National Park Service

U.S. Department of the Interior

Natural Resource Stewardship and Science

Colorado National Monument

Natural Resource Condition Assessment

Natural Resource Report NPS/COLM/NRR—2016/1356
ON THE COVER

The view of Colorado National Monument, looking east toward Grand Junction, Colorado.

Photograph courtesy of the National Park Service
Colorado National Monument

Natural Resource Condition Assessment

Natural Resource Report NPS/COLM/NRR—2016/1356

Kevin M. Benck

Kathy Allen

Andy J. Nadeau

Anna M. Davis

Sarah Gardner

Matt Randerson

Andy Robertson

GeoSpatial Services

Saint Mary’s University of Minnesota

890 Prairie Island Road 

Winona, Minnesota 55987

December 2016

U.S. Department of the Interior

National Park Service

Natural Resource Stewardship and Science 

Fort Collins, Colorado
ii

The National Park Service, Natural Resource Stewardship and Science office in Fort Collins, 

Colorado, publishes a range of reports that address natural resource topics. These reports are of 

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The Natural Resource Report Series is used to disseminate comprehensive information and analysis 

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The series supports the advancement of science, informed decision-making, and the achievement of 

the National Park Service mission. The series also provides a forum for presenting more lengthy 

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All manuscripts in the series receive the appropriate level of peer review to ensure that the 

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trade names or commercial products does not constitute endorsement or recommendation for use by 

the U.S. Government.

This report is available in digital format from the Integrated Resource Management Applications 

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(http://www.nature.nps.gov/publications/nrpm/). To receive this report in a format optimized for 

screen readers, please email irma@nps.gov. 

Please cite this publication as:

Benck, K. M., K. Allen, A. J. Nadeau, A. M. Davis, S. Gardner, M. Randerson, and A. Robertson.

2016. Colorado National Monument: Natural resources condition assessment. Natural Resource 

Report NPS/COLM/NRR—2016/1356. National Park Service, Fort Collins, Colorado.

NPS 119/135551, December 2016
iii

Contents

Page

Figures...................................................................................................................................................xi

Tables.................................................................................................................................................xvii

Photos................................................................................................................................................xxiii

Appendices.......................................................................................................................................xxvii

Executive Summary..........................................................................................................................xxix

Acknowledgments.............................................................................................................................xxxi

Acronyms and Abbreviations..........................................................................................................xxxiii

1. NRCA Background Information........................................................................................................1

2. Introduction and Resource Setting.....................................................................................................5

2.1 Introduction ..............................................................................................................................5

2.1.1 Enabling Legislation.........................................................................................................5

2.1.2 Geographic Setting ...........................................................................................................5

2.1.3 Visitation Statistics.........................................................................................................15

2.2 Natural Resources...................................................................................................................16

2.2.1 Ecological Units and Watersheds...................................................................................16

2.2.2 Resource Descriptions....................................................................................................19

2.2.3 Resource Issues Overview..............................................................................................24

2.3 Resource Stewardship ............................................................................................................28

2.3.1 Management Directives and Planning Guidance............................................................28

2.3.2 Status of Supporting Science..........................................................................................28

2.4 Literature Cited.......................................................................................................................29

3. Study Scoping and Design ...............................................................................................................35

3.1 Preliminary Scoping ...............................................................................................................35

3.1.1 Natural Resource Condition Assessment .......................................................................35

3.1.2 Climate Change Vulnerability Assessment Pilot Study .................................................36

3.2 Study Design for Natural Resource Condition Assessment ...................................................37

3.2.1 Indicator Framework, Focal Study Resources and Indicators........................................37

3.2.2 Reporting Area ...............................................................................................................42
iv

Contents (continued)

Page

3.2.3 General Approach and Methods.....................................................................................42

3.3 Study Design for Climate Change Vulnerability Assessment Pilot .......................................47

3.3.1 Component Selection and Assessment Variables...........................................................47

3.3.2 General Approach and Methods.....................................................................................49

3.4 Literature Cited.......................................................................................................................53

4. Natural Resource Conditions...........................................................................................................57

4.1 Pinyon-juniper Woodlands/Savannas.....................................................................................58

4.1.1 Description .....................................................................................................................58

4.1.2 Measures.........................................................................................................................59

4.1.3 Reference Conditions/Values.........................................................................................59

4.1.4 Data and Methods...........................................................................................................59

4.1.5 Current Condition and Trend..........................................................................................61

4.1.6 Sources of Expertise .......................................................................................................88

4.1.7 Literature Cited...............................................................................................................89

4.2 Sagebrush Shrublands/Shrub Steppe......................................................................................93

4.2.1 Description .....................................................................................................................93

4.2.2 Measures.........................................................................................................................94

4.2.3 Reference Conditions/Values.........................................................................................94

4.2.4 Data and Methods...........................................................................................................94

4.2.5 Current Condition and Trend..........................................................................................95

4.2.6 Sources of Expertise .....................................................................................................108

4.2.7 Literature Cited.............................................................................................................108

4.3. Riparian Habitats/Large Dry Washes..................................................................................112

4.3.1 Description ...................................................................................................................112

4.3.2 Measures.......................................................................................................................112

4.3.3 Reference Conditions/Values.......................................................................................112

4.3.4 Data and Methods.........................................................................................................113

4.3.5 Current Condition and Trend........................................................................................114
v

Contents (continued)

Page

4.3.6 Sources of Expertise .....................................................................................................128

4.3.7 Literature Cited.............................................................................................................128

4.4 Seeps and Springs and Tinaja Habitats ................................................................................131

4.4.1 Description ...................................................................................................................131

4.4.2 Measures.......................................................................................................................132

4.4.3 Reference Conditions/Values.......................................................................................132

4.4.4 Data and Methods.........................................................................................................132

4.4.5 Current Condition and Trend........................................................................................133

4.4.6 Sources of Expertise .....................................................................................................151

4.4.7 Literature Cited.............................................................................................................151

4.5 Mixed Salt Desert Scrub/Semi-desert Grassland..................................................................154

4.5.1 Description ...................................................................................................................154

4.5.2 Measures.......................................................................................................................155

4.5.3 Reference Conditions/Values.......................................................................................155

4.5.4 Data and Methods.........................................................................................................155

4.5.5 Current Condition and Trend........................................................................................156

4.5.6 Sources of Expertise .....................................................................................................169

4.5.7 Literature Cited.............................................................................................................169

4.6 Canyon Walls and Monolith Vegetation Communities........................................................172

4.6.1 Description ...................................................................................................................172

4.6.2 Measures.......................................................................................................................172

4.6.3 Reference Conditions/Values.......................................................................................172

4.6.4 Data and Methods.........................................................................................................173

4.6.5 Current Condition and Trend........................................................................................173

4.6.6 Sources of Expertise .....................................................................................................178

4.6.7 Literature Cited.............................................................................................................178

4.7 Montane Shrublands.............................................................................................................180

4.7.1 Description ...................................................................................................................180
vi

Contents (continued)

Page

4.7.2 Measures.......................................................................................................................181

4.7.3 Reference Conditions/Values.......................................................................................181

4.7.4 Data and Methods.........................................................................................................181

4.7.5 Current Condition and Trend........................................................................................182

4.7.6 Sources of Expertise .....................................................................................................191

4.7.7 Literature Cited.............................................................................................................192

4.8 Herptiles ...............................................................................................................................194

4.8.1 Description ...................................................................................................................194

4.8.2 Measures.......................................................................................................................194

4.8.3 Reference Conditions/Values.......................................................................................194

4.8.4 Data and Methods.........................................................................................................195

4.8.5 Current Condition and Trend........................................................................................195

4.8.6 Sources of Expertise .....................................................................................................204

4.8.7 Literature Cited.............................................................................................................204

4.9 Birds .....................................................................................................................................207

4.9.1 Description ...................................................................................................................207

4.9.2 Measures.......................................................................................................................207

4.9.3 Reference Conditions/Values.......................................................................................208

4.9.4 Data and Methods.........................................................................................................208

4.9.5 Current Condition and Trend........................................................................................211

4.9.6 Sources of Expertise .....................................................................................................219

4.9.7 Literature Cited.............................................................................................................219

4.10 Raptors................................................................................................................................222

4.10.1 Description .................................................................................................................222

4.10.2 Measures.....................................................................................................................223

4.10.3 Reference Conditions/Values.....................................................................................223

4.10.4 Data and Methods.......................................................................................................223

4.10.5 Current Condition and Trend......................................................................................225
vii

Contents (continued)

Page

4.10.6 Sources of Expertise ...................................................................................................237

4.10.7 Literature Cited...........................................................................................................237

4.11 Small Mammals..................................................................................................................241

4.11.1 Description .................................................................................................................241

4.11.2 Measures.....................................................................................................................241

4.11.3 Reference Conditions/Values.....................................................................................242

4.11.4 Data and Methods.......................................................................................................242

4.11.5 Current Condition and Trend......................................................................................242

4.11.6 Sources of Expertise ...................................................................................................249

4.11.7 Literature Cited...........................................................................................................250

4.12 Mountain Lion....................................................................................................................252

4.12.1 Description .................................................................................................................252

4.12.2 Measures.....................................................................................................................252

4.12.3 Reference Conditions/Values.....................................................................................252

4.12.4 Data and Methods.......................................................................................................253

4.12.5 Current Condition and Trend......................................................................................254

4.12.6 Sources of Expertise ...................................................................................................259

4.12.7 Literature Cited...........................................................................................................259

4.13 Bighorn Sheep ....................................................................................................................261

4.13.1 Description .................................................................................................................261

4.13.2 Measures.....................................................................................................................261

4.13.3 Reference Conditions/Values.....................................................................................261

4.13.4 Data and Methods.......................................................................................................262

4.13.5 Current Condition and Trend......................................................................................263

4.13.6 Sources of Expertise ...................................................................................................269

4.13.7 Literature Cited...........................................................................................................269

4.14 Kit Fox................................................................................................................................271

4.14.1 Description .................................................................................................................271
viii

Contents (continued)

Page

4.14.2 Measures.....................................................................................................................271

4.14.3 Reference Conditions/Values.....................................................................................272

4.14.4 Data and Methods.......................................................................................................272

4.14.5 Current Condition and Trend......................................................................................273

4.14.6 Sources of Expertise ...................................................................................................277

4.14.7 Literature Cited...........................................................................................................277

4.15 Bats.....................................................................................................................................279

4.15.1 Description .................................................................................................................279

4.15.2 Measures.....................................................................................................................279

4.15.3 Reference Conditions/Values.....................................................................................280

4.15.4 Data and Methods.......................................................................................................280

4.15.5 Current Condition and Trend......................................................................................280

4.15.6 Sources of Expertise ...................................................................................................285

4.15.7 Literature Cited...........................................................................................................285

4.16 Air Quality..........................................................................................................................287

4.16.1 Description .................................................................................................................287

4.16.2 Measures.....................................................................................................................287

4.16.3 Reference Conditions/Values.....................................................................................289

4.16.4 Data and Methods.......................................................................................................292

4.16.5 Current Condition and Trend......................................................................................295

4.16.6 Sources of Expertise ...................................................................................................307

4.16.7 Literature Cited...........................................................................................................307

4.17 Dark Night Skies................................................................................................................311

4.17.1 Description .................................................................................................................311

4.17.2 Measures.....................................................................................................................311

4.17.3 Reference Conditions/Values.....................................................................................312

4.17.4 Data and Methods.......................................................................................................313

4.17.5 Current Condition and Trend......................................................................................313
ix

Contents (continued)

Page

4.17.6 Sources of Expertise ...................................................................................................321

4.17.7 Literature Cited...........................................................................................................321

4.18 Viewscape...........................................................................................................................323

4.18.1 Description .................................................................................................................323

4.18.2 Measures.....................................................................................................................324

4.18.3 Reference Conditions/Values.....................................................................................324

4.18.4 Data and Methods.......................................................................................................324

4.18.5 Current Condition and Trend......................................................................................326

4.18.6 Sources of Expertise ...................................................................................................338

4.18.7 Literature Cited...........................................................................................................338

4.19 Soundscape and Acoustic Environment .............................................................................339

4.19.1 Description .................................................................................................................339

4.19.2 Measures.....................................................................................................................339

4.19.3 Reference Conditions/Values.....................................................................................339

4.19.4 Data and Methods.......................................................................................................340

4.19.5 Current Condition and Trend......................................................................................343

4.19.6 Sources of Expertise ...................................................................................................350

4.19.7 Literature Cited...........................................................................................................350

4.20 Paleontological Resources..................................................................................................353

4.20.1 Description .................................................................................................................353

4.20.2 Measures.....................................................................................................................357

4.20.3 Reference Conditions/Values.....................................................................................357

4.20.4 Data and Methods.......................................................................................................357

4.20.5 Current Condition and Trend......................................................................................359

4.20.6 Sources of Expertise ...................................................................................................365

4.20.7 Literature Cited...........................................................................................................366

4.21 Geologic Features and Processes........................................................................................369

4.21.1 Description .................................................................................................................369
x

Contents (continued)

Page

4.21.2 Measures.....................................................................................................................374

4.21.3 Reference Conditions/Values.....................................................................................374

4.21.4 Data and Methods.......................................................................................................374

4.21.5 Current Condition and Trend......................................................................................375

4.21.6 Sources of Expertise ...................................................................................................383

4.21.7 Literature Cited...........................................................................................................383

5. Discussion......................................................................................................................................385

5.1 Component Data Gaps..........................................................................................................385

5.2 Component Condition Designations.....................................................................................388

5.3 Park-wide Condition Observations.......................................................................................391

5.4 Literature Cited.....................................................................................................................396

Appendices.........................................................................................................................................399
xi

Figures 

Page

Figure 1. General location of COLM....................................................................................................6

Figure 2. Canyons and ephemeral stream network at COLM...............................................................7

Figure 3. Communities located in proximity to COLM........................................................................8

Figure 4. Average monthly precipitation for the period 1981-2010 for the COLM 

weather station (Station ID 051772) (WRCC 2015)..............................................................................9

Figure 5. Monthly temperature for the period 1981-2010 for the COLM weather station 

(Station ID 051772) (WRCC 2015).....................................................................................................10

Figure 6. Annual average temperature measured over all the Earth’s land and ocean 

surfaces ................................................................................................................................................11

Figure 7. Trends in (A) maximum monthly temperature, (B) minimum monthly 

temperature, and (C) annual precipitation for COLM .........................................................................12

Figure 8. Projected (A) average annual temperature and (B) total annual precipitation 

from a suite of models, driven by RCP scenarios................................................................................14

Figure 9. The Colorado Plateau and associated physiographic divisions (USGS 2011). ...................17

Figure 10. Level IV ecoregions for COLM. .......................................................................................18

Figure 11. Big Salt Wash-Colorado River watershed and sub-watersheds.........................................19

Figure 12. Location of proposed wilderness area within COLM........................................................24

Figure 13. Colorado National Monument natural resource condition assessment 

framework............................................................................................................................................39

Figure 14. Relationship between exposure, sensitivity, and adaptive capacity (Source: 

Stein et al. 2011). .................................................................................................................................48

Figure 15. The location of pinyon-juniper woodland/savanna alliances within COLM 

(Von Loh et al. 2007)...........................................................................................................................62

Figure 16. IEP infestations associated with mapped pinyon-juniper woodland/savannas..................75

Figure 17. Current geographic extent of pinyon-juniper keystone species (two-needle 

pinyon pine and Utah juniper) used in the climate change vulnerability analysis...............................78

Figure 18. Change in mean A) winter, B) spring, C) summer, and D) fall seasonal 

temperatures for COLM by the year 2100 (ClimateWizard 2014)......................................................79

Figure 19. Change in mean A) winter, B) spring, C) summer, and D) fall seasonal aridity 

for COLM by the year 2100 (ClimateWizard 2014)............................................................................80

Figure 20. Changes in A) mean annual temperature and B) mean annual aridity for 

COLM by the year 2100 (ClimateWizard 2014, NCCSC 2015) .........................................................81
xii

Figures (continued)

Page

Figure 21. Modeled bioclimate profiles for pinyon pine (Rehfeldt 2006) overlaid on the 

digitized range maps of the current distribution (from Little 1991) ....................................................82

Figure 22. Modeled bioclimate profiles for Utah juniper (Rehfeldt 2006) overlaid on the 

digitized range maps of the current distribution (from Little 1991) ....................................................83

Figure 23. The location of sagebrush shrubland/shrub steppe alliances within COLM 

(Von Loh et al. 2007)...........................................................................................................................97

Figure 24. IEP infestations associated with mapped sagebrush shrubland/shrub steppe..................104

Figure 25. The location of riparian vegetation alliances within COLM (Von Loh et al. 

2007). .................................................................................................................................................115

Figure 26. Location of cottonwood/coyote woodlands within COLM (Von Loh et al. 

2007). .................................................................................................................................................117

Figure 27. Location of coyote willow/mesic graminoid shrublands within COLM (Von 

Loh et al. 2007)..................................................................................................................................118

Figure 28. Location of quaking aspen/water birch forests within COLM ........................................119

Figure 29. Location of rubber rabbitbrush desert wash shrublands within COLM (Von 

Loh et al. 2007)..................................................................................................................................120

Figure 30. Location of Baltic rush herbaceous vegetation within COLM (Von Loh et al. 

2007). .................................................................................................................................................121

Figure 31. Seep and spring vegetation locations in COLM mapped by Von Loh et al. 

(2007).................................................................................................................................................134

Figure 32. Seep, spring, and tinaja sites inventoried by Lamm et al. (2014) (Reproduced 

from Lamm et al. 2014). ....................................................................................................................135

Figure 33. Current geographic extent of seep, spring, and tinaja habitats keystone species 

(A. Mancos columbine and B. smooth horsetail) used in the climate change vulnerability 

analysis...............................................................................................................................................144

Figure 34. Current geographic extent of seep, spring, and tinaja habitats keystone species 

(A. coyote willow and B. Rio Grande cottonwood) used in the climate change 

vulnerability analysis .........................................................................................................................145

Figure 35. Mixed salt desert scrub and semi-desert grassland locations within COLM 

(Von Loh et al. 2007).........................................................................................................................157

Figure 36. IEP observations within mapped mixed salt desert scrub and semi-desert 

grassland vegetation communities from 2003 and 2013 field seasons. .............................................165

Figure 37. Plots sampled in COLM and on surrounding BLM land in 2003 (Von Loh et 

al. 2007). ............................................................................................................................................174

Figure 38. Montane shrubland locations within COLM (Voh Loh et al. 2007). ..............................183
xiii

Figures (continued)

Page

Figure 39. IEP infestations associated with mapped montane shrublands........................................187

Figure 40. Mapping of locations within COLM where amphibians were observed by 

Platenberg and Graham (2003); it should be noted that some data points are offset slightly 

to reveal overlap.................................................................................................................................197

Figure 41. Mapping of locations within COLM where reptiles were observed by 

Platenberg and Graham (2003; it should be noted that some data points are offset slightly 

to reveal overlap). ..............................................................................................................................200

Figure 42. Zoogeographic regions of the world; shaded areas represent transition areas 

between regions (TPWD 2015). ........................................................................................................208

Figure 43. The CBC area that falls within COLM land....................................................................210

Figure 44. Breeding species richness observed on both of the RMBO landbird 

monitoring routes in COLM ..............................................................................................................213

Figure 45. Number of year-round bird species observed on both survey routes in 

COLM’s P-J habitat during RMBO landbird monitoring from 2005-2014.......................................214

Figure 46. The number of species observed during each year of the Grand Junction CBC 

(black, primary Y-axis) and the number of participants in the Grand Junction CBC (red, 

secondary Y-axis) from 1922-2013 ...................................................................................................215

Figure 47. The CBC area that falls within COLM land. The diameter of the count circle 

is 24-km (15 mi) and is surveyed by volunteers each winter.............................................................225

Figure 48. Number of raptor species observed on both survey routes in COLM’s pinyonjuniper habitat during RMBO monitoring from 2005-2014 ..............................................................227

Figure 49. The number of raptor species observed during each year of the Grand 

Junction CBC (black, primary axis) and the number of participants in the Grand Junction 

CBC (red, secondary Y-axis) from 1922-2013..................................................................................229

Figure 50. Number of raptor individuals observed on both survey routes in COLM’s 

pinyon-juniper habitat during RMBO monitoring from 2005-2014..................................................230

Figure 51. The number of individuals observed during each year of the Grand Junction 

CBC (black, primary Y-axis) and the number of participants in the Grand Junction CBC 

(red, secondary Y-axis) from 1922-2013...........................................................................................231

Figure 52. The location of COLM within GMU 40 and DAU L-22 (CPW 2015b). ........................254

Figure 53. Mountain lion range within the state of Colorado (CPW 2014a). ...................................256

Figure 54. Black Ridge Unit post-hunt population estimates (George et al. 2009; CPW 

unpublished data from Stephanie Durno). .........................................................................................264

Figure 55. Approximate distribution of the Black Ridge Unit herd as of 1988 (created 

from a description of population extent in Armstrong [1988])..........................................................265
xiv

Figures (continued)

Page

Figure 56. Bighorn sheep range within Colorado (CPW 2013)........................................................266

Figure 57. Camera locations for the 2012-2013 kit fox survey (from Neubaum and 

Duckett 2014).....................................................................................................................................273

Figure 58. Recent (2005) and historic distribution of the kit fox in Colorado (Recreated 

from Boyle and Reeder 2005)............................................................................................................275

Figure 59. Location of air quality monitoring sites that provided data used in the air 

quality analysis for COLM. ...............................................................................................................293

Figure 60. Ten year trend (2004–2013) in annual average concentrations (μeq/l) of 

nitrate in precipitation at Canyonlands National Park (NADP monitoring site UT09) 

(NPS 2015a).......................................................................................................................................296

Figure 61. Ten year trend (2004–2013) in annual average concentrations (μeq/l) of 

sulfate in precipitation at Canyonlands National Park (NADP monitoring site UT09) 

(NPS 2015a).......................................................................................................................................296

Figure 62. Ten year trend (2004–2013) in annual average concentrations (μeq/l) of 

ammonium in precipitation at Canyonlands National Park (NADP monitoring site UT09) 

(NPS 2015a).......................................................................................................................................297

Figure 63. Annual 4th highest 8-hour maximum ozone (O3) concentrations (ppb) at 

COLM, 2006-2012 (EPA 2015). .......................................................................................................298

Figure 64. W126 ozone exposure index for vegetation concentrations ( (ppm–hrs) at 

COLM (NPS 2015a) ..........................................................................................................................298

Figure 65. Annual 24-hour particulate matter (PM2.5) concentrations (weighted annual 

mean) near COLM, 2005-2015 (EPA 2015)......................................................................................299

Figure 66. Annual 24-hour particulate matter (PM10) concentrations (weighted annual 

mean) near COLM, 2005-2015 (EPA 2015)......................................................................................300

Figure 67. Ten year trend (2004–2013) in visibility for the 20% clearest days (dv) for 

COLM................................................................................................................................................301

Figure 68. Ten year trend (2004–2013) in visibility for the 20% clearest days (dv) for 

COLM................................................................................................................................................301

Figure 69. Composition of haze on clearest days (2009–2013) for COLM......................................302

Figure 70. Composition of haze on haziest days (2009–2013) for COLM. Data were 

interpolated from Canyonlands National Park (NADP monitoring site UT09) (NPS 

2015a) ................................................................................................................................................302

Figure 71. Total annual mercury wet deposition in 2013 (NADP 2014)..........................................303

Figure 72. Total mercury concentrations in 2013 (NADP 2014)......................................................304

Figure 73. Location of DNS sample site (Alpine Camp) in COLM. ................................................314
xv

Figures (continued)

Page

Figure 74. Grayscale representation of sky luminance from a location in Joshua Tree 

National Park (Figure provided by Dan Duriscoe, NPS NSNSD).....................................................316

Figure 75. False color representation of Figure 74 after a logarithmic stretch of pixel 

values (Figure provided by Dan Duriscoe, NPS NSNSD).................................................................316

Figure 76. Contour map of anthropogenic sky glow at a location in Joshua Tree National 

Park, analogous to Figure 75 with natural sources of light subtracted (Figure provided by 

Dan Duriscoe, NPS NSNSD).............................................................................................................317

Figure 77. False color mosaic image of the COLM night sky ..........................................................317

Figure 78. Levels of light pollution occurring in Grand Junction, Colorado and 

surrounding areas (Lorenz 2006; Danko 2014). ................................................................................320

Figure 79. Locations of vista/observation points, the proposed wilderness area, and 

wilderness trails in COLM.................................................................................................................325

Figure 80. Composite viewscape for observation points along Rim Rock Drive in 

COLM. ...............................................................................................................................................327

Figure 81. Composite viewscape for trails located in the recommended wilderness area 

of COLM............................................................................................................................................334

Figure 82. Change in urban development from 2001 to 2011 in cities to the east of 

COLM visible from Rim Rock Drive Overlook observation points (Jin et al. 2011)........................335

Figure 83. Locations of NSNSD acoustical monitoring sites in COLM (NPS 2013).......................342

Figure 84. Modeled predicted results for L50 dBA impact levels at COLM (Mennitt et al. 

2014). .................................................................................................................................................347

Figure 85. Location of the proposed wilderness area within COLM and the two nearby 

airports. ..............................................................................................................................................348

Figure 86. Conceptual diagram illustrating various environmental and anthropogenic 

factors and processes that might affect the stability of in situ paleontological resources..................362

Figure 87. A cross section of the rock layers (geological formations) exposed at COLM 

(reproduced from NPS 2005, adapted from Lohman 1965) ..............................................................370

Figure 88. Emission levels of main greenhouse gases by RCPs.......................................................400

Figure 89. Key components of vulnerability, illustrating the relationship between 

exposure, sensitivity, and adaptive capacity (Source: Stein et al. 2011). ..........................................402

xvii

Tables

Page

Table 1. Population estimates for Mesa County and municipalities. Population estimates 

are as of July 2013 (DOLA 2015)..........................................................................................................9

Table 2. Projected changes in average annual temperature and precipitation compared to 

the baseline period of 1980-2009.........................................................................................................15

Table 3. The geology of COLM is rich in fossil-bearing sedimentary rock formations 

(recreated from Tweet et al. 2012).......................................................................................................22

Table 4. IEP species that have been detected in COLM. Priority species are in bold. .......................25

Table 5. NCPN Vital Signs selected for monitoring in COLM (O’Dell et al. 2005)..........................28

Table 6. Scale for a measure’s Significance Level in determining a components overall 

condition. .............................................................................................................................................43

Table 7. Scale for Condition Level of individual measures. ...............................................................43

Table 8. Description of symbology used for individual component assessments...............................44

Table 9. Scale for results of climate change vulnerability analysis. ...................................................51

Table 10. Scale for results of CCVA uncertainty analysis..................................................................52

Table 11. An example of certainty and alternative vulnerability scores for plant 

community assessment variables.........................................................................................................52

Table 12. Areal extent of pinyon-juniper woodland/savanna vegetation alliances found in 

COLM (Von Loh et al. 2007). .............................................................................................................61

Table 13. Dominant plant species (by strata) within the two-needle pinyon-(one-seed 

juniper, Utah juniper)/needle and thread woodlands of COLM (Von Loh et al. 2007).......................64

Table 14. Dominant plant species (by strata) within the two-needle pinyon-Utah 

juniper/Utah serviceberry woodlands (Von Loh et al. 2007)...............................................................64

Table 15. Dominant plant species (by strata) within the two-needle pinyon-Utah 

juniper/Bigelow’s sagebrush woodlands (Von Loh et al. 2007)..........................................................65

Table 16. Dominant plant species (by strata) within the two-needle pinyon-Utah 

juniper/black sagebrush woodlands in COLM (Von Loh et al. 2007).................................................65

Table 17. Dominant plant species (by strata) within the two-needle pinyon-juniper/ 

littleleaf mountain-mahogany woodlands in COLM (Von Loh et al. 2007)........................................66

Table 18. Dominant plant species (by strata) within the two-needle pinyon-Utah 

juniper/mixed shrubs talus woodlands in COLM (Von Loh et al. 2007). ...........................................66

Table 19. Dominant plant species (by strata) within the two-needle pinyon-Utah 

juniper/grassy rock-goldenrod woodlands (Von Loh et al. 2007). ......................................................67
xviii

Tables (continued)

Page

Table 20. Dominant plant species (by strata) within the two-needle pinyon pine-Utah 

juniper-juniper species/(Wyoming big sagebrush, mountain big sagebrush) woodlands of 

COLM (Von Loh et al. 2007). .............................................................................................................68

Table 21. Dominant plant species (by strata) within the two-needle pinyon-juniper 

species/mountain-mahogany-mixed shrub woodlands of COLM (Von Loh et al. 2007)....................69

Table 22. Dominant plant species (by strata) within the two-needle pinyon-juniper 

species/saline wildrye grass woodlands of COLM (Von Loh et al. 2007). .........................................69

Table 23. Dominant plant species (by strata) within the blue spruce-two-needle pinyonUtah juniper/Gambel’s oak woodlands in COLM (Von Loh et al. 2007). ..........................................70

Table 24. Approximate BSC cover for each COLM pinyon-juniper community (Von Loh 

et al. 2007) ...........................................................................................................................................71

Table 25. Approximate vegetative cover for each COLM pinyon-juniper community 

along with notes on ground surface conditions (Von Loh et al. 2007)................................................73

Table 26. Number and location of non-native species occurrences in relation to pinyonjuniper woodlands/savannas. ...............................................................................................................76

Table 27. Certainty and alternative vulnerability scores for woodland plant community 

assessment variables. ...........................................................................................................................87

Table 28. Areal extent of sagebrush shrublands/shrub steppe alliances found in COLM 

(Von Loh et al. 2007)...........................................................................................................................96

Table 29. Dominant plant species (by strata) within the black sagebrush and grasses 

shrubland-graminoids community of COLM (Von Loh et al. 2007)...................................................98

Table 30. Dominant plant species (by strata) within the basin big sagebrush/cheatgrass 

semi-natural shrubland community of COLM (Von Loh et al. 2007). ................................................99

Table 31. Dominant plant species (by strata) within the Wyoming big sagebrush/seeded 

grasses semi natural shrubland community of COLM (Von Loh et al. 2007)...................................100

Table 32. Dominant plant species (by strata) within the Wyoming big sagebrush 

shrubland community of COLM (Von Loh et al. 2007). ...................................................................101

Table 33. Number and location of non-native species occurrences in relation to 

sagebrush shrubland/shrub steppe......................................................................................................103

Table 34. Areal extent of alliances associated with riparian habitat/large dry washes 

within COLM (Von Loh et al. 2007). ................................................................................................116

Table 35. Number of species by riparian habitat / dry wash habitat associations within 

COLM (Von Loh et al. 2007). ...........................................................................................................123

Table 36. Comparison of results from the for the last three IEP surveys for riparian areas 

within COLM (Perkins 2009, 2012, 2014). .......................................................................................124
xix

Tables (continued)

Page

Table 37. Water temperature (°C) and specific conductance (μS/cm) field measurements 

from sampled seeps and springs in COLM (Butler et al. 2003, Lamm et al. 2014) ..........................137

Table 38. Water quality measurements for springs with detailed sample analysis by 

Butler et al. (2003) or Springer et al. (2006), along with field measurements from Lamm 

et al. (2014)........................................................................................................................................138

Table 39. Discharge measurements for surveyed COLM seep and spring sites. Values are 

given in lpm (with gpm in parentheses), unless otherwise noted. .....................................................140

Table 40. Certainty, vulnerability, and alternative vulnerability scores for seep, spring, 

and tinaja plant community assessment variables..............................................................................150

Table 41. Vegetation alliances found within the mixed salt desert scrub and semi-desert 

grassland plant associations of COLM (Von Loh et al. 2007)...........................................................154

Table 42. Areal extent of mixed salt desert scrub and semi-desert grassland vegetation 

associations found in COLM (Von Loh et al. 2007)..........................................................................156

Table 43. Dominant plant species (by strata) within the fourwing saltbush shrublands of 

COLM (Von Loh et al. 2007). ...........................................................................................................158

Table 44. Dominant plant species (by strata) within the fourwing saltbush - Mormon tea 

talus shrublands of COLM (Von Loh et al. 2007). ............................................................................159

Table 45. Dominant plant species (by strata) within the shadscale - black greasewood 

shrublands of COLM (Von Loh et al. 2007)......................................................................................159

Table 46. Dominant plant species (by strata) within the shadscale/James’ galetta 

shrublands of COLM (Von Loh et al. 2007)......................................................................................160

Table 47. Dominant plant species (by strata) within the plains prickly pear/James’ galetta 

shrublands of COLM (Von Loh et al. 2007)......................................................................................160

Table 48. Dominant plant species (by strata) within the cheatgrass semi-natural 

herbaceous vegetation community of COLM (Von Loh et al. 2007). ...............................................161

Table 49. Dominant plant species (by strata) within the western wheatgrass herbaceous 

vegetation community of COLM (Von Loh et al. 2007). ..................................................................162

Table 50. Dominant plant species (by strata) within the needle and thread Great Basin 

herbaceous vegetation community of COLM (Von Loh et al. 2007). ...............................................162

Table 51. Dominant plant species (by strata) within the James’ galleta herbaceous 

vegetation community of COLM (Von Loh et al. 2007). ..................................................................163

Table 52. Dominant plant species (by strata) within the Indian ricegrass-cheatgrass 

herbaceous vegetation community of COLM (Von Loh et al. 2007). ...............................................163

Table 53. Plant species within the two COLM hanging gardens surveyed in 2003..........................175
xx

Tables (continued)

Page

Table 54. Areal extent of montane shrubland alliances found in COLM (Von Loh et al. 

2007). .................................................................................................................................................182

Table 55. Dominant plant species (by strata) within the Gambel’s oak/skunkbush sumac 

woodlands of COLM (Von Loh et al. 2007)......................................................................................184

Table 56. Dominant plant species (by strata) within the littleleaf mountainmahogany/slickrock sparse vegetation community of COLM (Von Loh et al. 2007).......................185

Table 57. Dominant plant species (by strata) within the Utah serviceberry shrubland of 

COLM (Von Loh et al. 2007). ...........................................................................................................186

Table 58. Number and location of non-native species occurrences in relation to montane 

shrubland............................................................................................................................................188

Table 59. Amphibian species known to occur or unconfirmed at COLM (NPS 2014). ...................196

Table 60. Amphibians included in the NPS species list with abundance column (NPS 

2014). .................................................................................................................................................196

Table 61. Reptiles documented or expected to occur in COLM. ......................................................198

Table 62. Reptiles included in the NPS species list with abundance (NPS 2014). ...........................199

Table 63. The 10 breeding bird species observed in COLM during Giroir (2001)’s 

breeding bird point counts. ................................................................................................................212

Table 64. Raptor species identified on NPS (2015). .........................................................................226

Table 65. Raptor species observed during the Grand Junction CBC from 1922-2013. ....................228

Table 66. Raptor abundance observed in COLM in 2000 during Giroir (2001). n=number 

of individuals, k=number of transects a species was detected on......................................................229

Table 67. Average annual raptor abundance during the Grand Junction CBC from 1922-

1924, 1945, 1950, and 1952-2013......................................................................................................232

Table 68. Raptor species abundance during the last 5 years (2009-2013) of the Grand 

Junction CBC.....................................................................................................................................233

Table 69. Peregrine falcon productivity at three eyries in COLM, with values to the right 

of the dashed line representing productivity estimates observed by Lambeth (1996).......................234

Table 70. The species of small mammals, (excluding bats) that have been documented or 

may occur in COLM. .........................................................................................................................243

Table 71. General abundance information for small mammals in COLM........................................244

Table 72. General description of small mammal distributions relative to the parks area 

(Miller 1964)......................................................................................................................................245
xxi

Tables (continued)

Page

Table 73. Locations of historical mountain lion or track observations within COLM, 

1938-1962 (Miller 1964)....................................................................................................................255

Table 74. Mountain lion harvest in GMU 40, 2002-2013 (CPW 2014b). ........................................257

Table 75. Record of bighorn sheep translocations in the Black Ridge Unit (recreated 

from Duckett 2006)............................................................................................................................264

Table 76. Lamb:ewe ratios observed during helicopter surveys of the Black Ridge Unit 

bighorn sheep herd (Sloan 1995, Duckett 2006)................................................................................267

Table 77. Occurrence of bat species within COLM (Adams 1994; NPS 2014)................................281

Table 78. Number of individuals of each bat species captured in surveys by Adams 

(1989. 1993, 1994).............................................................................................................................281

Table 79. National Park Service Air Resources Division air quality index values for wet 

deposition of nitrogen or sulfur, ozone, particulate matter, and visibility (NPS 2015c). ..................289

Table 80. National Park Service Air Resources Division air quality assessment matrix for 

mercury status (NPS 2015c) ..............................................................................................................290

Table 81. Photometric statistics for the ML (Finger Lakes MicroLine model camera)

instrument data mosaic (reference set only) (Retrieved from NPS NSNSD 2014). ..........................319

Table 82. Photometric statistics for the anthropogenic sky glow mosaic (reference set 

only) (Retrieved from NPS NSNSD 2014)........................................................................................319

Table 83. Examples of sound levels measured in national parks......................................................340

Table 84. Explanation of sound level values, for reference (NPS 2013). .........................................343

Table 85. Median existing and natural ambient levels at the four sites (McFarland 2015). .............343

Table 86. Mean percent time audible for all extrinsic sounds, aircraft, and vehicles 

(McFarland 2015). .............................................................................................................................344

Table 87. Percent time above Table 84 reference values during the day (7 a.m. to 7 p.m.) 

and night (7 p.m. to 7 a.m.) (NPS 2013)............................................................................................345

Table 88. Median L50 values in each condition: natural, existing, and impact .................................346

Table 89. Stratigraphy, fossils, and depositional setting of COLM (table recreated from 

Tweet et al. 2012) ..............................................................................................................................354

Table 90. Relative potential, by formation, for fossil vertebrates in the COLM area 

(reproduced from Armstrong and Kihm 1980)..................................................................................360

Table 91. Erodibility of rock formations within COLM (recreated from KellerLynn 

2006) ..................................................................................................................................................361
xxii

Tables (continued)

Page

Table 92. Major geological formations (i.e., rock layers) within COLM (adapted from 

Tweet et al. 2012) ..............................................................................................................................372

Table 93. High and strong wind events in the Grand Valley/Grand Junction area, 1996-

2014 (NCDC 2015a)..........................................................................................................................377

Table 94. Heavy rain events in the area around COLM, 1996-2014 (NCDC 2015a).......................377

Table 95. Recurrence intervals for various 24-hour rainfall amounts at the COLM 

headquarters rain gauge, based on 1948-2002 precipitation data, as calculated by Richard 

(2004).................................................................................................................................................377

Table 96. Historical flash floods (1921-2003) in the COLM vicinity summarized by 

Richard (2004). KGJT = Grand Junction Airport..............................................................................379

Table 97. Flash flood events reported in the area around COLM, 1996-2014 (NCDC 

2015a) ................................................................................................................................................379

Table 98. Identified data gaps or needs for the featured components. ..............................................385

Table 99. Summary of current condition and condition trend for featured NRCA 

components. .......................................................................................................................................389

Table 100. Description of symbology used for individual component assessments.........................391

Table 101. Summary of plant community vulnerability to projected climate change 

(2050–2100) at COLM. .....................................................................................................................395
xxiii

Photos

Page

Photo 1. Rim Rock Drive (NPS photo). ..............................................................................................16

Photo 2. The layers of sedimentary rock are exposed by erosional forces along many 

parts of Rim Rock Drive in the park; each horizontal layer represents a period of 

deposition through geologic time (Photo by Anna Davis, SMUMN GSS). ........................................20

Photo 3. A coyote at COLM (NPS photo)...........................................................................................22

Photo 4. An example of an open-canopy pinyon-juniper woodland/savanna upon a mesa 

top in COLM (Photo by Anna Davis, SMUMN GSS). .......................................................................58

Photo 5. Big Sagebrush (Artemisia tridentata) (NPS Photo)..............................................................93

Photo 6. The riparian habitat shown in this canyon bottom is discernable from the 

surrounding vegetation and grows along a large dry wash (Photo by Anna Davis, 

SMUMN GSS 2013)..........................................................................................................................112

Photo 7. A seep-fed pool in No Thoroughfare Canyon (left) and riparian vegetation at 

Lost Lunch Spring in Ute Canyon (Photos from Lamm et al. 2014).................................................131

Photo 8. Fourwing saltbush (NPS Photo)..........................................................................................154

Photo 9. Hanging gardens on a vertical canyon wall in COLM (Photo by Shannon 

Amberg, SMUMN GSS, 2013)..........................................................................................................172

Photo 10. Graffiti on COLM’s canyon walls (NPS photo). ..............................................................176

Photo 11. Gambel’s oak/skunkbush shubland at COLM (Von Loh et al. 2007 Photo). ...................180

Photo 12. The eastern collared lizard is one of several lizard species that inhabit the park 

(NPS Photo by Lynne Mager)............................................................................................................194

Photo 13. Gambel's quail (Callipepla gambelii) (NPS photo). .........................................................207

Photo 14. Peregrine falcon (USFWS Photo). ....................................................................................222

Photo 15. Desert cottontail (top) (Anna Davis, SMUMN GSS), Ord’s kangaroo rat 

(middle), and deer mouse (bottom) are all examples of small mammals found in COLM 

(NPS Photos)......................................................................................................................................241

Photo 16. Mountain lion (NPS photo)...............................................................................................252

Photo 17. Two desert bighorn rams at COLM (NPS photo). ............................................................261

Photo 18. Desert kit fox (V. macrotis arsipus) (NPS Photo). ...........................................................271

Photo 19. Big brown bat (Eptesicus fuscus) (Photo by Dr. Lloyd Glenn Ingles, California 

Academy of Sciences)........................................................................................................................279

Photo 20. View of COLM cliffs, canyons, and monoliths from Book Cliff (Photo by 

Shannon Amberg, SMUMN GSS).....................................................................................................323
xxiv

Photos (continued)

Page

Photo 21. View of Independence Monolith from the Independence Monument Overlook 

observation point, looking east (Photo by Shannon Amberg, SMUMN GSS)..................................326

Photo 22. View from Grand View Overlook observation point, looking north (top) and 

east (bottom) (Photos by Shannon Amberg, SMUMN GSS). ...........................................................328

Photo 23. View from Coke Ovens Overlook observation point, looking northeast (top) 

(Photo by Anna Davis, SMUMN GSS) and southeast (bottom) (Photo by Shannon 

Amberg, SMUMN GSS)....................................................................................................................329

Photo 24. View of Artist Point Overlook observation point, looking northeast (Photo by 

Shannon Amberg, SMUMN GSS).....................................................................................................330

Photo 25. View of Upper Ute Canyon Overlook observation point, looking northeast 

(Photo by Anna Davis, SMUMN GSS). ............................................................................................330

Photo 26. View of Fallen Rock Overlook observation point, looking southwest (Photo by 

Shannon Amberg, SMUMN GSS).....................................................................................................331

Photo 27. View of Red Canyon Overlook observation point, looking northeast (Photo by 

Anna Davis, SMUMN GSS)..............................................................................................................331

Photo 28. View of Cold Shiver Point Overlook observation point, looking northwest 

(top) and northeast (bottom) (Photos by Anna Davis, SMUMN GSS). ............................................332

Photo 29. Radio towers on Black Ridge just west of the park (Photo by Shannon 

Amberg, SMUMN GSS, Winter 2013)..............................................................................................336

Photo 30. Inversion in Fruita just northeast of the park (Photo by Anna Davis, SMUMN 

GSS, Winter 2013).............................................................................................................................336

Photo 31. Three-toed dinosaur track from COLM (NPS photo).......................................................353

Photo 32. Lizard tracks on Morrison Formation sandstone (NPS photo). ........................................356

Photo 33. Geological features in COLM include Window Rock (top) and Coke Ovens 

(bottom) (NPS photos).......................................................................................................................369

Photo 34. Independence Monument (photo by Anna Davis, SMUMN GSS)...................................369

Photo 35. The characteristic red color of the Chinle Formation (NPS photo). .................................370

Photo 36. Devils Kitchen in No Thoroughfare Canyon is an example of remnant Wingate 

sandstone capped and protected from erosion by the Kayenta Formation (USGS photo by 

T. F. Giles, from Lohman 1981). .......................................................................................................371

Photo 37. The Morrison Formation, exposed at the mouth of No Thouroughfare Canyon 

(photo from Lohman 1981)................................................................................................................373

Photo 38. A large slab of fallen rock in Ute Canyon, with slopes of sand and debris at the 

base of the canyon walls (photo from Lohman 1981). ......................................................................374
xxv

Photos (continued)

Page

Photo 39. Rock fall onto Rim Rock Drive in January 2000 (NPS photo by Ron Young). ...............376

Photo 40. Section of Rim Rock Drive washed out by flooding above the west entrance in 

August 1968 (NPS photo)..................................................................................................................380

Photo 41. Wash-out along Monument Road on 7 September 1978 (Photo by Jim 

Johnson, from Richard 2004).............................................................................................................380

xxvii

Appendices

Page

Appendix A. Overview of climate change vulnerability assessments..............................................399

Appendix B. Pinyon-juniper woodland/savanna community composition by 

association/alliances and growth habitat based on vegetation mapping project 

classification descriptions (Von Loh et al. 2007). .............................................................................405

Appendix C. Pinyon-juniper woodland community climate vulnerability scoring 

worksheet ...........................................................................................................................................411

Appendix D. Sagebrush shrubland/shrub steppe community composition and growth 

habitat based on Hogan et al. (2009) comprehensive list of plant species.........................................413

Appendix E. Riparian habitat/large dry wash community dominant species composition 

by growth habitat based on vegetation mapping project classification descriptions (Von 

Loh et al. 2007)..................................................................................................................................425

Appendix F. Seeps and springs community composition at No Thoroughfare and Lower 

Echo Canyon springs inventoried by Springer et al. (2006). .............................................................429

Appendix G. Seeps and springs community composition by canyon, as documented by 

Lamm et al. (2014).............................................................................................................................431

Appendix H. Seep, spring, tinaja habitats climate vulnerability scoring worksheet. .......................437

Appendix I. Montane shrubland and growth habitat based on Hogan et al. (2009) 

comprehensive list of plant species....................................................................................................439

Appendix J. Bird species observed in COLM during monitoring and survey efforts. .....................445

Appendix K. Annotated list of species-related name changes and adjustments made by 

SMUMN GSS to the Grand Junction CBC data................................................................................453

xxix

Executive Summary

The Natural Resource Condition Assessment (NRCA) Program aims to provide documentation about 

the current conditions of important park natural resources through a spatially explicit, multidisciplinary synthesis of existing scientific data and knowledge. Findings from the NRCA will help 

Colorado National Monument (COLM) managers to develop near-term management priorities, 

engage in watershed- or landscape-scale partnership and education efforts, conduct park planning, 

and report program performance (e.g., Department of the Interior’s Strategic Plan “land health” 

goals, Government Performance and Results Act).

The objectives of this assessment are to evaluate and report on current conditions of key park 

resources, to evaluate critical data and knowledge gaps, and to highlight selected existing stressors 

and emerging threats to resources or processes. For the purpose of this NRCA, staff from the 

National Park Service (NPS) and Saint Mary’s University of Minnesota – GeoSpatial Services 

(SMUMN GSS) identified key resources, referred to as “components” in the project. The selected 

components include natural resources and processes that are currently of the greatest concern to park 

management at COLM. The final project framework contains 21 resource components, each 

featuring discussions of measures, stressors, and reference conditions.

This study involved reviewing existing literature and, where appropriate, analyzing data for each 

natural resource component in the framework to provide summaries of current condition and trends 

in selected resources. When possible, existing data for the established measures of each component 

were analyzed and compared to designated reference conditions. A weighted scoring system was 

applied to calculate the current condition of each component. Weighted Condition Scores, ranging 

from zero to one, were divided into three categories of condition: low concern, moderate concern, 

and significant concern. These scores help to determine the current overall condition of each 

resource. The discussions for each component, found in Chapter 4 of this report, represent a 

comprehensive summary of current available data and information for these resources, including 

unpublished park information and perspectives of park resource managers, and present a current 

condition designation when appropriate. Each component assessment was reviewed by COLM 

resource managers, NPS Northern Colorado Plateau Network staff, or outside experts.

Existing literature, short- and long-term datasets, and input from NPS and other outside agency 

scientists support condition designations for components in this assessment. However, in some cases, 

data were unavailable or insufficient for several of the measures of the featured components. In other 

instances, data establishing reference condition were limited or unavailable for components, making 

comparisons with current information inappropriate or invalid. In these cases, it was not possible to 

assign condition for the components. Current condition was not able to be determined for nine of the 

21 components (43%) due to these data gaps.

For those components with sufficient available data, the overall condition varied. Only two 

components (riparian habitats/large dry washes and bighorn sheep) were determined to be in good 

condition. Five components (pinyon-juniper woodlands/savannas, seeps, springs and tinaja habitats, 

birds, air quality and paleontological resources) were of moderate concern. Birds were the only 
xxx

component where the available data were sufficient enough to assign a trend. At this time, the bird 

community exhibits a stable trend. Three components were determined to be of significant concern 

(kit fox, dark night skies, and viewscape). The high concern for kit fox was due to the species likely 

being extirpated from the region; as it is unlikely to return on its own, a stable trend was assigned. 

The remaining two components of significant concern (dark night skies and viewscape) are strongly 

influenced by urban land uses and other anthropogenic factors outside of NPS control. While they are 

currently exhibiting deteriorating trends, there is little that NPS managers can do to mitigate these 

trends. Detailed discussion of these designations is presented in Chapters 4 and 5 of this report.

Several park-wide threats and stressors influence the condition of priority resources in COLM. Those 

of primary concern include invasive exotic plant (IEP) species, regional climate change, and drought. 

Understanding these threats, and how they relate to the condition of park resources, can help the NPS 

prioritize management objectives and better focus their efforts to maintain the health and integrity of 

the park ecosystem.
xxxi

Acknowledgments 

We acknowledge Colorado National Monument staff for the technical expertise provided during 

scoping, through multiple stages of review, and via phone and email; specifically, Ken Mabery 

COLM Superintendent and Kim Hartwig COLM Chief of Resources Management. Northern 

Colorado Plateau Inventory and Monitoring Network staff, including Dusty Perkins (Program 

Manager) and Dana Witwicki (Vegetation Ecologist), offered logistical insight and critical review of 

interim documents. Additional program guidance and reviews were provided by Donna Shorrock, 

Intermountain Region NRCA Coordinator, and Jeff Albright, Natural Resource Condition 

Assessment Coordinator. Thank you to all others who assisted the development of this document.

xxxiii

Acronyms and Abbreviations

AET – Actual Evapotranspiration

AQI – Air Quality Index

ARD – Air Resources Division

BCSD – Bias Correction followed by Spatial Disaggregation

BLM – Bureau of Land Management

BPP – Bird Phenology Program

BPU – Biophysical Unit

BSC – Biological Soil Crust

CAA – Clean Air Act

CBC – Christmas Bird Count

CBS – Colorado Bat Society

CCD – Charge-coupled Device 

CCRP – Climate Change Response Program

CCVA – Climate Change Vulnerability Assessment

CNM – Colorado National Monument

COLM – Colorado National Monument

CPW – Colorado Parks and Wildlife

CSU – Colorado State University

DAU – Data Analysis Unit

dB – Decibel

dBA – Weighted Decibels

DEM – Digital Elevation Model

DO – Dissolved Oxygen

dv – Deciviews

EC – Emerging Contaminant
xxxiv

Acronyms and Abbreviations (continued)

EDC – Endocrine-disrupting Chemicals

EPA – Environmental Protection Agency

ET – Evapotranspiration

FAA – Federal Aviation Administration

GCM – General Circulation Model

GIS – Geographic Information System

GMU – Game Management Unit

gpm – Gallons Per Minute

GPRA – Government Performance and Results Act

GPS – Global Positioning System

Hg – Mercury

Hz – Hertz

I&M – Natural Resources Inventory & Monitoring

IBA – Important Bird Area

IEP – Invasive Exotic Plant

IMPROVE – Interagency Monitoring of Protected Visual Environments Program

IPCC – Intergovernmental Panel on Climate Change

IRMA – Integrated Resource Management Application

KGJT – Grand Junction Regional Airport

L50 – Median Existing Sound Levels

LEC – Lower Echo Canyon

Lnat – Median Natural Ambient Sound Levels

lpm – Liters Per Minute

LPR – Light Pollution Ratio

MCL – Maximum Contaminant Level
xxxv

Acronyms and Abbreviations (continued)

MDS – Mercury Deposition Network

MDTS – Minimum Detection Target Size

MMU – Minimum Mapping Unit

mya – Million Years Ago

N – Nitrogen

NAAQS – National Ambient Quality Standard

NADP – National Atmospheric Deposition Program

NAS – National Audubon Society

NCCSC – North Central Climate Science Center

NCDC – National Climatic Data Center

NCPN – Northern Colorado Plateau Network

NED – National Elevation Dataset

NO3 – Nitrate

NOx – Nitrogen Oxides

NPS – National Park Service

NRCA – Natural Resource Condition Assessment

NSNSD – Natural Sounds and Night Skies Division

NTC – No Thoroughfare Canyon

NTN – National Trends Network

NVC – National Vegetation Classification

NWS – National Weather Service

O3 – Ozone

PET – Potential Evapotranspiration

PI – Principle Investigator

PIT – Passive Integrated Tag
xxxvi

Acronyms and Abbreviations (continued)

P-J – Pinyon-Juniper

PM – Particulate Matter

POMS – Portable Ozone Monitoring Station

ppb – Parts Per Billion

ppm – Parts Per Million

RCP – Representative Concentration Pathway

RMBO – Rocky Mountain Bird Observatory

SC – Specific Conductance

SCPN – Southern Colorado Plateau Network

SL – Significance Level

SMUMN GSS – Saint Mary's University of Minnesota, GeoSpatial Services

SPL – Sound Pressure Level

SRES – Special Report on Emissions Scenarios

TNC – The Nature Conservancy

USFS – United States Forest Service

USGS – United States Geological Survey

UV-B – Ultraviolet B

VES – Visual Encounter Surveys

VOC – Volatile Organic Compound

WCS – Weighted Condition Score

WHO – World Health Organization

WNS – White-nose Syndrome

WRD – Water Resources Division

ZLM – Zenithal Limiting Magnitude
1

1. NRCA Background Information

Natural Resource Condition Assessments (NRCAs) evaluate current conditions for a subset of 

natural resources and resource indicators in national park units, hereafter “parks.” NRCAs also report 

on trends in resource condition (when possible), identify critical data gaps, and characterize a general 

level of confidence for study findings. The resources and indicators emphasized in a given project 

depend on the park’s resource setting, status of resource stewardship planning and science in 

identifying high-priority indicators, and availability of data and expertise to assess current conditions 

for a variety of potential study 

resources and indicators. 

NRCAs represent a relatively new 

approach to assessing and 

reporting on park resource 

conditions. They are meant to 

complement—not replace—

traditional issue-and threat-based 

resource assessments. As distinguishing characteristics, all NRCAs:

 Are multi-disciplinary in scope;1

 Employ hierarchical indicator frameworks;2

 Identify or develop reference conditions/values for comparison against current conditions;3

 Emphasize spatial evaluation of conditions and Geographic Information System (GIS) products;4

 Summarize key findings by park areas; 5and 

 Follow national NRCA guidelines and standards for study design and reporting products. 

Although the primary objective of NRCAs is to report on current conditions relative to logical forms 

of reference conditions and values, NRCAs also report on trends, when appropriate (i.e., when the 

underlying data and methods support such reporting), as well as influences on resource conditions. 

These influences may include past activities or conditions that provide a helpful context for 

The breadth of natural resources and number/type of indicators evaluated will vary by park. 

2 Frameworks help guide a multi-disciplinary selection of indicators and subsequent “roll up” and reporting of data for measures 

 conditions for indicators  condition summaries by broader topics and park areas 

3 NRCAs must consider ecologically-based reference conditions, must also consider applicable legal and regulatory standards, 

and can consider other management-specified condition objectives or targets; each study indicator can be evaluated against one 

or more types of logical reference conditions. Reference values can be expressed in qualitative to quantitative terms, as a single 

value or range of values; they represent desirable resource conditions or, alternatively, condition states that we wish to avoid or 

that require a follow-up response (e.g., ecological thresholds or management “triggers”).

4 As possible and appropriate, NRCAs describe condition gradients or differences across a park for important natural resources 

and study indicators through a set of GIS coverages and map products. 

5

In addition to reporting on indicator-level conditions, investigators are asked to take a bigger picture (more holistic) view and 

summarize overall findings and provide suggestions to managers on an area-by-area basis: 1) by park ecosystem/habitat types or 

watersheds, and 2) for other park areas as requested.

NRCAs Strive to Provide...

 Credible condition reporting for a subset of 

important park natural resources and indicators

 Useful condition summaries by broader resource 

categories or topics, and by park areas
2

understanding current conditions, and/or present-day threats and stressors that are best interpreted at 

park, watershed, or landscape scales (though NRCAs do not report on condition status for land areas 

and natural resources beyond park boundaries). Intensive cause-and-effect analyses of threats and 

stressors, and development of detailed treatment options, are outside the scope of NRCAs. 

Due to their modest funding, relatively quick timeframe for completion, and reliance on existing data 

and information, NRCAs are not intended to be exhaustive. Their methodology typically involves an 

informal synthesis of scientific data and information from multiple and diverse sources. Level of 

rigor and statistical repeatability will vary by resource or indicator, reflecting differences in existing 

data and knowledge bases across the varied study components. 

The credibility of NRCA results is derived from the data, methods, and reference values used in the 

project work, which are designed to be appropriate for the stated purpose of the project, as well as 

adequately documented. For each study indicator for which current condition or trend is reported, we

will identify critical data gaps and describe the level of confidence in at least qualitative terms. 

Involvement of park staff and National Park Service (NPS) subject-matter experts at critical points 

during the project timeline is also important. These staff will be asked to assist with the selection of 

study indicators; recommend data sets, methods, and reference conditions and values; and help 

provide a multi-disciplinary review of draft study findings and products.

NRCAs can yield new insights about current park resource conditions, but, in many cases, their 

greatest value may be the development of useful documentation regarding known or suspected 

resource conditions within parks. Reporting products can help park managers as they think about 

near-term workload priorities, frame data and study needs for important park resources, and 

communicate messages about current park resource conditions to various audiences. A successful 

NRCA delivers science-based information that is both credible and has practical uses for a variety of 

park decision making, planning, and partnership activities.

However, it is important to note that NRCAs do not establish management targets for study 

indicators. That process must occur through park planning and management activities. What an 

NRCA can do is deliver science-based information that will assist park managers in their ongoing, 

long-term efforts to describe and quantify a park’s desired resource conditions and management 

Important NRCA Success Factors

 Obtaining good input from park staff and other NPS subject-matter experts at 

critical points in the project timeline 

 Using study frameworks that accommodate meaningful condition reporting at 

multiple levels (measures  indicators  broader resource topics and park 

areas)

 Building credibility by clearly documenting the data and methods used, critical 

data gaps, and level of confidence for indicator-level condition findings
3

targets. In the near term, NRCA findings assist strategic park resource planning6 and help parks to 

report on government accountability measures.7In addition, although in-depth analysis of the effects 

of climate change on park natural resources is outside the scope of NRCAs, the condition analyses 

and data sets developed for NRCAs will be useful for park-level climate-change studies and planning 

efforts.

NRCAs also provide a useful complement to rigorous NPS science support programs, such as the 

NPS Natural Resources Inventory & Monitoring (I&M) Program.8 For example, NRCAs can provide 

current condition estimates and help establish reference conditions, or baseline values, for some of a 

park’s vital signs monitoring indicators. They can also draw upon non-NPS data to help evaluate 

current conditions for those same vital signs. In some cases, I&M data sets are incorporated into 

NRCA analyses and reporting products. 

Over the next several years, the NPS plans to fund an NRCA project for each of the approximately 

270 parks served by the NPS I&M Program. For more information visit the NRCA Program website.

6An NRCA can be useful during the development of a park’s Resource Stewardship Strategy (RSS) and can also be tailored to act 

as a post-RSS project.

7 While accountability reporting measures are subject to change, the spatial and reference-based condition data provided by 

NRCAs will be useful for most forms of “resource condition status” reporting as may be required by the NPS, the Department 

of the Interior, or the Office of Management and Budget. 

8 The I&M program consists of 32 networks nationwide that are implementing “vital signs” monitoring in order to assess the 

condition of park ecosystems and develop a stronger scientific basis for stewardship and management of natural resources 

across the National Park System. “Vital signs” are a subset of physical, chemical, and biological elements and processes of park 

ecosystems that are selected to represent the overall health or condition of park resources, known or hypothesized effects of 

stressors, or elements that have important human values.

NRCA Reporting Products...

Provide a credible, snapshot-in-time evaluation for a subset of important park 

natural resources and indicators, to help park managers:

 Direct limited staff and funding resources to park areas and natural resources that 

represent high need and/or high opportunity situations 

(near-term operational planning and management)

 Improve understanding and quantification for desired conditions for the park’s 

“fundamental” and “other important” natural resources and values

(longer-term strategic planning)

 Communicate succinct messages regarding current resource conditions to 

government program managers, to Congress, and to the general public 

(“resource condition status” reporting) 

5

2. Introduction and Resource Setting

2.1 Introduction 

2.1.1 Enabling Legislation

Colorado National Monument (COLM) was officially established on 24 May 1911 by President 

William Taft. The presidential proclamation (1126) stated the following:

Whereas, in Mesa County, Colorado, the extraordinary examples of erosion are of 

great scientific interest, and it appears that the public interest would be promoted by 

reserving these natural formations as a National Monument, together with as much 

public land as may be necessary for the proper protection thereof (LOC 1913, 

p.1681).

The area that eventually became COLM was originally included as part of the 1868 Colorado 

Ute Reservation Treaty (NPS 2005). The area was ceded in 1880 when the Utes were 

relocated to Utah, and settlers began to arrive and stake agricultural claims in the Grand 

Valley (NPS 2005). The area came under the management of the NPS with the initial 

designation of approximately 5,598 ha (13,883 ac) as a National Monument (LOC 1913). 

Over the years, COLM has undergone several boundary changes, with the most recent 

expansion in 1978 bringing the park to its current size of 8,310 ha (20,534 ac) (NPS 2005, 

NPS 2014a).

2.1.2 Geographic Setting

Geophysical Setting

COLM is located in northwestern Mesa County in western Colorado, near the border of Utah 

(Figure 1). It is situated on the northeastern portion of the Uncompahgre Plateau, near the 

northern tip of this formation (Tweet et al. 2012). The majority of the park is composed of a 

series of canyons and mesas formed by ephemeral streams draining into the Colorado River 

(Figure 2) (Tweet et al. 2012). Elevations within the park range from 1,408 m (4,620 ft) at 

the foot of the cliffs, to 2,166 m (7,107 ft) on the mesa tops (NPS 2004). Among the many 

canyons, Monument Canyon comprises much of the northern portion of COLM, and the 

entire southeastern portion includes much of No Thoroughfare Canyon (Figure 2). The area 

along the northeastern border of COLM is referred to as the Redlands, due to the color of the 

rocks (Tweet et al. 2012). The communities of Grand Junction and Fruita are located to the 

east and north of the park and are separated by the Colorado River, while Glade Park is 

located to the southwest (Figure 3). The latest census figures estimating the populations of 

Grand Junction, Fruita, and Mesa County are given in Table 1.
6

Figure 1. General location of COLM.
7

Figure 2. Canyons and ephemeral stream network at COLM.
8

Figure 3. Communities located in proximity to COLM.
9

Table 1. Population estimates for Mesa County and municipalities. Population estimates are as of July 

2013 (DOLA 2015).

Area Population Estimate

Mesa County 147,811

Fruita 12,615

Grand Junction 61,212

COLM has a semi-desert upland climate characterized by very hot and dry summers and cold, dry 

winters (NPS 2005). Precipitation is evenly distributed throughout the year with small peaks in the 

spring, late summer and early fall (Figure 4). Average monthly precipitation is 2.47 cm (0.95 in) with 

approximately 28.9 cm (11.4 in) precipitation annually (1981-2010 period; WRCC 2015). The 

average snow depth during the winter is 2.5 cm (1 in) with a total annual snowfall of 84.6 cm (33.3 

in), with the heaviest accumulations usually occurring in January (NPS 2005).

Daily temperatures vary from season to season with highs above 35 °C (90 °F) in the summer to 

winter lows that can drop below freezing (WRCC 2015). Annual average daily maximum 

temperature is 18.2 °C (64.7 °F) and the average minimum temperature is 6.2 °C (43.2 °F) (Figure 5) 

(WRCC 2015).

Figure 4. Average monthly precipitation for the period 1981-2010 for the COLM weather station (Station 

ID 051772) (WRCC 2015).

0

1

2

3

4

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Average Precipitation (cm)
10

Figure 5. Monthly temperature for the period 1981-2010 for the COLM weather station (Station ID

051772) (WRCC 2015).

Historical Climate Trends (1895-2012)

COLM is located in the semi-arid Southwest, one of the driest and hottest regions in the United 

States (Garfin et al. 2014). Water is typically scarce and its availability has defined the landscape 

(Garfin et al. 2014). This scarcity of water also limits plant growth (Running et al. 2004). Because 

water is such a key driver of natural and production systems, descriptions of climate variability that 

are associated with drought or aridity are of particular interest. The growth and vigor of vegetation 

influences physical processes such as erosion and the dynamics of native and domestic animals. 

These are key processes to management, and to the evaluation of climate change vulnerability.

Large areas of the central and western United States experienced severe droughts in the 1930s, 

1950s, and late 1990s to about 2004 (Woodhouse and Overpeck 1998, Cook et al. 2004). While these 

recent droughts persisted for multiple years and had profound effects on natural ecosystems and on 

agricultural production, over recent millennia, records reveal sustained droughts that persisted for 

decades (Woodhouse and Overpeck 1998, Cook et al. 2004, Meko et al. 2007, Cook et al. 2010, 

Routson et al. 2011). These decades-long droughts affected ecological processes such as broad 

patterns of fire (Brown et al. 2004), and they emphasize the vulnerability of the region to 

precipitation deficits. Projections of future climates including higher temperatures and increased 

evapotranspiration rates or changes in precipitation that change soil water availability are particularly 

important in climate analyses in this NRCA.

The climate at any location is determined by factors that operate at multiple spatial scales. At a 

global scale, the Earth has experienced a general warming trend over the past century, closely 

correlated with increases in the greenhouse gas CO2 (Figure 6) (Walsh et al. 2014). Global patterns 

of warming are modified by very broad-scale teleconnections, regional and local conditions, and the 

degree of warming or cooling varies geographically. Mote and Redmond (2012) provide a clear and 

-10

-5

0

5

10

15

20

25

30

35

40

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Temperature (oC) 

Maximum Temperature

Mean Temperature

Minimum Temperature
11

comprehensive review and evaluation of climate drivers at local to global scales with a focus on the 

western United States.

Figure 6. Annual average temperature measured over all the Earth’s land and ocean surfaces. Red and 

blue bars indicate years with temperatures above and below the 1901-2000 average, and the black line is 

the trend in atmospheric CO2 concentration. Figure from Walsh et al. (2014).

Recent historical climate patterns for COLM were evaluated using PRISM gridded climate data. 

These data are produced by the PRISM climate group at Oregon State University (Daly et al. 2002, 

PRISM 2015), and the analysis was completed by the North Central Climate Science Center 

(NCCSC). Over the period 1895-2010, the PRISM data exhibited a trend towards warming for both 

maximum (Tmax) and minimum (Tmin) average annual temperature, and a decline in average 

monthly precipitation (Figure 7A, B). The linear warming trends are 0.8 °C (1.4 °F) per century for 

Tmax and 0.7 °C (1.3 °F) per century for Tmin (NCCSC 2015)1. These trends were determined to be 

statistically significant, with p-values of 0.0003 and 0.0004 respectively (NCCSC 2015). Annual

precipitation exhibited a -2.4% per century decline, though it was determined to not be statistically 

significant (Figure 7C, NCCSC 2015). Another analysis shows that summer conditions over the past 

10-30 years, on average, were warmer than 95% of the historical range of conditions going back to 

1901 at the park (Monahan and Fisichelli 2014).

 

1 A change in temperature of 1 °C = a change of 1.8 °F
12

Figure 7. Trends in (A) maximum monthly temperature, (B) minimum monthly temperature, and (C) 

annual precipitation for COLM. The linear regressions for Tmax and Tmin were significant (P < 0.001). 

The dark blue line is the calculated 10-year rolling average and the light blue line is the linear trend. Data 

analysis provided by NCCSC (2015).

Projected Climate Trends (2050 and 2100)

Across the Southwest Region, the annual average temperature is projected to rise by 1.4 °C to 3.1 °C 

(2.5 °F to 5.5 °F) by 2040-2070 and by 3.1 °C to 5.3 °C (5.5 °F to 9.5 °F) by 2070-2100 under the 

high greenhouse gas emissions (“business as usual”) pathway, Representative Concentration Pathway 

(RCP) 8.5 (Garfin et al. 2014). Temperatures are projected to have greater increases in the summer 

and fall (Garfin et al. 2014). Under an emissions pathway with a substantial reduction in global 

emissions after mid-century (RCP 4.5), projected temperature increases are somewhat lower with a 
13

1.4 °C to 2.5 °C (2.5 °F to 4.5 °F) increase by 2040-2070 and a 1.9 °C to 3.1 °C (3.5 °F to 5.5 °F) 

increase by 2070-2100 (Garfin et al. 2014). In general, precipitation is projected to increase, but there 

is considerable variation in projections and confidence in precipitation projections is much lower 

than for temperature projections (Garfin et al. 2014).

For COLM, climate models project an increase in annual temperature and projections for all RCPs 

are indistinguishable until after about 2050, illustrating the ‘commitment’ to continuing climate 

change over the coming decades regardless of emissions pathway (Figure 8A). Average annual 

temperature is projected to increase 1.6 °C (2.9 °F) by 2030 with a 5.7 °C (10.2 °F) increase by the 

end of the century under RCP 8.5 (NCCSC 2015). This can be compared to a 0.5 °C (0.9 °F) increase 

over the period of 1980-2009 (NCCSC 2015). Precipitation at COLM is generally projected to 

slightly increase, but there is considerable variation in the projections (Figure 8B). While confidence 

in projections of seasonal or total precipitaiton is low, the models consistently project increased 

variation in both seasonal and annual precipitation. Such enhanced variation in the precipitation 

regime may manifest as both wetter and drier conditions, including heavier rain events and longer 

droughts (Melillo et al. 2014). Average monthly precipitation for COLM is projected to increase by 

2.5 mm (0.1 in) by 2020 and by 3.6 mm (0.14 in) by 2080 (NCCSC 2015). Projected change in 

temperature and precipitation under various RCPs is given in Table 2. Precipitation changes 

projected by the climate models reflect the general tendency for warmer climates to generate 

convection storms, and the projections overall suggest that the warmer seasons – spring and summer 

– are likely to experience an average increase in precipitation. The climate data used in these 

analyses provided no information on patterns of precipitation (e.g., drizzles vs. thunderstorms), but 

general predictions are for more temperature extremes and associated weather (Diffenbaugh and 

Ashfaq 2010, IPCC 2011, Gonzales 2013).

Overall, the climate is likely to be much hotter and plant-available moisture will likely decline due to 

changes in evapotranspiration. Evapotranspiration (ET) is the amount of moisture returned to the 

atmosphere through the combination of evaporation and plant transpiration. Climate scientists are 

concerned with two aspects of ET: actual evapotranspiration (AET) and potential evapotranspiration 

(PET). As its name suggests, AET is the amount of evapotranspiration that is actually occurring. PET 

is “a measure of the ability of the atmosphere to remove water from the surface” (Cowell and Urban 

2010, p. 741). Higher temperatures will drive greater rates of evapotranspiration, thus even with an 

increase in precipitation, soil water levels are projected to decrease (Cowell and Urban 2010). By the 

end of the 21st century, Cowell and Urban (2010) project an increase in PET of 227 mm (8.9 in) for 

the Colorado River Basin region. The projected increase in PET for the Colorado River Basin region 

is nearly 10 times the projected increase in precipitation, resulting in a huge increase (176 mm [6.9 

in]) in soil water deficit (Cowell and Urban 2010).

The ratio of AET to PET is used as an ‘aridity index’ that indicates the amount of moisture available 

to plants (Evan Girvetz, The Nature Conservancy (TNC), Senior Scientist, e-mail communication, 7 

June 2011). For example, a 0.15 decrease in this ratio can be interpreted as a 15% increase in aridity, 

or 15% less moisture available for plants (Girvetz, e-mail communication, 8 June 2011). While 

aridity is not expected to change much during the winter and summer, projections for the COLM 
14

region overall indicate an 8-13% increase in aridity (from a 1960-1990 reference period) during the 

fall and spring by 2050 (ClimateWizard 2014). By 2100, aridity is projected to increase by 

approximately 13-17% in the fall and spring under RCP 8.5 (ClimateWizard 2014).

Figure 8. Projected (A) average annual temperature and (B) total annual precipitation from a suite of 

models, driven by RCP scenarios. The solid line represents the mean of the models and shaded area 

represents the 25 and 75% quartiles. Data analysis was conducted by NCCSC (2015).
15

Table 2. Projected changes in average annual temperature and precipitation compared to the baseline 

period of 1980-2009. The value represents the mean for all available model predictions for each RCP. 

Data analysis was conducted by NCCSC (2015).

Year

Change in Temperature

(°C)

Change in Precipitation

(Average mm/month)

RCP 4.5 RCP 6.0 RCP 8.5 RCP 4.5 RCP 6.0 RCP 8.5

1980 to 2009 0.52 3.33

2020 1.55 1.53 1.62 2.57 2.39 2.48

2040 2.34 2.17 2.77 2.73 2.73 2.76

2060 2.95 3.03 4.16 2.95 2.72 3.49

2080 3.37 3.97 5.68 3.22 3.6 3.6

To summarize, models are very consistent in projecting a much warmer climate for COLM. 

Projections of trends in the amount of precipitation are much less certain, but the overall warming 

trend is very likely to result in greater seasonal and annual variation in the amount of precipitation. 

Projected combinations of higher temperatures, little or no increase in the amount of precipitation, 

and increased variation in rainfall, will very likely result in more frequent short-term and multi-year 

droughts.

2.1.3 Visitation Statistics

From 2010 to 2014, COLM received nearly 430,000 recreational visitors per year on average, with 

most visitations occurring between May and September (NPS 2015c). During this 5-year period,

visitation peaked in 2012 with a record 454,510 recreational visitors (NPS 2015c, Kim Hartwig, 

COLM Chief of Resources Management, written communication, 30 January 2016). In 2014, COLM

received nearly 417,000 visitors, which was slightly below average over the latest 5-year period 

(NPS 2015c). Visitation in 2015 set new records for total visitors (recreational and non-recreational) 

and recreational visitors (Hartwig, written communication, 30 January 2016). Overall 919,835 people 

visited the park in 2015, with 588,006 being recreational visitors (Hartwig, written communication, 

30 January 2016). Under the current method for collecting and analyzing visitation numbers (in place 

since 1978) the previous record of 780,710 total visitors was established in 1993, and as mentioned 

above, the record for recreational visitors was set in 2012 (Hartwig, written communication 30 

January 2016).

Many visitors come to the park to travel Rim Rock Drive (Photo 1), stopping at pull outs to view the 

incredible monoliths and canyons. There are 16 scenic overlooks along Rim Rock Drive, as well as 

several tunnels and switchback turns, making the drive a memorable experience (Figure 3). The park 

also features hiking trails, a campground, picnic areas, and the Saddlehorn visitor center. Hiking

trails vary in length and intensity, and provide opportunities to photograph the park’s scenic beauty 

and encounter wildlife.
16

Photo 1. Rim Rock Drive (NPS photo).

2.2 Natural Resources

2.2.1 Ecological Units and Watersheds

This area of western Colorado where COLM is located is part of the Colorado Plateau (Figure 9) 

(KellerLynn 2006). This physiographic province is an eroded desert landscape that covers parts of 

Colorado, Utah, Arizona, and New Mexico (Figure 9) (KellerLynn 2006). The park is situated in the 

northeastern portion of the Canyon Lands Division of the Colorado Plateau, on the northeast side of 

the topographic feature known as the Uncompahgre Plateau (Lohman 1965, KellerLynn 2006, Tweet 

et al. 2012). The Uncompahgre Plateau is a high, relatively flat elongated area that extends from 

Ridgeway, Colorado in a northwesterly direction to near Cisco, Utah (KellerLynn 2006).

This area of Colorado falls within the Environmental Protection Agency’s (EPA) Colorado Plateaus

Level III Ecoregion. According to the EPA (2010, p. 3), the Colorado Plateau is “an arid sagebrush 

steppe and grassland, surrounded on all sides by moister, predominately forested, mountainous 

ecological regions.” The EPA Level III Ecoregions are subdivided into smaller units and COLM is 

located within the Semiarid Benchlands and Canyonlands EPA Level IV Ecoregion (Figure 10). 

This Level IV Ecoregion is characterized by broad grass-, shrub-, and woodland-covered benches

and mesas (EPA 2010). The Gunnison River joins the Colorado River just to the east of the park, and 

their drainage roughly parallels the parks eastern and northern boundaries (Figure 11) (Tweet et al. 

2012). The park is located within the Colorado Headwater Plateau Subbasin of the Upper Colorado 

Region. The park is entirely within the Big Salt Wash-Colorado River Watershed and the canyons of 

the park are drained by a variety of subwatersheds (Figure 11).
17

Figure 9. The Colorado Plateau and associated physiographic divisions (USGS 2011).
18

Figure 10. Level IV ecoregions for COLM.
19

Figure 11. Big Salt Wash-Colorado River watershed and sub-watersheds.

2.2.2 Resource Descriptions

COLM preserves one of the grand landscapes in the American West (NPS 2015a). It is an area of 

sheer-walled canyons, towering monoliths, and colorful formations (NPS 2015a). It is also home to a 

representative example of an intact high desert ecosystem (NPS 2015a). Geologic processes, 

including sedimentation, faulting, uplifting, erosion, landslides, rockfalls, and flash flooding have 

resulted in the many landforms and geologic features within the park (NPS 2015a). 
20

COLM has a variety of notable geologic features, including hanging canyons, rock layers that 

contain a record of the geologic history of the area, and the park’s distinctive monoliths and canyons 

(NPS 2015a). The tops of formations, such as pedestals and spires, are isolated, ranging from 

approximately 1,700-2,100 m (5,600-6,900 ft) and have little soil that is accumulated through wind 

(eolian) processes (Kennard and Moore 2013). Canyon and monolith walls have occasional patches 

of vegetation that has taken root on ledges and holes.

No Thoroughfare Canyon, one of several canyons in COLM, has rock exposures that predate the 

formation of continental North America (1.74 billion years old) and have been uplifted and eroded 

into beautiful spires, valleys, and mesas (Tweet et al. 2012). The basement rocks of the canyon 

bottoms contain a disconformity of 1.5 billion years that alludes to the significant changes to the 

continental conditions and is studied throughout the extent of the Colorado Plateau Networks 

(Northern Colorado Plateau Network [NCPN] and Southern Colorado Plateau Network [SCPN]); the 

park serves as a key to understanding earth’s dynamisms (NPS 2005). The events that took place 

have created the beautiful shapes and colors seen along Rim Rock Drive, the main park road. Layers 

of depositional periods are easily differentiated in sedimentary rock faces; the color and texture are 

strikingly contrasted in some areas (Photo 2).

Photo 2. The layers of sedimentary rock are exposed by erosional forces along many parts of Rim Rock 

Drive in the park; each horizontal layer represents a period of deposition through geologic time (Photo by 

Anna Davis, SMUMN GSS).

Ecoregionally distinct vegetation communities, such as old-growth pinyon-juniper forests, hanging 

gardens and tinajas can be found within the boundaries of COLM (Von Loh et al. 2007, NPS 2015a). 

Other notable vegetation communities found within the park include riparian and wetland 

communities, native grasslands, and sagebrush shrublands (Von Loh et al. 2007, NPS 2015a). 

Dwarfed woodlands and sparse shrublands are the dominant vegetation types within the park (Von 

Loh et al. 2007). Within these types, pinyon-juniper woodland is the most widespread vegetation 

community on the upper mesas of COLM (Von Loh et al. 2007). These woodlands are primarily 

composed of two-needle pinyon pines (Pinus edulis) and Utah juniper (Juniperus osteosperma) trees 

(Von Loh et al. 2007). Tree canopy cover in these communities ranges up to 45%, and there is a 

sparse shrub and herbaceous understory (less than 5% total cover) (Von Loh et al. 2007). Biological 
21

soil crusts (BSCs) are also well developed between plants in these areas (Von Loh et al. 2007). There 

are more pinyon pines than junipers in terms of density, largely due to high numbers of small pinyon 

pines (Kennard and Moore 2013). However, the junipers are by far the older of the two species. The 

oldest juniper trees are estimated to be over 900 years old (Kennard and Moore 2013). Sagebrush 

shrublands are dominant in areas where deeper eolian soil deposits occur (Von Loh et al. 2007, 

Kennard and Moore 2013). Basin big sagebrush (Artemisia tridentata ssp. tridentata), Wyoming big 

sagebrush (A. tridentata ssp. wyomingensis), and black sagebrush (A. nova) are the most common 

species found in these communities (Von Loh et al. 2007). Mixed salt desert scrub is distributed in 

patches throughout the park and is also reliant on BSCs (Von Loh et al. 2007). 

Riparian habitat occurs along dry washes where seeps, springs, and intermittent flows during rain 

events support diverse biota (Von Loh et al. 2007). The riparian zones stand out against the more 

barren, rocky land adjacent to them, with tall cottonwoods visible from the mesa tops; these habitats 

are crucial to the ecology within COLM (Von Loh et al. 2007). The hanging gardens of COLM’s 

canyon walls are mesophytic plant communities that establish upon seeps and springs that lack actual 

surface flow (May et al. 1995). Water fed to these micro-habitats comes from seeps and springs 

within the bedrock (capillary fringe) and are isolated from the surrounding plant communities (May 

et al. 1995). The name “hanging garden” describes the behavior of vegetation which hangs from the 

roots, hugging the wetted surface of the cliff where “groundwater sapping” feeds the vegetation and 

creates a shelter from the otherwise arid climate (May et al. 1995). Tinajas are “ephemeral water 

pockets or scour pools in the American Southwest”. These potholes in the bedrock often form below 

waterfalls that are fed by seeps and springs that achieve streamflow during big rain events or melting 

periods (Osterkamp 2008).

BSCs are a valued feature of dryland ecosystems such as the Colorado Plateau (Belnap et al. 2008). 

BSCs are composed of intertwined communities of lichens, mosses, and cyanobacteria (Belnap et al. 

2008). These communities, along with green algae and microfungi, hold eolian silt and sand in place, 

creating slow-growing bacterial mats (NPS 2015b). Soil crusts are an essential part of the ecosystems 

where they occur, influencing soil stability, soil fertility, local hydrology, and soil biodiversity 

(Belnap et al. 2008). Simply stated, they create an environment that facilitates the germination of 

seeds from a variety of plants (NPS 2015b). Due to their fragile, slow-growing nature, measures are 

needed to avoid damaging these soil crusts (NPS 2015b).These measures include educating visitors

on the delicate nature of the soil crusts and posting signs instructing hikers to stick to the established 

trails (NPS 2015b).

COLM supports a variety of mammals, occupying various habitats. Common species include the 

desert cottontail (Sylvilagus audubonii), mule deer (Odocoileus hemionus), bats (Order Chiroptera), 

and many small mammals. Visitors occasionally spot coyotes (Canis latrans; Photo 3), bighorn sheep 

(Ovis canadensis), and gray foxes (Urocyon cinereoargenteus) (NPS 2014b). 
22

Photo 3. A coyote at COLM (NPS photo).

There are many resident, migratory, and breeding bird species that occur in COLM and rely on park 

resources for survival. COLM is recognized as an Important Bird Area (IBA) by the National 

Audubon Society (NAS); the park’s pinyon-juniper woodland habitat is largely intact and provides a 

valuable research opportunity in a protected setting (NAS 2013). Falcons, hawks, and owls of various 

species are found in COLM’s habitats as well as hummingbirds and songbirds, making the park an 

attractive scene for bird enthusiasts. 

Paleontological resources are present at COLM, and all the formations with the exception of the 

Proterozoic units and the Dakota Formation, contain fossils (Table 3). The Dakota Formation is 

included as a source of fossils found based on the descriptions of Scott et al. (2011). Certain rock 

layers are considered most likely to bear fossils. The fossil-bearing sedimentary units found in 

COLM are listed by age, formation name, and depositional environment in Table 3.

Table 3. The geology of COLM is rich in fossil-bearing sedimentary rock formations (recreated from 

Tweet et al. 2012).

Formation Age Fossils found in COLM Depositional Environment

Quaternary 

Sediments

PleistoceneHolocenePlant fossils, a mammoth or mastodon 

tooth, bones of nine other mammal and 

bird taxa, and packrat middens

Alluvial, eolian, fluvial, and landslide 

deposits

Dakota 

Formation

Early–Late 

Cretaceous

Possibly plant fossils, root traces, and 

invertebrate traces

Terrestrial (especially fluvial) 

becoming shallow marine over time

Burro Canyon 

Formation

Early 

Cretaceous

Petrified wood, root traces, invertebrate 

traces, and dinosaur bones

Fluvial, floodplain, and lacustrine 

settings
23

Table 3 (continued). The geology of COLM is rich in fossil-bearing sedimentary rock formations 

(recreated from Tweet et al. 2012).

Formation Age Fossils found in COLM Depositional Environment

Morrison 

Formation

Late Jurassic Bivalves, gastropods, horseshoe crab 

traces, a lungfish tooth plate, bones of 

turtles, crocodile relatives, and 

dinosaurs, and a pterosaur footprint

Fluvial, floodplain, and lacustrine 

settings

Wanakah 

Formation

Middle Jurassic Invertebrate traces and possible 

pterosaur feeding traces

Mud flats and/or shallow lakes

Entrada 

Sandstone

Middle Jurassic Bioturbation Coastal dunes and sand flats

Kayenta 

Formation

Early Jurassic Local bioturbation and two bones Primarily fluvial settings

Wingate 

Sandstone

Late Triassic–

Early Jurassic

Bioturbation from roots and burrows, 

and tracks of dinosaurs, other reptiles, 

and mammal relatives

Desert with large eolian sand dunes

Chinle 

Formation

Late Triassic Root traces, invertebrate traces, and 

rare bones

Fluvial, floodplain, and lacustrine 

settings, becoming drier over time

COLM encompasses some 8,094 ha (20,000 ac) of which approximately 6,070 ha (15,000 ac) has 

been identified or proposed as wilderness (Figure 12) (NPS 2015a). The original proposal in January 

1976 submitted a recommendation to Congress to designate 4,168 ha (10,300 ac) of COLM’s remote, 

rugged canyons as wilderness (NPS 1978). In January 1978, the NPS submitted a revised 

recommendation that expanded the proposed wilderness area to 5,602 ha (13,842 ac) and included an 

additional 379 ha (937 ac) be reserved as potential wilderness (NPS 1978). While the designation is 

still under consideration, the proposed area is managed under NPS policy as wilderness (NPS 2015a).
24

Figure 12. Location of proposed wilderness area within COLM.

2.2.3 Resource Issues Overview

Climate change is an issue that will affect not only natural and cultural resources within COLM, but 

also visitation patterns (Fisichelli et al. 2015). The recent rapid changes in Earth’s climate are well 

documented and include such impacts as significant increases in average temperatures and 

precipitation in the last 50 years, as well as increased incidence of extreme weather events (e.g., 

extended drought, heavy rainstorms) (IPCC 2007). These climatic shifts have already been linked to 
25

a number of impacts to natural systems, including such phenological changes as earlier onset of plant 

greenness, earlier insect emergence and flowering of plants, shifts in the onset of migration and 

breeding seasons, and changes in geographic ranges (summarized in Stein and Glick 2011).

In order to develop meaningful conservation strategies, managers must understand the wide range of 

impacts, risks, and uncertainties associated with projected climate changes, and try to estimate the 

relative vulnerability of different ecosystems and species to these projected changes. For instance, 

more vulnerable species and systems are more likely to experience greater impacts from climate 

change and would require a greater effort in conservation planning, while less vulnerable species and 

systems will be less affected, or may even benefit; this may require less intensive conservation 

planning relative to a changing climate. Managing for such changes in natural systems is rapidly 

becoming a priority for conservation agendas.

The control of non-native and invasive plant species is a high priority for the NPS (Perkins 2014). 

They are a significant threat to maintaining the integrity of natural ecosystems and to biodiversity 

(Scott and Wilcove 1998, Perkins 2014). Non-native and invasive species monitoring has been 

conducted at COLM since 2003 (Perkins 2014). This monitoring is based on a priority species list 

developed by the NCPN and park staff (Perkins 2014). Field crews are trained to conduct a focused 

search for the priority species, rather than for every possible invasive species (Perkins 2014).

Monitoring of invasive exotic species (IEPs) based on this priority list allows for the comparison 

across multiple survey years; however, the priority (or targeted species) in 2003 was different than 

for the 2009-2013 surveys (Perkins 2014). COLM is part of a long-term monitoring program for IEPs 

developed by the NCPN that focuses on early detection (Perkins 2014). The first survey of IEPs in 

the park was conducted in 2003 by Dewey and Anderson (2005). The initial survey in 2003 detected 

15 IEP species (Dewey and Anderson 2005). Since the 2003 survey, there have been three IEP 

monitoring surveys (2009, 2011, and 2013); the non-native species detected each year are shown in 

Table 4. In the 2009, 2011, and 2013 field seasons, 16, 22, and 14 species were detected, respectively 

(Perkins 2010, 2012, 2014).

Table 4. IEP species that have been detected in COLM. Priority species are in bold.

Scientific Name Common Name

Dewey and 

Anderson (2005)

Perkins 

(2010)

Perkins 

(2012)

Perkins 

(2014)

Acroptilon repens Russian knapweed X X X

Agropyron cristatum crested wheatgrass X

Alyssum desertorum desert madwort X

Arctium minus burdock X

Asparagus spp. asparagus X

Bassia sieversiana summer cypress X

Bromus inermis smooth brome X

Bromus tectorum cheatgrass X X X X
26

Table 4 (continued). IEP species that have been detected in COLM. Priority species are in bold.

Scientific Name Common Name

Dewey and 

Anderson (2005)

Perkins 

(2010)

Perkins 

(2012)

Perkins 

(2014)

Cardaria latifolia broad-leaf pepperwort X X

Carduus nutans musk thistle X X

Centaurea solstitialis yellow starthistle X

Cirsium arvense Canada thistle X

Cirsium vulgare bull thistle X X X

Conium maculatum poison hemlock X

Convolvulus arvensis field bindweed X X X X

Cylindropyrum cylindricum jointed goatgrass X

Elaeagnus angustifolia Russian olive X X X X

Erodium cicutarium redstem stork's bill X X

Halogeton glomeratus saltlover X

Halogeton glomeratus halogeton X

Lactuca serriola prickly lettuce X

Medicago sativa alfalfa X

Melilotus officinalis yellow sweetclover X X X X

Orthoceras spp. bur buttercup X

Poa bulbosa bulbous bluegrass X

Rumex crispus curly dock X

Salsola kali Russian thistle X X X

Sisymbrium altissimum tall tumblemustard X

Tamarix ramosissima saltcedar X X X X

Tragopogon dubius yellow salsify X X X

Ulmus pumila Siberian elm X X X

Verbascum thapsus woolly mullein X X X X

Populus alba white poplar X

Dewey and Anderson (2005) conducted non-native plant surveys along routes in Gold Star Canyon, 

Monument Canyon, No Thoroughfare Canyon, and Ute Canyon. Perkins (2009-2014) surveyed those 

canyons as well as Columbus Canyon, Kodels Canyon, Red Canyon, Wedding Canyon, East Glade 

Park Road, and Rim Rock Drive South.

Results of the most recent survey (conducted between 31 July and 16 August 2013) showed for the 

areas that have been monitored in all years, Russian olive (Elaeagnus angustifolia) declined to its 

lowest levels in 2013, following increases in the two previous surveys (2009 and 2011) (Perkins 

2014). The occurrence of Russian olive infestations dropped by 77% between 2011 and 2013, and 

declined on every route that was monitored in all years (Perkins 2014). Saltcedar (Tamarix 
27

ramosissima) has also declined over the period, with four infestations in 2013 (Perkins 2013). This 

represented an 81% reduction in tamarisk (Tamarix spp.) infestations since 2011, and a 96% 

reduction since 2003 (Perkins 2014). The decline in saltcedar is likely due to manual control efforts 

by seasonal park staff and volunteers (Perkins 2014). The park expects to expand these efforts to 

include Russian olive in the near future (Perkins 2014). Yellow sweetclover (Melilotus officinalis)

(added to the priority list in 2011) exhibited an increase in number of infestations between 2011 and 

2013 (Perkins 2014). It is unclear if this is due to actual changes in IEP presence or if it reflects 

environmental variation (e.g., varying weather could favor certain species) and/or slight differences 

in the timing and focus of surveys. The frequency of cheatgrass (Bromus tectorum) occurrences has 

been variable, ranging from 1% of transects surveyed in 2009 to appearing in 68% of transects in 

2011 (Perkins 2014). This increase between the 2009 and 2011 surveys was likely due to the wet 

spring in 2011 (Perkins 2014). In the latest survey (2013), the frequency of cheatgrass occurrences 

declined to 48% (Perkins 2014).

Concerted control efforts by park staff have been instrumental in reducing the infestations of priority 

species, both in number of infestations and aerial extent. Currently this program is no longer funded, 

and lack of another viable program to fund future efforts is a major threat to maintaining this 

decrease in IEP infestations within the park (Hartwig, written communication, 30 January 2016).

Under the historic fire regime, fires were likely infrequent and low intensity. The study conducted by 

Kennard and Moore (2013) estimated that significant fires occurred anywhere from 588 to 1,428 

years apart. Small, isolated fires at COLM are common; park staff describe the often-seen single tree 

burning caused by lightning strike, explaining that these small fires tend to stay isolated to one tree 

unless there are high winds that can blow sparks to a nearby tree. This phenomenon is indicative of 

the park having the persistent type of pinyon-juniper woodlands with low fire frequency, as was 

observed in the evidence of past fires in Kennard and Moore’s (2013) survey. Lack of understory 

fuels and open canopy stands contribute to this low frequency fire ecology where soil is thin to nonexistent and inhibits growth of fuels. The introduction of non-native species, especially cheatgrass, 

creates a fuel source to spread fire, and the potential to alter the natural fire regime.

The park does not limit foot travel to established trails. This has led to the creation of an extensive

social trail network (Hartwig, written communication, 18 November 2015). These social trails are 

found across all habitat types within the park, and increasing visitor use of these trails can lead to 

trampling of vegetation and potentially to an increase in erosion rates. Both of these factors can 

eventually lead to loss of habitat. An increase in recreational climbing within the park is another 

potential source of visitor impact to resources that is of a concern to park resource managers. This 

activity is a major threat to hanging garden vegetation and other cliff-face vegetation communities as 

well as to the wildlife species such as bats and raptors that use these cliff-faces.

Some of the park’s canyon areas were particularly impacted by a herd of bison (Bison bison) that 

grazed there from the 1930s until the 1980s (KellerLynn 2006). The bison were initially introduced 

in an effort to attract visitors to the park (KellerLynn 2006), but the herd’s presence had some 

negative impacts on sagebrush, scrub, grassland vegetation communities and the seep and spring 

communities (Wasser 1977). For example, species such as fourwing saltbush (Atriplex canescens) 
28

and some native grasses appeared to decrease under grazing pressure (Wasser 1977). Some invasive 

species, such as cheatgrass and saltcedar, seemed to increase as it appears the bison provided a vector 

for their introduction into the vegetation communities (Wasser 1977, O’Dell et al. 2005, KellerLynn 

2006). The bison also disturbed BSCs and compacted soils, resulting in reduced water infiltration 

rates (Wasser 1977, KellerLynn 2006). As the main source of water in the park, the bison also 

disturbed the seeps and springs communities through trampling of vegetation and soil compaction. 

The lingering impacts of this bison grazing on the canyon communities they inhabited have not been 

assessed.

2.3 Resource Stewardship

2.3.1 Management Directives and Planning Guidance

COLM is part of the National Park System, and is preserved for having a natural resource in 

the form of grand geologic, ecologic, and historical value to the people (NPS 2005). The NPS 

General Management Plan outlines the current mission and purpose of COLM as follows:

Mission - Bold, big, and brilliantly colored, the steep-walled canyons and towering masses 

of naturally sculpted rock provide an introduction to the red rock country of the Colorado 

Plateau. Easily accessible, Colorado National Monument provides awe-inspiring vistas and 

opportunities for solitude and personal connection to the cultural and natural heritage of the 

Grand Valley of western Colorado. The National Park Service will work in a spirit of 

partnership and collaboration to promote the understanding, appreciation, and protection of 

this national treasure (NPS 2005).

Purpose - The purpose of Colorado National Monument is to provide for the understanding, 

preservation, and enjoyment of the extraordinary erosional, geological, and historical 

landscapes of great scientific interest, the Rim Road, and all other natural and cultural 

resources for present and future generations (NPS 2005).

2.3.2 Status of Supporting Science

The NCPN identifies key resources network-wide and for each of its parks that can be used to 

determine the overall health of the parks. These key resources are called Vital Signs. In 2005, the 

NCPN completed and released a Vital Signs monitoring plan (O’Dell et al. 2005). Table 5 shows the 

network vital signs selected for monitoring in COLM.

Table 5. NCPN Vital Signs selected for monitoring in COLM (O’Dell et al. 2005). Bold indicates Vital 

Signs that currently are or will be monitored by the NCPN. Italics indicate Vital Signs being monitored by 

a network park, another NPS program, or another federal or state agency, using other funding.

Category NCPN Vital Signs

Air and Climate Air quality (ozone, wet and dry deposition, visibility and particulate matter), 

weather and climate

Geology & Soils Stream/ river channel characteristics, soil function and dynamics
29

Table 5 (continued). NCPN Vital Signs selected for monitoring in COLM (O’Dell et al. 2005). Bold 

indicates Vital Signs that currently are or will be monitored by the NCPN. Italics indicate Vital Signs being 

monitored by a network park, another NPS program, or another federal or state agency, using other 

funding.

Category NCPN Vital Signs

Water Water chemistry, ground and surface water dynamics, aquatic 

macroinvertebrates and algae

Biological Integrity Invasive/exotic plants, insect pests, animal diseases, riparian 

communities, freshwater communities, grassland vegetation, shrubland 

vegetation, amphibians, birds, bats, predominant plant communities, 

threatened and endangered species (T&E) (e.g., peregrine falcon) and T&E 

plant populations

Human Use Consumptive use, non-point source human effects, visitor usage

Ecosystem Pattern and Processes Fire and fuel dynamics, land cover and use, night sky, soundscape, 

nutrient dynamics, productivity

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changes in the western United States. Science 306:1015-1018.

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Megadroughts in North America: Placing IPCC projections of hydroclimatic change in a longterm palaeoclimate context. Journal of Quaternary Science (25):48-61.

Cowell, C. M., and M. A. Urban. 2010. The changing geography of the U.S. water budget: 

Twentieth-century patterns and twenty-first-century projections. Annals of the Association of 

American Geographers 100(4):740-754.

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approach to the statistical mapping of climate. Climate Research 22:99-113.

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https://www.colorado.gov/pacific/dola/population-data (accessed 25 September 2014).
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Dewey, S. A., and K. A. Andersen. 2005. An inventory of invasive non-native plants in Colorado 

National Monument (2003) final report. National Park Service, Northern Colorado Plateau 

Network, Moab, Utah.

Diffenbaugh, N. S., and M. Ashfaq. 2010. Intensification of hot extremes in the United States. 

Geophysical Research Letters 37.

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and IV Ecoregions of the continental United States. 

ftp://ftp.epa.gov/wed/ecoregions/us/Eco_Level_III_descriptions.doc (accessed 17 November 

2015).

Fisichelli, N., G. Schuurman, W. Monahan, and P. Ziesler. 2015. Protected area tourism in a 

changing climate: Will visitation at US national parks warm up or overheat? PLOS ONE doi: 

10.1371/journal.pone.0128226.

Garfin, G., G. Franco, H. Blanco, A. Comrie, P. Gonzalez, T. Piechota, R. Smyth, and R. Waskom. 

2014. Southwest. Pages 462-486 in Climate change impacts in the United States: The Third 

National Climate Assessment. J. M. Melillo, T.C. Richmond, and G. W. Yohe, Eds. U.S. Global 

Change Research Program. http://nca2014.globalchange.gov/report/regions/southwest%0D

(accessed 25 September 2015).

Gonzales, P. 2013. Memoranda - Climate change trends at Colorado National Monument, USA. 

National Park Service, Washington, D.C.

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Contribution of Working Groups I, II, and III to the fourth assessment report of the 

Intergovernmental Panel on Climate Change. Core Writing Team, R.K. Pachauri and A. 

Reisinger (eds.) Intergovernmental Panel on Climate Change, Geneva, Switzerland.

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(Special report on managing the risks of extreme events and disasters to advance climate change 

adaptation [SREX]). November 2011 draft report. Intergovernmental Panel on Climate Change, 

Cambridge, United Kingdom.

KellerLynn, K. 2006. Colorado National Monument geologic resource evaluation report. Natural 

Resource Report NPS/NRPC/GRD/NRR—2006/007. National Park Service, Denver, Colorado.

Kennard, D. K., and A. J. Moore. 2013. Fire history, woodland structure, and mortality in a piñonjuniper woodland in the Colorado National Monument. Natural Areas Journal 33(3):296-306.

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Washington, D.C.

Lohman, S. W. 1965. The geologic story of Colorado National Monument. Colorado and Black 

Canyon Natural History Association, Fruita, Colorado.
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May, C. L, J. F. Fowler, and N. L. Stanton. 1995. Geomorphology of the hanging gardens of the 

Colorado Plateau. Pages 3-24 in C. van Riper, III, editor. Proceedings of the Second Biennial 

Conference on Research in Colorado Plateau National Parks, 25-28 October 1993. National Park 

Service Transactions and Proceedings Series NPS/NRNAU/NRTP- 95/11.

Meko, D. M., C. A. Woodhouse, C. A. Baisan, T. Knight, J. J. Lukas, M. K. Hughes, and M. W. 

Salzer. 2007. Medieval drought in the upper Colorado River Basin. Geophysical Research Letters 

34:10705.

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States: The third national climate assessment. U.S. Global Change Research Program. 

doi:10.7930/J0Z31WJ2. National Park Service, Fort Collins, Colorado.

Monahan, W., and N. Fisichelli. 2014. Climate exposure of US national parks in a new era of change. 

PLoS ONE 9(7): e101302. doi:10.1371/journal.pone.0101302. Park data available from 

science.nature.nps.gov/climatechange.

Mote, P. W, and K. T. Redmond. 2012. Western climate change. Pages 3-28 in Ecological

consequences of climate change. E. A. Beever and J. L. Belant (eds). CRC Press, Boca Raton, 

Florida.

National Audubon Society (NAS). 2013. Important bird areas. Colorado National Monument site 

profile. http://netapp.audubon.org/IBA/Site/477 (accessed 4 March 2014).

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Appendix E, 

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(accessed 2 February 2, 2016)

National Park Service (NPS). 2005. Final general management plan environmental impact statement, 

Colorado National Monument. National Park Service. Fort Collins, Colorado.

National Park Service (NPS). 2014a. Listing of acreage (summary). 

https://irma.nps.gov/Stats/Reports/National (accessed 8 October 2015).

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March 2014).

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Colorado. National Park Service, Fort Collins, Colorado.
32

National Park Service (NPS). 2015b. Natural features & ecosystems. 

http://www.nps.gov/colm/learn/nature/naturalfeaturesandecosystems.htm (accessed 17 November 

2015).

National Park Service (NPS). 2015c. Visitor use statistics. https://irma.nps.gov/Stats/Reports/Park 

(accessed 8 October 2015).

North Central Climate Science Center (NCCSC). 2015. Data analysis and graphics for PRISM and 

downscaled netCDF data. Colorado State University, Fort Collins, Colorado.

O’Dell, T., S. Garman, A. Evenden, M. Beer, E. Nance, D. Perry, R. DenBleyker, S. Daw, A. Wight, 

M. A. Powell, and others. 2005. Northern Colorado Plateau Inventory and Monitoring Network, 

Vital Signs monitoring plan. National Park Service, Northern Colorado Plateau Inventory and 

Monitoring Network, Moab, Utah.

Osterkamp, W. R. 2008. Annotated definitions of selected geomorphic terms and related terms of 

hydrology, sedimentology, soil science, and ecology. U.S. Geologic Survey, Reston, Virginia.

Perkins, D. 2010. Invasive exotic plant monitoring at Colorado National Monument, 2009. Natural 

Resource Technical Report NPS/NCPN/NRTR—2010/354. National Park Service, Fort Collins, 

Colorado.

Perkins, D. 2012. Invasive exotic plant monitoring in Colorado National Monument: 2011 field 

season. Natural Resource Technical Report NPS/NCPN/NRTR—2012/556. National Park 

Service, Fort Collins, Colorado.

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season. Natural Resource Technical Report NPS/NCPN/NRTR—2014/859. National Park 

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Scott, R., A. Harding, W. Hood, R. Cole, R. Livaccari, J. Johnson, R. Shroba, and R. Dickerson. 201. 

Geologic map of Colorado National Monument and adjacent areas, Mesa County, Colorado. U.S. 

Geological Survey, Reston, Virginia.

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to climate change vulnerability assessment. Glick, P., B. A. Stein, and N. A. Edelson, editors. 

National Wildlife Federation, Washington, D.C.

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inventory and monitoring: Northern Colorado Plateau Network. Natural Resource Technical 

Report NPS/NCPN/NRTR—2012/585. National Park Service, Fort Collins, Colorado.

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Geological Survey, Water Webserver Team, Reston, Virginia.

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Technical Report NPS/NCPN/NRTR—2007/061. National Park Service, Fort Collins, Colorado.

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35

3. Study Scoping and Design

This NRCA is a collaborative project between the NPS and Saint Mary’s University of Minnesota 

Geospatial Services (SMUMN GSS). Project stakeholders include the COLM resource management 

team and NCPN Inventory and Monitoring Program staff. Before embarking on the project, it was 

necessary to identify the specific roles of the NPS and SMUMN GSS. Preliminary scoping meetings 

were held, and a task agreement (issued against the Pacific Northwest Cooperative Ecosystem 

Studies Unit [PNW CESU] and Joint Venture Agreement H8W07110001), and a scope of work 

document were created cooperatively between the NPS and SMUMN GSS.

3.1 Preliminary Scoping

3.1.1 Natural Resource Condition Assessment

A preliminary scoping meeting was held on 11-13 December 2013. At this meeting, SMUMN GSS 

and NPS staff confirmed that the purpose of the NRCA was to evaluate and report on current 

conditions, critical data and knowledge gaps, and selected existing and emerging resource condition 

influences of concern to COLM managers. Following NRCA program guidance, this NRCA, 

includes the following:

 Condition assessments are conducted using existing data and information;

 Identification of data needs and gaps is driven by the project framework categories;

 The analysis of natural resource conditions includes a strong geospatial component;

 Resource focus and priorities are primarily driven by COLM resource management.

This condition assessment provides a “snapshot-in-time” evaluation of the condition of a select set of 

park natural resources that were identified and agreed upon by the project team. Project findings will 

aid COLM resource managers in the following objectives:

 Develop near-term management priorities (how to allocate limited staff and funding

resources);

 Engage in watershed- or landscape-scale partnership and education efforts;

 Consider new park planning goals and take steps to further these;

 Report program performance (e.g., Department of Interior Strategic Plan “land health” goals, 

Government Performance and Results Act [GPRA]).

Specific project expectations and outcomes included the following:

 For key natural resource components, consolidate available data, reports, and spatial 

information from appropriate sources including: COLM resource staff, the NPS Integrated 

Resource Management Application (IRMA) website, NPS I&M Vital Signs program, and 

available third-party sources. The NRCA report will provide a resource assessment and 

summary of pertinent data evaluated through this project.
36

 When appropriate, define a reference condition so that statements of current condition may 

be developed. The statements will describe the current state of a particular resource with 

respect to an agreed upon reference point.

 Clearly identify “management critical” data (i.e., those data relevant to the key resources).

This will drive the data mining and gap definition process.

 Where applicable, develop GIS products that provide spatial representation of resource data, 

ecological processes, resource stressors, trends, or other valuable information that can be 

better interpreted visually.

 Utilize “gray literature” and reports from third party research to the extent practicable.

3.1.2 Climate Change Vulnerability Assessment Pilot Study

The NPS is considering strategies to integrate climate change resource vulnerability into the park 

NRCAs. In March 2014, NPS partnered with SMUMN GSS to implement a pilot project to assess the 

feasibility of slightly modifying existing NRCA project scopes to accommodate an assessment of 

resource vulnerability to climate change. This effort was collaboration between the SMUMN GSS

Principle Investigator (PI) for the COLM NRCA project, the NPS involved principles (including the 

Climate Change Response Program [CCRP]), the NRCA Program, the NRCA regional coordinators, 

COLM staff, and the North Central Climate Science Center (NCCSC).

The pilot project’s goal was to seek creative approaches to considering climate change vulnerabilities 

in the context of a NRCA project. A number of on-going NRCA projects were included in this pilot, 

so in order to provide comparative assessments; a fundamental general approach was developed. 

Each NRCA project in the pilot study used the following basic criteria to assess resource 

vulnerability to climate change:

 Information about modeled and downscaled climate change data needed to assess 

vulnerability was developed using existing resources through the NCCSC, the NPS CCRP, 

and the NPS I&M program;

 Discussion with park resource managers was conducted to identify park species, habitats, 

processes, communities, or landscapes viewed as most significant, iconic, or best indicator of 

park resource vulnerability;

 Climate change vulnerability assessments (CCVA) for selected park resources, processes, or 

landscapes was completed using national, regional, or local scale readily available 

information, literature searches, and discussion with park resource experts or others deemed 

relevant to this determination.

The overall expectations and outcome of the pilot project included the following:

 Minimally impact the ongoing NRCA,

 Implemented as a qualitative process,

 Inform the need or urgency to conduct a formal park resource CCVA,

 Inform the feasibility and potential benefits of integrating a CCVA into the NRCA process.
37

3.2 Study Design for Natural Resource Condition Assessment

3.2.1 Indicator Framework, Focal Study Resources and Indicators

Selection of Resources and Measures

As defined by SMUMN GSS in the NRCA process, a “framework” is developed for a park or 

preserve. This framework is a way of organizing, in a hierarchical fashion, bio-geophysical resource 

topics considered important in park management efforts. The primary features in the framework are 

key resource components, measures, stressors, and reference conditions. 

“Components” in this process are defined as natural resources (e.g., birds, plant communities), 

ecological processes or patterns (e.g., natural fire regime), or specific natural features or values (e.g., 

geological formations) that are considered important to current park management. Each key resource 

component has one or more “measures” that best define the current condition of a component being 

assessed in the NRCA. Measures are defined as those values or characterizations that evaluate and 

quantify the state of ecological health or integrity of a component. In addition to measures, current 

condition of components may be influenced by certain “stressors,” which are also considered during 

assessment. A “stressor” is defined as any agent that imposes adverse changes upon a component. 

These typically refer to anthropogenic factors that adversely affect natural ecosystems, but may also 

include natural processes or disturbances such as floods, fires, or predation (adapted from GLEI 

2010). 

During the NRCA scoping process, key resource components were identified by NPS staff and are 

represented as “components” in the NRCA framework. While this list of components is not a 

comprehensive list of all the resources in the park, it includes resources and processes that are unique 

to the park in some way, or are of greatest concern or highest management priority in COLM. 

Several measures for each component, as well as known or potential stressors, were also identified in 

collaboration with NPS resource staff.

Selection of Reference Conditions

A “reference condition” is a benchmark to which current values of a given component’s measures 

can be compared to determine the condition of that component. A reference condition may be a 

historical condition (e.g., flood frequency prior to dam construction on a river), an established 

ecological threshold (e.g., EPA standards for air quality), or a targeted management goal/objective 

(e.g., a bison herd of at least 200 individuals) (adapted from Stoddard et al. 2006).

Reference conditions in this project were identified during the scoping process using input from NPS 

resource staff. In some cases, reference conditions represent a historical reference before human 

activity and disturbance was a major driver of ecological populations and processes, such as “pre-fire 

suppression.” In other cases, peer-reviewed literature and ecological thresholds helped to define 

appropriate reference conditions. 

Finalizing the Framework

An initial framework was adapted from the organizational framework outlined by the H. John Heinz 

III Center for Science’s “State of Our Nation’s Ecosystems 2008” (Heinz Center 2008). Key 

resources for the park were adapted from the NCPN Vital Signs monitoring plan (O’Dell et al. 2005). 
38

This initial framework was presented to park resource staff to stimulate meaningful dialogue about 

key resources that should be assessed. Significant collaboration between SMUMN GSS analysts and 

NPS staff was needed to focus the scope of the NRCA project and finalize the framework of key 

resources to be assessed. 

The NRCA framework was finalized in March 2014 following acceptance from NPS resource staff. 

It contains a total of 21 components (Figure 13) and was used to drive analysis in this NRCA. This 

framework outlines the components (resources), most appropriate measures, known or perceived 

stressors and threats to the resources, and the reference conditions for each component for 

comparison to current conditions.
39

Figure 13. Colorado National Monument natural resource condition assessment framework.

Component Measures Stressors Reference Condition

Ecological Communities

Pinyon-juniper 

Woodlands/Savannas

community extent and change over time, 

percent cover biological soil crusts, percent 

bare ground, community composition, trends in 

invasive infestation, soil stability

exotic invasive species, unnatural fire regimes, 

trails (authorized and unauthorized), drought

Current pinyon-juniper woodlands on the mesa 

tops in the middle of the monument

Sagebrush Shrublands/Shrub 

Steppe

community extent and change over time, 

percent cover biological soil crusts, percent 

bare ground, community composition, trends in 

invasive infestation, soil stability, canopy gap 

size

exotic invasive species (cheat grass), unnatural 

fire regime, trails (authorized and unauthorized), 

drought, regional climate change

Within the natural variability of the current 

system, particularly in the center of the 

monument away from the boundary (currently 

a data gap)

Riparian Habitats/Large dry 

washes (including 

cottonwoods)

community extent and change over time, 

community composition, trends in invasive 

infestation, cottonwood regeneration, channel 

geomorphology, frequency and discharge of 

flash floods

exotic invasive species, trails (authorized and 

unauthorized), channelization outside park 

boundaries, regional climate change

Condition of riparian habitats prior to regional 

settlement

Seeps and Springs and Tinaja 

Babitats 

vegetation community extent and change over 

time, vegetation community composition, 

trends in invasive infestation, water quality, 

discharge

exotic invasive species, drought, development in 

surrounding communities (groundwater 

withdrawal and wastewater contamination), trails 

(authorized and unauthorized)

Condition of seeps, springs, and tinajas prior 

to regional settlement

Mixed Salt Desert Scrub/Semidesert Grassland

community extent and change over time, 

community composition, trends in invasive 

infestation, soil stability, percent cover 

biological soil crusts, percent bare ground

exotic invasive species (cheat grass), unnatural 

fire regime, trails (authorized and unauthorized), 

drought, regional climate change

Condition of mixed salt desert scrub and semidesert grassland prior to regional settlement

Canyon Walls and Monolith 

Vegetation Communities

community extent and change over time, 

community composition 

exotic invasive species, recreational climbing, 

proximity of road to habitat, graffitti, regional 

climate change

Condition of this communities prior to regional 

settlement

Montane shrubland

community extent and change over time, 

community composition, trends in invasive 

infestation, soil stability, percent cover 

biological soil crusts, percent bare ground

exotic invasive species (cheat grass & crested 

wheatgrass), unnatural fire regimes, trails 

(authorized and unauthorized), drought, regional 

climate variation 

Within the natural variability of the current 

community (currently a data gap)

Biotic Composition

Colorado National Monument

Natural Resource Condition Assessment 
40

Figure 13 (continued). Colorado National Monument natural resource condition assessment framework.

Component Measures (Significance Level) Stressors Reference Condition

Herptiles

amphibian richness, amphibian abundance, 

amphibian distribution, reptile richness, reptile 

abundance, reptile distribution

roadway mortality, habitat loss, regional climate 

change, drought, disease, visitor/human impacts 

(social trails), potential invasion of bull frogs

2002 herpetofauna inventory

Birds summer breeding bird richness, year-round 

bird richness

land cover change, habitat degradation and 

fragmentation, regional climate variation, 

predation by domestic/feral cats

Undefined

Raptors raptor richness, abundance, productivity, 

number of active nest sites

climbing activity disrupting nesting, recreation 

disturbance Undefined

Small Mammals species richness, abundance, distribution

vehicle traffic, roadway mortality, drought, 

regional climate change, feral/domestic cats, 

disease, habitat loss

1964 report on the distribution of mammals 

within COLM

Mountain Lion abundance, distribution, reproductive success

hunting (outside COLM boundary), conflicts with 

local landowners (ranchers), habitat loss (outside 

of COLM), negative impact of roads, 

encroachment of human activities

NPS historical reports (1939-1962)

Bighorn Sheep abundance, distribution, reproductive success

vehicle traffic, visitor activity, disease/parasites 

from domestic sheep, natural predators, hunting 

(outside COLM)

1995 CPW desert bighorn sheep management 

plan

Kit Fox abundance, distribution, reproductive success roads and vehicle mortality, habitat loss and 

fragmentation, off-road recreation

CPW trapping harvest numbers (1975-1991) 

and statewide population (c. 1996)

Bats

species richness, abundance, number of 

hibernation/roost sites, number of maternity 

sites

likely some threatened and endangereds, 

disease potential, habitat loss, pesticides, 

collisions, disturbance from climbers

Undefined exept for species richness and 

abundance data from 1989 and 1994 bat 

surveys

Biotic Composition

Herptiles

Birds

Mammals

Colorado National Monument

Natural Resource Condition Assessment 
41

Figure 13 (continued). Colorado National Monument natural resource condition assessment framework.

Component Measures (Significance Level) Stressors Reference Condition

Air Quality

atmospheric deposition of sulfur/nitrogen, 

ozone, particulate matter, visibility, 

atmospheric deposition of mercury

oil and gas development, vehicle emissions, 

smoke from wildfire and woodburning stoves, 

visibility impacts from haze and inversions

NPS ARD ratings for air quality conditions 

base don ecosystem thresholds and visibility 

improvement goals

Dark Night Skies

sky glow from anthropogenic light, light 

pollution ratio for horizontal and vertical 

luminance, average sky luminance, vertical 

illuminance, Bortle Class/Zenith Limiting 

Magnitude, Unihedron Sky Quality Meter

existing lighting structures and other sources of 

anthropogenic light (within the surrounding area)

Dark night sky conditions during presettlement 

of the region (The ratio of anthropogenic 

hemisphere illuminance to natural hemisphere 

illuminance does not exceed 20%)

Viewscape

noncontributing structures visible from within 

the recommended wilderness area, immediate 

viewscape at points along Rim Rock Drive

urban development, radio towers on adjacent 

lands, haze, management activities not 

contributing to immediate viewscape along Rim 

Rock Drive, commercial vehicle traffic

Viewscape at time of park creation (1911) 

from Rim Rock Drive and the overall grand 

viewscape

Soundscape and Acoustic 

Environment

occurrence of human-caused sound (loudness 

and percent of time audible), occurrence of 

human-caused sound within and outside of 

proposed wilderness area

vehicle traffic, overflights from air traffic 

Natural ambient sound level (environment of 

sound that would exist in the absence of 

anthropogenic-caused noise)

Paleontological Resources

changes in specimen abundance at localities, 

documentation and inventory of paleontological 

sites in the park, incidence of theft, amount 

paleontological resources eroded out each 

year, erosion rate at paleontological sites

erosion, weathering, regional climate change, 

theft, vandalism, recreation impacts (climbing) Undefined

Geologic Features and 

Processes

changes in rates of erosion, frequency of rock 

falls or slides, frequency of heavy rain and 

sustained wind events, frequency and 

discharge of flash floods

regional climate change (extreme weather 

events), vistior activities, park management 

activities

Undefined

Physical Characteristics

Geology

Environmental Quality

Colorado National Monument

Natural Resource Condition Assessment 
42

3.2.2 Reporting Area

Unless specifically noted, the current condition summaries describe the condition of the resource 

within the boundaries of COLM.

3.2.3 General Approach and Methods

This study involved gathering and reviewing existing literature and data relevant to each of the key 

resource components included in the framework. No new data were collected for this study; however, 

where appropriate, existing data were further analyzed to provide summaries of resource condition or 

to create new spatial representations. After all data and literature relevant to the measures of each 

component were reviewed and considered, a qualitative statement of overall current condition was 

created and compared to the reference condition when possible.

Data Mining

The data mining process (acquiring as much relevant data about key resources as possible) began at 

the initial scoping meeting, at which time COLM staff provided data and literature in multiple forms, 

including: NPS reports and monitoring plans, reports from various state and federal agencies, 

published and unpublished research documents, databases, tabular data, and charts. GIS data were 

also provided by NPS staff. Additional data and literature were acquired through subject matter 

experts, online bibliographic literature searches and inquiries on various state and federal government 

websites. Data and literature acquired throughout the data mining process were inventoried and 

analyzed for thoroughness, relevancy, and quality regarding the resource components identified at 

the scoping meeting.

Data Development and Analysis

Data development and analysis was highly specific to each component in the framework and 

depended largely on the amount of information and data available for the component, as well as 

recommendations from NPS reviewers and sources of expertise including NPS staff from COLM and 

the NCPN. Specific approaches to data development and analysis can be found within the respective 

component assessment sections located in Chapter 4 of this report.

Scoring Methods and Assigning Condition

Significance Level

A set of measures are useful in describing the condition of a particular component, but all measures 

may not be equally important. A “Significance Level” represents a numeric categorization (integer 

scale from 1-3) of the importance of each measure in assessing the component’s condition; each 

Significance Level is defined in Table 6. This categorization allows measures that are more important

for determining condition of a component (higher Significance Level) to be more heavily weighted in 

calculating an overall condition. Significance Levels were determined for each component measure 

in this assessment through discussions with park staff and/or outside resource experts.
43

Table 6. Scale for a measure’s Significance Level in determining a components overall condition.

Significance Level (SL) Description

1 Measure is of low importance in defining the condition of this component.

2 Measure is of moderate importance in defining the condition of this component.

3 Measure is of high importance in defining the condition of this component.

Condition Level

After each component assessment is completed (including any possible data analysis), SMUMN GSS 

analysts assign a Condition Level for each measure on a 0-3 integer scale (Table 7). This is based on 

all the available literature and data reviewed for the component, as well as communications with park 

and outside experts.

Table 7. Scale for Condition Level of individual measures.

Condition Level (CL) Description

0 Of NO concern. No net loss, degradation, negative change, or alteration.

1 Of LOW concern. Signs of limited and isolated degradation of the component.

2 Of MODERATE concern. Pronounced signs of widespread and uncontrolled 

degradation.

3 Of HIGH concern. Nearing catastrophic, complete, and irreparable degradation of the 

component.

Weighted Condition Score

After the Significance Levels (SL) and Condition Levels (CL) are assigned, a Weighted Condition 

Score (WCS) is calculated via the following equation:

WCS =

∑ SLi ∗ CLi

# of measures

i=1

3 ∗ ∑ SLi

# of measures

i=1

The resulting WCS value is placed into one of three possible categories: good condition (WCS = 0.0 

– 0.33); condition of moderate concern (WCS = 0.34 - 0.66); and condition of significant concern 

(WCS = 0.67 to 1.00). Table 8 displays the potential graphics used to represent a component’s 

condition in this assessment. The colored circles represent the categorized WCS; red circles signify a 

significant concern, yellow circles a moderate concern and green circles that a resource is in good 

condition. White circles are used to represent situations in which SMUMN GSS analysts and park 

staff felt there were currently insufficient data to make a statement about the condition of a 

component. For example, condition is not assessed when no recent data or information are available, 
44

as the purpose of an NRCA is to provide a “snapshot-in-time” of current resource conditions. The 

arrows inside the circles indicate the trend of the condition of a resource component, based on data 

and literature from the past 5-10 years, as well as expert opinion. An upward pointing arrow indicates 

the condition of the component has been improving in recent times. A horizontal arrow indicates an 

unchanging condition or trend, and an arrow pointing down indicates deterioration in the condition of 

a component in recent times. These are only used when it is appropriate to comment on the trend of 

condition of a component. In situations where the trend of the component’s condition is currently 

unknown, no arrow is given.

Table 8. Description of symbology used for individual component assessments.

Condition Status Trend in Condition

Confidence in 

Assessment

Resource is in Good 

Condition Condition is Improving High

Warrants

Moderate Concern Condition is Unchanging Medium

Warrants

Significant Concern Condition is Deteriorating Low

Examples of how the symbols should be interpreted:

Resource is in good condition, its condition is improving, high confidence in the 

assessment.

Condition of resource warrants moderate concern; condition is unchanging; medium 

confidence in the assessment.

Condition of resource warrants significant concern; trend in condition is unknown or 

not applicable; low confidence in the assessment.

Current condition is unknown or indeterminate due to inadequate data, lack of 

reference value(s) for comparative purposes, and/or insufficient expert knowledge to 

reach a more specific condition determination; trend in condition is unknown or not 

applicable; low confidence in the assessment. 
45

Preparation and Review of Component Draft Assessments

The preparation of draft assessments for each component was a highly cooperative process among 

SMUMN GSS analysts and COLM and NCPN staff. Though SMUMN GSS analysts rely heavily on 

peer-reviewed literature and existing data in conducting the assessment, the expertise of NPS 

resource staff also plays a significant and invaluable role in providing insights into the appropriate 

direction for analysis and assessment of each component. This step is especially important when data 

or literatures are limited for a resource component.

The process of developing draft documents for each component began with a detailed phone or email conversation with an individual or multiple individuals considered local experts on the resource 

components under examination. These conversations were a way for analysts to verify the most 

relevant data and literature sources that should be used and also to formulate ideas about current 

condition with respect to the NPS staff opinions. Upon completion, draft assessments were forwarded 

to component experts for initial review and comments.

Development and Review of Final Component Assessments

Following review of the component draft assessments, analysts used the review feedback from 

resource experts to compile the final component assessments. As a result of this process, and based 

on the recommendations and insights provided by COLM resource staff and other experts, the final 

component assessments represent the most relevant and current data available for each component 

and the sentiments of park resource staff and outside resource experts. 

Format of Component Assessment Documents

All resource component assessments are presented in a standard format. The format and structure of 

these assessments is described below.

Description

This section describes the relevance of the resource component to the park and the context within 

which it occurs in the park setting. For example, a component may represent a unique feature of the

park, it may be a key process or resource in park ecology or it may be a resource that is of high 

management priority. Also emphasized are interrelationships that occur among the featured 

component and other resource components included in the NRCA.

Measures

Resource component measures were defined in the scoping process and refined through dialogue 

with resource experts. Those measures deemed most appropriate for assessing the current condition 

of a component are listed in this section, typically as bulleted items.

Reference Conditions/Values

This section explains the reference condition determined for each resource component as it is defined 

in the framework. Explanation is provided as to why specific reference conditions are appropriate or 

logical to use. Also included in this section is a discussion of any available data and literature that 

explain and elaborate on the designated reference conditions. If these conditions or values originated 
46

with the NPS experts or SMUMN GSS analysts, an explanation of how they were developed is 

provided.

Data and Methods

This section includes a discussion of the data sets used to evaluate the component and if or how these 

data sets were adjusted or processed as a lead-up to analysis. If adjustment or processing of data 

involved an extensive or highly technical process, these descriptions are included in an appendix for 

the reader. Also discussed is how the data were evaluated and analyzed to determine current 

condition (and trend when appropriate).

Current Condition and Trend

This section presents and discusses in-depth key findings regarding the current condition of the 

resource component and trends (when available). The information is presented primarily with text 

but is often accompanied by detailed maps or plates that display different analyses, as well as graphs, 

charts, and/or tables that summarize relevant data or show interesting relationships. All relevant data 

and information for a component are presented and interpreted in this section.

Threats and Stressor Factors

This section provides a summary of the threats and stressors that may impact the resource and 

influence to varying degrees the current condition of a resource component. Stressors are defined as 

long-term changes in natural processes that may impact a natural resource, while threats are 

imminent events, actions, or factors that impact natural resources. Relevant stressors were described 

in the scoping process and are outlined in the NRCA framework. However, these are elaborated on in 

this section to create a summary of threats and stressors based on a combination of available data and 

literature, and discussions with resource experts and NPS natural resources staff.

Data Needs/Gaps

This section outlines critical data needs or gaps for the resource component. Specifically, what is 

discussed is how these data needs/gaps, if addressed, would provide further insight in determining 

the current condition or trend of a given component in future assessments. In some cases, the data 

needs/gaps are significant enough to make it inappropriate or impossible to determine condition of 

the resource component. In these cases, stating the data needs/gaps is useful to natural resources staff 

seeking to prioritize monitoring or data gathering efforts.

Overall Condition 

This section provides a qualitative summary statement of the current condition that was determined 

for the resource component using the WCS method. Condition is determined after thoughtful review 

of available literature, data, and any insights from NPS staff and experts, which are presented in the 

Current Condition and Trend section. The Overall Condition section summarizes the key findings 

and highlights the key elements used in determining and justifying the level of concern, if any, that 

analysts attribute to the condition of the resource component. Also included in this section are the 

graphics used to represent the component condition.
47

Sources of Expertise

This is a listing of the individuals (including their title and affiliation with offices or programs) who 

had a primary role in providing expertise, insight, and interpretation to determine current condition 

(and trend when appropriate) for each resource component.

3.3 Study Design for Climate Change Vulnerability Assessment Pilot

3.3.1 Component Selection and Assessment Variables

Selection of Resources 

A landscape scale community-based assessment was employed for the purpose of this pilot study. 

The selection of this type of assessment was based on the premise that plant communities and their 

related landscapes are the foundations for habitat and species. Plant communities are often priority 

resources that park managers express concern over when looking at ongoing park threats and longterm park resource sustainability. SMUMN GSS, the COLM NRCA project team, and the NPS 

climate change integration pilot team worked together to select two vegetation communities from the 

NRCA framework for an analysis of potential impacts from ongoing and future climate change. By 

selecting communities from this framework, the climate change integration pilot study would be a 

park-centric approach and it could build on the established NRCA process. Several considerations 

were taken into account during the discussions on selecting the components for inclusion in the pilot 

study. A specific set of selection criteria was not established, however COLM resource managers 

were asked to consider their long-term management as part of the selection process. With guidance 

from SMUMN GSS and the NPS climate change integration team, COLM resource managers 

selected pinyon-juniper woodlands/savanna, an iconic and important park plant community, and 

seep, spring and tinaja habitats, which depend upon unique physical resources, as the two 

communities to include in the pilot study. It is important to note that the seeps and springs and tinaja 

habitat climate assessment will be based on how representative plant communities within these 

habitats could be affected by climate change. This assessment will only have a limited analysis of 

how climate change will affect the availability of water or the overall aquatic habitat.

Variables of Interest

The approach utilized in this study is based on a modified community assessment methodology used 

by Amberg et al. (2012) in a climate change vulnerability assessment completed for Badlands 

National Park (BADL). Amberg et al. (2012) employed a modified adaptation of an approach 

originally developed by Hector Galbraith (Manomet Center for Conservation Sciences, Manomet, 

MA) that was used to assess the vulnerability of habitats in 13 northeastern states. Galbraith’s 

original approach used 11 variables to assess vulnerability (Galbraith 2011). Figure 14 illustrates 

how each variable was designed to capture to some degree either sensitivity, exposure, or adaptive 

capacity of a diversity of ecological communities, in an effort to assess their overall vulnerability to 

climate shifts. Amberg et al.’s (2012) adaptation of Galbraith’s approach selected six of the original 

variables to assess the vulnerability of the BADL plant communities to climate change. These six 

variables are (descriptions based on Galbraith 2011):
48

1. Location in geographical range of 

plant community. Plant communities 

close to the southern extremes of their 

distributions and that may be close to the 

southern edges of their range of climatic 

tolerances may be more vulnerable to a 

warming climate than communities that 

are further north of these bioclimatic 

edge zones. Plant communities closer to 

the northern edge of their current range 

may be more likely to persist in place 

and may benefit by being able to extend 

northward.

2. Sensitivity to extreme climatic events. 

Some plant communities may be more 

vulnerable than others to extreme 

climatic events or climate-induced 

events (drought, floods, ice storms, windstorms). Such events are projected to become more 

frequent and/or intense under climate change.

3. Dependence on specific hydrologic conditions. Some plant communities are confined to 

areas with specific and relatively narrow hydrologic conditions. Changes in precipitation 

amount, type (snow vs. rain), and timing are projected under all climate change models 

(though the direction and degree of change vary across models), potentially threatening these 

community types.

4. Intrinsic adaptive capacity. While all plant communities are likely to have characteristics 

that may enable them to withstand the effects of a changing climate, their adaptive capacities 

(their ability to resist or recover from stress) will vary, depending on their intrinsic and 

extrinsic characteristics and their condition:

a. The physical diversity within which a plant community exists may affect its 

resilience and adaptive capacity: communities with diverse physical and 

topographical characteristics (variety in aspects, slopes, geologies and soil types, 

elevations) may be more able to survive climate change than communities that are 

less varied, since the former, by existing across widely differing conditions, may be 

at lower risk of being eliminated by any future climatic conditions.

b. Some plant communities may be intrinsically more resistant to stressors because (for 

example) they have more rapid regeneration times. Communities in which the 

recovery period from the impacts of stressors is shorter (<20 years) may have greater 

intrinsic adaptive capacities than slower developing communities (recovery times of 

>20 years). For example, woodlands may take a hundred years or more to recover 

from fire or pest impacts. This may render them intrinsically more vulnerable to the 

Figure 14. Relationship between exposure, 

sensitivity, and adaptive capacity (Source: Stein et 

al. 2011).
49

potential intervening effects of climate change than plant communities that have 

shorter recovery periods (e.g., grasslands or shrub communities).

c. The current conditions of plant communities will also affect their adaptive capacities. 

Communities that support their full complement of species (or close to that), have 

high biodiversity, and that are relatively free from non-climate stressors are likely to 

be both more resistant and resilient to the effects of a changing climate. In contrast, 

plant communities that are in “poorer” condition with comparatively impoverished 

species representation and biodiversity, or that are being impacted by other stressors, 

may be less resilient and have lower adaptive capacity.

5. Vulnerability of ecologically influential species to climate change. Ecologically influential 

species are those that have substantial influences on community structure. Examples are 

abundant tree species in woodlands, such as pinyon pine in dry coniferous woodlands, or 

Mancos columbine (Aquilegia micrantha) in hanging gardens, whose disappearance from the 

system would significantly alter plant composition and community structure. If there is 

reason to believe that ecologically influential species in a plant community are particularly 

vulnerable to climate change, the whole community may be in jeopardy.

6. Potential for climate change to exacerbate impacts of non-climate stressors. For some 

plant communities, it is likely that significant impacts of climate change will be expressed 

through their exacerbating or mitigating effects on current or future non-climate stressors. 

One example is the potential magnifying effects of warming temperatures on cold-limited 

pest species or invasive species (e.g., pinyon ips bark beetle [Ips confusus]). In this variable it 

is the intent to capture the potential effects of this interaction between climate change and 

non-climate change stressors.

3.3.2 General Approach and Methods

This pilot study involved gathering and reviewing existing literature and data relevant to the two 

ecological communities selected for the CCVA. No new data were collected for this study; however, 

where appropriate, existing data were further analyzed to provide summaries of resource condition or 

to create new spatial representations. 

Data Mining

Recent historical climate patterns for COLM were evaluated using PRISM gridded climate data. 

These data are produced by the PRISM climate group at Oregon State University (Daly et al. 2002, 

PRISM 2015), and the analysis was completed by the NCCSC. 

The PRISM climate group uses point data, a digital elevation model, and other spatial data sets to 

generate gridded estimates of monthly, yearly, and event-based climatic parameters, such as 

precipitation, temperature, and dew point. PRISM is constantly updated to map climate in all 

situations, including high mountains, rain shadows, temperature inversions, coastal regions, and other 

complex climatic regimes. The PRISM system uses data from about 8,000 climate observation 

stations, and the results are considered state-of-the-art (Daly et al. 2002).
50

While PRISM data are both spatially and temporally complete, older data are estimated from fewer 

on-the-ground observations and these data are thus generally less reliable than more modern 

observations. PRISM data for the COLM area are likely highly reliable for analyses at the spatial and 

temporal scale of this analyses. Davey et al. (2006) inventoried climate observation stations relevant 

to monitoring parks in the NCPN, and their report included 10 records of stations relevant to 

evaluating COLM. Two of these 10 stations included climate observations from earlier than 1910. 

PRISM uses correlations between stations for infilling missing data, and the more than 100 years of 

observations provides a very rich data set to develop and evaluate these relationships. PRISM data 

are well-suited for evaluating regional-scale and longer-term climate patterns and dynamics, but they 

cannot capture weather dynamics at the scale of local convection storms that occur between 

observation stations, for example.

Climate projection summaries for COLM were produced using statistically downscaled model 

projections for temperature (minimum and maximum), precipitation and aridity. These datasets 

provide bias-corrected and spatially downscaled climate projections and are typically referred to as 

Bias Correction followed by Spatial Disaggregation (BCSD) (Wood et al. 2004). They have been 

corrected for model-observation biases in mean monthly temperature and then processed at various 

spatial scales (i.e., disaggregated) to accommodate mismatches between the global model outputs and 

local topographical and other effects (Wood et al. 2004).

Data Development and Analysis

For this assessment, historical climate patterns and projected climate changes out to the year 2100 

were examined for the COLM region. Historical climate patterns (mean minimum and maximum 

temperatures and total precipitation) were analyzed to create a picture of climate in COLM during the 

past century. Using PRISM climate data, historical temperature and precipitation patterns for the 

COLM area were summarized and evaluated to build a context of historical climate to which future 

climatic projections may be compared. Specifically, mean monthly minimum and maximum 

temperature (°C) and total monthly precipitation (mm) from 1895 to present were examined.

Given the limited funding and scope of this pilot project, analyses were only possible for a single 

future climate projection. For the purposes of the vulnerability assessments in this study, the climate 

change integration team selected the “business as usual” RCP 8.5 scenario and a general circulation 

model (GCM) ensemble average. This is recognized as a necessary limitation of this pilot effort. The 

high emissions RCP 8.5 is considered a “baseline” scenario, as it does not assume a climate 

mitigation target (Riahi et al. 2011). For more information on the RCPs and how they were 

developed, please refer to Appendix A.

Scoring Methods and Assigning Vulnerability Scores

Each of the six variables defined above were independently assessed and assigned a “best estimate” 

score from 1 (least vulnerable) to 5 (most vulnerable) on the likely vulnerability of a plant 

community to future climate change and non-climate stressors (based on the available scientific 

literature, data, and expert opinion). Scores were summed to produce an overall score for a plant 

community’s vulnerability. The total minimum score was six and the total maximum score was 30. 
51

The overall score was then organized into one of four categories: critically vulnerable, highly 

vulnerable, moderately vulnerable, and less vulnerable (Table 9). These translate into community 

response categories ranging from a plant community likely to be eradicated or greatly reduced in 

extent within the study area to a plant community that may sustain modest reduction or actually 

increase in extent within the study area.

Table 9. Scale for results of climate change vulnerability analysis.

Vulnerability Score Description

6-13 Least vulnerable - plant communities that may not be at adverse risk from climate 

change, or that may benefit and increase their extent within the study area.

14-19 Moderately vulnerable – plant communities at risk of being considerably reduced (by 20-

50%) in extent by climate change.

20-25 Highly vulnerable – plant communities at high risk of being greatly reduced (>50%) in 

extent by climate change.

26-30 Critically vulnerable – plant communities at high risk of being eliminated entirely from the 

study area by climate change.

Uncertainty Evaluation and Confidence in Vulnerability Assessments

Uncertainty is inherent at many stages in assessing climate change vulnerability, including the 

climate modeling process, assumptions about vulnerabilities of resources to climate shifts and/or 

non-climate stressors (and how these interact), and assumptions about the adaptive capacities of the 

resources. Many uncertainties are unavoidable despite the best modeling and data gathering efforts. It 

is crucial to provide a comprehensive and detailed appraisal of how certain analysts can be about 

vulnerability scores so that resource managers can determine how best to use the vulnerability 

information presented to them on the potential impacts of climate change.

Uncertainty in the plant community assessments is addressed in two ways: certainty 

evaluations/scores and alternative scores. Certainty scores are a method of documenting how 

confident analysts are regarding the validity and accuracy of the original vulnerability scores 

assigned to each variable (not the alternative scores). The scale of certainty scores used in this draft 

assessment is the same scale used by Galbraith (2011) in the Northeast habitat vulnerability 

assessments, which is an adaptation of a category scale developed by Moss and Schneider (2000) for 

the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report. One of three 

certainty scores – low (1), moderate (2), or high (3) – was applied to the original assigned 

vulnerability score for each variable. The certainty scores for each variable were then summed up to 

determine a certainty evaluation for the overall vulnerability score of the plant community. The total 

minimum score was six (6) and the total maximum score was 18. These certainty scores translate to a 

level of confidence – low, moderate, or high confidence – about the judgments made regarding the 

vulnerability scores for each variable (Table 10).
52

Table 10. Scale for results of CCVA uncertainty analysis.

Uncertainty Score Description

6-10 Low confidence - Low certainty

11-14 Moderate confidence - Moderate certainty

15-18 High confidence - High certainty

When a clear “best estimate” vulnerability score did not stand out, the analyst had the option of 

assigning an alternative score (a highly possible but less likely outcome than the best estimate) in 

addition to the best estimate score. The alternative score is the “next best estimate” of vulnerability 

for a variable, taking into account the uncertainty attached to a variable (i.e., the lack of information 

or understanding about a plant community or a species). These alternative scores, in conjunction with 

the best estimate vulnerability score, serve to capture the range of highly likely possibilities that may 

exist for the vulnerability of a plant community (adapted from Galbraith and Price 2011). When 

certainty is high, vulnerability will likely be represented by a single value; when certainty is low, 

vulnerability will be represented by a range of scores. The alternative scores also show the potential 

direction of the vulnerability, in that an alternative score for a variable may reflect a lesser or greater

vulnerability due to uncertainty or data gaps in the literature (see Table 11 below as an example). For 

instance, the sensitivity of an ecologically influential plant or tree species in a community to 

extended periods of drought (variable = sensitivity to extreme climatic events) may be debated in the 

scientific literature in that several sources show a drought tolerance while another source reports an 

intolerance or sensitivity to drier conditions. In this case, alternative scores could represent lesser or 

greater vulnerability due to conflicting scientific literature. As another example, a resource may be 

assigned an alternative score that represents a higher degree of vulnerability due to high uncertainty 

related to very little or no available scientific data or information.

Table 11. An example of certainty and alternative vulnerability scores for plant community assessment 

variables. For individual variables, 3 = high certainty, 2 = moderate certainty, and 1 = low certainty; total 

ranges are 6-10 = low confidence, 11-14 = moderate confidence, 15-18 = high confidence.

Variable

Certainty 

Score

Vulnerability 

Score

Alternative 

Scores

Location in geographical range/distribution of plant community 3 3

Sensitivity to extreme climatic events (e.g., drought, flash floods, 

windstorms)

2 4 3,5

Dependence on specific hydrologic conditions 2 4

Intrinsic adaptive capacity 1 3 4

Vulnerability of ecologically influential species to climate change 2 4 3

Potential for climate change to exacerbate impacts of non-climate 

stressors

2 5

Total 12 23 21-25
53

Preparation and Review of Climate Change Vulnerability Analysis

Narratives for each assessment were created to clearly explain why certain assumptions and/or scores 

were adopted over other possibilities. It is important that this explanation provide sufficient detail 

and transparency to allow a reader to be able to clearly and easily follow the process and logic-steps 

that lead analysts to conclusions about vulnerability. The purpose of the narratives is to clearly 

outline the review and evaluation of the scientific literature and the thought processes and 

assumptions that result in assigning the vulnerability scores to each of the variables of interest. When 

appropriate, GIS products, such as maps of distributions and ranges, were developed and included in 

the assessment to add depth and graphical representation to the interpretation of literature and data.

Once each narrative assessment was completed, it went through an iterative review process among 

SMUMN GSS analysts for consistency. Assessments were then provided to COLM resource experts 

and other outside experts (e.g., university researchers, government scientists) for an external review 

in which the document was examined for accuracy of content, validity and accuracy of 

categorizations, and appropriateness of interpretation of available scientific literature, and feedback 

was provided on how to refine the assessment. Following review by experts, the vulnerability 

assessment was modified to reflect feedback.

Integration of Climate Change Analysis into Natural Resource Condition Assessment Document

The resource component assessments will be presented in the standard format as described in Section 

3.2.2 with the following changes made to incorporate the climate change analysis.

Current Condition and Trend

This section will be amended to include the discussion of the components vulnerability to climate 

change. This section will precede the “Threats and Stressors” section. This includes how the 

projected change in climate will affect the variables of interest.

Overall Condition 

This section provides a qualitative summary statement of the current condition that was determined 

for each of the resource components using the WCS method as described in Section 3.2.2. In 

addition, the vulnerability scoring for components that are part of the pilot study will be incorporated 

here, just prior to the “Weighted Condition Score” section. The vulnerability score is determined after 

thoughtful review of available literature and data regarding the components vulnerability to climate 

change that was presented in the Current Condition and Trend section. Also included in this section 

is a table with the results of the component’s climate change vulnerability assessment. This section 

will also include a brief summary of any uncertainty and related alternative scoring that may have 

been applied to the analysis of climate change vulnerability.

3.4 Literature Cited

Amberg, S., K. Kilkus, S. Gardner, J. E. Gross, M. Wood, and B. Drazkowski. 2012. Badlands 

National Park: Climate change vulnerability assessment. Natural Resource Report 

NPS/BADL/NRR—2012/505. National Park Service, Fort Collins, Colorado.
54

Daly, C. D., W. P. Gibson, G. H. Taylor, G. L. Johnson, and P. Pasteris. 2002. A knowledge-based 

approach to the statistical mapping of climate. Climate Research 22:99-113.

Davey, C. A., K. T. Redmond, and D. B. Simeral. 2006. Weather and climate inventory, National 

Park Service, Northern Colorado Plateau Network. Natural Resource Technical Report 

NPS/NCPN/NRTR - 2006/002. National Park Service, Fort Collins, Colorado.

Galbraith, H. 2011. The NEAFWA regional habitat vulnerability model – A “user’s manual”. 

Unpublished report to Northeastern Association of Fish and Wildlife Agencies. Available from 

H. Galbraith, hg2@myfairpoint.net.

Galbraith, H., and J. Price. 2011. Case study 2: U.S. Environmental Protection Agency’s threatened 

and endangered species vulnerability framework. Pages 90-95 in Scanning the conservation 

horizon: A guide to climate change vulnerability assessment. Glick, P., B. A. Stein, and N. A. 

Edelson (eds.). National Wildlife Federation, Washington, D.C.

Great Lakes Environmental Indicators Project (GLEI). 2010. Glossary, Stressor. 

http://glei.nrri.umn.edu/default/glossary.htm (accessed 16 November 2015).

The H. John Heinz III Center for Science, Economics, and the Environment. 2008. The state of the 

nation’s ecosystems 2008: Measuring the land, waters, and living resources of the United States. 

Island Press, Washington, D.C.

Moss, R. H., and S. H. Schneider. 2000. Towards consistent assessment and reporting of 

uncertainties in the IPCC TAR. in Cross-cutting issues in the IPCC third assessment report. R. 

Pachauri and T. Taniguchi (eds.). Global Industrial and Social Progress Research Institute (for 

IPCC), Tokyo, Japan.

O’Dell, T., S. Garman, A. Evenden, M. Beer, E. Nance, S. Daw, A. Wight, M. Powell, D. Perry, R. 

DenBleyker, and more. 2005. Northern Colorado Plateau Inventory and Monitoring Network, 

Vital Signs monitoring plan. National Park Service, Northern Colorado Plateau Network, Moab, 

Utah.

PRISM Climate Group. 2015. PRISM Climate Group. Oregon State University. 

http://prism.oregonstate.edu/ (accessed 16 September 2015). 

Riahi, K., S. Roa, V. Krey, C. Cho, V. Chirkov, G. Fischer, G. Kindermann, N. Nakicenovic, and P. 

Rafaj. 2011. RCP 8.5 - A scenario of comparatively high greenhouse gas emissions. Climate 

Change 109(1):33-57.

Stoddard. J. L., D. P. Larsen, C. P. Hawkins, R. K. Johnson, and R. J. Norris. 2006. Setting 

expectations for the ecological condition of streams: The concept of reference condition. 

Ecological Applications 16(4):1267-1276.
55

Wood, A. W., L. R. Leung, V. Sridhar, and D. P. Lettenmaier. 2004. Hydrologic implications of 

dynamical and statistical approaches to downscaling climate model outputs. Climatic Change 

62:189-216.

57

4. Natural Resource Conditions

This chapter presents the background, analysis, and condition summaries for the 21 key resource 

components in the project framework. The following sections discuss the key resources and their 

measures, stressors, and reference conditions. The summary for each component is arranged around 

the following sections:

1. Description

2. Measures

3. Reference Condition

4. Data and Methods

5. Current Condition and Trend (including threats and stressor factors, data needs/gaps, and 

overall condition)

6. Sources of Expertise

7. Literature Cited

The order of components follows the project framework (Figure 13):

4.1 Pinyon-juniper Woodlands/Savannas

4.2 Sagebrush Shrublands/Shrub Steppe

4.3 Riparian Habitats/Large Dry Washes

4.4 Seeps and Springs and Tinaja Habitats

4.5 Mixed Salt Desert Scrub/Semi-desert Grassland

4.6 Canyon Walls and Monolith Vegetation Communities

4.7 Montane Shrubland

4.8 Herptiles

4.9 Birds

4.10 Raptors

4.11 Small Mammals

4.12 Mountain Lion

4.13 Bighorn Sheep

4.14 Kit Fox

4.15 Bats

4.16 Air Quality

4.17 Dark Night Skies

4.18 Viewscape

4.19 Soundscape

4.20 Paleontological Resources

4.21 Geologic Features
58

4.1 Pinyon-juniper Woodlands/Savannas

4.1.1 Description

Pinyon-juniper woodlands/savannas in COLM 

consist primarily of two-needle pinyon pines 

and Utah juniper trees with various mixtures of 

other shrubs and herbaceous vegetation. These 

woodlands are typically situated on flat and 

mildly sloped mesa tops (Photo 4) and are 

distributed across a large portion (4,751 ha 

[11,740 ac]) of the park, comprising over half 

(57.4%) of the entire park area (Von Loh et al. 

2007). The two-needle pinyon pines are widely distributed across a broad geographic range in North 

America that includes the western states of Colorado, Utah, Arizona, Nevada, California, New 

Mexico, Wyoming, Oklahoma, and Texas as well as part of Chihuahua, Mexico (USDA 2015a). The 

Utah juniper has a similar range with the addition of Montana and Idaho, and excluding Texas 

(USDA 2015b). The two-needle pinyon pine produces nutrient-rich pine nuts that are a staple in the 

diets of wildlife, often providing crucial sustenance to animals, particularily in harsh winters when 

deep snow accumulates (Nesom 2003). The various plant communities of pinyon-juniper woodlands 

and savannas are diverse and include several unique alliances that are considered rare, which 

contributes greatly to the overall biodiversity of the park (Von Loh et al. 2007). There have been 

uncertainties regarding the historic role of fire in pinyon-juniper woodlands/savannas, with 

assumptions that fire exclusion and livestock grazing have allowed unnatural encroachment of 

pinyon-juniper woodlands/savannas into other vegetation communities, such as grasslands (Johnson 

2013; Kennard and Moore 2012, 2013). The pinyon-juniper woodlands/savannas of COLM offer a 

unique opportunity to study the fire history of several persistent stands that have been largely 

unaltered; the estimated age of the oldest juniper in one COLM stand is 920 years (Kennard and 

Moore 2012, 2013).

Pinyon jays (Gymnorhinus cyanocephalus) can be found year-round in these woodlands (Hanophy 

and Teitelbaum. 2003). Other birds that can be found foraging and nesting in this habitat include the 

bushtit (Psaltriparus minimus) and lark sparrow (Chondestes grammacus) (Hanophy and Teitelbaum. 

2003). Raptors such as red-tailed hawks (Buteo jamaicensis), golden eagles (Aquila chrysaetos), 

American kestrels (Falco sparverius) and prairie falcons (Falco mexicanus) forage on the pinyon 

mouse (Peromyscus truei) and bush-tailed woodrat (Neotoma cinerea) commonly found in these 

woodlands (Hanophy and Teitelbaum. 2003). This vegetation community also supports two lizard 

species, the eastern collared lizard (Crotaphytus collaris) and the plateau side-blotched lizard (Uta 

stansburiana uniformis) (Hanophy and Teitelbaum. 2003). Other mammals found within this habitat 

include: ringtail (Bassariscus astutus), mule deer, elk (Cervus elaphus) and mountain lion (Puma 

concolor) (Hanophy and Teitelbaum. 2003).

Photo 4. An example of an open-canopy pinyonjuniper woodland/savanna upon a mesa top in 

COLM (Photo by Anna Davis, SMUMN GSS).
59

4.1.2 Measures

 Community extent and change over time

 Community composition

 Percent cover biological soil crusts

 Percent bare ground

 Trends in invasive infestation

 Soil stability

4.1.3 Reference Conditions/Values

The reference condition for this component is based on the current pinyon-juniper woodlands on the 

mesa tops in the middle of the park. These woodlands are considered by park resource managers to 

be intact examples of the community, and any degradation from this state is in the future is to be 

considered a deviation. This current state is defined by the vegetation mapping and descriptions of 

pinyon-juniper woodlands/savannas within the entire park as mapped by Von Loh et al. (2007). At 

that time the community composition, estimated amount of bare ground, and percent 

vegetation/canopy cover for each pinyon-juniper woodland/savanna vegetation classification (12 

alliances) were also documented and will serve as a baseline for future assessments (Von Loh et al. 

2007). The reference condition for IEP infestation is the assumption that only native species present 

prior to European settlement in the area.

4.1.4 Data and Methods

Kennard and Moore (2012, 2013) studied fire history, spatial structure, and mortality in a COLM 

pinyon-juniper woodland to identify the driving mechanisms of temporal dynamics and spatial 

patterns. One purpose of the study was to provide a baseline of these factors to assess the potential 

changes possible from climate change in the coming decades (Kennard and Moore 2012, 2013). The 

research focused on pinyon-juniper woodlands that are situated on mesa tops, where they are the 

predominant vegetation. In order to estimate the fire history and the age of the pinyon-juniper stands, 

the study looked for evidence of large (>100 ha [247.1 ac]) stand-replacing fires (Kennard and 

Moore 2012, 2013). Kennard and Moore (2012) used an approach that was developed particularly for 

pinyon-juniper woodlands because of the difficulty in using fire scar analysis, the usual method, with 

these species. This is because both trees are easily killed by fire and thus there is generally not 

detectable fire scarring on pinyon pine and juniper trees (Kennard and Moore 2012, 2013).

To detect previous fires the researchers looked for landscape-scale fire scars. The two tree species are 

very slow to regenerate, leaving a detectable perimeter around an area of markedly younger trees 

(Kennard and Moore 2012, 2013). Within the perimeter, the oldest tree ages are used to estimate the 

time of the last large fire. A spatial grid of sample points was developed to map the approximate age 

structure of the stands within the grid (Kennard and Moore 2012, 2013). The grid points were located 

using a GPS unit over a 3-year period (September 2007 to June 2010). Regression equations 

developed from tree ring analyses were used to estimate the ages of the largest pinyon pine and 

juniper trees that were within 10 m (32.8 ft) of each grid point. Additionally, at each grid point where 

the largest trees were measured, a 100 m2(1076.4 ft2) circular plot was established (Kennard and 
60

Moore 2012, 2013). Individual trees within these plots were measured at the trunk base or stem base 

to establish a size class for each tree (Kennard and Moore 2012, 2013). A review of records kept by 

COLM on fire occurrence, which included size and location of fires since 1942, was used to 

characterize more recent fires for comparison with field observations of charred wood (Kennard and 

Moore 2013). 

Von Loh et al. (2007) conducted a vegetation mapping project for the park and surrounding areas. 

The purpose of the project, conducted between 2003 and 2005, was to classify, describe, and map 

vegetation and fuels at COLM (Von Loh et al. 2007). Surrounding areas were included to support 

management of the urban-wildland interface and coordinated management on adjacent public lands 

(Von Loh et al. 2007). A team of ecologists, botanists, and photo interpreters worked together to 

identify the plant associations within the park. Vegetation mapping was completed through the use of 

aerial photography and computer modeling. The resultant maps were refined through a combination 

of ground sampling and accuracy assessments using vegetation plot and observation point sampling 

(Von Loh et al. 2007). A complete detailed methodology of the computer modeling and sampling 

design can be found in Von Loh et al. (2007).

Johnson (2013) studied aerial photos of COLM from 1937 and 2007 to establish the historic and 

current extent of both pinyon-juniper woodland/savanna and sagebrush communities. The goal was 

to spatially describe the historic extent of pinyon-juniper woodland/savannas in relation to sagebrush 

communities. This was in response to a lack of reliable data needed to understand the historic fire 

regime within the pinyon-juniper woodland/savannas in the park. Trends in community expansion 

and contraction, presence of charred wood, and community structure and composition were 

examined to determine whether best-management practices for pinyon-juniper woodland/ savannas 

should include prescribed burning (Johnson 2013).

Dewey and Anderson (2005) inventoried invasive plant species in COLM during 2003. The 

objectives included documenting the distribution and abundance of target invasive plants in the park, 

identifying potential sources of introduction and vectors for spreading the invasive plants, and testing 

and refining data collection methods and field inventory techniques (Dewey and Anderson 2005). 

Eleven invasive plant species were identified as high-priority and were systematically sought by 

inventory crew members.

Perkins (2010, 2012, and 2014) conducted IEP monitoring in COLM during the 2009, 2011, and 

2013 field seasons. Methodology for field work and analysis was similar for all three field seasons. 

For the assessment of condition in this NRCA, the most recent report (Perkins 2014) will be the 

primary source since it includes data from the previous reports. The field work for these monitoring 

efforts included transect and quadrat sampling with emphasis on roads, trails, and waterways 

(Perkins 2010, 2012, 2014). A list of IEP priority species was developed for the park prior to each 

year of monitoring, based on previously detected species and literature reviews (Perkins 2010, 2012, 

2014). Monitoring was conducted on foot and IEPs were detected visually. For each monitoring 

route, transect, and quadrat, each IEP detected was recorded, listing the IEP species, infestation size 

class, and canopy cover class (Perkins 2014).
61

This synthesis of the relevant scientific data and information does not include the climate data and 

information used in conducting the climate change vulnerability assessment for this resource. Please 

refer to Chapters 2.1.3 and 3.2.3 and Appendix A for a discussion of the data and methodology used 

in the climate change analysis.

4.1.5 Current Condition and Trend

Community Extent and Change over Time

Vegetation patterns vary across a landscape and a classification system is used to recognize and 

organize vegetation communities. Von Loh et al. (2007) employed the National Vegetation 

Classification (NVC) system, which is the standard used for all NCPN vegetation mapping projects 

(TNC and ESRI 1994, NatureServe 2003). The NVC is a hierarchical system that uses seven levels to 

classify vegetation; the upper five levels are based on physiognomic characters and the two lower 

levels are based on floristic data (TNC and ESRI 1994, NatureServe 2003). The two lower levels 

(alliance and association) are distinguished by variability in their floristic composition (TNC and 

ESRI 1994, NatureServe 2003). These two lower levels are used throughout this NRCA in the 

assessment and discussion of the vegetation communities of COLM.

The alliance and association levels are determined by the most abundant species (or diagnostic 

species) comprising the strata of a homogenous vegetation community (TNC and ESRI 1994, 

NatureServe 2003). Associations are defined as a vegetation community type that exhibits a 

consistent species composition, uniform physiognomy, and similar habitat conditions (Flahault and 

Schroter 1910). Associations are differentiated by their species composition (TNC and ESRI 1994a). 

An alliance is a grouping of plant associations sharing one or more dominant species (Reid et al. 

1999). Von Loh et al. (2007) identified several distinct types of pinyon-juniper woodland/savannas in 

COLM. The pinyon-juniper woodland/savanna communities mapped by Von Loh et al. (2007) were 

selected for assessment of the community extent. These associations and alliances are dominated by 

two-needle pinyon pine and Utah juniper. Various combinations of other plant species are found 

within these alliances and associations. The areal extent of pinyon-juniper woodland/savannas as 

mapped by Von Loh et al. (2007) is shown in Table 12 (Von Loh et al. 2007).

Table 12. Areal extent of pinyon-juniper woodland/savanna vegetation alliances found in COLM (Von Loh 

et al. 2007).

Alliances Acres Hectares

Percent 

of total 

park area

Pinyon-juniper woodland/savannas (all) 11,740 4,751 57.4%

Two-needle pinyon pine–Utah juniper/multiple shrub woodland 6,133 2,482 30.0%

Two-needle pinyon pine–Utah juniper/Wyoming big sagebrush woodland 2,763 1,118 13.5%

Two-needle pinyon pine–Utah juniper/black sagebrush woodland 1,682 681 8.2%

Two-needle pinyon pine–Utah juniper/sparse understory woodland 1,162 470 5.7%
62

One map unit, the two-needle pinyon pine–Utah juniper/multiple shrub woodlands, consists of seven 

distinct vegetation associations and was the most extensive vegetation community within COLM 

boundaries. The other three map units are one alliance each. Using the observation points and map 

units created by Von Loh et al. (2007), these vegetation alliances and associations are displayed in 

Figure 15.

Figure 15. The location of pinyon-juniper woodland/savanna alliances within COLM (Von Loh et al. 

2007).
63

Two alliances that were described in Von Loh et al. (2007) as a type of pinyon-juniper 

woodland/savanna are not shown in Figure 15. These are the two-needle pinyon-Utah juniper/Utah 

serviceberry (Amelanchier utahensis) woodlands and the blue spruce (Picea pungens)-two-needle 

pinyon-Utah juniper/Gambel’s oak (Quercus gambelii) woodland. All stands of these two types 

identified at COLM were below the minimum mapping unit of 0.5 ha (1.2 ac). The two-needle 

pinyon-Utah juniper/Utah serviceberry woodlands were observed and sampled near the south and 

west entrance to COLM and near Alcove Trail (Von Loh et al. 2007). The blue spruce two-needle 

pinyon-Utah juniper/Gambel’s oak woodland was a single stand of four to six blue spruce trees, and 

one sapling at one other site (Von Loh et al. 2007). The single stand of blue spruce two-needle 

pinyon-Utah juniper/Gambel’s oak woodland was observed and recorded near the terminus of Echo 

Canyon and the sapling was observed in Red Canyon (Von Loh et al. 2007).

Johnson (2007) compared the aerial photos of COLM from 1937 and 2007 in an attempt to identify 

changes in the extent of pinyon-juniper woodlands. Due to distortions in the 1937 imagery 

determination of actual percent estimates of change were problematic (Dr. Deborah Kennard, 

Colorado Mesa University, Department of Physical and Environmental Sciences, written 

communication 18 November 2015). Based on simple ocular comparisons of the aerial photos from 

1937 and 2007, Johnson (2013) concluded that pinyon-juniper woodlands were expanding into the 

park’s sagebrush shrublands. Due to the distortions in the 1937 images Johnson estimated the loss of 

sagebrush shrubland/shrub steppe due to the expansion of woodland species ranged from 

approximately 10% to 30% in certain areas of COLM (Johnson 2013). This suggests that pinyonjuniper woodland extent has likely increased at COLM in recent decades or, at the least, has not 

decreased.

Community Composition

The following descriptions of community composition for pinyon-juniper woodlands/savannas found 

in COLM are the results of the Von Loh et al. (2007) vegetation mapping project that included field 

work to determine dominant species of plants and other associated plants. All communities are open 

woodlands dominated by two-needle pinyon pine and Utah juniper along with a few other plant 

species that determine their individual classifications (Von Loh et al. 2007). 

Two-needle pinyon-(oneseed juniper [Juniperus monosperma], Utah juniper)/needle and thread 

(Hesperostipa comata) woodlands are dominated by a canopy of two-needle pinyon pine and Utah 

juniper with only a few other species scattered below (Table 13; Von Loh et al. 2007). The open 

canopy cover is typically 2-5 m (6.6-16.4 ft) tall, with Mormon tea (Ephedra viridis) shrubs beneath, 

and 1-5% cover of needle and thread (Von Loh et al. 2007). An herbaceous layer provides up to 10% 

cover; all plant species documented in this association are shown in Appendix B (column A) (Von 

Loh et al. 2007). A total of eight plant species, including two trees, one shrub, three graminoids, and 

two forbs, were observed in this woodland type (Appendix B, column A; Von Loh et al. 2007).
64

Table 13. Dominant plant species (by strata) within the two-needle pinyon-(one-seed juniper, Utah 

juniper)/needle and thread woodlands of COLM (Von Loh et al. 2007).

Two-needle pinyon-(one-seed juniper, Utah juniper) / needle-and-thread woodland

Scientific Name Common Name Strata

Pinus edulis two-needle pinyon pine Tree canopy

Juniperus osteosperma Utah juniper Tree canopy

Ephedra viridis Mormon tea Short shrub/sapling

Achnatherum hymenoides Indian ricegrass Herb

Hesperostipa comata needle and thread Herb

Two-needle pinyon-Utah juniper/Utah serviceberry woodlands are dominated by five plant species 

(Table 14). These include the typical two-needle pinyon pine and Utah juniper open tree canopy, 

averaging 2-10 m (6.6-32.8 ft) in height (Von Loh et al. 2007). Utah serviceberry, saline wildrye 

(Leymus salina), and cheatgrass, a non-native invasive annual grass, are also dominant and provide 

moderate cover (Von Loh et al. 2007). There were 14 other associated plant species (Appendix B, 

column B), including three trees, seven shrubs, four graminoids, and five forb species (Von Loh et al. 

2007).

Table 14. Dominant plant species (by strata) within the two-needle pinyon-Utah juniper/Utah serviceberry 

woodlands (Von Loh et al. 2007). 

Two-needle pinyon-Utah juniper/Utah serviceberry woodland

Scientific Name Common Name Strata

Pinus edulis two-needle pinyon pine Tree canopy

Juniperus osteosperma Utah juniper Tree canopy

Amelanchier utahensis Utah serviceberry Tall shrub/sapling

Bromus tectorum* cheatgrass Herb

Leymus salina saline wildrye Herb

*Indicates a non-native species.

The two-needle pinyon-Utah juniper/Bigelow’s sagebrush (Artemisia bigelovii) woodlands are 

dominated by 2-5 m (6.6-16.4 ft) tall two-needle pinyon pine and Utah juniper trees which provide 2-

20% cover (Von Loh et al. 2007). Other dominant plants include Harriman’s yucca (Yucca 

harrimaniae), needle and thread, cheatgrass, James’ galleta (Hilaria jamesii), and hairy false 

goldenaster (Heterotheca villosa) (Von Loh et al. 2007). Many other plant species occur within this 

association (a total of 42) in various combinations; those observed in COLM are listed in Appendix 

B (column C) (Von Loh et al. 2007). Species of plants that were observed included three trees, 17 

shrubs, eight graminoids, and 14 forbs (Von Loh et al. 2007).
65

Table 15. Dominant plant species (by strata) within the two-needle pinyon-Utah juniper/Bigelow’s 

sagebrush woodlands (Von Loh et al. 2007). 

Two-needle pinyon-Utah juniper/Bigelow’s sagebrush woodland

Scientific Name Common Name Strata

Juniperus osteosperma Utah juniper Tree canopy

Pinus edulis two-needle pinyon pine Tree canopy

Artemisia bigelovii Bigelow's sagebrush Shrub/sapling

Yucca harrimaniae Harriman’s yucca Shrub/sapling

Bromus tectorum* cheatgrass Herb

Hesperostipa comata needle and thread Herb

Heterotheca villosa hairy false goldenaster Herb

Hilaria jamesii James’ galleta Herb

*Indicates a non-native species.

Two-needle pinyon-Utah juniper/black sagebrush woodlands are dominated by 14 species, including 

two-needle pinyon pines and Utah junipers which are around 2-10 m (6.6-32.8 ft) in height with 3-

35% canopy cover (Table 16; Von Loh et al. 2007). Additional plant species that occur in this 

alliance are listed in Appendix B (column D), and include three trees, 14 shrubs, eight graminoids, 

and 21 forbs for a total of 46 observed plant species (Von Loh et al. 2007).

Table 16. Dominant plant species (by strata) within the two-needle pinyon-Utah juniper/black sagebrush 

woodlands in COLM (Von Loh et al. 2007).

Two-needle pinyon-Utah juniper/black sagebrush woodland

Scientific Name Common Name Strata

Pinus edulis two-needle pinyon pine Tree Canopy/subcanopy

Juniperus osteosperma Utah juniper Tree Canopy/subcanopy

Artemisia nova black sagebrush Short shrub/sapling

Ephedra viridis Mormon tea Short shrub/sapling

Opuntia fragilis brittle pricklypear Short shrub/sapling

Opuntia polyacantha plains pricklypear Short shrub/sapling

Yucca harrimaniae Harriman’s yucca Short shrub/sapling

Achnatherum hymenoides Indian ricegrass Herb

Gutierrezia sarothrae broom snakeweed Herb

Heterotheca villosa hairy false goldenaster Herb

Hilaria jamesii James’ galleta Herb

Leptodactylon pungens prickly phlox Herb

Leymus salina saline wildrye Herb

Petradoria pumila rock goldenrod Herb

Two-needle pinyon-Utah juniper /littleleaf mountain-mahogany (Cercocarpus ledifolius var.

intricatus) woodlands are dominated by eight species of plants, which include the typical open tree 
66

canopy of two-needle pinyon pine and Utah juniper trees (Table 17; Von Loh et al. 2007). The tree 

canopy provides sparse coverage, between 1% and 15%, with average heights of 2-10 m (6.6-32.8 ft) 

(Von Loh et al. 2007). This alliance had a total of 33 plant species observed by Von Loh et al. 

(2007), including three tree, nine shrub, eight graminoid, and 13 forb species (Appendix B, column 

E).

Table 17. Dominant plant species (by strata) within the two-needle pinyon-juniper/ littleleaf mountainmahogany woodlands in COLM (Von Loh et al. 2007).

Two-needle pinyon-Utah juniper/littleleaf mountain-mahogany woodland

Scientific Name Common Name Strata

Pinus edulis two-needle pinyon pine Tree canopy

Juniperus osteosperma Utah juniper Tree canopy

Fraxinus anomala singleleaf ash Tall shrub/sapling

Artemisia bigelovii Bigelow’s sagebrush Short shrub/sapling

Cercocarpus ledifolius var. intricatus littleleaf mountain-mahogany Short shrub/sapling

Yucca harrimaniae Harriman’s yucca Short shrub/sapling

Achnatherum hymenoides Indian ricegrass Herb

Aristida purpurea purple three-awn Herb

Hesperostipa comata needle and thread Herb

The two-needle pinyon-Utah juniper/mixed shrubs talus woodlands of COLM have a diverse 

community composition dominated by 14 plant species (Table 18). Two-needle pinyon pine, Utah 

juniper, and an occasional singleleaf ash (Fraxinus anomala) form the open tree canopy (Von Loh et 

al. 2007). The canopy composition is variable between two tree species; with Utah juniper typically 

providing up to 45% cover while the two-needle pinyon pine provides up to 15% cover (Von Loh et 

al. 2007). A total of 45 plant species were observed within this association, including three trees, 14 

shrubs, 11 graminoids, and 17 forbs (Appendix B, column F; Von Loh et al. 2007).

Table 18. Dominant plant species (by strata) within the two-needle pinyon-Utah juniper/mixed shrubs 

talus woodlands in COLM (Von Loh et al. 2007). 

Two-needle pinyon-Utah juniper/mixed shrubs talus woodland

Scientific Name Common Name Strata

Pinus edulis two-needle pinyon pine Tree canopy

Juniperus osteosperma Utah juniper Tree canopy

Fraxinus anomala singleleaf ash Tall shrub/sapling

Artemisia bigelovii Bigelow’s sagebrush Short shrub/sapling

Ephedra viridis Mormon tea Short shrub/sapling

Opuntia erinacea grizzlybear pricklypear Short shrub/sapling

Achnatherum hymenoides Indian ricegrass Herb

Bouteloua gracilis blue grama Herb
67

Table 18 (continued). Dominant plant species (by strata) within the two-needle pinyon-Utah 

juniper/mixed shrubs talus woodlands in COLM (Von Loh et al. 2007). 

Two-needle pinyon-Utah juniper/mixed shrubs talus woodland

Scientific Name Common Name Strata

Pinus edulis two-needle pinyon pine Tree canopy

Juniperus osteosperma Utah juniper Tree canopy

Fraxinus anomala singleleaf ash Tall shrub/sapling

Artemisia bigelovii Bigelow’s sagebrush Short shrub/sapling

Ephedra viridis Mormon tea Short shrub/sapling

Opuntia erinacea grizzlybear pricklypear Short shrub/sapling

Achnatherum hymenoides Indian ricegrass Herb

Bouteloua gracilis blue grama Herb

Brickellia microphylla littleleaf brickellbush Herb

Bromus tectorum* cheatgrass Herb

Hesperostipa comata needle and thread Herb

vLeymus salina saline wildrye Herb

Poa fendleriana mutton grass Herb

Selaginella densa dense spikemoss Herb

*Indicates a non-native species.

Two-needle pinyon-Utah juniper/grassy rockgoldenrod (Petradoria pumila) woodlands are 

dominated by five plant species, including the usual two-needle pinyon pine and Utah juniper that 

create an open tree canopy (Table 19; Von Loh et al. 2007). The tree canopy is between 2-10 m (6.6-

32.8 ft) tall, with two-needle pinyon pine providing 1-5% cover and Utah juniper providing around 1-

25% cover (Von Loh et al. 2007). The 23 plant species observed within this alliance are listed in 

Appendix B (column G) and include two trees, five shrubs, five graminoids, and 11 forbs (Von Loh 

et al. 2007).

Table 19. Dominant plant species (by strata) within the two-needle pinyon-Utah juniper/grassy rockgoldenrod woodlands (Von Loh et al. 2007).

Two-needle pinyon-Utah juniper/grassy rockgoldenrod woodland

Scientific Name Common Name Strata

Pinus edulis two-needle pinyon pine Tree canopy

Juniperus osteosperma Utah juniper Tree canopy

Opuntia fragilis brittle pricklypear Shrub

Gutierrezia sarothrae broom snakeweed Herb

Petradoria pumila grassy rockgoldenrod Herb

Two-needle pinyon-Utah juniper/sparse understory woodlands are dominated exclusively by twoneedle pinyon pine and Utah juniper trees; therefore, a table of dominant species is not included for 

this alliance (Von Loh et al. 2007). The tree canopy provides anywhere from 1-45% cover with trees 
68

that are typically 2-10 m (6.6-32.8 ft) tall (Von Loh et al. 2007). According to Von Loh et al. (2007), 

this association has a total of 50 plant species, although, as the name implies, the understory is 

sparsely vegetated. The various plant species observed in these woodlands are listed in Appendix B

(column H) (Von Loh et al. 2007). There were three tree, 15 shrub, nine graminoid, and 23 forb 

species observed within this alliance (Von Loh et al. 2007).

Two-needle pinyon pine-Utah juniper/Wyoming big sagebrush woodlands are dominated by 12 plant 

species (Table 20; Von Loh et al. 2007). The two-needle pinyon pines provide 0-25% canopy cover 

and Utah junipers provide 2-65% canopy cover, with an average tree height of 2-5 m (6.6-16.4 ft) 

(Von Loh et al. 2007). A total of 45 plant species were observed in this alliance, including two trees, 

13 shrubs, 10 graminoids, and 20 forbs (Appendix B, column I; Von Loh et al. 2007).

Table 20. Dominant plant species (by strata) within the two-needle pinyon pine-Utah juniper-juniper 

species/(Wyoming big sagebrush, mountain big sagebrush) woodlands of COLM (Von Loh et al. 2007). 

Two-needle pinyon pine-Utah juniper/Wyoming big sagebrush woodland

Scientific Name Common Name Strata

Pinus edulis two-needle pinyon pine Tree canopy

Juniperus osteosperma Utah juniper Tree canopy

Artemisia bigelovii Bigelow’s sagebrush Short shrub/sapling

Artemisia tridentata ssp. wyomingensis Wyoming big sagebrush Short shrub/sapling

Ephedra viridis Mormon tea Short shrub/sapling

Opuntia fragilis brittle pricklypear Short shrub/sapling

Opuntia polyacantha plains pricklypear Short shrub/sapling

Yucca harrimaniae Harriman’s yucca Short shrub/sapling

Bromus tectorum* cheatgrass Herb

Descurainia pinnata ssp. halictorum western tansymustard Herb

Gutierrezia sarothrae broom snakeweed Herb

Hesperostipa comata needle and thread Herb

*Indicates a non-native species.

Two-needle pinyon-juniper species/mountain mahogany (Cercocarpus montanus)-mixed shrub 

woodlands are dominated by two-needle pinyon pines, Utah juniper trees, and six other plant species 

that are listed in Table 21 (Von Loh et al. 2007). The tree canopy consists of two-needle pinyon pine 

and Utah juniper, which are generally 2-5 m (6.6-16.4 ft) tall and provide 1-25% canopy cover (Von 

Loh et al. 2007). There was one individual ponderosa pine (Pinus ponderosa) tree observed within 

this alliance and it provided 40% canopy cover due to its large size, which is typical of this species 

(Von Loh et al. 2007). The total number of plant species observed within this alliance was 53 

(Appendix B, column J), including five trees, 20 shrubs, 10 graminoids, and 18 forbs (Von Loh et al. 

2007).
69

Table 21. Dominant plant species (by strata) within the two-needle pinyon-juniper species/mountainmahogany-mixed shrub woodlands of COLM (Von Loh et al. 2007). 

Two-needle pinyon-juniper species/mountain-mahogany-mixed shrub woodland

Scientific Name Common Name Strata

Juniperus osteosperma Utah juniper Tree canopy

Pinus edulis two-needle pinyon pine Tree canopy/Tree subcanopy

Cercocarpus montanus true mountain mahogany Tall shrub/sapling

Purshia mexicana var. stansburyana cliffrose Tall shrub/sapling

Ephedra viridis Mormon tea Short shrub/sapling

Bromus tectorum* cheatgrass Herb

Heterotheca villosa hairy false goldenaster Herb

Petradoria pumila grassy rockgoldenrod Herb

Tetraneuris acaulis Arizona hymenoxys Herb

*Indicates a non-native species.

The dominant tree species of two-needle pinyon-juniper species/saline wildrye grass woodlands is 

the Utah juniper (Von Loh et al. 2007). The open canopy consists of trees that are 2-5 m (6.6-16.4 ft) 

tall, ranging in cover from 1% to 25%, with surface cover of 1-15% provided primarily by 

bunchgrass (saline wildrye) (Von Loh et al. 2007). There were a total of 32 plant species observed in 

this alliance, including two trees, eight shrubs, five graminoids, and 17 forbs (Appendix B, column 

K; Von Loh et al. 2007).

Table 22. Dominant plant species (by strata) within the two-needle pinyon-juniper species/saline wildrye 

grass woodlands of COLM (Von Loh et al. 2007).

Two-needle pinyon-juniper species/saline wildrye grass woodland

Scientific Name Common Name Strata

Juniperus osteosperma Utah juniper Tree Canopy

Atriplex confertifolia shadscale Herb

Chrysothamnus viscidiflorus yellow rabbitbrush Herb

Leymus salina saline wildrye Herb

Blue spruce-two-needle pinyon-Utah juniper/Gambel’s oak woodlands are dominated by blue spruce, 

two-needle pinyon pine, Utah juniper, Utah serviceberry, Gambel’s oak, and skunkbush sumac (Rhus 

aromatica var. pilosissima) (Table 23, Von Loh et al. 2007). The Von Loh et al. (2007) description is 

based on one stand in Echo Canyon where the composition of graminoids and forbs could not be 

determined due to difficulty reaching its location. The stand that is described is the only one of its 

kind within the park, although a single blue spruce sapling was observed in Red Canyon (Von Loh et 

al. 2007). The total number of plant species that may occur in this woodland type is unknown, but the 

species identified by Von Loh et al. (2007) are listed in Appendix B, column L.
70

The plant species observed within these 12 alliances, a total of 108, serve as a baseline plant list for 

comparing and updating subsequent vegetation inventories and monitoring efforts in COLM (Von 

Loh et al. 2007). The plant species list includes six tree, 32 shrub, 15 graminoid, and 55 forb species. 

There may be additional plant species within these various vegetation associations. In particular, the 

blue spruce-two-needle pinyon-Utah juniper/Gambel’s oak woodland that was in a difficult to access 

location was not assessed in terms of the graminoid and forb composition. This association, and 

others, will likely have additional species added as the NCPN continues with inventory and 

monitoring efforts. Some pinyon-juniper woodlands/savannas may be the target of invasive plant 

management and may become free of cheatgrass in the future.

Table 23. Dominant plant species (by strata) within the blue spruce-two-needle pinyon-Utah 

juniper/Gambel’s oak woodlands in COLM (Von Loh et al. 2007).

Blue spruce-two-needle pinyon-Utah juniper/Gambel’s oak woodland

Scientific Name Common Name Strata

Juniperus osteosperma Utah juniper Tree canopy

Picea pungens blue spruce Tree canopy

Pinus edulis two-needle pinyon pine Tree canopy

Amelanchier utahensis Utah serviceberry Tall shrub

Quercus gambelii Gambel’s oak Tall shrub

Rhus aromatica var. pilosissima skunkbush sumac Tall shrub

Percent Cover Biological Soil Crusts

BSCs have been studied extensively in arid ecosystems and research has revealed the important role 

they play in these systems, particularly in protecting surfaces from wind erosion (Belnap 1992, 

KellerLynn 2006). These BSCs form as a dark, crumbly looking surface of unvegetated soil and are 

fragile and highly susceptible to disturbances such as grazing animals and human activities (Dunne 

1989). They form very slowly and are comprised of a microfloral entanglement that spans the surface 

and subsurface of soils, effectively holding soil, moisture, and organic matter essential to vegetation 

establishment in arid lands (Dunne 1989, Miller 2005). They consist of cyanobacteria, moss, lichens, 

and fungi, many of which contribute carbon and nitrogen to the nutrient cycles of typically nutrientpoor ecosystems (Miller 2005, KellerLynn 2006). 

BSC cover was briefly mentioned in Von Loh et al. (2007) for each vegetation classification. 

Although percent BSC cover was not a focus of this study, it provides a starting point for future 

assessments in order to make comparisons and identify trends in BSCs. BSCs are most developed in 

areas where there is adequate soil for them to develop upon. Some of the pinyon-juniper woodlands 

and savannas have very limited BSCs due to the lack of soil in those areas, particularly on rocky 

soils, areas with high surface litter cover, or where bedrock is exposed. The descriptions of BSC 

cover in the 12 various pinyon-juniper woodland/savanna alliance descriptions are given in Table 24

(Von Loh et al. 2007).
71

Table 24. Approximate BSC cover for each COLM pinyon-juniper community (Von Loh et al. 2007)

Community BSC Cover

Two-needle pinyon-(one-seed juniper, Utah juniper)/needle-and-thread woodlands Well-developed, but patchy

Two-needle pinyon-Utah juniper/Utah serviceberry woodlands Was not mentioned as being present in alliance description

Two-needle pinyon-Utah juniper/Bigelow’s sagebrush woodlands Variable with some stands having very little, occasionally up to 50%

Two-needle pinyon-Utah juniper/black sagebrush woodlands Variable with some stands having very little, occasionally up to 75%

Two-needle pinyon-Utah juniper/littleleaf mountain-mahogany woodlands Sparse due to very little soil in stands for establishment

Two-needle pinyon-Utah juniper/mixed shrubs talus woodlands Absent or sparse on these active slopes

Two-needle pinyon-Utah juniper/grassy rock-goldenrod woodlands Sparse, typically less than 5%

Two-needle pinyon-Utah juniper/sparse understory woodlands Variable with some stands having very little, occasionally up to 65%

Two-needle pinyon-Utah juniper/Wyoming big sagebrush woodlands Variable with some stands having very little, occasionally up to 20%

Two-needle pinyon-juniper species/mountain-mahogany-mixed shrub woodlands Variable with some stands having very little, occasionally up to 60%

Two-needle pinyon-juniper species/saline wildrye grass woodlands May be totally absent or up to 35%

Blue spruce-two-needle pinyon-Utah juniper/Gambel’s oak woodlands Was not mentioned as being present in alliance description
72

Percent Bare Ground

In areas within the pinyon-juniper woodland/savannas of COLM where the surface is unvegetated, 

the percentage of bare ground may be high. Bare ground lacks any surface cover, including standing 

or fallen dead vegetation, litter, gravel, rock, bedrock, or BSCs. Areas with bare ground are more 

prone to erosive forces and increased runoff. A greater exposure to sunlight can lead to higher 

evaporation and saltation (Belnap 1992). The vegetation descriptions in Von Loh et al. (2007) briefly 

mention the ground surface conditions for each community as well as general vegetative cover

percentages. In general, each of the pinyon-juniper woodlands/savannas was highly variable in the 

percent of bare ground, depending on where the observations were made. COLM has many areas 

with exposed bedrock where soil doesn’t tend to settle or accumulate unless there is something to 

hold it there, such as plant litter, rocks, gravel, or cracks and crevices. Table 25 summarizes 

vegetative cover and general ground surface conditions for each pinyon-juniper woodland/savanna 

vegetation alliance in COLM.
73

Table 25. Approximate vegetative cover for each COLM pinyon-juniper community along with notes on ground surface conditions (Von Loh et al. 

2007).

Community

Ground 

Cover Notes

Two-needle pinyon-(one-seed juniper, Utah juniper)/needle-and-thread woodlands 45% Mostly gravel and large rock

Two-needle pinyon-Utah juniper/Utah serviceberry woodlands 26-43% Bedrock, large and small rocks, low to moderate litter

Two-needle pinyon-Utah juniper/Bigelow’s sagebrush woodlands 11-44% Low to high bare soil 

Two-needle pinyon-Utah juniper/black sagebrush woodlands 15-68% Low to moderate bare soil

Two-needle pinyon-Utah juniper/littleleaf mountain-mahogany woodlands 15-44% Moderate to high rock and bedrock, sparse bare soil

Two-needle pinyon-Utah juniper/mixed shrubs talus woodlands 4-61% Low to high bare soil, bedrock, and rocks

Two-needle pinyon-Utah juniper/grassy rock-goldenrod woodlands 17-51% Moderate to high bare ground, bedrock, and litter

Two-needle pinyon-Utah juniper/sparse understory woodlands 8-47% Moderate to high gravel, rocks, and bedrock

Two-needle pinyon-Utah juniper/Wyoming big sagebrush woodlands 12-62% Low to moderate bare ground, bedrock and rocks

Two-needle pinyon-juniper species/mountain-mahogany-mixed shrub woodlands 10-45% High bedrock, rock, and bare ground (variable)

Two-needle pinyon-juniper species/saline wildrye grass woodlands 7-20% Moderate to high bare ground and rocks

Blue spruce-two-needle pinyon-Utah juniper/Gambel’s oak woodlands 59% High litter and downed wood, bare ground absent
74

Trends in Invasive Infestation

COLM is part of a long-term monitoring program for IEPs developed by the NCPN that focuses on 

early detection (Perkins 2014). The first survey of IEPs in the park was conducted in 2003 by Dewey 

and Anderson (2005). The latest monitoring was conducted during the 2013 field season and will be 

used to assess this measure, since it includes the previously collected data on IEP infestations in 

COLM. A full discussion of IEPs park-wide, including a discussion of trends can be found in 

Chapter 2.2.2. In summary, during this 8-year time span (2003-2011), there was an overall decrease 

in Russian olive, tamarisk and woolly mullein (Verbascum thapsus) (Perkins 2014). However, the 

number of field bindweed infestations more than doubled during this same period (Perkins 2014).

In the most recent survey, conducted in 2013, a total of 462 IEP infestation points were identified 

within the park (Perkins 2014). The most frequently documented species of IEP were yellow 

sweetclover and cheatgrass. Several pinyon-juniper alliances included cheatgrass, and in some, as a 

dominant plant species (Von Loh et al. 2007). Two-needle pinyon-Utah juniper/Utah serviceberry 

woodlands, two-needle pinyon-Utah juniper/Bigelow’s sagebrush woodlands, and two-needle 

pinyon-juniper species/mountain-mahogany-mixed shrub woodland descriptions all listed cheatgrass 

as a dominant herbaceous species (Von Loh et al. 2007). Alliances where cheatgrass was identified 

during vegetation mapping were two-needle pinyon-Utah juniper/black sagebrush woodlands, twoneedle pinyon-Utah juniper/littleleaf mountain-mahogany woodlands, two-needle pinyon-Utah 

juniper/grassy rock-goldenrod woodlands, two-needle pinyon-Utah juniper/sparse understory 

woodlands, and two-needle pinyon-juniper species/(Wyoming big sagebrush, mountain big 

sagebrush) woodlands (Von Loh et al. 2007).

Trends in invasive plants have not been assessed specifically by vegetation association at COLM. To 

identify invasive species infestations associated with pinyon-juniper communities, spatial queries 

were performed using the data from the 2013 IEP survey and select pinyon-juniper vegetation 

communities mapped by Von Loh et al. (2007). Not all of the pinyon-juniper communities identified 

by Von Loh et al. (2007) could be mapped using a polygon representation of their location. These 

were mapped using a point representation, as they did not meet the MMU standard. The spatial 

queries were run using only the vegetation communities that were mapped as polygons. The spatial 

queries selected IEP points that were either within a mapped location of pinyon-juniper woodland or 

within 100 m (328 ft) of one of these communities. The analysis identified 79 (approximately 17%) 

of the IEP points met the criteria (Figure 16, Table 26). The most common IEPs selected by these 

queries were yellow sweetclover (37) and cheatgrass (27). All but two of the yellow sweetclover 

occurrences were located within polygons representing pinyon-juniper communities. All of the 

cheatgrass occurrences were within 100 m (328 ft) of a pinyon-juniper community. The results for all 

IEP occurrences that satisfied the spatial queries can be found in Table 26.
75

Figure 16. IEP infestations associated with mapped pinyon-juniper woodland/savannas.
76

Table 26. Number and location of non-native species occurrences in relation to pinyon-juniper 

woodlands/savannas.

Scientific Name Common Name

Number

Within

Number 

Adjacent

Total 

Number

Melilotus officinalis yellow sweetclover 35 2 37

Bromus tectorum cheatgrass 27 27

Tamarix ramosissima saltcedar 4 4

Ulmus pumila Siberian elm 4 4

Elaeagnus angustifolia Russian olive 3 3

Convolvulus arvensis field bindweed 2 2

Poa bulbosa bulbous bluegrass 1 1

Cirsium vulgare bull thistle 1 1

Totals 50 29 79

Soil Stability

A direct assessment of soil stability in the pinyon-juniper woodlands/savannas has not been 

conducted. In general, soil stability is dependent upon the soil aggregate composition (i.e., amount of 

clay, sand, and organic matter) (USDA 2008). Soil aggregate stability determines the resilience of 

soil against erosive forces, specifically raindrop impact, water erosion, abrasion, and wind erosion 

(USDA 2008). Slope can also influence soil stability, as steeper slopes generally experience faster or 

more intense surface runoff and face more pressure from gravity.

In the dry, windswept, desert environment of COLM, the stability of soils is largely reliant on BSCs

(Belnap 1992, 1994; Miller 2005). The absence of this living armor leaves soil vulnerable to the 

erosive forces of wind and water. Bare soil is also less able to facilitate ecological functions such as 

water infiltration and seed germination (Belnap 1992). In general, the pinyon-juniper 

woodlands/savannas are found on well-drained sandy loam soils, with slopes ranging from gentle to 

steep (Von Loh et al. 2007). Vegetation descriptions by Von Loh et al. (2007) contain information on 

the make-up of the unvegetated surfaces in pinyon-juniper woodlands; however, specific data on the 

percent bare ground are not available. The unvegetated ground cover is generally comprised of 

mixtures of litter/duff, gravel and rocks, exposed bedrock, down wood, cryptogams, and bare ground 

(Von Loh et al. 2007).

Vulnerability to Climate Change

The pinyon-juniper woodlands/savannas communities at COLM were selected (along with Seeps and 

Springs and Tinaja Habitats [Chapter 4.4.5]) for additional analysis on their vulnerability to climate 

change (See Chapter 3.1.2). The vulnerability of the two-needle pinyon pine-Utah juniper woodlands 

will be assessed based on five factors: location within the community’s geographic range, sensitivity 

to extreme climatic events, dependence on hydrologic conditions, the community’s adaptive 

capacity, vulnerability of ecologically influential species, and the potential for climate change to 

increase the impacts of non-climate stressors. A detailed description of this methodology and 

definition of these five variables is presented in Chapter 3.3 of this report.
77

The two-needle pinyon pine and Utah juniper can be found throughout the southern Rocky 

Mountains region (Figure 17). Within COLM, the pinyon-juniper woodlands/savannas are found at 

elevations ranging from 1,472 to 2,518 m (4,829 to 8,261ft) and generally on north or east aspects, 

although they are found on other aspects throughout the park (Von Loh et al. 2007). COLM is 

located in the north-central portion of the pinyon pine latitudinal range and on the eastern edge of the 

central part of the Utah juniper latitudinal range (Figure 17).

Based on COLM’s location within the geographical ranges of pinyon pine and Utah juniper, this

alone would not cause them to be significantly vulnerable to an increase in temperature. These 

woodlands are adapted to cold winter minimum temperatures and low rainfall, and are often a 

transitional community between grassland or desert shrubland and montane conifer systems (Brown 

1994, Peet 2000).

Pinyon pine growth is strongly dependent on two climatic variables: the availability of sufficient 

precipitation prior to their growing season (winter through early summer), and cooler June 

temperatures (Barger et al. 2009). Both of these variables are projected to change to conditions that 

are less favorable for pinyon pine (Decker and Rondeau 2014). Climate models project warmer and 

drier (more arid) conditions for COLM by 2100 using the RCP 8.5 scenario. Summertime 

temperatures (June-August) at COLM are projected to increase by up to 5.7 °C (10.3 °F) by 2100 

(Figure 18, ClimateWizard 2014). Higher temperatures will result in greater evapotranspiration rates 

which, despite a predicted increase in annual precipitation, would lead to an increase in aridity in all 

seasons, especially fall (September-November) and spring (March-May) (Figure 19, ClimateWizard 

2014). Under the RCP 8.5 scenario, the climate models predict an increase in mean annual 

temperature of 4.8 °C (8.6 °F) with up to a nearly 17% increase in mean annual aridity (Figure 20, 

ClimateWizard 2014).
78

Figure 17. Current geographic extent of pinyon-juniper keystone species (two-needle pinyon pine and 

Utah juniper) used in the climate change vulnerability analysis. The geographic extents are from Little 

1971.
79

Figure 18. Change in mean A) winter, B) spring, C) summer, and D) fall seasonal temperatures for COLM 

by the year 2100 (ClimateWizard 2014). Temperatures are from the E50 ensemble with the RCP 8.5 

scenario; change is determined as the departure from a 1961-1990 baseline. A 1 °C change equals a 1.8 

°F change in temperature.

A. Mean winter temperature B. Mean spring temperature

C. Mean summer temperature D. Mean fall temperature
80

Figure 19. Change in mean A) winter, B) spring, C) summer, and D) fall seasonal aridity for COLM by the 

year 2100 (ClimateWizard 2014). Aridity values are presented as the change in the ratio of actual 

evapotranspiration to potential evapotranspiration. Aridity values are from the E50 ensemble with the 

RCP 8.5 scenario; change is determined as the departure from a 1961-1990 baseline.as the percent 

change from the baseline period of 1961-1990. A -0.15 change is equal to a 15% increase in aridity.

A. Mean winter aridity B. Mean spring aridity

C. Mean summer aridity D. Mean fall aridity
81

Figure 20. Changes in A) mean annual temperature and B) mean annual aridity for COLM by the year 

2100 (ClimateWizard 2014, NCCSC 2015). Temperature and aridity values are from the E50 ensemble 

with the RCP 8.5 scenario; change is determined as the departure from a 1961-1990 baseline.

Rehfeldt et al. (2006) conducted species-specific bioclimate modeling for a number of western tree 

species. The bioclimate model uses each species’ climate condition requirements (temperature, 

precipitation) and calculates how well the projected climate conditions match the current climate 

requirements, producing a map of viability scores for each species (Rehfleft et al. 2006). The higher 

the viability score, the closer the projected climate conditions are to the current climate requirements, 

and the more likely the species can be viable under the projected climate conditions (Rehfeldt et al. 

2006). The maps can be used to estimate the location and overall geographic extent where western 

tree species could be found under the various RCP scenarios. The results of the bioclimate mapping 

are considered to have a high degree of accuracy, as testing of the models produced current mapped 

climate profiles that were in good agreement with current range maps (Rehfeldt et al. 2006). The 

bioclimate modeling under the RCP 8.5 scenario for pinyon pine and Utah juniper shows a predicted 

shift, primarily to the north and somewhat eastward. The model also predicts that both species will be 

able to exist far to the northwest, extending as far north as the Okanagan Valley in British Columbia 

(Figure 21, Figure 22) (Rehfeldt et al. 2006). Within COLM, the bioclimate maps for pinyon pine 

and Utah juniper show an overall decline in each species’ viability scores by the year 2100 (Figure 

21, Figure 22) (Rehfeldt et al. 2006). The models predict a climate at COLM that is less than 60% 

compatible with current climate conditions for both pinyon pine and Utah juniper by 2100 (Figure 

21, Figure 22) (Rehfeldt et al. 2006). Overall, the projected climate under the RCP 8.5 scenario is at 

the low end of viability for both pinyon pine and Utah juniper.

A. Change in mean annual temperature B. Change in mean annual aridity
82

Figure 21. Modeled bioclimate profiles for pinyon pine (Rehfeldt 2006) overlaid on the digitized range 

maps of the current distribution (from Little 1991). Map A represents modeled total geographic extent for 

2060 and Map B represents the modeled total geographic extent for 2090. Maps C and D are the 

modeled results for 2060 and 2090, respectively, but are zoomed in to show the general area around 

COLM. The bioclimate profiles are based on the RCP 8.5 scenario. The values are species viability 

scores in the range of 0 to 100%, where low numbers indicate that the climate is not consistent with 

where the species grows and high numbers indicates consistency (0%–20%, no color; 20%–40%, lightest 

green; 40%–60%, light green; 60%–80% dark green; and 80%–100%, darkest green).

A. Bioclimate profile for 2060 B. Bioclimate profile for 2090

C. Bioclimate profile for COLM area in 2060 D. Bioclimate profile for COLM area in 2090
83

Figure 22. Modeled bioclimate profiles for Utah juniper (Rehfeldt 2006) overlaid on the digitized range 

maps of the current distribution (from Little 1991). Map A represents modeled total geographic extent for 

2060 and Map B represents the modeled total geographic extent for 2090, Maps C and D are the 

modeled results for 2060 and 2090, respectively, but are zoomed in to show the general area around 

COLM. The bioclimate profiles are based on the RCP 8.5 scenario. The values are species viability 

scores in the range of 0 to 100%, where low numbers indicate that the climate is not consistent with 

where the species grows and high numbers indicates consistency (0%–20%, no color; 20%–40%, lightest 

green; 40%–60%, light green; 60%–80% dark green; and 80%–100%, darkest green).

A. Bioclimate profile for 2060 B. Bioclimate profile for 2090

C. Bioclimate profile for COLM area in 2060 D. Bioclimate profile for COLM area in 2090
84

The climate models’ predictions for extended periods of drought has the potential to cause greater 

tree mortality, especially in pinyon pine, as it is more susceptible to drought than the Utah juniper 

(Breshears et al. 2008). The drought experienced in 2002-2003 has been associated with mortality in 

pinyon pine and Utah juniper in the Southwest (Richardson et al. 2012). Extended periods of drought 

can also increase the frequency and intensity of insect outbreaks and wildfire (Miller 2005, Decker 

and Rondeau 2014). Pinyon pine are also susceptible to the fungal pathogen Leptographuum 

wageneri var. wageneri, which causes black stain root disease and infestations of the pinyon ips bark 

beetle (Ips confusus) (Kearns and Jacobi 2005, Miller 2005). During the drought of early 2000, 

pinyon pine and Utah juniper mortality increased at COLM, believed to be due to a root fungus that 

was likely exacerbated by drought (NPS 1999). While both species are susceptible to drought, the 

differences in the degree of susceptibility of pinyon pine and juniper could result in these woodlands 

becoming dominated by juniper under the projected climate conditions for the RCP 8.5 scenario 

(Decker and Rondeau 2014).

The pinyon-juniper woodlands are expected to have significant adaptive capacity. These woodlands 

are tolerant to the warmer, more arid climate currently being projected by the climate models under 

the RCP 8.5 scenario. Since the last glacial period, the distribution of the pinyon-juniper woodlands 

and their abundance has fluctuated with changing climate conditions (Decker and Rondeau 2014). 

Warming conditions over the last two hundred years, along with other factors such as changing fire 

regimes and nutrient enrichment from atmospheric pollution, have increased the potential for this 

community to expand into neighboring vegetation communities at higher and lower elevations 

(Tausch 1999). Both pinyon pine and Utah juniper have large ecological amplitudes, and are suited to 

the warmer, more arid conditions projected by the climate models under the RCP 8.5 scenario 

(Decker and Rondeau 2014).

As discussed in Chapter 2.1.2, the GCMs predict higher temperatures and slight increases in 

precipitation for this region. While there is a slight projected increase in precipitation, the higher 

temperatures (for all seasons) will create higher evapotranspiration rates, ultimately resulting in drier 

conditions. These hotter and drier conditions expected in COLM over the next century will likely 

exacerbate many of the current non-climate stressors of the pinyon-juniper woodland plant 

community. Researchers believe that drought and warmth across western North America over the 

past decade have already led to extensive insect outbreaks and increased mortality in many forest 

types (Miller 2005, Breshears et al. 2008, Allen et al. 2010, Richardson et al. 2012). Higher summer 

temperatures typically accelerate the development and reproductive rates of insects, while drought 

stress may increase many tree species’ vulnerability to insect attack (Allen and Breshears 1998, 

Kearns and Jacobi 2005, Miller 2005, Ayers and Lombardero 2000, Allen et al. 2010) and previous 

vulnerability assessments may have underestimated the mortality rate due to this synergy (Allen et al. 

2015).

It is difficult to assess how the warmer and drier conditions predicted for COLM will affect the nonnative plants already invading the pinyon-juniper communities. While Dukes and Mooney (1999) 

suggested that most aspects of global climate change will favor non-native species over natives, it is 

unknown if this pattern will apply to already arid environments such as COLM. The non-native 
85

species already present in COLM (Figure 16, Table 26) would likely be tolerant of warmer 

conditions, but may not survive the even drier predicted conditions. Drier conditions may also 

increase the potential for wildfires, which could be more intense due to the presence of invasive 

annual grasses in the understory of pinyon-juniper woodlands (Decker and Rondeau 2014).

Threats and Stressor Factors

There are several factors that are a concern in terms of the pinyon-juniper woodland/savannas at 

COLM. Park resource manager identified IEPs, unnatural fire regimes, social trails, drought, and 

climate change as the primary concerns in terms of this resource.

Exotic invasive species are a formidable threat to the pinyon-juniper woodland/savannas. IEPs 

disrupt the natural structure of native vegetation communities by displacing both plants and animals 

that are native to the community (Perkins 2014). Invasive plants can also alter the natural fire regime 

by accumulating fuels (e.g., dead grass) on the ground, a critical danger to pinyon-juniper 

woodland/savannas (Kennard and Moore 2013).

Altered fire intervals are a serious threat to the pinyon-juniper woodland/savannas, particularly where 

large, stand-replacing fires were historically infrequent (Kennard and Moore 2013). Kennard and 

Moore (2013) studied the fire histories of some of COLM’s pinyon-juniper woodland/savannas to 

identify drivers of community structure. The results indicated that these woodlands and savannas 

have very long (588-1,428 years) fire rotations, particularly in persistent stands like those found on 

mesa tops in COLM (Kennard and Moore 2013). Lighting-ignited fires are not uncommon; however 

they tend to be small in size, at times burning only a single tree (Kennard and Moore 2013). Fire 

within pinyon-juniper habitats can lead to conditions where these habitats are replaced by grasslands 

dominated by invasive species. Considering these findings, using prescribed burning as a 

management tool would likely prove detrimental to the pinyon-juniper woodland/savannas in 

COLM, since cheatgrass is present and has the potential of expanding its cover with fire.

Visitor impacts within the park’s pinyon-juniper habitats include damage to BSC present within these 

environments. Hikers, particularly those using unauthorized “social” trails, cause damage to these 

fragile habitats and the continued disturbance does not allow for the time needed for BSCs to 

regenerate. This can lead to invasive species encroaching and potentially replacing BSC habitats.

As a result of climate change, droughts are projected to increase in frequency, intensity, and duration 

throughout the southwestern states, including Colorado (Garfin et al. 2014). Extreme precipitation 

events, which often cause soil erosion, are also projected to increase in frequency and intensity 

(Garfin et al. 2014, Melillo et al. 2014). Temperatures will rise, accelerating evaporation and 

transpiration rates, and putting plants under further moisture stress (Garfin et al. 2014).

Data Needs/Gaps

A lack of an explicitly focused study on the pinyon-juniper woodland/savannas’ soil stability, percent 

cover of CBC and bare ground makes an assessment of current condition difficult. There are some 

brief descriptions of soil type, percent tree canopy cover, and the unvegetated surface composition in 

Von Loh et al. (2007). These provide a starting point for future research, as mentioned in the 
86

descriptions above. In addition, more information is needed on how the effects of a warmer, drier 

climate will change the non-native species composition of the pinyon-juniper woodlands. Research 

on the impacts from the proliferation of social trails within the park is also recommended.

Currently a guaranteed funding source for the invasive species removal/control has not been 

identified. Failure to secure funding for this management action will result in the loss of the gains 

that have been made in eradicating IEPs within the park. Additionally, another programmatic need 

for COLM is a trail management plan. Currently, visitors face no restrictions in their access to any 

areas within the park.

Overall Condition

Community Extent and Change over Time

A Significance Level of 3 was assigned to the community extent and change over time measure. In 

several western states, the extent of pinyon-juniper woodlands/savannas has reportedly increased, as 

they have encroached into sagebrush communities (Soule et al. 2003, Johnson 2013). Johnson (2013) 

concluded that pinyon-juniper woodlands potentially have expanding into the park’s sagebrush 

shrublands, which suggests that woodland extent has increased, or at least has not decreased.

Therefore, a Condition Level of 1 has been assigned, indicating low concern.

Community Composition

The community composition measure was assigned a Significance Level of 3. Von Loh et al. (2007) 

reports plant species lists for each of the 12 pinyon-juniper alliances within COLM. The presence of 

non-native plants within these alliances, in some cases as a dominant species, indicates somewhat 

serious degradation to the community (Von Loh et al. 2007). Based on the assumption that the 

original community composition included only native plants, the Condition Level was assigned a 2.

Percent Cover Biological Soil Crusts

The percent cover of BSC is largely a data gap, with only superficial estimates of the amount of BSC 

coverage described in Von Loh et al. (2007). This measure was assigned a Significance Level of 3, 

but cannot be assigned a Condition Level at this time. The percentage estimates described in the 

vegetation mapping field data (Von Loh et al. 2007) may be useful in assessing this measure in 

subsequent studies.

Percent Bare Ground

This measure was assigned a Significance Level of 2. The bare ground coverage was described 

briefly in Von Loh et al. (2007), but was not reported as an actual percentage. The descriptions are of 

the general surface conditions, not specific to bare ground. For this reason, a Condition Level cannot 

be assigned at this time.

Trends in Invasive Infestation

This measure was assigned a Significance Level of 3 by the project team. Over the last decade the 

park has focused control efforts on eradication of IEP’s. Future funding for these control measures is 

not available, so the potential for increased infestations is high (Hartwig, written communication 18 

November 2015). Considering this along with the presence of IEPs within the pinyon-juniper 
87

woodland/savannas detected in recent years, as well as several pinyon juniper woodland/savanna 

alliances now having cheatgrass as a dominant member of the community (Von Loh et al. 2007), the 

Condition Level has been assigned a 2.

Soil Stability

The soil stability measure was assigned a Significance Level of 2 and is largely a data gap. Von Loh 

et al. (2007) does provide short descriptions of soil type and percent slope, although this doesn’t 

address all parameters needed to assess overall soil stability in the pinyon-juniper 

woodland/savannas. A Condition Level cannot be assigned at this time since soil stability parameters 

have not been directly assessed in the pinyon-juniper woodland/savannas.

Climate Change Vulnerability Assessment

Analysis of the pinyon-juniper community within COLM showed that it is moderately vulnerable to 

the projected impacts to climate change, with an overall score of 17 (Table 27). While the confidence 

in the assessment is within the high range, with a value of 15, half of the variable scores were rated 

as “moderate” confidence due to a number of factors.

Table 27. Certainty and alternative vulnerability scores for woodland plant community assessment 

variables.

Variable

Certainty 

Score1

Vulnerability 

Score2

Alternative 

Scores3

Location in geographical range/distribution of plant community 2 4 3

Sensitivity to extreme climatic events (e.g., drought, flash 

floods, windstorms)

3 3

Dependence on specific hydrologic conditions 3 1

Intrinsic adaptive capacity 3 3

Vulnerability of ecologically influential species to climate 

change

2 3 4

Potential for climate change to exacerbate impacts of nonclimate stressors2 3 4

Total 15 17 16-19

1For individual variables, certainty scores are 3 = high, 2 = moderate, and 1 = low

2The certainty ranges are 6-10 = low confidence, 11-14 = moderate confidence, 15-18 = high 

confidence

3The vulnerability ranges are 6-13= least vulnerable, 14-19 = moderately vulnerable, 20-25 = highly 

vulnerable, 26-30 = critically vulnerable

To address some of the uncertainty within this assessment, alternative scores were identified for 

several variables in addition to the best estimate scores (Table 27). Alternative scores create a range 

of likely vulnerability for the plant community. The “location in the geographic range/distribution of 

the plant community” and the “vulnerability of ecologically influential species to climate change” 

variables were assigned alternative scores due to the variations in the climate models’ seasonal and 

annual precipitation projections. The potential for climate change to exacerbate impacts of nonclimate stressors was given an alternative score due to uncertainty of what effect the warmer, dryer 
88

climate would have on non-native species. When factored in, the range of vulnerability scores for the 

pinyon-juniper woodland community is 16 to 19, all of which are still within the “moderately 

vulnerable” category. With the high confidence certainty score, this suggests that, despite some 

uncertainty in climate projections and individual community variables, the classification of pinyonjuniper woodlands as moderately vulnerable appears fairly robust. The scoring worksheet developed 

for the pinyon-juniper woodlands is included in Appendix C.

Weighted Condition Score

The Weighted Condition Score for pinyon-juniper woodland/savannas is 0.56, which indicates 

moderate concern. This WCS is primarily due to the widespread presence of IEP species, which are 

major threats to the ecological health of the pinyon-juniper woodland/savannas in COLM.

Pinyon-juniper Woodlands/Savannas

Measures Significance Level Condition Level WCS = 0.56

Community Extent and 

Change over Time 3 1

Community 

Composition 3 2

Percent Cover 

Biological Soil Crusts 3 n/a

Percent Bare Ground 2 n/a

Trends in Invasive 

Infestation 3 2

Soil Stability 2 n/a

4.1.6 Sources of Expertise

Dusty Perkins, Program Manager, Northern Colorado Plateau Network

Nicholas Fisichelli Ph.D., Ecologist NPS Climate Change Response Program

Dr. Deborah Kennard, Colorado Mesa University

Marian Talbert, Research Statistician North Central Climate Science Center

Rebecca Weissinger, Ecologist NPS Northern Colorado Plateau Network

Dana Witwicki, Ecologist NPS Northern Colorado Plateau Network
89

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4.2 Sagebrush Shrublands/Shrub Steppe

4.2.1 Description

The sagebrush shrublands/shrub steppe 

association within COLM is comprised of the 

following plant communities: basin big 

sagebrush/cheatgrass semi-natural shrubland, 

black sagebrush and grasses shrublandgraminoids, Wyoming big sagebrush/seeded 

grasses semi-natural shrubland, and Wyoming 

big sagebrush shrubland (Von Loh et al. 2007). 

The primary sagebrush species found within 

these communities are: basin big sagebrush, 

Wyoming big sagebrush, and black sagebrush 

(Von Loh et al. 2007).

Basin big sagebrush/cheatgrass semi-natural 

shrubland communities within COLM are found 

on gentle slopes (0-10%) between 1,524 and 

1,926 m (5,000 and 6,319 ft) in elevation (Von 

Loh et al. 2007). Soils are generally loamy sand, sandy loam, silt loam, or clay loam (Von Loh et al. 

2007). This community is found along drainages or on terraces along the canyon bottom drainages 

and on alluvial fans (Von Loh et al. 2007).

Black sagebrush and grasses shrubland-graminoids communities are generally found on relatively 

gentle slopes (4-18%) between 1,641 and 1,983 m (5,384 and 6,506 ft) in elevation (Von Loh et al. 

2007). This community is found on the midslopes of hills and ridges and on an erosion fan with clay 

loam or silty clay soils (Von Loh et al. 2007).

Wyoming big sagebrush/seeded grasses semi-natural shrubland communities can be found on gentle 

slopes (2-10%) between 2,024 and 2,128 m (6,640 and 6,982 ft) in elevation with sandy loam or 

loamy sand soils (Von Loh et al. 2007). This community is found on mesa tops to the west and south 

of No Thoroughfare Canyon (Von Loh et al. 2007).

Wyoming big sagebrush shrubland communities are found on gentle to moderately steep (0-30%) 

slopes between 1,439 and 2,147 m (4,721 and 7,044 ft) in elevation (Von Loh et al. 2007). Soils are 

generally sandy loam (Von Loh et al. 2007). This community is found on the midslopes of canyons, 

along washes, in swales, valleys, and canyons, on both mesa tops and plains, and along drainage 

benches and terraces (Von Loh et al. 2007).

Basin big sagebrush/alkali sacaton (Sporobolus airoides) shrubland can be found approximately 2 

km (1.2 mi) north of the Monument Canyon trailhead, adjacent to the eastern boundary fence. This 

community was observed in a narrow gully at the toeslope of a low ridge. This site has a gentle slope 

(9%) and occurred at 1,873 m (6,145 ft) in elevation. Soils at this location are silty clay (Von Loh et 

al. 2007).

Photo 5. Big Sagebrush (Artemisia tridentata) 

(NPS Photo).
94

Wyoming big sagebrush – shadscale (Atriplex confertifolia) shrubland can be found near the east 

entrance, adjacent to the park boundary fence. This community was observed on the midslopes of a 

hill. This site has a gentle slope (9%) and occurred at 1,438 m (4,718 ft) in elevation with silty clay 

soils (Von Loh et al. 2007).

Sagebrush shubland/shrub steppe communities at COLM support a variety of wildlife species. These 

communities provide shade, shelter and nesting/burrowing sites for a variety of small animals

(Hanophy and Teitelbaum 2003). Reptile species such as the eastern collared lizard and the sideblotched lizard (Uta stansburiana) can be found within the sagebrush shrublands (Hanophy and 

Teitelbaum 2003). The California myotis (Myotis californicus) is known to roost in sagebrush 

(Hanophy and Teitelbaum 2003). Mexican woodrats (Neotoma mexicana), deer mice (Peromyscus 

maniculatus), Ord’s kangaroo rat (Dipodomys ordii), and black-tailed jackrabbits (Lepus 

californicus) are some of the small rodents that can be found in these habitat (Hanophy and 

Teitelbaum 2003). Red-tailed hawks, owls, coyotes, and gray fox actively forage for prey within 

these vegetation communities (Hanophy and Teitelbaum 2003). Large mammals such as mule deer

and elk also forage in these habitats (Hanophy and Teitelbaum 2003). Several avian species are 

closely associated with sagebrush habitat including the sage sparrow (Artemisiospiza belli) and the 

sage thrasher (Oreoscoptes montanus) (Hanophy and Teitelbaum 2003). Other birds commonly 

found in these habitats include the western scrub jay (Aphelocoma californica) and horned lark

(Eremophila alpestris) (Hanophy and Teitelbaum 2003).

4.2.2 Measures

 Community extent and change over time

 Community composition

 Percent cover biological soil crusts

 Percent bare ground

 Trends in invasive infestation

 Soil stability

 Canopy gap size

4.2.3 Reference Conditions/Values

An ideal reference condition for this component would use the natural variability of the current 

system, particularly in the center of COLM away from the boundary (e.g., Liberty Cap Trail). 

However, not enough information is available regarding the range of variability for the selected 

measures to determine clear reference conditions at this time. Conditions will be assessed based on 

best professional judgment given the available data.

4.2.4 Data and Methods

A vegetation mapping project by Von Loh et al. (2007) shows the locations of all dominant cover 

types present in COLM in the early 2000s. The methodology for this project included vegetation 

classification and attribute development based on the NVC, field reconnaissance and mapping, and 

development of a spatial database. The study area for the project included COLM, plus an additional 
95

area beyond the park border. Mapping was completed using both traditional photo interpretation and 

biophysical modeling. This allowed for consistent and accurate mapping in a cost effective manner. 

The project resulted in vegetation data and maps for COLM and its immediate vicinity.

The impacts of pinyon-juniper woodland encroachment were analyzed by Johnson (2013). This study 

used aerial photos from 1937 and 2007 to determine the change in sagebrush shrubland habitat within 

a portion of COLM. Polygons were delineated for each photo using ArcMapTM and area was 

calculated allowing for both visual and numerical comparisons.

Hogan et al. (2009) developed a comprehensive list of plant species found within the park (Appendix 

D). This effort involved reviewing existing literature and re-examining specimens in the COLM 

herbarium. It also included field work to confirm unverified species and to potentially locate new 

species. This list includes plants by habitat type, one of which is sage shrub, which includes plants 

from “communities dominated by big sagebrush” (Hogan et al. 2009).

Invasive non-native plant species monitoring and mapping has occurred since 2003 (Dewey and 

Anderson 2005). The NCPN completed the most recent inventory in 2013 (Perkins 2014). Perkins 

(2014) was based on a list of priority IEPs that had been developed by the staff at COLM and the 

NCPN. A minimum detection target size (MDTS) of 40 m2(431 ft2or approximately 20 x 20 ft) was 

also established for use in the ongoing monitoring program. Monitoring routes and quadrats were 

established along the roads, major drainages, and trails in the park. In addition to invasive exotic 

species composition, information was collected on several other attributes, including infestation size 

and cover (Perkins 2014).

4.2.5 Current Condition and Trend

Community Extent and Change over Time

Von Loh et al. (2007) represents the most recent estimate of sagebrush shrublands/shrub steppe 

extent in the park. Data from this vegetation mapping projects shows that sagebrush shrublands/shrub 

steppe comprise 819 ha (2,023 ac), or approximately 10% of the COLM landscape (Table 28, Figure 

23). Black sagebrush and grasses shrubland-graminoids communities within COLM can be found at 

the western Liberty Cap trailhead and adjacent to the Liberty Cap Trail. Basin big sagebrush/ 

cheatgrass semi-natural shrubland communities within COLM can be found in upper and middle Ute 

Canyon, upper and lower No Thoroughfare Canyon, near the East Entrance, and in Fruita Canyon 

(Von Loh et al. 2007).Wyoming big sagebrush/seeded grasses semi-natural shrubland communities 

within COLM can be found on the mesa south of No Thoroughfare Canyon to Little Park Road, on 

the west end of Old Gordon Road (Trail) and along DS Road (Von Loh et al. 2007).
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Table 28. Areal extent of sagebrush shrublands/shrub steppe alliances found in COLM (Von Loh et al. 

2007).

Percentage

Alliances

Area

ha (ac)

Sagebrush

shrublands/shrub steppe

Total 

Vegetation

Basin big sagebrush/cheatgrass

semi-natural shrubland

209.4 (84.7) 10.4% 1.0%

Black sagebrush and grasses

shrubland-graminoids

664.6 (268.9) 32.9% 3.2%

Wyoming big sagebrush/seeded

grasses semi-natural shrubland

347.4 (140.6) 17.2% 1.7%

Wyoming big sagebrush

shrubland

801.3 (324.3) 39.6% 3.9%

Sagebrush shrublands/shrub steppe total 2,022.7 (818.5) 100%

Park total 20,450 (8,275.8)

Wyoming big sagebrush shrubland communities within COLM can be found near Liberty Cap trail, 

at the mouth of Lizard Canyon, east of Kissing Couple in Monument Canyon, upper Monument 

canyon, near the Rim Rock Drive, on the mesa north of Red Canyon, on Rimrock Drive near the 

head of Ute Canyon, west of Columbus Canyon, mesa south of Ute Canyon, along Glade Park Road, 

on the No Thoroughfare Canyon Mesa, near the mouth of Monument Valley, south of Devil’s 

Kitchen Trail, near the park’s western boundary, and east of the Cold Shivers turnout (Von Loh et al. 

2007).

Two-needle pinyon and Utah juniper are the dominant woodland species in COLM (Von Loh et al. 

2007). For the past 150 years, they have expanded into sagebrush shrublands/shrub steppe habitats as 

they have become more broadly distributed and formed denser woodlands (Soulé et al. 2003). The 

sagebrush shrublands/shrub steppe are being crowded out and out-competed by the expanding 

pinyon-juniper woodlands (Johnson 2013). According to Johnson (2013), the loss of sagebrush 

shrubland/shrub steppe due to the expansion of woodland species ranged from approximately 10% to 

30% in certain areas of COLM over the past 70 years. As stated previously, distortions in the 1937 

imagery do not allow for an exact determination of percent change (Kennard, written communication 

18 November 2015). Ocular examination of the differences in the imagery does suggest that 

sagebrush shrubland/shrub steppe habitat has been lost to pinyon-juniper encroachment (Johnson 

2013). It is unclear if this is the result of human influence, an environmental change, or simply a 

natural successional process. 
97

Figure 23. The location of sagebrush shrubland/shrub steppe alliances within COLM (Von Loh et al. 

2007).

Community Composition

A comprehensive plant species list was developed by Hogan et al. (2009). A total of 289 plant 

species were identified that are either “present” or “reported” in sagebrush shrublands/shrub steppe

communities (Appendix D). Species were considered present if a confirmed specimen or observation 

has been made since 1970. Species were considered reported if they have been listed in existing 
98

literature (Hogan et al. 2009). This total was comprised of three trees, 42 shrubs, 142 perennial forbs, 

52 annual forbs, 35 perennial graminoids, 14 annual graminoids, and one fern (Hogan et al. 2009). Of 

these plants, 48 (16.6%) are introduced species while the remaining 241 (83.4%) are native species 

(NPS 2015).

The black sagebrush and grasses shrubland-graminoids communities contain a diverse shrub layer 

that includes black sagebrush, shadscale, yellow rabbitbrush (Chrysothamnus viscidiflorus) Torrey’s 

Mormon tea (Ephedra torreyana), Mormon tea, spiny hopsage (Grayia spinosa), broom snakeweed

(Gutierrezia sarothrae), winterfat (Krascheninnikovia lanata), claretcup (Echinocereus 

triglochidiatus), Mojave pricklypear (Opuntia phaeacantha var. major), and plains pricklypear

(Opuntia polyacantha) (Von Loh et al. 2007). The herbaceous layer is diverse but sparse, including 

graminoids such as Indian ricegrass (Achnatherum hymenoides), cheatgrass, six weeks fescue (Vulpia 

octoflora), needle and thread, James' galleta, muttongrass (Poa fendleriana), and Sandberg’s 

bluegrass (Poa secunda) and forbs such as Fendler’s sandwort (Eremogone fendleri), Gunnison’s 

mariposa (Calochortus gunnisonii), western tansymustard (Descurainia pinnata ssp. halictorum), 

dwarf draba (Draba reptans), Arizona hymenoxys (Tetraneuris acaulis), western stickseed (Lappula

occidentalis var. occidentalis), grassy rockgoldenrod, and scarlet globemallow (Sphaeralcea 

coccinea ssp. coccinea) (Von Loh et al. 2007). The most abundant species within this community by 

stratum can be found in Table 29.

Table 29. Dominant plant species (by strata) within the black sagebrush and grasses shrublandgraminoids community of COLM (Von Loh et al. 2007).

Black sagebrush and grasses shrubland-graminoids

Scientific Name Common Name Strata

Artemisia nova black sagebrush Short shrub/sapling

Achnatherum hymenoides Indian ricegrass Herb

Hesperostipa comata needle and thread Herb

Hilaria jamesii James' galleta Herb

Lappula occidentalis var. occidentalis western stickseed Herb

Poa fendleriana muttongrass Herb

Sphaeralcea coccinea ssp. coccinea scarlet globemallow Herb

Tetraneuris acaulis Arizona hymenoxys Herb

The basin big sagebrush/cheatgrass semi-natural shrubland communities are characterized by an open 

to closed canopy of basin big sagebrush, typically 1 to 5 m (3 to 16 ft) tall (Von Loh et al. 2007). 

Skunkbush sumac is also present in this community, though it represents less than 5% of the total 

cover (Von Loh et al. 2007). A few trees are present, providing up to 3% cover (Von Loh et al. 

2007). These trees include Utah juniper and two-needle pinyon and are typically 2 to 5 m (7 to 16 ft) 

tall (Von Loh et al. 2007). Other short and dwarf shrubs that contribute sparse to low cover in these 

communities include fourwing saltbush, Mormon tea, rubber rabbitbrush (Ericameria nauseosa), 

fringed sagebrush (Artemisia frigida), broom snakeweed, Mojave pricklypear, and plains pricklypear

(Von Loh et al. 2007). The herbaceous layer is generally sparse, though can have high cover of 
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cheatgrass (Von Loh et al. 2007). Other graminoids in this community include Indian ricegrass, 

squirreltail (Elymus elymoides), six weeks fescue, needle and thread, foxtail barley (Hordeum 

jubatum), muttongrass, and sand dropseed (Sporobolus cryptandrus) (Von Loh et al. 2007). Forbs 

commonly found in this community include tapertip onion (Allium acuminatum), goosefoot 

(Chenopodium spp.), western tansymustard, flixweed (Descurainia sophia), smallflower dragonhead 

(Dracocephalum parviflorum), stork’s bill (Erodium cicutarium), scarlet gilia (Ipomopsis aggregata 

ssp. aggregata), prickly lettuce (Lactuca serriola), western stickseed, mountain pepperweed

(Lepidium montanum), woolly plantain (Plantago patagonica), western groundsel (Senecio 

integerrimus), and tumble mustard (Sisymbrium altissimum) (Von Loh et al. 2007). The most 

abundant species within this community by stratum can be found in Table 30.

Table 30. Dominant plant species (by strata) within the basin big sagebrush/cheatgrass semi-natural 

shrubland community of COLM (Von Loh et al. 2007).

Basin big sagebrush/cheatgrass semi-natural shrubland community

Scientific Name Common Name Strata

Artemisia tridentata ssp. tridentata basin big sagebrush Tall shrub/sapling

Rhus aromatica var. pilosissima skunkbush sumac Tall shrub/sapling

Atriplex canescens fourwing saltbush Short shrub/sapling

Ericameria nauseosa rubber rabbitbrush Short shrub/sapling

Bromus tectorum* cheatgrass Herb

Hesperostipa comata needle and thread Herb

Lappula occidentalis var. occidentalis western stickseed Herb

Sporobolus cryptandrus sand dropseed Herb

*Indicates a non-native species.

The Wyoming big sagebrush/seeded grasses semi-natural shrubland communities are characterized 

by Wyoming big sagebrush and crested wheatgrass (Agropyron cristatum). These two species 

account for 4 to 40% cover and 1 to 25% cover, respectively (Von Loh et al. 2007). When present, a 

tree canopy of Utah juniper and two-needle pinyon (typically 2 to 5 m [7 to 16 ft] tall) provide up to 

8% cover (Von Loh et al. 2007). The remaining short/dwarf shrub layer is generally low in diversity 

and cover and includes yellow rabbitbrush, rubber rabbitbrush, Utah juniper, two-needle pinyon, 

tarragon (Artemisia dracunculus), fringed sagebrush, broom snakeweed, brittle pricklypear (Opuntia 

fragilis), and plains pricklypear (Von Loh et al. 2007). The herbaceous layer is also low in diversity 

and cover (Von Loh et al. 2007). Graminoids present include Indian ricegrass, purple three-awn 

(Aristida purpurea), blue grama (Bouteloua gracilis), cheatgrass, squirreltail, six weeks fescue, 

needle and thread, muttongrass, and sand dropseed (Von Loh et al. 2007). Forbs commonly found in 

this community include hoary dusty-maiden (Chaenactis douglasii), wavy-leaf thistle (Cirsium 

undulatum var. undulatum), western tansymustard, dwarf draba, hairy goldenaster, western stickseed, 

silvery lupine (Lupinus argenteus), sweetclover species (Melilotus spp.), pale evening primrose 

(Oenothera pallida ssp. trichocalyx), woolly plantain, western groundsel, and scarlet globemallow 

(Von Loh et al. 2007). The most abundant species within this community by stratum can be found in 

Table 31.
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Table 31. Dominant plant species (by strata) within the Wyoming big sagebrush/seeded grasses semi 

natural shrubland community of COLM (Von Loh et al. 2007).

Wyoming big sagebrush/seeded grasses semi natural shrubland

Scientific Name Common Name Strata

Juniperus osteosperma Utah juniper Tree canopy

Artemisia tridentata ssp. wyomingensis Wyoming big sagebrush Short shrub/sapling

Ericameria nauseosa rubber rabbitbrush Short shrub/sapling

Achnatherum hymenoides Indian ricegrass Herb

Agropyron cristatum* crested wheatgrass Herb

Bromus tectorum* cheatgrass Herb

Chrysothamnus viscidiflorus yellow rabbitbrush Herb

Elymus elymoides squirreltail Herb

Gutierrezia sarothrae broom snakeweed Herb

Heterotheca villosa hairy false goldenaster Herb

Opuntia phaeacantha var. major Mojave pricklypear Herb

Senecio integerrimus western groundsel Herb

Sporobolus cryptandrus sand dropseed Herb

*Indicates a non-native species.

The Wyoming big sagebrush shrubland communities are characterized by Wyoming big sagebrush, 

providing 1 to 45% cover (Von Loh et al. 2007). Utah juniper and two-needle pinyon pine are 

occasionally present as canopy trees, generally 2 to 5 m (7 to 16 ft) tall and provide up to 5% cover 

(Von Loh et al. 2007). These communities contain a highly variable shrub layer that include 

skunkbush sumac, black greasewood (Sarcobatus vermiculatus), fourwing saltbush, shadscale, 

yellow rabbitbrush, Mormon tea, rubber rabbitbrush, spiny hopsage, black sagebrush, broom 

snakeweed, winterfat, and prickly phlox (Linanthus pungens), claretcup, Mojave pricklypear, brittle 

pricklypear, berry pricklypear (Opuntia phaeacantha), plains pricklypear, Simpson's hedgehog 

cactus (Pediocactus simpsonii), and Harriman’s yucca (Von Loh et al. 2007). The herbaceous layer is 

diverse and provides low to moderate cover. This layer includes graminoids such as Mormon 

needlegrass (Achnatherum aridum), Indian ricegrass, crested wheatgrass, purple three-awn, blue 

grama, cheatgrass, squirreltail, needle and thread, junegrass (Koeleria macrantha), saline wildrye, 

western wheatgrass (Pascopyrum smithii), James’ galleta, muttongrass, and six weeks fescue (Von 

Loh et al. 2007). Forbs present in this layer include Fendler’s sandwort, fringed sagebrush, woolly 

milkvetch (Astragalus mollissimus), smallflower milkvetch (Astragalus nuttallianus), Gunnison’s 

mariposa, sagebrush buttercup (Ranunculus testiculatus), hoary dusty-maiden, bastard toadflax 

(Comandra umbellata), cryptantha (Cryptantha spp.), Nuttall’s larkspur (Delphinium nuttallianum), 

western tansymustard, dwarf draba, fleabane (Erigeron spp.), cushion buckwheat (Eriogonum 

ovalifolium var. ovalifolium), stork’s bill, hairy false goldenaster, prickly lettuce, western stickseed, 

prairie pepperwort (Lepidium densiflorum), mountain pepperweed, blue flax (Linum lewisii), silvery 

lupine, pale evening primrose, crenulate phacelia (Phacelia crenulata), longleaf phlox (Phlox 

longifolia), woolly plantain, western groundsel, sleepy catchfly (Silene antirrhina), scarlet 

globemallow, desert princesplume (Stanleya pinnata), long-beak fiddle-mustard (Streptanthella 
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longirostris), and hoary townsendia (Townsendia incana) (Von Loh et al. 2007). The most abundant 

species within this community by stratum can be found in Table 32.

Table 32. Dominant plant species (by strata) within the Wyoming big sagebrush shrubland community of 

COLM (Von Loh et al. 2007).

Wyoming big sagebrush shrubland

Scientific Name Common Name Strata

Artemisia tridentata ssp. wyomingensis Wyoming big sagebrush Short shrub/sapling

Chrysothamnus viscidiflorus yellow rabbitbrush Short shrub/sapling

Opuntia fragilis brittle pricklypear Short shrub/sapling

Opuntia polyacantha plains pricklypear Short shrub/sapling

Achnatherum hymenoides Indian ricegrass Herb

Aristida purpurea purple three-awn Herb

Astragalus nuttallianus smallflower milkvetch Herb

Bouteloua gracilis blue grama Herb

Bromus tectorum* cheatgrass Herb

Descurainia pinnata ssp. halictorum western tansymustard Herb

Elymus elymoides squirreltail Herb

Hesperostipa comata needle and thread Herb

Hilaria jamesii James’ galleta Herb

Lappula occidentalis var. occidentalis western stickseed Herb

Linanthus pungens prickly phlox Herb

Leymus salina saline wildrye Herb

Oenothera pallida ssp. trichocalyx pale evening primrose Herb

Poa fendleriana muttongrass Herb

Sphaeralcea coccinea ssp. coccinea scarlet globemallow Herb

*Indicates a non-native species.

Percent Cover Biological Soil Crusts

Belnap et al. (2008, p. 1,257) defines BSCs as intertwined communities of lichens, mosses, and 

cyanobacteria commonly found on soil surfaces in dryland regions. These communities are a very 

important part of the ecosystem because of their influence on local hydrology, soil stability and 

fertility, and overall biodiversity (Belnap et al. 2008). Biological soil crusts aggregate soil particles, 

making the soil stronger and less susceptible to erosional forces of wind and water, thereby retaining 

nutrients, organic matter, and seeds in the underlying soils (Miller 2005). BSCs within COLM are 

most commonly found on sites that are protected from disturbance and are also found to be redeveloping in areas that were once grazed or other-wise disturbed (Von Loh et al. 2007). Because of 

the ecological benefits provided by BSCs, they should be included in ecological monitoring 

programs where present (Belnap et al. 2008).

The percent cover of BSCs within COLM’s sagebrush shrublands/shrub steppe varies based on 

community type. Black sagebrush and grasses shrubland-graminoids communities usually have low 
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percent cover of BSC, though it may be as high as 45% in some stands (Von Loh et al. 2007). Cover 

of BSCs within basin big sagebrush/cheatgrass semi-natural shrubland communities is low and 

ranges from 3-10% (Von Loh et al. 2007). Wyoming big sagebrush/seeded grasses semi-natural 

shrubland communities have absent to low percent cover of BSCs, not exceeding 5% (Von Loh et al. 

2007). The percent cover of BSCs within Wyoming big sagebrush shrubland communities is 

variable, from sparse to as high as 85% (Von Loh et al. 2007).

Percent Bare Ground

Percent bare ground is important because it can impact soil stability, as vegetation helps prevent 

wind erosion (Witwicki et al. 2013). Areas where bare ground is the primary component of total 

ground cover have been associated with increased susceptibility to water erosion (NRCS 2010, 

Kachergis et al. 2011). Studies have also shown that large areas of bare ground can be indicative of 

low site stability and high erosion potential (Haveren 2000). 

Percent bare ground of sagebrush shrublands/shrub steppe varies with community type. In black 

sagebrush and grasses shrubland-graminoids communities, total vegetation canopy cover ranges from 

15 to 24% with low ground cover of litter and high ground cover of rocks and bare ground (Von Loh 

et al. 2007). Basin big sagebrush/cheatgrass semi-natural shrubland communities have total 

vegetation canopy cover that ranges from 33 to 120% with high ground cover of litter and low to 

high ground cover of bare ground (Von Loh et al. 2007). In Wyoming big sagebrush/seeded grasses 

semi-natural shrubland communities, total vegetation canopy cover ranges from 11 to 56% with 

moderate to high ground cover of litter and bare ground (Von Loh et al. 2007). Vegetation cover in 

Wyoming big sagebrush shrubland communities ranges from 11 to 62%, with low to high ground 

cover of litter, rocks, and bare ground (Von Loh et al. 2007).

Trends in Invasive Infestation

COLM is part of a long-term monitoring program for IEPs developed by the NCPN which focuses on 

early detection (Perkins 2014). The first survey of IEPs in the park was conducted in 2003 by Dewey 

and Anderson (2005). The latest monitoring was conducted during the 2013 field season (Perkins 

2014) and will be used to assess this measure, since it includes the previously collected data on IEP 

infestations in COLM. A full discussion of IEPs park-wide, including a discussion of trends can be 

found in Chapter 2.2.2. In summary, during this 8-year time span (2003-2011), there was an overall 

decrease in Russian olive, tamarisk and woolly mullein (Perkins 2014). However, the number of field 

bindweed infestations more than doubled during this same period (Perkins 2014).

In the most recent survey, conducted in 2013, a total of 462 IEP infestation points were identified 

within the park (Perkins 2014). The most frequently documented species of IEP were yellow 

sweetclover and cheatgrass. One of the sagebrush shrubland/shrub steppe alliances at COLM is 

named for its cheatgrass content (basin big sagebrush/cheatgrass semi-natural shrubland). The 

Wyoming big sagebrush shrubland and Wyoming big sagebrush/seeded grasses semi-natural 

shrubland descriptions lists cheatgrass as a dominant herbaceous species (Von Loh et al. 2007). 

Cheatgrass is also listed as being present in the black sagebrush grasses shrubland alliance (Von Loh 

et al. 2007).
103

Trends in IEP’s have not been assessed specifically by vegetation association at COLM. To identify 

invasive species infestations associated with sagebrush shrubland/shrub steppe vegetation 

communities’ spatial queries were performed using the data from the 2013 IEP survey and the 

sagebrush shrubland/shrub steppe vegetation communities mapped by Von Loh et al. (2007). The 

spatial queries selected IEP points that were either within a mapped location of sagebrush 

shrubland/shrub steppe or within 100 m (328 ft) of one of these communities. The analysis identified 

141 (approximately 33%) of the IEP points met the criteria (Figure 24, Table 33). The most common 

IEP’s selected by these queries were yellow sweetclover (65) and cheatgrass (44). The majority of 

these occurrences were within 100 m (328 ft) of a mapped sagebrush shrubland/shrub steppe 

community. In total, nearly 75% of the observed occurrences where found in close proximity (100 m 

[328 ft]) to sagebrush shrubland/shrub steppe communities. Yellow sweetclover and cheatgrass 

accounted for 83% of the infestations that occurred within a sagebrush shrubland/shrub steppe 

communities. The results for all IEP occurrences that satisfied the spatial queries can be found in 

Table 33.

Table 33. Number and location of non-native species occurrences in relation to sagebrush 

shrubland/shrub steppe.

Scientific Name Common Name

Number 

Within

Number 

Adjacent

Total 

Number

Melilotus officinalis yellow sweetclover 20 45 65

Bromus tectorum cheatgrass 10 34 44

Elaeagnus angustifolia Russian olive 3 4 7

Arctium minus burdock 6 6

Convolvulus arvensis field bindweed 5 5

Tribulus terrestris puncture vine 1 3 4

Ulmus pumila Siberian elm 1 2 3

Verbascum thapsus woolly mullein 1 2 3

Tamarix ramosissima saltcedar 2 2

Cirsium vulgare bull thistle 2 2

Totals 36 105 141
104

Figure 24. IEP infestations associated with mapped sagebrush shrubland/shrub steppe.

Soil Stability

Soil stability depends on a number of factors. The presence of BSCs, litter/duff, other non-vegetative 

ground cover, slope, soil composition, and soil texture are some of the factors that can influence soil 

stability (NRCS 1996, Belnap et al. 2008, Witwicki et al. 2013). Vegetative conditions (e.g., basal 

cover, height) also greatly influence soil stability (Whisenant 1985). Soil loss can be influenced by 

rainfall intensity, size and frequency of bare ground, soil type, topography, and plant cover, 
105

especially following a fire. Vegetation and slope are the best determinants of soil erosion in severe 

rainfall storms. Studies in various plant communities show that 60-70% vegetation cover appears 

necessary to ensure soil stability against erosion during rainfall (Packer 1963, Orr 1970, Whisenant 

1985). Specific data on soil stability within COLM are not available. A condition assessment of this 

measure is not possible due to lack of available data.

Canopy Gap Size

Canopy gap size is important because vegetative canopy cover can protect soils from wind and water 

erosion (BLM 2013, Witwicki et al. 2013). Canopy gap is defined by the NCPN as an area where the 

distance between plant canopies is greater than 20 cm (7.9 in) (Witwicki et al. 2013). While Von Loh 

et al. (2007) contains information on the canopy cover and basal ground cover within each of the 

communities, data are not available that could be used to determine canopy gap size.

Threats and Stressor Factors

NPS staff identified several potential threats and stressors to the sagebrush shrublands/shrub steppe

community: exotic invasive species (particularly cheat grass), unnatural fire regimes, drought, and 

regional climate variation. In general, the introduction of exotic invasive species can cause economic 

or environmental damage and pose a danger to human health (Executive Order 13112), and they are 

the second greatest threat to biodiversity in the country, behind habitat loss (Wilcove et al. 1998). 

Exotic invasive plant species negatively impact the natural environment by fragmenting native 

ecosystems, displacing native plants and animals, and altering ecosystem function (Scott and 

Wilcove 1998, Perkins 2014). In addition, exotic invasive species can alter fire regimes and increase 

trail maintenance requirements (Kennard and Moore 2013, Perkins 2014). Riparian corridors, roads, 

and trails provide possible pathways for IEPs to enter a park (Perkins 2014).

Fire can affect an ecosystem by altering the vegetation composition and structure and eliminating fire 

intolerant plant species (Miller 2005). The sagebrush and pinyon-juniper communities at COLM are 

closely associated. Studies have shown that pinyon-juniper may have encroached into sagebrush 

habitat at COLM (Johnson 2013). Since these two habitats are closely tied, the impacts of fire on 

pinyon-juniper habitat also impact sagebrush habitat. Altered fire intervals are a serious threat to the 

pinyon-juniper woodland/savannas, particularly where large, stand-replacing fires were historically 

infrequent (Kennard and Moore 2013). Kennard and Moore (2013) studied the fire histories of some 

of COLM’s pinyon-juniper woodland/savannas to identify drivers of community structure. The 

results indicated that these woodlands and savannas have very long (588-1,428 years) fire rotations, 

particularly in persistent stands like those found on mesa tops in COLM where pinyon-juniper habitat 

is intermixed with sagebrush habitat (Kennard and Moore 2013). It can be assumed that the 

sagebrush habitats have a similar fire regime.

Fire is also a concern for nearby residential areas. Fire within big sagebrush shrublands prior to 

European/American settlement was likely characterized by long rotations of high severity fires.

These fire rotations were likely 100-240 years at a minimum and were stand replacing fires (Baker et 

al. 2006). In recent years, Utah juniper and two-needle pinyon mortality has increased due to a root 

fungus probably brought on by drought (NPS 1999). These dead trees, along with the increasing 

cheatgrass cover, provide fuel for fires (NPS 1999). This fuel can cause the area to burn more 
106

frequently. After a fire, native bunchgrasses or non-native, invasive grasses may become established 

in the area, making it difficult for sagebrush to become a dominant species again (Witwicki et al. 

2013).

Visitor impacts within the park’s sagebrush shrubland/shrub steppe habitats include damage to BSC 

present within these environments. Hikers, particularly those using unauthorized “social” trails, cause 

damage to these fragile habitats and continued disturbance does not allow for the time needed for 

BSCs to regenerate. This can lead to invasive species encroaching and potentially replacing BSC 

habitats.

Drought can cause widespread mortality among the vegetation in COLM (Miller 2005). This can 

increase susceptibility to fire and insect outbreak as well as lower vegetation resistance to other 

stressors (Miller 2005). COLM averages 29 cm (11 in) of precipitation annually (WRCC 2015). With 

the exception of minor peaks in the spring and late summer, the precipitation pattern is distributed 

relatively evenly throughout the year. Any alteration in precipitation patterns due to climate change 

could result in longer and more frequent dry periods, which would stress the region’s sagebrush 

shrublands (Bradley 2010). 

Data Needs/Gaps

Although general descriptions of the percent cover of BSCs and percent bare ground are available for 

COLM communities (Von Loh et al. 2007), no actual data could be found for these measures. Data 

for soil stability and canopy gap size measures also were not available for COLM. Witwicki et al. 

(2013) briefly touch on these topics but only discuss a monitoring protocol, no actual data are 

included. Data referencing the IEP composition for each specific vegetation community is also a data 

gap at this time. Research on the impacts from the proliferation of social trails within the park is also 

recommended.

Currently a guaranteed funding source for the invasive species removal/control has not been 

identified. Failure to secure funding for this management action will result in the loss of the gains 

that have been made in eradicating IEPs within the park. Additionally, another programmatic need 

for COLM is a trail management plan. Currently, visitors face no restrictions in their access to any 

areas within the park.

Overall Condition

Community Extent and Change over Time

This measure was assigned a Significance Level of 3. Utah juniper and two-needle pinyon expanded 

into sagebrush shrublands/shrub steppe communities over the past 150 years (Soulé et al. 2003). This 

expansion has caused the sagebrush communities to decline by 9% to 29% over the past 70 years 

(Johnson 2013). As mentioned previously, it is unclear if this is the result of human influence, an 

environmental change, or simply a natural successional process. Because the extent of sagebrush 

shrublands/shrub steppe communities of COLM appears to be slowly decreasing, this measure was 

assigned a Condition Level of 1, indicating low concern.
107

Community Composition

A Significance Level of 3 was assigned to the community composition measure. According to Hogan 

et al. (2009), a total of 289 plant species are present in the sagebrush shrublands of COLM 

(Appendix D). Of these plant species, approximately 83% are native. With a high species richness 

and relatively high nativity, the Condition Level assigned to this measure is 1, indicating low 

concern.

Percent Cover Biological Soil Crusts

The percent cover of BSCs measure was assigned a Significance Level of 3. This measure is highly 

variable depending on sagebrush community type, with cover values ranging from zero to 85%. 

However, a reference condition is necessary to determine what appropriate values are for each 

community type. A Condition Level was not assigned to this measure due to lack of available data.

Percent Bare Ground

A Significance Level of 2 was assigned to this measure. Percent bare ground varies with community 

type. Total vegetation cover in the sagebrush shrublands/shrub steppe of COLM ranges from 11% to 

120%. Where vegetation is absent, cover of litter, rocks, and bare ground vary from low to high. 

Although some data exist for the percent bare ground measure, a reference condition and more 

detailed data are needed to determine the current overall condition of the measure. Due to this, a 

Condition Level could not be assigned.

Trends in Invasive Infestation

This measure was assigned a Significance Level of 3. Invasive species are one of the greatest threats 

to biodiversity in the United States (US) (Wilcove et al. 1998). Recent IEP surveys performed 

indicate many different species occur within COLM (Perkins 2010, 2012, 2014). Most IEP 

occurrence remained relatively constant from year to year based on number of infestations. 

Cheatgrass infestations have increased in number and size since 2009. Cheatgrass infestations 

account for a large portion of the total number of IEP’s in the most recent survey. Over the last 

decade the park has focused control efforts on eradication of IEP’s. Future funding for these control 

measures is not available, so the potential for increased infestations is high (Hartwig, written 

communication 18 November 2015). Due to these factors a Condition Level of 2 was assigned for 

this measure.

Soil Stability

The soil stability measure was assigned a Significance Level of 2. Specific data on soil stability 

within the sagebrush shrublands/shrub steppe of COLM were not available. Many variables that may 

contribute to soil stability are outlined throughout the document, though these often contain a range 

of values, making it difficult to accurately determine the soil stability within COLM. A Condition 

Level was not assigned to this measure because specific data on soil stability are not available.

Canopy Gap Size

A Significance Level of 3 was assigned to this measure. Data on canopy gap size within the 

sagebrush shrublands/shrub steppe communities was not available for COLM. A Condition Level

was not assigned to this measure due to the lack of available data.
108

Weighted Condition Score

A Weighted Condition Score was not calculated for this component because a Condition Level could 

not be assigned to over 50% of the measures due to lack of available data. Until more data becomes 

available for the other measures, the condition of sagebrush shrublands in COLM will be unknown.

Sagebrush Shrublands/Shrub Steppe

Measures Significance Level Condition Level WCS = N/A

Community Extent and 

Change over Time 3 1

Community 

Composition 3 1

Percent Cover 

Biological Soil Crusts 3 n/a

Percent Bare Ground 2 n/a

Trends in Invasive 

Infestation 3 2

Soil Stability 2 n/a

Canopy Gap Size 3 n/a

4.2.6 Sources of Expertise

Dusty Perkins, Program Manager, Northern Colorado Plateau Network

Dr. Deborah Kennard, Colorado Mesa University

Dana Witwicki, Ecologist NPS Northern Colorado Plateau Network

4.2.7 Literature Cited

Baker, W. L., D. J. Shinneman, and P. Lyon. 2006. Uncompahgre project pinyon-juniper/sagebrush 

zone vegetation study (native-plant restoration opportunities and constraints: A case study of the 

Uncompahgre Plateau, Western Colorado). University of Wyoming, Laramie, Wyoming.

Belnap, J., S. L. Phillips, D. L. Witwicki, and M. E. Miller. 2008. Visually assessing the level of 

development and soil surface stability of cyanobacterially dominated biological soil crusts. 

Journal of Arid Environments 72:1257-1264.
109

Bradley, B. A. 2010. Assessing ecosystem threats from global and regional change: Hierarchical 

modeling of risk to sagebrush ecosystems from climate change, land use and invasive species in 

Nevada, USA. Ecography 33(1):1998-208.

Bureau of Land Management (BLM). 2013. Monitoring evaluation: Massacre Lakes allotment and 

Massacre Lakes herd management area. U.S. Department of the Interior, Bureau of Land 

Management, Cedarville, California.

Dewey, S. and K. Anderson. 2005. An inventory of invasive nonnative plants in Colorado National 

Monument (2003). Weed Science Research Project Report No. SD0516A. Utah State University, 

Logan, Utah.

Hanophy, W., and H. Teitelbaum. 2003. Wild Colorado: Crossroads of biodiversity. Colorado 

Division of Wildlife, Education Section, Denver, Colorado.

Haveren, B. P. 2000. Ground cover dynamics in a sagebrush steppe community. Resource Notes No. 

19. Bureau of Land Management, Denver, Colorado.

Hogan, T., N. Lederer, and W. Fertig. 2009. Annotated checklist of vascular flora: Colorado National 

Monument. Natural Resource Technical Report NPS/NCPN/NRTR—2009/231. National Park 

Service, Fort Collins, Colorado.

Johnson, T. 2013. Pinyon-Juniper Encroachment into Sage Parks on the Colorado National 

Monument. National Park Service Unpublished Report, Fort Collins, Colorado.

Kachergis, E., M. E. Rocca, and M. E. Fernandez-Gimenez. 2011. Indicators of ecosystem function 

identify alternate states in the sagebrush steppe. Ecological Applications 21(7):2781-2792.

Kennard, D. K. and A. J. Moore. 2013. Fire history, woodland structure, and mortality in a piñonjuniper woodland in the Colorado National Monument. Natural Areas Journal 33:296-306.

Lyon, P., C. Pague, R. Rondeau, L. Renner, C. Slater, and C. Richard. 1996. Natural heritage 

inventory of Mesa County, Colorado. Colorado Natural Heritage Program, Fort Collins, 

Colorado.

Miller, M. E. 2005. The structure and functioning of dryland ecosystems—Conceptual models to 

inform long-term ecological monitoring. Scientific Investigations Report 2005-5197. U.S. 

Geological Survey, Reston, Virginia.

National Park Service (NPS). 2015. NPSpecies: Information on species in national parks. 

https://irma.nps.gov/NPSpecies/Search/SpeciesList/COLM (accessed 16 June 2015).

Natural Resources Conservation Service (NRCS). 1996. Soil quality indicators: Aggregate stability. 

http://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/nrcs142p2_052820.pdf (accessed 25 

February 2015).
110

Natural Resources Conservation Service (NRCS). 2010. NRI rangeland resource assessment - Bare 

ground, intercanopy gaps, and soil aggregate stability. 

http://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb1041839.pdf (accessed 19 May 

2015).

Orr, H. K. 1970. Runoff and erosion control by seeded and native vegetation on a forest burn: Black 

Hills, South Dakota. U.S. Forest Service Research Paper RM-60. U.S. Forest Service, Rocky 

Mountain Forest and Range Experiment Station, Fort Collins, Colorado.

Packer, P. E. 1963. Soil stability requirements for the Gallatin elk winter range. The Journal of 

Wildlife Management 27(3):401-410.

Perkins, D. W. 2010. Invasive exotic plant monitoring at Colorado National Monument, 2009. 

Natural Resource Technical Report NPS/NCPN/NRTR—2010/354. National Park Service, Fort 

Collins, Colorado.

Perkins, D. 2012. Invasive exotic plant monitoring in Colorado National Monument: 2011 Field 

Season. Natural Resource Technical Report NPS/NCPN/ NRTR—2012/556. National Park 

Service, Fort Collins, Colorado.

Perkins, D. 2014. Invasive exotic plant monitoring in Colorado National Monument: 2013 field 

season. Natural Resource Technical Report NPS/NCPN/NRTR—2014/859. National Park 

Service, Fort Collins, Colorado.

Scott, J. and D. Wilcove. 1998. Improving the future for endangered species. BioScience 48(8):579-

580.

Soulé, P. T., P. A. Knapp, H. D. Grissino-Mayer. 2003. Comparative rates of western juniper 

afforestation in south-central Oregon and the role of anthropogenic disturbance. The Professional 

Geographer 55(1): 43-55.

Springer, A., L. E. Stevens, and R. Harms. 2006. Inventory and classification of selected National 

Park Service springs on the Colorado Plateau. National Park Service, Fort Collins, Colorado.

Von Loh, J., K. Landgraf, A. Evenden, T. Owens, S. Blauer, and M. Reid. 2007. Vegetation 

classification and mapping project report, Colorado National Monument. Natural Resource 

Technical Report NPS/NCPN/NRTR—2007/061. National Park Service, Fort Collins, Colorado.

Weber, W. A., V. Siplivinsky, H. Beck, and C. Rector. 1982. Checklist of vascular plants: Colorado 

National Monument. University of Colorado Museum, Boulder, Colorado.

Western Regional Climate Center (WRCC). 2015. Colorado National Monument NCDC 1981-2010 

monthly normal. http://www.wrcc.dri.edu/cgi-bin/cliMAIN.pl?co1772 (accessed 25 September 

2015).
111

Whisenant, S. G. 1985. A multidisciplinary approach to evaluating fire effects. Pages 98-104 in

Rangeland fire effects. Proceedings of a symposium sponsored by Bureau of Land Management 

and University of Idaho at Boise, Idaho, November 27-29, 1984. Bureau of Land Management, 

Idaho State Office, Boise, Idaho.

Wilcove, D. S., D. Rothstein, J. Dubow, A. Phillips, and E. Losos. 1998. Quantifying threats to 

imperiled species in the United States. Bioscience 48(8):607-615.

Witwicki, D., H. Thomas, R. Weissinger, A. Wight, S. Topp, S. L. Garman, and M. E. Miller. 2013. 

Integrated upland monitoring protocol for the park units in the Northern Colorado Plateau

Network. National Park Service, Moab, Utah.
112

4.3. Riparian Habitats/Large Dry Washes

4.3.1 Description

Riparian habitats/large dry washes are of 

considerable ecological importance in COLM. 

There are different types of riparian habitat 

within the park; most are found along washes in 

the canyon bottoms that are periodically fed by 

snowmelt and rainfall from the mesas, and 

seeps and springs in the canyon rock faces 

(Photo 6). The vegetation communities that 

comprise these riparian habitats have adapted to 

their surroundings by utilizing the limited 

available water supply.

These riparian habitats provide critical cover 

and forage for desert amphibian species, such 

as red-spotted toads (Anaxyrus punctactus) and 

canyon tree frogs (Hyla arenicolor). Within 

Colorado, riparian and wetland communities 

contain the greatest diversity of bird species of 

any ecosystem (Hanophy and Teitelbaum 2003). Vireos (Vireo spp.), warblers, orioles (Icterus spp.), 

blackbirds, grosbeaks, finches and flycatchers (Empidonax spp.) can be found within COLM’s 

riparian habitats (Hanophy and Teitelbaum 2003). Raptors, such as golden eagles, prairie falcons, 

Cooper’s hawks (Accipiter cooperii), American kestrels, and great horned owls (Bubo virginianus) 

utilize these habitats for roosting and hunting (Hanophy and Teitelbaum 2003). Desert cottontail

mice, voles, and raccoons (Procyon lotor) are commonly found in these habitats along with larger 

mammals such as elk and deer (Hanophy and Teitelbaum 2003).

4.3.2 Measures

 Community extent and change over time

 Community composition

 Trends in invasive infestation

 Cottonwood regeneration

 Channel geomorphology

 Frequency and discharge of flash floods

4.3.3 Reference Conditions/Values

The reference condition of riparian/large dry wash habitats would ideally be from pre-settlement 

times or at the time of park establishment (1911) when the area was minimally developed. Although 

specific data aren’t available to determine a reference condition for each measure, the assumption for 

Photo 6. The riparian habitat shown in this canyon 

bottom is discernable from the surrounding 

vegetation and grows along a large dry wash (Photo 

by Anna Davis, SMUMN GSS 2013).
113

the community composition and trends in invasive species measures is that vegetation communities 

in riparian habitat and large dry washes historically included only native plant species. 

4.3.4 Data and Methods

Several sources were used to address the measures listed for this component and are briefly described 

below. The studies and projects provided information on conditions pertaining to riparian and large 

dry washes located in the park.

Richard (2004) compiled data on flash flooding in the area in and around COLM. The report 

provided data on topography, soil permeability, slope, and precipitation. It also included a literature 

review that created a record of flash floods originating from COLM drainages. Major drainages 

within the park were mapped, encompassing the areas where major flash flooding has occurred since 

establishment of the park (Richard 2004). The flooding records from NPS records and the Grand 

Junction newspaper archives, dating from 1921 through 2003 are included in this report (Richard 

2004).

Von Loh et al. (2007) conducted a vegetation mapping project for COLM and close vicinity. The 

purpose of the project, conducted between 2003 and 2005, was to classify, describe, and map 

vegetation and fuels at COLM (Von Loh et al. 2007). A team of ecologists, botanists, and photo 

interpreters worked together to identify the plant associations within the park (Von Loh et al. 2007). 

Vegetation mapping was completed through the use of aerial photography and computer modeling 

(Von Loh et al. 2007). The resultant maps were refined through a combination of ground sampling 

and accuracy assessments using vegetation plot and observation point sampling (Von Loh et al. 

2007). A complete detailed methodology of the computer modeling and sampling design can be 

found in Von Loh et al. (2007).

Hogan et al. (2009) compiled a comprehensive list of plant species within COLM. The project 

included conducting a review of park plant specimen collections, including specimens in the park 

herbarium and from the University of Colorado herbarium (Hogan et al. 2009). Field surveys were 

also conducted to confirm unverified species and to document previously unlisted species (Hogan et 

al. 2009). The products from this project included an annotated checklist with additional information 

about the flora found within COLM (e.g., geographic range, flowering period).

Fertig et al. (2012) updated the plant species list provided and maintained by Hogan et al. (2009). 

The focus of this study was to identify any previously undocumented species or the discovery of new 

species (Fertig et al. 2012). This report also provided a 2011 update to the NPSpecies database plants 

list for COLM (Fertig et al. 2012).

Kennard and Rogowski (2015) assessed the health of the cottonwood population in COLM. This 

study characterized the cottonwood populations’ structure, percent dead trees, and assessed 

regeneration, and examined the size versus age relationship within the parks cottonwood stands 

(Kennard and Rogowski 2015).
114

4.3.5 Current Condition and Trend

Community Extent and Change over Time

The riparian communities were mapped and classified by Von Loh et al. (2007) as part of the 

vegetation mapping project in COLM. Von Loh et al. (2007) utilized the national standard minimum 

mapping unit (MMU) of 0.5 ha (1.2 ac). A total of 11 associations and alliances comprise the 

riparian/large dry wash vegetation habitats at COLM. The selection was based on the vegetation 

classifications that Von Loh et al. (2007) identified as Riparian, Wetland, and Mesic Ecological 

Systems in the classification schema used for the vegetation mapping project.

Even though a large number of riparian/large dry wash habitats occur at the park, these areas 

comprised only 1% of the park’s vegetation, and should be considered rare within the park (Von Loh 

et al. 2007). Von Loh et al. (2007) could be used as a baseline for any subsequent, similar vegetation 

projects to determine what, if any, changes in extent or composition has occurred to the riparian/large 

dry wash habitats. Figure 25 shows the location of the habitats that were mapped as polygons, and a 

summary of the areal extent is provided in Table 34. Not all the riparian/large dry wash habitats 

identified during the project meet the MMU. For those habitats area is assumed to be less than the 

MMU.
115

Figure 25. The location of riparian vegetation alliances within COLM (Von Loh et al. 2007).
116

Table 34. Areal extent of alliances associated with riparian habitat/large dry washes within COLM (Von Loh et al. 2007).

Alliances Scientific Name

Hectares

(ha)

Acres

(ac)

Cottonwood/coyote willow woodland Populus deltoides/Salix exigua 10.6 26.3

Coyote willow/mesic graminoids shrubland Salix exigua 9.2 22.8

Quaking aspen/water birch forest Populus tremuloides/Betula occidentalis 6.5 16

Rubber rabbitbrush desert wash shrubland Ericameria nauseosa 3.0 7.4

Baltic rush herbaceous vegetation Juncus balticus 1.5 3.8

Box elder/disturbed understory woodland Acer negundo <0.5 <1.2

Quaking aspen western chokecherry forest Populus tremuloides-Prunus virginiana <0.5 <1.2

Singleleaf ash woodland Fraxinus anomala <0.5 <1.2

Skunkbush intermittently flooded shrubland Rhus aromatica <0.5 <1.2

Smooth horsetail herbaceous vegetation Equisetum laevigatum <0.5 <1.2

Water birch/starry false Solomon’s-seal shrubland Betula occidentalis/Maianthemum 

stellatum

<0.5 <1.2

Total (excluding values <0.5 ha [<1.2 ac]) 30.8 76.3
117

Cottonwood (Populus deltoides)/coyote willow (Salix exigua) woodlands are restricted to narrow 

drainages in canyon bottoms and alcoves where there is intermittent surface flow and groundwater 

seepage (Von Loh et al. 2007). This type of riparian woodland is considered the most common, 

occupying a total of 10.6 ha (26.3 ac) within COLM (Figure 26) (Von Loh et al. 2007). Its 

distribution is very patchy with the majority found in No Thoroughfare Canyon and the remainder 

scattered in small stands or clumps in Ute, Red and Columbus Canyons (Von Loh et al. 2007).

Figure 26. Location of cottonwood/coyote woodlands within COLM (Von Loh et al. 2007).

Coyote willow/mesic graminoids shrubland type were mapped in Ute, No Thoroughfare, Red, and 

Columbus Canyon bottoms (Von Loh et al. 2007). This habitat was found in confined drainages that 

are subject to flash flooding (Von Loh et al. 2007). There were 9.2 ha (22.8 ac) of this habitat in the 

park (Von Loh et al. 2007). The majority (5.3 ha/13.2 ac) was found in the bottom of No 

Thoroughfare Canyon, with approximately 3.4 ha (8.5 ac) in Ute Canyon, and a small 0.5 ha (1.1 ac) 

plot at the confluence of Red Canyon and Columbus Canyon (Figure 27) (Von Loh et al. 2007).
118

Figure 27. Location of coyote willow/mesic graminoid shrublands within COLM (Von Loh et al. 2007).

Quaking aspen (Populus tremuloides)/water birch (Betula occidentalis) forest occurs in only one 

known site at COLM. Two stands, totaling of 6.5 ha (16 ac) (Table 34), were found in the upper No 

Thoroughfare Canyon bottom (Figure 28) (Von Loh et al. 2007).

The rubber rabbitbrush desert wash shrublands are considered very rare and generally occur as 5 to 

10 m wide (16.4 to 32.8 ft) corridors along drainage channels that are subject to periodic flash 

flooding (Von Loh et al. 2007). A total of only 3.0 ha (7.4 ac) was mapped in small patches in three 

separate canyons in COLM (Von Loh et al. 2007). They were located in No Thoroughfare (1.4 ha/3.6 

ac), Ute (0.8 ha/2.1 ac), and Monument Canyons (0.7 ha/1.7 ac) (Figure 29) (Von Loh et al. 2007).
119

Figure 28. Location of quaking aspen/water birch forests within COLM. This riparian habitat was only 

found in No Thoroughfare Canyon during the vegetation mapping project (Von Loh et al. 2007).
120

Figure 29. Location of rubber rabbitbrush desert wash shrublands within COLM (Von Loh et al. 2007).
121

Baltic rush (Juncus balticus) herbaceous vegetation is confined to drainages with seepage and 

intermittent surface flow (Von Loh et al. 2007). There were 1.5 ha (3.8 ac) in total of this habitat 

occurring in two regions within COLM (Von Loh et al. 2007). One small area of Ute Canyon had 

two separate stands (totaling 1.1 ha/2.8 ac) and was located in the central part of the park, and the 

second 0.4 ha (1 ac) stand was in the northern portion of the park near the park boundary (Figure 30) 

(Von Loh et al. 2007).

Figure 30. Location of Baltic rush herbaceous vegetation within COLM (Von Loh et al. 2007).

The remaining riparian and large dry wash habitats described in Von Loh et al. (2007) were mapped 

as points instead of polygons as they did not meet the MMU. Due to the large size of the park, these 

points would have to be mapped at an exaggerated size in order to be visible. For this reason, maps 

for these habitats were not included in this assessment, but the locations of these communities are 

described in the paragraphs below. As with all riparian habitats, these are considered uncommon in 

COLM (Von Loh et al. 2007).
122

Box elder (Acer negundo)/disturbed understory woodlands consisted of one stand that occurred at the 

base of an ephemeral waterfall in Kodels Canyon (Von Loh et al. 2007). Von Loh et al. (2007) noted 

that this habitat may also occur in other canyons of COLM where similar conditions are found.

Quaking aspen western chokecherry (Prunus virginiana) forest was also found in only one location, 

at the head of a sub-canyon within No Thoroughfare Canyon (Von Loh et al. 2007). It was located 

along a large pour-off that has periodic surface flows (Von Loh et al. 2007).

Singleleaf ash woodlands were located along intermittent drainages, predominantly on eastern 

toeslopes (Von Loh et al. 2007). These woodlands were located in Fruita Canyon on narrow 

drainages lined with cobble and boulders (Von Loh et al. 2007).

Skunkbush (Rhus aromatica) intermittently flooded shrubland was found at only one location, in an 

alcove situated at the head of a canyon in Ute Canyon (Von Loh et al. 2007). It is possible that it may 

also be found in similar locations around COLM (Von Loh et al. 2007). 

Smooth horsetail (Equisetum laevigatum) herbaceous vegetation occurs only in canyons containing 

permanent seeps and springs (Von Loh et al. 2007). Nearly pure stands were found in the bottom of 

Ute Canyon (Von Loh et al. 2007). Smooth horsetail can also be found in association with other 

palustrine and riparian vegetation types in their limited distribution throughout the canyon bottoms of 

the park (Von Loh et al. 2007).

Water birch/starry false Solomon’s-seal (Maianthemum stellatum) shrubland is only known to occur 

in upper No Thoroughfare Canyon (Von Loh et al. 2007). It is generally found in areas of deep 

sediment that have water present for at least part of the year (Von Loh et al. 2007). 

Community Composition

The 11 riparian/large dry wash habitat communities are comprised of 64 different plant species 

(Table 35) (Von Loh et al. 2007). The most diverse community, with 32 species, is the 

cottonwood/coyote willow woodland habitat (Von Loh et al. 2007). A list of the dominant species for 

each association strata can be found in Appendix E.

In 2011, two non-native riparian species, the white poplar (Populus alba) and compressed rush 

(Juncus compressus), had their documentation status updated to “present” based on reported 

sightings (Fertig et al. 2012).The status of the white poplar was previously listed as “reported” and 

the compressed rush was previously listed as “potentially” present (Fertig et al. 2012).
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Table 35. Number of species by riparian habitat / dry wash habitat associations within COLM (Von Loh et 

al. 2007).

Riparian/dry wash Habitat Association

Number 

of Species

cottonwood/ coyote willow woodland 32

coyote willow/mesic graminoids shrubland 14

water birch/starflower false Solomon's-seal shrubland 11

Baltic rush herbaceous vegetation 11

singleleaf ash woodland 9

smooth horsetail herbaceous vegetation 6

quaking aspen/water birch 5

box elder/disturbed understory woodland 4

rubber rabbitbrush desert wash shrubland 3

skunkbush intermittently flooded shrubland 3

Trends in Invasive Infestation

COLM is part of a long-term monitoring program for IEPs developed by the NCPN which focuses on 

early detection (Perkins 2014). The first survey of IEPs in the park was conducted in 2003 by Dewey 

and Anderson (2005). The latest monitoring was conducted during the 2013 field season (Perkins 

2014) and will be used to assess this measure, since it includes the previously collected data on IEP 

infestations in COLM. A full discussion of IEPs park-wide, including a discussion of trends can be 

found in Chapter 2.2.2. Information on the occurrences of IEP infestation in riparian areas is 

documented in these surveys. Of all the vegetation communities within COLM, the riparian habitats 

have the most prevalent IEP infestations (Perkins 2014). The most widespread IEPs within the 

riparian/large dry wash habitats, based on the latest available survey (Perkins 2014), were yellow 

sweetclover, woolly mullein, field bindweed, and Siberian elm. Each of these was identified by the 

park and NCPN as priority IEPs (Perkins 2014). Cheatgrass, while not widespread within the 

riparian/large dry wash habitats, is the exotic species with the most extensive coverage in COLM and 

was most frequently encountered in all transects (Perkins 2014).

Total infestation numbers and infestations per 100 meters have declined within the riparian/large dry 

wash habitats since 2012 (Table 36). This bodes well for the park, considering an overall increase 

was observed between 2009 and 2012 (Table 36; Perkins 2009, 2012, and 2014). Additionally, the 

infestations found in Gold Star Canyon and Kodels Canyon in the 2011 survey were not found in the 

2013 survey (Perkins 2012, 2014). During the 2011 field season, these canyons averaged 0.29 

infestations/100 m and 0.74 infestations/100 m, respectively (Table 36; Perkins 2012, 2014). The 

decline in exotic plant infestations observed in riparian habitats is attributed to the park staff’s 

aggressive control efforts conducted between 2011 and 2013 (Perkins 2014).
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Table 36. Comparison of results from the for the last three IEP surveys for riparian areas within COLM 

(Perkins 2009, 2012, 2014).

Route Location Year

Length

(m)

Area 

Covered

(ha)

Infestation Infestations/100m

Total

Priority 

Only Total

Priority 

Only

Columbus Canyon 2009 1,883.0 n/a 0 0 0.00 0.00

2012 1,881.5 6.11 20 20 3.27 3.27

2014 1,881.5 2.27 20 19 1.06 1.01

Gold Star Canyon 2009 1,867.0 n/a 2 2 0.11 0.11

2012 1,531.0 7.00 2 2 0.29 0.29

2014 1,922.0 2.31 0 0 0.00 0.00

Kodels Canyon 2009 463.0 n/a 0 0 0.00 0.00

2012 461.9 1.34 1 1 0.74 0.74

2014 461.9 0.37 0 0 0.90 0.00

Monument Canyon 2009 9,837.0 n/a 35 34 0.36 0.35

2012 9,591.3 41.00 86 86 2.10 2.10

2014 9,259.6 10.43 43 43 0.00 0.46

No Thoroughfare Canyon 2009 10,302.0 n/a 39 39 0.38 0.38

2012 13,678.7 46.22 198 196 4.28 4.24

2014 12,633.9 11.20 117 117 0.46 0.93

Red Canyon 2009 4,014.0 n/a 19 19 0.47 0.47

2012 3,873.6 19.10 52 52 2.72 2.72

2014 4,014.2 3.72 40 40 0.93 1.00

Ute Canyon 2009 7,171.0 n/a 18 18 0.25 0.25

2012 8,032.5 23.53 82 82 3.49 3.49

2014 7,949.6 6.35 51 51 1.00 0.64

Wedding Canyon 2009 2,994.0 n/a 7 7 0.23 0.23

2012 4,250.9 17.08 18 18 1.05 1.05

2014 4,250.9 5.07 2 2 0.64 0.05

Limekin Gulch 2009 503.0 n/a 0 0 0.00 0.00

Hydro 03 2012 445.6 1.91 2 2 1.05 1.05

2014 445.6 0.43 4 4 0.00 0.90

Fruita Canyon 2012 2,156.5 12.03 0 0 0.00 0.00

2014 2,156.5 2.03 0 0 0.00 0.00

Lizard Canyon 2012 1,273.7 5.32 0 0 0.00 0.00

2014 1273.7 1.01 0 0 0.00 0.00

Perkins (2014) briefly described the trends of several target species of invasive plants. Tamarisk has 

continued to decline in recent years, now only infesting four areas of COLM (Perkins 2014). This is 

an 81% reduction from 2011 to 2013 and overall a 96% reduction since 2003. Russian olive has 

shown a promising pattern of decline as well, with a 77% reduction from 2011 to 2013 (Perkins 

2014). Yellow sweetclover has declined significantly in the park in the same time period (2011-2013) 
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with a 68% overall reduction (Perkins 2014). Further monitoring will continue in 2015 (Perkins 

2014). Perkins (2014) suggests targeting a few areas for control efforts that have shown the least 

amount of improvement; these are Columbus, Red, and No Thoroughfare Canyons.

Cottonwood Regeneration

Cottonwoods are an important structural component of riparian habitats, as the roots provide soil 

stability and increase permeability, which in turn reduces runoff and erosion (D’Amico 1997). 

Cottonwoods also provide valuable wildlife habitat, as they offer shelter to many species, particularly 

birds (CSFS 2015). Two cottonwood species, the Rio Grande cottonwood (Populus deltoides ssp.

wislizeni) and the narrow-leaved cottonwood (Populus angustifolia), are found in four of the riparian 

communities in COLM. These species generally require moist, bare soil (e.g., recently deposited 

stream sediments) for seed germination and seedling establishment (D’Amico 1997). A recent 

cottonwood assessment study at COLM reported few seedlings and small saplings are present, 

despite the abundance of large saplings and pole-sized cottonwood trees (Kennard and Rogowski 

2015). This lack of a younger regeneration suggests that regeneration conditions over the past 5 years 

have not been ideal for cottonwood seedling establishment and survival. 

Channel Geomorphology

While there are no perennial flowing streams within COLM, there are seeps and washes where 

riparian habitat is supported by water from permanent and ephemeral water sources (Von Loh et al. 

2007). Changes to channel geomorphology can occur due to heavy rainfall events (Richard 2004). 

Heavy rainfall on the Uncompahgre Plateau creates surface water flows that are the primary channel 

forming mechanism within the park (KellerLynn 2006). These flash flood events (discussed below) 

have historically been a phenomenon in the area and are one of the primary mechanisms that helped 

to create the geological formations in the park (Richard 2004). The impacts on riparian/large dry 

wash habitats from changes to channels have not been widely studied. However, increased channel 

incision, caused by flooding events could affect the availability of groundwater (Lamm et al. 2015, 

Kennard and Rogowski 2015). If channel incision were to reach the water table, the storage capacity 

of the alluvial fill could be lowered as groundwater would be available to augment stream flow.

Other major changes to channel structure that occur during flash floods include the scouring and 

deposition of large volumes of materials (i.e. mud, rock, and other debris) which inevitably impacts 

the extent and plant communities within riparian habitats (Richard 2004).

Frequency and Discharge of Flash Floods

The combination of low permeability, bare rock, steep canyons, and sparse vegetation that is typical 

of COLM tends to concentrate rainfall events into sudden, rushing torrents rather quickly (Richard 

2004). While periodic, these flood events are considered normal for the region (Richard 2004). Flash 

floods move large amounts of material, uprooting vegetation in some areas and burying it with rock, 

sand, and other debris in others (Richard 2004). Information on impacts on riparian habitat from flash 

floods is necessary to assess any trends for this measure and an analysis comparing vegetation before 

and after a known flash flood event would be useful. KellerLynn (2006) recommended the 

development of a flash flood model, using stage gages and stream channel ratings, in order to better 

assess and predict the impacts of flood events in COLM.
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Threats and Stressor Factors

There are several factors that are a concern in terms of the riparian and large dry wash habitats at 

COLM. Park resource manager identified IEPs, trail use (authorized and unauthorized), 

channelization outside park boundaries, and climate change as being of primary concern.

Invasive plants may impact riparian habitats by competing with or replacing native species and 

altering ecosystem functions (e.g., water and nutrient cycling). Invasive species may use more water 

than native species. For example, tamarisk infestations have reduced spring flow into rivers in 

several southwestern states, reducing the amount of water available for riparian vegetation 

(Westbrooks 1998). Thick stands of tamarisk and other invasive plants can limit the availability of 

germination sites for cottonwoods and other native riparian species (Westbrooks 1998).

Visitor impacts within the park’s riparian habitats include damage to soils and vegetation from hiking 

(unauthorized and authorized trails). Many of COLM’s trails cross or are located in drainages 

(Hartwig, written communication, 20 September 2015). Disturbance of soils from hiking can increase 

erosion rates or cause soil compaction, which reduces water infiltration rates (Cole and Landres 

1995). Hikers, particularly those using unauthorized “social” trails, can also trample vegetation. This 

trampling can kill sensitive plant species while those that survive often exhibit reduced vigor and 

reproductive success (Cole and Landres 1995).

Climate change is a concern since changes in precipitation, particularly large storm events that result 

in heavy rainfall and flash flood events have major impacts on the vegetation in large dry washes and 

riparian habitats. As a result of global climate change, western Colorado is expected to experience an 

increase in temperature with longer and hotter summer heat waves, an increased potential for 

drought, and an increase in precipitation falling as very heavy events (Lamm et al. 2014, Melillo et 

al. 2014). Even with the projected increase in precipitation, a hotter, drier environment could increase 

the rates at which surface water and soil moisture are lost to evaporation, meaning the moisture will 

be available to plants and wildlife for a shorter time (Lamm et al. 2014).

Data Needs/Gaps

Cottonwood regeneration is considered a data gap for the riparian/large dry wash habitat assessment. 

A preliminary study of cottonwood regeneration took place in the park during the summer of 2015, 

and additional, related research was planned for the fall of 2015. Additionally, the geomorphology 

(change in channel structure) and flash flood discharge and frequency are also considered data gaps 

at this time since the information available has not specifically addressed the impacts on riparian 

habitats. Research on the impacts from the proliferation of social trails within the park is also 

recommended.

Currently a guaranteed funding source for the invasive species removal/control has not been 

identified. Failure to secure funding for this management action will result in the loss of the gains 

that have been made in eradicating IEPs within the park. Additionally, another programmatic need 

for COLM is a trail management plan. Currently, visitors face no restrictions in their access to any 

areas within the park.
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Overall Condition

Community Extent and Change over Time

The project team assigned this measure a Significance Level of 3. Available literature and data 

suggest that it is unlikely that the extent of riparian communities has undergone unnatural change 

since the creation of the park. A Condition Level of 1, or of low concern, was assigned to this 

measure. The vegetation mapping project completed by Von Loh et al. (2007) may serve as a 

baseline for future assessments and analyses.

Community Composition

While it can be assumed that the pre-settlement reference condition consisted of all native species 

within the riparian/large dry wash communities, the exact species composition is unknown at the 

time of park establishment. There are lists available from the Von Loh et al. (2007) vegetation 

mapping project to specifically list plant species in the riparian and large dry wash habitats and is the 

earliest documentation available to assess community composition. This measure was assigned a 

Significance Level of 3; at this time a Condition Level of 1, or of low concern, has been assigned due 

to the presence of IEPs which are a threat to native flora.

Trends in Invasive Infestation

The Significance Level of invasive infestations is assigned a 3. A reference condition of little to no 

invasive species infestations can be assumed. Over the last decade the park has focused control 

efforts on eradication of IEP’s. Future funding for these control measures is not available, so the 

potential for increased infestations is possible (Hartwig, written communication 18 November 2015). 

A Condition Level of 1 was assigned, or of low concern, since there are still infestations occurring 

within riparian habitats that can repopulate other areas and efforts to control invasive plants should 

continue to be a park priority.

Cottonwood Regeneration

The project team assigned this measure a Significance Level of 2. Kennard and Rogowski (2015) 

reported that the adult cottonwood population in COLM appears to be healthy, however their appears 

to be a lack of regeneration due to the low number of seedlings and small saplings Due to this factor 

a Condition Level of 1, low concern was assigned. Continued monitoring is recommended in order to 

determine if this is a short term condition or a more long-term change that may be associated with 

groundwater availability (Kennard and Rogowski 2015).

Geomorphology (Change in Channel)

This measure was assigned a Significance Level of 3. Changes in channel morphology could 

influence the extent and composition of riparian and large dry wash plant communities. Data also 

were not available to establish a reference condition or to assess current condition for this measure at 

COLM. As a result, assigning a Condition Level is not possible at this time. 

Frequency and Discharge of Flash Floods

The physical characteristics of COLM (e.g., steep canyon walls, bare rock areas) make the area prone 

to flash flooding (Richard 2004). This measure was assigned a Significance Level of 2, but due to 

data gaps, a Condition Level cannot be assigned at this time. If the recommendations from 
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KellerLynn (2006) are carried out, data can be used to assess any trends in the frequency and 

discharges of subsequent flood events at COLM.

Weighted Condition Score

A Weighted Condition Score of 0.33 was calculated for the riparian habitat/large dry washes at 

COLM, indicating that the resource is in good condition. Currently no trends could be identified for 

this component. Future efforts focused on gathering additional data for these measures should be a 

priority for assessing any trends in the health and condition of riparian/large dry wash vegetation 

communities. Overall, the riparian/large dry washes should be priority habitat to monitor considering 

their importance to the desert ecology in COLM.

Riparian Habitats / Large Dry Washes

Measures Significance Level Condition Level WCS = 0.33

Community Extent and 

Change over Time 3 1

Community 

Composition 3 1

Trends in Invasive 

Infestation 3 1

Cottonwood 

Regeneration 2 1

Geomorphology 3 n/a

Frequency and 

Discharge of Flash 

Floods

2 n/a

4.3.6 Sources of Expertise

Dusty Perkins, Program Manager, Northern Colorado Plateau Network

Rebecca Weissinger, Ecologist NPS Northern Colorado Plateau Network

Kim Hartwig, COLM Chief of Resources Management

4.3.7 Literature Cited

Cole, D. N., and P. B. Landres. 1995. Indirect effects of recreation on wildlife. Pages 183-202 in

Wildlife and recreationists: Coexistence through management and research. Island Press, 

Washington, D.C.
129

Colorado State Forest Service (CSFS). 2015. Cottonwood management: Ecology, rehabilitation, 

wildfire and other considerations. Quick Guide Series FM 2015-1. Colorado State Forest Service, 

Fort Collins, Colorado.

D’Amico, D. R. 1997. Regeneration of plains and narrowleaf cottonwood on south Boulder Creek, 

Boulder Colorado. City of Boulder Open Space Department, Boulder, Colorado.

Dewey, S. and K. Anderson. 2005. An inventory of invasive nonnative plants in Colorado National 

Monument (2003). Weed Science Research Project Report No. SD0516A. Utah State University, 

Logan, Utah.

Fertig, W., S. Topp, M. Moran, T. Hildebrand, J. Ott, and D. Zobell. 2012. Vascular plant species 

discoveries in the Northern Colorado Plateau Network: Update for 2008–2011. Natural Resource 

Technical Report NPS/NCPN/NRTR—2012/582. National Park Service, Fort Collins, Colorado.

Hanophy, W., and H. Teitelbaum. 2003. Wild Colorado: Crossroads of biodiversity. Colorado 

Division of Wildlife, Education Section, Denver, Colorado.

Hogan, T., N. Lederer, and W. Fertig. 2009. Annotated checklist of vascular flora: Colorado National 

Monument. Natural Resource Technical Report NPS/NCPN/NRTR—2009/231. National Park 

Service, Fort Collins, Colorado.

KellerLynn, K. 2006. Colorado National Monument Geologic Resource Evaluation Report. Natural 

Resource Report NPS/NRPC/GRD/NRR—2006/007. National Park Service, Denver, Colorado.

Kennard, D. K. and K. Rogowski. 2015. An assessment of cottonwood (Populus deltoides ssp. 

wislizeni) populations in the Colorado National Monument. National Park Service, Fort Collins, 

Colorado.

Lamm, N., S. Igo, and M. Davlantes, 2014. Report of the 2014 Geocorps springs and seeps 

assessment, Colorado National Monument, Colorado. National Park Service, Fruita, Colorado.

Melillo, J. M., T. C. Richmond, and G. W. Yohe, eds. 2014. Climate change impacts in the United 

States: The third national climate assessment. U.S. Global Change Research Program, 

Washington, D.C. 

Perkins, D. 2010. Invasive exotic plant monitoring at Colorado National Monument, 2009. Natural 

Resource Technical Report NPS/NCPN/NRTR—2010/354. National Park Service, Fort Collins,

Colorado.

Perkins, D. 2012. Invasive exotic plant monitoring in Colorado National Monument: 2011 field 

season. Natural Resource Technical Report NPS/NCPN/NRTR—2012/556. National Park

Service, Fort Collins, Colorado.
130

Perkins, D. 2014. Invasive exotic plant monitoring in Colorado National Monument: 2013 field 

season. Natural Resource Technical Report NPS/NCPN/NRTR—2014/859. National Park 

Service, Fort Collins, Colorado.

Richard, G. A. 2004. Flash flooding at the Colorado National Monument 1921-2003. National Park 

Service, Fruita, Colorado.

Von Loh, J., K. Landgraf, A. Evenden, T. Owens, S. Blauer, and M. Reid. 2007. Vegetation 

Classification and Mapping Project Report, Colorado National Monument. Natural Resource 

Technical Report NPS/NCPN/NRTR—2007/061. National Park Service, Fort Collins, Colorado.

Westbrooks, R. G. 1998. Invasive plants: Changing the landscape of America. Federal Interagency 

Committee for the Management of Noxious and Exotic Weeds, Washington, D.C.
131

4.4 Seeps and Springs and Tinaja Habitats

4.4.1 Description

Seeps, springs, and tinajas (rocky, water-holding potholes) provide important water sources and 

habitats for plants and wildlife in semi-arid regions (Springer et al. 2006). Springs support some of 

the most diverse and productive ecosystems on the Colorado Plateau, but are also among the most 

threatened communities (Springer et al. 2006). Seeps and springs can serve as indicators of change in 

local and regional aquifers due to their reliance on groundwater, which is most often recharged by 

precipitation (SCPN 2012).

COLM’s seeps and springs emerge from three different sources: Wingate sandstone, alluvial valley 

fill, and fractures in Precambrian metamorphic “basement” rock (Lamm et al. 2014). Of the 38 seeps 

and springs identified in the park in 2014, 15 originated in Wingate sandstone, 16 from alluvial 

valley fill, and seven from Precambrian metamorphic rock (Lamm et al. 2014). Seeps and springs are 

commonly found in canyon heads, and along drainage channels. Historically, springs were also found 

at the ends of mesas (Nancy Lamm, GeoCorps Guest Scientist in the Park, written communication, 

24 November 2015). A recent survey of these springs reported that flows have diminished from what 

was reported in historic accounts (Lamm, written communication, 27 November 2015). Discharge 

from some seeps in COLM is minimal and ephemeral, and may only be notable as a wet surface on a 

rock or as discoloration from dried salts on the rock face. Other springs produce enough water to 

support small pools and riparian vegetation (as described previously in Chapter 4.3 of this document) 

(Lamm et al. 2014; Photo 7). These water sources may also support “hanging gardens”, pockets of

vegetation on nearly vertical canyon walls (Von Loh et al. 2007), which will be further described in 

Chapter 4.6 of this document.

Photo 7. A seep-fed pool in No Thoroughfare Canyon (left) and riparian vegetation at Lost Lunch Spring 

in Ute Canyon (Photos from Lamm et al. 2014).

The seeps and springs habitats at COLM are closely associated with the riparian habitats discussed in 

the previous chapter. Many of the same species that utilize those habitats also can be found within 

and around the seep and springs communities. This is especially true for amphibian species within 

COLM as the seep, spring and tinaja habitats provide shelter and a source of water (Platenberg and 
132

Graham 2003, Von Loh et al. 2007). A variety of aquatic macroinvertebrates and insects can be 

found within these communities and provide a major food source for COLM herptiles (NPS 2015).

4.4.2 Measures

 Vegetation community extent and change over time 

 Vegetation community composition

 Trends in invasive infestation

 Water quality

 Discharge

4.4.3 Reference Conditions/Values

The ideal reference condition for this component would be the condition of seeps, springs, and tinajas 

prior to settlement. However, little information is available from this time, making reference 

conditions a challenge to determine. For this assessment, conditions will be assessed based on best 

professional judgment given the available data. The information presented in this chapter may be 

used as baselines for future assessments.

4.4.4 Data and Methods

Lamm et al. (2014) conducted an inventory of COLM seeps and springs from May to July 2014. 

Thirty-eight seep- and spring-associated sites were visited. Data collected at each site included 

estimated discharge (i.e., flow), flora and fauna observations, and when sufficient amounts of water 

were available for testing; selected water quality parameters (temperature and specific conductance) 

were collected. A map of each site was also drawn and photographs were taken to document features 

of interest. Water samples were taken from four sites in late June for more detailed water quality 

analysis in a lab (Lamm et al. 2014).

Many of the sites inventoried by Lamm et al. (2014) had previously been visited and assessed by the 

United States Geological Survey (USGS) in 2000 and 2001 (Butler et al. 2003). The USGS 

assessment involved field measurements of discharge and water quality (e.g., temperature, pH, 

specific conductance, and dissolved oxygen) at 10 sites, and collection of water samples for detailed 

lab analysis. The USGS visited numerous additional sites for reconnaissance purposes but did not 

record any data (Butler et al. 2003).

Springer et al. (2006) inventoried 75 springs across 26 NPS units in the NCPN and SCPN. Field 

work was conducted in 2005 and included vegetation and invertebrate surveys, water quality 

analyses, and water quantity measurements (Springer et al. 2006). Two springs were surveyed at 

COLM: Echo Canyon Spring (lower) and No Thoroughfare Canyon (NTC) Spring.

Von Loh et al. (2007) conducted a vegetation classification and mapping project for COLM and 

surrounding areas. The resulting map shows the locations of all dominant vegetation types present 

within COLM in the early 2000s. The project involved traditional aerial photo interpretation and field 

sampling of 288 plots between May and October 2003 (Von Loh et al. 2007). Because most 

vegetation communities surrounding seeps and springs are smaller than the 0.5 ha (1.2 ac) minimum 
133

mapping unit used in this project, seep and spring vegetation communities were mapped as points 

rather than polygons. As a result, the total areal extent of these communities cannot be calculated.

This synthesis of the relevant scientific data and information does not include the climate data and 

information used in conducting the climate change vulnerability assessment for this resource. Please 

refer to Chapters 2.1.3 and 3.2.3 and Appendix A for a discussion of the data and methodology used 

in the climate change analysis.

4.4.5 Current Condition and Trend

Vegetation Community Extent and Change over Time

Spring, seep, and tinaja communities can be challenging to map, given their typically small size and 

sparse distribution across the landscape. Some of these features are also ephemeral and may be dry 

for portions of the year, making them difficult to identify. During a vegetation mapping and 

classification project, Von Loh et al. (2007) identified 17 point locations that supported seep and 

spring vegetation (Figure 31). Areal extent information (i.e., community/stand size) was not included 

with these data.

Lamm et al. (2014) visited 38 spring, seep, and tinaja sites. This report represents the evaluation of 

the known sites as well as new sites that were identified during the field inventory. However, it does 

not represent a complete inventory of all seeps and springs located within COLM (Lamm, written 

communication, 27 November 2015). Lamm et al. (2014) did visit some (but not all) of the locations 

mapped by Von Loh et al. (2007). These locations are displayed in Figure 32. While Lamm et al. 

(2014) recorded some observations on the sizes of pools or the distance water/moisture extended 

from a source, no uniform measurements of each site’s areal extent were conducted. Any differences 

in seep and spring location between Von Loh et al. (2007) and Lamm et al. (2014) are likely due to 

differences in methodology (e.g., areas of focus) rather than any change in seep or spring locations 

between studies. Lamm et al. (2014) also noted that time constraints prevented them from visiting 

every canyon in the park.

Vegetation Community Composition

Springer et al. (2006) surveyed vegetation at two COLM springs: Lower Echo Canyon (LEC) and No 

Thoroughfare Canyon (NTC) Springs. A combined total of 57 plant species were recorded at the two 

sites. Twenty-three species were documented at NTC Spring (18 native, five non-native) and 41 

species (34 native, seven non-native) at Lower Echo Canyon Spring (Springer et al. 2006). These 

species are listed in Appendix F.

Lamm et al. (2014) provides a more comprehensive record of plant community composition specific 

to COLM’s seep, spring, and tinaja habitats. At the 34 seeps and springs inventoried, 96 different 

plant species were documented, 19 of which were non-native (Lamm et al. 2014). On average, native 

plants made up 84% of the species at each site. Species richness per site ranged from six (Red 

Canyon) to 51 (NTC). Sites with low diversity were generally very small or included large areas of 

bare rock (Lamm et al. 2014).
134

Figure 31. Seep and spring vegetation locations in COLM mapped by Von Loh et al. (2007).
135

Figure 32. Seep, spring, and tinaja sites inventoried by Lamm et al. (2014) (Reproduced from Lamm et 

al. 2014).

The most common native species were desert saltgrass (Distichlis spicata), Baltic rush, hairy false 

goldenaster, narrow-leaved cottonwood, willows (Salix spp.), and Utah serviceberry (Lamm et al. 

2014). Non-native species observed include tamarisk, cheatgrass, bull thistle (Cirsium vulgare),

burdock (Arctium minus), poison-hemlock (Conium maculatum), woolly mullein, and yellow 
136

sweetclover (Lamm et al. 2014). Woody species (e.g., trees and shrubs) were present at all but one 

site, with 20 of the 34 sites supporting a tree canopy over 4 m (13.1 ft) high (Lamm et al. 2014). A 

full list of plant species documented by Lamm et al. (2014), by canyon, is included as Appendix G.

Trends in Invasive Infestation

A total of 22 IEP species have been detected at COLM’s seeps, springs, and tinajas (Springer et al. 

2006, Lamm et al. 2014; Appendix G). According to Lamm et al. (2014), non-native invasive plants 

do not dominate species richness or cover at the 34 seep and spring sample sites where vegetation 

was inventoried. The highest proportion of non-native species was at a site in NTC (Sunscreen Seep) 

where four of the eight plant species documented were non-native (Lamm et al. 2014). The only 

invasive species found at more than half the sites (25 of 34) was cheatgrass, although only trace 

amounts (<1% cover) were found at 14 of the 25 sites. However, one Wedding Canyon site (Stone 

Cistern Spring) had approximately 90% cheatgrass cover, and 25-50% cover was noted at a site in 

Upper Ute Canyon (Lamm et al. 2014). Potentially problematic levels of cheatgrass (10-25% cover) 

were also reported at two sites in Monument Canyon. The second most common non-native species 

was sweetclover, found at 14 of 34 sites. Only two sites in NTC showed potentially problematic 

levels (10-25%) of this species (Lamm et al. 2014). Tamarisk, classified as a noxious weed in 

Colorado, was found at four sites in four different canyons (NTC, Monument, Wedding, and Echo). 

The species comprised 10-25% cover at a Monument Canyon site (Bedrock Spring), 1-10% at an 

NTC site, and <1% at the remaining two sites. Lamm et al. (2014) recommended removal of the 

species from all sites. Other species classified as noxious weeds were found at only trace amounts 

(<1%) at one site (bull thistle, poison-hemlock, woolly mullein) or two sites (burdock) (Lamm et al. 

2014).

Water Quality

Water quality has a significant impact on organisms living in and around a water body, and on 

potential uses of that water (e.g., human or livestock consumption, recreation) (USGS 2010). 

Chemistry parameters of interest include pH, dissolved oxygen (DO), dissolved solids, ion levels 

(e.g., nitrates, phosphates, metals, salts), and contaminants of concern (e.g., surfactants, 

pharmaceuticals, pesticides). Butler et al. (2003) recorded field measurements (water temperature, 

specific conductance) at several park seeps and springs (Table 37) and collected samples from 11 

seeps and springs for detailed water quality analysis in a lab (Table 38). Springer et al. (2006) 

recorded field measurements and collected water samples for analysis from two COLM springs 

(Table 38). Most recently, Lamm et al. (2014) reported field measurements (water temperature, 

specific conductance) for 27 park seeps and springs (Table 37, Table 38); the remaining 11 sites 

visited by Lamm et al. (2014) did not have enough standing/flowing water to conduct measurements. 

Water quality information may not be directly comparable among surveys, as sampling may be 

conducted at different times of year, and it is not always clear if measurements were taken at the 

exact same location (i.e., the same pool or distance from spring source). Water temperature and 

specific conductance (SC) readings were highly variable (Table 37). There are a variety of factors 

that could be responsible for this variability. Seasonal differences in sampling could account for this 

variability. The variation in SC can also be correlated to different groundwater residence times (Don 

Weeks, NPS Water Resources Division (WRD) Climate Change Resource Planner, written 
137

communication, 27 November 2015). High SC readings during the winter months may be due to 

stagnant conditions (Lamm et al. 2014).

Table 37. Water temperature (°C) and specific conductance (μS/cm) field measurements from sampled 

seeps and springs in COLM (Butler et al. 2003, Lamm et al. 2014). All 2014 data were collected in June 

or July of that year.

Site

Sampling 

Period

Temp 

(°C)

Specific 

conductance 

(μS/cm) Site

Sampling 

Period

Temp 

(°C)

Specific 

conductance 

(μS/cm)

WC-1

1 11/2000 6.5 1,380 UC-3 2014 15.3 913

WC-2 2014 28.1 728 UC-6 2014 21.7 1,060

MC-2 2014 25.7 1,949 RC/UC-1 10/2000 12.2 397

2014 27.0 3,660

MC-3 1/2001 0.1 1,380 NTC-2 2014 24.4 943

2014 20.9 476 NTC-3 11/2000 -- 1,430

MC-6 11/2000 3.4 1,040 2014 21.0 1,260

2014 20.8 870 NTC-4 2014 22.3 1,390

MC-7 2014 23.5 1,836 NTC-5 2014 13.9 1,290

MC-10 2014 23.5 885 NTC-6 2014 22.5 1,640

MC-11 2014 26.2 1,270 NTC-8 2014 14.8 980

UC-1 2014 15.1 1,060 NTC-10 2014 11.0 1,005

UC-2 2014 16.4 1,090

1 Not enough water was available at this site in 2014 for testing.

Tributaries of the Colorado River (including surface water systems in COLM) are listed as impaired 

waters due to selenium concentrations (EPA 2015). Selenium is a natural occurring mineral and at 

high concentrations it has many toxic impacts upon fish and wildlife (Paschke et al. 2014). Selenium 

is commonly associated with upper Cretaceous marine sedimentary rocks such as the Mancos Shale 

formation at COLM (O’Dell 2005). Groundwater in contact with this formation is susceptible to 

elevated selenium levels (Paschke et al. 2014).

DO levels below 5.0 mg/L are generally considered low, and the data for COLM springs for the most 

part is near or below this level. While low DO values are quite common for springs within the 

NCPN, they can create very stressful aquatic environments (Rebecca Weissinger, NPCN Ecologist, 

written communication, 16 November 2015). Although only one sample (NTC-7 collected in 2005) 

exceeded EPA the drinking water quality standards (EPA 2009) for dissolved solids and sulfate 

(Table 38) (Springer et al. 2006), the DO levels and potential for high selenium concentrations 

suggest that the water quality of COLM seeps and springs is variable and can create extreme 

conditions (Weissinger, written communication, 16 November 2015)
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Table 38. Water quality measurements for springs with detailed sample analysis by Butler et al. (2003) or Springer et al. (2006), along with field 

measurements from Lamm et al. (2014). Values are in mg/L, unless otherwise indicated. All 2014 data were collected in June or July of that year.

Site or Subsite

Sampling 

Period

Temp 

(°C)

SC 

(μS/cm) pH DO

Dissolved 

Solids3 Sulfate4 Chloride4

Nitrogen5

(NO2 + NO3)

MC-4 4/2001 9.7 590 8.30 8.0 337 31.8 8.3 0.008

11/2001 8.2 632 8.30 7.8 371 40.0 13.0 <0.013

2014 20.7 582

MC-8 11/2000 1.6 3,670

4/2001 22.0 1,430 8.01 5.6 936 256 71.0 0.006

seep in E. trib. 2014 14.1 1,030

seep in W. trib 2014 24.8 1,216

distal end of a.v.f. 2014 27.8 2,430

MC-9 11/2000 1.4 580

4/2001 14.6 580 8.56 6.6 340 42.1 5.4 0.006

11/2001 8.0 544 8.71 11.3 344 38.0 5.9 0.124

2014 18.7 522

GS-1

1 11/2000 1.6 1,170

4/2001 13.0 646 8.83 5.2 400 91.1 13.4 5.080

UC-5

1 12/2000 8.5 600

4/2001 10.5 589 7.51 5.0 341 26.1 7.7 0.077

11/2001 11.6 727 7.30 1.5 353 15.3 10.4 est. 0.010

RC-1 4/2001 11.9 696 7.88 3.4 405 32.6 12.6 <0.005

11/2001 8.9 579 7.40 0.4 338 6.0 5.5 --

2014 16.2 870

1 Not enough water was available at these sites in 2014 for testing.

2 This spring had completely dried up when Lamm et al. (2014) visited in 2014.

3 The recommended maximum contaminant level (MCL) for total dissolved solids in drinking water is 500 mg/L (EPA 2009).

4 The recommended MCL for sulfate and chloride in drinking water are 250 mg/L (EPA 2009).

5 The required MCLs for nitrogen in drinking water are 1 mg/L for NO2 and 10 mg/L for NO3 (EPA 2009).
139

Table 38 (continued). Water quality measurements for springs with detailed sample analysis by Butler et al. (2003) or Springer et al. (2006), 

along with field measurements from Lamm et al. (2014). Values are in mg/L, unless otherwise indicated. All 2014 data were collected in June or 

July of that year.

Site or Subsite

Sampling 

Period

Temp 

(°C)

SC 

(μS/cm) pH DO

Dissolved 

Solids3 Sulfate4 Chloride4

Nitrogen5

(NO2 + NO3)

CC-1 11/2000 0.5 647

4/2001 10.3 646 7.95 7.2 376 38.6 10.2 0.167

11/2001 11.3 775 7.90 7.4 467 52.0 15.7 0.105

from pool 2014 27.5 375

NTC-1 1/2001 2.6 789

5/2001 10.0 826 7.70 9.0 482 49.6 22.4 <0.005

2014 12.5 468

NTC-7 7/2005 16.0 805 8.21 6.5 700 281.6 4.7 0.020

2014 9.3 900

EC-1 4/2001 12.7 628 7.38 5.2 381 72.3 8.2 0.023

11/2001 14.0 611 7.53 4.0 386 71.0 10.0 0.019

7/2005 15.3 512 7.01 4.5 400 71.9 8.6 0.030

5/13/2014 21.8 488

5/28/2014 30.3 644

Butler’s Sp-6B2 5/2001 9.9 767 7.21 3.1 441 23.4 9.7 <0.005

11/2001 7.2 275 8.00 5.4 155 2.2 1.8 <0.013

1 Not enough water was available at these sites in 2014 for testing.

2 This spring had completely dried up when Lamm et al. (2014) visited in 2014.

3 The recommended maximum contaminant level (MCL) for total dissolved solids in drinking water is 500 mg/L (EPA 2009).

4 The recommended MCL for sulfate and chloride in drinking water are 250 mg/L (EPA 2009).

5 The required MCLs for nitrogen in drinking water are 1 mg/L for NO2 and 10 mg/L for NO3 (EPA 2009).
140

Discharge

Availability of discharge data for COLM’s seeps and springs is limited. Butler et al. (2003) reported 

flows from ten park springs in April and/or November of 2001. These flows ranged from <0.04 liters 

per minute (lpm) (<0.01 gallons per minute [gpm]) to a reported 21.0 lpm (8.2 gpm) (Table 39). 

Springer et al. (2006) measured discharge at NTC and Lower Echo Canyon Springs in July 2005 

(Table 39). Lastly, Lamm et al. (2014) estimated discharge rates and noted those with no flow in 

June and July 2014. Discharges ranged from no flow to approximately 18.9 lpm (5.0 gpm) 

downstream from Echo Canyon Spring (Table 39). Nine springs or seeps had no noticeable flow, 

although wet soil or small pools were sometimes present, and an additional 14 springs had estimated 

discharges <0.95 lpm (<0.25 gpm). Lamm et al. (2014) noted that the timing of their sampling may 

have influenced water quantity at seeps and springs, as these sites are often drier during warm

summer weather. Discharge rates may not be directly comparable between surveys, as it is not 

always clear if measurements were taken at the exact same location or with similar methodologies.

Table 39. Discharge measurements for surveyed COLM seep and spring sites. Values are given in lpm 

(with gpm in parentheses), unless otherwise noted. 

Site or Subsite* Butler et al. (2003) Lamm et al. (2014) Springer et al. (2006)

WC-1 no flow

WC-2 <0.95 (<0.25) 

W-MC-1 <0.95 (<0.25)

MC-1 a couple drops/min not measurable

MC-2 approx. 3.8 (1.0)

MC-3 not measurable

MC-4 2.7 (0.72) (April) 1.9 (0.5)

MC-5 approx. 1.9 (0.5)

MC-6 no flow; pools present

MC-7 3.8 (1.0)

MC-8 1.8 (0.48) (April)

 eastern trib. <0.95 (<0.25) 

 western trib. <0.95 (<0.25) 

MC-9 est. 1.9 (0.5) (April); 

<0.4 (<0.1) (Nov.)

<0.95 (<0.25) 

MC-10 <0.95 (<0.25) 

MC-11 no flow; pools present

GS-1 <0.04 (<0.01) (April) <3.8 (<1.0)

GS-2 <3.8 (<1.0)

GS-3 no flow, wet soils

UC-1 no flow, pools and wet soils 

present

UC-2 <18.9 (<5.0) highest flow area 

*WC = Wedding Canyon, MC = Monument Canyon, UC = Ute Canyon, GS = Gold Star Canyon, RC = 

Red Canyon, CC = Columbus Canyon, NTC = No Thoroughfare Canyon, EC = Echo Canyon.
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Table 39 (continued). Discharge measurements for surveyed COLM seep and spring sites. Values are 

given in lpm (with gpm in parentheses), unless otherwise noted. 

Site or Subsite* Butler et al. (2003) Lamm et al. (2014) Springer et al. (2006)

UC-3 7.6 (2.0)

UC-4 <3.8 (<1.0)

UC-5 22.0 (5.8) (April);

31.0 (8.2) (Nov.)

no flow, small pool

UC-6 <3.8 (<1.0)

RC/UC-1 <3.8 (<1.0)

RC/UC-2 wet spots on rock no flow/pools

RC-1 1.4 (0.38) (April) no flow; pools present

CC-1 1.8 (0.48) (April);

<0.4 (<0.1) (Nov.)

5-10 drops/minute from several 

seeps

NTC-1 0.8 (0.2) (May) <0.95 (<0.25)

NTC-2 3.8 (1.0)

NTC-3 100 mL/min (<0.25)

NTC-4 50 mL/min (<0.25)

NTC-5 0.75 mL/min (<0.25 gpm) (6 m 

downstream from seeps)

NTC-6 30 mL/min (<0.25 gpm) (6 m 

downstream from spring)

NTC-7 1.9 (0.5) 1.4 (0.4) (35 m downstream)

NTC-8 approx. 3.8 (1.0)

NTC-9 no flow

NTC-10 approx. 0.95 (0.25)

EC-1 18.6 (4.9) (April); 

20.4 (5.4) (Nov.)

3.8 (1.0) at upper end, approx. 

18.9 (5.0) downstream

10.3 (2.7)

*WC = Wedding Canyon, MC = Monument Canyon, UC = Ute Canyon, GS = Gold Star Canyon, RC = 

Red Canyon, CC = Columbus Canyon, NTC = No Thoroughfare Canyon, EC = Echo Canyon.

Lamm et al. (2014) noted a pattern of minimal or diminished flow from Wingate sandstone springs

when compared to previous accounts, particularly in the eastern portion of the park. Several springs 

documented by Butler et al. (2003) were no longer viable water sources (e.g., Spring 6B in 

Monument Canyon, Spring 19 in Upper NTC). Lamm et al. (2014) theorized that groundwater flow 

to some portions of the park has been restricted by channel incision in canyon drainages. This is a 

naturally occurring phenomenon of canyon morphology over time and not the result of recent 

erosion. In these areas, channel incision has “downcut” through the entire thickness of the Wingate 

sandstone layer, stopping water movement through the aquifer (typically in a northeasterly direction) 

(Lamm et al. 2014). This appears to be occurring along Monument Mesa, between Ute and Red 

Canyons, and between Red and No Thoroughfare Canyons.

Vulnerability to Climate Change

The seep, spring, and tinaja habitats at COLM were selected (along with pinyon-juniper 

woodlands/savannas [Chapter 4.1.5]) for additional analysis of their vulnerability to climate change 
142

(See Chapter 3.1.1). Von Loh et al. (2007) describes several vegetation classifications within COLM 

that are found near or associated with seeps, springs, tinajas, or hanging gardens. The vegetation 

communities within these classifications are discussed in detail in Chapter 4.3 (Riparian 

habitats/large dry washes) and Chapter 4.6 (Canyon walls and monolith vegetation communities 

[hanging gardens]), respectively. For this climate change analysis, three vegetation associations were 

selected from these classifications to determine the vulnerability of seep, spring, and tinaja habitats to 

climate change. They are: the Mancos columbine herbaceous vegetation community, the smooth 

horsetail herbaceous vegetation community, and the cottonwood/coyote willow woodlands. The 

Mancos columbine herbaceous vegetation association was chosen as it is restricted to perennial seeps 

in the crevices, ledges, and alcoves in canyons walls and is found only in the canyons of western 

Colorado, eastern Utah, and eastern Arizona (Von Loh et al. 2007). The smooth horsetail herbaceous 

vegetation community within COLM is classified as a palustrine wetland community occurring only 

in canyons with permanent seeps and springs (Von Loh et al. 2007). The cottonwood/coyote willow 

woodland is also classified as a palustrine wetland community by Von Loh et al. (2007) and is found 

exclusively in mesic canyon bottoms, intermittent drainage banks or terraces, and alcoves (Von Loh 

et al. 2007). The most extensive stands of this community occupy stream banks in upper No 

Thoroughfare Canyon, where perennial flow is provided from runoff, seeps, and springs (Von Loh et 

al. 2007).

In order to assess the vulnerability of the seeps and springs, and tinaja habitats to climate change, 

using the landscape scale community-based methodology discussed in Chapter 3.3, representative 

plant species were selected. The namesake species where selected from each of the vegetation 

associations discussed above as representatives. These species were assessed using the methodology 

described in Chapter 3.3 to provide the climate change vulnerability of the seeps and springs and 

tinaja habitats at COLM. The representative species selected were Mancos columbine, smooth 

horsetail, Rio Grande cottonwood, and coyote willow. Their vulnerability to climate change will be 

assessed based on five factors: location within the community’s geographic range, sensitivity to 

extreme climatic events, dependence on hydrologic conditions, the community’s adaptive capacity, 

vulnerability of ecologically influential species, and the potential for climate change to increase the 

impacts of non-climate stressors. A detailed description of this methodology and definition of these 

five variables is presented in Chapter 3.3 of this report.

The Rio Grande cottonwood and Mancos columbine have a limited geographic extent, with Mancos 

columbine only found in western Colorado, southeastern Utah, and northeastern Arizona (Figure 33

and Figure 34, NRCS 2015). Coyote willow is widespread throughout the western United States and 

western Canada, while smooth horsetail is found throughout much of the northeast and western 

United States, Northern Great Plains, and Canada (Figure 33 and Figure 34, NRCS 2015). Within 

COLM, these four species are found between 1,511 and 1,833 m (4,957 to 6014 ft) in elevation and 

at north to easterly aspects (Von Loh et al. 2007). The Rio Grande cottonwood/coyote willow 

association can also be found along southeast aspects (Von Loh et al. 2007). COLM is more or less 

centrally located within the latitudinal range of smooth horsetail and coyote willow; however, it is 

located along the north and eastern margins of the latitudinal extent of both the Rio Grande 

cottonwood and Mancos columbine (Figure 33 and Figure 34, NRCS 2015).
143

Based on COLM’s location within the geographical ranges of Rio Grande cottonwood and Mancos 

columbine, location alone would not cause them to be significantly vulnerable to an increase in 

temperature and aridity caused by a northern and/or westward shift in these species preferred climatic 

conditions. These species are dependent on specific hydrologic regimes. These species are also 

dependent on the availability of shallow groundwater in their rooting zone (Decker and Rondeau 

2014). An abrupt or prolonged change in this availability through periods of drought or changing 

precipitation patterns can have a severe impact on the vegetation associated with seeps, springs, and 

tinajas (Evenden et al. 2002, Decker and Rondeau 2014, Lamm et al. 2014). As was previously 

discussed in Chapter 4.1.5, the climate models project warmer and drier (more arid) conditions for 

COLM by 2100. Western Colorado is expected to experience an increase in temperature with longer 

and hotter summer heat waves (Chapter 4.1.5 -Figure 18), an increased potential for drought and 

wildfires, and an increase in precipitation falling during very heavy events (ClimateWizard 2014, 

Lamm et al. 2014, Melillo et al. 2014). While the climate models predict an increase in annual 

precipitation, higher temperatures will result in greater evapotranspiration rates, leading to increased 

aridity in all seasons, especially fall (September-November) and spring (March-May) (Chapter 4.1.5 

- Figure 19, ClimateWizard 2014).
144

Figure 33. Current geographic extent of seep, spring, and tinaja habitats keystone species (A. Mancos 

columbine and B. smooth horsetail) used in the climate change vulnerability analysis. The geographic 

extents are based on county level data from NRCS 2015.

A. Mancos columbine

B. Smooth horsetail
145

Figure 34. Current geographic extent of seep, spring, and tinaja habitats keystone species (A. coyote 

willow and B. Rio Grande cottonwood) used in the climate change vulnerability analysis. The geographic 

extents are based on county level data from NRCS 2015.

A. Coyote willow

B. Rio Grande cottonwood
146

The groundwater supply that feeds COLM’s seeps and springs, particularly those in the alluvial 

valley fill, is strongly influenced by annual and seasonal precipitation (Lamm et al. 2014). While the 

alluvial valley fill aquifers will be directly impacted on a seasonal basis, the impact to the bedrock 

aquifers will take a much longer period of time before they become apparent in spring discharge 

(Lamm et al. 2014). In many cases the recharge to these bedrock aquifers is directly related to the 

groundwater availability in the overlying alluvial valley fill (Lamm, written communication, 27 

November 2015). During droughts, groundwater recharge will decline and, in turn, contribute to a 

decline in seep and spring discharge. Reduced water availability will negatively impact the 

vegetation and wildlife that rely on these sites, potentially reducing biodiversity. Weather extremes 

of heavy precipitation and flooding also pose a threat to seeps and springs (Richard 2004). These 

events can trigger mudslides, move boulders and trees, and erode stream banks, all of which could 

alter or destroy spring, seep, and tinaja habitats (Richard 2004). Heavy precipitation could accelerate 

erosion of the alluvial valley fill aquifer, reducing water storage capacity and potentially eliminating 

springs or seeps (Lamm et al. 2014).

The vegetation communities that rely on the soil moisture and groundwater supplied by seeps, 

springs, and tinajas at COLM do not have significant adaptive capacity. A hotter, drier environment 

could increase the rate at which water from seeps and springs or in tinajas is lost to evaporation, 

meaning it will be available to plants and wildlife for a shorter time (Chapter 4.1.5 - Figure 20,

ClimateWizard 2014, Lamm et al. 2014). The projected changes in precipitation, temperature, and 

evaporation rates are likely to reduce the number of tinajas that hold water (Evenden et al. 2002). 

Warmer, drier conditions will likely lead to the loss of these vegetation communities to other, more 

xeric vegetation communities or non-native species (Decker and Rondeau 2014).

As discussed in Chapter 2.1.2, the GCM predict higher temperatures and slight increases in 

precipitation for this region. While there is a slight projected increase in precipitation, the higher 

temperatures (for all seasons) will create higher evapotranspiration rates, ultimately resulting in drier 

conditions. These hotter and drier conditions expected in COLM over the next century will likely 

exacerbate many of the current non-climate stressors of the seep, spring, and tinaja habitats at 

COLM. Development in the surrounding communities along with changes in other adjacent land uses 

has the potential to negatively impact groundwater resources. If groundwater withdrawals for 

agricultural or domestic uses were to increase in the region, seep and spring flow could be negatively 

impacted. In the case of COLM, there is concern that residential development in the Glade Park area 

southwest of COLM may already be affecting groundwater flow and supply to park springs (Martin 

2013, Lamm et al. 2014). Wells in this development primarily draw water from the Wingate 

Sandstone aquifer (Martin 2013). As of 2009, there were 440 residences in this area, 150 of which 

were very close to the COLM boundary (Sharrow 2009). The cumulative impact of so many wells 

could lower the water table or capture recharge that otherwise would flow towards the park, 

decreasing groundwater flow to COLM’s seeps and springs (Martin 2013).

It is difficult to assess how the warmer and drier conditions predicted for COLM will affect the IEPs 

already invading the seep, spring, and tinaja communities. While Dukes and Mooney (1999)

suggested that most aspects of global climate change will favor invasive species over natives, it is 
147

unknown if this pattern will apply to already arid environments such as COLM. Currently, IEP

species are not found in significant numbers or areal coverage in the seeps, springs, and tinaja

habitats at COLM (Lamm et al. 2014). Tinaja and other springs that are protected from flooding tend 

to be resilient to IEPs, due to the lack of room for germination (Weissinger, written communication, 

16 November 2015). Increased numbers of IEPs may occur in flood-prone springs, although the 

saturated conditions in the springs themselves will prevent the invasion of any IEP that is not 

phreatophytic (Weissinger, written communication, 16 November 2015). However, future drier 

conditions could cause areas that currently have spring-related vegetation to convert to more xeric 

species, both native and non-native. These drier conditions are expected to be more favorable for 

tamarisk and cheatgrass (Bradley et al. 2009, Bradley and Wilcove 2009), which are presently two of 

the more common non-native species in these habitats. Currently, cheatgrass and tamarisk are found 

in small amounts, but future conditions could lead to an increase in the extent of these and other nonnative species, especially if an IEP removal program is not maintained.

Threats and Stressor Factors

Park resource managers identified influences from a changing climate (e.g. increase in mean and 

annual temperature, increase in extreme drought /precipitation events), increases in IEPs, visitor 

impacts, and development in surrounding communities (e.g. groundwater removal and wastewater 

contamination) as the primary concerns in terms of this resource.

The threats associated with climate change are addressed in detail above. Invasive plants may impact 

spring, seep, and pond communities by competing with or replacing native species and altering 

ecosystem functions (e.g., water and nutrient cycling). Invasive species may use more water than 

native species and can cause changes in soil nutrients; for example, tamarisk and Russian olive also 

concentrate salt in their foliage and cause increases in soil salinity (Westbrooks 1998).

Several of the park’s seeps and springs are near hiking trails, which often provide a vector for the 

introduction and spread of invasive species (Lamm et al. 2014). The way in which visitors use the 

parks trail system also contributes to impacts to seeps and spring habitat in the park. The park does 

not limit foot travel to established trails. The major trail systems are located in the drainages at 

COLM, providing easy access to seep and spring sites (Hartwig, written communication, 18 

November 2015). Due to COLM’s high desert environment, water is an attraction for visitors. 

Visitors entering the larger spring pools can lead to the introduction of contaminants (sunscreen). The 

social trails also lead to trampling of vegetation and increased erosion, which can contribute to loss 

of habitat.

Adjacent development has the potential to threaten seep and spring water quality. Increased demands 

for groundwater by wells in the vicinity coupled with the potential for declining recharge due to 

climate change are two of the more significant threats to seeps and springs. Groundwater is a finite 

resource, and as these two factors deplete the available amounts of groundwater any contaminant 

levels can become more concentrated. In addition, much of the residential development bordering 

parks is considered low density, and wastewater is disposed through septic systems, which discharge 

directly into the ground nearby (Sharrow 2009). This septic discharge could potentially contaminate 

groundwater aquifers which supply park seeps and springs. A category of compounds called 
148

“emerging contaminants” (ECs) are of particular concern. These ECs can be natural or synthetic and 

are most often found in domestic and industrial wastewater (Sharrow 2009). These compounds 

include domestic pesticides, disinfectants, industrial solvents, surfactants, flame retardants, 

plasticizers, and pharmaceuticals (Zaugg et al. 2007, Sharrow 2009). A particular group of ECs 

called endocrine-disrupting chemicals (EDCs) can impact reproductive and development processes in 

fish and other wildlife species (EPA 1997) and are known to have such effects at very low 

concentrations (Kaiser 2000, Sharrow 2009).

Data Needs/Gaps

Limited information is available regarding the water quality and discharge for COLM’s seep, spring, 

and tinaja habitats. Additionally the potential for endemic plant and animal species is high but 

unconfirmed. Consistent monitoring, in both frequency and methodology, would allow for a more 

thorough assessment of these measures. While the locations of most of the park’s seeps and springs 

have been mapped, several potential sites in Lizard Canyon, Kodels Canyon, and tributaries of NTC 

have not been visited recently to confirm the existence of water sources (Lamm et al. 2014). A list of 

potential addition spring sites to be evaluated has been submitted to COLM resource staff (Lamm, 

written communication, 27 November 2015). The full extent of associated habitats at mapped sites 

also has not been measured. Regular monitoring of invasive plant species would be helpful in 

identifying any trends in or impacts of these species on the sensitive seep and spring sites. 

Monitoring of groundwater resources could also be useful in understanding the condition of the 

park’s seeps and springs, particularly how current climate conditions influence spring flows (Lamm 

et al. 2014) and how projected climate futures might influence groundwater resources.

Overall Condition

Vegetation Community Extent and Change over Time

The project team assigned this measure a Significance Level of 2. While the locations of many 

springs, seeps, and tinajas in COLM are known, the extent of the communities/habitats supported by 

these features is not known. Differences in seep and spring locations mapped by Von Loh et al. 

(2007) and Lamm et al. (2014) were noted, but these are likely due to differences in methodology 

(e.g., areas of focus) or project constraints (e.g., time, terrain) rather than any change in seep or 

spring locations between studies. Because the full extent of spring, seep, and tinaja habitats is not 

known, a Condition Level could not be assigned for this measure.

Vegetation Community Composition

The community composition measure was assigned a Significance Level of 3. Lamm et al. (2014) 

documented a total of 98 plant species at 34 park seeps and springs, 19 of which were non-native. On 

average, native plants made up 84% of the species per site (Lamm et al. 2014). Since species richness 

is relatively high and not dominated by non-native species, so at this time the measure is of low 

concern (Condition Level = 1). However the potential for greater invasion is present and conditions 

could rapidly change (worsen) due to factors such as climate change.
149

Trends in Invasive Infestation

This measure also received a Significance Level of 3. Lamm et al. (2014) found that non-native 

invasive plants did not dominate species richness or cover at their 34 inventory sites in COLM. 

Tamarisk, a state noxious weed, was found at four sites and its removal is recommended (Lamm et 

al. 2014). Park-wide current infestations of tamarix appear to be at control levels mainly due to the 

control efforts by volunteers and park staff (Perkins 2014). Cheatgrass was the most common 

invasive species, occurring at a majority of sites (25 of 34), but with potentially problematic cover 

levels at only four sites. Increasing visitation is likely to increase the spread of cheatgrass (Perkins 

2014). Russian olive infestations are also increasing (Perkins 2014). Over the last decade the park has 

focused control efforts on eradication of IEP’s. Future funding for these control measures is not 

available, so the potential for increased infestations is high (Hartwig, written communication 18 

November 2015). Therefore, this measure is assigned a Condition Level of 2, indicating moderate 

concern.

Water Quality

The water quality measure was also assigned a Significance Level of 3. Water quality data for 

COLM’s seeps and springs are limited, and it is unclear if methodologies (e.g., exact sampling 

locations and timing) were similar enough among studies to be comparable. However, available data 

and information suggest that water from COLM’s seeps and springs is of variable quality and has the 

potential to exhibit extreme conditions. Therefore, this measure is considered of moderate concern 

(Condition Level = 2).

Discharge

This measure was assigned a Significance Level of 3. Discharge from COLM’s seeps and springs has 

been measured or estimated several times since 2000 (Butler et al. 2003, Springer et al. 2006, Lamm 

et al. 2014). However, these data represent single points in time, and discharge has not been 

consistently measured at any sites in the park. Lamm et al. (2014) did note minimal or diminished 

flow from several Wingate sandstone springs, likely related to natural incision/erosion in the park’s 

canyons. Because of this concern, the discharge measure is assigned a Condition Level of 2.

Climate Change Vulnerability Assessment

Analysis of the seeps, springs, and tinaja habitats within COLM showed that they are highly 

vulnerable to the projected impacts of climate change, with an overall score of 24 (Table 40). While 

the certainty scores are in the “high” category with a value of 18, alternative scores were assigned to 

some of the variables as the degree of impact is difficult to assess due to the differences in the 

assessed species’ geographic ranges and overall adaptability.

To address some of the uncertainty in the potential impact of climate change on individual species 

within this assessment, alternative scores were identified for several variables in addition to the best 

estimate scores (Table 40). Alternative scores create a range of likely vulnerability for the plant 

community. The “location in the geographic range/distribution of the plant community” and the 

“vulnerability of ecologically influential species to climate change” variables were assigned 

alternative scores due to the wide ranging differences in the geographic extents of the four species 

used in the analysis and the potential for a worst-case scenario of the potential for loss of the species 
150

under projected future climate conditions. The “intrinsic adaptive capacity” and “potential for climate 

change to exacerbate impacts of non-climate stressors” were given the higher alternative scores due 

to the potential for total loss of these vegetation communities under projected climate change and 

increased water use scenarios. When factored in, the range of vulnerability scores for seep, spring, 

and tinaja habitats is 22 to 26, placing it potentially in the “critically vulnerable” category under a 

worst-case scenario. With the high certainty score, this suggests that, despite some uncertainty in the 

degree of impact to the selected species, the classification of seep, spring, and tinaja habitats as 

highly vulnerable is fairly robust. The scoring worksheet developed for the seep, spring, and tinaja 

habitats is included in Appendix H.

Table 40. Certainty, vulnerability, and alternative vulnerability scores for seep, spring, and tinaja plant 

community assessment variables.

Variable

Certainty 

Score1

Vulnerability 

Score2

Alternative 

Scores3

Location in geographical range/distribution of plant community 3 4 3

Sensitivity to extreme climatic events (e.g., drought, flash 

floods, windstorms)

3 4

Dependence on specific hydrologic conditions 3 4

Intrinsic adaptive capacity 3 4 5

Vulnerability of ecologically influential species to climate 

change

3 4 3

Potential for climate change to exacerbate impacts of nonclimate stressors3 4 5

Total 18 24 22-26

1For individual variables, certainty scores are 3 = high, 2 = moderate, and 1 = low

2The certainty ranges are 6-10 = low confidence,11-14 = moderate confidence,15-18 = high 

confidence

3The vulnerability ranges are 6-13= least vulnerable, 14-19 = moderately vulnerable, 20-25 = highly 

vulnerable, 26-30 = critically vulnerable

Weighted Condition Score

The Weighted Condition Score for this component is 0.58, indicating moderate concern. Because 

data are limited to single points in time for most measures, a trend could not be assigned.
151

Seeps and Springs and Tinaja Habitats

Measures Significance Level Condition Level WCS = 0.58

Community Extent and 

Change over Time 2 n/a

Community 

Composition 3 1

Trends in Invasive 

Infestation 3 2

Water Quality 3 2

Discharge 3 2

4.4.6 Sources of Expertise

Nicholas Fisichelli Ph.D., Ecologist NPS CCRP

Nancy Lamm, GeoCorps Guest Scientist in the Park

Marian Talbert, Research Statistician North Central Climate Science Center

Don Weeks, NPS WRD Climate Change Resource Planner NPS WRD

Rebecca Weissinger, Ecologist NPS Northern Colorado Plateau Network

4.4.7 Literature Cited

Bradley, B., M. Oppenheimer, and D. Wilcove. 2009. Climate change and plant invasions: 

Restoration opportunities ahead? Global Change Biology 15:1511-1521.

Bradley, B. and Wilcove, D. 2009. When invasive plants disappear: Transformative restoration 

possibilities in the Western United States resulting from climate change. Restoration Ecology 

17(5):715-721.

Butler, D., P. von Guerard, and K. Leib. 2003. Water quality inventory and monitoring, Colorado 

National Monument. U.S. Geological Survey, Water Resources Division, Grand Junction, 

Colorado.

ClimateWizard. 2014. Custom analysis: Change in AET/PET ratio by 2100. Downloadable dataset. 

http://climatewizardcustom.org/ (accessed 23 July 2014).
152

Decker, K. and R. Rondeau. 2014. San Juan /Tres Rios Climate Change Ecosystem Vulnerability 

Assessment. Colorado Natural Heritage Program. Colorado State University. Fort Collins, 

Colorado.

Dukes, J., and H. Mooney. 1999. Does global change increase the success of biological invaders? 

TREE 14(4):135-139.

Environmental Protection Agency (EPA). 1997. Special report on environmental endocrine 

disruption: An effects assessment and analysis. EPA/630/R-96/012. U.S. Environmental 

Protection Agency, Washington, D.C.

Environmental Protection Agency (EPA). 2009. National primary drinking water regulations. 

http://water.epa.gov/drink/contaminants/upload/mcl-2.pdf (accessed 13 August 2015).

Environmental Protection Agency (EPA). 2015. Water quality assessment report, Colorado, 

Colorado headwaters-plateau watershed. http://water.epa.gov/drink/contaminants/upload/mcl2.pdf (accessed 15 December 2015).

Evenden, A., M. Miller, M. Beer, E. Nance, S. Daw, A. Wright, M. Estenson, and L. Cudlip. 2002. 

Northern Colorado Plateau vital signs network and prototype cluster, plan for natural resources 

monitoring: Phase I report, October 1, 2002. National Park Service, Northern Colorado Plateau 

Network, Moab, Utah.

Kaiser, J. 2000. Endocrine disrupters: Panel cautiously confirms low-dose effects. Science

290(5492):695-697.

Lamm, N., S. Igo, and M. Davlantes, 2014. Report of the 2014 Geocorps springs and seeps 

assessment, Colorado National Monument, Colorado. National Park Service, Fruita, Colorado.

Martin, L. 2013. Groundwater resources tributary to Colorado National Monument. National Park 

Service, Water Resources Division, Fort Collins, Colorado.

Melillo, J. M., T. C. Richmond, and G. W. Yohe, eds. 2014. Climate change impacts in the United 

States: The third national climate assessment. U.S. Global Change Research Program, 

Washington, D.C.

National Park Service (NPS). 2015. Colorado National Monument natural features and 

ecosystems. http://www.nps.gov/colm/naturescience/naturalfeaturesandecosystems.htm

(accessed 13 January 2015).

O’Dell, T. E., S. L. Garman, A. Evenden, M. Beer, E. Nance, S. Daw, A. Wight, M. A. Powell, D. 

Perry, R. DenBleyker, and others. 2005. Appendix A. Biophysical setting and park descriptions 

in Northern Colorado Plateau Inventory and Monitoring Network: Vital signs monitoring plan. 

National Park Service, Moab, Utah.
153

Paschke, S., K. Leib, C. Williams, D. Brown, D. Dearstyne, M. Mast, J. Thomas, B. Osmundson, T. 

Schmidt, and J. Dupree. 2014. Science plan in support of the Selenium Management Program, 

Lower Gunnison River Basin, Colorado (Selenium Science Plan). U.S. Geological Survey, Grand 

Junction, Colorado.

Platenberg, R., and T. Graham. 2003. Northern Colorado Plateau Network herpetofauna inventory 

2002 annual report. USGS Canyonlands Field Station, Moab, Utah.

Richard, G. A. 2004. Flash flooding at the Colorado National Monument, 1921-2003. National Park 

Service, Fruita, Colorado.

Sharrow, D. 2009. Assessment of wastewater contamination in springs downgradient from 

proliferating septic systems. National Park Service, Northern Colorado Plateau Network, Moab, 

Utah.

Southern Colorado Plateau Network (SCPN). 2012. Monitoring spring ecosystems. National Park 

Service, Southern Colorado Plateau Network, Flagstaff, Arizona.

Springer, A., L. E. Stevens, and R. Harms. 2006. Inventory and classification of selected National 

Park Service springs on the Colorado Plateau. National Park Service, Northern Colorado Plateau 

Network, Moab, Utah.

Natural Resources Conservation Service (NRCS). 2015. The PLANTS database. U.S. Department of 

Agriculture, National Plant Data Team, Greensboro, North Carolina. http://plants.usda.gov

(accessed 2 October 2015). 

U.S. Geological Survey (USGS). 2010. Common water measurements: USGS water science for 

schools. U.S. Geological Survey. Information from “A Primer on Water Quality” by Swanson, H. 

A., and H. L. Baldwin, U.S. Geological Survey, 1965. 

http://ga.water.usgs.gov/edu/characteristics.html (accessed 1 March 2012).

Von Loh, J., K. Landgraf, A. Evenden, T. Owens, S. Blauer, and M. Reid. 2007. Vegetation 

classification and mapping project report, Colorado National Monument. Natural Resource 

Technical Report NPS/NCPN/NRTR—2007/061. National Park Service, Fort Collins, Colorado.

Westbrooks, R. G. 1998. Invasive plants: Changing the landscape of America. Federal Interagency 

Committee for the Management of Noxious and Exotic Weeds, Washington, D.C.

Zaugg, S. D., S. G. Smith, M. P. Schroeder, L. B. Barber, and M. R. Burkhardt. 2007. Methods of 

analysis by the U.S. Geological Survey National Water Quality Laboratory—Determination of 

wastewater compounds by polystyrene-divinylbenzene solid-phase extraction and capillarycolumn gas chromatography/mass spectrometry. Water-Resources Investigations Report 01-

4186. U.S. Geological Survey, Denver, Colorado.
154

4.5 Mixed Salt Desert Scrub/Semi-desert 

Grassland

4.5.1 Description

Mixed salt desert scrub and semi-desert 

grassland communities are two of the less 

common ecological systems found in COLM. 

Mixed salt desert scrub communities found in 

COLM include fourwing saltbush and fourwing 

saltbush –Mormon tea talus shrubland (Von 

Loh et al. 2007). Fourwing saltbush scrub is 

located on alluvial fans and on the toeslopes of 

ridges near COLM’s eastern border (Von Loh 

et al. 2007). Shadscale desert scrub 

communities are also found within the park 

(Table 41). Grasslands primarily occur in small patches on the eastern side of the park. The most 

common semi-desert grasslands in COLM are stands of cheatgrass and crested wheatgrass (Von Loh 

et al. 2007). These species were introduced to COLM as a result of livestock management practices 

near the park (Von Loh et al. 2007). Native grass species found in COLM’s semi-desert grasslands 

include Indian ricegrass, needle and thread, and James’ galleta (Von Loh et al. 2007). Western 

wheatgrass also occurs in some areas; although native to the western U.S., this species may have 

been introduced to COLM (Von Loh et al. 2007).

Table 41. Vegetation alliances found within the mixed salt desert scrub and semi-desert grassland plant 

associations of COLM (Von Loh et al. 2007).

Plant Association Vegetation Alliance

Inter-Mountain Basins Mixed Salt Desert Scrub Fourwing saltbush shrubland 

Fourwing Saltbush - Mormon tea talus shrubland 

Shadscale/James’ galleta shrubland 

Shadscale - black greasewood shrubland

Inter-Mountain Basins Semi-Desert Grassland Crested wheatgrass semi-natural herbaceous alliance 

Indian ricegrass - cheatgrass semi-natural herbaceous 

vegetation

Cheatgrass semi-natural herbaceous vegetation

Needle and thread Great Basin herbaceous vegetation)

Plains pricklypear/James’ galleta shrubland 

Western wheatgrass herbaceous vegetation

James’ galleta herbaceous vegetation

A wide variety of wildlife can be seen within these habitats. Rodents and small mammals found 

within these communities include: rabbits, mice, bats, chipmunks, gophers, shrews, weasels, and 

skunks (Hanophy and Teitelbaum 2003, DW 2016). These habitats also provide cover, foraging and 

Photo 8. Fourwing saltbush (NPS Photo).
155

nesting habitat for a wide variety of birds (Hanophy and Teitelbaum 2003, DW 2016). Hawks, 

golden eagles, owls and other raptors utilize these habitats for foraging (Hanophy and Teitelbaum 

2003, DW 2016). Other predators found within these habitats include coyotes, foxes, and badgers 

(Taxidea taxus) (DW 2016). Mule deer also can be found foraging within these habitats (Hanophy

and Teitelbaum 2003).

4.5.2 Measures

 Community extent and change over time

 Community composition

 Trends in invasive infestation

 Soil stability

 Percent cover biological soil crusts

 Percent bare ground

4.5.3 Reference Conditions/Values

The ideal reference condition for the mixed salt desert scrub and semi-desert grassland areas of 

COLM is the condition of these communities prior to regional settlement. Unfortunately, little 

information is available from this time, making reference conditions difficult to determine. For this 

assessment, conditions will be assessed based on best professional judgment given the available data. 

The information presented here may be used as baselines for future assessments.

4.5.4 Data and Methods

A comprehensive list of plant species within COLM was compiled by Hogan et al. (2009). This 

effort included a review of existing literature and a reexamination of specimens from the COLM 

herbarium. This project also conducted field surveys to confirm unverified species as well as to 

document previously unlisted species (Hogan et al. 2009). The products from this project included an 

annotated checklist with additional information about the flora found within COLM. Although 

Hogan et al. (2009) identified species that occurred within some of the major plant communities of 

COLM, species that occurred within mixed salt desert scrub or semi-desert grasslands were not 

highlighted. 

A vegetation classification system and map were generated for COLM and surrounding areas by Von 

Loh et al. (2007). The results show the spatial distribution of dominant cover types present within 

and around the park during the early 2000s. Surrounding areas were included to support management 

of the urban-wildland interface and coordinated management on adjacent public lands (Von Loh et 

al. 2007). The report also includes descriptions of the vegetation associations identified during the 

project. 

The NCPN funded the first park-wide invasive plant inventory and mapping project in 2003 (Dewey 

and Anderson 2005). Later, Perkins (2010, 2012, 2014) conducted IEP monitoring in COLM during 

the 2009, 2011, and 2013 field seasons as part of an ongoing NCPN monitoring program. The 

methodologies for field work and data analysis were similar for all three of these more recent field 
156

seasons, with surveys conducted between late June and August each year. For the purpose of this 

assessment of condition, Perkins (2014) will be the primary source since it includes data from the 

previous reports. The field work for these monitoring efforts included transect and quadrat sampling 

with an emphasis on roads, trails, and waterways (Perkins 2010, 2012, 2014). A list of IEP priority 

species was developed for COLM prior to monitoring, and was based on previously detected species 

and literature reviews (Perkins 2010, 2012, 2014). Monitoring was conducted on foot and IEPs were 

detected visually. For each monitoring route, transect and quadrat, each IEP detected was recorded 

by species, infestation size class, and canopy cover class (Perkins 2010, 2012, 2014).

4.5.5 Current Condition and Trend

Community Extent and Change Over Time

Von Loh et al. (2007) represent the most recent estimate of vegetation community extent in the park. 

Unfortunately, several of the mixed salt desert scrub and semi-desert vegetation classes occurred 

only in patches below the project’s MMU size of 0.5 ha (1.2 ac). As a result, the extent of the 

following vegetation classes cannot be calculated: shadscale/James’ galleta shrubland, Indian 

ricegrass - cheatgrass semi-natural herbaceous vegetation, needle and thread Great Basin herbaceous 

vegetation, plains prickly-pear/James’ galleta shrubland, western wheatgrass herbaceous vegetation, 

and James’ galleta herbaceous vegetation. Von Loh et al. (2007) did note that western wheatgrass 

herbaceous vegetation and needle and thread Great Basin herbaceous vegetation were both rare, each 

observed at only two locations in the park. 

The three mixed salt desert scrub vegetation classes that were mapped covered a total of 60.9 ha 

(150.5 ac) or 0.3% of COLM’s total area (Table 42) (Von Loh et al. 2007). Just over half of this area 

consisted of shadscale – black greasewood shrubland (Figure 35). The two mapped semi-desert 

grassland communities totaled just 16.6 ha (41.0 ac), or only 0.1% of the park, with the cheatgrass 

vegetation class covering nearly four times as much area as the crested wheatgrass class (Von Loh et 

al. 2007(Table 42)). However, it is worth noting that both of these grassland types are dominated by 

non-native species.

Table 42. Areal extent of mixed salt desert scrub and semi-desert grassland vegetation associations 

found in COLM (Von Loh et al. 2007).

Plant Association Vegetation Alliance

Area in 

ha (ac)

Percent 

of Park

Mixed salt desert scrub Fourwing saltbush shrubland 15.3 (37.8) <0.1%

Fourwing Saltbush - Mormon tea talus shrubland 14.4 (35.6) <0.1%

Shadscale - black greasewood shrubland 31.2 (77.1) 0.2%

Total 60.9 (150.5) 0.3%

Semi-desert grasslands Crested wheatgrass semi-natural herbaceous 

alliance 

3.5 (8.6) <0.1%

Cheatgrass semi-natural herbaceous vegetation 13.1 (32.4) <0.1%

Total 16.6 (41.0) 0.1%
157

Figure 35. Mixed salt desert scrub and semi-desert grassland locations within COLM (Von Loh et al. 

2007).

Community Composition

Four different types of mixed salt desert scrub and seven types of semi-desert grassland were 

identified within COLM by Von Loh et al. (2007) (Table 41). Community composition information 

was provided by Von Loh et al. (2007) for all but the crested wheatgrass semi-natural herbaceous 

alliance, as sampling of this community was limited.
158

Fourwing saltbush shrubland communities are characterized by fourwing saltbush, with canopy 

coverage from 8-12% (Von Loh et al. 2007). Other shrubs and succulents include Wyoming big 

sagebrush, Mormon tea, brittle pricklypear, berry pricklypear, and plains pricklypear (Von Loh et al. 

2007). The herbaceous layer in this community includes the graminoids Indian ricegrass, crested 

wheatgrass, cheatgrass, six weeks fescue, needle and thread, James’ galleta, and sand dropseed and 

the forbs smallflowered milkvetch, western tansymustard, sleepy catchfly, tumble mustard, and 

scarlet globemallow (Von Loh et al. 2007). The most abundant species within this community by 

stratum are listed in Table 43.

Table 43. Dominant plant species (by strata) within the fourwing saltbush shrublands of COLM (Von Loh 

et al. 2007). 

Fourwing saltbush shrublands

Scientific Name Common Name Strata

Artemisia tridentata spp. wyomingensis Wyoming big sagebrush Short shrub/sapling

Atriplex canescens fourwing saltbush Short shrub/sapling

Opuntia phaeacantha berry pricklypear Short shrub/sapling

Opuntia polyacantha plains pricklypear Short shrub/sapling

Astragalus nuttallianus smallflowered milkvetch Herb

Descurainia pinnata ssp. halictorum western tansymustard Herb

Erodium cicutarium* stork’s bill Herb

Hesperostipa comata needle and thread Herb

Hilaria jamesii James’ galleta Herb

Sporobolus cryptandrus sand dropseed Herb

*Indicates a non-native species.

Fourwing saltbush - Mormon tea talus shrubland communities are characterized by fourwing saltbush 

and Mormon tea (Von Loh et al. 2007). Other shrubs and succulents include Bigelow’s sagebrush, 

claretcup, Torrey’s Mormon tea, broom snakeweed, winterfat, grizzlybear pricklypear (Opuntia 

polyacantha var. erinacea), berry pricklypear, and skunkbush sumac. Utah juniper provides sparse 

canopy cover, usually less than 5% (Von Loh et al. 2007). The herbaceous layer in this community 

includes the graminoids Indian ricegrass, purple three-awn, cheatgrass, needle and thread, and James’ 

galleta and the forbs western tansymustard, milkvetch (Astragalus spp.), fleabane, stork’s bill, desert 

trumpet (Eriogonum inflatum), prairie pepperwort, mountain pepperweed, scarlet globemallow, and 

long-beak fiddle-mustard (Von Loh et al. 2007). The most abundant species within this community 

by stratum are listed in Table 44.

The rare shadscale – black greasewood shrubland communities are characterized by black 

greasewood and shadscale (Von Loh et al. 2007). Other shrubs and succulents include claretcup, 

grizzlybear pricklypear, plains pricklypear, and broom seepweed (Suaeda calceoliformis) (Von Loh 

et al. 2007). The herbaceous layer in this community is sparse and includes the graminoids 

cheatgrass, six weeks fescue, James’ galleta, and sand dropseed and the forbs smallflowered 
159

milkvetch and western tansymustard (Von Loh et al. 2007). Table 45 lists the most abundant species 

within this community.

Table 44. Dominant plant species (by strata) within the fourwing saltbush - Mormon tea talus shrublands

of COLM (Von Loh et al. 2007).

Fourwing saltbush – Mormon tea talus shrublands

Scientific Name Common Name Strata

Juniperus osteosperma Utah juniper Tree canopy

Atriplex canescens fourwing saltbush Short shrub/sapling

Ephedra torreyana Torrey's Mormon tea Short shrub/sapling

Ephedra viridis Mormon tea Short shrub/sapling

Table 45. Dominant plant species (by strata) within the shadscale - black greasewood shrublands of 

COLM (Von Loh et al. 2007). 

Shadscale - black greasewood shrublands

Scientific Name Common Name Strata

Atriplex confertifolia shadscale Short shrub/sapling

Sarcobatus vermiculatus black greasewood Short shrub/sapling

Opuntia polyacantha plains pricklypear Short shrub/sapling

Bromus tectorum* cheatgrass Herb

Hilaria jamesii James’ galleta Herb

*Indicates a non-native species.

Shadscale/James’ galetta shrubland is common within COLM, and consists of an open canopy of 

shadscale with a sparse herbaceous layer of James’ galetta (Von Loh et al. 2007). Trees such as Utah 

juniper and singleleaf ash are present but are rare (Von Loh et al. 2007). Additional shrub species 

present include Wyoming big sagebrush, Mormon tea, Torrey’s Mormon tea, winterfat, black 

greasewood, bud sagebrush (Picrothamnus desertorum), yellow rabbitbrush, slender wild buckwheat 

(Eriogonum microthecum var. laxiflorum), broom snakeweed, broom seepweed, and spineless 

horsebrush (Tetradymia canescens) (Von Loh et al. 2007). Other shrubs and succulents found within 

this community are similar to those found in the previously described, with the addition of Whipple’s 

fishhook cactus (Sclerocactus whipplei) and Harriman's yucca (Von Loh et al. 2007). The herbaceous 

layer is also similar to previous communities, but also includes muttongrass, Sandberg’s bluegrass, 

Gunnison’s mariposa, yellow-eye crypantha (Cryptantha flavoculata), longleaf wild buckwheat

(Eriogonum lonchophyllum), western stickseed (Lappula occidentalis var. occidentalis), pale evening 

primrose, woolly plantain, oblongleaf basindaisy (Platyschkuhria integrifolia), large-flowered 

breadroot (Pediomelum megalanthum), and western groundsel (Von Loh et al. 2007). The most 

abundant species by stratum within this community are listed in Table 46.
160

Table 46. Dominant plant species (by strata) within the shadscale/James’ galetta shrublands of COLM 

(Von Loh et al. 2007).

Shadscale/James’ galetta shrubland

Scientific Name Common Name Strata

Atriplex confertifolia shadscale Short shrub/sapling

Opuntia polyacantha plains pricklypear Short shrub/sapling

Astragalus nuttallianus smallflowered milkvetch Herb

Bromus tectorum* cheatgrass Herb

Descurainia pinnata ssp. halictorum western tansymustard Herb

Erodium cicutarium* stork’s bill Herb

Hilaria jamesii James’ galleta Herb

Lappula occidentalis var. occidentalis western stickseed Herb

Picrothamnus desertorum bud sagebrush Herb

Sporobolus cryptandrus sand dropseed Herb

*Indicates a non-native species.

Although panhandle pricklypear/James’ galleta shrubland has “shrubland” in its name, Von Loh et al. 

(2007) classified it as a semi-desert grassland community. It is a low succulent community where 

plains pricklypear became common due to historical grazing (Von Loh et al. 2007). Utah juniper 

occurs rarely, along with Wyoming big sagebrush, fourwing saltbush, yellow rabbitbrush, Mormon 

tea, shadscale, slender wild buckwheat, winterfat, spiny hopsage, black greasewood, broom 

snakeweed, and berry pricklypear (Von Loh et al. 2007). Common herbaceous layer species include 

Indian ricegrass, cheatgrass, six weeks fescue, needle and thread, sand dropseed, smallflowered 

milkvetch, western stickseed, prairie pepperwort, scarlet globemallow, and long-beak fiddle-mustard

(Von Loh et al. 2007). Table 47 lists the most abundant species by stratum within this community.

Table 47. Dominant plant species (by strata) within the plains prickly pear/James’ galetta shrublands of 

COLM (Von Loh et al. 2007).

Plains pricklypear/James’ galetta shrubland

Scientific Name Common Name Strata

Artemisia tridentata ssp. wyomingensis Wyoming big sagebrush Short shrub/sapling

Atriplex canescens fourwing saltbush Short shrub/sapling

Atriplex confertifolia shadscale Short shrub/sapling

Ephedra viridis Mormon tea Short shrub/sapling

Opuntia polyacantha plains pricklypear Short shrub/sapling

Astragalus nuttallianus smallflowered milkvetch Herb

Bromus tectorum* cheatgrass Herb

Gutierrezia sarothrae broom snakeweed Herb

Hilaria jamesii James’ galleta Herb

Vulpia octoflora six weeks fescue Herb

*Indicates a non-native species.
161

Cheatgrass semi-natural herbaceous vegetation is characterized by cheatgrass, which accounted for 

up to 55% of vegetative cover in this community (Von Loh et al. 2007). Other graminoids present 

include Indian ricegrass, crested wheatgrass, purple three-awn, smooth brome (Bromus inermis), 

desert saltgrass, squirreltail, smooth horsetail, western wheatgrass, sand dropseed, and the nonnatives Kentucky bluegrass (Poa pratensis) and wheat (Triticum aestivum) (Von Loh et al. 2007). 

Forbs and shrubs are also sparse and include both native and non-native species (Von Loh et al. 

2007). Additional non-native species found in this community include tumble mustard, sagebrush 

buttercup, yellow salsify (Tragopogon dubius), little-pod false flax (Camelina microcarpa), Russian 

thistle (Salsola kali), and tamarisk (Von Loh et al. 2007). The most abundant species within this 

community by stratum can be found in (Table 48).

Table 48. Dominant plant species (by strata) within the cheatgrass semi-natural herbaceous vegetation 

community of COLM (Von Loh et al. 2007). 

Cheatgrass semi-natural herbaceous vegetation

Scientific Name Common Name Strata

Artemisia tridentata ssp. wyomingensis Wyoming big sagebrush Short shrub/sapling

Ericameria nauseosa rubber rabbitbrush Short shrub/sapling

Sarcobatus vermiculatus black greasewood Short shrub/sapling

Aristida purpurea purple three-awn Herb

Bromus tectorum* cheatgrass Herb

Descurainia pinnata ssp. halictorum western tansymustard Herb

Erodium cicutarium* stork’s bill* Herb

Hesperostipa comata needle and thread Herb

Hilaria jamesii James’ galleta Herb

Krascheninnikovia lanata winterfat Herb

Poa secunda Sandberg's bluegrass Herb

Salsola kali* Russian thistle Herb

Sisymbrium altissimum* tumble mustard Herb

Sphaeralcea coccinea ssp. coccinea scarlet globemallow Herb

*Indicates a non-native species.

Western wheatgrass herbaceous vegetation occurs in moderately vegetated patches (28-36% cover) 

(Von Loh et al. 2007). In addition to western wheatgrass, the non-native graminoids crested 

wheatgrass, cheatgrass, field brome (Bromus arvensis), and Kentucky bluegrass were also present 

(Von Loh et al. 2007). The shrubs rubber rabbitbrush and basin big sagebrush are present but 

uncommon, as are weedy, native forbs such as povertyweed (Iva axillaris), goldenrod (Solidago 

spp.), and the non-native yellow salsify (Von Loh et al. 2007). The most abundant species by stratum 

within this community are shown in Table 49.

The rare needle and thread Great Basin herbaceous vegetation community is characterized by 

sparsely vegetated grasslands (Von Loh et al. 2007). These grasslands are dominated by needle and 

thread and James’ galetta, with some Indian ricegrass, cheatgrass, muttongrass, and six weeks fescue 
162

(Von Loh et al. 2007). Forbs are uncommon but include smallflowered milkvetch, western 

tansymustard, fleabane, long-beak fiddle-mustard, and gilia (Gilia spp.) when present (Von Loh et al. 

2007). Shrubs are also sparse but diverse (Von Loh et al. 2007). Table 50 lists the most abundant 

species by stratum within this community.

Table 49. Dominant plant species (by strata) within the western wheatgrass herbaceous vegetation 

community of COLM (Von Loh et al. 2007).

Western wheatgrass herbaceous vegetation

Scientific Name Common Name Strata

Agropyron cristatum* crested wheatgrass Herb

Bromus tectorum* cheatgrass Herb

Pascopyrum smithii western wheatgrass Herb

Poa pratensis* Kentucky bluegrass Herb

*Indicates a non-native species.

Table 50. Dominant plant species (by strata) within the needle and thread Great Basin herbaceous 

vegetation community of COLM (Von Loh et al. 2007).

Needle and thread Great Basin herbaceous vegetation

Scientific Name Common Name Strata

Chrysothamnus viscidiflorus yellow rabbitbrush Short shrub/sapling

Gutierrezia sarothrae broom snakeweed Short shrub/sapling

Opuntia polyacantha plains pricklypear Short shrub/sapling

Achnatherum hymenoides Indian ricegrass Herb

Astragalus nuttallianus smallflowered milkvetch Herb

Hesperostipa comata needle and thread Herb

Hilaria jamesii James’ galleta Herb

James’ galleta herbaceous vegetation is dominated by James’ galetta; other grasses such as Indian 

ricegrass, cheatgrass, needle and thread, purple three-awn, muttongrass, and sand dropseed are also 

present (Von Loh et al. 2007). Trees such as Utah juniper and pinyon pine trees are found within this 

community, but are rare occurrences (Von Loh et al. 2007). Forbs are diverse with a composition 

similar to the shadscale/James’ galetta shrubland community, with the addition of Fendler’s 

sandwort, pallid milkweed (Asclepias cryptoceras), ridge-seeded spurge (Euphorbia glyptosperma), 

red dome blanketflower (Gaillardia pinnatifida), canaigre dock (Rumex hymenosepalus), and prickly 

phlox (Von Loh et al. 2007). The most abundant species by stratum are found in Table 51.

Indian ricegrass-cheatgrass herbaceous vegetation communities are sparsely vegetated and dominated 

by either Indian ricegrass or cheatgrass (Von Loh et al. 2007). Species diversity is high for the 

community as a whole but is typically low within individual patches (Von Loh et al. 2007). 

Additional grasses include purple three-awn, squirreltail, saline wildrye, six weeks fescue, needle and 

thread, James’ galleta, and muttongrass (Von Loh et al. 2007). Utah juniper and pinyon pine occur at 
163

some sites, and short shrubs are common (Von Loh et al. 2007). Table 52 lists the most abundant 

species by stratum within this community.

Table 51. Dominant plant species (by strata) within the James’ galleta herbaceous vegetation community

of COLM (Von Loh et al. 2007).

James’ galleta herbaceous vegetation

Scientific Name Common Name Strata

Juniperus osteosperma Utah juniper Tree canopy

Pinus edulis two-needle pinyon pine Tree canopy

Opuntia polyacantha plains pricklypear Shrub

Opuntia polyacantha var. erinacea grizzlybear pricklypear Shrub

Aristida purpurea purple three-awn Herb

Astragalus nuttallianus smallflowered milkvetch Herb

Atriplex confertifolia shadscale Herb

Bromus tectorum* cheatgrass Herb

Erodium cicutarium* stork’s bill* Herb

Hesperostipa comata needle and thread Herb

Hilaria jamesii James’ galleta Herb

Lappula occidentalis var. occidentalis western stickseed Herb

Sphaeralcea coccinea ssp. coccinea scarlet globemallow Herb

*Indicates a non-native species.

Table 52. Dominant plant species (by strata) within the Indian ricegrass-cheatgrass herbaceous 

vegetation community of COLM (Von Loh et al. 2007).

Indian ricegrass-cheatgrass herbaceous vegetation

Scientific Name Common Name Strata

Juniperus osteosperma Utah juniper Tree canopy

Pinus edulis two-needle pinyon pine Tree canopy

Artemisia tridentata ssp. wyomingensis Wyoming big sagebrush Short shrub

Ericameria nauseosa rubber rabbitbrush Short shrub

Gutierrezia sarothrae broom snakeweed Dwarf shrub

Opuntia polyacantha var. erinacea grizzlybear pricklypear Dwarf shrub

Achnatherum hymenoides Indian ricegrass Herb

Agropyron cristatum* crested wheatgrass Herb

Bromus tectorum* cheatgrass Herb

Elymus elymoides squirreltail Herb

Grindelia squarrosa curlycup gumweed Herb

Hesperostipa comata needle and thread Herb

Heterotheca villosa hairy false goldenaster Herb

Lepidium montanum mountain pepperweed Herb

Leymus salinus saline wildrye Herb

*Indicates a non-native species.
164

Trends in Invasive Infestation

COLM is part of a long-term monitoring program for IEPs developed by the NCPN which focuses on 

early detection (Perkins 2014). The first survey of IEPs in the park was conducted in 2003 by Dewey 

and Anderson (2005). The latest monitoring was conducted during the 2013 field season (Perkins 

2014) and will be used to assess this measure, since it includes the previously collected data on IEP 

infestations in COLM. A full discussion of IEPs park-wide, including a discussion of trends can be 

found in Chapter 2.2.2. The mixed salt desert scrub and semi-desert grasslands are along the urbaninterface, which is considered an area at high risk of invasive plant infestations.

Trends in invasive plants have not been assessed specifically by vegetation association at COLM. To 

identify invasive species infestations associated with mixed salt desert scrub and semi-desert 

grasslands, spatial queries were performed using the data from the 2013 IEP survey and the mixed 

salt desert scrub and semi-desert grasslands mapped by Von Loh et al. (2007). The spatial queries 

selected IEP points that were either within a mapped location of mixed salt desert scrub and semidesert grasslands or within 100 m (328 ft) of one of these communities.

During the latest field season (2013), Perkins (2014) detected a total of 462 IEP infestation points 

within COLM. Spatial queries conducted using the 2013 data identified nine (2%) IEP occurrences

were associated with the mixed salt desert scrub and semi-desert grasslands (Figure 36). Cheatgrass 

(7) and puncture vine (2) (Tribulus terrestris) were the only two IEP species detected within the 

mixed salt desert scrub and semi-desert grasslands. All nine of these infestations were located within 

the mapped vegetation boundaries. Puncture vine is considered a priority IEP species in the park 

(Perkins 2014). Differences in the number of infestations and species detected between 2003 (Dewey 

and Anderson 2005) and 2013 (Perkins 2014) is due to differences in methodology and areas 

monitored rather than actual change over time. 
165

Figure 36. IEP observations within mapped mixed salt desert scrub and semi-desert grassland 

vegetation communities from 2003 and 2013 field seasons.

Soil Stability

As discussed in previous chapters, soil stability depends on a number of factors, including slope, soil 

composition, and the presence of BSC or other ground cover (NRCS 1996, Belnap et al. 2008, 

Witwicki et al. 2013). The presence of BSC and other cover within COLM’s mixed salt desert scrub 
166

and semi-desert grasslands will be addressed in the following two sections. Specific data on soil 

stability within COLM’s vegetation communities are not available at this time.

Percent Cover Biological Soil Crusts

BSC are a very important part of desert and semi-desert ecosystems, as they influence local 

hydrology and soil stability, fertility, and biodiversity (Belnap et al. 2008). The organisms within 

BSC aggregate soil particles, making the soil stronger and less likely to erode from wind or water. 

These crusts also aid in retention of mineral nutrients, organic matter, and seeds (Miller 2005). BSC 

within COLM are most common on sites that are protected from disturbance and are re-developing in 

areas that were once grazed or otherwise disturbed (Von Loh et al. 2007). Some of the park’s canyon 

areas were particularly impacted by a herd of bison that grazed there from the 1940s until the 1980s 

(KellerLynn 2006). Although Von Loh et al. (2007) noted that BSC were present in the Indian 

ricegrass - cheatgrass semi-natural herbaceous vegetation community, specifics on the percent cover 

of BSCs in COLM vegetation communities was not provided.

Percent Bare Ground

Percent bare ground impacts soil stability, as vegetation helps prevent wind and water erosion 

(Kachergis et al. 2011, Witwicki et al. 2013). Sufficient data could not be found to assess the 

condition of percent of bare ground within COLM’s mixed salt desert scrub and semi-desert 

grassland communities. Von Loh et al. (2007) describes these communities as sparsely to moderately 

vegetated, so it is highly likely that bare ground is present and may be prevalent in some areas.

Threats and Stressor Factors

Threats to COLM’s mixed salt desert scrub and semi-desert grassland areas identified by natural 

resource staff include IEPs, unnatural fire regimes, drought, and regional climate variation. 

Cheatgrass and crested wheatgrass are two exotic plants known to occur within COLM’s semi-desert 

grasslands (Von Loh et al. 2007). Cheatgrass was first documented in COLM in 1948 and crested 

wheatgrass in 1962 (Hogan et al. 2009). Cheatgrass, which is currently on the Colorado state noxious 

weed list (Hogan et al. 2009), is notable in formerly burned areas of COLM (Von Loh et al. 2007). 

Both naturally occurring and prescribed fires can alter vegetation composition and structure by 

damaging or eliminating fire-intolerant plant species (Miller 2005). Historically, low intensity fires 

may have played a role in preventing woody vegetation from invading some semi-desert grassland 

communities (Miller 2005). When fire is excluded for long periods of time, fuels accumulate in 

grassland and scrub communities; when fires do occur, they are usually more damaging and of a 

higher intensity than those from a more natural fire regime (O’Dell et al. 2005). The loss of 

vegetative cover, as a result of intense fires, can increase soil erosion in these communities (Miller 

2005). The invasion of some exotic plants, particularly cheatgrass, has contributed to an unnatural 

buildup of fuels in arid plant communities (Brooks et al. 2004). This fuel may increase fire frequency 

and extent in some areas to a point where native species have difficulty recovering (Brooks et al. 

2004). In certain plant communities, such as desert scrub and semi-desert grasslands, prescribed fire 

may actually contribute to the dominance of exotic annual grasses (Miller 2005). The park’s 

proximity to an urban area may increase the risk of human-caused fires, which could spread into the 

park (Hartwig, written communication, 20 September 2015).
167

Visitor impacts within the park’s mixed salt desert scrub/semi-desert grassland habitats include 

damage to BSC present within these environments. Hikers, particularly those using unauthorized 

“social” trails, cause damage to these fragile habitats and continued disturbance does not allow for 

the time needed for BSCs to regenerate. This can lead to invasive species encroaching and potentially 

replacing BSC habitats.

Drought can cause widespread mortality in the vegetation at COLM. It can also lower a plants

resistance/resilience to other stressors, such as fire and insect outbreaks (Miller 2005). At the 

opposite extreme, heavy precipitation and flooding can also impact vegetation community structure

and function (Miller 2005). In western Colorado, global climate change is expected to cause an 

increase in temperature with longer and hotter summer heat waves, an increased potential for drought 

and wildfires, and an increase in heavy precipitation events (Lamm et al. 2014, Melillo et al. 2014). 

All of these changes could impact the park’s desert scrub and semi-desert grassland communities.

Data Needs/Gaps

Though there are data available regarding community extent and community composition, 

insufficient data exist within COLM for the analysis of the percent cover of BSC, percent bare 

ground, or soil stability measures. Witwicki et al. (2013) briefly touches on these topics but only 

discusses a monitoring protocol, no actual data are presented. Although data are available for IEP

infestations in the park as a whole, it is unclear how these species are impacting specific native plant 

communities (Perkins 2012). Research on the impacts from the proliferation of social trails within the 

park is also recommended.

Currently a guaranteed funding source for the invasive species removal/control has not been 

identified. Failure to secure funding for this management action will result in the loss of the gains 

that have been made in eradicating IEPs within the park. Additionally, another programmatic need 

for COLM is a trail management plan. Currently, visitors face no restrictions in their access to any 

areas within the park.

Overall Condition

Community Extent and Change over Time

This measure was assigned a Significance Level of 3. The presence of mixed salt desert scrub and 

semi-desert grasslands including cheatgrass and crested wheatgrass has been noted by various 

researchers (Von Loh 2007) (Perkins 2012). However, not enough data are available to confidently 

assess any change in community extent over time. Therefore, the Condition Level was not assigned to 

this measure.

Community Composition

A Significance Level of 3 was assigned to the community composition measure. Von Loh et al. 

(2007) reports that many of COLM’s mixed salt desert scrub and semi-desert grassland communities 

show high plant species diversity. However, many of the most dominant plant species are nonnatives (e.g., cheatgrass, crested wheatgrass, stork’s bill). As a result, the Condition Level assigned to 

this measure is 2, indicating moderate concern.
168

Trends in Invasive Infestation

This measure was assigned a Significance Level of 3. The number of IEPs documented in or near 

mixed salt desert scrub or semi-desert grasslands is relatively low. However, the invasive species 

cheatgrass and crested wheatgrass are known to dominate two of COLM’s semi-desert grassland 

types and cheatgrass is present in many other grasslands and desert scrub communities (Von Loh et 

al. 2007). Over the last decade the park has focused control efforts on eradication of IEP’s. Future 

funding for these control measures is not available, so the potential for increased infestations is high 

(Hartwig, written communication 18 November 2015).While it is unclear from this recent monitoring 

if or how invasive infestations are impacting mixed salt desert scrub or semi-desert grassland areas, 

these species are still a cause for moderate concern (Condition Level = 2).

Soil Stability

The soil stability measure was assigned a Significance Level of 2. Data on soil stability within COLM 

do not exist. Because there are no available data, a Condition Level could not be assigned.

Percent Cover Biological Soil Crusts

The percent cover BSC measure was assigned a Significance Level of 3. Data on the percent cover of 

BSCs are not currently available. Due to the lack of data related to this measure, a Condition Level

was not assigned.

Percent Bare Ground

A Significance Level of 3 was assigned to this measure. No data are available on percent bare ground 

within COLM. Due to the lack of data, a Condition Level could not be assigned.

Weighted Condition Score

A Weighted Condition Score was not calculated for this component because Condition Levels could 

not be assigned to greater than 50% of the measures due to lack of available data. Until more data 

become available for the other measures, the condition of mixed salt desert scrub/semi-desert 

grassland areas in COLM will be unknown.
169

Mixed Salt Desert Scrub/Semi-Desert Grassland

Measures Significance Level Condition Level WCS = N/A

Community Extent and 

Change over Time 3 n/a

Community 

Composition 3 2

Trends in Invasive 

Infestation 3 2

Soil Stability 2 n/a

Percent Cover 

Biological Soil Crusts 3 n/a

Percent Bare Ground 3 n/a

4.5.6 Sources of Expertise

Dusty Perkins, Program Manager, Northern Colorado Plateau Network

4.5.7 Literature Cited

Belnap, J., S. L. Phillips, D. L. Witwicki, and M. E. Miller. 2008. Visually assessing the level of 

development and soil surface stability of cyanobacterially dominated biological soil crusts. 

Journal of Arid Environments 72:1257-1264.

Brooks, M. L., C. M. D’Antonio, D. M. Richardson, J. B. Grace, J. E. Keeley, J. M. DiTomaso, R. J. 

Hobbs, M. Pellant, and D. Pyke. 2004. Effects of invasive alien plants on fire regimes. 

Bioscience 54(7):677-688.

Defenders of Wildlife (DW). 2016. Grasslands – Temperate grasslands fact sheet. 

http://www.defenders.org/grasslands/temperate-grasslands. (accessed 9 February 2016).

Dewey, S. and K. Anderson. 2005. An inventory of invasive nonnative plants in Colorado National 

Monument (2003). Weed Science Research Project Report No. SD0516A. Utah State University, 

Logan, Utah.

Hanophy, W., and H. Teitelbaum. 2003. Wild Colorado: Crossroads of biodiversity. Colorado 

Division of Wildlife, Education Section, Denver, Colorado.

Hogan, T., N. Lederer, and W. Fertig. 2009. Annotated checklist of vascular flora: Colorado National 

Monument. Natural Resource Technical Report NPS/NCPN/NRTR—2009/231. National Park 

Service, Fort Collins, Colorado.
170

Kachergis, E., M. E. Rocca, and M. E. Fernandez-Gimenez. 2011. Indicators of ecosystem function 

identify alternate states in the sagebrush steppe. Ecological Applications 21(7):2781-2792.

KellerLynn, K. 2006. Colorado National Monument geologic resource evaluation report. Natural 

Resource Report NPS/NRPC/GRD/NRR—2006/007. National Park Service, Denver, Colorado. 

Lamm, N., S. Igo, and M. Davlantes, 2014. Report of the 2014 Geocorps springs and seeps 

assessment, Colorado National Monument, Colorado. National Park Service, Fruita, Colorado.

Melillo, J. M., T. C. Richmond, and G. W. Yohe, eds. 2014. Climate change impacts in the United 

States: The third national climate assessment. U.S. Global Change Research Program, 

Washington, D.C. 

Miller, M. E. 2005. The structure and functioning of dryland ecosystems—Conceptual models to 

inform long-term ecological monitoring. Scientific Investigations Report 2005-5197. U.S. 

Geological Survey, Reston, Virginia.

Natural Resources Conservation Service (NRCS). 1996. Soil quality indicators: Aggregate stability. 

http://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/nrcs142p2_052820.pdf (accessed 25 

February 2015).

O’Dell, T. E., S. L. Garman, A. Evenden, M. Beer, E. Nance, S. Daw, A. Wight, M. A. Powell, D. 

Perry, R. DenBleyker, and others. 2005. Northern Colorado Plateau Inventory and Monitoring 

Network: Vital signs monitoring plan. National Park Service, Moab, Utah.

Perkins, D. 2010. Invasive exotic plant monitoring at Colorado National Monument, 2009. Natural 

Resource Technical Report NPS/NCPN/NRTR—2010/354. National Park Service, Fort Collins, 

Colorado.

Perkins, D. 2012. Invasive exotic plant monitoring in Colorado National Monument: 2011 Field 

Season. Natural Resource Technical Report NPS/NCPN/ NRTR—2012/556. National Park 

Service, Fort Collins, Colorado.

Perkins, D. 2014. Invasive exotic plant monitoring in Colorado National Monument: 2013 field 

season. Natural Resource Technical Report NPS/NCPN/NRTR—2014/859. National Park 

Service, Fort Collins, Colorado.

Shinneman, D. J., and W. L. Baker. 2009. Historical fire and multidecadal drought as context for 

pinyon–juniper woodland restoration in western Colorado. Ecological Applications 19(5):1231-

1245.

Von Loh, J., K. Landgraf, A. Evenden, T. Owens, S. Blauer, and M. Reid. 2007. Vegetation 

Classification and Mapping Project Report, Colorado National Monument. Natural Resource 

Technical Report NPS/NCPN/NRTR—2007/061. National Park Service, Fort Collins, Colorado.
171

Witwicki, D., H. Thomas, R. Weissinger, A. Wight, S. Topp, S. L. Garman, and M. E. Miller. 2013. 

Integrated upland monitoring protocol for the park units in the Northern Colorado Plateau 

Network. National Park Service, Moab, Utah
172

4.6 Canyon Walls and Monolith 

Vegetation Communities

4.6.1 Description

Canyon walls and monoliths are important 

geological features in COLM. The deep 

canyons, canyon walls, and monoliths are 

characteristic of the Upper Colorado Plateau 

region and played a large part in the 

establishment of the park (NPS 2005). 

Monoliths are a great example of the powers of

erosion and other ecological processes as they 

are formed when sections of the canyon walls 

collapse (Harris 1985). The canyon walls and 

monoliths in COLM have vertical slopes that 

are sparsely vegetated. Hanging gardens are one of the only vegetative communities that grow on 

these vertical walls (Photo 9).

A hanging garden is a unique wetland habitat. Hanging gardens are associated with permanent seeps 

on vertical canyon walls (Malanson and Kay 1980). This habitat is a result of seeps creating 

favorable growing conditions by eroding the canyon wall enough to create a small ledge with a 

slighter slope. Hanging gardens are described as “pocketed wetlands” with draping vegetation 

located along cliff faces (Von Loh et al. 2007). According to Von Loh et al. (2007), there are three 

types of hanging gardens (alcove, terrace, and windowblind); these types exist in slightly different 

areas, depending on geologic formation and whether or not joint systems (series of connecting breaks 

in the canyon wall that allow for water to pass through) are present. Most of the vegetation in 

hanging gardens is short (<1 m [<3 ft]) herbaceous species; tree saplings and shrubs have also been 

known to grow in these habitats (Malanson and Kay 1980). These gardens are an important water

source for rare plants in COLMs semi-arid climate (KellerLynn 2006). Common maidenhair 

(Adiantum capillus-veneris) and Eastwood’s monkeyflower (Mimulus eastwoodiae) are examples of 

rare plants that have been known to occur in hanging gardens (CSU 2013). The Eastwood’s 

monkeyflower has a global rank of G3G4 and is considered “highly vulnerable” (CSU 2013).

These communities provide important nesting and roosting areas for a variety of species of birds and 

bats. The hanging garden communities also provide a source of water that can support the variety of 

amphibian species found within the park.

4.6.2 Measures

 Community extent and change over time

 Community composition

4.6.3 Reference Conditions/Values

The reference condition for the vegetation on canyon walls and monoliths in COLM is the condition 

of this vegetation prior to regional settlement. Prior to settlement, the canyon wall and monolith 

Photo 9. Hanging gardens on a vertical canyon wall 

in COLM (Photo by Shannon Amberg, SMUMN 

GSS, 2013).
173

vegetation would have been undisturbed and unaffected by anthropogenic stressors (e.g., invasive 

species, recreational climbing, development of Rim Rock Drive, graffiti).

4.6.4 Data and Methods

Von Loh et al. (2007) conducted a vegetation classification and mapping project for COLM and 

surrounding areas. The NVC plant associations known to occur in the Upper Colorado Plateau were 

used as a preliminary community list. Then historic COLM vegetation reports were consulted to 

refine the number of possible plant associations to 176 for the project area. In the end, the study area 

was divided into 67 plant associations. Prior to the field study, the park was first divided into five 

biophysical classes (relatively flat mesa tops, gently sloping alluvial fans, steep-walled canyons, 

ridges, and tilted bedrock formations), then divided again into biophysical units (BPUs). BPUs were 

categorized by their aspect and geology. BPUs were combined with orthoimages to create maps for 

the field study. Photo interpretation of true color digital orthoimagery was performed to help identify 

vegetation and landuse in a plot. Approximately 12,685 ha (31,344 ac) in the park and on Bureau of 

Land Management (BLM) land surrounding the park were mapped (Figure 37). There were 288 plots 

sampled. Field samples were collected at the plots between May and October 2003. Most sampling 

occurred in large patches of homogeneous vegetation; however, small patches were sampled if there 

were rare species or associations present (hanging gardens, wetlands, or relict plant communities). 

The report includes descriptions of the ecological systems and plant associations (globally and in 

COLM) as well as listing common plants in those associations.

4.6.5 Current Condition and Trend

Community Extent and Change over Time

At the time of publication, there were no complete data regarding hanging garden community extent 

in COLM, so an assessment of change over time could not be made. Von Loh et al. (2007) may have 

documented vegetation throughout the park, however, hanging gardens on canyon walls and 

monoliths were difficult and in some cases too dangerous to access and accurately assess. Two 

hanging gardens were documented at one plot during this study in COLM (Figure 37). These hanging 

gardens were observed in alcoves, on both sides (above and below) of Rim Rock Drive near the 

eastern tunnel, which is located in the southeast portion of the park. The alcoves contained loamy 

sand soil and were located at 1,716 m (5,630 ft) and 1,786 m (5,860 ft) in elevation, on slopes 

ranging from 3% to 40% (Von Loh et al. 2007).

Historical reports would also be needed to compare the change over time. Data on hanging 

community extent and change over time are important because changes in extent may indicate a lack 

of water (e.g., dried up seep, presence of invasive species) or presence of other stressors. The 

presence of hanging gardens or lack thereof may give park staff an idea of other factors influencing 

hanging gardens other than permanent seeps.
174

Figure 37. Plots sampled in COLM and on surrounding BLM land in 2003 (Von Loh et al. 2007).

Community Composition

Von Loh et al. (2007) documented one NVC plant association that has been known to occur in 

hanging gardens on COLM’s canyon walls. That association was Mancos herbaceous vegetation. The 

vegetation cover in these hanging gardens ranged from 45% to 95%, which is considered moderately 

to densely vegetated. A total of 27 species were observed in the two hanging gardens sampled (Table 

53) (Von Loh et al. 2007). Fourteen of those species were considered more abundant than the others. 
175

Mancos columbine was the most abundant species recorded; contributing 3% to 35% of the 

vegetative cover (Von Loh et al. 2007). The two-needle pinyon was the most abundant tree sapling 

observed (Von Loh et al. 2007). All three tall shrub species documented were considered abundant. 

Longleaf brickellbush (Brickellia longifolia), fendlerbush (Fendlera rupicola), and oceanspray 

(Holodiscus discolor var. dumosus) were abundant short shrubs, and the non-native Kentucky 

bluegrass was the only abundant graminoid species (Von Loh et al. 2007). Other abundant forbs 

included Cainville thistle (Cirsium arizonicum var. bipinnatum) and brown-plume wire-lettuce 

(Stephanomeria pauciflora) (Von Loh et al. 2007).

Table 53. Plant species within the two COLM hanging gardens surveyed in 2003. 

Scientific Name Common Name Strata

Juniperus osteosperma Utah juniper Tree canopy

Pinus edulis†

two-needle pinyon Tree canopy

Populus deltoides ssp. wislizeni Rio Grande cottonwood Tree canopy

Amelanchier utahensis† Utah serviceberry Tall shrub

Cercocarpus ledifolius var. intricatus†

littleleaf mountain-mahogany Tall shrub

Fraxinus anomala† singleleaf ash Tall shrub

Brickellia longifolia†

longleaf brickellbush Short/dwarf shrubs

Ephedra viridis Mormon tea Short/dwarf shrubs

Ericameria nauseosa rubber rabbitbrush Short/dwarf shrubs

Fendlera rupicola†

fendlerbush Short/dwarf shrubs

Holodiscus discolor var. dumosus† oceanspray Short/dwarf shrubs

Opuntia polyacantha plains pricklypear Short/dwarf shrubs

Dactylis glomerata* orchard grass Graminoids

Muhlenbergia richardsonis mat muhly Graminoids

Poa pratensis*† Kentucky bluegrass Graminoids

Apocynum spp. dogbane Forbs

Aquilegia micrantha† Mancos columbine Forbs

Artemisia ludoviciana Louisiana wormwood Forbs

Castilleja scabrida Eastwood's paintbrush Forbs

Cirsium arizonicum var. bipinnatum† Cainville thistle Forbs

Galium coloradoense† Colorado bedstraw Forbs

Lepidium montanum mountain pepperweed Forbs

Solidago simplex Mt. Albert goldenrod Forbs

Stephanomeria pauciflora† brown plume wire lettuce Forbs

Toxicodendron rydbergii western poison ivy Forbs

Trifolium spp. clover Forbs

Clematis ligusticifolia white virgin's bower Liana

*Indicates a non-native species.

†Were the most abundant species (also in bold).
176

Threats and Stressor Factors

COLM staff identified several possible threats to the vegetation communities found on canyon walls 

and monoliths in the park. Those threats include invasive species, recreational climbing, climate 

change, proximity of the road to habitats, and graffiti. While the ecological impacts of graffiti or its 

extent in COLM have not been studied, its occurrence clearly degrades the natural character of the 

park’s canyons and monoliths (Photo 10).Invasive species are a threat to the hanging garden plant 

communities in COLM. Von Loh et al. (2007) recorded two non-native species in the hanging 

gardens in the park: Orchard grass (Dactylis glomerata) and Kentucky bluegrass. Invasive species 

are a threat because they outcompete native species and can change the nutrient cycle (NPS 2015). 

According to KellerLynn (2006), the Fruita pipeline may have been a source of the spread of 

invasive species to the hanging gardens in the park. The pipeline is no longer in use, but it leaked 

water when it was in use, which resulted in artificial habitat for exotic species. 

As mentioned in previous chapters, western Colorado is expected to experience an increase in 

temperature with longer and hotter summer heat waves, an increased potential for drought, and an 

increase in precipitation falling as very heavy events as a result of global climate change (Lamm et 

al. 2014, Melillo et al. 2014). Since canyon vegetation communities such as hanging gardens often 

rely on seeps that are recharged by precipitation, any shifts in 

climate could impact the water supply to these communities. 

Shifts in climate could also change erosion patterns (Peizhen et 

al. 2001), which have shaped and continue to influence COLM’s 

canyon walls and monoliths 

Recreational climbing may also cause unneeded stress on the 

canyon wall vegetation and wildlife, including bats, birds, and 

raptors (Camp and Knight 1998). Approximately 300 climbing 

routes have been documented in COLM, with heavy use in areas 

such as Independence Monument, Lower Monument Slabs, and 

Liberty Cap Buttress (Zacher and Hertenstein 2014). Climbing 

activity may result in damage or removal of vegetation in the 

hanging gardens. Vegetation could be pulled from the hanging 

garden or crushed if the ledge were used as a foot- or handhold 

(Camp and Knight 1998). Rocks or soil could also be loosened 

by climbers, resulting in them falling on and/or covering the 

vegetation. 

Data Needs/Gaps

There are no historic or current data on hanging garden community extent in COLM. This makes 

assessing the change in community extent impossible until a baseline study has been conducted. Von 

Loh et al. (2007) located a hanging garden community in the “wilderness area” of COLM, but it was 

difficult to assess the full extent and composition of these gardens in the park because of their 

inaccessible location. The Von Loh et al. (2007) mapping project is also 10 years old and cannot be 

considered current, but may be considered a baseline for future study. If a more accurate and safe 

Photo 10. Graffiti on COLM’s 

canyon walls (NPS photo).
177

method of studying hanging gardens is discovered in the future, it would aid park managers in 

documenting community composition and extent in COLM.

Overall Condition

Community Extent and Change over Time

The project team defined the Significance Level for community extent and change over time as a 2. 

There are no historic or current data for vegetation community extent on canyon walls and monoliths, 

so an assessment of change over time is not possible. Hanging gardens and their associated 

vegetation are of special concern to COLM because the park is located in an arid climate where water 

is a limited resource. Two hanging gardens were recorded during the Von Loh et al. (2007) 

assessment, but the complete community extent could not be determined due to difficult-to-reach and 

dangerous locations high on the canyon walls. As a result, a Condition Level could not be assigned 

for this measure.

Community Composition

The project team defined the Significance Level for community composition as a 3. Von Loh et al.

(2007) documented plant community composition for two COLM hanging gardens in 2003. There 

were 27 species (trees, shrubs, graminoids, forbs, vines) observed at the two hanging gardens, with 

14 species considered abundant. The vegetation cover in these hanging gardens ranged from 45% to 

95%, which is considered moderately to densely vegetated. Although community composition was 

reported, only two gardens were analyzed. A complete community composition description for all 

hanging gardens in COLM could not be due to their hazardous locations. Therefore, a Condition 

Level was not assigned for this measure.

Weighted Condition Score

A Weighted Condition Score was not calculated for canyon walls and monolith vegetation in COLM 

due to a lack of historic and current community extent and composition data. Von Loh et al. (2007) 

documented community composition in the two observable hanging gardens in 2003; however, data 

from two hanging gardens may not accurately represent the community composition throughout the 

park.
178

Canyon Walls and Monolith Vegetation Communities

Measures Significance Level Condition Level WCS = N/A

Community Extent and 

Change over Time 2 n/a

Community 

Composition 3 n/a

4.6.6 Sources of Expertise

Dusty Perkins, Program Manager, Northern Colorado Plateau Network

4.6.7 Literature Cited

Camp, R. J., and R, L. Knight. 1998. Effects of rock climbing on cliff plant communities at Joshua 

Tree National Park, California. Conservation Biology 12(6):1302-1306.

Colorado State University (CSU). 2013. Colorado rare plant guide: Mesa County. Colorado Natural 

Heritage Program online. 

http://www.cnhp.colostate.edu/download/projects/rareplants/list_location.aspx?GeoScaleID=3

(accessed 16 February 2015).

Harris, D. V. 1985. The geologic story of the national parks and monuments, 4th edition. John Wiley 

and Sons Australia, Limited, Australia. 

KellerLynn, K. 2006. Colorado National Monument geologic resource evaluation report. Natural 

Resource Report NPS/NRPC/GRD/NRR—2006/007. National Park Service, Denver, Colorado. 

Lamm, N., S. Igo, and M. Davlantes, 2014. Report of the 2014 Geocorps springs and seeps 

assessment, Colorado National Monument, Colorado. National Park Service, Fruita, Colorado.

Malanson, G. P., and J. Kay. 1980. Flood frequency and the assemblage of dispersal types in hanging 

gardens of the Narrows, Zion National Park, Utah. The Great Basin Naturalist 40(4):365.

Melillo, J. M., T. C. Richmond, and G. W. Yohe, eds. 2014. Climate change impacts in the United 

States: The third national climate assessment. U.S. Global Change Research Program, 

Washington, D.C. 

National Park Service (NPS). 2005. Final general management plan and environmental impact 

statement: Colorado National Monument. National Park Service, Fort Collins, Colorado. 

National Park Service (NPS). 2015. Nonnative plants. 

http://www.nps.gov/glca/naturescience/nonnativeplants.htm (accessed 23 February 2015).
179

Peizhen, Z., P. Molnar, and W. R. Downs. 2001. Increased sedimentation rates and grain sizes 2–

4 myr ago due to the influence of climate change on erosion rates. Nature 410:891-897.

Von Loh, J., K. Landgraf, A. Evenden, T. Owens, S. Blauer, and M. Reid. 2007. Vegetation 

Classification and Mapping Project Report, Colorado National Monument. Natural Resource 

Technical Report NPS/NCPN/NRTR—2007/061. National Park Service, Fort Collins, Colorado.

Zacher, J., and T. Hertenstein. 2014. Climbing route survey report. National Park Service 

Unpublished Report, Fruita, Colorado.
180

4.7 Montane Shrublands

4.7.1 Description

Montane shrublands are a transitional zone 

between grasslands and montane forest 

(Hanophy and Teitelbaum 2003). Pinyonjuniper woodlands or sagebrush shrublands 

border these montane shrublands at the lower 

limits of their elevation, while ponderosa pine 

can be found at the upper edge of their 

elevation (Vankat 2013). The montane 

shrublands association within COLM is 

comprised of the following plant communities: 

Gambel’s oak/skunkbush sumac woodland, 

littleleaf mountain-mahogany/slickrock sparse vegetation, and Utah serviceberry shrubland. 

Common shrubs of these communities include Gambel’s oak, true mountain-mahogany, and Utah 

serviceberry (Von Loh et al. 2007).

Gambel’s oak/skunkbush sumac woodland communities within COLM can be found on moderately 

steep slopes (6-16%) between 1,814 and 1,948 m (5,951 and 6,391 ft) in elevation (Von Loh et al. 

2007). Soils are generally sandy loam or loam (Von Loh et al. 2007). This community can be found 

on the colluvial slope and associated terrace in canyons, at the base of sandstone formations adjacent 

to small canyons, in canyon bottoms, midslopes in canyons, and on the upper slopes of canyons (Von 

Loh et al. 2007).

Littleleaf mountain-mahogany/slickrock sparse vegetation communities within COLM are found on 

gentle to steep slopes (6-60%) between 1,586 and 1,953 m (5203 and 6,407 ft) in elevation (Von Loh 

et al. 2007). Soils are generally sandy loam, silty clay, or clay loam (Von Loh et al. 2007). This 

community can be found on talus or rockfall slopes in canyons, upper slopes in canyons, midslopes 

of ravines, midslopes of ridges, ridgetops, and in alcoves.

Utah serviceberry shrubland communities within COLM can be found on moderately steep to steep 

slopes (16-76%) between 1,481 and 2,028 m (4,859 and 6,654 ft) in elevation (Von Loh et al. 2007). 

Soils are generally silt loam (Von Loh et al. 2007). This community type can be found on high slopes 

and midslopes of canyons or on areas of talus or rockfall (Von Loh et al. 2007).

Mice, chipmunks, ground squirrels, and other rodents are present in this ecosystem due to the 

abundance of seeds, acorns, and berries (Hanophy and Teitelbaum 2003). Desert cottontails, mule 

deer, elk, raccoons, and black bears (Ursus americanus) can also be found foraging in these areas 

(Axelson 2002, Hanophy and Teitelbaum 2003). Gray fox, red fox (Vulpes vulpes), bobcats (Lynx 

rufus), skunks, long-tailed weasels (Mustela frenata), and coyotes actively hunt rodents and reptiles 

in this ecosystem, while mountain lion pursue deer (Hanophy and Teitelbaum 2003). Reptiles within 

montane shrublands include midget faded rattlesnakes (Crotalus oreganus concolor), bullsnakes 

(Pituophis catenifer), eastern fence lizards (Sceloporus undulatus), side-blotched lizards, and plateau 

Photo 11. Gambel’s oak/skunkbush shubland at 

COLM (Von Loh et al. 2007 Photo).
181

striped whiptails (Aspidoscelis velox). Birds of montane shrublands include golden eagles, 

Swainson’s hawks (Buteo swainsoni), red-tailed hawks, sharp-shinned hawks (Accipiter striatus), 

western scrub jays, lazuli buntings (Passerina amoena), western tanagers (Piranga ludoviciana), 

black-headed grosbeaks (Pheucticus melanocephalus), spotted towhees (Pipilo maculatus), dusky 

flycatchers (Empidonax oberholseri), and wild turkeys (Meleagris gallopavo) (Hanophy and 

Teitelbaum 2003).

4.7.2 Measures

 Community extent and change over time

 Community composition 

 Trends in invasive infestation

 Soil stability

 Percent cover biological soil crusts

 Percent bare ground

4.7.3 Reference Conditions/Values

An ideal reference condition for the montane shrublands of COLM would use the natural variability 

of the current community. However, not enough information is available regarding the range of 

variability for the selected measures to determine clear reference conditions at this time. Conditions 

will be assessed based on best professional judgment given the available data.

4.7.4 Data and Methods

A checklist of vascular plants was developed by Weber et al. (1982), documenting 66 families, 250 

genera, and 450 species within COLM and adjacent Mesa County. A number of other collectors, 

researchers, and specialists also documented new plant species in COLM during this time (Hogan et 

al. 2009). 

Abbey (c. 1985) developed a vegetation map of COLM consisting of 24 classes. The Colorado 

Natural Heritage Program completed an inventory for Mesa County in 1996, documenting the 

locations of 14 state sensitive plant species within COLM (Lyon et al. 1996). The NCPN funded a 

park-wide invasive plant inventory and mapping project in 2003 (Dewey and Anderson 2005). The 

NCPN reviewed the checklist of vascular plants developed by Weber et al. (1982) in 2005, and 

updated the vascular plant list to include 58 families and 351 species (Von Loh et al. 2007).

A vegetation mapping project conducted by the Von Loh et al. (2007) shows the locations of all 

dominant vegetation types present in COLM in the early 2000s. The methodology for this project 

included vegetation classification and attribute development based on the NVC, field reconnaissance 

and mapping, and development of a spatial database. The study area for the project included COLM, 

plus an additional area beyond the park border. Mapping was completed using both traditional photo 

interpretation and biophysical modeling. This allowed for consistent and accurate mapping in a cost 

effective manner. The project resulted in vegetation data and maps for COLM and its immediate 

vicinity.
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Hogan et al. (2009) developed a comprehensive list of plant species found within the park. This 

effort involved reviewing existing literature and re-examining specimens in the COLM herbarium. It 

also included field work to confirm unverified species and to potentially locate new species. This list 

includes plants by habitat type, one of which is sage shrub, which includes plants from “woodlands 

dominated by Gambel’s oak and other montane shrubs”.

Invasive species monitoring and mapping has occurred within COLM since 2003 (Dewey and 

Anderson 2005). The most recent inventory was completed in 2014 (Perkins 2014). This inventory 

was based on a list of priority IEPs that had been developed by the staff at COLM and the NCPN 

(Perkins 2014). A MDTS of 40 m2(431 ft2or approximately 20 x 20 ft) was established for use in the 

ongoing monitoring program. Monitoring routes and quadrats were established along the roads, 

major drainages, and trails in the park. In addition to invasive species composition, information was 

also collected on additional attributes, including size and canopy.

4.7.5 Current Condition and Trend

Community Extent and Change over Time

Von Loh et al. (2007) represent the most recent estimate of the extent of montane shrublands at 

COLM. Data from this vegetation mapping projects show that montane shrublands comprise 579 ha 

(1,431 ac), or 7% of the COLM landscape (Table 54, Figure 38). Gambel’s oak/skunkbush sumac 

woodland communities within COLM can be found at the head of Ute Canyon and its associated 

drainages on the mesa tops and at the head of No Thoroughfare Canyon (Von Loh et al. 2007). 

Littleleaf mountain-mahogany/slickrock sparse vegetation communities of COLM can be found in 

Fruita Canyon, Ute Canyon, above Kodels Canyon, Monument Canyon near Kissing Couple, near 

the Highland View overlook on Rimrock Drive, near the Artist’s Point overlook on Rimrock Drive, 

and along Liberty Cap Trail, No Thoroughfare Canyon, and Wedding Canyon (Von Loh et al. 2007). 

Utah serviceberry shrubland communities of COLM can be found in Kodels, Gold Star, and No 

Thoroughfare Canyon. Because this community is present on steep slopes, it is more widespread than 

sampling indicates (Von Loh et al. 2007).

Table 54. Areal extent of montane shrubland alliances found in COLM (Von Loh et al. 2007).

Alliances

Area

ha (ac)

Percentage

Montane

shrublands

Total

vegetation

Gambel’s oak/skunkbush woodland 51.3 (20.8) 3.6% 0.3%

Littleleaf mountain-mahogany/slickrock sparse vegetation 93.2 (37.7) 6.5% 0.5%

Utah serviceberry shrubland 1,286.4 (520.6) 89.9% 6.3%

Montane shrublands total 1,430.9 (579.1) 100% 7.0%

Park total 20,450 (8,275.8)
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Figure 38. Montane shrubland locations within COLM (Voh Loh et al. 2007).

Community Composition

A comprehensive plant species list was developed by Hogan et al. (2009). A total of 136 plant 

species were classified as either “present” or “reported” in montane shrubland communities 

(Appendix I). Species were considered “present” if a confirmed specimen or observation has been 

made since 1970. Species are considered “reported” if they have been listed in existing literature 

(Hogan et al. 2009). This total was comprised of six trees, 25 shrubs, 70 perennial forbs, 14 annual 
184

forbs, 15 perennial graminoids, two annual graminoids, and four ferns and allies (Hogan et al. 2009). 

Of these plants, seven (5.2%) are introduced, while the remaining 129 (95%) are native (NPS 2015).

The Gambel’s oak/skunkbush woodland communities are characterized by a closed tree canopy of 

Gambel’s oak, typically 2 to 10 m (7 to 33 ft) tall (Von Loh et al. 2007). Utah juniper and two-needle 

pinyon may also provide some canopy cover in these stands. (Von Loh et al. 2007) The shrub layer

in these stands is diverse, and includes plants such as skunkbush sumac, Utah serviceberry, basin big 

sagebrush, true mountain-mahogany, rubber rabbitbrush, and western chokecherry (Von Loh et al. 

2007). Short and dwarf shrubs in this community include Wyoming big sagebrush, rubber 

rabbitbrush, Gambel’s oak, western snowberry (Symphoricarpos occidentalis), Oregon grape, and 

plains pricklypear (Von Loh et al. 2007). The herbaceous layer includes graminoids such as Indian 

ricegrass, crested wheatgrass, slender wheatgrass (Elymus trachycaulus), cheatgrass, squirreltail, 

littleseed ricegrass (Piptatherum micranthum), and muttongrass and forbs such as tarragon, 

lambsquarters, bastard toadflax, western tansymustard, hairy false goldenaster, littleleaf alumroot 

(Heuchera parvifolia), prairie pepperwort, mountain pepperweed, starry false Solomon’s-seal, sleepy 

catchfly, tumble mustard, long-beak fiddle-mustard, and American vetch (Vicia americana) (Von 

Loh et al. 2007). The liana white virgin’s bower (Clematis ligusticifolia) was found in one stand 

(Von Loh et al. 2007). The most abundant species within this community by stratum can be found in 

Table 55.

Table 55. Dominant plant species (by strata) within the Gambel’s oak/skunkbush sumac woodlands of 

COLM (Von Loh et al. 2007).

Gambel’s oak/skunkbush woodland

Scientific Name Common Name Strata

Quercus gambelii Gambel's oak Tree canopy

Artemisia tridentata ssp. tridentata basin big sagebrush Tall shrub/sapling

Prunus virginiana western chokecherry Tall shrub/sapling

Quercus gambelii Gambel's oak Tall shrub/sapling

Rhus aromatica var. pilosissima skunkbush sumac Tall shrub/sapling

Rosa woodsii Woods' rose Short shrub/sapling

Achnatherum hymenoides Indian ricegrass Herb

Berberis repens Oregon grape Herb

Bromus tectorum* cheatgrass Herb

Elymus trachycaulus slender wheatgrass Herb

Maianthemum stellatum starry false Solomon’s-seal Herb

Piptatherum micranthum littleseed ricegrass Herb

Poa fendleriana muttongrass Herb

*Indicates a non-native species.

The littleleaf mountain-mahogany/slickrock sparse vegetation communities are characterized by a 

tall shrub canopy of Utah serviceberry and true mountain-mahogany, typically 2 to 10 m (7 to 33 ft) 

tall (Von Loh et al. 2007). A sparse canopy layer in these communities includes singleleaf ash, Utah 
185

juniper, and two-needle pinyon (Von Loh et al. 2007). The shrub layer is sparse and diverse, 

including plants such as basin big sagebrush, Bigelow’s sagebrush, white sagebrush (Artemisia 

ludoviciana ssp. albula), Wyoming big sagebrush, Mormon tea, rubber rabbitbrush, skunkbush 

sumac, littleleaf brickellbush, yellow rabbitbrush, rimrock wild buckwheat (Eriogonum corymbosum 

var. orbiculatum), and broom snakeweed, and the succulents plains pricklypear, Whipple’s fishhook 

cactus, and Harriman's yucca (Von Loh et al. 2007). The herbaceous layer typically accounts for less 

than 5% cover and includes graminoids such as Indian ricegrass, cheatgrass, squirreltail, six weeks 

fescue, needle and thread saline wildrye, muttongrass, and bluebunch wheatgrass (Pseudoroegneria 

spicata) and forbs such as Fendler’s sandwort, hoary dusty-maiden, ridge-seeded spurge, plateau 

yellow cryptanth (Cryptantha flava), western tansymustard, dwarf draba, Colorado bedstraw (Galium 

coloradoense), hairy false goldenaster, mountain pepperweed, grassy rockgoldenrod, longleaf phlox, 

sharpleaf twinpod (Physaria acutifolia), western groundsel, sleepy catchfly, scarlet globemallow, 

desert princesplume, and long-beak fiddle-mustard (Von Loh et al. 2007). The most abundant species 

within this community by stratum can be found in Table 56.

Table 56. Dominant plant species (by strata) within the littleleaf mountain-mahogany/slickrock sparse 

vegetation community of COLM (Von Loh et al. 2007). 

Littleleaf mountain-mahogany/slickrock sparse vegetation

Scientific Name Common Name Strata

Fraxinus anomala singleleaf ash Tree canopy

Juniperus osteosperma Utah juniper Tree canopy

Pinus edulis two-needle pinyon Tree canopy

Amelanchier utahensis Utah serviceberry Tall shrub/sapling

Cercocarpus montanus true mountain-mahogany Tall shrub/sapling

Artemisia tridentata ssp. wyomingensis Wyoming big sagebrush Short shrub/sapling

Ephedra viridis Mormon tea Short shrub/sapling

Achnatherum hymenoides Indian ricegrass Herb

Artemisia bigelovii Bigelow's sagebrush Herb

Bromus tectorum* cheatgrass Herb

Chaenactis douglasii hoary dusty-maiden Herb

Galium coloradoense Colorado bedstraw Herb

Leymus salina saline wildrye Herb

Poa fendleriana muttongrass Herb

Pseudoroegneria spicata bluebunch wheatgrass Herb

*Indicates a non-native species.

The Utah serviceberry shrubland communities are characterized by Utah serviceberry shrubs, 

typically 2 to 5 m (7 to 16 ft) tall. (Von Loh et al. 2007) Two-needle pinyon and Utah juniper provide 

some canopy cover in these communities. (Von Loh et al. 2007)The shrub layer is sparse and 

consists of the tall shrub singleleaf ash and the short shrubs; Wyoming big sagebrush, yellow 

rabbitbrush, Mormon tea, and skunkbush sumac, and the dwarf shrubs; white sagebrush, broom 

snakeweed, prickly phlox, and plains pricklypear (Von Loh et al. 2007). The herbaceous layer is 
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typically sparse and includes graminoids such as Indian ricegrass, purple three-awn, cheatgrass, six 

weeks fescue, needle and thread, saline wildrye, James’ galleta, and muttongrass and forbs such as 

pallid milkweed, Eastwood’s paintbrush (Castilleja scabrida), sulfur wild buckwheat (Eriogonum 

umbellatum), common hyalineherb (Hymenopappus filifolius), mountain pepperweed, Colorado four 

o’clock (Mirabilis multiflora), and sharpleaf twinpod (Von Loh et al. 2007). The most abundant 

species within this community by stratum can be found in Table 57.

Table 57. Dominant plant species (by strata) within the Utah serviceberry shrubland of COLM (Von Loh et 

al. 2007). 

Littleleaf mountain-mahogany/slickrock sparse vegetation

Scientific Name Common Name Strata

Amelanchier utahensis Utah serviceberry Tall shrub/sapling

Achnatherum hymenoides Indian ricegrass Herb

Bromus tectorum* cheatgrass Herb

Hymenopappus filifolius common hyalineherb Herb

*Indicates a non-native species.

Trends in Invasive Infestation

COLM is part of a long-term monitoring program for IEPs developed by the NCPN which focuses on 

early detection (Perkins 2014). The first survey of IEPs in the park was conducted in 2003 by Dewey 

and Anderson (2005). The latest monitoring was conducted during the 2013 field season (Perkins 

2014) and will be used to assess this measure, since it includes the previously collected data on IEP 

infestations in COLM. A full discussion of IEPs park-wide, including a discussion of trends can be 

found in Chapter 2.2.2. In summary, during this 8-year time span (2003-2011), there was an overall 

decrease in Russian olive, tamarisk and woolly mullein (Perkins 2014). However, the number of field 

bindweed infestations more than doubled during this same period (Perkins 2014).

In the most recent survey, conducted in 2013, a total of 462 IEP infestation points were identified 

within the park (Perkins 2014). The most frequently documented species of IEP were yellow 

sweetclover and cheatgrass. Several IEP species were documented as present in the descriptions of 

the vegetation associations by Von Loh et al. (2007). Von Loh et al. (2007) identified cheatgrass as 

one of the dominant herbaceous species in all three associations used to describe montane shrublands 

in this assessment; the Gambel’s oak/skunkbush sumac woodland, the littleleaf mountainmahogany/slickrock sparse vegetation, and the Utah serviceberry shrubland.

Trends in invasive plants have not been assessed specifically by vegetation association at COLM. To 

identify invasive species infestations associated with montane shrublands, spatial queries were 

performed using the data from the 2013 IEP survey and the montane shrubland communities mapped 

by Von Loh et al. (2007). The spatial queries selected IEP points that were either within a mapped 

location of a montane shrubland or within 100 m (328 ft) of one of these communities.

The analysis identified 118 (approximately 26%) of the IEP points met the criteria (Figure 39, Table 

58). The most common IEP’s selected by these queries were yellow sweetclover (57) and cheatgrass 
187

(26). Nearly all of the occurrences of yellow sweetclover, and all but one of the cheatgrass 

occurrences were within 100 m (328 ft) of a mapped montane shrubland (Table 58). Overall, nearly 

90% of the IEP occurrences selected by the spatial queries met the proximity criterion (within 100 m 

[328 ft]). The results for all IEP occurrences that satisfied the spatial queries can be found Table 58.

Figure 39. IEP infestations associated with mapped montane shrublands.
188

Table 58. Number and location of non-native species occurrences in relation to montane shrubland. 

Scientific Name Common Name

Number 

Within

Number 

Adjacent

Total 

Number

Melilotus officinalis yellow sweetclover 6 51 57

Bromus tectorum cheatgrass 1 25 26

Convolvulus arvensis field bindweed 1 8 9

Verbascum thapsus woolly mullein 1 8 9

Tamarix ramosissima saltcedar 2 3 5

Cirsium vulgare bull thistle 3 3

Ulmus pumila Siberian elm 1 2 3

Arctium minus burdock 2 2

Elaeagnus angustifolia Russian olive 2 2

Poa bulbosa bulbous bluegrass 1 1 2

Totals 13 105 118

Yellow sweetclover and cheatgrass accounted for 70% of the infestations that occurred within or in 

close proximity to montane shrublands. These two species are also the most widespread IEPs in 

COLM (Perkins 2014). Yellow sweetclover had not been detected in previous years, primarily as it 

was not part of the priority species list until 2011 (Perkins 2014).

Soil Stability

Soil stability depends on a number of factors. The presence of cryptobiotic crusts, litter/duff, other 

non-vegetative ground cover, slope, soil composition, and soil texture are some of the factors that can 

influence soil stability (NRCS 1996, Belnap et al. 2008, Witwicki et al. 2013). Vegetative conditions 

also greatly influence soil stability (Whisenant 1985). Soil loss can be influenced by rainfall 

intensity, size and frequency of bare areas, soil type, topography, and plant cover, especially 

following a fire. Vegetation and slope are the best determinants of soil erosion in severe rainfall 

storms. Studies in various plant communities show that 60-70% vegetation cover appears necessary 

to ensure soil stability against erosion during rainfall (Orr 1970, Whisenant 1985). Specific data on 

soil stability within COLM were not available; therefore a condition assessment of this measure is 

not possible.

Percent Cover Biological Soil Crusts

Belnap et al. (2008, p. 1,257) defines BSCs as “intertwined communities of lichens, mosses, and 

cyanobacteria commonly found on soil surfaces in dryland regions”. These communities are a very 

important part of the ecosystem because of their influence on local hydrology, soil stability and 

fertility, and overall biodiversity (Belnap et al. 2008). BSCs aggregate soil particles, making the soil 

stronger and less susceptible to erosional forces of wind and water, thereby retaining nutrients, 

organic matter, and seeds in the underlying soils (Miller 2005). BSCs within COLM are most 

commonly found on sites that are protected from disturbance and are re-developing in areas that were 

once grazed or otherwise disturbed (Von Loh et al. 2007). Because of the ecological benefits 

provided by BSCs, they should be included in ecological monitoring programs where present 
189

(Belnap et al. 2008). Cover of BSCs within littleleaf mountain-mahogany/slickrock sparse vegetation 

communities is sparse, rarely reaching 5% cover (Von Loh et al. 2007). Data on percent cover of 

cryptobiotic crusts and soils for the Gambel’s oak/skunkbush sumac woodland and Utah serviceberry 

shrubland communities are not available. Due to lack of available data, a condition assessment is not 

possible for this measure.

Percent Bare Ground

Percent bare ground is important because it can impact soil stability, as vegetation helps prevent 

wind erosion (Witwicki et al. 2013). Refer to the percent bare ground measure of the sagebrush 

shrublands/shrub steppe component (Chapter 4.2.5) for more information regarding the importance 

of percent bare ground.

Percent bare ground of montane shrublands varies with community type. In the Gambel’s 

oak/skunkbush sumac woodland communities, total vegetation canopy cover ranges from 67 to 106% 

with high ground cover of litter in the form of oak mast in unvegetated areas (Von Loh et al. 2007). 

Littleleaf mountain-mahogany/slickrock sparse vegetation communities have total vegetation canopy 

cover that ranges from 10 to 50% with low to moderate ground cover of litter and low to high ground 

cover of bedrock, large rocks, small rocks, and bare soil in unvegetated areas (Von Loh et al. 2007). 

In Utah serviceberry shrubland communities, total vegetation canopy cover ranges from 17 to 27% 

with high ground cover of bedrock, large rocks, small rocks, and bare soil in unvegetated areas (Von 

Loh et al. 2007).

Threats and Stressor Factors

NPS staff identified several potential threats and stressors to the montane shrubland community: IEPs 

(particularly cheat grass and crested wheatgrass), unnatural fire regimes, drought, and regional 

climate variation. Refer to the threats and stressor factors section of the sagebrush shrublands/shrub 

steppe component for more detailed discussions regarding the IEPs, drought, and regional climate 

variation at COLM.

Fire can affect an ecosystem by altering the vegetation composition and structure and eliminating fire 

intolerant plant species (Miller 2005). Montane shrublands are highly susceptible to fire due to their 

high density and tall shrubs (Witwicki et al. 2013). After a fire kills the above ground portions of 

Gambel’s oak and serviceberry, these plants resprout prolifically through roots, rhizomes, and 

lignotubers (Floyd et al. 2000). Mountain mahogany may resprout or reestablish by seed after being 

killed by a fire. Because of their dense structure, leaf litter, and the continuous fuel of grasses and 

forbs in between shrubs, many stands of Gambel’s oak shrubland are highly flammable (Floyd et al. 

2000). Brown (1958) suggests that dense stands of Gambel’s oak occurring on steep slopes may be 

due to the tendency for fire to spread over larger areas and burn more thoroughly on steep slopes than 

on level ground, causing a more widespread resprouting.

Visitor impacts within the park’s montane shrubland habitats include damage to BSC present within 

these environments. Hikers, particularly those using unauthorized “social” trails, cause damage to 

these fragile habitats and continued disturbance does not allow for the time needed for BSCs to 

regenerate. This can lead to invasive species encroaching and potentially replacing BSC habitats.
190

Data Needs/Gaps

Though data exist within COLM for the community extent and change over time and percent bare 

ground measures, a reference condition is necessary for these measures to determine whether or not 

the collected data are unusual for these communities. Data for soil stability were not available for 

COLM. Witwicki et al. (2013) briefly touch on this topic but only discuss monitoring protocol, no 

actual data are presented. Data for each community type for percent cover of BSCs as well as a 

reference condition are needed in order to accurately assess the condition for this measure. Research 

on the impacts from the proliferation of social trails within the park is also recommended.

Currently a guaranteed funding source for the invasive species removal/control has not been 

identified. Failure to secure funding for this management action will result in the loss of the gains 

that have been made in eradicating IEPs within the park. Additionally, another programmatic need 

for COLM is a trail management plan. Currently, visitors face no restrictions in their access to any 

areas within the park.

Overall Condition

Community Extent and Change over Time

This measure was assigned a Significance Level of 3. Though the community extent of montane 

shrublands has been documented in the vegetation mapping project (Von Loh et al. 2007), data for 

land cover change analysis were not available. Since land cover change analysis could not be done, a 

Condition Level was not assigned to this measure.

Community Composition

The community composition measure was assigned a Significance Level of 3. According to Hogan et 

al. (2009), a total of 136 plant species are present in the montane shrublands of COLM. Of these 

plant species, 95% are native. With relatively high species richness and nativity, the Condition Level

assigned to this measure is 1, indicating low concern.

Trends in Invasive Infestation

A Significance Level of 3 was assigned to this measure. Invasive species are one of the greatest 

threats to biodiversity in the U.S. (Wilcove et al. 1998). Invasive exotic plant surveys performed by 

Perkins (2010, 2012) indicate many different species of IEPs occurring within COLM. Analysis 

conducted for this assessment showed that many of these IEPs occur within the 100 m (328 ft) of 

montane shrublands of COLM, the most common of which are yellow sweetclover and cheatgrass. 

Based on the number of infestations, most IEP occurrence remained relatively constant from year to 

year. Over the last decade the park has focused control efforts on eradication of IEP’s. Future 

funding for these control measures is not available, so the potential for increased infestations is high 

(Hartwig, written communication 18 November 2015). Because cheatgrass makes up such a large 

portion of the total IEPs, a Condition Level of 2 was assigned for this measure.

Soil Stability

A Significance Level of 2 was assigned to the soil stability measure. Specific data on soil stability 

within the sagebrush shrublands/shrub steppe of COLM were not available. Many variables that may 

contribute to soil stability are outlined throughout the document, though these often contain a range 
191

of values, making it difficult to accurately determine the soil stability within COLM. A Condition 

Level was not assigned to this measure because specific data on soil stability are not available.

Percent Cover Biological Soil Crusts

This measure was assigned a Significance Level of 3. Data for this measure only exist for one of the 

three montane shrubland community types. Data for the remaining community types are needed to 

accurately assess the condition for this measure. A Condition Level was not assigned to this measure 

due to lack of available data.

Percent Bare Ground

The percent bare ground measure was assigned a Significance Level of 2. Percent bare ground varies 

with community type. Where vegetation is absent, cover of litter, rocks, and bare soil vary from low 

to high. Although some data exist for the percent bare ground measure, a reference condition is 

needed to determine the current overall condition of the measure. Because a reference condition is 

not available, this measure was not assigned a Condition Level.

Weighted Condition Score

A Weighted Condition Score was not calculated for this component because Condition Levels could 

not be assigned to greater than 50% of the measures due to lack of available data. The condition of 

montane shrublands in COLM will remain unknown until more data are available for the selected 

measures.

Montane Shrublands

Measures Significance Level Condition Level WCS = N/A

Community Extent and 

Change over Time 3 n/a

Community 

Composition 3 1

Trends in Invasive 

Infestation 3 2

Soil Stability 2 n/a

Percent Cover 

Biological Soil Crusts 3 n/a

Percent Bare Ground 2 n/a

4.7.6 Sources of Expertise

Dusty Perkins, Program Manager, Northern Colorado Plateau Network
192

4.7.7 Literature Cited

Abbey, M. C. c1985. A vegetation map for Colorado National Monument. Colorado National 

Monument, Fruita, Colorado.

Axelson, J. 2002. Big game hunter’s guide to Colorado. Wilderness Adventures Press, Inc., Belgrade, 

Montana.

Belnap, J., S. L. Phillips, D. L. Witwicki, and M. E. Miller. 2008. Visually assessing the level of 

development and soil surface stability of cyanobacterially dominated biological soil crusts. 

Journal of Arid Environments 72:1257-1264.

Brown, H. E. 1958. Gambel oak in west-central Colorado. Ecology 39(2):317-327.

Dewey, S. and K. Anderson. 2005. An inventory of invasive nonnative plants in Colorado National 

Monument (2003). Weed Science Research Project Report No. SD0516A. Utah State University, 

Logan, Utah.

Floyd, M. L., W. H. Romme, and D. D. Hanna. 2000. Fire history and vegetation pattern in Mesa 

Verde National Park, Colorado, USA. Ecological Applications 10(6):1666-1680.

Hanophy, W., and H. Teitelbaum. 2003. Wild Colorado: Crossroads of biodiversity. Colorado 

Division of Wildlife, Education Section, Denver, Colorado.

Haveren, B. P. 2000. Ground cover dynamics in a sagebrush steppe community. Resource Notes No. 

19. Bureau of Land Management, Denver, Colorado.

Hogan, T., N. Lederer, and W. Fertig. 2009. Annotated checklist of vascular flora: Colorado National 

Monument. Natural Resource Technical Report NPS/NCPN/NRTR—2009/231. National Park 

Service, Fort Collins, Colorado.

Kachergis, E., M. E. Rocca, and M. E. Fernandez-Gimenez. 2011. Indicators of ecosystem function 

identify alternate states in the sagebrush steppe. Ecological Applications 21(7):2781-2792.

Lyon, P., C. Pague, R. Rondeau, L. Renner, C. Slater, and C. Richard. 1996. Natural heritage 

inventory of Mesa County, Colorado. Colorado Natural Heritage Program, Fort Collins, 

Colorado.

Miller, M. E. 2005. The structure and functioning of dryland ecosystems—Conceptual models to 

inform long-term ecological monitoring. Scientific Investigations Report 2005-5197. U.S. 

Geological Survey, Reston Virginia.

National Park Service (NPS). 2015. NPSpecies: Information on species in national parks. 

https://irma.nps.gov/NPSpecies/Search/SpeciesList/COLM (accessed 23 June 2015).

Natural Resources Conservation Service (NRCS). 1996. Soil quality indicators: Aggregate stability. 

http://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/nrcs142p2_052820.pdf (accessed 25 

February 2015).
193

Natural Resources Conservation Service (NRCS). 2010. NRI rangeland resource assessment - Bare 

ground, intercanopy gaps, and soil aggregate stability. 

http://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb1041839.pdf (accessed 19 May 

2015).

O’Dell, T. E., S. L. Garman, A. Evenden, M. Beer, E. Nance, S. Daw, A. Wight, M. A. Powell, D. 

Perry, R. DenBleyker, and others. 2005. Northern Colorado Plateau Inventory and Monitoring 

Network: Vital Signs monitoring plan. National Park Service, Moab, Utah.

Perkins, D. 2010. Invasive exotic plant monitoring at Colorado National Monument, 2009. Natural 

Resource Technical Report NPS/NCPN/NRTR—2010/354. National Park Service, Fort Collins, 

Colorado.

Perkins, D. 2012. Invasive exotic plant monitoring in Colorado National Monument: 2011 Field 

Season. Natural Resource Technical Report NPS/NCPN/ NRTR—2012/556. National Park 

Service, Fort Collins, Colorado.

Perkins, D. 2013. Invasive exotic plant monitoring. National Park Service, Fort Collins, Colorado.

Springer, A., L. E. Stevens, and R. Harms. 2006. Inventory and classification of selected National 

Park Service springs on the Colorado Plateau. National Park Service, Fort Collins, Colorado.

Vankat, J. L. 2013. Vegetation dynamics on the mountains and plateaus of the American Southwest. 

Springer Science and Business Media, Dordrecht, Netherlands.

Von Loh, J., K. Landgraf, A. Evenden, T. Owens, S. Blauer, and M. Reid. 2007. Vegetation 

classification and mapping project report, Colorado National Monument. Natural Resource 

Technical Report NPS/NCPN/NRTR—2007/061. National Park Service, Fort Collins, Colorado.

Weber, W. A., V. Siplivinsky, H. Beck, and C. Rector. 1982. Checklist of vascular plants: Colorado 

National Monument. University of Colorado Museum, Boulder, Colorado.

Whisenant, S. G. 1985. A multidisciplinary approach to evaluating fire effects. In Rangeland fire 

effects: A symposium: Proceedings of a symposium sponsored by Bureau of Land Management 

and University of Idaho at Boise, Idaho, November 27-29, 1984. Idaho State Office, US 

Department of the Interior, Bureau of Land Management, Boise, Idaho.

Wilcove, D. S., D. Rothstein, J. Dubow, A. Phillips, and E. Losos. 1998. Quantifying threats to 

imperiled species in the United States. Bioscience 48(8):607-615.

Witwicki, D., H. Thomas, R. Weissinger, A. Wight, S. Topp, S. L. Garman, and M. E. Miller. 2013. 

Integrated upland monitoring protocol for the park units in the Northern Colorado Plateau 

Network. National Park Service, Moab, Utah.
194

4.8 Herptiles

4.8.1 Description

Herptiles include two ectothermic vertebrate groups: 

reptiles and amphibians. Amphibians require water for a 

portion of their lifecycle and are considered a high 

priority Vital Sign for monitoring at COLM (O’Dell et 

al. 2005). A total of 22 native herptile species (five 

amphibians and 17 reptiles) occur within COLM’s 

boundaries, with two additional species that likely occur 

but are currently unconfirmed (NPS 2014). Common 

species include the red-spotted toad, whiptails 

(Aspidoscelis spp.), and the eastern collared lizard (Photo 

12) (NPS 2014). Despite limited water resources, COLM 

offers a variety of habitats that support herpetofauna, 

from canyon bottoms to the mesa tops.

Riparian corridors line ephemeral washes that are 

interspersed throughout the canyon bottoms and alcoves 

and are fed by seeps and springs which provides a 

somewhat mesic environment (Von Loh et al. 2007). 

This is often where herptiles have been spotted, as these habitats provide shelter from the semi-arid 

desert climate (Platenberg and Graham 2003). The mesa tops are pocked with natural potholes 

(solution pits or tinajas) that hold water after rain events and collect wind-blown dust (NPS 2015). 

Natural potholes and riparian habitats are important land features relied on by herpetofauna as well as 

insects for breeding and survival through the juvenile/larval stages (NPS 2015).

4.8.2 Measures

 Amphibian richness

 Amphibian abundance

 Amphibian distribution

 Reptile richness

 Reptile abundance

 Reptile distribution

4.8.3 Reference Conditions/Values

The reference condition for herptiles at COLM is based on the herpetofauna inventory survey 

conducted in 2002 (Platenberg and Graham 2003); this survey had an estimated inventory 

completeness of 52% for the park. There are no other published surveys or studies on reptiles or 

amphibians in COLM since Platenberg and Graham (2003), and there are no data indicative of 

herptile richness, abundance, or distribution prior to the inventory.

Photo 12. The eastern collared lizard is 

one of several lizard species that inhabit 

the park (NPS Photo by Lynne Mager).
195

4.8.4 Data and Methods

Platenberg and Graham (2003) inventoried COLM herpetofauna in 2002 from 21-24 June and again 

from 7-9 August. The primary goal of the survey effort was to obtain 90% documentation of species 

present as a baseline inventory for the NCPN units; determining general abundance and distribution 

was a secondary goal. General visual encounter surveys (VES) with a global positioning system 

(GPS) device comprised the bulk of survey efforts at COLM; some night driving, nighttime VES, 

and habitat/time/area constrained searches (TACS) were also conducted. The inventory also included 

data mining efforts for documentation of species not observed during field work to revise and update 

the NPS master species lists for all NCPN parks.

From March to early September of 2011, Board (2011) recorded weekly observations of amphibian 

species at a known breeding location in No Thoroughfare Canyon. The main site was a small 

seasonal “plunge pool” 1.9 km (1.2 mi) from the trailhead near Grand Junction. Board (2011) 

documented water level and temperature, along with the amphibian species present (calls and visual 

observations, calling activity, evidence of reproduction (e.g., eggs and tadpoles).

Lamm et al. (2014) conducted an inventory of COLM seeps and springs from May to July 2014. 

Thirty-eight seep- and spring-associated sites were visited during this period. This number does not 

represent the total number of seeps and springs within the park (Lamm, written communication 27 

November 2015). Data collected at each site included estimated discharge (i.e., flow), flora and fauna 

observations, and when sufficient amounts of water were available for testing selected water quality 

parameters (temperature and specific conductance) were collected. Lamm et al. (2014) found 

amphibians at 15 of the sites surveyed, although most of the sightings were tadpoles. The majority of 

amphibian sightings occurred in Monument Canyon (Lamm et al. 2014).

4.8.5 Current Condition and Trend

Amphibian Richness

Platenberg and Graham (2003) listed two amphibian species that were confirmed during the 

herpetofauna inventory in 2002: Woodhouse’s toad (Anaxyrus woodhousii) and Great Basin 

spadefoot (Spea intermontana). Table 59 lists the five amphibian species documented at COLM and 

one unconfirmed species, according to NPS (2014). Board (2011) identified four amphibian species 

at a No Thoroughfare Canyon pool in 2011. During the 2014 seeps and springs survey, Lamm et al. 

(2014) observed five species of amphibians (including tadpoles and frogs eggs). A sighting of the 

northern leopard frog, a species of “special concern” in the state of Colorado, was reported by Board 

(2011) at the site in the summer of 2010 after a flooding event. Lamm et al. (2014) reported two 

sightings of the northern leopard frog, one each in Echo and Ute Canyon.

Amphibian Abundance

There are no detailed abundance data for amphibians at this time. There are general abundance 

descriptions provided in the NPS species list for COLM (Table 60).
196

Table 59. Amphibian species known to occur or unconfirmed at COLM (NPS 2014).

Scientific Name Common Name NPS (2014) Board (2011) Lamm et al. (2014)

Ambystoma tigrinum eastern tiger salamander X

Anaxyrus punctatus red-spotted toad X X X

Anaxyrus woodhousii Woodhouse's toad X X X

Hyla arenicolor canyon treefrog U X

Lithobates pipiens northern leopard frog X X

Spea intermontana Great Basin spadefoot X X

U = unconfirmed

Table 60. Amphibians included in the NPS species list with abundance column (NPS 2014).

Scientific Name Common Name Abundance

Ambystoma tigrinum eastern tiger salamander Rare

Anaxyrus punctatus red-spotted toad Common

Anaxyrus woodhousii Woodhouse's toad Uncommon

Lithobates pipiens northern leopard frog Unknown

Spea intermontana Great Basin spadefoot Uncommon

Amphibian Distribution

Amphibians within COLM utilize areas with available water and vegetation cover. Distribution of 

amphibians generally follows these riparian habitats located throughout the canyon bottoms of 

COLM. Platenberg and Graham (2003) used GIS to record the locations where amphibians were 

observed during the herpetofauna inventory survey effort in 2002 (Figure 40). Board (2011)

confirmed the presence of four amphibian species in No Thoroughfare Canyon in 2011. Lamm et al. 

(2014) also reported amphibians Monument, Ute, and Echo Canyons.
197

Figure 40. Mapping of locations within COLM where amphibians were observed by Platenberg and 

Graham (2003); it should be noted that some data points are offset slightly to reveal overlap. Key: 

T=tadpoles, M=metamorphs, and D=dead

Reptile Richness

The NPS (2014) lists 17 reptile species as occurring at COLM, with one additional species likely to 

occur but currently unconfirmed (Table 61). Platenberg and Graham (2003) confirmed the presence 
198

of seven lizard and three snake species during the inventory effort at COLM in 2002. During the 

2014 seeps and springs survey, Lamm et al. observed four reptile species within the park.

Table 61. Reptiles documented or expected to occur in COLM.

Scientific Name Common Name

NPS 

(2014)

Platenberg 

and Graham 

(2003)

Lamm et al. 

(2014)

Aspidoscelis tigris septentrionalis plateau tiger whiptail X X

Aspidoscelis velox plateau striped whiptail X X X

Coluber constrictor North American racer U

Coluber taeniatus striped whipsnake X X

Crotalus oreganus concolor midget faded rattlesnake X X

Crotaphytus collaris eastern collared lizard X X

Gambelia wislizenii long-nosed leopard lizard X

Hypsiglena chlorophaea loreala Mesa Verde nightsnake X X

Lampropeltis triangulum milksnake X

Pantherophis emoryi Great Plains ratsnake X

Phrynosoma hernandesi greater short-horned lizard X

Pituophis catenifer gophersnake X

Sceloporus graciosus graciosus northern sagebrush lizard X X X

Sceloporus tristichus plateau fence lizard X X

Tantilla hobartsmithi

Smith's black-headed 

snake X

Thamnophis elegans terrestrial gartersnake X X

Urosaurus ornatus wrighti northern tree lizard X X

Uta stansburiana uniformis plateau side-blotched lizard X X X

U = unconfirmed

Reptile Abundance

There are no detailed abundance data for reptiles at this time. General abundance descriptions are 

provided in the NPS species list for COLM (Table 62).
199

Table 62. Reptiles included in the NPS species list with abundance (NPS 2014).

Scientific Name Common Name Abundance

Aspidoscelis tigris septentrionalis plateau tiger whiptail Common

Aspidoscelis velox plateau striped whiptail Common

Coluber constrictor North American racer Unconfirmed

Coluber taeniatus striped whipsnake Uncommon

Crotalus oreganus concolor midget faded rattlesnake Unknown

Crotaphytus collaris eastern collared lizard Common

Gambelia wislizenii long-nosed leopard lizard Rare

Hypsiglena chlorophaea loreala Mesa Verde nightsnake Rare

Lampropeltis triangulum milksnake Unknown

Pantherophis emoryi Great Plains ratsnake Unknown

Phrynosoma hernandesi greater short-horned lizard Uncommon

Pituophis catenifer gophersnake Uncommon

Sceloporus graciosus graciosus northern sagebrush lizard Common

Sceloporus tristichus plateau fence lizard Common

Tantilla hobartsmithi Smith's black-headed snake Unknown

Thamnophis elegans terrestrial gartersnake Uncommon

Urosaurus ornatus wrighti northern tree lizard Uncommon

Uta stansburiana uniformis plateau side-blotched lizard Common

Reptile Distribution

Reptiles can be found throughout COLM. Platenberg and Graham (2003) used GIS to record the 

locations where reptiles were observed during the herpetofauna inventory survey effort in 2002 

(Figure 41).
200

Figure 41. Mapping of locations within COLM where reptiles were observed by Platenberg and Graham 

(2003; it should be noted that some data points are offset slightly to reveal overlap).

Threats and Stressor Factors

There are several factors that are a concern to herptiles at COLM. Roadway mortality, habitat loss, 

climate change, disease, drought, radiation, visitor/human impact, and possible bull frog (Lithobates 

catesbeianus) invasion were of primary concern to park resource managers.
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The indirect effects that roadways have on herpetofauna have been poorly studied; much of the 

research on this topic has been dedicated to mammalian and avian species (Jochimsen et al. 2004). 

Nocturnal reptiles frequently use roadways for thermal heating, resulting in an increased likelihood 

of mortality. Roads often serve as a boundary between habitat types, sometimes separating breeding 

areas from foraging areas (Patla 1997), and fragmenting normally continuous habitats. Furthermore, 

certain species may use roads as corridors for movement increasing their risk of vehicular strike. 

Snakes and lizards are frequently struck by motor vehicles as they are slow-moving and difficult to 

see as they cross roadways. Roads are also corridors that provide a pathway for exotic/invasive 

species to become established in new areas. Seabrook and Dettmann (1996) observed that the roads 

and trails across Australia allowed for the range expansion of an introduced toad species. The 

fragmentation of habitat by roads is thought to have contributed to altered distribution patterns in 

reptiles (Rudolph et al. 1998), lower recolonization rates and increased extinction risks in local 

reptile populations (Vos and Chardon 1998), and lowered species richness in snakes (Kjoss and 

Litvaitis 2001).

The loss and fragmentation of habitat poses one of the largest threats to herptile populations 

(Cushman 2006). The potential negative impacts of habitat loss from fire-fuel removal methods on 

the distribution, abundance, and diversity of lizards in pinyon-pine woodland habitats was studied at 

COLM over a 10-year period by James and M’Closkey (2003) who observed preferential use of 

standing dead trees by both terrestrial and arboreal lizard species in the Colorado Plateau during 

1990, 1992, and 2000. A reduction in dead vegetation, such as standing trees, eliminates this microhabitat feature that lizards, and many other animals, are reliant upon for foraging and cover. The 

lizards included for the study were the side-blotched lizard, common sagebrush lizard, tree lizard, 

and the eastern fence lizard (James and M’Closkey 2003). World-wide amphibian decline has been 

linked with regional changes to the hydrologic landscape that are occurring with global climate 

change (McMenamin et al. 2008). This phenomenon has been documented in Yellowstone National 

Park where amphibian habitat has been reduced due to drought conditions associated with the 

changing climate. The landscape has changed as annual precipitation has decreased while annual 

warm-season temperature has risen; desiccation of wetlands and extreme disruptions to pulse-driven 

biota has caused drastic amphibian declines at the park (McMenamin et al. 2008).

The herptiles of COLM rely on the availability of water and moist soils, especially amphibians. 

Potholes where water collects are used as foraging sites by reptiles. The groundwater supply that 

feeds COLM’s seeps and springs, particularly those in the alluvial valley fill, is strongly influenced 

by annual and seasonal precipitation (Lamm et al. 2014). During droughts, groundwater recharge will 

decline and, in turn, contribute to a decline in seep and spring discharge. Reduced water availability 

will negatively impact the vegetation and wildlife that rely on these sites, potentially reducing 

biodiversity. The opposite weather extremes of heavy precipitation and flooding can also pose a 

threat to seeps and springs (Richard 2004). These events can trigger mudslides, move boulders and 

trees, and erode stream banks, all of which could alter or destroy spring, seep, and tinaja habitats 

(Richard 2004). Heavy precipitation could accelerate erosion of the alluvial valley fill aquifer, 

reducing water storage capacity and potentially eliminating springs or seeps (Lamm et al. 2014).
202

The hotter and drier conditions expected in COLM over the next century will likely exacerbate many 

of the current non-climate stressors of the aquatic and riparian habitats at COLM. A hotter, drier 

environment could increase the rate at which water is lost to evaporation from aquatic and riparian 

habitats, meaning it will be available to plants and wildlife for a shorter time (ClimateWizard 2014, 

Lamm et al. 2014).

The aquatic Batrachochytrium dendrobatidis (Bd), or chytrid fungus, causes chytridiomycosis, a 

lethal skin disease in amphibians that is linked to population declines in many areas of the world, 

including the Rocky Mountain region (Weldon et al. 2004, Hossack et al. 2009). The fungus 

parasitizes the host’s keratinized skin and mouthparts; and is afflicting hundreds of species around 

the world (Kriger 2006). In several locations within the state of Colorado, the fungus has been 

positively identified in amphibians (Olson 2014). The nearest positive sample was in the Kannah 

Creek drainage in Grand Mesa, where 13 out of 39 individuals tested positive. Test conducted on 

specimens collected in 2000 from Echo Canyon had negative results for chytid fungus (Olson 2014). 

Six Woodhouse’s toads and one canyon treefrog (Hyla arenicolor) were tested, however the entire 

sample size is unknown (Olson 2014). Specimen collection specifically for detection of the chytrid 

fungus has not been conducted in COLM.

According to Blaustein et al. (1998), some amphibian species are highly susceptible to the 

deleterious effects of ultraviolet B (UV-B) radiation at the embryonic stage and have had very high 

embryonic mortality rates as a result of exposure. Experiments conducted to assess amphibian 

declines suggested that there are at least three factors that seem to be exacerbated when combined 

with UV-B exposure; pathogenic algae called Saprolegnia ferax (embryos infected with it turn white 

and die before they hatch), low pH, and a polycyclic aromatic hydrocarbon called fluoranthene which 

is a component of petroleum contamination (Blaustein et al. 1998). Whether or not these factors 

could be impacting amphibians at COLM is unknown.

Anthropogenic impacts affect the conditions at COLM in a number of ways. General presence of 

visitors in the park affects wildlife behavior and can also unintentionally alter the landscape. Vehicle 

traffic, discussed below, tends to be a stressor to wildlife because of the noise and collisions, most of 

which are fatal. Foot traffic has long been a source of visitor-caused biological soil crust destruction 

at the park, a natural and crucial component of the ecosystem that is highly fragile (Belnap 2013). 

General human disturbances, such as biological soil crust damage, are likely to have unknown 

negative impacts to amphibian and reptile populations via habitat alteration. The way in which 

visitors use the parks trail system also contributes to habitat fragmentation. The park does not limit 

foot travel to established trails. Several of these trails lead directly to and are located within riparian 

areas. Due to COLM’s high desert environment, water is an attraction for visitors. Visitors entering 

these aquatic habitats can lead to the introduction of contaminants (sunscreen). The social trails also 

lead to trampling of vegetation and increased erosion, which can contribute to loss of habitat.

According to Peterson et al. (2013), the bullfrog is a threat to local native amphibian populations. 

They are transport vectors of deadly amphibian pathogens, including chytrid fungus, and have also 

been connected with general native amphibian declines (Peterson et al. 2013). Bullfrogs are predators 

and competitors of native amphibians. Bullfrogs have been introduced in over 40 countries and have 
203

spread far beyond their native range within North America as well. Bullfrogs are spread by humans, 

often deliberately, but also unintentional introductions have resulted in breeding populations that 

disperse to new aquatic habitats opportunistically. While the potential presence of bullfrogs within 

COLM is currently a data gap, they are a concern to managers.

Other issues that pose a threat to the herptiles within COLM are illegal specimen collection, 

especially collared lizards and midget-faded rattlesnakes. Another threat, primarily along the 

urbanized border of the park, comes from domestic cats, which like to prey on these species.

Data Needs/Gaps

COLM has had only one park-wide herpetological inventory (Platenberg and Graham 2003), which 

was conducted in 2002. This may serve as a baseline, but regular monitoring of herptiles is needed to 

make any assessments on their condition or trends in population or community dynamics. There are 

no data available to assess abundances of any herptiles at this time.

Overall Condition

Species Richness

The project team defined the Significance Level for both amphibian and reptile species richness as a 

3. While current herptile species lists are available, a lack of consistent monitoring over time does 

not allow for assessment of any changes in species richness. COLM’s only park-wide herpetological 

inventory was conducted over a decade ago (Platenberg and Graham 2003) and conditions may have 

changed since that time. Therefore, Condition Levels cannot be assigned.

Species Abundance

The project team defined the Significance Level for amphibian and reptile species abundance as a 2.

Because of a lack of data for this measure, Condition Levels also cannot be assigned.

Species Distribution

The project team defined the Significance Level for amphibian and reptile species distribution as a 1.

Again, due to a significant data gap for this measure, Condition Levels cannot be assigned.

Weighted Condition Score

A Weighted Condition Score for herptiles in COLM was not assigned since the only available data 

are outdated and has no baseline. Rather, the available data (Platenberg and Graham 2003) will serve 

as the baseline for comparison with future monitoring and inventory efforts.
204

Herptiles

Measures Significance Level Condition Level WCS = N/A

Amphibian Richness 3 n/a

Amphibian 

Abundance 2 n/a

Amphibian Distribution 1 n/a

Reptile Richness 3 n/a

Reptile Abundance 2 n/a

Reptile Distribution 1 n/a

4.8.6 Sources of Expertise

This assessment relied on published literature as the primary source of expertise, with review by NPS 

staff.

4.8.7 Literature Cited

Belnap, J. 2013. Cryptobiotic soils: Holding the place in place. 

http://geochange.er.usgs.gov/sw/impacts/biology/crypto/ (accessed 8 August 2014).

Board, B. 2011. A review of historical accounts of amphibians in Colorado National Monument and 

observations from a breeding season in No Thoroughfare Canyon. National Park Service 

Unpublished Report, Fruita, Colorado.

ClimateWizard. 2014. Custom analysis: Change in AET/PET ratio by 2100. Downloadable dataset. 

http://climatewizardcustom.org/ (accessed 23 July 2014).

Cushman, S. A. 2006. Effects of habitat loss and fragmentation on amphibians: A review and 

prospectus. Biological Conservation 128:231-240.

Hossack, B. R., E. Muths, C.W. Anderson, J. D. Kirshtein, and P. S. Corn. 2009. Distribution limits 

of Batrachochytrium dendrobatidis: A case study in the Rocky Mountains, USA. Journal of 

Wildlife Diseases 45:1198-1202.

James, S. E., and R. T. M’Closkey. 2003. Lizard microhabitat and fire fuel management. Biological 

Conservation 114:293-297.
205

Jochimsen, D. M., C. R. Peterson, K. M. Andrews, and J. W. Gibbons. 2004. A literature review 

of the effects of roads on amphibians and reptiles and the measures used to minimize those 

effects: Final Draft. Idaho Fish and Game Department, Boise, Idaho, and USDA Forest 

Service, Aiken, South Carolina.

Kjoss, V. A., and J. A. Litvaitis. 2001. Community structure of snakes in a human-dominated 

landscape. Biological Conservation 98:285-292.

Kriger, K. M. 2006. The ecology of chytridiomycosis in eastern Australia. Thesis. Griffith 

University, Gold Coast, Australia.

Lamm, N., S. Igo, and M. Davlantes, 2014. Report of the 2014 Geocorps springs and seeps 

assessment, Colorado National Monument, Colorado. National Park Service, Fruita, Colorado.

McMenamin,S. K., E. A. Hadly, and C. K. Wright. 2008. Climatic change and wetland desiccation 

cause amphibian decline in Yellowstone National Park. PNAS 105(44):16988-16993.

National Park Service (NPS). 2014. NPSpecies: Information on species in national parks, 

Colorado National Monument. https://irma.nps.gov/NPSpecies/Search/SpeciesList/COLM

(accessed 13 January 2015).

National Park Service (NPS). 2015. Colorado National Monument natural features and 

ecosystems. http://www.nps.gov/colm/naturescience/naturalfeaturesandecosystems.htm

(accessed 13 January 2015).

O’Dell, T., S. Garman, A. Evenden, M. Beer, E. Nance, D. Perry, R. DenBleyker, S. Daw, A. Wight, 

M. A. Powell, and others. 2005. Northern Colorado Plateau Inventory and Monitoring Network, 

Vital Signs Monitoring Plan. National Park Service, Inventory and Monitoring Network, Moab, 

Utah.

Olson, D. 2014. Aquatic Ecology and Management Team Batrachochytrium dendrobatidis (Bd) 

global snapshot map. http://www.bd-maps.net/maps/ (accessed 1 August 2014).

Palta, D. A. 1997. Changes in a population of spotted frogs in Yellowstone National Park 

between 1953 and 1995: The effects of habitat modification. Thesis. Idaho State University,

Pocatello, Idaho.

Platenberg, R., and T. Graham. 2003. Northern Colorado Plateau Network herpetofauna inventory 

2002 annual report. USGS Canyonlands Field Station, Moab, Utah.

Peterson, A. C., K. L. D. Richgels, P. T. J. Johnson, and V. J. McKenzie. 2013. Investigating the 

dispersal routes used by an in invasive amphibian, Lithobates catesbeianus, in human-dominated 

landscapes. Biological Invasions 15:2179-2191.

Richard, G. A. 2004. Flash flooding at the Colorado National Monument, 1921-2003. National Park 

Service, Fruita, Colorado.
206

Rudolph, D. C., S. J. Burgdorf, R. N. Conner, and J. G. Dickson. 1998. The impact of roads on 

the timber rattlesnake (Crotalus horridus) in eastern Texas. Pages 236-239 in Proceedings of 

the international conference on wildlife ecology and transportation. Florida Department of 

Transportation, Tallahassee, Florida.

Seabrook, W. A., and E. B. Dettman. 1996. Roads as activity corridors for cane toads in 

Australia. Journal of Wildlife Management 60:363-368.

Von Loh, J., K. Landgraf, A. Evenden, T. Owens, S. Blauer, and M. Reid. 2007. Vegetation 

classification and mapping project report, Colorado National Monument. Natural Resource 

Technical Report NPS/NCPN/NRTR—2007/061. National Park Service, Fort Collins, 

Colorado.

Vos, C. C., and J. P. Chardon. 1998. Effects of habitat fragmentation and road density on the 

distribution pattern of the moor frog (Rana arvalis). Journal of Applied Ecology 35:44-56.

Weldon, C., L. H. duPreez, A. D. Hyatt, R. Muller, and R. Speare. 2004. Origin of the amphibian 

chytrid fungus. Emerging Infectious Diseases 10(12):2100–2105.
207

4.9 Birds

4.9.1 Description

Bird populations often act as excellent indicators of an 

ecosystem’s health (Morrison 1986, Hutto 1998, NABCI 

2009). Birds are often highly visible components of 

ecosystems, and bird communities often reflect the 

abundance and distribution of other organisms with 

which they co-exist (Blakesley et al. 2010). The unique 

ecosystems and physical formations in COLM provide 

bird species with a wealth of habitat types and food 

sources. Due to COLM’s intact pinyon-juniper (P-J) 

habitats, steep-walled cliffs, and settings that are 

conducive to intensive bird research, the park has been 

recognized by the National Audubon Society as a State 

Important Bird Area (NAS 2013).

COLM has confirmed the presence of more than 160

species of birds, and about 29% of these birds are 

migratory species on their way to breeding grounds in the park or farther north (NPS 2015). Longdistance migratory species are highly informative indicator species, as their overall health depends on 

several different ecosystems. Global Christmas Bird Count (CBC) data indicate significant declines 

in migratory bird numbers in recent years (Peterjohn and Sauer 1999, Vickery and Herkert 2001). 

Nearctic-Neotropic migrants, hereafter Neotropical migrants, are bird species that breed in the 

temperate latitudes of the U.S. and Canada, but migrate to the tropical latitudes of Central and South 

America in the winter months (Figure 42). Stotz et al. (1996) estimates that approximately 420 bird 

species are classified as Neotropical migrants.

Not all of the species found in COLM are traveling to/from their breeding grounds, however, as 

several species breed in the park or maintain year-round populations in the park. Examples of 

common breeding species in COLM include the Gambel’s quail (Callipepla gambelii), rock wren 

(Salpinctes obsoletus), and the gray (Vireo vicinior) and plumbeous vireos (V. plumbeus) (NPS 

2015). Additionally, COLM is home to a large number of resident species (i.e., species that remain in 

the park throughout the year). Examples of some common resident species include the American 

robin (Turdus migratorius), the juniper titmouse (Baeolophus ridgwayi), and the black-billed magpie 

(Pica hudsonia).

4.9.2 Measures

 Summer breeding bird richness

 Year-round bird richness

Photo 13. Gambel's quail (Callipepla 

gambelii) (NPS photo).
208

Figure 42. Zoogeographic regions of the world; shaded areas represent transition areas between regions 

(TPWD 2015).

4.9.3 Reference Conditions/Values

The reference condition for birds in COLM is currently undefined. While NPS (2015) represents the 

park’s certified species list, it is likely that species not included on that list frequent the park. 

Continuation of the Rocky Mountain Bird Observatory (RMBO) monitoring in the park, combined 

with past records of species (including, but not limited to Giroir 2001 and NPS 2015) could be used 

in the future as a reference condition for species richness in the park.

4.9.4 Data and Methods

The NPS Certified Bird Species List (NPS 2015) for COLM was used to both determine the 

confirmed species in the park and to determine residency of species for this assessment; this list 

represents all of the confirmed and probably present bird species in the park (Appendix J). In 

instances where NPS (2015) did not assign residency, the American Ornithologists’ Union and the 

Cornell University Lab of Ornithology’s Birds of North America Online Database 

(http://bna.birds.cornell.edu/bna/) was used to approximate a species’ residency as either breeding, 

migratory, resident, or vagrant. This component’s measures separate species richness discussions for 

breeding birds and for resident (year-round) birds. Species in NPS (2015) that had residency 

designations of “Breeder” and “Resident” are discussed in the summer breeding bird richness 

measure, as NPS (2015) defines breeder as a species that reproduces within the park and resident as a 

species with a year round presence in the park. Only species that had residency designations of 

“Resident” are discussed in the year-round bird richness measure, as this classification refers only to 

species that occur in the park at year round. There will be some degree of overlap between these 

metrics, as resident species will be discussed in both measures. However, this is due to the fact that 

resident species are often breeding species as well and overlap is ultimately inevitable when using 

these two metrics as indicators of condition. While raptor species are also discussed separately in 

Chapter 4.10 of this document, these species are still included in the richness estimates for the 

identified measures of this component.
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Giroir (2001) conducted a breeding bird inventory in COLM during the spring of 2000, and 

represents one of the first comprehensive bird studies to occur within the park. The objective of 

Giroir (2001) was to establish a baseline of breeding bird information for the park, and the author 

utilized distance sampling methodologies (similar to those described in Buckland et al. 1993) to 

sample the population. Traditionally, distance sampling uses both line and point transects; however, 

Giroir (2001) chose to use only point transects as they tend to be the preferred transect type for rough 

terrain (Fancy and Sauer 2000). Twenty-seven transects, each with 10 points on them, were randomly 

chosen within COLM, with replacement random transects being chosen when a location was deemed 

too hazardous. Points were spaced 250 m (820 ft) apart along a transect, and were observed for 5 

minutes each. All species observed (aurally or visually) were recorded.

The RMBO, in a partnership with the NPS, has conducted annual landbird monitoring across the 

NCPN since 2005, with McLaren (2014) representing the most recent publication (covering the 2013 

field season). The surveys conducted provide park managers with long-term trend data for most 

regularly occurring landbird species throughout the NCPN, as each year’s data are pooled to allow 

for more accurate estimates of density and abundance. The RMBO monitoring is habitat-based (i.e., 

only specific habitat types are surveyed), and in COLM, only the P-J habitat type is surveyed. This 

habitat type typically occurs at elevations just above 1,500 m (4,921 ft), and is dominated by pinyon 

pine and juniper species (Juniperus spp.); P-J habitat habitats often contain a significant sagebrush

component as well.

RMBO methodology utilized “...GIS and the Southwest Regional Re-GAP Analysis Project to 

randomly select sites from a pool of habitat ‘stands’ that were large enough to accommodate 

transects (Lowry et al. 2005)” (McLaren 2014, p. 3). Areas with >50% slope were excluded from this 

pool in order to include only areas that could be safely surveyed by foot. Areas that were determined 

to be appropriate stands have been surveyed every year since 2005. Surveys consist of 15-minute 

point counts at each point location on a transect, and each location is spaced approximately 250 m 

(820 ft) apart. Sites have been surveyed twice a summer, and typically occur between one half-hour 

before sunrise and five hours after sunrise (McLaren 2014). In COLM, there are two transects (CPPJ06 and CP-PJ07); each is located in a P-J habitat, and has been surveyed every year of the study. 

Data related to the RMBO surveys of COLM were retrieved from the Rocky Mountain Avian Data 

Center (http://rmbo.org/v3/avian/ExploretheData.aspx).

The Grand Junction CBC falls within COLM boundaries; this CBC is part of the International CBC, 

which started in 1900 and is coordinated internationally by the Audubon Society. Grand Junction’s

CBC has been conducted regularly since 1950, although 3 years of data from the early 1920s also 

exist. During a CBC, multiple volunteers survey a 24-km (15-mi) diameter on one day, typically 

between 14 December and 5 January; the center point of the 24-km (15 mi) diameter count circle for 

the Grand Junction CBC is 39°7’14.9478” N, -108°36’29.25” W (Figure 43). Unlike typical breeding 

bird surveys, the CBC surveys overwintering and resident birds that are not territorial and singing; 

this often results in different survey results than those conducted during the breeding season. The 

total number of species and individuals are recorded each year; data for the Grand Junction CBC is 
210

current through 2013. Counts were completed in 2014; however the data are not yet available 

through the Audubon data retrieval database.

Figure 43. The CBC area that falls within COLM land. The diameter of the count circle is 24-km (15 mi) 

and is surveyed by volunteers each winter.

The organization of the COLM CBC data (obtained from 

http://netapp.audubon.org/CBCObservation/Historical/ResultsByCount.aspx#) required SMUMN
211

GSS to make some adjustments. These adjustments were made to update the data to the currently 

accepted taxonomic standards, and to eliminate duplicate or historic references that were erroneous. 

After the adjustments were made, the data were analyzed and organized for an accurate assessment 

of the survey’s results. An annotated list of all adjustments is provided in Appendix K. The CBC 

samples areas outside the park that contains habitats that are not truly representative of the habitat 

types typical of COLM (e.g., the Colorado and Gunnison Rivers). Because of this, the CBC will 

frequently report observations of species that would not typically occur in the park, notably species 

that associate with riparian areas. Individual observation points are not recorded during the CBC, so 

it is not possible to exclude those species that were observed outside of the park’s boundaries; care 

should be taken when observing the CBC data, as it is highly likely that some species included on the 

CBC list have not been observed within COLM boundaries.

4.9.5 Current Condition and Trend

Summer Breeding Bird Richness

Species richness measures represent a total count of the number of species observed in an area or 

population. For this measure, only the richness of the summer breeding birds in COLM is discussed. 

Breeding birds are defined as species identified with a residency of “Breeder” or “Resident” by NPS 

(2015). As this measure discusses the summer species richness of the park, the CBC data are not 

discussed in this measure.

NPS Certified Bird Species List (NPS 2015)

The NPS Certified Bird Species List contains 161 species, 26 (16%) of which are “Breeders” and 84 

(52%) of which are “Resident” and are discussed in this section (Appendix J). An analysis of annual 

species richness is not possible using these data alone, as no record of when the species was observed 

is recorded.

Giroir (2001)

During one of the first surveys of the bird community of COLM in 2000, Giroir (2001) documented 

60 species that were either breeding species (10 species; 17%) or resident species (50 species; 83%) 

Table 63 identifies the 10 species identified as breeding birds that were observed in COLM in 2000. 

One of the biases of Giroir’s (2001) methodology (and many bird surveys in general) was that 

species that are more likely to be calling or vocalizing during surveys are more likely to be detected. 

Because of this, several species that is less vocal and more reclusive/difficult to see may not have 

been adequately observed or represented in the data. 
212

Table 63. The 10 breeding bird species observed in COLM during Giroir (2001)’s breeding bird point 

counts.

Common Name Scientific Name

black-throated sparrow Amphispiza bilineata

bushtit Psaltriparus minimus

Gambel's quail Callipepla gambelii

golden eagle Aquila chrysaetos

gray vireo Vireo vicinior

mourning dove Zenaida macroura

peregrine falcon Falco peregrinus

plumbeous vireo Vireo plumbeus

prairie falcon Falco mexicanus

rock wren Salpinctes obsoletus

RMBO Landbird Monitoring (2005-present)

The number of summer breeding bird species observed in COLM was variable during RMBO 

monitoring between 2005 and 2014, with the average total number of summer breeding bird species 

observed between the two routes being 36.7. The total number of observed summer breeding species 

was 67, of which 15 were breeders (22%) and 52 were residents (78%). 

Fifty-one different summer breeding bird species were observed on route CP-PJ06 (42 resident 

species, nine breeding species), while 57 species were observed on route CP-PJ07 (45 resident 

species, 12 breeding species). When looking at both routes combined, peak summer breeding species 

richness values were reported in 2005 (46 species), while the lowest species richness values were 

observed in 2013 (30 species) (Figure 44). Route CP-PJ06 reported lower species richness values in 

every year of the RMBO monitoring (Figure 44).

The summer breeding bird richness values observed in 2014 were below average for both routes. In 

fact, both routes reported the lowest species richness value for the duration of the 10-year study 

(Figure 44). The 2014 species richness value for the CP-PJ06 route (18 species) was below the 10-

year average for that route (24 species). The 2014 richness value for the CP-PJ07 route was 24 

species, which was below the 10-year average for that route as well (31.6 species). When species 

richness values from 2014 were combined for both routes in COLM, 31 species were observed in the 

park, which fell below the 10-year average for both routes combined which were 36.7.

There are a few factors that may have influenced the RMBO species richness estimates in COLM. 

RMBO monitoring sites are located in only P-J habitat types, and may miss breeding species that 

occur outside of this habitat zone. Additionally, and as has been previously mentioned, species such 

as raptors that are not highly vocal species during the breeding season are less likely to be observed 

during point counts. The terrain of the point counts may make the observation of these non-vocal 

species difficult, unless the species are flying directly overhead. 
213

Figure 44. Breeding species richness observed on both of the RMBO landbird monitoring routes in 

COLM. Surveys have been conducted annually since 2005, and only report the landbird species 

observed in P-J habitats of the park. Data were retrieved from the Rocky Mountain Avian Data Center 

(http://rmbo.org/v3/avian/ExploretheData.aspx).

Year-Round Bird Richness

NPS Certified Bird Species List (NPS 2015)

The NPS Certified Bird Species List contains 161 species, 84 (52%) of which are “Resident”

(Appendix J). As previously described, an analysis of annual year-round species richness is not 

possible using these data alone, as no record of when the species was observed is recorded.

Giroir (2001)

Giroir (2001) observed 50 resident species (as defined by NPS 2015) during surveys of COLM in 

2000 (Appendix J). Giroir (2001) also indicated that surveys took place in order to coincide with the 

peak of singing for species that frequent the P-J habitat. Because of this, several species that begin 

their breeding and singing cycles earlier in the year (e.g., western-scrub jay, common raven [Corvus

corax], and juniper titmouse) may not have been accurately represented in the data.

RMBO Landbird Monitoring (2005-present)

Year-round species richness has fluctuated during RMBO landbird monitoring in COLM, with 

richness estimates ranging between 22 species (2013) and 36 species (2005, 2011) (Figure 45). The 

average species richness estimate for year-round landbird species, with both routes combined, was 

29.4 species. The CP-PJ07 route has had higher species richness during every year of the RMBO 

monitoring (Figure 45), and has averaged 24.9 year-round species/year compared to route CP-PJ06’s 

19.1 year-round species/year. 

0

5

10

15

20

25

30

35

40

45

50

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Number of Summer Breeding Birds

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CP-PJ06

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Total Species Richness
214

Figure 45. Number of year-round bird species observed on both survey routes in COLM’s P-J habitat 

during RMBO landbird monitoring from 2005-2014. Species classified as either resident, migratory, or 

vagrant by NPS (2015) are included in the richness values of this figure. Data related to the RMBO 

surveys of COLM were retrieved from the Rocky Mountain Avian Data Center 

(http://rmbo.org/v3/avian/ExploretheData.aspx).

Perhaps somewhat concerning is the fact that the two most recent surveys in the park (2013 and 

2014) have produced the lowest estimates of species richness for both routes (Figure 45). Overall 

species richness estimates in 2014 (25 species) for COLM fell below the 10-year average for the park 

(29.4), as did each individual route’s species richness estimate (CP-PJ06: 15 compared to 19.1 

species; CP-PJ07: 19 compared to 24.9 species).

Grand Junction Christmas Bird Count

The Grand Junction, CO CBC represents the most continuous source of bird data in the COLM 

region, with counts occurring almost every year from 1950-present (counts also exist from 1922-24, 

and 1945). The CBC methodology is an example of an index count, which is a methodology that 

tallies the number of bird detections during surveys of points, transects, or other defined regions 

(Kendeigh 1944, Verner 1985, Bibby et al. 1992, Ralph et al. 1995, Rosenstock et al. 2002). Index 

counts quantify bird species’ distribution, occurrence, habitat relationships, and population trends 

(Rosenstock et al. 2002).

The Grand Junction CBC surveys only a portion of COLM (Figure 43), so results from the survey are

not indicative of the species richness trends for resident and overwintering species in the entire park.

Counts such as the CBC (or other index counts, e.g., breeding bird surveys) are neither censuses nor 

density estimates, and results should only be viewed as indices of population size (Link and Sauer 

0

5

10

15

20

25

30

35

40

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Number of Year-Round Species

Year

CP-PJ06

CP-PJ07

Total Species Richness
215

1998). Possible bias of count locations, weather on the day of the count, and the number of observers 

limit the overall usefulness of index count data, and it is often not advisable to estimate overall 

population sizes from these data alone (Link and Sauer 1998); these biases may influence how many 

individuals are observed in a given year, and may potentially explain the annual variation observed in 

species each year. The effects of observer bias are especially apparent in the early years of the Grand 

Junction CBC, when only one observer participated. Additionally, the CBC samples areas and habitat 

types outside the park that are not typical of habitats found within COLM (e.g., Colorado and 

Gunnison Rivers). Because of this, some species identified on the CBC may not be actually utilizing 

COLM lands.

For the duration of the Grand Junction CBC, 76 species of year-round residents were observed 

(Appendix J); the average number of species observed during a count year was 39.8 species. The 

highest number of species observed during a count year occurred in 2004 when 58 species were 

observed, while the lowest species richness value during the CBC was eight species, which was 

recorded in 1924. Many of the historically low species richness estimates for COLM (see 1922-1964) 

occurred during years with only single-digit numbers of observers. The first year to eclipse the 

double-digit observer mark was 1965; the number of species observed each year appeared to coincide 

with the number of observers in a given year (Figure 46).

Figure 46. The number of species observed during each year of the Grand Junction CBC (black, primary 

Y-axis) and the number of participants in the Grand Junction CBC (red, secondary Y-axis) from 1922-

2013. Data retrieved from http://netapp.audubon.org/CBCObservation/Historical/ResultsByCount.aspx#.

0

10

20

30

40

50

60

70

80

90

0

10

20

30

40

50

60

70

Number of Participants

Number of Observed Species

Year

Number of Species

Number of Participants
216

Threats and Stressor Factors

One of the major threats facing bird populations across all habitat types is land cover change 

(Morrison 1986). Land cover change is not restricted to the breeding habitat; many species depend on 

specific migratory and wintering habitat types that are also changing. Altered habitats can also 

compromise the reproductive success or wintering survival rates of species adapted to that habitat.

Migratory bird species face deteriorating habitat conditions along their migratory routes and 

wintering grounds. Most of the birds that breed in the United States winter in the Neotropics 

(MacArthur 1959); deforestation has occurred in these wintering grounds at an annual rate up to 

3.5% (Lanly 1982). While forest and habitat degradation does occur in the United States, it does not 

approach the level of degradation seen in the tropics (WRI 1989). Furthermore, Robbins et al. (1989) 

supported the suggestion that deforestation in the tropics has a more direct impact on Neotropical 

migrant populations than deforestation and habitat loss in the United States.

As urban areas continue to develop and grow, modern alterations to the landscape often foster 

competition between native and non-native bird species. Human-made structures may fragment a 

landscape and reduce the continuity of a landscape, and often as these changes occur, non-native bird 

species are able to inhabit the areas. Marzluff (2001, pp. 26-28) states that, “The most consistent 

effects of increasing settlement were increases in non-native species of birds, increases in birds that 

use buildings as nest sites (e.g., swallows and swifts), increases in nest predators and nest parasites 

(brown-headed cowbirds [Molothrus ater]), and decreases in interior- and ground-nesting species.” 

Another threat facing land bird populations is shifts in the reproductive phenology of land birds, 

which is primarily driven by climate change. Several bird species depend on temperature ranges or 

weather cycles to cue their breeding. As global temperatures change, some bird species have adjusted 

by moving their home ranges north (Hitch and Leberg 2007). Other species have adjusted their 

migratory period and have begun returning to their breeding grounds earlier in the spring (Bradley et 

al. 1999, Inouye et al. 2000, Lane and Pearman 2003, Butler 2003, Murphy-Klassen et al. 2005). For 

example, American robins in the Colorado Rocky Mountains are now returning to their breeding 

grounds 14 days earlier compared to 1981 (NABCI 2009). A concern is that this shift in migration 

may be out of sync with food availability and could ultimately lead to lowered reproductive success.

The North American Bird Phenology Program (BPP) is currently analyzing the migration patterns 

and distribution of migratory bird species across North America (USGS 2008). Information from this 

analysis will provide new insights into how bird distribution, migration timing, and migratory 

flyways have changed since the later part of the 19th century. This information may also be applied to 

estimate changes in breeding initiation periods in specific habitats.

Domestic and feral cats (Felis catus) are one of the largest causes of bird mortality in the United 

States. According to Loss et al. (2012), annual bird mortality caused by outdoor cats is estimated to 

be between 1.4 and 3.7 billion individuals. The median number of birds killed by cats was estimated 

at 2.4 billion individuals, and almost 69% of bird mortality due to cat predation was caused by unowned cats (i.e., strays, barn cats, and completely feral cats) (Loss et al. 2012). The relatively close 
217

proximity of COLM to Grand Junction and Fruita likely increases the risk for cat predation, as stray 

and house cats may enter the park and surrounding areas.

Data Needs/Gaps

As was mentioned previously, this assessment did not incorporate the recently published McLaren 

(2015), which summarizes the results of the landbird monitoring in the park during 2014. 

Continuation of the RMBO’s annual landbird monitoring in the park will provide park managers with 

a valuable long-term data set that will accurately depict trends in abundance, density, and richness in 

the P-J habitat of COLM, however the design of this study is done to make inference to the entire 

NCPN set of parks, so if park-specific trend information is desired, more monitoring would need to 

be added. Expansion of the survey methodology to include a variety of habitat types would provide a 

more complete picture of the avifauna of the park as a whole. Additionally, the expansion of survey 

timing would also help managers obtain a better understanding of the trends and status of year-round 

bird species in the park. Current methodology samples the breeding population of the park, and the 

CBC in the area samples the overwintering population, but no survey exists during the spring and fall 

migration period. 

Overall Condition

Summer Breeding Bird Richness

The project team defined the Significance Level for summer breeding bird richness as a 3. Compared 

to the RMBO 10-year average (36.7 species), COLM has had below average summer breeding bird 

richness estimates in recent years. 2013 had the lowest species richness estimate for both routes 

combined, and for the CP-PJ06 route (Figure 44). In 2014, overall species richness slightly increased 

(from 30 to 31 species) but still remained below the 10-year average of 36.7. Both of the routes had 

below average richness values in 2014, and the CP-PJ07 route exhibited the lowest species richness 

estimate that had been observed in the 10 years of RMBO monitoring. 

The Gunnison sage grouse (Centrocercus minimus) is one species absent from the park that 

historically occupied habitats within COLM; however, this species has spatially isolated habitat 

patches across its former range, and has experienced dramatic declines over the past few decades. 

Due primarily to low recent estimates of species richness observed during the RMBO monitoring of 

P-J habitats, the summer breeding bird richness measure was assigned a Condition Level of 2, 

indicating moderate concern.

Year-Round Bird Richness

The project team defined the Significance Level for year-round bird richness as a 3 during project 

scoping. The RMBO landbird monitoring has provided species richness values for year-round 

residents during the breeding season since 2005.Species richness values for resident species steadily 

increased during the CBC efforts in the park, with a peak value reaching 58 species in 2004. Recent 

(2008-2013) species richness values from the CBC in the park have ranged from 46 (2013) to 49 

(2011, 2012) species (Figure 46), which are above the historic average of approximately 40 species. 

As was mentioned previously, the CBC estimates and trends need to be interpreted carefully, as 
218

variations in survey locations and the number of observers can all influence the number of species 

reported each year.

During the RMBO landbird surveys, total species richness values (both routes combined) have 

ranged from 22 (2013) to 36 (2005, 2011) species (Figure 45). While route CP-PJ07 has had higher

species richness values in every year of the study, both routes have experienced the lowest species 

richness estimates of the study during the last 2 years (2013, 2014; Figure 45). 

Despite relatively long-term stability in species richness values for year-round species in COLM, 

recent declining trends in richness are worth mentioning and warrant future monitoring. While it is 

certainly possible that these are simply natural, temporal variations in richness, monitoring may help 

to identify long-term trends or issues. The year-round bird richness measure was assigned a 

Condition Level of 1, indicating low concern.

Weighted Condition Score

The bird’s component was assigned a Weighted Condition Score of 0.5, indicating a current 

condition of moderate concern. A stable trend arrow was assigned to the component, although there 

is some minor evidence that the trend may be declining as is evidenced by recent declines in 

abundance observed during RMBO efforts.
219

Birds

Measures Significance Level Condition Level WCS = 0.50

Summer Breeding 

Birds Richness 3 2

Year-Round Bird 

Richness 3 1

4.9.6 Sources of Expertise

Dusty Perkins, Program Manager, Northern Colorado Plateau Network

4.9.7 Literature Cited

Blakesley, J. A., D. C. Pavlacky Jr., and D. J. Hanni. 2010. Monitoring bird populations in Wind 

Cave National Park. Technical Report M-WICA09-01. Rocky Mountain Bird Observatory, 

Brighton, Colorado.

Bibby, C. J., N. D. Burgess, and D. A. Hill. 1992. Bird census techniques. Academic Press, New 

York, New York.

Bradley, N. L., A. C. Leopold, J. Ross, and W. Huffaker. 1999. Phenological changes reflect climate 

change in Wisconsin. Proceedings of the National Academy of Sciences USA 96:9701-9704.

Butler, C. 2003. The disproportionate effect of global warming on the arrival dates of short-distance 

migratory birds in North America. Ibis 145:484-495.

Fancey, S. G., and J. R. Sauer. 2000. Recommended methods for inventorying and monitoring 

landbirds in National Parks. National Park Service unpublished report, Fort Collins, Colorado.

Giroir, G. 2001. Final report on the breeding bird inventory at Colorado National Monument, western 

Colorado. Rocky Mountain Bird Observatory unpublished report, Grand Junction, Colorado.

Hitch, A. T., and P. L. Leberg. 2007. Breeding distributions of North American bird species moving 

north as a result of climate change. Conservation Biology 21(2): 534-539.

Hutto, R. L. 1998. Using landbirds as an indicator species group. Avian conservation: Research and 

management. Island Press, Washington, D.C.

Inouye, D. W., B. Barr, K. B. Armitage, and B. D. Inouye. 2000. Climate change is affecting 

altitudinal migrants and hibernating species. Proceedings of the National Academy of Science 

USA 97:1630-1633.

Kendeigh, S. C. 1944. Measurement of bird populations. Ecological Monographs 14:67-106.
220

Lane, R. K., and M. Pearman. 2003. Comparison of spring return dates of Mountain Bluebirds, Sialia 

currucoides, and Tree Swallows, Tachycineta bicolor, with monthly air temperatures. Canadian 

Field-Naturalist 117:110-112.

Loss, S. R., T. Will, and P. P. Marra. 2012. The impact of free-ranging domestic cats on wildlife of 

the United States. Nature Communications 4:1396.

Lanly, J. P. 1982. Tropical forest resources. FAO Forestry Paper 30. Food and Agriculture 

Organization of the United Nations (FAO), Rome, Italy.

Link, W. A., and J. R. Sauer. 1998. Estimating population change from count data: Application to the 

North American Breeding Bird Survey. Ecological Applications 8(2):258-268.

Lowry, J. H., Jr., R. D. Ramsey, K. Boykin, D. Bradford, P. Comer, S. Falzarano, W. Kepner, J. 

Kirby, L. Langs, J. Prior- Magee, and others. 2005. Southwest Regional Gap Analysis Project: 

Final report on land cover mapping methods. Logan, Utah. 

http://earth.gis.usu.edu/swgap/swregap_landcover_report.pdf (accessed 15 May 2015). 

MacArthur, R. H. 1959. On the breeding distribution pattern of North American migrant birds. Auk 

76:318-325.

Marzluff, J. M. 2001. Worldwide urbanization and its effects on birds. Pages 19-47 in Marzluff, J. 

M., R. Bowman, and R. Donnelly (Eds.). Avian ecology in an urbanizing world. Kluwer 

Academic Publishers, Norwell, Massachusetts.

McLaren, M. 2014. Landbird monitoring in the Northern Colorado Plateau Network: 2013 field 

season. Natural Resource Technical Report NPS/NCPN/NRTR—2014/890. National Park 

Service, Fort Collins, Colorado. 

McLaren, M. 2015. Landbird monitoring in the Northern Colorado Plateau Network: 2014 field 

season. Natural Resource Technical Report NPS/NCPN/NRR—2015/974. National Park Service, 

Fort Collins, Colorado.

Morrison, M. L. 1986. Bird populations as indicators of environmental change. Current Ornithology 

3:429-451.

Murphy-Klassen, H. M., T. J. Underwood, S. G. Sealy, and A. A. Czyrnyj. 2005. Long-term trends in 

spring arrival dates of migrant birds at Delta March, Manitoba, in relation to climate change. The 

Auk 122(4):1130-1148.

National Park Service (NPS). 2015. NPSpecies: Information on species in national parks. 

https://irma.nps.gov/NPSpecies/Search/SpeciesList/COLM (accessed 16 May 2015).

North American Audubon Society (NAS). 2013. Audubon important bird areas: Colorado National 

Monument site profile. http://netapp.audubon.org/IBA/Site/477 (accessed 3 June 2015).
221

North American Bird Conservation Initiative, U.S. Committee (NABCI). 2009. The State of the 

Birds, United States of America, 2009. U.S. Department of the Interior, Washington, D.C.

Peterjohn, B. G., and J. R. Sauer. 1999. Population status of North American grassland birds. Studies 

in Avian Biology 19:27-44.

Ralph, C. J., J. R. Sauer, and S. Droege. 1995. Monitoring bird populations by point count. General 

Technical Report PSW-149. U.S. Forest Service, Pacific Southwest Research Station, Albany, 

California.

Robbins, C. S., J. R. Sauer, R. S. Greenberg, and S. Droege. 1989. Population declines in North 

American birds that migrate to the Neotropics. Proceedings of the National Academy of Sciences 

of the United States of America 86(19) 7658-7662.

Rosenstock, S. S, D. R. Anderson, K. M. Giesen, T. Leukering, and M.F. Carter. 2002. Landbird 

counting techniques: Current practices and an alternative. The Auk 119(1):46-53.

Stotz, D. F., F. W. Fitzpatrick, T. A. Parker III, and D. K. Moskovits. 1996. Neotropical birds: 

Ecology and conservation. University of Chicago Press, Chicago, Illinois.

Texas Parks & Wildlife Department (TPWD). 2015. Nearctic-Neotropical migrants. 

http://www.tpwd.state.tx.us/huntwild/wild/birding/migration/migrants/nn_migrants/ (accessed 15 

April 2015).

U.S. Geological Survey (USGS). 2008 North American bird phenology program. 

(http://www.pwrc.usgs.gov/bpp/about.cfm). Accessed 11 May 2015.

Verner, J. 1985. Assessment of counting techniques. Current Ornithology 2:247-302.

Vickery, P. D. and J. R. Herkert. 2001. Recent advances in grassland bird research: Where do we go 

from here? Auk 118: 11-15.

World Resources Institute (WRI). 1989. World Resources 1988-89. Basic Books, New York, New 

York.
222

4.10 Raptors

4.10.1 Description

Raptors are top-level predators and are 

excellent bioindicators of the health of their 

associated ecosystem (Morrison 1986, Hutto 

1998). In the 1940s, raptor populations across 

North America experienced a substantial 

population decline due to the use of 

organophosphates (e.g., 

dichlorodiphenyltrichloroethane – DDT) as 

insecticides. Bioaccumulation of these 

chemicals (particularly DDE, a persistent 

metabolite of DDT) inhibited calcium 

metabolism in many raptor species (Fischer 2000). DDT magnified though the food chain, and more 

chemicals were concentrated within apex predators than in other animals within the same 

environment (Connell 1999). As a result, affected birds laid eggs that were too thin for successful 

incubation; eggs that did not break during incubation often contained dead embryos, and mortality 

rates for hatchlings were high (Ratcliffe 1993, Fischer 2000).

DDT was banned in the United States in December 1972 and reproductive success rates subsequently 

increased following this ban (Fischer 2000). Species especially affected by the use of 

organochlorines, such as the peregrine falcon (Falco peregrinus), experienced a dramatic population 

recovery following the ban. The peregrine falcon populations in the continental United States 

rebounded to over 2,000 breeding pairs in 2002 (White et al. 2002, as cited in USFWS 2003), and the 

Colorado population of peregrine falcons was estimated to have increased tenfold in the 35 years 

following the ban on DDT. The COLM population of peregrine falcons served as a refuge for the 

species during this decline, and was utilized as part of the range-wide captive breeding and 

reintroduction effort (Hartwig, written communication, 4 August 2015). These affected raptor species 

recovered to population levels that allowed for their removal from the Endangered Species List (the 

peregrine falcon was delisted in 1999) (USFWS 2003).

The many diverse habitats of COLM (e.g., canyon walls, sagebrush shrublands, and montane 

shrublands) can support a variety of different raptor species. The canyon walls of COLM are of 

particular importance to nesting prairie (Falco mexicanus) and peregrine falcons. In addition to the 

prairie and peregrine falcons, common raptor species in COLM include the red-tailed hawk, golden 

eagle, northern pygmy owl (Glaucidium gnoma), and the turkey vulture (Cathartes aura). 

Due to COLM’s intact pinyon-juniper habitats, steep-walled cliffs, and settings that are conducive to 

intensive bird research, the park has been recognized by the National Audubon Society as a State 

Important Bird Area (NAS 2013). Monitoring of these apex level avian predators will provide park 

managers with not only a current understanding of the health of the raptor population, but also a 

snapshot into the overall health of the ecosystems and microhabitats that they frequent.

Photo 14. Peregrine falcon (USFWS Photo).
223

4.10.2 Measures

 Raptor richness

 Abundance

 Productivity

 Number of active nest sites

4.10.3 Reference Conditions/Values

The reference condition for raptors in COLM is currently undefined. While NPS (2015) represents 

the park’s certified species list, it is likely that some raptor species included on that list may be rare 

visitors to the park. With no raptor-specific monitoring taking place in the park, it is difficult to 

assess current condition. Additionally, each species of raptor is likely to have variable productivity 

and occupancy requirements that would indicate a stable population (e.g., bald eagles may have 

different productivity/occupancy goals than peregrine falcons). For this assessment, a reference 

condition is not provided, and best professional judgment will be used to assess current condition for 

the metrics that have available data.

4.10.4 Data and Methods

The NPS Certified Bird Species List (NPS 2015) for COLM was used for this assessment; this list 

includes all of the confirmed raptor species present in the park. As this component deals only with 

raptor species, NPS (2015) was adjusted to include only raptor species. For a detailed discussion of 

all bird species, see Chapter 4.9 of this assessment.

The only raptor-specific monitoring project to occur within COLM (Lambeth 1996) occurred in 1994 

and 1995, and focused on monitoring three peregrine falcon nests within the park. Lambeth (1996) 

monitored all peregrine falcon nesting sites on BLM and adjacent lands within the Grand Junction 

District (which included COLM). Sites were monitored beginning in April of 1994 and 1995, and 

observations continued periodically until after fledging occurred, typically in mid-June. 

Outside of Lambeth (1996), no raptor-specific monitoring has been conducted within COLM 

boundaries. However, additional inventories, surveys, and monitoring efforts of all bird species in the 

park have taken place, and raptor species were frequently documented. The results of the studies 

described below have been adjusted to only include raptor species for this assessment.

Giroir (2001) conducted a breeding bird inventory in COLM during the spring of 2000, and 

represents one of the first comprehensive bird studies to occur within the park. The objective of 

Giroir (2001) was to establish a baseline of breeding bird information in the park, and the author 

utilized distance sampling methodologies (similar to those described in Buckland et al. 1993) to 

sample the population. Traditionally, distance sampling uses both line and point transects; however, 

Giroir (2001) chose to use only point transects as they tend to be the preferred transect type for rough 

terrain (Fancey and Sauer 2000). Twenty-seven transects, each with 10 points on them, were 

randomly chosen within COLM, with replacement random transects being chosen when a location 

was deemed too hazardous. Points were spaced 250 m (820 ft) apart along each transect, and were 

observed for 5 minutes each. All species observed (aurally or visually) were recorded. One of the 
224

biases of Giroir’s (2001) methodology (and many bird surveys in general) was that species that are 

more likely to be calling or vocalizing during surveys are more likely to be detected. Because of this, 

several species that are less vocal and more reclusive/difficult to see (e.g., raptors) may not have been 

adequately observed or represented in the data. 

The RMBO, in a partnership with the NPS, has conducted annual landbird monitoring across the 

NCPN since 2005, with McLaren (2014) representing the most recent publication (covering the 2013 

field season). McLaren (2015) was completed and published in 2015, and summarizes the results of 

the 2014 field season. However, this publication was not available during the initial writing of this 

document and has not been incorporated. The surveys conducted provide park managers with longterm trend data for most regularly occurring landbird species throughout the NCPN, as each year’s 

data are pooled to allow for more accurate estimates of density and abundance. The RMBO 

monitoring is habitat-based (i.e., only specific habitat types are surveyed), with these habitats being 

selected due to the fact that they represent distinct bird communities. In COLM, only the P-J habitat 

type is surveyed. This habitat type typically occurs at elevations just above 1,500 m (4,921 ft), and is 

dominated by pinyon pines and juniper species; P-J habitats often contain a significant sagebrush

component as well.

RMBO methodology utilized “...GIS and the Southwest Regional Re-GAP Analysis Project to 

randomly select sites from a pool of habitat ‘stands’ that were large enough to accommodate 

transects (Lowry et al. 2005)” (McLaren 2014, p. 3). Areas with >50% slope were excluded from this 

pool in order to include only areas that could be safely surveyed by foot. Areas that were determined 

to be appropriate stands have been surveyed every year since 2005. Surveys consist of 15-minute 

point counts at each point location on a transect, and each location is spaced approximately 250 m 

(820 ft) apart. Sites have been surveyed twice a summer, typically between one half-hour before 

sunrise and five hours after sunrise (McLaren 2014). In COLM, there are two transects (CP-PJ06, 

and CP-PJ07); each is located in a P-J habitat, and has been surveyed every year of the study. As was 

previously mentioned, species such as raptors are not highly vocal species during the breeding season 

and are less likely to be observed during point counts. The terrain of the point counts may make the 

observation of these non-vocal species difficult, unless the species were flying directly overhead.

The Grand Junction CBC falls within COLM boundaries; this CBC is part of the International CBC, 

which started in 1900 and is coordinated internationally by the Audubon Society. The park’s CBC 

has been conducted regularly since 1946, although 3 years of data from the early 1920s also exist. 

During a CBC, multiple volunteers survey a 24-km (15-mi) diameter on one day, typically between 

14 December and 5 January; the center point of the 24-km (15-mi) diameter count circle for the 

Grand Junction CBC is 39°7’14.9478” N, -108°36’29.25” W (Figure 47). Unlike typical breeding 

bird surveys, the CBC surveys overwintering and resident birds that are not territorial and singing; 

this results in different survey results than those conducted during the breeding season. The total 

number of species and individuals are recorded each year; data for the Grand Junction CBC is current 

through 2013. Counts were completed in 2014; however the data are not yet available through the 

Audubon data retrieval database.
225

Figure 47. The CBC area that falls within COLM land. The diameter of the count circle is 24-km (15 mi) 

and is surveyed by volunteers each winter.

4.10.5 Current Condition and Trend

Raptor Richness

Species richness measures represent a total count of the number of species observed in an area or 

population. For this measure, only the richness of the raptors in COLM is discussed.
226

NPS Certified Bird Species List (NPS 2015)

The NPS Certified Bird Species List contains 161 species, 24 (15%) of which are raptors and are 

discussed in this section (Table 64). This list, however, does not allow for a specific analysis of 

annual species richness, as no yearly data are collected.

Table 64. Raptor species identified on NPS (2015).

Common Names

American kestrel long-eared owl prairie falcon

bald eagle merlin* red-tailed hawk

barn owl* northern goshawk rough-legged hawk*

burrowing owl* northern harrier sharp-shinned hawk

Cooper's hawk northern pygmy-owl Swainson's hawk*

ferruginous hawk* northern saw-whet owl turkey vulture

golden eagle osprey western screech-owl

great horned owl peregrine falcon zone-tailed hawk

*Indicates a species listed as “probably present” in the park.

Giroir (2001)

During one of the first surveys of the bird community of COLM in 2000, Giroir (2001) documented 

60 bird species, seven of which were raptor species. Species classified as raptors made up 

approximately 12% of all bird observations during the study. The seven raptor species identified 

during Giroir (2001) included: American kestrel, golden eagle, northern pygmy owl, peregrine 

falcon, prairie falcon, sharp-shinned hawk, and turkey vulture.

RMBO Landbird Monitoring (2005-present)

RMBO monitoring efforts in COLM have focused on two survey routes, both of which are located in 

P-J habitats. Route CP-PJ06 has had relatively low raptor richness values during the study, with a 

peak raptor richness value of three species occurring in 2011 and 5 years where no raptors were 

observed (2007-2010, 2013; Figure 48). Raptors have been observed on Route CP-PJ07 in every year 

of the surveys, although numbers were also relatively low (Figure 48). Peak richness values for 

raptors on this route (three species) were observed in 2009, 2010, and 2014. The lowest species 

richness for raptors reported during the survey (one species) was in 2013. Overall species richness 

(i.e., number of unique species observed between both routes combined) for the survey peaked at 

four species (Figure 48).
227

Figure 48. Number of raptor species observed on both survey routes in COLM’s pinyon-juniper habitat 

during RMBO monitoring from 2005-2014. Data were retrieved from the Rocky Mountain Avian Data 

Center (http://rmbo.org/v3/avian/ExploretheData.aspx).

Grand Junction Christmas Bird Count

The Grand Junction, CO CBC represents the most continuous source of raptor data in the COLM 

region, with counts occurring almost every year from 1950-present (counts also exist from 1922-24, 

and 1945). The CBC methodology is an example of an index count, which is a methodology that 

tallies the number of bird detections during surveys of points, transects, or other defined regions 

(Kendeigh 1944, Verner 1985, Bibby et al. 1992, Ralph et al. 1995, Rosenstock et al. 2002). Index 

counts quantify bird species’ distribution, occurrence, habitat relationships, and population trends 

(Rosenstock et al. 2002).

The Grand Junction CBC surveys only a portion of COLM (Figure 47), so results from the survey are

not indicative of the raptor species richness trends for the entire park. Counts such as the CBC (or 

other index counts, e.g., breeding bird surveys) are neither censuses nor density estimates, and results 

should only be viewed as indices of population size (Link and Sauer 1998). Possible bias of count 

locations and the number of observers limit the overall usefulness of index count data, and it is often 

not advisable to estimate overall population sizes from these data alone (Link and Sauer 1998); these 

biases may influence how many individuals are observed in a given year, and may potentially explain 

the annual variation observed in species each year. The effects of observer bias may be especially 

apparent in the early years of the Grand Junction CBC, when only one observer participated.

For the duration of the Grand Junction CBC, 22 species of raptors were observed (Table 65); the 

average number of raptor species observed during a count year was 10 species. The highest number 

0

1

2

3

4

5

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Number of raptor species

Year

CP-PJ06

CP-PJ07

Total Species Richness
228

of raptor species observed during a count year occurred in 2000 and 2004 when 18 species were 

observed, while the lowest raptor species richness value during the CBC was one species, which was 

recorded in 1924 and 1945. Many of the historically low species richness estimates for COLM (see 

1922-1964) occurred during years with only single-digit numbers of observers. The first year to 

eclipse the double-digit observer mark was 1965; the number of species observed each year appeared 

to coincide with the number of observers in a given year (Figure 49).

Table 65. Raptor species observed during the Grand Junction CBC from 1922-2013.

Common Name

American kestrel northern pygmy-owl

bald eagle northern saw-whet owl

barn owl peregrine falcon

Cooper's hawk prairie falcon

ferruginous hawk red-shouldered hawk

golden eagle red-tailed hawk

great horned owl rough-legged hawk

long-eared owl sharp-shinned hawk

merlin Swainson's hawk

northern goshawk turkey vulture

northern harrier western screech-owl
229

Figure 49. The number of raptor species observed during each year of the Grand Junction CBC (black, 

primary axis) and the number of participants in the Grand Junction CBC (red, secondary Y-axis) from 

1922-2013. Data retrieved from 

http://netapp.audubon.org/CBCObservation/Historical/ResultsByCount.aspx#.

Abundance

Giroir (2001)

Of the seven raptor species observed during Giroir (2001), the turkey vulture was the most abundant 

with 11 individuals being observed along six transects throughout the park (Table 66; Giroir 2001). 

Golden eagles (five individuals), peregrine falcons (five individuals), and American kestrels were all 

observed more than once during Giroir (2001).

Table 66. Raptor abundance observed in COLM in 2000 during Giroir (2001). n=number of individuals, 

k=number of transects a species was detected on.

Species n k

turkey vulture 11 6

sharp-shinned hawk 1 1

golden eagle 5 5

American kestrel 3 2

prairie falcon 1 1

peregrine falcon 5 4

northern pygmy-owl 1 1

0

10

20

30

40

50

60

70

80

90

0

2

4

6

8

10

12

14

16

18

20

Number of Observers

Number of Raptor Species

Year

Number of Species

Number of Participants
230

RMBO Landbird Monitoring (2005-present)

RMBO monitoring efforts in the pinyon-juniper habitats of COLM resulted in 83 individual raptors 

being observed between 2005 and 2014. Of the two routes surveyed in COLM, route CP-PJ07 had 

the highest abundance estimates, with 69 individuals observed. The peak abundance values for this 

route were reported in 2010, when 15 individuals were observed (Figure 50). The lowest raptor 

abundance value for route CP-PJ07 was reported in 2013, when only two individuals were observed.

Figure 50. Number of raptor individuals observed on both survey routes in COLM’s pinyon-juniper habitat 

during RMBO monitoring from 2005-2014. Data were retrieved from the Rocky Mountain Avian Data 

Center (http://rmbo.org/v3/avian/ExploretheData.aspx).

Route CP-PJ06 had much lower abundance values, with only 14 individuals being observed between 

2005 and 2014. The highest number of individuals observed in a year was in 2011, when three 

raptors were observed. There were 5 years where no raptors were observed on route CP-PJ06 (2007-

2010, 2013).

Grand Junction Christmas Bird Count

Average raptor abundance during the Grand Junction CBC was 142.57 individuals/year. The highest 

number of individuals observed in a count year occurred in 2000, when 332 individual raptors were 

observed. The lowest number of raptors observed during a count year was five, which occurred twice 

(1922, 1945), although both of these counts had only single-digit numbers of participants (Figure 51). 

The most abundant species during the CBC was the American kestrel, which was recorded an 

average of 45.85 observations/year. Other frequently observed raptor species during the Grand 

Junction CBC included the red-tailed hawk (32.89 observations/year), western screech-owl 

0

2

4

6

8

10

12

14

16

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Number of raptor individuals

Year

CP-PJ06

CP-PJ07

Total Abundance
231

(Megascops kennicotti) (13.54 observations/year), and the northern harrier (Circus cyanus) (13.42 

observations/year) (Table 67).

Figure 51. The number of individuals observed during each year of the Grand Junction CBC (black, 

primary Y-axis) and the number of participants in the Grand Junction CBC (red, secondary Y-axis) from 

1922-2013. Data retrieved from 

http://netapp.audubon.org/CBCObservation/Historical/ResultsByCount.aspx#.

0

10

20

30

40

50

60

70

80

90

0

50

100

150

200

250

300

350

Number of observers

Number of raptor individuals

Year

Number of Individuals

Number of Participants
232

Table 67. Average annual raptor abundance during the Grand Junction CBC from 1922-1924, 1945, 

1950, and 1952-2013. Data have not been standardized by the number of CBC observers per year and 

should be interpreted with caution. Data retrieved from 

http://netapp.audubon.org/CBCObservation/Historical/ResultsByCount.aspx#.

Common Name Avg. # of Ind./Year

American kestrel 45.85

red-tailed hawk 32.89

western screech-owl 13.54

northern harrier 13.42

bald eagle 7.08

sharp-shinned hawk 6.72

Cooper's hawk 6.26

golden eagle 4.98

prairie falcon 2.49

great horned owl 2.35

merlin 1.68

long-eared owl 1.16

barn owl 1.03

ferruginous hawk 0.91

northern goshawk 0.83

peregrine falcon 0.57

rough-legged hawk 0.55

red-shouldered hawk 0.31

northern pygmy-owl 0.11

turkey vulture 0.06

northern saw-whet owl 0.03

Swainson's hawk 0.03

CBC results from the last 5 years (2009-2013) indicate similar trends as those observed for the 

duration of the CBC (Table 68). Red-tailed hawks continued to be the most abundant species in the 

Grand Junction area (82.6 individuals/year), with American kestrels and western screech-owls also 

being frequently observed. Species that were observed historically but were absent in the last 5 years 

included: long-eared owl (Asio otus), barn owl (Tyto alba), red-shouldered hawk (Buteo lineatus), 

northern pygmy-owl, turkey vulture, and the Swainson’s hawk.
233

Table 68. Raptor species abundance during the last 5 years (2009-2013) of the Grand Junction CBC. 

Average yearly abundance was calculated using only the 5 years of data presented in the table, and total 

abundance represents the sum of all individuals of a species observed over the 5 years.

Species 2009 2010 2011 2012 2013

Average 

Yearly 

Abundance

Total 

Abundance

red-tailed hawk 94 68 86 88 77 82.6 413

American kestrel 56 89 70 59 55 65.8 329

western screech-owl 33 33 54 64 52 47.2 236

bald eagle 49 11 16 9 27 22.4 112

northern harrier 40 14 13 17 13 19.4 97

Cooper's hawk 18 18 22 11 27 19.2 96

sharp-shinned hawk 16 14 19 13 12 14.8 74

great horned owl 4 3 11 10 14 8.4 42

golden eagle 3 4 6 6 3 4.4 22

merlin 7 3 3 4 3 4 20

peregrine falcon 2 5 1 0 3 2.2 11

prairie falcon 1 4 3 3 0 2.2 11

rough-legged hawk 2 1 1 1 2 1.4 7

ferruginous hawk 3 0 1 0 0 0.8 4

northern goshawk 1 0 0 1 0 0.4 2

northern saw-whet owl 0 0 1 0 0 0.2 1

Total Yearly Abundance 179 110 151 139 156 1,477

Productivity

Raptor productivity can be reported many ways, often depending upon the species of interest. For 

example, Ambrose et al. (2008) reported productivity for peregrine falcons as the number of 

nestlings per total and successful pairs, while Postupalski (1974) defined productivity for bald eagles 

as the number of fledglings or large young per occupied nest. Similarly, the reference conditions for 

the minimum productivity levels to support a raptor population are also variable and understudied. 

According to data collected pre-1955 and post-1985 (Hickey and Anderson 1969; Enderson and 

Craig 1974; Radcliffe 1993; USFWS 2003), a healthy peregrine falcon population typically has nest 

success rates of 45-66%. For bald eagles, a nesting success rate of 50% and 0.7 young per occupied 

nest has been suggested for bald eagle populations to maintain themselves (Tetreau 1998). Because 

of the variability observed in productivity requirements for different raptor species, a specific 

reference condition is likely not broadly applicable for this measure.

Only one study has occurred within COLM that has documented raptor productivity (Lambeth 1996), 

and this study was specific to peregrine falcons. During Lambeth (1996), peregrine falcon occupancy 

and productivity were observed during the 1994 and 1995 breeding seasons. Three active eyries were 

documented in COLM: Colorado National Monument eyrie (CNM), Ute Canyon eyrie, and No 

Thoroughfare eyrie. From 1994-1995, approximately 14 peregrine falcon chicks fledged from these 

three nest sites. The CNM eyrie fledged two females and one male in both 1994 and 1995. The Ute 
234

Canyon eyrie had four chicks banded in 1994, although these chicks likely did not survive until 

fledgling age (reported as failed in July 1994). In 1995, the Ute Canyon nest fledged two female 

chicks. The No Thoroughfare eyrie fledged two females and one male in both 1994 and 1995.

Prior to the Lambeth (1996) report, the CNM eyrie had been previously observed from 1986-1993, 

and the Ute Canyon eyrie had been observed in 1993. The results of historic monitoring are presented 

in Lambeth (1996), although the methodology and timing of the observations are not indicated. 

Productivity estimates for all eyries in COLM from 1986-1995 are presented in Table 69.

Table 69. Peregrine falcon productivity at three eyries in COLM, with values to the right of the dashed line 

representing productivity estimates observed by Lambeth (1996). An * indicates a re-nesting effort by a 

pair (production of a second nest after the first one failed).

Eyrie 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

CNM Eyrie 2 4 4 2 3* 3 2 2 3 3

Ute Canyon Eyrie 3 ? 2

No Thoroughfare Eyrie 3 3

Number of Active Nest Sites

While there are likely many raptors that nest within the park, only the nest sites of the peregrine 

falcon have been studied in COLM. Lambeth (1996) documented peregrine nest sites in three 

different locations in the park: the CNM eyrie was located just to the southwest of Independence 

Monument, the Ute Canyon eyrie was located in the central portion of Ute Canyon, on the east rim of 

the canyon, and the No Thoroughfare eyrie was located just south of Devils Kitchen in the No 

Thoroughfare Canyon.

Despite the fact that the nesting sites of other raptors have been understudied, COLM likely offers 

important nesting habitats for many species. Counting the number of active nests in a territory, rather 

than all the nests in a territory is crucial, as several species (e.g., bald eagle, golden eagle) may 

construct several alternate nests in a territory. Counting all nests in a territory, rather than only the 

active nests, would yield an incorrect estimate of productivity and occupancy for raptors in the park. 

The tall cliffs of COLM provide excellent nesting platforms for species such as the peregrine falcon, 

prairie falcon, red-tailed hawk, and golden eagles. The juniper stands of the park also provide 

potential nesting habitat (or adequate cover for ground nests) for red-tailed hawks, ferruginous 

hawks, and northern harriers. Some species, such as the western screech-owl, prefer the hollowed out 

cavities of dead trees or rock crevices. This measure represents a data gap in the park, and warrants 

future monitoring and investigation.

Threats and Stressor Factors

According to Postovit and Postovit (1987), human activities impact raptors in at least three ways: 1) 

by directly harming (physically) or killing eggs, young, or adults; 2) by altering raptor habitats; and 

3) by disturbing or disrupting normal raptor behavior. Recreational activities often result in incidental 

disturbance to raptors, and in COLM one such activity is rock climbing. Rock climbing has the 

potential to have severe impacts on nesting raptors, even if the climbers do not directly come into 
235

contact with the nest site or nesting birds (Richardson and Miller 1997). The shouting, yelling, or 

other disruptive noises produced by climbers may be loud enough to flush nesting raptors from the 

nest (Call 1979, Ratcliffe 1980); even short periods away from eggs or nestlings could cause nest 

failure in many species (Suter and Joness 1981, Richardson and Miller 1997). The ferruginous hawk 

and peregrine falcon, both commonly observed species in COLM, are known to abandon nests if 

exposed to nearby rock climbing or human activity (Snow 1972, Olsen and Olsen 1980, White and 

Thurow 1985). Furthermore, Boeker and Ray (1971) found that human disturbances were the 

primary cause of 85% of nesting losses for golden eagles. Careful monitoring of the raptor nests in 

areas of high recreational use will be critical to observe potential trends in occupancy or productivity 

in nearby nesting raptors.

Data Needs/Gaps

As was mentioned previously, this assessment did not incorporate the recently published McLaren 

(2015), which summarizes the results of the landbird monitoring in the park during 2014. Annual 

monitoring of the raptor population of COLM is needed to assess this component’s current condition. 

Currently, no data exist relating specifically to raptor richness, abundance, productivity, or the 

number of active nest sites in the park. Some bird studies have taken place in the park and have 

documented raptor presence. However, these studies have not focused on raptors specifically, and 

monitoring methodology (and timing) may have certain biases that make detecting raptors more 

difficult. A monitoring program dedicated to the park’s raptor population, and that samples during 

the breeding, migration, and winter seasons, would allow for a more complete assessment of 

condition for this resource. 

Overall Condition

Raptor Richness 

The project team defined the Significance Level for raptor richness as a 3. NPS (2015) identifies 24 

raptor species as either present or probably present in the park; this list can only be used as a 

checklist for comparison as the list is not the direct result of one specific field-based study. No 

raptor-specific monitoring effort has taken place in COLM (outside of limited productivity monitored 

by Lambeth [1996] from 1994-95), but two studies of the bird community in COLM have taken place 

during the breeding season in the past two decades. Giroir (2001) sampled the avifauna of COLM 

exclusively during the breeding season and documented seven raptors. RMBO monitoring efforts in 

COLM have focused on the pinyon-juniper habitats during the breeding season from 2005-2014. 

Between the two routes, RMBO staff observed seven different raptor species in the park, with yearly 

combined species richness peaking at four species (Figure 48). Many of the historically low species 

richness estimates for COLM (see 1922-1964) occurred during years with only single-digit numbers 

of observers.

RMBO monitoring results have been relatively low when looking at raptors only, but this may be due 

in part to sampling biases that exist in the survey methodology, as has been previously discussed. 

However, there is limited recent and long-term data and assessment of current condition and trends 

would likely be speculative at best. Because of this, the Condition Level for raptor richness in COLM 

was determined to be unknown.
236

Abundance

The abundance measure was assigned a Significance Level of 2 during project scoping. While Giroir 

(2001) and RMBO monitoring have produced some raptor abundance statistics, the surveys were not 

specific to raptors, and utilized a methodology that made it difficult for raptor species to be observed 

(i.e., raptors are not highly vocal, and transects were in areas where only raptors directly overhead 

would be observed). Because of this, raptor abundance levels were low during the two studies.

Although a good deal of data exists from the Grand Junction CBC, there are inherent biases that exist 

in the survey’s methodology that makes assessment of current condition problematic. The Grand 

Junction CBC surveys only a portion of COLM (Figure 47), so results from the survey are not 

indicative of the abundance trends for all raptor species, individual count points, or the entire park. 

Count locations and the number of observers limit the overall usefulness of index count data, and it is 

often not advisable to estimate overall population sizes (i.e., abundance) from these data alone (Link 

and Sauer 1999); these biases may influence how many individuals are observed in a given year, and 

may potentially explain the annual variation observed in species each year. 

Two of the five most abundant raptor species observed on the Grand Junction CBC exhibited rangewide declines when comparing breeding bird survey (BBS) data from 1966-2010 (Sauer et al. 2011). 

The American kestrel experienced a population decline of approximately 1.5% per year from 1966-

2010, which resulted in a cumulative population decline of 48% over that time period (Sauer et al. 

2011). The northern harrier declined 0.8% per year, and experienced a population decline of 30% 

over the same time period (Sauer et al. 2011). Conversely, the red-tailed hawk, which was the most 

abundant raptor during CBC efforts, has increased in population size over the same period and has 

expanded much of its range in North America (Sauer et al. 2011). Until raptor abundance is more 

closely monitored in COLM, neither a Condition Level nor a current trend can be assigned. 

Productivity 

Productivity was assigned a Significance Level of 3 by COLM and NPS managers. Outside of some 

peregrine falcon nest monitoring efforts in the late 1980s and early 1990s, there has not been any 

active monitoring of raptor productivity in the park. The canyon walls, pinyon juniper forests, and 

shrublands of the park likely provide critical nesting habitat for many of the raptor species in the 

park. How productivity is monitored for each species often varies; however, some sort of monitoring 

protocol is needed in the park in order to assess the current condition of this resource. Because of this 

data gap, a Condition Level was not assigned to this measure.

Number of Active Nest Sites 

The number of active nest sites in COLM was assigned a Significance Level of 3 during project 

scoping. Outside of Lambeth (1996) there has been no project that documented the number of active 

nesting sites in the park. Lambeth (1996) only focused on nesting peregrine falcons; there are 

numerous other raptor species in the park that nest in a variety of habitats. Until these nesting sites 

are documented, a Condition Level cannot be assigned to this measure.
237

Weighted Condition Score

A Weighted Condition Score was not assigned to the Raptors measure due to a lack of data for three 

of the four specified measures. Similarly, a trend designation was also not made. Until data are 

collected that specifically relates to abundance, productivity, and the number of active nest sites, the 

current condition of this resource is unable to be determined.

Raptors

Measures Significance Level Condition Level WCS = N/A

Abundance 2 n/a

Raptor Richness 3 n/a

Productivity 3 n/a

Number of Active Nest 

Sites 3 n/a

4.10.6 Sources of Expertise

This assessment relied on published literature as the primary source of expertise, with review by NPS 

staff.

4.10.7 Literature Cited

Ambrose, R. E., C. Florian, J. Burch, and M. Flamme. 2008. American peregrine falcon (Falco 

peregrinus anatum) monitoring along the Upper Yukon River in Yukon-Charley Rivers National 

Preserve, Central Alaska Network: 2008 report. Natural Resource Technical Report 

NPS/CAKN/NRTR—2008/138. National Park Service, Fort Collins, Colorado.

Bibby, C. J., N. D. Burgess, and D. A. Hill. 1992. Bird census techniques. Academic Press, New 

York, New York.

Boeker, E. L., and T. D. Ray. 1971. Golden eagle population studies in the Southwest. Condor 

73:463-467.

Buckland, S. T., D. R. Anderson, K. P. Burnham, and J. L. Laake. 1993. Distance sampling: 

Estimating abundance of biological populations. Chapman and Hall, London. 

Call, M. 1979. Habitat management guide for birds of prey. Technical Note 338, U.S. Bureau of 

Land Management, Washington, D.C.
238

Connell, D., P. Lam, B. Richardson, and R. Wu. 1999. Introduction to ecotoxicology. Blackwell 

Science Ltd, Oxford, United Kingdom. 

Enderson, J. H., and J. Craig. 1974. Status of the peregrine falcon in the Rocky Mountains in 1973. 

The Auk 91: 727-736. 

Fancey, S. G., and J. R. Sauer. 2000. Recommended methods for inventorying and monitoring 

landbirds in National Parks. National Park Service unpublished report, Fort Collins, Colorado.

Fischer, R. A. 2000. Bald eagle recovery efforts at Corps of Engineers projects. EMRRP Technical 

Notes Collection (ERDC TN-EMRRP-SI-16), U.S. Army Engineer Research and Development 

Center, Vicksburg, Mississippi.

Giroir, G. 2001. Final report on the breeding bird inventory at Colorado National Monument, western 

Colorado. Rocky Mountain Bird Observatory unpublished report, Grand Junction, Colorado.

Hickey, J. J., and D. W. Anderson. 1969. The Peregrine Falcon: Life history and population 

literature. Pages 3-42 in Peregrine falcon populations: their biology and decline. J. J. Hickey, ed. 

University of Wisconsin Press, Madison, Wisconsin. 

Hutto, R. L. 1998. Using landbirds as an indicator species group. Avian conservation: Research and 

management. Island Press, Washington, D.C.

Kendeigh, S. C. 1944. Measurement of bird populations. Ecological Monographs 14:67-106.

Lambeth, R. 1996. Peregrine falcon monitoring: Grand Junction BLM district. Unpublished report, 

U.S. Bureau of Land Management, Grand Junction, Colorado.

Link, W. A., and J. R. Sauer. 1998. Estimating population change from count data: Application to the 

North American Breeding Bird Survey. Ecological Applications 8(2):258-268.

Lowry, J. H., Jr., R. D. Ramsey, K. Boykin, D. Bradford, P. Comer, S. Falzarano, W. Kepner, J. 

Kirby, L. Langs, J. Prior- Magee, and others. 2005. Southwest Regional Gap Analysis Project: 

Final report on land cover mapping methods. Logan, Utah. 

http://earth.gis.usu.edu/swgap/swregap_landcover_report.pdf (accessed 15 May 2015). 

McLaren, M. 2014. Landbird monitoring in the Northern Colorado Plateau Network: 2013 field 

season. Natural Resource Technical Report NPS/NCPN/NRTR—2014/890. National Park 

Service, Fort Collins, Colorado. 

McLaren, M. 2015. Landbird monitoring in the Northern Colorado Plateau Network: 2014 field 

season. Natural Resource Technical Report NPS/NCPN/NRR—2015/974. National Park Service, 

Fort Collins, Colorado.

Morrison, M. L. 1986. Bird populations as indicators of environmental change. Current Ornithology 

3:429-451.
239

National Park Service (NPS). 2015. NPSpecies: Information on species in national parks, 

Colorado National Monument. https://irma.nps.gov/NPSpecies/Search/SpeciesList/COLM

(accessed 16 May 2015).

North American Audubon Society (NAS). 2013. Audubon important bird areas: Colorado National 

Monument site profile. http://netapp.audubon.org/IBA/Site/477 (accessed 3 June 2015).

Olsen, J., and P. Olsen. 1980. Alleviating the impact of human disturbance on the breeding peregrine 

falcon II. Public and recreational lands. Corella 4:54-57.

Postovit, H. R., and B. C. Postovit. 1987. Impacts and mitigation techniques. Pages 183-208 in 

Federal raptor management techniques manual. National Wildlife Federation, Washington, D.C.

Postupalsky, S. 1974. Raptor reproductive success: Some problems with methods, criteria and 

terminology. Raptor Research Report 2:21-31.

Ralph, C. J., J. R. Sauer, and S. Droege. 1995. Monitoring bird populations by point count. General 

Technical Report PSW-149. U.S. Forest Service, Pacific Southwest Research Station, Albany, 

California.

Ratcliffe, D. A. 1980. The peregrine falcon. Buteo books, Vermillion, South Dakota.

Ratcliffe, D. A. 1993. The peregrine falcon. T & A Poyser Ltd., London, England.

Richardson, C. T., and C. K. Miller. 1997. Recommendations for protecting raptors from human 

disturbance: A review. Wildlife Society Bulletin 25(3):634-638.

Rosenstock, S. S, D. R. Anderson, K. M. Giesen, T. Leukering, and M.F. Carter. 2002. Landbird 

counting techniques: Current practices and an alternative. The Auk 119(1):46-53.

Sauer, J. R., J. E. Hines, J. E. Fallon, K. L. Pardieck, D. J. Ziolkowski, Jr., and W. A. Link. 2011. 

The North American Breeding Bird Survey, results and analysis 1966 - 2010. Version 

12.07.2011 USGS Patuxent Wildlife Research Center, Laurel, Maryland.

Snow, C. 1972. Habitat management series for endangered species. Rep. No. 1. American peregrine 

falcon and Arctic peregrine falcon. U.S. Bureau of Land Management, Washington D.C.

Suter, G. W. II, and J. L. Joness. 1981. Criteria for golden eagle, ferruginous hawk, and prairie falcon 

nest site protection. Raptor Research 15:12-18.

Tetreau, M. 1998. Bald eagle surveys on the coast of Kenai Fjords National Park, 1997 and 1998. 

Kenai Fjords National Park, Project Number KEFJ-N-107.0. National Park Service, Seward, 

Alaska.

U.S. Fish and Wildlife Service (USFWS). 2003. Monitoring plan for the American Peregrine Falcon, 

A species recovered under the Endangered Species Act. U.S. Fish and Wildlife Service, 
240

Divisions of Endangered Species and Migratory Birds and State Programs, Pacific Region, 

Portland, Oregon.

Verner, J. 1985. Assessment of counting techniques. Current Ornithology 2:247-302.

White, C. M., N. J. Clum, T. J. Cade and W. G. Hunt. 2002. Peregrine falcon (Falco peregrinus). In

The birds of North America, No. 660. The Academy of Natural Sciences, Philadelphia, and the 

American Ornithologists' Union, Washington, D.C.

White, C. M., and T. L. Thurow. 1985. Reproduction of ferruginous hawks exposed to controlled 

disturbance. Condor 87:14-22.
241

4.11 Small Mammals

4.11.1 Description

Small mammals are important as prey items for 

predatory birds, herpetofauna, and other 

mammals, and also as influential members of 

the ecological communities where they occur 

(Cook et al. 2006). Small mammals can directly 

affect successional dynamics in their habitats 

by feeding on plants and insects at various 

intensities, depending on their abundance and 

composition (Cook et al. 2006). 

Determining what constitutes a small mammal 

versus a medium to large mammal is somewhat 

loosely defined. Merrit (2010) defined “small” 

to include all mammals weighing less than 5 kg 

(11 lbs). Since this criterion is rather arbitrary 

in nature, there is room for inclusion of a 

mammal that may reach a slightly heavier 

weight. Typical small mammals found in 

COLM include rabbits, squirrels, rats, mice, 

bats, chipmunks, gophers, shrews, weasels, and 

skunks (Photo 15). North American porcupines 

(Erethizon dorsatus) are also included, but tend 

to range in weight from 5kg to 11.5 kg (11 lbs 

to 25 lbs), which will be the largest of the small 

mammal included here (Roze 2009). Bats are 

also considered small mammals; however they 

are not discussed in this section, as they are 

discussed in depth in Chapter 4.15 of this 

report. 

4.11.2 Measures

 Species richness

 Abundance

 Distribution

Photo 15. Desert cottontail (top) (Anna Davis, 

SMUMN GSS), Ord’s kangaroo rat (middle), and 

deer mouse (bottom) are all examples of small 

mammals found in COLM (NPS Photos).
242

4.11.3 Reference Conditions/Values

The reference condition for small mammals consists of data collected by Miller (1964). Data in this 

report include species observed, relative abundance, and general descriptions of where each type of 

mammal was most often observed and where there were successful collections.

4.11.4 Data and Methods

Miller (1964) conducted mammal sampling in the park in 1961 and 1962. The purpose was to 

document and catalog the extent of mammals that inhabited the park and to describe their ecological 

distributions (Miller 1964). Sampling was conducted at 30 sites during the two year period and notes 

were recorded on the site area, vegetation association, elevation, and the sample dates. Sampling was 

accomplished though the trapping and shooting of specimens. Traps including museum special traps, 

Victor rat traps, and mouse traps were set in lines intended to cross-section the area’s major habitat 

types and were set approximately 2.4-3.0 m (8-10 ft) apart (Miller 1964). 

Miller (1980) compiled a list of mammal species that occur in COLM as well as some species that 

are likely to occur in the park due to known species ranges or existence of suitable habitat. This list 

was later revised by Armstrong (1988). While not mammal field surveys or studies, they were 

compilations of information from natural history reports and anecdotal accounts of mammal 

observations. Armstrong (1988) also provided some details on where species were usually observed 

and the general abundance of each species. This list includes all mammals, but for the purposes of 

this assessment, the larger and winged mammals were excluded.

NPS (2015) contains a list of species that have been confirmed within the park or have overlapping 

geographic ranges and suitable habitat in the park, and therefore probably occur.

4.11.5 Current Condition and Trend

Species Richness

The NPS Certified Species List (2015) lists a total of 28 small mammal species that are either 

confirmed as occurring within the park (20), probably present (6) or unconfirmed (2). Miller (1964) 

confirmed 21 small mammal species occurring within the park. Miller (1980) identified 21 species 

occurring within the park and four that hypothetically could occur in the park. Armstrong (1988) 

identified 22 species within COLM and another six species outside park boundaries but nearby. A 

comparison to the NPS certified species list (NPS 2015) is shown in Table 70.
243

Table 70. The species of small mammals, (excluding bats) that have been documented or may occur in 

COLM. 

Scientific Name Common Name

Miller 

(1964)

Miller 

(1980)

Armstrong

(1988)

NPS 

(2015)

Ammospermophilus leucurus white-tailed antelope squirrel X X X X

Bassariscus astutus ringtail X X X X

Cynomys leucurus white-tailed prairie dog X X X U

Dipodomys ordii Ord's kangaroo rat X X X X

Erethizon dorsatus North American porcupine X X X X

Lepus californicus black-tailed jackrabbit X X X X

Lepus townsendii white-tailed jackrabbit X X X X

Marmota flaviventris yellow bellied marmot X X

Mephitis mephitis striped skunk X X X X

Microtus longicaudus long-tailed vole H Z P

Mus musculus house mouse X X X X

Mustela frenata long-tailed weasel X X

Neotoma cinerea bushy-tailed woodrat X X X X

Neotoma lepida desert woodrat H Z

Neotoma mexicana Mexican woodrat X X X X

Notiosorex crawfordi Crawfords' desert shrew P

Onychomys leucogaster northern grasshopper mouse H Z P

Perognathus flavescens plains pocket mouse X X X X

Peromyscus boylii brush mouse P

Peromyscus crinitus canyon mouse X X X X

Peromyscus maniculatus deer mouse X X X X

Peromyscus truei pinyon mouse X X X

Reithrodontomys megalotis western harvest mouse X X X X

Spermophilus lateralis golden-mantled ground squirrel H Z U

Spermophilus variegatus rock squirrel X X X X

Spilogale gracilis western spotted skunk X X X X

Sylvilagus audubonii desert cottontail X X X X

Tamias minimus least chipmunk X X Z P

Tamias rufus Hopi chipmunk X X

Thomomys bottae Botta's pocket gopher H Z P

X = confirmed, U = unconfirmed, P=probably present, H=hypothetically occurs, Z = not documented 

in COLM, but nearby

Abundance

Knowing the abundances of small mammals is useful for assessing the ecological health of the park 

since they are a primary food source and can directly influence the population dynamics of many 

other fauna (Cook 2001). Data regarding the abundance of small mammals in COLM is very limited. 

Miller (1964) is used as the reference condition, and other than the certified species list (NPS 2015), 

the other report that was used for comparison was Armstrong (1988). Though not a field study, it 
244

does contain information on abundance. According to Miller (1964), 14 species were common or 

abundant and six species were uncommon or rare. The NPS (2015) lists the abundance of most small 

mammals as “unknown”; only one species is considered common, one uncommon, and one rare. A 

comparison is shown in Table 71.

Table 71. General abundance information for small mammals in COLM.

Scientific Name Common Name Miller (1964) Armstrong (1988) NPS (2015)

Ammospermophilus 

leucurus

white-tailed antelope 

squirrel

uncommon fairly common unknown

Bassariscus astutus ringtail common possibly common unknown

Cynomys leucurus white-tailed prairie dog rare frequent at lower 

elevations

unknown

Dipodomys ordii Ord's kangaroo Rat common abundant unknown

Erethizon dorsatus North American 

porcupine

common common unknown

Lepus californicus black-tailed jackrabbit common common most years uncommon

Lepus townsendii white-tailed jackrabbit common uncommon most years rare

Marmota flaviventris yellow bellied marmot - uncommon unknown

Mephitis mephitis striped skunk uncommon common unknown

Mus musculus house mouse common (only 

near buildings)

common unknown

Mustela frenata long-tailed weasel - reported increasingly 

since 1981

unknown

Neotoma cinerea bushy-tailed woodrat common common unknown

Neotoma mexicana Mexican woodrat common common unknown

Perognathus 

flavescens

plains pocket mouse uncommon common unknown

Peromyscus crinitus canyon mouse common common unknown

Peromyscus 

maniculatus

deer mouse abundant abundant unknown

Peromyscus truei pinyon mouse abundant common unknown

Reithrodontomys 

megalotis

western harvest mouse common common unknown

Spermophilus 

variegatus

rock squirrel very common fairly common unknown

Spilogale gracilis western spotted skunk uncommon fairly common unknown
245

Table 71 (continued). General abundance information for small mammals in COLM.

Scientific Name Common Name Miller (1964) Armstrong (1988) NPS (2015)

Sylvilagus audubonii desert cottontail abundant frequently common; 

fluctuates

common

Tamias minimus least chipmunk uncommon undocumented unknown

Tamias rufus Hopi chipmunk - abundant unknown

Distribution

The distribution of small mammals within the park has not been assessed since Miller (1964), which 

serves as both the reference condition as well as the only source describing distributions of the listed 

mammal species in the park (Table 72). Current condition and trend is not available and is considered 

a data gap. Surveying the park to determine the distribution of small mammals would be useful for 

many of the same reasons abundances are useful.

Table 72. General description of small mammal distributions relative to the parks area (Miller 1964).

Scientific Name Common Name Distribution

Lepus californicus black-tailed jackrabbit lower elevations, but also throughout the park areas

Lepus townsendii white-tailed jackrabbit higher abundances at 2km (6500 ft) and above, but distributed 

throughout the park

Sylvilagus audubonii desert cottontail throughout the park

Dipodomys ordii Ord's kangaroo rat areas with deep sandy soils

Perognathus 

flavescens 

plains pocket mouse areas with sparse vegetation and loose, sandy soils, possibly 

dependent on prickly pear

Mus musculus house mouse observed only in employee residences sporadically as 

imported with human activities; a permanent population was 

suspected in the warehouse

Neotoma cinerea bushy-tailed woodrat throughout the park

Neotoma mexicana Mexican woodrat throughout the park, but most found in piñon-juniper

Peromyscus crinitus canyon mouse rocky areas

Peromyscus 

maniculatus

deer mouse throughout the park

Reithrodontomys 

megalotis

western harvest mouse sparsely vegetated areas with sandy soils

Ammospermophilus 

leucuru

white-tailed antelope 

squirrel

lower elevations preferred, greasewood-saltbrush-sagebrush 

flats

Tamias minimus least chipmunk wide altitudinal distributions, recorded from 2 to 3.8 km (6500 

to 12500 feet)
246

Table 72 (continued). General description of small mammal distributions relative to the parks area (Miller 

1964).

Scientific Name Common Name Distribution

Spermophilus 

variegatus

rock squirrel throughout the park, but most found in piñon-juniper

Erethizon dorsatus North American 

porcupine

populated canyon floors and rim communities where 

coniferous forest was most dense

Bassariscus astutus ringtail rocky canyons and canyon rims

Spilogale gracilis western spotted skunk most observed near canyon rims and near the camping area

Mephitis mephitis striped skunk most sightings occurred near the camping area; frequently 

caught dumpster diving

Threats and Stressor Factors

Several factors were identified by park natural resource managers that are considered threats or 

stressors to the small mammal populations and habitats at COLM. Vehicle traffic and roadway 

mortality, regional climate change and drought, feral and domestic cats, disease, and habit loss were 

the primary threats expressed by park resource managers.

Road traffic poses a potential threat to the small mammals of COLM. NPS staff observed a high 

number of small mammal fatalities along park roadways each year (Hartwig, written communication, 

14 August 2015). The effects of roadways have also been the topic of many research studies

(Jochimsen et al. 2004). While species react differently to the presence of roads, some mortality in 

small mammals is expected to occur. Observations suggest that species active during the day are 

likely more vulnerable to road mortality at the park, as traffic volumes are higher than at night 

(Hartwig, written communication, 14 August 2015). Some small mammals actually favor the unique 

habitat in road rights-of-way (Adams and Geis 1983), which may increase their risk of being struck 

by vehicles. In addition to direct mortality, roads can fragment habitat, restrict animal movements, 

and provide a vector for the introduction of exotic species (Bissonette and Rosa 2009). 

Drought can have adverse effects on small mammals. Regional climate change may impact the 

ranges of small mammals (Moritz et al. 2008). In response to global warming, certain species may 

expand their range to higher elevations to compensate for the temperature change, leading to a shift 

in community composition (Moritz et al. 2008). Damage to desert habitats during severe droughts 

can be catastrophic when combined with regional increases in anthropogenic activities such as 

livestock grazing, energy exploration and developments, and certain types of recreational activities 

(USGS 2007). The Upper Colorado River Basin, where the park is located, has been experiencing 

increases in these anthropogenic activities, and others, while simultaneously being one of the driest 

regions in the U.S. (USGS 2007). These factors make protected areas, such as COLM, important 

habitat areas for small mammal communities and the wildlife that rely upon them (USGS 2007). 

Even within a protected area such as COLM, losses of nitrogen-fixing organisms and flora often 

result when drought periods become extensive due to increased temperatures and drier conditions 

that are associated with global climate change (USGS 2007). The ecosystem processes within COLM 
247

are highly dependent on the structural and functional services of various grasses, lichens, and 

biological soil crusts; damage to these key ecosystem components can negatively impact small 

mammals, as many are reliant on them for food and habitat (USGS 2007).

Feral cats are considered a threat to small mammals and, in some scenarios, have been implicated in 

numerous wildlife extinctions (Loss et al. 2013). Feral cats likely prey on small mammals at COLM, 

particularly near the eastern urban boundary. According to Loss et al. (2013), feral cats have 

substantial, negative impacts on various wildlife species and may require controls to reduce their 

impact. The estimate of mammal mortalities caused by feral cats annually is between 6.8 and 20.7 

billion, with differences between landscape types (Loss et al. 2013). The findings indicated that 75-

100% of the prey taken by feral cats consist of native species, even in areas where non-native 

counterparts are the dominant taxa (Loss et al. 2013).

Sylvatic plague is a concern to park management since it can infect many species of mammals, 

including humans. The plague is a bacterial (Yersinia pestis) disease spread by fleas and infects 

various wild rodent species (USGS 2013). Several small mammals are likely susceptible to plague, 

including chipmunks (Tamias spp.) and prairie dogs (Cynomys spp.). Prairie dogs are especially 

susceptible to plague; prairie dog colonies in some regions have been completely wiped out by 

plague with an estimated ≥90% mortality rate (USGS 2013). COLM’s prairie dog population is 

thought to be extirpated, likely due to plague (Hartwig, written communication, 14 August 2015). 

Another disease of concern is tularemia, caused by the bacteria Francisella tularensis. This disease 

occurs naturally in rodents and lagomorphs (e.g., rabbits) and can be transmitted to a variety of other 

vertebrates, including humans (OIE 2008).

Porcupines were once abundant in COLM. Wildlife reports dating back to the 1940’s cite the 

presence of porcupines and that the evidence of their activity could be found throughout the park 

(Smith 1941, Finch 1942). In fact, in his 1942 wildlife report, Finch noted that “...these animals are 

becoming more numerous, or more correctly, are becoming thick” (Finch 1942 p. 2). A wildlife 

distribution study of COLM in the 1960’s reported that the majority of the porcupine population was 

located in the canyon floors and rim communities (Miller 1964). Miller (1964) based this on the 

frequency of sight records and porcupine sign in these more dense coniferous forest areas. Miller 

(1964) noted that porcupines had caused extensive damage to pinyon pines in many locations 

throughout the park. Miller (1964) also noticed annual fluctuations in the porcupine population. 

During this period, the Protection Division was authorized to control porcupines in certain locations 

within the park (Miller 1964). During the period 1960-1964 approximately 80 porcupines were killed 

along Rim Rock Drive (Miller 1964). Miller (1964) recommended that the porcupine reduction 

policy be evaluated periodically, as to determine the validity of controlling the porcupine population 

on the basis that they are not compatible with the pinyon pine. Miller (1964) suggested an alternative 

control method where only porcupines found in the immediate vicinity of developments, such as the 

residential and visitor center areas should be eliminated. Miller (1964) further stated that the 

“indiscriminate killing of porcupines over the entire length of the Rim Rock Drive does not presently 

appear to be necessary or desirable as a continuous practice” (Miller 1964 p. 74).
248

Current records of the presence of porcupines within COLM could not be found, with the exception 

of Miller (1980), Armstrong (1988), and NPS (2015). Miller (1980) noted that porcupines were 

present within COLM, while Armstrong (1988) noted they were present and common. NPSpecies 

lists porcupines as present, but the abundance is unknown (NPS 2015). Porcupine or porcupine sign 

have not been reported to park staff in recent memory (Hartwig, written communication, 19 

November 2015). Road kill is a normally a good indicator of the presence of porcupine, but park staff 

have not observed or received any reports of porcupines being struck by vehicles (Hartwig, written 

communication, 19 November 2015). There appears to be growing evidence and concern that, similar 

to the prairie dog, porcupines were once abundant but are no longer present within COLM. Further 

study would be needed to confirm this assumption.

A major threat to small mammal communities, as well as other wildlife, is loss of suitable habitat. 

Habitat loss can occur by fragmentation, disturbances (natural and anthropogenic), and regional 

climate changes. Fragmentation is often caused by land developments such as roadway construction, 

urban development, recreation, grazing, and energy exploration and development; all of these 

activities are occurring around the park boundaries.

Habitat loss and fragmentation contributed to the significant decline in prairie dog populations during 

the 20th century (Antolin et al. 2002). According to Miller (1964), the white tailed prairie dog had 

once been present in COLM. Miller (1964) interviewed a former park employee that described 

colonies of white tailed prairie dogs that occurred near the west entrance and along the Redlands 

Road during the 1940s. Surveys found abandoned colonies near the east entrance and one road-kill 

specimen was obtained within COLM on Rim Rock Drive (Miller 1964). Miller (1964) suspected 

soil depth and precipitation may have been limiting factors in the lack of white tailed prairie dog 

presence in COLM at that time (1958-1962). However, Armstrong and Rector (1988) described the 

white tailed prairie dog presence in the park as “frequent at lower elevations”; unfortunately, the 

details as to precise localities was not included for the time period of this particular observation. 

According to NPS (2015), the species is currently “unconfirmed” within COLM. NPS staff believes 

they are extirpated from the park (Hartwig, written communication, 14 August 2015). Five prairie 

dogs were observed at one colony near White Rocks in 1991; other former colonies appeared 

abandoned (Rodgers 1991). When the colonies were revisited in 2003, no prairie dogs or signs of 

activity were located (Rodgers 2003).

Data Needs/Gaps

Small mammal species richness, abundance, and distribution have been briefly and anecdotally 

documented by Miller (1964) and Armstrong and Rector (1988); these data sources are now 

outdated. The establishment of a routine small mammal survey that could document species richness, 

abundance, and distribution would provide managers with meaningful information that can be used 

to assess the condition of small mammals in the future. This survey, or a similar one, could establish 

whether the North American porcupine has been extirpated from the park.
249

Overall Condition

Species Richness

The species richness measure was assigned a Significance Level of 3. Outside of the NPS Certified 

Species List (NPS 2015), only two outdated sources of data are available (Miller 1964, Armstrong 

and Rector 1988); there are no recent data available to assess the overall condition or determine any 

trends. Because of this data gap, a Condition Level cannot be assigned at this time.

Abundance

This measure was assigned a Significance Level of 3. Recent data regarding the abundance of small 

mammals within COLM are not available for comparison with the reference condition (Miller 1964), 

which is outdated. Due to this data gap a Condition Level could not be assigned to this measure.

Distribution

A Significance Level of 2 was assigned to the distribution measure. No data are available on the 

distribution of small mammals within COLM specifically; Miller (1964) has some distribution 

descriptions of small mammal ranges and notes where species have been observed in the park. Since 

there are only outdated, generalized information regarding distributions, a Condition Level could not 

be assigned.

Weighted Condition Score

A Weighted Condition Score was not calculated for this component since there are no recent data 

available for the selected measures. Until data becomes available for these three measures, the 

current condition and trends in small mammal populations in COLM cannot be assessed. 

Small Mammals

Measures Significance Level Condition Level WCS = N/A

Species Richness 3 n/a

Abundance 3 n/a

Distribution 2 n/a

4.11.6 Sources of Expertise

This assessment relied on published literature as the primary source of expertise, with review by NPS 

staff.
250

4.11.7 Literature Cited

Adams, L. W., and A. D. Geis. 1983. Effects of roads on small mammals. Journal of Applied 

Ecology 20:403-415.

Antolin, M. F., P. Gober, B. Luce, D. E. Biggins, W. E. Van Pelt, D. B. Seery, M. Lockhart, and M. 

Ball. 2002. The influence of sylvatic plague on North American wildlife at the landscape level, 

with special emphasis on black-footed ferret and prairie dog conservation. Pages 105-127 in

Transactions of the 67th North American Wildlife and Natural Resources Conference. Wildlife 

Management Institute, Washington, D.C.

Armstrong, D. M. 1988. Annotated checklist of mammals of Colorado National Monument, Mesa 

County, Colorado. National Park Service, Fruita, Colorado.

Bissonette, J. A., and S. A. Rosa. 2009. Road zone effects in small-mammal communities. Ecology 

and Society 14(1):27.

Cook, R. P., K. M. Boland, and T. Dolbeare. 2006. Inventory of small mammals at Cape Cod 

National Seashore with recommendations for long-term monitoring. Technical Report 

NPS/NER/NRTR—2006/047. National Park Service, Boston, Massachusetts.

Cook, R. P. 2001. Small mammals, big role. Cape Cod National Seashore newspaper article. National 

Park Service, Boston, Massachusetts.

Fahrig, L., and T. Rytwinski. 2009. Effects of roads on animal abundance: An empirical review and 

synthesis. Ecology and Society 14(1):21.

Finch, B. 1942 Annual wildlife report for Colorado National Monument, 1942. National Park 

Service, Fruita, Colorado.

Jochimsen, D. M., C. R. Peterson, K. M. Andrews, and J. W. Gibbons. 2004. A literature review 

of the effects of roads on amphibians and reptiles and the measures used to minimize those 

effects: Final Draft. Idaho Fish and Game Department, Boise, Idaho, and USDA Forest 

Service, Aiken, South Carolina.

Loss, S. R., T. Will and P. Marra. 2013. The impact of free-ranging domestic cats on wildlife of the 

United States. Nature Communications 4:1396.

Merritt, J. F. 2010. The biology of small mammals. The John’s Hopkins University Press, Baltimore, 

Maryland. 

Miller, P. H. 1964. The ecological distribution of mammals in Colorado National Monument, Mesa 

County, Colorado. Thesis. Oklahoma State University, Stillwater, Oklahoma.

Miller, P. H. 1980. A list of Colorado National Monument mammals. National Park Service, Fruita, 

Colorado.
251

Moritz, C., J. L. Patton, C. J. Conroy, J. L. Parra, G. C. White, and S. R. Bessinger. 2008. Impact of a 

century of climate change on small-mammal communities in Yosemite National Park, USA. 

Science 322:261-264.

National Park Service (NPS). 2015. NPSpecies: Information on species in national parks. 

https://irma.nps.gov/NPSpecies/Search/SpeciesList/COLM (accessed 28 January 2015).

Organisation Mondiale de la Sante Animale (OIE). 2008. Tularemia. Pages 361-366 in Terrestrial 

Manual 2008. Organisation Mondiale de la Sante Animale (World Organization for Animal 

Health), Paris, France.

Rodgers, L. 1991. Prairie dog colony survey. National Park Service Unpublished Memo, Colorado 

National Monument, Colorado. 

Rodgers, L. 2003. Prairie dog colony survey. National Park Service Unpublished Memo, Colorado 

National Monument, Colorado.

Roze, U. 2009. The North American porcupine. Cornell University Press, Ithaca, New York. 

Smith, C. 1941. Annual wildlife report for Colorado National Monument, 1941. National Park 

Service, Fruita, Colorado.

U.S. Geological Survey (USGS). 2007. Impacts of climate change on water and ecosystems in the 

Upper Colorado River Basin. U.S. Geological Survey, Reston, Virginia.

U.S. Geological Survey (USGS). 2013. National wildlife health center: Sylvatic plague immunization 

in black-footed ferrets and prairie dogs. 

http://www.nwhc.usgs.gov/disease_information/sylvatic_plague/ (accessed 28 January 2015).
252

4.12 Mountain Lion

4.12.1 Description

The mountain lion (also referred to as cougar, 

puma or panther) is the largest of the wild cat 

species found in Colorado (Photo 16). Male 

lions weigh approximately 68 kg (150 lbs) and 

may be 2.4 m (8 ft) in length (CPW 2015a). 

Females are smaller and weigh on average 42.8 

kg (90 lbs) and are up to 2.1 m (7 ft) in length. 

The body of a mountain lion is covered in short, 

tawny or beige colored fur. The underbody and 

chest are paler or white in color. The mountain 

lion has a distinctive long tail with a black tip. 

Black tips are also found on the ears of 

mountain lions (CPW 2015a).

The mountain lion has an extensive range in areas where terrain and vegetation cover provide access 

to adequate prey populations. Suitable habitat for the mountain lion is found in many parts of 

Colorado, including the western portion of the state where COLM is located (CPW 2015a). 

Indicators of mountain lion presence in COLM were first documented in a 1939 wildlife report (NPS 

1939). The home ranges of individual male mountain lions are greater than those of females (CPW 

2015a). Females typically reproduce every other year beginning at 1 1⁄2 - 2 1⁄2 years of age. Most 

litters are born between May and October and average three kittens (CPW 2015a). The young are 

nursed for approximately two months, then stay with their mother until they are 11-18 months old 

(CPW 2015a).

A staple of the mountain lion’s diet are ungulates, particularly deer. Mountain lions also prey on elk 

and bighorn sheep, as well as a variety of other small mammals such as mice, squirrels, raccoons, or 

rabbits. Livestock (e.g., cattle and sheep) as well as domestic pets may also fall prey to mountain 

lions (CPW 2015a). Classified as a predator, a bounty system was used to control the presence of 

mountain lions throughout the state of Colorado from 1929 through the mid-1960s (Watkins 2004). 

In 1965, the state of Colorado classified the mountain lion as a big game species. At that time, a 

quota system was employed and the collection of harvest data has since been recorded by the 

Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) (Watkins 2004).

4.12.2 Measures

 Abundance

 Distribution

 Reproductive success

4.12.3 Reference Conditions/Values

Reference conditions for the abundance of mountain lions in COLM include historic accounts of 

occurrence documented in the park’s annual wildlife reports from 1939 to 1962 (NPS 1939-1962). 

Photo 16. Mountain lion (NPS photo).
253

The earliest report noted the status of the mountain lion in COLM as “occasionally reported” (NPS 

1939). In each of the subsequent Annual Wildlife Reports available, the number of mountain lions 

was estimated at zero to five individuals. They were considered to be uncommon and only drifting 

through COLM (NPS 1939-1962).

The distribution reference condition for mountain lions in COLM is also based on historical COLM 

wildlife reports (NPS 1939-1962, Miller 1964), which give only general location data. Historical 

sightings occurred at various locations in the park and were not concentrated in any particular areas. 

Again, it should be noted that mountain lions were thought to be passing through COLM 

occasionally as part of their extended territory (NPS 1939-1962). 

The reference condition for reproductive success of mountain lions in COLM is not defined. Very 

little information is available regarding the reproductive success of mountain lions utilizing COLM 

and Miller (1964) stated that “it is unlikely that lions den in the Monument very often”.

4.12.4 Data and Methods

The mountain lion was documented by COLM personnel in summary wildlife reports prepared 

annually or biannually for the park service between 1939 and 1962 (1939, 1941-1951, 1953-1959, 

1962). These reports included occurrence estimates based on mountain lion tracks and actual 

sightings reported by park staff and visitors. The general location of each observation was sometimes 

included. Miller (1964) included a review of COLM wildlife reports dating back to 1938 and 

previously collected specimens, as well as interviews and field connections. No mountain lion 

specimens were collected; however, observation and track set records were summarized.

Armstrong and Rector (1988) completed an annotated checklist of mammals for COLM. This list 

includes a physical description as well as very general information about the distribution of the 

mountain lion. Field recognition signs for the mountain lion were also described including scrapes, 

prey, and the use of rock shelters near brush or woodlands (Armstrong and Rector 1988).

When the mountain lion was reclassified as a big game species in the state, CPW began collecting 

mortality statistics within each Game Management Unit (GMU) (Watkins 2004). These data include 

the number of hunting days, mortality, and sex of harvested lions for GMU 40 where COLM is 

located (Watkins 2004) (Figure 52). GMUs are further grouped into data analysis units (DAUs) to 

address broader management needs; COLM falls within DAU L-22 (Figure 52). A management plan 

for DAU L-22 was released in 2004 (Watkins 2004). This plan includes a summary of

harvest/mortality history, a population estimate, and harvest objectives for the DAU as a whole 

(Watkins 2004). Hunting is not allowed within COLM, but harvest data for the GMU or DAU may 

provide some insight into the status of mountain lions in the region surrounding the park.
254

Figure 52. The location of COLM within GMU 40 and DAU L-22 (CPW 2015b).

4.12.5 Current Condition and Trend

Abundance

Estimating mountain lion abundance is challenging, due to the species’ large home ranges, low 

density, and secretive nature (Watkins 2004). Historical wildlife reports from COLM estimate the 

number of mountain lions in the park between zero and five individuals (NPS 1939-1962). No more 

recent abundance estimates specific to the park are available. According to Watkins (2004), the 

portion of GMU 40 in which COLM is located is likely to be a “high density” mountain lion area 

(4.6 lions/100 km2), due to the presence of favorable habitat (pinyon-juniper and mixed mountain 

shrub) and relatively high prey populations in the area. Given this estimate and the size of COLM 

(<100 km2), it is unlikely that the park could support more than four mountain lions.

Distribution

Historical COLM wildlife reports (NPS 1939-1962) included only general mountain lion distribution 

data and were based on three sightings within the park: in the vicinity of Ute Canyon in 1944, around 

Coke Ovens in 1949, and a visitor sighting on Rim Rock Drive in 1950. Mountain lion tracks were 

also observed in areas adjacent to the park and within COLM near the northwest boundary and in Ute 

Canyon (NPS 1939-1962). Miller (1964) reported 12 observations of mountain lions or tracks within 
255

COLM (Table 73), some of which likely overlapped with the NPS (1939-1962) reports. The only 

more recent information on the distribution of the mountain lion within COLM was the report of a 

distinct print at No Thoroughfare Canyon Alcove Spring in the summer of 2014 (Lamm et al. 2014). 

Park staff receives several unconfirmed reports of mountain lion sightings each year. These sightings 

are often brief encounters of an animal crossing in front of a vehicle or occasional reports of animals 

spotted on trails. These sightings have been reported throughout the park.

Table 73. Locations of historical mountain lion or track observations within COLM, 1938-1962 (Miller 

1964).

Location Date Notes

Mouth of Fruita Canyon May 1938

East Glade Park Rd. September 1942 Chasing two fawns

Black Ridge October 1942

Near Red Canyon November 1944

Fruita Canyon October 1949

Near Artists Point February 1953 Tracks in snow

Near Red Canyon August 1954

50 yds north of Artists Point November 1958 Tracks in snow

Kodels Canyon Early October 1959 Tracks and deer carcass

Lower end of Kodels Canyon Late October 1959 Tracks

3⁄4 mile west of West Glade Park Road on Rim Rock Drive July 1962

Rim Rock Drive at West Glade Park Road junction August 1962 Lying alongside road

The CPW considers the current extent of mountain lion habitat in the state to encompass COLM and 

surrounding lands (Figure 53; Watkins 2004). Since lions are present year round in the park and 

surrounding area, this is most likely the reason why he number of sightings also tends to be higher in 

the higher visitation months when the increased number of visitors provides more opportunities to 

encounter lions.
256

Figure 53. Mountain lion range within the state of Colorado (CPW 2014a).

Reproductive Success

No research was found that can be cited regarding the current reproductive success of the mountain 

lion within the boundaries of COLM or the surrounding area. No mountain lion dens or young have 

ever been reported within park boundaries, but it is possible that they are present.

Threats and Stressor Factors

Hunting outside park boundaries is a potential threat to mountain lions that utilize COLM. Data on 

mountain lion harvest in GMU 40 (Figure 53), which surrounds COLM, was obtained from the CPW 

website (CPW 2014b). Annual harvests between 2002 and 2013 ranged from one to eight mountain 

lions, with an annual mean of 4.7 lions (Table 74).

The predatory nature of mountain lions often leads to conflicts with rural landowners, particularly 

ranchers. Mountain lions using or moving through COLM may prey on the livestock of nearby 

landowners. An annual average of six loss claims were filed in the L-22 mountain lion DAU from 

1995 to 2003 (Watkins 2004). The lion management plan for the L-22 area allows for the removal of 

mountain lions preying on livestock or causing public safety threats. The CPW (2014c) reported that 

on average four mountain lions were killed annually as a result of nuisance in the L-22 area between 
257

2009 and 2014. A longer-term average, from 1989 to 2014, is 1.4 nuisance or “control” kills per year, 

which suggests that nuisance kills may have increased in recent years (CPW 2014c). While a female 

mountain lion suspected of preying upon several domestic sheep was killed by CPW just outside the 

park’s southern boundary, near Glade Park in August 2013, the park has not received or recorded any 

negative mountain lion conflicts with park visitors (Hartwig, written communication 30 January 

2016). The safety of park visitors and mountain lions is a management priority and areas are posted 

when the presence of a mountain lion is reported (Hartwig, written communication, 30 January 

2016).

Table 74. Mountain lion harvest in GMU 40, 2002-2013 (CPW 2014b).

Year Males Females Total

2002 1 3 4

2003 0 4 4

2004 0 1 1

2005 1 0 1

2006 4 0 4

2007 7 1 8

2008 3 1 4

2009 5 2 7

2010 3 1 4

2011 4 3 7

2012 3 4 7

2013 4 1 5

A primary threat to the mountain lion includes the loss of habitat outside of COLM. The growth and 

increasing urbanization of the Grand Junction area is impacting suitable wildlife habitat along park 

boundaries (Evenden et al. 2002, NPS 2005). The result is habitat loss and increased fragmentation, 

which can impair the range and movements of large animals such as the mountain lion. Urban growth 

and development can lead to increased interactions and conflicts between humans and mountain lions 

(Hartwig, written communication, 20 September 2015). This could lead to increased control/removal 

efforts of “nuisance” mountain lions and limited tolerance for the species as a whole.

As a wide-ranging species, mountain lions are vulnerable to negative impacts from roads. These 

include vehicle-caused mortality, habitat fragmentation, and limitation of animal movements 

(Forman and Alexander 1998, Watkins 2004). The encroachment of human activities also threatens 

the mountain lion in COLM. These threats may be the result of increasing visitation, various 

recreational activities, and the need for associated infrastructure. In the 1980s and 1990s, park 

visitation averaged around 330,000 people annually (NPS 2015). In the past 5 years (2010-2014) 

visitation at COLM has risen to an average of nearly 430,000 visitors annually (NPS 2015). This 

increased visitation also raises concerns over potential human-mountain lion interactions, which 

could have negative impacts for both the mountain lions and the humans. 
258

Data Needs/Gaps

Very few studies have documented mountain lion abundance and distribution in COLM and no 

studies of reproductive success have occurred (Evenden et al. 2002). Regular surveys or monitoring 

of mountain lions in COLM and the surrounding area would allow for more adequate assessment of 

this resource. Future studies on mountain lion movements in and around COLM would help 

managers better understand the status of the park’s mountain lion population and potentially reduce 

the occurrence of mountain lion/human conflicts (Hartwig, written communication, 20 September 

2015). 

Overall Condition

Abundance

The abundance measure was assigned a Significance Level of 3. Though some data for the mountain 

lion in Colorado exists, there is no abundance data for the species specifically within COLM. 

Therefore, a Condition Level could not be assigned. 

Distribution

The distribution measure was assigned a Significance Level of 2. Although some historic observation 

locations have been noted, there is no recent distribution data for mountain lion within COLM. Due 

to this lack of data, a Condition Level could not be assigned

Reproductive Success

The reproductive success measure was assigned a Significance Level of 3. No mountain lion dens 

have been reported within the park, but it is possible that they are present. Because there is no 

specific reproductive data on the mountain lion in COLM, a Condition Level was not assigned to this 

measure.

Weighted Condition Score

A Weighted Condition Score could not be assigned for mountain lions in COLM due to a lack of 

recent data. The current condition of the species within the park is unknown.
259

Mountain Lion

Measures Significance Level Condition Level WCS = N/A

Abundance 3 n/a

Distribution 2 n/a

Reproductive Success 3 n/a

4.12.6 Sources of Expertise

Kim Hartwig, COLM Chief of Resources

Mike Wrigley, United State Forest Service (USFS) Wildlife Biologist

Stephanie Durno, CPW Biologist

4.12.7 Literature Cited

Armstrong, D. M., and C. Rector. 1988. Annotated checklist of mammals of Colorado National 

Monument, Mesa County, Colorado. National Park Service, Grand Junction, Colorado.

Colorado Parks and Wildlife (CPW). 2014a. Mountain lion overall range. GIS shapefile. 

Downloaded from 

http://www.arcgis.com/hom/group.html?id=0e6f9051b06146018038e9a929ab4910 (accessed 14 

July 2015).

Colorado Parks and Wildlife (CPW). 2014b. Mountain lion harvest reports, 2002-2013. Data 

downloaded from http://cpw.state.co.us/thingstodo/Pages/LionStatistics.aspx (accessed 8 July 

2015).

Colorado Parks and Wildlife (CPW). 2014c. Colorado puma mortality, 1980-present, by DAU & 

type of mortality. Excel spreadsheet. Colorado Parks and Wildlife, Denver, Colorado.

Colorado Parks and Wildlife (CPW). 2015a. Mountain lion identification and education course. 

Available from http://www.cougarfund.org/downloads/cougarfund_22.pdf (accessed 8 July 

2015).
260

Colorado Parks and Wildlife (CPW). 2015b. Game management unit boundaries. GIS shapefile. 

Downloaded from 

http://www.arcgis.com/home/group.html?id=a9490456f04f4a3aad8ff590ba5de33d (accessed 13 

October 2015).

Currier, M. J. 1983. Felis concolor. Mammalian Species 200:1–7.

Evenden, A., M. Miller, M. Beer, E. Nance, S. Daw, A. Wight, M. Estenson, and L. Cudlip. 2002. 

Northern Colorado Plateau vital signs network and prototype cluster, plan for natural resources 

monitoring, phase I report. National Park Service, Moab, Utah.

Forman, R. T. T., and L. E. Alexander. 1998. Roads and their major ecological effects. Annual 

Review of Ecology and Systematics 29:207-231.

Miller, P. H. 1964. The ecological distribution of mammals in Colorado National Monument, Mesa 

County, Colorado. Thesis. Oklahoma State University, Stillwater, Oklahoma. 

National Park Service (NPS). 1939-1962. Annual Wildlife Reports, Colorado National Monument. 

National Park Service, Grand Junction, Colorado. 

National Park Service (NPS). 2005. Colorado National Monument final general management plan/ 

environmental impact statement. National Park Service, Fruita, Colorado.

National Park Service (NPS). 2015. Annual park visitors: Colorado National Monument. 

https://irma.nps.gov/Stats/SSRSReports/Park Specific Reports/Annual Park Recreation Visitation 

(accessed 30 April 2015).

Watkins, B. 2004. Mountain lion data analysis unit L-22 management plan. Colorado Division of 

Wildlife, Denver, Colorado.
261

4.13 Bighorn Sheep

4.13.1 Description

Desert bighorn sheep (Ovis canadensis nelsoni) are present in 

COLM solely as the result of reintroduction efforts that began in

Colorado in the 1970s (George et al. 2009). Desert bighorn 

sheep are a subspecies of bighorn sheep and are adapted to the 

desert ecosystems found in the southwestern areas of North 

America (Douglas 1999, George et al. 2009; Photo 17). These 

medium-sized ungulates forage on various trees, shrubs, grasses, 

and forbs. As a ruminant species, their four chambered stomachs 

feature high rates of nutrient extraction from the vegetation they 

consume (Armstrong 1988, Douglas 1999). Desert bighorn 

sheep generally reproduce in their third year, with breeding 

occurring in autumn and births in the spring (Douglas 1999). 

Typically, a single lamb is born after approximately a 6-month 

gestation period (Douglas 1999).

Desert big horn sheep are present at COLM due to the 

translocation of herds from Arizona and Nevada (George et al. 2009). This translocated herd is 

known as the Black Ridge Unit, S-56, or Devil’s-Mee Canyon Unit herd (George et al. 2009). For the 

sake of consistency, this assessment will refer to it as the Black Ridge Unit herd. The historical

occurrence of bighorn sheep in the park is uncertain, with only a few skeletal remains and Native 

American pictographs of sheep suggesting that the species once occupied the area near the park 

(BLM and CPW 1989, Sloan 1995).

Statewide, desert bighorn sheep experienced drastic declines in Colorado from the late 1800s into the 

1970s, with estimations of the total U.S. population declining by nearly 70% from 1915 to 1970 

(McCutchen 1995, George et al. 2009). The arrival of human settlers and their domestic livestock 

(e.g., sheep and goats) in the early 1800s competed with bighorn sheep for space, harvested them for 

food, and inadvertently introduced exotic diseases and parasites (Singer et al. 1996, George et al. 

2009). These factors are thought to have heavily contributed to the decline in Colorado’s bighorn 

sheep population (Singer et al. 1996, George et al. 2009).

4.13.2 Measures

 Abundance

 Distribution

 Reproductive success

4.13.3 Reference Conditions/Values

Graham (1995) outlined short- and long-term management objectives for the Black Ridge Unit 

bighorn sheep herd. The short-term goal was to increase the population to 200 individuals by 2000. 

The long-term goal is to support an estimated population of 400 sheep (Graham 1995, Holland and 

Photo 17. Two desert bighorn 

rams at COLM (NPS photo).
262

Broderick 2013). These objectives will serve as reference conditions for the abundance measure. 

Reproduction is known to occur in the park, as lambs are regularly observed (Hartwig, written 

communication, 15 September 2015), but reproductive success has not been directly assessed and a 

reference condition has not been identified.

4.13.4 Data and Methods

Armstrong (1988) conducted a habitat inventory and population monitoring project in the Grand 

Junction, Colorado area. The population study monitored two separate bighorn sheep populations, the 

Black Ridge Unit herd and the Dominquez herd, from 28 April to 27 September 1988. This 

assessment primarily references the Black Ridge Unit herd as it resides in COLM. The range use of 

the Black Ridge Unit herd was also inventoried from 28 April to 4 September 1988 (Armstrong 

1988).

The BLM and CPW published a management plan for Colorado’s desert bighorn sheep in 1989. This 

was preceded by the 1987 desert bighorn sheep management plan, and was tailored to include 

restoration guidance for projects occurring on public lands (BLM and CPW 1989). Evaluation and 

monitoring for population status, crucial use areas, artificial water units, and forage composition and 

trends are outlined, with recommendations and guidance for future activities (e.g., introductions, 

baseline studies, and habitat improvement) (BLM and CPW 1989).

Graham (1995) produced a management update for the COLM-Black Ridge Unit herd. This report 

officially updated the unit name in the plan, from the “Devils-Mee Canyon Unit” to the “Black Ridge 

Unit” to better reflect the geographical distribution of the herd. In 1997, the 1989 BLM/CPW 

management plan was updated and included an overview of the history and trends of the population, 

recommendations for continued monitoring, and a discussion of management concerns (Graham 

1997).

Sloan (1995) prepared a history of the Black Ridge Unit herd, with a focus on their use of COLM. 

This history covers the initial planning stages for the reintroduction through early 1995. The fates of 

each relocated bighorn group are addressed, along with threats to the population (e.g., hunting, 

disease, habitat alteration, and early population survey results (1991-1994) are included.

Singer et al. (1996) is a collaborative assessment of bighorn sheep populations in 15 Rocky Mountain 

region national park units. Five scientific advisory committees, consisting of 14 scientists from 11 

institutions, were convened to assess the bighorn sheep research and management needs for these 

parks. The intent of the advisory committees was to outline management strategies that would 

address the “commonality of needs on a regional, subregional, or metapopulation basis” (Singer et al. 

1996). The final report included a brief history of the COLM Black Ridge Unit herd along with 

recommendations to managers at the park for general future management strategies (Singer et al. 

1996).

Duckett (2006) also describes the Black Ridge Unit herd in terms of its history, distribution, 

population status, and management concerns. Population estimates were determined through the use 

of helicopter and ground surveys (Duckett 2006). Duckett (2006) determined that the ground and air 
263

survey results were insufficient to produce an accurate population model; however, a population 

estimate was produced using the ground and air surveys in conjunction with anecdotal accounts from 

local entities such as employees of BLM, CPW and USFS, sheep hunters and other members of the 

public (Duckett 2006).

Sheep in the Black Ridge Unit herd were radio-collared and monitored by CPW between 2007 and 

2012 to determine population size, range, survival rates, fecundity, and mortality causes (Stephanie 

Durno, CPW Biologist, written communication, 16 October 2015).

George et al. (2009) produced a 10-year management plan (2009-2019) for bighorn sheep in 

Colorado, including the Black Ridge Unit herd within COLM. Topics discussed in the plan include 

historical trends, current status, statewide objectives and planning, inventory and population 

estimation, population and harvest management, habitat management, health monitoring and 

management, and threats to the species (George et al. 2009).

Holland and Broderick (2013) produced an addendum to the 1997 Colorado bighorn sheep 

management plan. It also included a 2012 post-hunt population estimate of the Black Ridge Unit herd 

and percent of herd that resides within COLM (Holland and Broderick 2013).

4.13.5 Current Condition and Trend

Abundance

Prior to the reintroduction of bighorn sheep to the park in 1979-1980, there were no records that 

indicated a population had ever been sustained specifically within COLM. The last known population 

of bighorn sheep nearest to COLM was in what is now Dinosaur National Monument (George et al. 

2009). This herd was reportedly extirpated as a result of an all-age die-off that occurred in 1933 

(George et al. 2009).

Translocation preparations began in 1977, and the first group of 11 desert bighorn sheep was released 

in Devil’s Canyon, just west of COLM, in November 1979 (Sloan 1995). This was done as part of 

the original BLM-led state-wide desert bighorn sheep restoration effort (BLM and CPW 1989). The 

initial goals for the Black Ridge Unit herd were to attain and sustain a minimum population of 400 

animals (BLM and CPW 1989). The translocation program eventually relocated an additional nine 

bighorn sheep into Devil’s Canyon, bringing the initial population to 20 (Sloan 1995). Relocated 

desert bighorn sheep were also reintroduced into Monument Canyon, with the release of 16 

individuals (seven rams and nine ewes) in June 1980 (Sloan 1995). These sheep were captured from 

a wild population in Lake Mead National Recreation Area in Nevada (Sloan 1995). A summary of 

reintroductions by age group and sex is shown in Table 75.

Hunting is prohibited within COLM, but the Black Ridge Unit herd is susceptible to hunting in areas 

outside the park. Post-hunt population estimates for the Black Ridge Unit herd include those desert 

bighorn sheep that utilize the park for all or part of the year. Post-hunt population estimates for the 

Black Ridge Unit from 1986-2014 are shown in Figure 54. The population fluctuated from 1989-

1995, but for the most part remained stable (George et al. 2009). The Black Ridge Unit herd has 

exhibited an overall decline over the period of record, from a peak of 150 in 1992 to low of 70 from 
264

1995-2006, with a slight increase to 75 animals in 2007 (George et al. 2009). The most recent posthunt population estimate published for the Black Ridge Unit is from 2012. This estimated the 

population of the Black Ridge Unit herd at 200, with approximately 40 animals (20%) occupying

COLM (Holland and Broderick 2013). According to CPW unpublished data (received from 

Stephanie Durno, October 2015), the population estimate showed a large increase up to 230 sheep in 

2010, and has remained stable at 200 animals since 2011. This represents an increase of 125 since 

2007; while the population likely has increased since the early 2000s, survey methodologies have 

also improved to produce a refined and more accurate population estimate (Durno, written 

communication, 16 October 2015).

Table 75. Record of bighorn sheep translocations in the Black Ridge Unit (recreated from Duckett 2006).

Year Release Site Rams:Ewes:Lambs Total

1979 Devil's Canyon 3:8:0 11

1980 Monument Canyon 4:7:5 16

1981 Devil's Canyon 0:9:0 9

1995 Knowles Canyon 4:18:0 22

Figure 54. Black Ridge Unit post-hunt population estimates (George et al. 2009; CPW unpublished data 

from Stephanie Durno).

Distribution

The reintroduced bighorn sheep did not expand their range throughout COLM in the first decades 

after their release (Duckett 2006). The sheep reintroduced to Monument Canyon unexpectedly left 

the canyon within a week of their release; most individuals travelled west and out of the park, to the 

vicinity of Devil’s Canyon (Sloan 1995). In the late 1980s, bighorn sheep reportedly occupied only 

Kodels Canyon in the far northeastern corner of COLM (Armstrong 1988) (Figure 55). Some range 

expansions were noted during the 1990s, with a group of sheep observed around Balanced Rock and 

a lone ram reported above the Coke Ovens in 1993-1995 (Sloan 1995). By 2006, lambing had been 

50

70

90

110

130

150

170

190

210

230

250

Population Estimate
265

documented in Monument Canyon (Duckett 2006). According to the CPW (2013), the overall range 

of bighorn sheep in Colorado includes all of COLM, as well as areas to the northwest and southeast 

(Figure 56).

Figure 55. Approximate distribution of the Black Ridge Unit herd as of 1988 (created from a description of 

population extent in Armstrong [1988]).
266

Figure 56. Bighorn sheep range within Colorado (CPW 2013).

Reproductive Success

Although reproductive success has not been directly studied at COLM, regular observations of lambs 

indicate that reproduction is occurring. Sloan (1995) reported that Devil’s Canyon ewes produced 

lambs in 1982-83, the years immediately following their relocation. Sloan (1995) and Duckett (2006) 

reported lamb:ewe ratios for the Black Ridge Unit herd in the 1990s and in 2003 (based on CPW 

helicopter surveys) ranging from 26.7-66.7% (Table 76).

The lowest number is likely due to the different survey timing, as fewer lambs are likely to survive to 

October. In an April 2014 ground survey of the herd, which included areas of COLM, observers 

documented 25 ewes and 15 lambs, for a lamb:ewe ratio of 60% (Duckett 2014). Three yearlings 

were also observed, indicating that some of the previous year’s lambs had survived the winter 

(Duckett 2014).
267

Table 76. Lamb:ewe ratios observed during helicopter surveys of the Black Ridge Unit bighorn sheep 

herd (Sloan 1995, Duckett 2006).

Year Date Lamb:Ewe ratio

1991 13 June 53.8%

1993 23 June 61.0%

1994 12 October 26.7%

1995 June 50.0%

2003 June 66.7%

2014 24 April 60.0%

Threats and Stressor Factors

While the desert bighorn sheep are protected from hunter disturbance and livestock interaction within 

COLM, there are several human threats and stressors that have the potential to impact the population 

within the park. These include vehicle traffic and visitor activity (Armstrong 1988). Sheep utilizing 

habitats along Rim Rock Drive are often harassed by visitors, particularly photographers trying to get 

close to individuals (Graham 1997; Hartwig, written communication, 15 September 2015). Six 

vehicle (motor vehicle-and bicycle) sheep collisions have been reported along Rim Rock Drive; the 

fate of the injured animals is unknown (Hartwig, written communication, 15 September 2015). It is 

likely that other collisions have occurred but have gone unreported (Hartwig, written communication, 

19 October 2015). In areas outside the park, the herd also faces hunting pressure (Armstrong 1988). 

Hunting permits are heavily regulated and distributed based on post-hunt population estimates from 

the previous year on a unit by unit basis. For example, the 2015 desert bighorn sheep hunt had only 

four resident ram licenses and one nonresident ram license available for the Black Ridge Unit herd 

during the November desert rifle season (CPW 2015).

Although disease has not been a major cause for concern in the Black Ridge herd recently, it has 

impacted the population in the past. There was likely a respiratory disease outbreak in the early 

1990s, when a sick ewe was observed in the area of Pollock and Rattlesnake Canyons. This 

coincided with a population decline that reduced the herd to an estimate of <50 individuals. During 

this same period, three skulls were found that showed signs of chronic sinusitis, which is caused by a 

species of parasitic fly larvae (Graham 1997). Exposure to domestic sheep can pose a threat to desert 

bighorn sheep, since there is a high potential for disease transmission (Graham 1997). Management 

plan recommendations explicitly state that domestic sheep and desert bighorn sheep should not share 

the same habitat (Graham 1997). An NPS assessment of COLM desert bighorn sheep habitat 

identified 11 domestic animal allotments that area within 16 km (10 mi) of the park (Gudorf et al. 

1995). Since these could potentially expose desert bighorn sheep to domestic sheep, translocations 

into those areas are considered at an increased risk of disease transmission (Gudorf et al. 1995). 

Other diseases and parasites that have been observed in desert bighorn sheep include scabies, scab, 

mange (caused by mites), nasal bots (parasitic fly larvae that causes sinusitis in bighorn sheep), 

hemorrhagic septicemia-pasteurellosis, lungworms (natural bighorn parasite), and pneumonia 

(George et al. 2009). Disease testing of 38 sheep during capture by CPW in 2008, 2009, and 2010 

showed that animals in the Black Ridge herd have been exposed to parainfluenza (PI3), bovine 
268

respiratory syncytial virus (BRSV), and both hemolytic and nonhemolytic strains of Pasteurellaceae

bacteria (Durno, written communication, 16 October 2015). These animals were also tested for 

Mycoplasma bacteria, and one animal tested positive.

Natural Predators

Mountain lions are a known predator of desert bighorn sheep and are most detrimental to smallersized herds where any loss of a member can lead to an inability to maintain a sustainable population 

(Graham 1997). Predation by mountain lions can have a significant impact on the Black Ridge Unit 

herd (Graham 1997). During a 5-month period between November 1995 and May 1996, seven radiocollared desert bighorn sheep were found dead; field examinations determined five were killed by a 

mountain lion and one was likely killed by a mountain lion (Graham 1997). The majority of 

identifiable mortalities to CPW-collared animals between 2007 and 2012 were from predators 

(Durno, written communication, 16 October 2015). Additional predators of bighorn lambs include 

coyotes, bobcats, and golden eagles (George et al. 2009).

Data Needs/Gaps

Reproductive success is considered a data gap at this time; without available genetic history or birth 

and death rates, the rate of growth is only estimated using the post-hunt population counts. These are 

of very limited value in the assessment of the reproductive success of the desert bighorn sheep. Any 

genetic evaluation to assess the rate of exchange in genetic material would require blood sampling to 

determine genetic lineages in the herds.

CPW plans to capture and GPS-collar ten sheep in the Black Ridge unit in winter 2015-2016 for 

ongoing monitoring purposes (Durno, written communication, 16 October 2015). This monitoring is 

expected to improve the ability to observe lamb:ewe ratios, mortality causes, and range usage. CPW 

will also be developing a DAU management plan beginning in early 2016 (Durno, written 

communication, 16 October 2015). DAU plans are developed through a public process and compile 

historical information, known research, and provide management objectives, including population 

size and harvest priorities for big game herds throughout Colorado.

Overall Condition

Abundance

The Significance Level for abundance was assigned a 3. The most recent Black Ridge Unit 

population estimate published is the 2012 post-hunt estimate of 200 animals (Holland and Broderick 

2013). According to Holland and Broderick (2013), about 20% of this population occupies COLM. 

Survey results show that the population has grown and remained stable at approximately 200 animals 

for several years, but the herd has not yet met the long-term goal of 400 sheep established in the 

management plan. For this reason, a Condition Level of 1 has been assigned, meaning low concern.

Distribution

The distribution of desert bighorn sheep was assigned a Significance Level of 2. The population at 

COLM resulted from relocation efforts that were part of a larger desert bighorn reestablishment 

project. According to the CPW (2013) and park staff (Hartwig, written communication, 15 
269

September 2015), bighorn sheep now utilize the entire park area. As a result, a Condition Level of 0 

has been assigned, indicating no current concern.

Reproductive Success

A Significance Level of 3 was assigned for this measure. Reproductive success in the desert bighorn 

sheep at COLM has not been specifically studied, although reproduction is known to occur. Sloan 

(1995) and Duckett (2006, 2014) have reported lamb:ewe ratios for the Black Ridge herd ranging 

from 26.7-66.7%. The most recent survey from April 2014 resulted in a lamb:ewe ratio of 60%. 

However, due to large temporal gaps in the data, a Condition Level cannot be assigned.

Weighted Condition Score

A Weighted Condition Score of 0.20 was calculated for COLM’s bighorn sheep, indicating the 

resource is currently in good condition. Future monitoring and management actions should focus on 

including annual population estimates (possibly more frequent if resources are available) and 

encouraging research on the reproductive success of the herd.

Bighorn Sheep

Measures Significance Level Condition Level WCS = 0.20

Abundance 3 1

Distribution 2 0

Reproductive Success 3 n/a

4.13.6 Sources of Expertise

Stephanie Durno, CPW biologist

4.13.7 Literature Cited

Armstrong, J. 1988. Desert bighorn inventory report. Bureau of Land Management, Grand Junction, 

Colorado.

Bureau of Land Management (BLM) and Colorado Parks and Wildlife (CPW). 1989. Colorado desert 

bighorn sheep management plan. Colorado Division of Wildlife, Denver, Colorado.

Colorado Parks and Wildlife (CPW). 2015. 2015 Colorado sheep and goat (hunting season brochure). 

Colorado Parks and Wildlife, Denver, Colorado.

Douglas, C. L. 1999. Comparative ecology of desert bighorn sheep and feral burros. Mojave Desert 

Science Symposium. 
270

http://www.werc.usgs.gov/ProjectSubWebPage.aspx?SubWebPageID=12&ProjectID=216&List

=SubWebPages&Web=Project_216&Title=Bighorn%20sheep%20and%20burros (accessed 18 

February 2015).

Duckett, S. 2006. DRAFT - Unit S-56, the Black Ridge desert bighorn sheep herd. Colorado Parks 

and Wildlife, Denver, Colorado.

Duckett, S. 2014. Results from 2014 survey. Email communication with Kim Hartwig, COLM Chief 

of Resources. Colorado Parks and Wildlife, Denver, Colorado.

Graham, V. K. 1995. Colorado desert bighorn sheep management plan, Colorado National 

Monument-Black Ridge herd unit update. Colorado Division of Wildlife, Grand Junction, 

Colorado.

Graham, V. K. 1997. Colorado Division of Wildlife desert bighorn sheep management plan, Black 

Ridge herd unit revision, March 1997. Colorado Division of Wildlife, Terrestrial Wildlife 

Section, Grand Junction, Colorado.

George, J. L., R. Kahn, M. W. Miller, and B. Watkins. 2009. Colorado bighorn sheep management 

plan 2009-2019. Special report number 81. Colorado Division of Wildlife, Denver, Colorado.

Gudorf, M., P. Sweanor, F. Singer, V. Bleich, J. Cordova, C. Hauke, L. Lee, T. Lytle, P. Perrotti, S. 

Petersburg, and B. Sloan. 1995. Bighorn sheep habitat assessment of the greater Colorado 

National Monument area. National Park Service and National Biological Service, Colorado 

National Monument, Colorado.

Holland, A., and J. Broderick. 2013. Desert bighorn sheep addendum to the Colorado bighorn sheep 

management plan, 2009-2019. Draft report. Colorado Parks and Wildlife, Denver, Colorado.

McCutchen, H. E. 1995. Desert bighorn sheep. Pages 333-336 in Our living resources: a report to the 

nation on the distribution, abundance, and health of the U.S. plants, animals, and ecosystems. 

LaRoe, E. T, G. S. Farris, C. E. Puckett, P. D. Doran, and M. J. Mac (eds). U.S. Department of 

the Interior, National Biological Service, Washington, D.C. 

Singer, F., W. Adrian, F. Allendorf, J. Baily, J. Berger, V. Bleich, and M. Bogan. 1996. Bighorn 

sheep in the Rocky Mountain Region: Reports of five scientific advisory committees to the 

National Park Service. U.S. Geological Survey, Fort Collins, Colorado.

Sloan, W. B. 1995. A herd history of the bighorn sheep of the Colorado National Monument and the

Black Ridge, Colorado. National Park Service, Moab, Utah.
271

4.14 Kit Fox

4.14.1 Description

The kit fox (Vulpes macrotis) is a small 

mammal of the southwest desert weighing 

about 1.5 to 2.5 kg (3.3 to 5.5 lbs) as adults 

(Meaney et al. 2006). They stand 30 to 32 cm 

(0.98 to 1.05 ft) high at the shoulder and are 73 

to 84 cm (2.40 to 2.76 ft) in length (Meaney et 

al. 2006). Kit foxes are similar in appearance to 

swift foxes found on the eastern plains of 

Colorado, but they have larger ears and a more 

angular appearance (Meaney et al. 2006). They 

have long, black-tipped, bushy tails, dark 

muzzles, yellow-gray to grizzled dorsal fur, and pale yellow to white ventral fur (Meaney et al. 2006) 

(Photo 18).

Kit foxes occur in a variety of shrublands including semi-desert shrublands, sagebrush shrublands, 

and shrubby margins of pinyon-juniper woodlands (Boyle and Reeder 2005). Suitable habitat extends 

from north of Montrose to Grand Junction, Colorado (BLM 2010). Kit foxes are nocturnal and 

remain in or near their dens during the day; dens are used for resting, shelter, raising young, and 

avoiding predators (Meaney et al. 2006). They dig their own dens or sometimes adapt badger 

diggings or prairie dog burrows into dens (Boyle and Reeder 2005). Kit foxes are opportunistic 

consumers and scavengers and feed primarily on rabbits (Order Lagomorpha), prairie dogs, and 

kangaroo rats (Dipodomys spp.), but will also eat birds, reptiles, small mammals, and insects 

(Meaney et al. 2006). They will also cache food to consume at a later time (Meaney et al. 2006). Kit 

foxes mate some time between December and February, with most litters containing four to five pups 

(Boyle and Reeder 2005).

The kit fox is a state endangered species in Colorado and is considered one of the state’s most 

vulnerable animals (BLM 2010). Habitat loss, degradation, and fragmentation, competition with 

coyotes and other foxes, and road strikes are the main causes for the decline of the species (Meaney 

et al. 2006). Some other potential threats include recreational impacts, domestic livestock grazing, 

control of predators and rodents, and the decline in white-tailed prairie dogs (Cynomys leucurus) 

(Meaney et al. 2006). The kit fox was once a furbearer in Colorado and has been protected from 

harvest since 1994 (Boyle and Reeder 2005).

4.14.2 Measures

 Abundance

 Distribution

 Reproductive success

Photo 18. Desert kit fox (V. macrotis arsipus) (NPS 

Photo).
272

4.14.3 Reference Conditions/Values

Kit fox harvest numbers were reported by trappers returning questionnaires to the CPW from 1975 to 

1991, though the numbers were sporadic (Boyle and Reeder 2005). After four years of study, 

Fitzgerald (1996) speculated that fewer than 100 kit foxes remained in Colorado. Since no data 

regarding kit foxes specifically within COLM exist, this will serve as the reference condition for 

abundance. A map created by Boyle and Reeder (2005) shows the historic range of the kit fox (see 

Figure 58) and will serve as a reference condition for the distribution measure. A reference condition 

has not been established for reproductive success.

4.14.4 Data and Methods

The most recent kit fox survey in Colorado was done by the CPW (Neubaum and Duckett 2014). The 

study area encompassed the Grand Valley in west-central Colorado bounded on the north and south 

by the Mesa County line, the Colorado-Utah state line to the west, and Grand Mesa to the east

(Neubaum and Duckett 2014). Eighteen sites within the study area were chosen based on where kit 

foxes have previously been reported or documented (Neubaum and Duckett 2014). Elevations of 

sites surveyed ranged from 1,409 m (4,650 ft) in Rabbit Valley to 1,892 m (6,244 ft) in COLM

(Neubaum and Duckett 2014). Habitat in the area consisted of semi-desert shrublands with rocky 

outcrops, often bordered by pinyon pine and oneseed juniper forest (Neubaum and Duckett 2014). 

The climate in the area is characterized as high desert with an annual precipitation of just over 23.9 

cm (9.4 in) and an average temperature of 12 °C (53 °F) (Neubaum and Duckett 2014).

A GPS unit was used to collect coordinates for each camera location (Neubaum and Duckett 2014). 

Survey duration varied for each site though each camera was run for at least one month (Neubaum 

and Duckett 2014). Remote cameras were typically placed 1 m (3.3 ft) off the ground on a T-post in a 

lockable security enclosure (Neubaum and Duckett 2014). A map of the cameras placed for this 

survey can be found in Figure 57. A scent station baited with skunk lure was placed on a stick or rock 

approximately 3m (10 ft) out in front of the camera (Neubaum and Duckett 2014). Cameras were 

typically checked every 7 to 14 days at which time the memory cards and batteries were swapped and 

the scent lure refreshed (Neubaum and Duckett 2014). Towards the end of the survey a few sites 

were supplemented with canned mackerel as an additional bait to see if it would attract kit foxes 

(Neubaum and Duckett 2014). Cameras were programmed to take photos on rapid fire whenever the 

infrared beam was broken (Neubaum and Duckett 2014). However, no kit foxes were documented by 

these cameras (Neubaum and Duckett 2014).
273

Figure 57. Camera locations for the 2012-2013 kit fox survey (from Neubaum and Duckett 2014). COLM 

is near the center of the map, where camera 1 was located.

4.14.5 Current Condition and Trend

Abundance

After four consecutive years of study in the early to mid-1990s, Fitzgerald (1996) speculated that 

fewer than 100 kit foxes were present in Colorado, and that the populations were likely not selfsustaining. Further study by Beck (1999, 2000) strongly suggested that the small fox population had 

declined and was close to extirpation from the state (Boyle and Reeder 2005). A recent kit fox survey 

using infrared cameras detected no kit foxes, though interspecific competitors such as gray and red 

foxes, coyotes, and domestic dogs were documented (Neubaum and Duckett 2014). According to 

Dan Neubaum (CPW, Wildlife Conservation Biologist, written communication, 4 August 2014), a 

couple of kit foxes have been documented in COLM, though these are most likely wandering 

juveniles or unusual sightings. Reliable sightings from the Grand Valley tend to be in much more 

open portions of the desert where bands of rock occurred, generally at lower elevations than most of 

COLM. Pinyon-juniper is well established over much of COLM, creating habitat that is more 

suitable for the gray fox, a competitor of the kit fox, which would likely inhibit the kit fox from using 

such habitat (Neubaum, written communication, 4 August 2014). Neubaum (written communication, 

4 August 2014) also believes it is likely that kit foxes have been extirpated from Colorado or that 

only a few individuals remain. However, a population is present just over the state line in Cisco, 
274

Utah, and could act as a source of immigrating individuals if they do attempt to repopulate the valley 

(Neubaum, written communication, 4 August 2014).

Distribution

In Colorado, the kit fox’s historic range encompassed approximately 1.83 million ha (4.52 million 

ac) (Figure 58) (Boyle and Reeder 2005). In 2005, there were only about 120,000 ha (296,525 ac) 

remaining (Boyle and Reeder 2005). Based on historical records, anecdotal reports, known 

occurrences in adjacent counties in Utah, and the availability of suitable habitat, kit foxes are 

expected to occur in eight Colorado counties (Boyle and Reeder 2005). However, Fitzgerald (1996) 

only observed or captured kit foxes in the lower Colorado and lower Gunnison River drainages in 

Delta, Montrose, Garfield, and Mesa counties. Centers of abundance were southeast of Delta and east 

of Montrose in the Uncompahgre Valley. The only recorded reports of kit fox observations within 

COLM are from the early 1960s (Miller 1964). One individual was found at the junction of Rim 

Rock Drive and West Glade Park Road, on the western boundary of the park, in October 1960 and in 

June 1962 another was spotted along Rim Rock Drive, 2 km (1.25 mi) west of Red Canyon View 

(Miller 1964). Figure 58 depicts the 2005 and historic distribution of the kit fox, though as previously 

mentioned, it is likely that kit foxes have now been extirpated from Colorado.
275

Figure 58. Recent (2005) and historic distribution of the kit fox in Colorado (Recreated from Boyle and 

Reeder 2005).

Reproductive Success

Data regarding the reproductive success for the kit fox in COLM do not exist. Using reproductive 

success as a measure to assess the current condition generally works better with a defined, 

established population. Due to the rarity of kit foxes in Colorado, trail cameras and hair snares are 
276

being used to confirm their presence rather than using reproductive success to assess the population, 

as these methods are less invasive to the animal (Neubaum, written communication, 4 August 2014).

Threats and Stressor Factors

A primary threat to the kit fox in COLM is habitat loss and fragmentation. Habitat that was once 

considered suitable for kit foxes (lower elevations along the northern boundary) is no longer suitable 

due to fragmentation and urbanization along the Redlands (Neubaum, written communication, 4 

August 2014). With the increase in energy and residential development in western Colorado, the 

Grand Junction area is one of the fastest growing regions in Colorado. This development may not 

only degrade and destroy kit fox habitat, but also causes fragmentation which may impair the 

movement of kit foxes between certain areas. Loss of dispersal corridors is a serious concern because 

of loss of movement between sub-populations (Meaney et al. 2006). Immigration by reproductive 

individuals can make a relatively large difference in population persistence, making habitat 

connectivity crucial (Meaney et al. 2006). This is also important in the long term to prevent genetic 

inbreeding within small isolated populations (Meaney et al. 2006).

Roads are known to contribute to vehicle-caused mortality and also reduce habitat connectivity for a 

number of wildlife species (Meaney et al. 2006). The negative impacts to wildlife associated with 

roadways are proportional to road width, traffic volume, and speed limit (Meaney et al. 2006). As 

development increases in western Colorado, roads will become wider, carry higher traffic volumes, 

and become more inhospitable to wildlife. Narrow dirt roads can even pose a threat to the kit fox as 

they allow easy access to otherwise remote areas, allowing human disturbance to occur (Meaney et 

al. 2006). This human disturbance by recreational enthusiasts, especially off-road vehicle (ORV) 

users, can pose a major threat to kit fox denning areas (Meaney et al. 2006).

Data Needs/Gaps

Though abundance data for the kit fox in Colorado exists, there are no abundance data for the kit fox 

specifically within COLM. A map created by Boyle and Reeder (2005) shows the historical 

distribution of kit foxes (Figure 58), though more recent distribution data are needed. Data regarding 

the reproductive success of the kit fox are also not available for COLM. At this time, it is likely that 

the species is extirpated from Colorado (Neubaum, written communication, 4 August 2014).

Overall Condition

Abundance

The abundance measure was assigned a Significance Level of 3. Based on the reports of Fitzgerald 

(1996), Beck (1999, 2000), Boyle and Reeder (2005), and Neubaum and Ducket (2014), the 

Condition Level for this measure is 3, indicating high concern. Due to habitat loss and fragmentation, 

along with other threats and stressors to kit foxes, they may now be extirpated from Colorado.

Distribution

The distribution measure was assigned a Significance Level of 2. Boyle and Reeder (2005) created a 

current and historical distribution map, though according to Dan Neubaum (email communication, 4 

August 2014), the species is likely extirpated from Colorado. Given that the distribution of the kit fox 

possibly now excludes Colorado, the Condition Level of this measure is 3, indicating high concern.
277

Reproductive Success

The reproductive success measure was assigned a Significance Level of 3. Because there is no data 

for COLM and Colorado populations are too low to use reproductive success to assess the condition 

of the kit fox, a Condition Level was not assigned to this measure.

Weighted Condition Score

The Weighted Condition Score for this component is 0.83. With kit foxes likely extirpated from 

Colorado, this species is of high concern to management. More extensive surveys within COLM are 

necessary to confirm their presence or absence. The condition of the kit fox is currently unchanging, 

as the population likely cannot decrease further than it already has.

Kit Fox

Measures Significance Level Condition Level WCS = 0.83

Abundance 3 3

Distribution 2 3

Reproductive Success 3 n/a

4.14.6 Sources of Expertise

Dan Neubaum, CPW Wildlife Conservation Biologist

4.14.7 Literature Cited

Beck, T. D. I. 1999. Kit fox (Vulpes macrotis) status in Colorado. In Wildlife Research Report, 

Project No. W-153-R-12, Work Package 0663, Task 1. Colorado Division of Wildlife, Denver, 

Colorado.

Beck, T. D. I. 2000. Kit fox augmentation study. In Wildlife Research Report, Project No. W-153-R13, Work Package 0663, Study No. 1. Colorado Division of Wildlife, Denver, Colorado.

Boyle, S. A., and D. R. Reeder. 2005. Colorado sagebrush: A conservation assessment and strategy. 

Colorado Parks and Wildlife, Denver, Colorado.

Bureau of Land Management (BLM). 2010. Analysis of the management situation for the BLM 

Uncompahgre planning area. Bureau of Land Management, Montrose, Colorado.

Fitzgerald, J. P. 1996. Status and distribution of the kit fox (Vulpes macrotis) in western Colorado. 

Final report. Project No. W-153-R-7. Colorado Division of Wildlife, Denver, Colorado.
278

Meaney, C. A., M. Reed-Eckert, and G. P. Beauvais. 2006. Kit fox (Vulpes macrotis): A technical 

conservation assessment. Available from 

http://www.fs.fed.us/r2/projects/scp/assessments/kitfox.pdf (accessed 18 July 2014).

Miller, P. H. 1964. The ecological distribution of mammals in Colorado National Monument, Mesa 

County, Colorado. Thesis. Oklahoma State University, Stillwater, Oklahoma.

Neubaum, D. J., and S. Duckett. 2014. Use of remote infrared cameras to survey for kit fox (Vulpes 

macrotis) in the Grand Valley, Colorado. Colorado Parks and Wildlife, Grand Junction, 

Colorado.
279

4.15 Bats

4.15.1 Description

Bats have the potential to be used as 

bioindicators for a number of reasons. Bats are 

important to biodiversity, they possess 

ecological and economic value as ecosystem 

components, and they are vulnerable to rapid 

population declines (O’Shea et al. 2003). 

Species with specialized roosting requirements 

and limited suitable roosts are important to 

monitor, as they are particularly vulnerable to 

habitat loss and local extirpation (O’Shea et al. 

2003). Due to the vast amount of insects they 

consume, fluctuations in bat populations will 

affect the agricultural and forestry segments of 

the economy, ecosystem function, and the 

overall biodiversity (O’Shea et al. 2003). These 

fluctuations can be related to climate change, 

changes in water quality, agricultural 

intensification, loss and fragmentation of 

forests, fatalities at wind turbines, disease, 

pesticide use, and overhunting (Jones et al. 

2009). For the reasons listed above, bat 

monitoring programs would be beneficial to 

park management.

Based on distributional ranges, 17 different species of bats could potentially occur in COLM (Adams 

1989). A recently completed bat inventory of COLM has confirmed the presence of these 17 species 

within COLM (Hartwig, written communication, 30 January 2016). Availability and abundance of 

roost sites may be the most important factor concerning the distribution of bats in COLM. Freestanding water (e.g., ponds, lakes, slow-moving streams) is also important because it supports high 

densities of insects for bats to eat, as well as for drinking while in flight (Adams 1989).

4.15.2 Measures

 Species richness

 Abundance

 Number of hibernation/roost sites

 Number of maternity sites

Photo 19. Big brown bat (Eptesicus fuscus) (Photo 

by Dr. Lloyd Glenn Ingles, California Academy of 

Sciences).
280

4.15.3 Reference Conditions/Values

The reference condition for species richness at COLM was established by Adams (1989, 1994). 

Reference conditions have not been established for abundance, number of hibernation/roost sites, or 

number of maternity sites.

4.15.4 Data and Methods

A census of bat fauna by Rick Adams began at COLM in 1989. This was the first attempt to identify 

species richness of bats within COLM. The initial census lasted two years (1989-1990) and was 

reinitiated in 1993 and 1994 by The Colorado Bat Society (CBS) (Adams 1994). The bats were 

trapped using Japanese mist nets. All bats were identified to species, weighed, sexed, forearm 

measured, reproductive condition noted, location of capture noted, and released. No bats were 

banded or marked in any other way. Areas of COLM which have permanent water were used as trap 

sites, as well as pinyon-juniper woodland (Adams 1989). At the conclusion of this survey, 12 out of 

the 17 species expected to be present within COLM were verified. Data from a recently concluded 

2014–2015 bat survey of the park will also be useful in future assessments of this resource.

4.15.5 Current Condition and Trend

Species Richness

Populations of 17 of the 18 species of bats known or expected to have distributional ranges including 

Colorado could potentially occur in COLM (Adams 1989). While the presence of these 17 species 

has been confirmed by a recent study, published data are not yet available at the time of this writing. 

In the absence of this new data, the species richness is based currently available information from 

NPSpecies. A total of 13 different species are present in COLM according to NPSpecies (Table 77; 

NPS 2014); however, the recently completed 2014-2015 bat survey will provide further insight into 

this measure. This effort has already documented several bat species in the park that were previously 

unconfirmed (Neubaum, written communication, 4 August 2014).

Abundance

Data regarding abundance for bats in COLM are very limited. Adams (1989, 1993, 1994) 

documented the number of individuals of each species captured during the three surveys. However, 

these results may be influenced by survey effort (e.g., number of sites and days spent surveying) and 

weather conditions and may not reflect actual abundance within the park. Many more individuals 

were observed in flight but could not be captured or counted accurately (Adams 1989, 1994). The 

2014-2015 bat survey will provide further insight into this measure.

Number of Hibernation/Roost Sites

As mentioned previously, availability and abundance of roost sites is thought to be a key factor 

influencing the distribution of bats within Colorado (Adams 1989). Therefore, information on the 

number of hibernation and roost sites could contribute to a better understanding of the park’s bat 

population. Unfortunately, data on the number of hibernation/roost sites for bats in COLM was not 

available for inclusion in this assessment. Bats have been observed roosting in west-side auto tunnels 

(Adams 1989, 1993). The 2014-2015 bat survey is expected to provide insight into this measure.
281

Table 77. Occurrence of bat species within COLM (Adams 1994; NPS 2014).

Scientific name Common name Adams (1994) NPS (2014)

Antrozous pallidus pallid bat Present Present

Corynorhinus townsendii Townsend's big-eared bat Present Present

Eptesicus fuscus big brown bat Present Present

Euderma maculatum spotted bat Unconfirmed Unconfirmed

Idionycteris phyllotis Allen's big-eared bat Unconfirmed Unconfirmed

Lasionycteris noctivagans silver-haired bat Present Present

Lasiurus cinereus hoary bat Unconfirmed Probably Present

Myotis californicus California myotis Unconfirmed Present

Myotis ciliolabrum western small-footed myotis Present Present

Myotis evotis long-eared myotis Unconfirmed Probably Present

Myotis lucifugus little brown bat Present Present

Myotis thysanodes fringed myotis Present Present

Myotis volans long-legged myotis Present Present

Myotis yumanensis Yuma myotis Present Present

Nyctinomops macrotis big free-tailed bat Present* Present

Parastrellus hesperus western pipistrelle Present Present

Tadarida brasiliensis Brazilian free-tailed bat Present Present

*Found injured on road

Table 78. Number of individuals of each bat species captured in surveys by Adams (1989. 1993, 1994).

Species Name Common Name 1989 (4 sites) 1993 (3 sites) 1994 (2 sites)

Eptesicus fuscus big brown bat 5 13 2

Myotis ciliolabrum western small-footed myotis 1 5 1

Myotis lucifugus little brown bat 1 1 0

Myotis thysanodes fringed myotis 0 0 1

Myotis volans long-legged myotis 0 1 1

Myotis yumanensis Yuma myotis 13 6 6

Parastrellus hesperus western pipistrelle 1 3 5

Tadarida brasiliensis Brazilian free-tailed bat 1 0 0

Totals 22 29 16

Number of Maternity Sites

Specific data regarding the number of maternity sites in COLM was not available at the time of this 

assessment; however the recently completed 2014-2015 bat survey did identify several important 

maternal colony sites (Hartwig, written communication, 30 January 2016). Other studies have 

documented a maternity colony of Yuma myotis (Myotis yumanensis) on the west side of the park 

and the capture of lactating Brazilian free-tailed bats (Tadarida brasiliensis) indicates there is a 

maternity roost in or near the park (Adams 1989, 1993). The capture of a very young western 
282

pipistrelle (Parastrellus hesperus) in No Thoroughfare Canyon in 1994 also suggests that the species 

has a maternity roost site there (Adams 1994). 

Threats and Stressor Factors

While there are no threatened or endangered species of bats within COLM, there is one bat 

(Townsend’s big-eared bat [Corynorhinus townsendii]) that is listed as a species of state special 

concern. The main concern for this particular species is disturbance, with recreational caving and 

abandoned mine closures being the largest threat to the animal (Pierson et al. 1999). Surveys using 

passive integrated transponder (PIT) tags are currently in place to mark Townsend’s big eared bats in 

Colorado, which will help generate survival estimates for the species for the first time. These 

estimates may help analyze populations of this species within COLM. In addition to the species of 

state special concern, there are also several other species that are of concern to federal agencies 

including the spotted bat (Euderma maculatum), the big free-tailed bat (Nyctinomops macrotus), and 

the fringed myotis (Myotis thysanodes), all of which occur within COLM (Neubaum, email 

communication, 4 August 2014).

White-nose syndrome (WNS) is a disease affecting hibernating bats caused by a newly discovered 

fungus, Pseudogymnoascus destructans (USFWS 2014). This fungus is psychrophilic, or coldadapted, and grows at temperatures of 3 to 15 °C (37.4 to 59 °F) and greater than 90% humidity 

(Foley et al. 2011). Transmission generally occurs through direct bat-to-bat contact, although 

exposure to environments in which the fungus is present and human or animal vectors are also 

possible. In autumn, hibernating bats build up fat reserves in preparation for winter. During 

hibernation, these bats must arouse to restore homeostatic balance (e.g., drink, urinate, relocate, and 

probably induce immune functioning), consuming some of the stored body fat. WNS causes bats to 

arouse more frequently or for longer periods than usual, depleting their body fat prematurely and 

causing them to starve. Direct mortality from infection of the wings may also occur (Foley et al. 

2011). Bats with WNS may act strangely during the winter, including flying outside during the day 

and clustering near the entrances of caves and other hibernation areas (USFWS 2014).

As of June 2014, bats with WNS were confirmed in 25 states, primarily in the east and central parts 

of the country, and five Canadian provinces (USFWS 2014). Species on which WNS has been 

confirmed include the big brown bat (Eptesicus fuscus), the eastern small-footed myotis (Myotis 

leibii), the gray bat (Myotis grisescens), the Indiana bat (Myotis sodalis), the little brown bat (Myotis 

lucifugus), the northern long-eared bat (Myotis septentrionalis), and the tricolored bat (Perimyotis 

subflavus). Species on which P. destructans has been detected with no confirmation of WNS include 

the southeastern myotis (Myotis austroriparius), the silver-haired bat (Lasionycteris noctivagans), 

and the Virginia big-eared bat (Corynorhinus townsendii virginianus) (USFWS 2014).

WNS is not currently present in Colorado. COLM does, however, contain two species that have been 

confirmed to have WNS (the big brown bat and the little brown bat) and one species on which P. 

destructans has been detected with no confirmation of WNS (the silver-haired bat). Controlling the 

spread of this fungus is important to maintaining current populations of bats around the country. 

Public education may encourage people to report cases of WNS, avoid inadvertent spread of the 

fungus, and avoid disturbance of hibernacula (Foley et al. 2011).
283

Habitat loss can have negative impacts on the bats of COLM. Roost selections serve a number of 

functions and vary by season. For many temperate bats, roosts can be separated into winter 

hibernacula, maternity roosts, and summer roosts. Suitable roost selection is important for growth, 

development and survival of young, protection from predators, protection from the elements, and 

reduction of thermoregulatory costs (Agosta 2002). In addition, many bats use specific night roosts in 

close proximity to foraging areas as resting places and to provide opportunities for social 

interactions. Examples of potential roosting sites for bats include caves, tunnels, mines, buildings, bat 

boxes, tree cavities, rock crevices, storm sewers, and wood piles. Human disturbance to these roosts 

can be harmful to bat populations (Agosta 2002). The greatest contributor to the decline of bats is the 

loss of roosting habitat due to cave and mine closure, vandalism, intentional habitat destruction, 

development and deforestation, and the removal of live trees, snags, and hedgerows from agricultural 

fields, farmlands and other rural landscapes. Managing open fields to provide diversity in vegetation 

and insect composition and preserving tree roosts such as snags and hedgerows is a good way to 

promote healthy bat roosting areas (NRCS 1999).

Pesticides have a variety of effects on bats including direct mortality, altered behavior, and 

transferring toxins to nursing young (Agosta 2002). Pesticides may also indirectly affect 

insectivorous bats by reducing their food source, though little is known on this topic (McCracken 

1989). With organochlorine pesticides (e.g., DDTs) now banned in the U.S. less toxic 

organophosphate and carbamate pesticides are now being used. Although these are less toxic than 

organochlorine pesticides, some pesticides being used still cause mortality in birds and mammals. 

Pesticide exposure may be the cause of decline for some populations of insectivorous bats, 

particularly those whose diets include agricultural pests (Agosta 2002).

With wind energy becoming one of the fastest growing sources of renewable energy, impacts of wind 

energy development on bats and other wildlife are increasingly becoming a concern. This topic 

received little attention in North America until 2003, when estimated 1,400–4,000 bats were killed at 

the Mountaineer Wind Energy Center in West Virginia (Arnett et al. 2010). Bat fatalities in relation 

to wind turbines are heavily skewed towards migratory bats, particularly those within the genus 

Lasiurus, and generally occur more often in midsummer through fall. Fatalities are also the highest 

during periods of low wind speed and are related to weather variables associated with the passage of 

weather fronts. Red strobe lights recommended by the Federal Aviation Administration (FAA) did 

not influence bat mortality and fatalities were not concentrated at individual turbines (Arnett et al. 

2010). Reducing turbine blade speed and operating time on low-wind nights in summer and fall can 

substantially reduce bat fatalities (Arnett et al. 2013).

Human disturbance to roosts sites can have adverse effects on bat populations. The increase in 

recreational climbing routes and their impact on bat populations is of particular concern to COLM 

resource managers. Disturbance can cause bats to abandon roost sites, sometimes relocating to a less 

ideal site (Gruver and Keinath 2006). Disturbance raises the general level of activity within roosts, 

which can result in greater energy expenditure. This may in turn increase foraging demands and 

cause the bat to spend more time outside where they are vulnerable to predation. Clustering bats gain 

thermal benefits from being surrounded by other bats. Disturbance may cause the colony size to 
284

decrease, which may in turn decrease thermal benefits of the colony (McCracken 1989). Disturbance 

during hibernation is especially unfavorable as it can cause bats to deplete energy reserves needed for 

them to survive the winter (Thomas et al. 1990).

Data Needs/Gaps

Bat species richness has been documented by Adams (1989, 1990, 1993, 1994); however, abundance 

and distribution data are mostly absent from COLM. The bat survey currently in process could be 

repeated routinely to document species richness, abundance, number of hibernation/roost sites, and 

number of maternity sites would provide managers with meaningful information that can be used to 

assess the condition of bats in the future. The results from this CPW bat survey, conducted from 

2014-2015 were not available at the time of this writing. The data collected by this survey will help 

managers to have a better understanding of the current bat populations within COLM.

Overall Condition

Species Richness

The species richness measure was assigned a Significance Level of 3. With nearly all species of bat 

expected to occur within COLM documented (Neubaum, email communication, 4 August 2014), the 

Condition Level of this measure is 0, indicating no concern. The completion of the 2014-2015 bat 

survey will provide greater insight to this measure.

Abundance

The abundance measure was assigned a Significance Level of 3. Data on the abundance of bats within 

COLM are limited, though the 2014-2015 will likely provide some information. Due to the lack of 

data related to abundance, a Condition Level was not assigned to this measure.

Number of Hibernation/Roost Sites

This measure was assigned a Significance Level of 2. Data on hibernation/roost sites of bats within 

COLM are not currently available. A Condition Level was not assigned to this measure due to the 

lack of data.

Number of Maternity Sites

The number of maternity sites measure was assigned a Significance Level of 2. No data are available 

on maternity sites of bats within COLM, though the 2014-2015 could provide insight into this 

measure. Due to the lack of data on maternity sites, a Condition Level could not be assigned.

Weighted Condition Score

A Weighted Condition Score was not calculated for this component since Condition Level could only 

be assigned to one measure (species richness) due to lack of available data. Until data become 

available for the other measures, possibly at the conclusion of the 2014-2015 bat survey, the 

condition of bats in COLM will be unknown.
285

Bats

Measures Significance Level Condition Level WCS = N/A

Species Richness 3 0

Abundance 3 n/a

Number of 

Hibernation / 

Roost Sites

2 n/a

Number of Maternity 

Sites 2 n/a

4.15.6 Sources of Expertise

Dan Neubaum, CPW Wildlife Conservation Biologist

4.15.7 Literature Cited

Adams, R. A. 1989. Bat species abundance and distribution in Colorado National Monument. 

National Park Service Unpublished Report, Boulder, Colorado.

Adams, R. A. 1994. Continued census of the bat fauna at Colorado National Monument. National 

Park Service Unpublished Report, Boulder, Colorado.

Agosta, S. J. 2002. Habitat use, diet, and roost selection by the big brown bat (Eptesicus fuscus) in 

North America: A case for conserving an abundant species. Mammal Review 32:179-198.

Arnett, E. B., W. K. Brown, W. P. Erickson, J. K. Fiedler, B. L. Hamilton, T. H. Henry, A. Jain, G. 

D. Johnson, J. Kerns, R. R. Koford, and others. 2010. Patterns of bat fatalities at wind energy 

facilities in North America. The Journal of Wildlife Management 72:61-78.

Arnett, E. B., R. MR. Barclay, and C. D. Hein. 2013. Thresholds for bats killed by wind turbines. 

Frontiers in Ecology and the Environment 11:171-171.

Foley, J., D. Clifford, K. Castle, P. Cryan, and R. S. Ostfeld. 2011. Investigating and managing the 

rapid emergence of white-nose syndrome, a novel, fatal, infectious disease of hibernating bats. 

Conservation Biology 25(2):223-231.

Gruver, J. C., and D. A. Keinath. 2006. Townsend’s big-eared bat (Corynorhinus townsendii): A 

technical conservation assessment. U.S. Forest Service, Rocky Mountain Region, Golden, 

Colorado.
286

Jones, G., D. S. Jacobs, T. H. Kunz, M. R. Willig, and P. A. Racey. 2009. Carpe noctem: The 

importance of bats as bioindicators. Endangered Species Research 8:93-115.

McCracken, G. F. 1989. Cave conservation: Special problems of bats. NSS Bulletin 51:49-51.

National Park Service. NPSpecies: Information on species in national parks. 

https://irma.nps.gov/NPSpecies/Search/SpeciesList/COLM (accessed 17 July 2014).

Natural Resources Conservation Service (NRCS). 1999. Bats (order: Chiroptera). Fish and Wildlife 

Habitat Management Leaflet No.5. Natural Resource Conservation Service, Madison, 

Mississippi.

O’Shea, T. J., M. A. Bogan, and L. E. Ellison. 2003. Monitoring trends in bat populations of the 

United States and territories: Status of the science and recommendations for the future. Wildlife 

Society Bulletin 31:16-29.

Pierson, E. D., M. C. Wackenhut, J. S. Altenbach, P. Bradley, P. Call, D. L. Genter, C. E. Harris, B. 

L. Keller, B. Lengus, L. Lewis, and others. 1999. Species conservation assessment and strategy 

for Townsend’s big-eared bat (Corynorhinus townsendii townsendii and Corynorhinus 

townsendii pallescens). Idaho Conservation Effort, Idaho Department of Fish and Game, Boise, 

Idaho.

Thomas, D. W., M Dorais, and J. M. Bergeron. 1990. Winter energy budgets and cost of arousals for 

hibernating little brown bats, Myotis lucifugus. Journal of Mammalogy 71:475-479.

U.S. Fish and Wildlife Service (USFWS). 2014. White-nose syndrome: The devastating disease of 

hibernating bats in North America. U.S. Fish and Wildlife Service, Hadley, Massachusetts.
287

4.16 Air Quality

4.16.1 Description

Air pollution can significantly affect natural resources and their associated ecological processes, and 

the health of park visitors. In the Clean Air Act (CAA), Congress set a national goal to preserve, 

protect, and enhance the air quality in national parks, national wilderness areas, national monuments, 

national seashores, and other areas of special national or regional natural, recreational, scenic or 

historic value (42 U.S.C. §7470(2)). This goal applies to all units of the National Park System. The 

act includes special provisions for 48 park units, called “Class I” areas under the CAA; all other NPS 

areas are designated as Class II, including COLM. Class I area designations must be made by 

Congress and have only been done once, in the 1977 revisions to the CAA. For Class II airsheds, the 

increment ceilings for additional air pollution above baseline levels are slightly greater than for Class 

I areas which can allow for more development (EPA 2013a). Additional authority to consider and 

protect air quality in Class II parks is provided by Title 54 (54 USC 100101(a) et seq.), commonly 

known as the NPS Organic Act, and the Wilderness Act.

Parks designated as Class I and II airsheds typically use the EPAs National Ambient Air Quality 

Standards (NAAQS) for criteria air pollutants as the ceiling standards for allowable levels of air 

pollution. EPA standards are designed to protect human health and the health of natural resources 

(EPA 2013a). The CAA also establishes that current visibility impairment in Class I areas must be 

remedied and future impairment prevented (EPA 2013a). To comply with CAA and NPS Organic 

Act mandates, the NPS established a monitoring program that measures air quality trends in many 

park units for key air quality indicators, including atmospheric deposition, ozone, and visibility (NPS 

2008).

Located along the Grand Valley in Colorado, the primary pollutants likely to affect air quality at 

COLM include nitrogen (N) and sulfur (S) compounds (nitrate [NO3-], ammonium [NH4+], and 

sulfate [SO4

2-

]); ground-level ozone (O3); haze-causing particles; and airborne toxics (Ksienya 

Pugacheva, NPS Air Resources Division Natural Resources Specialist, written communication, 11 

December 2015). These challenges to air quality are generated by a variety of sources including; 

local emissions generated by traffic and development, air inversions, and through contaminants 

carried into the region via prevailing seasonal winds. Air pollution may impair the scenic views that 

many visitors come to COLM to enjoy.

4.16.2 Measures

 Atmospheric deposition of sulfur and nitrogen

 Ozone

 Particulate matter

 Visibility

 Atmospheric deposition of mercury
288

Atmospheric Deposition of Sulfur and Nitrogen

Sulfur and nitrogen are emitted into the atmosphere primarily through the burning of fossil fuels, 

industrial processes, and agricultural activities (EPA 2012a). While in the atmosphere, these 

emissions form compounds that may be transported long distances and settle out of the atmosphere in 

the form of pollutants such as particulate matter (e.g., sulfates, nitrates, ammonium) or gases (e.g., 

nitrogen dioxide, sulfur dioxide, nitric acid, ammonia) (EPA 2012a, NPS 2008). Atmospheric 

deposition can be in wet (i.e., pollutants dissolved in atmospheric moisture and deposited in rain, 

snow, low clouds, or fog) or dry (i.e., particles or gases that settle on dry surfaces as with windblown 

dusts) form (EPA 2012a). Deposition of sulfur and nitrogen can have significant effects on 

ecosystems including acidification of water and soils, excess fertilization or increased eutrophication, 

changes in the chemical and physical characteristics of water and soils, and accumulation of toxins in 

soils, water and vegetation (NPS 2008, reviewed in Sullivan et al. 2011a and 2011b).

Ozone

Ozone occurs naturally in the earth’s upper atmosphere where it protects the earth’s surface against 

ultraviolet radiation (EPA 2012a). However, it also occurs at the ground level (i.e., ground-level 

ozone) where it is created by a chemical reaction between nitrogen oxides (NOx) and volatile organic 

compounds (VOCs) in the presence of heat and sunlight (NPS 2008). Ozone precursors are emitted 

from a variety of source types, including power plants, industry, motor vehicles, oil and gas 

development, and others. Forest fires also emit ozone precursors (EPA 2014a).

Ozone is one of the most widespread pollutants affecting vegetation in the U.S. (NPS 2008). 

Considered phytotoxic, ozone can cause significant foliar injury and growth effects for sensitive 

plants in natural ecosystems (NPS 2008, EPA 2012b). Specific effects include reduced 

photosynthesis, premature leaf loss, and reduced biomass; prolonged exposure can increase 

vulnerability to insects and diseases or other environmental stresses (NPS 2008). Plant species 

occurring in COLM that are known to be sensitive to ozone include quaking aspen and ponderosa 

pine (Kohut 2004).

At high concentrations, ozone can aggravate respiratory and cardiovascular diseases in humans, by 

reduced lung function, acute respiratory problems, and increased susceptibility to respiratory 

infections (EPA 2012a, 2012c, 2013b). Visitors and staff engaging in aerobic activities in the park, 

such as hiking, as well as children, the elderly, and people with heart and lung diseases are especially 

sensitive to elevated ozone levels.

Particulate Matter and Visibility

Particulate matter (PM) is a complex mixture of extremely small particles and liquid droplets that 

become suspended in the atmosphere. Particulate matter largely consists of acids (such as nitrates and 

sulfates), organic chemicals, metals, and soil or dust particles (EPA 2013c, 2014a). There are two 

particle size classes of concern: PM2.5 – fine particles found in smoke and haze, which are 2.5 

micrometers in diameter or less; and PM10 – coarse particles found in wind-blown dust, which have 

diameters between 2.5 and 10 micrometers (EPA 2012a). Fine particles are a major cause of reduced 

visibility (haze) in many national parks and wildernesses (EPA 2012a). PM2.5 can be directly emitted 

from sources such as forest fires or they can form when gases emitted from power plants, industry 
289

and/or vehicles react with air (EPA 2013c, EPA 2014a). Particulate matter either absorbs or scatters 

light. As a result, the clarity, color, and distance seen by humans, decreases, especially during humid 

conditions when additional moisture is present in the air (EPA 2012a, 2013c). PM2.5 is also a concern 

for human health as these particles can easily pass through the throat and nose and enter the lungs 

(EPA 2012a, 2013c, 2014a). Short-term exposure to these particles can cause shortness of breath, 

fatigue, and lung irritation (EPA 2012a, 2013c).

Atmospheric Deposition of Mercury

Sources of atmospheric mercury (Hg) include fuel combustion and evaporation (especially coal-fired 

power plants), waste disposal, mining, industrial sources, and natural sources such as volcanoes and 

evaporation from enriched soils, wetlands, and oceans (EPA 2008). Atmospheric deposition of Hg 

from coal-burning power plants has been identified as a major source of Hg to remote ecosystems 

(Landers et al. 2008). Because of the size and number of coal-burning power plants in the NCPN

region, Hg is a potential problem for ecosystems in these parks (Pugacheva, written communication, 

11 December 2015).

Mercury deposited into rivers, lakes, and oceans can accumulate in various aquatic species, resulting 

in exposure to wildlife and humans that consume them (EPA 2008). Mercury exposure can cause 

liver, kidney, and brain (neurological and developmental) damage (EPA 2008). High mercury 

concentrations in birds, mammals, and fish can result in reduced foraging efficiency, survival, and 

reproductive success (Mast et al. 2010; Eagles-Smith et al. 2014).

4.16.3 Reference Conditions/Values

The NPS Air Resources Division (ARD) developed an approach for rating air quality conditions in 

national parks, based on the current NAAQS, ecosystem thresholds, and visibility improvement goals 

(NPS 2015c). This approach is discussed by indicator in the following paragraphs and the ratings are 

summarized in Table 79 and Table 80.

Table 79. National Park Service Air Resources Division air quality index values for wet deposition of 

nitrogen or sulfur, ozone, particulate matter, and visibility (NPS 2015c).

Condition Level

Wet Deposition 

of N or S

(kg/ha-yr)

Human Health 

Risk from O3

(ppb)

Vegetation Health 

Risk from O3

(ppm-hrs)

Human Health 

Risk from PM25

(ppb)

Visibility 

(dv*)

Significant Concern >3 ≥71 >13 ≥35.5 >8

Moderate Concern 1–3 55–70 7-13 12.1–35.4 2–8

Good Condition <1 ≤55 <7 ≤12 <2

*a unit of visibility proportional to the logarithm of the atmospheric extinction; one deciview represents 

the minimal perceptible change in visibility to the human eye.

Atmospheric Deposition of Sulfur and Nitrogen

Assessment of current condition of nitrogen and sulfur atmospheric deposition is based on wet (rain 

and snow) deposition. Wet deposition is used as a surrogate for total deposition (wet plus dry), 

because wet deposition is the only nationally available monitored source of nitrogen and sulfur 

deposition data (NPS 2015c). Values for nitrogen (from ammonium and nitrate) and sulfur (from 
290

sulfate) wet deposition are expressed as amount of nitrogen or sulfur in kilograms deposited over a 

one-hectare area in one year (kg/ha/yr). The NPS ARD selected a wet deposition threshold of 1.0 

kg/ha/yr as the level below which natural ecosystems are likely protected from harm, based on 

studies linking early stages of aquatic health decline correlated with 1.0 kg/ha/yr wet deposition of 

nitrogen both in the Rocky Mountains (Baron et al, 2011), and in the Pacific Northwest (Sheilbley et

al. 2014). Parks with less than 1 kg/ha/yr of atmospheric wet deposition of nitrogen or sulfur 

compounds are assigned Good Condition, those with 1–3 kg/ha/yr are assigned Moderate Condition, 

and parks with depositions greater than 3 kg/ha/yr are assigned Significant Concern (NPS 2015c).

Table 80. National Park Service Air Resources Division air quality assessment matrix for mercury status 

(NPS 2015c). Green = Good condition, yellow = Moderate Concern, and Red = Significant Concern.

Predicted Methylmercury 

Concentration Rating

MercuryWet Deposition Rating

Very Low

(<3 g/m2/yr)

Low

( 3–<6 

g/m2/yr)

Moderate

( 6–<9

g/m2/yr)

High

( 9–<12 

g/m2/yr)

Very High

( 12 g/m2/yr)

Very Low (< 0.038 ng/L)

Low ( 0.038–< 0.053 ng/L)

Moderate ( 0.053–<0.075

ng/L)

High ( 0.075–<0.12 ng/L)

Very High ( 0.12 ng/L)

Ozone

The primary NAAQS for ground-level ozone is set by the EPA, and is based on human health effects. 

The 2008 NAAQS for ozone was a 4th-highest daily maximum 8-hour ozone concentration of 75 ppb

(parts per billion) (NPS 2015c). On October 1, 2015, the EPA strengthened the national ozone 

standard by setting the new level at 70 ppb (Pugacheva, written communication, 11 December 2015). 

The NPS ARD recommends a benchmark for Good Condition ozone status in line with the updated 

Air Quality Index (AQI) breakpoints (NPS 2015c).

Current condition for human health risk from ozone is based on the estimated 5-year 4th-highest daily 

maximum 8-hour ozone average concentration in ppb (NPS 2015c). Ozone concentrations greater 

than or equal to 71 ppb are assigned a Significant Concern (NPS 2015c). Ozone concentrations from 

55–70 ppb are assigned Moderate Condition (NPS 2015c). A Good Condition is identified when 

ozone concentrations are less than 55 ppb (NPS 2015c).

In addition to being a concern to human health, long-term exposures to ozone can cause injury to 

ozone-sensitive plants (EPA 2014b). The W126 metric relates plant response to ozone exposure and 

is a better predictor of vegetation response than the metric used for the primary (human-health based) 

standard (EPA 2014b). The W126 metric measures cumulative ozone exposure over the growing 

season in “parts per million-hours” (ppm-hrs) and is used for assessing the vegetation health risk 

from ozone levels (EPA 2014b).
291

The W126 condition thresholds are based on information in EPA’s Policy Assessment for the 

Review of the Ozone NAAQS (EPA 2014b). Research has found that for a W126 value of:

 ≤ 7 ppm-hrs, tree seedling biomass loss is ≤ 2 % per year in sensitive species; and

 ≥13 ppm-hrs, tree seedling biomass loss is 4–10 % per year in sensitive species.

NPS ARD recommends a W126 of < 7 ppm-hrs to protect most sensitive trees and vegetation and is 

considered Good Condition; 7-13 ppm-hrs to be in Moderate Condition; >13 ppm-hrs is considered 

to be of Significant Concern (NPS 2015c).

Particulate Matter

The particulate matter condition is based on the NAAQS for PM2.5 and PM10, which are established 

by EPA to protect human health (NPS 2015c). NPS units that are in EPA designated nonattainment 

areas for particulate matter are assigned Significant Concern condition for particulate matter (NPS 

2015c). The NAAQS primary standard for PM2.5 is a weighted annual mean of 15.0 μg/m3or 35 

μg/m3in a 24-hour period over an average of 3 years (EPA 2011a). The primary and secondary 

NAAQS for PM10 measured over a 24-hour period is set at 150 μg/m3(EPA 2011a).

For NPS units that are outside particulate matter nonattainment areas, EPA AQI breakpoints for 24-

hour average (μg/m3) are used to assign a particulate matter condition (NPS 2015c). PM2.5

concentrations greater than or equal to 35.5 ppb are assigned a Significant Concern (NPS 2015c). 

PM2.5 concentrations from 35.4–12.1 ppb are assigned Moderate Condition (NPS 2015c). A Good 

Condition is identified when PM2.5 concentrations are less than or equal to 12 ppb (NPS 2015c).

Visibility

Visibility conditions are assessed in terms of a Haze Index, a measure of visibility (termed deciviews 

[dv]) that is derived from calculated light extinction and represents the minimal perceptible change in 

visibility to the human eye (NPS 2011). Conditions measured near 0 dv are clear and provide 

excellent visibility, and as dv measurements increase, visibility conditions become hazier (NPS 

2011). NPS ARD assesses visibility condition status based on the deviation of the estimated current 

visibility on mid-range days from estimated natural visibility on mid-range days (i.e., those estimated 

for a given area in the absence of human- caused visibility impairment, EPA-454/B003- 005) (NPS 

2015c). The NPS ARD chose reference condition ranges to reflect the variation in visibility 

conditions across the monitoring network (NPS 2015c). Visibility on mid-range days is defined as 

the mean of the visibility observations falling within the range of the 40th through the 60th percentiles 

(NPS 2015c). A visibility condition estimate of less than 2 dv above estimated natural conditions 

indicates a Good Condition, estimates ranging from 2-8 dv above natural conditions indicate 

Moderate Condition, and estimates greater than 8 dv above natural conditions indicate Significant 

Concern (NPS 2015c).

Visibility trends are computed from the Haze Index values on the 20% haziest days and the 20% 

clearest days, consistent with visibility goals in the CAA and Regional Haze Rule, which include

improving visibility on the haziest days and allowing no deterioration on the clearest days (NPS 

2015c). Although this legislation provides special protection for NPS areas designated as Class I, the 
292

NPS applies these standard visibility metrics to all units of the NPS. If the Haze Index trend on the 

20% clearest days is deteriorating, the overall visibility trend is reported as deteriorating (NPS 

2015c). Otherwise, the Haze Index trend on the 20% haziest days is reported as the overall visibility 

trend (NPS 2015c).

Mercury Deposition

The condition of mercury was assessed using estimated 3-year average mercury wet deposition 

(micrograms per meter squared per year [μg/m2/yr]) and the predicted surface water methylmercury 

concentrations (nanograms per liter [ng/L]) at NPS I&M parks (NPS 2015c). It is important to 

consider both mercury deposition inputs and ecosystem susceptibility to mercury methylation when 

assessing mercury condition because atmospheric inputs of elemental or inorganic mercury must be 

methylated before it is biologically available and able to accumulate in food webs (NPS 2015c). 

Thus, mercury condition cannot be assessed according to mercury wet deposition alone. Other factors 

like environmental conditions conducive to mercury methylation (e.g., dissolved organic carbon, 

wetlands, pH) must also be considered (NPS 2015c). Mercury wet deposition and predicted 

methylmercury concentrations are considered concurrently in the mercury status assessment matrix 

displayed below to identify one of three park-specific mercury/toxics status categories: Good 

Condition, Moderate Condition, and Significant Concern. (NPS 2015c)

4.16.4 Data and Methods

Monitoring in the Park

Air quality monitoring in the park has been limited. Ozone was monitored from June 2006 through 

September 2012 using a portable ozone monitoring station (POMS) (Perkins 2010, EPA 2015). 

Ozone was also monitored at the park from 1990–1992; while these data are too outdated to be useful 

in determining current condition, they may provide insight into trends over time. Historic data were 

obtained through the EPA AirData website (EPA 2015). Atmospheric deposition, PM2.5, and 

visibility have not been measured within COLM.

NPS Data Resources

Although data on most air quality parameters are not actively collected within park boundaries, data 

collected at several regional monitoring stations for various parameters can be used to estimate air 

quality conditions in COLM (Figure 59). NPS ARD provides estimates of ozone, wet deposition 

(nitrogen, sulfur, and mercury), and visibility that are based on interpolations of data from all air 

quality monitoring stations operated by NPS, EPA, various states, and other entities, averaged over 

the most recent 5 years (2009–2013). Estimates and conditions data for COLM were obtained from 

the NPS Air Quality by Park data products page 

(http://www.nature.nps.gov/air/data/products/parks/index.cfm).

On-site or nearby data are needed for a statistically valid trends analysis. There are no on-site or 

nearby representative monitors to assess ozone and nitrogen, sulfur and mercury deposition trends. 

For visibility trend analysis, monitoring data from an Interagency Monitoring of Protected Visual 

Environments Program (IMPROVE) is required (NPS 2015c). An IMPROVE monitoring site 

considered being representative of a Class II park has to be between within +/- 30.48 m (100 ft) or 
293

10% of maximum and minimum elevation of the park and at a distance of no more than 150 km (93 

mi) (NPS 2015c). The IMPROVE Canyonlands National Park site (CANY1; operational since March 

1988) meets this criteria and was used to represent COLM (Figure 59) (NPS 2015c). 

Figure 59. Location of air quality monitoring sites that provided data used in the air quality analysis for 

COLM.
294

Other Air Quality Data Resources

The EPA Air Trends Database provides annual average summary data for nitrogen deposition, PM2.5

concentrations, and visibility near COLM (EPA 2015). The nearest PM2.5 monitor is located in Grand 

Junction (Powell Building, Site ID: 08-077-0017) and operated by the Colorado Department of 

Public Health and the Environment (Figure 59). This station, which has collected data from 2002–

2015, is located approximately 7 km (4.3mi) from the COLM boundary. Although NPS ARD has not 

developed national guidelines for selecting representative particulate matter monitoring sites, this 

location is considered reasonable for evaluating local conditions (Pugacheva, written communication, 

11 December 2015).

The National Atmospheric Deposition Program–National Trends Network (NADP NTN) database 

provides annual average summary data for nitrogen and sulfur concentration and deposition across 

the U.S. (NADP 2015a). The NADP NTN monitoring site closest to COLM is located at 

Canyonlands National Park, in eastern Utah (site ID: UT09), approximately 115 km (71.5 mi)

southwest of COLM (Figure 59). This site has collected deposition data for the region since 1997 and 

is currently active in monitoring (NADP 2015a). Data summaries, for this monitor are viewable on 

the NPS Air Quality by Park data products page (NPS 2015a).

The NADP Mercury Deposition Network (MDN) provides weekly summary data for mercury 

deposition and concentration (NADP 2015b). Wet mercury deposition trends are evaluated using 

pollutant concentrations in precipitation (micro equivalents/liter) so that yearly variations in 

precipitation amounts do not influence trend analyses. Trends are computed for parks with a 

representative NADP MDN wet deposition monitor that is within 16 km of park boundaries (NPS 

2015c). The monitor closest to COLM is at Mesa Verde National Park in southwestern Colorado, 

nearly 200 km (120 mi) south of COLM (NADP 2015b) (Figure 59). Predicted methylmercury 

concentrations in surface water were obtained from a model that predicts surface water 

methylmercury concentrations for hydrologic units throughout the U.S. based on relevant water 

quality characteristics (pH, sulfate, and total organic carbon) and wetland abundance (USGS 2015).

Special Air Quality Studies

Sullivan et al. (2011a) identified ecosystems and resources at risk to acidification and excess nitrogen 

enrichment in national parks. These reports provide a relative risk assessment of acidification and 

nutrient enrichment impacts from atmospheric nitrogen and sulfur deposition for parks in 32 I&M 

networks. Ecosystem sensitivity ratings to acidification from atmospheric deposition were based on 

percent sensitive vegetation types, number of high-elevation lakes, length of low- order streams, 

length of high-elevation streams, average slope, and acid-sensitive areas within the park (Sullivan et 

al. 2011a). Ecosystem sensitivity ratings to nutrient enrichment effects were based on percent 

sensitive vegetation types and number of high-elevation lakes within the park (Sullivan et al. 2011b).

Kohut et al. (2004) employed a biologically-based method to evaluate the risk of foliar injury from 

ozone at parks within the 32 Vital Signs Networks, the Appalachian National Scenic Trail, and the 

Natchez Trace National Scenic Trail. The assessment allows resource managers at each park to better 

understand the risk of ozone injury to vegetation within their park and permits them to make a better 

informed decision regarding the need to monitor the impacts of ozone on plants.
295

Pardo et al. (2011) synthesizes current research relating atmospheric nitrogen deposition to effects on 

terrestrial and aquatic ecosystems in the U.S. and to identify empirical critical loads for atmospheric 

nitrogen deposition.

4.16.5 Current Condition and Trend

Atmospheric Deposition of Nitrogen and Sulfur

Five-year interpolated averages of nitrogen (from nitrate and ammonium) wet deposition and sulfur 

(from sulfate) wet deposition are used to estimate condition for deposition. The current 5-year 

average (2009-2013) estimates wet deposition of nitrogen in COLM is 1.1 kg/ha/yr, while wet

deposition of sulfur is 0.5 kg/ha/yr (NPS 2015b). Relative to the NPS ratings for air quality 

conditions (see Table 79 for ratings values), atmospheric deposition of nitrogen is in the Moderate 

Condition category, while sulfur deposition falls into the Good Condition category.

In addition to assessing wet deposition levels, critical loads can also be a useful tool in determining 

the extent of deposition impacts (i.e., nutrient enrichment) to park resources (Pardo et al. 2011). A 

critical load, defined as the level of deposition below which harmful effects to the ecosystem are not 

expected (Pardo et al. 2011). For COLM, Pardo et al. (2011) suggested following critical load ranges 

for total nitrogen deposition (wet plus dry) in the North American Deserts ecoregion:

 3.0 kg/ha/yr to protect lichen

 3.0–8.4 kg/ha/yr to protect herbaceous vegetation

The lowest critical load level (3.0 kg/ha/yr) is identified as an appropriate management goal because 

it will protect the full range of vegetation in the park (Pardo et al. 2011). The estimated 2010–2012 

average for total (wet plus dry) nitrogen deposition was 3.0 kg/ha/yr in the North American Deserts 

ecoregion where COLM is located (Pardo et al. 2011). Therefore, the total nitrogen deposition level 

in the park is at the minimum ecosystem critical load for some park vegetation communities, 

suggesting that lichen and herbaceous vegetation is at risk for harmful effects.

Concentrations (mg/L) of nitrogen, sulfur, and ammonium compounds in wet deposition can be used 

to evaluate trends in deposition of nitrogen and sulfur. Since atmospheric wet deposition can vary 

greatly depending on the amount of precipitation that falls in any given year, it can be useful to 

examine concentrations of pollutants, which factor out the variation introduced by precipitation. 

Annual averages from Canyonlands National Park (1998-2014) suggest that nitrate concentrations in 

the COLM region have varied between years but with no statistically significant trends (NPS 2015a). 

Ammonium and sulfate concentrations have remained more stable with no statistically significant 

trends (NPS 2015a). Figure 60, Figure 61, and Figure 62 show the annual concentration of nitrate, 

sulfate, and ammonium recorded at the Canyonlands National Park NADP monitor (approximately 

115 km [71.5 mi] southwest of the park).

Ecosystems in the park were rated as having high sensitivity to acidification effects and low 

sensitivity to nutrient enrichment effects relative to all Inventory & Monitoring parks (Sullivan et al. 

2011c; Sullivan et al. 2011d).
296

Figure 60. Ten year trend (2004–2013) in annual average concentrations (μeq/l) of nitrate in precipitation 

at Canyonlands National Park (NADP monitoring site UT09) (NPS 2015a). Graph was produced by the 

NPS ARD Air quality conditions and trends website (NPS 2015a).

Figure 61. Ten year trend (2004–2013) in annual average concentrations (μeq/l) of sulfate in precipitation 

at Canyonlands National Park (NADP monitoring site UT09) (NPS 2015a). Graph was produced by the 

NPS ARD Air quality conditions and trends website (NPS 2015a).
297

Figure 62. Ten year trend (2004–2013) in annual average concentrations (μeq/l) of ammonium in 

precipitation at Canyonlands National Park (NADP monitoring site UT09) (NPS 2015a). Graph was 

produced by the NPS ARD Air quality conditions and trends website (NPS 2015a).

Ozone

The condition of human risk from ozone in NPS units is determined by calculating the 5-year 

average of the fourth-highest daily maximum of 8-hour average ozone concentrations measured at 

each monitor within an area over each year (NPS 2011). The most recent 5-year (2009–2013) 

estimated average for 4th highest 8-hour ozone concentration at COLM is 65.9 ppb (NPS 2015b), 

which is considered Moderate Condition.

Vegetation health risk from ground-level ozone condition is determined by estimating a five-year 

average of annual maximum 3-month 12-hour W126 values. The 2009–2013 estimated W126 metric 

of 9.5 ppm-hrs falls in the Moderate Condition category (NPS 2015b).

Ozone was monitored at COLM from June 2006 to September 2012 (Perkins 2010, EPA 2015).

Figure 63 illustrates the trend in annual fourth-highest daily maximum 8-hour values during this 

period. For 2006-2012, the trend in ozone concentration remained relatively unchanged (no 

statistically significant trend) (NPS 2015b). Concentrations ranged from 58.0 ppb in 2009 to 72.0 ppb 

for 2006 (June–Dec.) (EPA 2015). All measurements were below the 2008 national standard 

considered protective of human health, although two years (2006, 2012) were within 5 ppb of the 

2008 ozone standard (Figure 63). These concentrations were slightly higher than those measured in 

COLM from 1990–1992, when ozone ranged from 59 to 66 ppb (EPA 2015).
298

Figure 63. Annual 4th highest 8-hour maximum ozone (O3) concentrations (ppb) at COLM, 2006-2012 

(EPA 2015).

For 2006–2012, the trend in the W126 metric at COLM also remained relatively unchanged (no 

statistically significant trend) (NPS 2015b). Values ranged from 3.6 to 22.9 ppm-hrs and three of 

years had values greater than 13 ppm-hr or the significant concern category level (Figure 64, NPS 

2015b).

Figure 64. W126 ozone exposure index for vegetation concentrations ( (ppm–hrs) at COLM (NPS 

2015a). Graph was produced by the NPS ARD Air quality conditions and trends website (NPS 2015a).

Kohut (2004) assessed ozone concentrations in the NCPN and the risk of injury to plant species that 

are sensitive to sustained ozone exposure. Estimations by kriging indicate that, from 1995-1999, 

ambient ozone concentrations in COLM frequently exceeded 60 ppb and only occasionally exceeded 

80 ppb (less than 30 hours each year); concentrations exceeded 100 ppb very rarely (total of 7 hours 

30

35

40

45

50

55

60

65

70

75

80

2006 2007 2008 2009 2010 2011 2012

Ozone (ppb)

2008 National Ozone Standard

2015 National Ozone Standard
299

across 5 years of monitoring) (Kohut 2004). Sensitive plant species begin to experience foliar injury 

when exposed to ozone concentrations of 80-120 ppb/hour for extended periods of time (8 hours or 

more), and drier soil conditions can decrease the ability of plants to absorb ozone; thus increasing 

ambient ozone concentrations (Kohut 2004). However, the infrequent incidence of concentrations 

higher than 80 ppb in COLM and rare or mild drought conditions made the risk of foliar injury from 

ozone low at that time (Kohut 2004). If the level of risk increases in the future, ozone foliar damage 

may be assessed using quaking aspen and ponderosa pine as indicator species (Kohut 2004). Ozone 

sensitive vegetation species found within COLM are common dogbane, coyote willow, Goodding's 

black willow (Salix gooddingii), singleleaf ash, quaking aspen, and Utah serviceberry (NPS 2015d).

Particulate Matter

COLM is located in the Mesa County, Colorado, which meets the NAAQS for the PM2.5 24-hour and 

annual PM2.5 public health standards as well as the 24-hour PM10 standard (Pugacheva, written 

communication, 11 December 2015). Therefore, the park is within an EPA-designated attainment 

area for both PM2.5 and PM10 (EPA 2015). Particulate matter concentrations collected at a monitor in 

Grand Junction are available from 2002 through 2015. The 3-year (2013–2015) average of 98th

percentile 24-hour PM2.5 concentration at the Grand Junction monitor is 27.3 μg /m3and the annual 

mean PM2.5 concentration is 7.5 μg /m3(EPA 2015). The 3-year (2013–2015) average of the annual 

mean PM10 concentration is 18 μg /m3(EPA 2015). The 98th percentile 24-hour PM2.5 concentration 

falls into the Moderate Condition category based on EPA AQI categories (NPA2015c).

Weighted annual average 24-hour PM2.5 concentrations for 2005-2015 are shown in Figure 65. Daily 

hourly values ranged from a minumum of 1.2 μg /m3on 7 February 2014 to a maximum of 59.1 μg 

/m3on 1 January 2009 (EPA 2015). Overall, during this 10-year period, the weighted concentrations 

appeared to be relatively stable in Grand Junction, with a slight decline in recent years (EPA 2015).

The weighted concentrations never exceeded 10 μg/m3, and were well within the EPA standards for 

levels that are protective of human health during this period (Figure 65).

Figure 65. Annual 24-hour particulate matter (PM2.5) concentrations (weighted annual mean) near COLM, 

2005-2015 (EPA 2015). Monitoring station is located in Grand Junction (Powell Building).

2

4

6

8

10

12

14

16

18

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Concentration (μg/m3)

National Standard
300

The annual average 24-hour PM10 concentrations for 2005-2015 are shown in Figure 66. Daily 

hourly values ranged from a minumum of 2 μg /m3on three occasions (19 April 2005, 1 November 

2014, and 1 June 2015) to a maximum of 169 μg /m3on 19 April 2005 (EPA 2015). Similar to the 

24-hour PM2.5 results, during this 10-year period, the weighted concentrations appeared to be 

relatively stable in Grand Junction, with a slight decline in recent years (EPA 2015). The weighted 

concentrations never exceeded 150 μg/m3, and were well within the EPA standards for levels that are 

protective of human health during this period (Figure 65).

Figure 66. Annual 24-hour particulate matter (PM10) concentrations (weighted annual mean) near COLM, 

2005-2015 (EPA 2015). Monitoring station is located in Grand Junction (Powell Building).

Visibility

Five-year estimated averages of visibility on mid-range days minus natural condition visibility on 

mid-range days is used to estimate condition for visibility. The 2009–2013 estimated visibility on 

mid-range days was 2.9 dv above estimated natural conditions (NPS 2015c). This estimate falls into 

the Moderate Condition category based on NPS criteria for air quality assessment. 

For 2004–2013, the trend in visibility at the Canyonlands IMPROVE monitor remained relatively 

unchanged (no statistically significant trend) on the 20% clearest days (Figure 67) and remained 

relatively unchanged (no statistically significant trend) on the 20% haziest days (Figure 68) (NPS 

2015a). The primary visibility impairing pollutants on both the clearest and haziest days from 2009–

2013 were ammonium sulfate, ammonium nitrate, coarse mass, and organic carbon (Figure 67 and 

Figure 68, NPS2013b). Ammonium sulfate originates mainly from coal-fired power plants and 

smelters; ammonium nitrate mainly originates from coal-fired power plants, mobile sources, and oil 

and gas development; coarse mass consists of wind-blown dust, while organic carbon originates 

primarily from combustion of fossil fuels and biomass, as well as directly from vegetation (NPS 

2015a).

0

20

40

60

80

100

120

140

160

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Concentration (μg/m3)

National Standard
301

Figure 67. Ten year trend (2004–2013) in visibility for the 20% clearest days (dv) for COLM. Values were 

interpolated from conditions at Canyonlands National Park (NADP monitoring site UT09) (NPS 2015a). 

Graph was produced by the NPS ARD Air quality conditions and trends website (NPS 2015a).

Figure 68. Ten year trend (2004–2013) in visibility for the 20% clearest days (dv) for COLM. Values were 

interpolated from conditions at Canyonlands National Park (NADP monitoring site UT09) (NPS 2015a). 

Graph was produced by the NPS ARD Air quality conditions and trends website (NPS 2015a).
302

Figure 69. Composition of haze on clearest days (2009–2013) for COLM. Data were interpolated from 

Canyonlands National Park (NADP monitoring site UT09) (NPS 2015a). Graph was produced by the NPS 

ARD Air quality conditions and trends website (NPS 2015a).

Figure 70. Composition of haze on haziest days (2009–2013) for COLM. Data were interpolated from 

Canyonlands National Park (NADP monitoring site UT09) (NPS 2015a). Graph was produced by the NPS 

ARD Air quality conditions and trends website (NPS 2015a).
303

Atmospheric Deposition of Mercury

The 2011–2013 estimated wet mercury deposition is low at the park, ranging from 4.9 to 5.7 

μg/m2/yr and predicted methylmercury concentrations in surface waters is very high, ranging from 

0.11 to 0.12 ng/l (NPS 2015c). To maintain the highest level of protection in the park, the highest 

values for each factor were compared to mercury status assessment matrix (see Table 80) to 

determine the Moderate Condition status.

The NPS ARD has measured mercury wet deposition at 16 parks across the U.S (NPS 2013). The 

location closest to COLM where monitoring has occurred is Mesa Verde National Park, 

approximately 200 km (120 mi) south of COLM (Figure 59). The 3-year (2011–2013) average wet 

mercury deposition at Mesa Verde is 9.7 ng/l (NADP 2015b). Interpolations based on 2013 data 

suggest that COLM may be on the edge of a “hot spot” for mercury deposition (Figure 71, NADP 

2014). According to the NPS (2013), mercury deposition did not show any trends from 2000-2009. 

As with nitrogen and sulfur deposition, concentrations of mercury in wet deposition can be used to 

evaluate trends in mercury deposition.

Figure 71. Total annual mercury wet deposition in 2013 (NADP 2014).

The 3-year (2011–2013) average mercury concentration at the Mesa Verde site is of 27.1 ng/l

(NADP 2015b). Interpolations suggest that mercury concentrations were relatively high in portions 

of several western states, including southwest Colorado near COLM (Figure 72, NADP 2014).

Eagles-Smith et al. (2014) examined fish from 21 national parks in the western U.S., including two 

NCPN parks, Capitol Reef National Park (in the Fremont River) and Zion National Park (Virgin 

River). This study found elevated mercury levels in small prey fish (speckled dace [Rhinichthys 

osculus]) at both parks. Speckled dace serve as potential prey for predatory fishes and piscivorous 

birds, and concentrations in dace from both parks exceeded levels associated with biochemical and 

reproductive effects in fish and reproductive impairment in birds (Eagles-Smith et al. 2014).
304

Figure 72. Total mercury concentrations in 2013 (NADP 2014).

Threats and Stressor Factors

COLM NPS natural resource managers identified several potential threats to COLM’s air quality 

including oil and gas development, vehicle emissions from the valley, wildfire smoke and 

woodburning stoves, and visibility impacts from haze and inversions. 

COLM is located within the Uintah-Piceance oil and gas basins, an area with extensive historic and

ongoing oil and gas development (NGI 2015). The basins are located in northeastern Utah and 

northwestern Colorado. According to state agency databases, in 2015 there were approximately 

34,382 active, producing, drilling or permitted/permit application well sites within the basin 

(Pugacheva, written communication, 11 December 2015). In the past 10–12 years, new technologies 

in the oil and gas industry, such as horizontal drilling and hydraulic fracturing (e.g., unconventional 

development), have led to a resurgence in oil and natural gas production within the basins (NGI 

2015).

There are numerous types of equipment associated with oil and gas development and production, 

such as drill rigs, fracturing engines, valves, seals, compressors, heaters/treaters, separators, 

dehydration units, tanks, etc. Each of these individually small “sources” emit air pollutants (NOx, 

VOCs, greenhouse gases [GHGs], hydrogen sulfide [H2S], PM, and Hazardous air pollutants [HAPs] 

that cumulatively contribute to regional air quality concerns (Pugacheva, written communication, 11 

December 2015). In addition, exhaust and dust from motor vehicles on and near COLM emit 

nitrogen oxide, volatile organic compounds, and particulate matter (Pugacheva, written 

communication, 11 December 2015).

The majority of existing development within the basin lies to the north and northwest of the park. 

Significant air quality issues due to oil and gas activity within the basin have been identified, 

including violations of the ozone standard that occur under specific wintertime conditions and 

associated potential ozone nonattainment in the most active development regions (Lyman and 
305

Shorthill, 2013, Edwards et al., 2014). While COLM lies just to the south of this activity, and is 

outside of the areas exhibiting the most significant air quality impacts, NPS modeling results suggest 

that park air quality may be affected by oil and gas in the region (Pugacheva, written communication, 

11 December 2015). Consequently, ongoing air quality monitoring in the region is crucial to track the 

temporal and geographic extent of air quality issues in the basin, including areas on the periphery like 

COLM.

Droughts throughout the west have increased the frequency and severity of wildfires (Westerling et 

al. 2006), which produce particulates and can significantly impair visibility (Perkins 2010). Wildfires 

may also become more frequent if plant biomass increases as a result of nutrient enrichment from 

nitrogen deposition. Research in the arid environment of California’s Joshua Tree National Park 

showed that nitrogen deposition as low as 3 kg/ha/yr increased wildfire risk in pinyon-juniper 

communities, due to increased growth of fine fuels such as annual grasses (Rao et al. 2010).

According to the EPA and IPCC, global climate change is expected to negatively affect air quality 

(EPA 2011b). Both ozone and particulate pollution are heavily influenced by weather shifts. The 

EPA projects that climate change could increase summertime average ground-level ozone 

concentrations in many areas by 2-8 ppb. It could also cause particulate pollution to increase in some 

regions and decrease in others (EPA 2011b).

Data Needs/Gaps 

There are no wet deposition or ozone air quality monitors within the acceptable distance (to 

accurately represent conditions in the park. The nearest active NADP monitor that provides annual 

averages for nitrogen and sulfur deposition is located at Canyonlands National Park in eastern Utah, 

approximately 115 km (71.5 mi) southwest of COLM. The nearest visibility monitoring site is also at 

Canyonlands. The nearest mercury deposition monitor is even further away, at Mesa Verde National 

Park approximately 200 km (120 mi) to the south of COLM. Periodic or consistent monitoring of 

atmospheric deposition, ozone, and particulate matter would help managers better understand the 

local air quality conditions in and around COLM and how they may affect other park resources.

Overall Condition

Atmospheric Depositon of Sulfur and Nitrogen

The Significance Level for this measure was defined as a 3. Current NPS estimated averages for 

nitrogen deposition are considered to be in Moderate Condition while sulfur deposition is in Good 

Condition, based on NPS criteria for rating air quality. Sullivan et al. (2011c, 2011d) rated total 

nitrogen deposition at COLM at the minimum ecosystem critical load for some park vegetation 

communities, suggesting lichen and herbaceous vegetation is at risk for harmful effects. Overall, 

atmospheric deposition was assigned a Condition Level of 2, or of moderate concern.

Ozone Concentration

The Significance Level for ozone was also defined as a 3. Current human health and vegetation risk 

from ground-level ozone fall into the Moderate Condition category based on NPS criteria for rating 

air quality condition. Annual 4th highest 8-hour maximum concentrations from 2006 through 2013

were below EPA 2008 standard protective of human health, although two years were within 5 ppb of 
306

this level (EPA 2015). These concentrations were also slightly higher than those measured at COLM 

from 1990-1992 (59-66 ppb), suggesting a possible increasing trend in recent decades. Therefore, the 

Condition Level for ozone concentration was assigned a 2, indicating moderate concern.

Particulate Matter

The Significance Level for particulate matter was also defined as a 3. While all measurements were 

well within the EPA standards for levels that are protective of human health, the 98th percentile 24-

hour PM2.5 concentration falls into the Moderate Condition category based on EPA AQI categories. 

Weighted annual average PM2.5 concentrations at the Grand Junction monitor have been relatively 

stable, with a slight decline in recent years (EPA 2015). As a result of this, the Condition Level for 

particulate matter was assigned a 2, or of moderate concern.

Visibility

The Significance Level for visibility was also defined as a 3. Current interpolated average visibility 

estimates fall into the Moderate Condition category based on NPS criteria. Estimated visibility on the 

20% clearest days also falls just within the moderate concern category (close to good condition), 

while visibility on the 20% haziest days falls into the significant concern category. The Condition 

Level for visibility was assigned a 2, indicating visibility is of moderate concern.

Atmospheric Deposition of Mercury

This measure was assigned a Significance Level of 3. Based on estimated wet mercury deposition and 

predicted methylmercury concentrations in surface waters, the mercury deposition condition falls 

into the Moderate Condition category based on NPS criteria. Due to this the Condition Level for 

atmospheric deposition of mercury deposition was assigned a Condition Level of 2, meaning 

moderate concern.

Weighted Condition Score

The Weighted Condition Score for COLM air quality is 0.67, which is on the lower end of the 

significant concern range. A trend was not assigned, due to the lack of consistent data from within or 

near the park itself. Because of the use of interpolated air quality estimates for most measures rather 

than on-site data, the confidence level in this condition assessment is medium.
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Air Quality

Measures Significance Level Condition Level WCS = 0.67

Atmospheric Deposition 

of Sulfur and Nitrogen 3 2

Ozone Concentration 3 2

Particulate Matter 3 2

Visibility 3 2

Atmospheric Deposition 

of Mercury 2 2

4.16.6 Sources of Expertise

National Park Service Air Resources Division members Ksienya Pugacheva, Andrea Stacy, Barkley 

Sive, Michael George, John Vimont, Jim Cheatham, and Melanie Peters.

4.16.7 Literature Cited

Baron, J., C. Driscoll, J. Stoddard, and E. Richer. 2011. Empirical critical loads of atmospheric 

nitrogen deposition for nutrient enrichment and acidification of sensitive US lakes. BioScience 

61(8):602-613.

Eagles-Smith, C., J. Willacker, and C. Flanagan Pritz. 2014. Mercury in fishes from 21 national parks 

in the Western United States - Inter and intra-park variation in concentrations and ecological risk. 

U.S. Geological Survey Open-File Report 2014-1051. U.S. Geological Survey, Reston, Virginia.

Edwards, P, S. Brown, J. Roberts, R. Ahmadov, R. Banta, J. deGouw, W. Dubé, R. Field, J. Flynn, J. 

Gilman, and others. 2014. High winter ozone pollution from carbonyl photolysis in an oil and gas 

basin. Nature 514, 351–354.

Environmental Protection Agency (EPA). 2008. National air quality: Status and trends through 2007. 

EPA-454/R-08-006. Office of Air Quality Planning and Standards, Air Quality Assessment 

Division, Research Triangle Park, North Carolina.

Environmental Protection Agency (EPA). 2011a. Policy assessment for the review of the secondary 

national ambient air quality standards for oxides of nitrogen and oxides of sulfur. EPA-452/R-11-

005a. Office of Air Quality Planning and Standards Health and Environmental Impacts Division. 

Research Triangle Park, North Carolina.
308

Environmental Protection Agency (EPA). 2011b. Climate change and air quality. 

http://www.epa.gov/airquality/airtrends/2011/report/climatechange.pdf (accessed 22 July 2014).

Environmental Protection Agency (EPA). 2012a. Our nation’s air: Status and trends through 2010. 

EPA-454/R-12-001. Office of Air Quality Planning and Standards, Air Quality Assessment 

Division, Research Triangle Park, North Carolina.

Environmental Protection Agency (EPA). 2012b. Ground level ozone: Ecosystem effects. 

http://www.epa.gov/airquality/ozonepollution/ecosystem.html (accessed 2 June 2014).

Environmental Protection Agency (EPA). 2012c. Ground level ozone: Health effects. 

http://www.epa.gov/airquality/ozonepollution/health.html (accessed 2 June 2014).

Environmental Protection Agency (EPA). 2013a. Air and radiation: Clean Air Act Title I. 

http://epa.gov/oar/caa/title1.html#ic (accessed 4 April 2014).

Environmental Protection Agency (EPA). 2013b. Ground-level ozone standards designations. 

http://www.epa.gov/ozonedesignations/ (accessed 4 April 2014).

Environmental Protection Agency (EPA). 2013c. Particulate matter (PM). 

http://www.epa.gov/airquality/particlepollution/ (accessed 2 June 2014).

Environmental Protection Agency (EPA). 2014a. Air quality index: A guide to air quality and your 

health. EPA-456/F-14-002. Office of Air Quality Planning and Standards, Outreach and 

Information Division. Research Triangle Park, North Carolina. 

http://www.epa.gov/airnow/aqi_brochure_02_14.pdf (accessed 4 April 2014).

Environmental Protection Agency (EPA). 2014b. Policy assessment for the review of the ozone 

national ambient air quality standards: Second external review draft. Environmental Protection 

Agency, Office of Air Quality Planning and Standards, Ambient Standards Group, Research 

Triangle Park, North Carolina.

Environmental Protection Agency (EPA). 2015. Air data. http://www.epa.gov/airdata/ad_maps.html

(accessed 4 November 2015).

Kohut, R. J. 2004. Assessing the risk of foliar injury from ozone on vegetation in parks in the 

Northern Colorado Plateau Network. National Park Service, Fort Collins, Colorado. 

Landers, D., S. Simonich, D. Jaffe, L. Geiser, D. Campbell, A. Schwindt, C. Schreck, M. Kent, W. 

Hafner, H. Taylor, and others. 2008. The fate, transport, and ecological impacts of airborne 

contaminants in western National Parks (USA). U.S. Environmental Protection Agency Report 

EPA/600/R-07/138. Environmental Protection Agency, Office of Research and Development, 

NHEERL, Western Ecology Division, Corvallis, Oregon.
309

Lyman, S. and H. Shorthill. 2013. Final Report: 2012 Uintah Basin winter ozone & air quality study. 

Doc. No. CRD13-320.32, Commercialization and Regional Development, Utah State University, 

Logan, Utah.

Mast, M., D. Manthorne, D. Roth. 2010, Historical deposition of mercury and selected trace elements 

to high-elevation national parks in the Western U.S. inferred from lake-sediment cores. 

Atmospheric Environment 44(2010):2577-2586.

National Atmospheric Deposition Program (NADP). 2014. Annual MDN maps. National 

Atmospheric Deposition Program, Champaign, Illinois.

National Atmospheric Deposition Program (NADP). 2015a. National Atmospheric Deposition 

Program – National Trends Network monitoring location UT09 (Canyonlands, UT). 

http://nadp.sws.uiuc.edu/data/sites/map/?net=NTN (accessed 4 November 2015).

National Atmospheric Deposition Program (NADP). 2015b. National Atmospheric Deposition 

Program - Mercury Deposition Network monitoring location CO99 (Mesa Verde, CO). 

http://nadp.sws.uiuc.edu/data/sites/map/?net=MDN (accessed 5 November 2015).

National Park Service (NPS). 2008. Air Atlas summary tables for I & M parks. 

http://www.nature.nps.gov/air/permits/ARIS/networks/docs/SummariesAirAtlasRevised1107200

3.pdf (accessed 4 April 2014).

National Park Service (NPS). 2011. Rating air quality conditions. Air Resources Division, Natural 

Resources Program Center. National Park Service, Denver, Colorado. 

http://nature.nps.gov/air/planning/docs/20111122_Rating-AQ-Conditions.pdf (accessed 4 April 

2014).

National Park Service (NPS). 2013. Air quality in national parks: Trends (2000-2009) and conditions 

(2005-2009). Natural Resources Report NPS/NRSS/ARD/NRR—2013/683. National Park 

Service, Denver, Colorado.

National Park Service (NPS). 2015a. Air quality conditions and trends, Canyonlands NP. 

http://www.nature.nps.gov/air/data/products/parks/index.cfm (accessed 18 December 2015).

National Park Service (NPS). 2015b. Air quality conditions and trends, Colorado NM. 

http://www.nature.nps.gov/air/data/products/parks/index.cfm (accessed 18 December 2015).

National Park Service (NPS). 2015c. Draft National Park Service air quality analysis method. Air 

Resources Division, Natural Resources Program Center. National Park Service, Denver, 

Colorado.

National Park Service (NPS) 2015d. NPSpecies: Ozone sensitive species in Colorado National 

Monument (COLM). 

https://irma.nps.gov/NPSpecies/Reports/Systemwide/List%20of%20Ozone-sensitive%20Species

(accessed 18 December 2015).
310

Natural Gas Intelligence (NGI). 2015. North American shale and resource plays 2015 factbook. 

Natural Gas Intelligence, Sterling, Virginia. 

Pardo, L. M. Fenn, C. Goodale, L. Geiser, C. Driscoll, E. Allen, J. Baron, R. Bobbink, W. Bowman, 

C. Clark, and others. 2011. Effects of nitrogen deposition and empirical nitrogen critical loads for 

ecoregions of the United States. Ecological Applications 21(8):3049-2082

Perkins, D. W. 2010. Air quality monitoring in the Northern Colorado Plateau Network: Annual 

report 2009. Natural Resource Technical Report NPS/NCPN/NRTR—2010/374. National Park 

Service, Fort Collins, Colorado.

Rao, L. E., E. B. Allen, and T. Meixner. 2010. Risk-based determination of critical nitrogen 

deposition loads for fire spread in southern California deserts. Ecological Applications 

20(5):1320–1335.

Sheilbley, R., M. Enache, P. Swarzenski, P. Moran, and J.Foreman. 2014. Nitrogen deposition effects 

on diatom communities in lakes from three national parks in Washington state. Water, Air, and 

Soil Pollution 225:1-23.

Sullivan, T. J., G. T. McPherson, T. C. McDonnell, S. D. Mackey, and D. Moore. 2011a. Evaluation 

of the sensitivity of inventory and monitoring national parks to acidification effects from 

atmospheric sulfur and nitrogen deposition: Main report. Natural Resource Report 

NPS/NRPC/ARD/NRR—2011/349. National Park Service, Denver, Colorado.

Sullivan, T. J., T. C. McDonnell, G. T. McPherson, S. D. Mackey, and D. Moore. 2011b. Evaluation 

of the sensitivity of inventory and monitoring national parks to nutrient enrichment effects from 

atmospheric nitrogen deposition: Main report. Natural Resource Report 

NPS/NRPC/ARD/NRR—2011/313. National Park Service, Denver, Colorado.

Sullivan, T. J., T. C. McDonnell, G. T. McPherson, S. D. Mackey, and D. Moore. 2011c. Evaluation 

of the sensitivity of inventory and monitoring national parks to acidification effects from 

atmospheric sulfur and nitrogen deposition: Northern Colorado Plateau Network (NCPN). 

Natural Resource Report NPS/NRPC/ARD/NRR—2011/366. National Park Service, Denver, 

Colorado.

Sullivan, T. J., T. C. McDonnell, G. T. McPherson, S. D. Mackey, and D. Moore. 2011d. Evaluation 

of the sensitivity of inventory and monitoring national parks to nutrient enrichment effects from 

atmospheric nitrogen deposition: Northern Colorado Plateau Network (NCPN). Natural Resource 

Report NPS/NRPC/ARD/NRR—2011/321. National Park Service, Denver, Colorado.

U.S. Geological Survey. 2015. Predicted surface water methylmercury concentrations in National 

Park Service Inventory and Monitoring Program Parks. 

http://wi.water.usgs.gov/mercury/NPSHgMap.html (accessed 18 December 2015).

Westerling, A. L., H. G. Hidalgo, D. R. Cayan, and T. W. Swetnam. 2006. Warming and earlier 

spring increase western U.S. forest wildfire activity. Science 313(5789):940-943.
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4.17 Dark Night Skies

4.17.1 Description

A lightscape is a place or environment characterized by the natural rhythm of the sun and moon 

cycles, clean air, and of dark nights unperturbed by artificial light (NPS 2014). The NPS directs each 

of its units to preserve, to the greatest extent possible, these natural lightscapes (NPS 2006). Natural 

cycles of dark and light periods during the course of a day affect the evolution of species and other 

natural resource processes such as plant phenology (NPS 2006, 2014). Several species require 

darkness to hunt, hide their location, navigate, or reproduce (NPS 2014). In addition to the ecological 

importance of dark night skies, park visitors expect skies to be free of light pollution and allow for 

star observation. 

The resource of a dark night sky is important to the NPS for a variety of reasons. First, the 

preservation of natural lightscapes (the intensity and distribution of light on the landscape at night) 

will keep the nocturnal photopic environment within the range of natural variability. Excursions 

outside this natural range may result in a modification to natural ecosystem function, especially to 

systems involving the behavior and survival of nocturnal animals. The natural night sky is therefore 

one of the physical resources under which natural ecosystems have evolved. Second, the “scenery” of 

national park areas does not just include the daytime hours (NPS 2012). A natural starry sky absent 

of anthropogenic light is one of their key scenic resources, especially large wilderness parks remote 

from major cities. Third, the history and culture of many civilizations are steeped in interpretations of 

night sky observations, whether for scientific, religious, or time-keeping purposes (NPS 2012). As 

such, the natural night sky may be a very important cultural resource, especially in areas where 

evidence of aboriginal cultures is present. Fourth, the recreational value of dark night skies is 

important to campers and backpackers, allowing the experience of having a campfire or “sleeping 

under the stars” (NPS 2012). And fifth, night sky quality is an important wilderness value, 

contributing to the ability to experience a feeling of solitude in a landscape free from signs of human 

occupation and technology (NPS 2012).

4.17.2 Measures

During site visits, the NPS Natural Sounds and Night Skies Division (NSNSD) collects data for a 

suite of measures in order to define the current condition of dark night skies in a park unit. These 

measures typically include:

 Sky luminance over the hemisphere in high resolution (thousands of measurements comprise 

a data set), reported in photometric luminance units (V magnitudes per square arc second or 

milli-candela per square meter) or relative to natural conditions, often shown as a sky 

brightness contour map of the entire sky. V magnitude is a broadband photometric term in 

astronomy, meaning the total flux from a source striking a detector after passing through a 

“Johnson-Cousins V” filter. It is similar to the “CIE photopic” broadband function for 

wavelengths of light to which the human eye is sensitive (Bessell 1990);

 Integrated measures of anthropogenic sky glow from selected areas of sky that may be 

attributed to individual cities or towns (known as city light domes), reported in milli-Lux of 

hemispheric illuminance or vertical illuminance;
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 Integration of the entire sky illuminance measures, reported either in milli-Lux of total 

hemispheric (or horizontal) illuminance, milli-Lux of anthropogenic hemispheric (or 

horizontal) illuminance, V-magnitudes of the integrated hemisphere, or ratio of 

anthropogenic illuminance to natural illuminance;

 Vertical illuminance from individual (or groups of) outdoor lighting fixtures at a given 

observing location (such as the Wilderness boundary), in milli-Lux;

 Visual observations by a human observer, such as Bortle Class and Zenithal limiting 

magnitude;

 Integrated synthesized measure of the luminance of the sky within 50 degrees of the Zenith, 

as reported by the Unihedron Sky Quality Meter, in V magnitudes per square arc second.

4.17.3 Reference Conditions/Values

The reference condition for dark night skies in COLM was that of the dark night sky conditions 

during presettlement of the region. The reference condition for this resource is defined in terms of 

sky luminance and illuminance at the observer’s location from anthropogenic sources as follows:

No portion of the sky background brightness exceeds natural levels by more than 200 

percent, and the sky brightness at the Zenith does not exceed natural Zenith sky brightness by 

more than 10 percent. The ratio of anthropogenic hemispheric illuminance to natural 

hemispheric illuminance from the entire night sky does not exceed 20 percent. The observed 

light from a single visible anthropogenic source (light trespass) is not observed as brighter 

than the planet Venus (0.1 milli-Lux) when viewed from within any area of the park 

designated the naturally dark zone (Dan Duriscoe, NPS NSNSD, pers. comm., 2011).

Achieving this reference condition for preserving natural night skies is well summarized in the NPS 

Management Policies (2006) as follows in section 4.10:

The Service will preserve, to the greatest extent possible, the natural lightscapes of parks, 

which are natural resources and values that exist in the absence of human-caused light.

Implementing this directive in COLM requires that facilities within the park and local communities 

around the park meet outdoor lighting standards that provide for the maximum amount of 

environmental protection while meeting human needs for safety, security, and convenience. This 

means that outdoor lights within the park:

 produce zero light trespass beyond the boundary of their intended use; 

 be of an intensity that meets the minimum requirement for the task, but does not excessively 

exceed that requirement; 

 be of a color that is toward the yellow or orange end of the spectrum to minimize sky glow; 

 be controlled intelligently, preventing unnecessary dusk to dawn bright illumination of areas.
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4.17.4 Data and Methods

COLM is located in an area of west Colorado that is relatively close to Grand Junction, Colorado 

(one of Colorado’s largest cities). Smaller cities nearby include Fruita and Redlands. The close 

proximity to a major city may greatly impact the quality of its night sky. It is particularly important 

that within-park sources of light be contained, eliminating light trespass and minimizing 

anthropogenic sky glow.

Data were collected for baseline dark sky documentation in COLM from a ridgeline between the 

Visitor Center and the maintenance yard on 25 September 2014. Images were collected by Bob 

Meadows of the NPS NSNSD. Data were collected for a suite of measures during this visit. Figure 73

displays the data collection site (Alpine Camp) in relation to the Visitor Center.

4.17.5 Current Condition and Trend

Background for NPS Night Sky Division’s Suite of Measures

Anthropogenic light in the night environment can be very significant, especially on moonless nights. 

Unshielded lamps mounted on tall poles have the greatest potential to cause light pollution, since 

light directly emitted by the lamp has the potential to follow an unobstructed path into the sky or the 

distant landscape. This type of light spill has been called glare, intrusive light, or light trespass 

(Narisada and Schreuder 2004). The dark-adapted human eye will see these individual light sources 

as extremely bright points in a natural environment. These sources also have the potential to 

illuminate the landscape, especially vertical surfaces aligned perpendicular to them, often to a level 

that approaches or surpasses moonlight. The brightness of such objects may be measured as the 

amount of light per unit area striking a “detector” or a measuring device, or entering the observer’s 

pupil. This type of measure is called illuminance (Ryer 1997).

Illuminance is measured in lux (metric) or foot-candles (English), and is usually defined as luminous 

flux per unit area of a flat surface (1 lux = 1 lumen/m2). However, different surface geometries may 

be employed, such as a cylindrical surface or a hemispheric surface. Integrated illuminance of a 

hemisphere (summed flux per unit area from all angles above the horizon) is a useful, unbiased 

metric for determining the brightness of the entire night sky. Horizontal and vertical illuminance are

also used; horizontal illuminance weights areas near the Zenith much greater than areas near the 

horizon, while vertical illuminance preferentially weights areas near the horizon, and an azimuth of 

orientation must be specified.

Direct vertical illuminance from a nearby anthropogenic source will vary considerably with the 

location of the observer, since this value varies as the inverse of the square of the distance from light 

source to observer (Ryer 1997). Therefore, measures of light trespass are usually made in sensitive 

areas (such as public campgrounds).
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Figure 73. Location of DNS sample site (Alpine Camp) in COLM.

Anthropogenic light which results in an upward component will be visible to an observer as “sky 

glow”. This is because the atmosphere effectively scatters light passing through it. The sky is blue in 

daytime because of Rayleigh scattering by air molecules, which is more effective for light of shorter 

wavelengths. For this reason, bluish light from outdoor fixtures will produce more sky glow than 

reddish light. Larger particles in the atmosphere (aerosols and water vapor droplets) cause Mie 

scattering and absorption of light, which is not as wavelength-dependent and is more directional. 
315

When the air is full of larger particles, this process gives clouds their white appearance and produces 

a whitish glow around bright objects (e.g., the sun and moon). The pattern of sky glow as seen by a 

distant observer will appear as a dome of light of decreasing intensity from the center of the city on 

the horizon. As the observer moves closer to the source, the dome gets larger until the entire sky 

appears to be luminous (Garstang 1989).

Light propagated at an angle near the horizon will be effectively scattered and the sky glow produced 

will be highly visible to an observer located in the direction of propagation. Predictions of the 

apparent light dome produced by a sky glow model demonstrate this (Luginbuhl et al. 2009). Light 

reflected off surfaces (e.g., a concrete road or parking area) becomes visible light pollution when it is 

scattered by the atmosphere above it, even if the light fixture has a “full cutoff” design and is not 

visible as glare or light trespass to a distant observer. For this reason, the intensity and color of 

outdoor lights must be carefully considered, especially if light-colored surfaces are present near the 

light source.

Light domes from many cities, as they appear from a location within Joshua Tree National Park, are 

shown in Figure 74 and Figure 75, as a grayscale and in false color. This graphic demonstrates that 

the core of the light dome may be tens or hundreds of times brighter than the extremities. A 

logarithmic scale for sky luminance and false color are commonly used to display monochromatic 

images or data with a very large dynamic range, and are used extensively in reports of sky brightness 

by the NSNSD.

The brightness (or luminance) of the sky in the region of the light domes may be measured as the 

number of photons per second reaching the observer for a given viewing angle, or area of the sky 

(such as a square degree, square arc minute, or square arc second). The NPS NSNSD utilizes a digital 

camera with a large, dynamic range, monochromatic charge-coupled device (CCD) detector and an 

extensive system of data collection, calibration, and analysis procedures (Duriscoe et al. 2007). This 

system allows for the accurate measurement of both luminance and illuminance, since it is calibrated 

on standard stars that appear in the same images as the data and the image scale in arc seconds per 

pixel is accurately known. Sky luminance is reported in astronomical units of V-magnitudes per 

square arc second, and in engineering units of milli-candela per square meter. High resolution 

imagery of the entire night sky reveals details of individual light domes that may be attributed to 

anthropogenic light from distant cities or nearby individual sources. These data sets may be used for 

both resource condition assessment and long-term monitoring.

Figure 74 and Figure 75 contain information on natural sources of light in the night sky as well as 

anthropogenic sources. The appearance of the natural night sky may be modeled and predicted in 

terms of sky luminance and illuminance over the hemisphere, given the location, date, time, and the 

relative brightness of the natural airglow (the so-called “permanent aurora” which varies in intensity 

over time) (Roach and Gordon 1973). The NPS NSNSD has constructed such a model, and uses it in 

analysis of data sets to remove the natural components. This results in a more accurate measure of 

anthropogenic sky glow (Figure 76). Figure 75 represents “total sky brightness” while Figure 76

displays “anthropogenic sky glow” or “net light pollution.” This is an important distinction, 

especially in areas where anthropogenic sky glow is of relatively low intensity.
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Figure 74. Grayscale representation of sky luminance from a location in Joshua Tree National Park 

(Figure provided by Dan Duriscoe, NPS NSNSD).

Figure 75. False color representation of Figure 74 after a logarithmic stretch of pixel values (Figure 

provided by Dan Duriscoe, NPS NSNSD).

The accurate measurement of both anthropogenic light in the night sky and the accurate prediction of 

the brightness and distribution of natural sources of light allows for the use of a very intuitive metric 

of the resource condition - a ratio of anthropogenic to natural light. Both luminance and illuminance 

for the entire sky or a given area of the sky may be described in this manner (Hollan 2010). This socalled “light pollution ratio” is unitless and is always referenced to the brightness of a natural 

moonless sky under average atmospheric conditions, or, in the case of the NSNSD data, the 

atmospheric conditions determined from each individual data set. 

The reference conditions for anthropogenic sky luminance were identified as no more than 200 

percent brighter than natural conditions in any area of the sky and no more than 10 percent brighter at 

the Zenith. These values correspond to light pollution ratios of 2.0 and 0.1, respectively. The NSNSD

has obtained values of 50-100 for this measure at the core of city light domes seen from several areas 

administered by the NPS, including Lake Mead National Recreation Area, Saguaro National Park, 

and Colorado National Monument (NPS NSNSD, unpublished data). This is because these NPS areas 

are very close to the cities of Las Vegas, Nevada; Tucson, Arizona; and Grand Junction, Colorado, 

respectively. COLM is one of these unfortunate locations. As such, the park subjected to bright light 

domes, which can significantly impair sky quality at distances of 100 mi or more from the center of 

the city. 

A quick and accurate method of quantifying sky brightness near the Zenith is the use of a Unihedron 

Sky Quality Meter. The Unihedron Sky Quality Meter is a single-channeled hand-held photometric 

device. A single number in magnitudes per square arc second is read from the front of the device 

after its photodiode and associated electronics are pointed at the Zenith and the processor completes 

its integration of photon detection. Because the meter is relatively inexpensive and easy to use, a 

database of measures has grown since its introduction (see 
317

http://unihedron.com/projects/darksky/database/index.php). The NPS NSNSD produces values from 

each data set as both a synthesized value derived from the high-resolution images and by hand held 

measures with a Unihedron Sky Quality Meter. The performance of the Sky Quality Meter has been 

tested and reviewed by Cinzano (2001). While fairly accurate and easy to use, the value it produces is 

biased toward the Zenith. Therefore, the robustness of data collected in this manner is limited to 

areas with relatively bright sky glow near the Zenith, corresponding to severely light polluted areas. 

While not included in the reference condition, a value of about 21.85 would be considered “pristine”, 

providing the Milky Way is not overhead and/or the natural airglow is not unusually bright when the 

reading is taken. 

Figure 76. Contour map of anthropogenic sky glow at a location in Joshua Tree National Park, analogous 

to Figure 75 with natural sources of light subtracted (Figure provided by Dan Duriscoe, NPS NSNSD).

Figure 77. False color mosaic image of the COLM night sky. Image taken from the Alpine Camp near the 

Visitor Center. Night sky glow from Fruita, CO (north/center) and Grand Junction, CO (east/right) are 

visible. The Milky Way is also clearly visible as an arc across the mosaic image. Image provided by Dan 

Duriscoe of the NPS NSNSD.

Visual observations are important in defining sky quality, especially in defining the aesthetic 

character of night sky features. A published attempt at a semi-quantitative method of visual 

observations is described in the Bortle Dark Sky Scale (Bortle 2001). Observations of several 

features of the night sky and anthropogenic sky glow are synthesized into a 1-9 integer interval scale, 

where class 1 represents a “pristine sky” filled with easily observable features and class 9 represents 

an “inner city sky” where anthropogenic sky glow obliterates all the features except a few bright 
318

stars. Bortle Class 1 and 2 skies possess virtually no observable anthropogenic sky glow (Bortle 

2001). 

Another visual method for assessing sky quality is Zenithal Limiting Magnitude (ZLM), which is the 

apparent brightness or magnitude of the faintest star observable to the unaided human eye, which 

usually occurs near the Zenith. This method involves many factors, the most important of which is 

variability from observer to observer. A ZLM of 7.0-7.2 is usually considered “pristine” or 

representing what should be observed under natural conditions; observation of ZLM is one of the 

factors included in the Bortle Dark Sky Scale. Zenith Limiting Magnitude is often referenced in 

literature on the quality of the night sky, and is the basis for the international “Globe at Night” 

citizen-scientist program (see http://www.globeatnight.org/index.html). The NPS NSNSD has 

experimented with the use of this observation in predicting sky quality, and has found that it is a 

much coarser measure and prone to much greater error than accurate photometric measures over the 

entire sky. For these reasons, it is not included in the reference conditions section.

NPS Suite of Measures

NPS NSNSD (2014) documented high levels of light pollution from within the park. Several 

measures indicated unfavorable dark night sky conditions. According to NPS NSNSD (2014), there 

was a high level of sky glow as a result of anthropogenic light. The light pollution ratio (LPR) for 

horizontal and vertical illuminance was 1.04 and 3.65, respectively. The average sky luminance and 

vertical illuminance were 176% and 365% brighter than the average natural conditions, respectively, 

most likely as a result of city light domes and unshielded lights. In the false color image, light 

intrusions from surrounding communities are visible from Alpine Camp. Communities that are 

visible include Fruita, CO (bearings 350-25), and Grand Junction, CO (bearings 50-135) (Figure 77). 

The arc of the Milky Way is clearly visible to the west, as is the glow from Fruita, CO on the middle 

horizon, and the glow from Grand Junction, CO on the right horizon. Table 81 and Table 82 display

the photometric statistics from the dark night sky summary data.
319

Table 81. Photometric statistics for the ML (Finger Lakes MicroLine model camera) instrument data mosaic (reference set only) (Retrieved from 

NPS NSNSD 2014).

Date

Average Sky Luminance Zenith Sky Luminance Brightest Luminance Illuminance

mag arcsec-2 μcd/m2 mag arcsec-2 μcd/m2 mag arcsec-2 Horizontal Maximum Vertical

Sep 25 20.46 709 21.15 376 14.18 1.633 2.392

Table 82. Photometric statistics for the anthropogenic sky glow mosaic (reference set only) (Retrieved from NPS NSNSD 2014).

Average Sky Luminance

Zenith 

Luminance

Brightest 

Luminance

Illuminance

Date All Sky Zenith Angle 80 ̊ Zenith Angle 70 ̊ Horizontal

Maximum 

Vertical

mag 

arcsec-2

mLux LPR ucd/m2 LPR ucd/m2 LPR mags ucd/m2 mags ucd/m2 mLux LPR mLux LPR

Sep 25 -7.52 2.60 1.77 313.0 - 239.3 - 22.55 103 17.16 14735 0.832 1.04 1.462 3.65
320

Threats and Stressor Factors

COLM park staff has identified existing lighting structures as a major threat to dark night skies in 

COLM. Situated in close proximity to a major urban area, COLM is subjected to high levels of 

anthropogenic light pollution. This light pollution comes from urban development east of the park 

because there are little to no light fixtures within the park. Many businesses have unobstructed lights 

that are orientated upwards, and these lights remain on even when the business’s operating hours 

have passed. Lorenz (2006) and Danko (2014) recreated a light pollution map that displays the level 

of light pollution occurring in Grand Junction and surrounding areas (Figure 78). The park is located 

in two levels of light pollution ranging from three to four on the Bortle Scale, which means the dark 

night sky is slightly to moderately impaired.

Figure 78. Levels of light pollution occurring in Grand Junction, Colorado and surrounding areas (Lorenz 

2006; Danko 2014).

Data Needs/Gaps

There were no data from the period of reference to provide a baseline for comparison. NPS NSNSD

(2014) summarized dark night skies data in COLM, which may serve as a baseline dataset for the 

future management. It should be noted that the NPS NSNSD (2014) summary did not include Bortle 

Scale or ZLM values. Measurements should occur on a periodic basis, about once every 5 years, with 

the highest point in the park serving as the preferred observing site, in order to track external threats.
321

Overall Condition

NPS Night Sky Division’s Suite of Measures

During scoping meetings, the COLM NRCA team assigned the NPS NSNSD’s suite of measures a 

Significance Level of 3. The NPS NSNSD collected night skies data for the park in the 25 September 

2014. This data may serve as a baseline for dark night sky condition in the park. It is clear that the 

current condition of dark night skies is negatively impacted by urban areas such as Fruita, Colorado 

(north) and Grand Junction, Colorado (east). The NPS NSNSD (2014) data summary did not include 

Bortle Scale estimates of ZML; however, the levels of light pollution from Grand Junction, Colorado 

and the surrounding area estimates from Lorenz (2006) and Danko (2014) could serve as a 

supplement for this assessment (Figure 78) According to Lorenz (2006) and Danko (2014), the 

extrapolated Bortle Scale estimate for the park ranged from 3 to 4, which is considered low to 

moderate impairment. The data suggest that the level of concern for this resource is believed to be of 

concern. As result, this measure was assigned a Condition Level of 2, or moderate concern.

Weighted Condition Score

The Weighted Condition Score for Dark Night Skies in COLM was 0.67, indicating an overall 

condition of high concern. The 2014 COLM dark night sky report serves as a baseline as well as the 

only dark night skies data. Since urbanization is most likely to continue in areas surrounding the 

park, a negative trend was assigned to this measure.

Dark Night Skies

Measures Significance Level Condition Level WCS = 0.67

NPS Night Sky 

Divisions Suite of 

Measures

3 2

4.17.6 Sources of Expertise

National Park Service Night Sky Division members Dan Duriscoe, Chad Moore, Teresa Jiles, Jeremy 

White, and Robert Meadows

4.17.7 Literature Cited

Bessell, M. S. 1990. UBVRI Passbands. Publications of the Astronomical Society of the Pacific. 

102:1181.

Bortle, J. 2001. Introducing the Bortle dark-sky scale. Sky & Telescope 101(2):126-129. 

Cinzano, P., F. Falchi, and C. D. Elvidge. 2001. The first world atlas of artificial sky brightness. 

Monthly Notices of the Royal Astronomical Society 328:689-707.
322

Danko, A. 2014. Colorado National Monument light pollution map. Clear Dark Sky Online. 

http://cleardarksky.com/lp/ClrdNMCOlp.html?Mn=Solar%20Power (accessed 29 December 

2014).

Duriscoe, D. M., C. B. Luginbuhl, and C. A. Moore. 2007. Measuring night-sky brightness with a 

wide-field CCD camera. Publications of the Astronomical Society of the Pacific 119:192-213.

Garstang, R. H. 1989. Night-sky brightness at observatories and sites. Publications of the 

Astronomical Society of the Pacific 101:306-329.

Hollan, J. 2010. What is light pollution and how do we quantify it? Workshop paper at Dark-sky 

2007 conference, Brno, Czech Republic. http://amper.ped.muni.cz/hollan/light/lp_what_is.pdf

(accessed 29 December 2014).

Lorenz, D. 2006. Light pollution atlas 2006. http://djlorenz.github.io/astronomy/lp2006/ (accessed 29

December 2014).

Luginbuhl, C. B., D. M. Duriscoe, C. W. Moore, A. Richman, G. W. Lockwood, and D. R. Davis. 

2009. From the ground up II: Sky glow and near-ground artificial light propagation in Flagstaff, 

Arizona. Publications of the Astronomical Society of the Pacific 121:204-212. 

Narisada, K., and D. Schrueder. 2004. Light pollution handbook. Astrophysics and space sciences 

library volume 322. Springer Publishing, New York, New York.

National Park Service (NPS). 2006. Management policies 2006. ISBM 0-16-076874-8. U.S. 

Department of the Interior. National Park Service, Washington, D.C.

National Park Service (NPS). 2012. Managing lightscapes. 

http://www.nature.nps.gov/night/management.cfm (accessed 29 December 2014).

National Park Service (NPS). 2014. Air resources division – natural lightscapes. 

http://nature.nps.gov/night/index.cfm (accessed 29 December 2014).

National Park Service Natural Sounds and Night Skies Division (NPS NSD). 2014. Summary of 

night skies data collection for Colorado National Monument, September 25, 2014. Department of 

the Interior, National Park Service, Natural Sounds and Night Skies Division. Fort Collins, 

Colorado.

Ryer, A. 1997. The light measurement handbook. International Light, Inc., Technical Publications 

Division, Newburyport, Massachusetts. 

Roach, F. E., and J. L Gordon. 1973. The light of the night sky. D. Reidel Publishing, Dordrecht, 

Holland.
323

4.18 Viewscape

4.18.1 Description

A viewshed is the area that is visible from a particular location or set of locations, often developed 

using GIS analysis tools. Two datasets are required to calculate a viewshed using GIS: a digital 

elevation model (DEM) and point or polyline data defining points in which a person would be 

viewing a landscape. With the defined data, GIS software determines visibility to and from a 

particular cell or set of cells in a DEM resulting in a viewshed layer. This viewshed layer is a raster 

that defines the visible area on the landscape from the point or set of points contained within an 

outline of a polygon. Combining viewshed layers with layers that identify areas of undesirable 

impacts on the landscape creates a quantitative description of visual stress on a viewshed; repeating 

this process for multiple viewshed layers in a pre-defined landscape, such as a National Park, 

provides a quantitative description of stress across the viewscape in the area.

Photo 20. View of COLM cliffs, canyons, and monoliths from Book Cliff (Photo by Shannon Amberg, 

SMUMN GSS).

Multiple studies indicate that people prefer natural compared to develop landscapes (Sheppard and 

Sheppard 2001, Kearney et al. 2008, Han 2010). The National Park Service Organic Act (16 U.S.C. 

l) implies the need to protect the viewscapes of National Parks, Monuments, and Reservations. 

Specifically, the enabling legislation for COLM states the parks should “provide for the 

understanding, preservation, and enjoyment of the extraordinary erosional, geological, and historical 

landscapes of great scientific interest, the Rim Rock Drive, and all other natural and cultural

resources for present and future generations” (NPS 2005). However, defining a desirable viewscape 

is widely regarded as a subjective and difficult process, because what is preferable is intrinsically 

humanistic and varies by individual. In COLM, development is minimal compared to many areas in 
324

the conterminous United States, yet some non-natural features still exist. Many of these non-natural 

features, such as roads, overlooks, trails, and parking areas enable recreational access to the park’s 

resources, which is a primary purpose for the park (NPS 2005). Therefore, this assessment relied on 

input from park and NCPN staff to determine desirable and undesirable features within the park’s 

viewscape.

4.18.2 Measures

 Immediate viewscape at points along Rim Rock Drive

 Noncontributing structures visible from within the recommended wilderness area

4.18.3 Reference Conditions/Values

The reference condition for the park’s viewscape is defined as the viewscape at time of park creation

(1911), with emphasis on the viewscape along Rim Rock Drive and Grand viewscape.

4.18.4 Data and Methods

The 16 scenic pullouts and overlooks along Rim Rock Drive were chosen as priority observation 

points within the park for this analysis: East Entrance, Redlands, Historic Trails, Fruita, 

Independence, Grand View, Monument Canyon View, Coke Ovens, Monument Canyon, Artist Point, 

Highland View, Upper and Lower Ute Canyon, Fallen Rock, Red Canyon, and Cold Shivers (Figure 

79). Trails located in the recommended wilderness areas were used in an analysis to determine the 

non-contributing features visible from within the wilderness area. Visitors frequently observe the 

landscape in the park from the defined observation points. At each of these points, a viewshed was 

calculated using ESRI’s Spatial Analyst Viewshed Tool in ArcGIS 10.2, which requires point or 

polyline GIS data (representing the viewing location) and a DEM. For each of the observation points, 

a point shapefile was created for use with the Viewshed tool and the DEM used for each observation 

point was mosaicked from the National Elevation Dataset (NED), which has a resolution of 

approximately 10 m. A 1.7-m (5.5-ft) offset was applied to each observation point shapefile to 

account for average human height. The result of the operation is a theoretical viewshed layer that 

represents the visible area from a point without correcting for visibility factors (e.g., vegetation, 

smoke, humidity, heat shimmer, or curvature of the earth). 

Ground condition photos were taken in winter 2013 to supplement the GIS data. Photo points, 

oriented towards cardinal directions, were selected for eight of the observation points. The photos 

provide an illustration of typical views at each location. However, they are not useful in providing 

quantifiable information for the viewscape of the park.
325

Figure 79. Locations of vista/observation points, the proposed wilderness area, and wilderness trails in 

COLM.
326

4.18.5 Current Condition and Trend

Immediate Viewscape at Points along Rim Rock Drive

The composite visible area from all observation points (hereafter, composite viewshed) is 1,674

km2(646 m2) (Figure 79). Approximately 1,324 ha (3,271 ac) of COLM is visible from all of the 

vistas. That is approximately 16% of the park. Natural landscapes dominate the visible area from 

all observation points (Photo 21 - Photo 28). Although the road is visible from all selected 

observation points, there are very few other non-contributing features inside the park. Visibility 

of development features at observation points may be minimal, but a few development features 

are visible as visitors travel through the park. The primary park road traverses south to north 

from the Grand Junction entrance to the Fruita entrance. There are no visible power lines or light 

poles along the road; however, radio towers on adjacent lands are visible from the road at several 

vistas. Most of the development features in the park provide safety and are of interpretive value 

to visitors, such as the viewing platforms, guard rails and the Visitor Center. Other development 

that is visible from the park vistas is located to the east in Fruita, Redlands, and Grand Junction.

Independence Monument View

Photo 21. View of Independence Monolith from the Independence Monument Overlook observation point, 

looking east (Photo by Shannon Amberg, SMUMN GSS).

Photo points were acquired for eight of the 16 vistas. Photo points include Independence, Grand, 

Cook Ovens, Artist Point, Upper Ute Canyon, Fallen Rock, Red Canyon, and Cold Shiver Point 

(Figure 80). Grand Junction can be seen in the distance from Independence, Grand, Red Canyon, 

and Cold Shivers Point. 
327

Figure 80. Composite viewscape for observation points along Rim Rock Drive in COLM.
328

Grand View

Photo 22. View from Grand View Overlook observation point, looking north (top) and east (bottom) 

(Photos by Shannon Amberg, SMUMN GSS). 
329

Coke Ovens 

Photo 23. View from Coke Ovens Overlook observation point, looking northeast (top) (Photo by Anna 

Davis, SMUMN GSS) and southeast (bottom) (Photo by Shannon Amberg, SMUMN GSS).
330

Artist Point

Photo 24. View of Artist Point Overlook observation point, looking northeast (Photo by Shannon Amberg, 

SMUMN GSS).

Upper Ute Canyon View

Photo 25. View of Upper Ute Canyon Overlook observation point, looking northeast (Photo by Anna 

Davis, SMUMN GSS).
331

Fallen Rock

Photo 26. View of Fallen Rock Overlook observation point, looking southwest (Photo by Shannon 

Amberg, SMUMN GSS).

Red Canyon View

Photo 27. View of Red Canyon Overlook observation point, looking northeast (Photo by Anna Davis, 

SMUMN GSS).
332

Cold Shiver Point

Photo 28. View of Cold Shiver Point Overlook observation point, looking northwest (top) and northeast 

(bottom) (Photos by Anna Davis, SMUMN GSS).
333

Noncontributing Structures Visible from within the Recommended Wilderness Area

The composite visible area from the wilderness trails viewshed is 2,512 km2(970 m

2

) (Figure 81). 

Approximately 4,467 ha (11,038 ac) of COLM is visible from all of the vistas. That is approximately 

54% of the park. The external viewscape includes all of the cities to the east of the park. Black Ridge 

to the west and the mountains to the east are the features that limit the external viewscape. Within the 

composite viewshed, the primary anthropogenic features include Rim Rock Drive and the radio 

towers on Black Ridge. The composite viewscape for the wilderness trails may have more visible 

area because together they cover a large range of elevations and extend from the west side of the park 

to the eastern boundary, whereas Rim Rock Drive primarily runs through the west side of the park.
334

Figure 81. Composite viewscape for trails located in the recommended wilderness area of COLM.

Threats and Stressor Factors

The COLM park staff identified several existent and potential threats to viewscape in the park. These 

threats include urban development, radio towers located on land adjacent to the park (owned by the 

BLM), haze, management activities not contributing to vistas along Rim Rock Drive, and 

commercial vehicle traffic occurring on the east and west side of the park.
335

Urban development can be a major threat to NPS units, especially those located in or near larger 

cities. COLM is located just west of Grand Junction, which is a larger city in Colorado. According to 

NPS (2013), light pollution is a result of urban development and negatively impacts park viewscapes. 

There was a moderate amount of development in Fruita that is visible from the park. Figure 82 

displays changes in urban development that are visible from vistas in COLM (Jin et al. 2011). It 

should be noted that the data used for the analysis are from 2001 to 2011. Any recent or future 

developments are not reflected in this data.

Figure 82. Change in urban development from 2001 to 2011 in cities to the east of COLM visible from 

Rim Rock Drive Overlook observation points (Jin et al. 2011).

Radio towers and utility poles take away from the natural viewscape. Radio towers are located 

directly west of the park in the McInnis Canyons National Conservation Area on Black Ridge. These 

towers can easily be seen to the northwest of Rim Rock Drive where East Black Ridge Trail and 

Liberty Cap Trail meet (Photo 29).
336

Air pollution is another threat to the COLM viewscape, especially haze which reduces visibility. 

Haze occurs when sunlight reflects off pollution particles floating in the air, resulting in a reduction 

in clarity and color of a vista (EPA 2012) (Photo 30). This reduction in visibility can worsen when 

weather becomes more humid (EPA 2012).

Management activities not contributing to the immediate viewscape along Rim Rock Drive also

detract from the natural viewscape. These include common maintenance and road construction. 

Special events (e.g., marathons or cycling tours) can attract up to 2,000 people, which may result in 

impacts to the viewshed (Hartwig, written communication, 12 May 2015).

The volume of commercial vehicle traffic can negatively affect a viewscape. The difference in 

commercial vehicular traffic on the east side of the park versus the west side results in different park 

experiences. The east side is designated as a public right of way and services commercial traffic 

traveling to and from the community of Glade Park to the south. This can include cattle trucks, 

construction dump trucks, and hay hauling semis. In September 2014, 102 tractor trailer loads of 

paving material traveled the East Hill in an 8-hour period (Hartwig, written communication, 12 May 

2015).

Photo 29. Radio towers on Black Ridge just west of 

the park (Photo by Shannon Amberg, SMUMN GSS, 

Winter 2013).

Photo 30. Inversion in Fruita just northeast of the 

park (Photo by Anna Davis, SMUMN GSS, Winter 

2013).
337

Data Needs/Gaps

While this assessment provides some baseline information regarding the park’s visual resources, it 

should not be considered all-inclusive. Incorporation of different and new GIS data sets, such as a 

higher resolution DEM, additional non-natural feature layers, or land ownership data with more 

coverage, would enhance a future analysis. Continued development of spatial data that explain 

landscape change will enable accurate and up-to-date viewshed assessments of the metrics examined 

in this analysis. In addition, continued monitoring of observation points through on-the-ground 

photography is a low-cost task that can help document changes in visual resources over time.

Overall Condition

Immediate Viewscape at Points along Rim Rock Drive

The Significance Level for the immediate viewscape at points along Rim Rock Drive is a 2.The 

natural landscape at COLM is the primary visible feature at all observation points examined along 

Rim Rock Drive. Most of the development features in the park provide safety or are of interpretive 

value to visitors, such as the viewing platforms, guard rails and the Visitor Center. Other 

development that is visible from the park vistas is located to the east in Fruita, Redlands, and Grand 

Junction. Most of these features are acceptable according to mandates from the park’s enabling 

legislation. There are no visible power lines or light poles along the road; however, some 

development features on adjacent lands are visible from the road at several vistas. Some features, 

such as the radio towers and light fixtures on Black Ridge just west of Rim Rock Drive, impair small 

portions of the natural viewscape within the park. Although these features are visible from only a 

portion of the road, their impact on the natural character and overall visitor experience can be 

significant (Hartwig, written communication, 12 May 2015). Therefore, the Condition Level for this 

measure is 2, or of moderate concern.

Noncontributing Structures Visible from within the Recommended Wilderness Area

The Significance Level for the noncontributing structures visible from within the “wilderness area” is 

a 2.The viewscape from within the wilderness area is important because it may provide primitive and 

unconfined recreation opportunities for visitors wanting to experience remote wilderness areas. The 

primary anthropogenic features visible in this area include urban development, Rim Rock Drive, and 

the radio towers on Black Ridge. External viewscape from the wilderness trails extends through most 

of the valley and to the cities east of the park. The viewscape for the wilderness trails may have more 

visible area than the immediate viewscape along Rim Rock Drive because together the trails cover a 

large range of elevations and extend from the west side of the park to the eastern boundary, whereas 

a majority of Rim Rock Drive is on the west side of the park. Most of the wilderness viewscape may 

be natural; however, growth in nearby cities is a cause for concern. Therefore, the Condition Level

for this measure is 2, or of moderate concern.

Weighted Condition Score

The Weighted Condition Score for this component is 0.67, which is on the lower end of the

significant concern range. The immediate viewscape and ground photos currently display natural 

landscapes with few or no non-contributing features. The viewscape from the wilderness trails

includes few to no non-contributing features within the park; however, urban development outside 
338

the park is visible and increased between 2001 and 2011. The significant impression made by the 

contrast between the visible non-contributing features (e.g., radio towers) and the dramatic natural 

landscape is the primary cause for concern. The increase in development surrounding COLM

suggests a declining trend for viewscape.

Viewscape

Measures Significance Level Condition Level WCS = 0.67

Immediate Viewscape 

at Points along Rim 

Rock Drive

2 2

Noncontributing 

Structures Visible from 

within the 

Recommended 

Wilderness Area

2 2

4.18.6 Sources of Expertise

Kim Hartwig, COLM Chief of Resources

4.18.7 Literature Cited

Environmental Protection Agency (EPA). 2012. Visibility. United States Environmental Protection 

Agency. http://www.epa.gov/visibility/ (accessed 18 December 2014).

Han, K-T. 2010. An exploration of relationships among responses to natural scenes. Scenic beauty, 

preference and restoration. Environment and Behavior 42(2):243–270.

Jin, S., L. Yang, P. Danielson, C. Homer, J. Fry, and G. Xian. 2013. A comprehensive change 

detection method for updating the National Land Cover Database to circa 2011. Remote Sensing 

of Environment 132:159-175.

Kearney, A. R., G. A. Bradley, C. H. Petrich, R. Kaplan, S. Kaplan, and D. Simpson-Colebank. 2008. 

Public perception as support for scenic quality regulation in a nationally treasured landscape. 

Landscape and Urban Planning 87:117–128. 

National Park Service (NPS). 2005. Colorado National Monument: Final general management plan/ 

environmental impact statement. U.S. Department of the Interior, Fort Collins, Colorado.

Sheppard, S. R. J. 2001. Beyond visual resource management: Emerging theories of an ecological 

aesthetic and visible stewardship. Pages 149-172 in Sheppard, S. R. J., Harshaw, H. W. (eds.), 

Forests and Landscapes: Linking Ecology, Sustainability and Aesthetics. CABI Publishing, New 

York, New York.
339

4.19 Soundscape and Acoustic Environment

4.19.1 Description

Acoustic resources are physical sound sources, including both natural sounds (wind, water, wildlife, 

vegetation) and cultural and historic sounds (battle reenactments, tribal ceremonies, quiet reverence) 

(NPS 2014). The acoustic environment is the combination of all the acoustic resources within a given 

area, natural sounds and human-caused sounds (NPS 2014). The acoustic environment includes 

sounds made by geological processes, biological activity, and even sounds that are inaudible to most 

humans, such as bat echolocation calls (NPS 2014). Soundscape is the component of the acoustic 

environment that can be perceived by humans (NPS 2014). The character and quality of the 

soundscape influence human perceptions of an area, providing a sense of place that differentiates 

from other places (NPS 2014). Noise refers to sound which is unwanted either because of its effects 

on humans and wildlife, or its interference with the perception or detection of other sounds (NPS 

2014). The natural soundscape is an inherent component of the scenery and the natural and historic 

objects and the wildlife protected by the Organic Act of 1916 (NPS 2014). NPS Management 

Policies (§ 4.9) require the NPS to preserve the park’s natural soundscape, to restore the degraded 

natural conditions wherever possible, and to prevent or minimize noise (NPS 2014).

Visitors to national parks often indicate that an important reason for visiting the parks is to enjoy the 

relative quiet that parks can offer. In a 1998 survey of the American public, 72% of respondents 

identified opportunities to experience natural quiet and the sounds of nature as an important reason 

for having national parks (Haas and Wakefield 1998). Additionally, 91% of NPS visitors consider 

enjoyment of natural quiet and the sounds of nature as compelling reasons for visiting national parks 

(McDonald et al. 1995). Despite this desire for quiet environments, anthropogenic noise continues to 

intrude upon natural areas and has become a source of concern in national parks (Lynch et al. 2011).

Noise not only affects visitor experience, it can also alter the behavior of wildlife. Studies have 

shown that wildlife can be adversely affected by sounds that intrude on their habitats. While the 

severity of the impacts varies depending on the species being studied and other conditions, research 

strongly supports the fact that wildlife can suffer adverse behavioral and physiological changes from 

intrusive sounds (noise) and other human disturbances. Documented responses of wildlife to noise 

include increased heart rate, startle responses, flight, disruption of behavior, and separation of 

mothers and young (Selye 1956, Clough 1982, USFS 1992, Anderssen et al. 1993, NPS 1994).

Repeated noise can cause chronic stress to animals, possibly affecting their energy use, reproductive 

success, and long-term survival (Radle, 2007). Even low levels of noise can interfere with ecological 

processes in surprising and complex ways (Shannon et al. 2015).

4.19.2 Measures

 Occurrence of human-caused sound - loudness and percent of time audible

 Occurrence of human-caused sound -within and outside of proposed wilderness area

4.19.3 Reference Conditions/Values

Reference conditions should address the effects of noise on human health and physiology, the effects 

of noise on wildlife, the effects of noise on the quality of the visitor experience, and finally, how 
340

noise impacts the acoustic environment itself. NPS policy states that the natural ambient sound level 

is the baseline (reference condition) and standard against which current conditions in a soundscape is 

to be measured and evaluated (NPS 2006).The NPS defines natural ambient sound level as the 

environment of sound that would exist in the absence of human-caused noise (NPS 2006).

4.19.4 Data and Methods

Sound Science

Humans and wildlife perceive sound as an auditory sensation created by pressure variations that 

move through a medium such as water or air. Sound is measured in terms of frequency (pitch) and 

volume (amplitude), or sound level (Templeton et al. 1997, Harris 1998). Noise, essentially the 

negative evaluation of sound, is defined as extraneous or undesired sound (Morfey 2001).

Frequency, measured in Hertz (Hz), describes the cycles per second of a sound wave (NPS 2014). 

Humans with normal hearing can hear sounds between 20 Hz and 20,000 Hz, and are most sensitive 

to frequencies between 1,000 Hz and 6,000 Hz (NPS 2014). High frequency sounds are more readily 

absorbed by the atmosphere or scattered by obstructions than low frequency sounds. Low frequency 

sounds diffract more effectively around obstructions. Therefore, low frequency sounds travel farther.

In addition to the pitch of a sound, humans also perceive the amplitude (or level) of a sound (NPS 

2014). This metric is described in decibels (dB). The decibel scale is logarithmic, meaning that every 

10 dB increase in sound pressure level (SPL) represents a tenfold increase in sound energy (NPS 

2014). This also means that small variations in sound pressure level can have significant effects on 

the acoustic environment (NPS 2014). Sound pressure level is commonly summarized in terms of 

dBA (A-weighted decibels) (NPS 2014). Table 83 provides examples of A-weighted sound levels 

measured in national parks.

Table 83. Examples of sound levels measured in national parks

Park Sound Sources Common Sound 

Sources dBA

Volcano crater (Haleakala National Park) Human breathing at 3m 10

Leaves rustling (Canyonlands NP) Whispering 20

Crickets at 5m (Zion NP) Residential area at night 40

Conversation at 5m (Whitman Mission National Historic Site Busy restaurant 60

Snowcoach at 30m (Yellowstone National Park) Curbside of busy street 80

Thunder (Arches National Park) Jackhammer at 2m 100

Military jet at 100m AGL (Yukon-Charley Rivers National Preserve) Train horn at 1m 120

The natural acoustic environment is vital to the function and character of a national park. Natural 

sounds include those sounds upon which ecological processes and interactions depend. Examples of 

natural sounds in parks include:

 Sounds produced by birds, frogs or insects to define territories or attract mates

 Sounds produced by bats to navigate or locate prey
341

 Sounds produced by physical processes such as wind in trees, flowing water, or thunder

Although natural sounds often dominate the acoustic environment of a park, human-caused noise has 

the potential to mask these sounds. Noise impacts the acoustic environment much like smog impacts 

the visual environment; obscuring the listening horizon for both wildlife and visitors. Examples of 

human-caused sounds heard in parks include:

 Aircraft (i.e., high-altitude and military jets, fixed-wing, helicopters)

 Vehicles 

 Generators

 Watercraft

 Grounds care (lawn mowers, leaf blowers)

 Human voices

Monitoring in the Park

The NSNSD conducted baseline acoustical monitoring for COLM from April to May of 2013 (NPS 

2013, McFarland 2015). Four sites Figure 83, were selected for acoustic monitoring as they are 

representative of high (COLM001 and COLM002) and low (COLM003 and COLM004) use areas in 

the park (Katie Nuessly, NPS Biologist/Modeling Specialist, written communication, 1 December 

2015). At the monitoring sites, sound pressure level (SPL) measurements were taken, along with 

digital audio recordings and meteorological data (McFarland 2015).

Auditory analysis was used to calculate the audibility of sound sources at COLM, using the acoustic 

monitoring data from each site. Trained technicians at CSU analyzed a subset of audio samples (10 

seconds every two minutes for eight days of audio) in order to identify durations of audible sound 

sources. Staff used the total percent time human-caused sounds were audible to calculate the natural 

ambient sound level (McFarland 2015).

The goal of impact analysis is to present sound level data in a way that is meaningful and allows park 

managers to protect the acoustic environment (McFarland 2015). Table 84 summarizes sound levels 

that relate to human health and speech, as documented in the scientific literature. Human responses 

can serve as a proxy for potential impacts to other vertebrates because humans have more sensitive 

hearing at low frequencies than most species (Dooling and Popper 2007). 
342

Figure 83. Locations of NSNSD acoustical monitoring sites in COLM (NPS 2013).

The first, 35 dBA, is designed to address the health effects of sleep interruption (McFarland 2015). 

Recent studies suggest that sound events as low as 35 dB can have adverse effects on blood pressure 

while sleeping (Haralabidis, 2008). The second value addresses the World Health Organization’s 

(WHO) recommendations that noise levels inside bedrooms remain below 45 dBA (Berglund et al., 

1999). The third value, 52 dBA, is based on the EPA’s speech interference threshold for speaking in 

a raised voice to an audience at 10 meters (EPA 1974). This threshold addresses the effects of sound 
343

on interpretive presentations in parks. The final value, 60 dBA, provides a basis for estimating 

impacts on normal voice communications at 1 meter (EPA 2014). Hikers and visitors viewing scenic 

vistas in the park would likely be conducting such conversations.

Table 84. Explanation of sound level values, for reference (NPS 2013).

Sound Levels 

(dBA) Relevance

35 Blood pressure and heart rate increase in sleeping humans (Haralabidis et al. 2008)

45 World Health Organization’s recommendation for maximum noise levels inside bedrooms 

(Berglund et al. 1999)

52 Speech interference for interpretive programs (EPA 1974)

60 Speech interruption for normal conversation ( EPA 1974)

4.19.5 Current Condition and Trend

Occurrence of Human-caused Sound - Loudness and Percent of Time Audible

Sources of noise at COLM include vehicles on nearby roads, traffic from nearby metropolitan areas, 

and aircraft. Table 85 displays median existing sound levels (L50) and median natural ambient sound 

levels (Lnat) for daytime (7 am – 7 pm) and nighttime (7 pm – 7am) conditions. The L50 is the sound 

level exceeded 50% of the hour and is relatively unaffected by transient events like sparse animal 

vocalizations and isolated military jet operations. The Lnat is the natural ambient level and this metric 

excludes all man-made sound.

Table 85. Median existing and natural ambient levels at the four sites (McFarland 2015).

Site ID

Median Existing Ambient (L50) in dBA Median Natural Ambient (Lnat) in dBA

Day Night Day Night

COLM001 24.8 18.5 19.3 15.0

COLM002 29.4 22.1 22.9 18.1

COLM003 25.1 20.0 20.0 17.1

COLM004 24.9 15.8 22.2 15.3

Median L50 values ranged between 24.9 and 29.4 dBA during the day and 15.8 and 22.1 dBA at 

night. These values exceeded the baseline condition (median Lnat) by 2.7 to 6.5 dBA during the day 

and 0.5 to 4 dBA at night. A one decibel change is not readily perceivable by the human ear, but any 

addition to this difference could begin to impact listening ability.

To assess the condition of the acoustic environment, it is useful to consider the functional effects that 

increases in sound level might produce. For instance, the listening area, the area in which a sound 

can be perceived by an organism, will be reduced when background sound levels increase. The 

failure to perceive a sound because other sounds are present is called masking. Masking interferes 

with wildlife communication, reproductive and territorial advertisement, and acoustic location of 

prey or predators (Barber, Crooks, & Fristrup, 2010). However, the effects of masking are not limited 
344

to wildlife. Masking also inhibits human communication and visitor detection of wildlife sounds. In 

urban settings, masking can prevent people from hearing important sounds like approaching people 

or vehicles, and interfere with the way visitors experience cultural sounds or interpretive programs. 

Seemingly small increases in sound level can have substantial effects, particularly when quantified in 

terms of loss of listening area (Payne & Webb, 1971; Barber, Crooks, & Fristrup, 2010). Each 3 dB 

increase in the background sound level will reduce a given listening area by half.

Therefore, the daytime L50 values that exceeded the daytime Lnat values by 2.7 to 6.5 dBA resulted in 

a listening area reduction of 46 to 78%. During the night, the L50 values that exceeded the Lnat values 

by 0.5 to 4 dBA reduced the listening area by 10.9 to 60.2%.

Results also indicated that the natural ambient sound levels at the monitoring sites ranged between 

19.3 and 22.9 dBA during the day and 15 and 18.1 dBA at night. For comparison, a comprehensive 

1982 study of noise levels in residential areas found that nearly 87% of US residents were exposed to 

day-night sound levels over 55 dB (and an additional 53% was exposed to day-night sound levels 

over 60 dB) (EPA 1982). Therefore, the results imply that the natural ambient sound level during the 

monitoring period was considerably quieter than most residential areas. 

However, noise still exists in COLM’s acoustical environment. A detailed analysis of audibility at 

this site (Table 86) found that the two major noise sources (aircraft and vehicles) contributed 

significant amounts of noise to the acoustical environment (ranging from about 9 to 62 % average 

audibility in a 24 hour period). These are the sources of noise which have the potential to mask the 

natural sounds that provide a sense of place at COLM. Of the sites monitored (Figure 83), human

caused sounds were audible most often at COLM001, COLM002 and COLM003, and least 

frequently at COLM004 (5% average percent time audible over 24 hours). The most common noise 

source at COLM001, COLM002 and COLM003 was vehicle traffic, while the most common noise 

source at COLM004 was aircraft.

Table 86. Mean percent time audible for all extrinsic sounds, aircraft, and vehicles (McFarland 2015).

Site ID

Mean percent time audible (in 24 hour time period)

All Extrinsic Aircraft Vehicles

COLM001 13.7 30 61.7

COLM002 14.4 17.4 57.1

COLM003 12.5 29.0 19.6

COLM004 5.2 22.8 8.6

Percent time audible is the amount of time that various sound sources are audible to humans with 

normal hearing. It is a measure that can correlate with visitor complaints of excessive noise and 

annoyance. Most noise sources are audible to humans at lower levels than virtually all wildlife 

species. Therefore, percent time audible is a protective proxy for wildlife.
345

Table 87 shows the percent of time that the reference sound levels in Table 84 were exceeded for 

each sample site during day and nighttime hours. Sound at these sites rarely exceeded 45 dBA. At all 

four sites, sound levels mainly exceeded the 35 dBA metric with 10 to 26% of daytime hours above 

this level. As would be expected, existing nighttime sound levels were lower than daytime sound 

levels (NPS 2013).

Table 87. Percent time above Table 84 reference values during the day (7 a.m. to 7 p.m.) and night (7 

p.m. to 7 a.m.) (NPS 2013).

Site

% Time above sound level: day % Time above sound level: night

35 dBA 45 dBA 52 dBA 60 dBA 35 dBA 45 dBA 52 dBA 60 dBA

COLM001 10.38 1.35 0.03 0.03 2.34 0.20 0.03 0.00

COLM002 16.70 1.52 0.30 0.04 4.43 0.27 0.02 0.00

COLM003 26.00 4.06 0.66 0.08 6.73 0.27 0.06 0.00

COLM004 11.56 1.05 0.19 0.00 3.52 0.23 0.03 0.00

At site COLM001 (closest to the Saddlehorn campground) nighttime sound levels only exceeded the 

35 dBA reference value 2.34% of the time. During 2.4% of the nighttime hours, the value at which 

blood pressure increases in sleeping humans was exceeded. Despite the minimal amount of time this 

sleeping metric was exceeded, it’s important to keep in mind that this reference value refers to sleep 

inside households, while campers at Saddlehorn campground may be more sensitive to lower noise 

levels as they are housed in tents. In addition, vehicles were audible nearly 62% of the time at site 

COLM001. The audibility of this particular noise source, in addition to the audible aircraft (30%) and 

other extrinsic sounds (14%), may further disrupt campers.

In addition to specific monitoring data that distinguishes between natural and human-caused sound, 

park-wide acoustic condition assessment and trend are also available. NSNSD estimates these 

acoustic conditions and trend using predictions from a geospatial sound model (Mennitt et al. 2014). 

For the model, sound pressure levels for the continental U.S. were predicted using actual acoustical 

measurements (including the four COLM sites described in this report) combined with a multitude of 

explanatory variables such as location, climate, landcover, hydrology, wind speed, and proximity to 

noise sources (roads, railroads, and airports). The model predicts daytime sound levels during 

midsummer. It should be noted that while the model excels at predicting acoustic conditions over

large landscapes, it may not reflect recent localized changes such as new access roads or 

development (Mennitt et al. 2014).

Model parameters useful for assessing a park’s acoustic environment include the understanding of a) 

natural conditions, b) existing acoustic conditions including both natural and human-caused sounds, 

and c) the impact of human-caused sound sources in relation to natural conditions. The impact 

condition demonstrates the influence of human activities to the acoustic environment and is 

calculated by subtracting the natural condition from the existing condition.
346

Figure 84 shows the impact between natural and existing acoustic conditions. This provides a 

condition assessment of the acoustic resource because it tells us how much the area is influenced by 

human-caused sounds. The mean impact is predicted to be 2.4 dBA (ranging from 0.3 dBA in the 

least impacted areas to 19.3 dBA in the most impacted areas.) That is, the average existing sound 

level (including natural and human-caused sound) is predicted to be 2.4 dBA above natural 

conditions on a typical summer day in the park.

Summary statistics of the L50 values for the natural, existing, and impact conditions are provided in 

Table 88. Average values represent the average L50 value occurring within the park boundary and 

since this value is a mean, visitors may experience sound levels higher and lower than the average 

L50.

Table 88. Median L50 values in each condition: natural, existing, and impact. Values represent the 

average, minimum and maximum L50 measurements in each condition.

Acoustic Environment Condition

Median L50 (dBA)

Minimum Maximum Average

Natural 22.5 28.1 26.9

Existing 27.4 43.7 29.3

Impact 0.3 19.3 2.4

A one decibel change is not readily perceivable by the human ear, but any addition to this difference 

could begin to impact listening ability. The impact condition value for COLM is 2.4 dBA and this 

increase would reduce the listening area for wildlife and visitors by 42.5 %. For example, if a 

predator can hear a potential prey animal in an area of 100 square feet in a setting with natural 

ambient sounds, that animal’s ability to hear would be reduced to 17.5 m2(57.5 ft2) if the sound 

levels were increased by 2.4 dBA. Similar reduction would occur for visitors and their ability to hear 

natural sounds or interpretive programs.
347

Figure 84. Modeled predicted results for L50 dBA impact levels at COLM (Mennitt et al. 2014).
348

Occurrence of Human-caused Sound - Within and Outside of Proposed Wilderness Area

All four of the sites surveyed by NSNSD were within the proposed wilderness area (NPS 2013) 

(Figure 85). The difference between human-caused and natural sounds is 2.4 dBA, representing a 

loss in listening area of 42.5%. The main source of audible noise at COLM001, COLM002, and 

COLM003 was vehicles and the main source of audible noise at COLM004 was aircraft.

Figure 85. Location of the proposed wilderness area within COLM and the two nearby airports.
349

Threats and Stressor Factors

Threats to the park’s soundscape include vehicle traffic, specifically on the north east side because of 

Interstate 70 and County Road 340 (seen in sound levels at COLM001, COLM002, and COLM003), 

and air traffic from two different airports (seen in sound levels at COLM004). Grand Junction 

Regional Airport (KGJT) and Mack Mesa Airport (10CO) are the two airports that concern COLM 

staff (Figure 85). Mack Mesa Airport (10CO) is the smaller of the two airports with only one runway, 

located 25.4 km (15.8 mi) away from the park (AirNav 2014b). An average of only 30 aircraft 

operations a day goes through Mack Mesa Airport (AirNav 2014b). KGJT has two runways, each 

larger than Mack Mesa’s single runway, and is only 15.5 km (9.6 mi) away from the east border of 

COLM. According to AirNav (2014a), KGJT is base for 86 single engine planes; nine multi engine 

planes, four jets, and three helicopters. An average of 140 aircraft operations occur per day at KGJT, 

causing noise disturbance over most of COLM, especially on the eastern boundary.

Data Needs/Gaps

In 1990, COLM was one of three parks on the Colorado Plateau were acoustic monitoring was 

conducted to document the perceived low ambient sound levels in these national parks (NPS NSNSD 

2013). The goal of this project was to develop baseline sound levels in order to protect sound 

resources (NPS NSNSD 2013). For unknown reasons, the data collected at COLM was not analyzed 

by the study researchers (NPS NSNSD 2013). In 2013, the NSNSD collected acoustic measurements 

at the park from April to May of 2013 (NPS 2013). Due to differences in the equipment and the 

methodologies the majority of the data collected in 1990 cannot be compared to 2013 (NPS NSNSD 

2013). The continuation of annual measurements of sound levels and sound recordings is essential 

for the management of the park’s soundscape. Using the 2013 monitoring results as a baseline, future 

researchers would have a better understanding of the sound levels in the park and their driving forces 

(NPS NSNSD 2013).

Overall Condition

Occurrence of Human-caused Sound - Loudness and Percent of Time Audible

The project team defined the Significance Level for this measure as a 3. McFarland (2015) found that 

sound levels at the four study sites exceeded the 35 dBA reference value less than 25% of the time 

during the daytime period and less than 7% at night. Sound levels ranged between 19.3 and 22.9 dBA 

during the day, and 15 and 18.1 dBA at night (McFarland 2015). There are two major noise sources 

(aircraft and vehicles) that contribute significant amounts of noise to the acoustical environment of 

COLM (McFarland 2015). Sounds from these sources are present from about 9 to 62 % of the time in 

a 24 hour period (McFarland 2015). Due to these factors a Condition Level of 1 was assigned. The 

vehicle and air traffic noise has the potential to mask the natural sounds at COLM (McFarland 2015). 

Due to this factor a declining trend was also assigned to this measure.

Occurrence of Human-caused Sound - Within and Outside of Proposed Wilderness Area

The project team defined the Significance Level for this measure as a 3. All four of the sound 

monitoring points are located within the proposed wilderness area at COLM (Figure 85). Median L50

values for these sites ranged from 24.9 and 29.4 dBA during the day and 15.8 and 22.1 dBA at night

(McFarland 2015). These values exceeded the baseline condition (median Lnat) by 2.7 to 6.5 dBA 
350

during the day (listening area reduction of 46 to 78%) and 0.5 to 4 dBA at night (listening reduction 

of 10.9 to 60.2%) (McFarland 2015). As one of the qualities of wilderness character is the 

opportunity for solitude or primitive and unconfined recreation these noise levels are an intrusion due 

to audibility of vehicles 9 to 62% of the time, aircraft (17 to 30%) and other extrinsic sounds (5 to

14%) (McFarland 2015). Due to this a Condition Level of 2, or moderate concern was assigned. A 

declining trend was also assigned due to increases in these noise sources (McFarland 2015).

Weighted Condition Score

The soundscape and acoustic environment was assigned a Weighted Condition Score of 0.5, 

indicating a current condition of moderate concern. Due to the potential for increases in the noise for 

vehicle and aircraft a downward trend was also assigned.

Soundscape and Acoustic Environment

Measures Significance Level Condition Level WCS = 0.50

Occurrence of 

Human-caused 

Sound - Loudness 

and Percent of Time 

Audible

3 1

Occurrence of 

Human-caused 

Sound - Within and 

Outside of Proposed 

Wilderness Area

3 2

4.19.6 Sources of Expertise

Katie Nuessly, NPS Biologist/Modeling Specialist

4.19.7 Literature Cited

AirNav LLC. 2014a. FAA information effective 24 July 2014. Grand Junction Regional Airport. 

http://www.airnav.com/airport/KGJT (accessed 13 August 2014).

AirNav LLC. 2014b. FAA information effective 24 July 2014. Mack Mesa Airport. 

http://www.airnav.com/airport/10CO (accessed 13 August 2014).

Anderssen, S.H., R.B. Nicolaisen, and G.W. Gabrielsen. 1993. Autonomic response to auditory 

stimulation. Acta Paediatrica 82:913-918.

Barber, J.R., K. R. Crooks, K. M. Fristrup. The costs of chronic noise exposure for terrestrial 

organisms. 2010. Trends in Ecology and Evolution 25(3):180-189.
351

Berglund, B., T. Lindvall, and D. H. Schwela (eds.). 1999. Guidelines for community noise. World 

Health Organization, Geneva, Switzerland.

Clough, G. 1982. Environmental effects on animals used in biomedical research. Biological Reviews 

57:487-523.

Dooling, R., and A. Popper. 2007. The effects of highway noise on birds. Environmental 

BioAcoustics LLC. Rockville, Maryland.

Environmental Protection Agency (EPA). 1974. Information on levels of environmental noise 

requisite to protect public health and welfare with an adequate margin of safety. Environmental 

Protection Agency, Washington, DC.

Environmental Protection Agency (EPA). 1982. National ambient noise survey. Office of Noise 

Abatement and Control, Washington, DC.

Haas, G., and T. Wakefield. 1998. National parks and the American public: A national public opinion 

survey on the national park system. National Parks and Conservation Association and Colorado 

State University, Washington DC and Fort Collins, Colorado.

Haralabidis, A. S., K. Dimakopoulou, F. Vigna-Taglianti, M. Giampaolo, A. Borgini, M. Dudley, G. 

Pershagen, G. Bluhm, D. Houthuijs, W. Babisch, and more. 2008. Acute effects of night-time 

noise exposure on blood pressure in populations living near airports. European Heart Journal 

29(5):658-664.

Harris, C. M. (1998). Handbook of Acoustical Measurements and Noise Control, 3rd edition 

McGraw-Hill, New York, New York.

Lynch, E., D. Joyce, and K. Fristrup. 2011. An assessment of noise audibility and sound levels in 

U.S. National Parks. Landscape Ecology 26:1297-1309.

Forest Service (USFS). 1992. Report to Congress. Potential impacts of aircraft overflights of 

National Forest System wildernesses. U.S. Department of Agriculture, Forest Service, 

Washington DC.

Haas, G. and T.Wakefield. 1998. National parks and the American public: A national public opinion 

survey on the national park system. National Parks and Conservation Association and Colorado 

State University, Washington DC and Fort Collins, Colorado.

McDonald, C., R. Baumgartner, and R. Iachan. 1995. National Park Service aircraft management 

studies. U.S. Department of Interior Rep. No. 94-2. National Park Service, Denver, Colorado.

McFarland, S. 2015. Colorado National Monument: Acoustical monitoring report 2013. Natural 

Resource Report NPS/NRSS/NRR—2015/918. National Park Service, Fort Collins, Colorado.

Mennitt, D., K. Sherrill, and K. Fristrup. A geospatial model of ambient sound pressure levels in the 

contiguous United States. The Journal of the Acoustical Society of America 135(5): 2746-2764.
352

Morfey, C. 2001. Dictionary of Acoustics, Academic Press, San Diego, California.

National Park Service (NPS). 1994. Report to Congress. Report on effects of aircraft overflights on 

the National Park System. http://www.nonoise.org/library/npreport/intro.htm#TABLE OF 

CONTENTS (accessed 20 December 2015)

National Park Service (NPS). 2006. Management Policy 8.2.3: Use of Motorized Equipment. Pages 

103–104 in National Park Service Management Policies 2006. National Park Service, 

Washington, DC.

National Park Service (NPS). 2013. Colorado National Monument acoustical monitoring snapshot. 

National Park Service, Natural Sounds and Night Skies Division, Fort Collins, Colorado.

National Park Service (NPS). 2014. Science of sound. http://www.nature.nps.gov/sound/science.cfm

(accessed 13 August 2014).

National Park Service Natural Sounds and Night Skies Division (NPS NSNSD). 2013. Natural 

Sounds and Night Skies Division looks to the past to evaluate current acoustical conditions in 

Colorado National Monument. Department of the Interior, National Park Service, Natural Sounds 

and Night Skies Division. Unpublished Report, Fort Collins, Colorado.

Payne, R., and D.Webb. 1971. Orientation by means of long range acoustic signaling in baleen 

whales. Annals of the New York Academy of Sciences, 188(1), 110–141.

Radle, A. L. 2007. The effect of noise on wildlife: A literature review. World Forum for Acoustic 

Ecology Online Reader. http://wfae.proscenia.net/library/articles/radle_effect_noise_wildlife.pdf

(accessed 22 October 2014).

Shannon, G., et al. (in press). A synthesis of two decades of research documenting the effects of 

noise on wildlife. Biological Reviews.

Selye, H. 1956. The stress of life. McGraw-Hill. New York, New York.

Templeton, D., P. Sacre, P. Mapp, and D. Saunders. 1997. Acoustics in the built environment: 

Advice for the design team 2

nd edition. Architectural Press. Oxford, England.
353

4.20 Paleontological Resources

4.20.1 Description

COLM hosts a diverse paleontological record 

contained within rocks that date back to as early 

as the Precambrian. Although fossiliferous 

exposures are not well inventoried within the 

park, investigators have found paleontological 

materials in the area that include vertebrate, 

invertebrate, and trace fossils (KellerLynn 

2006; Photo 31). One of the first 

paleontological investigations in COLM was a 

1977 inventory of the Morrison Formation that 

documented 14 fossil localities that contained 

bivalves, gastropods, turtles, crocodilians, and 

dinosaurs (Callison 1977, KellerLynn 2006). 

The majority of these findings were located in 

the lower Salt Wash and Brushy Basin 

Members of the Morrison Formation 

(KellerLynn 2006). The Morrison Formation is world famous for its fossils, in particular its large 

dinosaurs (Tweet et al. 2012).

The Morrison Formation is the most fossiliferous unit at COLM, and fossils have been discovered in 

each member of the formation present within COLM (Tweet et al. 20012). Due to the abundance of 

fossils in the Morrison formation, it is considered to have the highest potential of all the formations 

within COLM for producing vertebrate fossils (Armstrong and Kihm 1980). A number of significant 

fossil discoveries have occurred near the park (Armstrong and Kihm 1980, KellerLynn 2006). In 

1900, the first skeleton of a Brachiosaurus, a giant plant-eating Jurassic dinosaur, was discovered 

just to the east of COLM at Riggs Hill (KellerLynn 2006). The discovery of the forelimb and 

shoulder blade of Camarasaurus occurred just to the north of COLM (KellerLynn 2006). While the 

Morrison Formation is known for gigantic and unusual dinosaurs, its exposures in the Fruita area are 

most well-known for fossils of smaller vertebrates (KellerLynn 2006).

The oldest exposed rocks at COLM, commonly referred to as “basement rocks,” consist of gneiss, 

schist, and granites known as the Black Canyon Group that are 1.7 to 1.5 billion years old (NPS 

2014). These Precambrian rocks, overlain by younger igneous dikes dating to the Mesoproterozoic, 

are extremely unlikely to contain fossils given their lithology and metamorphism (Tweet et al. 2012). 

With the exception of the Dakota Formation, the younger sedimentary rocks preserved above, 

deposited by wind and water during the Mesozoic Era, do contain fossil specimens from the Triassic, 

Jurassic, and Cretaceous periods (Tweet et al. 2012). These sedimentary units, dating from oldest to 

youngest, include the Triassic Chinle Formation, the Glen Canyon Group (Wingate Sandstone and 

the Kayenta Formation), the San Rafael Group (Entrada Sandstone and Wanakah Formation), the 

Morrison Formation, the Burro Canyon Formation, and the Dakota Formation. These stratigraphic 

Photo 31. Three-toed dinosaur track from COLM 

(NPS photo)
354

units, including their associated depositional environment and paleontological resources within 

COLM, are present in Table 89.

Table 89. Stratigraphy, fossils, and depositional setting of COLM (table recreated from Tweet et al. 2012). 

Formations are listed in order of age, from oldest (metamorphosed sedimentary and igneous rocks) to 

youngest (Quaternary sediments).

Formation Age Fossils within COLM Depositional Environment

Metamorphosed 

sedimentary and 

igneous rocks

At least 

Paleoproterozoic

None to date; fossils are extremely

unlikely because of lithology and

metamorphism

Not applicable (igneous rocks

that solidified at depth and

strongly metamorphosed

sedimentary rocks)

Igneous dikes Mesoproterozoic Unfossiliferous (intrusive igneous

rocks)

Not applicable (igneous rocks

that solidified at depth)

Chinle Formation Late Triassic Root traces, invertebrate traces,

and rare bones

Fluvial, floodplain, and lacustrine

settings, becoming drier over

time

Wingate Sandstone Late Triassic - Early

Jurassic

Bioturbation from roots and

burrows, and tracks of dinosaurs,

other reptiles, and mammal

relatives

Desert with large aeolian sand 

dunes

Kayenta Formation Early Jurassic Local bioturbation and two bones Primarily fluvial settings

Entrada Sandstone Middle Jurassic Bioturbation Coastal dunes and sand flats

Wanakah Formation Middle Jurassic Invertebrate traces and possible

pterosaur feeding traces

Mud flats and/or shallow lakes

Morrison Formation Late Jurassic Bivalves, gastropods, horseshoe

crab traces, a lungfish tooth plate,

bones of turtles, crocodile 

relatives, and dinosaurs, and a 

pterosaur footprint

Fluvial, floodplain, and lacustrine

settings

Burro Canyon Formation Early Cretaceous Petrified wood, root traces,

invertebrate traces, and dinosaur

bones

Fluvial, floodplain, and lacustrine

settings

Dakota Formation Early - Late 

Cretaceous

Possibly plant fossils, root traces,

and invertebrate traces

Terrestrial (especially fluvial)

becoming shallow marine over

time

Quaternary sediments Pleistocene -

Holocene

Plant fossils, a mammoth or

mastodon tooth, bones of nine

other mammal and bird taxa, and 

packrat middens

Alluvial, aeolian, fluvial, and 

landslide deposits

The Chinle Formation lies above the Precambrian basement and is a heterogeneous terrestrial unit 

deposited in a variety of fluvial and lacustrine settings in an environment interpreted as a vegetated 

floodplain or mud flat with shallow ponds and streams that became drier over time (Tweet et al. 

2012). Within COLM, only the Red Siltstone Member of the Chinle Formation is present (dating to 

the late Triassic), and although generally not known for vertebrate fossils, it is fossiliferous within 

COLM (Tweet et al. 2012). Ichnofossils, possible microbial laminations in the limestone, and general 
355

bioturbation are common in this formation (Scott et al. 2001b, Tweet et al. 2012). The bioturbation is 

represented by disruptions of the sedimentary structures in the form of plant roots, crayfish and 

beetle larval burrows, and horseshoe crab walking traces (Scott et al. 2001b). A theropod dinosaur 

track site, interpreted to be Grallator-like, was discovered within the Chinle Formation in 1990 near 

the east entrance of the park (Scott et al. 2001b). Petrified wood may be present in the rocks of 

COLM as it has been found in the Chinle Formation on the Colorado Plateau (KellerLynn 2006).

Overlying the Chinle Formation is the Glen Canyon Group, which is further divided into the Wingate 

Sandstone and the Kayenta Formation within COLM. The Wingate Sandstone is a well-sorted, winddeposited sandstone unit of the Lower Jurassic with large, sweeping crossbeds dating to 200 million 

years in age (NPS 2014). Vertebrate fossils are rare from the Wingate Sandstone, as aeolian 

deposition rarely preserves these remains; given the abrasive nature of windblown sand that quickly 

erodes any vertebrate remains prior to burial and fossilization (Armstrong and Kihm1980). Like the 

Chinle Formation, the Wingate Sandstone is fossiliferous at COLM in the form of trace discoveries 

consisting of bioturbation from plant roots and burrows (Scott et al. 2001a). Tracks from mammal 

relatives, dinosaurs, and other reptiles are also reported, including five localities with 18 trackways 

and 79 tracks assigned to the theropod ichnogenus Grallator (Tweet et al. 2012).

The Kayenta Formation of the Glen Canyon Group is composed of fine- to coarse-grained sandstone 

with minor shale and conglomerates that date to 190 million years old (NPS 2014). These sediments 

reflect a return to a fluvial environment, with the nature of the bedding making it possible for the 

preservation of footprints, as well as the presence of conglomerates increasing the potential for 

vertebrate fossils (Armstrong 1980). However, within COLM this unit is sparsely fossiliferous with 

local bioturbation and two bones being reported from a mudstone-pebble conglomerate near the top 

of this formation (Tweet et al. 2012).

The Entrada Sandstone and the Wanakah Formation compose the San Rafael Group in COLM. The 

Entrada Sandstone is dominated by aeolian deposits with a distinct red color dating to 165 million 

years in age (NPS 2014). The Entrada Sandstone is further divided into two geologic units within 

COLM: the Slick Rock Member and the Board Beds Member. While the Slick Rock Member is 

interpreted as being a coastal dune field with wet interdunes, the Board Beds Member is interpreted 

as representing a wet coastal sand flat depositional environment (Tweet et al. 2012). These ancient 

near-shore environments generally have a low potential for vertebrate remains and age-diagnostic 

fossils, with preserved footprints having the highest potential (Armstrong and Kihm1980). Both 

members, however, have been reported to exhibit bioturbation within COLM (Scott et al. 2001a, 

Tweet et al. 2012).

The younger Wanakah Formation of the San Rafael Group is composed of thin red mudstone, 

sandstone, and green shale that date to 160 million years in age (NPS 2014). Although this formation 

is not known for its fossils, within COLM a few invertebrate trace fossils and possible pterosaur 

feeding traces have been identified (Tweet et al. 2012). Evidence of bioturbation in the form of plant 

roots and animal burrows are also present within this formation at COLM (KellerLynn 2006).
356

The most fossiliferous geologic unit at COLM 

is the Morrison Formation, which represents the 

last geologic formation of the Jurassic in 

COLM (Tweet et al. 2012). This fossil 

assemblage represents a decrease in aridity and 

an increase in more humid conditions as 

Pangaea pushed north, allowing for a greater 

biomass to be supported leading to greater 

species diversity (Tweet et al. 2012). The 

Morrison Formation is famous for its fossils, 

containing one of the best terrestrial fossil 

records of the Mesozoic Era. Discoveries on the 

Colorado Plateau have included traces of 

microbial, faunal, and photosynthetic organisms, invertebrate traces such as brachiopods and 

gastropods, vertebrates known from body fossils such as turtles and crocodile relatives, and large 

dinosaurs such as Allosaurus, Brachiosaurus, and Stegosaurus (Tweet et al. 2012). Within COLM, 

the Morrison Formation is divisible into three geologic units: the Tidwell Member, the Salt Wash 

Member, and the Brushy Basin Member (NPS 2014). All three members are fossiliferous within 

COLM, and display evidence of bioturbation in the form of trace fossils such as plant roots and 

burrows from insects and animals (Tweet et al. 2012). The Tidwell Member is a fluvial and 

lacustrine unit yielding algal and microbial laminations, charophytes, gastropods, ostracodes, 

horseshoe crab traces, and a lungfish tooth plate within COLM, as well as containing a dinosaur 

locality and a pterosaur footprint (Tweet et al. 2012). The Salt Wash Member developed in fluvial, 

floodplain, and lake settings, and produces charophytes, petrified wood, ostracodes, and bones from 

theropods and sauropods (Tweet et al. 2012). The Brushy Basin Member is the most poorly exposed 

unit of the Morrison Formation in COLM due to mass wasting (i.e., landslides) (Scott et al. 2001a). 

Its depositional environment has been interpreted as a mudflat to shallow lacustrine setting (Scott et 

al. 2001a). Fossils found within this member at COLM include turtle shell remains and dinosaur 

bones (Tweet et al. 2012).

The Burro Canyon Formation (early Cretaceous) represents fluvial and floodplain depositional 

environments, with minor lacustrine deposition found only on Black Ridge (Tweet et al. 2012). 

Fossils of the Burro Canyon Formation are generally not well known at this time, but the formation 

possesses plant root traces, bioturbation in the form of burrows, and petrified wood that is locally 

abundant in sandstone beds within COLM (Scott et al. 2001a, KellerLynn 2006, Tweet et al. 2012). 

Additionally, dinosaur bones have been reported in fallen Burro Canyon Formation blocks in the 

park (Tweet et al. 2012).

The Dakota Formation is interpreted as a terrestrial depositional environment (especially fluvial) that 

became shallow marine over time and is limited to the cap of Black Ridge within COLM (Scott et al. 

2001a). Generally regarded as being 100 million years in age, the transgression and regression of the 

Western Interior Seaway over the land during the deposition of the Dakota Formation caused the age 

to differ across the landscape as different areas were affected by the encroaching sea at different 

Photo 32. Lizard tracks on Morrison Formation 

sandstone (NPS photo).
357

times (Tweet et al. 2012). The fossils of the Dakota Formation are diverse; however, within COLM 

this formation is not specifically known to be fossiliferous (Tweet et al. 2012). Recent reports 

suggest that it may contain fossils, as Scott et al. (2001a) found bioturbation in the form of plant 

roots and animal burrows to be common within this formation in the COLM area. Other reports of 

fossils within this formation in the region include plant fossil fragments (particularly angiosperm 

leaves), invertebrate traces, and vertebrate tracks (KellerLynn 2006, Tweet et al. 2012).

The final geologic unit present in COLM consists of Quaternary sediments deposited through 

alluvial/fluvial, aeolian, and colluvial (i.e., landslides) processes that date from the Pleistocene 

through Holocene (Tweet et al. 2012). On the Colorado Plateau, these deposits are sometimes found 

to contain fossil material useful for paleoecological and paleoclimatological studies (e.g., pollen and 

packrat middens) (Tweet et al. 2012). Isolated bones of large mammals such as sloths, mammoths, 

mastodons, horses, and camels have also been found in these deposits (Tweet et al. 2012). Within 

COLM fossils found in this unit include bone and plant specimens collected from a fissure exposure, 

a possible mammoth or mastodon tooth, and unpublished pack rat middens (Tweet et al. 2012).

4.20.2 Measures

 Changes in specimen abundance at paleontological localities

 Documentation and inventory of paleontological sites within the park

 Incidence of theft

 Amount of paleontological resources eroded out each year

 Erosion rate at paleontological sites

4.20.3 Reference Conditions/Values

A reference condition/value for paleontological resources was not defined by park staff. Ideally, the 

100% documentation of all paleontological sites within the park would provide the best baseline data 

for reference conditions/values. Currently, a wide variety of fossils have already been discovered at 

COLM (Tweet et al. 2012). However, a systematic inventory of these fossil resources does not exist 

at this time (KellerLynn 2006). Until recently, COLM reported annually to the GPRA Goal Ia9 

(Paleontological Localities Condition) concerning 75 localities, 72 of which were reported to be in 

good condition in 2010 (Tweet et al. 2012).

4.20.4 Data and Methods

The remarkable scenic value at COLM places an emphasis on its geologic character, while 

paleontological components of the park continue to be identified and analyzed (Tweet et al. 2012). 

Although numerous publications exist that refer to the geology and paleontology of COLM, many 

only briefly mention the park or deal primarily with faulting and deformation (Tweet et al. 2012). 

Therefore, these sources are not applicable to a park-wide assessment of the paleontological resource 

condition.

Reports of fossil findings in the Grand Junction, Colorado area date back to at least 1885 (Chenoweth 

1987). The fossil resources found within COLM have historically been overshadowed by discoveries 

at Morrison Formation sites just outside of park boundaries (Tweet et al. 2012) One of the earliest 
358

reports of fossil findings in the area was by Elmer S. Riggs, who extracted fossils from the Morrison 

Formation just outside the current boundaries of COLM (Tweet et al. 2012). Other early fossil 

resource inventories were conducted by Holt (1942) and Callison (1977). Holt (1942) collected 

freshwater invertebrate fossils from the Grand Junction, Colorado area. Callison (1977) discovered 

12 vertebrate-fossil producing localities in Morrison Formation rocks within COLM. These were 

mainly dinosaur bones and bone scrap; however, due to the no-collection policy of the NPS, they 

were largely unidentified (Armstrong and Kihm 1980). Other reports documenting paleontological 

resources at COLM include; Hasiotis (1997), Engelmann (1999), Engelmann and Hasiotis (1999),

Scott et al. (1999), Engelmann and Fiorillo (2000), and Anderson et al. (2000).

The initial complete paleontological resource inventory and summary at COLM was completed in 

2002 by Koch and Santucci (2002). Additional paleontological resource inventories conducted 

between 2002 and 2006 identified 75 paleontological localities within COLM (Santucci et al. 2006). 

King et al. (2004) reported at least 79 theropod tracks, identified as the ichogenera Grallator, from 

five localities in the Wingate Sandstone within COLM. Several localities with numerous theropod 

tracks in the Wingate Sandstone were also reported by Trujillo and Walker (2004, 2005). Lucas et al. 

(2006) recorded a manus imprint, identified as Pteraichnus, from the Summerville Formation (a 

member of the San Rafael Group). Fossil vertebrate tracks were found in the Salt Wash Member of 

the Morrison Formation by Lockley and Foster (2006). The tracks included a theropod, small 

ornithopod dinosaur (ichnogenus Dinehichnus) and turtles (ichnogenus Chelonichnium) (Lockley and 

Foster 2006).

Tweet et al. (2012) prepared paleontological summaries with preliminary paleontological resource 

management recommendations for the parks of the NCPN. This report compiled information through 

extensive literature reviews and interviews with park staff, geologists, and paleontologists. The report 

consolidates baseline paleontological resource data for each NCPN park to support management 

operations, planning, and science-based decision-making (Tweet et al. 2012).

Additional sources with broader overviews that were useful for this assessment include Evenden et 

al. (2002), KellerLynn (2006), and Scott et al. (2001b). Evenden et al. (2002) is a Phase I natural 

resources monitoring report summarizing existing information on NPS and related natural resource 

monitoring programs within the NCPN, presenting overviews of biological and physical resources of 

network parks, including describing monitoring goals and needs, and presents a theoretical 

framework with conceptual models for guiding future efforts. KellerLynn (2006) is a geologic 

resource evaluation report specific to COLM that contains information relevant to resource 

management and scientific research, and was developed to accompany the digital geologic map of 

the park. Following the initiation of the first comprehensive inventory of paleontological resources in 

the national parks and monuments in Colorado in 2000, the Scott et al. (2001b) report presents 

baseline paleontological resource data obtained during the survey to assist NPS staff with the 

management and protection of paleontological resources within their respective parks.

Green (2014) conducted a paleontological survey of COLM from 3 June 2013 to 18 October 2013. 

The goal of this project was two-fold; to locate and evaluate fossils sites documented in previous 

studies and to explore the park in an attempt to identify new fossil sites (Green 2014). Of the 
359

localities identified in previous studies, Green (2014) confirmed that seven had been collected and 

were located within the COLM museum collection, eight could not be relocated due erosion or illegal 

collection, nine could not be located due to errors in the recording of the original collection 

coordinates, and two were not researched due to time constraints. Green (2014) also identified a total 

of 23 new localities.

4.20.5 Current Condition and Trend

Changes in Specimen Abundance at Paleontological Localities

The potential for future fossil discoveries within COLM are possible, as demonstrated by the Scott et 

al. (2001b) survey. Due to the abundance of fossils found in the Morrison Formation, especially in 

the COLM area, this formation has a high potential to yield vertebrate fossils (Armstrong and Kihm 

1980). Currently, a wide variety of fossils and other paleontological materials have been documented 

in and around the park. A systematic inventory of fossil resources would likely result in the discovery 

of new paleontological resources (KellerLynn 2006). Continued paleontological fieldwork and 

research would also likely result in new discoveries of fossils in the future (Santucci et al. 2006).

In an attempt to aid in the management of paleontological resources in COLM and the Grand 

Junction area, Armstrong and Kihm (1980) ranked the geologic units in terms of their relative

potential for producing scientifically valuable vertebrate fossils. The units were ranked and divided 

into four groups (Table 90). Group 1 formations are those that have a proven potential for containing 

fossil vertebrate resources (Armstrong and Kihm 1980). Group 2 are those formations that have 

produced fossil vertebrates on the Colorado Plateau. Formations in this group likely contain fossil 

vertebrate localities, but have not been identified due to limited fieldwork in the area (Armstrong and 

Kihm 1980). Group 3 includes the formations that have only occasionally produced fossils or 

localities are at a great distance from the COLM/Grand Junction area. Group 4 contains those 

formations where there was a general lack of information available (Armstrong and Kihm 1980).

Documentation and Inventory of Paleontological Sites within the Park

COLM has produced a wide variety of fossils, and studies in the surrounding area have produced 

paleontological materials (KellerLynn 2006). While a systematic, park-wide paleontological 

inventory and monitoring program has yet to be established at COLM, several investigations within 

the park have provided data that can be used as a partial paleontological resource inventory baseline 

dataset (KellerLynn 2006, Tweet et al. 2012). Callison (1977) documented 14 fossil localities within 

COLM. Scott et al. (2001b) conducted a preliminary inventory of paleontological resources at 

COLM. Additional paleontological resource inventories include surveys by Koch and Santucci 

(2002) and Trujillo et al. (2004). These studies, and others, have greatly advanced the paleontological 

knowledge of the park and indicated the potential for future discoveries (KellerLynn 2006). COLM 

reported on 75 localities to the GPRA Goal 1A9 (Paleontological Localities Condition), 72 of which 

were reported to be in good condition as of 2010 (Tweet et al. 2012). COLM also maintains a 

collection of paleontological specimens. Currently this collection contains 443 catalog numbers 

(excluding nine educational models); however, this number does include specimens collected from 

formations not found within COLM (Tweet et al. 2012).
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Table 90. Relative potential, by formation, for fossil vertebrates in the COLM area (reproduced from 

Armstrong and Kihm 1980).

Group Formation

Relative 

Rank

Present at 

COLM Potential

Group 1 Morrison 1 X High

Mancos Shale 2

Burro Canyon 3 X

Group 2 Chinle 4 X

Mount Garfield 5

Pleistocene deposits 6

DeBeque 7

Green River 8

Group 3 Kayenta 9 X

Dakota 10 X

Wingate Sandstone 11 X

Cutler 12

Group 4 Summerville 13 X

Hunter Canyon 14

Sego Sandstone 15

Entrada Sandstone 16 X Low

Incidence of Theft

The growing scientific and public interest in paleontological resources within NPS units is paralleled 

by an increasing number of documented thefts or incidents of vandalism (Santucci et al. 2006). These 

incidents have ranged from damage due to poor or inappropriate casting techniques to unauthorized 

collection (Santucci 2006). Fossil theft and vandalism are a concern for COLM resource managers 

(Tweet et al. 2012). Incidents have occurred at COLM; for example, one locality inventoried by 

Callison (1997) has been vandalized (Engelmann and Fiorillo 2000, KellerLynn 2006, Tweet et al. 

2012). Without a park-wide inventory as a baseline, it is difficult to accurately assess if and/or where 

paleontological resources within COLM have been lost due to theft or vandalism (KellerLynn 2006).

Amount of Paleontological Resources Eroded Out Each Year

The natural process of erosion is responsible for creating the landforms of COLM (KellerLynn 

2006). Erosional processes can cover known resources as well as uncover new paleontological 

resources (KellerLynn 2006). Slope failure occurs continuously throughout the park and is a constant 

maintenance issue in areas of COLM like Rim Rock Drive (KellerLynn 2006). Landslides, rockfalls, 

and debris flows can increase the amount of paleontological resources eroded out, which can be 

aggravated through human activities such as road construction and vehicle vibration (KellerLynn 

2006). Flash floods are another agent that can form and modify the landscape of COLM. Intense 

summer thunderstorms are common on the Uncompahgre Plateau, supplying large volumes of water 

in short periods of time to canyon areas (KellerLynn 2006). Increases in both flow rates and flood 

heights in constricted canyon areas subsequently elevate the amount of sediment eroded out 
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(KellerLynn 2006). Determination of the amount of paleontological resources eroded out each year is 

difficult to determine given the lack of a park-wide inventory and monitoring program and is 

considered a data gap for this assessment.

Erosion Rate at Paleontological Sites

The ecosystem present today within COLM was developed by the work of erosional processes 

(KellerLynn 2006). The erosional rates of the various formations within COLM are dependent on the 

susceptibility of rocks to erosion and the thickness of the formation (KellerLynn 2006). The 

formations with lower erosion rates (less erodibility) generally form cliffs, canyons, and ledges while 

those with higher erosion rates tend to form slopes (KellerLynn 2006). These highly erodible slopes 

contain the majority of the paleontological resources found within COLM (KellerLynn 2006). Slope 

failure can take the form of landslides, rockfalls and debris flows and occurs continually at COLM 

(KellerLynn 2006). Although a natural process, slope failure can be worsened by human activities 

such as construction, the use of climbing equipment, and the use of social trails (KellerLynn 2006). 

Less erodible, fossil-bearing formations such as the Wingate Formation, Kayenta Formation, and the 

Salt Wash Member of the Morrison Formation formed unstable cliffs that can produce rockfalls. 

Table 91 provides a brief summary for rates of erosion associated with the formations found within 

COLM. The rates reflect the degree of erodibility compared to other formations found within COLM.

Table 91. Erodibility of rock formations within COLM (recreated from KellerLynn 2006). The degree of 

erodibility is in reference to the other formations found within COLM only.

Formation Erodibility

Precambrian Low erodibility

Kayenta

Dakota Sandstone

Wingate Sandstone

Entrada Sandstone

Burro-Canyon

Morrison

Wanakah

Chinle High erodibility

Threats and Stressor Factors

There are many environmental and anthropogenic factors and processes that can affect 

paleontological resources. Figure 86 shows a conceptual diagram of some of these potential threats 

and stressors to paleontological resources as well as how they interact. Park staff identified several of 

these as being of concern at COLM: erosion, weathering, climate change, theft, vandalism, and 

recreation impacts (specifically climbing).
362

Figure 86. Conceptual diagram illustrating various environmental and anthropogenic factors and 

processes that might affect the stability of in situ paleontological resources. The graphic is a NPS diagram 

reproduced from Santucci and Koch (2003).

The process of erosion is responsible for the formation of the colored canyons, arches, natural 

bridges, alcoves, pinnacles, and balanced rocks that are some of the most important geological 

features in COLM (KellerLynn 2006). However, erosion through aeolian and hydrologic processes 

can lead to both the exposure of new fossil resources and the loss of existing fossil resources to 

natural deterioration (KellerLynn 2006). The erosional processes can also increase the potential for 

fossil theft and vandalism (KellerLynn 2006).

Wind erosion and freeze-thaw process are forms of weathering of the rock formations that occur 

within COLM. The wind acts on exposed sediments and friable rock formations, causing erosion 

(and abrasion) in addition to the collection of airborne sediment and soil particles (KellerLynn 2006). 

Increased weathering could have a detrimental impact on the quality of exposed paleontological 

resources.

Changes to the timing, frequency, and duration of precipitation events associated with climate 

change, coupled with the highly erodible landscape within COLM, has the potential to influence the 

erosional and weathering rates of paleontological resources within COLM. Climate change could 

lead to an increase in the timing, frequency, and duration of sudden and extreme precipitation events, 

which in turn leads to increased runoff and accelerating erosion (Wei et al. 2009), particularly in 

those formations that are most susceptible to erosion (see Table 91; KellerLynn 2006). Alterations to 

vegetation and ground cover brought on by climate change could make the landscape more 

susceptible to wind erosion. Aeolian sand on upland locations within COLM is locally stabilized by 

trees such as juniper and in other areas by sage, rabbitbrush, and bunch grass (KellerLynn 2006). 
363

Reductions in these vegetation types could further expose paleontological resources to erosion and 

weathering. Climate change resulting in extreme precipitation events can result in heavy flash 

flooding increasing erosion activity within the park (KellerLynn 2006).

Theft and vandalism of fossil resources at COLM has been documented (Engelmann and Fiorillo 

2000, KellerLynn 2006, Tweet et al. 2012). Increased visitor access and exposure of new fossil 

resources by erosion can increase the number of paleontological resources that can potentially be 

impaired or lost to the effects of vandalism and theft (KellerLynn 2006). Increased visitation can 

impact fossil resources in a number of ways in addition to greater potential for theft and vandalism. 

The rapid creation of social trails, which is tied to increasing visitation, has caused increased erosion 

in Monument Canyon, lower Liberty Cap Trail, No Thoroughfare Canyon, the trail between the 

visitor center and Book Cliffs View, and on Alcove Trail (KellerLynn 2006). Another anthropogenic 

induced increase in erosion can come from the use of climbing equipment (KellerLynn 2006). The 

use of bolts and pitons can result in the erosion of rock faces, causing both aesthetic and physical 

damage to the rocks (KellerLynn 2006).

Data Needs/Gaps

Continued research of the paleontological resources at COLM can provide a better understanding of 

the past as well as potential future conditions (KellerLynn 2006, Tweet et al. 20102). While only one 

of the measures (amount of paleontological resources eroded out each year) is considered a data gap, 

all the measures would benefit from a systematic park-wide inventory of paleontological resources 

(KellerLynn 2006). In addition to providing baseline information, such a survey would likely 

discover new fossil resources (KellerLynn 2006). The baseline data could provide a basis for a 

monitoring program, which would limit the future loss of paleontological material, and ensure its 

availability for scientific study (KellerLynn 2006). Additionally, a comprehensive inventory would 

provide a basis for NPS and public understanding of the paleontological resources at the park

(KellerLynn 2006).

After compilation of a baseline, the next phase of paleontological resource management is a 

monitoring program (Tweet et al. 2012). A preliminary strategy for implementing a paleontological 

monitoring protocol has been presented by Santucci and Koch (2003), which also identified natural 

and human-related impacts to fossils (Tweet et al. 2012). A more comprehensive strategy including 

natural and anthropogenic stressors, a study design and case studies was presented by Santucci et al. 

(2009).

Park staff should be encouraged to observe exposed sedimentary rocks and their eroded deposits for 

fossil material (KellerLynn 2006). Staff should photo-document and monitor discoveries; however, 

the fossils and the surrounding rock should be left in place unless they are subject to direct human 

impact or artificially increased natural processes (KellerLynn 2006). Park staff should also be 

encouraged to take advantage of opportunities to observe paleontological resources in the field or 

take part in paleontological field studies with trained paleontologists (KellerLynn 2006).
364

Overall Condition

Changes in Specimen Abundance at Paleontological Localities

The project team assigned a Significance Level of 2 for this measure. The geologic formations within 

COLM contain significant fossil resources and there is the potential for new discoveries. Visitor 

impacts through vandalism and theft have impacted the abundance of specimens at paleontological 

sites within COLM. Other parks with paleontological resources, such as Fossil Butte National 

Monument, have implemented management actions to minimize the impacts of theft and vandalism. 

COLM resource managers have expressed concern over fossil theft and vandalism (Tweet et al. 

2012). While the potential exists for changes to specimen abundance at localities, only a few 

instances have been documented. Due to this, the measure has been assigned a Condition Level of 1, 

meaning low concern.

Documentation and Inventory of Paleontological Sites within the Park

The project team defined the Significance Level of 2 for this measure. In 2010 the GPRA Goal Ia9 

report submitted by COLM reported on 75 paleontological localities, 72 of which were determined to 

be in good condition (Tweet et al. 2012). The current park collection contains 443 catalog numbers 

for paleontological specimens; however, some of these did not originate within COLM (Tweet et al. 

2012). Several preliminary inventories have been completed, but a systematic inventory of fossil 

resources park-wide has not been completed (KellerLynn 2006, Tweet et al. 2012, Green 2014). Such 

an inventory would provide a baseline for a monitoring program and provide a basis for better NPS 

and public understanding of the paleontological resources at COLM (KellerLynn 2006). Based on the 

lack of this inventory and the impact it would have on all the measures, this measure is assigned a 

Condition Level of 2, meaning moderate concern.

Incidence of Theft

This measure was also assigned a Significance Level of 2 by park staff. Incidents of theft and 

vandalism have been documented within COLM (Engelmann and Fiorillo 2000, KellerLynn 2006, 

Tweet et al. 2012, Green 2014). Increased visitor access and exposure of new fossil resources by 

erosion can increase the number of paleontological resources that can potentially be impaired or lost 

to the effects of vandalism and theft (KellerLynn 2006). While only one documented reference to 

theft of paleontological resources has been officially recorded, the lack of a comprehensive baseline 

inventory and associated monitoring likely contributes to this lack of reported instances. Green 

(2014) was unable to locate eight of the known localities and attributed this to either illegal collection 

or erosion. Due to these factors, this measure is assigned a Condition Level of 2, meaning moderate

concern.

Amount of Paleontological Resources Eroded Out Each Year

Park staff assigned this measure a Significance Level of 2. While information on erosion rates for the 

fossil-bearing formations at COLM was available, no information was available to quantify the 

amount of paleontological resources uncovered by erosion each year. Therefore, this measure is 

considered a data gap and as such, a Condition Level cannot be assigned at this time.
365

Erosion Rates at Paleontological Sites

Park staff assigned a Significance Level of 3 to this measure. The Morrison Formation contains the 

majority of the fossil resources found at COLM. As can be seen in Table 90 and Table 91, the 

Morrison Formation along with the Burro Canyon and Chinle Formations have the highest potential 

for fossil resources in COLM. They also are some of the most erodible formations within COLM. 

Due to these two factors, a Condition Level of 2 has been assigned to this measure.

Weighted Condition Score

The Weighted Condition Score for COLM’s paleontological resources is 0.59, indicating condition 

for the paleontological resources warrants moderate concern. Given the lack of a park-wide baseline 

inventory, a trend assessment was not determined.

Paleontological Resources

Measures Significance Level Condition Level WCS = 0.59

Changes in Specimen 

Abundance at 

Paleontological 

Localities

2 1

Documentation and 

Inventory of 

Paleontological Sites 

Within the Park

2 2

Incidence of Theft 2 2

Amount of 

Paleontological 

Resources Eroded Out 

Each Year

2 n/a

Erosion Rate at 

Paleontological Sites 3 2

4.20.6 Sources of Expertise

Tim Connors, NPS Geological Resources Division Geologist/Mapping Coordinator

Justin Tweet, Tweet Paleo-Consulting

Vincent Santucci, NPS Geological Resources Division Senior Geologist/Paleontology Program 

Coordinator
366

4.20.7 Literature Cited

Anderson, R. S., J. L. Betancourt, J. I. Mead, R. H. Hevly, and D. P. Adam. 2000. Middle- and lateWisconsin paleobotanic and paleoclimatic records from the southern Colorado Plateau, USA. 

Palaeogeography, Palaeoclimatology, Palaeoecology 155(1-2):31-57.

Armstrong, H. J., and A. J. Kihm. 1980. An evaluation of the fossil vertebrate resources of the Glade 

Park and Mount Garfield planning area. Grand Junction District of the Bureau of Land 

Management, Western Colorado. Grand River Institute, Grand Junction, Colorado.

Callison, G. L. 1977. Inventory of fossil vertebrates in Morrison Formation rocks on the Colorado 

National Monument. Colorado National Monument Association, Fruita, Colorado.

Chenoweth, W. L. 1987. The Riggs Hill and Dinosaur Hill sites, Mesa County, Colorado. Pages 97-

100 in Paleontology and geology of the Dinosaur Triangle. Averett, W. R., editor. Museum of 

Western Colorado, Grand Junction, Colorado.

Engelmann, G. F. 1999. Stratigraphic and geographic distribution of fossils in the upper part of the 

Upper Jurassic Morrison Formation of the Rocky Mountain region. Pages 115-120 in Vertebrate 

paleontology in Utah. Gillette, D. D., editor. Miscellaneous Publication 99-1. Utah Geological 

Survey, Salt Lake City, Utah. 

Engelmann, G. F., and A. R. Fiorillo. 2000. The taphonomy and paleoecology of the Upper Jurassic 

Morrison Formation determined from a field study of fossil localities. GeoResearch Forum 

6:533–540.

Engelmann, G. F., and S. T. Hasiotis. 1999. Deep dinosaur tracks in the Morrison Formation: Sole 

marks that are really sole marks. Pages 179-184 in Vertebrate paleontology in Utah. Gillette, D. 

D., editor. Miscellaneous Publication 99-1. Utah Geological Survey, Salt Lake City, Utah. 

Evenden, A., M. Miller, M. Beer, E. Nance, S. Daw, A. Wight, M. Estenson, and L. Cudlip. 2002. 

Northern Colorado Plateau Vital Signs Network and Prototype Cluster, Plan for Natural 

Resources Monitoring: Phase I Report, October 1, 2002. [Two volumes]. National Park Service, 

Northern Colorado Plateau Network, Moab, Utah. 

Green, C. 2014. 2013 report on the paleontological inventory of the Colorado National Monument 

June - October 2013. National Park Service, Unpublished Report, Colorado National Monument, 

Colorado

Hasiotis, S. 1997. In search of behavior in ancient life – animals and plant trace fossils in national 

parks and national monuments in the Four Corner states. Pages 82-84 in Partners in 

paleontology: Proceedings of the fourth conference of fossil resources. Johnston, J. and J. 

McChristal, editors. Natural Resources Report NPS/NRFLO/NPR-97/01. National Park Service, 

Fort Collins, Colorado.

Holt, E. L. 1942. A new Unio from the Morrison Formation of the Grand River Valley, Colorado. 

Journal of Paleontology 16(4):459-460.
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KellerLynn, K. 2006. Colorado National Monument geologic resource evaluation report. Natural 

Resource Report NPS/NRPC/GRD/NRR—2006/007. National Park Service, Denver, Colorado. 

King, M., J. Smith, and J. Foster. 2004. First report of vertebrate tracks from the Wingate Sandstone 

(Triassic-Jurassic) of Colorado National Monument, Colorado. Journal of Vertebrate 

Paleontology 24(supplement to 3):78A.

Koch, A. L., and V. L. Santucci. 2002. Paleontological resource inventory and monitoring - Northern 

Colorado Plateau Network. TIC# D-206. National Park Service, Denver, Colorado.

Lockley, M. G., and J. R. Foster. 2006. Dinosaur and turtle tracks from the Morrison Formation 

(Upper Jurassic) of Colorado National Monument, with observations on the taxonomy of 

vertebrate swim tracks. Pages 193-198 in Paleontology and geology of the Upper Jurassic 

Morrison Formation. Foster, J. R. and S. G. Lucas, editors. Bulletin 36. New Mexico Museum of 

Natural History and Science, Albuquerque, New Mexico. 

Lucas, S. G., A. P. Hunt, and W. R. Dickinson. 2006. Stratigraphy and the base of the Jurassic 

Morrison Formation in Colorado National Monument, Mesa County, Colorado. Pages 9-15 in

Paleontology and geology of the Upper Jurassic Morrison Formation. Foster, J. R. and S. G. 

Lucas, editors. Bulletin 36. New Mexico Museum of Natural History and Science, Albuquerque, 

New Mexico. 

National Park Service (NPS). 2014. Colorado National Monument geologic formations. 

http://www.nps.gov/colm/naturescience/geologic-formations.htm (accessed 8 August 2014).

Santucci, V. L., and A. L. Koch. 2003. Paleontological resource monitoring strategies for the 

National Park Service. Park Science 22(1):22-25. 

Santucci, V. L., A. P. Hunt, T. Nyborg, and J. P. Kenworthy. 2006. Additional fossil vertebrate tracks 

in National Park Service areas. Pages 152-158 in America’s Antiquities: 100 Years of Managing 

Fossils on Federal Lands. Seventh Fossil Resource Conference, May 22-23, 2006. New Mexico 

Museum of Natural History and Science, Albuquerque, New Mexico. 

Santucci, V. L., J. P. Kenworthy, and A. L. Mims. 2009. Monitoring in situ paleontological 

resources. Pages 189-204 in Geological monitoring. Young, R. and L. Norby, editors. Geological 

Society of America, Boulder, Colorado. 

Scott, R. B., W. C. Hood, J. B. Johnson, R. Tausch, T. O. Sexton, and P. Perrotti. 1999. Charcoal 

record in sediments and fire ecology history of pinon-juniper uplands of the Uncompahgre Uplift, 

western Colorado. Abstracts with Programs - Geological Society of America 31(7):482-483.

Scott, R. B., A. E. Harding, W. C. Hood, R. D. Cole, R. F. Livaccari, J. B. Johnson, R. R. Shroba, 

and R. P. Dickerson. 2001a. Geologic map of the Colorado National Monument and adjacent 

areas, Mesa County, Colorado. U.S. Geologic Investigations Series 2740. Geological Survey, 

Reston, Virginia. 
368

Scott, R. L., V. L. Santucci, and T. Connors. 2001b. An inventory of paleontological resources from 

the national parks and monuments in Colorado. Pages 178-202 in Proceedings of the 6th fossil 

resource conference: 2001 a fossil odyssey. Santucci, V. L. and L. McClelland, editors. 

NPS/NRGRD/GRDTR—01/01. National Park Service, Geological Resource Division, 

Lakewood, Colorado.

Trujillo, K., M. Imhof, and Z. Walke. 2004. Report on 2004 paleontological survey and inventory 

management plan. National Park Service, Colorado National Monument, Colorado.

Trujillo, K., M. Imhof, and Z. Walke. 2005. Report on a comprehensive paleontological survey of 

Colorado National Monument. Journal of Vertebrate Paleontology 25(supplement to 3):124A.

Tweet, J. S., V. L. Santucci, T. Connors, and J. P. Kenworthy. 2012. Paleontological resource 

inventory and monitoring: Northern Colorado Plateau Network. Natural Resource Technical 

Report NPS/NCPN/NRTR - 2012/585. National Park Service, Fort Collins, Colorado.

Wei, W., L. Chen, and B. Fu. 2009. Effects of rainfall change on water erosion processes in 

terrestrial ecosystems: a review. Progress in Physical Geography 33(3):307-318.
369

4.21 Geologic Features and Processes

4.21.1 Description

COLM’s erosional and exposed rock geologic 

features were the driving force behind the 

establishment of the park and still attract many 

visitors to the site today (NPS 2005). COLM 

lies on the northeast edge of the Uncompahgre 

Plateau, an uplifted area which covers an area 

approximately 150 km (90 mi) long by 45 km 

(27 mi) wide (Scott et al. 2001).

Erosion has created a variety of amazing and 

colorful geologic features at COLM, from sheer 

canyon walls to impressive monoliths, 

archways, and balanced rocks. Wind and water 

wear away the more erodible rock layers (e.g., 

Wingate sandstone, soft shales), leaving the 

resistant strata behind, and sometimes in 

seemingly unnatural shapes (KellerLynn 2006). 

In Monument Canyon, for example, visitors can 

view Window Rock, Coke Ovens (Photo 33), 

and Independence Monument (Photo 34), an 

erosional remnant that rises 137 m (450 ft) from 

the canyon floor (KellerLynn 2006).

The park’s geologic features provide an 

excellent illustration of how various physical 

processes, particularly erosion and uplift, have 

shaped the greater Colorado Plateau region 

(KellerLynn 2006). For example, COLM 

contains a monocline (i.e., a step-like dip or 

fold in rock strata) where erosion has exposed a 

series of rock layers which provide a visual 

record of geologic history (KellerLynn 2006). 

This monocline is a classic example of the 

Laramide orogeny, a period of mountainbuilding that began 70 million years ago (mya) 

and continued for approximately 20 million 

years (Scott 2001). Visitors can observe a 

remarkable sequence of Mesozoic (252-66 

mya) rock layers and even Precambrian (>540 

Photo 33. Geological features in COLM include 

Window Rock (top) and Coke Ovens (bottom) (NPS 

photos).

Photo 34. Independence Monument (photo by Anna 

Davis, SMUMN GSS).
370

mya) basement rocks (KellerLynn 2006) (Figure 87). The rock layers also show several 

“unconformities”, or places where strata of very different geological ages meet. These are due to the 

erosion of the rock layer that should have been in between, prior to deposition of the next layer. For 

example, erosion removed all of the Paleozoic Era (540-252 mya) strata in the park prior to 

deposition of the Mesozoic Era strata, resulting in a more than one-billion-year gap in the rock layers 

(Harris and Kiver 1985, KellerLynn 2006) (Figure 87). The major geological formations within

COLM are listed by age in Table 92. Rock outcrops on the west side of the park are generally 

younger and older formations are found on the east side in canyon bottoms (Scott et al. 2001, Tweet 

et al. 2012).

Figure 87. A cross section of the rock layers (geological formations) exposed at COLM (reproduced from 

NPS 2005, adapted from Lohman 1965). A “U” represents the location of an unconformity. Triassic, 

Jurassic, and Cretaceous are all periods within the Mesozoic Era.

The oldest geologic formation exposed in 

COLM is metamorphosed sedimentary rock 

from Precambrian times, at least 1,740 mya 

(Tweet et al. 2012). COLM is one of only a few 

places on the Colorado Plateau where this 

formation is exposed (KellerLynn 2006). Just 

above the Precambrian strata is the Chinle 

Formation. This rock layer is distinguished by 

the red color that can be seen in many of 

COLM’s canyons (Armstrong and Kihm 1980; 

Photo 35). The formation contains shales interbedded with thin sandstone and some volcanic 

Photo 35. The characteristic red color of the Chinle 

Formation (NPS photo).
371

sediment, due to eruptions that occurred during the period of deposition (Armstrong and Kihm 1980, 

Tweet et al. 2012). The next formation on top of the Chinle is Wingate Sandstone. This rock layer 

was formed during an arid period, when wind-blown sands formed large dunes in the area 

(Armstrong and Kihm 1980, Tweet et al. 2012). The lime-rich sandstone that resulted is orangetinted, with brown or reddish siltstone also present within the formation (Tweet et al. 2012). Many of 

the park’s impressive geologic features, including Independence Monument, are composed of 

Wingate Sandstone (Armstrong and Kihm 1980).

The early Jurassic Kayenta Formation consists 

of red and buff-colored sandstone with some 

purplish siltstone and shale (Armstrong and 

Kihm 1980, Tweet et al. 2012). The Kayenta 

formed during a wetter period when the region 

was a floodplain, and sediments were deposited 

by meandering streams and rivers (Tweet et al. 

2012). These rocks are more resistant to erosion 

than the sandstone layers above and below it, 

and often forms benches or ledges within cliffs. 

Kayenta Formation “caps” often protect the 

underlying Wingate Sandstone from erosion, 

producing some of COLM’s spectacular 

monoliths (Lohman 1981; Photo 36). Without 

the Kayenta “caps” the Wingate Sandstone 

would weather into rounded do

mes (Lohman 1981). The overlying Entrada 

Sandstone, like the Wingate, was formed during 

a drier period when sand dunes existed in the 

region (Tweet et al. 2012). The Entrada can also form impressive cliffs and geologic features, such as 

the “Saddlehorn” near the COLM visitor center (Lohman 1981). The layer contains a variety of 

colors including pink (when freshly exposed), red, pale orange, and white (Armstrong and Kihm 

1980, Tweet et al. 2012),

Photo 36. Devils Kitchen in No Thoroughfare 

Canyon is an example of remnant Wingate 

sandstone capped and protected from erosion by 

the Kayenta Formation (USGS photo by T. F. Giles, 

from Lohman 1981).
372

Table 92. Major geological formations (i.e., rock layers) within COLM (adapted from Tweet et al. 2012). Notes are from Armstrong and Kihm 

(1980), Harris and Kiver (1985), and Tweet et al. (2012).

Geologic Era Formation Age Depositional Environment Notes

Quaternary Quaternary Sediments Pleistocene-Holocene 

(2 mya-present)

Alluvial, eolian, fluvial, and 

landslide deposits

-

Precambrian Metamorphosed 

sedimentary and igneous 

rocks

At least Paleoproterozoic

(2500-1600 mya)

N/A Highly resistant to erosion; exposed in No 

Thoroughfare Canyon, one of the few places 

on the Colorado Plateau where these strata 

can be seen

Igneous dikes Mesoproterozoic

(1600-1000 mya)

N/A Highly resistant to erosion; exposed in No 

Thoroughfare Canyon, one of the few places 

on the Colorado Plateau where these strata 

can be seen

Mesozoic Chinle Formation Late Triassic

(228-200 mya)

Fluvial, floodplain, and lacustrine 

settings, becoming drier over time

Distinctive red color; 27-29 m thickness in 

COLM

Wingate Sandstone Late Triassic- Early 

Jurassic

(228-175 mya)

Desert with large eolian sand 

dunes

Forms many of COLM’s impressive geologic 

features; 95-110 m thickness in COLM

Kayenta Formation Early Jurassic

(200-175 mya)

Primarily fluvial settings More resistant to erosion than the under- and 

over-lying sandstones; 14-24 m thickness

Entrada Sandstone Middle Jurassic 

(175-162 mya)

Coastal dunes and sand flats Forms prominent cliffs; approximately 47 m in 

thickness

Wanakah (formerly 

Summerville) Formation

Middle Jurassic 

(175-162 mya)

Mud flats and/or shallow lakes Distinctive green-over-red coloration; about 9 

m thick

Morrison Formation Late Jurassic

(162-145 mya)

Fluvial, floodplain, and lacustrine 

settings

Heterogeneous and variegated unit; around 

160 m in thickness

Burro Canyon Formation Early Cretaceous 

(145-100 mya)

Fluvial, floodplain, and lacustrine 

settings

Heterogeneous; lower part of layer forms 

white to yellowish cliffs; around 30 m thick on 

Black Ridge

Dakota Sandstone Early-Late Cretaceous

(145-66 mya)

Terrestrial (especially fluvial), 

becoming shallow marine over time

Only park unit containing marine sediments; 

approximately 31 m thick on Black Ridge
373

The Wanakah Formation is comprised primarily of 

mudstone and characterized by a distinctive “green-overred” coloration (Scott et al. 2001). It was deposited during a 

time when the region supported a shallow lake or mudflats 

(Armstrong and Kihm 1980, Scott et al. 2001). In COLM, 

the formation is exposed near the tops of canyon walls and 

forms gentle, rolling slopes when weathered (Armstrong and 

Kihm 1980). The overlying Morrison Formation is a diverse 

rock layer, consisting of a mix of mudstone, claystone, 

siltstone, sandstone and limestone (Photo 37) (Armstrong 

and Kihm 1980, Tweet et al. 2012). Colors vary from gray 

and green, to red and light purple. It is believed to have 

formed under a semi-arid, seasonal climate, when the Grand 

Junction area was on the edge of a vast, shallow basin 

(Tweet et al. 2012). Sediments in the Morrison Formation 

are most likely lake, mudflat, and floodplain deposits 

(Armstrong and Kihm 1980, Tweet et al. 2012). The Burro 

Canyon Formation also formed under a semi-arid climate 

and includes a mix of sandstone, siltstone, shale, 

conglomerate, and limestone (Tweet et al. 2012). The lower 

portion of the layer is dominated by cliff-forming, white to yellowish gray sandstone, while the upper 

portion is primarily pale red or greenish siltstone. The sandstone portion likely originated from 

stream and floodplain deposits while the upper siltstone layer is from lake and floodplain deposits 

(Armstrong and Kihm 1980, Tweet et al. 2012). At COLM, the Burro Canyon Formation is found 

only on Black Ridge (Tweet et al. 2012).

The youngest of the Mesozoic deposits in COLM is the Dakota Sandstone. It is unique in that it is the 

only formation in COLM that contains marine deposits, as the Western Interior Seaway advanced 

and retreated several times during the Cretaceous Period (Lohman 1981, Tweet et al. 2012). The 

Dakota Sandstone contains a variety of layers, reflecting environmental changes at the time of 

deposition. The layers include a grayish coaly mudstone, light-colored sandstone, and a sandstoneshale conglomerate (Armstrong and Kihm 1980, Tweet et al. 2012). Outcrops often weather into 

yellow-brown cliffs and ledges, with broken-off blocks forming talus (i.e., rock debris) slopes 

(Armstrong and Kihm 1980). Overlying the Dakota Sandstone are Quaternary Sediments, which are 

primarily surficial units consisting of deposits left by water (alluvium), wind (eolian), and gravity 

(colluvium) (Tweet et al. 2012). At COLM, Quaternary Sediments include alluvium, eolian sand, 

colluvium, and rockfall and landslide deposits (KellerLynn 2006).

Photo 37. The Morrison Formation, 

exposed at the mouth of No 

Thouroughfare Canyon (photo from 

Lohman 1981).
374

The erosional processes that carved the canyons 

of COLM and exposed this series of geological 

formations continue to act in the park today. 

The U-shaped canyon valleys were shaped by 

stream erosion over time; although permanent 

streams no longer occur in COLM, surface 

runoff from snowmelt and precipitation feeds 

intermittent streams, which continue the 

process of erosion (Harris and Kiver 1985). 

Streamflow, particularly during flash floods, 

can erode away less resistant formations 

underlying more resistant formations, resulting 

in undercutting. Eventually, large slabs of the 

overlying, more resistant layer may break off 

and fall to the canyon floor, leaving sheer cliff 

walls behind (Lohman 1981, Harris and Kiver 

1985). The slabs break up over time, creating 

slopes of sand and sediment at the base of the 

canyon walls (Photo 38). These rockfalls can cause safety hazards for park visitors, particularly along 

canyon hiking trails and at overlooks along Rim Rock Drive (KellerLynn 2006). In addition, some 

rocks at COLM contain expansive clays, which swell when wet, increasing the likelihood of 

landslides in the area (KellerLynn 2006). Rapid shifts in temperature experienced at COLM, such as 

solar heating on summer days and cooling at night, cause rocks to expand and contract, which can 

cause layers to crack and break off (Lohman 1981). During winter, the freeze-and-thaw cycle of 

ice/water in cracks near cliff faces can also break apart rocks (Lohman 1981). Lastly, winds can also 

erode exposed rock surfaces (KellerLynn 2006).

4.21.2 Measures

 Changes in rates of erosion

 Frequency of rock falls or slides

 Frequency of heavy rain and sustained wind events

 Frequency and discharge of flash floods

4.21.3 Reference Conditions/Values

Reference conditions have not been established for geological features and processes. Historical 

records of rock falls/slides, flash floods, heavy rains, and sustained wind events are not consistent, so 

it is difficult to identify a “baseline” frequency. The information presented in this assessment for high 

wind, heavy rain, and flash flood frequency could be used as a baseline for future assessments.

4.21.4 Data and Methods

The geology and notable features of COLM have been described in many publications since the 

1960s. Earlier literature utilized in this assessment include Armstrong and Kihm (1980), Lohman 

Photo 38. A large slab of fallen rock in Ute Canyon, 

with slopes of sand and debris at the base of the 

canyon walls (photo from Lohman 1981).
375

(1981), and Harris and Kiver (1985). In 2001, Scott et al. (2001) published a geologic map of COLM 

and the surrounding region, which included descriptions of each geologic formation and a discussion 

of the key geologic processes at COLM. Several years later, the NPS produced a geological resource 

evaluation report for COLM (KellerLynn 2006). This report summarized the geologic history, 

features, and processes of the park, as well as geologic issues (e.g., erosion, flash floods, slope 

failure). More recently, Tweet et al. (2012) prepared a summary of paleontological resource 

inventory and monitoring in the NCPN, which included descriptions of fossil-bearing geological 

formations at COLM.

Richard (2004) published a history of flash flooding at COLM from 1921-2003. This summary was 

based on NPS records and Grand Junction’s local newspaper, and is not a comprehensive report of 

every flood that has occurred adjacent to COLM (Richard 2004). Additional data on extreme weather 

events (flash floods, high winds, and heavy rain) were obtained from the National Climatic Data 

Center (NCDC) storm events database (http://www.ncdc.noaa.gov/stormevents/). Records were 

available for the area around COLM (e.g., Grand Valley, Grand Junction, Fruita, Glade Park) from 

1996 through 2014 (NCDC 2015a).

The NPS Geologic Resources Division has recently completed a geohazard assessment for Rim Rock 

Drive at COLM. This report was not available for review for this assessment, but would be a 

valuable asset that could provide further insight for future assessments of this resource at COLM.

4.21.5 Current Condition and Trend

Changes in Rates of Erosion

As discussed above, erosion has played a critical role in creating the stunning geologic features of 

COLM. This natural process continues to act today and will eventually wear away the monoliths and 

other features that attract visitors to the park. Shifts in environmental conditions (e.g., climate) and 

human activities can change erosion rates (Lohman 1981, KellerLynn 2006). To date, erosion rates 

have not been specifically studied at COLM. Pederson et al. (2002) used GIS to estimate erosion and 

uplift rates on the Colorado Plateau during the Cenozoic Era; investigators estimated that 843 m 

(2,766 ft) of erosion have occurred over the past 30 million years. This equates to an average of 28.1 

m (92.2 ft) of erosion per million years. However, the time scale of this estimate is not practical for 

measuring or detecting present changes in erosion rates.

Frequency of Rock Falls or Slides

Rock falls, landslides, and debris flow are all types of “slope failure”, a natural process that occurs 

constantly throughout COLM (KellerLynn 2006). Rock falls are common along cliffs of Wingate 

Sandstone, the Kayenta Formation, and the Salt Wash Member of the Morrison Formation (Scott et 

al. 2001). Human activities such as road construction and vibrations from heavy vehicles can 

accelerate this natural process, which is a constant maintenance concern along Rim Rock Drive in the 

park. Slope failures along Rim Rock Drive and its overlooks are a threat to visitor safety and to 

access/travel for both staff and visitors (KellerLynn 2006). In January of 2000, car-sized sandstone 

blocks fell onto Rim Rock Drive and blocked traffic for over a month (Photo 39) (Scott et al. 2001). 

Slope failure is also a danger along park trails, particularly along Serpents Trail, near the park’s east 
376

entrance (KellerLynn 2006). The recently 

completed geohazards assessment of Rim Rock 

Drive could provide further insight into this 

measure.

Frequency of Heavy Rain and Sustained Wind 

Events

Heavy rains and sustained high winds can 

contribute to sudden, dramatic incidences of 

erosion, such as the types of slope failures 

described above. Intense thunderstorms are 

common during the summer throughout the 

Uncompahgre Plateau (Scott et al. 2001, 

KellerLynn 2006). These storms often produce 

high winds and large amounts of rain in a short time period. Heavy rain and high wind events have 

not been documented consistently over time at COLM. As a result, it is difficult to determine if their 

frequency has changed over time. The NCDC storm events database contains records of heavy rain 

and high or strong wind events in the COLM area from 1996 through 2014 (NCDC 2015a). These 

records are presented here and may be used to analyze trends in event frequency in the future.

High winds are defined as sustained winds of at least 64 km/hr (40 mph) for an hour or more or any 

winds over 93 km/hr (58 mph) (NWS 2007). Winds that do not meet these thresholds but result in 

injuries or significant property damage are categorized as strong wind events (NWS 2007). During 

the 19 year period of record, 28 high or strong wind events were reported in the Grand Valley/Grand 

Junction area (Table 93). At least one event occurred in 15 of the 19 years; the highest number of 

events in a single year was five, occurring in 2009. Events were distributed between late February to 

early June and from mid-September to late November (NCDC 2015a). No trends in frequency are 

apparent during this period of record.

Heavy rains are defined as unusually high amounts of rain that do not cause flash flooding but do 

cause damage (i.e., human/economic impact) (NWS 2007). During the 19 year period of record for 

the area around COLM, 21 separate heavy rain events were reported (Table 94). All events occurred 

between late April and early October, with the majority between June and September. The most 

events in a single year were five in 2006 (NCDC 2015a).

Richard (2004) used 1948-2002 daily precipitation records for June-September to determine 

recurrence intervals for storms likely to cause flash flooding. According to those calculations, the 

heaviest rainstorm on record (6.5 cm [2.5 in] in August 1957) had a 100-year recurrence interval 

(Table 95). Storms with 1.8 cm (0.7 in) of rain occurred approximately every 2 years based on 1948-

2002 data. However, in both 2013 and 2014, two rain events of this magnitude or greater were 

recorded each year at the COLM rain gauge (2.5 cm [1 in] and 1.9 cm [0.7 in] in September 2013, 

2.9 cm [1.1 in] and 2.4 cm [0.9 in] in August 2014) (NCDC 2015b).

Photo 39. Rock fall onto Rim Rock Drive in January 

2000 (NPS photo by Ron Young).
377

Table 93. High and strong wind events in the Grand Valley/Grand Junction area, 1996-2014 (NCDC 

2015a).

Event Type Date Event Type Date

High wind 10/19/1996 Strong wind 9/21/2005

High wind 3/27/1997 Strong wind 10/4/2005

High wind 10/2/1997 Strong wind 4/17/2006

High wind 10/7/1997 Strong wind 11/14/2006

High wind 11/26/1997 High wind 4/18/2007

High wind 2/24/1998 Strong wind 6/6/2007

High wind 9/29/1998 Strong wind 9/29/2007

High wind 4/18/2000 High wind 3/22/2009

High wind 3/14/2001 High wind 3/29/2009

High wind 4/20/2001 Strong wind 4/15/2009

Strong wind 4/2/2003 Strong wind 4/25/2009

Strong wind 6/16/2003 High wind 9/30/2009

Strong wind 9/17/2003 Strong wind 6/16/2010

Strong wind 6/10/2004 High wind 3/26/2012

Table 94. Heavy rain events in the area around COLM, 1996-2014 (NCDC 2015a).

Location Date Location Date

Grand Junction 7/29/1998 Redlands and Fruita 10/5/2006

Fruita 9/12/1998 Fruita 7/27/2008

Glade Park 6/19/2003 Grand Junction 8/8/2008

Fruita 8/23/2003 Grand Junction 6/18/2009

Fruita 9/10/2003 Grand Junction 6/26/2009

Fruita 4/24/2005 Fruita 8/4/2010

Glade Park and Grand Junction 9/21/2005 Fruita 7/23/2012

Grand Junction 7/19/2006 Glade Park 7/31/2012

Glade Park 8/13/2006 Grand Junction 7/13/2013

Fruita 9/8/2006 Grand Junction 7/17/2013

Grand Junction 10/3/2006

Table 95. Recurrence intervals for various 24-hour rainfall amounts at the COLM headquarters rain 

gauge, based on 1948-2002 precipitation data, as calculated by Richard (2004).

Recurrence Interval (years)

Parameter 100 50 10 5 2

Rainfall (cm/in) 6.5 (2.5) 5.8 (2.3) 3.8 (1.5) 2.5 (1.0) 1.8 (0.7)

Frequency and Discharge of Flash Floods

A flash flood is defined by the National Weather Service (NWS) as “a rapid and extreme flow of 

high water into a normally dry area, or a rapid water level rise in a stream or creek above a 
378

predetermined flood level” (NWS 2007, p. 32). The rate and duration of rainfall, soil conditions, 

topography, and ground cover all contribute to flash flood occurrence (Richard 2004). The 

physical setting at COLM (steep canyon walls, bare rock surfaces, semi-arid climate) increases 

the likelihood of flash flood occurrence (Richard 2004). The impermeable rock surfaces prevent 

precipitation from infiltrating into the ground and the steep canyon walls channels water into 

small areas, increasing the rate and force of the flow. Within COLM’s boundaries, 57% of the 

area is categorized as rock or soil with moderate to very slow permeability (Richard 2004). 

During historic floods in COLM’s canyons, floodwaters have moved boulders over 2 m (6.6 ft) 

in diameter (Scott et al. 2001).

Richard (2004) summarized 13 different flash flood events that occurred in or were fueled by 

COLM’s canyons between 1921 and 2003 (Table 96). All reported flash floods occurred between 

July and early September. Table 96 shows that flash floods are not always correlated with high 

rainfall amounts at existing rain gauges, demonstrating that flash flood-causing storms can be 

localized and isolated (Richard 2004). 

The NCDC storm events database recorded flash floods in the COLM vicinity between 1996 and 

2014 (NCDC 2015a), a period of record which partially overlaps with Richard (2004). During these 

years, the NCDC documented 16 flash flood events in the area (Table 97). These events cover a 

wider portion of the year than those documented by Richard (2004), extending from mid-June to 

early October. The available data (Richard 2004, NCDC 2015a) seem to suggest that flash flood 

frequency may be increasing over time (13 recorded events from 1921-2003, 16 events from 1997-

2014), but this could be due to differences in record-keeping (e.g., less attention given to 

documenting flash floods in the early mid-20th century) rather than actual change. More attention has 

been given to flash flooding occurrence and potential since development has increased along the 

park’s eastern boundary (Richard 2004, KellerLynn 2006).

Little information is available regarding the discharge of flash floods in COLM’s canyons. The rare 

and sudden nature of these events likely makes them difficult to study. The only available data are 

from a USGS analysis of flows from NTC and Red and Columbus Canyons combined during the 

September 1978 flood. According to USGS estimates, peak discharge from NTC was 263.1 cms 

(9,290 cfs) with a unit discharge (total discharge volume divided by drainage area) of 5.4 m3/sec/km2

(494 ft3/sec/mi2) (Richard 2004). Peak discharge from Red Canyon was 81.8 cms (2,890 cfs) with a

unit discharge of 7.3 m3/sec/km2(664 ft3/sec/mi2) (Richard 2004).
379

Table 96. Historical flash floods (1921-2003) in the COLM vicinity summarized by Richard (2004). KGJT 

= Grand Junction Airport.

Date

Rainfall (cm)

COLM KGJT Notes

8/24/1921 - 3.60 Damaged 20 county bridges; made the road between Fruita and Grand 

Junction impassable

8/8/1948 0.30 2.30 Storm dropped 1.1 cm (0.4 in) of rain in 15 min.; flash flood along the 

eastern park boundary

7/3/1949 0.40 - Extensive damage on a southern portion of Rim Rock Drive and Serpents 

Trail 7/7/1949 0.05 -

7/28/1950 0.40 0.30 Damaged Rim Rock Drive and two diversion ditches

8/6/1957 6.50 1.40 4.7 cm (1.9 in) fell in 2 hours, damaging fences in East Monument 

Canyon and causing numerous rock and mud slides on Rim Rock Drive.

8/8/1968 4.90 - Caused a major washout of Rim Rock Drive between the two tunnels 

above the west entrance; see Photo 40

9/7/1978 1.70 1.10 Bridge washed away on Monument Road in NTC, and power lines were 

downed; see Photo 41

9/2/1990 0.70 1.30 Caused rock falls that closed Rim Rock Drive and overtopped a bridge on 

Monument Road

8/4/1991 - - Eroded NTC trail and moved large rocks

7/11/1992 0.05 1.10 Floodwaters threatened to breach one of the Redlands Water & Power 

Co. canals

7/24/1998 2.30 - 5 cm (2 in) of rain fell in 40 minutes near the east entrance, damaged a 

large portion of Serpents Trail

7/10/2001 4.10 - 4.1 cm (1.6 in) of rain fell in less than 2 hours, flooding the Visitor Center 

and other park buildings; Rim Rock Drive was covered in mud near the 

east entrance

Table 97. Flash flood events reported in the area around COLM, 1996-2014 (NCDC 2015a). The 

locations for 2014 flooding were reported only as “Mesa County”; it is not known which specific 

communities where flooding occurred.

Location Date Location Date

Grand Junction 8/5/1997 Fruita 8/11/2005

Grand Junction 7/23/1998 Grand Junction 10/6/2006

Grand Junction 9/19/1999 Redlands 6/18/2009

Redlands 7/10/2001 Glade Park 8/27/2013

Redlands 8/3/2001 Redlands 8/27/2013

Grand Junction 9/12/2002 Mesa County 7/25/2014

Fruita 8/23/2003 Mesa County 7/29-30/2014

Glade Park 8/8/2005 Mesa County 8/4/2014
380

Photo 40. Section of Rim Rock Drive washed out by flooding above the west entrance in August 1968 

(NPS photo).

Photo 41. Wash-out along Monument Road on 7 September 1978 (Photo by Jim Johnson, from Richard 

2004).
381

Threats and Stressor Factors

Threats to COLM’s geologic features and processes include climate change (especially extreme 

weather events), human activities, and park management activities. Management activities that 

impact park geology include road maintenance, trail creation and maintenance, and drainage 

management (e.g., culverts, ditches). Many of these activities are necessary to maintain visitor safety 

and enjoyment.

Human activities influence natural geological processes such as erosion and slope failure, usually 

increasing their rate or frequency (KellerLynn 2006). The best example of this at COLM is Rim 

Rock Drive. Traffic along the road, particularly from heavy vehicles such as buses and semi-trucks, 

causes vibrations that can contribute to rock falls and slope failures (KellerLynn 2006). Development 

in surrounding areas has increased traffic on Rim Rock Drive, as it is the shortest route from Glade 

Park to Grand Junction. The existence of the road alone has increased runoff and altered drainage 

patterns (KellerLynn 2006). The creation of social trails, which often occurs with increased 

visitation, also contributes to localized erosion (e.g., Monument Canyon, No Thoroughfare Canyon, 

and the trail from the Visitor Center to Book Cliffs View). Lastly, rock climbing and the use of 

climbing equipment (e.g., bolts installed in rock faces) can cause erosion and damage to the rock 

surfaces (KellerLynn 2006).

The semi-arid climate of the COLM region has contributed to the stunning nature of the park’s 

geological features. According to Lohman (1981), a wetter climate would have resulted in a 

“smoother” landscape, with most of the rocks and geological features obscured by vegetation. The 

climate in western Colorado is predicted to shift as a result of global climate change (Melillo et al. 

2014). Likely changes include an increase in temperature with longer and hotter summer heat waves, 

an increased potential for drought and wildfires, and an increase in precipitation falling as very heavy 

events (Lamm et al. 2014, Melillo et al. 2014). More precipitation falling in heavy events would have 

a direct influence on erosion rates, flash flooding frequency, and slope failures and fluvial resources 

(Wei et al. 2009). An increased occurrence of wildfires could also contribute to erosion and slope 

failure, as fire removes vegetation and litter that cover ground surfaces, protecting them from water 

and wind (KellerLynn 2006, Wei et al. 2009).

Data Needs/Gaps

Additional data are needed for every measure selected for this resource. Erosion rates, which will 

vary between geological formations, have not been studied in the park. Consistent record-keeping of 

slope failures is needed to determine their frequency. An inventory of areas with high potential for 

slope failure along Rim Rock Drive and its overlooks would also be useful for park management 

(KellerLynn 2006). A simple method for monitoring gradual movement or creep that could indicate 

risk of slope failure is to place stakes in loose material along the road and track any position changes 

on an annual or biennial basis (KellerLynn 2006). Additional study on the how much of the surface 

within the park is in its “native” condition (has not been altered by human activity). The “native” 

versus altered surfaces could be analyzed in terms of absorption and run-off to gain a better 

understanding of areas that contribute to flash flooding. Park staff can also monitor cracks in the 

asphalt along Rim Rock Drive, another potential indicator of slope creep.
382

Continued collection of weather event data (e.g., heavy rain, high winds, and flash floods) will allow 

for the detection of any changes in the frequency of these events. Given the localized nature of some 

heavy precipitation events in the region, the installation of additional weather stations in the park 

may help managers better understand the relationship between precipitation and flash floods. In 

addition, repeat photography may be used to document the impact of flash floods on COLM’s 

geological features. Further study of flash flooding (e.g., recurrence intervals, floodplain 

identification, and discharge rates) would be beneficial in understanding the risks of expanded 

development downstream of the park’s canyons (Richard 2004, KellerLynn 2006). This could 

involve creating and running flash flood models for each drainage in COLM. Verifying the model 

would require collecting data on peak flow drainages, which could be obtained by installing creststage gages and using the step- backwater method to rate stream channels (KellerLynn 2006).

Overall Condition

Changes in Rates of Erosion

This measure has been assigned a Significance Level of 3. Erosion is a natural process and has 

created the spectacular geological features of COLM. However, changes in erosion rates could 

threaten these geologic features, as well as the safety and enjoyment of visitors to the park. To date, 

erosion rates have not been measured within COLM. Therefore, a Condition Level cannot be 

assigned for this measure.

Frequency of Rock Falls or Slides

This measure also received a Significance Level of 3. While slope failures such as rock falls and 

slides are also natural processes, they can be exacerbated by human activities and pose a threat to 

visitor safety and access within the park. Slope failures are known to occur at COLM and have 

damaged or closed Rim Rock Drive, but records have not been officially kept regarding their 

frequency. As a result, a Condition Level cannot be assigned for this measure. However, the recently 

completed geohazards assessment of Rim Rock Drive could provide further insight into this measure.

Frequency of Heavy Rain and Sustained Wind Events

The frequency of these events was assigned a Significance Level of 2. Heavy rains and high winds 

contribute to erosion of COLM’s geological features. If these events were to increase in frequency, 

erosion rates would likely also increase. The NCDC has some records (1996-2014) of heavy rain and 

high/strong wind events in the COLM vicinity. Using 1948-2002 precipitation data, Richard (2004) 

estimated that storms producing 1.8 cm of rain occurred once every two years. However, two events 

of this magnitude occurred annually in 2013 and 2014 (NCDC 2015b), suggesting an increase in the 

frequency of heavy rain events. A Condition Level of 2 was assigned to this measure, indicating 

moderate concern.

Frequency and Discharge of Flash Floods

This measure received a Significance Level of 3. Flash floods have played a key role in shaping the 

canyons and geological features of COLM (KellerLynn 2006). They are also a threat to people and 

property both within and outside the park. Flash floods have washed out portions of Rim Rock Drive 

and various park trails, and covered other portions in mud or debris. Flood waters have also washed 
383

out bridges and caused property damage at the lower ends of COLM’s canyons, in the Grand 

Junction and Redlands areas. Sixteen flash flood events were recorded in the area around COLM 

from 1996-2014 (NCDC 2015a), while only 13 events were reported from 1921-2003 (Richard 

2004). This suggests that flash flood frequency may be increasing, but the change could be at least 

partially due to differences in record-keeping. The possible increase in heavy precipitation event 

frequency discussed previously would likely also increase flash flood frequency. Therefore, this 

measure is also assigned a Condition Level of 2 for moderate concern. 

Weighted Condition Score

A Weighted Condition Score was not calculated for this component due to a lack of data for two of 

the four measures. The current condition of COLM’s geological features and processes is considered 

unknown.

Geologic Features and Processes

Measures Significance Level Condition Level WCS = N/A

Changes in Rates of 

Erosion 3 n/a

Frequency of Rock 

Falls or Slides 3 n/a

Frequency of Heavy 

Rain and Sustained 

Wind Events

2 2

Frequency and 

Discharge of Flash 

Floods

3 2

4.21.6 Sources of Expertise

Tim Connors, NPS Geological Resources Division Geologist/Mapping Coordinator

Hal Pranger, NPS Geologic Resources Division Geologic Features and Systems Branch Chief

4.21.7 Literature Cited

Armstrong, H. J. and A. J. Kihm. 1980. An evaluation of the fossil vertebrate resources of the Glade 

Park and Mount Garfield Planning Areas, Grand Junction District of the Bureau of Land 

Management, Western Colorado. Grand River Institute, Grand Junction, Colorado.

Harris, D. V. and E. P. Kiver. 1985. Colorado National Monument. Pages 247 - 250 in The geologic 

story of the National Parks and Monuments 4th edition. John C. Wiley and Sons, New York, New 

York.
384

KellerLynn, K. 2006. Colorado National Monument geologic resource evaluation report. Natural 

Resource Report NPS/NRPC/GRD/NRR—2006/007. National Park Service, Denver, Colorado. 

Lohman, S. W. 1965. The geologic story of Colorado National Monument. Colorado and Black 

Canyon Natural History Association, Fruita, Colorado.

Lohman. S. W. 1981. The geologic story of Colorado National Monument, US Geological Bulletin 

1508. U.S. Geological Survey, Reston, Virginia.

National Climatic Data Center (NCDC). 2015a. Storm events database (Mesa County search). 

http://www.ncdc.noaa.gov/stormevents/ (accessed 4 September 2015).

National Climatic Data Center (NCDC). 2015b. Climate data online search: Daily precipitation, 

Colorado National Monument, 2013-2014. Downloaded from https://www.ncdc.noaa.gov/cdoweb/search (accessed 8 September 2015).

National Park Service (NPS). 2005. Final general management plan and environmental impact 

statement: Colorado National Monument. National Park Service, Fort Collins, Colorado. 

National Weather Service (NWS). 2007. National Weather Service instruction 10-1605: Storm data 

preparation. National Weather Service, Silver Spring, Maryland.

Pederson, J. L., R. D. Mackley, and J. L. Eddleman. 2002. Colorado Plateau uplift and erosion 

evaluated using GIS. GSA Today 12(8):4–10.

Richard, G. A. 2004. Flash flooding at the Colorado National Monument, 1921-2003. National Park 

Service, Fruita, Colorado.

Scott, R. B., A. E. Harding, W. C. Hood, R. D. Cole, R. F. Livaccari, J. B. Johnson, R. R. Shroba, 

and R. P. Dickerson. 2001. Geologic map of the Colorado National Monument and adjacent 

areas, Mesa County, Colorado, U.S. Geologic Investigations Series 2740. Geological Survey, 

Reston, Virginia.

Tweet, J. S., V. L. Santucci, T. Connors, and J. P. Kenworthy. 2012. Paleontological resource 

inventory and monitoring: Northern Colorado Plateau Network. Natural Resource Technical 

Report NPS/NCPN/NRTR—2012/585. National Park Service, Fort Collins, Colorado.

Wei, W., L. Chen, and B. Fu. 2009. Effects of rainfall change on water erosion processes in 

terrestrial ecosystems: A review. Progress in Physical Geography 33(3):307-318.
385

5. Discussion

Chapter 5 provides an opportunity to summarize assessment findings and discuss the overarching 

themes or common threads that have emerged for the featured components. The data gaps and needs 

identified for each component are summarized and the role these play in the designation of current 

condition is discussed. Also addressed is how condition analysis relates to the overall natural 

resource management issues of the park.

5.1 Component Data Gaps

The identification of key data and information gaps is an important objective of NRCAs. Data gaps 

or needs are those pieces of information that are currently unavailable, but are needed to help inform 

the status or overall condition of a key resource component in the park. Data gaps exist for most key 

resource components assessed in this NRCA. Table 98 provides a detailed list of the key data gaps by 

component. Each data gap or need is discussed in further detail in the individual component 

assessments (Chapter 4).

Table 98. Identified data gaps or needs for the featured components.

Component Data Gaps/Needs

Pinyon-juniper 

Woodlands/Savannas

 Further vegetation studies that provide information on the percent ground cover of 

cryptobiotic crusts and soils, percent bare ground, invasive species composition, 

and soil stability within this vegetation community are needed.

 Further research on the effects of climate change on the pinyon-juniper 

distribution

 Research on the overall effects of climate change on the non-native species 

composition within this habitat 

 Research on the impact of social trails within all habitat types

Sagebrush 

Shrublands/Shrub 

Steppe

 Further vegetation studies that provide information on the percent ground cover of 

cryptobiotic crusts and soils, percent bare ground, canopy gap size, invasive 

species composition, and soil stability within this vegetation community is needed.

 Research on the impact of social trails within all habitat types

Riparian 

Habitats/Large Dry 

Washes

 Research into amphibian populations within riparian communities.

 Additional research or modeling of flash floods and how they impact channel 

geomorphology.

 Research on the impact of social trails within all habitat types

Seeps and Springs and 

Tinaja Habitats

 Additional research on water quality parameters including discharge.

 Research and monitoring of riparian dependent species, including amphibians

 Research on the presence of invertebrates.

 Development of a monitoring program of these habitats.

 Complete mapping of all seeps, springs, and tinaja habitats within COLM.

 Further research on the effects of climate change on seeps and springs and their 

associated native and non-native plant species composition
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Table 98 (continued). Identified data gaps or needs for the featured components.

Component Data Gaps/Needs

Mixed Salt Desert 

Scrub/Semi-desert 

Grassland

 Further vegetation studies that provide information on the percent ground cover of 

cryptobiotic crusts and soils, percent bare ground, invasive species composition, 

and soil stability within this vegetation community are needed.

 Research on the impact of social trails within all habitat types

Canyon Walls and 

Monolith Vegetation 

Communities

 No historic or current data adequate or detailed enough to assess the current 

extent or composition of these habitats.

 Safety is a concern when conducting vegetation studies on these habitats; 

discovery of a more accurate and safe method of studying hanging gardens in the 

future would aid resource managers in documenting the community composition 

and extent of this habitat.

Montane Shrubland  Further vegetation studies that provide information on the percent ground cover of 

cryptobiotic crusts and soils, percent bare ground, invasive species composition, 

and soil stability within this vegetation community are needed.

 Research on the impact of social trails within all habitat types

Herptiles  Additional studies and monitoring of herptiles is needed to better understand this 

resource. This assessment was only able to identify one study of this resource, 

which was conducted in 2002.

Birds  Continuation of the RMBO’s annual landbird monitoring in the park will provide 

resource managers with a valuable long-term data set that will accurately depict 

trends in abundance, density, and richness in the P-J habitat of COLM, however 

the design of this study is done to make inference to the entire NCPN set of parks, 

so if park specific trend information is desired, more monitoring would need to be 

added.

 Expansion of the survey methodology to include a variety of vegetation 

communities and habitat types would provide a more complete picture of the 

avifauna of the park as a whole.

 Addition of bird surveys during the winter would provide resource managers with a 

better understanding of the trends and status of year-round bird species in the 

park.

Raptors  Annual studies specifically for raptors are needed in order to assess this 

component. Bird studies have taken place in the park and have documented 

raptor presence. However, these studies have not focused on raptors specifically, 

and monitoring methodology (and timing) may have certain biases that make 

detecting raptors more difficult. The only raptor specific studies were peregrine 

falcon nest monitoring conducted in 1994 and 1995 (Lambeth 1996).

 A monitoring program dedicated to the park’s raptor population, and that samples 

during the breeding season, would allow for a more complete assessment of 

condition for this resource.

Small Mammals  Development and implementation of a routine small mammal survey that could 

document species richness, abundance, and distribution would provide managers 

with meaningful information that can be used to assess the condition of small 

mammals in the future.

 Survey to determine if the North American porcupine has been extirpated from 

COLM.
387

Table 98 (continued). Identified data gaps or needs for the featured components.

Component Data Gaps/Needs

Mountain Lion  Regular surveys or monitoring of mountain lions in COLM and the surrounding 

area would allow for more adequate assessment of this resource.

 Studies on mountain lion movements in and around COLM would help resource 

managers better understand the status of the park’s mountain lion population and 

potentially reduce the occurrence of mountain lion/human conflicts.

Bighorn Sheep  Availability of genetic history or birth and death rates. Projects that included blood 

sampling would be useful in determining the genetic lineage of the herds within 

COLM.

 GPS-collaring and monitoring of sheep within the Black Ridge Unit by the CPW is 

expected to take place in 2015-2016. This data will provide information on 

lamb:ewe ratios, mortality causes, and range use. 

Kit Fox  Historical data show the distribution of kit fox within the COLM vicinity. It is 

currently thought to be extirpated from Colorado. 

Bats  A bat survey was recently completed for COLM, but was not published in time to 

be included in this assessment. The results of this survey should give resource 

managers a better understanding of the current bat populations at COLM

 Continued monitoring of the bat population at COLM would give resource 

managers a better understanding of this resource.

Air Quality  No active air quality monitors within the distance (16 km [10 mi]) necessary to 

accurately represent conditions in the park.

 Periodic or consistent monitoring of atmospheric deposition, ozone, particulate 

matter, and visibility would help managers better understand the local air quality 

conditions in and around COLM and how they may affect other park resources.

Dark Night Skies  Continued monitoring by the NPS NSNSD would provide additional data that 

could be compared to the 2014 results in order to determine the changes and 

trends in the dark night skies at COLM.

Viewscape  Continued development of spatial data that explain landscape change as it relates 

to viewscape analysis is recommended. Additional attributes such as height above 

surface for would improve the results of this line of sight analysis.

 Continued on-the-ground photography from observation points.

Soundscape and 

Acoustic Environment

 Regular measurements (annual or biennial) of sound levels and sound recordings.

 Additional focus on the frequency and duration of non-contributing sounds or the 

percent of time they are audible.

 Create a soundscape management plan or integrate soundscape into other 

planning documents.

Paleontological 

Resources

 Continued research of the paleontological resources at COLM is recommended.

 A systematic park-wide inventory of paleontological resources would provide a 

baseline for future studies, but would also undoubtedly lead to new discoveries.

 Development and implementation of an ongoing monitoring program.
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Table 98 (continued). Identified data gaps or needs for the featured components.

Component Data Gaps/Needs

Geologic Features and 

Processes

 Studies of erosion rates in the park are needed.

 An inventory of areas with high potential for slope failure is recommended. This, 

coupled with consistent record-keeping of slope failure, would allow an accurate 

determination of the frequency of their occurrence.

 Additional research on how the surface conditions affect the ability to absorb or 

mitigate run-off from extreme precipitation events

 Continuation of ongoing collection of weather event data.

 Additional studies (or modeling) of flash flooding and its effects within COLM.

The majority of the park’s vegetation communities would benefit from research on habitat elements 

such as the invasive species occurrences, percent cover of cryptobiotic crusts and soils and other 

measures related to percent ground cover, for specific vegetation communities. Other outstanding 

data needs involve continuing monitoring programs to accumulate enough data for identifying any 

trends over time (e.g., air quality, dark night skies, and paleontological resources). Other 

components, such as birds, would benefit from sampling efforts specifically focused on the spatial 

extent of the park.

5.2 Component Condition Designations

Table 99 displays the conditions assigned to each resource component presented in Chapter 4 

(definitions of condition graphics are located in Table 100 following Table 99). It is important to 

remember that the graphics represented are simple symbols for the overall condition and trend 

assigned to each component. Because the assigned condition of a component (as represented by the 

symbols in Table 99) is based on a number of factors and an assessment of multiple literature and 

data sources, it is strongly recommended that the reader refer back to each specific component 

assessment in Chapter 4 for a detailed explanation and justification of the assigned condition. 

Condition designations for some components are supported by existing datasets and monitoring 

information and/or the expertise of NPS staff, while other components lack historic data, a clear 

understanding of reference conditions (i.e., what is considered desirable or natural), or even current 

information. Condition could not be determined for 10 of the 21 selected components: sagebrush 

shrublands/shrub steppe, mixed salt desert scrub/semi-desert grasslands, canyon walls and monolith 

vegetation communities, montane shrubland, herptiles, raptors, small mammals, mountain lion, bats, 

and geologic features and processes. 

For featured components with available data and/or fewer information gaps, assigned conditions 

varied. Only two components were considered to be in good condition (riparian habitats/large dry 

washes and bighorn sheep). Five components (pinyon-juniper woodlands/savannas, seep and springs 

and tinaja habitats, birds, soundscape, and paleontological resources) were of moderate concern. Four 

components were of high concern: kit fox, dark night skies, air quality, and viewscape. The high 

concern for kit fox was due to it being extirpated from the region, and for the other three

components, the concern was primarily due to the urban land uses surrounding the park and are 

largely beyond NPS control.
389

Table 99. Summary of current condition and condition trend for featured NRCA components.

Component WCS Condition

Biotic Composition

Ecological Communities

Pinyon-juniper Woodlands/Savannas 0.56

Sagebrush Shrublands/Shrub Steppe N/A

Riparian Habitats/Large Dry Washes 0.33

Seeps and Springs and Tinaja Habitats 0.58

Mixed Salt Desert Scrub/Semi-desert Grassland N/A

Canyon Walls and Monolith Vegetation 

Communities N/A

Montane Shrubland N/A

Herptiles

Herptiles N/A

Birds

Birds 0.50

Raptors N/A
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Table 99 (continued). Summary of current condition and condition trend for featured NRCA components.

Component WCS Condition

Biotic Composition

Mammals

Small Mammals N/A

Mountain Lion N/A

Bighorn Sheep 0.20

Kit Fox 0.83

Bats N/A

Environmental Quality

Air Quality 0.67

Dark Night Skies 0.67

Viewscape 0.67

Soundscape and Acoustic Environment 0.50

Paleontological Resources 0.59

Geologic Features and Processes N/A
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Table 100. Description of symbology used for individual component assessments.

Condition Status Trend in Condition Confidence in 

Assessment

Resource is in Good 

Condition Condition is Improving High

Warrants

Moderate Concern Condition is Unchanging Medium

Warrants

Significant Concern Condition is Deteriorating Low

Examples of how the symbols should be interpreted:

Resource is in good condition, its condition is improving, high confidence in 

the assessment.

Condition of resource warrants moderate concern; condition is unchanging; 

medium confidence in the assessment.

Condition of resource warrants significant concern; trend in condition is 

unknown or not applicable; low confidence in the assessment.

Current condition is unknown or indeterminate due to inadequate data, lack of 

reference value(s) for comparative purposes, and/or insufficient expert knowledge 

to reach a more specific condition determination; trend in condition is unknown or 

not applicable; low confidence in the assessment. 

5.3 Park-wide Condition Observations 

Vegetation Communities

COLM is located in a region that exhibits several ecoregionally distinct communities, three of which 

are found within COLM (old growth pinyon-juniper woodlands, hanging gardens, and tinajas). Other 

vegetation communities typical to semi-desert upland climates, such as sagebrush and mixed salt 

desert grasslands are also present within the park. Additionally, riparian communities have 

established in areas where seeps, springs, and intermittent flows during rain events provide the soil 

moisture necessary for these habitats. Given a lack of data for several key measures, a condition 

assessment could not be completed for the majority of the vegetation communities. Data were
392

available to assess the condition of the pinyon-juniper woodlands, riparian habitats/large dry washes, 

and the seeps and springs and tinaja habitats. Of these three, the riparian habitats were considered to 

be in good condition, while the other two were determined to be of moderate concern. A trend could 

not be determined for any of these three communities.

Other Biotics

Other biotic components included in the NRCA were herptiles, birds, raptors, small mammals, 

mountain lion, bighorn sheep, kit fox, and bats. Given the lack of data for the measures, a condition 

assessment could only be completed for bighorn sheep, birds, and kit fox. Bighorn sheep were 

considered to be in good condition with a stable trend. Birds were considered to be of moderate 

concern with a stable trend. Kit fox was determined to be of significant concern due to its likely 

extirpation from the region.

Environmental Quality

Environmental quality is important in maintaining healthy functioning ecosystems. The health of 

terrestrial and aquatic organisms in parks can be affected substantially by the condition of air quality. 

Air quality was determined to be of significant concern for COLM, although the Weighted Condition 

Score is near the threshold for moderate concern. Monitoring data from inside park boundaries was 

not available for most of the air quality parameters, so data from representative regional monitoring 

sites was used to interpret the air quality conditions at COLM. Air quality data collected at COLM 

would need to be collected to confirm that the interpolated and estimated data used in this NRCA 

accurately reflect conditions in the park. The park’s dark night skies and viewscape are also of high 

concern. Similar to air quality, the Weighted Condition Scores for these two resources were also just 

above the upper threshold for assigning moderate concern. The soundscape and acoustic environment 

was determined to be of moderate concern. All four of these components are being negatively 

impacted due to the urban growth and oil and gas development around the park.

A trend was not assigned to the air quality component, due to the lack of consistent data from within 

or near the park itself. Since urbanization is most likely to continue in areas surrounding the park, a 

negative trend was assigned to the dark night skies, viewscape, and soundscape and acoustic 

environment components.

Physical Characteristics

COLM is widely known for the geologic features that define its landscape. The park also hosts a 

diverse paleontological record contained within rocks that date back to as early as the Precambrian. 

Due to data gaps for the majority of the measures identified to assess the geologic features, a 

condition assessment could not be made. The paleontological resources were determined to be of 

moderate concern. Given the lack of a park-wide baseline inventory, a trend assessment was not 

determined.

Park-wide Threats and Stressors

Several threats and stressors influence the condition of multiple resources within COLM. These 

include invasive plant species, climate change, and the impacts associated with visitor use. Exotic 

plant species are a threat to all of the park’s vegetation communities, as they can out-compete native 
393

plants and alter ecological processes such as fire regime and nutrient cycling (Scott and Wilcove 

1998, Perkins 2014).

Other programmatic issues are contributing to degradation of multiple habitats within the park. The 

invasive species removal/control program has resulted in a significant reduction in the number and 

areal extent of IEP infestations within the park. Currently, there is no guaranteed funding to continue 

this program beyond the 2015 field season. Loss of this program, for even one field season, has the 

potential to erase all the gains that have been made in eradicating IEP’s from the park (Hartwig, 

written communication, 30 January 2016). Another programmatic issue facing the park is the lack of 

a trail management plan. This has resulted in the proliferation of social trails through the park, 

including through sensitive areas such as seeps and springs habitat and BSC habitat.

Climate Change Vulnerability Assessment

The objectives of the climate change pilot were threefold: 1) assess the vulnerability of key 

resources; 2) to provide an understanding of why these resources are vulnerable, including providing 

insights on the interactions of climate changes with existing threats and stressors to resources; and 3) 

to serve as a pilot project for integrating climate change vulnerability assessments (in particular a 

landscape scale community-based assessment) into the existing NRCA process and report template.

Using a framework for vulnerability assessment initially developed by Galbraith (2011) and modified 

by Amberg et al. (2012), the climate change assessment methodology employed is a multi-scale 

analysis that focuses on the vulnerability of select ecological communities in COLM (defined by 

vegetation types). A focus on the overall vulnerability of ecological communities in the park provides 

an umbrella under which vulnerability may be examined and inferred for key species inhabiting those 

communities; the degree of vulnerability for a plant community would presumably directly influence 

the sensitivity and vulnerability of individual animal species residing in that community. For 

instance, if a specific plant community is expected to change very little despite projected climate 

shifts (i.e., low vulnerability), it is probable that many of the animal species that rely on the 

community would also be less vulnerable to many of the potential stresses of climate change. 

Likewise, if a plant community is expected to experience dramatic changes in composition or 

distribution, it is highly probable that species dependent upon that community for habitat would also 

be greatly affected.

This assessment presents a summary of projected climate changes for the COLM region and analysis 

of the vulnerability of select park natural resources to these changes. As the methodology employed 

in this pilot was to be a landscape scale community-based assessment, two vegetation communities 

from the COLM NRCA framework were selected for inclusion in this pilot study. By selecting 

communities from this framework, the climate change integration pilot study would be a park-centric 

approach and it could build on the established NRCA process. Several considerations were taken into 

account during the discussions on selecting the components for inclusion in the pilot study. A 

specific set of selection criteria was not established, however COLM resource managers were asked 

to consider their long-term management as part of the selection process. With guidance from 

SMUMN GSS and the NPS climate change integration team, COLM resource managers selected 
394

pinyon-juniper woodlands/savanna, an iconic and important park plant community, and seeps, 

springs, and tinaja habitats, which depend upon unique physical resources, as the two communities to 

include in the pilot study. Each assessment considers the exposure of the resource to projected

climate changes, the degree of sensitivity to such changes, and the ability to cope with and adapt to 

these changes.

Historical conditions

Analysis of historical (1895-2010) PRISM data indicates a warming trend for both maximum and 

minimum average annual temperatures in the COLM region. Maximum average annual temperatures 

have increased 0.8 °C (1.4 °F) and minimum average annual temperature increased 0.7 °C (1.3 °F) 

over the past century. Annual precipitation exhibited a -2.4% per century decline, though it was 

determined to not be statistically significant.

Projected future conditions 

Average annual temperatures in the COLM region are projected to increase by 1.6 °C (2.9 °F) by 

2030 and by 5.7 °C (10.2 °F) by the end of the century under RCP 8.5 (NCCSC 2015). By 2100, it is 

estimated that average summer and fall temperatures will increase more than average winter and 

spring temperatures (Garfin et al. 2014). In general, precipitation is projected to increase by the end 

of the century, but there is considerable variation in projections and confidence in precipitation 

projections is much lower than for temperature projections (Garfin et al. 2014). Overall, even with an 

increase in precipitation, the projected climate by 2050–2100 at COLM is estimated to become much 

drier, as higher temperatures will drive increased evapotranspiration rates. The projected increase in 

evapotranspiration is estimated to exceed (substantially) the projected increase in precipitation, 

which would result in significantly reduced soil moisture. General predictions for the region for 

2050–2100 also suggest an increase in extreme temperature (number of excessively hot days) and 

weather events (increase in strong convective storms).

Vegetation community assessment

Two of the seven ecological communities identified in the NRCA framework were assessed for 

vulnerability to climate change (pinyon-juniper woodlands/savannas and the seeps and springs and 

tinaja habitats). Vulnerability was determined by examining six variables: current location of the 

plant community in its known geographical range, sensitivity to extreme climatic events, dependence 

on specific hydrologic conditions, intrinsic adaptive capacity, vulnerability of ecologically influential 

species in the community, and potential for climate change to exacerbate the influence of non-climate 

stressors. The plant communities range in vulnerability to climate change from least vulnerable to 

highly vulnerable. Table 101 summarizes the vulnerability of the plant communities examined and 

the confidence in these vulnerability scores based on current available science.
395

Table 101. Summary of plant community vulnerability to projected climate change (2050–2100) at COLM.

Community

Climate Change 

Vulnerability* Confidence+

Alternative Vulnerability 

Scores

Pinyon-juniper 

woodland/savannas

Moderate (17) Moderate (15) 16-19

Seeps, springs, and 

tinaja habitats

High (24) High (18) 22-26

*6-13= least vulnerable, 14-19 = moderately vulnerable, 20-25 = highly vulnerable, 26-30 = critically 

vulnerable

+6-10 = low confidence, 11-14 = moderate confidence, 15-18 = high confidence.

Seeps, springs, and tinaja habitats at COLM were determined to be highly vulnerable to climate 

change. The projected warmer, drier climate conditions and increased variability in precipitation for 

the region will likely impact the amount of available surface and ground water that supply these 

habitats. This in turn will have a detrimental impact on the vegetation communities that rely on the 

moist soil conditions these areas provide. More research is needed to understand the dynamics of 

these features with regard to available water to better determine overall vulnerability to climate 

change. The pinyon-juniper woodlands were determined to be moderately vulnerable to climate 

change. These woodlands are tolerant to the warmer, more arid climate currently being projected by 

the climate models. Both pinyon pine and Utah juniper have large ecological amplitudes, and are 

suited to the warmer, more arid conditions projected by the climate models.

Uncertainty in assessing vulnerability. Uncertainty is inherent at every stage of this type of 

assessment. The future scenarios for climate do not cover the entire range of plausible future 

conditions and, thus, do not capture the full range of potential resource vulnerability. Uncertainty is 

also present in the analysis of vulnerability conducted by SMUMN GSS, resulting from a lack of 

definitive literature and scientific knowledge that characterizes the relationship of many natural 

resources to climate shifts and/or non-climate stressors and how these resources will respond to 

climate change. While it is possible to reduce some uncertainties by building better models or by 

gathering additional data, many are unavoidable and irreducible, and managers must make decisions 

in the face of uncertainty.

Overall Conclusions

COLM is an extremely diverse park, supporting a range of unique features, sheer-walled canyons, 

towering monoliths, and colorful formations (NPS 2015). It is also home to a representative example 

of an intact high desert ecosystem (NPS 2015). This assessment serves as a review and summary of 

available data and literature for featured natural resources in the park. The information presented here 

may serve as a baseline against which any changes in condition of components in the future may be 

compared. Current condition could not be determined for many components due to data gaps. For 

resources where condition could be assessed, the majority were in moderate condition or of 

significant concern. Where they could be determined, trends were relatively stable, with dark night 

skies, viewscape, and soundscape and acoustic environments showing a declining trend.
396

Understanding the condition of these resources can help managers prioritize management objectives 

and better focus conservation strategies to maintain the health and integrity of these ecosystems. The 

changing climate will have impacts on all of these resources to some degree. Traditionally, 

conservation strategies have been developed before climate change became a major consideration for 

natural resource managers. However, recent science has increased our awareness of the ecological 

consequences of climate change, and managers now are tasked with adapting and refining 

conservation approaches that work to best protect natural resources from the influences of changing 

climate. Essential to the adaptation effort is identifying and, when possible, quantifying the 

comparative vulnerabilities of important ecological resources, such as through a vulnerability 

assessment. This provides natural resource managers with greater understanding of which climate 

influences or resources require the most immediate attention.

This report incorporates a community-based process for a qualitative assessment of climate change 

vulnerability for select natural resources in COLM. These resources are characterized using the 

projected regional downscaled climate changes and the best estimates of resource vulnerabilities 

based on available literature and professional judgment. The project team believes the statistical 

downscaling approach to developing regional climate change projections is both appropriate and 

applicable for vulnerability assessment and the results of the assessment provides resource managers 

with a credible way of estimating resource vulnerabilities in COLM.

The results of the climate change assessment show that the ecological resources in COLM can 

exhibit a wide range of climate change vulnerabilities and, consequently, it is likely that managers 

can expect to see substantial changes in the distribution of many of these resources in the next several 

decades. This type of assessment is a very important first step in understanding how park resources 

may change with ongoing and future climate change. It will also provide managers a starting point 

from which to begin identifying the resources that may not cope well with climate change and those 

that may be resilient to projected changes.

5.4 Literature Cited

Amberg, S., K. Kilkus, S. Gardner, J. E. Gross, M. Wood, and B. Drazkowski. 2012. Badlands 

National Park: Climate change vulnerability assessment. Natural Resource Report 

NPS/BADL/NRR—2012/505. National Park Service, Fort Collins, Colorado.

Galbraith, H. 2011. The NEAFWA regional habitat vulnerability model – A “user’s manual”. 

Unpublished report to Northeastern Association of Fish and Wildlife Agencies. Available from 

H. Galbraith, hg2@myfairpoint.net.

Garfin, G., G. Franco, H. Blanco, A. Comrie, P. Gonzalez, T. Piechota, R. Smyth, and R. Waskom. 

2014. Southwest. Pages 462-486 in Climate change impacts in the United States: The Third 

National Climate Assessment, J. M. Melillo, Terese (T.C.) Richmond, and G. W. Yohe, Eds., 

U.S. Global Change Research Program. 

http://nca2014.globalchange.gov/report/regions/southwest%0D (accessed 25 September 2015).
397

Lambeth, R. 1996. Peregrine falcon monitoring: Grand Junction BLM district. Unpublished report, 

U.S. Bureau of Land Management, Grand Junction, Colorado.

National Park Service (NPS). 2015. Foundation document: Colorado National Monument, Colorado. 

National Park Service, Fort Collins, Colorado.

North Central Climate Science Center (NCCSC). 2015. Data analysis and graphics for PRISM and 

downscaled netCDF data. Colorado State University, Fort Collins, Colorado.

Perkins, D. 2014. Invasive exotic plant monitoring in Colorado National Monument: 2013 field 

season. Natural Resource Technical Report NPS/NCPN/NRTR—2014/859. National Park 

Service, Fort Collins, Colorado.

Scott, J., and D. Wilcove. 1998. Improving the future for endangered species. BioScience 48(8):579-

580.

399

Appendices

Appendix A. Overview of climate change vulnerability assessments

Climate change has been linked in large part to the long-term and accelerating release of carbon into 

the atmosphere. The Special Report on Emissions Scenarios (SRES) A1B and A2 family of carbon 

emissions scenarios are often used to estimate potential future changes in climate; these scenarios are 

commonly referred to as ‘moderate’ and ‘high’ carbon emissions scenarios (Nakicenovic et al. 2000). 

The difference between these two scenarios can be summarized by differences in the projected 

emissions of CO2, the atmospheric component that is primarily responsible for global warming 

(IPCC 2007). These A1B and A2 emission scenarios have very similar rates of atmospheric CO2

increases until about 2050, when the A2 (high) scenario diverges with higher projected emissions of 

greenhouse gases than the A1B (moderate) scenarios. Since these emissions scenarios were published 

(Nakicenovic et al. 2000), the rate of increase in atmospheric CO2 has equaled or exceeded the 

highest projected emissions scenarios examined by the IPCC (Rahmstorf et al. 2007).

Moss et al. (2010) identified the need for new scenarios for the research community. This was due to 

several factors; the current generation of climate models need more detailed information than what 

was provided by previous emission scenarios, an increase in interest for scenarios that incorporate the 

impacts of different climate policies in addition to the no-climate-policy scenarios explored 

previously (e.g., SRES), and increasing interest in exploring the role of adaptation (van Vuuren 

2011). Rather than incorporating this into their process, the IPPC asked the research community to 

develop a new set of scenarios (IPCC 2007, van Vuuren 2011). This development process was 

guided by a set of design criteria (Moss et al. 2008, 2010). In order to evaluate how climate might 

change in the future, the IPCC requested the research community develop a set of scenarios based on 

the following criteria: provide the current generation of climate models with more detailed 

information than what was provided by previous emission scenarios, address an increased interest for 

scenarios that incorporate the impacts of different climate policies in addition to the no-climatepolicy scenarios explored in earlier scenarios, and increase interest in exploring the role of adaptation 

(Moss et al. 2008, 2010, van Vuuren 2011). The research community developed a new set of 

scenarios, each referred to as a RCP. The term “representative” signifies that each of the RCPs is 

representative of a larger set of scenarios already defined in the literature (van Vuuren 2011).

As a whole, the RCP’s are meant to be compatible with the full range of emissions scenarios 

available in the current scientific literature both with and without climate policy (van Vuuren 2011). 

The term “concentration pathway” emphasizes that these RCP’s are not final new, fully integrated 

scenarios, but rather an internally consistent set of projections of the components of radiative forcing 

(the change in energy in the atmosphere due to GHG emissions) that are to be used in subsequent 

phases of new or updated scenarios (van Vuuren 2011). The use of “concentration” instead of 

“emissions” also emphasizes that concentrations are used as the primary product of the RCP’s, and 

they are designed as input to climate models (van Vuuren 2011). Coupled carbon-cycle climate 

models can then calculate associated emission levels (van Vuuren 2011). A set of four pathways 

were produced that lead to radiative forcing levels of 8.5, 6, 4.5 and 2.6 W/m2, by 2100 (van Vuuren 
400

2011). Each of the RCPs covers the 1850–2100 period, and extensions have also been formulated for 

modeling climate change up to the year 2300 (van Vuuren 2011). Since they were developed with the 

current emission levels in mind, they can be related to the emission scenarios produced by the IPCC. 

They represent different possible futures determined in complex ways by demographic development, 

socio-economic development, and technological change (Nakicenovic et al. 2000, van Vuuren 2011). 

For the purposes of this report, the main differences in the RCP’s can be summarized by differences 

in greenhouse gas emissions (Figure 88).

Figure 88. Emission levels of main greenhouse gases by RCPs. The grey areas indicate the 98th and 90th

percentiles (light/dark grey) of the literature. The dotted lines indicate four of the SRES marker scenarios

(from van Vuuren 2011).

Climate change can impair the natural and cultural resources that the NPS was established to 

preserve. Jonathon Jarvis, director of the NPS, has referred to climate change as the greatest 

challenge to maintaining “America’s natural and cultural heritage unimpaired for future generations” 

(Jarvis 2009, p. 2). The NPS recognizes the importance of understanding the impacts and influences 

of climate change on national park resources and developing adaptation strategies to best conserve 

species and ecosystems in light of rapidly shifting climate. A recent initiative in the NPS CCRP 

focuses on building a greater understanding of the effects and influences that projected climate shifts 

may have on natural and cultural resources across the National Park System. This initiative 

encourages the use of CCVAs as part of a strategy to determine and better understand natural and 

cultural resource vulnerability to climate change and the synergistic relationships these changes may 

have with existing threats and stressors to those resources.

A CCVA is an assessment of the likelihood and extent to which projected climatic shifts (including 

such variables as precipitation and temperature) will have adverse or beneficial influences on a given 

natural or cultural resource (e.g., species, plant community, or ecosystem; sacred sites, archeological 

artifacts) (IPCC 2007, Stein and Glick 2011). As a result, CCVAs are increasingly viewed as a key 

tool for providing resource managers with information that can be used to aid adaptation planning 

efforts for vulnerable natural and cultural resources. Specifically, a CCVA makes three main 

contributions to resource management. First, a vulnerability assessment helps identify which

resources are most or least vulnerable to estimated climate changes, a determination that better 
401

enables managers to prioritize resources for enhanced conservation (Stein and Glick 2011). Second, a 

CCVA can uncover why resources are vulnerable or resilient (Stein and Glick 2011). The assessment 

process helps to determine the characteristics of a resource that make it more vulnerable to or better 

able to cope with climatic shifts and the associated environmental changes; this information can 

better equip resource managers with the understanding necessary to develop the most appropriate and 

practical management responses to climatic shifts in their region. Finally, a CCVA can help elucidate 

gaps in knowledge that exist for certain cultural and natural resources in general, so that these gaps 

can be filled and the vulnerability of these resources more accurately assessed.

Assessing the vulnerability of natural systems to climate change is a relatively new science and 

where completed, they have exhibited a wide range of project approaches, primarily in regard to the 

scale at which analysis occurs. Some projects have focused on the vulnerability of certain 

ecologically influential species in a natural system, particularly those listed as threatened or 

endangered (Galbraith and Price 2011). Others have focused on the vulnerability of specifically 

defined ecosystems within a region (e.g., vulnerability of Massachusetts fish and wildlife habitats 

[Galbraith and O’Leary 2011]; species vulnerability assessment for the Middle Rio Grande, New 

Mexico [Finch et al. 2011]) and, based on the vulnerability of the ecosystem as a whole, make 

inferences about the subsequent effect on the species that primarily use those ecosystems.

The NPS is considering several strategies to integrate climate change resource vulnerability into the 

park NRCAs. In March 2014, NPS partnered with CSU and SMUMN GSS to implement a pilot 

project to assess the feasibility of slightly modifying existing NRCA project scopes to accommodate 

an assessment of resource vulnerability to climate change. The pilot project’s goal is to seek creative 

approaches to considering climate change vulnerabilities in the context of the park’s NRCA project.

As part of this effort, SMUMN GSS employed a landscape scale community-based assessment for 

select resource components of the COLM NRCA. The type of assessment focuses on ecological 

communities. This type of evaluation casts a broader net in the examination of resources, rather than 

looking at a list of individual species. By focusing on the community scale it is possible to infer that 

the degree of vulnerability for a community would directly influence the sensitivity and vulnerability 

of key species residing in that community. For example, if a community has low vulnerability to 

climate change and is expected to change very little despite projected climate shifts, it is likely that 

the diversity of key species residing in that community would also not experience much change or 

stress due to climate change. Likewise, if a community is estimated to be highly vulnerable to 

climate change and is expected to experience dramatic changes in composition or distribution, it is 

likely that the key species dependent upon that community for habitat would also be affected. Thus, a 

focus on the vulnerability of ecological communities within a landscape (i.e., the ecosystem or 

community scale) can provide a larger umbrella under which vulnerability may be examined and 

inferred for species inhabiting those communities. These are also typically priority resources that 

park managers express concern over when looking at ongoing park threats and long-term park 

resource sustainability.
402

SMUMN GSS worked collaboratively with 

COLM resource staff and the NPS climate 

change integration pilot team to incorporate 

climate change analysis into the NRCA. After 

evaluating the ecological communities 

represented in the COLM NRCA framework 

(Chapter 3, Figure 13), the pinyon-juniper 

woodlands/savannas and seep, spring and tinaja 

habitats were selected to be evaluated in terms 

of their vulnerability to climate change. For the 

purpose of this analysis, vulnerability is defined 

as “the extent to which a species, habitat, or 

ecosystem is susceptible to harm from climate 

change impacts” (Schneider et al. 2007, as cited 

by Stein and Glick 2011, p. 9). Vulnerability 

consists of three key components: 1) sensitivity

of a system to climate changes; 2) exposure of a 

system to climate changes; and 3) adaptive capacity to respond to those changes (IPCC 2007, as 

cited by Stein et al. 2011). Sensitivity is a measure of the degree to which a system is affected, either 

adversely or beneficially, by a given change in climate. Exposure is a measure of the amount of 

climatic and environmental change that a species or system is likely to experience. Adaptive capacity 

is the ability of a species or system to accommodate or cope with climatic and environmental change 

impacts with minimal disruption. Figure 89 illustrates the theoretical relationship among the three 

components and how they interact to determine overall vulnerability.

Literature Cited

Finch, D., M. Friggens, and K. Bagne. 2011. Case study 3: Species vulnerability assessment for the 

middle Rio Grande River, New Mexico. Pages 96-103 in Scanning the conservation horizon: A 

guide to climate change vulnerability assessment. Glick, P., B. A. Stein, and N. A. Edelson 

(eds.). National Wildlife Federation, Washington, D.C.

Galbraith, H., and J. O’Leary. 2011. Case study 4: Vulnerability of Massachusetts fish and wildlife 

habitats to climate change. Pages 103-113 in Scanning the conservation horizon: A guide to 

climate change vulnerability assessment. Glick, P., B. A. Stein, and N. A. Edelson (eds.). 

National Wildlife Federation, Washington, D.C.

Galbraith, H., and J. Price. 2011. Case study 2: U.S. Environmental Protection Agency’s threatened 

and endangered species vulnerability framework. Pages 90-95 in Scanning the conservation 

horizon: A guide to climate change vulnerability assessment. Glick, P., B. A. Stein, and N. A. 

Edelson (eds.). National Wildlife Federation, Washington, D.C.

Intergovernmental Panel on Climate Change (IPCC). 2007. Report of the 26th session of the IPCC. 

Bangkok. April 30–May 4 2007. Intergovernmental Panel on Climate Change, Geneva, 

Switzerland.

Figure 89. Key components of vulnerability, 

illustrating the relationship between exposure, 

sensitivity, and adaptive capacity (Source: Stein et 

al. 2011).
403

Jarvis, J. 2009. Statement of Jonathan B. Jarvis, Director, National Park Service, U.S. Department of 

the Interior, before the senate committee on energy and natural resources subcommittee on 

national parks, on climate change in national parks.

Moss, R. H., and S. H. Schneider. 2000. Towards consistent assessment and reporting of 

uncertainties in the IPCC TAR. in Cross-cutting issues in the IPCC third assessment report. R. 

Pachauri and T. Taniguchi (eds.). Global Industrial and Social Progress Research Institute (for 

IPCC), Tokyo, Japan.

Moss, R., M. Babiker, S. Brinkman, E. Calvo, T. Carter, J. Edmonds, I. Elgizouli, S. Emori, L. Erda, 

and K. Hibbard. 2008. Towards new scenarios for analysis of emissions, climate change, impacts, 

and response strategies. IPCC Expert Meeting Report on New Scenarios. Intergovernmental 

Panel on Climate Change, Noordwijkerhout, Netherlands.

Moss, R., J. Edmonds, K. Hibbard, M. Manning, S. Rose, D. van Vuuren, T. Carter, S. Emori, M. 

Kainuma, and T. Kram. 2010. The next generation of scenarios for climate change research and 

assessment. Nature 463:747-756.

Nakicenovic, N., J. Alcamo, G. Davis, B. de Vries, J. Fenhann, S. Gaffin, K. Gregory, A. Grübler, T. 

Jung, T. Kram and others. 2000. Special report on emissions scenarios: A special report of 

Working Group III of the Intergovernmental Panel on Climate Change. N. Nakicenovic and R. 

Swart (eds.). Cambridge University Press, Cambridge, United Kingdom.

Rahmstorf, S., A. Cazenave, J. A. Church, J. E. Hansen, R. F. Keeling, D. E. Parker, and R. C. 

Somerville. 2007. Recent climate observations compared to projections. Science 316:709.

Schneider, S.H., S. Semenov, A. Patwardhan, I. Burton, C.H.D. Magadza, M. Oppenheimer, A.B. 

Pittock, A. Rahman, J.B. Smith, A. Suarez, and F. Yamin. 2007. Assessing key vulnerabilities 

and the risk from climate change. Pages 779-810 in M.L. Parry, O.F. Canziani, J.P. Palutikof, 

P.J. van der Linden, and C.E. Hanson (eds.) Climate change 2007: Impacts, adaptation and 

vulnerability. Contribution of Working Group II to the fourth assessment report of the 

Intergovernmental Panel on Climate Change. Intergovernmental Panel on Climate Change, 

Geneva, Switzerland.

Stein, B., and P. Glick. 2011. Introduction. Pages 6-18 in Scanning the conservation horizon: A guide 

to climate change vulnerability assessment. Glick, P., B. A. Stein, and N. A. Edelson, editors. 

National Wildlife Federation, Washington, D.C.

Stein, B., P. Glick, and J. Hoffman. 2011. Vulnerability assessment basics. Pages 19-38 in Scanning 

the conservation horizon: A guide to climate change vulnerability assessment. Glick, P., B. A. 

Stein, and N. A. Edelson, editors. National Wildlife Federation, Washington, D.C.

van Vuuren, D., J. Edmonds, M. Kainuma, K. Riahi, A. Thomson, K. Hibbard, G. Hurtt, T. Kram, V. 

Krey and others. 2011. The representative concentration pathways: An overview. Climate 

Change 109(1):5-31.

405

Appendix B. Pinyon-juniper woodland/savanna community composition by association/alliances and growth habitat 

based on vegetation mapping project classification descriptions (Von Loh et al. 2007).

Key to coded columns- A: Two-needle pinyon-(one-seed juniper, Utah juniper) / needle-and-thread woodland, B: Two-needle pinyon-Utah 

juniper/Utah serviceberry woodland, C: Two-needle pinyon-Utah juniper/Bigelow’s sagebrush woodland, D: Two-needle pinyon-Utah 

juniper/black sagebrush woodland, E: Two-needle pinyon-Utah juniper/littleleaf mountain-mahogany woodland, F: Two-needle pinyonUtah juniper/mixed shrubs talus woodland, G: Two-needle pinyon-Utah juniper/grassy rock-goldenrod woodland, H: Two-needle pinyonUtah juniper/sparse understory woodland, I: Two-needle pinyon-Utah juniper/Wyoming big sagebrush woodlands, J: Two-needle pinyonjuniper species/mountain-mahogany-mixed shrub woodland, K: Two-needle pinyon-juniper species/saline wildrye grass woodland, and L: 

Blue spruce-two-needle pinyon-Utah juniper/Gambel’s oak woodland. 

Species Type Scientific Name Common Name A B C D E F G H I J K L

Tree Species Fraxinus anomala singleleaf ash X X X X X X X

Juniperus osteosperma Utah juniper X X X X X X X X X X X X

Picea pungens blue spruce X

Pinus edulis two-needle pinyon pine X X X X X X X X X X X X

Pinus ponderosa ponderosa pine X

Quercus gambelii Gambel’s oak X X

Shub Species Amelanchier utahensis Utah serviceberry X X X X X X

Artemisia bigelovii Bigelow's sagebrush X X X X X

Artemisia nova black sagebrush X X X

Artemisia tridentata ssp. tridentata basin big sagebrush X X

Artemisia tridentata ssp. wyomingensis Wyoming big sagebrush X X X X X

Atriplex canescens fourwing saltbush X X

Atriplex confertifolia shadscale X X

Berberis repens Oregon grape X

Brickellia microphylla var. scabra rough brickellbush X X X

Cercocarpus ledifolius var. intricatus littleleaf mountain-mahogany X X

Cercocarpus montanus true mountain-mahogany X X X X X X X

*Indicates a non-native species.
406

Species Type Scientific Name Common Name A B C D E F G H I J K L

Shub Species 

(continued)

Chrysothamnus depressus dwarf rabbitbrush X

Chrysothamnus viscidiflorus ssp.

viscidiflorus

slenderleaf rabbitbrush X X X X X X X X

Echinocereus triglochidiatus claretcup X X X X X X X

Ephedra viridis Mormom tea X X X X X X X X X X X

Ericameria nauseosa rubber rabbitbrush X X

Ericameria parryi Parry's rabbitbrush X

Eriogonum corymbosum crispleaf buckwheat X X X

Eriogonum microthecum var. laxiflorum slender wild buckwheat X X X

Fendlera rupicola fendlerbush X X X

Grayia spinosa spiny hopsage X X

Holodiscus discolor var. dumosus oceanspray X

Krascheninnikovia lanata winterfat X

Opuntia fragilis brittle pricklypear X X X X

Opuntia phaeacantha berry pricklypear X X X X X

Opuntia polyacantha plains pricklypear X X X X X X

Opuntia polyacantha var. erinacea grizzlybear pricklypear X X X X X X X X

Opuntia spp. pricklypear species X

Purshia Mexicana var. stansburyana cliffrose X X

Rhus aromatica var. pilosissima skunkbush sumac X X X X X

Sclerocactus whipplei Whipple's fishhook cactus X X X X X

Yucca harrimaniae Harriman's yucca X X X X X X X X X

Graminoid 

Species

Achnatherum hymenoides Indian ricegrass X X X X X X X X X X X

Agropyron cristatum* crested wheatgrass X

Aristida purpurea purple three-awn X X X X

Bouteloua gracilis blue grama X X X

Bromus tectorum* cheatgrass X X X X X X X X X

Elymus elymoides squirreltail X X X X X X X X

*Indicates a non-native species.
407

Species Type Scientific Name Common NameABCDEFGHIJKL

Graminoid 

Species 

(continued)

Hesperostipa comata needle and thread

XXXXXXX

Hilaria jamesii James’ galleta

XXXXXXXXX

Leymus salina saline wildrye

XXXXX

Pascopyrum smithii western wheatgrass

X

Poa fendleriana mutton grass

XXXXXXXXXX

Poa secunda Sandberg's bluegrass

X

Pseudoroegneria spicata bluebunch wheatgrass

XX

Sporobolus cryptandrus sand dropseed

X

Vulpia octoflora six weeks fescue

XXXXXXXXX

Forb Species Aliciella stenothyrsa Uinta giliaX

Allium acuminatum tapertip onion

X

Allium textile textile onion

XX

Arabis pulchra beautiful rockcress

X

Arabis spp. rockcress

X

Arenaria fendleri Fendler's sandwort

XXXXX

Arenaria spp. sandwort

X

Artemisia ludoviciana Louisiana wormwood

X

Astragalus mollissimus woolly locoweed

X

Calochortus gunnisonii Gunnison's mariposa

XX

Calochortus nuttallii sego lily

X

Ceratocephala testiculata curveseed butterwort

XX

Chaenactis douglasii hoary dusty

-maidenXX

Chenopodium album* lambsquarters

XX

Cirsium undulatum var. undulatum wavy

-leaf thistleX

Cryptantha flavoculata yellow

-eye cryptanthaX

Cryptantha spp. cryptantha

XXXX

Cymopterus bulbosus onion springparsley

XX

Cymopterus glomeratus Fendler's springparsley

X

*Indicates a non-native species.
408

Species Type Scientific Name Common Name A B C D E F G H I J K L

Forb Species 

(continued)

Cymopterus purpureus Colorado Plateau springparsley X

Delphinium nuttallianum Nuttall's larkspur X

Descurainia pinnata ssp. halictorum western tansymustard X X X X X X X X X

Draba reptans dwarf draba X X X X X

Eremogone hookeri var. hookeri Hooker's sandwort X

Eriogonum alatum winged buckwheat X

Eriogonum ovalifolium var. ovalifolium cushion buckwheat X

Erodium cicutarium* stork's bill X X

Erysimum capitatum western wallflower X

Euphorbia glyptosperma ridge-seeded spurge X X

Galium coloradoense Colorado bedstraw X X

Gutierrezia sarothrae broom snakeweed X X X X X X X X X X

Heterotheca villosa hairy false goldenaster X X X X X X X

Hymenoxys richardsonii Colorado rubber-plant X

Lappula occidentalis var. occidentalis western stickseed X X X X X X

Lepidium montanum mountain pepperwort X X X X X X X X X X

Linanthus pungens prickly phlox X X X

Mirabilis multiflora Colorado four o'clock X

Oenothera pallida ssp. trichocalyx pale evening primrose X X X

Penstemon caespitosus mat penstemon X X

Petradoria pumila grassy rockgoldenrod X X X X X X X

Phlox austromontana desert phlox X

Phlox longifolia longleaf phlox X X X X

Physaria acutifolia sharpleaf twinpod X X X X X

Selaginella densa dense spikemoss X X

*Indicates a non-native species.
409

Species Type Scientific Name Common Name A B C D E F G H I J K L

Forb Species 

(continued)

Senecio integerrimus western groundsel X X X X X

Silene antirrhina sleepy catchfly X X X X X X X X X

Sphaeralcea coccinea ssp. coccinea scarlet globemallow X X X

Stanleya pinnata desert princesplume X

Stenotus armerioides thrift goldenweed X

Streptanthella longirostris longbeak fiddle mustard X X X X X X X X X

Streptanthus cordatus heartleaf jewelflower X X X X

Tetraneuris acaulis Arizona hymenoxys X X X X

Tetraneuris ivesiana Canyonlands hymenoxys X

Townsendia incana hoary townsendia X

Valeriana edulis tobacco root X X X

*Indicates a non-native species.

411

Appendix C. Pinyon-juniper woodland community climate vulnerability scoring worksheet

1. Location in geographical range/distribution Close to (<200 kms) southern limit of community distribution 5 High 3 Pinyon pine is at northern end

of community More distant from southern limit of community distribution 1 Medium 2 of geograhic range, while Utah

Low 1 juniper is more centrally 

Score 4 Score 2 3 located

2. Sensitivity to extreme climatic events Highly vulnerable to extreme climatic events 5 High 3 Both are somewhat sensitive

(e.g., drought, floods, windstorms, icestorms)Less vulnerable to extreme climatic events 3 Medium 2 to drought, however the pinyon

Not vulnerable to extreme climatic events 1 Low 1 pine has higher sensitivity

Score 3 Score 3

5. Dependence on specific hydrologic conditions community is dependent on specific hydrologic conditions 5 High 3 Niether is dependent on a

community is less dependent on specific hydrologic conditions 1 Medium 2 hydrologic regime

Low 1

Score 1 Score 3

4. Intrinsic adaptive capacity Unlikely to be significant (low adaptive capacity) 5 High 3 Previously pinyon-juniper has

 Likely to be significant (high adaptive capacity) 1 Medium 2 been successful expaning into

Low 1 other areas in the Southwest

Score 3 Score 3 under similar warmer arid condition

6. Vulnerability of Foundation/Keystone species Foundation/keystone spp. likely to be particularly vulnerable to climate change 5 High 3 The pinyon pine is more

to climate change Foundation/keystone spp. unlikely to be vulnerable to climate change1 Medium 2 vulnerable to the changing

Low 1 climate conditions than the 

Score 3 Score 2 4 Utah juniper. Juniper could become dominant

7. Potential for climate change to exacerbate impacts Potential for large increase in stressor impacts 5 High 3 Potential change in invasive

of non-climate stressors Potential low 1 Medium 2 composition, increased wildfire

Low 1 regime. Insect and disease outbreaks

Score 3 Score 2 4

Total score Vulnerability category Confidence scores

Range of 7-35 7 to 16 Less Vulnerable 7 to 11 Low Totals 17 15 16-19

17 to 23 Vulnerable 12 to 16 Moderate

24 to 30 Highly Vulnerable 17 to 21 High

31 to 35 Critically Vulnerable

413

Appendix D. Sagebrush shrubland/shrub steppe community composition and growth habitat based on Hogan et al. 

(2009) comprehensive list of plant species.

Species Type Scientific Name Common name Nativity Park status

Tree Species Celtis reticulata netleaf hackberry Native Present

Elaeagnus angustifolia Russian olive Non-native Present

Ulmus pumila Siberian elm Non-native Present

Shrub Species Amelanchier utahensis Utah serviceberry Native Present

Artemisia bigelovii Bigelow's sagebrush Native Present

Artemisia frigida fringed sagebrush Native Present

Artemisia nova black sagebrush Native Present

Artemisia tridentata ssp. tridentata basin big sagebrush Native Present

Artemisia tridentata ssp. wyomingensis Wyoming big sagebrush Native Probably present

Atriplex canescens fourwing saltbush Native Present

Atriplex confertifolia shadscale Native Present

Atriplex corrugata mat saltbush Native Present

Atriplex gardneri Garnder's saltbush Native Probably present

Berberis fremontii Fremont's berberis Native Present

Brickellia californica California brickellbush Native Present

Brickellia microphylla var. scabra rough brickellbush Native Present

Brickellia oblongifolia Mohave brickellbush Native Present

Cercocarpus montanus alderleaf mountain-mahogany Native Present

Chrysothamnus depressus dwarf rabbitbrush Native Present

Chrysothamnus vaseyi Vasey's rabbitbrush Native Probably present

Chrysothamnus viscidiflorus yellow rabbitbrush Native Present

Ephedra torreyana Torrey's Mormon tea Native Present

Ephedra viridis Mormons tea Native Present

Ericameria nauseosa rubber rabbitbrush Native Present

Eriogonum corymbosum var. orbiculatum rimrock wild buckwheat Native Present

*Nativity and park status are assumed to be the same as the species level for these subspecies.
414

Species Type Scientific Name Common name Nativity Park status

Shrub Species 

(continued)

Eriogonum lonchophyllum longleaf wild buckwheat Native Present

Eriogonum microthecum var. simpsonii Simpson's buckwheat Native Present

Glossopetalon spinescens spiny greasebush Native Present

Grayia brandegeei Brandegee's siltbush Native Present

Grayia spinosa spiny hopsage Native Present

Gutierrezia sarothrae broom snakeweed Native Present

Holodiscus discolor var. dumosus oceanspray Native Present

Krascheninnikovia lanata winterfat Native Present

Linanthus pungens prickly phlox Native Present

Picrothamnus desertorum bud sagebrush Native Probably present

Rhus aromatica var. pilosissima skunkbush sumac Native Present

Ribes leptanthum trumpet gooseberry Native Present

Sarcobatus vermiculatus black greasewood Native Present

Symphoricarpos longiflorus longleaf snowberry Native Probably present

Symphoricarpos rotundifolius mountain snowberry Native Present

Tetradymia canescens spineless horsebrush Native Present

Tetradymia spinosa shortspine horsebrush Native Present

Yucca harrimaniae Harriman's yucca Native Present

Perennial Forb 

Species

Abronia elliptica fragrant sand-verbena Native Present

Ageratina herbacea white thoroughwort Native Present

Aliciella stenothyrsa Uinta gilia Native Probably present

Allionia incarnata trailing four o'clock Native Present

Allium acuminatum tapertip onion Native Present

Allium textile textile onion Native Present

Ambrosia psilostachya western ragweed Native Present

Androstephium breviflorum pink funnel-lily Native Present

Artemisia biennis biennial wormwood Non-native Present

Artemisia ludoviciana ssp. albula white sagebrush Native Present

*Nativity and park status are assumed to be the same as the species level for these subspecies.
415

Species Type Scientific Name Common name Nativity Park status

Perennial Forb 

Species 

(continued)

Asclepias asperula ssp. asperula spider milkweed Native Present

Asclepias cryptoceras pallid milkweed Native Present

Asclepias subverticillata whorled milkweed Native Present

Aster spp. hybrid aster Native Present

Astragalus amphioxys var. vespertinus Sheldon's milkvetch Native Present

Astragalus chamaeleuce cicada milkvetch Native Present

Astragalus convallarius lesser rushy milkvetch Native Present

Astragalus eastwoodiae Eastwood's milkvetch Native Present

Astragalus flavus yellow milkvetch Native Present

Astragalus lentiginosus var. palans straggling milkvetch Native Present

Astragalus mollissimus var. thompsoniae woolly milkvetch Native Present

Astragalus multiflorus pulse milkvetch Native Present

Astragalus wingatanus Fort Wingate milkvetch Native Present

Boechera formosa desert rockcress Native Present

Calochortus gunnisonii Gunnison's mariposa lily Native Probably present

Calochortus nuttallii sego-lily Native Present

Castilleja angustifolia northwestern paintbrush Native Present

Castilleja linariifolia Wyoming paintbrush Native Present

Castilleja scabrida Eastwood's paintbrush Native Present

Chaetopappa ericoides rose-heath Native Present

Cichorium intybus chicory Non-native Present

Cirsium neomexicanum New Mexico thistle Native Present

Cirsium tracyi Tracy's thistle Native Present

Comandra umbellata bastard toadflax Native Present

Convolvulus arvensis field bindweed Non-native Present

Cryptantha flava plateau yellow cryptanth Native Present

Cryptantha flavoculata yellow-eye crypantha Native Present

Cryptantha humilis dwarf cryptanth Native Present

*Nativity and park status are assumed to be the same as the species level for these subspecies.
416

Species Type Scientific Name Common name Nativity Park status

Perennial Forb 

Species 

(continued)

Cymopterus bulbosus bulbous spring parsley Native Present

Cymopterus purpureus Colorado Plateau springparsley Native Present

Delphinium nuttallianum Nuttall's larkspur Native Present

Dieteria canescens hoary-aster Native Present

Dracocephalum parviflorum smallflower dragonhead Native Probably present

Echinocereus triglochidiatus claretcup Native Present

Eremogone hookeri var. hookeri Hooker's sandwort Native Probably present

Eremogone kingii basin sandwort Native Present

Erigeron aphanactis hairy aster Native Present

Erigeron divergens spreading daisy Native Present

Erigeron engelmannii Engelmann's daisy Native Present

Erigeron flagellaris trailing daisy Native Present

Eriogonum alatum winged buckwheat Native Present

Eriogonum inflatum desert trumpet Native Present

Eriogonum ovalifolium var. ovalifolium cushion buckwheat Native Present

Eriogonum umbellatum sulfur wild buckwheat Native Probably present

Erysimum capitatum western wallflower Native Present

Euphorbia brachycera shorthorn spurge Native Present

Euphorbia fendleri Fendler's spurge Native Present

Gaillardia pinnatifida red dome blanketflower Native Present

Gilia ophthalmoides eyed gilia Native Present

Grindelia hirsutula hairy gumweed Native Present

Grindelia squarrosa curlycup gumweed Native Present

Hedysarum boreale northern sweetvetch Native Present

Heterotheca villosa hairy false goldenaster Native Present

Hymenopappus filifolius common hyalineherb s Native Present

Hymenoxys richardsonii Colorado rubber-plant Native Probably present

Ipomopsis aggregata ssp. aggregata scarlet gilia Native Present

*Nativity and park status are assumed to be the same as the species level for these subspecies.
417

Species Type Scientific Name Common name Nativity Park status

Perennial Forb 

Species 

Continued)

Ipomopsis roseata San Rafael gilia Native Present

Lepidium draba whitetop Non-native Unconfirmed

Lepidium montanum mountain pepperweed Native Present

Linanthus watsonii Watson's prickly-phlox Native Present

Linaria vulgaris butter -and-eggs Non-native Present

Linum lewisii blue flax Native Present

Lithospermum incisum showy stoneseed Native Present

Lomatium eastwoodiae Eastwood's tall pepperwort Native Present

Lomatium grayi Milfoil lomatium Native Probably present

Lupinus argenteus silvery lupine Native Present

Lygodesmia grandiflora showy rush-pink Native Present

Maianthemum stellatum starry false Solomon's-seal Native Present

Medicago sativa alfalfa Non-native Present

Melilotus officinalis yellow sweetclover Non-native Present

Mirabilis linearis narrow-leaf four-o'clock Native Present

Mirabilis multiflora Colorado four o'clock Native Present

Oenothera cespitosa ssp. marginata long-tube evening-primrose Native Present

Oenothera lavandulifolia lavender-leaf sundrops Native Present

Oenothera pallida ssp. trichocalyx pale evening primrose Native Present

Opuntia fragilis brittle pricklypear Native Present

Opuntia phaeacantha berry pricklypear Native Present

Opuntia polyacantha plains pricklypear Native Present

Opuntia polyacantha var. erinacea grizzlybear pricklypear Native Probably present

Orobanche fasciculata clustered broomrape Native Present

Orobanche ludoviciana Cooper's broomrape Native Present

Packera multilobata basin groundsel Native Present

Pediocactus simpsonii Simpson's hedgehog cactus Native Present

Pediomelum aromaticum aromatic breadroot Native Present

*Nativity and park status are assumed to be the same as the species level for these subspecies.
418

Species Type Scientific Name Common name Nativity Park status

Perennial Forb 

Species 

(continued)

Pediomelum megalanthum large-flowered breadroot Native Present

Penstemon caespitosus mat penstemon Native Present

Penstemon comarrhenus dusty penstemon Native Present

Penstemon cyanocaulis bluestem penstemon Native Present

Penstemon moffatii Moffatt penstemon Native Present

Petradoria pumila grassy rockgoldenrod Native Present

Phlox austromontana desert phlox Native Probably present

Phlox hoodii Hood's phlox Native Present

Phlox longifolia longleaf phlox Native Present

Physalis virginiana Virginia ground-cherry Native Present

Physaria acutifolia sharpleaf twinpod Native Present

Physaria ludoviciana silver bladderpod Native Present

Physaria rectipes Colorado Plateau bladderpod Native Probably present

Plantago lanceolata English plantain Non-native Present

Plantago major common plantain Non-native Present

Platyschkuhria integrifolia oblongleaf basindaisy Native Present

Psilostrophe bakeri Baker's paperflower Native Present

Rhinotropis subspinosa cushion milkwort Native Present

Rumex hymenosepalus canaigre dock Native Present

Rumex triangulivalvis willow dock Native Present

Sclerocactus whipplei Whipple's fishhook cactus Native Present

Sedum lanceolatum lance-leaved stonecrop Native Present

Senecio integerrimus western groundsel Native Probably present

Sisymbrium linifolium flax-leaved plainsmustard Native Present

Solidago velutina three-nerve goldenrod Native Present

Sphaeralcea coccinea ssp. coccinea scarlet globemallow Native Present

Sphaeralcea parvifolia small-leaf globemallow Native Present

Stanleya pinnata desert princesplume Native Present

*Nativity and park status are assumed to be the same as the species level for these subspecies.
419

Species Type Scientific Name Common name Nativity Park status

Perennial Forb 

Species 

(continued)

Stenotus acaulis stemless goldenweed Native Probably present

Stenotus armerioides thrift goldenweed Native Present

Stephanomeria pauciflora brownplume wirelettuce Native Probably present

Streptanthus cordatus heartleaf jewelflower Native Present

Symphyotrichum ascendens Pacific aster Native Present

Taraxacum officinale common dandelion Non-native Present

Tetraneuris acaulis Arizona hymenoxys Native Probably present

Tetraneuris ivesiana Canyonlands hymenoxys Native Present

Thelypodiopsis elegans Westwater tumblemustard Native Present

Thelypodium integrifolium elegant thelypody Native Present

Townsendia incana hoary townsendia Native Present

Toxicoscordion paniculatum foothills death camas Native Present

Toxicoscordion venenosum meadow deathcamas Native Present

Tragopogon dubius yellow salsify Non-native Present

Valeriana edulis tobacco root Native Probably present

Verbascum thapsus woolly mullein Non-native Present

Verbena bracteata prostrate vervain Native Present

Vicia americana American vetch Native Probably present

Xanthisma grindelioides gumweed aster Native Present

Annual Forb 

Species

Alyssum simplex alyssum Non-native Probably present

Amaranthus albus tumble pigweed Non-native Present

Ambrosia acanthicarpa bur ragweed Native Present

Androsace occidentalis western rock-jasmine Native Present

Androsace septentrionalis pygmy-flower rock-jasmine Native Present

Astragalus nuttallianus smallflower milkvetch Native Present

Atriplex rosea tumbling orache Non-native Present

Camelina microcarpa little-pod false flax Non-native Probably present

Chaenactis stevioides Stevia dusty-maiden Native Present

*Nativity and park status are assumed to be the same as the species level for these subspecies.
420

Species Type Scientific Name Common name Nativity Park status

Annual Forb 

Species 

(continued)

Chenopodium album* lambsquarters Non-native Probably present

Chenopodium fremontii Fremont's goosefoot Native Present

Chenopodium leptophyllum narrow-leaf goosefoot Native Present

Chorispora tenella blue mustard Non-native Present

Cryptantha fendleri sand dune cryptanth Native Probably present

Cryptantha gracilis slender cryptanth Native Present

Cryptantha pterocarya wing-nut cryptanth Native Present

Cuscuta indecora large-seed dodder Native Present

Descurainia pinnata ssp. halictorum western tansymustard Native Present

Descurainia sophia flixweed Non-native Present

Draba reptans dwarf draba Native Probably present

Eriogonum cernuum nodding wild buckwheat Native Present

Eriogonum hookeri Hooker's wild buckwheat Native Present

Erodium cicutarium stork’s bill Non-native Probably present

Euphorbia glyptosperma ridge-seeded spurge Native Present

Gilia sinuata shy gilia Native Present

Helianthus annuus common sunflower Native Present

Kochia scoparia summer-cypress Non-native Present

Lactuca serriola prickly lettuce Non-native Present

Lappula marginata cupseed stickseed Native Present

Lappula occidentalis var. occidentalis western stickseed Native Present

Lepidium densiflorum prairie pepperwort Native Present

Lepidium lasiocarpum hairy-pod pepperwort Native Present

Lepidium perfoliatum clasping pepperwort Non-native Present

Medicago lupulina black medick Non-native Present

Melilotus albus white sweetclover Non-native Present

Mentzelia albicaulis white-stem blazingstar Native Present

Mimulus rubellus reddish monkeyflower Native Present

*Nativity and park status are assumed to be the same as the species level for these subspecies.
421

Species Type Scientific Name Common name Nativity Park status

Annual Forb 

Species 

(continued)

Peritoma lutea yellow beeplant Native Present

Peritoma serrulata Rocky Mountain beeplant Native Present

Phacelia crenulata crenulate phacelia Native Present

Phacelia ivesiana Ives' phacelia Native Present

Plantago patagonica woolly plantain Native Present

Polanisia dodecandra clammy-weed Native Present

Portulaca oleracea common purslane Non-native Present

Ranunculus testiculatus sagebrush buttercup Non-native Present

Salsola australis Russian thistle Non-native Present

Silene antirrhina sleepy catchfly Native Present

Sisymbrium altissimum tumble mustard Non-native Present

Solanum rostratum buffalobur Native Present

Stephanomeria exigua white-plume wire-lettuce Native Present

Strigosella africana African mustard Non-native Present

Tribulus terrestris puncture vine Non-native Present

Perennial 

Graminoid 

Species

Achnatherum aridum Mormon needlegrass Native Present

Achnatherum hymenoides Indian ricegrass Native Present

Agropyron desertorum desert wheatgrass Non-native Present

Aristida purpurea purple three-awn Native Present

Bouteloua curtipendula sideoats grama Native Present

Bouteloua gracilis blue grama Native Probably present

Bromus inermis smooth brome Non-native Present

Dactylis glomerata orchard grass Non-native Present

Elymus elymoides squirreltail Native Probably present

Elymus elymoides ssp. elymoides* bottlebrush squirreltail Native Probably present

Elymus repens quackgrass Non-native Present

Elymus trachycaulus slender wheatgrass Native Present

Erioneuron pilosum hairy tridens Native Present

*Nativity and park status are assumed to be the same as the species level for these subspecies.
422

Species Type Scientific Name Common name Nativity Park status

Perennial 

Graminoid 

Species 

(continued)

Hesperostipa comata needle and thread Native Present

Hesperostipa neomexicana New Mexico feathergrass Native Present

Hilaria jamesii James’galleta Native Present

Hordeum jubatum foxtail barley Native Present

Koeleria macrantha junegrass Native Present

Leymus salina saline wildrye Native Present

Muhlenbergia richardsonis mat muhly Native Probably present

Muhlenbergia thurberi Thurber's muhly Native Present

Panicum virgatum switchgrass Native Present

Pascopyrum smithii western wheatgrass Native Present

Poa bulbosa bulbous bluegrass Non-native Present

Poa fendleriana muttongrass Native Present

Poa pratensis Kentucky bluegrass Non-native Present

Poa pratensis ssp. angustifolia* Agassiz's bluegrass Non-native Present

Poa secunda Sandberg's bluegrass Native Present

Pseudoroegneria spicata bluebunch wheatgrass Native Probably present

Puccinellia nuttalliana Nuttall's alkaligrass Native Present

Sporobolus airoides alkali sacaton Native Present

Sporobolus contractus spike dropseed Native Present

Sporobolus cryptandrus sand dropseed Native Present

Sporobolus flexuosus mesa dropseed Native Present

Thinopyrum intermedium ssp. 

intermedium

intermediate wheatgrass Non-native Present

Annual 

Graminoid 

Species

Bromus diandrus ripgut brome Non-native Present

Bromus japonicus Japanese brome Non-native Probably present

Bromus tectorum cheatgrass Non-native Present

Cenchrus longispinus field sandbur Native Present

Echinochloa crus-galli barnyard grass Non-native Present

*Nativity and park status are assumed to be the same as the species level for these subspecies.
423

Species Type Scientific Name Common name Nativity Park status

Annual 

Graminoid 

Species 

(continued)

Eragrostis barrelieri Mediterranean lovegrass Non-native Present

Hordeum pusillum little barley Native Present

Muhlenbergia depauperata sixweeks muhly Native Present

Muhlenbergia minutissima annual muhly Native Present

Munroa squarrosa false buffalograss Native Present

Panicum capillare witchgrass Native Present

Setaria viridis green bristlegrass Non-native Present

Triticum aestivum wheat Non-native Probably present

Vulpia octoflora six weeks fescue Native Present

Fern Species Cheilanthes feei slender lip fern Native Present

*Nativity and park status are assumed to be the same as the species level for these subspecies.

425

Appendix E. Riparian habitat/large dry wash community dominant species composition by growth habitat based on 

vegetation mapping project classification descriptions (Von Loh et al. 2007).

Key to coded columns- A: Cottonwood/coyote willow woodland, B: Coyote willow/mesic graminoids shrubland, C: Quaking aspen/water 

birch forest, D: Rubber rabbitbrush desert wash shrubland, E: Baltic rush herbaceous vegetation, F: Box elder/disturbed understory 

woodland, G: Quaking aspen western chokecherry forest, H: Singleleaf ash woodland, I: Skunkbush intermittently flooded shrubland, J: 

Smooth horsetail herbaceous vegetation, and K: Water birch/starry false Solomon’s-seal shrubland. 

Species Type Scientific Name Common Name A B C D E F G H I J K

Tree Species Acer glabrum Rocky Mountain maple X

Acer negundo boxelder X

Betula occidentalis water birch X X

Celtis reticulata netleaf hackberry X

Fraxinus anomala singleleaf ash X X

Juniperus osteosperma Utah juniper X X X X

Populus angustifolia narrow-leaved cottonwood X

Populus deltoides ssp. wislizeni Rio Grande cottonwood X X X X

Populus tremuloides quaking aspen X X

Quercus gambelii Gambel’s oak X

Shrub Species Amelanchier utahensis Utah serviceberry X X

Artemisia bigelovii Bigelow's sagebrush X

Artemisia tridentata ssp. tridentata basin big sagebrush X

Artemisia tridentata ssp. wyomingensis Wyoming big sagebrush X

Elaeagnus angustifolia* Russian olive X

Ericameria nauseosa rubber rabbitbrush X X X X

Prunus virginiana western chokecherry X

Rhus aromatica skunkbush X X

Rosa woodsii Woods’ rose X X

Salix exigua coyote willow X X X

*Indicates a non-native species.
426

Species Type Scientific Name Common Name

ABCDEFGHIJK

Shrub Species 

(continued)

Salix fragilis* crack willow

XX

Salix lucida whiplash willow

X

Salix monticola mountain willow

XX

Sarcobatus vermiculatus black greasewood

X

Tamarix ramosissima* saltcedar

X

Graminoid 

Species

Achnatherum hymenoides Indian ricegrass

X

Agrostis gigantea* redtop

XXX

Bromus japonicus* Japanese chess

XXXX

Bromus tectorum* cheatgrass

XXXXXX

Dactylis glomerata* orchard grass

X

Distichlis spicata desert saltgrass

XXXX

Hesperostipa comata needle and thread

X

Hordeum jubatum foxtail barley

X

Juncus balticus Baltic rush

XXXXX

Muhlenbergia asperifolia scratchgrass

X

Pascopyrum smithii western wheatgrass

X

Phragmites australis common reed

XX

Poa pratensis* Kentucky bluegrass

XXXX

Sporobolus airoides alkali sacaton

X

Forb Species Artemisia ludoviciana ssp. albula white sagebrushX

Cirsium undulatum var. undulatum wavy

-leaf thistleX

Clematis ligusticifolia white virgin’s bower

XXX

Equisetum arvense field horsetail

X

Equisetum laevigatum smooth horsetail

XXXX

Glycyrrhiza lepidota Nuttall’s licorace

X

Heterotheca villosa hairy false goldenaster

X

Iva axillaris povertyweed

X

Maianthemum stellatum starry false Solomon's

-sealXX

*Indicates a non-native species.
427

Species Type Scientific Name Common Name A B C D E F G H I J K

Forb Species 

(continued)

Melilotus officinalis* yellow sweetclover X X

Ranunculus cymbalaria marsh buttercup X

Typha latifolia broad-leaved cattail X

*Indicates a non-native species.

429

Appendix F. Seeps and springs community composition at No Thoroughfare and 

Lower Echo Canyon springs inventoried by Springer et al. (2006).

Scientific name Common Name NTC LEC

- algae X

- moss X

Agrostis stolonifera* creeping bentgrass X

Aquilegia desertorum Chiricahua Mountain columbine X

Artemisia spp. sagebrush X X

Asclepias speciosa showy milkweed X

Asparagus officinalis* garden asparagus X

Astragalus spp. milkvetch X

Betula occidentalis water birch X

Brickellia microphylla littleleaf brickellbush X

Bromus tectorum* cheatgrass X

Carex spp. sedge X

Castilleja linariifolia Wyoming paintbrush X

Cirsium neomexicanum New Mexico thistle X

Cirsium undulatum var. undulatum wavy-leaf thistle X

Clematis ligusticifolia white virgin's bower X X

Dactylis glomerata* orchardgrass X

Eleocharis spp. spikerush X

Elymus canadensis Canada wildrye X

Epilobium ciliatum fringed willowherb X

Epilobium spp. willowherb X

Epipactis gigantea giant helleborine X

Equisetum laevigatum smooth horsetail X

Equisetum variegatum northern scouring-rush X

Ericameria spp. rabbitbrush X

Euthamia occidentalis western goldenrod X

Fendlerella utahensis Utah fendlerella X

Grindelia fastigiata erect gumweed X

Heterotheca villosa hairy false goldenaster X

Hordeum spp. barley X

Ipomopsis aggregata scarlet gilia X

Juncus arcticus Arctic rush X X

Lactuca serriola* prickly lettuce X

Lactuca spp. lettuce X

Maianthemum stellatum starry false Solomon’s-seal X

Medicago sativa* alfalfa X

*Indicates a non-native species.
430

Scientific name Common Name NTC LEC

Melilotus officinalis* yellow sweetclover X

Muhlenbergia andina foxtail muhly X

Muhlenbergia asperifolia scratchgrass X

Oenothera spp. evening primrose X

Perityle congesta Grand Canyon rockdaisy X

Plantago lanceolata* English plantain X

Populus angustifolia narrow-leaved cottonwood X

Populus fremontii Fremont cottonwood X

Pseudotsuga menziesii Douglas-fir X

Rhus aromatica var. pilosissima skunkbush sumac X

Salix bebbiana Bebb’s willow X

Salix eriocephala Missouri River willow X

Salix exigua coyote willow X X

Salix laevigata red willow X

Salix spp. willow X

Schoenoplectus pungens three-square bulrush X

Sisymbrium altissimum* tumblemustard X

Stephanomeria spp. wirelettuce X

Symphyotrichum lanceolatum Siskiyou aster X

Taraxacum officinale* common dandelion X X

Toxicodendron rydbergii western poison ivy X

Tragopogon dubius* yellow salsify X

Typha domingensis southern cattail X

Totals† 21 41

*Indicates a non-native species.

†Totals do not include the first five table rows, since these organisms are described broadly rather 

than to species or genus.
431

Appendix G. Seeps and springs community composition by canyon, as documented by Lamm et al. (2014).

Unidentified species (e.g., “unknown highly serrated plant”) were excluded. Numbers in parentheses indicate the number of sites visited in 

each canyon. 

Scientific Name Common Name

Site**

EC

(1)

UC

(5)

MC

(13)

NTC

(10)

WC

(2)

RC

(1)

CC

(2)

- Algae (green, blue) X X X X X

- Biological Soil Crust X

- Black algae X

- Moss X X X X

- Red algae X

Acer glabrum Rocky Mountain maple X

Achnatherum hymenoides Indian ricegrass X X X X

Agropyron desertorum* desert wheatgrass X

Agrostis gigantea* redtop X X

Alyssum simplex* allysum X X

Amelanchier utahensis Utah serviceberry X X X X X X

Apocynum cannabinum common dogbane X

Arctium minus burdock X

Artemisia ludoviciana ssp. incompta Columbia River wormwood X

Artemisia tridentata big sagebrush X X X X X X

Asclepias speciosa showy milkweed X X

Astragalus desperatus rimrock milkvetch X

Astragalus lentiginosus var. palans straggling milkvetch X

Betula occidentalis water birch X X

*Indicates a non-native species.

** EC = Echo Canyon, UC = Ute Canyon, MC = Monument Canyon, NTC = No Thoroughfare Canyon, WC = Wedding Canyon, RC = Red 

Canyon, CC = Columbus Canyon.
432

Site**

Scientific Name Common Name

EC

(1)

UC

(5)

MC

(13)

NTC

(10)

WC

(2)

RC

(1)

CC

(2)

Brickellia microphylla var. scabra rough brickellbush X X

Bromus inermis* smooth brome X

Bromus tectorum* cheatgrass X X X X X X

Carex microptera small-wing sedge X

Castilleja angustifolia var. dubia desert paintbrush X

Castilleja linariifolia Wyoming paintbrush X

Castilleja minor ssp. minor annual paintbrush X

Cirsium spp. thistle X X X X X X

Cirsium vulgare* bull thistle X

Clematis ligusticifolia white virgin's bower X X X X X X

Comandra umbellata bastard toadflax X

Conium maculatum* poison-hemlock X

Conyza canadensis Canadian horseweed X X

Dactylis glomerata* orchard grass X X X

Descurainia pinnata ssp. halictorum western tansymustard X X

Distichilis spicata desert saltgrass X X X X X X X

Elymus trachycaulus slender wheatgrass X X X X X X

Epipactis gigantea giant helleborine X

Equisetum laevigatum smooth horsetail X X X X X

Ericameria nauseosa rubber rabbitbrush X X X X X

Erigeron divergens spreading daisy X

Erigeron utahensis Utah daisy X X

Fendlera rupicola fendlerbush X

*Indicates a non-native species.

** EC = Echo Canyon, UC = Ute Canyon, MC = Monument Canyon, NTC = No Thoroughfare Canyon, WC = Wedding Canyon, RC = Red 

Canyon, CC = Columbus Canyon.
433

Site**

Scientific Name Common Name

EC

(1)

UC

(5)

MC

(13)

NTC

(10)

WC

(2)

RC

(1)

CC

(2)

Fraxinus anomala singleleaf ash X X X X X X

Grindelia squarrosa curlycup gumweed X

Gutierrezia sarothrae broom snakeweed X X

Hesperostipa comata needle and thread X

Heterotheca villosa hairy false goldenaster X X X X X X

Hilaria jamesii James' galleta X X

Hordeum jubatum foxtail barley X X X X

Hymenopappus filifolius common hyalineherb X

Ipomopsis aggregata ssp. aggregata scarlet gilia X

Ipomopsis roseata San Rafael gilia X

Juncus arcticus Arctic rush X X X X X

Juniperus osteosperma Utah juniper X X X X

Koeleria macrantha junegrass X

Lactuca serriola* prickly lettuce X X X

Lepidium montanum mountain pepperweed X X X X

Leymus salina saline wildrye X

Lomatium eastwoodiae Eastwood's tall pepperwort X X X X X

Maianthemum stellatum starry false Solomon's-seal X X

Melilotus officinalis* yellow sweetclover X X X X X

Oenothera pallida ssp. trichocalyx pale evening primrose

Opuntia spp. pricklypear X

Packera multilobata basin groundsel X X

Panicum capillare witchgrass X

*Indicates a non-native species.

** EC = Echo Canyon, UC = Ute Canyon, MC = Monument Canyon, NTC = No Thoroughfare Canyon, WC = Wedding Canyon, RC = Red 

Canyon, CC = Columbus Canyon.
434

Site**

Scientific Name Common Name

EC

(1)

UC

(5)

MC

(13)

NTC

(10)

WC

(2)

RC

(1)

CC

(2)

Penstemon cyanocaulis bluestem penstemon X

Phalaris arundinacea reed canary grass X

Phragmites australis common reed X

Physaria acutifolia sharpleaf twinpod X

Pinus edulis two-needle pinyon pine X X X X X

Plantago lanceolata* English plantain X

Poa pratensis* Kentucky bluegrass X X X

Populus angustifolia narrow-leaved cottonwood X X X X X

Populus fremontii Fremont cottonwood X X X X X X X

Quercus gambelii Gambel's oak X X

Rhus aromatica var. pilosissima skunkbush sumac X X X X

Rosa woodsii Woods' rose X X

Salix spp. willow X X X X X X X

Sarcobatus vermiculatus black greasewood X

Silene antirrhina sleepy catchfly X

Sisymbrium altissimum* tumble mustard X

Solidago velutina three-nerve goldenrod X

Sporobolus cryptandrus sand dropseed X

Stephanomeria tenuifolia slender wirelettuce X X

Tamarix ramosissima* saltcedar X X X

Taraxacum officinale* common dandelion X

Tetraneuris ivesiana Canyonlands hymenoxys X

Thelypodiopsis elegans elegant thelypody X

*Indicates a non-native species.

** EC = Echo Canyon, UC = Ute Canyon, MC = Monument Canyon, NTC = No Thoroughfare Canyon, WC = Wedding Canyon, RC = Red 

Canyon, CC = Columbus Canyon.
435

Site

Scientific Name Common Name

EC

(1)

UC

(5)

MC

(13)

NTC

(10)

WC

(2)

RC

(1)

CC

(2)

Tragopogon dubius* yellow salsify X X X X

Typha latifolia broad-leaved cattail X X X

Verbascum thapsus* woolly mullein X

Veronica anagallis-aquatica water speedwell X

Vicia americana American vetch X X

Yucca harrimaniae Harriman's yucca X

Zannichellia palustris horned pondweed X

Totals† 24 42 49 51 19 6 28

*Indicates a non-native species.

** EC = Echo Canyon, UC = Ute Canyon, MC = Monument Canyon, NTC = No Thoroughfare Canyon, WC = Wedding Canyon, RC = Red 

Canyon, CC = Columbus Canyon.

†Totals do not include the first five table rows, since these organisms are described broadly rather than to species or genus.
436
437

Appendix H. Seep, spring, tinaja habitats climate vulnerability scoring worksheet.

Vulnerability Score Confidence Score Alternative Score Notes:

1. Location in geographical range/distribution Close to (<200 kms) southern limit of community distribution 5 High 3 COLM is located at the northern

of community More distant from southern limit of community distribution 1 Medium 2 and eastern margin of geographic

Low 1 range of Mancos columbine and 

Score 4 Score 3 3 Rio Grande cottonwood

2. Sensitivity to extreme climatic events Highly vulnerable to extreme climatic events 5 High 3 Increased frequency and intensity

(e.g., drought, floods, windstorms, icestorms) Less vulnerable to extreme climatic events 3 Medium 2 of extreme weather events can be 

Not vulnerable to extreme climatic events 1 Low 1 detrimental to seep, spring, and 

Score 4 Score 3 tijana habitas. Extremely drought sensitive

5. Dependence on specific hydrologic conditions community is dependent on specific hydrologic conditions 5 High 3 Rely on availability of precipitation,

community is less dependent on specific hydrologic conditions 1 Medium 2 both rain and snow for recharge

Low 1 Reduced winter snowpack and

Score 4 Score 3 seasonal rains 

4. Intrinsic adaptive capacity Unlikely to be significant (low adaptive capacity) 5 High 3 Require a degree of soil moisture

 Likely to be significant (high adaptive capacity) 1 Medium 2 in order to survive. Very little 

Low 1 adaptability to a hotter, drier

Score 4 Score 3 5 climate for Mancos columbine

6. Vulnerability of Foundation/Keystone species Foundation/keystone spp. likely to be particularly vulnerable to climate change 5 High 3 Mancos columbine is niche species

to climate change Foundation/keystone spp. unlikely to be vulnerable to climate change 1 Medium 2 Smooth horsetail, Rio Grande

Low 1 cottonwood and coyote willow

Score 4 Score 3 3 more tolerant of projected conditions

7. Potential for climate change to exacerbate impacts Potential for large increase in stressor impacts 5 High 3 Potential change in invasive

of non-climate stressors Potential low 1 Medium 2 composition, increased wildfire

Low 1 regime. Potential for increased

Score 4 Score 3 5 water demand for urban & ag needs

Total score Vulnerability category Confidence scores

Range of 7-35 7 to 16 Less Vulnerable 7 to 11 Low Totals 2 4 1 8 22-26

17 to 23 Vulnerable 12 to 16 Moderate

24 to 30 Highly Vulnerable 17 to 21 High

31 to 35 Critically Vulnerable

439

Appendix I. Montane shrubland and growth habitat based on Hogan et al. (2009) comprehensive list of plant species.

Species Type Species name Common name Nativity Park status

Tree Species Celtis reticulata netleaf hackberry Native Present

Juniperus osteosperma Utah juniper Native Present

Pinus ponderosa ponderosa pine Native Present

Populus tremuloides quaking aspen Native Present

Pseudotsuga menziesii Douglas-fir Native Present

Quercus gambelii Gambel's oak Native Present

Shrub Species Acer glabrum Rocky Mountain maple Native Present

Amelanchier utahensis Utah serviceberry Native Present

Arctostaphylos patula greenleaf manzanita Native Present

Artemisia tridentata ssp. tridentata basin big sagebrush Native Present

Berberis repens Oregon grape Native Present

Cercocarpus ledifolius curl-leaf mountain mahogany Native Present

Cercocarpus montanus true mountain-mahogany Native Present

Chrysothamnus depressus dwarf rabbitbrush Native Present

Ephedra viridis Mormon tea Native Present

Ericameria nauseosa rubber rabbitbrush Native Present

Eriogonum microthecum var. laxiflorum slender wild buckwheat Native Present

Eriogonum microthecum var. simpsonii Simpson's buckwheat Native Present

Fraxinus anomala singleleaf ash Native Present

Gutierrezia sarothrae broom snakeweed Native Present

Holodiscus discolor var. dumosus oceanspray Native Present

Juniperus communis common juniper Native Probably present

Linanthus pungens prickly phlox Native Present

Paxistima myrsinites mountain-lover Native Present

Philadelphus microphyllus littleleaf mock-orange Native Present

Prunus virginiana western chokecherry Native Present

Purshia mexicana var. stansburyana cliffrose Native Present

Quercus X undulata few-lobe oak Native Present
440

Species Type Species name Common name Nativity Park status

Shrub Species 

(continued)

Ribes inerme whitestem gooseberry Native Probably present

Rosa woodsii Woods' rose Native Present

Symphoricarpos rotundifolius mountain snowberry Native Present

Perennial Forb 

Species

Ageratina herbacea white thoroughwort Native Present

Allium textile textile onion Native Present

Antennaria marginata sandstone pussytoes Native Present

Artemisia dracunculus tarragon Native Present

Artemisia ludoviciana ssp. incompta Columbia River wormwood Native Present

Astragalus desperatus rimrock milkvetch Native Present

Astragalus eastwoodiae Eastwood's milkvetch Native Present

Astragalus flavus yellow milkvetch Native Present

Astragalus mollissimus var. 

thompsoniae

woolly milkvetch Native Present

Astragalus multiflorus pulse milkvetch Native Present

Astragalus wingatanus Fort Wingate milkvetch Native Present

Brickellia grandiflora tassel-flower brickellbush Native Present

Calochortus gunnisonii Gunnison's mariposa Native Probably present

Calochortus nuttallii sego-lily Native Present

Castilleja angustifolia northwestern paintbrush Native Present

Castilleja linariifolia Wyoming paintbrush Native Present

Castilleja scabrida Eastwood's paintbrush Native Present

Chaenactis douglasii hoary dusty-maiden Native Present

Comandra umbellata bastard toadflax Native Present

Corallorhiza maculata spotted coral-root Native Present

Cryptantha flavoculata yellow-eye crypantha Native Present

Delphinium nuttallianum Nuttall's larkspur Native Present

Dieteria canescens hoary aster Native Present

Dracocephalum parviflorum smallflower dragonhead Native Probably present

Eremogone fendleri Fendler's sandwort Native Probably present

Erigeron aphanactis hairy daisy Native Present
441

Species Type Species name Common name Nativity Park status

Perennial Forb 

Species

(continued)

Erigeron utahensis Utah daisy Native Present

Eriogonum alatum winged buckwheat Native Present

Eriogonum umbellatum sulfur wild buckwheat Native Probably present

Euphorbia brachycera shorthorn spurge Native Present

Galium coloradoense Colorado bedstraw Native Present

Hedysarum boreale northern sweetvetch Native Present

Heterotheca villosa hairy false goldenaster Native Present

Heuchera parvifolia littleleaf alumroot Native Present

Ipomopsis aggregata ssp. aggregata scarlet gilia Native Present

Ipomopsis roseata San Rafael gilia Native Present

Lathyrus lanszwertii var. leucanthus whiteflower sweetpea Native Present

Linum lewisii blue flax Native Present

Lupinus argenteus silvery lupine Native Present

Maianthemum stellatum starry false Solomon’s-seal Native Present

Mirabilis linearis narrowleaf four-o'clock Native Present

Mirabilis oxybaphoides spreading four-o'clock Native Present

Oenothera cespitosa ssp. marginata long-tube evening-primrose Native Present

Oenothera pallida ssp. trichocalyx pale evening primrose Native Present

Opuntia fragilis brittle pricklypear Native Present

Opuntia phaeacantha berry pricklypear Native Present

Opuntia polyacantha plains pricklypear Native Present

Packera multilobata basin groundsel Native Present

Penstemon comarrhenus dusty penstemon Native Present

Penstemon cyanocaulis bluestem beardtongue Native Present

Petradoria pumila grassy rockgoldenrod Native Present

Phlox austromontana desert phlox Native Probably present

Phlox hoodii Hood's phlox Native Present

Phlox longifolia longleaf phlox Native Present

Physaria ludoviciana silver bladderpod Native Present
442

Species Type Species name Common name Nativity Park status

Perennial Forb 

Species

(continued)

Sedum lanceolatum lance-leaved stonecrop Native Present

Senecio integerrimus western groundsel Native Probably present

Sisymbrium linifolium flax-leaved plainsmustard Native Present

Solidago velutina three-nerve goldenrod Native Present

Sphaeralcea coccinea ssp. coccinea scarlet globemallow Native Present

Sphaeralcea parvifolia small-leaf globemallow Native Present

Stanleya pinnata desert princesplume Native Present

Stenotus acaulis stemless goldenweed Native Probably present

Stephanomeria tenuifolia slender wirelettuce Native Present

Streptanthus cordatus heartleaf jewelflower Native Present

Symphyotrichum ascendens Pacific aster Native Present

Taraxacum officinale common dandelion Non-native Present

Thelypodium laxiflorum slate thelypody Native Probably present

Verbascum thapsus woolly mullein Non-native Present

Vicia americana American vetch Native Probably present

Annual Forb 

Species

Alyssum simplex alyssum Non-native Probably present

Androsace occidentalis western rock-jasmine Native Present

Androsace septentrionalis pygmy-flower rock-jasmine Native Present

Chenopodium foliosum leafy goosefoot Native Present

Chenopodium fremontii Fremont's goosefoot Native Present

Cryptantha fendleri sand dune cryptanth Native Probably present

Cryptantha gracilis slender cryptanth Native Present

Descurainia pinnata ssp. halictorum western tansymustard Native Present

Gilia sinuata shy gilia Native Present

Lactuca serriola prickly lettuce Non-native Present

Lappula marginata cupseed stickseed Native Present

Lappula occidentalis var. occidentalis western stickseed Native Present

Phacelia ivesiana Ives' phacelia Native Present

Salsola australis Russian thistle Non-native Present
443

Species Type Species name Common name Nativity Park status

Perennial 

Graminoid 

Species

Achnatherum hymenoides Indian ricegrass Native Present

Aristida purpurea purple three-awn Native Present

Carex rossii Ross' sedge Native Present

Elymus elymoides squirreltail Native Probably present

Elymus trachycaulus slender wheatgrass Native Present

Hesperostipa comata needle and thread Native Present

Koeleria macrantha junegrass Native Present

Muhlenbergia richardsonis mat muhly Native Probably present

Panicum virgatum switchgrass Native Present

Pascopyrum smithii western wheatgrass Native Present

Piptatherum micranthum littleseed ricegrass Native Present

Poa fendleriana muttongrass Native Present

Poa pratensis Kentucky bluegrass Non-native Present

Poa secunda Sandberg's bluegrass Native Present

Pseudoroegneria spicata bluebunch wheatgrass Native Probably present

Annual 

Graminoid 

Species

Bromus japonicus Japanese chess Non-native Probably present

Panicum capillare witchgrass Native Present

Ferns and 

Allies Species

Argyrochosma fendleri Fendler's false cloak fern Native Present

Cheilanthes feei slender lip-fern Native Present

Cystopteris fragilis brittle bladder fern Native Present

Pellaea atropurpurea purple cliffbrake Native Present

445

Appendix J. Bird species observed in COLM during monitoring and survey efforts.

Species

NPS 

(2015)* CBC*

Giroir 

(2001)*

RMBO 

Monitoring*

American Coot B

American Crow R R R

American Dipper R

American Goldfinch R R R

American Kestrel R R R R

American Pipit M M

American Robin R R R

American Tree Sparrow M M

American White Pelican M

American Wigeon M

Anna's Hummingbird V

Ash-throated Flycatcher R R R

Bald Eagle M M

Band-tailed Pigeon B

Bank Swallow B

Barn Owl R R

Barn Swallow R

Barrow's Goldeneye M

Belted Kingfisher M M

Bewick's Wren R R R R

Black Phoebe V

Black Rosy-Finch M M

Black-and-white Warbler V

Black-billed Magpie R R R

Black-capped Chickadee R R R

Black-chinned Hummingbird R R R

Black-chinned Sparrow M

Black-crowned Night-Heron B

Black-headed Grosbeak R R R

Black-throated Blue Warbler V

Black-throated Gray Warbler R R R

Black-throated Sparrow B B B B

Blue Grosbeak M M

Blue Grouse M

Blue Jay R

Blue-gray Gnatcatcher R R R R

Blue-winged Teal B

Bohemian Waxwing M M

*R = resident species, B = breeding species, M = migratory species, V = vagrant species.
446

Species

NPS 

(2015)* CBC*

Giroir 

(2001)*

RMBO 

Monitoring*

Brewer's Blackbird R R R

Brewer's Sparrow R R R

Broad-tailed Hummingbird R R R

Brown Creeper M M

Brown-capped Rosy-Finch M M

Brown-headed Cowbird R R R R

Bufflehead M

Bullock's Oriole R R R

Burrowing Owl B

Bushtit B B B B

Cackling Goose M

California Gull M

California Quail R

Canada Goose R

Canvasback M

Canyon Wren R R R R

Cassin's Finch M M M

Cassin's Vireo M

Cedar Waxwing M M

Chipping Sparrow R R R R

Chukar R R R

Clark's Nutcracker R R R R

Cliff Swallow R R R

Common Goldeneye M

Common Grackle B

Common Loon M

Common Merganser B

Common Nighthawk B B

Common Poorwill B

Common Raven R R R R

Common Redpoll M

Common Yellowthroat M M

Cooper's Hawk B B B

Cordilleran Flycatcher R

Dark-eyed Junco R R R R

Double-crested Cormorant M

Downy Woodpecker R R

Dunlin M

Dusky Flycatcher R R R

*R = resident species, B = breeding species, M = migratory species, V = vagrant species.
447

Species

NPS 

(2015)* CBC*

Giroir 

(2001)*

RMBO 

Monitoring*

Eared Grebe B

Eastern Bluebird V V

Eastern Kingbird R

Eastern Phoebe V

Eurasian Collared-Dove R R R

European Starling R R

Evening Grosbeak R R

Ferruginous Hawk B B

Fox Sparrow M

Gadwall B

Gambel's Quail B B B B

Golden Eagle B B B B

Golden-crowned Kinglet R R

Golden-crowned Sparrow V

Grace's Warbler B B

Gray Catbird B

Gray Flycatcher R R R

Gray Jay R

Gray Vireo B B B

Gray-crowned Rosy-Finch M M

Great Blue Heron M M

Great Egret M

Great Horned Owl B B

Great-tailed Grackle R

Greater Scaup M

Greater White-fronted Goose V

Greater Yellowlegs M

Green Heron M

Green-tailed Towhee R R R R

Green-winged Teal R

Gunnison Sage-Grouse R

Hairy Woodpecker R R R

Hammond's Flycatcher M

Harris's Sparrow M

Hermit Thrush R R R R

Hooded Merganser M

Horned Grebe M

Horned Lark R R

House Finch R R R R

*R = resident species, B = breeding species, M = migratory species, V = vagrant species.
448

Species

NPS 

(2015)* CBC*

Giroir 

(2001)*

RMBO 

Monitoring*

House Sparrow R R

House Wren R R R R

Juniper Titmouse R R R R

Killdeer R R

Lapland Longspur M

Lark Bunting M

Lark Sparrow R R R

Lazuli Bunting R R R

Least Sandpiper M

Lesser Goldfinch R R R R

Lesser Scaup M

Lesser Yellowlegs M

Lewis's Woodpecker R R

Lincoln's Sparrow B B B

Loggerhead Shrike R R

Long-eared Owl M M

MacGillivray's Warbler M M

Magnificent Hummingbird V

Mallard M M

Marsh Wren R

Merlin M M

Mountain Bluebird R R R R

Mountain Chickadee R R R R

Mountain Quail V

Mourning Dove B B B B

Mute Swan V

Northern Flicker R R R R

Northern Goshawk M M

Northern Harrier M M

Northern Mockingbird R R

Northern Pintail R

Northern Pygmy-Owl R R R

Northern Rough-winged Swallow B B

Northern Saw-whet Owl M M

Northern Shoveler B

Northern Shrike R R

Oak Titmouse V

Olive-sided Flycatcher B B

Orange-crowned Warbler M M

*R = resident species, B = breeding species, M = migratory species, V = vagrant species.
449

Species

NPS 

(2015)* CBC*

Giroir 

(2001)*

RMBO 

Monitoring*

Osprey M M

Peregrine Falcon B B B B

Pied-billed Grebe R

Pine Grosbeak R R

Pine Siskin R R R R

Pinyon Jay R R R R

Plumbeous Vireo B B B

Prairie Falcon B B B

Pygmy Nuthatch R

Red Crossbill R R

Red-bellied Woodpecker V

Red-breasted Merganser M

Red-breasted Nuthatch M M M

Red-naped Sapsucker M M

Red-shouldered Hawk V

Red-tailed Hawk R R R

Red-winged Blackbird M M

Redhead B

Ring-billed Gull M

Ring-necked Duck M

Ring-necked Pheasant R R

Ringed Turtle-Dove V

Rock Dove R R R R

Rock Wren B B B B

Rose-breasted Grosbeak M

Ross's Goose M

Rough-legged Hawk M M

Ruby-crowned Kinglet M M M

Ruddy Duck B

Rufous Hummingbird M

Rufous-crowned Sparrow R

Rusty Blackbird M

Sage Sparrow M M

Sage Thrasher M M

Sandhill Crane M

Savannah Sparrow M

Say's Phoebe R R R R

Sedge Wren V

Scott's Oriole B

*R = resident species, B = breeding species, M = migratory species, V = vagrant species.
450

Species

NPS 

(2015)* CBC*

Giroir 

(2001)*

RMBO 

Monitoring*

Semipalmated Sandpiper M

Sharp-shinned Hawk R R R

Snow Goose M

Song Sparrow R R R

Sora B

Spotted Sandpiper B

Spotted Towhee R R R R

Steller's Jay R R

Swainson's Hawk B B

Swamp Sparrow M

Townsend's Solitaire R R

Townsend's Warbler M

Tree Swallow M M M

Trumpeter Swan V

Tundra Swan M

Turkey Vulture R R R R

Varied Thrush V

Vaux's Swift M

Vermilion Flycatcher V

Vesper Sparrow R R R

Violet-green Swallow R R R

Virginia Rail B

Virginia's Warbler R R R

Warbling Vireo R R R

Western Bluebird R R R R

Western Grebe B

Western Kingbird R R

Western Meadowlark R R R

Western Screech-owl M R

Western Scrub-Jay R R R R

Western Tanager R R R

Western Wood-Pewee R R

White-breasted Nuthatch R R R R

White-crowned Sparrow R R

White-throated Sparrow M

White-throated Swift R R R

White-winged Dove B

White-winged Scoter V

Wild Turkey R R

*R = resident species, B = breeding species, M = migratory species, V = vagrant species.
451

Species

NPS 

(2015)* CBC*

Giroir 

(2001)*

RMBO 

Monitoring*

Williamson's Sapsucker B

Willow Flycatcher M M

Wilson's Snipe B

Wilson's Warbler M

Wood Duck M

Yellow Warbler M M

Yellow-bellied Sapsucker V

Yellow-breasted Chat M

Yellow-headed Blackbird B

Yellow-rumped Warbler M M M

Zone-tailed Hawk V

# of Resident Species 84 77 50 52

# of Migratory Species 46 66 0 10

# of Breeding Species 26 30 10 15

# of Vagrant Species 5 18 0 0

Total Species 161 191 60 77

*R = resident species, B = breeding species, M = migratory species, V = vagrant species.

453

Appendix K. Annotated list of species-related name changes and adjustments made 

by SMUMN GSS to the Grand Junction CBC data.

 Observations that were not specific to a bird species (e.g., vireo sp., Buteo sp.) were omitted 

from analysis.

 Records of the American eared grebe were merged with records of the eared grebe, as these 

are both accepted common names of Podiceps nigricollis.

 Records of the American green-winged teal were merged with records of the green-winged 

teal, as these are both accepted common names of Anas crecca.

 Records of the American magpie were merged with records of the black-billed magpie, as 

both are common names of Pica hudsonia.

 Records of the American merganser were merged with records of the common merganser, as 

both are common names of Mergus merganser.

 Records of the American raven were combined with records of the common raven, as both 

are common names of Corvus corax.

 Records of the Batchelder’s woodpecker were treated as observations of the downy 

woodpecker; both species share the Latin name Picoides pubescens.

 Records of the common barn owl were merged with records of the barn owl, as both are 

common names of Tito alba.

 Records of the common crow were merged with records of the American crow, as both are 

common names of Corvus brachyrhynchos.

 Dark-eyed junco, gray-headed dark-eyed junco, dark-eyed junco (Oregon race), pink-sided 

dark-eyed junco, Shuteldt’s junco, and slate-sided dark-eyed junco observations were treated 

as one species (Junco hyemalis) (Sibley and Ahlquist 1983).

 Records of the English sparrow were merged with records of the house sparrow, as both are 

common names of Passer domesticus.

 Records of Gambel’s partridge were merged with records of Gambel’s quail, as both are 

common names for Callipepla gambelii.

 Records of Gambel’s sparrow were merged with records of white-crowned sparrow, as both 

are common names for Zonotrichia leucophrys.

 Records of Harlan’s hawk were merged with records of red-tailed hawks, as there is 

uncertainty regarding speciation of the Harlan’s hawk. Both records were treated using the 

Latin name Buteo jamaicensis.

 Records of the marsh hawk were merged with records of the northern harrier, as both are 

common names for Circus cyanus.

 Records of mockingbird were merged with records of the northern mockingbirds, as both 

refer to the species Mimus polyglottos.
454

 Records of the mountain song sparrow were merged with records of the song sparrow, as 

both are common names of Melospiza melodia.

 Observations for northern flicker, red-shafted northern flicker, and yellow-shafted northern 

flicker were merged and renamed to Colaptes auratus. Yellow- and red-shafted flickers were 

previously believed to be separate species, but genetic analysis has classified them as one 

species (Sibley and Ahlquist 1983).

 Records of the pale goldfinch were merged with records of the American goldfinch, as both 

are/were common names of Spinus tristis.

 Records of the pigeon hawk were merged with records of the merlin, as both common names 

referred to Falco columbarius.

 Records of plain titmouse were merged with records of oak titmouse, as both are common 

names for Baeolophus inornatus.

 Records of the robin were merged with records of the American robin, as both are common 

names of Turdus migratorius.

 Records of the rock pigeon were merged with records of the rock dove, as both are accepted 

common names of Columba livia.

 Records of the rufous-sided towhee were treated as records of the spotted towhee, as spotted 

towhee is the preferred common name for Pipilo maculatus. The rufous-sided towhee was 

previously the accepted common name for this species before the eastern towhee and the 

spotted towhee were identified as separate species.

 All forms of the snow goose (e.g., blue-form) were treated as a single species, Chen 

caerulescens.

 Records of the sparrow hawk were merged with records of the American kestrel, as both 

represent common names of Falco sparverius.

 Records of ‘starling’ and ‘common starling’ were treated as records for the European starling, 

Sturnus vulgaris.

 Observations of American pipit and water pipit were merged as these are both accepted 

common names for Anthus rubescens.

 Records of the common snipe and Wilson’s snipe were merged, as these are both common 

names of Gallinago delicate.

 Records of the tree sparrow and the American tree sparrow were merged, as these are both 

common names of Spizella arborea.

 Records of the green-backed heron were merged with records of the green heron, as both are 

/were common names of Butorides virescens.

 Records of the gray shrike were merged with records of the northern shrike, as both refer to 

Lanius excubitor.
455

 Yellow-rumped warbler, Audubon’s yellow-rumped warbler, and Myrtle yellow-rumped 

warbler observations were treated as one species (Dendroica coronata) (Sibley and Ahlquist 

1983, Hunt and Flaspohler 1998).

Literature Cited

Hunt, P. D., and D. J. Flaspohler. 1998. Yellow-rumped warbler (Setophaga coronata), in The Birds 

of North America Online (A. Poole, Ed.). Cornell Lab of Ornithology, Ithaca, New York.

Sibley, C. G., and J. E. Ahlquist. 1983. The phylogeny and classification of birds based on data of 

DNA-DNA hybridization. Pages 245-92 in Johnston, R. F. (ed). 1983. Current Ornithology, Vol. 

1. Plenum Publishing, New York, New York

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