can include (1) relative abundance, (2) seasonal movements, and (3) 
47

effects of environmental factors (temperature, light intensity, and others). Roosts would be 

selected by the BMGR biologist and include one roost of a “high priority” species and a second 

roost of any bat species. Investigators would need to know the species inhabiting a roost and 

roost type before beginning monitoring. Investigators would also need to know background 

information on the roosting habits of the target species, likely reproductive condition and 

physiological state of the roosting individuals, times of nightly emergence and return, effects of 

temperature and precipitation on roosting behavior, and nightly foraging activities. This 

knowledge could be used to design a sampling protocol for a specific roost that can reduce 

disturbance to the bats and minimize sample bias. In a situation where roosts are unknown before 

monitoring, it is suggested that bats be captured during mist-netting, fitted with radio transmitters 

and tracked back to their roosts (Ball, 2002; Kuntz, 2003). 

Figure 3.6. Location of Arizona Game and Fish Department Bat Monitoring Sites on Barry M. Goldwater 

Range–West.
48

Regional Monitoring Status

Bat monitoring is currently (2011) conducted at BMGR–West, BMGR–East, OPCNM, 

and CPNWR. 

3.2.5 Amphibian and Reptile Surveys 

The status and distribution of amphibians and reptiles on the BMGR is not well known. 

There have been no comprehensive surveys or monitoring conducted to date. Thus, current 

(2011) management considerations and understanding of these species is based largely on the 

results of focused sampling of a few at-risk species (see sections below that discuss flat-tailed 

horned lizard, desert tortoise, and Cowles fringe-toed lizard) and some opportunistic and 

historical sampling and data collection for other herpetofauna. The following sections include a 

brief summary of I&M efforts aimed at these at-risk species, followed by suggestions for more 

general herpetological monitoring approaches. 

Flat-Tailed Horned Lizard 

The flat-tailed horned lizard (FTHL) was first proposed as a threatened species under the 

Endangered Species Act in 1993. The FTHL proposal has been removed three times since 1993 

as a result of legal challenges. The FTHL status is currently being considered by the Department 

of the Interior and is to be decided in 2011. In response to the proposed listing, the AZGFD 

developed a flat-tailed horned lizard management strategy that includes monitoring protocols and 

data analysis techniques (Flat-tailed Horned Lizard Interagency Coordinating Committee, 2003). 

The Conservation Agreement that resulted from the management strategy remains in effect 

today, and the rangewide monitoring strategy continues to be implemented by all Conservation 

Agreement signatory agencies. In an effort to standardize monitoring efforts throughout the 

species range, FTHL monitoring protocols were updated and refined in 2008 as the “Flat-tailed 

Horned Lizard Monitoring Plan.” Various AZGFD FTHL monitoring efforts are currently (2011) 

underway at BMGR–West (fig. 3.7). 

Cowles Fringe-Toed Lizard

Cowles fringe-toed lizard is endemic to the Sonoran Desert and only found in the Gran 

Desierto in Mexico and adjoining portions in the United States (the Yuma Desert and Pinta 

Sands) and in the Mohawk Dunes on the BMGR. The Gran Desierto of Mexico and the Mohawk 

Dunes on the BMGR are considered critical areas for the species and the Mohawk Dune habitat 

is largely free from stressors related to off-highway vehicles. It would be helpful to monitor the 

lizard population and the habitat quality of Mohawk Dunes regularly, with particular focus on 

invasive species and visitor use impacts on dune habitat. Turner and others (1997) conducted an 

initial Cowles fringe-toed lizard inventory at four sites in the Mohawk Dunes. 
49

Figure 3.7. Flat-tailed horned lizard Management Area, including plot locations, survey points, and 

observation locations. 
50

Desert Tortoise 

The desert tortoise is currently listed as Federally threatened in the northern one-third of 

its geographic range (U.S. Fish and Wildlife Service, 1990). Declines in the Mojave Desert 

populations have been attributed to direct and indirect human-caused mortality and inadequate 

regulatory mechanisms to protect desert tortoises and their habitat. Specific stressors identified in 

the listing included destruction, degradation, and fragmentation of habitat from urbanization, 

agricultural development, livestock grazing, mining, and roads. 

On December 14, 2010, the USFWS announced a 12-month finding to list desert tortoises 

in the Sonoran Desert as a distinct population segment under the Endangered Species Act of 

1973, adding the Sonoran population of the desert tortoise to the candidate species list. With the 

new listing of the desert tortoise, commercial and Federal projects that threaten the tortoise are 

required to obtain incidental take authorization from the USFWS. In addition, listing will require 

the designation of critical habitat, which would impose additional restrictions on solar energy 

development. 

In fiscal year 2008, the AZGFD was awarded DOD Legacy Funding to identify landscape 

habitat patterns and subspecies designation of desert tortoises on BMGR and YPG. As a result, 

the AZGFD is developing a landscape-level habitat model that identifies locations with the 

highest likelihood of occupancy. Coupled with training area maps, specific locations where there 

is overlap are identified and appropriate measures taken to reduce potential conflicts between 

MCAS-Yuma activities and tortoise habitat. During the AZGFD 2008 survey, evidence of one 

tortoise (n=1) was detected in the Tinajas Altas Mountains on the BMGR–West.

The following information provides basic desert tortoise survey protocols designed by 

AZGFD for contractors surveying for development projects. If conducting rangewide, long-term 

desert tortoise monitoring, see “Survey Protocol for Sonoran Desert Tortoise Monitoring Plots: 

Reviewed and Revised” by Averill-Murray (2000) for protocol information 

(http://www.AZGFD.gov/pdfs/w_c/tortoise/Monitoring%20Plot%20Protocol.pdf). The AZGFD 

provides “Desert Tortoise Survey Guidelines for Environmental Consultants”, which is a set of 

informal guidelines that are intended to aid private consultants surveying for the presence of 

tortoises at development projects in the Sonoran Desert 

(http://www.azgfd.gov/hgis/pdfs/SurveyGuidelinesForConsultants.pdf). 

General Herpetological Monitoring Approach

Data on herpetofauna occurrence can be inferred to some extent from data from land 

areas surrounding the BMGR–West. In the absence of systematic and BMGR-wide sampling and 

inventory, the following monitoring suggestions are made: 

Herpetological monitoring on the Barry M. Goldwater Range may first require a baseline 

inventory. For reptiles and some amphibians, snake traps and arrays of pitfall traps utilizing 

cover boards can be implemented over several years until the accumulated data can be analyzed. 

Based on the results, the sampling methods, duration, and (or) intensity can be refined. See 

Heyer and others (1994) and Fisher and others (2008) for comprehensive pitfall trapping survey 

methods. Besides the recommended pitfall sampling, it would also be important to implement 

Visual Encounter Surveys (Crump and Scott, 1994) at all waters on the BMGR–West (fig. 3.3). 

Although other methods for trap design and layout may be utilized (for example, Heyer 

and others, 1994; Fisher and others, 2008), Turner and others (1997) have used their method for 
51

inventory of Cowles fringe-toed lizard. Likewise, surveys for Cowles fringe-toed lizards may be 

included in the BMGR–West-wide herpetofaunal inventory and monitoring. In the past, Turner 

and others (1997) utilized six trap arrays, each consisting of four pitfall traps and some with an 

additional six funnel traps (Campbell and Christman, 1982; Gibbons and Semlitsch, 1982). 

Pitfalls were 19-liter (5-gallon) buckets sunk into the ground to their rims. These were placed in 

arrays, each consisting of a central pitfall circled by three others, which were distributed at 

roughly 120° angles with radii of 7.7 m. Four arrays had low metal drift fences connecting the 

central pitfalls with their outliers. Drift fences were occasionally augmented with funnel traps 

made from metal screening. Two arrays with drift fences were placed in dune swales, while the 

remainder were on crests. Reptiles were also captured by noose and by hand, on the dunes and in 

areas adjacent to the dunes. Reptiles were also detected in the course of walking transects as part 

of the monitoring component of this project, while conducting mark-recapture studies of fringetoed lizards and shovel-nosed snakes, while collecting specimens for ecological studies of fringetoed lizards, and while walking to and from camps and vehicles (Crump and Scott, 1994). These 

methods were supplemented by night-time road surveys on dirt roads (Campbell and Christman, 

1982). 

Data Collection: For each survey it is important to collect information in a standardized 

manner, and the following template is suggested:

1. Date

2. Start and end time of survey 

3. Name/s of observer/s

4. Coordinates 

5. Name or number of transect 

6. Habitat type

7. Weather conditions (for example, sunny, cloudy, dry, or rainy) 

8. Air temperature

9. Elevation

Species Information:

1. Species name

2. Sample location (GPS coordinates, UTM NAD83) 

3. Sex and/or age of individual 

4. Habitat individual was found in/on 

5. Substrate (boulder, gravel, leaf litter) found in/on 

The collected data would be summarized and a species list generated that shows the 

number of species, the number of individuals of each species, and the geographic distribution of 

the sampled species. The relative abundance and diversity of herpetofauna can be estimated and 

compared with historical data. 
52

Regional Monitoring Status

OPCNM staff monitor lizards and snakes using various methods, including transects and 

trap stations. AZGFD conducts various monitoring efforts in the area surrounding BMGR–West 

(see above).

3.3 Anthropogenic Impacts

Anthropogenic impacts on BMGR–West lands were considered the highest priority for 

monitoring by surveyed stakeholders and monitoring experts. Human activities, especially 

vehicle-based activities, can directly impact soils, vegetation, and local hydrology (Brooks and 

Lair, 2009). Repeated use of established or informal campsites can create impacts such as soil 

compaction, waste disposal, and firewood depletion in the campsite vicinity. Heavy foot and 

vehicular traffic can impact forbs and grasses (dune species may be especially vulnerable), and 

can disturb desert pavements and cryptogamic crusts, producing negative aesthetic and biological 

effects (Kuss, 1986; Gilewitch, 2004). The effects from foot traffic alone may be locally 

significant, but they are generally more subtle than similar effects produced by vehicle traffic 

and are best monitored with ground-based data collection in plots or along transects. Surface 

disturbances caused by vehicles can be seen in aerial and high-spatial-resolution satellite imagery 

and can thus be monitored using repeated imagery acquisitions. With georeferenced imagery in a 

GIS, surface disturbances such as road widening, new spurs, vegetation damage, and damage to 

desert pavements can be identified, quantified, and compared from one time period to another. A 

trails and roads inventory is currently (2011) being developed for OPCNM and CPNWR using 

remotely sensed imagery (2008 border aerials, see section below). For the CPNWR area, image 

interpreters are digitizing unauthorized vehicle tracks, and for the OPCNM area, historical roads, 

foot trails, and off-highway vehicle tracks are being digitized (Sue Rutman, OPCNM, oral 

commun., 2010). 

The sections below outline basic protocols for monitoring anthropogenic effects on 

surface resources that are generally visible in remotely sensed imagery. However, it should be 

noted that image interpretation and feature extraction rely heavily on field reconnaissance and 

auxiliary data collection. Moreover, human visual interpretation of imagery is still usually more 

productive and accurate than an automated approach, if one can even be found that approximates 

the desired results.

The maximum objectivity of visual interpretation among observers and between time 

periods increases mapping accuracy. Drake and others (2004) showed that it is feasible to train 

different observers to produce consistent interpretations of high-spatial-resolution imagery with a 

minimum of effort. Consistently applied protocols and the opportunity to directly overlay 

multidate image sets for comparison also increases objectivity.

3.3.1 Transportation Corridors

Acquiring Aerial Imagery

The repeat interval for monitoring anthropogenic impacts may depend as much on 

institutional factors, such as budgets and availability of personnel, as on biological and physical 

factors. Documentation of ecosystem status and trends through imagery would be an important 

component of monitoring, and because of the cost of custom acquisition of commercial satellite 
53

imagery, it may prove most feasible to use public-domain, open-source, or shared imagery 

obtained opportunistically, such as the datasets described below. Transportation monitoring may 

be accomplished using a retrospective look at 1996 Digital Orthophoto Quarter Quadrangle 

(DOQQ) imagery for a semiquantitative comparison with 2008 border area orthoimagery as a 

“current” baseline and using future aerial photograph/satellite imagery acquisitions at 3- to 5-

year intervals (or as available) for monitoring change from the baseline.

High-resolution (30 cm) color aerial imagery was acquired in 2008 for the entire United 

States-Mexico borderlands area, with a minimum area of 30 miles north and 10 miles south of 

the boundary line. The dataset was created to provide geospatial data for Federal, State, and local 

emergency responders, as well as for homeland security efforts. The spectral and spatial 

resolutions of the dataset provide sufficient information to establish a baseline inventory of 

unauthorized roads and trails. 

High-resolution aerial datasets that are currently (2011) available: 

1996 Digital Orthophoto Quarter Quadrangles (USGS).—A digital orthophoto 

quadrangle (DOQ) is a computer-generated image of an aerial photograph in which image 

displacement caused by terrain relief and camera tilts has been removed. A DOQ combines the 

image characteristics of a photograph with the geometric qualities of a map. DOQs produced by 

the USGS are either gray-scale, natural color, or color-infrared (CIR) images with 1-m ground 

resolution and 3.75-minute spatial extent. All DOQs are referenced to the North American 

Datum of 1983 (NAD 83) and projected according to the Universal Transverse Mercator (UTM) 

projection (U.S. Geological Survey, 1998).

1996 Digital Orthophoto Quarter Quadrangles (DOQQs) may be a sufficient scale to help 

document (possibly only semiquantitatively) ecosystem change at BMGR–West between 1996 

and 2008. DOQQs of BMGR–West can be found at: http://aria.arizona.edu/. 

2007 Digital Orthophoto Quarter Quadrangles (National Agriculture Imagery Program, 

2009).—The NAIP acquires aerial imagery during the agricultural growing seasons in the 

continental United States. A primary goal of the NAIP is to make digital orthophotography 

available to governmental agencies and the public within a year of acquisition. NAIP imagery is 

acquired at a 1-m ground sample distance (GSD), with a horizontal accuracy that matches within 

six meters of photo-identifiable ground control points that are used during image inspection. The 

default spectral resolution is natural color (red, green, and blue, or RGB), but beginning in 2007, 

imagery for some States has been delivered with four bands of data: RGB and near infrared. 

The 2007 DOQQs could be used as a bridge to help interpret the 2008 imagery for 

comparison with the 1996 DOQQs, because the 1996 and 2008 datasets have different formats 

and image quality. The 2007 DOQQs are organized by State and are on an ArcGIS server

maintained by the USDA Farm Service Agency (FSA). 

2008 Border Area Orthoimagery (Arizona State Land Department, Arizona Land 

Resource Information System).—The 2008 border-area orthoimagery data were collected as a 

result of the need for geospatial data immediately available and easily accessible to provide 

geographic reference for Federal, State , and local emergency responders, as well as for 

homeland security efforts. Orthoimages also serve a number of additional purposes, from interim 

maps to field references for earth science investigations and analysis. For the 2008 imagery, 

natural color orthoimages were produced at 0.3-m (approximately 1-ft) pixel resolution. Natural 

color orthoimagery is organized in three color bands or channels, which represent the red, green, 

and blue portions of the spectrum. The design accuracy is estimated not to exceed 6-m horizontal 
54

Root Mean Square Error (RMSE) for locations within the United States. Each orthoimage 

provides imagery for a 1,500-m by 1,500-m block on the ground. The projected coordinate 

system is UTM with datum NAD83.

The imagery was collected at an average altitude of 9,500 ft above mean terrain (AMT) 

using an ADS40-II digital sensor. The ADS40-II sensor collects 12-bit image data, which 

requires radiometric adjustment for output in standard 8-bit image channels. Converting to eight 

bits results in a reduction of the color range from 4,096 to 256 levels. Thus, loss of radiometric 

detail is inevitable. In addition to color balancing, these eight-bit images were adjusted to create 

seamless imagery to the highest extent practically achievable. The imagery was mosaicked using 

a combination of automated and manual seamline generation. Project-specified tiles were 

extracted from the mosaic to produce a natural color digital orthophoto image map. 

Conducting Road Inventory

In 1999, the BLM completed a comprehensive map of authorized roads at BMGR–West 

before transferring natural and cultural resource management responsibility to the Secretary of 

the Navy and the Secretary of the Air Force. MCAS-Yuma updated this authorized road network 

in 2008 for completion of the BMGR–West Visitor’s Guide and Map. Roads were mapped using 

a Leica System GPS500 with GPS and positional accuracies of 30 cm. The roads are mapped on 

a continual basis to meet requirements of ongoing projects. The protocol below describes the 

process required to develop an inventory map documenting additional (unauthorized) roads on 

BMGR–West.

Unauthorized Roads

 Aerial imagery can be imported into a GIS environment for road network digitization. A 

“Roads” shapefile can be created and digitization done using the ArcEditor extension of 

ArcMap. Accurate delineation of roads, trails, and border-related and visitor-related impacts 

depends on the local substrate and GIS operator’s experience with high-resolution image 

interpretation and knowledge of histogram manipulation techniques. Identifying trails in the 

imagery is a subjective process, the results of which depend on the interpreter’s experience and 

familiarity with the area; accurate interpretation depends on a set of intuitive, perhaps not easily 

articulated, criteria for identifying a lineament as a trail rather than a drainage, a random 

alignment of shrubs, or another natural landscape feature that might look somewhat like a trail. 

The following information would be described or developed using the road inventory 

data, and can be updated at a regular interval with the acquisition of new imagery: 

• Total number of miles of roads 

• Number of road segments 

• Segment lengths 

• Qualitative scoring of erosion-potential of soil based on adjacent disturbances 

• Road width and number of spurs 

• Baseline inventory using 1996 imagery to compare with 2006 imagery

Field transects are necessary to verify the accuracy of digitized maps and may be 

necessary in areas where it is difficult to interpret aerial imagery (for example, Mohawk Dunes). 

The general procedure would be to establish a transect route beforehand in a GIS environment 

and send a field crew out to that location to collect data (with hardcopy maps of aerial imagery). 
55

Field crews would record locations with a GPS and note the type (road/trail) and general usage 

(low, moderate, or heavy). 

Road and Trail Erosion Monitoring

Once a road inventory is complete, it is possible to identify areas with high erosion 

potential by overlaying the digitized road network with a potential erosion map raster layer 

(section 3.1.4). Ground-based road and trail erosion monitoring (section 3.1.4) would occur in 

areas with high erosion potential. 

Road and trail erosion monitoring would be done with a similar assortment of survey and 

sediment trap methods to those of the Vegetation Community and Soils plots and StreamChannel Erosion Monitoring (sections 3.1.3 and 3.1.5). Road and trail cross-sectional surveys 

used along with more selectively placed wind- and water-based sediment traps would be used to 

try to estimate road contribution to area erosion. A complete road and trail inventory is the most 

essential tool for implementing a proper erosion monitoring sampling design. The proximity to 

the United States-Mexico border and military uses of BMGR–West make this a potentially tough 

inventory to maintain. Thus, from whatever inventory is available, a statistical sampling routine 

would be created to produce a set of points along trails and roads that allow statistical inference 

to the entire inventoried landscape. Stratification by road and trail type would also be necessary, 

and point placement would be weighted more heavily towards areas with higher wind and 

erosion potentials as modeled in the erosion potential inventory maps. Points would be allocated 

using the GRTS method (Hubbard and others, 2009; Stevens and Olsen, 2004) in a manner 

similar to that of the basin-level Stream-Channel Erosion Monitoring method (section 3.1.5). 

At each sampling site, a transect would be run perpendicular to the road or trail covering 

the full extent of the influenced area. The transect endpoints would be permanently marked and 

recorded by a GPS for repeat measurements. The elevation profile of this transect would be 

measured at 0.25-m intervals. Vegetation life-form and surface cover would also be measured at 

each interval in a line-point intercept following Hubbard and others (2009), with the exception of 

recording vegetation to the species level (that is, only recording if any vegetation was hit in each 

height class). Eighteen soil aggregate stability samples (Herrick and others, 2001; Hubbard and 

others, 2009) would also be collected at evenly spaced intervals along the transect. Each sample 

would be referenced to a length along the transect so the location along the road/trail transect can 

be used in analysis. Cross-sectional areas would help provide actual soil loss estimates at these 

transects, while cover and aggregate stability provide additional ecological data and indicate if 

potential exists for erosion spreading from actual road or trail cuts. 

Depending on the availability of resources, all or a sampled subset of trail and road points 

can be monitored with sediment traps for both wind and water. If all points cannot be 

instrumented, a random sampling scheme would be used weighted towards points with higher 

potential erosion in the erosion inventory. Sites may also be selected in retrospect after doing 

initial cross sections. In that case, sites with noticeable erosion cutting could be weighted more 

heavily in selection, but within a statistically randomized selection process so inference to the 

greater area is still possible. 

Sediment trap placement requires more preparation for a road or trail, because water bars 

and off-track sediment traps are required. Placement of water-sediment traps would follow the 

arrangement outlined by Luce and Black (2001), where the trap is co-located with a water bar to 

sample an upslope segment of road. This water-bar trap setup would be located downslope of the 
56

transect, so that the transect falls in about the middle of the segment of trail/road being sampled. 

Variations of the Wells and Wohlgemuth (1987) trap would be used for smaller trails, and the 

larger watershed outlet type trap used for larger trails and roads (Robichaud and others, 2008; 

Robichaud and Brown, 2003). 

Wind traps would be set along the cross-section transect to see if proximity to the road 

increases sediment yields. Fryrear dust samplers (Fryrear, 1986) would be set, with optimal 

arrangements including at least two traps near the ends of the transects (away from road) and two 

as close to the road as possible (preferably on both sides). Similarly to the vegetation plots, any 

road sites that show high wind erosion requiring more detailed wind-emission data would be 

equipped with the 10-m tower air samplers (Nickling and Gillies, 1993). 

3.3.2 Visitor Use

Monitoring visitor use at BMGR–West would follow a two pronged approach: (1) 

monitoring long-term changes in visitor and vehicle numbers through the range visitor permit 

system and (2) monitoring the physical impacts of visitors on roads, trails, and campsites 

(including associated soils and vegetation). It is suggested that roads, trails, and campsites be 

monitored every 3–5 years and sampling be both random and nonrandom (for example, at known 

camp destinations). 

Visitor-use monitoring protocols, particularly campsite monitoring, often rely on changes 

in soil and plant parameters as indicators of use. Campsites in desert environments are typically 

void of biotic soil crusts and vascular plants; repeated, moderate to heavy use of desert campsites 

is known to cause soil compaction, reducing the ability of desert plants to establish healthy root 

systems and decreasing germination and establishment rates (Cole, 1986). Ironwood (Olneya 

tesota), paloverde (Parkinsonia spp.), and mesquite trees in the vicinity of campsites are often 

targeted for fuel wood collection. 

There exist no maintained campsites at BMGR–West, but visitors gravitate towards 

certain areas where the physical environment is conducive to camping. Monitoring data on the 

impacts of primitive camping on the soils and vegetation of areas can be used to reduce repeated 

impacts and site expansion and for restoration of areas that appear significantly degraded. 

Visitor Permit Monitoring 

The permit system at BMGR–West provides a virtual census of all visitors entering the 

range (as opposed to nonmandatory visitor registers or pressure counters), allowing management 

to assess trends and patterns at fine temporal scales. The permit process at BMGR–West requires 

visitors to fill out the necessary paperwork by mail or in person at the MCAS-Yuma Range Pass 

and ID Office located on the north side of the main gate. The permit form includes information 

on the number of vehicles, number of visitors in the party, date of visit, and length of visit. 

Permit data would be entered monthly into a spreadsheet/database and analyzed for 

trends annually. Several descriptive metrics (sum, mean, and standard deviation) can be derived 

from the data for collected variables, including the number of visitors, the number of vehicles, 

and the length of visits. 
57

Campsite Monitoring 

Campsite locations at the BMGR–West may be inventoried every 3–5 years and locations 

determined by driving the entire road network and identifying both areas used repeatedly as 

campsites and areas with new signs of light or low-use camping. The campsite monitoring 

protocol includes three steps: a qualitative condition assessment, measurement of disturbed 

areas, and photographic documentation of the site (appendix F).
58

4.0 Data Management

Data management is critical to the success of BMGR–West monitoring efforts. Vigilant 

and systematic data entry and management ensure data quality, interpretability, security, 

longevity, and availability. Data availability is an important component of collaborative 

monitoring and collaborative adaptive management. The following sections provide a basic 

framework for establishing a sound data management system and suggestions for establishing 

and maintaining a monitoring data repository for multiagency monitoring datasets that span the 

Sonoran Desert Ecoregion. 

Standard operating procedures (SOPs) can be developed and maintained for all 

implemented monitoring protocols. It is suggested that all changes and revisions to protocols and 

SOPs be kept as a record in a “protocol revision history” form, ensuring that the decisionmaking 

process is transparent and provides a knowledge base for future monitoring staff. 

4.1 Data Entry, Metadata, and Archiving

Careful and accurate recording of measurements in the field is a first step to ensuring 

quality monitoring data, but it is important to establish safeguards to reduce both systematic and 

random data entry errors. Several quality assurance and quality control (QA/QC) mechanisms 

help identify and correct data entry and measurement errors. QA/QC methods include (1) 

defining and enforcing data formats, measurement units, and unit/plot naming conventions, (2) 

checking for data entry errors, unusual patterns in the data and outliers, and (3) checking for 

compatibility among datasets. After all data for a field season have been entered, verified, 

validated, and certified, the seasonal data would be appended to a master monitoring database. 

All resource-specific and master monitoring databases would be archived on a secure server with 

regularly scheduled backups (weekly backups suggested). It is suggested that all datasets include 

some level of metadata, providing documentation of how, why, when, and where data were 

collected and including spatial information (for example, coordinate system, datum) when 

appropriate. An example of metadata standards is available at 

http://www.fgdc.gov/metadata/geospatial-metadata-standards. 

Staff operating the SODN provided Microsoft Access databases for Vegetation and Soils 

and Bird monitoring protocols. To update, modify, or develop additional Microsoft Access 

monitoring databases for BMGR–West, see the National Park Service Database Template 

(http://science.nature.nps.gov/im/apps/template/).

4.2 Geospatial Data Management

Datasets collected for I&M processes represent a critical component of the overall natural 

resources management strategy of BMGR–West. GEOFidelis, as the USMC geospatial program 

of record, recognizes the importance of collecting accurate, reliable, up-to-date, authoritative 

data to support efficient and effective conservation of resources, efficient and effective planning 

to avoid and minimize environmental impacts, and sharing data in regional and national contexts. 

Data need to meet multiple uses at multiple scales and standards to support key data 

infrastructure goals.
59

4.3 Monitoring Data Repository: Location and Oversight

Several options exist for a central data repository to house BMGR–West I&M program 

data:

1. Heritage Data Management System (HDMS), AZGFD (URL: 

http://www.AZGFD.gov/w_c/edits/species_concern.shtml). The HDMS is an integrated data 

management system of maps, computer files, and paper files. Data concerning the location of 

species of concern and habitats are mapped; data concerning the ecological status of species 

are cataloged; and data concerning the biology of species are consolidated into a wellorganized system whereby a myriad of information can be easily retrieved. Information is 

constantly being added and updated, creating a dynamic system. Information included in the 

HDMS comes from published and unpublished reports, data collected by cooperating 

agencies, museum and herbarium collections, the scientific and academic communities, and 

many other sources. 

2. Arizona Regional Image Archive (ARIA), University of Arizona (URL: 

http://aria.arizona.edu/). The ARIA is an interdisciplinary resource system for digital image 

and map data for the Sonoran Desert region, including the southwestern United States and 

northern Mexico. ARIA is an image repository maintained by volunteers at the Arizona 

Remote Sensing Center (ARSC) and the Office of Arid Lands Studies (OALS) at the 

University of Arizona. ARIA is primarily a satellite image and map database.

3. Earth Resources Observation and Science (EROS) Center (URL: http://eros.usgs.gov/). 

EROS is a remotely sensed data management, systems development, and research field 

center of the USGS. Although EROS primarily houses geospatial data (cartographic and 

satellite imagery), there exists potential for integrating species and plot data. For example, 

the USGS is leading a cooperative national effort of amphibian monitoring, research, and 

conservation through the National Amphibian Research and Monitoring Initiative (ARMI). 
60

5.0 Management Actions as a Result of Inventory and Monitoring

The purpose of this I&M Plan is to guide the implementation and development of a I&M 

program that would provide MCAS-Yuma with useful information for describing the status of 

BMGR–West ecological resources. Data collected through the I&M process would ultimately 

help to identify potential changes in the amount, distribution, or quality of BMGR–West 

resources. Certain management actions or interventions may be indicated if changes in a 

monitoring parameter are detected and the condition of a resource deviates from the stated 

monitoring objectives (see section 1.2) of BMGR–West and MCAS-Yuma (fig. 5.1). It is 

suggested that resource thresholds be determined beforehand by BMGR–West management and 

that they be based on well-defined objectives and desired conditions for each resource being 

monitored. 

Figure 5.1. The relationship between an ecological monitoring program and management activities 

(adapted from Vos and others, 2000).
61

6.0 Programmatic Review of Monitoring and Management Activities

A thorough analysis of monitoring data from all implemented protocols may be 

undertaken after the first 3 years of monitoring, and a timeframe for future reviews could be 

established based on the initial program review. An initial 3-year review could involve extensive 

quantitative analyses to evaluate the efficiency of the program design, results, and ability to meet 

managers’ goals and objectives. At that time, monitoring teams may have identified field 

techniques and adjustments to the original protocols that warrant inclusion in or revision of the 

original protocols. A major component of the review would involve suggested revisions to the 

monitoring program, with explicit justification of each revision. 

The program review effort can include trend assessment of monitoring parameters, 

variance partitioning and power analysis, and an assessment of sampling methods and spatial 

inferences. BMGR–West staff may want to contract or hire a suitable program reviewer with the 

appropriate skills and experience to independently review all aspects of the BMGR–West 

monitoring program. 
62

Acknowledgments

The authors wish to thank Brian Powell and Laura Norman for their reviews of this 

material. The authors would also like to thank the Barry M. Goldwater Range–West I&M 

workshop presenters and participants for their input and reviews of the documents. We would 

like to thank Andy Hubbard, Evan Gwilliam, Kristin Beaupre, and the rest of the National Park 

Service Sonoran Desert Network staff for their help and the use of protocols and databases for 

this plan. 

References Cited

Arnett, M., and Douglas, P.P., 1996, Floristic inventory of Barry M. Goldwater Air Force Range. 

Maricopa, Pima and Yuma Counties, Arizona: Center for Ecological Inventory of Military 

Lands, Department of Forest Sciences, Colorado State University, Fort Collins CO, 60p. 

Arizona Game and Fish Department, 2010, Hunting unit report, Game Management Unit 40B, 

http://www.azgfd.gov/h_f/hunting_units_40b.shtml 

Averill-Murray, R.C., 2000, Survey protocol for Sonoran Desert Tortoise monitoring plots;

reviewed and revised: Arizona Interagency Desert Tortoise Team, 46 p. 

Ball, L.C., 2002, A strategy for describing and monitoring bat habitat: The Journal of Wildlife 

Management, v. 66, no. 4, p. 1,148–1,153. 

Bewket, W., and Sterk, G., 2003, Assessment of soil erosion in cultivated fields using a survey 

methodology for rills in the Chemoga watershed, Ethiopia: Agriculture, Ecosystems and 

Environment, v. 97, p. 81–93. 

Bright, J.L., and Hervert, J.J., 2002, Sonoran Pronghorn population monitoring progress report; 

1999-2001: Arizona Game and Fish Department, Technical Report, 209 p. 

Bright, J.L., Hervert, J.J., Piest, L.A., Henry, R.S., and Brown, M.T., 1999, Sonoran Pronghorn 

1998 aerial survey summary: Arizona Game and Fish Department, Technical Report, 152 p. 

Bright, J.L., Hervert, J.J, and Brown, M.T., 2001, Sonoran Pronghorn 2000 aerial survey 

summary: Arizona Game and Fish Department, Technical Report, 180 p. 

Brooks, M.L., and Berry, K.H., 2006, Dominance and environmental correlates of alien annual 

plants in the Mojave Desert, USA: Journal of Arid Environments, v. 67, (Supplement 1), p. 

100–124. 

Brooks, M.L., and Lair, B.M., 2009, Ecological effects of vehicular routes in a desert ecosystem,

in Webb, R.H., Fenstermaker, L., Heaton, J., Hughson, D., McDonald, E., and Miller, D., eds., 

The Mojave Desert; ecosystem processes and sustainability: Reno, University of Nevada Press, 

168–195 p. 

Brooks, M.L., D’Antonio, C.M., Richardson, D.M., Grace, J., Keeley, J.J., DiTomaso, J., Hobbs, 

R., Pellant, M., and Pyke, D., 2004, Effects of invasive alien plants on fire regimes:

Bioscience, v. 54, 677–688 p. 

Brown, J.R., and Archer, S., 1999. Shrub invasion of grassland; recruitment is continuous and 

not regulated by herbaceous biomass or density: Ecology, v. 80, no. 7, p. 2,385–2,396. 

Broyles, B. 1997, Wildlife water-developments in southwestern Arizona: Journal of the ArizonaNevada Academy of Science, v. 30, no.1, p. 30–42. 
63

Buckland, S.T., Anderson, D.R., Burnham, K.P., Laake, J.L., Borchers, D.L., and Thomas, L., 

2001, Introduction to distance sampling; estimating abundance of biological populations: 

Oxford, U.K., Oxford University Press.

Burnham, K.P., and Anderson, D.R., 2002, Model selection and multimodel inference; a 

practical information-theoretic approach (2d ed.): New York, Springer Verlag. 

Burt, R., ed., 2004, Soil survey laboratory methods manual: U.S. Department of Agriculture 

Natural Resources Conservation Service, Soil Survey Investigations Report No. 42, version 

4.0, ftp://ftp-fc.sc.egov.usda.gov/NSSC/Lab_Methods_Manual/SSIR42_2004_print.pdf. 

Cabeza Prieta National Wildlife Refuge, 1995, Plants of Cabeza Prieta NWR. (Available online 

at http://www.fws.gov/southwest/refuges/arizona/cabplant.html).

Campbell, H.W., and Christman, S.P., 1982, The herpetological components of Florida 

 sandhill and sand pine scrub associations, in Scott, N.J., Jr., ed., Herpetological Communities:

Washington, DC., US Fish and Wildlife Service, p. 163–171. 

Cohen, J., 1988, Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: 

Lawrence Erlbaum Associates. 

Cole, D.N., 1986, Recreational impacts on backcountry campsites in Grand Canyon National 

Park, Arizona, USA: Environmental Management, v.10, no. 5, p. 651–659. 

Crump, M.L., and Scott, N.J., Jr., 1994, Visual encounter surveys, in Heyer, W.R., Donnelly, 

M.A., McDiarmid, R.W., Hayek, L.C., and Foster, M.S., eds., Measuring and monitoring 

biological diversity; standard methods for amphibians: Washington, D.C., Smithsonian 

Institution Press, 405 p. 

D’Antonio, C., and Vitousek. P., 1992, Biological Invasions by exotic grasses, the grass/fire 

cycle, and global change: Annual Review of Ecology and Systematics, v. 23, p. 63–87. 

Daubenmire, R.F., 1959, Canopy coverage method of vegetation analysis: Northwest Science, v. 

33, p. 43–64. 

David, O.O., 1999, Improvement in field texture accuracy for sustainable agriculture: Journal of 

Sustainable Agriculture, v. 15, no. 2, p. 61–68. 

Drake, S., Sanova, N., and Hubbard, A.J., 2004, Use of remote sensing techniques to quantify 

border impacts at Coronado National Memorial and Organ Pipe Cactus National Monument: 

Report for National Park Service Sonoran Desert Network, 30 p. 

Drake, S., Buckley, S., Villarreal, M.L., Studd, S., and Hubbard, A.J., 2009, Vegetation 

classification, distribution and mapping report: Fort Collins, Colorado, National Park Service,

Tumacácori National Historical Park, Natural Resource Report NPS/SODN/NRR-2009/148. 

Duncan, D.K., Fernandez, E., and McCasland, C., 2010, The U.S.-Mexico border and 

endangered species. P. 123–130 in Halvorson, W., Schwalbe, C., and van Riper, C., III, eds., 

Southwestern desert resources: Tucson, The University of Arizona Press. 

Elzinga, C.L., Salzer, D.W., Willoughby, J.W., and Gibbs, J.P., 2001, Monitoring plant and 

animal populations: Malden, Massachusetts, Blackwell Science, Inc., 360 pages. 

Executive Order 13112 of February 3, 1999: Federal Registry, v. 64, no. 25. 

Felger, R.S., B. Broyles, M. Wilson, and Nabhan, G.P., 1997, The binational Sonoran Desert 

Biosphere Network and its plant life. Journal of the Southwest v. 39, p. 411–560. 

Fisher, R., Stokes, D., Rochester, C., Brehme, C., Hathaway, S., and Case, T., 2008, 

Herpetological monitoring using a pitfall trapping design in southern California: U.S. 

Geological Survey Techniques and Methods, 2-A5, 44 p. 
64

Flat-tailed Horned Lizard Interagency Coordinating Committee, 2003, Flat-tailed horned lizard 

rangewide management strategy, 2003, revision: 80 p. plus appendixes. (Available online at 

http://www.fws.gov/southwest/es/arizona/Documents/SpeciesDocs/FTHL/Rangewide_Plan_Final_FTHL.pdf). 

Flesch, A.D., 2008, Population and community dynamics of lizards and rodents in Organ Pipe 

Cactus National Monument 1989–2006 and implications for future monitoring: Desert 

Southwest Cooperative Ecosystems Studies Unit, Cooperative Agreement No H1200050003, 

UAZDS-221 and 262, 88 p. (Available online at http://www.nps.gov/orpi/QDWXUHVFLHQFHXSORDG

3RSXODWLRQDQGFRPPXQLW\G\QDPLFVRIVPDOOYHUWHEUDWHVLQ

253,B)OHVFKSGI).

Forman, R.T.T., and Alexander, L.E., 1998, Roads and their major ecological effects: Annual 

Review Ecological Systems, v. 29, p. 207–231. 

Fryrear, D.W., 1986, A field dust sampler: Journal of Soil and Water Conservation, v. 41, p. 17–

120. 

Fryrear, D.W., Sutherland, P.L., Davis, G., Hardee, G., and Dollar, M., 2001, Wind erosion 

estimates with RWEQ and WEQ, in Stott, D.E., Mohtar, R.H., and Steinhardt, G.C., eds., 

Sustaining the global farm: Selected papers from the 10th International Soil Conservation 

Organization, May 24–29, 1999, at Purdue University and the USDA-ARS National Soil 

Erosion Research Laboratory, 6 p. (Available online from 

http://www.tucson.ars.ag.gov/isco/isco10/sustainingTheGlobalFarm/P120-Fryrear.pdf). 

Gibbons, J.W., and Semlitsch, R.D., 1982, Terrestrial drift fences with pitfall traps; an effective 

technique for quantitative sampling of animal populations: Brimleyana, v.7, p. 1–6. 

Gilewitch, D., 2004, The effect of military operations on desert pavement: case study from 

Butler Pass, AZ. in D.R. Caldwell, J. Ehlen and R.S. Harmon, eds., Studies in Military 

Geography and Geology:Kluwer Academic Publishers, Dordrecht, The Netherlands. 

Guo-ping, Z., Zeng-xiang, Z., and Ji-yuan, L., 2001, Spatial distribution of wind erosion and its 

driving factors in China: Journal of Geographic Sciences, v. 11, no. 2, p. 127–139. 

Hall, E.R., 1981, The Mammals of North America, Volume 1: John Wiley and Sons, New York, 600 p.

Hall, J.A., Comer, P., Gondor, A., Marshall, R., and Weinstein, S., 2001, Conservation elements 

of and a Biodiversity Management Framework for the Barry M. Goldwater Range, Arizona: 

Tucson, The Nature Conservancy of Arizona, 199 + ix p. + 15 unpaginated figures. 

Herrick, J.E., Whitford, W.G., de Soyza, A.G., Van Zee, J.W., Havstad, K.M., Seybold, C.A., 

and Walton, M., 2001, Field soil aggregate stability kit for soil quality and rangeland health 

evaluations: Catena, v. 44, no. 1, p. 27–35. 

Herrick, J.E., Van Zee, J.W., Havstad, K.M., Burkett, L.M., and Whitford, W.G., 2005a, 

Monitoring manual for grassland, shrubland and savanna ecosystems. Volume. 1, Quick start:

USDA-ARS Jornada Experimental Range, 42 p. (Available online at ftp://ftpfc.sc.egov.usda.gov/GLTI/CBC_Range/References/CBC_GL_Refs%20(D)/Quick_Start.pdf). 

Herrick, J.E., Van Zee, J.W., Havstad, K.M., Burkett, L.M., and Whitford, W.G., 2005b, 

Monitoring manual for grassland, shrubland and savanna ecosystems. Volume 2, Design, 

supplementary methods and interpretation: USDA-ARS Jornada Experimental Range, 206 p

Heyer, W.R., Donnelly, M., McDiarmid, R.W., Hayek, L.A., and Foster, M.S., 1994, Measuring 

and monitoring biological diversity; standard methods for amphibians: Washington D.C. and 

London, Smithsonian Institution Press, 364 p. 

Hoffmeister, D.F., 1986, Mammals of Arizona: Tucson, AZ, University of Arizona Press. 
65

Hubbard, J.A., Mau-Crimmins, T.M., Powell, B.F., Albrecht, E.W., Chambers, N., and Carder, 

L., 2003, National Park Service Sonoran Desert Network monitoring plan. Phase II: Sonoran 

Desert Network, Tucson, Ariz., 72 p. (Available online at 

http://pubs.usgs.gov/of/2006/1076/of2006-1076.pdf). 

Hubbard, J.A., McIntyre, C.L., Studd, S.E., Nauman, T.W., Angell, D., Connor, M.K., and 

Beaupre, K., 2009, Terrestrial vegetation and soils monitoring protocol and standard operating 

procedures for the Sonoran Desert Network: Natural Resource Report NPS/SODN/NRR—

2009/0XX. National Park Service, Fort Collins, Colorado. (Available online at 

http://science.nature.nps.gov/im/monitor/protocols/SODN_Uplands_Protocol_v100.pdf).

Integrated Natural Resources Management Plan, 2007, Integrated Natural Resources 

Management Plan for Barry M. Goldwater Range, Yuma, Pima, and Maricopa Counties, 

Arizona: Prepared by Departments of the Air Force and Navy in cooperation with Department 

of the Interior and Arizona Game and Fish Department, 101 p. 

Jabbar, M., Chen, X., and Li, H., 2006, Land degradation due to soil wind erosion in arid and 

semi-arid regions with the aid of geo-information technology: Geoscience and Remote Sensing 

Symposium, 2006 (IGARSS 2006), IEEE International Conference, Denver, Colo., 3292 p. 

Jones, C., McShea, W.J., Conroy, M.J. and Kunz, T.H., 1996, Capturing mammals, in Cole, F.R., 

Nichols, J.D., Rudran, R. and Foster, M.S., eds., Measuring and monitoring biological 

diversity; standard methods for mammals: Washington, D.C., Smithsonian Institution Press, p. 

115–155. 

Klik, A., 2000, Wind erosion assessment in Austria using Wind Erosion Equation and GIS: 

(Available online at 

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.124.9706&rep=rep1&type=pdf).

Kouli, M., Soupios, P., and Valliantos, F., 2009, Soil erosion prediction using the Revised 

Universal Soil Loss Equation (RUSLE) in a GIS framework, Chania, Northwestern Crete, 

Greece: Environmental Geology, v. 57, p. 483–497. 

Kuenzi, A.J., and Morrison, M.L., 2003, Temporal patterns of bat activity in southern Arizona: 

The Journal of Wildlife Management, v.67, no.1, p. 52–64. 

Kuntz, T.H., 2003, Censusing bats; challenges, solutions, and sampling biases, in O’Shea, T.J., 

and Bogan, M.A., eds., Monitoring trends in bat populations of the United States and 

territories; problems and prospects: U.S. Geological Survey, Information and Technology 

Report, USGS/BRD/ITR--2003–0003, 274 p. 

Kuperman, B.I., Matey, V.E., Fisher, R.N., Ervin, E.L., Warburton, M.L., Bakhireva, L., and 

Lehman, C.A., 2004, Parasites of the African clawed frog, Xenopus laevis, in southern 

California, U.S.A: Comparative Parasitology, v.71, no.2, p. 229–232. 

Kuss, F.R., 1986, A review of major factors influencing plant responses to recreation impacts: 

Environmental Management, v. 10, p. 637–650. 

Lagacherie, P., and McBratney, A.B., 2007, Spatial soil information systems and spatial soil 

inference systems; perspectives for digital soil mapping, in Lagacherie, P., McBratney, A.B., 

and Voltz, M., eds., Digital soil mapping; an introductory perspective: Amsterdam, Elsevier, p. 

3–22. 

Leys, J., McTainsh, G., and Shao, Y., 2001, Wind erosion monitoring and modeling techniques

in Australia, in Scott, D.E., Mohtar, R.H., and Steinhardt, G.C., eds., Sustaining the global 

farm: Selected Papers from the 10th International Soil Conservation Organization Meeting 

held May 24–29, 1999, at Purdue University and the USDA-ARS National Soil Erosion 
66

Research Laboratory, 11 p. 

Lovich, J.E., and Bainbridge, D., 1999, Anthropogenic degradation of the Southern California 

desert ecosystem and prospects for natural recovery and restoration: Environmental 

Management, v. 24, no. 3, p. 309–326. 

Lovich, R.E., Ryan, M.J., Pessier, A.P., and Claypool, B., 2008, Infection with the fungus 

Batrachochytrium dendrobatidis in a non-native Lithobates berlandieri below sea level in the 

Coachella Valley, California, USA: Herpetological Review, v. 39, no. 3, p. 315–317. 

Lowe, C.H., Wirt, E.B., and Rosen, P.C., 1995, Vegetation structure and diversity in Natural 

Communities Monitoring Protocol for the Ecological Monitoring Program in Organ Pipe 

Cactus National Monument, Arizona: University of Arizona, Department of Ecology and 

Evolutionary Biology, 61 p. 

Luce, C. H. and Black, T. A., 2001, Spatial and temporal patterns in erosion from forest roads. 

Influence of Urban and Forest Land Uses on the Hydrologic-Geomorphic Responses of 

Watersheds. M.S. Wigmosta and S.J. Burges, Editors. American Geophysical Union, 

Washington, D.C., p. 165–178. 

Mackenzie, D.I., and Royle, J.A., 2005, Designing occupancy studies; general advice and 

allocating survey effort: Journal of Applied Ecology, v. 42, p. 1,105–1,114. 

Malusa, J., 2003, Vegetation of the Cabeza Prieta National Wildlife Refuge, Arizona: Report 

submitted to Organ Pipe Cactus National Monument, National Park Service, NPS Cooperative 

Agreement CA1248.00.002, Task Agreement UA2-71, 81 p. (Available online at 

http://sdrsnet.srnr.arizona.edu/data/sdrs/cabezablmveg/docs/final_cabeza.pdf). 

Malusa, J., 2009, Vegetation mapping at the Barry M. Goldwater Range, Marine Corps Air 

Station, Arizona. Phase I, Mohawk Mountains and Dunes: Cooperative Agreement DACA87-

05-H-0018, Modification P00012, 2 p. 

Malusa, J., Halvorson, W.L., and Angell, D., 2003, Distribution of the exotic mustard, Brassica 

tournefortii, in the Mohawk Dunes and Mountains, Arizona: Desert Plants, v. 19, p. 31–36. 

McBratney, A.B., Santos, M.L.M., and Minasny, B., 2003, On digital soil mapping: Geoderma, 

v. 117, no. 1-2, p. 3–52. 

McBratney, A.B., Minasny, B., and Rossel, R.V., 2006, Spectral soil analysis and inference 

systems; a powerful combination for solving the soil data crisis: Geoderma, v.136, p. 272–278. 

Miles, R., and McTainsh, G.H., 1994, Wind erosion and land management in the mulga lands of 

Queensland: Journal of Soil and Water Conservation, v. 7, p. 41–45. 

Mitasova, H., and Mitas, L, 1999, Erosion/deposition modeling with USPED using GIS: Online 

at http://skagit.meas.ncsu.edu/~helena/gmslab/erosion/usped.html. 

Moore, I.D., Gessler, P.E., Nielsen, G.A., and Petersen, G.A., 1993, Terrain attributes; 

estimation methods and scale effects, in Jakeman, A.J., Beck, M.B., and McAleer, M., eds., 

Modelling change in environmental systems: London, Wiley, p. 189–214. 

Nauman, T., 2009, Digital Soil Subgroup map of selected areas of the Barry M. Goldwater 

Range for Arizona Game and Fish:Unpublished Report, AZGF PO #E0075088, 7 p. 

National Agriculture Imagery Program (NAIP), 2009, Information sheet: 

http://www.fsa.usda.gov/Internet/FSA_File/naip_2009_info_final.pdf. 

Nickling, W.G., and Gillies, J.A., 1993, Dust emission and transport in Mali, West Africa: 

Sedimentology, v. 40, p. 859–868. 
67

North American Weed Management Association, 2002, North American Invasive Plant mapping 

standard:. Accessed online January 2010 at http://www.nawma.org/. 

Odeh, I.O.A., Crawford, M., and McBratney, A.B., 2007, Digital mapping of soil attributes for 

regional and catchment modelling, using ancillary covariates, statistical and geostatistical 

techniques, in Lagacherie, P., and McBratney, A.B., eds., Digital soil mapping; an introductory 

perspective: Amsterdam, Elsevier, p. 437–453. 

O'Farrell, M.J., Miller, B.W., and Gannon, W.L., 1999, Qualitative identification of free-flying 

bats using the Anabat Detector: Journal of Mammalogy, v. 80, no. 1, p. 11–23. 

Organ Pipe Cactus National Monument, 2006, Ecological Monitoring Program Report 1997– 

2005. Organ Pipe Cactus National Monument, Arizona, 25 p. 

Pate, A., 2006, Bats, chap. 9 of Organ Pipe Cactus National Monument. Ecological Monitoring 

Program Report 1997– 2005: Organ Pipe Cactus National Monument, Arizona, p. 1–26 

(Available online from http://www.nps.gov/orpi/naturescience/orpi-ecological-monitoringreport.htm). 

Petryszyn, Y., and Russ, S., 1996, Nocturnal rodent population densities and distribution at 

Organ Pipe Cactus National Monument, Arizona: Tucson, University of Arizona, Cooperative 

National Park Resources Studies Unit, Technical Report No. 52, 52 p. 

Pimentel, D., Lach, L., Zuniga, R., and Morrison, D., 1999, Environmental and economic 

 costs of non-indigenous species in the United States: BioScience, v. 50, p. 53–65. 

Powell, B.F., Flesch, A.D., Angell, D., Beaupre, K., and Halvorson, W.L., 2007, Landbird 

monitoring protocol for the Sonoran Desert Network, Version 1.02: Fort Collins, Colo., 

National Park Service, Natural Resource Report NPS/SODN/NRTR-2007/00X, 

http://science.nature.nps.gov/im/monitor/protocols/SODN_Landbird.pdf 

Prose, D.V., and Wilshire, H.G., 2000, The lasting effects of tank maneuvers on desert soils and 

intershrub flora: U.S. Geological Survey Open File Report 00-512, 26 p. 

Rejman, J., and Brodowski, R., 2005, Rill characteristics and sediment transport as a function of 

slope length during a storm event on loess soil: Earth Surface Processes and Landforms, v. 30, 

p. 231–239. 

Renard, K., Foster, G., Weesies, G., McCool, D., and Yoder, D., 1997, Predicting soil erosion by 

water; a guide to conservation planning with the Revised Universal Soil Loss Equation 

(RUSLE): U.S. Department of Agriculture, Agricultural Handbook No. 703, 23 p. (Available 

online at 

http://www.techtransfer.osmre.gov/nttmainsite/Library/hbmanual/rusle/ah703toc.pdf). 

Ritter, D.F., Kochel, R.C., and Miller, J.R., 2002, Process geomorphology (4th ed.): New York, 

McGraw-Hill, 652 p. 

Robichaud, P.R., and Brown, R.E., 2003, Quick response small catchment monitoring techniques 

for comparing post-fire rehabilitation treatment effectiveness, in Proceedings of the First 

Interagency Conference on Research in the Watersheds, 27–30 October 2003, Benson, Ariz.: 

Tucson, USDA Agricultural Research Service, p. 663–667. 

Robichaud, P.R., Wagenbrenner, J.W., Brown, R.E., Wohlgemuth, P.M., and Beyers, J.L., 2008, 

Evaluating the effectiveness of contour-felled log erosion barriers as a post-fire runoff and 

erosion mitigation treatment in the western United States: International Journal of Wildland 

Fire, v. 17, p. 255–273. 

Rosenstock, S.S., O'Brien, C.S., Waddell, R.B., and Rabe, M.J., 2004, Studies of wildlife-water 

developments in southwestern Arizona; wildlife use, water quality, wildlife diseases, wildlife 
68

mortalities, and influences on native pollinators: Arizona Game and Fish Department 

Technical Guidance Bulletin 8, 17 p. (Available online fat 

http://www.azgfd.gov/pdfs/w_c/research/Res_Branch%20Tech%20Bulletin%20No8.pdf). 

Rutman, S., and Dickson, L., 2002, Management of buffelgrass on Organ Pipe Cactus National 

Monument, Arizona, in Tellman, B., ed., Invasive exotic species in the Sonoran Region: 

Tucson, The University of Arizona Press and the Arizona-Sonora Desert Museum, p. 311–318. 

Schmidt, C.A., Powell, B.F., Swann, D.E., and Halvorson, W.L., eds., 2006, Vascular plant and 

vertebrate inventory of Organ Pipe Cactus National Monument: U.S. Geological Survey OpenFile Report 2006–1076. (http://pubs.usgs.gov/of/2006/1076/). 

Schoeneberger, P.J., Wysocki, D.A. , Benham, E.C., and Broderson,, W.D., eds. 2002, Field 

book for describing and sampling soils, Version 2.0: Natural Resources Conservation Service, 

National Soil Survey Center, Lincoln, Nebr. 

Schreuder, H.T., Ernst, R., and Ramirez-Maldonado, H., 2004, Statistical techniques for 

sampling and monitoring natural resources: Fort Collins, Colo., U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station, General Technical Report 

RMRS-GTR-126, 111 p. 

Scull, P., Franklin, J., Chadwick, O.A., and McArthur, D., 2003, Predictive soil mapping; a 

review: Progress in Physical Geography, v. 27, no. 2, p. 171–197. 

Scull, P., Franklin, J., and Chadwick, O.A., 2005, The application of classification tree analysis 

to soil type prediction in a desert landscape: Ecological Modeling, v.181, no. 1, p. 1–15. 

Seager, R., Ting, M.F., Held, I.M., Kushnir, Y., Lu, J., Vecchi, G., Huang, H.-P., Harnik, N., 

Leetmaa, A., Lau, N.-C., Li, C., Velez, J., and Naik, N., 2007, Model projections of an 

imminent transition to a more arid climate in southwestern North America: Science, v. 316. no. 

5828, p. 1,181–1,184. 

Shinneman, D.J., and Baker, W.L., 2009, Environmental and climatic variables as potential 

drivers of post-fire cover of cheatgrass (Bromus tectorum) in seeded and unseeded semi-arid 

ecosystems: International Journal of Wildland Fire, v. 18, p. 191–202. 

Sogge, M.K., van Riper, C., III, and Drost, C., 1989, Design considerations for monitoring land 

birds in Channel Islands National Park: Transactions of the Western Section of the Wildlife 

Society, v. 25, p. 65–71. 

Sprouse, T.W., Emanuel, R.M., and Strorrer, S.A., 2005, Water quality monitoring for highpriority water bodies in the Sonoran Desert network, in Gottfried, G.J., Gebow, B.S., Eskew, 

L.G., Edminster, and C.B., compilers, Connecting mountain islands and desert seas; 

biodiversity and management of the Madrean Archipelago II: Fort Collins, Colo., U.S. 

Department of Agriculture, Forest Service, Rocky Mountain Research Station, Proceedings 

RMRS-P-36, p. 219–222. 

Stevens, D.L., and Olsen, A.R., 2004, Spatially balanced sampling of natural resources: Journal 

of the American Statistical Association, v. 99, p. 262–278. 

Strahler, A.N., 1952, Hypsometric (area-altitude) analysis of erosional topology: Geological 

Society of America Bulletin v. 63, no. 11, p. 1,117–1,142. 

Strahler, A.N., 1957, Quantitative analysis of watershed geomorphology: Transactions of the 

American Geophysical Union, v. 8, no. 6, p. 913–920. 

Tarboton, D., 1997, A new method for the determination of flow directions and upslope areas in 

grid digital elevation models: Water Resources Research. v. 33, no. 2, p. 309–319. 
69

Tellman, B., ed., 2002, Invasive exotic species in the Sonoran Region: Tucson, University of 

Arizona Press and the Arizona-Sonora Desert Museum, 423 p. 

Thomas, L., Laake, J. L., Strindberg, S., Marques, F. F. C., Buckland, S. T.. Borchers, D. L., 

Anderson, D. R., Burnham, K. P., Pollard S. L., Hedley, J. H., Bishop, J. R. B., and Marques, 

T.A., 2005, Distance 5.0. Release Beta 5. Research Unit for Wildlife Population Assessment, 

University of St. Andrews, Scotland. http://www.ruwpa.st-and.ac.uk/distance/. 

Turner, D.S., Schwalbe, C.R., and Warren, P.L., 1997, Reptile and plant inventory of the 

Mohawk Dunes; inventory and monitoring of unique sand dune ecosystems, Barry M. 

Goldwater Air Force Range, Arizona: Legacy Resource Management Program, School of 

Renewable Natural Resources, University of Arizona and The Nature Conservancy, Arizona 

Chapter, Project #95-1009, 46 p. 

Turner, D.S., Felger, R.S., Mauz, K., Funicelli, C., Van Devender, T., and Malusa, J., 2000, 

Biological resources of the proposed Sonoran Desert National Monument, Arizona: Tucson, 

Drylands Institute, for the Sonoran Desert National Park Project, 87 p. 

U.S. Department of Agriculture, Natural Resources Conservation Service, 2002. Wind erosion: 

National Agronomy Handbook Part 502, 3rd Edition, p. 23–125. 

U.S. Department of Agriculture, Natural Resources Conservation Service, 2004, Soil survey 

laboratory methods manual: Soil Survey Investigations Report No. 42, Version 4.0, Rebecca

Burt, ed., 735 p. (Available online at 

ftp://ftp-fc.sc.egov.usda.gov/NSSC/Lab_Methods_Manual/SSIR42_2004_view.pdf.).

U.S. Fish and Wildlife Service, 1990, Endangered and threatened wildlife and plants; 

determination of threatened status for the Mojave population of the desert tortoise: 55 Federal 

Register 12178, April 2, 1990. 

U.S. Fish and Wildlife Service, 1994, Sonoran Pronghorn revised recovery plan: Albuquerque, 

New Mexico, U.S. Fish & Wildlife Service, 40 p. 

U.S. Geological Survey, 1998, Ditigal orthophoto quadrangles: U.S. Geological Survey Fact 

Sheet FS-129-95, 2 p. 

U.S. Geological Survey, 2009 (variously dated, recent version 2009), National field manual for 

the collection of water-quality data: U.S. Geological Survey Techniques of Water-Resources 

Investigations, book 9, chaps. A1-A9, available online at http://pubs.water.usgs.gov/twri9A. 

van Riper, C., III, 1982, Censuses and breeding observations of the birds on Kohala Mountain, 

Hawaii: Wilson Bulletin, v. 94, no. 4, p. 463–476. 

van Riper, C., III, Sogge, M.K., and Drost, C., 1988, Land bird monitoring handbook; Channel 

Islands National Park, California: National Park Service, U.S. Department of the Interior, 23 

p., Append., 5 p. 

Vos, P., Meelis, E., and Ter Keurs, W.J., 2000, A framework for the design of ecological 

monitoring programs as a tool for environmental and nature management: Environmental 

Monitoring and Assessment, v. 61, p. 317–344. 

Wake, D.B., and Vredenburg, V.T., 2008, Are we in midst of the sixth mass extinction? A view 

from the world of amphibians: Proceedings of the National Academy of Sciences, v. 105, p. 

11,466–11,473. 

Warburton, M., Kuperman, B., Matey, V., and Fisher, R.N., 2002, Parasite analysis of native and 

non-native fish in the Angeles National Forest, 2001 final report: Prepared for the U.S. Forest 

Service, Angeles National Forest, 14 p. 
70

Warren, P.L., Mortenson, B.K., Treadwell, B.D., Bowers, J.E., and Reichhardt, K.L., 1981, 

Vegetation of Organ Pipe Cactus National Monument: Tucson, University of Arizona, 

Cooperative National Park Resources Studies Unit, Technical Report No. 8, 80 p. (Available 

online from http://sdrsnet.srnr.arizona.edu/data/techreports/TECHRPT08.pdf.) 

Warren, P.L., and Laurenzi, A.W., 1987, Rare Plant Survey of the Yuma District. Unpublished 

report prepared for U.S. Bureau of Land Management, Yuma, Arizona by The Nature 

Conservancy of Arizona, Tucson, 61 p. 

Webb, N.P., and McGowan, H.A., 2009, Approaches to modeling land erodibility by wind: 

Progress in Physical Geography, v. 33, p. 587–613. 

Webb, R.H., 2002, Recovery of severely compacted soils in the Mojave Desert, California, USA: 

Arid Land Research and Management, v.16, no. 3, p. 291–305. 

Webb, R.H., Belnap, J., and Thomas, K.A., 2009, Natural recovery from severe disturbance in 

the Mojave Desert, in Webb, R.H., Fenstermaker, L.F., Heaton, J.S., Hughson, D.L., 

McDonald, E.V., and Miller, D.M., eds., The Mojave Desert; ecosystem processes and 

sustainability: Reno, University of Nevada Press, p. 343–377. 

Wells, W.G., and Wohlgemuth, P.M., 1987, Sediment traps for measuring onslope surface 

sediment movement: Berkeley, Calif., U.S. Department of Agriculture, Forest Service, Pacific 

Southwest Forest and Range Experiment Station, Research Note PSW-393, 6 p. 

Wiberg, P.L., and Smith, J.D., 1989, Model for calculating bedload transport of sediment: 

Journal of Hydraulic Engineering, v. 115, no. 1, p. 101–123. 

Williams, B. K., Nichols, J. D., and Conroy, M.J., 2002, Analysis and management of animal 

populations: San Diego, CA, Academic Press.

Williams, B. K., Szaro, R. C., and Shapiro, C.D., 2009, Adaptive Management: The U.S. 

Department of the Interior Technical Guide. Adaptive Management Working Group, U.S. 

Department of the Interior, Washington, DC, 86 p. 

Wilson, D.E., Cole, F.R., Nichols, J.D., Rudran, R., and Foster, M.S., 1996, Measuring and 

monitoring biological diversity; standard methods for mammals: Washington, D.C. and 

London, Smithsonian Institution Press, 406 p. 

World Meteorological Organization, 1983, Guide to Meteorological Instruments and

 Methods of Observation: No. 8, 5th edition, Geneva Switzerland. 

Yuma Proving Ground, Environmental Sciences Division, 2010, Environmental assessment 

impact areas expansion. 

http://www.yuma.army.mil/docs/IAExpansion_EA_Draft_FONSI_25Mar10.pdf. 

Zobeck, T.M., Parker, N. C., Haskell, S., and Guoding, K., 2000, Scaling up from field to region 

for wind erosion prediction using a field-scale wind erosion model and GIS: Agriculture, 

Ecosystems & Environment, v. 82, p. 247–259 
71

Appendix A. Vegetation Inventory and Mapping Protocol 

Vegetation field sampling and mapping follow the protocols established for the CPNWR 

and the BMGR–East. The CPNWR protocol is described in a report titled “Vegetation of the 

Cabeza Prieta National Wildlife Refuge, Arizona” (Malusa, 2003), and the BMGR–East protocol 

is described in a report titled “Vegetation of the North and South Tactical Ranges, Luke Air 

Force Base, Barry M. Goldwater Range, Arizona” (University of Arizona Office of Arid Lands, 

2006). The following is a summary of the two protocols. 

Each vegetation sampling site is designated by the first letters of the 7.5-minute quad 

sheet name and numbered sequentially (for example, the first sample from the Raven Butte quad 

would be RB-1). For each sample, record the (a) GPS location (Universal Transverse Mercator, 

WGS 1984), (b) environment description, and (c) vegetation description of perennial species. 

The vegetation description includes the mean height (n=10) of common species estimated to the 

nearest 10 cm and tree heights estimated to the nearest 0.5 m. Classification of percent plant 

covers is summarized in table A.1. In addition, the perennial species with more than 1-percent 

cover are estimated using the “diameter” method (Malusa, 2003), similar to “nearest neighbor” 

estimates.

Table A.1. Percent cover system for vegetation mapping.

Class Percent cover

0 unknown

1 <1%

2 1-4%

3 5-9%

4 10-14%

5 15-25%

6 26-40%

7 41-60%

8 61-80%

9 81-100%

 

All data are entered into the database initiated by Malusa (2003) and currently (2011) 

available at http://sdrsnet.srnr.arizona.edu/index.php?page=datamenu&lib=2&sublib=16.

Representative photographs of perennial vegetation are taken at each sampling site, along 

with the GPS coordinates and photograph azimuth (compass heading). The photographs are 

stored with file names indexed to the sample site.

Vegetation types are classified to the association level where stand delineation is based 

on floristic, physiognomic, and habitat homogeneity. The classification includes a hierarchical 

delineation of vegetative physiognomic classes within the attributes of each feature class 

polygon. The project uses a standard 1:24,000-scale USGS topographic quadrangle with a 

minimum mapping unit of 1.0 hectare. Each stand is designated as a polygon feature in a GIS 
72

feature class. Stands less than 1.0 hectare are mapped as point or linear features when deemed 

biologically significant.

The boundaries between vegetation stands are identified using a combination of photointerpretation and field observations. GPS routes traveled during the study are recorded as a 

separate layer in the GIS database. The field crew also maps the locations of invasive plant 

species when possible. 
73

Appendix B. Invasive Species Monitoring Protocol

Invasive Plant Mapping and Monitoring

Comprehensive census-style surveys are not practical on the BMGR–West because it is 

so large. Instead, the I&M plan targets areas considered to be common pathways for the spread 

of invasive plant species. Limiting the search to road, trail, and wash corridors allows managers 

to cover a considerably larger portion of the range and design a survey that can be reasonably 

and efficiently repeated over time. In addition to these usually linear pathways, disturbed areas—

for example, sites of military operations, fire, undocumented alien (UDA) routes), or areas of 

high management value (for example, xeroriparian, dune habitat, and pronghorn habitat)—may 

also be considered for monitoring. The extent to which these can be included depends on 

available resources, access issues, and BMGR–West management priorities. However, it is 

suggested that monitoring of heavily impacted, newly disturbed areas be considered if only for 

an initial survey and one followup survey. 

Surveys along roads can be conducted by vehicle, provided the surveyor has sufficient 

knowledge and experience to recognize target species from a short distance away. Depending on 

the type and size of trail corridors, trails could be surveyed by foot, on horseback, or with any 

motorized vehicle able to navigate the terrain. Washes may prove to be such extensive (long) 

pathways with access difficulties that it is not feasible to cover them in their entirety. Instead, it 

is suggested that surveys be conducted for a specified distance at locations where the wash 

crosses a road or trail, thus providing access to the area. The distance surveyed at each wash/road 

intersection can be determined by time and personnel constraints, but a minimum of 20 m in 

either direction is suggested. 

Mapping can occur opportunistically, or a more rigorous sampling scheme can be 

implemented. The exact length of “transects” in opportunistic maps would vary from time to 

time, as would the distance of the survey extent from the pathway edge. The intended monitoring 

area in precise mapping can be subdivided into equal-length blocks with a predetermined width 

and assigned a unique identifier. Each block is then assessed for invasive species, and those 

found are described as they occur within each block. While this method requires more field effort 

and spatial data management, recording presence/absence by block allows reporting of 

infestations as a percent cover or frequency by species across all blocks sampled. If the proposed 

area to be monitored is too large to complete in a season, the area can be divided in a manner so 

that each area identified can be surveyed within the time allotted (season, year, or other). This 

allows managers to evaluate the data with statistical methods. 

Field Methods

It is suggested that the data collected at least satisfy the minimum requirements proposed 

by the North American Weed Management Association (2002). Essential fields include:

• species name (scientific name is preferred)

• location in UTM coordinates or latitude and longitude 

• extent, mapped polygon 

• density (within polygon), using Daubenmire cover classes (Daubenmire, 1959): 

• <1%, 2–5%, 6–25%, 26-50%, 51–75%, 76–95%, and 96–100%. 

• observation date and observer name. 
74

Additional metadata do not take much extra effort to collect and provide useful ancillary 

information. These may include aspect, topographic position, soil type, and distance to 

roads/trails. An example of a field data sheet is given at the end of this appendix. If used, 

electronic data-collection devices can be loaded with predefined templates to ensure that proper 

data standards are met. 

Before the field season: 

• Ensure that all observers are properly trained in identifying all target species in each of their 

different life stages. Note: Eradication treatment of species before the setting of seeds is 

preferable. Thus, including life stage as a data field may help prioritize management actions. 

We suggest using SODN’s “Field Identification cards for invasive non-native species known 

to threaten AZ wildlands,” as a field resource

(http://www.southwestlearning.org/sites/default/files/products/ID_Cards_Glossary_Info.pdf). 

• Purchase GPS or hand-held mapping devices equipped with mapping software. 

• Develop appropriate data sheets or electronic data entry forms. 

• Identify areas to be surveyed; prepare maps and schedules. 

• Write detailed standard operating procedures for how to collect data and rules for 

contingency sampling. 

Surveys: 

• Record the survey start date and the total area surveyed for invasive plants. Include a notation 

if the surveyor was unable to complete the survey to the standard requirements. This allows 

managers to schedule followup efforts. 

• Along each pathway (or pathway unit) identified, collect point or polygon data on each target 

species encountered. Points are collected when the infestation is a single plant or a patch of 

plants less than 5 m across—5 m is currently (2011) the average accuracy of hand-held GPS 

devices. Points are recorded at the midpoint of the patch. Use notes or cover class fields to 

describe the patch density or number of plants. 

• Polygons are used to describe patches greater than 5 m across. The observer walks around the 

outer limits of the patch with a GPS. Polygon data fields are identical to point features. It is 

possible to record multiple species per polygon and later split these polygons by species. The 

template includes repeat fields for species name and cover class. 

• Multiple species are only recorded within the same polygon if the distribution of those 

species is a close match. This is often the case with delineated areas (for example, roadsides, 

old fields, or disturbed areas). 

• Single plants seen within a patch of another exotic species (mapped as a polygon) are 

recorded as separate points. 

• Assign only one species per point even if different species are present. This simplifies later 

data management. 

• Use common sense to determine whether exact locations (points) are used (for example, a 

species that is highly invasive and requires management) or whether a rough polygon is 

sufficient to describe the total area affected (which may lower the estimated cover class). 

Specific management objectives are considered, as well as efficiencies of time and available 

funding. 
75

Data Management

It is suggested that each dataset be identified by the date of observation and the species 

observed and that the names of polygon files reflect attributes collected, either as one file that 

contains many species (for example, BMGR-W_20100422_exotics) or as multiple files that 

represent individual species locations (for example, BMGR-W_20100422_SIIR, BMGRW_2010_BRTO). Regardless of the method used, it is suggested that standards for file naming 

and data management be established and organized so that the observation date and species name 

are foremost in the data-management structure. 

If management actions are implemented to treat invasive species, it is suggested that the 

geodatabase or attribute table of each species recorded be modified to reflect the treatment type 

and date of treatment. For ongoing and multiple treatment efforts, a geodatabase structure is 

ideal. This would facilitate ongoing updates and evaluation of treatment effects. 

If photos have been included in data collection, it is suggested these be named to reflect 

the species identified, the date of observation, and the area in which the species was seen (for 

example, BMGR-W_PECI_20100103_Zone1a.jpeg). Naming conventions are flexible, but it is 

suggested that they be standardized and contain all relevant information for identification.
76

Invasive Species Monitoring

Field Data Sheet: 

Protocol version : 1.00 Datasheet Version: 1.00

Proofread by: __________________

Copied by: __________________

Entered by: __________________

Verified by: __________________

Transect Area/Number Code: - - 

 

Example: Barry M. Goldwater Range West-Tinajas Altas-Site #3 (BMGRW-TA-03) 

Recorder(s): 

Date: 

Species: 

Point ID and UTM: , E, , , N (UTM, NAD 83, Zone 11 N) 

Polygon ID and UTM: , E, , , N 

Estimated Polygon Extent: GIS Verified Polygon Extent (computed in lab): 

Cover Class within Polygon: (<1%, 2-5%, 6-25%, 26-50%, 50-75%, 76-95% and 96-100%.)

Photograph File Name(s) 

Additional Information

Human 

disturbance: Y/N

Roads: Y/N Trails: Y/N Natural Vegetation Type

 

Notes and Sketches (continue on back): 

 
77

Appendix C. Soil Inventory and Erosion Monitoring Protocol

Soil Map

Because BMGR–West is a large, remote area with access constraints, conventional fieldbased soil survey methods would be difficult to implement. However, there are a large number of 

new methods that utilize digital mapping technologies and computer modeling algorithms to 

optimize the limited field data that could be realistically collected in the BMGR–West. These 

technologies use remotely sensed spectral data (for example, satellite imagery) and digital 

elevation models (DEM) as well as other spatial data available in geographic information 

systems (GIS) format to interpolate soil type across large areas from limited field observations 

through specialized sampling schemes (Lagacherie and McBratney, 2007; McBratney and others, 

2006; McBratney and others, 2003; Odeh and others, 2007; Scull and others, 2005; Scull and 

others, 2003). 

In 2009, Nauman Geospatial used a digital mapping approach to develop a predictive soil 

map of the entire BMGR using data from adjacent soil maps and GIS datasets to create a 

predictive extrapolation of soil types into the range (fig. 3.2). Datasets and the predictive map 

from that project could be utilized for BMGR–West mapping. The predictive map would enable 

creation of an optimized statistical sampling design to check the Nauman Geospatial pre-map 

classification accuracy or, if necessary, a new model could be created using the GIS dataset 

(satellite imagery and DEM). With validation and some correction, the original predictive map 

might serve as a suitable final soil survey. Nauman Geospatial has also been in contact with Phil 

Camp, Arizona State Soil Scientist with the Natural Resources Conservation Service (NRCS), 

and has oral agreement that any final soil map project can be reviewed by the NRCS for 

inclusion into the national Soil Service Geographic (SSURGO) database.

(http://soils.usda.gov/survey/geography/ssurgo/) dataset. The final products from these survey 

efforts would be 30-m-pixel raster soil class and property maps, as well as an aggregated 

1:24,000 polygon soil class map that would serve as the SSURGO product. 

Field work for validation and/or modeling would require at least 30 full soil profile 

descriptions backed by laboratory data supported by at least another 30 field descriptions. Thirty 

profile and field samples would ensure at least one soil profile per map unit and provide enough 

degrees of freedom in model validation statistics. Obtaining full descriptions would involve 

digging pits or taking auger samples to a depth of about 150 cm or bedrock, if it is shallower than 

that depth. Soil horizons can be described by standard methods and sampled for further 

laboratory work with methods comparable to National Soil Survey standards (U.S. Department 

of Agriculture, Natural Resources Conservation Service, 2004). It is suggested that handtexturing (David, 1999) and other field soil description methods (Schoeneberger, 2002) be used 

to describe soils without full laboratory work to help fill in spatial gaps between full description 

sites without the full cost of laboratory work. 

Erosion Potential Maps

Water Erosion.—Digital erosion-potential modeling techniques can be used in GIS to 

help elucidate areas where water erosion issues are likely to occur. One of the more flexible 

erosion potential model approaches, the Unit Stream Power-based Erosion and Deposition, or 

USPED (Mitasova and Mitas, 1999) method, can be used to create an erosion-yield or erosion-
78

potential index using a variety of data sources. Base data needed to do this include a DEM, 

Normalized Difference Vegetation Index (NDVI) or other vegetation cover parameter source 

data, and digital soil survey data. 

 USPED modifies the Revised Universal Soil Loss Equation, or RUSLE (Renard and 

others, 1997), to include two-dimensional topographical flow patterns. Soil erodibilities can be 

calculated from SSURGO equivalent or better soil survey data. Slope factors can be calculated 

according to the USPED model after filling sinks in a DEM and using Tarboton’s (1997) 

“Deterministic Infinity” flow routing routine for flow accumulation to replace the slope-length 

erosion factor. For vegetation cover, a gridded Cover-Management Factor raster can be 

calculated from Landsat NDVI following Kouli and others, (2009). The final map from USPED 

can take several forms, depending on how much of the RUSLE equation is modeled. As outlined, 

an index is created that indicates where erosion or deposition in a system is likely to occur. 

Wind Erosion.—Wind erosion potential can be modeled in GIS similarly to water erosion 

modeling. The Wind Erosion Equation (WEQ; U.S. Department of Agriculture, Natural 

Resources Conservation Service, 2002) and Revised Wind Equation (RWEQ; Fryrear and others, 

2001) can be used as a framework to create a wind erosion index. Factors in these equations can 

be represented in a GIS and combined in an empirical form to create a relative prediction of wind 

erosion susceptibility. Imagery, soil survey data, and topographic data in a GIS will be used to 

represent the different equation factors required to generate a wind erosion potential map 

(Zobeck and others, 2000; Leys and others, 2001; Klik, 2000; Guo-ping and others, 2001). 

Soil particle size data from the soil inventory, satellite imagery, and digital elevation 

models would be used in a GIS to create proxy variables for use in a wind erosion equation 

index. Raster layers representing all these variables would be plugged into either the wind 

erosion equation or into a process-based model depending on data availability (Leys and others, 

2001; Zobeck and others, 2000; Webb and McGowan, 2009). NDVI would be used to represent 

the vegetation cover factor (Leys and others, 2001; Jabbar and others; 2006), and a topographical 

wetness index (Moore and others, 1993) would be used to highlight areas that hold soil moisture 

for greater periods of the year. A neighborhood terrain analysis used to model proximity to 

sheltered parts of mountains and hills would be created using a DEM to help determine local 

wind breaks. Imagery would be used to help identify other structures or vegetation that might 

help slow wind as well. These topographical data along with any barriers delineated from 

imagery would be used to calculate unsheltered wind distances for use in modeling (Klik, 2000). 

Climate data would be approximated from local climate stations and interpolated to the best 

extent possible. Results would yield predicted wind erosion rates that can be used at least as a 

relative index of wind erosion potential on a pixel-by-pixel basis (most likely 30-m pixels). 

Hillslope Erosion Monitoring at Uplands Soil and Vegetation Plots

The NPS-based protocol for soil-vegetation plots (Hubbard and others, 2009) proposed 

for the BMGR–West (Section 3.1.3) offers a unique opportunity to also measure co-located 

erosion rates. These data would prove valuable in the greater ecological context of vegetation 

and soil parameters collected at those sites. Since these plots would also have a greater statistical 

spatial inference, erosion parameters can be applied to that greater inference. Based on resources 

available, it is suggested that quantitative erosion rate data are collected at all vegetation plots or 

as large of a subset as possible. If a subset is selected, quantitative methods could be randomly 

applied to plots to maintain statistical inference with a greater weight placed on plots in areas 

with higher predicted erosion potential, or with field-observed erosion features. 
79

The NPS SODN protocol (Hubbard and others, 2009) includes some qualitative field 

observations to identify the presence of any signs of water erosion (features) at vegetation-soil 

plots. However, these data are only an estimate of rough percentage classes of commonly found 

water-erosion-related features (that is, sheeting, rills, gullies, pedestals, burrowing, terracettes, 

and tunneling). Lacking from the NPS SODN protocol are wind erosion features, including 

desert lag or pavement, blowout depressions or swales, dune or microdune drifts, or other wind 

erosion features. However, all these erosion-feature observations that are available to field 

scientist only offer information on the presence and rough trends of erosion processes and not a 

quantitative measure of erosion rates.

Of greater value would be more direct measures of actual erosion rates. Base-level pin 

surveys and sediment traps are the most common methods for erosion-rate monitoring. At the 

very least, it is suggested that rills, gullies, and obvious areas of sheet erosion be surveyed to 

estimate soil loss volumes. More effective would be implementation of sediment traps at plots, or 

at least a subset of plots, to the extent resources permit.

Erosion Feature Survey

Cross-section profiles along with areal-extent estimates of rills, gullies, and sheet erosion 

areas would provide a measure of the volume of soil lost in plots. This would involve a focus on 

measuring dimensions of active erosion features, which can be tedious and destructive to soil 

resources, if an area is highly eroded and exhibits many features. To keep survey measurements 

simple, a single measurement of approximate depth and width would be taken at every 2-m 

length of any of these erosion features. The measurements would be integrated into volume 

calculations to give an estimate of soil loss (Bewket and Sterk, 2003; Rejman and Brodowski, 

2005). Because it would not be known how long the feature has been forming, repeat 

measurements are needed to yield erosion rates. To begin incorporating more subtle measures of 

soil loss and wind erosion, it is suggested that wind-erosion features also be surveyed along with 

some randomly placed rebar or other surface elevation references for repeat base level 

measurements. All rills and rebar used would be diagrammed by analysts for reference during 

future measurements. The field crew may decide to not make measurements, if an area is 

unstable and performing the survey would cause further damage. 

Sediment Traps

To get a more integrated idea of sediment movement in plots, small hillslope sediment 

traps would be monitored as well at selected sites. Simple field models for water erosion (Wells 

and Wohlgemuth, 1987) and wind erosion sediment traps (Fryrear, 1986; Leys and others, 2001) 

would be used in different arrangements. The water-sediment traps to be used are welded sheetmetal boxes with an apron for mounting on the slope surface. Dimensions are 30 by 10 cm in 

aperture with a 15-cm depth (Wells and Wohlgemuth, 1987). Design dimensions may be 

adjusted for field conditions if this proves too big or small for observed sediment collections. 

The advantage of these traps is the simple design, construction, and installation that allows for 

flexibility and low costs for the amount of data. 

Data collected are recorded in units of mass per slope width. The sampling design allows 

statistical inference across the slope contour at the bottom of the plot to get an average (with 

error estimates) soil mass lost per unit slope width. From this, the bulk density of soil samples 

taken in the plot can be used to convert that measurement to a volumetric soil loss per unit width. 

Terrain analysis of a local DEM would be used to get an estimate of upslope flow-contributing 
80

area (Tarboton, 1997) to the plot to get an estimate of the area contributing sediment loss to the 

slope contour across the bottom of the plot. From this area a volumetric soil loss per area can be 

calculated. High-accuracy GPS points of the plot corners would be used in a GIS to direct the 

terrain analysis. 

Plots selected for erosion-rate monitoring would be set with at least three water-sediment 

traps along the downslope boundary, with placement based on random distance selections. 

Additional traps would be set at any rills or gully outlets at the downhill line of the plot. A 1-m 

buffer on each side of plot vegetation transects would be excluded from possible water-sediment 

traps because of monitoring team disturbance at those locations. Larger gullies may require a 

custom larger trap or another specialized trap design used for small watershed outlets 

(Robichaud and others, 2008; Robichaud and Brown, 2003). 

To measure wind erosion rates, three modern Fryrear field dust-sampler traps would be 

randomly placed in subplot areas, excluding a 1-m buffer on each side of the vegetation 

transects. These samplers consist of small triangular prism sheet-metal samplers mounted on a 

small tower. These traps collect windborne sediments mainly from local saltation and have been 

used for extensive monitoring over multiple-year time periods (Miles and McTainsh, 1994). 

After initial plot assessment and a period of monitoring, plots with higher wind erosion may 

require additional instrumentation to better assess sediment emission. Fryrear traps do not 

efficiently sample particles smaller than 40 microns, nor can they distinguish between point 

emission and particles carried by saltation from a distance. If plots are identified for more 

investigation, high-volume air samplers based on the 10-m tower design of Nickling and Gillies 

(1993) would be used to fully characterize plot wind-sediment emissions. 

Sampling Intervals and Reporting

For all sediment-trap sampling described above, it is suggested that initial sampling be 

done at least biannually. Traps collect sediment and thus need to be emptied at each 

measurement. If the traps completely fill up, sediment will overflow or build up behind traps, 

introducing error into the measurement. Therefore, it is suggested that initially the sampling 

interval be relatively short until analysts know how often emptying of the traps is necessary. It is 

also suggested that local climate stations and storms be monitored because large precipitation 

events may accelerate trap filling. Climate data are also valuable for analysis of the erosion data, 

and, to the extent possible, coordination of climate and erosion monitoring sites would be 

valuable.

 The best way to measure sediment caught in traps is to bring a portable battery-powered 

scale and measure the entire sample mass in the field. Following the field measurement, a 

subsample can be put into a sealed container to take back and dry in a laboratory, so that the 

mass can be corrected for soil moisture content. The other option is to remove all trapped 

sediment from the field for mass measurement in a laboratory. It is suggested that the method for 

measuring sediment be considered in monitoring plan logistics, as some of these methods would 

be difficult to implement in poorly accessible areas. Accessibility may need to be considered as 

part of sample weighing, as was done by Hubbard and others (2009). 

It is suggested that erosion-feature surveys be done at the same frequency as vegetation 

plot evaluations. Plot and sediment-trap data would be integrated for each year, with a focus on 

trends and identifying areas of extreme erosion or degradation that might require management 

actions.
81

Reporting would be done on an annual basis for all sites with sediment collection traps. 

Data from each site would be tabulated and summarized, and trends and spatial patterns observed 

in different areas and watersheds at BMGR–West would be discussed.
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83

Appendix D. Small Mammals and Nocturnal Rodents Monitoring Protocol

1. Live Traps and Materials

We suggest the Sherman long (7.6 × 9.5 × 30.5 cm, model XLK) or extra large (10.2 × 

11.4 × 38 cm, model XLF15) traps for relatively level conditions and small (7.6 × 8.9 × 22.9 cm, 

model LFA) traps for rocky areas (http://www.shermantraps.com/). Forty-nine traps are required 

for a 7 × 7 monitoring grid. For additional monitoring equipment see table D.1.

2. Procedures for Grid and Trap Setup

Establish a grid of 7 × 7 Sherman traps spaced at 15-m intervals (90 × 90-m total grid 

area). After identifying and navigating to the locations for live trap grids, place rebar stakes at 

the grid corners. It is suggested that the grid be laid using a 100-m tape to follow site topography, 

with transects running upslope and cross transects running along the contours. 

Trapping during weather extremes increases metabolic stress on animals, increasing their 

risk of mortality, and it is suggested that traps always be checked first thing in the morning 

before temperatures begin to rise to extreme levels. Traps are covered with corrugated plastic 

shade covers of a light color to regulate temperatures within traps and to reduce maximum 

temperatures that might harm captured animals. Polyester batting (for example, DacronTM) is 

placed in traps (~2-in. diameter ball at back of trap) to provide warmth in locations where 

temperatures are likely to drop near or below freezing. 

Sherman traps are baited with a mixture of rolled oats and mixed bird seed containing 

sunflower seeds and millet. Mix one gallon of rolled oats to one gallon of mixed bird seed. It is 

important to use consistent types of bait and percentages of each type over time. To properly 

place bait in a Sherman trap, sprinkle a small handful of oats and seed on the front and inside the 

back of the trap. It is suggested that traps be baited around dusk. 

3. Data Collection, Handling and Weighing Mammals 

Morning trap checks are completed first thing in the morning before temperatures rise 

and potentially stress the trapped animal. Each day, record the status of each trap (“OK” or 

“closed” and “bait missing,” “bait OK,” or “capture”). Traps are closed after checking them in 

the morning and reset each evening. This design will result in 98 trap nights (2 nights × 49 traps) 

per grid. 

To remove a trapped mammal, place a zip-lock or cloth bag over the opening of the trap 

and tilt the trap so that the opening is upward until the mammal crawls up and out into the bag. 

Twist the end of the bag, and using a scale, weigh the bag and the sample. Weigh the bag before 

inserting anything into the bag. This will ensure a proper weight, in case dirt, excrement, or 

foreign materials are introduced to the bag. Captured animals are identified to species, sex, age 

(as juveniles, subadults or adults), examined for breeding status (for example, pregnant, 

lactating, enlarged testes, or nonbreeding), marked with a black permanent marker on the 

animal’s ventral surface, weighed, and released (no markings are necessary on the second 

morning). 
84

Field data sheet:

Trapping Session (1 or 2) 

Date 

Plot (11, 12, E3, E4, 8, 14) 

Trap Station (letter and number)

Time

Species

Weight (in grams) 

Sex (determined by size of genitals and their distance from anus, and 

presence of mammary glands)

Age Class (Based on pelage color; divide into juveniles, sub-adults, and 

 adults)

Reproductive Condition (Females: 0 = non-breeding no swelling, 1 = 

 Genitals slightly swollen, 2 = Pronounced swelling in genitals). 

Also record whether female is lactating (mammary glands not 

 swollen = 0, slightly swollen = 1, swollen = 2) (Males: 0 = nonbreeding, 1 = testes slightly descended, 2 = testes fully descended).

Capture Code

 C = Trap Closed, nothing in it. 

N = New Capture (record this if animal has no mark from previous 

trap day) 

R = Recapture (if animal already has an ear tag). 

Measurements (Measure body and tail sizes in mm while the animal is in the bag)

 Tail length

 Body length 

 Right Hind Foot 

 Right Ear 

Weather (see bat protocol)

Notes (Anything important not listed above, general observations, 

 and other information) 

It is suggested that all traps be cleaned and disinfected after two days of sampling. Empty 

traps of all bait, organic material, and polyester batting and place the traps into a mild 

bleach/water (Centers for Disease Control recommends 3 Tablespoons/1 gal) solution or 5-

percent Lysol solution for approximately 10 minutes. 
85

Table D.1. Small mammals and nocturnal rodents monitoring equipment list.

Item Number Remarks

Latex or vinyl gloves 10 To handle animals

Plastic zip lock bags and cloth bags Pillow cases will work for bags

Pesola Weight scales 3 60 g, 100 g, and a 300-g scale

Bag of oats and sterile bird seed 1

Data sheets and mechanical pencils Many

Sharpie (for marking captured animals) 5

Small and large ruler 2 For measuring body length

Polyester batting 49 One for each trap

Cut corrugated plastic 49 One for each trap

Compass 1

100-m tapes 3

Soap, water, and hand sanitizer 1 container of each
86

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87

Appendix E. Bat Guild Monitoring Protocol 

1. Procedures for Mist Netting

It is suggested that nets be in place at sunset and that monitoring occur from sunset to 4.5 

hours after sunset. To minimize the capture of any birds, keep the nets closed until just before 

dark. Usually, it is obvious when birds such as doves, thrashers, swallows, and others stop flying 

for the evening. 

Nets are set across the middle of small pools, if at all practical. For larger pools, a net is 

set up at the lip of one edge of the pool. 

It is much easier to set up nets with two people. One person can hold the pole and net, 

while the other places the panel end-loops over the pole and anchors the pole with cord. The cord 

may be tied to any nearby object stout enough to hold both the pole and net or tied to stakes 

driven into the ground for that purpose. See table E.1 for the monitoring equipment list. 

When anchoring the poles that hold the net, it is suggested that the top three panel endloops be placed above the anchor cord and the bottom two loops below the anchor cord. 

Occasionally, the terrain may warrant more net area below the anchor cord (such as across a 

small ravine, where the poles are on slopes). Under these conditions, three panel end-loops are 

placed below the anchor cord.

It is suggested that the net be spread taut enough so that a 2.5-cm (1-in.) bag droop occurs 

in each of the panels. The net itself is stretched tight. As the evening progresses, the rise in 

humidity will cause the net to droop, so periodic adjustments are made to keep the net taut. 

It is suggested that the nets be placed less than 30.5 m (100 ft) apart. Any greater distance 

makes it cumbersome to check nets, and time is lost traveling between them.

Nets are checked every 5 min., because bats are capable of swiftly chewing holes in nets. 

If the nets are left unattended, they may become riddled with holes in a short time. 

Nets are maintained until midnight, at which time they are closed. Much of the bat 

activity at water sources occurs in the first half of the night. Maintaining nets until midnight 

provides an adequate representation of bat use. 

To close a net, push all the panel end-loops together at the anchor cord on the pole. Take 

a 30.5-cm (12-in.) piece of plastic flagging and tie the end-loops together at each end of the net, 

using a single knot, but do not include the anchor cord. One end of the net can then be taken off 

the pole and folded toward the other end. When the net is completely folded, place the tied endloops together and stuff the net into a bag for safe keeping. 

For best netting results, it is advisable to consider the following: 

1. Sample water sources at different locations; however, whether the water source is small, 

large, in the open, secluded, or so forth, it is suggested that the same water source be 

monitored from year to year. 

2. Monitor the sites during the latter part of May or in June. This is the driest time of the year 

with the chance of storms almost nonexistent. In May and June it is warm enough for insects 

to be active, and therefore bats should be active as well. Also, because the number of 

available water sources is limited at this time of year, bats are usually more concentrated.

3. Net during moonless nights. Bats possess good eyesight and they are capable of seeing a 

moonlit net.
88

2. Capturing and Handling Bats

Capture and handling of bats requires full concentration and attention. Bats can chew 

holes in the net if left unattended for any length of time, and they can easily become entangled. 

In the intervals between checking the nets, bat extraction, and data collection, flashlights are off 

and talking is kept to a minimum. This helps both to maintain concentration and to avoid scaring 

off the bats. 

When a bat is caught in the net, quickly move to extract it before it can escape or become 

further entangled. Determine from which side of the net the bat entered. Immobilize the bat with 

a gloved hand (or give the bat a gloved finger to chew on for distraction) and carefully remove 

the net strands from head, body, and wings. Be especially careful with the fragile wing 

membrane and bones. 

Place the bat in a cloth bag if it cannot be processed right away.

For best sampling results, it is advisable to consider the following: Do not mark the bats. 

It can safely be assumed that each bat captured in a net during any given night will not be 

recaptured in that same net during that same night. Past experience with hundreds of marked bats 

has proven that only a fraction of a percent are ever recaptured the same night. Nonetheless, if 

there is a desire to mark bats in order to periodically check the probability of recaptures during 

the same night, a spot of “white-out” applied to the back of the bat’s head works well as a 

temporary mark. The “white-out” is nontoxic and wears off after several days.

3. Data Collection and Measurements

All data are entered into the database after completion of monitoring. Therefore, a data 

sheet must be completed for each trapping event at each location. The sample data sheet may be 

modified; however, certain information is necessary to ensure that critical data are collected.

Example of field data sheet information:

1. Location. This is the name of the water source or flyway. Include drainage, wash, or canyon

name, GPS coordinates, and elevation. 

2. Date. Indicate the day, month, and year that netting occurred. 

3. Weather conditions: 

a. Daily maximum and minimum air temperatures in °C, measured 2 m above ground, is 

standard

b. Air termperatures in °C at the start of data collection (when nets are opened) and at the 

end of data collection (when nets are closed) 

c. Cloud cover: 0-25%, 26-50%, 51-75%, or ≥76%

d. Precipitation in last 24 hours: Yes or No, with comments. 

e. Wind speed and direction: Use anemometers, in Beaufort scale.

f. Relative humidity: Use sling psychrometer or hand-held thermohygrometer (%). 

g. Barometric pressure: Use hand-held or automatic barometer (in HG). 

h. Time of sunset: From nearest newspaper, with field check, including time zone. 

4. Moon. Indicate the phase of the moon, duration of moon shine while netting, and when 

moonrise or moonset occurred. 

5. Time. Record the capture time for each bat in the net. Occasionally, the capture time may be 

approximated when several bats are being removed from the net at the same time. 

6. Species. Record the species of each bat captured. To speed up the process, a four-letter 

acronym using the first two letters of the genus and species may be used, for example, PIHE, 

MYCA, and others (see table E.2 for species codes).
89

7. Sex. Use the symbols ♂ for male and ♀ for female

8. Forearm. Record forearm length (right or left, length is undifferentiated). Record the 

measurement in millimeters; however, do not include a “mm” suffix—this measurement is 

understood to be in millimeters. Not all bats need to be measured; only those for which this 

measurement may aid in identification. Those species for which forearm measurement may 

be helpful in identification are members of the genera Myotis, Eumops, and Nyctinomops. 

9. Ear. Record ear length (right or left, length is undifferentiated). Record the measurement in 

millimeters. However, do not include a “mm” suffix—this measurement is understood to be 

in millimeters. Not all bats need to be measured; only with some Myotis is ear size helpful in 

identification. 

10. Weight. If possible, it is suggested that each bat be weighed. The bat may be placed in a 

plastic zip-lock storage bag and weighed on a scale (a Pesola scale suggested). Be certain to 

deduct the weight of the bag from the total weight when determining the weight of the bat. 

The use of a 50-g (1.75-oz) capacity scale would be preferred for all species except for 

members of the genus Eumops, which may require the use of a 100-g (3.5-oz) capacity scale. 

The brief span of confinement in the storage bag during weighing is not detrimental to the 

bat.

11. Individual notes. Indicate breeding status (for females: pregnant, lactating, postlactating, 

nonparous; for males: testes descended [TD]); whether adult or juvenile; presence of 

ectoparasites; any anatomical damage (for example, hole in wing and so forth) for individual 

samples.

12. Time net opened/time net closed. Record the time when the net was opened as well as when 

it was closed.

13. Collective notes. Record comments and other remarks regarding overall observations. 

4. Procedures for Roost Monitoring 

It is important for observers to be thoroughly familiar with the operation of monitoring 

instruments (binoculars, night vision scopes, video cameras, ultrasonic detectors, and others) and 

understand their detection limits. 

Monitoring Techniques: Nightly emergence counts made as bats depart from day roosts 

(caves, mines, buildings, tree cavities) are an effective way to estimate the number of bats 

without disturbing them. Counts are made at predetermined intervals in order to assess 

intracolony variation in numbers of bats present and/or to determine seasonal variation. In warm 

weather, it is suggested that roosts be monitored beginning at sunset, until 2.5 hours after sunset. 

Nightly emergence counts are most effective when departing bats are silhouetted against a clear 

sky, and there are several observers occupying different vantage points. The following 

measurements are made at each roost (per data sheet):

1. Site name and coordinates 

2. Names of observers 

3. Date. Indicate the day, month, and year that roost monitoring occurred. 

4. Times of: sunset; beginning and ending times of survey; first bat sighted in area; first bat 

exiting roost; greatest emergence (usually a range of time)

5. Number of entrances observed; number of entrances suspected.

6. Observation technique: Ambient light; red light; night vision; and others 
90

7. Bat detector use; Frequency setting; and other information 

8. Number of bats: visually counted; passed on detector; estimated from emergence duration; 

and other information 

Table E.1. Bat guild monitoring equipment list.

Technique 

Item

 

Mist net Roost Comments

X Mist nets 18, 30, 60 and 120 ft (two 60-ft nets tied together). 

X Poles

Two 5-ft segments joined by a sleeve are needed at each end of the 

net. 

X Anchor cord for poles

X Tent Stakes

X Millimeter ruler Flexible plastic, 150 mm (6 in.) is sufficient. 

X Scales (2) 100 g (3.5 oz) (Pesola suggested).

X Zip-lock storage bags

For containing bats while weighing. Quart capacity will suffice for 

most bats.

X Cloth bags

For holding bats after removing from net. Should have string or 

cloth ties.

X X Headlamp Extra batteries and red filters

X 

Light gathering 

binoculars

X Night vision goggles

X Bat detector

X White sheet For backdrop

X X Leather gloves Lightweight, deerskin preferred

X X Watch To note the time of capture

X X Clipboard For holding data forms

X X Data forms

X X White-out For marking bats

X X Pencils

X X Reference Books Hoffmeister, 1986; Hall, 1981

X X Digital Camera Camera with flash

X X Sling psychrometer

X X Thermometer

X X Barometer

X X Anemometer
91

Table E.2. Bat species codes.

Common name Scientific name CODE

Allen’s Big-eared Bat Idionycteris phyllotis IDPH

Big Brown Bat Eptesicus fuscus EPFU

Big Free-tailed Bat Nyctinomops macrotis NYMA

Brazilian Free-tailed Bat Tadarida brasiliensis TABR

California Leaf-nosed Bat Macrotus californicus MACA

California Myotis Myotis californicus MYCA

Cave Myotis Myotis velifer MYVE

Fringed Myotis Myotis thysanodes MYTH

Ghost Faced Bat Mormoops megalophylla MOME

Hoary Bat Lasiurus cinereus LACI

Lesser Long-nosed Bat Leptonycteris curasoae LECU

Little brown Myotis Myotis occultus MYOC

Long-eared Myotis Myotis evotis MYEV

Long-legged Myotis Myotis volans MYVO

Mexican Long-tongued Bat Choeronycteris Mexicana CHME

Pallid Bat Antrozous pallidus ANPA

Pocketed Free-tailed Bat Nyctinomops femorosaccus NYFE

Silver-haired Bat Lasionycteris noctivagans LANO

Southern Yellow Bat Lasiurus ega LAEG

Southwestern Myotis Myotis auriculus MYAU

Spotted Bat Euderma maculatum EUMA

Townsend’s Big-eared Bat Corynorhinus townsendii COTO

Underwood’s Mastiff Bat Eumops underwoodi EUUN

Western Mastiff Bat Eumops perotis EUPE

Western Pipistrelle Pipistrellus Hesperus PIHE

Western Red Bat Lasiurus blossevillii LABL
92

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93

Bat Guild Monitoring

Field Data Sheet: 

Protocol version : 1.00 Datasheet Version: 1.00

Proofread by: __________________

Copied by: __________________

Entered by: __________________

Verified by: __________________

Date ___/____/_____ Personnel ____________________________________________ Time net opened ___________ Time net closed ____________ 

 # of nets ____________ (Sketch on back? ____) Net hours _____________ Moon phase __________ Temp. _____/______ Cloud________ Wind _____/______ 

Humidity________ Barometric___________ Netting conditions*________________ 

Time Species Net # Age Sex Repro. 

Status

FA (mm) Wt. (gm) Notes

* Excellent = no adverse conditions (wind, rain, moon), Good = 1 adverse condition for less than 25% of net time, Fair = 1 or more adverse conditions less than 50 % of net time, 

Poor = 1 or more adverse conditions more than 50 % of net time

Location Name: Location Coordinates: 
94

Additional Notes: 
95

Appendix F. Visitor Use Monitoring Protocol

1. Campsite Condition Assessment

First consider the condition class of the site and record-pertinent data on the Campsite 

Inventory form. Where there is little perennial vegetation, use the size of the central area that has 

experienced long-term flattening of the soil surface to differentiate between class 2 and class 3. 

In ecosystem types with a poorly developed organic soil horizon, use the level of soil compaction 

to differentiate between class 3 and class 4 campsites.

• Class 1: The recreation site is barely recognizable. There is only a slight loss of vegetation 

and minimal disturbance of soil. 

• Class 2: Soil surface flattened (for the long term) around fireplace or center of activity.

• Class 3: Soil surface flattened (for the long term) on most of the site, but exposed soil not 

highly compacted except in a few areas.

• Class 4: Mineral soil exposed and highly compacted (to a cement-like state) over most of the 

campsite. 

• Class 5: Soil erosion is obvious. Plant roots are exposed because of severe erosion of the 

campsite.

Record any additional information on the data sheet, including the amount of litter 

(trash), human waste, invasive plants, user-developed trails and user-created structures.

2. GPS Mapping of Disturbed Areas at Campsites

It is suggested that the location of the disturbed area of Condition Class 2-5 sites be 

recorded with a GPS unit and that the extent of the disturbed area be mapped as a polygon. Such 

mapping may be achieved by using the GPS tracking function or with a handheld GPS/GIS unit 

(for example, Trimble Recon Handheld (http://www.trimble.com/recon_mgis_handheld.shtml) in 

conjunction with ESRI ArcPad (http://www.esri.com/software/arcgis/arcpad/index.html)). 

Using the GPS in GIS mode, map a polygon of the campsite area and define the extent of 

the disturbed area by evidence of foot trampling and tire tracks. Signs of disturbed vegetation 

(damaged woody shrubs and trees used for firewood) are recorded by marking the location of the 

disturbed specimen with a GPS point. Note the type and amount of damage on the data sheet. 

3. Site Photography

If possible, campsite photography is conducted near midday, reducing the effects of 

morning and evening shadows. After photographing a site, check all photographs to make sure 

they are clearly focused, and 

1. Determine the location of the estimated center point of the campsite using a GPS. 

2. Standing at the center position, consult a compass and photograph the campsite in both the 

cardinal and intercardinal directions (N-NE-E-SE-S-SW-W-NW), starting the first photo in 

the North. For each photograph, focus the center of the camera viewfinder an estimated 20 ft 

from the site center. 

3. Repeat step 2 with another 8 photographs focused at 5 ft from the site center. 

Write on the datasheet the campsite ID, UTM coordinates (campsite center) and all image 

file IDs and photograph directions. 
96

Campsite Inventory Form

Field Data Sheet: 

Protocol version : 1.00 Datasheet Version: 1.00

Proofread by: __________________

Copied by: __________________

Entered by: __________________

Verified by: __________________

Campsite Number: - - 

 

Example: Barry M. Goldwater Range West-Tinajas Altas-Site #3

Campsite Number: BMGRW-TA-03 

Recorder(s): 

Date: 

Condition Class Rating (1-5) 

Site Center GPS Coordinates: UTM: , E, , , N (UTM, NAD 83, 

Zone 11 N) 

General Site Description: 

Photograph File Name(s) 20 m (N-NE-E-SE-S-SW-W-NW) 

 

Photograph File Name(s) 5 m (N-NE-E-SE-S-SW-W-NW) 

 

Additional Information 

Litter: None, 

Some, 

Abundant

Human Waste: 

None, Some, 

Abundant

Invasive 

Plants (spp): 

User 

Developed 

Trails: Y/N

User Created Structures 

(list type and number)

 

Notes and Sketches (continue on back)
97

Appendix G. BMGR–West Workshop Participants, Followup Survey, and Survey 

Results

Workshop participant 

name Email Phone Affiliation

John Arnett John.Arnett@luke.af.mil 623-856-8491 LAFB

Scott Blackman sblackman@AZGFD.gov 520-742-1911 AZGFD

Daniel Garcia Daniel.Garcia@luke.af.mil 623-856-4265 LAFB/BMGR-East

Evan Gwilliam evan_gwilliam@nps.gov 520-403-3055 NPS

Edwin Juarez EJuarez@AZGFD.gov 602-789-3516 AZGFD

Jim Malusa jimmalusa@hotmail.com 520-621-6424 UA

Paul Merkley paul.merkley@dhs.gov 928-341-6513 DHS

Valerie Morrill valerie.morrill@us.army.mil 928-328-2244 unaffiliated

Lin Piest lpiest@AZGFD.gov 928-341-4049 AZGFD

Brian Powell brian.powell@pima.gov 520-740-6440 Pima County Planning

Helen Raichle hraichle@usgs.gov 520-626-5529 USGS

Robert Webb rhwebb@usgs.gov 520-670-6671 x238 USGS

Richard Whittle Richard.Whittle@luke.af.mil 623-856-9476 LAFB

Sam Drake sdrake@nexus.srnr.arizona.edu 520-621-4501 UA/OALS/ARSC

Charles Drost charles_drost@usgs.gov 928-556-7187 USGS

Jeff Fehmi jfehmi@email.arizona.edu 520-621-7268 UA-SNRE

Brad Hollingsworth bhollingsworth@sdnhm.org 619-255-0277 SDNHM

Bill Knowles bknowles@AZGFD.gov 928-341-4047 AZGFD

Kim Lovich KLovich@sandiegozoo.org 619-685-3209 San Diego Zoo

Rob Lovich robert.lovich@navy.mil 619-889-7587 Navy

Robert Mesta robert_mesta@fws.gov 520-882-0047 USFWS

Pam Nagler pnagler@usgs.gov 520-975-3814 USGS

Larry Norris lnorris@ag.arizona.edu 520-621-7998 UA

Rob Palmer robert.l.palmer@navy.mil 619-532-1817 Navy

Ron Pearce ronald.pearce@usmc.mil 928-269-3404 MCAS-Yuma

Cecil Schwalbe cschwalbe@usgs.gov 520-621-5508 USGS

Sid Slone Sid_Slone@fws.gov 520-387-4993 USFWS

Charles van Riper charles_van_riper@usgs.gov 520-626-7027 USGS

Miguel Villarreal miguelluisvillarreal@gmail.com 520-626-9156 USGS

Cynthia Wallace cwallace@usgs.gov 520-670-5589 USGS
98

Summary: The BMGR–West workshop followup survey was hosted online September 21–28, 

2009. The survey link was e-mailed to all 26 workshop participants, and 22 completed the survey. 

Below is a brief summary of responses to each question, followed by the complete survey results and 

related statistics:

1. Please rank the following specific VEGETATION resources in order of priority (1 = 

HIGHEST, 4 = LOWEST) 

Invasive species were ranked highest priority (average rating = 1.76) followed by vegetation 

communities (2.19). Rare plants and dune endemic plants were both considered low priority. 

2. Please rank the following specific CLIMATE resources in order of priority (1 = HIGHEST, 3 = 

LOWEST)

Precipitation was ranked highest (1.40) followed by temperature (2.21) and air quality/dust (2.33). One 

respondent noted that they were all high priority and could be bundled together for monitoring. 

3. Please rank the following specific BIRD resources in order of priority (1 = HIGHEST, 7 = 

LOWEST)

General bird surveys stood out as the highest priority (1.70), Le Conte’s thrasher second (3.33), 

followed by overwintering birds (3.40). Raptors, Pygmy owl, excavators, and European starling were 

generally all low priority.

4. Please rank the following specific MAMMAL/WILDLIFE resources in order of priority (1 = 

HIGHEST, 6 = LOWEST) 

Sonoran pronghorn were ranked highest priority (1.52), followed by bat guild and Bighorn sheep (2.81 

and 2.86, respectively). Kit fox, coyote, and invasive animals were all lower priority.

5. Please rank the following specific AMPHIBIAN resources in order of priority (1 = HIGHEST, 4 

= LOWEST)
99

Sonoran Desert toad and Couch’s Spadefoot were highest priority (1.78 and 1.94, respectively). Three 

respondents suggested that all amphibian species monitoring could be bundled together, so ranking 

individual species was not critical. One respondent indicated “would not do any.” 

6. Please rank the following specific REPTILE resources in order of priority (1 = HIGHEST, 3 = 

LOWEST)

Flat-tailed horned lizard was ranked highest (1.37), followed by desert tortoise (2.15) and fringe-toed 

lizard (2.30). 

7. Please rank the following specific ANTHROPOGENIC IMPACTS in order of priority (1 = 

HIGHEST, 6 = LOWEST) 

Transportation corridors (roads and trails) were ranked highest priority (1.29), and visitor use (2.67) and 

military use (2.90) moderate priority. 

8. Please rank the following specific SOIL resources in order of priority (1 = HIGHEST, 3 = 

LOWEST)

Soil erosion (1.48) and channel change/washes (1.71) were highest priority.

9. Please rank the following specific WATER resources in order of priority (1 = HIGHEST, 3 = 

LOWEST)

Seeps, springs, and tinajas were overwhelmingly ranked highest priority (1.15). 

10. In your opinion, how important is it to monitor each of the following 11 broad resource 

categories on the BMGR–West ? Please assign a priority level to the each of the following: 

High priority resource categories (in order of importance) included (1) anthropogenic impacts, (2) 

vegetation, (3) water resources, and (4) climate. Medium priority resources were amphibians, birds and 

reptiles (tie), soils, and mammal/wildlife. Low priority resources were invertebrates and natural 

disturbances (tie).
100

SURVEY RESULTS

Note: Grey boxes highlight the majority column value (priority rank) for each row (resource) based on number of responses. 

Respondent comments are included at the bottom where applicable.

1. Please rank the following specific VEGETATION resources in order of priority (1 = HIGHEST, 4 = LOWEST)

 1 2 3 4 Rating

Average

Response

Count

Invasive species 47.6% (10) 33.3% (7) 14.3% (3) 4.8% (1) 1.76 21

Vegetation 

communities 38.1% (8) 28.6% (6) 9.5% (2) 23.8% (5) 2.19 21

Rare plants 5.0% (1) 10.0% (2) 65.0% (13) 20.0% (4) 3.00 20

Dune endemic plants 4.8% (1) 28.6% (6) 14.3% (3) 52.4% (11) 3.14 21

1. Sahara mustard.

2. Especially DOD Species at risk.

3. Not clear on the concept: does this mean additional monitoring of veg communities? If so, I don't give veg 

communities a high priority, because they are currently being mapped. Naturally, I think the map should be 

completed, and, once completed, the effort would turn to invasives and dune endemics

4. Desert wash plant associations

4 

2. Please rank the following specific CLIMATE resources in order of priority (1 = HIGHEST, 3 = LOWEST)

 1 2 3 Rating

Average

Response

Count

Temperature 10.5% (2) 57.9% (11) 31.6% (6) 2.21 19

Precipitation 75.0% (15) 10.0% (2) 15.0% (3) 1.40 20

Air Quality/Dust 19.0% (4) 28.6% (6) 52.4% (11) 2.33 21

1.These could all be bundled, as all are really a #1 priority 1 

3. Please rank the following specific BIRD resources in order of priority (1 = HIGHEST, 7 = LOWEST)

 1 2 3 4 5 6 7 Rating

Average

Response

Count

General Bird 

surveys

70.0% 

(14)

10.0% 

(2)

10.0% 

(2) 5.0% (1) 0.0% (0) 5.0% (1) 0.0% (0) 1.70 20

Overwintering 

birds 0.0% (0) 40.0% (8)

25.0% 

(5)

10.0% 

(2)

10.0% 

(2)

10.0% 

(2) 5.0% (1) 3.40 20

Le Conte's 21.1% 31.6% 5.3% (1) 10.5% 10.5% 15.8% 5.3% (1) 3.26 19
101

3. Please rank the following specific BIRD resources in order of priority (1 = HIGHEST, 7 = LOWEST)

thrasher (4) (6) (2) (2) (3)

Raptors 0.0% (0) 0.0% (0) 17.6% 

(3)

35.3% 

(6)

41.2% 

(7) 0.0% (0) 5.9% (1) 4.41 17

Cactus 

ferruginous 

pygmy-owl

10.5% 

(2)

10.5% 

(2)

10.5% 

(2) 0.0% (0) 26.3% 

(5)

26.3% 

(5)

15.8% 

(3) 4.63 19

Primary 

Excavator 

(Cavity) Guild

0.0% (0) 5.3% (1) 26.3% 

(5)

21.1% 

(4)

10.5% 

(2)

21.1% 

(4)

15.8% 

(3) 4.63 19

European 

starling 0.0% (0) 5.3% (1) 5.3% (1) 15.8% (3) 0.0% (0) 21.1% (4)

52.6% 

(10) 5.84 19

1.Golden Eagle Surveys

2.Most are low priority 

3.gray vireo (utilizes elephant tree fruits)

3 

4. Please rank the following specific MAMMAL/WILDLIFE resources in order of priority (1 = HIGHEST, 6 = 

LOWEST)

 1 2 3 4 5 6 Rating

Average

Response

Count

Pronghorn 81.0% (17) 4.8% (1) 4.8% (1) 0.0% (0) 9.5% (2) 0.0% (0) 1.52 21

Bat Guild 9.5% (2) 38.1% (8) 23.8% (5) 23.8% (5) 0.0% (0) 4.8% (1) 2.81 21

Kit Fox 0.0% (0) 15.0% (3) 10.0% (2) 30.0% (6) 35.0% (7) 10.0% (2) 4.15 20

Coyote 0.0% (0) 13.6% (3) 13.6% (3) 4.5% (1) 31.8% (7) 36.4% (8) 4.64 22

Invasive animals 4.8% (1) 0.0% (0) 19.0% (4) 23.8% (5) 14.3% (3) 38.1% (8) 4.57 21

Bighorn Sheep 9.5% (2) 33.3% (7) 33.3% (7) 14.3% (3) 4.8% (1) 4.8% (1) 2.86 21

1. nocturnal rodents 1

5. Please rank the following specific AMPHIBIAN resources in order of priority (1 = HIGHEST, 4 = LOWEST)

 1 2 3 4 Rating

Average

Response

Count

Sonoran Desert 

toad 44.4% (8) 33.3% (6) 22.2% (4) 0.0% (0) 1.78 18

red-spotted toad 11.8% (2) 35.3% (6) 29.4% (5) 23.5% (4) 2.65 17

Couch’s spadefoot 43.8% (7) 18.8% (3) 37.5% (6) 0.0% (0) 1.94 16

Great Plains toad 5.6% (1) 11.1% (2) 11.1% (2) 72.2% (13) 3.50 18

1.These too, could be bundled, and all would receive similar priority 2.They all comprise the same guild of desert 

anurans, therefore the breeding habitat (for example, ephemeral pools) needs monitoring 

3.auditory surveys for all species – general 

4.would not do any 

5.not qualified to respond

5 
102

6. Please rank the following specific REPTILE resources in order of priority (1 = HIGHEST, 3 = LOWEST)

 1 2 3 Rating

Average

Response

Count

Desert tortoise 30.0% (6) 25.0% (5) 45.0% (9) 2.15 20

Fringe-toed lizard 5.0% (1) 60.0% (12) 35.0% (7) 2.30 20

Flat-tailed horned 

lizard 73.7% (14) 15.8% (3) 10.5% (2) 1.37 19

1.Is the desert tortoise even found on BMGR westwest

2.not qualified to respond

3.Diurnal lizards, Nocturnal snakes (method-specific) 3 

7. Please rank the following specific ANTHROPOGENIC IMPACTS in order of priority (1 = HIGHEST, 6 = 

LOWEST)

 1 2 3 4 5 6 Rating

Average

Response

Count

Transportation Corridors 

(Roads and Trails) 76.2% (16) 19.0% (4) 4.8% (1) 0.0% (0) 0.0% (0) 0.0% (0) 1.29 21

Visitor use 9.5% (2) 42.9% (9) 23.8% (5) 19.0% (4) 4.8% (1) 0.0% (0) 2.67 21

Neighboring Land Use/Land 

Cover 0.0% (0) 0.0% (0) 20.0% (4) 35.0% (7) 40.0% (8) 5.0% (1) 4.30 20

Military 20.0% (4) 30.0% (6) 20.0% (4) 10.0% (2) 10.0% (2) 10.0% (2) 2.90 20

Firewood depletion 0.0% (0) 9.5% (2) 23.8% (5) 19.0% (4) 42.9% (9) 4.8% (1) 4.10 21

Rockhounding 0.0% (0) 0.0% (0) 9.5% (2) 14.3% (3) 0.0% (0) 76.2% (16) 5.43 21

1.Border fence 1 

8. Please rank the following specific SOIL resources in order of priority (1 = HIGHEST, 3 = LOWEST)

 1 2 3 Rating

Average

Response

Count

Channel change/Washes 42.9% (9) 42.9% (9) 14.3% (3) 1.71 21

Soil erosion 52.4% (11) 47.6% (10) 0.0% (0) 1.48 21

Aeolian saltation of soils 9.5% (2) 9.5% (2) 81.0% (17) 2.71 21

1. Dune sands 1 
103

9. Please rank the following specific WATER resources in order of priority (1 = HIGHEST, 3 = LOWEST)

 1 2 3 Rating

Average

Response

Count

Seeps, springs and 

tinajas 90.0% (18) 5.0% (1) 5.0% (1) 1.15 20

Ground water 10.5% (2) 57.9% (11) 31.6% (6) 2.21 19

Water quality 5.0% (1) 35.0% (7) 60.0% (12) 2.55 20

10. In your opinion, how important is it to monitor each of the following 11 broad resource categories on the Barry 

M. Goldwater Range West? Please assign a priority level to the each of the following:

 Low Medium High Rating

Average

Response

Count

Vegetation 0.0% (0) 27.3% (6) 72.7% (16) 2.73 22

Climate 22.7% (5) 22.7% (5) 54.5% (12) 2.32 22

Birds 4.8% (1) 57.1% (12) 38.1% (8) 2.33 21

Mammal/Wildlife 14.3% (3) 47.6% (10) 38.1% (8) 2.24 21

Amphibians 23.8% (5) 66.7% (14) 9.5% (2) 1.86 21

Reptiles 9.5% (2) 57.1% (12) 33.3% (7) 2.24 21

Anthropogenic impacts 9.1% (2) 9.1% (2) 81.8% (18) 2.73 22

Invertebrates 52.4% (11) 33.3% (7) 14.3% (3) 1.62 21

Natural disturbances 52.4% (11) 19.0% (4) 28.6% (6) 1.76 21

Soil 33.3% (7) 52.4% (11) 14.3% (3) 1.81 21

Water resources 14.3% (3) 28.6% (6) 57.1% (12) 2.43 21