National Park Service

U.S. Department of the Interior

Natural Resource Stewardship and Science

Grant-Kohrs Ranch National Historic Site

Natural Resource Condition Assessment

Natural Resource Report NPS/GRKO/NRR—2015/1071
ON THE COVER

View from the back porch of the Grant-Kohrs Ranch House, looking northwest

Photograph by: Kathy Allen, SMUMN GSS
Grant-Kohrs Ranch National Historic Site 

Natural Resource Condition Assessment

Natural Resource Report NPS/GRKO/NRR—2015/1071

Kathy Allen

Sarah Gardner

Kevin Benck

Andy Nadeau

Lonnie Meinke

Thomas Walker

Mike Komp

Keaton Miles

Barry Drazkowski

GeoSpatial Services

Saint Mary’s University of Minnesota

890 Prairie Island Road 

Winona, Minnesota 55987

October 2015

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 

interest and applicability to a broad audience in the National Park Service and others in natural 

resource management, including scientists, conservation and environmental constituencies, and the 

public.

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

about natural resources and related topics concerning lands managed by the National Park Service. 

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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reporting of the data, and whose background and expertise put them on par technically and 

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

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

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screen readers, please email irma@nps.gov.

Please cite this publication as:

Allen, K., S. Gardner, K. Benck, A. Nadeau, L. Meinke, T. Walker, M. Komp, K. Miles, and B. 

Drazkowski. 2015. Grant-Kohrs Ranch National Historic Park: Natural resources condition 

assessment. Natural Resource Report NPS/GRKO/NRR—2015/1071. National Park Service, Fort 

Collins, Colorado.

NPS 451/130317, October 2015
iii

Contents

Page

Figures...................................................................................................................................................ix

Tables...................................................................................................................................................xv

Photos..................................................................................................................................................xix

Appendices..........................................................................................................................................xxi

Executive Summary..........................................................................................................................xxiii

Acknowledgments..............................................................................................................................xxv

Acronyms and Abbreviations...........................................................................................................xxvii

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

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

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

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

2.1.2 Geographic Setting ...........................................................................................................6

2.1.3 Visitation Statistics...........................................................................................................7

2.2 Natural Resources.....................................................................................................................7

2.2.1 Ecological Units and Watersheds.....................................................................................7

2.2.2 Resource Descriptions......................................................................................................8

2.2.2 Resource Issues Overview..............................................................................................11

2.3 Resource Stewardship ............................................................................................................16

2.3.1 Management Directives and Planning Guidance............................................................16

2.3.2 Status of Supporting Science..........................................................................................16

Literature Cited........................................................................................................................18

Chapter 3 Study Scoping and Design ..................................................................................................21

3.1 Preliminary Scoping ...............................................................................................................21

3.2 Study Design ..........................................................................................................................22

3.2.1 Indicator Framework, Focal Study Resources and Indicators........................................22
iv

Contents (continued)

Page

3.2.2 General Approach and Methods.....................................................................................25

Literature Cited........................................................................................................................31

Chapter 4 Natural Resource Conditions...............................................................................................33

4.1 Grazing ...................................................................................................................................34

4.1.1 Description .....................................................................................................................34

4.1.2 Measures.........................................................................................................................36

4.1.3 Reference Conditions/Values.........................................................................................36

4.1.4 Data and Methods...........................................................................................................36

4.1.5 Current Condition and Trend..........................................................................................38

4.1.6 Sources of Expertise.......................................................................................................45

4.1.7 Literature Cited...............................................................................................................46

4.2 Riparian Area..........................................................................................................................49

4.2.1 Description .....................................................................................................................49

4.2.2 Measures.........................................................................................................................53

4.2.3 Reference Conditions/Values.........................................................................................53

4.2.4 Data and Methods...........................................................................................................54

4.2.5 Current Condition and Trend..........................................................................................56

4.2.6 Sources of Expertise.......................................................................................................74

4.2.7 Literature Cited...............................................................................................................75

4.3 Pastures and Hayfields ...........................................................................................................79

4.3.1 Description .....................................................................................................................79

4.3.2 Measures.........................................................................................................................81

4.3.3 Reference Conditions/Values.........................................................................................81

4.3.4 Data and Methods...........................................................................................................82

4.3.5 Current Condition and Trend..........................................................................................82
v

Contents (continued)

Page

4.3.6 Sources of Expertise.......................................................................................................92

4.3.7 Literature Cited...............................................................................................................93

4.4 Uplands (Grasslands, Non-irrigated)......................................................................................96

4.4.1 Description .....................................................................................................................96

4.4.2 Measures.........................................................................................................................97

4.4.3 Reference Conditions/Values.........................................................................................97

4.4.4 Data and Methods...........................................................................................................98

4.4.5 Current Condition and Trend..........................................................................................99

4.4.6 Sources of Expertise.....................................................................................................105

4.4.7 Literature Cited.............................................................................................................106

4.5 Birds .....................................................................................................................................109

4.5.1 Description ...................................................................................................................109

4.5.2 Measures.......................................................................................................................110

4.5.3 Reference Conditions/Values.......................................................................................110

4.5.4 Data and Methods.........................................................................................................110

4.5.5 Current Condition and Trend........................................................................................112

4.5.6 Sources of Expertise.....................................................................................................133

4.5.7 Literature Cited.............................................................................................................134

4.6 Periphyton.............................................................................................................................137

4.6.1 Description ...................................................................................................................137

4.6.2 Measures.......................................................................................................................138

4.6.3 Reference Conditions/Values.......................................................................................138

4.6.4 Data and Methods.........................................................................................................139

4.6.5 Current Condition and Trend........................................................................................140

4.6.6 Sources of Expertise.....................................................................................................142
vi

Contents (continued)

Page

4.6.7 Literature Cited.............................................................................................................143

4.7 Aquatic Macroinvertebrates .................................................................................................146

4.7.1 Description ...................................................................................................................146

4.7.2 Measures.......................................................................................................................146

4.7.3 Reference Conditions/Values.......................................................................................146

4.7.4 Data and Methods.........................................................................................................147

4.7.5 Current Condition and Trend........................................................................................148

4.7.6 Sources of Expertise.....................................................................................................152

4.7.7 Literature Cited.............................................................................................................153

4.8 Air Quality............................................................................................................................156

4.8.1 Description ...................................................................................................................156

4.8.2 Measures.......................................................................................................................156

4.8.3 Reference Conditions/Values.......................................................................................158

4.8.4 Data and Methods.........................................................................................................158

4.8.5 Current Condition and Trend........................................................................................160

4.8.6 Sources of Expertise.....................................................................................................167

4.8.7 Literature Cited.............................................................................................................168

4.9 Water Quality .......................................................................................................................171

4.9.1 Description ...................................................................................................................171

4.9.2 Measures.......................................................................................................................173

4.9.3 Reference Conditions/Values.......................................................................................176

4.9.4 Data and Methods.........................................................................................................177

4.9.5 Current Condition and Trend........................................................................................178

4.9.6 Sources of Expertise.....................................................................................................192

4.9.7 Literature Cited.............................................................................................................193
vii

Contents (continued)

Page

4.10 Soundscape.........................................................................................................................197

4.10.1 Description .................................................................................................................197

4.10.2 Measures.....................................................................................................................197

4.10.3 Reference Conditions/Values.....................................................................................197

4.10.4 Data and Methods.......................................................................................................198

4.10.5 Current Condition and Trend......................................................................................198

4.10.6 Sources of Expertise ...................................................................................................203

4.10.7 Literature Cited...........................................................................................................204

4.11 Viewscape...........................................................................................................................205

4.11.1 Description .................................................................................................................205

4.11.2 Measures.....................................................................................................................206

4.11.3 Reference Conditions/Values.....................................................................................206

4.11.4 Data and Methods.......................................................................................................206

4.11.5 Current Condition and Trend......................................................................................208

4.11.6 Sources of Expertise ...................................................................................................227

4.11.7 Literature Cited...........................................................................................................228

4.12 Hydrology...........................................................................................................................229

4.12.1 Description .................................................................................................................229

4.12.2 Measures.....................................................................................................................230

4.12.3 Reference Conditions/Values.....................................................................................230

4.12.4 Data and Methods.......................................................................................................231

4.12.5 Current Condition and Trend......................................................................................231

4.12.6 Sources of Expertise ...................................................................................................243

4.12.7 Literature Cited...........................................................................................................244

4.13 Soils....................................................................................................................................247
viii

Contents (continued)

Page

4.13.1 Description .................................................................................................................247

4.13.2 Measures.....................................................................................................................248

4.13.3 Reference Conditions/Values.....................................................................................249

4.13.4 Data and Methods.......................................................................................................250

4.13.5 Current Condition and Trend......................................................................................253

4.13.6 Sources of Expertise ...................................................................................................266

4.13.7 Literature Cited...........................................................................................................267

Chapter 5 Discussion .........................................................................................................................273

5.1 Component Data Gaps..........................................................................................................273

5.2 Component Condition Designations.....................................................................................274

5.3 Park-wide Condition Observations.......................................................................................278

5.4 Literature Cited................................................................................................................281

Appendices.........................................................................................................................................283
ix

Figures

Page

Figure 1. Location of GRKO in Deer Lodge Valley.............................................................................6

Figure 2. Main historic buildings and features, including the Visitor Center and main 

entrance to the park................................................................................................................................7

Figure 3. Landscape components of GRKO. ........................................................................................8

Figure 4. Change in mean annual temperature and mean spring temperature in the GRKO 

region between 1951 and 2006 ............................................................................................................13

Figure 5. Change in mean annual precipitation in the GRKO region between 1951 and 

2006......................................................................................................................................................13

Figure 6. Projected change in mean annual temperature and mean annual precipitation 

in the GRKO region by 2050 ...............................................................................................................14

Figure 7. Projected change in mean summer temperature and mean summer

precipitation in the GRKO region by 2050..........................................................................................14

Figure 8. Projected change in mean annual temperature and mean annual precipitation 

in the GRKO region by 2100 scenario.................................................................................................15

Figure 9. Projected change in mean summer temperature and mean summer

precipitation in the GRKO region by 2100..........................................................................................15

Figure 10. Projected change in mean annual aridity and mean summer aridity by 2100, as 

predicted by the change in AET:PET ratio ..........................................................................................16

Figure 11. Grant Kohrs Ranch National Historical Park natural resource condition 

assessment framework. ........................................................................................................................24

Figure 12. Location of grazed fields where Range Condition was calculated and ROMN 

sampling sites where moderate (MM) or moderate to extreme (MX) evidence of 

disturbance/erosion were observed. .....................................................................................................39

Figure 13. Columbian ground squirrel and burrow numbers at GRKO, 2009-2014 ..........................44

Figure 14. Riparian vegetation community distribution in the northern portion of GRKO................50

Figure 15. Riparian vegetation community distribution in the southern portion of GRKO ...............51

Figure 16. Locations of natural cottonwood trees (e.g., not planted) within GRKO as of 

2002......................................................................................................................................................52

Figure 17. Locations of four creeks sampled in 2014 using the NRCS Riparian 

Assessment Method. ............................................................................................................................55
x

Figures (continued)

Page

Figure 18. Extent of wetlands (polygons) within GRKO according to the NWI database .................61

Figure 19. Extent of linear wetlands within GRKO according to the NWI database .........................63

Figure 20. Irrigated pastures and hayfields of GRKO. .......................................................................80

Figure 21. Forage yield (tons/acre) by field and overall for GRKO from 2008-2013........................84

Figure 22. ROMN sampling sites in GRKO hayfields, 2009-2012, that met the reference 

condition of no more than 1% invasive species, met the reference condition when lower 

priority species such as dandelion were excluded, and that did not meet the reference 

condition with or without lower priority species included ..................................................................87

Figure 23. Location of upland grassland vegetation types within GRKO. .........................................97

Figure 24. Upland grasslands with Range Condition determinations, and ROMN 

sampling locations where soil/site stability indicator observations have been recorded...................101

Figure 25. Approximate extent of the CBC survey area (purple circle) including GRKO...............111

Figure 26. Species richness values for each of the survey methods utilized by Atkinson 

and Smucker (2013)...........................................................................................................................113

Figure 27. Species richness values during each year of GRKO’s annual Christmas Bird 

Count..................................................................................................................................................114

Figure 28. Species richness values reported from each of the surveys completed in 

GRKO. ...............................................................................................................................................115

Figure 29. Survey points in riparian and grassland habitats that were used during the 

Giroir and Beason (2005) avian inventory of GRKO. .......................................................................117

Figure 30. Survey areas during the Larson (2011) grassland and agricultural avian 

surveys. ..............................................................................................................................................118

Figure 31. The two point count transects that were established in GRKO by Atkinson 

and Smucker (2013)...........................................................................................................................119

Figure 32. Number of species observed in each habitat type during the three major 

surveys in GRKO...............................................................................................................................120

Figure 33. Number of individuals observed in each habitat type during the three major 

surveys in GRKO...............................................................................................................................120

Figure 34. Abundance of species of special concern observed during the Giroir and 

Beason (2005) survey of GRKO........................................................................................................122
xi

Figures (continued)

Page

Figure 35. Number of species and number of individual species of special concern 

observed during the annual GRKO Christmas Bird Count, 2006-2012. ...........................................125

Figure 36. Number of species of special concern observed during each of the major 

survey efforts in GRKO.....................................................................................................................126

Figure 37. Number of individuals of special concern observed during each of the major 

survey efforts in GRKO. The red line indicates the average number of individuals 

observed during a survey (75)............................................................................................................127

Figure 38. Avian abundance during the annual GRKO CBC, 2006-2012........................................131

Figure 39. The location of the sample reach in relation to the USGS stream gage ..........................139

Figure 40. The location of the sample reach in relation to the USGS stream gage ..........................147

Figure 41. Locations of the air quality monitoring stations nearest to GRKO. ................................158

Figure 42. Annual average concentrations of sulfate (SO4), nitrate (NO3), and ammonium 

(NH4) (mg/L) in precipitation in GRKO, 1984-2012 (NADP monitoring site MT07)......................161

Figure 43. Annual 4th highest 8-hour maximum ozone (O3) concentrations (ppb) in the 

GRKO region, 2011-2014..................................................................................................................162

Figure 44. Annual particulate matter (PM2.5) concentrations (weighted annual mean) near 

GRKO, 2008-2013.............................................................................................................................163

Figure 45. Annual average visibility in the GRKO region, 2001-2008 ............................................164

Figure 46. Grant-Kohrs location map with water quality sampling locations. .................................172

Figure 47. Mean 7-day maximum water temperature for water years, 2001-2010 at Deer 

Lodge USGS gauge............................................................................................................................179

Figure 48. Seasonal variation in specific conductance at a GRKO sampling site, 1982-

2004....................................................................................................................................................180

Figure 49. Seasonal variation in copper concentration, 1982-2004.................................................188

Figure 50. Seasonal variation in arsenic concentration, 1982-2004 .................................................188

Figure 51. Palmer Hydrologic Drought Index 1997-2007 ................................................................190

Figure 52. The location of the sampling site in relation to the Ranch House and GRKO 

Visitor Center.....................................................................................................................................198

Figure 53. Sound pressure level graphs from the months of July and January at GRKO.................200
xii

Figures (continued)

Page

Figure 54. Location of the airport, railroad, and interstate in relation to GRKO..............................201

Figure 55. Locations of the three areas with the most visible change in development 

between 1947 and 2013. ....................................................................................................................206

Figure 56. Locations of the 10 selected viewing areas in GRKO.....................................................207

Figure 57. Composite viewshed using vistas in GRKO....................................................................208

Figure 58. Landcover classification of visible areas in and around GRKO......................................210

Figure 59. Internal viewshed analysis. Visible landcover change in GRKO between 2001 

and 2011.............................................................................................................................................211

Figure 60. External viewshed analysis. Visible land cover change in areas surrounding 

GRKO between 2001 and 2011 .........................................................................................................213

Figure 61. Aerial photos of Area A in 1947, 1972, and 2013...........................................................214

Figure 62. Aerial photos of Area B in 1947, 1972, and 2013...........................................................215

Figure 63. Aerial photos of Area C in 1947, 1972, and 2013 ...........................................................216

Figure 64. The location of each selected photo point in GRKO, and the direction each 

photo is facing....................................................................................................................................217

Figure 65. Location of Clark Fork River in western Montana..........................................................229

Figure 66. Location of Clark Fork River at GRKO. .........................................................................230

Figure 67. Hydrograph of mean monthly discharge rates of the Clark River from USGS 

Gage Station 12324200 located near Deer Lodge, MT. ....................................................................232

Figure 68. Daily discharge rates (Oct 1978 - present) of the Clark River from USGS 

Gage Station 12324200 located near Deer Lodge, MT. ....................................................................232

Figure 69. Flow monitoring points along Cottonwood Creek ..........................................................234

Figure 70. Flow rates for Cottonwood Creek (21 April through 19 October 2009). ........................235

Figure 71. Flow rate in the Westside Ditch 2 ft. parshall flume within GRKO for the 

2012 season........................................................................................................................................235

Figure 72. 1980-2010 normal precipitation for Deer Lodge, MT (Cooperative Weather 

Station Deer Lodge 3W) ....................................................................................................................237
xiii

Figures (continued)

Page

Figure 75. Depth to groundwater for selected monitoring wells at GRKO ...................................... 239

Figure 76. Palmer Hydrologic Drought Index (PHDI) for Montana................................................. 240

Figure 77. The Clark Fork floodplain and slickens areas at GRKO. ................................................ 247

Figure 78. GRKO soil map and description of soil map units. ......................................................... 251

Figure 79. Map of soil pH in 2000 by sampling location. ................................................................ 254

Figure 80. GRKO hayfields with soil sample test results. ................................................................ 255

Figure 81. Soil nutrient levels from sampled GRKO hayfields in 2008 and 2013. .......................... 256

Figure 82. Soil microbial biomass and community richness at GRKO both decline as 

metal contamination increases. .......................................................................................................... 260

Figure 83. Map of soil arsenic concentrations in 2000 by sampling location ................................... 262

Figure 84. Tetratech soil pit locations. .............................................................................................. 264

xv 

Tables 

Page

Table 1. 30-year climate normals (1981-2010) for the Deer Lodge 3W weather station 

near GRKO ............................................................................................................................................ 6

Table 2. ROMN Vital Signs selected for monitoring in GRKO ......................................................... 17

Table 3. Scale for a measure’s Significance Level in determining a components overall 

condition. ............................................................................................................................................. 26

Table 4. Scale for Condition Level of individual measures. ............................................................... 26

Table 5. Description of symbology used for individual component assessments. .............................. 27

Table 6. Plant species that decrease or increase in density with light to moderate cattle 

grazing .................................................................................................................................................. 35

Table 7. Attributes and indicators used in Rangeland Health Assessments. ....................................... 38

Table 8. Range Condition scores and classes (based on percent composition) and 

similarity indices (based on dry weight) for six grazed locations at GRKO in 2014 .......................... 39

Table 9. Indicators of disturbance and/or erosion documented in GRKO’s grazed lands. ................. 40

Table 10. Number of ground squirrels observed in grazed fields throughout GRKO 

during May surveys .............................................................................................................................. 43

Table 11. Riparian vegetation communities described by Hansen et al. (1995) that occur 

within GRKO and their equivalent map unit name in Rice et al.’s (2012) vegetation 

mapping and classification system for GRKO ..................................................................................... 54

Table 12. Dominant plant species (in descending order) in the Clark Fork and 

Cottonwood Creek riparian zones, as documented by Rice and Ray (1984) ....................................... 57

Table 13. Percent cover composition of dominant, co-dominant, or community type 

indicator species in the GRKO riparian area in 1993 and 2000. .......................................................... 58

Table 14. The fifteen most dominant plant species in riparian area monitoring plots in 

2009 and 2010 ...................................................................................................................................... 59

Table 15. Area of NWI wetland polygons (ha and ac) within GRKO ................................................ 60

Table 16. Length of NWI linear wetlands (m) within GRKO ............................................................. 62

Table 17. Extent of primarily riparian/wetland vegetation communities within GRKO, 

according to Thompson et al. (1995) and Rice et al. (2012) ................................................................ 64

Table 18. NRCS Riparian Health Assessment scores for No Name, Johnson, 

Cottonwood, and Taylor Creeks .......................................................................................................... 65
xvi

Tables (continued) 

Page

Table 19. Greenline Assessment results for transects on the Clark Fork in GRKO, 

September 2014. .................................................................................................................................. 66

Table 20. Greenline Assessment results for transect on the Cottonwood Creek in GRKO, 

September 2014 ................................................................................................................................... 67

Table 21. Stability classes and successional status for community types documented 

during the GRKO Greenline Assessment ............................................................................................ 67

Table 22. Ecological effect size (A) calculations and significance (p) for riparian 

communities at GRKO ......................................................................................................................... 68

Table 23. Invasive plant species documented in the Clark Fork riparian area by Rice 

(2003b). ................................................................................................................................................ 69

Table 24. Productivity estimates (without irrigation) by rangeland site and soil map unit ................. 81

Table 25. Beef cattle nutrient requirements (in % of dry matter) from NRC (2000). ......................... 82

Table 26. Forage production in GRKO hayfields, 2008-2013 ............................................................ 82

Table 27. GRKO hayfields with large infested areas identified during the 2003 nonnative plant survey ............................................................................................................................... 85

Table 28. Invasive species abundance by ROMN sampling location ................................................. 85

Table 29. Hay nutrient analysis ........................................................................................................... 90

Table 30. Typical plant species composition of silty 10-14” P.Z. rangeland sites.............................. 98

Table 31. Range Condition scores and classes (based on percent composition) and 

similarity indices (based on dry weight) for four upland grasslands at GRKO in 2014 .................... 100

Table 32. Indicators of disturbance and/or erosion documented in GRKO’s upland 

grasslands ........................................................................................................................................... 102

Table 33. Invasive plant species documented in upland grasslands by Rice (2003). ........................ 103

Table 34. Species richness and abundance values for the two habitat types that were 

sampled during the Giroir and Beason (2005) survey of GRKO in 2004. ......................................... 117

Table 35. Species richness and abundance values for the two habitat types that were 

sampled during the Atkinson and Smucker (2013) survey of GRKO in 2013. ................................. 119

Table 36. Number of individuals identified as species of special concern observed during 

the Larson (2011) survey of GRKO. .................................................................................................. 123
xvii

Tables (continued) 

Page

Table 37. Number of individuals identified as species of special concern observed during 

the Atkinson and Smucker (2013) survey of GRKO. ........................................................................ 124

Table 38. Annual abundance of species of special concern during the GRKO Christmas 

Bird Count, 2006-2012. ..................................................................................................................... 125

Table 39. Sediment increaser taxa used in the sediment increaser model for the Rocky 

Mountain Ecoregion ........................................................................................................................... 138

Table 40. Sediment increaser model metrics and thresholds (i.e., reference assessment 

points) according to Montana DEQ standards ................................................................................... 138

Table 41. Sediment increaser model metrics for the Clark Fork River at GRKO in 2008 

and 2009 ............................................................................................................................................. 140

Table 42. Macroinvertebrate metrics with ecoregion thresholds (Schweiger et al. 2014) 

and reference condition assessment points. ....................................................................................... 147

Table 43. The RIVPACS metrics from the Clark Fork River at GRKO during the 

summers of 2008 and 2009 ................................................................................................................ 148

Table 44. Core macroinvertebrate metrics for the Clark Fork River in GRKO during the 

summers of 2008 and 2009 ................................................................................................................ 149

Table 45. MMI and MVFP metric values and impairment class recorded at the Deer 

Lodge Station in 2011 ........................................................................................................................ 150

Table 46. National Park Service Air Resources Division air quality index values. .......................... 158

Table 47. Applicable reference standards for selected parameters of surface water at 

GRKO. ............................................................................................................................................... 177

Table 48. Applicable reference points for selected metals in surface water at GRKO ..................... 177

Table 49. Water temperatures (°C) in the Clark Fork at Deer Lodge, 2011 ..................................... 179

Table 50. Specific conductance (μS/cm) in the Clark Fork at Deer Lodge, 2011 ............................ 181

Table 51. pH values for the Clark Fork at Deer Lodge, 2011 ........................................................... 181

Table 52. Dissolved oxygen measurements for the Clark Fork at Deer Lodge, 2011 ..................... 182

Table 53. Nutrient levels (mg/L) of surface waters in GRKO .......................................................... 182

Table 54. Nutrient levels (mg/L) in groundwater at GRKO ............................................................. 183
xviii

Tables (continued) 

Page

Table 55. Nutrient levels (mg/L) in surface waters at GRKO, 2008-2010 ....................................... 183

Table 56. Nutrient levels (mg/L) in the Clark Fork at Deer Lodge, 2011 ........................................ 184

Table 57. Dissolved and total trace elements (μg/L) in surface water at GRKO .............................. 184

Table 58. Trace elements (μg/L) in groundwater at GRKO. ............................................................. 185

Table 59. Summary of water physiochemistry for the Clark Fork River in Grant-Kohrs 

Ranch National Historic Site, 2008-2010 .......................................................................................... 187

Table 60. 2011 NLCD viewable landcover composition in GRKO .................................................. 211

Table 61. NLCD landcover change in GRKO between 2001 and 2011 ........................................... 212

Table 62. Discharge data from the Clark Fork River (Deer Lodge USGS station 

12324200) near GRKO. ..................................................................................................................... 233

Table 63. Stream flow in Cottonwood Creek. All results are in cms with cfs equivalents 

in parenthesis ..................................................................................................................................... 234

Table 64. 1980-2010 normals for Deer Lodge 3W ........................................................................... 236

Table 65. Soil stability classes according to methods described by Herrick et al. (2005) ................ 252

Table 66. pH measurements from GRKO. ........................................................................................ 253

Table 67. Organic matter content measurements from GRKO. ........................................................ 255

Table 68. Nutrient measurements from GRKO. ................................................................................ 257

Table 69. Soil aggregate stability measurements from GRKO. ........................................................ 258

Table 70. Bulk density measurements (g/cm3) from GRKO. ............................................................ 258

Table 71. Microbial respiration measurements (μM/m2/s) from plots at GRKO .............................. 259

Table 72. Wildlife soil criteria for selected wildlife and livestock; metal levels are given 

in mg/kg ............................................................................................................................................. 260

Table 73. Mean metal contaminant levels in GRKO soils in mg/kg ................................................. 261

Table 74. Identified data gaps or needs for the featured components. .............................................. 273

Table 75. Summary of current condition and condition trend for featured NRCA 

components. ....................................................................................................................................... 275

Table 76. Description of symbology used for individual component assessments. .......................... 277
xix 

Photos 

Page

Photo 1. Rear yard of the Grant-Kohrs Ranch House, circa 1890. ....................................................... 5

Photo 2. The Grant-Kohrs ranch house ................................................................................................. 7

Photo 3. The Clark Fork River in GRKO .............................................................................................. 8

Photo 4. Native grasses growing on northern slope of foothill in GRKO upland grassland ................. 9

Photo 5. Cattle breeds managed on GRKO, including Hereford, Shorthorn, and Longhorn .............. 10

Photo 6. Bull trout ............................................................................................................................... 10

Photo 7. Clark Fork River bank with visible metal tailings approximately one to two feet 

below the vegetation layer. .................................................................................................................. 12

Photo 8. Cattle grazing at GRKO ........................................................................................................ 34

Photo 9. Longhorn cattle grazing in a GRKO hayfield ....................................................................... 35

Photo 10. Columbian ground squirrel. ................................................................................................ 43

Photo 11. The Clark Fork riparian area within GRKO. ...................................................................... 49

Photo 12. A slickens area within the GRKO riparian zone ................................................................. 52

Photo 13. Moose in the GRKO riparian area, captured by a park wildlife camera in 

August 2013. ........................................................................................................................................ 70

Photo 14. On left, a beaver dam on Cottonwood Creek in GRKO. On right, beaver 

damage to a large cottonwood at GRKO after protective wire broke and fell off ............................... 71

Photo 15. Historic haying operations at the ranch, circa 1937. ........................................................... 79

Photo 16. An irrigated hayfield at GRKO with introduced pasture grasses ........................................ 80

Photo 17. Canada thistle. ..................................................................................................................... 88

Photo 18. Upland grassland within GRKO ......................................................................................... 96

Photo 19. Bobolink. ........................................................................................................................... 109

Photo 20. Willow flycatcher .............................................................................................................. 111

Photo 21. Riparian habitat along the Clark Fork River in GRKO..................................................... 115

Photo 22. Osprey nest on top of an electrical pole in GRKO ........................................................... 128
xx

Photos (continued) 

Page

Photo 23. Benthic, soft-bodied algae in Cottonwood Creek in GRKO.............................................137

Photo 24. ROMN sampling in the Clark Fork at GRKO ..................................................................139

Photo 25. Caddisfly species that is common in the Clark Fork River at GRKO ..............................146

Photo 26. View from Grant Kohrs Ranch on a clear, high visibility day..........................................156

Photo 27. Upper Clark Fork River at GRKO....................................................................................171

Photo 28. Water clarity in a tributary to Clark Fork within GRKO..................................................174

Photo 29. Metal tailings buried feet under the riparian top soil........................................................176

Photo 30. Sound monitoring equipment in the field at GRKO. ........................................................197

Photo 31. Westward view of the mountains from a trail on the southeast side of GRKO ................205

Photo 32. The view from comparative point 12 in the early 1900s, 2002, and 2014........................218

Photo 33. The view from comparative point 13 in the early 1900s, 2002, and 2014........................219

Photo 34. The view from comparative point 22 in the early 1900s, 2002, and 2014........................220

Photo 35. The view from comparative point 12 in the early 1900s, 2002, and 2014........................221

Photo 36. The view from vista RE 20 in 2002 and 2014 ..................................................................222

Photo 37. The view from vista G 01 in 2002 and 2014.....................................................................222

Photo 38. The view from vista M 13 in 2002 and 2014....................................................................223

Photo 39. The view from vista O 16 in 2002 and 2014.....................................................................223

Photo 40. The view from vista N 22 in 2002 and 2014.....................................................................224

Photo 41. The view from vista P 13 in 2002 and 2014 .....................................................................224

Photo 42. The view from vista E 01 in 2002 and 2014.....................................................................225

Photo 43. An unvegetated slickens area along the Clark Fork in GRKO; note the white 

crust of heavy metals salts .................................................................................................................248
xxi

Appendices 

Page

Appendix A. Non-native plants species documented in GRKO (NPS 2014). ..................................283

Appendix B. Ecological Effect Size Examples.................................................................................285

Appendix C. Plant species documented throughout Montana in the 19 riparian 

community types that occur within GRKO by Hansen et al. (1995), in GRKO riparian 

areas by Rice and Hardin (2002) or Rice and Smith (2011)..............................................................288

Appendix D. NRCS riparian health assessment worksheets for GRKO...........................................306

Appendix E. Invasive Species Monitoring .......................................................................................321

Appendix F. Species of conservation concern that have been identified in GRKO. ........................359

Appendix G. Bird species identified as present or probably present in GRKO................................362

Appendix H. Species observed in GRKO based on each survey method during Atkinson 

and Smucker (2013)...........................................................................................................................369

Appendix I. Species distribution and abundance during the Giroir and Beason (2005) 

survey in GRKO. ...............................................................................................................................372

Appendix J. Species abundance during the Larson (2011) survey of the 

grassland/agricultural habitats in GRKO. ..........................................................................................374

Appendix K. Species distribution and abundance during the Atkinson and Smucker 

(2013) survey in GRKO.....................................................................................................................376

Appendix L. NLCD landcover class composition and change (2001-2011) within GRKO 

external viewshed...............................................................................................................................378

xxiii

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 

Grant-Kohrs Ranch National Historic Site (GRKO) 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 GRKO. The final project framework contains 13 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 GRKO 

resource managers, NPS Rocky Mountain Network staff, and outside experts, when appropriate.

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

academic 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 3 of the 13 components (23%) due to these data gaps.

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

were determined to be in good condition: pastures and hayfields, birds, periphyton, aquatic 

macroinvertbrates, air quality, and viewscape. However, periphyton and aquatic macroinvertbrates 

scores were at the edge of the good condition range, and any small decline in the community could 
xxiv

shift them into the moderate concern range. Of the components in good condition, only viewscape 

showed a declining trend, due to increasing development outside the park. The remaining four 

components (riparian area, water quality, soundscape, and soils) were of moderate concern. Water 

quality showed a slightly improving trend while soundscape showed a declining trend, due to 

increased traffic (air, train, and road). No components were considered to be of significant concern. 

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 GRKO. Those 

of primary concern include invasive exotic plant species, historic mining contamination, and 

associated Superfund remediation activities. 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, as well as its cultural landscape.
xxv

Acknowledgments 

We acknowledge Grant-Kohrs Ranch National Historic Site staff (present and past) for the technical 

expertise provided during scoping, through multiple stages of review, and via phone and email; 

specifically, Jason Smith, Jeff Johnson, Chris Ford, and Eric Mason. Bret Olson and Peter Rice 

assisted with project scoping, data gathering, and document review. Rocky Mountain Inventory and 

Monitoring Network staff, including Mike Britten and Billy Schweiger, offered logistical insight and 

critical review of interim documents. Donna Shorrock, Intermountain Region NRCA Coordinator, 

and Jeff Albright, Natural Resource Condition Assessment Coordinator, provided program guidance. 

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

xxvii

Acronyms and Abbreviations

AUM - Animal Unit Month

BLM – Bureau of Land Management

CAA - Clean Air Act

CBC - Christmas Bird Count

CGS - Columbian Ground Squirrel

CLR - Cultural Landscape Report

dB - Decibels

DEM – Digital Elevation Model

DO - Dissolved Oxygen 

EPA – Environmental Protection Agency

GIS – Geographic Information System

GRKO - Grant-Kohrs Ranch National Historic Site

HCPC - Historic Climax Plant Community

I&M - Inventory and Monitoring

IMPROVE - Interagency Monitoring of Protected Visual Environments Program

IMR - Intermountain Region

MMI - Multimetric Indices

MSU - Montana State University

MT DEQ - Montana Department of Environmental Quality

NAAQS - National Ambient Air Quality Standards

NADP - National Atmospheric Deposition Program

NCDC - National Climatic Data Center

NLCD – National Land Cover Dataset

NPS - National Park Service

NPS ARD – National Park Service Air Resources Division
xxviii

NRCA – Natural Resource Condition Assessment

NRCS - Natural Resources Conservation Service

NRM EPMT - Northern Rocky Mountain Exotic Plant Management Team 

NVC – National Vegetation Classification

NWI - National Wetland Inventory

PLFA - phospholipid fatty acid

PM – Particulate Matter

P.Z. - Precipitation Zone

RIVPACS - River Invertebrate Prediction and Classification

ROMN - Rocky Mountain Network

SMUMN GSS – Saint Mary’s University of Minnesota, Geospatial Services 

TSS - Total Suspended Sediment

USDA - United States Department of Agriculture

USFS – United States Forest Service 

USFWS – United States Fish and Wildlife Service 

USGS – United States Geological Survey

VCSS - Vegetation Composition, Structure, and Soils

WCS - Weighted Condition Score
1

Chapter 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 issueand 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 GIS (map) products;

4

• summarize key findings by park areas; and5

• follow national NRCA guidelines and standards for study design and reporting products.

 

1 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-on 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

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 

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 decisionmaking, 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, 

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

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

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

report on government accountability measures.

7 In 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 a NRCA project for each of the approximately 

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

http://nature.nps.gov/water/nrca/index.cfm.

 

6 An 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

Chapter 2 Introduction and Resource Setting

2.1 Introduction

2.1.1 Enabling Legislation

Grant-Kohrs Ranch National Historic Site (GRKO) was established by President Richard Nixon on 

25 August 1972:

Be it enacted by the Senate and House of Representatives of the United States of America in 

Congress assembled that in order to provide an understanding of the frontier cattle era of the 

Nation’s history, to preserve Grant-Kohrs Ranch, and to interpret the nationally significant 

values thereof for the benefit and inspiration of present and future generations, the Secretary 

of the Interior is hereby authorized to designate not more than two thousand acres in Deer 

Lodge Valley, Powell County, Montana, for the establishment as the Grant-Kohrs Ranch 

National Historic Site. (PL 92-406)

The ranch at GRKO was founded in 1862 by John Grant and was later purchased by Conrad Kohrs,

who operated the ranch from 1866-1920. On 19 December 1960, GRKO was designated as a 

National Historic Landmark

(John Milner Associates et 

al. 2004). GRKO is 

considered an exceptional 

demonstration of the open 

range cattle industry that 

was present in the 

American West during the 

19th and early 20th 

centuries (John Milner 

Associates et al. 2004). The 

1972 historic site legislation 

created a boundary that 

included 558 ha (1,378 ac). 

In 1988, an additional 48.6 

ha (120 ac) were purchased 

from Conrad Kohrs-Warren 

and added to the park under public law (PL 91-646).

On 11 July 2003, Grant-Kohrs Ranch-Warren Ranch historic district was listed on the National 

Register of Historic Places by the Montana State Historic Preservation Office for its importance to 

the state of Montana under Criteria A and C in the areas of agriculture and architecture (John Milner 

Associates et al. 2004). The GRKO historic district boundary encompasses all of the land within the 

National Historic Landmark boundary and also includes the Warren Hereford Ranch. GRKO 

continues to be an actively operating ranch with ongoing activities facilitated by the NPS that 

Photo 1. Rear yard of the Grant-Kohrs Ranch House, circa 1890 

(Grant-Kohrs Ranch NHS Archives 6280H).
6

include: livestock grazing, hay production, irrigation, fencing, and noxious weed control (John 

Milner Associates et al. 2004).

2.1.2 Geographic Setting

GRKO is located in the intermountain 

grassland region of western Montana, 

along the Clark Fork of the Columbia 

River in Deer Lodge Valley (John Milner 

Associates et al. 2004; Figure 1). The 

ranch is positioned just northwest of the 

city of Deer Lodge in Powell County. 

When GRKO was established by

Congress in 1972, the NPS was given 

permission to acquire no more than 810 ha 

(2,000 ac) of land in Deer Lodge Valley. 

After the initial founding of the park, land 

acquisitions and scenic easements were 

purchased throughout the 1980s and 

1990s, increasing the park from its 

original 88 ha (217 acres) to 655 ha (1,618

acres) (John Milner Associates et al.

2004). 

The Deer Lodge Valley has a semi-arid 

inland mountain climate, with average 

annual high and low temperatures of 

13.3°C (55.9°F) and -3.1°C (26.4°F)

degrees, respectively (NCDC 2015; Table 1). On average, 27 cm (10.6 in) of precipitation occurs per 

year, with the majority during the months of May and June (NCDC 2015).

Table 1. 30-year climate normals (1981-2010) for the Deer Lodge 3W weather station near GRKO

(NCDC 2015).

Jan

FebMar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Annual

Average Temperature (°C)

Max 1.2 3.2 8.2 12.9 17.3 21.6 26.8 26.7 21.1 14.1 5.9 0.1 13.3

Min -11.4 -10.5 -6.3 -3.2 0.7 4.5 6.6 5.5 1.2 -3.4 -8.4 -12.7 -3.1

Average Precipitation (cm)

Total 0.6 0.8 1.0 1.8 4.8 5.2 4.2 3.3 2.5 1.4 0.7 0.6 27.0

Figure 1. Location of GRKO in Deer Lodge Valley.
7

2.1.3 Visitation Statistics 

From 2010 to 2014, GRKO received

an average of 19,775 recreational 

visitors per year (NPS 2015a). 

During that 5-year period, visitation 

peaked in 2010 when just over

22,000 people visited. In 2012, 

17,095 people visited GRKO, which 

is the second lowest number during 

the 36 years of tracking recreational 

visitation (there were 16,663 visitors 

in 2008) (NPS 2015a).

The main activities that attract 

visitors to GRKO are the 

interpretive programs. Interpretive 

uses are focused within the Home 

Ranch Complex, which contains 

interpretive exhibits coupled with 

the surrounding landscape (Photo 

2); this provides context for visitors 

to acquire an understanding of 

historic ranching operations (Figure 

2). There are a large variety of 

interpretive programs, including: 

demonstrations by cowboys and 

ranch hands of the different skills 

needed in ranching (e.g., cattle

wrangling and haying), tours of the 

main ranch house, interpretive tours 

in horse-drawn wagons, and 

costumed interpretation of ranch life 

(NPS 2015b).

2.2 Natural Resources

2.2.1 Ecological Units and Watersheds 

The ranch lies within the Northern Rocky Mountains Physiographic Province, which contains recent 

alluvial and glacial deposits in addition to rocks of Precambrian to Tertiary age (Thornberry-Ehrlich 

2007). GRKO also falls within the Environmental Protection Agency’s (EPA) Middle Rockies Level 

III Ecoregion. According to the EPA (2010, p. 4), intermontane valleys in this ecoregion “are grassand/or shrub-covered and contain a mosaic of terrestrial and aquatic fauna that is distinct from the 

Photo 2. The Grant-Kohrs ranch house (photo by Sarah 

Gardner, SMUMN GSS 2013).

Figure 2. Main historic buildings and features, including the 

Visitor Center and main entrance to the park.
8

nearby mountains. Many mountain-fed, perennial streams occur and differentiate the intermontane 

valleys from the Northwestern 

Great Plains.”

GRKO sits within the Clark Fork 

River-Deer Lodge Watershed. The 

Clark Fork River (Photo 3) and its 

tributaries are responsible for 

depositing the rich alluvial soils 

found on the ranch that are a fertile 

mixture of sand, clay, and organic 

matter (John Milner Associates et 

al. 2004). The topography, rich 

soils, and abundant fresh water 

provide the necessary natural 

resources to support domestic and 

ranching activities (John Milner 

Associates et al. 2004). 

2.2.2 Resource Descriptions

GRKO’s greatest resource is its 

historical significance and its 

accurate portrayal of its history to 

the public, along with the 

preservation of the landscape. It 

should be noted that the small 

size of GRKO may limit 

management’s influence over the 

natural resources because not all 

of the resources that fall within 

the park boundaries stay within 

park boundaries.

GRKO supports a number of 

vegetation communities and a 

variety of plant species. 

Originally, this area was 

dominated by native grasses with 

trees and shrubs along the riparian 

areas (Rice et al. 2012). Today, 

the ranch can be divided into 

three broad vegetation 

communities: upland grasslands, 

Photo 3. The Clark Fork River in GRKO (photo by Sarah 

Gardner, SMUMN GSS 2013).

Figure 3. Landscape components of GRKO.
9

irrigated pastures and hayfields, and riparian areas (Figure 3). The upland grasslands are still 

dominated by native species and are not irrigated, while the pastures and hayfields contain primarily 

introduced grasses to provide forage for livestock (Rice et al. 2012). The riparian areas include the 

Clark Fork floodplain, several tributaries, and a small number of isolated wetlands. These areas

support herbaceous species (grasses and forbs) as well as shrubs and trees. 

According to the NPS (2014), 

341 plant species have been 

documented in the park. 

Approximately 25% of these 

species are non-native, 

although many were 

introduced for ranching 

purposes and are now 

considered part of the cultural 

landscape of the park (John 

Milner Associates et al. 2004).

Native grasses present include 

bluebunch wheatgrass 

(Pseudoroegneria spicata),

western wheatgrass 

(Pascopyrum smithii), needleand-thread (Hesperostipa comata), and blue grama (Bouteloua gracilis) (Photo 4; Rice et al. 2012).

Common introduced grasses are smooth brome (Bromus inermis), timothy (Phleum pratense),

Kentucky bluegrass (Poa pratensis), and redtop (Agrostis stolonifera). The riparian areas support 

several species of willow (Salix spp.) and isolated stands of black cottonwood (Populus balsamifera

ssp. trichocarpa) (Rice et al. 2012).

Since the park is a working ranch, cattle, horses, and ranch cats are the most commonly seen animals 

at GRKO. The cattle population consists of three cow breeds: Hereford, Shorthorn, and Longhorn

(Photo 5; NPS 2013). GRKO is also abundant in wildlife, with at least 35 species of mammals that 

either pass through seasonally or live on the ranch year round (NPS 2013). These species include 

white-tailed deer (Odocoileus virginianus), moose (Alces alces), coyote (Canis latrans), beaver

(Castor canadensis), and many small mammals (NPS 2013). 

Photo 4. Native grasses growing on northern slope of foothill in 

GRKO upland grassland (photo by Kathy Allen, SMUMN GSS 2013).
10

Photo 5. Cattle breeds managed on GRKO, including Hereford, Shorthorn, and Longhorn (from left to 

right) (NPS photo).

A wide variety of bird species also inhabit the ranch at various times of year. According to NPS 

(2014), 230 bird species are classified as “present” or “probably present” in GRKO. Some common 

resident birds include bald eagles (Haliaeetus leucocephalus), chickadees (Poecile spp.), and blackbilled magpies (Pica pica). Common breeding birds are great blue heron (Ardea herodias), red-tailed 

hawk (Buteo jamaicensis), and several duck species (family Anatidae) (NPS 2013). Osprey (Pandion 

haliaetus) are uncommon, but have nested on a power pole inside the park. 

The Clark Fork River and its 

associated creeks are home to 11 

fish species, both native and nonnative (NPS 2014). Common 

native species in GRKO include 

suckers (Catostomus spp.), mottled 

sculpin (Cottus bairdii), and

redside shiner (Richardsonius

balteatus). The Clark Fork River is 

also critical habitat for bull trout 

(Salvelinus confluentus), a 

federally threatened species (Photo 

6), although none have been 

documented within the park 

recently (NPS 2011a). The bull trout is just one species that has been adversely affected by polluted 

waters; however, habitat conditions seem to be improving due to remediation efforts along the Clark 

Fork (described in Section 2.2.2 below) (Eric Mason, former GRKO Superfund Manager, oral 

communication, 30 October 2013). The three non-native species found in the park are rainbow trout

(Oncorhynchus mykiss), brown trout (Salmo trutta), and brook trout (Salvelinus fontinalis) (NPS 

2014). Trout are an important park resource, as fishing opportunities in the Clark Fork have been 

known to draw visitors to the ranch. 

The riparian areas also provide habitat for reptiles, amphibians, and aquatic macroinvertebrates. 

Reptiles such as the painted turtle (Chrysemys picta) and common garter snake (Thamnophis sirtalis) 

are found at the park. Amphibian species documented in the park include the western toad (Anaxyrus 

boreas), and Columbia spotted frog (Rana luteiventris) (NPS 2013).

Photo 6. Bull trout (NPS photo).
11

2.2.2 Resource Issues Overview

Effectively allocating resources associated with sustaining a working ranch in an environmentally 

responsible manner, while simultaneously conducting public education through interpretation as a 

National Historic Site provides many challenges. A working ranch can be described as a selfsustaining agricultural business with the intent to generate profit from the production of livestock 

(John Milner Associates et al. 2004). The GRKO ranch is unlike a privately-owned ranch, since its 

purpose is for public education and preservation of the historic ranching lifestyle, rather than 

generating a profit from livestock production (NPS 1993). In addition to the difficulties that are 

associated with maintaining a working cattle ranch, there are difficulties that arise when presenting 

an interpretation of the history of the western U.S. range cattle industry. For example, the ranch must 

operate efficiently, but the animals must also be visible to park visitors while still remaining within 

the necessary constraints of public safety, animal welfare, and responsible land use (John Milner 

Associates et al. 2004). Further challenges are posed by trying to meet ranching and interpretive 

objectives while preventing further “wear and tear” on the various historic features (e.g., fences, 

barns, other outbuildings) as well as natural community processes (John Milner Associates et al.

2004).

Much of the vegetation found on the ranch consists of non-native species of grasses and forbs, many 

of which were introduced as hay species and pasture grasses. Although these intentionally-introduced 

species are non-native, they are considered “contributing features” on the cultural landscape, as they 

represent the history of ranching in the area (John Milner Associates et al. 2004). Other non-native 

species are considered invasive and have become a significant concern at GRKO. These include 

spotted knapweed (Centaurea stoebe), leafy spurge (Euphorbia esula), yellow toadflax (Linaria 

vulgaris), Canada thistle (Cirsium arvense), and field bindweed (Convolvulus arvensis) (Rice 2003, 

Wood and Rew 2005). These invasive species can alter plant community composition and ecological 

processes (e.g., water and nutrient cycling) and contribute to biodiversity and habitat losses (Lacey et 

al. 1989, NPS 2008). At GRKO, invasive plants also threaten the cultural landscape the park was set 

aside to protect, and can reduce forage quality (Manier et al. 2011). A full list of non-native species 

documented in GRKO is included as Appendix A. Species classified as noxious weeds by the state of 

Montana or identified as priority species for control by the Northern Rocky Mountains Exotic Plant 

Management Team (NPS 2011b) are noted in this appendix.

The GRKO riparian area is located within the Upper Clark Fork River Superfund Site, which was 

designated by the EPA in 1992 (NPS 2007). The upper reaches and tributaries of the Clark Fork 

River contain heavy metals, such as arsenic, cadmium, copper, zinc, and lead as a result of historic 

mining, milling, and smelting activities occurring in Anaconda and Butte, Montana (MT DEQ 2013). 

Mining for gold and silver in the Upper Clark Fork (south of GRKO) began on a small scale in the 

1860s and 1870s (Horstman 1984). However, the completion of a transcontinental railroad line in 

1883 allowed heavy equipment to be transported into the area and mining activities intensified 

(Horstman 1984). The wastes from these mining activities, called “tailings”, accumulated along the 

stream banks where mining occurred. The flood of 1908, which is the largest recorded flood event 

for the area, washed these tailings downstream and into GRKO. According to Thornberry-Ehrlich 

(2007), there is a 10 km (6 mi) stretch of river in the Deer Lodge River Valley with as much as 
12

704,000 m3 (24,862,00 ft3

) of contaminated sediment in a 274 ha (677 ac) area. These metal tailings, 

now mixed in with the soils on the floodplain, pose a threat to wildlife and human health (Photo 7; 

MT DEQ 2013). In the coming years, Superfund remediation efforts will remove approximately 

296,110 m3 (387,297 yd3

) of soil to an average depth of 0.7 m (2.3 ft) from the GRKO riparian zone

in order to restore the health of area (Jeff Johnson, GRKO CERCLA Project Manager, written 

communication, 17 October 2014). These areas will be backfilled with clean soil to support native 

plant revegetation and return the floodplain to a 2-year flood level (NPS 2007).

Photo 7. Clark Fork River bank with visible metal tailings approximately one to two feet below the 

vegetation layer (photo by Sarah Gardner, SMUMN GSS 2013).

Global climate change is expected to impact the entire U.S. during this century, although the 

expected changes vary across the country. Since 1951, the regional climate around GRKO has shown 

little change; annual mean temperatures have remained relatively stable, although mean spring 

temperatures have increased slightly (Figure 4; PRISM 2014). Mean annual precipitation also 

increased slightly (Figure 5; PRISM 2014). Over the next century, mean annual precipitation around 

GRKO is predicted to remain stable or increase slightly (2-3% by 2100), but summer precipitation is 

actually predicted to decrease (~10% by 2050, ~19% by 2100) (Figure 7, Figure 9; Maurer et al. 

2007). Annual mean temperature is expected to increase by 2.2-2.8°C (4-5°F) by 2050 and 3.3-3.9°C 

(6-7°F) by 2100 (Figure 6, Figure 8; Maurer et al. 2007). Even though annual precipitation is 

predicted to increase slightly in the area, the expected warmer temperatures will increase evaporation 

rates and plant transpiration (i.e., plant water use). This is predicted to result in greater aridity, 

meaning overall drier conditions, particularly in the summer (Figure 10; Maurer et al. 2007).
13

 

Figure 4. Change in mean annual temperature (left) and mean spring temperature (right) in the GRKO 

region between 1951 and 2006 (PRISM 2014).

Figure 5. Change in mean annual precipitation in the GRKO region between 1951 and 2006 (PRISM 

2014).
14

 

Figure 6. Projected change in mean annual temperature (left) and mean annual precipitation (right) in 

the GRKO region by 2050 (Maurer et al. 2007). Projections based on an ensemble average (E-50) 

circulation model and the A1B (medium) emissions scenario.

 

Figure 7. Projected change in mean summer temperature (left) and mean summer precipitation (right) in 

the GRKO region by 2050 (Maurer et al. 2007). Projections based on an ensemble average (E-50) 

circulation model and the A1B (medium) emissions scenario.
15

 

Figure 8. Projected change in mean annual temperature (left) and mean annual precipitation (right) in 

the GRKO region by 2100 (Maurer et al. 2007). Projections based on an ensemble average (E-50) 

circulation model and the A1B (medium) emissions scenario.

 

Figure 9. Projected change in mean summer temperature (left) and mean summer precipitation (right) in 

the GRKO region by 2100 (Maurer et al. 2007). Projections based on an ensemble average (E-50) 

circulation model and the A1B (medium) emissions scenario.
16

 

Figure 10. Projected change in mean annual aridity (left) and mean summer aridity (right) by 2100, as 

predicted by the change in AET:PET ratio (Maurer et al. 2007). Projections based on an ensemble 

average (E-50) circulation model and the A1B (medium) emissions scenario.

2.3 Resource Stewardship

2.3.1 Management Directives and Planning Guidance

GRKO’s general management plan (NPS 1993, p. 3) established three management objectives for the 

park:

• To provide opportunities for the visitor to understand the cattle industry and its evolution 

from the open range of the mid-1860s, to mechanized feedlot operations that began in the

1930s and extended until establishment of the park in the 1970s.

• To maintain historic structures, buildings, objects, and landscapes in such a manner as to

complement the ranch’s primary purpose and enhance visitor understanding and appreciation 

of cattle ranch operations.

• To manage natural resources in such a manner as to compliment the historic context of the 

ranch and cattle ranching operations.

GRKO also strives towards sustainable ranching, which “maintains and improves grassland and 

riparian health, supports vigorous livestock and wildlife populations that result in economic success, 

educational opportunity and community benefit beyond a single generation” (NPS 2011c).

2.3.2 Status of Supporting Science 

The Rocky Mountain Network (ROMN) 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 
17

Vital Signs. In 2007, the ROMN completed and released a Vital Signs Monitoring Plan (Britten et al. 

2007). Table 2 shows the network vital signs selected for monitoring in GRKO.

Table 2. ROMN Vital Signs selected for monitoring in GRKO (Britten et al. 2007). Bold indicates Vital 

Signs being monitored by a network park, another NPS program, or another federal or state agency, 

using other funding. 

Category ROMN Vital Signs

Air and Climate Weather and climate 

Geology & Soils Stream/ river channel characteristics, soil function and 

dynamics (grasslands)

Water Water chemistry, surface water dynamics, aquatic 

macroinvertebrates and algae, groundwater dynamics

Biological Integrity Invasive/exotic plants, grassland vegetation

Landscapes (Ecosystem Pattern 

and Processes) Land cover and use

In addition to the ROMN, researchers from several universities in the region (e.g., University of 

Montana in Missoula and Montana State University in Bozeman) have contributed to the scientific 

knowledge base for GRKO. This work provided valuable information for the NRCA.
18

Literature Cited

Britten, M., E. W. Schweiger, B. Frakes, D. Manier, and D. Pillmore. 2007. Rocky Mountain 

Network Vital Signs monitoring plan. Natural Resource Report NPS/ROMN/NRR-2007/010. 

National Park Service, Fort Collins, Colorado.

Environmental Protection Agency (EPA). 2010. Primary distinguishing characteristics of Level III 

and IV Ecoregions of the continental United States. 

http://www.epa.gov/wed/pages/ecoregions/level_iii_iv.htm (accessed 17 February 2015).

Horstman, M. C. 1984. Historical events associated with the Upper Clark Fork drainage. Montana 

Department of Fish, Wildlife, and Parks, Helena, Montana.

John Milner Associates, Rivanna Archaeological Consulting, Susan Maxman and Partners 

Architects. 2004. Cultural landscape report. National Park Service, Deer Lodge, Montana.

Lacey, J. R., C. B. Marlow, and J. R. Lane. 1989. Influence of spotted knapweed (Centaurea 

maculosa) on surface runoff and sediment yield. Weed Technology 3(4):627-631.

Manier, D., D. Shorrock, E. W. Schweiger, I. Ashton, B. Frakes, M. Britten, D. Pillmore, and J. 

Burke. 2011. Rocky Mountain Network vegetation composition structure and soils monitoring 

protocol: Small park grasslands, shrublands, and woodlands; Version 1.0. Natural Resource 

Report NPS/ROMN/NRR-2011/383. National Park Service, Fort Collins, Colorado.

Maurer, E. P., L. Brekke, T. Pruitt, and P. B. Duffy. 2007. Base climate projections (downscaled): 

2050 mid century (2040-2069), 2100 end century (2070-2099) (12km resolution). 

http://www.climatewizard.org/ (accessed 28 July 2014).

Montana Department of Environmental Quality (MT DEQ). 2013. Clark Fork River operable unit. 

Montana.gov official website. http://deq.mt.gov/fedsuperfund/cfr.mcpx (accessed 15 January 

2014).

National Climatic Data Center (NCDC). 2015. 1981-2010 normals for Deer Lodge 3W. 

http://www.ncdc.noaa.gov/cdo-web/datatools/normals (accessed 17 February 2015).

National Park Service (NPS). 1993. Grant-Kohrs Ranch National Historic Site: Environmental 

impact statement for a general management plan and development concept plan. National Park 

Service, Deer Lodge, Montana.

National Park Service (NPS) 2007. Federal restoration plan for Grant-Kohrs Ranch National Historic 

Site. National Park Service, Deer Lodge, Montana.

National Park Service (NPS). 2008. Exotic plant management team: 2008 annual report. National 

Park Service, Biological Resources Management Division, Fort Collins, Colorado.
19

National Park Service (NPS). 2011a. Fisheries biological assessment and evaluation (bull trout). 

Appendix Q in Northern Rocky Mountains invasive plant management plan and environmental 

assessment. National Park Service, Fort Collins, Colorado.

National Park Service (NPS). 2011b. Northern Rocky Mountains invasive plant management plan. 

National Park Service, Fort Collins, Colorado.

National Park Service (NPS) 2011c. Grant-Kohrs Ranch: Sustainable ranching. 

http://www.nps.gov/grko/learn/management/upload/Sustainable-Ranching-2-28-11.pdf (accessed 

17 February 2015).

National Park Service (NPS). 2013. Animals. http://www.nps.gov/grko/naturescience/animals.htm

(accessed 18 December 2013).

National Park Service (NPS). 2014. NPSpecies. http://irma.nps.gov/NPSpecies/Search/ (accessed 18

November 2014).

National Park Service (NPS). 2015a. Visitor use statistics. https://irma.nps.gov/Stats/Reports/Park 

(accessed 17 February 2015).

National Park Service (NPS). 2015b. Grant-Kohrs National Historic Site: Guided tours. 

http://www.nps.gov/grko/planyourvisit/guidedtours.htm (accessed 17 Februrary 2015).

PRISM Climate Group. 2014. Climate data: United States (Lower 48 and Conterminous) past 50 

years (1951-2006) (4km resolution). http://www.prism.oregonstate.edu/historical/ (accessed 28 

July 2014).

Rice, P. M. 2003. Discussion outline for Grant-Kohrs Ranch weed management and restoration. 

National Park Service unpublished report, Deer Lodge, Montana.

Rice, P. M., E. W. Schweiger, W. Gustafson, C. Lea, D. Manier, D. Shorrock, B. Frakes, and L. 

O’Gan. 2012. Vegetation classification and mapping project report, Grant-Kohrs Ranch National 

Historic Site. Natural Resource Report NPS/ROMN/NRR-2012/589. National Park Service, Fort 

Collins, Colorado.

Thornberry-Ehrlich, T. 2007. Grant-Kohrs Ranch National Historic Site geologic resource evaluation 

report. Natural Resource Report NPS/NRPC/GRD/NRR—2007/004. National Park Service, 

Denver, Colorado.

Wood, S. D., and D. L. J. Rew. 2005. Non-native plant survey at Grant-Kohrs Ranch National 

Historic Site. Montana State University, Bozeman, Montana. 

21

Chapter 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 GRKO resource management 

team and ROMN 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 and a scope of work document were created cooperatively between 

the NPS and SMUMN GSS.

3.1 Preliminary Scoping

A preliminary scoping meeting was held on 29-31 October 2013. At this meeting, SMUMN GSS and 

NPS staff confirmed that the purpose of the GRKO 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 GRKO managers. Certain constraints were placed on this NRCA, including 

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 GRKO 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 GRKO 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: GRKO resource staff, the NPS Integrated 

Resource Management Application (IRMA) website, Inventory and Monitoring Vital Signs

program, and available third-party sources. The ROMN report will provide a resource 

assessment and summary of pertinent data evaluated through this project.
22 

• 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.

3.2 Study Design

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 GRKO 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 GRKO. 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 
23 

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 primarily adapted from the ROMN Vital Signs monitoring plan (Britten 

et al. 2007). 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 ROMN project and finalize the 

framework of key resources to be assessed. 

The NRCA framework was finalized in January 2014 following acceptance from NPS resource staff. 

It contains a total of 13 components (Figure 11) 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.
24

Figure 11. Grant Kohrs Ranch National Historical Park natural resource condition assessment framework.

Component Measures Stressors Reference Condition

Grazing Range condition/Similarity index, rangeland health (17 indicators) Drought, invasive species (unpalatable), drought, climate change, 

management actions, Columbian ground squirrels Range/Ecological site descriptions

Ecological Communities

Riparian area Species richness, species composition, extent of wetlands, NRCS riparian health 

assessment, Greenline assessment, ecological effect size (A)

Located within and adjacent to Superfund site (to be remediated in the 

next few years), invasive species, climate change, wildlife browsing, 

beaver activity, overgrazing, flooding, irrigation practices

Hansen et al. 1995

Pastures/ hayfields 

(improved/irrigated)

Hay & forage production (tons/acre), abundance of invasives vs. desired species, hay 

nutrient analysis

Invasive species, drought, climate change, improper grazing (amount, 

timing, distribution), irrigation practices, unplanned fire, Columbian 

ground squirrels, grasshopper outbreaks 

Production estimates from soil survey, < 

1% invasives, beef cattle nutrient 

requirements

Uplands (grasslands, nonirrigated) Range condition/Similarity index), rangeland health (17 indicators), ecological effect 

size (A)

Invasive species, drought, climate change, improper grazing (amount, 

timing, distribution), unplanned or extreme fire, Columbian ground 

squirrels, grasshopper outbreaks 

Range/ecological site descriptions, 

Mueggler & Stewart (1980)

Birds

Birds Species richness, distribution (riparian, upland), abundance, status of species of 

special concern

Contamination from Superfund site and other mining activity (and 

remediation); grazing/ranching practices (disturbance), climate change Undetermined

Freshwater Biota

Periphyton Sediment increaser model metrics (percent relative abundance, probablity of 

impairment)

Contamination from Superfund site, point & non-pont sources, 

dewatering, climate change (water temps, flow rates & timing) MT DEQ criteria

Aquatic Macroinvertebrates RIVPACS modeling (observed to expected [O:E] and Bray Curtis metrics), MMI 

(multimetric indices)

Contamination from Superfund site, point & non-pont sources, 

dewatering, climate change (water temps, flow rates & timing)

From Schweiger et al. (2014), based on 

MT DEQ criteria

Air Quality Sulfate deposition, nitrogen deposition, ozone, particulate matter (PM 2.5), visibility Burning (agricultural, riparian), climate change; air pollution could be a 

threat to historical buildings NPS ARD air quality index values

Water Quality Water temperature, specific conductance, pH, total suspended sediment, dissolved 

oxygen, coliform bacteria, nutrients, metals

Mining contamination, fertilizer, point and nonpoint source discharge, 

drought, dewatering MT DEQ criteria

Soundscape Characteristics of sounds - types of sounds, sound levels (loudness)

Increased airport traffic, increased train traffic, increased interstate traffic 

(semis), Superfund remediation, ranch construction activities, increased 

development outside park

Types of sounds - keep the percentage of 

new sounds (using NPS 2012 as a 

baseline) that are non-contributing below 

10%; Sound levels - below 60 dBA for noncontributing sounds

Viewscape

Change in land use cover type inside the park (internal viewscape), change in land 

use cover type outside the park (external viewscape), change at selected photo 

points

Gravel mining south of park, invasive species, Superfund remediation 

activities, development, conspicuousness of non-contributing features

Maintain viewscapes contributing to 

cultural landscape significance (see 

cultural landscape report)

Geologic and Hydrologic

Hydrology (surface and 

groundwater dynamics)

Stream discharge (amount, timing), irrigation flow inputs, timing and amount of 

precipitation, depth to groundwater

Climate change (precipitation), drought, dewatering, human alteration of 

river (removal of contamination ponds upstream)

Hydrograph conditions (1980-2012), 

historic precipitation records for Deer 

Lodge, Woessner & Johnson (2001) 

(groundwater)

Soils Soil aggregate stability, chemistry (nutrients & organic matter), soil microbial 

composition (and activity/respiration), bulk density

Erosion, contamination from Superfund site, remediation activities, 

improper grazing, improper irrigation, removal of vegetation

NRCS and Montana State Extension 

guidelines

Environmental Quality

Physical Characteristics

Disturbance Regimes

Ecosystem Extent and Function

Biotic Composition

GRKO NRCA Framework 

Natural Resource Condition Assessment Framework
25 

3.2.2 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 GRKO 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 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 GRKO and 

the ROMN. 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 3. 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.
26 

Table 3. 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 4). This is based on 

all the available literature and data reviewed for the component, as well as communications with park 

and outside experts.

Table 4. 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: 

WWW = 

∑ Si ∗ i

# oo mmmmmmmm

i=1

3 ∗ ∑ Si

# oo mmmmmmmm

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 = 0.67-1.0). Table 5 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 
27 

component. For example, condition is not assessed when no recent data or information are available, 

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 5. Description of symbology used for individual component assessments.

Condition Status Trend in Condition Confidence in 

Assessment

Warrants 

Significant Concern Condition is Improving High

Warrants 

Moderate Concern Condition is Unchanging Medium

Resource is in Good 

Condition Condition is Deteriorating Low

An open (uncolored) circle indicates that current condition is unknown or indeterminate; 

this condition status is typically associated with unknown trend and low confidence 

(explanation is required if a trend symbol or a medium/high confidence band is shown) 
28 

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. 

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 GRKO and ROMN 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 literature 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 GRKO 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. 
29 

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 

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 or a GIS metadata file. 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. 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. 
30 

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. 

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. 

Literature Cited

This is a list of formal citations for literature or datasets used in the analysis and assessment of 

condition for the resource component. Note, citations used in appendices referenced in each section 

(component) of Chapter 4 are listed in that component’s “Literature Cited” section. 
31 

Literature Cited

Britten, M., E. W. Schweiger, B. Frakes, D. Manier, and D. Pillmore. 2007. Rocky Mountain 

Network Vital Signs monitoring plan. Natural Resource Report NPS/ROMN/NRR-2007/010. 

National Park Service, Fort Collins, Colorado. 

Great Lakes Environmental Indicators Project (GLEI). 2010. Glossary, Stressor. 

http://glei.nrri.umn.edu/default/glossary.htm (accessed 31 January 2013). 

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.

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.

33 

Chapter 4 Natural Resource Conditions 

This chapter presents the background, analysis, and condition summaries for the 13 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 11): 

4.1 Grazing 

4.2 Riparian Area 

4.3 Pastures and Hayfields 

4.4 Uplands (Grasslands, Non-irrigated) 

4.5 Birds 

4.6 Periphyton 

4.7 Aquatic Macroinvertebrates 

4.8 Air Quality 

4.9 Water Quality 

4.10 Soundscape 

4.11 Viewscape 

4.12 Hydrology 

4.13 Soils
34 

4.1 Grazing

4.1.1 Description

Grazing is a key component of the cultural experience that GRKO was set aside to preserve. Cattle 

were first brought to the Deer Lodge Valley in 1857, when Johnny Grant overwintered his herd in the 

vicinity of what is now GRKO (John Milner Associates et al. 2004). Grazing has shaped the 

landscape over time; ditches were dug to irrigate pastures and hayfields and non-native grasses were 

introduced in an effort to improve forage for livestock (John Milner Associates et al. 2004, Rice et al. 

2012). Currently, approximately 332 ha (820 ac) of the irrigated pastures and hayfields are utilized 

by park managers for grazing, as well as 95 ha (235 ac) of the upland grasslands (Jason Smith, 

GRKO Natural Resource Specialist, written communication, January 2015). Fields are grazed on a 

rotational basis to prevent overgrazing and protect other park resources (e.g., vegetation, wildlife). 

Photo 8. Cattle grazing at GRKO (Photo by Kathy Allen, SMUMN GSS 2013).

Native plant species respond differently to even light grazing by cattle. Some species decrease in 

abundance or density with grazing, whereas others will increase. Common grassland species in 

GRKO that typically decrease with grazing include bluebunch wheatgrass (Pseudoroegneria spicata) 

and green needlegrass (Nassella viridula), whereas species such as western wheatgrass (Pascopyrum 

smithii) and needle-and-thread (Hesperostipa comata) tend to increase (NRCS 1982). Additional 

“increasers” and “decreasers” are listed in Table 6.
35 

Table 6. Plant species that decrease or increase in density with light to moderate cattle grazing (NRCS 

1982). 

Decreasers Increasers

Scientific name Common name Scientific name Common name

Pseudoroegneria spicata bluebunch wheatgrass Hesperostipa comata needle-and-thread

Nassella viridula green needlegrass Pascopyrum smithii western wheatgrass

Festuca campestris rough fescue Carex spp. sedges

Achnatherum hymenoides Indian ricegrass Festuca idahoensis Idaho fescue

Glyceria spp. mannagrasses Cornus spp. dogwood

Catabrosa aquatica brookgrass Tetradymia spp. horsebrush

Deschampsia cespitosa tufted hairgrass Rosa spp. rose

Elymus caninus bearded wheatgrass Potentilla fruticosa shrubby cinquefoil

Elymus cinereus basin wildrye native perennial forbs

Carex nebrascensis Nebraska sedge

Krascheninnikovia lanata winterfat

Atriplex nuttallii Nuttall saltbush

Vicia americana American vetch

Grazing has the potential to benefit the ecosystems in which it occurs. At low levels, grazing can 

increase plant primary productivity and improve forage quality (Briske et al. 2008). The manure 

produced by grazing animals contributes to nutrient cycling and can increase soil fertility (Metera et 

al. 2010). Grazing can also create and maintain habitat for a variety of wildlife species, including 

native ungulates, grassland birds, and invertebrates (Severson and Urness 1994, Derner et al. 2009, 

Metera et al. 2010). With grassland birds, a group of species that have declined in recent decades, 

grazing can be managed to increase vegetation heterogeneity, creating the range of habitats required 

by many species to complete their breeding cycles (Derner et al. 2009). 

The number and type 

of livestock maintained 

at the ranch varies, 

depending on available 

resources and 

economic viability 

(John Milner 

Associates et al. 2004). 

GRKO’s cattle herd, 

which remains on-site 

year-round, presently 

includes three breeds: 

Herefords, Longhorns, 

and Shorthorns (NPS 

2013; Photo 9). These 

three breeds were all 

raised on the ranch 

historically (John Milner Associates et al. 2004). As of 1 June 2014, the herd included 47 cows, 17 

Photo 9. Longhorn cattle grazing in a GRKO hayfield (Photo by Sarah Gardner, 

SMUMN GSS 2013).
36 

yearlings (seven heifers and 10 steers), 13 two-year old steers, and three bulls (Smith, written 

communication, January 2015). The park also keeps three saddle horses (quarter horses) and two 

draft horse teams (Belgian and Percheron) that perform ranch management tasks, such as hay 

harvest, and contribute to educational programs. 

A pasture or range site’s grazing potential can be estimated in “animal unit months” (AUMs). An 

AUM is defined as the amount of forage required to feed one “animal unit” for 1 month (Metz 2007). 

An “animal unit” is typically one 454 kg (1,000 lb) cow and a calf up to 6 months old, or their 

equivalent. The Natural Resources Conservation Service (NRCS) considers 13.6 kg (30 lbs) of airdry forage per day the standard forage demand for one AUM (Metz 2007). Based on this demand 

estimate, an AUM would require 415 kg (915 lbs) of forage per month. In 1994, the NRCS 

conducted a feed and forage inventory at GRKO and determined that there were 1,676 AUMs 

available annually through pasture and hay production (Smith, e-mail communication, 19 September 

2014). In 2012, park staff used data from the NRCS Web Soil Survey 

(http://websoilsurvey.nrcs.usda.gov) to calculate potential annual forage production and, 

subsequently, AUMs. Without any irrigation inputs, GRKO’s fields and pastures are estimated to 

yield 1,679 AUMs in a favorable year, 1,320 AUMs in a normal year, and 820 AUMs in an 

unfavorable year (Smith, e-mail communication, 19 September 2014). Given that irrigation is 

occurring in many hayfields, these numbers are likely even higher. In 2011and 2012, park livestock 

utilized 1,248 AUMs and 1,224 AUMs, respectively, meaning the ranch had a surplus of AUMs in 

those years (Smith, e-mail communication, 19 September 2014). 

4.1.2 Measures

• Range Condition/Similarity Index

• Rangeland Health (17 indicators)

4.1.3 Reference Conditions/Values

For the purposes of this assessment, the reference condition for the Range Condition measure in 

upland, non-irrigated pastures will be scores in the good or excellent range, which suggest that 

grazing has not significantly altered the vegetation community. The reference condition for 

Rangeland Health will be ratings in the “none to slight” category, which indicate that ecological 

processes are not significantly altered by grazing. However, it is important to keep in mind that 

Range Condition and Rangeland Health measures can be influenced by factors other than grazing 

(e.g., drought, fire, human activity) (Bret Olson, Montana State University [MSU] Professor of 

Range Ecology, written communication, 4 January 2015). 

4.1.4 Data and Methods

Two methods are commonly used to assess the status of grazed lands throughout the U.S.: Range 

Condition/similarity index and Rangeland Health. Regarding the Range Condition/similarity index, 

the USDA Soil Conservation Service (SCS) developed the Range Condition concept in the 1940s. 

Range Condition is determined by comparing the present vegetation community on a “range site” to 

a historic reference (the “climax” community), whereby the soils, geography and climate dictate the 

potential characteristic, native plant community that would be expected on that “range site”, barring 
37 

significant natural or human-induced disturbances (Pellant et al. 2005). To determine Range 

Condition, plant biomass on appropriately selected plots is clipped and weighed, or estimated, to 

determine percent species composition. Using a technical guide, these current percentages are 

compared with percentages expected for a climax community for that site to determine a Range 

Condition score (i.e., how similar they are) (Olson, written communication, 6 January 2015). Scores 

range from 0-100%, with 100% indicating a site’s species composition is identical to the historic 

climax plant community. With this approach, vegetation communities are classified as excellent (76-

100%), good (51-75%), fair (26-50%), or poor (0-25%). The NRCS range site descriptions (NRCS 

1982) were used as the historical reference or “climax” condition (Olson, email communication, 3 

October 2014). As mentioned above, the reference condition for this NRCA will be scores in the 

good or excellent categories. 

In the mid-1990s, the SCS changed its name to the Natural Resources Conservation Service; with 

this change, they began to institute the concept of Similarity Index (SI), which is similar to but not 

the same as Range Condition (Olson, written communication, 6 January 2015). The primary 

difference is that when plant biomass on plots is clipped and weighed, or estimated, the actual (dry) 

weights are compared with dry weights of plant species expected to represent historic climax plant 

communities (HCPC, from an Ecological site description [ESD]). Ecological site descriptions have 

not yet been developed for western Montana and are therefore not available for GRKO. The NRCS 

has dropped the terms “excellent”, “good”, “fair” and “poor”, and simply presents SIs, which reflect 

the successional status of a plant community (i.e., its departure from HCPC). Using the same data set, 

Range Condition (based on percent species composition) and similarity indices (based on actual 

biomass) were calculated for six pasture locations within GRKO during the summer of 2014. 

Although ESDs have not been developed for western Montana yet, a best fit ESD from central 

Montana was used to determine the SIs (Olson, written communication, 6 January 2015). Ecological 

site descriptions for GRKO should be available soon, as the NPS has entered into a cooperative 

agreement with NRCS to identify ecological sites and prepare ESDs that include reference state 

conditions (Smith, written communication, January 2015). 

Rangeland Health, in contrast, focuses on the integrity of soils, ecological processes (e.g., water and 

nutrient cycling), and the ecosystem as a whole (Pellant et al. 2005). Rangeland Health Assessment 

methods are intended to, “provide a preliminary evaluation of soil/site stability, hydrologic function, 

and biotic integrity (at the ecological site level)” and “provide early warnings of potential problems 

and opportunities by helping land managers identify areas that are potentially at risk of degradation 

or where resource problems currently exist” (Pellant et al. 2005, p. 1). Since ecological processes are

often challenging to measure, Rangeland Health techniques utilize biological and physical 

characteristics that can serve as indicators of ecosystem integrity. Rather than taking quantitative 

measurements, researchers assign a qualitative rating based on the degree of variance from expected 

levels. The three main attributes in such an assessment and the indicators used for each are 

summarized in Table 7. Rangeland Health indicators and assessment methods are described in further 

detail in Pellant et al. (2005). Although GRKO managers and grazing experts agree that this method 

would be useful for assessing the condition of the ranch’s grazed lands, full Rangeland Health 

Assessments have not been completed at the park. 
38 

Table 7. Attributes and indicators used in Rangeland Health Assessments (Pellant et al. 2005). Each 

indicator is assigned one of the five following ratings based on the variance from expected conditions: 

None to slight, slight to moderate, moderate, moderate to extreme, extreme to total. 

Indicators Attributes

Soil/Site Stability Hydrologic Function Biotic Integrity

Rills x x

Water flow patterns x x

Pedestals and/or terracettes x x

Bare ground x x

Gullies x x

Wind-scoured, blowouts, and/or deposition 

 areas

x 

Litter movement x

Soil surface resistance to erosion x x x

Soil surface loss or degradation x x x

Plant community composition & 

 distribution relative to infiltration

x

Compaction layer x x x

Functional/structural groups x

Plant mortality/decadence x

Litter amount x x

Annual production x

Invasive plants x

Reproductive capability of perennial plants x

4.1.5 Current Condition and Trend

Range Condition/Similarity Index 

Range Condition and similarity indices were determined for six grazed fields at GRKO during the 

summer of 2014 (locations shown in Figure 12). Four of these fields are upland grasslands dominated 

by native species, while two (the effluent fields) are irrigated pastures that have been planted with 

non-native grasses. Range Condition is based on percent species composition (by dry weights) 

whereas similarity index is based on species composition directly based on dry weights (Table 8). 

Range Condition scores showed that two of the upland pastures (Ridge Road and Gravel Pit) were in 

the excellent condition class and two (Taylor Ridge and Upper Northwest Range) were in the good

condition class (NPS 2014a). The two irrigated pastures received index scores in the poor condition 

class (Table 8). However, this is because the historic reference condition used for comparison 

includes only native species and does not account for non-native species that are accepted as part of 

the cultural landscape at GRKO (Smith, e-mail communication, 26 September 2014). If these 

culturally acceptable species (particularly smooth brome [Bromus inermis]) were considered part of 

the historic reference condition, the two effluent fields would likely fall in the good condition class. 

The similarity indices for the six fields show that the two pastures with excellent Range Condition 

scores (Ridge Road and Gravel Pit) are also closest to the HCPC, with scores above 92% (Table 8). 

Upper Northwest Range was also very similar to the HCPC with a score just below 92%. Taylor 

Ridge Pasture was much lower with a similarity index of just 55%. The effluent fields yielded the 

lowest similarity indices (11.3% and 20%) because these areas are dominated by non-native species 

that are not considered part of the HCPC. 
39 

Table 8. Range Condition scores and classes (based on percent composition) and similarity indices 

(based on dry weight) for six grazed locations at GRKO in 2014 (NPS 2014a). Class designations are 

applied only for Range Condition scores and are not used with similarity indices.

Field Range Condition -

% Compostion Range Condition Class Similarity Index -Dry weight

Ridge Road Pasture 79% Excellent 92.2%

Upper Northwest Range 72% Good 91.8%

Taylor Ridge Pasture 54% Good 55%

Gravel Pit Pasture 93% Excellent 92.7%

Effluent Field 3 10% Poor 11.3%

Effluent Field 4 15% Poor 20%

Figure 12. Location of grazed fields where Range Condition was calculated and ROMN sampling sites 

where moderate (MM) or moderate to extreme (MX) evidence of disturbance/erosion were observed (see 

below). Note that only sites GRKO_004 and GRKO_044 are in upland grassland ranges and all others 

are in irrigated pastures/hayfields.

Rangeland Health 

Rangeland Health scores, as described by Pellant et al. (2005), have not been calculated at GRKO. 

However, the ROMN Vegetation Composition, Structure and Soils (VCSS) monitoring protocol has 

recorded observations on several of the soil/site stability indicators (surface flow patterns, 

rills/gullies, and pedestals) from 2006-2012. These features may suggest that grazing is causing 

disturbance and/or erosion, which can negatively impact soil stability (Pellant et al. 2005). 

Monitoring crews recorded whether evidence of these indicators at 27 sampling locations in grazed 
40 

areas was none to slight (NS), slight to moderate (SM), moderate (MM), moderate to extreme (MX), 

or extreme (XX) (Table 9). Evidence of pedestals has been NS during all observations except for one 

location, which received an SM in 2011. Although the vast majority of locations have also shown NS 

evidence of surface flow (87%) and rills/gullies (92%), MX observations have been recorded for 

rills/gullies at two locations (Table 9). One of these locations also showed MX evidence of surface 

flow in the same year (2009). However, these data represent only three of the 17 indicators used by 

Pellant et al. (2005) to calculate Rangeland Health and do not provide a comprehensive picture of the 

condition of GRKO’s grazed lands alone. 

Table 9. Indicators of disturbance and/or erosion documented in GRKO’s grazed lands (ROMN 2006-

2012). For vegetation type, P/H = irrigated pastures and hayfields and UG = upland grasslands (nonirrigated). NS - none to slight, SM = slight to moderate, MM = moderate, MX = moderate to extreme.

Plot (Veg type) # of 

Observations Surface Flow Rills/Gullies Pedestals

2006

GRKO_001 (P/H) 6 5 NS, 1 SM NS NS

GRKO_004 (UG) 5 2 NS, 3 SM NS NS

GRKO_005 (P/H) 6 3 NS, 3 SM NS NS

GRKO_007 (P/H) 6 NS NS NS

GRKO_008 (P/H) 3 NS NS NS

GRKO_009 (P/H) 3 NS NS NS

GRKO_010 (P/H) 3 SM NS NS

GRKO_011 (P/H) 6 3 NS, 1 SM, 2 MM 4 NS, 2 SM NS

GRKO_012 (P/H) 3 NS NS NS

GRKO_015 (P/H) 3 NS NS NS

GRKO_016 (P/H) 6 SM NS NS

GRKO_020 (P/H) 6 NS NS NS

GRKO_027 (P/H) 6 NS NS NS

Totals 62 43 NS, 17 SM, 2 MM 60 NS, 2 SM 62 NS

2007

GRKO_001 (P/H) 3 NS NS NS

GRKO_004 (UG) 3 2 NS, 1 MM NS NS

GRKO_005 (P/H) 3 NS NS NS

GRKO_007 (P/H) 3 NS 2 NS, 1 SM NS

GRKO_008 (P/H) 3 NS 2 NS, 1 SM NS

GRKO_009 (P/H) 3 NS NS NS

GRKO_010 (P/H) 3 NS NS NS

GRKO_011 (P/H) 3 NS NS NS

GRKO_012 (P/H) 3 NS NS NS

GRKO_015 (P/H) 3 NS NS NS

GRKO_016 (P/H) 3 2 NS, 1 SM NS NS

GRKO_018 (P/H) 3 NS NS NS

GRKO_019 (P/H) 3 NS NS NS

GRKO_020 (P/H) 3 NS NS NS

GRKO_021 (P/H) 3 NS NS NS

GRKO_022 (P/H) 3 NS NS NS

GRKO_024 (P/H) 3 NS NS NS

GRKO_027 (P/H) 3 NS NS NS

Totals 54 52 NS, 1 SM, 1 MM 52 NS, 2 SM 54 NS
41 

Table 9. Indicators of disturbance and/or erosion documented in GRKO’s grazed lands (ROMN 2006-

2012). For vegetation type, P/H = irrigated pastures and hayfields and UG = upland grasslands (nonirrigated). (continued)

Plot (Veg type) # of 

Observations Surface Flow Rills/Gullies Pedestals

2008

GRKO_001 (P/H) 3 NS NS NS

GRKO_004 (UG) 3 NS NS NS

GRKO_005 (P/H) 3 NS NS NS

GRKO_007 (P/H) 6 NS NS NS

GRKO_008 (P/H) 6 NS NS NS

GRKO_009 (P/H) 3 NS NS NS

GRKO_010 (P/H) 3 NS NS NS

GRKO_011 (P/H) 3 NS NS NS

GRKO_012 (P/H) 3 NS NS NS

Totals 33 33 NS 33 NS 33 NS

2009

GRKO_001 (P/H) 1 NS NS NS

GRKO_012 (P/H) 1 NS NS NS

GRKO_028 (P/H) 1 MX MX NS

GRKO_032 (UG) 1 NS NS NS

GRKO_033 (P/H) 1 NS NS NS

GRKO_036 (UG) 1 SM SM NS

Totals 6 4 NS, 1 SM, 1MX 4 NS, 1 SM, 1MX 6 NS

2010

GRKO_001 (P/H) 1 NS SM NS

GRKO_004 (UG) 1 NS NS NS

GRKO_005 (P/H) 1 MM MX NS

GRKO_012 (P/H) 1 NS NS NS

GRKO_037 (P/H) 1 NS MM NS

GRKO_040 (UG) 1 NS SM NS

GRKO_041 (UG) 1 NS SM NS

GRKO_043 (P/H) 1 NS NS NS

GRKO_044 1 NS MM NS

Totals 9 8 NS, 1 MM 3 NS, 3 SM, 2 MM, 1 MX 9 NS

2011

GRKO_007 (P/H) 1 NS NS NS

GRKO_008 (P/H) 1 NS NS NS

GRKO_009 (P/H) 1 NS NS NS

GRKO_010 (P/H) 1 NS NS NS

GRKO_011 (P/H) 1 NS NS NS

GRKO_015 (P/H) 1 NS NS NS

GRKO_016 (P/H) 1 NS NS NS

GRKO_020 (P/H) 1 NS NS NS

GRKO_040 (UG) 1 NS SM NS

GRKO_041 (UG) 1 NS NS NS

Totals 10 10 NS 9 NS, 1 SM 10 NS

2012

GRKO_015 (P/H) 1 NS NS NS

GRKO_016 (P/H) 1 NS NS NS

GRKO_018 (P/H) 1 NS NS SM
42 

Table 9. Indicators of disturbance and/or erosion documented in GRKO’s grazed lands (ROMN 2006-

2012). For vegetation type, P/H = irrigated pastures and hayfields and UG = upland grasslands (nonirrigated). NS - none to slight, SM = slight to moderate, MM = moderate, MX = moderate to extreme.

(continued)

Plot (Veg type) # of 

Observations Surface Flow Rills/Gullies Pedestals

2012 (cont.)

GRKO_019 (P/H) 1 NS NS NS

GRKO_021 (P/H) 1 NS SM NS

GRKO_022 (P/H) 1 NS NS NS

GRKO_024 (P/H) 1 NS NS NS

GRKO_027 (P/H) 1 NS NS NS

Totals 8 8 NS 7 NS, 1 SM 7 NS, 1 SM

Grand Totals 182 158 NS, 19 SM,

4 MM, 1 MX

168 NS, 10 SM,

2MM, 2MX 181 NS, 1 SM

Threats and Stressor Factors 

Threats to grazing at GRKO include invasive plant species, Columbian ground squirrels 

(Spermophilus columbianus), management actions (i.e., decisions that impact where and when to 

graze or not graze), fire, drought, and climate change. Invasive species are widely recognized as a 

major threat to native vegetation communities and ecosystems as a whole. They can also negatively 

impact grazing, a key cultural component at GRKO. Invasion by noxious weeds can increase soil 

erosion and reduce livestock carrying capacity on grazed lands, as invasive species often outcompete 

desirable native species (Mack et al. 2000, Davison et al. 2006). Some noxious weeds are avoided by 

livestock for a variety of reasons. They may contain high levels of toxins, have physical defenses 

(e.g., thorns), or simply be low in nutrients and/or digestibility (Molyneaux and Ralphs 1992, 

Davison et al. 2006). For example, yellow toadflax (Linaria vulgaris) contains alkaloids and 

glucosides that may be toxic to livestock in large amounts. Houndstongue (Cynoglossum officianale) 

and leafy spurge (Euphorbia esula) also contain toxins that can be harmful to cattle and horses 

during the plant’s active growth phase (Lym and Kirby 1987, Molyneaux and Ralphs 1992). 

Livestock often avoid these species unless no other forage is available (Olson, written 

communication, 31 July 2015). 

Precipitation has been linked to forage production on shortgrass rangelands. Lower May and June 

precipitation levels resulted in lower forage yields in a shortgrass prairie dominated by needle-andthread, western wheatgrass, and blue grama (Bouteloua gracilis) (Smoliak 1956). Although GRKO is 

not classified as a shortgrass prairie, two of the dominant species in this study (needle-and-thread and 

western wheatgrass) are common in the park’s upland grasslands. This study suggests that decreased 

precipitation (i.e., drought) has the potential to negatively impact grazing by reducing forage yields. 

Global climate change may cause an increase in droughts, as well as higher temperatures and shifts in 

precipitation regimes (Gray and Andersen 2009, McWethy et al. 2010). Research suggests that 

climate change will impact grazers. Craine et al. (2010) analyzed forage quality data from across the 

continental U.S. over 14 years. According to their analysis, dietary crude protein and digestible 

organic matter decreased with increasing temperatures and declining precipitation for regions with 

continental climates. This suggests that cattle nutritional stress will likely increase with climate 

change (Craine et al. 2010). The increased CO2 levels associated with climate change may also 
43 

impact grazing. Morgan et al. (2004) found that elevated CO2 levels during growth reduced the 

digestibility of blue grama, western wheatgrass, and needle-and-thread (the latter two species are 

common in GRKO). This suggests that increased CO2 will reduce forage quality, and livestock will 

have to consume more to achieve the same weight gains (Morgan et al. 2004). 

When Columbian ground squirrel (Photo 10) numbers are high, 

their feeding and digging can reduce forage production in pastures 

and croplands (Swant 2011, MDA 2013). Their burrows and dirt 

mounds are also a hazard to grazing livestock and haying equipment 

(Swant 2011). Columbian ground squirrels (CGS) prefer short grass 

habitats with deep soils. They typically avoid areas with taller 

grasses, rocky soils, or high water tables and fields that are flood 

irrigated (Swant 2011). In GRKO, CGS are often found on southfacing foothills or along fencerows adjacent to irrigated hayfields, 

or in portions of the hayfields that are rarely reached by floodwaters 

(Swant 2011). NPS staff have conducted visual surveys for CGS 

throughout the park every May since 2009 (NPS 2014b). During 

this survey period, squirrel numbers in grazed areas peaked in 2010 

with 209 individuals observed (Table 10, Figure 13). Only 34 

squirrels were observed in grazed areas in 2014. During early 

surveys, the highest numbers were observed in Big Gulch, but in 

2013-2014, squirrel numbers were highest in Upper Taylor (Table 

10). Ground squirrel burrows were also counted each June. With the 

exception of 2012, burrow numbers in grazed areas have increased every year, peaking around 700 in 

2014 (Figure 13). 

Table 10. Number of ground squirrels observed in grazed fields throughout GRKO during May surveys 

(NPS 2014b).

Field

# of 

Waypoints 2009 2010 2011 2012 2013 2014

Effluent Field 1 2 3 0 NS 1 0 0

Effluent Field 2 2 0 0 0 0 0 0

Effluent Field 3 3 0 0 0 2 0 0

Effluent Field 4 5 4 17 0 8 17 3

Effluent Field 5 3 0 0 0 0 0 0

Big Gulch 4 78 69 0 0 8 5

Little Gulch 4 45 27 0 0 14 6

Lower Taylor 2 12 3 4 0 7 3

Upper Taylor 2 22 47 0 0 39 11

West Field 3 5 23 46 0 1 11 2

West Field 4 4 7 NS 7 0 3 4

Feedlots 2 NS NS NS 16 NS NS

Photo 10. Columbian ground 

squirrel (NPS photo).
44 

Figure 13. Columbian ground squirrel and burrow numbers at GRKO, 2009-2014 (NPS 2014b).

Data Needs/Gaps

Full Rangeland Health Assessments have not been completed at GRKO. Some of the 17 indicators 

used in these assessments have been documented in the park’s grazed lands, but others have not (e.g., 

litter movement, reproductive capability of perennial plants). Repetition of the Range Condition 

assessments and similarity indices in the future will help determine if grazing is impacting any of the 

pastures at GRKO. Similarity indices could also be re-calculated to include culturally acceptable 

non-native species in the reference or “desired” plant community. 

Overall Condition 

Range Condition /Similarity Index

The Range Condition measure was assigned a Significance Level of 3. Similarity indices were 

calculated for six of GRKO’s grazed fields during the summer of 2014. The four upland pastures met 

the selected reference condition with scores in the excellent and good ranges. The two irrigated 

fields, which have been planted with non-native grasses to enhance forage production, were rated as 

poor. However, this is because the historic reference condition used for comparison did not include 

non-native grasses that are considered part of the cultural landscape at GRKO. This measure is 

currently of low concern (Condition Level = 1). 

Rangeland Health

Rangeland Health was also assigned a Significance Level of 3. Full Rangeland Health Assessments 

have not been completed for any of the grazed lands at GRKO. The ROMN VCSS monitoring 

protocol has recorded observations on several of the soil/site stability indicators, but these are only 

three of the 17 indicators used to calculate Rangeland Health. Although the ROMN observations do 

not suggest any cause for concern regarding the condition of grazed lands, they do not provide 

enough information to fully assess this measure at this time. Therefore, a Condition Level has not 

been assigned.

0

100

200

300

400

500

600

700

800

2009 2010 2011 2012 2013 2014

Number of CGS/burrows

CGS numbers

Burrow numbers
45 

Weighted Condition Score 

A Weighted Condition Score was not calculated for grazing at GRKO, since condition could not be 

assigned for one of the two measures. Given that Range Condition has only been assessed during one 

year, no trends could be identified. The current condition and trend for grazing at GRKO are 

unknown. 

Grazing

Measures Significance 

Level

Condition 

Level WCS = N/A 

Range Condition 3 1 

Rangeland Health 3 n/a

4.1.6 Sources of Expertise

Jason Smith, GRKO Natural Resource Specialist 

Bret Olson, Professor of Range Ecology, Montana State University
46 

4.1.7 Literature Cited

Briske, D. D., J. D. Derner, J. R. Brown, S. D. Fuhlendorf, W. R. Teague, K. M. Havstad, R. L. 

Gillen, A. J. Ash, and W. D. Willms. 2008. Rotational grazing on rangelands: Reconciliation and 

experimental evidence. Rangeland Ecology and Management 61(1):3-17.

Craine, J. M., A. J. Elmore, K. C. Olson, and D. Tolleson. 2010. Climate change and cattle 

nutritional stress. Global Change Biology 16:2901-2911. 

Davison, J. C., E. Smith, and L. M. Wilson. 2006. Livestock grazing guidelines for controlling 

noxious weeds in the western United States. Western Region Sustainable Agriculture Research 

and Education, Logan, Utah. 

Derner, J. D., W. K. Lauenroth, P. Stapp, and D. J. Augustine. 2009. Livestock as ecosystem 

engineers for grassland bird habitat in the western Great Plains of North America. Rangeland 

Ecology and Management 62(2):111-118. 

Gray, S., and C. Andersen. 2009. Assessing the future of Wyoming’s water resources: Adding 

climate change to the equation. William D. Ruckelshaus Institute of Environment and Natural 

Resources. University of Wyoming, Laramie, Wyoming. 

John Milner Associates, Rivanna Archaeological Consulting, Susan Maxman and Partners 

Architects. 2004. Cultural landscape report. Grant-Kohrs Ranch National Historic Site, Deer 

Lodge, Montana. 

Lym, R. G., and D. R. Kirby. 1987. Cattle foraging behavior in leafy spurge-infested rangeland. 

Weed Technology 1(4):314-318. 

Mack, R. N., D. Simberloff, W. M. Lonsdale, H. Evans, M. Clout, and F. A. Bazzaz. 2000. Biotic 

invasions: Causes, epidemiology, global consequences, and control. Ecological Applications 

10(3):689-710. 

McWethy, D. B., S. T. Gray, P. E. Higuera, J. S. Littell, G. T. Pederson, A. J. Ray, and C. Whitlock. 

2010. Climate and terrestrial ecosystem change in the U.S. Rocky Mountains and Upper 

Columbia Basin: Historical and future perspectives for natural resource management. Natural 

Resource Report NPS/GRYN/NRR—2010/260. National Park Service, Fort Collins, Colorado. 

Metera, E., T. Sakowski, K. Sloniewski, and B. Romanowicz. 2010. Grazing as a tool to maintain 

biodiversity of grassland - a review. Animal Science Papers and Reports 28(4):315-334. 

Metz, R. 2007. Montana grazing animal unit month (AUM) estimator. Range Technical Note No. 

MT-32. Natural Resources Conservation Service, Bozeman, Montana. 

Molyneaux, R. J., and M. H. Ralphs. 1992. Plant toxins and palatability to herbivores. Journal of 

Range Management 45:13-18. 
47 

Montana Department of Agriculture (MDA). 2013. The Columbian ground squirrel: Its biology and 

control. Montana Department of Agriculture, Helena, Montana. 

Morgan, J. A., A. R. Mosier, D. G. Milchunas, D. R. LeCain, J. A. Nelson, and W. J. Parton. 2004. 

CO2 enhances productivity, alters species composition, and reduces digestibility of shortgrass 

steppe vegetation. Ecological Applications 14(1):208-219. 

National Park Service (NPS). 2013. Grant-Kohrs Ranch: Cattle. 

http://www.nps.gov/grko/naturescience/cattle.htm (accessed 21 November 2013). 

National Park Service (NPS). 2014a. Range site and condition record data sheets. Unpublished data 

collected by Bret Olson and Jarrett Payne, Montana State University. Received from Jason 

Smith, 26 September 2014. 

National Park Service (NPS). 2014b. Grant-Kohrs Ranch National Historic Site: Annual survey for 

Columbian ground squirrel. Microsoft Excel spreadsheet. Received from Jason Smith, 20 August 

2014. 

Natural Resources Conservation Service (NRCS). 1982. Technical range site descriptions. Field 

office technical guide, section II-E-8. Natural Resources Conservation Service, Washington, D.C. 

Pellant, M., P. Shaver, D. A. Pyke, and J. E. Herrick. 2005. Interpreting indicators of Rangeland 

Health, version 4. Technical Reference 1734-6. U.S. Department of the Interior, Bureau of Land 

Management, National Science and Technology Center, Denver, Colorado. 

Rice, P. M., E. W. Schweiger, W. Gustafson, C. Lea, D. Manier, D. Shorrock, B. Frakes, and L. 

O’Gan. 2012. Vegetation classification and mapping project report, Grant-Kohrs Ranch National 

Historic Site. Natural Resource Report NPS/ROMN/NRR—2012/589. National Park Service, 

Fort Collins, Colorado. 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2006. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2006. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2007. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2007. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2008. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2008. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2009. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2009. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 
48 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2010. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2010. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2011. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2011. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2012. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2012. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Severson, K. E., and P. J. Urness. 1994. Livestock grazing: A tool to improve wildlife habitat. Pages 

232-249 in Ecological implications of livestock herbivory in the west. Vavra, M., A. Laycock, 

and R. D. Pieper (eds.). Society for Range Management, Denver, Colorado. 

Smoliak, S. 1956. Influence of climatic conditions on forage production of shortgrass rangeland. 

Journal of Range Management 9(2):89-91.

Swant, G. D. 2011. Grant-Kohrs Ranch National Historic Site: Survey protocol for Columbian 

ground squirrel (Spermophilus columbianus). National Park Service, Deer Lodge, Montana.
49 

4.2 Riparian Area

4.2.1 Description

Riparian and wetland areas are of critical importance in semiarid regions of the west, such as in and 

around GRKO. These areas influence water quality and quantity, stream stability, and provide habitat 

for terrestrial and aquatic wildlife (Hansen et al. 1995). Riparian vegetation stabilizes streambanks, 

protecting them from erosion by water (streamflow and runoff), wind, and trampling (Hansen et al. 

1995, Griffin and Smith 2001). This vegetation also provides shade and cover for wildlife and 

contributes detritus to streams to provide habitat for aquatic organisms such as fish and invertebrates 

(Hansen et al. 1995, Rice and Hardin 2002). The shade from vegetation can prevent water 

temperature fluctuations, which are harmful for aquatic life (Meehan et al. 1977, Hansen et al. 1995). 

Riparian areas typically have higher soil moisture than surrounding areas and, therefore, are more 

productive and can support different plant species than the neighboring uplands. This attracts wildlife 

and adds to the overall diversity of the landscape (Hansen et al. 1995). 

Photo 11. The Clark Fork riparian area within GRKO (photo by Kathy Allen, SMUMN GSS 2013).

The riparian areas of GRKO are dominated by a mix of shrubs and herbaceous species with scattered 

stands of trees, primarily black cottonwood (Populus balsamifera ssp. trichocarpa). Dominant shrubs 

include a variety of willows (Salix spp.), water birch (Betula occidentalis), and western snowberry 

(Symphoricarpos occidentalis) (Bedunah and Jones 2001). Common graminoids are redtop (Agrostis 

stolonifera), smooth brome, Baltic rush (Juncus balticus), quackgrass (Elymus repens), and 

bluegrasses (Poa spp.) (Bedunah and Jones 2001). Many of the graminoids are non-native but are 

important components of the cultural landscape. The distribution of riparian vegetation communities 
50 

within GRKO is shown in Figure 14 and Figure 15, while natural (e.g., not planted by humans) 

cottonwood tree locations are depicted in Figure 16. 

Figure 14. Riparian vegetation community distribution in the northern portion of GRKO (Rice et al. 2012). 

H.V. = Herbaceous Vegetation.
51 

Figure 15. Riparian vegetation community distribution in the southern portion of GRKO (Rice et al. 2012). 

H.V. = Herbaceous Vegetation.
52 

Figure 16. Locations of natural cottonwood trees (e.g., not planted) within GRKO as of 2002 (NPS 2002).

The riparian areas at GRKO have 

been heavily impacted by past 

human disturbance, especially 

mining contamination from 

upstream and livestock grazing 

(Bedunah and Jones 2001). The 

dominant vegetation communities 

were classified by Thompson et al. 

(1995) and Bedunah and Jones 

(2001) as “disturbance type 

communities” (as originally defined 

by Hansen et al. 1995). The riparian 

areas within the park were fenced 

off in 1994 to exclude cattle 

(Bedunah and Jones 2001). 

Mining occurred in the Clark Fork 

watershed for over a century and 

Photo 12. A slickens area within the GRKO riparian zone 

(photo by Kathy Allen, SMUMN GSS 2013).
53 

flooding washed mining wastes downstream. Toxic metals were deposited throughout the Deer 

Lodge Valley floodplain, contaminating soils and impacting riparian vegetation (Rice 2003a). Some 

patches in the riparian area, called slickens (Photo 12), are so contaminated that they are completely 

devoid of vegetation (Rice and Hardin 2002). Tufted hairgrass (Deschampsia cespitosa), a native 

grass, is known to be metal tolerant and is often associated with these slickens areas (Rice and Ray 

1984, Bedunah and Jones 2001). 

4.2.2 Measures

• Species richness 

• Species composition (cover/biomass) 

• Extent of wetlands 

• NRCS riparian health assessment 

• Greenline assessment 

• Ecological effect size (A) 

4.2.3 Reference Conditions/Values

The reference condition for species richness and composition is Hansen et al. (1995). Hansen et al. 

(1995) surveyed riparian and wetland areas across Montana to develop a vegetation-based ecological 

site classification system for wetlands and riparian areas across the state. Nineteen of the riparian 

vegetation communities described by Hansen et al. (1995) occur at GRKO; these communities, along 

with their equivalent map unit names from the Rice et al. (2012) vegetation classification system, are 

presented in Table 11. Hansen et al. (1995) is also used as the reference condition for ecological 

effect size analyses (see Appendix B). 
54 

Table 11. Riparian vegetation communities described by Hansen et al. (1995) that occur within GRKO 

and their equivalent map unit name in Rice et al.’s (2012) vegetation mapping and classification system 

for GRKO. Hansen et al. (1995) communities in bold are considered climax communities while all others 

are seral (i.e., successional) stages. 

Hansen et al. (1995) Community Rice et al. (2012) Map Unit Name

Agrostis stolonifera Pasture - Redtop

Betula occidentalis Riparian Birch

Bromus inermis Pasture - Smooth Brome

Carex aquatilis Herbaceous Wetland - Water Sedge

Carex lasiocarpa Herbaceous Wetland - Woollyfruit Sedge

Carex rostrata Wetland - Beaked Sedge

Eleocharis palustris Herbaceous Wetland - Spike Rush

Equisetum fluviatile Herbaceous Wetland - Horsetail

Juncus balticus Herbaceous Wetland - Baltic Rush

Poa pratensis Pasture - Kentucky Bluegrass

Populus trichocarpa/herbaceous understory Riparian Cottonwood

Populus trichocarpa/Symphoricarpos 

 occidentalis

Riparian Cottonwood - Symphoricarpos

Rosa woodsii Shrub Rose

Salix bebbiana Riparian Bebb Willow

Salix exigua Riparian Narrowleaf Willow

Salix geyeriana Mesic Geyer Willow

Salix geyeriana/Carex rostrata Riparian Geyer Willow - Beaked Sedge

Symphoricarpos occidentalis Shrub Snowberry

Typha latifolia Herbaceous Wetland - Broadleaf Cattail - 

Narrowleaf Cattail

4.2.4 Data and Methods

The earliest botanical survey of GRKO was Rice and Ray (1984). While the authors did not generate 

a species list solely for the riparian area, they did document the most dominant plant species and 

explored metal contamination levels in vegetation. Just over a decade later, Thompson et al. (1995) 

completed a vegetative inventory and studied the distribution of communities across the park. A total 

of 48 polygons were surveyed, comprising 359 ha (888 ac); 33 of the surveyed polygons contained 

riparian areas or wetlands (Thompson et al. 1995). 

In 2000, Bedunah and Jones (2001) re-surveyed the riparian polygons sampled by Thompson et al. 

(1995) that had been fenced off to exclude livestock in 1994. The final study area included 17 

polygons with a total area of 49 ha (122 ac). Community composition metrics were compared to 

results from Thompson et al. (1995) to determine if changes had occurred since grazing exclusion 

(Bedunah and Jones 2001). Also in 2000, Rice and Hardin (2002) mapped and surveyed GRKO’s 

riparian areas. Similarity indices were used to compare the park’s riparian vegetation communities to 

the community types developed by Hansen et al. (1995) for the Montana Riparian and Wetlands 

Association. 

Rice and Smith (2011) surveyed vegetation plots in the riparian area in 2009 and 2010 to explore the 

efficacy of herbicide treatments on invasive species, particularly leafy spurge and yellow toadflax. 

The study focused on an area known to be impacted by invasive plants, as identified in a 2003 park-
55 

wide survey (Wood and Rew 2005), and did not represent a random sampling of the entire riparian 

zone. Both species richness and species composition were documented. 

To evaluate the extent of wetlands within GRKO, SMUMN GSS analysts used National Wetland 

Inventory (NWI) data for Powell County based on 1984 aerial photos that were converted into GIS 

data by SMUMN GSS in 2007 (USFWS and SMUMN GSS 2007). The conversion involved 

scanning hard copies of maps with delineated wetlands, orthorectifying the images, and converting 

the mapped wetlands to polygon features in a GIS database. Narrow wetlands (e.g., ditches or small 

streams) are sometimes mapped as linear features. The data are available through the U.S. Fish and 

Wildlife’s “Wetlands Mapper” website at http://www.fws.gov/wetlands/. Vegetation mapping efforts 

by Thompson et al. (1995) and Rice et al. (2012) may also provide some insight into the extent of 

wetlands within the park. 

In 2014, GRKO assessed the 

riparian health in the park using 

the NRCS Riparian Assessment 

Method (NRCS 2012) at four 

different locations: Taylor Creek, 

Cottonwood Creek, North and 

South Fork Johnson Creek, and No 

Name Creek (NPS 2014a; Figure 

17). The method evaluates 

physical and ecological attributes 

and can be a source for defining 

long-term trends. Ten parameters 

are used to make this assessment: 

stream incisement; lateral cutting; 

stream balance; deep, binding 

rootmass; riparian/wetland 

vegetative cover; noxious weeds; 

undesirable plants; woody species 

establishment; browse utilization; 

and riparian area/flood plain 

characteristics (NRCS 2012). These parameters are scored based on potential and actual conditions, 

and the final score is a percentage (actual/potential). Scores are placed into one of three categories: 

sustainable (80-100%), at risk (50-80%), and not sustainable (<50%) (NRCS 2012). 

Winward (2000) describes a three-phase method for analyzing riparian vegetation. Part of this is a 

Greenline composition assessment. The Greenline is defined by Winward (2000, p. 3) as “the first 

perennial vegetation that forms a lineal grouping of community types on or near the water’s edge. 

Most often it occurs at or slightly below the bankful stage.” Sampling the Greenline according to 

Winward’s (2000) methods occurs by walking transects and recording the composition of each step, 

which results in a percent composition measurement for the entire transect. At GRKO, Montana State 

Figure 17. Locations of four creeks sampled in 2014 using the 

NRCS Riparian Assessment Method.
56 

University researchers examined two locations in 2014 using the Greenline Assessment method 

(NPS 2014b). The first was along the Clark Fork and consisted of three total transects; the second 

was along Cottonwood Creek and consisted of one transect. 

4.2.5 Current Condition and Trend

Species Richness

A total of 184 plant species have been documented in the GRKO riparian area (Appendix C). This is 

over 50% of the total number of plant species found within the park as a whole. One of the earliest 

efforts to inventory riparian vegetation within the park was Rice and Hardin (2002). During this 

study, 172 plant species were observed: two tree species, 18 shrubs, 39 graminoids, and 113 forbs. 

More recently, Rice and Smith (2011) recorded 69 and 61 species in riparian sample plots in 2009 

and 2010, respectively. However, these observations included 10 species not previously documented 

in the riparian area by Rice and Hardin (2002). As of 2010, 58 non-native plant species have been 

confirmed in the riparian area (Rice 2003b, Rice and Smith 2011), which is nearly one-third of the 

species in the riparian area. 

Appendix C contains a list of all 667 plant species documented by Hansen et al. (1995) across 

Montana in the 19 riparian community types that occur within GRKO. Only 151 of these species 

have been confirmed in the GRKO riparian area. However, 55 of the species documented in Montana 

by Hansen et al. (1995) that have not been found in GRKO are non-native species and would be 

undesirable at GRKO (e.g., saltcedar [Tamarix chinensis]). An additional 67 species on the Hansen et 

al. (1995) list have been documented at GRKO but not in the riparian area. It is also worth noting that 

Hansen et al. (1995) covered the entire state of Montana and some of the species observed may have 

ranges that do not include the area around GRKO. 

Species Composition (cover/biomass) 

Rice and Ray (1984) documented the dominant plant species in the Clark Fork and Cottonwood 

Creek riparian areas within GRKO (Table 12). Only two species were among the five most dominant 

species in both riparian areas: redtop and narrowleaf willow (Salix exigua). In the Clark Fork riparian 

area, eight of the 13 dominant species were graminoids (four native and four non-native), with the 

other species including three shrubs, one forb and one tree (Rice and Ray 1984). Nine of the 13 

dominant species were graminoids within the Cottonwood Creek riparian area (six non-natives and 

three natives); the remaining species included two non-native forbs, one shrub, and one tree (Table 

12). Rice and Ray (1984) identified eight low-density cottonwood groves scattered throughout the 

ranch, with up to 10 trees each. 
57 

Table 12. Dominant plant species (in descending order) in the Clark Fork and Cottonwood Creek riparian 

zones, as documented by Rice and Ray (1984). An asterisk denotes a non-native species.

Clark Fork Riparian Zone Cottonwood Creek Riparian Zone

Scientific Name Common Name Scientific Name Common Name

Agrostis stolonifera* redtop; creeping bentgrass Bromus inermis* smooth brome

Salix exigua narrowleaf willow Agrostis stolonifera* redtop; creeping 

bentgrass

Juncus filiformis thread rush Poa pratensis* Kentucky bluegrass

Betula occidentalis water birch Alopecurus pratensis* meadow foxtail

Salix bebbiana Bebb willow Salix exigua narrowleaf willow

Bromus inermis* smooth brome Populus balsamifera ssp.

trichocarpa

black cottonwood

Deschampsia cespitosa tufted hairgrass Elymus repens* quackgrass

Poa pratensis* Kentucky bluegrass Juncus filiformis thread rush

Trifolium repens* white clover Trifolium repens* white clover

Carex nebrascensis Nebraska sedge Centaurea stoebe* spotted knapweed

Carex stipata awlfruit sedge Carex stipata awlfruit sedge

Alopecurus pratensis* meadow foxtail Agropyron cristatum* crested wheatgrass

Populus balsamifera ssp.

trichocarpa

black cottonwood Carex nebrascensis Nebraska sedge

Bedunah and Jones (2001) studied GRKO’s riparian communities and compared their results to those 

of Thompson et al. (1995). They found little difference in species composition and community 

structure between 1993 and 2000. The dominant and co-dominant plant species were similar, 

although percent cover varied significantly for three shrub, four graminoid, and three forb species 

(Table 13). The three shrub species and total shrub cover decreased, as did two non-native grasses 

and one non-native forb (white clover [Trifolium repens]). The two grasses and white clover typically 

increase with disturbances such as grazing, so these species likely decreased because grazing was 

excluded from the riparian area in 1994 (Bedunah and Jones 2001). While percent cover of shrubs 

decreased, shrub regeneration increased and utilization (i.e., browsing by animals) decreased between 

1993 and 2000 (Bedunah and Jones 2001). This change would be expected with the elimination of 

grazing (Ehrhart and Hansen 1997). Bedunah and Jones (2001) also noted that two of the four 

cottonwood stands sampled in 2000 consisted of only mature and decadent trees with no seedlings, as 

was the case with all three cottonwood stands sampled by Thompson et al. (1995) in 1993. 
58 

Table 13. Percent cover composition of dominant, co-dominant, or community type indicator species in 

the GRKO riparian area in 1993 (Thompson et al. 1995) and 2000 (Bedunah and Jones 2001).

Species 1993 

(Thompson et al. 1995)

2000 

(Bedunah and Jones 2001)

Trees

Populus trichocarpa 0.6 1.78

Shrubs

Alnus incana 0.25 0.11

Betula occidentalis 12.94 11.12

Cornus stolonifera 0.38** 0.09

Ribes spp. 1.08 0.37

Rosa woodsii 1.00* 0.37

Salix bebbiana 2.17 3.29

Salix boothii 9.45 9.44

Salix exigua 5.80** 3.51

Salix geyeriana 0.28 0.52

Salix lasiandra 0.12 0.09

Symphoricarpos occidentalis 2.25 1.94

Other shrubs 0.07 0.19

Total Shrubs 35.79* 31.05

Graminoids

Agrostis stolonifera^ 24.17* 16.72

Elymus repens^ 3.58 4.89

Bromus inermis^ 4.71* 10.70

Carex spp. 1.03 1.53

Deschampsia cespitosa 0.53* 3.16

Juncus balticus 5.57 9.82

Poa pratensis^ 5.91* 1.39

Phleum pratense^ 0.53 0.30

Other grasses 0.57 1.69

Non-native grasses 39.45 34.00

Total graminoids 46.60 50.20

Forbs

Centaurea stoebe ssp. micranthos^ 0.77 0.80

Cirsium arvense^ 7.71 7.00

Equisetum spp. 0.11 0.31

Euphorbia esula^ 1.35* 4.41

Glycyrrhiza lepidota 0.15* 2.93

Argentina anserina 0.62 0.13

Solidago spp. 0.48 0.56

Trifolium repens^ 3.64* 0.08

Other forbs 1.66 2.93

Noxious forbs1 9.15 12.9

Total forbs 16.49 19.15

* Means of the same species are significantly different (p≤0.10) between the 2 years.

** Means of the same species are significantly different (p≤0.05) between the 2 years.

^ Non-native species 1 Noxious forbs = sum of Centaurea stoebe ssp. micranthos, Cirsium arvense, and Euphorbia esula. 

Rice and Smith (2011) also documented the most dominant plant species in a portion of the GRKO 

riparian area in 2009 and 2010 (Table 14). The study plots were dominated by non-native species, 
59 

averaging 72% canopy cover, with introduced grasses being most common (Rice and Smith 2011). 

Approximately 10% of the area in the monitoring plots was bare ground or litter, primarily in spots 

where noxious weeds had been treated with herbicide (Rice and Smith 2011). Total noxious forb 

cover in 2010 was less than 2%, an improvement over the 12.9% cover reported by Bedunah and 

Jones (2001) in 2000. Seven of the 15 most dominant species identified by Rice and Smith (2011) 

were also among the most dominant species documented by Rice and Ray (1984), and 11 species 

were also considered dominant or co-dominant by Bedunah and Jones (2001). 

Table 14. The fifteen most dominant plant species in riparian area monitoring plots in 2009 and 2010 

(Rice and Smith 2011). Note that the study area was selected because it was known to be impacted by 

non-native species and did not represent a random sampling of the entire riparian zone.

2009 2010

Scientific Name % Cover Scientific Name % Cover

Elymus repens* 25.3 Elymus repens* 30.4

Bromus inermis* 19.3 Bromus inermis* 22.6

Agrostis stolonifera* 13.0 Poa secunda 11.1

Poa secunda 10.5 Agrostis stolonifera* 9.3

Juncus balticus 3.3 Juncus balticus 4.2

Deschampsia caespitosa 2.5 Deschampsia caespitosa 2.5

Salix bebbiana 2.0 Salix bebbiana 2.1

Linaria vulgaris* 0.6-1.8 Salix boothii 1.3

Euphorbia esula* 1.1 Euphorbia esula* 1.1

Cirsium arvense* 1.1 Iris missouriensis 1.0

Salix boothii 1.0 Betula occidentalis 0.5

Betula occidentalis 1.0 Symphoricarpos occidentalis 0.5

Poa compressa* 0.8 Sonchus arvensis* 0.5

Salix exigua 0.6 Poa compressa* 0.4

Iris missouriensis 0.6 Linaria vulgaris* 0.4

* Non-native species

Extent of Wetlands 

According to the NWI database, wetland polygons cover just over 170.1 ha (420.3 ac) (Table 15, 

Figure 18; USFWS and SMUMN GSS 2007). This is based on interpretation of aerial imagery from 

1984. However, the vast majority (102 of the 170 ha) is river or stream (R3UBH; see Table 15). 

Wetlands with emergent vegetation (herbaceous plants) cover approximately 44.5 ha (110 ac) while 

scrub-shrub wetlands cover 9.4 ha (23.2 ac) and forested wetlands cover less than 0.4 ha (<1 ac) 

(USFWS and SMUMN GSS 2007). The total area of vegetated wetland polygons (emergent, scrubshrub, and forested) is 54.3 ha (134.1 ac). 
60 

Table 15. Area of NWI wetland polygons (ha and ac) within GRKO (USFWS and SMUMN GSS 2007).

Wetland code* Number Area Wetland code* Number Area

(ha) (ac) (ha) (ac)

PEMA 4 6.6 16.3 PSSA 7 8.0 19.8

PEMB 1 0.05 0.1 PSSC 5 1.4 3.5

PEMC 16 31.4 77.6 PABF 15 2.3 5.7

PEMF 3 3.2 7.9 PABKx 5 9.1 22.5

PEMKx 1 3.4 8.4 R3UBH 1 102.7 253.8

PFOA 1 0.4 1.0 R3USA 24 1.8 4.4

Total 83 170.1 420.3

Vegetated 

Wetlands

38 54.3 134.2

* PEMA = Palustrine, emergent vegetation, temporarily flooded

 PEMB = Palustrine, emergent vegetation, saturated

 PEMC = Palustrine, emergent vegetation, seasonally flooded

 PEMF = Palustrine, emergent vegetation, semipermanently flooded

 PEMKx = Palustrine, emergent vegetation, artificially flooded, excavated

 PFOA = Palustrine, forested, temporarily flooded

 PSSA = Palustrine, scrub-shrub vegetation, temporarily flooded

 PSSC = Palustrine, scrub-shrub vegetation, seasonally flooded

 PABF = Palustrine, aquatic bed, semipermanently flooded

 PABKx = Palustrine, aquatic bed, artificially flooded, excavated

 R3UBH = Riverine, upper perennial, unconsolidated bottom, permanently flooded

 R3USA = Riverine, upper perennial, unconsolidated shore, temporarily flooded
61 

Figure 18. Extent of wetlands (polygons) within GRKO according to the NWI database (USFWS and 

SMUMN GSS 2007). See footnote of Table 15 above for explanation of wetland codes.

The NWI also identified an additional 44,737.8 m (146,780.0 ft) of linear wetlands (e.g., ditches or 

small, often intermittent streams) (Table 16, Figure 19). Most of these wetlands (74% of the total 

length) were vegetated (emergent or forested). 
62 

Table 16. Length of NWI linear wetlands (m) within GRKO (USFWS and SMUMN GSS 2007).

Wetland code* Number Length (m) Wetland code* Number Length (m)

PEMA 2 389.9 PABF 2 472.7

PEMC 38 9,692.1 R3UBF 1 10,713.9

PEMCh 1 151.8 R3USC 2 357.9

PEMCx 8 21,695.2 Total 60 44,737.8

PEMF 4 391.0 Vegetated Wetlands 55 33,193.3

PFOA 2 873.3

*PEMA = Palustrine, emergent vegetation, temporarily flooded

PEMC = Palustrine, emergent vegetation, seasonally flooded (x = excavated, h = impounded)

PEMF = Palustrine, emergent vegetation, semipermanently flooded

PFOA = Palustrine, forested, temporarily flooded

PABF = Palustrine, aquatic bed, semipermanently flooded

R3UBF = Riverine, upper perennial, unconsolidated bottom, semipermanently flooded

R3USC = Riverine, upper perennial, unconsolidated shore, seasonally flooded
63 

Figure 19. Extent of linear wetlands within GRKO according to the NWI database (USFWS and SMUMN 

GSS 2007). See footnote of Table 16 above for explanation of wetland codes.

Thompson et al. (1995) and Rice et al. (2012) mapped the extent of vegetation communities within 

GRKO. The total area of vegetation communities typically found in riparian/wetland areas can 

provide a rough estimate of wetland extent within the park at the time of mapping. However, these 

communities may extend outside wetlands, or communities not identified as primarily riparian may 

actually extend into wetlands. Based on 1993 surveys, Thompson et al. (1995) identified 168.6 ha 

(416.5 ac) of primarily riparian vegetation communities (Table 17). With field surveys completed in 

2006-2007, Rice et al. (2012) mapped 87.1 ha (215.2 ac) of riparian vegetation communities, plus 

21.8 ha (53.8 ac) of open water (Table 17; also see Figure 14 and Figure 15). The extent of 

riparian/wetland communities mapped by Rice et al. (2012) is notably lower than riparian 

communities mapped by Thompson et al. (1995). Whether this difference is due to an actual change 
64 

in wetland extent or due to differences in classification and methodologies between the two studies is 

unclear. 

Table 17. Extent of primarily riparian/wetland vegetation communities within GRKO, according to 

Thompson et al. (1995) and Rice et al. (2012). H.V. = Herbaceous vegetation.

Thompson et al. (1995) 

Community Code Rice et al. (2012) community name

Extent in ha (ac)

Thompson et 

al. (1995)

Rice et al. 

(2012)

SALGEY Geyer’s willow /Mesic Graminoids Shrubland 41.0 (101.3) 24.8 (61.4) SALGEY/CALCAN1 4.5 (11.1)

SALGEY/CARROS - Not identified/mapped - 8.6 (21.3) --

- Not identified - Geyer’s willow/NW Territory Sedge Shrubland -- 8.1 (19.9)

JUNBAL Baltic Rush H.V. 31.7 (78.4) 1.3 (3.2)

POPTRI/CORSTO Black Cottonwood/Snowberry Forest 14.5 (35.8) 0.2 (0.6)

BROINE Smooth Brome - (Western Wheatgrass) H.V. 11.0 (27.1) 8.8 (21.8)

AGRSTO (Giant Bentgrass, Spreading Bentgrass) H.V. 10.3 (25.4) 2.9 (7.1)

BETOCC Water Birch Shrubland 9.6 (23.7) 9.3 (22.9)

CARROS - Not identified/mapped - 9.6 (23.7) --

- Not identified - Northwest Territory Sedge (Carex utriculata) H.V. -- 0.7 (1.7)

TYPLAT (Broadleaf Cattail, Narrowleaf Cattail) Western H.V. 9.6 (23.6) 5.6 (13.8)

POAPRA Kentucky Bluegrass Seasonally Flooded H.V. 6.2 (15.3) 0.1 (0.3)

SALBEB Riparian Bebb Willow 5.0 (12.3) --

SALEXI Narrowleaf (Coyote) Willow Temporarily Flooded 

Shrubland

3.6 (8.8) 13.7 (33.8)

CARAQU Aquatic Sedge H.V. 2.0 (5.0) 2.1 (5.2)

SPAGRA2 - Not identified/mapped - 0.5 (1.2) --

ALNINC3 - Not identified/mapped - 0.3 (0.8) --

Slickens - Unvegetated, not mapped - 0.3 (0.7) --

DESCES Tufted Hairgrass Slickens Sparse Vegetation 0.2 (0.5) 1.4 (3.4)

POPTRI/herbaceous Black Cottonwood/Mixed Herbs Forest 0.2 (0.4) 1.2 (3.0)

ROSWOO - Not identified/mapped - 0.04 (0.1) --

- Not identified - Wooly Sedge (Carex pellita)H.V. -- 0.6 (1.4)

- Not identified - Marsh Spikerush (Eleocharis palustris) H.V. -- 0.4 (0.9)

- Not identified - Water Horsetail (Equisetum fluvitale) H.V. -- 0.5 (1.2)

- Not identified - Rocky Mountain Riparian Bar Sparse Vegetation -- 3.9 (9.6)

- Not identified - Western Snowberry Shrubland -- 1.6 (4.0)

Totals 168.6 (416.5) 87.1 (215.2)

Open Water -- 21.8 (53.8)

1

CALCAN = bluejoint (Calamagrostis canadensis) 2 Alkali cordgrass (Spartina gracilis) 3 Gray alder (Alnus incana) 

NRCS Riparian Health Assessment 

The full record sheets of the Riparian Health Assessment are located in Appendix D. Overall, the 

four creeks’ percent potential scores in 2014 were 68%, 73%, 78%, and 80% for Taylor Creek, 

Johnson Creek, Cottonwood Creek, and No Name Creek, respectively (NPS 2014a). Three 

parameters received an “actual score” of 0, indicating highly degraded conditions: woody species 

establishment at No Name Creek and Taylor Creek, and riparian/wetland vegetative cover at Taylor 

Creek (Table 18). Johnson, Cottonwood, and Taylor Creeks fall into the category of “at risk” 
65 

according to the assessment; No Name Creek is right on the border between “sustainable” and “at 

risk” (NPS 2014a). 

Table 18. NRCS Riparian Health Assessment scores for No Name, Johnson, Cottonwood, and Taylor 

Creeks (NPS 2014a).

Potential

No Name 

Creek

North and South 

Fork Johnson 

Creek

Cottonwood 

Creek

Taylor 

Creek

Stream Incisement 8 8 6 8 8 

Lateral Cutting 8 8 8 5 8 

Stream Balance 6 6 6 6 6 

Deep, Binding Rootmass 6 6 4 6 4 

Riparian/Wetland Vegetative 

Cover 6 4 2 2 0 

Noxious Weeds 3 2 2 2 2 

Undesirable Plants 3 3 3 3 3 

Woody Species 

Establishment 8 0 4 6 0 

Browse Utilization 4 3 3 3 4 

Riparian Area/Flood plain 

Characteristics 8 8 6 6 6 

Total 60 48 44 47 41

Percent of Potential N/A 80% 73% 78% 68%

Non-native pasture grasses make up a large portion of the riparian vegetation at Taylor Creek. In 

addition, recruitment and cover associated with woody species at Taylor Creek is poor. In certain 

stretches of the stream, woody riparian species appear to be colonizing; assessors predict this trend 

will continue into the future. Overall, the stream appears stable (NPS 2014a). 

Lower portions of Cottonwood Creek (near the confluence with the Clark Fork) show apparent 

lateral cutting; non-native grass colonization may be causing this to occur. Riparian wetland cover 

and cottonwood/willow recruitment are also a concern at Cottonwood Creek. Overall, the stream’s 

riparian health appears to be improving though, with evidence of willow recruitment, bank 

stabilizations and beaver (Castor canadensis) activity along the extent of the waterway (NPS 2014a). 

The major concerns at Johnson Creek are stream down-cutting, low numbers of woody species, 

noxious weed prevalence, and insufficient in-stream structure (e.g., woody debris or rocks) to 

dissipate stream energy and trap sediment. A railroad runs near the stream and in those locations 

bank stabilization is a concern. Yet overall, the stream appears to be improving. Assessors note that 

active weed management should be successful in eliminating noxious species along this waterway 

(NPS 2014a). 

No Name Creek was on the border between “sustainable” and “at risk”. However, the threat of 

pasture grass expansion and low willow recruitment could push this stream into the “at risk” 

category. Noxious weeds could also negatively impact riparian health if they are not controlled or 
66 

eliminated. The stream’s health appears to be improving, but is vulnerable to disturbance and 

subsequent vegetation changes in the future (NPS 2014a). 

Greenline Assessment

The Greenline Assessment of three transects on the Clark Fork revealed a high percent composition 

of mesic graminoids (NPS 2014b, Table 19). Mesic graminoids accounted for 70% of the 

composition of community types and many of the other communities present include mesic 

graminoids. Agrostis stolonifera was the second most prevalent community in the analyzed area and 

is also a non-native species.

Table 19. Greenline Assessment results for transects on the Clark Fork in GRKO, September 2014 (NPS 

2014b). 

Transect 1 Transect 2 Transect 3

Community 

Type Left Right Left Right Left Right

Total 

Steps

Percent 

Composition

Mesic 

Graminoid 85 56 70 64 119 95 489 69.66

Carex spp. 9 0 0 0 0 0 9 1.28

Juncus balticus 12 7 1 8 0 10 38 5.41

Betula 

occidentalis /

Mesic 

Graminoid

2 33 2 14 0 0 51 7.27

Agrostis 

stolonifera 0 23 41 34 1 0 99 14.10

Deschampsia

cespitosa 0 0 2 4 0 0 6 0.85

Salix exigua / 

Mesic 

Graminoid

0 0 0 5 0 0 5 0.71

Salix boothii / 

Mesic 

Graminoid

0 0 0 0 1 0 1 0.14

Calamagrostis 

stricta ssp. 

stricta

0 0 0 0 0 2 2 0.28

Scirpus 

microcarpus 0 0 0 0 0 2 2 0.28

Woody species regeneration was present along Transects 2 and 3 of the assessment. Beaver browsing 

was also present along the transects, resulting in die off. Overall, the riparian area appears to have 

sufficient and continued woody species establishment along the Clark Fork (NPS 2014b). 

A Greenline Assessment along Cottonwood Creek also took place in 2014 (Table 20). Mesic 

graminoids accounted for 42.1% of the community composition at this location (NPS 2014b). 

Agrostis stolonifera presence was minimal and Phalaris arundinacea was the second most prevalent 

community type. 
67 

Table 20. Greenline Assessment results for transect on the Cottonwood Creek in GRKO, September 

2014 (NPS 2014b).

Transect 1

Community Type Left Right

Total 

Steps

Percent 

Composition

Salix exigua / Mesic Graminoid 2 0 2 0.87

Carex utriculata 13 5 18 7.83

Phalaris arundinacea 38 15 53 23.04

Salix boothii / Mesic Graminoid 5 0 5 2.17

Agrostis stolonifera 3 1 4 1.74

Mesic Graminoid 34 63 97 42.17

Populus tremuloides / Mesic Graminoid 3 15 18 7.83

Scirpus microcarpus 12 5 17 7.39

Woody Litter 2 0 2 0.87

Salix amygdaloides / Mesic Graminoid 3 11 14 6.09

Surveyors at Cottonwood Creek noted that this is a relatively small reach and that is why only one 

transect was examined. Beaver impacts were not as substantial here as along the Clark Fork transects. 

Overall, woody seedlings were limited on the transect, possibly due to no flooding during the 

previous spring to promote regeneration (NPS 2014b). 

Greenline Assessment results can be used to determine successional status and to calculate a bank 

stability rating (Winward 2000). However, this can only be done if the individual community types at 

a site have been assigned a stability class and successional status. Not all the community types 

documented at GRKO have stability classes and successional status assigned. Communities for 

which these classifications are known are presented in Table 21. 

Table 21. Stability classes and successional status for community types documented during the GRKO 

Greenline Assessment (Winward 2000). For stability class, 1-2 = very low, 3-4 = low, 5-6 = mid, 7-8 = 

high, and 9-10 = excellent. For successional status, E = early, L = late.

Community type name Stability class Successional status

Betula occidentalis/Mesic graminoid 6-8 E/L*

Salix boothii/Mesic graminoid 7-10 E/L*

Salix exigua/Mesic graminoid 7-10 E/L*

Agrostis stolonifera 3 E

Calamagrostis stricta ssp. stricta 7 L

Carex utriculata 9 L

Deschampsia cespitosa 4 E

Juncus balticus 9 L

Scirpus microcarpus 9 L

* These types are considered late seral only if the following, or similar, mesic/hydrophytic graminoids 

dominate the undergrowth (at least 25% cover): Carex lanuginosa, Carex nebrascensis, Juncus balticus.

Ecological Effect Size (A)

In simple terms, an “effect size” describes the magnitude of the difference between two groups (see 

Appendix B). In the case of vegetation, the two “groups” being compared would be the existing plant 

community and an identified reference community, sometimes referred to as a potential natural 
68 

community (PNC). For the GRKO riparian area, the riparian area vegetation communities described 

in Hansen et al. (1995) can be used as a reference. Using multi-response permutation procedure tests 

(MRPP) to calculate ecological effect size, Rice and Hardin (2002) determined that the species 

composition of ten GRKO riparian communities evaluated differed significantly from the Hansen et 

al. (1995) reference communities (Table 22). As of 2000, those ten communities comprised 63% 

(32.2 ha) of the fenced riparian zone within the park (Rice and Hardin 2002). Several of the GRKO 

riparian communities could not be evaluated for ecological effect size by Rice and Hardin (2002), as 

there was only one plot for the community either within GRKO or in Hansen et al. (1995). 

Table 22. Ecological effect size (A) calculations and significance (p) for riparian communities at GRKO. 

Community types in bold differed significantly between GRKO and Hansen et al. (1995). For this study, 

p<0.05 is considered a significant result (Rice and Hardin 2002).

Number of plots

Community type Hansen et al. 

(1995)

GRKO Ecological 

effect size (A)

p<

Salix geyeriana 67 43 0.0878 0.0000

Betula occidentalis 20 28 0.1428 0.0000

Salix geyeriana/Carex rostrata 70 5 0.0323 0.0100

Salix exigua 114 25 0.0645 0.0001

Juncus balticus 10 9 0.0334 0.1130

Symphoricarpos occidentalis* 53 9 0.0370 0.0026

Carex rostrata * 232 7 0.0077 0.0189

Salix bebbiana * 28 6 0.0499 0.0205

Populus trichocarpa/Symphoricarpos 

 occidentalis

21 2 0.0135 0.3080

Rosa woodsii 56 5 0.0179 0.0819

Carex lasiocarpa * 32 5 0.0782 0.0061

Deschampsia cespitosa * 35 6 0.1467 0.0000

Typha latifolia * 81 4 -0.0011 0.4183

Carex aquatilis * 64 2 0.0117 0.1011

Eleocharis palustris 60 3 0.0195 0.0423

* Species constancy was 5%; all other community types used 20% constancy. A 20% constancy means that only 

plant species present in at least 20% of sampled plots were used in the evaluation.

Threats and Stressor Factors 

Threats to GRKO’s riparian areas include Superfund contamination and remediation activities, 

invasive plants, overgrazing, wildlife browsing, beaver activity, flooding, dewatering (e.g., for 

irrigation), and climate change. As mentioned previously, 58 non-native species have been 

documented in GRKO’s riparian areas; however, many of these are considered part of the cultural 

landscape. Non-native, invasive species that are of particular concern are those designated as noxious 

weeds by the state of Montana (Table 23). These aggressive species have the potential to outcompete 

and displace desirable plant species, alter ecological processes (e.g., nutrient and water cycling) and 

diminish wildlife habitat (NPS 2008). In the early 2000s, leafy spurge and yellow toadflax invasions 

in the GRKO riparian area became particularly extensive. A massive effort to reduce these 

infestations was initiated by the Northern Rocky Mountains Exotic Plant Management Team (NRM 

EPMT) in 2006. In the first two years, 32.6 ha (80.5 ac) and 46.5 ha (115 ac) were treated with 

Plateau herbicide, respectively (NPS 2011). In 2008, 21.9 ha (54 ac) were retreated; since then, the 
69 

size of infestations requiring herbicide treatment has been below 4 ha (10 ac) (NPS 2011). Between 

2003 and 2009, canopy cover of leafy spurge and yellow toadflax in the Clark Fork riparian zone 

decreased by 93% and 91%, respectively (Rice and Smith 2011). Further information on changes in 

invasive species coverage throughout the park over the past decade can be found in Appendix E.

Table 23. Invasive plant species documented in the Clark Fork riparian area by Rice (2003b).

Scientific Name Common Name Scientific Name Common Name

Montana noxious weeds

Cirsium arvense* Canada thistle Linaria vulgaris* yellow toadflax

Euphorbia esula* leafy spurge Tanacetum vulgare* common tansy

Lepidium latifolium* perennial pepperweed Rhaponticum repens* Russian knapweed

Centaurea stoebe ssp. 

micranthos*

spotted knapweed Potentilla recta* sulfur cinqufoil

Lepidium draba* hoary cress, whitetop Cynoglossum officianale* houndstongue

Introduced grasses

Poa pratensis Kentucky bluegrass Poa compressa Canada bluegrass

Elymus repens quackgrass Bromus tectorum* cheatgrass, downy 

brome

Agrostis gigantea redtop Phalaris arundinacea reed canarygrass

Bromus inermis smooth brome Phleum pratense timothy

Alopecurus pratensis meadow foxtail Lolium pratense meadow fescue

Potential problem forbs

Melilotus officinalis sweetclover Sonchus arvensis perennial sowthistle

Silene latifolia bladder campion Verbascum thapsus common mullein

*Also identified as priority species by the NRM EPMT (2011).

The heavy metal contamination from mining wastes that triggered the Superfund designation in the 

Upper Clark Fork region is a serious concern at GRKO (Thornberry-Ehrlich 2007). Heavy metals in 

the soil and water can impact plant health and productivity as well as ecological processes such as 

decomposition and nutrient cycling (Gannon and Rillig 2002, Kapustka 2002). In the early 1980s, 

Rice and Ray (1984) used redtop samples to evaluate metal contamination in GRKO’s vegetation. In 

grass from the riparian zone, metal concentrations were 10.4 μg/g for copper, 1.4 μg/g for arsenic, 

and 0.12 μg/g for cadmium. All of these levels were at least twice as high as would be expected in an 

uncontaminated area (Rice and Ray 1984). Kapustka (2002) conducted field and lab tests to 

determine the toxicity of GRKO soils to plants (i.e., phytotoxicity). This study found that metals 

concentration accounted for 85% of the variation in maximum plant growth. Higher metal 

concentrations negatively impacted shoot height, number of leaves and branches, root length, and 

total plant mass (Kapustka 2002). 

Beginning in late 2015, a massive remediation effort will take place along the Clark Fork within 

GRKO to remove much of this heavy metal contamination from the site. Areas targeted will be those 

within the 100-year channel migration zone (i.e., primarily riparian areas) where the cumulative 

contaminants of concern (COC) exceed 800 mg/kg and the depth of contamination is 61 cm (24 in) 

or greater. This will involve removing approximately 296,110 m3

 (387,297 yd3) of soil to an average 

depth of 0.7 m (2.3 ft) (Johnson, written communication, 17 October 2014). These areas will be 

backfilled with clean soil and “uncontaminated rooting medium” to support native plant revegetation 
70 

and return the flood plain to a 2-year flood level (NPS 2007, p. 3-2). While the removal of this 

contamination will benefit GRKO in the long run, the short-term damage to riparian area vegetation 

will be extensive.

It has long been known that livestock grazing can negatively impact riparian communities if not 

carefully managed (Marcuson 1977, Platts 1979). Improper use of these areas by livestock can alter 

or eliminate vegetation, as well as changing channel morphology, typically by widening and 

shallowing the stream (Platts 1979). Excessive cattle grazing alters the number, size, and shape of 

live and dead willow stems in a riparian community (Knopf and Cannon 1982). Willow seedlings are 

especially sensitive to grazing and trampling damage (Kovalchik and Elmore 1992). Marcuson 

(1977) found that shrub production was 13 times greater and canopy cover 82% greater in an 

ungrazed area than in a severely overgrazed area. Nearly all riparian areas at GRKO were fenced off 

to exclude cattle in 1994, partly to protect these areas from the negative impacts of grazing, but also 

to protect livestock and visitors from the contamination there (John Milner Associates et al. 2004). 

However, cattle may still occasionally get into these areas if fences are damaged or worn. While 

livestock grazing has potential negative impacts, a complete absence of disturbances (e.g., grazing, 

fire, flooding) can also impact riparian communities. Pearson and Dyer (2006) compared plant and 

arthropod communities in an unmanaged (i.e., ungrazed) grassland intermixed with riparian forest 

and a grazed, flood irrigated pasture on a ranch in northern Colorado. This study showed that the 

unmanaged grassland had lower plant abundance and species richness, as well as lower arthropod 

abundance and richness, than the grazed and irrigated pasture (Pearson and Dyer 2006). 

Wildlife browsing (particularly ungulates 

such as moose [Photo 13] and deer) can 

also affect riparian vegetation. Several 

studies have shown that native ungulate 

herbivory slows the restoration or 

recovery of degraded riparian areas (Case 

and Kaufmann 1997, Opperman and 

Merenlender 2000). Extremely high 

concentrations of native ungulates can 

eliminate woody vegetation such as 

willows and cottonwoods, partly by 

reducing seed production (Kay 1994). 

Grazing and trampling by ungulates also 

tends to decrease shrubs and tall forbs in 

favor of grasses and sedges. These two 

factors combined can reduce the cover value of riparian habitats for other wildlife (Kay 1994). 

Bedunah and Jones (2001) noted evidence of shrub browsing by wild ungulates in the GRKO 

riparian area, averaging almost 5%, during their 2000 study. 

Beavers are a natural part of riparian ecosystems in the western United States and can be beneficial to 

these systems in many ways. Beaver dams impound water that can raise the water table and actually 

Photo 13. Moose (Alces alces) in the GRKO riparian area, 

captured by a park wildlife camera in August 2013 (NPS 

photo).
71 

expand riparian communities (Kay 1994; Photo 14). These impoundments can also regulate stream 

flow, reducing flooding and supplementing low flows during dry periods (Kay 1994). However, 

beavers are often considered a nuisance to agriculture, as they can block irrigation ditches and 

culverts (Grasse and Putnam 1955). In other areas, including GRKO, they are a threat to large 

cottonwoods which are a key component of the visual landscape (Photo 14). The removal of large 

shade trees along streams could increase water temperatures, which may negatively impact aquatic 

organisms (Churchill 1980, Kay 1994). Cottonwood stands are not common within the park and are 

seen as a valuable resource for both the natural and cultural landscape. Some of the largest trees are 

protected with wire fencing wrapped around the base of the trunk. 

 

Photo 14. On left, a beaver dam on Cottonwood Creek in GRKO. On right, beaver damage to a large 

cottonwood at GRKO after protective wire broke and fell off (Photos by Sarah Gardner, SMUMN GSS 

2013). 

Flooding is also a natural and important process in riparian systems, particularly for cottonwood 

regeneration (Kalischuk et al. 2001), but extreme floods can do significant damage to riparian 

vegetation. Floodwaters can uproot or damage plants and long periods of inundation can kill 

vegetation or severely set back its growth (Richardson et al. 2007). Erosion from flood flows can 

cause riverbanks to collapse, eliminating the bank vegetation. Floodwaters can spread invasive plants 

and create disturbed areas for these invaders to colonize (Tickner et al. 2001, Richardson et al. 2007). 

Irrigation water for GRKO’s hayfields is diverted through historic ditches from the Clark Fork and its 

tributaries during the growing season (Rice et al. 2012). Some of this water returns to the river 

through surface or groundwater flow and may enhance riparian communities in some areas or allow 

them to expand. However, if too much water is removed from the river for irrigation, the water 

available for some riparian communities could be reduced. This could influence community 

composition and extent. Irrigation practices and other dewatering activities in the watershed but 

outside the park could also impact GRKO’s riparian areas. 
72 

Climate has a strong influence on vegetation communities, both directly and indirectly through its 

impact on ecological processes (e.g., nutrient and water cycling, erosion) (McWethy et al. 2010). As 

a result of climate change, the western U.S. is projected to experience more frequent dry periods 

(droughts) during the 21st century, due to increased temperatures and evapotranspirtation, as well as 

changes in surface hydrology (Gray and Andersen 2009, as cited by McWethy et al. 2010). In the last 

half of the 20th century, snowmelt and peak runoff were already occurring earlier on average, 

reducing surface water storage and river baseflows during the summer months (McWethy et al. 

2010). An increase in drought frequency or duration could impact riparian community extent and 

composition, as some riparian plant species are more tolerant of drought than others, while climate 

warming may influence plant phenology (Loehman 2009, Perry et al. 2012). 

Data Needs/Gaps

The riparian area is the most studied vegetation community within GRKO. However, riparian areas 

along the Clark Fork are expected to change drastically due to Superfund remediation efforts over the 

next several years. Much of the research described in this assessment could be repeated following 

remediation to document likely changes in the composition of the riparian area. Ecological effect 

sizes could be revisited to determine if remediation brings GRKO’s riparian communities closer to 

the Hansen et al. (1995) reference communities. NRCS Riparian Health and Greenline Assessment 

techniques should also be repeated to identify any changes over time. In addition, an update of NWI 

data using more recent aerial imagery would be helpful in determining any changes in wetland 

extent. 

Overall Condition 

Species Richness

This measure was assigned a Significance Level of 2. A total of 184 plant species have been 

documented in the GRKO riparian area, nearly one-third of which are non-native. However, many of 

these non-native species, particularly pasture grasses, are an important part of the ranch’s cultural 

landscape. Species richness is currently of low concern (Condition Level = 1).

Species Composition

The species composition measure was assigned a Significance Level of 3. Many of the plant species 

that were identified as most dominant in the early 1980s (Rice and Ray 1984) were still dominant in 

2009-2010 (Rice and Smith 2011). Bedunah and Jones (2001) also found little change in riparian 

area species composition between 1993 (Thompson et al. 1995) and 2000, despite the exclusion of 

grazing in 1994. Noxious forbs such as leafy spurge and yellow toadflax expanded their coverage in 

the riparian area in the late 1990s and early 2000s, but efforts by the EPMT have greatly reduced 

these weeds in the past 5 years (NPS 2010). The Condition Level for this measure is 2, indicating 

moderate concern 

Extent of Wetlands

The project team assigned this measure a Significance Level of 2. According to the NWI data, 

wetland polygons cover 170.1 ha (420.3 ac) and 44,737.8 m (146,780.0 ft) in linear features within 

GRKO. However, these data are based on interpretation of 1984 aerial imagery and wetland extent 
73 

may have changed since that time. Vegetation mapping identified 168.6 ha (416.5 ac) of primarily 

riparian or wetland communities in 1993 (Thompson et al. 1995) and 87.1 ha (215.2 ac) in 2006-07 

(Rice et al. 2012). Whether the difference in riparian/wetland community extent between these two 

mapping efforts is due to an actual change or differences in methodology and classification systems 

is unclear. An update of the NWI data for the park could help determine if wetland area has changed 

over time. The extent of wetlands is of low concern at this time (Condition Level = 1).

NRCS Riparian Health Assessment

This measure was also assigned a Significance Level of 2. Three of the four creeks evaluated with 

this method in 2014 within GRKO fell into the “at risk” category, while one (No Name Creek) was 

right on the border between “at risk” and “sustainable” (NPS2014a). As a result, this measure is 

assigned a Condition Level of 2, indicating moderate concern. 

Greenline Assessment

The Greenline assessment measure was assigned a Significance Level of 2. While Greenline 

assessment results can be used to determine successional status and to calculate a bank stability 

rating, this can only be done if all the individual community types identified have been rated. At 

GRKO, several of the communities along the Greenline have not been rated. Therefore, a Condition 

Level was not assigned.

Ecological Effect Size (A)

The project team assigned this measure a Significance Level of 3. Using ecological effect size, Rice 

and Hardin (2002) determined that 10 of the 15 GRKO riparian communities sampled were 

significantly different from the reference communities described by Hansen et al. (1995). As a result, 

this measure is of moderate concern (Condition Level = 2).

Weighted Condition Score (WCS) 

The Weighted Condition Score for GRKO’s riparian areas is 0.54, indicating moderate concern. An 

overall trend could not be determined. Some measures appear stable (e.g., species richness) but 

others only have data from one point in time, so no change can be detected. 
74 

Riparian Area

Measures Significance 

Level

Condition 

Level WCS = 0.54 

Species Richness 2 1 

Species 

Composition 3 2 

Extent of Wetlands 3 1 

NRCS Riparian 

Health 2 2 

Greenline 

Assessment 3 n/a

Ecological Effect 

Size 3 2 

4.2.6 Sources of Expertise

Peter Rice, University of Montana Research Ecologist

Jason Smith, GRKO Natural Resource Specialist 

Bret Olson, Professor of Range Ecology, Montana State University 
75 

4.2.7 Literature Cited

Bedunah, D., and T. Jones. 2001. Flood plain vegetation changes on the Grant-Kohrs Ranch National 

Historic Site between 1993 and 2000. National Park Service, Deer Lodge, Montana. 

Case, R. L., and J. B. Kauffman. 1997. Wild ungulate influences on the recovery of willows, black 

cottonwood and thin-leaf alder following cessation of cattle grazing in northeastern Oregon. 

Northwest Science 71(2):115-126. 

Churchill, J. E. 1980. Beaver are killing our trout streams. Trout 21(4):22-25. 

Ehrhart, R. and P. L. Hansen. 1997. Effective cattle management in riparian zones: A field survey 

and literature review. Montana BLM Riparian Technical Bulletin No. 3. Bureau of Land 

Management, Montana State Office, Billings, Montana. 

Gannon, J. E., and M. Rillig. 2002. Relationship of heavy metal contamination to soil respiration. 

National Park Service, Deer Lodge, Montana. 

Grasse, J. E., and E. F. Putnam. 1955. Beaver management and ecology in Wyoming. Second edition. 

Wyoming Game and Fish Commission, Cheyenne, Wyoming. 

Gray, S., and C. Andersen. 2009. Assessing the future of Wyoming’s water resources: Adding 

climate change to the equation. William D. Ruckelshaus Institute of Environment and Natural 

Resources. University of Wyoming, Laramie, Wyoming.

Griffin, E. R., and J. D. Smith. 2001. Analysis of vegetation controls on bank erosion rates, Clark 

Fork of the Columbia River, Deer Lodge Valley, Montana. U.S. Geological Survey, Denver, 

Colorado. 

Hansen, P. L., R. D. Pfister, K. Boggs, B. J. Cook, J. Joy, and D. K. Hinckley. 1995. Classification 

and management of Montana’s riparian and wetland sites. Montana Riparian and Wetland 

Association, University of Montana School of Forestry, Missoula, Montana. 

John Milner Associates, Rivanna Archaeological Consulting, Susan Maxman and Partners 

Architects. 2004. Cultural landscape report. Grant-Kohrs Ranch National Historic Site, Deer 

Lodge, Montana. 

Kalischuk, A. R., S. B. Rood, and J. M. Mahoney. 2001. Environmental influences on seedling 

growth of cottonwood species following a major flood. Forest Ecology and Management 

144(1):75-89. 

Kapustka, L. A. 2002. Phytotoxicity tests on soils from the Grant-Kohrs Ranch National Historic 

Site, Deer Lodge, Montana. National Park Service, Deer Lodge, Montana. 

Kay, C. E. 1994. The impact of native ungulates and beaver on riparian communities in the 

intermountain west. Natural Resources and Environmental Issues 1:23-44. 
76 

Knopf, F. L., and R. W. Cannon. 1982. Structural resilience of a willow riparian community to 

changes in grazing practices. Pages 198-209 in Wildlife-livestock relationships symposium: 

Proceedings 10. University of Idaho Forest, Wildlife, and Range Experiment Station, Moscow, 

Idaho. 

Kovalchik, B. L., and W. Elmore. 1992. Efects of cattle grazing systems on willow dominated plant 

associations in central Oregon. Pages 111-119 in Proceedings - Symposium on ecology and 

management of riparian shrub communities, May 29-31, 1991. U.S. Forest Service, 

Intermountain Research Station, Ogden, Utah. 

Loehman, R. 2009. Understanding the science of climate change: Talking points - impacts to prairie 

potholes and grasslands. Natural Resource Report NPS/NRPC/NRR—2009/138. National Park 

Service, Fort Collins, Colorado. 

Marcuson, P. E. 1977. The effect of cattle grazing on brown trout in Rock Creek, Montana. Project 

Number F-20-R-21-11a. Montana Department of Fish and Game, Helena, Montana. 

McWethy, D. B., S. T. Gray, P. E. Higuera, J. S. Littell, G. T. Pederson, A. J. Ray, and C. Whitlock. 

2010. Climate and terrestrial ecosystem change in the U.S. Rocky Mountains and Upper 

Columbia Basin: Historical and future perspectives for natural resource management. Natural 

Resource Report NPS/GRYN/NRR—2010/260. National Park Service, Fort Collins, Colorado. 

Meehan, W. R., F. J. Swanson, and J. R. Sedell. 1977. Influences of riparian vegetation on aquatic 

ecosystems with particular reference to salmonid fishes and their food supply. Pages 137-145 in

Importance, preservation and management of riparian habitat: a symposium. Johnson, R. R., and 

D. A. Jones (eds.). U.S. Forest Service General Technical Report RM-43. Rocky Mountain 

Forest and Range Experiment Station, Fort Collins, Colorado. 

National Park Service (NPS). 2002. nat_ctnwd.shp ArcGIS shapefile. National Park Service, Deer 

Lodge, Montana. 

National Park Service (NPS). 2007. Federal restoration plan for Grant-Kohrs Ranch National 

Historic Site. National Park Service, Deer Lodge, Montana.

National Park Service (NPS). 2008. Exotic plant management team: 2008 annual report. National 

Park Service, Biological Resources Management Division, Fort Collins, Colorado. 

National Park Service (NPS). 2010. Northern Rocky Mountain exotic plant management team: FY 

2010 report. National Park Service, Biological Resources Management Division, Fort Collins, 

Colorado. 

National Park Service (NPS). 2011. Northern Rocky Mountains invasive plant management plan. 

National Park Service, Fort Collins, Colorado. 
77 

National Park Service (NPS). 2014a. NRCS riparian assessment data sheets. Unpublished data 

collected by Bret Olson and Jarrett Payne, Montana State University. Received from Jason 

Smith, 8 July 2014. 

National Park Service (NPS). 2014b. Greenline assessment data sheets. Unpublished data collected 

by Bret Olson and Jarrett Payne, Montana State University. Received from Jason Smith, 26 

September 2014. 

National Park Service (NPS). 2014c. NPSpecies online database. 

https://irma.nps.gov/App/Species/Search (accessed 18 November 2014). 

Natural Resources Conservation Service (NRCS). 2012. Riparian assessment: Using the NRCS 

riparian assessment method. Environment Technical Note No. MT-2 (Rev. 1). Natural Resource 

Conservation Service, Washington, D.C. 

Opperman, J. J., and A. M. Merenlender. 2000. Deer herbivory as an ecological constraint to 

restoration of degraded riparian corridors. Restoration Ecology 8(1):41-47. 

Pearson, C. V., and L. A. Dyer. 2006. Trophic diversity in two grassland ecosystems. Journal of 

Insect Science 6(1):25. 

Perry, L. G., D. C. Andersen, L. V. Reynolds, S. M. Nelson, and P. B. Shafroth. 2012. Vulnerability 

of riparian ecosystems to elevated CO2 and climate change in arid and semiarid western North 

America. Global Change Biology 18:821-842. 

Platts, W. S. 1979. Livestock grazing and riparian/stream ecosystems: An overview. Pages 39-45 in 

Proceedings, Forum - Grazing and Riparian/Stream Ecosystems. Trout Unlimited, Inc., Vienna, 

Virginia.

Rice, P. M., and P. C. Ray. 1984. Floral and faunal survey and toxic metal contamination study of the 

Grant-Kohrs Ranch National Historic Site. National Park Service, Deer Lodge, Montana. 

Rice, P. M., and J. Hardin. 2002. Riparian plant community structure at Grant-Kohrs Ranch. National 

Park Service, Deer Lodge, Montana. 

Rice, P. M. 2003a. Baseline vegetation types for Grant-Kohrs Ranch. National Park Service, Deer 

Lodge, Montana. 

Rice, P. M. 2003b. Discussion outline for Grant-Kohrs Ranch weed management and restoration. 

National Park Service unpublished report, Deer Lodge, Montana. 

Rice, P. M., and J. Smith. 2011. Evaluation of the effectiveness of noxious weed management 

through inventory and establishment of long-term monitoring plots at Grant-Kohrs NHS. 

National Park Service, Deer Lodge, Montana. 
78 

Rice, P. M., E. W. Schweiger, W. Gustafson, C. Lea, D. Manier, D. Shorrock, B. Frakes, and L. 

O’Gan. 2012. Vegetation classification and mapping project report, Grant-Kohrs Ranch National 

Historic Site. Natural Resource Report NPS/ROMN/NRR—2012/589. National Park Service, 

Fort Collins, Colorado. 

Richardson, D. M., P. M. Holmes, K. J. Esler, S. M. Galatowitsch, J. C. Stromberg, S. P. Kirkman, P. 

Pysek, and R. J. Hobbs. 2007. Riparian vegetation: degradation, alien plant invasions, and 

restoration prospects. Diversity and Distributions 13:126-139. 

Thompson, B., B. Ehrhart, and P. Hansen. 1995. Vegetation mapping any analysis of the GrantKohrs Ranch National Historical Site. Montana Riparian and Wetland Association, University of 

Montana School of Forestry, Missoula, Montana.

Thornberry-Ehrlich, T. 2007. Grant-Kohrs Ranch National Historic Site geologic resource evaluation 

report. Natural Resource Report NPS/NRPC/GRD/NRR—2007/004. National Park Service, 

Denver, Colorado. 

Tickner, D. P., P. G. Angold, A. M. Gurnell, and J. O. Mountford. 2001. Riparian plant invasions: 

Hydrogeomorphological control and ecological impacts. Progress in Physical Geography 

25(1):22-53. 

U.S. Fish and Wildlife Service (USFWS) and St. Mary’s University of Minnesota Geospatial 

Services (SMUMN GSS). 2007. National Wetlands Inventory data for Powell County, Montana. 

http://www.fws.gov/wetlands/ (accessed 12 December 2014). 

Winward, A. H. 2000. Monitoring the vegetation resources in riparian areas. General Technical 

Report RMRS-GTR-47. U.S. Forest Service, Rocky Mountain Research Station, Ogden, Utah. 

Wood, S. D., and D. L. J. Rew. 2005. Non-native plant survey at Grant-Kohrs Ranch National 

Historic Site. Montana State University, Bozeman, Montana. 
79 

4.3 Pastures and Hayfields

4.3.1 Description

Pastures and hayfields were critical to the western ranches of the late 19th and early 20th centuries and 

are a key component of GRKO today. Pastures provide forage for livestock during the growing 

season, while hayfields are harvested to feed livestock through the winter. Ranchers often converted 

bottomlands and rich meadows to irrigated crop fields in order to meet the needs of their herds. At 

GRKO, many of the native plant communities were altered or replaced with pasture grasses as early 

as the 1870s (Rice et al. 2012). European grasses were introduced in an effort to increase hay 

production. By the 1930s, approximately 365 ha (900 ac) were in cultivation at GRKO (Photo 15; 

Rice et al. 2012). Starting in 1862, many of these fields were flood or sub-irrigated with water 

diverted through ditches from the Clark Fork or its western tributaries, a practice that continues to 

this day (NPS 2011a, Rice et al. 2012). The current Kohrs-Manning Ditch is believed to include 

portions of the earliest ditches excavated by Johnny Grant, one of the first ranchers in the valley in 

the late 1850s and early 1860s (Shapins Belt Collins 2009). 

Photo 15. Historic haying operations at the ranch, circa 1937 (NPS photo, from GRKO archives).

Currently, around 60% of GRKO consists of irrigated pastures and hayfields (Rice et al. 2012). 

These areas provide visitors with an opportunity to view a vast open range landscape, stand in 

healthy pastures and hayfields, and experience haying with horses (NPS 2008a). The majority of 

hayfields lie just west of the Clark Fork, extending up wide gullies into the upland grasslands (Figure 

20). Additional sub-irrigated fields are found in the southeast portion of the park, while pastures in 

the northeast have recently been sprinkler irrigated with treated effluent from the municipal sewage 

system (Rice et al. 2012). GRKO’s goal with regard to these hayfields is to maintain sustained yields 

“to ensure that the continued historic and cultural landscape remains indefinitely” (Olson and Leinard 
80 

2013, p. 29). Hayfields can also 

serve as pastures for cattle after 

the hay is harvested in late 

summer or fall (NPS 2011a). 

The irrigated hayfields and 

pastures are dominated by 

introduced grasses such as 

smooth brome, timothy (Phleum 

pratense), quackgrass, Kentucky 

bluegrass (Poa pratensis), 

meadow fescue (Festuca 

pratensis), and redtop (Shapins 

Belt Collins 2009, Rice et al. 

2012; Photo 16). Additional 

grasses that occur in these areas, 

including some native species, are 

western wheatgrass, meadow 

foxtail (Alopecurus pratensis), 

crested wheatgrass (Agropyron 

cristatum), needle-and-thread, 

and orchardgrass (Dactylis 

glomerata). Hayfield community 

composition is variable over time, 

since many fields have been 

seeded with several grass species, 

and the dominance of these 

species is dependent on the amount, timing, 

and distribution of water (irrigation and 

subsurface flow) (Rice et al. 2012). 

Several of the hayfields at GRKO have 

been designated as prime farmland by the 

U.S. Department of Agriculture (USDA). 

These areas include Taylor Field and 

portions of the West Fields with Varney 

Clay Loam and Con Loam soils and 0-4% 

slopes (NPS 2011a). Prime farmland is 

“land that has the best combination of 

physical and chemical characteristics for 

producing food, feed, fiber, forage, oilseed, 

and other agricultural crops with minimum 

inputs of fuel, fertilizer, pesticides, and 

Photo 16. An irrigated hayfield at GRKO with 

introduced pasture grasses (NPS photo).

Figure 20. Irrigated pastures and hayfields of GRKO.
81 

labor, and without intolerable soil erosion, as determined by the Secretary [of Agriculture]” (7 USC 

73 §§ 4201 et seq., 1981) (NPS 2011a). GRKO’s protected prime farmlands are a valuable resource, 

as prime farmlands are threatened with conversion across the country and in Montana. Between 1982 

and 2007, 9,227 ha (22,800 ac) of prime farmland were converted to developed land across Montana 

(Farmland Information Center 2010). 

4.3.2 Measures

• Hay and forage production (tons per acre)

• Abundance of invasive vs. desired species 

• Hay nutrient analysis 

4.3.3 Reference Conditions/Values

Each of the measures listed above has a separate reference condition. For hay and forage production, 

reference condition will be taken from the recently completed soil survey (NPS 2013a). Production 

estimates vary by rangeland sites (described in NRCS 1982) and include numbers for normal, 

favorable, and unfavorable years (Table 24). The normal year estimates will be the reference 

condition for this assessment. Based on this information, the majority of fields at GRKO (Big and 

Little Gulch, Upper and Lower Taylor, and the West Fields) will have an estimated production of 0.6 

tons/acre in a normal year. Only Stuart Field and Bull Pasture have a higher estimated production, 

with 1.75 tons/acre. These estimates are without irrigation, which typically increases production. 

Table 24. Productivity estimates (without irrigation) by rangeland site and soil map unit (NPS 2013a). P.Z. 

= precipitation zone. 

Rangeland Site Soil map units Total dry-weight production (tons/ac)

Favorable year Normal year Unfavorable 

year

Silty, 10-14” P.Z. 24B, 24C, 24D, 31B, 31C, 

34B, 36C, 36D, 351E

0.75 0.6 0.4

Wet meadow, 10-14” P.Z. & 

15-19” P.Z.

109, 635, 735, 835 2.25 1.75 1.0

Shallow to gravel, 10-14” P.Z. 132B, 132C, 332B 0.55 0.4 0.2

Subirrigated, 10-14” P.Z. 444, 545 1.25 1.0 0.75

With regard to the abundance of invasive and desired plant species, the reference condition selected 

by park managers is no more than 1% invasive species. Grasses or other plants that are non-native 

but were planted for ranching purposes are considered desired species, not invasive species. For hay 

nutrients, the reference condition will be the beef cattle nutrient requirements published by the 

National Research Council (NRC 2000). These nutrient requirements vary with the condition of the 

animal (e.g., age, sex, weight, gestating, lactating, etc.). For the purpose of this assessment, GRKO 

staff selected three conditions that are common for cattle at the ranch, to provide a general idea of 

what the nutrient requirements of the herd may be (Table 25).
82 

Table 25. Beef cattle nutrient requirements (in % of dry matter) from NRC (2000). TDN = total digestible 

nutrients, CP = crude protein, Ca = calcium, P = phosphorous, BCS = body condition score, ADG = 

average daily gain (weight in pounds).

TDN CP Ca P

1,200 lb mature weight pregnant yearling replacement 

heifer, middle 1/3 of pregnancy, BCS=5 at 850 lbs, 1.5 ADG 56% 9.1% 0.41% 0.18%

1,200 lb lactating cow, 20 lb peak milk 58% 9.8% 0.28% 0.19%

2,000 lb mature bull at 1,500 lbs, 0.5 ADG 50% 7.0% 0.17% 0.12%

4.3.4 Data and Methods

Hay and forage production data and hay nutrient analysis information for 2008-2013 were provided 

by GRKO. Hay nutrient analyses were performed by Montana State University (MSU) in 2008, by 

AgSource Laboratories in 2013, and by Midwest Laboratories, Inc. from 2009-2012 and in 2014. 

Information regarding the abundance of invasive and desired species was calculated from ROMN 

vegetation monitoring data for 2009-2012 (ROMN 2009, 2010, 2011, 2012). Only data from 

monitoring plots located in hayfields or pastures (as mapped by Rice et al. 2012) were used in this 

assessment. Invasive species included those listed as noxious by the state of Montana, those treated 

by the NRM EPMT, any species identified as “non-contributing” features in the GRKO cultural 

landscape report (Shapins Belt Collins 2009), and additional species identified by park staff (Smith, 

email communication, 17 September 2014). SMUMN GSS analysts highlighted invasive species 

within ROMN percent cover data and added the percentages to determine invasive species abundance 

by plot. Each sampling location included 10 plots along three different transects. The percent 

invasive species from each plot was then averaged, resulting in overall mean invasive species 

abundance by sampling location. The number of hayfield/pasture locations sampled each year ranged 

from four in 2009 to eight in 2011 and 2012. 

4.3.5 Current Condition and Trend

Hay and Forage Production 

Annual forage production by field from 2008-2013 is presented in Table 26. Yields during this time 

typically ranged between 1 and 2 tons per acre, with annual means for all fields combined of 1.4 to 

1.7 tons per acre. 

Table 26. Forage production in GRKO hayfields, 2008-2013 (NPS 2008b, 2009a, 2010, 2011b, 2012, 

2013b).

Year Field Acres harvested Hay harvest (tons) Yield (tons/ac)

20081 Big Gulch 35.1 36.6 1.0

Little Gulch 17.0 22.5 1.3

Taylor 38.0 67.4 1.8

Stuart 18.6 44.9 2.4

Stuart - loose hay 6.7 16.3 (approx.) --

Bull Pasture 8.8 10.9 1.2

West Field 1 47.0 67.4 1.4

West Field 2 26.7 31.7 1.2

Totals 197.9 297.6 1.5
83 

Table 26. Forage production in GRKO hayfields, 2008-2013 (NPS 2008b, 2009a, 2010, 2011b, 2012, 

2013b) (continued).

Year Field Acres harvested Hay harvest (tons) Yield (tons/ac)

2009 Big Gulch 45.4 57.2 1.3

Little Gulch 17.7 23.6 1.3

Lower Taylor 62.1 97.5 1.6

Upper Taylor 15.3 30.4 2.0

Stuart 25.3 52.1 2.1

West Field 1 49.7 60.6 1.2

West Field 3 28.0 5.1 0.2

Totals2 216 (244) 321 (326) 1.5 (1.3)

2010 Big Gulch 45.1 60.9 1.3

Little Gulch 6.1 10.4 1.7

Lower Taylor 63.6 104.3 1.6

Upper Taylor 16.6 24.3 1.5

Stuart 25.3 47.8 1.9

West Field 1 52.6 80.0 1.5

West Field 2 40.1 53.9 1.3

West Field 3 19.4 17.4 0.9

Totals 269 399 1.5

2011 Big Gulch 55.6 100.2 1.8

Little Gulch 12.7 24.5 1.9

Lower Taylor 63.7 105.5 1.7

Upper Taylor 15.5 29.8 1.9

Stuart 24.9 54.2 2.2

West Field 1 51.6 83.1 1.6

West Field 2 38.2 57.3 1.5

West Field 3 5.1 5.1 1.0

Totals 267 446 1.7

2012 Big Gulch 45.6 79.3 1.7

Little Gulch 14.0 20.1 1.7

Lower Taylor 63.9 77.4 1.2

Upper Taylor 16.3 30.1 1.8

Stuart 25.3 45.2 1.8

West Field 1 51.3 66.9 1.3

West Field 2 39.8 49.7 1.2

West Field 3 10.7 6.8 0.6

Totals 267 376 1.4

2013 Big Gulch 53.0 90.3 1.7

Little Gulch 16.8 23.6 1.4

Lower Taylor 65.0 94.0 1.4

Upper Taylor 16.6 28.9 1.7

Stuart 24.4 43.3 1.8

West Field 1 52.9 87.8 1.7

West Field 2 40.5 63.1 1.6

Totals 269 431 1.6 1 In 2008, total harvest was not weighed, but the number of bales was recorded; 14 bales were weighed and 

averaged 6o lbs. Hay harvests for 2008 were estimated by SMUMN GSS based on the number of bales and the 60 

lb. average per bale.

2 West Field 3 was not scheduled for hay production and, as a result, was not irrigated, but was cut for hay in order to 

perform ditch and field maintenance in 2010. Therefore, annual totals and averages are calculated first without West 

Field 3, and with West Field 3 in parentheses.
84 

Nearly every field met or exceeded the estimated production numbers from the GRKO soil survey 

(NPS 2013a) for a normal year (see Table 24). Annual yields for the most frequently harvested fields 

in comparison to the selected reference condition are shown in Figure 21. Many fields exceeded the 

“favorable year” production estimate of 0.75 tons/acre. Stuart Field was consistently the most 

productive field, likely due to its soil type. 

Figure 21. Forage yield (tons/acre) by field and overall for GRKO from 2008-2013 (NPS 2008b, 2009a, 

2010, 2011b, 2012, 2013b). The black dashed line represents the estimated production of 0.6 tons/acre in 

a normal year for all fields shown except Stuart. The red dashed line represents the estimated production 

of 1.75 tons/acre in a normal year, the reference condition for Stuart Field. 

Abundance of Invasive vs. Desired Species 

The earliest documentation of invasive species abundance in GRKO was during efforts to suppress 

Canada thistle (Cirsium arvense) in the West Fields during the early 2000s (Rice and Hardin 2004). 

In 2001, the frequency of Canada thistle in these four fields ranged from 11.5% to 19.9%, with a 

mean of 15.4% (Rice and Hardin 2004). Three of the four fields were then treated with herbicide in 

2002 and 2003, while one was left untreated as a control. After 2 years of treatment, the frequency of 

Canada thistle in the three treated fields decreased to a mean of 1.8% while frequency in the 

untreated field increased in 2002 and then decreased to 6.9% in 2003 (Rice and Hardin 2004). 

The first ranch-wide efforts to quantify invasive species abundance occurred during a 2003 nonnative plant survey (Wood 2005). This survey found that several of GRKO’s hayfields had large and 

complex infestations (Wood 2005), particularly of Canada thistle and field bindweed (Convolvulus 

arvensis). The affected fields, percent of the field infested, and estimated percent cover (i.e., 

abundance) of the invasive species are presented in Table 27. Based on these estimates, the three 

listed fields would not have met the reference condition of no more than 1% invasive species. 

0

0.5

1

1.5

2

2.5

3

Big Gulch Little Gulch Lower

Taylor

Upper

Taylor

Stuart West Field

1

West Field

2

Mean - all

GRKO

fields

Yield (tons/ac)

Field

2008 2009 2010 2011 2012 2013
85 

Table 27. GRKO hayfields with large infested areas identified during the 2003 non-native plant survey 

(Wood 2005).

Field Species % of Field Infested Est. % Cover

Lower Taylor Convolvulus arvensis 50 2

Cirsium arvense 80 5

Big Gulch Cirsium arvense 50 5

Little Gulch Convolvulus arvensis 30 10

The current abundance of invasive versus desired plant species varies greatly across GRKO, 

depending on environmental factors and land history. According to ROMN sampling data, some 

hayfield sub-plots are weed-free, while a few are dominated by invasives (ROMN 2009-2012). Table 

28 shows the abundance of invasive species by ROMN sampling location (a mean across 10 plots) 

during 4 years of monitoring and the percent of plots meeting the selected reference condition of no 

more than 1% invasive species. The invasive species of highest concern are those designated as 

noxious weeds by the state of Montana, and species identified as “high priority” by the NRM EPMT. 

Therefore, SMUMN GSS analysts also calculated the abundance of these invasives alone. Data show 

that lower priority invasive species, such as common dandelion (Taraxacum officinale), made up a 

relatively large percentage of invasives in several fields, frequently pushing locations above the 1% 

reference condition. With all invasive species included, only five of the 25 locations (20%) sampled 

from 2009-2012 had an invasives abundance of 1% or less. When only state-designated noxious 

weeds and high priority species are considered, the number increases to 17 out of 25 (68%). 

Sampling locations and whether or not they met the reference condition are shown in Figure 22. 

Table 28. Invasive species abundance by ROMN sampling location (ROMN 2009-2012). The middle 

column contains mean percent cover of all invasive species (10 plots per location) while the final column 

contains the percent cover when lower priority species are subtracted. The reference condition for this 

measure is no more than 1% invasive species. Note that results are not comparable between years, as 

different locations were sampled each year.

Sampling Location Total % Invasives % Invasives without 

Lower Priority Species

2009

 GRKO_001_05 7.1 3.6

 GRKO_012_04 0 0

 GRKO_028_01 0.3 0.1

 GRKO_033_01 16 13.1

% of plots meeting reference 50% 50%

2010

 GRKO_001_06 5 1.2

 GRKO_005_05 0.5 0.3

 GRKO_012_05 0.5 0.1

 GRKO_037_01 2.8 0.4

 GRKO_043_01 1.6 1.1

% of plots meeting reference 40% 60%
86 

Table 28. Invasive species abundance by ROMN sampling location (ROMN 2009-2012). Note that results 

are not comparable between years, as different locations were sampled each year. (continued)

Sampling Location Total % Invasives % Invasives without 

Lower Priority Species

2011

 GRKO_007_06 15.7 0.2

 GRKO_008_05 1.6 0.7

 GRKO_009_04 3 0.2

 GRKO_010_04 1.4 0

 GRKO_011_05 0.8 0.2

 GRKO_015_03 1.4 0.2

 GRKO_016_04 7.5 6.6

 GRKO_020_04 7.2 4.3

% of plots meeting reference 12.5% 75%

2012

 GRKO_015_04 2.2 0.4

 GRKO_016_05 10.2 8.1

 GRKO_018_02 9.4 0.9

 GRKO_019_02 1.9 0

 GRKO_021_02 9.1 0.2

 GRKO_022_02 7.9 0.1

 GRKO_024_02 4.5 2.3

 GRKO_027_04 1.3 0.5

% of plots meeting reference 0% 75%

Total % of plots meeting 

reference over all years 20% 68%
87 

Figure 22. ROMN sampling sites in GRKO hayfields, 2009-2012, that met the reference condition of no 

more than 1% invasive species (green), met the reference condition when lower priority species such as 

dandelion were excluded (yellow), and that did not meet the reference condition with or without lower 

priority species included (ROMN 2009-2012). 

Threats and Stressor Factors 

The park’s pastures and hayfields are threatened by invasive species, drought, climate change, 

improper grazing or irrigation practices, unplanned fires, Columbian ground squirrels, and 

grasshopper outbreaks. Invasive plant species are a major concern at GRKO and are recognized 
88 

globally as a significant threat to ecosystem stability 

(NPS 2008c, Rice et al. 2012). Some invasives can 

alter ecosystems by changing soil chemistry and water 

availability, which are particularly important in 

hayfields (NPS 2008c). At GRKO, invasive plants 

also threaten the cultural landscape the park was set 

aside to protect, and often reduce forage quality in the 

pastures and hayfields (NPS 2011a, Manier et al. 

2011). Invasive species common in GRKO’s hayfields 

include Canada thistle (Photo 17), field bindweed, and 

annual weeds from the Brassicaceae family, such as 

field pennycress (Thlaspi arvense), herb sophia 

(Descurainia sophia), and madworts (Alyssum spp.) 

(Wood 2005, Rice et al. 2012). The park has used 

mowing to reduce seed production of annual weeds in 

irrigated pastures and has experimented with 

prescribed grazing (e.g., training livestock to eat weeds) to reduce Canada thistle and other invasive 

plants (NPS 2011a). However, there is no evidence that prescribed grazing has been effective. 

Further information on changes in invasive species coverage throughout the park over the past 

decade can be found in Appendix E. 

Two processes that are a natural part of grassland ecosystems - grazing and fire - can be stressors to 

hayfields that are managed for forage production. Unplanned fires have the potential to destroy the 

entire crop in a hayfield, and may cause erosion or nutrient loss if the ash from the burned vegetation 

is blown or washed off the field. Overgrazing, particularly during peak vegetative growth periods, 

reduces the amount of leaf area to capture sunlight and generate energy for growth; if fields are not 

given time to recover, stand vigor can be reduced (Olson and Leinard 2013). Milchunas et al. (1994) 

found that heavy grazing (60% consumption) over long periods (25-50 years) can reduce forage 

production by 12-18% in dry or average years. Grazing when soils are wet often causes soil 

compaction, which can affect plant growth and field productivity (da Silva et al. 2003). 

Columbian ground squirrels play an important role in natural ecosystems, as their digging activity 

creates habitat diversity and improves soil aeration and moisture retention (MDA 2013). However, in 

agricultural areas, this digging may contribute to soil erosion and create disturbed areas where 

invasive species can colonize. The squirrel’s feeding and digging can cover and kill crops, which 

reduces forage production. Additionally, their holes are a possible hazard for grazing livestock and 

can damage harvesting equipment (MDA 2013). At GRKO, ground squirrels occasionally burrow 

into irrigation ditches, which can weaken the ditches and eventually cause them to wash out (Shapins 

Belt Collins 2009). Grasshoppers are also an important natural part of western ecosystems, but 

increased herbivory during population outbreaks often results in serious forage losses (Branson et al. 

2006). Large outbreaks could temporarily reduce the productivity of GRKO’s hayfields and pastures. 

Photo 17. Canada thistle (NPS photo, 

courtesy of Rocky Mountain National Park).
89 

Climate has a strong influence on vegetation communities, both directly and indirectly through its 

impact on ecological processes (e.g., nutrient cycling, erosion) (McWethy et al. 2010). Climate 

change is projected to trigger more frequent dry periods (droughts) the western U.S. during the 21st

century, due to increased temperatures and evapotranspiration, as well as changes in surface 

hydrology (Gray and Andersen 2009, as cited by McWethy et al. 2010). Snowmelt and peak runoff 

were already occurring earlier on average in the last half of the 20th century, reducing surface water 

storage and river baseflows during the summer months (McWethy et al. 2010). This would likely 

impact the amount of water available for irrigation of hayfields at GRKO. An increase in drought 

frequency or duration could also impact grassland composition and production, while climate 

warming may influence plant phenology (Loehman 2009, Bloor et al. 2010) and forage quality 

(Craine et al. 2010). Since GRKO receives an average of only 26.9 cm (10.6 in) of precipitation 

annually (NPS 2009b), any small change in the amount or timing of this precipitation would likely 

influence plant growth and species composition (Peter Rice, University of Montana Research 

Ecologist, written communication, January 2015). 

Data Needs/Gaps

A recently completed best management practices (BMP) plan for GRKO (Olson and Leinard 2013) 

recommends establishing sustainable and realistic yield goals for hayfields, “based on soil 

productivity, information from the soil survey, historical yield data, climatic conditions, level of 

management and/or local research on similar soil, cropping systems, and soil and manure/organic 

byproducts tests” (Olson and Leinard 2013, p. 30). It also suggests utilizing a “nutrient budget” for 

nitrogen, phosphorus, and potassium, to track all nutrients applied to hayfields and pastures. Potential 

nutrient sources to be considered include commercial fertilizer, animal manure, crop residue, legume 

credits, and irrigation water (Olson and Leinard 2013). 

Beginning in 2015, effluent from the city’s sewage system will no longer be used to irrigate pastures 

in the northeast section of the park (NPS 2014). A plan is needed for managing these fields once this 

water source is no longer available.

Overall Condition 

Hay and Forage Production 

Hay and forage production was assigned a Significance Level of 3. Nearly all hayfields harvested 

from 2008-2013 met or exceeded the production estimates established in the recent GRKO soil 

survey (NPS 2013a). As a result, this measure is assigned a Condition Level of 0, meaning it is 

currently of no concern. 

Abundance of Invasive vs. Desired Species 

This measure was also assigned a Significance Level of 3. Invasive species have long been an issue at 

GRKO, and are a particular concern in pastures and hayfields where they can reduce forage quality. 

Recent ROMN vegetation sampling shows that invasive species abundance is highly variable across 

the park. Of the 25 irrigated pasture and hayfield locations sampled by the ROMN, only five (20%) 

met the selected reference condition of 1% or less invasive species abundance. However, when only 
90 

“high priority” species are considered, the number of locations meeting the reference condition 

increases to 17 (68%). Therefore, this measure is of moderate concern (Condition Level = 2). 

Hay Nutrient Analysis 

The project team assigned this measure a Significance Level of 1. Measures with a Significance Level

of 1 are not discussed in detail in the Current Condition section of this text, rather they are briefly 

summarized here in the Overall Condition section. The low significance of this measure is due 

partially to the fact that hay nutrient levels can be influenced by so many factors other than the 

condition of the vegetation itself. For example, nutrient levels are affected by the life stage at which 

the plant is cut, how long the hay lays in the field before being baled, or if it is rained on before being 

baled (Smith, written communication, January 2015). Hay nutrient analyses were performed for 

several GRKO fields between 2008 and 2013 (Table 29). When compared to beef cattle nutrient 

requirements (see Table 25), it appears that hay from most GRKO fields sampled are meeting the 

nutritional needs of at least two of the three selected cattle conditions. Crude protein (CP) values 

appear to fall below nutrient requirements most often, with four fields falling below the requirements 

for all three selected cattle conditions, each in a different year. Calcium (Ca) levels consistently meet 

requirements while phosphorous (P) levels are regularly just below the requirements for lactating and 

pregnant cows. These results are typical for the type of grass species in GRKO’s hayfields (Smith, 

email communication, 25 September 2014). The USDA Agricultural Marketing Service adopted 

grass hay quality guidelines based on crude protein content (USDA 2003); the majority of GRKO 

fields would fall into the “fair” category (5-9%) with a few results in the “good” category (9-13%) 

(Table 29). This measure was assigned a Condition Level of 1, indicating low concern. It is 

interesting to note that the total digestible nutrients (TDN) results that fall below requirements are 

from the 2 years when analyses were not performed by Midwest Laboratories (2008, 2012). The 

variance in results could be due to differences in analytical methods rather than actual variance in 

hay nutrient levels. 

Table 29. Hay nutrient analysis (MSU 2008, Midwest Laboratories 2009, 2010, 2012, 2014, AgSource 

Laboratories 2013). TDN = total digestible nutrients, CP = crude protein, Ca = calcium, P = phosphorous. 

Red numbers indicate results that are below the nutrient requirements for all three cattle conditions 

selected by GRKO staff while purple numbers are below just one or two of the nutrient requirements 

among the three conditions (typically lactating and/or pregnant cows).

Year Field TDN CP Ca P

20081 Big Gulch 53.5% 6.5%

Little Gulch-Taylor 53.4% 7.5%

Stuart-Bull Pasture 53.2% 7.5%

West Field 1 and 2 52.8% 6.9%

2009 Big Gulch-Little Gulch 68.9% 6.73% 0.56% 0.16%

Stuart 63.2% 7.18% 0.56% 0.15%

Lower Taylor 63.8% 7.84% 0.51% 0.17%

Upper Taylor 61.7% 13.3% 1.30% 0.25%

2010 Upper Taylor 10.4% 0.49% 0.21%

Lower Taylor 7.18% 0.38% 0.17%

Stuart 7.21% 0.60% 0.15%

West Field 1 6.45% 0.58% 0.15%

West Field 2 7.33% 0.52% 0.16%
91 

Table 29. Hay nutrient analysis (MSU 2008, Midwest Laboratories 2009, 2010, 2012, 2014, AgSource 

Laboratories 2013). TDN = total digestible nutrients, CP = crude protein, Ca = calcium, P = phosphorous. 

Red numbers indicate results that are below the nutrient requirements for all three cattle conditions 

selected by GRKO staff while purple numbers are below just one or two of the nutrient requirements 

among the three conditions (typically lactating and/or pregnant cows). (continued)

Year Field TDN CP Ca P

2011 Lower Taylor 67.3% 9.36% 0.85% 0.19%

Upper Taylor 65.4% 13.0% 1.08% 0.23%

Stuart 63.2% 7.89% 0.96% 0.16%

West Side 66.8% 7.94% 0.65% 0.17%

Weed free 65.5% 9.07% 0.83% 0.17%

20122 Stuart 47.7% 6.8% 0.33% 0.17%

West Field 1 - North 48.1% 7.0% 0.21% 0.19%

West Field 1 - South 49.0% 8.1% 0.41% 0.18%

2013 Big Gulch-West Field 2 61.4% 7.45% 0.56% 0.14%

Taylor 64.2% 9.8% 0.78% 0.21%

1 TDN values for 2008 are reported on an “as received” basis (i.e., before drying), not as % dry matter. Dry matter 

values would likely be slightly higher.

2 According to lab reports, TDN values from this year are estimates. 

Weighted Condition Score 

The Weighted Condition Score for GRKO’s pastures and hayfields is a 0.33, indicating the resource 

is in good condition. However, this score is at the top of the good condition range, and a small 

decline in condition could shift the resource into the “moderate concern” range. The measures 

considered in this assessment have been relatively consistent in recent years, suggesting the condition 

of this community is stable.

Pastures and Hayfields

Measures Significance 

Level

Condition 

Level WCS = 0.33 

Hay/Forage 

Production 3 0 

Abundance of 

Invasive vs. Desired 

Species

3 2 

Hay Nutrient 

Analysis 1 1 
92 

4.3.6 Sources of Expertise

Jason Smith, GRKO Natural Resource Specialist 

Peter Rice, University of Montana Research Ecologist

Bret Olson, Professor of Range Ecology, Montana State University 
93 

4.3.7 Literature Cited

AgSource Laboratories. 2013. Hay nutrient analysis, 2012 crop. AgSource Laboratories, Jerome, 

Idaho. 

Bloor, J. M. G., P. Pichon, R. Falcimagne, P. Leadley, and J. Soussana. 2010. Effects of warming, 

summer drought, and CO2 enrichment on aboveground biomass production, flowering 

phenology, and community structure in an upland grassland ecosystem. Ecosystems 13:888-900. 

Branson, D. H., A. Joern, and G. A. Sword. 2006. Sustainable management of insect herbivores in 

grassland ecosystems: New perspectives in grasshopper control. Bioscience 56(9):743-755. 

Craine, J. M., A. J. Elmore, K. C. Olson, and D. Tolleson. 2010. Climate change and cattle 

nutritional stress. Global Change Biology 16:2901-2911. 

da Silva, A. P., S. Imhoff, and M. Corsi. 2003. Evaluation of soil compaction in an irrigated shortduration grazing system. Soil and Tillage Research 70:83-90. 

Farmland Information Center. 2010. 2007 NRI: Changes in land cover/use - data tables. 

http://www.farmlandinfo.org/sites/default/files/FIC_NRI%202007%20Data%20Tables.pdf 

(accessed 8 September 2014). 

Gray, S., and C. Andersen. 2009. Assessing the future of Wyoming’s water resources: Adding 

climate change to the equation. William D. Ruckelshaus Institute of Environment and Natural 

Resources. University of Wyoming, Laramie, Wyoming. 

Loehman, R. 2009. Understanding the science of climate change: Talking points - impacts to prairie 

potholes and grasslands. Natural Resource Report NPS/NRPC/NRR—2009/138. National Park 

Service, Fort Collins, Colorado. 

Manier, D., D. Shorrock, E. W. Schweiger, I. Ashton, B. Frakes, M. Britten, D. Pillmore, and J. 

Burke. 2011. Rocky Mountain Network vegetation composition structure and soils monitoring 

protocol: Small park grasslands, shrublands, and woodlands; Version 1.0. Natural Resource 

Report NPS/ROMN/NRR-2011/383. National Park Service, Fort Collins, Colorado. 

McWethy, D. B., S. T. Gray, P. E. Higuera, J. S. Littell, G. T. Pederson, A. J. Ray, and C. Whitlock. 

2010. Climate and terrestrial ecosystem change in the U.S. Rocky Mountains and Upper 

Columbia Basin: Historical and future perspectives for natural resource management. Natural 

Resource Report NPS/GRYN/NRR—2010/260. National Park Service, Fort Collins, Colorado. 

Midwest Laboratories, Inc. 2009. Hay nutrient analysis, 2009. Midwest Laboratories, Inc., Omaha, 

Nebraska. 

Midwest Laboratories, Inc. 2010. Hay nutrient analysis, 2010. Midwest Laboratories, Inc., Omaha, 

Nebraska. 
94 

Midwest Laboratories, Inc. 2012. Hay nutrient analysis, 2011 crop. Midwest Laboratories, Inc., 

Omaha, Nebraska. 

Midwest Laboratories, Inc. 2014. Hay nutrient analysis, 2013 crop. Midwest Laboratories, Inc., 

Omaha, Nebraska. 

Milchunas, D. G., J. R. Forwood, and W. K. Lauenroth. 1994. Productivity of long-term grazing 

treatments in response to seasonal precipitation. Journal of Range Management 47:133-139. 

Montana Department of Agriculture (MDA). 2013. The Columbian ground squirrel: Its biology and 

control. Montana Department of Agriculture, Helena, Montana. 

Montana State University (MSU). 2008. Hay nutrient analysis, 2008. Agriculture Experiment Station 

Analytical Laboratory, Montana State University, Bozeman, Montana. 

National Park Service (NPS). 2008a. Grant-Kohrs Ranch National Historic Site: Foundation for 

planning and management. National Park Service, Deer Lodge, Montana. 

National Park Service (NPS). 2008b. 2008 Fields cut for hay: Grant-Kohrs Ranch. National Park 

Service, Deer Lodge, Montana.

National Park Service (NPS). 2008c. Exotic plant management team: 2008 annual report. National 

Park Service, Biological Resources Management Division, Fort Collins, Colorado. 

National Park Service (NPS). 2009a. Grant-Kohrs Ranch NHS: 2009 fields cut for hay. National Park 

Service, Deer Lodge, Montana.

National Park Service (NPS). 2009b. Annual climate report for Grant-Kohrs Ranch National 

Historic Site, 2007. National Park Service, Deer Lodge, Montana. 

National Park Service (NPS). 2010. Grant-Kohrs Ranch NHS: 2010 fields cut for hay. National Park 

Service, Deer Lodge, Montana.

National Park Service (NPS). 2011a. Northern Rocky Mountains invasive plant management plan. 

National Park Service, Fort Collins, Colorado. 

National Park Service (NPS). 2011b. Grant-Kohrs Ranch NHS: 2011 fields cut for hay. National 

Park Service, Deer Lodge, Montana. 

National Park Service (NPS). 2012. Grant-Kohrs Ranch NHS: 2012 fields cut for hay. National Park 

Service, Deer Lodge, Montana.

National Park Service (NPS). 2013a. Grant-Kohrs Ranch National Historic Site, Montana: Soil 

survey – DRAFT. National Park Service, Fort Collins, Colorado. 

National Park Service (NPS). 2013b. Grant-Kohrs Ranch NHS: 2013 fields cut for hay. National 

Park Service, Deer Lodge, Montana. 
95 

National Park Service (NPS). 2014. Foundation document: Grant-Kohrs Ranch National Historic 

Site. National Park Service, Deer Lodge, Montana. 

National Research Council (NRC). 2000. Nutrient requirements of beef cattle. Seventh edition. 

National Academy Press, Washington, D.C. 

Natural Resources Conservation Service (NRCS). 1982. Technical range site descriptions. Field 

office technical guide, section II-E-8. Natural Resources Conservation Service, Washington, D.C. 

Olson, B., and B. Leinard. 2013. BMP Report: Grant-Kohrs Ranch National Historic Site. National 

Park Service, Deer Lodge, Montana. 

Rice, P. M., and J. Hardin. 2004. Suppression of Canada thistle at the Grant-Kohrs Ranch NHS: Year 

3 progress report. National Park Service unpublished report, Deer Lodge, Montana. 

Rice, P. M., E. W. Schweiger, W. Gustafson, C. Lea, D. Manier, D. Shorrock, B. Frakes, and L. 

O’Gan. 2012. Vegetation classification and mapping project report, Grant-Kohrs Ranch National 

Historic Site. Natural Resource Report NPS/ROMN/NRR—2012/589. National Park Service, 

Fort Collins, Colorado. 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2009. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2009. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2010. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2010. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2011. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2011. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2012. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2012. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Shapins Belt Collins. 2009. Grant-Kohrs Ranch cultural landscape report, part two. National Park 

Service, Fort Collins, Colorado. 

U.S. Department of Agriculture (USDA). 2003. USDA announces hay quality designations for 

nationwide market news reporting. http://www.nass.usda.gov/Statistics_by_State/Kansas/ 

Publications/Crops/Hay/hay01.html (accessed 12 January 2015). 

Wood, S. D. 2005. Non-native plant survey 2004 geodatabase for Grant-Kohrs Ranch National 

Historic Site. ArcGIS geodatabase. National Park Service, Deer Lodge, Montana
96 

4.4 Uplands (Grasslands, Non-irrigated)

4.4.1 Description

The upland grasslands at GRKO primarily occur west of the Clark Fork River, in the southwest 

corner of the park. These rolling foothills with a mix of primarily native and some introduced grass 

species have been utilized for grazing since the beginning of the ranching era (Rice and Hardin 2002; 

Photo 18). The uplands “are among the best examples of native plant communities within the park, 

and they may constitute some of the last native prairie remnants in the Deer Lodge Valley” (Shapins 

Belt Collins 2009, p. 3). The remaining natural character may reflect the fact that these areas were 

historically grazed in the fall, which has less impact on native grasses than grazing in the spring 

when plants are actively growing (Rice et al. 2012). Small patches of native upland grasses also 

occur east of the Clark Fork (e.g., along the railroad bed) (Rice and Hardin 2002). 

Photo 18. Upland grassland within GRKO (Photo by Sarah Gardner, SMUMN GSS 2013).

Rice et al. (2012) identified five different upland grassland types within the GRKO boundary, three 

dominated by native grasses and two types characterized by significant levels of introduced grasses 

(Figure 23). The native grassland types are Bluebunch Wheatgrass - Western Wheatgrass 

(Pseudoroegneria spicata - Pascopyrum smithii) Mixedgrass Prairie, Bluebunch Wheatgrass – Curly 

(or Sandberg) Bluegrass (Pseudoroegneria spicata – Poa secunda) Grassland, and Needle-andThread - Blue Grama - Threadleaf Sedge (Hesperostipa comata – Bouteloua gracilis – Carex 

filifolia) Mixedgrass Prairie. Additional native grasses found in the park include prairie junegrass 

(Koeleria macrantha), green needlegrass, and fescues (Festuca spp.). The two grassland types 

characterized by introduced species are Crested Wheatgrass - (Western Wheatgrass, Needle-andThread Grass) (Agropyron cristatum – [Pascopyrum smithii, Hesperostipa comata]) Semi-natural 

Grassland and Intermediate Wheatgrass (Thinopyrum intermedium) Semi-natural Grassland. The 

Intermediate Wheatgrass Grassland occurs in only a single strip historically seeded along the railroad 

in the northeast part of the park (Rice et al. 2012). The non-native cheatgrass (Bromus tectorum) is 

also found in both the native and semi-natural upland grasslands. 
97 

Upland grasslands have been 

a vital resource throughout 

the ranching era and are still 

utilized for grazing within 

GRKO today. Given the 

purpose of GRKO (to 

preserve and interpret this 

historical period), the 

maintenance of this unique 

landscape and plant 

community is very important 

to park staff (Shapins Belt 

Collins 2009). 

4.4.2 Measures

• Range Condition/ 

Similarity Index 

• Rangeland Health (17 

indicators) 

• Ecological effect size 

(A) 

4.4.3 Reference 

Conditions/Values

Reference conditions for 

GRKO’s upland grasslands 

can be found in Mueggler and 

Stewart (1980) and in NRCS range site descriptions (NRCS 1982). Mueggler and Stewart (1980) 

studied grasslands and shrublands in western Montana and generated a habitat type classification 

system for these habitats in the region. Six of the grassland habitat types identified by Mueggler and 

Stewart (1980) occur within GRKO. Information provided in their report includes plant species 

composition, physical characteristics (e.g., landscape position, soils), productivity, and responses to 

grazing and fire. 

Technical range sites are classified based on geography/location, soil characteristics, and 

precipitation zones. Range site descriptions (NRCS 1982) provide information similar to that in 

Mueggler and Stewart (1980) and also provide a guide to initial stocking rates (for grazing purposes). 

The majority of upland grasslands at GRKO fall within the silty 10-14” precipitation zone (P.Z.) 

technical range site, with just a few small areas of shallow to gravel 10-14” P.Z. range sites. 

According to the NRCS (1982) description for silty 10-14” P.Z. range sites, these grasslands are 

typically composed of 93% graminoids, 5% forbs, and 2% woody species. Common species and 

percent composition ranges are listed in Table 30. With grazing pressure, palatable grasses like 

Figure 23. Location of upland grassland vegetation types within 

GRKO (Rice et al. 2012).
98 

bluebunch wheatgrass and green needlegrass tend to decrease, while prairie junegrass, needle-andthread, and western wheatgrass increase (NRCS 1982). According to the range site description, 

species most likely to invade include cheatgrass, leafy spurge, knapweed, and toadflax. 

Table 30. Typical plant species composition of silty 10-14” P.Z. rangeland sites (NRCS 1982).

Scientific name Common name % Composition

Graminoids

Pseudoroegneria spicata bluebunch wheatgrass 60-80

Festuca campestris rough fescue* 0-30

Nassella viridula green needlegrass 0-5

Festuca idahoensis Idaho fescue* 0-5

Hesperostipa comata needle-and-thread 0-5

Pascopyrum smithii western wheatgrass 0-5

Carex spp. sedges 0-5

other native perennial grasses 5-15

Forbs

Lupinus spp. lupine

4-7 

Astragalus spp. milkvetch

Heterotheca villosa hairy goldenaster

Vicia americana American vetch

Gaillardia spp. blanketflower

Phlox spp. phlox

Lomatium spp. desert parsley, biscuitroot

Antennaria spp. pussytoes

other native perennial forbs

Woody species

Krascheninnikovia spp. winterfat

0-5 Artemisia tridentata big sagebrush

Tetradymia spp. horsebrush

other native shrubs

* Rough and Idaho fescue usually occur near the upper end of the P.Z. or in favorable, sheltered pockets.

For the purposes of this assessment, the reference condition for the Range Condition measure will be 

scores in the good or excellent range, while the reference condition for Rangeland Health will be 

ratings in the “none to slight” category. 

4.4.4 Data and Methods

Vegetation surveys were conducted at GRKO in the early 1980s (Rice and Ray 1984) and in 2002 

(Rice and Hardin 2002). A vegetation classification and mapping project was completed for the park 

in 2012 (Rice et al. 2012). The initial mapping and community typing primarily used the Mueggler 

and Stewart (1980) classifications for the uplands, then in the post accuracy assessment stage these 

were cross-walked to the classification followed the National Vegetation Classification Standards

(NVCS) established by the Federal Geographic Data Committee (FGDC). Additional information on 

GRKO vegetation, particularly invasive species, was obtained from NRM EPMT reports (NPS 2011, 

2012) and Rice (2003). The GRKO cultural landscape report for upland pastures (Shapins Belt 

Collins 2009) identified contributing (i.e., culturally acceptable) and non-contributing (undesirable or 

invasive) plant species for the upland grassland landscape.
99 

The ROMN recently established a Vegetation Composition, Structure and Soils (VCSS) protocol for 

small parks (Manier et al. 2011) that includes GRKO. This protocol utilizes transect and plot-based 

methods to estimate cover and frequency of vegetation, litter, bare ground extent, and invasive 

species. Field crews also recorded evidence of disturbance, both natural and human-induced. See 

Manier et al. (2011) for a detailed description of methods. Results from 2009 monitoring at GRKO 

are found in Shorrock et al. (2010). 

Two common methods for assessing the condition of grazed grasslands are Range 

Condition/similarity index and Rangeland Health. As explained in Chapter 4.1 of this assessment, 

Range Condition is determined by comparing the present vegetation community on a “range site” to 

a historic reference (the “climax” community) (Pellant et al. 2005). Lower scores do not necessarily 

indicate lower ecosystem function, they simply mean that there are lower percentages of the climax 

plant community represented (i.e., a greater percentage of earlier successional stages). Range 

Conditions and similarity indices were determined for four upland grasslands at the ranch during the 

summer of 2014. The methodology utilized at GRKO is described in Chapter 4.1. 

Rangeland Health, in contrast, focuses on the integrity of soils, ecological processes (e.g., water and 

nutrient cycling), and the ecosystem as a whole (Pellant et al. 2005). Rangeland Health Assessment 

methods are intended to, “provide a preliminary evaluation of soil/site stability, hydrologic function, 

and biotic integrity (at the ecological site level)” and “provide early warnings of potential problems 

and opportunities by helping land managers identify areas that are potentially at risk of degradation 

or where resource problems currently exist” (Pellant et al. 2005, p. 1). Since ecological processes are

often challenging to measure, Rangeland Health techniques utilize biological and physical 

characteristics that can serve as indicators of ecosystem integrity. The three main attributes in such 

an assessment and the indicators used for each were summarized previously in Section 4.1 of this 

assessment (see Table 7). Rangeland Health indicators and assessment methods are described in 

further detail in Pellant et al. (2005). Although Rangeland Health scores have not been calculated for 

any of GRKO’s vegetation communities, the ROMN VCSS monitoring protocol has recorded 

observations on several of the soil/site stability indicators (surface flow patterns, rills/gullies, and 

pedestals) in recent years (ROMN 2006-2011). However, very few of the ROMN sampling locations 

have been within the park’s upland grasslands. Four upland grassland plots were sampled in 2010, 

two in 2009, and one each in 2006-2008 and 2011.

4.4.5 Current Condition and Trend

Range Condition/Similarity Index 

Range Condition and similarity indices were determined for four upland grassland pastures during 

the summer of 2014: Ridge Road, Upper Northwest, Taylor Ridge, and Gravel Pit (locations shown 

in Figure 24). Range Condition is based on percent species composition (by dry weights) whereas 

similarity index is based on species composition directly based on dry weights (Table 31). The Range 

Condition scores showed that two grasslands (Ridge Road and Gravel Pit) were in the excellent 

condition class and two (Taylor Ridge and Upper Northwest Range) were in the good condition class 

(NPS 2014). All of these scores fall within the reference condition selected for this measure (good or 

excellent class), although Taylor Ridge’s scores are near the bottom of the good class. Similarity 
100 

indices show that the two pastures with excellent Range Condition scores are also closest to the 

climax plant community, with scores above 92% (Table 31). Upper Northwest Range was also very 

similar to the HCPC with a score just below 92%, whereas Taylor Ridge Pasture was much lower 

with a similarity index of just 55%. 

Table 31. Range Condition scores and classes (based on percent composition) and similarity indices 

(based on dry weight) for four upland grasslands at GRKO in 2014 (NPS 2014). Class designations are 

applied only for Range Condition scores and are not used with similarity indices. Grassland locations are 

shown in Figure 24. 

Field Range Condition -

% Compostion

Range Condition Class Similarity Index -

Dry weight

Ridge Road Pasture 79% Excellent 92.2%

Upper Northwest Range 72% Good 91.8%

Taylor Ridge Pasture 54% Good 55%

Gravel Pit Pasture 93% Excellent 92.7%
101 

Figure 24. Upland grasslands with Range Condition determinations (names in bold), and ROMN 

sampling locations (discussed below) where soil/site stability indicator observations have been recorded 

(ROMN 2006-2011). NS = none to slight, SM = slight to moderate, MM = moderate. 

Rangeland Health (17 indicators) 

Rangeland Health scores have not been calculated for any vegetation communities in GRKO. 

However, the ROMN VCSS monitoring protocol has recorded observations on several of the soil/site 

stability indicators (surface flow patterns, rills/gullies, and pedestals) used in Rangeland Health 

Assessments. The presence of these indicator features would suggest that disturbance and/or erosion 

are occurring and negatively impacting soil stability (Pellant et al. 2005). Monitoring teams recorded 

whether evidence of these indicators was none to slight (NS), slight to moderate (SM), moderate 

(MM), moderate to extreme (MX), or extreme (XX). No MX or XX observations have been recorded

at the GRKO upland grassland sampling locations since monitoring began in 2006 (Table 32). 

Moderate evidence of these indicators has only been noted twice (once for surface flow in 2007 and 
102 

once for rills/gullies in 2010). Four SM observations have been reported for surface flow and 

rills/gullies; evidence of pedestals has been NS at every location during the monitoring period. It is 

important to note that these data represent only three of the 17 indicators used to calculate Rangeland 

Health and do not provide a comprehensive picture of the grassland community’s condition alone.

Table 32. Indicators of disturbance and/or erosion documented in GRKO’s upland grasslands (ROMN 

2006-2011). NS - none to slight, SM = slight to moderate, MM = moderate. 

Year/Plot # of Observations Surface Flow Rills/Gullies Pedestals

2006

 GRKO_004 5 2 NS, 3 SM 5 NS 5 NS

2007

 GRKO_004 3 2 NS, 1 MM 3 NS 3 NS

2008

 GRKO_004 3 3 NS 3 NS 3 NS

2009

 GRKO_032 1 NS NS NS

 GRKO_036 1 SM SM NS

2010

 GRKO_004 1 NS NS NS

 GRKO_040 1 NS SM NS

 GRKO_041 1 NS SM NS

 GRKO_044 1 NS MM NS

2011

 GRKO_040 1 NS SM NS

Totals 18 13 NS, 4 SM, 1 MM 13 NS, 4 SM, 1 MM 18 NS

Ecological Effect Size (A)

As previously described in Chapter 4.2 of this assessment, an “effect size” describes the magnitude 

of the difference between two groups, in this case the existing plant community and an identified 

reference community. For the upland grasslands at GRKO, Mueggler and Stewart’s (1980) grassland 

type descriptions (community composition, etc.) could be used as reference communities. While 

some current information on upland grassland community composition has been gathered through the 

ROMN monitoring program, not enough recent data are available to calculate ecological effect size 

for these communities (Rice, email communication, 31 July 2014). 

Threats and Stressor Factors 

Threats to GRKO’s upland grasslands include invasive species, drought, climate change, improper 

grazing, unplanned or extreme fire, Columbian ground squirrels, and grasshopper outbreaks. Invasive 

plant species are a major concern at GRKO and are recognized globally as a significant threat to 

ecosystem stability (NPS 2008, Rice et al. 2012). These species can alter plant community 

composition and ecological processes (e.g., water and nutrient cycling) and contribute to biodiversity 

and habitat losses (Lacey et al. 1989, NPS 2008). In GRKO, invasive plants also threaten the park’s 

cultural landscape and can reduce forage quality (NPS 2011, Manier et al. 2011). Invasive species 

common in the upland grasslands include spotted knapweed (Centaurea stoebe ssp. micranthos), 

cheatgrass, field bindweed, and smooth brome (Rice 2003, Rice et al. 2012). Species documented in 

the park’s upland grasslands by Rice (2003) are listed in Table 33. Spotted knapweed is one of the 
103 

most destructive invaders of western grasslands, reducing native plant diversity and cover by 90% in 

some areas (Ridenour and Callaway 2001, Callaway et al. 2004). The NRM EPMT has been 

intensively treating spotted knapweed at the park since 2004, leading to a noticeable decrease in 

density in recent years (NPS 2012). The park has also used biological control insects and 

experimented with prescribed grazing (e.g., training livestock to eat weeds) to reduce spotted 

knapweed and other invasive plants (NPS 2011). However, there is no evidence that prescribed 

grazing has been effective.

Table 33. Invasive plant species documented in upland grasslands by Rice (2003).

Upland Ranges

Scientific Name Common Name Railroad 

Remnant

Gravel Pit Taylor 

Ridge

Upper NW No Name

Montana noxious weeds

Cirsium arvense* Canada thistle X X

Euphorbia esula* leafy spurge X X

Lepidium latifolium* perennial pepperweed X

Centaurea stoebe ssp. 

micranthos*

spotted knapweed X X X X X

Convolvulus arvensis* field bindweed X X

Lepidium draba* hoary cress, whitetop X

Cynoglossum officianale* houndstongue X

Introduced grasses

Poa pratensis Kentucky bluegrass X X X X

Elymus repens quackgrass X X

Agrostis gigantea redtop X

Bromus inermis smooth brome X X X X X

Agropyron cristatum crested wheatgrass X X X X X

Poa compressa Canada bluegrass X X X X

Bromus tectorum* cheatgrass X X X X

Thinopyrum intermedium intermediate wheatgrass X X X X X

Bromus arvensis field brome X

Potential problem forbs

Melilotus officinalis sweetclover X X X X X

Silene latifolia bladder campion X

Gypsophila paniculata* baby's breath X X X X

Verbascum thapsus common mullein X

*Also identified as priority species by the NRM EPMT (NPS 2011).

Two processes that are a natural part of grassland ecosystems - grazing and fire - can be stressors to 

the community in certain situations. If fires are followed by dry periods, the production of some 

native grasses (e.g., needle-and-thread) can be negatively impacted for 2-3 years (Whisenant and 

Uresk 1989). Overgrazing in the ranch’s upland grasslands could impact plant species composition 

and soil characteristics (Fleischner 1994, Manier et al. 2011). With heavy grazing, more palatable 

grasses such as western wheatgrass, bluebunch wheatgrass, prairie junegrass, and green needlegrass 

usually decrease (Mueggler and Stewart 1980). Unpalatable woody species and forbs, including 

fringed sagebrush (Artemisia frigida), broom snakeweed (Gutierrezia sarothrae), rubber rabbitbrush 

(Ericameria nauseosa), and plains pricklypear (Opuntia polyacantha), often increase with heavy 

grazing (Mueggler and Stewart 1980). 
104 

Columbian ground squirrels play an important role in natural ecosystems, as their digging activity 

creates habitat diversity and improves soil aeration and moisture retention (MDA 2013). However, in 

agricultural and ranching areas, this digging may contribute to soil erosion and create disturbed areas 

where invasive species can colonize. Additionally, their holes are a possible hazard for grazing 

livestock (MDA 2013). Grasshoppers are also an important natural part of grassland ecosystems, but 

increased herbivory during population outbreaks often creates serious competition with grazing 

livestock (Branson et al. 2006). Large outbreaks could temporarily reduce the productivity of 

GRKO’s grasslands and decrease vegetative cover, possibly increasing the risk of erosion. 

Climate has a strong influence on vegetation communities, both directly and indirectly through its 

impact on ecological processes (e.g., fire, nutrient cycling) (McWethy et al. 2010). As a result of 

climate change, the western U.S. is projected to experience more frequent dry periods (droughts) 

during the 21st century, due to increased temperatures and evapotranspirtation, as well as changes in 

surface hydrology (Gray and Andersen 2009, McWethy et al. 2010). In the last half of the 20th

century, snowmelt and peak runoff were already occurring earlier on average, reducing surface water 

storage and river base flows during the summer months (McCabe and Clark 2005, Stewart et al. 

2005, McWethy et al. 2010). An increase in drought frequency or duration could impact grassland 

composition and production, while climate warming will likely influence plant phenology (Loehman 

2009, Bloor et al. 2010). 

Data Needs/Gaps

Additional community surveys are needed in the upland grasslands in order to calculate ecological 

effects sizes for the five grassland types. This will be aided by the development of Ecological Site 

Descriptions (similar to range site descriptions but more detailed) by the NRCS, which are currently 

in the initial stages (Smith, written communication, 5 May 2015). Further surveying is also required 

to complete full Rangeland Health Assessments. While some of the 17 indicators used in these 

assessments have been documented at GRKO, others have not (e.g., litter movement, reproductive 

capability of perennial plants). Repetition of the Range Condition assessments in the future will help 

determine if any changes are occurring in the upland grassland community. 

Overall Condition 

Range Condition/Similarity Index

The Range Condition measure was assigned a Significance Level of 3. All of the four upland 

grasslands for which Range Condition was determined during 2014 met the selected reference 

condition of good or excellent class. However, Taylor Ridge was near the bottom of the good class 

with similarity indices of 54% and 55%. This measure is currently considered of low concern 

(Condition Level = 1). 

Rangeland Health (17 Indicators)

The project team also assigned this measure a Significance Level of 3. Rangeland Health scores have 

not been calculated for any vegetation communities in GRKO. While the ROMN VCSS monitoring 

protocol has recorded observations on several of the soil/site stability indicators, these are only three 
105 

of the 17 indicators used to calculate Rangeland Health and do not provide a comprehensive picture 

of the grassland community’s condition. Therefore, a Condition Level has not been assigned. 

Ecological Effect Size (A)

This measure was assigned a Significance Level of 3. However, not enough recent data on upland 

community composition is available to reliably calculate ecological effect sizes. As a result, a 

Condition Level could not be assigned. 

Weighted Condition Score 

A Weighted Condition Score was not calculated for GRKO’s uplands due to a lack of data for two of 

the three measures. The current condition and any trend for the upland grassland community are 

unknown. 

Uplands (Grasslands, Non-irrigated) 

Measures Significance 

Level

Condition 

Level WCS = N/A 

Range Condition 3 1 

Rangeland Health 3 n/a

Ecological Effect Size 3 n/a

4.4.6 Sources of Expertise

Peter Rice, University of Montana Research Ecologist

Bret Olson, Professor of Range Ecology, Montana State University 
106 

4.4.7 Literature Cited

Bloor, J. M. G., P. Pichon, R. Falcimagne, P. Leadley, and J. Soussana. 2010. Effects of warming, 

summer drought, and CO2 enrichment on aboveground biomass production, flowering 

phenology, and community structure in an upland grassland ecosystem. Ecosystems 13:888-900. 

Branson, D. H., A. Joern, and G. A. Sword. 2006. Sustainable management of insect herbivores in 

grassland ecosystems: New perspectives in grasshopper control. Bioscience 56(9):743-755. 

Callaway, R. M., G. C. Thelen, S. Barth, P. W. Ramsey, and J. E. Gannon. 2004. Soil fungi alter 

interactions between the invader Centaurea maculosa and North American natives. Ecology 

85(4):1062-1071. 

Fleischner, T. L. 1994. Ecological costs of livestock grazing in western North America. Conservation 

Biology 8(3):629-644. 

Gray, S., and C. Andersen. 2009. Assessing the future of Wyoming’s water resources: Adding 

climate change to the equation. William D. Ruckelshaus Institute of Environment and Natural 

Resources. University of Wyoming, Laramie, Wyoming. 

Lacey, J. R., C. B. Marlow, and J. R. Lane. 1989. Influence of spotted knapweed (Centaurea 

maculosa) on surface runoff and sediment yield. Weed Technology 3(4):627-631. 

Loehman, R. 2009. Understanding the science of climate change: Talking points - impacts to prairie 

potholes and grasslands. Natural Resource Report NPS/NRPC/NRR—2009/138. National Park 

Service, Fort Collins, Colorado. 

Manier, D., D. Shorrock, E. W. Schweiger, I. Ashton, B. Frakes, M. Britten, D. Pillmore, and J. 

Burke. 2011. Rocky Mountain Network vegetation composition structure and soils monitoring 

protocol: Small park grasslands, shrublands, and woodlands; Version 1.0. Natural Resource 

Report NPS/ROMN/NRR-2011/383. National Park Service, Fort Collins, Colorado. 

McCabe, G. J., and M. P. Clark. 2005. Trends and variability in snowmelt runoff in the western 

United States. Journal of Hydrometeorology 6:476-482. 

McWethy, D. B., S. T. Gray, P. E. Higuera, J. S. Littell, G. T. Pederson, A. J. Ray, and C. Whitlock. 

2010. Climate and terrestrial ecosystem change in the U.S. Rocky Mountains and Upper 

Columbia Basin: Historical and future perspectives for natural resource management. Natural 

Resource Report NPS/GRYN/NRR—2010/260. National Park Service, Fort Collins, Colorado. 

Montana Department of Agriculture (MDA). 2013. The Columbian ground squirrel: Its biology and 

control. Montana Department of Agriculture, Helena, Montana. 

Mueggler, W. F., and W. L. Stewart. 1980. Grassland and shrubland habitat types of western 

Montana. USDA Forest Service General Technical Report INT-66. U.S. Forest Service, 

Intermountain Forest and Range Experiment Station, Ogden, Utah. 
107 

National Park Service (NPS). 2008. Exotic plant management team: 2008 annual report. National 

Park Service, Biological Resources Management Division, Fort Collins, Colorado. 

National Park Service (NPS). 2011. Northern Rocky Mountains invasive plant management plan. 

National Park Service, Fort Collins, Colorado. 

National Park Service (NPS). 2012. Northern Rocky Mountains exotic plant management team: FY 

2012 report. National Park Service, Fort Collins, Colorado. 

National Park Service (NPS). 2014. Range site and condition record data sheets. Unpublished data 

collected by Bret Olson and Jarrett Payne, Montana State University. Received from Jason 

Smith, 26 September 2014. 

Natural Resources Conservation Service (NRCS). 1982. Technical range site descriptions. Field 

office technical guide, section II-E-8. Natural Resources Conservation Service, Washington, D.C. 

Pellant, M., P. Shaver, D. A. Pyke, and J. E. Herrick. 2005. Interpreting indicators of Rangeland 

Health, version 4. Technical Reference 1734-6. U.S. Department of the Interior, Bureau of Land 

Management, National Science and Technology Center, Denver, Colorado. 

Rice, P. M. 2003. Discussion outline for Grant-Kohrs Ranch weed management and restoration. 

National Park Service Unpublished Report, Deer Lodge, Montana.

Rice, P. M., and G. J. Ray. 1984. Floral and faunal survey and toxic metal contamination study of the 

Grant-Kohrs Ranch National Historic Site. National Park Service, Deer Lodge, Montana. 

Rice, P. M., and J. G. Hardin. 2002. Vascular plant survey of Grant-Kohrs Ranch National Historic 

Site. National Park Service, Deer Lodge, Montana. 

Rice, P. M., E. W. Schweiger, W. Gustafson, C. Lea, D. Manier, D. Shorrock, B. Frakes, and L. 

O’Gan. 2012. Vegetation classification and mapping project report, Grant-Kohrs Ranch National 

Historic Site. Natural Resource Report NPS/ROMN/NRR—2012/589. National Park Service, 

Fort Collins, Colorado. 

Ridenour, W. M., and R. M. Callaway. 2001. The relative importance of allelopathy in interference: 

The effects of an invasive weed on a native bunchgrass. Oecologia 126:444-450. 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2006. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2006. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2007. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2007. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 
108 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2008. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2008. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2009. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2009. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2010. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2010. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2011. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2011. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Shapins Belt Collins. 2009. Grant-Kohrs Ranch cultural landscape report, part two. National Park 

Service, Fort Collins, Colorado. 

Shorrock, D, I. Ashton, M. Britten, J. Burke, D. Pillmore, and E. W. Schweiger. 2010. Vegetation 

composition, structure and soils monitoring at Grant-Kohrs Ranch National Historic Site: 2009 

annual data report. Natural Resource Data Series. Published Report-2165172. Natural Resource 

Program Center, Fort Collins, Colorado. 

Stewart, I. T., D. R. Cayan, and M. D. Dettinger. 2005. Changes toward earlier streamflow timing 

across western North America. Journal of Climate 18:1136-1155. 

Whisenant, S., and D. Uresk. 1989. Burning upland, mixed prairie in Badlands National Park. The 

Prairie Naturalist 21 (4):221-227. 
109 

4.5 Birds

4.5.1 Description

Bird populations often act as excellent indicators of an ecosystem’s health (Morrison 1986, Hutto 

1998, NABCI 2009). Birds are typically 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). Migratory birds can serve as ecological indicators of broad environmental 

conditions because a 

disturbance adversely affecting 

any of the habitats used by these 

species (e.g., stopover, 

wintering, or breeding habitats) 

can cause declines in 

populations and a decrease in 

species’ reproductive success 

(Zöckler 2005). Conversely, 

trends in resident bird species’ 

populations are likely due to 

changes occurring in their 

immediate habitat or ecosystem, 

and (in theory) it is possible to 

study all of their population 

processes directly throughout 

the year (Koskimies 1989).

GRKO is unique among NPS 

units, as it is actively managed 

as a functional ranch by the NPS. Ranching activities that are facilitated by the NPS include livestock 

grazing, hay production and harvest, irrigation, fencing, and noxious weed control (John Milner 

Associates et al. 2004). Ranching activities can create unique habitats for bird species, particularly in 

the grassland and hayfield areas. Some species, such as the bobolink (Dolichonyx oryzivorus, Photo 

19), have exhibited a preference for agricultural fields when there is an absence of true grasslands 

(Dale et al. 1997, Larson 2011). However, mowing and cutting of hayfields has been cited as a major 

disturbance for breeding grassland bird species (Warner and Etter 1989, Bollinger et al. 1990, 

Frawley and Best 1991, Herkert et al. 1996, Perlut et al. 2006). 

NPS (2014) confirmed the presence of 143 bird species within the park, and another 87 species have 

been identified as probably occurring in the park. Among the confirmed species are several birds 

designated as species of concern by at least one agency (Appendix F). Grassland species have been 

experiencing range-wide declines in recent years (NABCI 2009), and GRKO is home to several 

grassland species of concern. Examples of these species include the ferruginous hawk (Buteo 

regalis), long-billed curlew (Numenius americanus), and the bobolink (NPS 2014). 

Photo 19. Bobolink (NPS Photo).
110 

4.5.2 Measures

• Species richness 

• Distribution 

• Abundance 

• Status of species of special concern 

4.5.3 Reference Conditions/Values

A reference condition was not established for birds during project scoping. Much of the research that 

has been done for birds in GRKO has occurred since 2004. The synthesis and summary of research 

from 2004-present that is provided in this document could likely serve as a baseline or reference 

condition for future condition assessments. This baseline data will be particularly important in the 

riparian areas, as a decontamination and excavation project is slated to begin in 2015. This largescale disturbance will likely affect the bird community in the riparian areas for several years, and 

baseline data will be valuable to monitor the recovery of the bird community.

4.5.4 Data and Methods

The NPS Certified Bird Species List (NPS 2014) for GRKO was used for this assessment; this list 

represents all of the confirmed bird species present in the park (Appendix G). 

Rice and Ray (1984) investigated the floral and faunal communities of GRKO, in addition to 

studying the toxic metal contamination of the park’s riparian habitats. Avian surveys were informal, 

and the procedure used to identify birds is poorly documented. However, from 1982-1983 Rice and 

Ray (1984) documented 27 species of birds within the park. 

In 2004, Giroir and Beason (2005) completed an avian inventory of GRKO, with the following 

specific objectives:

1. To document the occurrence of bird species; 

2. To describe the distribution and, where possible, the population densities of those species; 

3. To identify critical bird habitats; 

4. To identify bird species of special management concern; 

5. To recommend a long-term bird monitoring program (Giroir and Beason 2005, p. iii). 

Giroir and Beason (2005) surveyed the breeding, wintering, migratory, and nocturnal bird species in 

GRKO. Two transect locations in the park were selected to monitor the breeding bird populations: 

one situated in a grassland habitat, and one along the park’s riparian habitat near the Clark Fork 

River. The grassland transect had 14 point counts, while the riparian transect had 20 point counts. At 

each point, all birds seen and heard were recorded during a 5-minute period. Approximate distances 

were also recorded using a laser rangefinder. Informal surveys were also conducted throughout the 

park to inventory the wintering, migratory, and nocturnal species of the ranch. Complete 

methodology is detailed in Giroir and Beason (2005). 
111 

In 2010, Larson (2011) surveyed the breeding bird species 

of the Stuart, Taylor, and West Fields in GRKO, in order to 

develop best management practices (BMPs) for the pasture 

and hayfields of the park. Fourteen survey points were 

selected arbitrarily, with nine located in Taylor Field, two 

in West Field, and three in Stuart Field. Each point was 

surveyed for 10 minutes, and all species that were observed 

visually and aurally were recorded. Larson (2011) also 

documented active nests that were found, as well as 

informal species observations that occurred outside of the 

survey time frame.

Atkinson and Smucker (2013) surveyed two habitat types in 

GRKO (grassland and riparian) in 2013, with the objective 

of establishing a baseline for the pre-restoration bird 

community in GRKO. A point count transect was 

established in both the riparian and grassland areas of the 

park; each transect had 16 randomly selected points in a square kilometer. Field methodology closely 

resembled that of the Integrated Monitoring in Bird Conservation Regions (IMBCR) program; this is 

the same procedure that Giroir and Beason (2005) utilized, and allows for some comparisons 

between the two studies. Observers walked to each point and recorded the number of birds observed 

visually and aurally during a 6-minute period. In 

addition to the point counts, Atkinson and Smucker 

(2013) also conducted nest searches and recorded 

informal species observations (i.e., species observed, 

but not during a point count period or nest search). 

The GRKO Christmas Bird Count has occurred 

annually since 2006 and is part of the International 

Christmas Bird Count (CBC), which started in 1900 

and is coordinated internationally by the Audubon 

Society. The CBC surveys overwintering and 

resident birds that are not territorial and singing; this 

often results in different survey results than other 

breeding bird surveys or inventories. Typically, a 

CBC will be completed by multiple volunteers who 

survey a 24-km (15-mi) diameter on one day. 

Volunteers record the total number of species and 

individuals each year; data for the GRKO CBC are 

current through 2012 (National Audubon Society 

2014). The boundary of the GRKO CBC circle 

extends beyond park borders, and data from this 

count includes records that are likely located outside 

Photo 20. Willow flycatcher (Photo 

©Jim Schmidt)

Figure 25. Approximate extent of the CBC 

survey area (purple circle) including GRKO.
112 

of the park itself (Figure 25). 

4.5.5 Current Condition and Trend

Species Richness

The species richness measure allows for an assessment of the number of species present across the 

park for the entire land bird community. This measure can also indicate overall habitat suitability for 

birds. However, there may be undetected changes in species richness of native species compared to 

non-native species, or in Neotropical migrant species compared to resident species. Such changes 

would not be apparent in the tables and figures presented in this document. The various surveys that 

have occurred in the park have utilized different methodologies, habitats, and seasons. The unique 

timing and survey methodology means that each survey will present unique results that may or may 

not accurately compare to each other or the reference condition. 

NPS Certified Bird Species List (NPS 2014) 

The NPS Certified Bird Species List (NPS 2014) identifies 230 bird species as either ‘present’ or 

‘probably present’ in GRKO (Appendix G). This list, however, does not allow for an analysis of 

species richness as no data are collected other than the potential presence of the listed species.

Rice and Ray (1984) 

Rice and Ray (1984) documented all bird species that were visually observed during an informal 

survey of the ranch from 1982-1983 (Appendix G). The authors documented 27 species throughout 

GRKO.

Giroir and Beason (2005) 

As part of an avian inventory at GRKO in 2004, Giroir and Beason (2005) surveyed the grassland 

and riparian areas of the park during the breeding season, and conducted informal surveys during the 

migratory and winter periods. Survey efforts resulted in positive identification of 104 bird species in 

GRKO. Intensive surveys in the grassland and riparian habitats identified 54 species (Appendix G); 

the remaining 50 species were documented during informal surveys in the migratory and winter 

periods. 

Larson (2011) 

From mid-May to mid-July 2010, Larson (2011) surveyed 14 point count locations in GRKO 

hayfields. Survey sites were located in Stuart Field (3 points), West Field (2 points), and Taylor Field 

(9 points), and corresponded with hay mowing and other agricultural activities (Larson 2011). A total 

of 46 species were observed during survey efforts (Appendix G). 

Atkinson and Smucker (2013) 

On 12 June and 20 June 2013, Atkinson and Smucker (2013) surveyed two point count transects 

within GRKO, which resulted in 42 species being observed (Appendix G, Appendix H). In addition 

to the point counts, Atkinson and Smucker (2013) also conducted a nest search in portions of the 

park, and found 13 nests of 10 species, two species of which were not observed on the point counts 

(American crow [Corvus brachyrhynchos] and bank swallow [Riparia riparia]). Bird banding and 

mist netting resulted in 51 species being observed (35 of which were not observed on the point 
113 

counts; Appendix H). Area searches yielded the highest number of observed species, with 104 

species, 65 of which were not observed on the point counts (Appendix H). Figure 26 displays the 

species richness values for each of the survey methods used by Atkinson and Smucker (2013). 

Figure 26. Species richness values for each of the survey methods utilized by Atkinson and Smucker 

(2013).

Christmas Bird Count Data (2006-2012) 

The CBC efforts in GRKO have been conducted on a regular basis since 2006, and represent the 

largest source of continuous bird data for the park. Unlike most other bird surveys conducted in the 

park, the CBC surveys overwintering, migratory, and resident birds that are not territorial and 

singing. Because of this, the species richness estimates obtained from the CBC may not be directly 

comparable to the results of other surveys that have occurred in the park. The CBC count circle also 

includes areas both inside and outside park boundaries. 

The total number of bird species identified annually during GRKO CBC efforts is presented in Figure 

27. From 2006-2012, the average number of bird species observed on the CBC was 38 species 

(Figure 27), and the number of species observed each year ranged from 32 (2006) to 48 (2011). 

While the range of species observed per year does not appear to be extremely large, variations from 

year to year could be attributed to the level of effort for the survey, which may have a direct effect on 

the number of species observed. 

0

20

40

60

80

100

120

Point Count Mist Netting/Banding Area Search

# of Observed Species

Survey Method
114 

Figure 27. Species richness values during each year of GRKO’s annual Christmas Bird Count. The 

average species richness value for the duration of the count is represented by the continuous red line.

Figure 28 displays the species richness values from each of the studies that have taken place in 

GRKO from 1982-present. The average number of species observed for the duration of each survey 

was 46.6. The Giroir and Beason (2005) data includes only the species that were documented on 

formal surveys, and the Atkinson and Smucker (2013) data includes only species that were observed 

during point count surveys. When all years of data are pooled, the CBC has observed the highest 

number of species (64). Excluding the CBC, overall species richness has ranged from 27 species 

(Rice and Ray 1984) to 54 species (Giroir and Beason 2005). 

0

10

20

30

40

50

60

2006 2007 2008 2009 2010 2011 2012

# of Species

Year

Average

(38)
115 

Figure 28. Species richness values reported from each of the surveys completed in GRKO. * indicates 

data that only includes species that were observed on formal point count surveys.

Distribution 

The two primary habitat types 

utilized by the bird community in 

GRKO are the riparian areas along 

the Clark Fork River, and the 

grassland/agricultural areas. The 

riparian habitat (Photo 21) in the park 

is dominated by cottonwood, willows, 

alder (Alnus sp.), and birch species 

(Giroir and Beason 2005); several 

other types of riparian vegetation, 

such as cattail (Typha sp.), are also

present along the shores of the Clark 

Fork. The grassland and agricultural 

areas of GRKO are dominated by 

grass species, and lack many tree and 

shrub species. In addition to the 

native grassland species, the 

grassland areas of the park also include irrigated hayfields dominated by non-native grasses. 

0

10

20

30

40

50

60

70

Rice and Ray

(1984)

Giroir and

Beason (2005)

*

Larson (2011) Atkinson and

Smucker (2013)

*

CBC (2006-

2012)

# of Species

Study

Photo 21. Riparian habitat along the Clark Fork River in 

GRKO (Photo by Sarah Gardner, SMUMN GSS).
116 

Understanding the current distribution of the bird species in GRKO, and how species utilize those 

habitats, is of particular importance for GRKO managers, as the critical areas of the park are actively 

managed for non-avian related activities. Heavy metal contamination in the Clark Fork River and 

along its shorelines is a major concern to land managers in the GRKO area. Starting in 2015, the 

riparian habitat along the Clark Fork River in GRKO is scheduled to be excavated in order to remove 

soils that are contaminated by heavy metals and toxins (Atkinson and Smucker 2013). While these 

areas will be replanted after excavation and decontamination processes are complete, it is important 

to document baseline distribution and abundance levels in these areas of the park to monitor recovery 

efforts. 

Stuart, Taylor, and West Fields in GRKO are cut and harvested annually, and understanding which 

species utilize these fields, and during what season, is important to managers to minimize potential 

disturbances during critical periods for grassland species. The establishment of baseline distribution, 

richness, and abundance values in these harvested areas is vital to park managers. 

Three surveys have occurred in the park that have documented the distribution of bird species in 

GRKO (Giroir and Beason 2005, Larson 2011, Atkinson and Smucker 2013). These surveys have all 

been 1-year efforts, and have had different methodologies, timing, and sampling locations. 

Individually, these surveys are not sufficient to determine trends, or the overall health of the GRKO 

bird community. However, it is possible to synthesize the results of these surveys to gather a better 

understanding of the distribution of bird species in the park, particularly in regards to the species’ 

utilization of the riparian and grassland areas. 

Giroir and Beason (2005) 

Giroir and Beason (2005) documented 557 individuals during a 2004 avian inventory of the park. 

The majority of individuals (412, 74% of all individuals observed) and species (49, 91% of all 

species observed) were located in the riparian habitat (Figure 29, Table 34). The most commonly 

observed species in the grassland habitat were the savannah sparrow (Passerculus sandwichensis; 

21% of all observations) and the western meadowlark (Sturnella neglecta; 20%). In the riparian 

habitat, the savannah sparrow was also the most commonly observed species (11%), followed by the 

brown-headed cowbird (Molothrus ater; 7.5%) and the yellow warbler (Septophaga petechia; 6%) 

(Appendix I). While the grassland habitat that was surveyed had a noticeable reduction in birds 

observed compared to the riparian area, this result was not unexpected; fewer survey points were 

utilized in the grassland habitat (14 compared to 20 in the riparian), and riparian habitats provide 

vital habitat for a wider variety of species (Giroir and Beason 2005). 
117 

Figure 29. Survey points in riparian and grassland habitats that were used during the Giroir and Beason 

(2005) avian inventory of GRKO.

Table 34. Species richness and abundance values for the two habitat types that were sampled during the 

Giroir and Beason (2005) survey of GRKO in 2004.

Habitat # of Point Counts # of Species # of Individuals

Grassland 14 19 145

Riparian 20 49 412

Total 34 54 557
118 

Larson (2011) 

The 2010 bird surveys completed by Larson (2011) were focused only on the grassland and 

agricultural fields of GRKO, and there is no discussion of distribution beyond these habitat types. 

Three general survey locations were used (Taylor, Stuart, and West Fields), each with a separate 

subset of survey point locations (14 in total) (Figure 30). Four hundred eighty-nine individuals of 46 

species were observed at the survey points in the grassland/agricultural habitats of GRKO. The 

savannah sparrow was the most commonly observed species in 2010 (31 % of all observations), 

followed by the bobolink (11%), and the western meadowlark (9%) (Appendix J). 

Figure 30. Survey areas during the Larson (2011) grassland and agricultural avian surveys.

Atkinson and Smucker (2013) 

Atkinson and Smucker (2013) surveyed the grassland/agricultural and riparian habitats of GRKO in 

the summer of 2013. The data presented in this section represent only the point count survey data; 

area searches and nest searches also yielded observations, and are included in Appendix H. 
119 

Atkinson and Smucker (2013) observed 321 individuals 

in 2013; the majority of individuals (175, 55% of all 

individuals observed) and species (35, 83% of all 

species observed) were located in the 

grassland/agricultural habitat (Figure 31, Table 35). In 

the grassland/agricultural habitat, the most commonly 

observed species were the savannah sparrow (26% of all 

observations) and the red-winged blackbird (Agelaius 

phoeniceus; 17%). The savannah sparrow (17%) and 

black-billed magpie (Pica hudsonia; 14%) were the 

most commonly observed species in the riparian habitat 

(Appendix K). 

Atkinson and Smucker (2013) documented more species 

and individuals in the grassland/agricultural areas of the 

park whereas Giroir and Beason (2005) (the only other 

study to survey both riparian and grassland habitats) 

observed more species and individuals distributed along 

the Clark Fork River in the riparian areas of the park 

(Figure 32, Figure 33). A potential reason for this result 

is that Atkinson and Smucker (2013) had a higher 

number of point count locations in the 

grassland/agricultural area (14) compared to the riparian 

and wetland areas (8; Table 35); Giroir and Beason 

(2005) exhibited a similar trend, albeit in reverse, as 20 point count locations were in riparian 

habitats and only 14 were in grassland habitats (Table 34). Figure 32 and Figure 33 represent a rough 

comparison of the number of species and individuals observed during each survey in the park. 

Comparison across surveys with the purpose of evaluating trends or current condition is not 

advisable, as biases in each survey may make comparisons unreliable. 

Table 35. Species richness and abundance values for the two habitat types that were sampled during the 

Atkinson and Smucker (2013) survey of GRKO in 2013.

Habitat # of Point Counts # of Species # of Individuals

Grassland/Agriculture 14 35 175

Riparian/Wetland 8 29 146

Total 22 42 321

Figure 31. The two point count transects 

that were established in GRKO by Atkinson 

and Smucker (2013). Point count locations 

that have a red X were not surveyed in 2013 

due to time constraints (Image reproduced 

from Atkinson and Smucker 2013).
120 

Figure 32. Number of species observed in each habitat type during the three major surveys in GRKO. * 

indicates a survey that did not have any riparian/wetland survey points.

Figure 33. Number of individuals observed in each habitat type during the three major surveys in GRKO. 

* indicates a survey that did not have any riparian/wetland survey points.

Status of Species of Special Concern

The Montana Natural Heritage Program (MTNHP) and the Montana Department of Fish, Wildlife, 

and Parks (MFWP) compiled a list of avian species of concern (MTNHP and MFWP 2009) which 

was used for this assessment. This list includes a species’ global, state, and federal status, as well as 

the species’ current conservation tier as identified in MFWP (2005). Additionally, species of 

conservation concern identified as Priority Tiers I-III by the Montana Partners in Flight Bird 

Conservation Plan (MTPIF 2000) were included in this assessment; all species of conservation 

concern that have been documented in the park can be found in Appendix F. 

0

10

20

30

40

50

60

Giroir and Beason

(2005)

Larson (2011)* Atkinson and Smucker

(2013)

# of Species

Study

Grassland/Agricultural

Riparian/Wetland

0

100

200

300

400

500

600

Giroir and Beason

(2005)

Larson (2011)* Atkinson and Smucker

(2013)

# of Individuals

Study

Grassland/Agricultural

Riparian/Wetland
121 

Assessing the trends and current status of species of special concern in GRKO is difficult, as many of 

the recent studies that have taken place in the park were 1-year studies that utilized different survey 

protocols. Additionally, many of the species of special concern in the park are migratory, and their 

presence/absence in GRKO is often erratic (Giroir and Beason 2005). 

NPS Certified Bird Species List (NPS 2014) 

Of the 230 species identified on the NPS Certified Species List (NPS 2014), 72 species of special 

concern are identified (31% of all species on NPS 2014). Because NPS (2014) only documents the 

historic presence/absence of species in the park, trend estimates for priority species are not possible 

from this data source. 

Rice and Ray (1984) 

Rice and Ray (1984) documented eight species of special concern (30% of all species observed) 

during an informal survey of the ranch from 1982-1983. Similar to NPS (2014), Rice and Ray (1984) 

only documented the presence of species, so it is not possible to analyze trends in priority species 

from these data. 

Giroir and Beason (2005) 

Giroir and Beason (2005) observed 13 species of special concern during a 2004 survey of the 

grassland and riparian habitats of the park. All 13 species were identified as either a Priority Tier II 

or III species by MTPIF (2000). Two other priority species, the bobolink and long-billed curlew were 

identified on multiple conservation lists (Appendix F). The bobolink has a state rank of S3B, 

indicating that this breeding species is “potentially at risk because of limited and/or declining 

numbers, range, and/or habitat, even though it may be abundant in some areas” (MTNHP and MFWP 

2009, p. 3). The long-billed curlew also has a state rank of S3B, and is identified as a sensitive 

species by the Bureau of Land Management (BLM) (MTNHP and MFWP 2009). MFWP (2005) 

listed the long-billed curlew as a tier I species, indicating it is a species of greatest conservation need 

in Montana. 

Abundance data for the species of special concern that were observed during Giroir and Beason 

(2005) are presented in Figure 34. Due to the duration of the survey, trend analysis is not possible 

using only the data from this study. The red-winged blackbird was observed most frequently (23 

individuals), followed by the willow flycatcher (Empidonax traillii; 21), and the song sparrow 

(Melospiza melodia; 18). 
122 

Figure 34. Abundance of species of special concern observed during the Giroir and Beason (2005) 

survey of GRKO. * indicates species that was on two or more conservation lists. 

Larson (2011) 

Larson (2011) documented 11 species of special concern during a survey of the agricultural and 

grassland habitats of GRKO in 2010; one of these species, the killdeer (Charadrius vociferus), was 

observed only between point counts. Nine of the species observed were classified as a Priority Tier 

III species by MTPIF (2000), while the willow flycatcher was the only Priority Tier II species 

observed. Both the bobolink and the alder flycatcher (Empidonax alnorum) were designated S3 

species by MTNHP and MFWP (2009); the alder flycatcher was further designated as a tier II-I 

species by MFWP (2005). 

The bobolink was the most abundant species of special concern observed during 2010, with 57 

observations. The red-winged blackbird was the only other species of special concern with doubledigit observations (28; Table 36). Table 36 shows the Larson (2011) abundance data for all species of 

special concern observed in GRKO. 

0

5

10

15

20

25

# of Individuals

Species
123 

Table 36. Number of individuals identified as species of special concern observed during the Larson 

(2011) survey of GRKO. 

Species # of Individuals

alder flycatcher* 2

bobolink* 57

Brewer's blackbird 1

chipping sparrow 3

killdeer † n/a

lark sparrow 1

northern harrier 1

red-winged blackbird 28

song sparrow 9

Swainson's hawk 2

willow flycatcher 3

* Species documented on two or more conservation lists

† Species observed between point counts but not counted.

Atkinson and Smucker (2013) 

Nine species of special concern were documented during surveys completed by Atkinson and 

Smucker (2013). Eight species were identified by MTPIF (2000) as priority species; six species were 

assigned to Priority Tier III, while two species (long-billed curlew, willow flycatcher) were assigned 

to Priority Tier II (Appendix F). The bobolink and long-billed curlew were also classified as S3B 

species by MTNHP and MFWP (2009); the great blue heron (Ardea herodias) was classified as an 

S3 species, which is the same designation as S3B, only it indicates it is not a breeding species in the 

state.

The red-winged blackbird was by far the most numerous species of special concern observed during 

the Atkinson and Smucker (2013) surveys, with 40 individuals observed. The bobolink was the 

second most commonly observed species of special concern with five observations. Table 37 shows 

the Atkinson and Smucker (2013) abundance data for all species of special concern observed in 

GRKO.
124 

Table 37. Number of individuals identified as species of special concern observed during the Atkinson 

and Smucker (2013) survey of GRKO. 

Species # of Individuals

bobolink* 5

great blue heron* 2

killdeer 1

long-billed curlew* 3

MacGillivray's warbler 2

northern harrier 1

red-winged blackbird 40

song sparrow 4

willow flycatcher 2

* Species documented on two or more conservation lists

Christmas Bird Count Data (2006-2012) 

Care must be taken when interpreting count data sources, such as the CBC, as the data are largely 

dependent upon the effort of the observers. The counts may not provide an accurate depiction of the 

trends or current status of species of special concern in GRKO. 

From 2006-2012, 17 species of special concern have been observed during the annual CBC in 

GRKO. Fifteen of the observed species were identified as Priority Species by MTPIF (2000), with 

the brown creeper being the only Priority Tier I Species (indicating it is a “Conservation Action” 

species; MTPIF 2000). The gray-crowned rosy-finch has been observed during two CBCs, and has a 

state conservation ranking of S2B, indicating this breeding species is “at risk because of very limited 

and/or declining numbers, range, and/or habitat, making it vulnerable to global extinction or 

extirpation in the state” (MTNHP and MFWP 2009, p. 3). 

The most commonly observed species of special interest from 2006-2012 were the bald eagle 

(Haliaeetus leucocephalus; 119 individuals), Townsend’s solitaire (Myadestes townsendi; 94), and 

Brewer’s blackbird (Euphagus cyanocephalus; 57). Only three species of special concern were 

observed during all seven CBC efforts: the bald eagle, downy woodpecker (Picoides pubescens), and 

Townsend’s solitaire. The highest number of species/individuals observed occurred from 2010-2012 

(Table 38, Figure 35). 
125 

Table 38. Annual abundance of species of special concern during the GRKO Christmas Bird Count, 

2006-2012.

Species 2006 2007 2008 2009 2010 2011 2012

American dipper 3 1 1 1 1 2

bald eagle 13 8 14 19 14 29 22

Barrow's goldeneye 1 4 2 5

Brewer's blackbird 37 20

brown creeper 1

Clark's nutcracker 1 2 6 10 2 3

downy woodpecker 4 2 3 7 8 6 2

gray-crowned rosy-finch 1 3

great blue heron 4 1 2 3

killdeer 4

northern goshawk 1 1

northern harrier 3 7 1 3 4 2

red crossbill 20

red-winged blackbird 30 4

sharp-shinned hawk 1 3 4 1

song sparrow 1 3 2 1

Townsend's solitaire 8 2 4 9 26 32 13

Figure 35. Number of species and number of individual species of special concern observed during the 

annual GRKO Christmas Bird Count, 2006-2012.

0

20

40

60

80

100

120

140

0

2

4

6

8

10

12

14

2006 2007 2008 2009 2010 2011 2012

# of Individuals

# of Species

Year

# of Individuals

# of Species
126 

Figure 36 represents a chronological depiction of the species richness data for the species of 

conservation concern that have been documented during the various avian surveys/inventories, while 

Figure 37 depicts the abundance data for species of conservation concern. The average number of 

species of conservation concern observed during the surveys was 9.73, while the average number of 

individuals was 75 (Figure 36, Figure 37). 

Figure 36. Number of species of special concern observed during each of the major survey efforts in 

GRKO. The red line indicates the average number of species of special concern observed during the 

surveys (9.73).

0

2

4

6

8

10

12

14

# of Species

Study
127 

Figure 37. Number of individuals of special concern observed during each of the major survey efforts in 

GRKO. The red line indicates the average number of individuals observed during a survey (75).

Nationwide Trends 

Grassland bird species are among North America’s most threatened bird communities; grassland 

birds have experienced “steeper, more consistent, and more geographically widespread declines than 

any other behavioral or ecological guild” (Knopf 1994, p. 251). NABCI (2009) indicates that 

grassland birds have been rapidly declining over the past 50 years, and that 55% of grassland species 

are showing significant population declines. Furthermore, 48% of North American grasslandbreeding bird species are of conservation concern. 

Many of the declines in grassland species appear to be the result of loss and degradation of grassland 

habitats (Noss et al. 1995, Vickery and Herkert 2001). Three iconic grassland species found in 

GRKO, the bobolink, western meadowlark, and short-eared owl (Asio flammeus), have declined 

globally by 38-77% since 1968 (NABCI 2009). 

Nearly 25% of all North American bird species rely on riparian and wetland habitats (NABCI 2009). 

Several riparian/wetland species that are found in GRKO are experiencing global declines. The rusty 

blackbird (Euphagus carolinus) has experienced a 75% population decline during the last 40 years, 

and the lesser scaup (Aythya affinis) has experienced almost a 50% population decline during the 

same period (NABCI 2009). Despite the decline in many species, management and conservation 

efforts in these habitats have had success in many areas. Species such as the bald eagle, osprey 

(Pandion halieatus), sandhill crane (Grus canadensis), and American white pelican (Pelecanus 

erythrorhynchos) have all benefitted from wetland restoration and management practices. 

0

20

40

60

80

100

120

140

# of Individuals

Study
128 

Threats and Stressor Factors 

Contamination from the Clark Fork River represents a major threat to the bird community of GRKO. 

The Clark Fork River has been exposed to heavy metal contamination for over a century. Metals 

washed downstream from the historic copper sulfate mining districts of Anaconda and Butte, MT; 

large amounts of metallic mining waste were washed downstream during record floods in the early 

1900s and were deposited and settled beneath the soil sediments along the Clark Fork River 

floodplain in GRKO (Kapustka 2002, Ramsey et al. 2005). Mining wastes were unevenly distributed 

and further agitated by subsequent floods and channel migration, leading to extensive spatial 

variation in contaminant concentration within the soils (Ramsey et al. 2005). In 1992, the EPA

designated the Clark Fork River upstream of the Milltown Dam to the Warm Springs Ponds a 

Superfund Site. 

High trophic level avian predators with a 

primarily piscivorous diet, such as the bald 

eagle and osprey, have been used as 

sentinels for studying environmental 

contamination (Toschik et al. 2005, 

Hopkins et al. 2007, Rattner et al. 2008, 

Rivera-Rodriguez and Rodriguez-Estrella 

2011, Langner et al. 2011). The osprey is a 

frequently observed species in GRKO, as 

many visitors spot the birds nesting on 

electrical poles in the park (Photo 22). 

Recently, Langner et al. (2011) 

documented variable levels of copper, 

arsenic, cadmium, lead, zinc and mercury 

in the blood of osprey chicks along the 

Clark Fork River. The most notable 

finding of the study, though, was that the 

lowest blood concentrations of mercury 

were observed in the osprey chicks located 

along the most upstream river sections, 

including GRKO. The highest mercury 

concentrations in osprey chicks were documented downstream from contaminated tributaries 

(Langner et al. 2011), which enter the Clark Fork downstream of GRKO. Continued monitoring of 

the contaminant levels in the blood of high trophic level raptors, especially as remediation efforts 

continue, will provide GRKO managers with valuable information regarding both the health of the 

bird community and the health of the Clark Fork River. 

Beginning in 2015, the riparian habitat along the Clark Fork River in GRKO is scheduled to be 

excavated as part of the Superfund site remediation process (Atkinson and Smucker 2013). The 

riparian areas will be replanted after the excavation and decontamination processes are complete, but 

the large-scale disturbance that will affect the riparian-dependent bird species may have major, shortPhoto 22. Osprey nest on top of an electrical pole in 

GRKO (Photo by Sarah Gardner, SMUMN GSS).
129 

term impacts on this community. The increase in human presence in the park (i.e., machinery, 

construction workers, and noise) may also have secondary impacts on the neighboring communities, 

such as the grassland and agricultural bird communities. 

The annual haying of the agricultural fields poses a threat to the grassland bird communities of 

GRKO. Earlier and more frequent harvests are commonly cited as major causes of grassland 

songbird population declines (Perlut et al. 2006). Since most grassland species nest on or near the 

ground, the haying process often results in total nest failure if completed during the incubating or 

brooding stage. During a 2002-2005 study of grassland songbirds in Vermont and New York, Perlut 

et al. (2006) reported that haying caused 99% of active savannah sparrow nests and 100% of active 

bobolink nests to fail. In GRKO, haying typically begins in mid-July, which is nearing the end of the 

bobolink’s nesting period (the bobolink is a late nester and is a well-suited indicator of when the 

grassland breeding period concludes; Larson 2011). GRKO has purposely delayed haying until the 

latest possible date to minimize negative impacts to nesting birds in these fields. These delayed 

harvests (as suggested by Larson 2011) should continue, as a shift in the haying timeline could have 

significant impacts on the breeding grassland bird species in the park. 

Avian brood parasite species (e.g., brown-headed cowbird) may pose a threat to several avian species 

in GRKO. Brood parasites are species that lay their eggs in the nests of other breeding species, which 

then in turn incubate and care for the young (Payne 1977). Brood parasitism generally reduces the 

reproductive success of the host species, as host species typically fledge fewer young compared to 

other non-parasitized parents of the same species (Payne 1977). Brown-headed cowbirds are native 

to the GRKO region, and can directly contribute to the reduced nesting success of host species, as 

they will often puncture or remove host species eggs (Friedmann 1963). Brown-headed cowbirds 

often hatch earlier than host species eggs, and grow larger and faster than the host species, which 

often results in the death of the host chicks due to starvation, neglect, overcrowding, or direct 

mortality by trampling or removal from the nest (Friedmann 1963, Payne 1977). Many breeding 

species are targeted by brood parasites, although warblers, blackbirds, and vireos are among the most 

commonly parasitized species. While a natural phenomenon, brood parasitism can be actively 

managed against; instances of cowbird egg removal from host nests has resulted in increased 

reproductive success in various parts of the species’ home range (Walkinshaw 1972, Payne 1977). 

Another threat facing bird populations is climate change; of particular concern are shifts in the 

reproductive phenology of breeding bird species. 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 range north (Hitch and Leberg 2007). Other species have adjusted 

their migratory period and have begun returning to their breeding grounds earlier in the spring; 

American robins (Turdus migratorius) 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 
130 

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. 

Data Needs/Gaps

GRKO has had several bird surveys and inventories in the last two decades; however, these have all 

been 1 year efforts. The establishment of an annual survey with increased yearly sampling (>1 

survey/year) and a spatially balanced bird protocol (similar to Atkinson and Smucker 2013) would 

allow for density and occupancy estimates in the future. These estimates could provide baseline 

values that would serve as sources of comparison for future studies. 

Christmas bird counts provide snapshots in time of species richness. However, only one survey/visit 

per year yields little information in terms of population trends. Further observations in the winter 

could help to remedy this data gap and could potentially help the park better understand the status of 

wintering bird species in the park. 

Overall Condition 

Species Richness 

The species richness measure was assigned a Significance Level of 3 during project scoping. While 

no long-term monitoring of birds has occurred in GRKO, the several 1-year surveys and inventories 

that have occurred have recorded species richness values, and suggest that species richness is 

relatively stable in the park. Most surveys have taken place during the breeding season, and have 

documented species richness values between 42-54 species. The average species richness value for 

the surveys completed after 2000 was 47 species. CBC efforts have yielded species richness values 

ranging from 32-48 species; these counts do not sample breeding birds and do not count many of the 

migratory species that pass through the park in the spring and fall. A Condition Level of 0, indicating 

no current concern, was assigned for species richness in GRKO. 

Distribution

Distribution was assigned a Significance Level of 2 by GRKO staff. There are two major habitat 

types utilized by the GRKO bird community: riparian and grassland/agricultural. Giroir and Beason 

(2005) observed more avian usage of the riparian habitat (74% of individuals observed, 91% of 

species), while Atkinson and Smucker (2013) documented more avian species and individuals in the 

grassland habitat (55% of individuals, 83% of species). However, the dominant habitat type in each 

study had a higher number of survey points, which likely influenced the number of species and 

individuals observed. There does not appear to be major concern regarding the current distribution of 

birds in GRKO, and a Condition Level of 1 was assigned to this measure. With Superfund 

remediation efforts set to take place in the riparian habitat of GRKO in 2015, monitoring of the 

distribution of avian species in the park will be needed to document any potential shifts in abundance 

or habitat utilization, particularly during the breeding season. 
131 

Abundance 

The abundance measure was assigned a Significance Level of 1 during project scoping. Measures 

with a Significance Level of 1 are not discussed in the body of the text, rather they are briefly 

summarized in the Overall Condition section. In addition to the annual CBC in GRKO, three surveys 

have documented avian abundance in the park (Appendix I, Appendix J, Appendix K). Figure 33 in 

the Current Condition section of this document displays the abundance, by habitat type, of all 

individuals observed during these three studies. There is no evidence to indicate any cause for 

concern regarding avian abundance in the park, but it is difficult to compare results across these three 

surveys. The three studies were 1-year efforts, and it is difficult to combine the results to assess 

current condition and trend; sampling biases, such as survey duration, location, and timing, may 

contribute to the differing results regarding species abundance. 

The CBC represents a continuous source of abundance data for GRKO, as it has occurred annually 

since 2006. The CBC in GRKO saw a large increase in abundance from 2010-2011, while 2012 was 

still an above average year (Figure 38). No data are currently available from 2013 or 2014. However, 

biases such as number of observers, ability of the observers, and weather conditions/seasonal timing 

may contribute to annual variations in abundance. 

Figure 38. Avian abundance during the annual GRKO CBC, 2006-2012.

A Condition Level of 1 was assigned to the abundance measure, indicating the measure is currently 

of low concern. The establishment of an annual breeding bird survey or inventory would be 

beneficial for future assessments of condition, and would allow for a more thorough comparison of 

yearly abundance estimates.

0

10

20

30

40

50

60

2006 2007 2008 2009 2010 2011 2012

# of Species

Year

Average (38)
132 

Status of Species of Special Concern 

The status of species of special concern measure was assigned a Significance Level of 3. In GRKO, 

the three major surveys that have taken place identified 9.73 species of special concern on average 

(Figure 11). The average number of individuals of special concern observed during these surveys was 

75 (Figure 12). The CBC in the park observed 17 species of special concern from 2006-2012, and 

abundance values fluctuated annually (Figure 11). The CBC data contains observations from outside 

of the park boundaries, and it is impossible to know exactly how many of these observed species 

were detected within park boundaries. 

It is difficult to ascertain any trends in species of special concern in GRKO, as surveys that have 

taken place utilize different methodologies and have occurred during different time periods. The 

CBC does not observe many migratory or breeding species of special concern, and the surveys that 

took place during breeding likely missed species that only overwinter in the park. Nationwide trends 

for species of special concern suggest that the grassland and riparian obligate species (the two 

dominant types in the park) are experiencing population declines of great numbers (NABCI 2009). 

While the status of species of special concern is currently of low concern in the park (Condition 

Level of 1), the trends across the nation and the future remediation efforts in the riparian habitats may 

increase this level in future condition assessments.

Weighted Condition Score 

The birds component was assigned a Weighted Condition Score of 0.22, indicating that this 

component is currently in good condition. Survey efforts in the last 10 years have resulted in 

estimates that indicate this component’s current trend is stable. However, remediation efforts along 

the Clark Fork River will likely impact the bird community of the park, and will warrant future 

monitoring efforts to verify that the community does not begin to show signs of declining health. 

Birds 

Measures Significance 

Level

Condition 

Level WCS = 0.22 

Species Richness 3 0 

Distribution 2 1 

Abundance 1 1 

Status of Species of 

Special Concern 3 1 
133 

4.5.6 Sources of Expertise

This assessment relied on published literature as the primary source of expertise, with review by 

GRKO staff.
134 

4.5.7 Literature Cited

Atkinson, K., and K. Smucker. 2013. Grant-Kohrs Ranch National Historic Site bird monitoring 

project. Avian Science Center, Division of Biological Sciences, University of Montana, 

Missoula, Montana. 

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. 

Bollinger, E. K., P. B. Bollinger, and T. A. Gavin. 1990. Effects of hay-cropping on eastern 

populations of the bobolink. Wildlife Society Bulletin 18(2):142-150. 

Dale, B. C, P. A. Martin, and P. S. Taylor. 1997. Effects of hay management on grassland songbirds 

in Saskatchewan. Wildlife Society Bulletin 25(3):616-626. 

Frawley, B. J., and L. B. Best. 1991. Effects of mowing on breeding bird abundance and species 

composition in alfalfa fields. Wildlife Society Bulletin 19:135-142. 

Friedmann, H. 1963. Host relations of the parasitic cowbirds. Bulletin of the United States National 

Museum 233. Smithsonian Institution, Washington, D. C. 

Giroir, G., and J. Beason. 2005. Report on the general avian inventory of Grant-Kohrs Ranch 

National Historic Site, Montana. Rocky Mountain Bird Observatory, Fort Collins, Colorado. 

Herkert, J. R., D. W. Sample, and R. E. Warner. 1996. Management of Midwestern grassland 

landscapes for the conservation of migratory birds. Pages 89-116 in Management of midwestern 

landscapes for the conservation of Neotropical migratory birds. Edited by F. R. Thompson, III. 

General Technical Report NC-187.United States Department of Agriculture, St. Paul, Minnesota. 

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. 

Hopkins, W. A., L. B. Hopkins, J. M. Unrine, J. Snodgrass, and J. D. Elliot. 2007. Mercury 

concentrations in tissues of osprey from the Carolinas, USA. Journal of Wildlife Management 

71:1819-1829. 

Hutto, R. L. 1998. Using landbirds as an indicator species group. Pages 75-92 in Avian conservation: 

Research and management. Island Press, Washington, D.C. 

John Milner Associates, Rivanna Archaeological Consulting, Susan Maxman and Partners 

Architects. 2004. Cultural landscape report. Grant-Kohrs Ranch National Historic Site, Deer 

Lodge, Montana. 

Kapustka, L. A. 2002. Phytotoxicity tests on soils from the Grant-Kohrs Ranch National Historic 

Site, Deer Lodge, Montana. National Park Service, Deer Lodge, Montana. 
135 

Knopf, F. L. 1994. Avian assemblages on altered grasslands. Studies in Avian Biology 15:247-257. 

Koskimies, P. 1989. Birds as a tool in environmental monitoring. Annales Zoologici Fennici 26:153-

166. 

Langner, H. W., E. Greene, R. Domenech, and M. R. Staats. 2011. Mercury and other mining-related 

contaminants in ospreys along the Upper Clark Fork River, Montana, USA. Archives of 

Environmental Contamination and Toxicology 62:681-695. 

Larson, M. 2011. Summary of 2010 bird surveys, Grant-Kohrs Ranch National Park: Stuart and 

Taylor Field Sites. University of Montana, Missoula, Montana. 

Montana Fish Wildlife and Parks (MFWP). 2005. Montana’s comprehensive fish and wildlife 

conservation strategy. Montana Fish, Wildlife and Parks, Helena, Montana.

Montana Natural Heritage Program and Montana Fish Wildlife and Parks (MTNHP and 

MFWP). 2009. Montana animal species of concern. Montana Natural Heritage Program 

and Montana Department of Fish Wildlife and Parks, Helena, Montana.

Montana Partners In Flight (MTPIF). 2000. Partners In Flight Draft Bird Conservation Plan, 

Montana: Version 1.0. Montana Partners In Flight, Kalispell, Montana. 

Morrison, M. L. 1986. Bird populations as indicators of environmental change. Current Ornithology 

3:429-451. 

National Audubon Society. 2014. The Christmas Bird Count Historical Results. 

http://www.christmasbirdcount.org (accessed 14 August 2014). 

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. 

Noss, R. F., E. T. LaRoe III, and J. M. Scott. 1995. Endangered ecosystems of the United States: a 

preliminary assessment of loss and degradation. National Biological Service Biological Report 

28, National Biological Service, Washington, D.C. 

National Park Service (NPS). 2014. NPSpecies. http://irma.nps.gov/NPSpecies/Search/ (accessed 14 

August 2014).

Payne, R. B. 1977. The ecology of brood parasitism in birds. Annual Review of Ecology, Evolution, 

and Systematics 8:1-28. 

Perlut, N., A. Strong, T. Donovan, and N. Buckley. 2006. Grassland songbirds in a dynamic 

management landscape: behavioral responses and management strategies. Ecological 

Applications 16:2235-2247. 
136 

Ramsey, P. W., M. C. Rillig, K. P. Feris, J. N. Moore, and J. E. Gannon. 2005. Mine waste 

contamination limits soil respiration rates: A case study using quantile regression. Soil Biology 

and Biochemistry 37:1177-1183. 

Rattner, B. A., N. H. Golden, P. C. Toschik, P. C. McGowan, and T. W. Custer. 2008. 

Concentrations of metals in blood and feathers of nestling ospreys (Pandion haliaetus) in 

Chesapeake and Delaware Bays. Archives of Environmental Contamination and Toxicology 

54:114–122.

Rice, P. M., and P. C. Ray. 1984. Floral and faunal survey and toxic metal contamination study of the 

Grant-Kohrs Ranch National Historic Site. National Park Service, Deer Lodge, Montana. 

Rivera-Rodrıguez, L. B., and R. Rodriguez-Estrella. 2011. Incidence of organochlorine pesticides 

and the health condition of nestling ospreys (Pandion haliaetus) at Laguna San Ignacio, a pristine 

area of Baja California Sur, Mexico. Ecotoxicology 20:29–38.

Toschik, P. C, B. A. Rattner, P. C. McGowan, M. C. Christman, D. B. Carter, and R. C. Hale. 2005. 

Effects of contaminant exposure on reproductive success of ospreys (Pandion haliaetus) nesting 

in Delaware River and Bay, USA. Environmental Toxicology and Chemistry 24:617–628. 

U.S. Geological Survey (USGS). 2008. North American bird phenology program. 

http://www.pwrc.usgs.gov/bpp/about.cfm (accessed 11 August 2014). 

Vickery, P. D., and J. R. Herkert. 2001. Recent advances in grassland bird research: where do we go 

from here? The Auk 118:11-15. 

Walkinshaw, L. H. 1972. Kirtland’s warbler-endangered. American Birds 26(1):3-9. 

Warner, R. E., and S. L. Etter. 1989. Hay cutting and the survival of pheasants: a long-term 

perspective. Journal of Wildlife Management 53:455-461. 

Zöckler, C. 2005. Migratory bird species as indicators for the state of the environment. Biodiversity 

6(3):7-13.
137 

4.6 Periphyton

4.6.1 Description

Periphyton are primary producers that serve many purposes in aquatic ecosystems; they are an 

important part of stream food webs, stabilize substrata, and provide habitat for other organisms 

(Stevenson and Bahls 2012). There are several types of periphyton in most streams and rivers. 

Diatoms (phylum Chrysophyta, class Bacillariophyceae) and soft-bodied algae (phyla Chlorophyta, 

Cyanophyta, Chrysophyta, and Rhodophyta; Photo 23) are most commonly used in environmental 

monitoring. Diatoms are the primary focus of monitoring in Montana (MT DEQ 2011) because they 

are abundant in most stream ecosystems, have rapid reproduction rates, have a well understood range 

in tolerance to stressors such as nutrients and metals, and are the focus of similar monitoring efforts 

in the western states (Stevenson and Bahls 2012; Spaulding et al. 2010). Stream communities, which 

include diatoms, are one of the ROMN’s Vital Signs, chosen to represent the overall health and 

condition of the park’s water resources (Schweiger et al. 2014). 

Photo 23. Benthic, soft-bodied algae in Cottonwood Creek in GRKO (Photo by SMUMN GSS 2013).

The Clark Fork River provides much of the periphyton habitat within GRKO. The river has been 

impacted by human activities for over 100 years (Bahls 1993). Mining activities are responsible for 

contaminating these river reaches with both metal and organic pollutants (McGuire 1990). Metals 

from mine wastes upstream (south) of GRKO, such as tailings and contaminated sediment, have been 

washed into the river and spread throughout the watershed (Atkins et al. 2012). Contaminants settle 

in the river sediment and floodplain soils, where they are taken up by vegetation and small aquatic 

organisms (including periphyton), eventually accumulating in higher-level consumers such as fish 

and birds. These contaminants have been documented in the water, sediments, and aquatic organisms 

(insects and fish) of the Upper Clark Fork (Smith et al. 1998). 
138 

The Montana Department of Environmental Quality (MT DEQ) has developed several models and 

associated thresholds that describe the biological condition of diatoms in a body of water (Teply and 

Bahls 2005; Teply 2010a, 2010b; MT DEQ 2011). These include the sediment, nutrient, and metal 

increaser models. The most current of these three models is a sediment increaser model created 

specifically for cold water steams in the Middle Rockies Ecoregion (Teply 2010a). This assessment 

will focus on the sediment increaser model, given its specificity to the ecoregion surrounding the 

Clark Fork and its use by MT DEQ. This model estimates a probability of impairment as a result of 

fine sediments, using diatom taxa on an increaser taxa list (Table 1) and their percent relative 

abundance (PRA) (Teply 2010a). Diatoms on this list are considered useful indicators of sediment 

impairment. 

Table 39. Sediment increaser taxa used in the sediment increaser model for the Rocky Mountain 

Ecoregion (Teply 2010a, 2010b).

Sediment Increaser Taxa

Amphora inariensis Navicula lanceolata

Cocconeis pediculus Navicula tripunctata

Cocconeis pseudolineata Nitzschia recta

Eolimna minima Planothidium frequentissimum

Geissleria acceptata Planothidium lanceolatum

Gomphonema drutelingense Reimeria sinuata

Meridion circulare Sellaphora pupula

Navicula gregaria Staurosirella leptostauron

4.6.2 Measures

• Sediment increaser model metrics

4.6.3 Reference Conditions/Values

The reference conditions assigned to periphyton in the Upper Clark Fork River at GRKO are MT 

DEQ criteria. Schweiger et al. (2014) provides sediment increaser thresholds used by the MT DEQ 

(Table 2). The current criteria to determine impairment by sediment is a probability threshold of 

51%, which corresponds to a PRA of sediment increaser taxa greater than 15.3%. The MT DEQ 

would consider any site with a value above this for a sediment-impairment designation. 

Table 40. Sediment increaser model metrics and thresholds (i.e., reference assessment points) according 

to Montana DEQ standards (Teply 2010a, 2010b).

Sediment Increaser Metric Reference Assessment Point

Percent Relative Abundance <15.3%

Probability of Impairment ≤51%
139 

4.6.4 Data and Methods

Schweiger et al. (2014) 

presented results from several 

years of monitoring the 

ecological integrity of the 

Clark Fork River at GRKO, 

including 2 years of 

periphyton data (2008 and 

2009). Biological samples 

were collected from 11 

transects systematically 

spread along a 500-m (1,640 

ft) sample reach (Figure 39) 

using methods largely derived 

from the EPA Environmental 

Monitoring and Assessment Program 

(EMAP) (Stoddard et al. 2005) and 

the MT DEQ (MT DEQ 2012). All 

biological data were collected at base 

flow. Methods used to assess 

periphyton communities included the 

sediment increaser model, as well as 

increaser models for nutrients and 

metals (Teply and Bahls 2005) and a 

suite of historic diatom metrics 

(Bahls 1993). 

Atkins et al. (2012) produced an 

environmental monitoring report for 

the Clark Fork River Operable Unit 

in 2011. Aquatic biota samples were

collected once during the year from 

seven monitoring sites along the 

Clark Fork, including one at the U.S. 

Geological Survey (USGS) gaging 

station in Deer Lodge just south of 

GRKO (Figure 39). The periphyton 

community was assessed using the 

sediment increaser model (Atkins et 

al. 2012). Figure 39. The location of the sample reach (yellow) in relation 

to the USGS stream gage (outside the park) (Schweiger et al. 

2014).

Photo 24. ROMN sampling in the Clark Fork at GRKO (NPS photo by 

Billy Schweiger).
140 

4.6.5 Current Condition and Trend

Sediment Increaser Model 

Schweiger et al. (2014) documented sediment increaser taxa in the Middle Rockies Ecoregion in 

2008 and 2009. Seven sediment increaser taxa were found in 2008, and 10 in 2009. The percent 

relative abundance (PRA) in 2008 and 2009 were 13.1% and 10.8%, respectively (Table 3). Both of 

these values were below the threshold value for the state of 15.3%, indicating that the MT DEQ 

would not classify the site as sediment impaired. These PRA values suggest the GRKO site had 

approximately a 42% and 36% probability of being impaired as a result of sediment in 2008 and 

2009, respectively; both were less than the MT DEQ threshold (51%). Schweiger et al. (2014) 

observed diatoms, cyanobacteria, green algae, and red algae. The most common taxa were Diatoma 

moniliformis, Gomphonema parvulum, Nitzschia inconspicua, N. dissipata, Cocconeis pediculus, and 

Reimeria sinuata. Of these, only the last two are on the sediment increaser taxa list (Table 39). D. 

moniliformis, the most abundant diatom, is considered relatively intolerant of general anthropogenic 

disturbance (Spaulding et al. 2010). Two other common species (G. parvulum and C. pediculus) can 

be indicative of nutrient enrichment, particularly associated with sedimentation (van Dam et al. 1994, 

Schweiger et al. 2014). 

Table 41. Sediment increaser model metrics for the Clark Fork River at GRKO in 2008 and 2009 

(Schweiger et al. 2014). 

Metric Base Flow Summer 2008 Base Flow Summer 2009

Number of Sediment Increaser Taxa 7 10

Percent Relative Abundance (PRA)

Probability of Impairment 

13.1%

42.4%

10.8%

35.8%

Atkins et al. (2012) documented six sediment increaser taxa in the Clark Fork River at GRKO in 

2011. The PRA was 6.5%, well below the Montana threshold value. The Deer Lodge site had 

approximately 20% probability of being impaired as a result of sediment, which was also below the 

Montana threshold value of 51%.The dominant species observed during this study was N. dissipata, a 

diatom that is relatively tolerant to pollution, although it is not on the sediment increaser list. Atkins

et al. (2012) collected eight metal tolerant taxa (7% of the total taxa) at the Deer Lodge site, 

suggesting a low probability of impairment due to metal contamination. However, the presence of a 

green algae species (Stigeoclonium spp.) suggested that nutrient enrichment was occurring (Atkins et 

al. 2012). 

Threats and Stressor Factors 

NPS staff identified several major threats to periphyton at GRKO. Most of the threats involve point 

source and non-point anthropogenic disturbances, including metals contamination, excess nutrients, 

sedimentation, riparian habitat modification, dewatering, and shifts in temperature and precipitation 

due to climate change. 

Point sources of contamination in the Clark Fork watershed that threaten the park’s periphyton 

include historic mining and smelting operations. Those point sources leaking or running off into the 

Upper Clark Fork River resulted in the Superfund site designation. Mining contamination includes 

high concentrations of metals, dissolved solids, and salts, all of which can impact and reduce 
141 

populations of aquatic organisms, including diatoms (Medley and Clements 1998, Fore and Grafe 

2002). Fore and Grafe (2002) found that diatom communities near mining sites in Idaho differed 

from other communities in taxa richness, community composition, and organism morphology (e.g., 

deformities). Non-point source threats to the periphyton community include fine inorganic sediment. 

Increased levels of fine sediment negatively impact primary and secondary production and nutrient 

cycling by increasing turbidity (Relyea et al. 2000). Turbidity reduces or blocks the sunlight needed 

by many periphyton for photosynthesis. 

Excess nutrients, particularly nitrogen and phosphorus, are a cause of concern for periphyton in 

GRKO. According to McGuire (2010), the Clark Fork is susceptible to nutrient pollution in the Deer 

Lodge Valley and has been observed to be impaired in past years. Nitrogen and phosphorus generate 

algae growth (McGuire 1990). According to Schweiger et al. (2014), filamentous algal cover in the 

Clark Fork at GRKO was at 75% in 2008, which is over 35 times the mean ecoregion value (2%). 

While algae create habitat and cover for fish and macroinvertebrates, an excess of nutrients can cause 

algal blooms, which can be detrimental to stream health (Smith and Schindler 2009, Schweiger et al. 

2014). Due to excess nutrients and lower stream flows in GRKO, algal blooms have occurred in the 

park from the 1970s through 2011 (Suplee et al. 2012, Schweiger et al. 2014). Three blue-green algae 

species that occur in Montana are capable of producing toxins when blooming that can be harmful to 

livestock and wildlife (Surber 2009). 

Dewatering is another threat to periphyton in GRKO. Dewatering may impact periphyton by altering 

streamflow. Water may also be lost from the system at the Warm Springs settling ponds upstream of 

GRKO, where the surface area of the water is increased and flow is slowed, allowing for increased 

evaporation (Smith, written communication, 5 September 2014). Decreases in species richness have 

occurred as a result of low or fluctuating flow rates (Benenatti et al. 1998, as cited in Poff et al. 

2012). Low flow rate also decreases water quality by increasing heavy metal concentrations, which 

in turn can negatively affect periphyton (Watson 1985). 

Climate change is a growing concern for periphyton in GRKO. Increasing water temperatures and 

low flow rates are often attributed to climate change (Isaak et al. 2012, Leppi et al. 2012). 

Temperature can impact periphyton growth, with high temperatures and low flows resulting in an 

explosion of periphyton growth, which can impact water quality (Shilling 2007). Studies in Arctic 

lakes have shown dramatic shifts in diatom communities over the past two centuries that seem to 

parallel climate warming (Douglas et al. 1994, Smol et al. 2005). 

Data Needs/Gaps

There are no historical or long-term data from the sediment increaser model, making it impossible to 

identify any trends in the periphyton community over time based on this metric alone. The most 

recent data for GRKO and the surrounding area are from 2008 and 2009 (Schweiger et al. 2014) and 

2011 (Atkins et al. 2012). The ROMN collected additional data from 2011-2013, but it was not yet 

ready for publication at the time this NRCA was written. Continued yearly monitoring efforts will 

aid in future assessments of the Clark Fork River periphyton community in GRKO. With 

Superfund remediation activities occurring along the Clark Fork in GRKO in the coming years, an 
142 

opportunity exists to study how periphyton are impacted by the initial disturbance and by the 

subsequent “improved” (e.g., less contaminated) conditions. 

Overall Condition 

Sediment Increaser Model 

The Significance Level for the sediment increaser model was assigned a 3. Schweiger et al. (2014) 

found PRA and probability of impairment to be below MT DEQ thresholds in 2008 and 2009. Atkins 

et al. (2012) documented a lower PRA and probability of impairment in 2011, also below the MT 

DEQ thresholds. Both studies found little evidence of impairment due to metal contamination, but 

taxa suggestive of nutrient enrichment were common (Atkins et al. 2012, Schweiger et al. 2014). 

Given that all sediment increaser model metrics available for GRKO and Deer Lodge met MT DEQ 

standards, the Condition Level for this measure was assigned a 1, or low concern. 

Weighted Condition Score (WCS) 

The WCS for periphyton in GRKO is 0.33. This suggests that the periphyton community in the park 

is currently in good condition. However, this score is at the very top of the good condition range, and 

any small decline in the community could shift it into the moderate concern range. There are not 

enough data available at this time to assign a trend. 

Periphyton 

Measures Significance 

Level

Condition 

Level WCS = 0.33 

Sediment Increaser 

Model 3 1 

4.6.6 Sources of Expertise

Billy Schweiger, Rocky Mountain Network Ecologist
143 

4.6.7 Literature Cited

Atkins, Rhithron Associates, Inc., and Montana Fish, Wildlife and Parks. 2012. Monitoring report for 

2011: Clark Fork River Operable Unit. Montana Department of Environmental Quality and 

Montana Department of Justice, Helena, Montana.

Bahls, L. L. 1993. Periphyton bioassessment methods for Montana streams. Water Quality Bureau, 

Montana Department of Health and Environmental Sciences, Helena, Montana. 

Benenatti, P. L., J. P. Shannon, and D. W. Blinn. 1998. Desiccation and recolonization of 

phytobenthos in a regulated desert river: Colorado River at Lees Ferry, Arizona, USA. Regulated 

Rivers: Research Management 14:519-532. 

Douglas, M. S. V., J. P. Smol, and W. Blake Jr. 1994. Marked post-18th century environmental 

change in high-Arctic ecosystems. Science 266(5184):416-419. 

Fore, L. S., and C. Grafe. 2002. Using diatoms to assess the biological condition of large rivers in 

Idaho (U.S.A). Freshwater Biology 47:2015-2037. 

Isaak, D. J., S. Wollrab, D. Horan, and G. Chandler. 2012. Climate change effects on stream and 

river temperatures across the northwest U.S. from 1980-2009 and implications for salmonid 

fishes. Climatic Change 133:499-524. 

Leppi, J. C., T. H. De Luca, S. W. Harrar, S. W. Running. 2012. Impacts of climate change on 

August stream discharge in the Central-Rocky Mountains. Climatic Change 112:997-1014. 

McGuire, D. L. 1990. Aquatic macroinvertebrate surveys in the Clark Fork River, 1986 to 1988. 

Clark Fork Symposium. University of Montana, Missoula, Montana. 

McGuire, D. L. 2010. Clark Fork River biomonitoring: Macroinvertebrate community assessments in 

2009. U.S. Environmental Protection Agency, Region 8, Denver, Colorado. 

Medley, C. N., and W. H. Clements. 1998. Responses of diatom communities to heavy metals in 

streams: the influence of longitudinal variation. Ecological Applications 8(3):631-644. 

Montana Department of Environmental Quality (MT DEQ). 2011. Periphyton standard operating 

procedure. Montana Department of Environmental Quality, Helena, Montana. 

Montana Department of Environmental Quality (MT DEQ). 2012. Water quality planning bureau 

field procedures manual for water quality assessment monitoring. Version 3.0. Montana 

Department of Environmental Quality, Helena, Montana. 

Poff, B., K. A. Koestner, D. G. Neary, and D. Merritt. 2012. Threats to western United States riparian 

ecosystems: A bibliography. General Technical Report RMRS-GTR-269. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, Colorado. 
144 

Relyea, C. D., G. W. Minshall, R. J. Danehy. 2000. Stream insects as bioindicators of fine sediment. 

Watershed Management 2000 Conference. Stream Ecology Center, Department of Biological 

Sciences, Idaho State University, Pocatello, Idaho. 

Schweiger, E. W., L. O’Gan, D. Shorrock, and M. Britten. 2014. Stream ecological integrity at 

Grant-Kohrs Ranch National Historic Site: Rocky Mountain Inventory & Monitoring Network 

2008-2010 stream monitoring report. Natural Resource Technical Report NPS/ ROMN/NRTR—

2014/881. National Park Service, Fort Collins, Colorado. 

Shilling, F. 2007. Periphyton (attached algae and aquatic plants) as indicators of watershed condition. 

Chapter 4 in The California Watershed Assessment Manual. California Natural Resources 

Agency, Sacramento, California. 

Smith, J. D., J. H. Lambing, D. A. Nimick, C. Parrett, M. Ramey, and W. Schafer. 1998. 

Geomorphology, flood-plain tailings, and metal transport in the Upper Clark Fork Valley, 

Montana. Water-Resources Investigations Report 98-4170. U.S. Geological Survey, Helena, 

Montana. 

Smith, V. H., and D. W. Schindler. 2009. Eutrophication science: Where do we go from here? Trends 

in Ecology and Evolution 24(4):201-207. 

Smol, J. P., A. P. Wolfe, H. J. Birks, M. S. V. Douglas, V. J. Jones, A. Korhola, R. Pienitz, K. 

Ruhland, S. Sorvari, D. Antoniades, and others. 2005. Climate-driven regime shifts in the 

biological communities of Arctic lakes. Proceedings of the National Academy of Sciences 

102(12):4397-4402. 

Spaulding, S. A., D. J. Lubinski, and M. Potapova. 2010. Diatoms of the United States. 

http://westerndiatoms.colorado.edu (accessed 25 September 2014). 

Stevenson, R. J., and L. L. Bahls. 2012. Chapter 6: periphyton protocols. Pages 6-2 – 6-23 in

Barbour, M. T., J. Gerritsen, B. D. Snyder, and J. B. Stribling (eds). 2012. Rapid bioassessment 

protocols for use in streams and wadeable rivers: periphyton, benthic macroinvertebrates, and 

fish – second edition. U.S. Environmental Protection Agency, Washington, D.C. 

Stoddard, J. L., D. V. Peck, S. G. Paulsen, J. Van Sickle, C. P. Hawkins, A. T. Herlihy, R. M. 

Hughes, P. R. Kaufmann, D. P. Larsen, G. Lomnicky, and others. 2005. An ecological 

assessment of western streams and rivers. U.S. Environmental Protection Agency, Washington, 

D.C. 

Suplee, M. W., V. Watson, W. K. Dodds, and C. Shirley. 2012. Response of algal biomass to largescale nutrient controls in the Clark Fork River, Montana, United States. Journal of the American 

Water Resources Association 48(5):1008-1021. 

Surber, G. 2009. Toxic algae: Potential in drought limited water supplies. Montana State University 

Extension Service, Bozeman, Montana. 
145 

Teply, M., and L. Bahls. 2005. Diatom biocriteria for Montana streams. Montana Department of 

Environmental Quality, Helena, Montana. 

Teply, M. 2010a. Diatom biocriteria for Montana streams. Montana Department of Environmental 

Quality, Helena, Montana.

Teply, M. 2010b. Interpretation of periphyton samples from Montana streams. Montana Department 

of Environmental Quality, Helena, Montana.

van Dam, H., A. Mertens, and J. Sinkeldam. 1994. A coded checklist and ecological indicator values 

of freshwater diatoms from The Netherlands. Netherlands Journal of Aquatic Ecology 28(1):117-

133. 

Watson, V. J. 1985. A synthesis of water quality problems in the Clark Fork River Basin. In

Proceedings of the Clark Fork River symposium. Montana College of Mineral Science and 

Technology, Butte, Montana.
146 

4.7 Aquatic Macroinvertebrates

4.7.1 Description

Macroinvertebrates are often used as biological indicators in assessing overall aquatic ecosystem 

health (EPA 2012). Their absence may reflect disturbances, such as metal contamination, that can 

affect higher trophic levels (EPA 2012). In the Clark Fork River, macroinvertebrates are an important 

food source for birds, fish, and other wildlife (EPA 2012). Stream communities, which include 

macroinvertebrates, are one of the ROMN’s Vital Signs, chosen to represent the overall condition of 

the park’s water resources (Schweiger et al. 2014). Macroinvertebrate indicator species can range 

from sensitive species, such as many 

stoneflies (order Plecoptera), caddisflies 

(order Trichoptera; Photo 25), and 

mayflies (order Ephemeroptera) to the 

much more tolerant midge (Diptera) and 

aquatic worm (Oligochaeta) species.

The Upper Clark Fork River is the main 

body of water that runs through the park. 

The Clark Fork has been impacted by 

human disturbance for over 100 years, 

particularly mining activities which are

responsible for contaminating the river 

with both metal and organic pollutants 

(McGuire 1990). Elevated concentrations 

of metals have been documented in the 

river’s water, sediments, and aquatic 

organisms (insects and fish) (Smith et al. 

1998). Estimates of the Clark Fork aquatic macroinvertebrate community’s biointegrity in the Deer 

Lodge area from the mid-1980s to mid-2000s suggested it was slightly to moderately impaired, but 

showing some improvement in the late 2000s (McGuire 2010). 

4.7.2 Measures

• RIVPACS modeling (observed to expected [O:E] and Bray Curtis metrics) 

• Multimetric indices (MMI)

4.7.3 Reference Conditions/Values

The reference conditions for this assessment are those used by Schweiger et al. (2014), selected 

largely following Montana DEQ guidance (MT DEQ 2012a, b, c) with a few from other agencies or 

that were found in the literature. Schweiger et al. (2014) also developed ecoregion thresholds for 

select metrics using reference sites in the Middle Rockies Ecoregion (see Schweiger et al. [2014] for 

details on how thresholds were established). Reference assessment points were taken from multiple 

sources to aid in evaluating the condition of macroinvertebrates in the Clark Fork River in GRKO. A 

Photo 25. Caddisfly species (Hydropsyche sp.) that is 

common in the Clark Fork River at GRKO (NOAA photo by 

Dr. Dwayne Meadows).
147 

subset of metrics and assessment points were selected from Schweiger et al. (2014) and are shown in 

Table 42. 

Table 42. Macroinvertebrate metrics with ecoregion thresholds (Schweiger et al. 2014) and reference 

condition assessment points. 

Macroinvertebrate Metrics Ecoregion Threshold1 Reference Assessment Points

RIVPACS O:E2 >1.0 >0.8

RIVPACS Bray Curtis1 <0.30 -- 

Low Valley Multimetric Index2 >60.1 >48

Valley/Foothill Prairies Multimetric Index3 -- >75

Karr Benthic Index of Biotic Integrity4 -- >46

Hilsenhoff Biotic Index (Nutrients)5 -- <3

Fine Sediment Biotic Index6 -- >8

Temperature Index -- -- 

Metal Tolerance Index7 -- <4 1 Note that these thresholds and/or metrics are NOT used by the MT DEQ and have no regulatory significance.

2 RIVPACS O:E and MMI metrics were used by the MT DEQ through 2011 (MT DEQ 2012c); values above or equal 

to a criterion are in reference while values less than a criterion are in non-reference. 3 Used by MT DEQ prior to the current MMI model (Bukantis 1998); described in Bollman (1998).

4 Has never been used by the MT DEQ; described in Karr (1998).

5 Can be used by the MT DEQ in support of other nutrient data; described in Hilsenhoff (1988).

6 Has never been used by the MT DEQ; described 

in Relyea et al. (2000).

7 This index is specific to the Clark Fork (McGuire 

1987, 1989; Ingman and Kerr 1989) and may be 

used by the MT DEQ.

4.7.4 Data and Methods

Schweiger et al. (2014) presents results from 

several years of monitoring the ecological 

integrity of the Clark Fork River at GRKO, 

including 2 years of macroinvertebrate data 

(2008 and 2009). Biological samples were 

collected from 11 transects systematically 

spread along a 500-m (1,640 ft) sample 

reach (Figure 40) using methods largely 

derived from the EPA Environmental 

Monitoring and Assessment Program 

(EMAP) (Stoddard et al. 2005) and the 

Montana DEQ (MT DEQ 2012a). All 

biological data were collected at base flow. 

The two primary aquatic macroinvertebrate 

bioassessment methods utilized in this 

NRCA are the Montana Low Valley 

Multimetric Index (MMI) (Jessup et al. 

Figure 40. The location of the sample reach (yellow) 

in relation to the USGS stream gage (outside the park) 

(Schweiger et al. 2014).
148 

2006, MT DEQ 2012c) and the River Invertebrate Prediction and Classification (RIVPACS) model 

(Hawkins et al. 2000, Van Sickle 2008, MT DEQ 2012c). The MMI incorporates five component 

metrics (i.e., macroinvertebrate community characteristics): percent EPT (Ephemeroptera, 

Plecoptera, and Trichoptera), percent Chironomidae, percent Crustacea and Mollusca, percent 

shredder taxa, and percent predators (Jessup et al. 2006). RIVPACS models use macroinvertebrate 

observations from high quality streams in the region to create a reference (i.e., expected taxa) for 

similar streams (Jessup et al. 2006, Van Sickle 2008). This assessment will focus on two particular 

components from RIVPACS recommended by the MT DEQ (2012c): the observed:expected (O:E) 

and Bray Curtis dissimilarity metrics.

Atkins et al. (2012) prepared a monitoring report for the Clark Fork River Operable Unit in 2011. 

Several stations along the Clark Fork River were sampled; however, only one station (USGS gaging 

station at Deer Lodge) is used in this NRCA because of its proximity to the park. Four samples were 

collected from the station, one each in April, June, September, and December of 2011. The aquatic 

macroinvertebrate bioassessment methods utilized in Atkins et al. (2012) include the Low Valley 

MMI (Jessup et al. 2006, MT DEQ 2012c), Montana Valleys/ Foothill Prairies (MVFP) (Bollman 

1998), and RIVPACS (Hawkins 2005, Jessup et al. 2006). 

4.7.5 Current Condition and Trend

RIVPACS

Schweiger et al. (2014) presents two RIVPACS model-derived metrics from 2008 and 2009. The 

ratio of observed to expected taxa (O:E) was above the MT DEQ threshold (0.8) and met the 

ecoregion threshold (>1.0) for both sample events (Table 43). This indicates that a high proportion 

of the macroinvertebrate taxa observed at GRKO were characteristic of those expected from a 

reference stream in Montana. The Bray Curtis dissimilarity metrics for 2008 and 2009 showed 

similar results, with both values falling within the ecoregion threshold (< 0.30) developed by 

Schweiger et al. (2014) (Note that the ecoregion thresholds developed by Schweiger et al. [2014] are 

not used by the MT DEQ and have no regulatory significance). This suggests there is little 

dissimilarity between the macroinvertebrate community in a regional reference stream and that 

observed at GRKO (Schweiger et al. 2014). 

Table 43. The RIVPACS metrics from the Clark Fork River at GRKO during the summers of 2008 and 

2009 (Schweiger et al. 2014).

Metric Base Flow Summer 

2008

Base Flow Summer 

2009

RIVPACS O:E (P>0.5) >1.0 >1.0

RIVPACS Bray Curtis dissimilarity (P>0.5) 0.22 0.20

Atkins et al. (2012) calculated a RIVPACS value from sampling on the Clark Fork River at Deer 

Lodge in 2011. The mean value for the RIVPACS O:E metric was 0.78, which is just below the MT 

DEQ impairment threshold (0.8). The minimum and maximum values at this station ranged from 

approximately 0.7 to 1.0 (Atkins et al. 2012). These RIVPACS values indicate some impairment of 

the macroinvertebrate community in the Clark Fork River at Deer Lodge in 2011. 
149 

Multimetric Indices (MMI)

Schweiger et al. (2014) presents 2008 and 2009 results from GRKO for three MMI metrics, several 

stressor specific metrics, and the component metrics for the most current MMI. The Low Valley 

MMI was above the MT DEQ threshold of 48 in both years (Table 44). This indicates that MT DEQ 

would have likely considered the GRKO macroinvertebrate community characteristic of a reference 

condition macroinvertebrate assemblage. When compared to the more conservative ecoregion 

threshold of 60 developed by Schweiger et al. (2014), GRKO values are above this point in 2008 and 

slightly below in 2009. The Valley/Foothill Prairies MMI was slightly below the reference point in 

both years (Table 44). This MMI was developed for lower-order streams (i.e., further upstream in a 

watershed) and may actually be a more useful index for sites where sediment is an important stressor, 

like the Clark Fork (Schweiger et al. 2014). The Karr Benthic Index of Biotic Integrity was also 

below the reference point, suggesting a slightly more impaired condition than the other MMIs. 

However, this index was originally calibrated for the Pacific Northwest and may not be well suited 

for the specific disturbance regime in the Clark Fork at GRKO (Schweiger et al. 2014). All stressor 

specific metrics with established reference assessment points (see Table 42 footnotes) suggest that 

nutrients, sediment, and metal concentrations were causing some impairment of the 

macroinvertebrate community in 2008 and 2009 (Table 44). 

Table 44. Core macroinvertebrate metrics for the Clark Fork River in GRKO during the summers of 2008 

and 2009 (Schweiger et al. 2014).

Metric Base Flow Summer 

2008

Base Flow Summer 

2009

Reference 

Assessment Points

Mulimetric Indices (MMI)

Low Valley Multimetric Index 65 58.7 >48

Valley/Foothill Prairies Multimetric 

Index 61 56 >75

Karr Benthic Index of Biotic Integrity 30 36 >46

Stressor Specific Metrics

Hilsenhoff Biotic Index (Nutrients) 4.83 5.03 <3

Fine Sediment Biotic Index 4.21 4.47 >8

Temperature Index 15.85 15.91 -- 

Metal Tolerance Index 4.21 5.07 <4

Components of the above MMIs

Percent EPT1 35.1 16.5

Percent Chironomidae1 37.8 27.1

Percent Crustacea and Mollusca2 0.1 0.7

Shredder Taxa Richness2 3 3 

Percent Predator1 9.8 15.4 1

typically decreases with increased stress, 2 increases with increased stress 

In terms of the component metrics within the MMIs, the percent Chironomidae was relatively high in 

both years and percent EPT was high in 2008, which contributed to the high MMI scores (Table 44). 

The very low percent Crustacea and Mollusca and shredder taxa richness also likely drove up the 

MMI scores. The percent predator taxa was relatively high as well, suggesting a more intact aquatic 

insect food web (Schweiger et al. 2014). 
150 

Atkins et al. (2012) documented mean MMI and MVFP values from the Clark Fork River at Deer 

Lodge in 2011. The MMI mean value was 59.6, which was above the MT DEQ reference assessment 

point (>48); however, the MMI value was just below the ecoregion threshold developed by 

Schweiger et al. (2014) (>60.1). The MVFP mean value was 47.2, which was low compared to the 

MT DEQ reference assessment point (>75). The MVFP indicates moderate impairment in the Clark 

Fork River at Deer Lodge in 2011 (Table 45). 

Table 45. MMI and MVFP metric values and impairment class recorded at the Deer Lodge Station in 

2011 (Atkins et al. 2012).

Metric Score Impairment Class

MMI 59.6 Not impaired

MVFP 47.22 Moderate impairment

Threats and Stressor Factors

NPS staff identified several threats to macroinvertebrates in the park. Most of the threats involve 

point source and non-point anthropogenic disturbances, including metals contamination, excess 

nutrients, sedimentation, riparian habitat modification, dewatering, and shifts in temperature and 

precipitation due to climate change. 

Point sources of contamination in the Clark Fork watershed that threaten macroinvertebrates include 

historic mining and smelting operations. Those point sources leaking or running off into the Upper 

Clark Fork River resulted in the Superfund site designation. Mining contamination includes high 

concentrations of metals, dissolved solids, and salts, all of which can impact and reduce populations 

of aquatic organisms, especially macroinvertebrates (Cain et al. 2004). Elevated metal levels can be 

found in the water, sediment, and aquatic organisms of the Clark Fork (Smith et al. 1998). Non-point 

sources include fine inorganic sediment. Increased levels of fine inorganic sediment negatively 

impact macroinvertebrates, fish, primary and secondary production, and nutrient cycling by 

increasing turbidity (Relyea et al. 2000). Increased turbidity leads to lower primary production which 

in turn leads to habitat reduction for macroinvertebrates. Available food sources can also be buried 

under the increased inorganic sediment (Relyea et al. 2000). 

Excess nutrients are a cause of concern for macroinvertebrates in GRKO. Nitrogen and phosphorus 

generate algae growth, which in turn may cause significant changes in macroinvertebrate abundance 

and composition (McGuire 1990). Macroinvertebrate densities may initially increase due to nutrient 

enrichment. However, once nutrient levels become too high, they become toxic and cause 

macroinvertebrate densities to decline (McGuire 1990). Taxa composition also changes with higher 

levels of nutrients. Numbers of tolerant species increase while sensitive species decline in numbers 

(McGuire 1990). McGuire (2007) showed that nutrient/organic pollution was a concern in the Clark 

Fork near GRKO (Deer Lodge Station) in 2006. This site was one of 11 sites along the Clark Fork 

that were considered to have significant biological impairment (McGuire 2007). According to 

McGuire (2010), the Clark Fork is susceptible to nutrient pollution in the Deer Lodge Valley and has 

been observed to be impaired in past years. 

Dewatering is another threat to macroinvertebrates in GRKO. Water withdrawal for irrigational 

operations is the main type of dewatering affecting macroinvertebrates in the Clark Fork basin 
151 

(Watson 1985). Water may also be lost from the system at the Warm Springs settling ponds upstream 

of GRKO, where the surface area of the water is increased and flow is slowed, allowing for increased 

evaporation (Smith, written communication, 5 September 2014). These water losses may impact 

macroinvertebrates by altering streamflow, which in turn may decrease water quality, especially by 

increasing heavy metal concentrations (Watson 1985). Dewatering has resulted in decreased aquatic 

macroinvertebrate abundance, richness, and evenness (Muehlbauer et al. 2011). 

Climate change is a growing concern and threat to macroinvertebrates in GRKO. Increasing water 

temperatures and low flow rates are often attributed to climate change (Isaak et al. 2012, Leppi et al. 

2012). Increasing water temperatures cause dissolved oxygen (DO) levels to decrease. When DO 

levels are low, respiration becomes more difficult for aquatic life (e.g., fish and macroinvertebrates) 

(USGS 2014). Low flow rates and droughts may result in a skewed macroinvertebrate community

(Boulton 2003), favoring smaller organisms as well as organisms more tolerant of drought. Climate 

change has also been known to change sediment type, which can be either beneficial or problematic 

for aquatic macroinvertebrates. When fine sediment increases as a result of climate change, pools can 

fill and cause habitat degradation, which is detrimental to aquatic life especially macroinvertebrates 

(Goode et al. 2012). In addition, climate change may impact invertebrate phenology. Harper and 

Peckarsky (2006) suggest that warmer water temperatures and lower flow rates could cause temporal 

shifts in mayfly metamorphosis. 

Data Needs/Gaps

There are no historical or long-term RIVPACS or MMI data for aquatic macroinvertebrates in 

GRKO, making it impossible to identify any trends in the community over time based on these 

metrics alone. The most recent data available for macroinvertebrate communities in or near GRKO 

are from a 2011 study (Atkins et al. 2012). The ROMN collected additional data from 2011-2013, but 

it was not yet ready for publication at the time this NRCA was written. Future monitoring of 

macroinvertebrates in the Upper Clark Fork River at GRKO will be needed to better assess the 

current condition and possible trends. With Superfund remediation activities occurring along the 

Clark Fork in GRKO in the coming years, an opportunity exists to study how aquatic 

macroinvertebrates are impacted by the initial disturbance and by the subsequent “improved” (e.g., 

less contaminated) conditions. 

Overall Condition 

RIVPACS

The Significance Level for RIVPACS was assigned a 3. Schweiger et al. (2014) presented two 

RIVPACS metrics for each year during the study. The O:E RIVPACS metrics in both years met the 

ecoregion threshold (1.0) developed by Schweiger et al. (2014) and were also above the reference 

assessment point of 0.8 utilized by the MT DEQ, meaning the state would deem the community “not 

impaired”. The Bray Curtis dissimilarity metrics for 2008 and 2009 were both within the ecoregion 

threshold (<0.30) developed by Schweiger et al. (2014). Atkins et al. (2012) presented a RIVPACS 

value of 0.78 at Deer Lodge in 2011, which suggests some impairment. The Condition Level for this 

measure is a 1, or low concern. 
152 

Multimetric Indices (MMI) 

The Significance Level for MMI was assigned a 3. Schweiger et al. (2014) calculated results for three 

MMI metrics, several stressor specific metrics, and the component metrics for the most current MMI 

for macroinvertebrates in GRKO during 2008 and 2009. The Low Valley MMI was above the MT 

DEQ threshold of 48 in both years, indicating that the agency would likely consider the 

macroinvertebrate community characteristic of a reference condition macroinvertebrate assemblage. 

When compared to the ecoregion threshold of 60 developed by Schweiger et al. (2014), GRKO 

values are above this point in 2008 and slightly below in 2009. Several other biotic indices calculated 

by Schweiger et al. (2014) did not meet reference points established in the literature, which may be 

of concern. However, it is important to note that these additional indices are not currently used by the 

MT DEQ and have no regulatory significance. Atkins et al. (2012) documented MMI and MVFP 

values in 2011 on the Clark Fork River at the Deer Lodge station. The MMI mean value was 59.6, 

which was above the MT DEQ reference assessment point (> 48); however, this value was just below 

the ecoregion threshold developed by Schweiger et al. (2014) (>60.1). The MVFP mean value was 

47.2, which was low compared to the MT DEQ reference assessment point (>75). The MVFP 

suggests impairment, although the metric is not currently used by the MT DEQ. Because the results 

from GRKO meet the reference assessment points for the MMI currently used by the MT DEQ, the 

Condition Level for this measure is a 1, or of low concern. 

Weighted Condition Score (WCS) 

The WCS for aquatic macroinvertebrates in GRKO was 0.33. This indicates that the aquatic 

macroninvertebrate community in the park is in good condition. However, this score is at the very 

top of the good condition range, and any small decline in the community could shift it into the 

moderate concern range. A trend could not be assessed due to the lack of historical and long-term 

data for the selected measures.

Aquatic Macroinvertebrates

Measures Significance 

Level

Condition 

Level WCS = 0.33 

RIVPACS 3 1 

MMI 3 1 

4.7.6 Sources of Expertise

Billy Schweiger, Rocky Mountain Network Ecologist
153 

4.7.7 Literature Cited

Atkins, Rhithron Associates, Inc., and Montana Fish, Wildlife and Parks. 2012. Monitoring report for 

2011: Clark Fork River Operable Unit. Montana Department of Environmental Quality and 

Montana Department of Justice, Helena, Montana.

Bollman, W. 1998. Improving stream bioassessment methods for the Montana Valley and Foothill 

Prairies Ecoregion. Thesis. University of Montana, Missoula, Montana.

Boulton, A. J. 2003. Parallels and contrasts in the effects of drought on stream macroinvertebrate 

assemblages. Freshwater Biology 48:1173-1185. 

Bukantis, R. 1998. Rapid bioassessment macroinvertebrate protocols: Sampling and sample analysis 

SOPs. Montana Department of Environmental Quality, Planning and Prevention and Assistance 

Division, Helena, Montana. 

Cain, D. J., S. N. Luoma, and W. G. Wallace. 2004. Linking metal bioaccumulation of aquatic 

insects to their distribution patterns in a mining-impacted river. Environmental Toxicology and 

Chemistry 23(6):1463-1473. 

Environmental Protection Agency (EPA). 2012. Macroinvertebrates and habitat. U.S. Environmental 

Protection Agency. http://water.epa.gov/type/rsl/monitoring/vms40.cfm (accessed 21 July 2014). 

Goode, J. R., C. H. Luce, and J. M. Buffington. 2012. Enhanced sediment delivery in a changing 

climate in semi-arid mountain basins: implications for water resource management and aquatic 

habitat in the Northern Rocky Mountains. Geomorphology 139-140:1-15. 

Harper, M. P., and B. L. Peckarsky. 2006. Emergence cues of a mayfly in a high-altitude stream 

ecosystem: potential response to climate change. Ecological Applications 16(2):612-621. 

Hawkins, C. P., R. H. Norris, J. N. Hogue, and J. W. Feminella. 2000. Development and evaluation 

of predictive models for measuring the biological integrity of streams. Ecological Applications 

10:1456-1477. 

Hawkins, C. P. 2005. Development of a RIVPACS (O:E) Model for assessing the biological integrity 

of Montana streams. The Western Center for Monitoring and Assessment of Freshwater 

Ecosystems, Utah State University, Logan, Utah. 

Hilsenhoff, W. L. 1988. Rapid field assessment of organic pollution with a family-level biotic index. 

Journal of the North American Benthological Society 7:65-68. 

Ingman, G. L., and M. A. Kerr. 1989. Water quality in the Clark Fork River basin Montana: state 

fiscal years 1988-1989. Montana Department of Health and Environmental Sciences, Water 

Quality Bureau. Helena, Montana. 
154 

Isaak, D. J., S. Wollrab, D. Horan, and G. Chandler. 2012. Climate change effects on stream and 

river temperatures across the northwest U.S. from 1980-2009 and implications for salmonid 

fishes. Climatic Change 133:499-524. 

Jessup, B., C. Hawkins, and J. Stribling. 2006. Biological indicators of stream condition in Montana 

using benthic macroinvertebrates. Prepared for the Montana department of Environmental 

Quality by TetraTech, Inc., Owing Mills, MD, and the Western Center for Monitoring and 

Assessment of Freshwater Ecosystems, Utah State University, Logan, Utah.

Karr, J. R. 1998. Rivers as sentinels: Using the biology of rivers to guide landscape management. 

Pages 502-528 in R. J. Naiman and R. E. Bilby (eds.). River ecology and management: Lessons 

from Pacific coastal ecosystems. Springer Publishing, New York, New York. 

Leppi, J. C., T. H. De Luca, S. W. Harrar, S. W. Running. 2012. Impacts of climate change on 

August stream discharge in the Central-Rocky Mountains. Climatic Change 112:997-1014. 

McGuire, D. L. 1987. Clark Fork River macroinvertebrates study, 1986. Technical report prepared 

for the Montana Governor’s office and Montana Water Quality Bureau. Helena, Montana. 

McGuire, D. L. 1989. Clark Fork River aquatic macroinvertebrate survey, August, 1987. Technical 

report prepared for the Montana Department of Health and Environmental Sciences/Water 

Quality Bureau. Helena, Montana. 

McGuire, D. L. 1990. Aquatic macroinvertebrate surveys in the Clark Fork River, 1986 to 1988. 

Clark Fork Symposium. University of Montana, Missoula, Montana. 

McGuire, D. L. 2007. Clark Fork River biomonitoring: macroinvertebrate community assessments, 

2006. United States Environmental Protection Agency, Region 8, Denver, Colorado. 

McGuire, D. L. 2010. Clark Fork River biomonitoring: Macroinvertebrate community assessments in 

2009. U.S. Environmental Protection Agency, Region 8, Denver, Colorado. 

Montana Department of Environmental Quality (MT DEQ). 2012a. Water quality planning bureau 

field procedures manual for water quality assessment monitoring. Version 3.0. Montana 

Department of Environmental Quality, Helena, Montana. 

Montana Department of Environmental Quality (MT DEQ). 2012b. Montana 2012 Final Water 

Quality Integrated Report. Montana Department of Environmental Quality, Helena, Montana.

Montana Department of Environmental Quality (MT DEQ). 2012c. Sample collection, sorting, 

taxonomic identification, and analysis of benthic macroinvertebrate communities standard 

operating procedure. Montana Department of Environmental Quality, Helena, Montana. 

Muehlbauer, J. D., M. W. Doyle, and E. S. Bernhardt. 2011. Macroinvertebrate community responses 

to a dewatering disturbance gradient in a restored stream. Hydrology Earth System Sciences 

15:1771-1783. 
155 

Relyea, C. D., G. W. Minshall, R. J. Danehy. 2000. Stream insects as bioindicators of fine sediment. 

Watershed Management 2000 Conference. Stream Ecology Center, Department of Biological 

Sciences, Idaho State University, Pocatello, Idaho. 

Schweiger, E. W., L. O’Gan, D. Shorrock, and M. Britten. 2014. Stream ecological integrity at 

Grant-Kohrs Ranch National Historic Site: Rocky Mountain Inventory & Monitoring Network 

2008-2010 stream monitoring report. Natural Resource Technical Report NPS/ ROMN/NRTR—

2014/881. National Park Service, Fort Collins, Colorado. 

Smith, J. D., J. H. Lambing, D. A. Nimick, C. Parrett, M. Ramey, and W. Schafer. 1998. 

Geomorphology, flood-plain tailings, and metal transport in the Upper Clark Fork Valley, 

Montana. 

Stoddard, J. L., D. V. Peck, S. G. Paulsen, J. Van Sickle, C. P. Hawkins, A. T. Herlihy, R. M. 

Hughes, P. R. Kaufmann, D. P. Larsen, G. Lomnicky, and others. 2005. An ecological 

assessment of western streams and rivers. U.S. Environmental Protection Agency, Washington, 

D.C. 

U.S. Geological Survey (USGS). 2014. Water properties and measurements. 

http://ga.water.usgs.gov/edu/characteristics.html (accessed 17 September 2014). 

Van Sickle, J. 2008. An index of compositional dissimilarity between ovserved and expected 

assemblages. Journal of the North American Benthological Society 27:227-235. 

Watson, V. J. 1985. A synthesis of water quality problems in the Clark Fork River Basin. University 

of Montana, Missoula, Montana. 

http://cas.umt.edu/clarkfork/Past_Proceedings/1985_proceedings/Watson/Watson.htm (accessed 

3 July 2014). 
156 

4.8 Air Quality

4.8.1 Description

Air pollution can significantly affect natural resources and their associated ecological processes, and 

the health of park visitors. Consequently, air quality in parks and wilderness areas is protected and 

regulated through the 1916 Organic Act and the Clean Air Act of 1977 (CAA) and the CAA’s 

subsequent amendments. The Clean Air 

Act defines two distinct categories of 

protection for natural areas, Class I and 

Class II airsheds. Class I airsheds receive 

the highest level of air quality protection 

as offered through the CAA; only a small 

amount of additional air pollution is 

permitted in the airshed above baseline 

levels. For Class II airsheds, the increment 

ceilings for additional air pollution above 

baseline levels are slightly greater than for 

Class I areas and allows for moderate 

development (EPA 2013a). GRKO is 

designated as a Class II airshed. 

Parks designated as Class I and II airsheds typically use the EPA’s National Ambient Air Quality 

Standards (NAAQS) for criteria air pollutants as the ceiling standards for allowable levels of air 

pollution. The EPA believes these standards, if not exceeded, protect human health and the health of 

natural resources (EPA 2013a). The CAA also establishes that current visibility impairment in these 

areas must be remedied and future impairment prevented (EPA 2013a). However, the EPA 

acknowledges that the current NAAQS are not necessarily protective of ecosystems and is currently 

developing secondary NAAQS for ozone, nitrogen, and sulfur compounds to protect sensitive plants, 

lakes, streams, and soils (EPA 2010, EPA 2011a). 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). 

GRKO is located in semirural western Montana, which has allowed it to be relatively unaffected by 

industrial air pollution; however, some air pollution does occur (NPS 1993). Agricultural burning, 

sawmill activity, timber slash, road dust, and residential fuelwood burning have all been observed 

and may be contributing to pollution in the area (NPS 1993). Poor visibility is an issue caused by air 

pollution; visibility issues are mostly attributed to regional forest fires and regional prescribed burns 

(Smith, written communication, 16 September, 2014). 

4.8.2 Measures

• Sulfate deposition 

• Nitrogen deposition 

Photo 26. View from Grant Kohrs Ranch on a clear, high 

visibility day (NPS photo).
157 

• Ozone 

• Particulate matter (PM2.5) 

• Visibility

Atmospheric Deposition of Sulfur and Nitrogen 

Sulfur and nitrogen oxides 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 atmosphere where, in the upper atmosphere, 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 and 

volatile organic compounds (VOCs) in the presence of heat and sunlight (NPS 2008). Ozone is also 

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 2012c). 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). At high concentrations, ozone can aggravate respiratory 

and cardiovascular diseases, reduce lung function, cause acute respiratory problems, and increase 

susceptibility to respiratory infections (EPA 2012a, EPA 2012d, EPA 2013b); this would be a 

concern for visitors and staff engaging in aerobic activities in the park, such as hiking. 

Particulate Matter (PM) 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, EPA 2014b). 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 and/or vehicles react with air (EPA 2013c, EPA 2014b). 

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, EPA 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, EPA 2013c, EPA 2014b). Short-term 
158 

exposure to these particles can cause shortness of breath, fatigue, and lung irritation (EPA 2012a, 

EPA 2013c). 

4.8.3 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 

(Table 46) (NPS 2011). Assessment of current condition of nitrogen and sulfur atmospheric 

deposition is based on wet (rain and snow) deposition. Ozone condition is based on the NAAQS 

standard of 75 parts per billion (ppb) (an annual fourth-highest daily maximum 8-hr concentration, 

averaged over 3 years). The NAAQS standard for PM2.5 is a weighted annual mean of 15.0 μg/m3

 or 

35 μg/m3 in a 24-hour period over an average of 3 years (EPA 2011a). Visibility conditions are 

assessed in terms of a Haze Index, a measure of visibility (termed deciviews) that is derived from 

calculated light extinction and represents the minimal perceptible change in visibility to the human 

eye (NPS 2011). Finally, NPS ARD recommends the following values for determining air quality 

condition (Table 46). The “good condition” metrics may be considered the reference condition for 

GRKO.

Table 46. National Park Service Air Resources Division air quality index values (NPS 2011).

Condition

Ozone 

Concentration 

(ppb)

Wet Deposition of N 

or S

(kg/ha/yr)

Visibility

(dv*)

Significant Concern ≥76 >3 >8

Moderate Condition 61-75 1-3 2-8

Good Condition ≤60 <1 <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.

4.8.4 Data and Methods

Monitoring in the Park 

There is no active on-site 

monitoring of air quality 

parameters in Deer Lodge or 

within GRKO. The closest 

monitoring locations are in Butte, 

Clancy, Helena, and Missoula, 

Montana. Figure 41 displays the 

locations of the air quality 

monitoring stations nearest to 

GRKO.

NPS Data Resources 

Although data on air quality 

parameters are not actively 

collected within park boundaries, 

Figure 41. Locations of the air quality monitoring stations nearest 

to GRKO.
159 

data collected at several regional monitoring stations for various parameters can be used to estimate 

air quality conditions in GRKO. NPS ARD provides estimates of ozone, wet deposition of nitrogen 

and sulfur, 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 (2008 - 2012). These estimates are available from the Explore Air website (NPS 2014) and are 

used to evaluate air quality conditions. On-site or nearby data are needed for a statistically valid 

trends analysis, while a 5-year average interpolated estimate is preferred for the condition 

assessment. NPS (2010) describes air quality conditions and trends in an annual report for over 200 

park units, including GRKO. 

Other Air Quality Data Resources 

The EPA Air Trends Database provides annual average summary data for ozone concentrations near 

GRKO (EPA 2014a). Ozone concentrations are collected at a monitor in Missoula, MT (site ID 30-

063-0024), located approximately 137 km (85 mi) from GRKO. The site is operated by the MT DEQ

Air Quality Division and has collected data from June 2010 through January 2014 (EPA 2014a). 

Since 2014 data are not complete at the time of assessment, data through December 2013 are used for 

assessment. The nearest monitors collecting data on particulate matter concentrations (PM2.5) are 

located at Butte (Site ID: 30-093-0005), Helena (Site ID: 30-049-0026), and Missoula (site ID 30-

063-0024), Montana. The Butte monitoring station is approximately 48 km (30 mi) from GRKO; this 

monitor has collected data from March 2008 through January 2014. The Helena monitoring station is 

72 km (45 mi) from the park and has collected data from August 2008 through January 2014. The 

Missoula site (ID 30-063-0024), which is the same monitor location as ozone, has collected 

particulate matter data from November 2008 through January 2014. All three monitors are currently 

active in data collection and are operated by the MT DEQ Air Quality Division. Results from 

monitors located within 16 km (10 mi) from parks are generally considered to be representative of 

park conditions. Data recorded at monitors beyond this distance from parks may represent regional 

conditions, but may not be representative of actual park conditions, and caution exhibited in drawing 

conclusions about park condition (Ellen Porter, NPS Air Resources Division Air Quality Specialist, 

phone communication, 25 October 2012). 

The National Atmospheric Deposition Program–National Trends Network (NADP) database 

provides annual average summary data for nitrogen and sulfur concentration and deposition across 

Montana (NADP 2014). The nearest NADP monitoring site is located at Clancy, MT (site ID:

MT07), approximately 109 km (68 mi) east of GRKO. This site has collected deposition data for the 

region since 1984 and is currently active in monitoring (NADP 2014). The proximity of this monitor 

to GRKO, as well as access to the monitor data summaries, is viewable on the NPS Air Atlas – 

Estimated Atmospheric Deposition website (NPS 2013b). 

The Interagency Monitoring of Protected Visual Environments Program (IMPROVE) actively 

monitors visibility conditions in Class I airsheds across the U.S. The IMPROVE monitoring site 

nearest to GRKO is located northeast of Helena, MT, in the Gates of the Mountains Wilderness 

(monitor ID GAMO1), approximately 97 km (60 mi) from the park. The Visibility Information 

Exchange Web System (VIEWS) database provides average annual visibility monitoring data (in 
160 

deciviews) and trend graphics for the GAMO1 monitoring site from 2000-2008 for the clearest and 

haziest 20% of days for the region (VIEWS 2010). Due to its distance from GRKO, data from this 

monitor are likely representative of conditions in the area overall, but may not accurately represent 

conditions at the park specifically; thus, data are interpreted with care. 

Special Air Quality Studies

Sullivan et al. (2011a) assessed the relative sensitivity of national parks to the potential effects of 

acidification caused by acidic atmospheric deposition from nitrogen and sulfur compounds. The 

relative risk for each park was assessed by examining three variables: the level of exposure to 

emissions and deposition of nitrogen and sulfur; inherent sensitivity of park ecosystems to acidifying 

compounds (N and/or S) from deposition; and level of mandated park protection against air pollution 

degradation (i.e., Wilderness and Class I). The outcome was an overall risk assessment that estimates 

the relative risk of acidification impacts to park resources from atmospheric deposition of nitrogen 

and sulfur (Sullivan et al. 2011a). Using the same approach, Sullivan et al. (2011b) assessed the 

sensitivity of national parks to the effects of nutrient enrichment by atmospheric deposition of 

nitrogen. The outcome was an overall risk assessment that estimates the relative risk to park 

resources of nutrient enrichment from increased nitrogen deposition. 

4.8.5 Current Condition and Trend

Atmospheric Deposition of Nitrogen and Sulfur 

Five-year interpolated averages of total nitrogen (from nitrate and ammonium) wet deposition and 

total sulfur (from sulfate) wet deposition are used to estimate condition for deposition; using a fiveyear average smoothes out annual variations in precipitation, such as heavy precipitation one year 

versus drought conditions in another (NPS 2014). The current 5-year average (2008 - 2012) estimates 

deposition of total nitrogen in GRKO at 0.6 kg/ha/yr, while total deposition of sulfur is 0.2 kg/ha/yr 

(NPS 2014). Five-year averages for wet deposition of ammonium (NH4) is estimated at 0.4 kg/ha/yr , 

and estimates for deposition of sulfate (SO4) and nitrate (NO3) are 0.7 kg/ha/yr and 1.1 kg/ha/yr, 

respectively (NPS 2014). Relative to the NPS ratings for air quality conditions (see Table 46 for 

ratings values), atmospheric deposition of both nitrogen and sulfur falls into the Good Condition 

category. 

Concentrations (mg/L) of nitrogen, sulfur, and ammonium compounds in wet deposition can be used 

to evaluate trends in deposition of total 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 1984-2012 indicate that sulfate concentrations in GRKO have decreased 

overall, while ammonium has increased slightly, and nitrate has fluctuated substantially across the 

near 30 year period of record (NADP 2014). Figure 42 shows the annual concentration of nitrate, 

sulfate, and ammonium recorded at the nearest NADP monitor, located in Clancy, Montana 

(approximately 109 km [68 mi] north of the park). 
161 

Figure 42. Annual average concentrations of sulfate (SO4), nitrate (NO3), and ammonium (NH4) (mg/L) in 

precipitation in GRKO, 1984-2012 (NADP monitoring site MT07) (Source: NADP 2014). Note: Ammonium 

(NH4) is included because it adds significantly to total nitrogen deposition.

Relative risk of acidification and nutrient enrichment of ecosystems was assessed by examining 

exposure to nitrogen deposition and acidification, inherent sensitivity of park ecosystems, and 

mandates for park protection. Sullivan et al. (2011c) ranked GRKO as having very low exposure to 

acidifying (nitrogen and sulfur) pollutants, very low ecosystem sensitivity to acidification, and 

moderate park protection due to its Class II airshed status. The ranking of overall risk from 

acidification due to acid deposition was very low relative to other parks (Sullivan et al. 2011c). In a 

separate examination, Sullivan et al. (2011d) used the same approach to assess the sensitivity of 

national parks to nutrient enrichment effects from atmospheric nitrogen deposition relative to other 

parks. GRKO was ranked as having very low risk for nitrogen pollutant exposure, high ecosystem 

sensitivity, and moderate park protection mandates (Class II airshed). The ranking of overall risk of 

effects from nutrient enrichment from atmospheric nitrogen deposition was very low relative to other 

parks (Sullivan et al. 2011d). 

Ozone 

The NAAQS standard for ground-level ozone is the benchmark for assessing current ozone 

conditions within park units. In 2008, the standard was strengthened from 80 ppb to 75 ppb, based on 

the annual fourth highest daily maximum 8-hour concentration, averaged over 3 years (EPA 2012b). 

The condition of ozone in NPS units is determined by calculating the 5-year average of the fourthhighest daily maximum of 8-hour average ozone concentrations measured at each monitor within an 

area over each year (NPS 2011). The current 5-year average (from 2008 - 2012) for GRKO indicates 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

19841985198619871988198919901991199219931994199519961997199819992000200120022003200420052006200720082009201020112012

Concentration (mg/L)

Nitrate (NO3) Sulfate (SO4) Ammonium (NH4)
162 

an average ground-level ozone concentration of 61.2 ppb (NPS 2014), which falls under the 

Moderate Condition category based on NPS guidelines (NPS 2013a). 

Long-term data that characterize ozone concentrations within the park do not exist. However, ozone 

concentrations are monitored daily by MT DEQ at the Sieben Flatts monitoring site near Helena, 

MT, approximately 80.5 km (50 mi) east of GRKO. Although results from this monitor may not be 

representative of ozone concentrations within GRKO, they are considered to represent concentrations 

in the general region of the park. Figure 43 illustrates the trend in annual fourth-highest daily 

maximum 8-hour values from 2011 to 2014; these are presented with revised national standards to 

provide perspective on acceptable versus potentially harmful ozone conditions in the region. 

Concentrations range from 46.0 to 57.0 ppb (EPA 2014b); all measurements are well within the 

standards considered protective of human health. 

Figure 43. Annual 4th highest 8-hour maximum ozone (O3) concentrations (ppb) in the GRKO region, 

2011-2014 (Source: EPA 2014b). Note: Seiben Flatts, MT monitoring site 30-049-0004 is located 

approximately 80.5 km (50 mi) east of GRKO. 

Kohut (2004) assessed ozone concentrations in ROMN 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 around GRKO frequently exceeded 60 ppb and only occasionally exceeded 80 

ppb (less than 20 hours each year); concentrations exceeded 100 ppb very rarely (total of 6 hours 

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. However, the infrequent incidence of concentrations higher than 80 

ppb in GRKO and rare or mild drought conditions make the risk of foliar injury from ozone low 

20

30

40

50

60

70

80

90

2011 2012 2013 2014

Concentration (ppb)

National Standard
163 

(Kohut 2004). If the level of risk increases in the future, ozone foliar damage may be assessed using 

quaking aspen (Populus tremuloides) as an indicator species (Kohut 2004). 

Particulate Matter (PM2.5) 

The NAAQS standard for PM2.5 is a weighted annual mean of 15.0 μg/m3 or 35 μg/m3 in a 24-hour 

period over an average of 3 years (EPA 2012b). Particulate matter concentrations collected at 

monitors in Helena, Missoula, and Butte, Montana are available from 2008 through 2013. Weighted 

annual average PM2.5 concentrations in the GRKO region during the time of data collection appear to 

be relatively stable in recent years, fluctuating slightly between 7 and 11 μg/m3

 (Figure 44)(EPA 

2014a). All measurements were well within the EPA standards for levels that are protective of human 

health at the time of active data collection.

Figure 44. Annual particulate matter (PM2.5) concentrations (weighted annual mean) near GRKO, 2008-

2013 (EPA 2014a). Note: Monitoring stations are located in Butte, Helena, and Missoula, MT.

Visibility

Visibility impairment occurs when airborne particles and gases scatter and absorb light; the net effect 

is called “light extinction,” which is a reduction in the amount of light from a view that is returned to 

an observer (EPA 2003). In response to the mandates of the CAA of 1977, federal and regional 

organizations established IMPROVE in 1985 to aid in monitoring of visibility conditions in Class I 

airsheds. The goals of the program are to 1) establish current visibility conditions in Class I airsheds; 

2) identify pollutants and emission sources causing the existing visibility problems; and 3) document 

long-term trends in visibility (NPS 2010, NPS 2013a). 

The most current 5-year average (2008 - 2012) estimates average visibility in GRKO to be 3.1 dv 

above average natural visibility conditions (NPS 2014). This estimate falls into the Moderate 

Condition category based on NPS criteria for air quality assessment. 

3

5

7

9

11

13

15

17

2008 2009 2010 2011 2012 2013

Concentration (μg/m3)

Butte Helena Missoula

National Standard 
164 

The clearest and haziest 20% of days each year are also examined for parks (NPS 2014), as these are 

the measures used by states and EPA to assess progress towards meeting the national visibility goal. 

Conditions measured near 0 dv are clear and provide excellent visibility, and as dv measurements 

increase, visibility conditions become hazier. The most current 5-year average (2008 - 2012) 

estimates visibility at GRKO at 2.7 dv on the 20% clearest days and 14.2 dv on the 20% haziest days 

(NPS 2014). These estimates fall into the Moderate Condition and Significant Concern categories, 

respectively. Figure 45 displays visibility data (in dv) collected at Gates of the Mountains wilderness 

area (monitor ID GAMO1), approximately 97 km northeast of GRKO; data represented show the 

average visibility on the clearest and haziest 20% of days each year for the region (VIEWS 2010). 

Figure 45. Annual average visibility in the GRKO region, 2001-2008 (VIEWS 2010). The Gates of the 

Mountains (GAMO1) monitor is located northwest of Helena, MT, approximately 97 km (60 mi) from 

GRKO. Values shown indicate average visibility during the 20% clearest and 20% haziest days each 

year. Values at 2064 are the natural background visibility conditions, set by EPA Regional Haze Rule, to 

which all Class I areas are required to restore visibility conditions by 2064. 

Threats and Stressor Factors 

The GRKO park staff identified two potential threats to air quality in the park. These threats to the air 

quality in the park include agricultural and riparian burning. Pollution, affecting historical buildings, 

is a potential threat that could result from poor air quality. Agricultural burning occurs on an annual 

basis in GRKO, while riparian burning has been a more recent effort to restore the riparian corridor 

inside the park. According to Jimenez (2002), agricultural burning can impact air quality. Increased 

PM2,5 concentrations are one characteristic of impacted air quality from agricultural burning (Jimenez 

2002). Air pollution is another threat because it adversely affects the historic buildings and structures 
165 

located in GRKO. Atmospheric corrosion may occur on the historic buildings as a result of dry and 

wet deposition of pollutants (Kucera and Fitz 1995). 

According to the EPA and the Intergovernmental Panel on Climate Change (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 air quality monitors within the acceptable distance (16 km [10 mi]) to accurately 

represent conditions in the park. The closest monitors are located more than 56 km (35 mi) away. 

Monitors in Helena and Butte provide particulate matter and ozone concentration data as both daily 

and annual average summaries. The nearest active NADP monitor that provides annual averages for 

nitrogen and sulfur deposition is located in Clancy, Montana, approximately 109 km (68 mi) west of 

GRKO. The nearest IMPROVE site, which monitors visibility, is located in Glacier National Park, 

over 333 km (207 mi) northwest of GRKO. Periodic or consistent monitoring of nitrogen and sulfur 

deposition, ozone, particulate matter, and visibility would help managers better understand the local 

air quality conditions in and around GRKO and how they may affect other park resources. 

Overall Condition 

Sulfate Deposition 

The Significance Level for sulfate deposition was also defined as a 3. Current NPS interpolated 

averages for nitrogen deposition are considered to be in Good Condition, based on NPS criteria for 

rating air quality (NPS 2014). Sullivan et al. (2011a, 2011c) rate GRKO as having very low exposure 

to acidifying (nitrogen and sulfur) pollutants, very low ecosystem sensitivity to acidification, and 

moderate park protection due to its Class II airshed status, with a very low overall risk from 

acidification due to acid deposition relative to other parks. NADP (2014) data show relatively stable 

concentrations of sulfate over the past 10 years, all measuring less than 1 mg/L. As a result, sulfate

deposition was assigned a Condition Level of 0, or no concern/good condition. 

Nitrogen Deposition 

The Significance Level for nitrogen deposition was also defined as a 3. Current NPS interpolated 

averages for nitrogen deposition are considered to be in Good Condition, based on NPS criteria for 

rating air quality (NPS 2014). Likewise, Sullivan et al. (2011b, 2011d) rate GRKO as having very 

low risk for nitrogen pollutant exposure, high ecosystem sensitivity, and moderate park protection 

mandates (Class II airshed), with a very low overall risk of effects from nitrogen deposition of 

relative to other parks. NADP (2014) data show relatively stable concentrations of nitrate and 

ammonium over the past 10 years, all measuring less than 1 mg/L. As a result, nitrogen deposition 

was assigned a Condition Level of 0, or no concern/good condition. 
166 

Ozone Concentration 

The Significance Level for ozone was also defined as a 3. Current average ground-level ozone 

concentrations fall into the moderate condition category based on NPS criteria for rating air quality 

condition. Annual 4th highest 8-hour maximum concentrations (2011 through 2014) show relatively 

stable concentrations for the short period of record; this is not a long enough record of data to assess 

a trend. All measurements are well within EPA standards protective of human health. Kohut (2004) 

suggests the risk of foliar injury from ozone is low for the park. Therefore, the Condition Level for 

ozone concentration is a 0, of no concern/good condition. 

Particulate Matter 

The Significance Level for particulate matter was also defined as a 3. Weighted annual average PM2.5

concentrations in the GRKO region appear to be relatively stable in recent years (2009-2013), 

fluctuating only slightly (EPA 2014a). All measurements were well within the EPA standards for 

levels that are protective of human health. As a result of this, the Condition Level for particulate 

matter was assigned a 0, or no concern/good condition. 

Visibility

The Significance Level for visibility was also defined as a 3. Current interpolated average visibility 

estimates fall into the moderate concern category based on NPS criteria. Visibility on the 20% 

clearest days also falls into the moderate concern category (though just barely), while visibility on 

the 205 haziest days falls into the significant concern category. The Condition Level for visibility was 

assigned a 2, indicating visibility is of moderate concern. 

Weighted Condition Score 

The Weighted Condition Score for the component is 0.13, indicating air quality is in good condition 

overall, warranting no concern. Available data and estimates imply the trend for all assessed air 

quality parameters is stable, as indicated by the horizontal double arrow in the graphic. This 

condition designation is assigned with a moderate level of confidence based on the available data 

from multiple agencies and estimates provided by the NPS Air Resources Division. Air quality is 

considered a vital sign for GRKO and, although it is not monitored directly in the park, air quality 

information is interpolated from regional air monitors and basic parameters are estimated for the park 

on a yearly basis.
167 

Air Quality

Measures Significance 

Level

Condition 

Level WCS = 0.13 

Nitrogen Deposition 3 0 

Sulfur Deposition 3 0 

Ozone Concentration 3 0 

Particulate Matter 3 0 

Visibility 3 2 

4.8.6 Sources of Expertise

Ellen Porter, Biologist, NPS Air Resources Division 
168 

4.8.7 Literature Cited

Environmental Protection Agency (EPA). 2003. Guidance for estimating natural visibility conditions 

under the Regional Haze Rule. EPA-454/B-03-005. Office of Air Quality Planning and 

Standards. Emissions, Monitoring and Analysis Division, Research Triangle Park, North 

Carolina. 

Environmental Protection Agency (EPA). 2010. Policy assessment for the review of the Secondary 

National Ambient Air Quality Standards for NOx and SOx: Second external review draft. 

EPA452/P-10-008. Office of Air Quality Planning and Standards Health and Environmental 

Impacts 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. 

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. Air & radiation: National Ambient Air Quality 

Standards (NAAQS). http://www.epa.gov/air/criteria.html (accessed 30 May 2014). 

Environmental Protection Agency (EPA). 2012c. Ground level ozone: ecosystem effects. 

http://www.epa.gov/airquality/ozonepollution/ecosystem.html (accessed 2 June 2014). 

Environmental Protection Agency (EPA). 2012d. 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 data. http://www.epa.gov/airdata/ad_maps.html 

(accessed 4 April 2014). 
169 

Environmental Protection Agency (EPA). 2014b. 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). 

Jimenez, J. R. 2002. Air quality from agricultural field burning in eastern Washington. Thesis. 

Washington State University, Pullman, Washington

Kohut, R. J. 2004. Ozone risk assessment for Rocky Mountain Network. NPS/NRPC/ARD/NRTR—

2004. National Park Service, Fort Collins, Colorado. 

Kucera, V., and S. Fitz. 1995. Direct and indirect air pollution effects on materials including cultural 

monuments. Water, Air, and Soil Pollution 85:153-165. 

National Atmospheric Deposition Program (NADP). 2014. National Atmospheric Deposition 

Program – National Trends Network Monitoring location MT07 (Clancy, Montana). 

http://nadp.sws.uiuc.edu/sites/siteinfo.asp?id=MT07&net=NTN (accessed 3 April 2014). 

National Park Service (NPS). 1993. Grant-Kohrs Ranch National Historic Site environmental impact 

statement for a general management plan and development concept plan. National Park Service, 

Rocky Mountain Region, Fort Collins, Colorado. 

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). 2010. Air quality in national parks: 2009 annual performance and 

progress report. Natural Resource Report NPS/NRPC/ARD/NRR—2010/266. National Park 

Service, Denver, Colorado. 

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). 2013a. 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). 2013b. Air Atlas – Estimated atmospheric deposition. 

http://www.nature.nps.gov/air/Maps/AirAtlas/deposition.cfm (accessed 3 June 2014). 

National Park Service (NPS). 2014. NPS air quality estimates: ozone, wet deposition, and visibility. 

http://www.nature.nps.gov/air/Maps/AirAtlas/IM_materials.cfm (accessed 4 May 2014). 
170 

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., G. T. McPherson, T. C. McDonnell, 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: Rocky Mountain Network (ROMN). Natural 

Resource Report NPS/NRPC/ARD/NRR—2011/371. National Park Service, Denver, Colorado. 

Sullivan, T. J., G. T. McPherson, T. C. McDonnell, 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: Rocky Mountain Network (ROMN). Natural Resource Report 

NPS/NRPC/ARD/NRR—2011/324. National Park Service, Denver, Colorado. 

Visibility Information Exchange Web System (VIEWS). 2010. Air quality data, tools, and resources: 

Trends analysis – Gates of the Mountains (GAMO1) monitor. 

http://views.cira.colostate.edu/web/Trends/ (accessed 2 July 2014).
171 

4.9 Water Quality

4.9.1 Description

A healthy ecosystem requires good quality ground and surface water. Water quality affects species 

abundance and distribution for both plant and aquatic species, as well as the overall health of the 

natural ecosystem and the human inhabitants of an area. Water chemistry has been identified as a 

Vital Sign for parks in the ROMN, including GRKO (Britten et al. 2007). Water temperature, 

specific conductance, pH, total suspended sediment, dissolved oxygen, coliform bacteria, nutrients, 

and metals are the core water quality measures of concern identified by the park. 

The Clark Fork River (Photo 27) drains a large portion of western Montana, beginning at the 

confluence of Silver Bow Creek and Warm Springs Creek near Butte, MT, and ultimately emptying 

into the Columbia River in Washington (Thornberry-Ehrlich 2007). Approximately 5.5 km (3.4 mi) 

of the Upper Clark Fork River run through the center of the GRKO property (Figure 46). This 

portion of the river is directly downstream of the city of Deer Lodge, MT, with the northern section 

of the park containing the municipal waste water treatment facility for the city. GRKO lies between 

Cottonwood Creek on the upstream (south) end and Fred Burr Creek on the downstream (north) end. 

Most of the park’s surface water is contained in the Clark Fork River; however, numerous springs 

and creeks that feed into the Clark Fork also contribute to the total surface waters in GRKO. Several 

shallow level aquifers also contribute to the flow of the river throughout the park (ThornberryEhrlich 2007). 

Photo 27. Upper Clark Fork River at GRKO (photo by Sarah Gardner, SMUMN GSS 2013).
172 

Figure 46. Grant-Kohrs location map with water quality sampling locations (reproduced from Mast 2007).
173 

The Clark Fork River at GRKO is downstream from historic mining activity that has significantly

impacted the area. Mining began in the Deer Lodge Valley in 1864 when gold was discovered 

(Horstman 1984). Gold mining transitioned to silver mining and then to copper mining by the late 

1800s. The arrival of the railroad in 1883 allowed heavy mining equipment to be transported into the 

valley (Horstman 1984). Metals processing, as well as hydraulic mining, resulted in large quantities 

of minerals and waste products accumulating in the flood plain. Record flooding in the late 1800s 

and early 1900s (particularly in spring 1908) distributed these wastes throughout the 193 km (120 

mi) of the Upper Clark Fork River, eventually causing the Deer Lodge Valley to be designated as a 

Superfund site. Sediments deposited during these floods raised the level of the valley’s floodplain by 

a meter or more (Ramsey et al. 2005). High levels of mining contaminants including arsenic, 

cadmium, copper, magnesium, lead, zinc and iron are now embedded in the floodplain soils 

(Thornberry-Ehrlich 2007). Erosion continues to expose and re-distribute contaminated sediments, 

exposing the ecosystem to these toxic metals repeatedly. Superfund remediation activities will begin 

within the GRKO riparian corridor in late 2015 (Johnson, written communication, 10 February 

2015). Remediation will completely alter the riparian area, removing vegetation along with 

contaminated soils. The area will be replanted with grasses, shrubs and trees to restore its natural 

setting, but full recovery is expected to take more than 10 years (Johnson, written communication, 10 

February 2015). 

4.9.2 Measures

• Water temperature 

• Specific conductance 

• pH 

• Total suspended sediment 

• Dissolved oxygen

• Coliform bacteria 

• Nutrients

• Metals 

Water Temperature

Water temperature greatly influences water chemistry and can strongly affect aquatic organisms. Not 

only can temperature affect the ability of water to hold oxygen, but water temperature also affects 

biological activity within water systems (Allan 1995). All aquatic organisms, from fish to insects to 

zoo- and phytoplankton, have a preferred or ideal temperature range (Allan 1995). As temperature 

increases or decreases too far past this range, the number of individuals and species able to live there 

eventually decreases. In addition, higher temperatures allow some compounds or pollutants to 

dissolve more easily in water and can be more toxic to aquatic life (USGS 2014). 
174 

Specific Conductance 

Specific conductance is 

a measure of the ability 

of water to conduct 

electrical current, which 

depends largely on the 

amount of dissolved ions 

in the water (Allan 

1995). Water with low 

amounts of dissolved 

ions (such as purified or 

distilled water) will have 

a low specific 

conductance, while 

water with high amounts 

of dissolved solids (such 

as salty sea water) will 

have a higher specific 

conductance (Allan 

1995). Specific 

conductance is an important water quality parameter to monitor because high levels can indicate that 

water is unsuitable for drinking or aquatic life (USGS 2014). 

pH 

pH is a measure of the level of acidity or alkalinity of water and is measured on a scale from 0 to 14, 

with 7 being neutral (Allan 1995). Water with a pH of less than 7.0 indicates acidity, whereas water 

with a pH greater than 7.0 indicates alkalinity. Aquatic organisms have a preferred pH range that is 

ideal for growth and survival (USGS 2014). Chemicals in water can change the pH and harm animals 

and plants living in the water; thus, monitoring pH can be useful for detecting natural and humancaused changes in water chemistry (USGS 2014). 

Total Suspended Sediment (TSS)

Total suspended sediments (TSS) are inorganic and organic particles (e.g., sand, silt, algae) 

suspended within a water body. Suspended sediment is often measured by the dry weight of sediment 

collected in the water column (Robertson et al. 2006). TSS can also be measured indirectly through 

turbidity, which measures the extent of light scattered in water. Erosion along river banks increases 

the total suspended sediments in the river (Thornberry-Ehrlich 2007), and is currently a management 

concern in GRKO. Because much of the floodplain within the Deer Lodge Valley contains mining 

contaminants, an increase in suspended sediment in the water due to river bank erosion can raise the 

concentrations of toxic chemicals and metals in the river (Thornberry-Ehrlich 2007).

Photo 28. Water clarity in a tributary to Clark Fork within GRKO (photo by 

Sarah Gardner, SMUMN GSS 2013).
175 

Dissolved Oxygen

Dissolved oxygen (DO) is critical for organisms that live in water. Fish and zooplankton filter out or 

“breathe” dissolved oxygen from the water to survive (USGS 2014). Oxygen enters water from the 

air when atmospheric oxygen mixes with water at turbulent, shallow riffles in a waterway, or when 

released by aquatic plants as a byproduct of photosynthesis. As the amount of DO drops, it becomes 

more difficult for aquatic organisms to survive (USGS 2014). The concentration of DO in a water 

body is closely related to water temperature (cold water holds more DO than does warm water), 

altitude, salinity, and steam structure (turbulent, rapid waterways integrate more DO than slowmoving, stagnant waterways) (Allan 1995). Thus, DO concentrations are subject to seasonal 

fluctuations as low temperatures in the winter and spring allow water to hold more oxygen, and 

warmer temperatures in the summer and fall cause water to hold less oxygen (USGS 2014). 

Coliform Bacteria 

Total coliform is a measure used to assess the level of disease-causing microorganisms present in the 

water (EPA 1997). Coliform contamination can originate from point source urban discharge as well 

as from non-point source runoff. Fecal coliform is the most commonly used indicator of coliform 

bacteria in water (EPA 1997). 

Nutrients

Nutrients are chemical elements which are essential for plant and animal survival, but can become 

contaminants at higher concentrations in water (Mueller and Helsel 2013). Nitrates and phosphorus 

are two common nutrient contaminants in water bodies (Mueller and Helsel 2013). While nitrogen 

and phosphorus occur naturally in soils and thus in surface waters, they are increased by human 

inputs such as sewage, fertilizers, and livestock waste (Muir 2012). These nutrients can cause a host 

of water quality related problems when present in high concentrations, such as excessive plant and 

algae growth which depletes dissolved oxygen available to aquatic organisms, a process known as 

eutrophication (EPA 1997, 2012). Sources of nutrients entering the Clark Fork River include urban 

inputs (e.g., the Butte municipal wastewater treatment plant) and runoff as well as non-point source 

agricultural runoff (Mast 2007). 

Metals

Heavy metals have been present in elevated concentrations in the Clark Fork River sediment and 

water for many years (Smith et al 1998). Cadmium, copper, lead, zinc, and arsenic are some of the 

heavy metals found in the water and surrounding soils (Photo 29). While trace amounts of these 

metals occur naturally in the soils, the elevated levels in the Clark Fork floodplain are a result of 

historic mining and smelting processes upstream of the park (Thornberry-Ehrlich 2007). Toxic 

metals can accumulate in the food chain, causing damage to organisms (Besser and Leib 2007, EPA 

2013). Mercury contamination is caused by airborne deposition originating from coal combustion, 

waste incineration, mining, and natural sources (EPA 2014). In water, mercury is converted to 

methylmercury, a neurotoxin that is biomagnified in the aquatic food web (EPA 2014). 
176 

Photo 29. Metal tailings buried feet under the riparian top soil (photo by Sarah Gardner, SMUMN GSS 

2013)

4.9.3 Reference Conditions/Values

As noted in Schweiger et al. (2014, p. 8), the primary motivation of the NPS when monitoring stream 

health (including water quality) at GRKO is “to understand and document the long-term ecological 

condition of GRKO’s aquatic resources in order to better protect and manage them.” The NPS does 

not have any regulatory authority over waters in the park. Therefore, NPS water quality monitoring 

and analysis uses criteria that are deemed most useful for an ecological interpretation (Schweiger et 

al. 2014). These may include current state criteria, older criteria no longer in use, criteria still in 

development, or reference points newly developed by the NPS from ecological reference sites. 

For this assessment, the reference conditions for surface water quality in GRKO are primarily the 

MT DEQ water quality standards for aquatic life, or applicable EPA standards. Not all of the 

measures in this assessment have applicable state or federal (EPA) water quality standards. When 

measures are compared to other study results, or to suggested standards that do not carry the weight 

of law, it has been noted. 

Some measures have a relative standard, such as water temperature (Table 47, Table 48). Montana 

surface water temperature standards are based on the naturally occurring temperature in each water 

body and an acceptable variance from that. Other standards vary by classification or characteristics of 

the water body, such as hardness, pH, or season. The Clark Fork in the Deer Lodge Valley is 

classified as a C-1 surface water body, meaning it is “suitable for bathing, swimming, and recreation; 

growth and propagation of salmonid fishes and associated aquatic life, waterfowl, and furbearers; and 

agricultural and industrial water supply” (Mohr 2012, p. 7). 
177 

Table 47. Applicable reference standards for selected parameters of surface water at GRKO.

Parameter Surface Water Standard

Temperature No state-wide standard; variation allowed depends on natural water temperature 

range in each water body (MT DEQ 2006).

Specific Conductance No standard set for Clark Fork River. A 500 μs/cm standard recommended for 

Tongue River in eastern Montana (EPA 2007). This number was used as an 

informal reference condition for GRKO by Schweiger et al. (2014).

pH Induced variation in pH within the range of 6.5-8.5 must be less than 0.5 (MT DEQ 

2006). Natural pH outside this range must be maintained without change. Natural 

pH above 7.0 must be maintained above 7.0 (MT DEQ 2002). 

Total Suspended Sediment N/A

Dissolved Oxygen Early life stages: 9.5 mg/L (7-day mean) or 8.0 mg/L (1-day min)

Other Life Stages: 6.5 mg/L (30-day mean) or 4.0 mg/L (1-day min) (MT DEQ 

2012)

Coliform Bacteria 1 April - 31 October:<126 colony forming units (cfu) per 100 ml, and 10% of the 

total samples may not exceed 252 cfu per 100 ml during any 30-day period. 1 

November - 31 March: <630 cfu per 100 ml and 10% of the samples may not 

exceed 1,260 cfu per 100 ml during any 30-day period (MT DEQ 2006)

Total Phosphorus 21 June -21 September : 30 μg/L (Suplee and Watson 2013)

Total Nitrogen 21 June21 - 21 September : 300 μg/L (Suplee and Watson 2013)

Table 48. Applicable reference points for selected metals in surface water at GRKO (MT DEQ 2012). 

Note that these are not adjusted for hardness; given the water chemistry of the Clark Fork, reference 

points for cadmium, copper, and lead would be higher within GRKO (Schweiger et al.2014). 

Parameter Acute Chronic

Arsenic 340 μg/L 150 μg/L

Cadmium 0.52 μg/L 0.097 μg/L 

Copper 3.79 μg/L 2.85 μg/L 

Lead 13.98 μg/L 0.545 μg/L 

Zinc 37 μg/L 37 μg/L 

4.9.4 Data and Methods

At present, the EPA’s Storage and Retrieval water quality database management system (STORET) 

has more than 2,200 sampling event entries dating back to 1969 within 1 km (0.6 mi) of the park’s 

boundary. These sampling events include both surface and ground water, with a variety of 

parameters reported. Most of these data have been incorporated and interpreted into the following 

three reports.

Mast (2007) summarized surface and groundwater water quality monitoring for GRKO over 20 years 

(through 2004). The majority of this data was obtained from STORET or the USGS’s National Water 

Information System (NWIS). Parameters discussed include water temperature, DO, pH, specific 

conductance, nutrients, and metals. 

Schweiger et al. (2014) investigated the stream ecological integrity (SEI) in GRKO using data 

collected between May and mid-November from 2008-2010. NPS staff sampled a reach of the Clark 

Fork River that extended from the main bridge to the southern border of the park. Additional water 

temperature data from May 2001 through April 2010 were also obtained from the USGS water 
178 

monitoring station in Deer Lodge. Sample data from this study summarized in this NRCA include 

water temperature, nutrients, and water column and sediment metal concentration. 

Atkins et al. (2012) collected water quality measurements on a quarterly basis (April, June, 

September, and December) from the USGS gaging station on the Clark Fork at Deer Lodge (just 

upstream of GRKO) in 2011. Parameters monitored included water temperature, pH, DO, specific 

(electrical) conductance, nutrients. 

4.9.5 Current Condition and Trend

Water Temperature

Mast (2007) identified the median surface water temperature for the Clark Fork in or near GRKO as 

9.6°C (49.3°F). The minimum recorded was 0.0°C (32°F), and the maximum recorded temperature 

was 26.5°C (79.9°F). The data analyzed for this report were collected over a 24-year period from 

1980-2004, and included 637 sample results. Sampling locations are presented in Figure 46. 

Groundwater temperatures were sampled 79 times from 20 different wells (Figure 46; Mast 2007); 

all 20 wells were in or near GRKO. The median temperature recorded was 11.6°C (52.9°F), the 

minimum recorded temperature was 7.6°C (45.7°F), and the maximum recorded temperature was

17.4°C (63.3°F). The data analyzed for this report were collected over a 20 year period from 1980-

2000 and included 52 sample results (Mast 2007). 

Schweiger et al. (2014) also documented minimum, median, and maximum water temperatures for 

surface water in GRKO. Between 2008 and 2010, the median temperature was 5.5°C (41.9°F), the 

minimum temperature was 4.8°C (40.6°F), and the maximum temperature was 19.1°C (66.4°F). The 

variations in sampling timing and methodologies between Mast (2007) and Schweiger et al. (2014) 

may account for the differences in temperature ranges observed. 

Using data collected from the USGS gauging station at Deer Lodge, Schweiger et al. (2014) 

summarized the 7-day mean maximum temperatures from 2001-2010. These data were compared to 

the summer maximum temperature threshold of 15 °C for optimal bull trout (Salvelinus confluentus) 

rearing (USFWS 1998; Figure 47). Approximately 86% of summer temperatures during this period 

were above the maximum temperature threshold. When Schweiger et al. (2014) applied a flow and 

seasonally adjusted trend model (ESTREND; Schertz et al. 1991, Slack and Lorenz 2003) to these 

temperature data, a slight (but insignificant) positive trend in minimum water temperatures was seen, 

suggesting stream temperatures may have increased slightly over time. 
179 

Figure 47. Mean 7-day maximum water temperature for water years, 2001-2010 at Deer Lodge USGS 

gauge. Horizontal red line depicts maximum summer temperature threshold (USFWS 1998) for optimal 

bull trout rearing. Dotted vertical gray lines delineate water year boundaries (Reproduced from Schweiger 

et al. 2014).

Atkins et al. (2012) recorded water temperatures in the Clark Fork at Deer Lodge ranging from just 

above 0°C (32°F) in December to 10.9°C (51.6°F) in September (Table 49). All values fell within a 

similar range as Mast (2007) and Schweiger et al. (2014). 

Table 49. Water temperatures (°C) in the Clark Fork at Deer Lodge, 2011 (Atkins et al. 2012).

April June September December

Water Temperature (°C) 6.1 9.9 10.9 0.1

Specific Conductance 

Mast (2007) reported the median value for specific conductance of surface waters in GRKO from 

1980-2004 at 524 μS/cm, while the minimum recorded value was 208 μS/cm and the maximum was 

1,890 μS/cm. There were 534 sample results that measured specific conductance over this time 

period. Figure 48 below illustrates the specific conductance and its seasonal variance from a single 

sampling location (S3) over the course of 12 months. 
180 

Figure 48. Seasonal variation in specific conductance at a GRKO sampling site, 1982-2004 (reproduced 

from Mast 2007).

Mast (2007) reported that the specific conductance of GRKO’s groundwater had a median value of 

457 μS/cm, while the minimum recorded was 242 μS/cm and the maximum recorded was 799 

μS/cm. The data analyzed for this report were collected over a 20-year period from 1980 - 2000 and 

included 53 sample results. 

Schweiger et al. (2014) also documented minimum, median, and maximum specific conductance 

values of surface water at GRKO between 2008 and 2010. The median specific conductance value 

was 428.3 μS/cm, while the minimum specific conductance value was 266 μS/cm, and the maximum 

specific conductance value was 480.9 μS/cm. Montana has no formal state-wide reference condition 

for specific conductance, but the EPA (2007) developed criteria for the Tongue River tributaries in 

eastern Montana that suggested 500 μS/cm as a reference threshold. This criterion was used as an 

informal reference for GRKO by Schweiger et al. (2014) but has no regulatory significance; all 

measurements during the 2008-2010 study period met this suggested threshold. Schweiger et al. 

(2014) found a fairly large decreasing trend in conductivity (-3.5 μmhos/yr) at the nearby USGS 

gauging station over 15 years. This likely suggests an improving trend in water chemistry, as specific 

conductance is a useful general indicator of overall water quality (Billy Schweiger, ROMN 

Ecologist, written communication, 26 November 2014). 
181 

Atkins et al. (2012) recorded a median specific conductance of 267.5 μS/cm with a range of 211.8 to 

370.0 μS/cm (Table 50). None of the measurements exceeded the informal reference condition of 

500 μS/cm, and all fell within a similar range as Mast (2007) and Schweiger et al. (2014). 

Table 50. Specific conductance (μS/cm) in the Clark Fork at Deer Lodge, 2011 (Atkins et al. 2012).

April June September December

Specific conductance 290.0 211.8 370.0 245.0

pH 

Mast (2007) reported the median value for pH of surface water from 1980-2004 as 8.27. The 

minimum recorded pH value was 6.70 and the maximum recorded pH value was 8.91 (Mast 2007). 

Flow and seasonally adjusted trend models suggested an upward trend in pH from 1989 to 2004. 

Groundwater pH had a median value of 7.31 with a minimum of 6.45 and a maximum of 7.68 over a 

20-year period from 1980-2000 (Mast 2007). 

Schweiger et al. (2014) documented minimum, median, and maximum pH values of surface water in 

GRKO between 2008 and 2010. The median pH was 8.5; the minimum pH was 8.1, and the 

maximum pH was 8.6. According to Schweiger et al. (2014), there is no evidence that these pH 

values were outside the “natural” range of variation for the Clark Fork. pH is likely naturally 

somewhat basic (i.e., above 7.0) because of the geological source materials (e.g., rocks and minerals) 

in the watershed. Schweiger et al. (2014) also states that a more basic pH may be beneficial for 

GRKO as heavy metals are more soluble and bioavailable, and therefore more toxic, in acidic waters. 

Atkins et al. (2012) recorded pH values between 7.74 and 8.17, with a median of 8.15 (Table 51). All 

values fell within a similar range as Mast (2007) and Schweiger et al. (2014). 

Table 51. pH values for the Clark Fork at Deer Lodge, 2011 (Atkins et al. 2012).

April June September December

pH 7.74 8.13 8.17 8.01

Total Suspended Sediment (TSS)

While Mast (2007) did not analyze data regarding TSS, the report mentioned that TSS often exceeds 

50 mg/L during the spring runoff at GRKO. This elevated amount of suspended sediment is partially 

caused by erosion of the mine tailings that have been deposited throughout the Clark Fork floodplain 

(Mast 2007). 

No TSS values were reported for groundwater in either Mast (2007) or Schweiger et al. (2014). 

Schweiger et al. (2014) documented minimum, median, and maximum for TSS in surface water in 

GRKO between 2008 and 2010. The median TSS was recorded as 13.1 mg/L; the minimum TSS was 

6.4 mg/L, and the maximum TSS reading was 42.4 mg/L. There is no applicable state of Montana 

standard regarding TSS in the Clark Fork. 
182 

Dissolved Oxygen

The State of Montana established the minimum instantaneous DO concentration standard for surface 

waters at 8 mg/L for early life stages of fish, and 4 mg/L for other life stages in class C-1 Rivers like 

the Clark-Fork (MT DEQ 2002). The median value for DO in GRKO’s surface waters from 1980-

2004 was reported at 10.4 mg/L; the minimum recorded value was 6.2 mg/L, and the maximum was 

12.4 mg/L (Mast 2007). There were 94 sample results that measured dissolved oxygen over this time 

period. While the median value met the MT DEQ standard, the minimum fell below the standard of 8 

mg/L for early life stages of fish. 

Dissolved oxygen in groundwater had a median value of 5.6 mg/L; the minimum recorded was 4.6 

mg/L, and the maximum recorded was 6.4 mg/L (Mast 2007). The data analyzed by Mast (2007) 

were collected over a 20 year period from 1980-2000 but included just three sample results. 

Schweiger et al. (2014) documented minimum, median, and maximum DO values of surface water in 

GRKO between 2008 and 2010. The median DO was 9.3 mg/L, the minimum DO was 8.2 mg/L, and 

the maximum DO was 12.2 mg/L. 

Atkins et al. (2012) recorded DO measurements between 9.90 mg/L and 12.08 mg/L with a median 

of 10.16 mg/L (Table 52). 

Table 52. Dissolved oxygen measurements (mg/L) for the Clark Fork at Deer Lodge, 2011 (Atkins et al. 

2012).

April June September December

Dissolved Oxygen 10.42 9.90 8.98 12.08

Dissolved oxygen levels in Schweiger et al. (2014) and Atkins et al. (2012) were above the MT DEQ

minimum standard during all sampling events. There is no specific DO standard that applies to 

groundwater. 

Nutrients

Mast (2007) presents results for ammonia, nitrate, and orthophosphate from 1987 to 1995 (Table 53). 

Overall, nutrient levels were generally low, although concentrations of nitrogen were up to five times 

higher in the winter months compared to the summer months (Mast 2007). While median values met 

the state standards that were in effect at the time, some maximum values did exceed those standards. 

Table 53. Nutrient levels (mg/L) of surface waters in GRKO (Mast 2007).

Nutrients (mg/L)

Number of 

Analyses

Minimum 

Value

Median 

Value

Maximum 

Value State Standard1 

Ammonia, dissolved 90 0 mg/L 0.01 mg/L 0.23 mg/L ≤ 2.14 mg/L

Nitrate, total 185 0.02 mg/L 0.18 mg/L 0.94 mg/L Total N ≤ 0.3 mg/L (21 

June – 21 Sept.)

Orthophosphate 89 0.001 mg/L 0.006 mg/L 0.024 mg/L Total P ≤ 0.03 mg/L

(21 June – 21 Sept.)

1 Ammonia state standard from MT DEQ (2012), for a pH of 8.5 and assuming fish are present; Total N and P 

standards from Suplee and Watson (2013).
183 

Mast (2007) also used three components to analyze the nutrient levels of groundwater in GRKO. 

Orthophosphate, phosphorus, and nitrate measurements were analyzed from groundwater from 1980 

to 2000 and are presented in Table 54 below. 

Table 54. Nutrient levels (mg/L) in groundwater at GRKO (Mast 2007).

Nutrients (mg/L)

Number of 

Analyses

Minimum 

Value

Median 

Value

Maximum 

Value

Nitrate, dissolved 19 <0.01 0.5 2.2

Orthophosphate, total 4 <0.1 <0.1 0.2

Phosphorus, total 18 <0.01 0.05 0.16

Schweiger et al. (2014) present data for several nutrients including total nitrogen, total phosphorus, 

and nitrites plus nitrates in the Clark Fork River at GRKO between 2008 and 2010. In general, 

nutrients increased as flow rates increased, but rarely exceeded Montana water quality standards. 

Although nutrient levels did marginally exceed standards in some sample events, there were not 

enough data to complete the full MT DEQ nutrient assessment protocol (Suplee and Sada de Suplee 

2011). Nutrient levels have historically been higher in this area (Dodds et al. 1997, Suplee et al. 

2012); the recent lower nutrient levels may be an indicator of improved water quality due to 

remediation efforts. Table 55 displays the nutrient level data from the Clark Fork River in GRKO 

between 2008 and 2010. 

Table 55. Nutrient levels (mg/L) in surface waters at GRKO, 2008-2010 (as reported in Schweiger et al. 

2014). Except as indicated, assessment points are state of MT chronic aquatic-life criteria with humanhealth values in parentheses.

Nutrients (mg/L)

Number of 

Analyses

Minimum 

Value

Median 

Value

Maximum 

Value Standard

Nitrite + Nitrate, dissolved 

(mg/L as N) 7 0.004 0.02 0.11 0.1(10) 1

Nitrogen, total (mg/L as N) 8 0.16 0.26 0.31 0.32

Phosphorous, total (mg/L 

as P) 8 0.007 0.02 0.03 0.032 

1 The nitrite + nitrate standard is informal and is for a base flow in the Middle Rockies Ecoregion (Suplee et al. 

2008); the human health standard in parenthesis is from MT DEQ (2012). 

2 Also for base flow in the Middle Rockies ecoregion (Suplee and Watson 2013).

Atkins et al. (2012) recorded nitrites plus nitrates, total nitrogen, and total phosphorus at the Deer 

Lodge station in 2011. However, there also were not enough data to complete the full MT DEQ 

nutrient assessment protocol. It is important to note that MT DEQ standards for these nutrients only 

apply from 21 June to 21 September. While September nutrient levels met state standards, total 

nitrogen and phosphorus measurements exceeded these standards in June (Table 56). Atkins et al. 

(2012) suggests this is likely due to peak spring runoff conditions. Total suspended sediment is high 

during runoff conditions and total phosphorus levels are often correlated with TSS, as phosphorus 

readily adheres to sediment particles in surface water. Nitrogen can also increase during this time due 

to increased agricultural nonpoint source runoff (Atkins et al. 2012). 
184 

Table 56. Nutrient levels (mg/L) in the Clark Fork at Deer Lodge, 2011 (Atkins et al. 2012).

Nutrients (mg/L) April June September December Median

Nitrite + Nitrate, dissolved 0.15 0.09 0.08 0.27 0.12

Total Nitrogen 0.65 0.57 0.25 0.39 0.48

Total Phosphorus 0.027 0.176 0.017 0.013 0.022

Metals

Due to the impact of historic mining practices, the presence of metals is a primary concern in the 

surface waters of the Clark Fork within GRKO. Arsenic, cadmium, copper, iron, lead, manganese, 

and zinc are all associated with mine tailings and have been detected in both surface and ground 

water samples, as well as soils (Lambing 1991). Metals enter the river by direct erosion of mine 

tailings that have been deposited in the floodplain over years of flooding, as well as leaching from 

soil directly into water (Smith et al. 1998). Table 57 presents summary statistics of trace element 

measurements that were collected from 1980-2004 and summarized in Mast (2007). 

Table 57. Dissolved and total trace elements (μg/L) in surface water at GRKO (Mast 2007). Except as 

indicated, standards are state of MT chronic aquatic-life criteria with human-health values in parentheses.

Constituent (μg/L)

No. 

Analyses 

(no. 

censored)

Minimum 

Value

Median 

Value

Maximum 

Value

Aquatic-Life 

(humanhealth) 

standard

Arsenic, dissolved 146 6 13 39 150* (10)

Cadmium, dissolved 144 (108) 0.022 0.1 5 0.46* (5)

Copper, dissolved 251 3 8 120 3.6* (1,300)

Iron, dissolved 247 (25) 32 13 190 (300)3

Lead, dissolved 148 (108) 0.042 0.6 50 0.9* (15)

Manganese, dissolved 243 1 50 400 (50)3

Zinc, dissolved 247 0.9 11 230 36.5* (2,000)

Aluminum, total 122 18 100 1,129 874

Arsenic, total 321 2 4 240 150 (18*)

Cadmium, total 287 (89) 0.062 1 8 0.52*

Copper, total 442 2 25 1,500 3.8*

Iron, total 434 27 310 29,000 1,000

Lead, total 291 (8) 0.52 6 200 0.55*

Manganese, total 417 8 120 4,600 50*

Zinc, total 444 (2) 52 40 1,700 37*

* Standard taken from Schweiger et al. (2014), calculated using a median hardness of 186 mg/L as CaCO3. 

1 Table value standard calculated for hardness of 250 mg/L.

2 Minimum reported value less than minimum censored value.

3 Secondary standard based on aesthetic properties such as taste, odor, and staining.

4 Dissolved concentration.

Mast (2007) also compiled summary data on trace metals in groundwater. These data were collected 

from 1980–2000 and are presented in Table 58 below. The data that Mast (2007) summarized for 

groundwater included 10 trace elements; however, only six of the elements were frequently found in 

groundwater samples. Aluminum (48% of samples), arsenic (32% of samples), copper (32% of 

samples), iron (97% of samples), and zinc (100% of samples) were the most frequently detected trace 
185 

elements. The most probable source for the arsenic, copper, and zinc is the mine tailings that have 

been deposited in the floodplain (Mast 2007). 

Table 58. Trace elements (μg/L) in groundwater at GRKO (reproduced from Mast 2007).

Constituent (μg/L)

No. 

Sites

No. 

Analyses 

(no. 

censored)

Minimum 

Value

Median 

Value

Maximum 

Value

HumanHealth 

Standard

Aluminum, dissolved 18 75 (39) <10 <10 280 --

Arsenic, dissolved 18 75 (51) 31 <5 39 10

Cadmium, dissolved 18 75 (72) <1 <1 5 5

Chromium, dissolved 18 75 (71) <2 <5 5 100

Copper, dissolved 18 75 (51) <2 <3 7 1,300

Iron, dissolved 17 72 (2) <2.0 36 707 3002

Lead, dissolved 17 73 (70) <10 <10 <40 15

Manganese, dissolved 17 72 (2) <1 13 605 502

Zinc, dissolved 18 75 1 3 120 2,000

1 Minimum reported value less than minimum censored value.

2 Secondary standard based on aesthetic properties such as taste, odor, and staining

While the wells tested are not used for human consumption, Mast (2007) used the human health 

standards applicable in Montana for a frame of reference. The only element to exceed the human 

health standard was arsenic, with its current standard set at 10 μg/L (changed from 50 μg/L in 2001). 

Arsenic levels that exceeded the standard were found in a total of 12 samples in four wells. The 

samples that exceeded the standard ranged from 11 μg/L to 39 μg/L (Mast 2007). 

Mercury is another trace element of concern for GRKO that is associated with mining. Schweiger et 

al. (2014) reported that the median value for total mercury in the sediment surrounding the Clark 

Fork River on GRKO was 0.337 mg/kg. The minimum reported value for mercury in sediment was 

0.146 mg/kg, and the maximum was 0.594 mg/kg (Schweiger et al. 2014). It is important to note that 

total mercury values represent inorganic mercury compounds and do not measure organic forms like 

methylmercury, which are highly toxic and easily absorbed by aquatic organisms (Schweiger et al. 

2014). 

Neither Montana nor federal thresholds or standards exist for levels of total mercury in sediment, but 

MacDonald et al. (2000) suggested thresholds that could be used as guidelines in freshwater 

ecosystems. MacDonald et al. (2000) reports a range of values for 28 different contaminants, each 

bounded by a “threshold effect concentration” (TEC) on the low end and a “probable effect 

concentration” (PEC) on the high end. The TEC is intended to represent a lower limit below which 

no toxicity to sediment dwelling organisms should occur, and the PEC is intended to provide an 

upper limit at which toxicity to sediment dwelling organisms is highly probable to occur (MacDonald 

et al. 2000). 

A TEC of 0.18 mg/kg (dry weight) and a PEC of 1.06 mg/kg (dry weight) were suggested by 

MacDonald et al. (2000) as the threshold for mercury in sediment. In subsequent tests, MacDonald et 

al. (2000) determined that the TEC was only 34% accurate (i.e., of the 35 samples predicted to be 
186 

non-toxic, only 12 actually were non-toxic). This suggests that the TEC for mercury is likely lower 

than 0.18 mg/km. Only four samples above the PEC were available for testing, which is insufficient 

for drawing conclusions, but 100% of those samples were toxic, as predicted. The median mercury 

level from Schweiger et al. (2014) of 0.337 mg/kg is above MacDonald et al.’s (2000) initially 

proposed TEC, meaning mercury could be negatively affecting sediment dwelling organisms within 

GRKO. 

Schweiger et al. (2014) reported both dissolved and total metal concentrations for surface water 

samples from 2008-2010 (Table 59). The State of Montana requires total metals as a reporting 

criteria, but because it is primarily the dissolved form of the metals that causes aquatic toxicity, the 

EPA (1996) recommended reporting dissolved concentrations as well. In comparing 2008-2010 data 

to historic data from the nearby USGS gauge using a flow and seasonally adjusted trend model 

(ESTREND; Schertz et al. 1991, Slack and Lorenz 2003), Schweiger et al. (2014) found that the 

2008-2010 data show decreases (i.e., improvements) in the levels of several metals, particularly 

cadmium, copper, lead, and zinc. 
187 

Table 59. Summary of water physiochemistry for the Clark Fork River in Grant-Kohrs Ranch National 

Historic Site, 2008-2010. Except as indicated, assessment points are state of MT chronic aquatic-life 

criteria with human-health values in parentheses. For additional clarifications on table content, see notes 

below (Modified from Schweiger et al. 2014). 

1 Values for dissolved trace elements are derived from the State of Montana water quality numeric criteria using 

formulas from EPA (2009) and a median hardness of 186 mg/L as CaCO3

2 Human health value is a secondary standard based on aesthetic properties such as taste, odor, and staining 

and is more conservative than chronic standards. MT DEQ does not assess iron secondary standards that apply 

to taste and odor to water-dwelling organisms are expected, whereas PECs are the concentrations at which 

negative effects on sediment dwelling organisms are judged more likely to occur than not

3 Derived from criteria in Record of Decision (EPA 2004) using formulas from EPA (2009) and a median 

hardness of 186 mg/L as CaCO3; may differ from statewide standards

* Value or median contains predicted results from regression on order statistics (ROS) model

** >80% of results at Detection Limit(s), results tenuous

 ^ All results were at detection limits (i.e., very low), no analysis possible

Many metals have a strong diurnal and/or seasonal concentration pattern in the Clark Fork River. 

Figure 49 represents the copper concentration at GRKO over a 12-month period. The highest 

Constituent or property (μg/L) No. Analyses

Minimum 

Value

Median 

Value

Maximum 

Value

Criteria or 

Assessment 

Point

Metals in water, total recoverable

Aluminum, total 7 52.8** 210** 865 --

Arsenic, total 8 9.3 14.5** 22 150(18)3

Barium, total 4 43 49 52.7 (1000)

Beryllium, total^ 4 -- -- -- (4)

Cadmium, total 3 0.3** 0.3** 0.3** 0.52(5)3

Chromium, total^ 4 -- -- -- (100)

Copper, total 8 6 21.8 74 3.8(1300)3

Iron, total 8 50.9 283.5** 1190 1000(300)2

Lead, total 7 0.7** 2.6** 13 0.55(15)3

Manganese, total 8 35** 75.4** 120 502

Selenium, total^ 8 -- -- -- 5(50)

Zinc, total^ 3 -- -- -- 37(2000)3

Metals in water, dissolved

Aluminum, dissolved^ 8 -- -- -- 87

Arsenic, dissolved 7 5.6* 10.3* 19.9 150(10)1

Barium, dissolved 3 30.9 46 1 46 3 --

Beryllium, dissolved^ 4 -- -- -- --

Cadmium, dissolved^ 3 -- -- -- 0.46(4.41)1

Chromium, dissolved^ 3 -- -- -- (86)1

Copper, dissolved 7 5 9* 12 3.6(1248)1

Iron, dissolved^ 7 -- -- -- --

Lead, dissolved 7 77.8 186 216 0.9(10.5)1

Manganese, dissolved 7 0.008* 0.30* 25.2 --

Selenium, dissolved^ 7 -- -- -- 5(50)1

Zinc, dissolved^ 4 -- -- -- 36.5(1972)1
188 

concentration of metals generally coincided with peak flow. This may be due to the greater 

amounts of suspended sediment in the river during high flow conditions such as spring snowmelt 

(Lambing 1991, Mast 2007). This is also demonstrated by the seasonal variation in arsenic 

concentration illustrated in Figure 50. 

Figure 49. Seasonal variation in copper concentration, 1982-2004 (reproduced from Mast 2007).

Figure 50. Seasonal variation in arsenic concentration, 1982-2004 (reproduced from Mast 2007).

Threats and Stressor Factors 

GRKO staff identified several potential threats and stressors to the water quality in the park. While 

most of the threats are anthropogenic (mining contamination, nutrient enrichment, point and nonpoint 

source discharge, and dewatering), one is naturally occurring (drought). 
189 

The impact of historical mining to the area is a significant threat to water quality at GRKO. Mining 

contamination from tailings includes high concentrations of metals, dissolved solids, and salts that 

have been distributed throughout the floodplain. All of these contaminants can impact and reduce 

populations of aquatic organisms, especially ecological indicator species (e.g., macroinvertebrates, 

fish). Mine tailings can adversely affect water quality over a long period of time. According to the 

Safe Drinking Water Foundation (SDWF 2009), mine tailings can cause pollution that requires 

remediation anywhere from decades to centuries. Sudden influxes of residual metals due to heavy 

rain events are also known to cause fish kills (Lipton et al. 1995). 

Nutrient enrichment (e.g., from fertilizer) is another threat to water quality in GRKO. Fertilizers can 

enter the water after a rain event causing an influx of nutrients (e.g., phosphorous, nitrogen) into the 

Clark Fork. An excess of nutrients can result in eutrophication, which affects several water quality 

parameters such as dissolved oxygen, water temperature, and pH (Suplee et al. 2008). To minimize 

nutrient enrichment from fertilizer, park management has the soil analyzed to determine the exact 

amount of nutrients the plants will utilize for that growing season. Best Management Practices 

utilized to prevent runoff include maintaining buffer strips along waterways and fertilizing when the 

plants are actively growing and will uptake the fertilizer (Smith, written communication, 27 January 

2015). 

Concerns for point source pollution include the wastewater treatment site for the municipality of 

Butte (population approximately 34,000) and other smaller cities (e.g., Anaconda) as well as 

numerous individual septic systems upstream from GRKO. Non-point source pollution concerns 

include cattle/animal wastes entering the stream as well as runoff due to agricultural irrigation (Mast

2007). 

Dewatering is another potential stressor for water quality at GRKO. During the summer months, 

irrigation ditches divert water from tributaries as well as the main stem of the Clark Fork for crops. 

Poff et al. (1997) states that when river waters are diverted for human use (e.g., irrigation) the 

resulting changes in hydrology can affect the survival, reproduction, and migration of biota. For 

example, dewatering may contribute to the fact that flow in the Clark Fork in August and September 

is often less than adequate for maintaining a salmonid fishery (USFWS 1998). The effects of 

dewatering also cause groundwater to become a major source of flow for the Clark Fork during the 

summer months. Specific conductance in the river increases during this time, as groundwater 

introduces more dissolved solids into the stream. This effect is due to the groundwater’s longer 

interaction time with rock/soil (Pilgrim et al. 1979). 

Drought, which is a natural occurrence that can be exacerbated by human activity, was identified by 

park staff as a concern. As illustrated by Figure 51, the Palmer Hydrologic Index for the state of 

Montana shows that Montana experienced severe and extreme drought between 10% and 20% of the 

time over the last 100 years (MDES 2013). Drought can result in low water levels, which increases 

metal concentration, influences pH and temperature, and can cause larger amounts of sediment to be 

released into the river during rain events. 
190 

Figure 51. Palmer Hydrologic Drought Index 1997-2007 (reproduced from MDES 2013). 

Data Needs/Gaps

Because of the historic impacts of mining and Superfund status of the Clark Fork River area, there 

are many documents available addressing surface water quality issues around GRKO. However, 

much less data are available for groundwater quality than for surface water quality, particularly 

within the last 6-8 years. Data are also limited for TSS and no data could be found for coliform 

bacteria in GRKO’s surface waters. 

In the coming years, Superfund remediation activities will be occurring along the Clark Fork riparian 

zone in GRKO. This will involve the removal of contaminated sediments and soil from the 100-year 

channel migration zone, followed by backfilling with clean soil and revegetation with native species 

(Johnson, written communication, 10 February 2015). This will provide an opportunity to study how 

such efforts impact water quality parameters in both the short and long-term. 

Overall Condition 

Water Temperature 

The project team defined the Significance Level for water temperature as a 3. Schweiger et al. (2014) 

examined existing data as well as collecting new data on water temperature. The authors concluded 

that the stream temperature was within an acceptable range, but the data suggested temperatures may 

be on the rise. The authors acknowledge that the length of the sampled data (2001-2010) was short 

and that more data are needed to increase the confidence level in their conclusion. Therefore, water 

temperature is presently of low concern (Condition Level = 1) but warrants careful monitoring and 

analysis in the future. 
191 

Specific Conductance 

The project team defined the Significance Level for specific conductance as a 3. The median 

measurement of specific conductance from 1980-2004 (524 μS/cm) was slightly above the suggested 

informal threshold of 500 μS/cm (EPA 2007, Schweiger et al. 2014). Over the last 15 years, a trend 

of decreasing conductivity has been noted at the nearby USGS gauging station (Schweiger et al. 

2014). From 2008-2010, the median specific conductance within GRKO, as measured by Schweiger 

et al. (2014), was 428.3 μS/cm. As a result, specific conductance is of low concern (Condition Level

= 1). 

pH 

The project team defined the Significance Level for pH as a 3. The pH level of a stream has a 

profound influence on the biota that inhabit the water. At GRKO, pH appears to be within a natural 

range of variation. Therefore, pH is of low concern (Condition Level = 1). 

Total Suspended Sediment

The project team defined the Significance Level for total suspended sediment (TSS) as a 3. 

Montana’s administrative rules prohibit any increase in sediment that would be harmful, detrimental, 

or injurious to public health and welfare, recreation, safety, livestock, or wildlife (MT DEQ 2006). 

Since no numeric standards exist within the state of Montana and limited data are available for 

GRKO, a Condition Level for TSS was not assigned at this time.

Dissolved Oxygen

The project team defined the Significance Level for DO as a 3. The State of Montana established the

minimum instantaneous DO concentration for surface waters at 8 mg/L for early life stages of fish, 

and 4 mg/L for other life stages in class C-1 rivers like the Clark Fork (MT DEQ 2012). Dissolved 

oxygen in Schweiger et al. (2014) and Atkins et al. (2012) met this reference condition during all 

sampling events. At present, there is no evidence indicating a cause for concern regarding DO levels

(Condition Level = 0). 

Coliform Bacteria

The project team defined the Significance Level for coliform bacteria as a 1. Measures with a 

Significance Level of 1 are not discussed in the current condition section of the text, rather they are 

briefly summarized in the Overall Condition section. Data regarding coliform bacteria in the park are 

limited. No measurements for coliform bacteria in GRKO’s surface waters could be found. Moore 

and Woessner (2001) detected coliform bacteria in several groundwater monitoring wells. While 

most measurements were <1 CFU/100 ml, two records exceeded 500 CFU/100ml. However, given 

the lack of data, a Condition Level for coliform bacteria cannot be assigned at this time.

Nutrients

The project team defined the Significance Level for nutrients as a 3. While the majority of median 

nutrient levels recorded by Schweiger et al. (2014) fell within MT DEQ standards, some maximum 

values exceeded these standards, and Atkins et al. (2012) documented exceedances for nitrogen and 

phosphorus at the Deer Lodge station in June 2011. While high nutrient levels have historically been 
192 

an issue on the Clark Fork, recent work suggests that they are not a major concern at this time 

(Schweiger et al. 2014). Because of this, nutrients are currently of low concern (Condition Level = 1). 

Metals 

The project team defined the Significance Level for metals as a 3. Because of the historic mining 

activity in the area, as well as the continued presence of metals and trace elements associated with 

mining, metals continue to be a concern for GRKO. Metals detected in water samples at GRKO 

include arsenic, cadmium, copper, iron, lead, manganese, and zinc. Because of these continued 

concerns, metals are of high concern (Condition Level = 3). 

Weighted Condition Score 

The Weighted Condition Score for water quality in GRKO is 0.39, meaning the current condition is 

of moderate concern. The trend in water quality for many parameters appears to be improving 

slightly over time.

Water Quality

Measures Significance 

Level

Condition 

Level WCS = 0.39 

Water Temperature 3 1 

Specific Conductance 3 1 

pH 3 1 

Total Suspended Sediment 3 n/a

Dissolved Oxygen 3 0 

Coliform Bacteria 1 n/a

Nutrients 3 1 

Metals 3 3 

4.9.6 Sources of Expertise

Billy Schweiger, ROMN Ecologist 

Jason Smith, GRKO Natural Resource Specialist 

Jeff Johnson, GRKO CERCLA Project Manager
193 

4.9.7 Literature Cited

Allan, J. D. 1995. Stream ecology: structure and function of running waters. Chapman and Hall, 

London, England. 

Atkins, Rhithron Associates, Inc., and Montana Fish, Wildlife and Parks. 2012. Monitoring report for 

2011: Clark Fork River Operable Unit. Montana Department of Environmental Quality and 

Montana Department of Justice, Helena, Montana.

Besser, J. M., and K. J. Leib. 2007. Toxicity of metals in water and sediment to aquatic biota. Pages 

839-849 in Integrated investigations of environmental effects of historical mining in the Animas 

River Watershed, San Juan County, Colorado. Church, S. E., P. von Guerard, and S. E. Finger 

(eds.). U.S. Geological Survey, Reston, Virginia. 

Britten, M., E. W. Schweiger, B. Frakes, D. Manier, and D. Pillmore. 2007. Rocky Mountain 

Network Vital Signs monitoring plan. Natural Resource Report NPS/ROMN/ NRR-2007/010. 

National Park Service, Fort Collins, Colorado. 

Dodds, W. K., V. H. Smith, and B. Zander. 1997. Developing nutrient targets to control benthic 

chlorophyll levels in streams: A case study of the Clark Fork River. Water Research 31(7):1738-

1750. 

Environmental Protection Agency (EPA). 1996. Sampling ambient water for trace metals at EPA 

water quality criteria levels. U.S Environmental Protection Agency, Office of Water, 

Washington, D.C. 

Environmental Protection Agency (EPA). 1997. Fecal bacteria: What are fecal bacteria and why are 

they important? In Volunteer stream monitoring: A methods manual. U.S. Environmental 

Protection Agency, Washington, D.C. 

Environmental Protection Agency (EPA). 2004. Clark Fork River Operable Unit of the Milltown 

Reservoir/Clark Fork River Superfund Site, Record of Decision Part 1: Declaration. U.S. EPA 

BOI032130003.DOC/KM. U.S. Environmental Protection Agency, Washington, D.C.

Environmental Protection Agency (EPA). 2007. National rivers and streams assessment: Field 

operations manual. EPA-841-B-07-009. U.S. Environmental Protection Agency, Washington, 

D.C. 

Environmental Protection Agency (EPA). 2009. National recommended water quality criteria. U.S. 

Environmental Protection Agency, Office of Science and Technology, Washington, D.C.

Environmental Protection Agency (EPA). 2012. Phosphorus. 

http://www.epa.gov/agriculture/ag101/impactphosphorus.html (accessed 12 June 2014). 

Environmental Protection Agency (EPA). 2013. Secondary drinking water regulations: Guidance for 

nuisance chemicals. http://water.epa.gov/drink/contaminants/secondarystandards.cfm (accessed 

12 June 2014). 
194 

Environmental Protection Agency (EPA). 2014. Mercury: basic information. 

http://www.epa.gov/mercury/about.htm (accessed 12 June 2014). 

Horstman, M. C. 1984. Historical events associated with the Upper Clark Fork drainage. Montana 

Department of Fish, Wildlife, and Parks, Helena, Montana. 

Lambing, J. H. 1991. Water quality and transport characteristics of suspended sediment and trace 

elements in streamflow of the Upper Clark Fork Basin from Galena to Missoula, Montana, 1985-

90. U.S. Geological Survey, Helena, Montana. 

Lipton, J., H. Bergman, D. Chapman, T. Hillman, M. Kerr, J. Moore, and D. Woodward. 1995. 

Aquatic resources injury assessment report, Upper Clark Fork River Basin. State of Montana, 

Natural Resource Damage Litigation Program, Helena, Montana. 

MacDonald, D. D., C. G. Ingersoll, and T. A. Berger. 2000. Development and evaluation of 

consensus-based sediment quality guidelines for freshwater ecosystems. Archives of 

Environmental Contamination and Toxicology 39:20-31. 

Mast, M. A. 2007. Assessment of historical water-quality data for National Park units in the Rocky 

Mountain Network, Colorado and Montana through 2004. U.S. Geological Survey Scientific 

Investigations Report 2007-5147. U.S. Geological Survey, Reston, Virginia

Mohr, J. 2012. A guide to Montana water quality regulation. Environmental Quality Council, 

Legislative Environmental Policy Office, Helena, Montana.

Montana Department of Environmental Quality (MT DEQ). 2002. Water-use classifications: 

Administrative Rules of Montana 17.30.607 to 17.30.611. Montana Department of 

Environmental Quality, Helena, Montana.

Montana Department of Environmental Quality (MT DEQ). 2006. Surface water quality standards 

and procedures. Chapter 30, subchapter 6 in Administrative rules of Montana: Environmental 

quality. Montana Department of Environmental Quality, Helena, Montana. 

Montana Department of Environmental Quality (MT DEQ). 2012. Montana numeric water quality 

standards. Circular DEQ-7. Montana Department of Environmental Quality, Water Quality 

Planning Bureau, Helena, Montana. 

Montana Disaster and Emergency Services (MDES). 2013 State of Montana multi-hazard mitigation 

plan and statewide hazard assessment: 2013 update. http://letsmitigatemontana.com/draft-pdmplan/ (accessed 20 August 2014). 

Moore, J. N., and W. W. Woessner. 2001. Geologic, soil water, and groundwater report - 2000: 

Grant-Kohrs Ranch National Historic Site. National Park Service, Deer Lodge, Montana. 

Mueller, D. K., and D. R. Helsel. 1996. Nutrients in the nation’s waters—too much of a good thing? 

U.S. Geological Survey, Reston, Virginia. 
195 

Muir, P. 2012. Oregon State University Online: Eutrophication. 

http://people.oregonstate.edu/~muirp/eutrophi.htm (accessed 12 June 2014). 

Pilgrim, D. H., D. D. Huff, and T. D. Steele. 1979. Use of specific conductance and contact time 

relations foe separating flow components in storm runoff. Water Resources Research 15(2):329-

339. 

Poff, N. L., J. D. Allan, M. B. Bain, J. R. Karr, K. L. Prestegaard, B. D. Richter, R. E. Sparks, and J. 

C. Stromberg. 1997. The natural flow regime. Bioscience 47(11):769-784. 

Ramsey, P. W., M. C. Rillig, K. P. Feris, J. N. Moore, and J. E. Gannon. 2005. Mine waste 

contamination limits soil respiration rates: A case study using quantile regression. Soil Biology 

and Biochemistry 37:1177-1183. 

Robertson, M. J., D. A. Scruton, R. S. Gregory, and K. D. Clarke 2006. Effect of suspended sediment 

on freshwater fish and fish habitat. Canadian Technical Report of Fisheries and Aquatic Sciences 

2644. Fisheries and Oceans Canada, St. John’s, Newfoundland and Labrador. 

Safe Drinking Water Foundation (SDWF). 2009. Mining and water pollution. 

http://www.safewater.org/PDFS/resourcesknowthefacts/Mining+and+Water+Pollution.pdf

(accessed 4 August 2014). 

Schertz, T. L., R. B. Alexander, and D. J. Ohe. 1991. The computer program EStimate TREND 

(ESTREND): A system for the detection of trends in water-quality data. U.S. Geological Survey 

Water-Resources Investigations Report, Reston, Virginia. 

Schweiger, E. W., L. O’Gan, D. Shorrock, and M. Britten. 2014. Stream ecological integrity at 

Grant-Kohrs Ranch National Historic Site: Rocky Mountain Inventory & Monitoring Network 

2008-2010 stream monitoring report. Natural Resource Technical Report NPS/ ROMN/NRTR—

2014/881. National Park Service, Fort Collins, Colorado. 

Slack, J. R., and D. L. Lorenz. 2003. USGS library for S-PLUS for Windows, Release 2: U.S. 

Geological Survey Open-File Report 2003–357. http://pubs.er.usgs.gov/usgspubs/ofr/ofr03357 

(accessed 29 December 20014). 

Smith, J. D., J. H. Lambing, D. A. Nimick, C. Parrett, M. Ramey, and W. Schafer. 1998. 

Geomorphology, flood-plain tailings, and metal transport in the Upper Clark Fork Valley, 

Montana. 

Suplee, M. W., V. Watson, A. Varghese, and J. Cleland. 2008. Scientific and technical basis of the 

numeric nutrient criteria for Montana’s wadeable streams and rivers, and addendums. Montana 

Department of Environmental Quality, Helena, Montana. 

Suplee, M. W., and R. Sada de Suplee. 2011. Assessment methodology for determining wadeable 

stream impairment due to excess nitrogen and phosphorus levels. Montana Department of 

Environmental Quality, Helena, Montana. 
196 

Suplee, M. W., V. Watson, W. K. Dodds, and C. Shirley. 2012. Response of algal biomass to largescale nutrient controls in the Clark Fork River, Montana, United States. 

Suplee, M. W., and V. Watson. 2013. Scientific and technical basis of the numeric nutrient criteria 

for Montana’s wadeable streams and rivers - Update 1. Montana Department of Environmental 

Quality, Helena, Montana.

Thornberry-Ehrlich, T. 2007. Grant- Kohrs Ranch National Historic Site: Geologic resource 

evaluation report, Natural Resource Report NPS/NRPC/GRD/NRR—2007/004. National Park 

Service, Fort Collins, Colorado. 

U.S. Fish and Wildlife Service (USFWS). 1998. A framework to assist in making Endangered 

Species Act determinations of effect for individual or grouped actions at the bull trout 

subpopulation watershed scale. U.S. Fish and Wildlife Service, Washington, D.C. 

U.S. Geological Survey (USGS). 2014. Water properties and measurements 

http://water.usgs.gov/edu/characteristics.html (accessed 12 June 2014). 
197 

4.10 Soundscape

4.10.1 Description

The NPS’s mission is to 

preserve natural 

resources, including 

natural soundscapes, 

associated with the 

national park units. The 

definition of soundscape 

in a national park is the 

total ambient sound 

environment of the park, 

which is comprised of 

both natural ambient 

sound and human-made 

sounds (NPS 2000). 

Intrusive sounds are of 

concern to park visitors, 

as they detract from their 

natural and cultural resource experiences (NPS 2000). These sounds can also disturb wildlife or 

livestock, possibly altering their behavior (NPS 2012a). In addition, traffic or other human-caused 

noises may interrupt interpretive programs being held within a park. According to a survey 

conducted by the NPS, many visitors come to national parks to enjoy, equally, the natural 

soundscape and natural scenery (NPS 1994). 

GRKO has a very unique cultural soundscape, as the soundscape of the park is that of a working 

ranch (NPS 2012b). The sounds of working ranch hands, whinnying horses, crowing roosters, and 

cattle activity are essential to GRKO’s soundscape. 

4.10.2 Measures

• Characteristics of sounds (sound type, sound level) 

4.10.3 Reference Conditions/Values

Sound monitoring at GRKO from 2009-2010 (NPS 2012b) established a baseline characterization of 

the soundscape at the ranch that could be used for comparison in the future. However, this report did 

not identify any reference or “target” levels for sound characteristics (e.g., type of sound, loudness, 

duration). Given the mission of the park, sounds will be judged differently depending on their 

cultural significance; certain sounds are expected on a historic ranch while others are not (e.g., 

airplanes, semi traffic, motorized construction). Reference conditions for soundscape should 

determine acceptable and unacceptable levels for these unexpected or “non-contributing” sounds. 

Regarding sound level (i.e., loudness), the EPA (1974) determined that sounds above 60 dBA 

interfere with outdoor conversation, and would likely interrupt interpretive programs at the park. For 

Photo 30. Sound monitoring equipment in the field at GRKO (NPS photo).
198 

the purpose of this assessment, 60 dBA will be used as a reference condition for sound level for noncontributing sounds. For types of sound, the reference will be to keep the percentage of new sounds 

(using NPS 2012b as a baseline) that are non-contributing to the cultural landscape and visitor 

experience below 10% (Christine Ford, GRKO Integrated Resource Program Manager, email 

communication, 20 August 2014). 

4.10.4 Data and Methods

NPS (2012b) conducted baseline 

sound monitoring for GRKO 

from March 2009 to March 2010. 

GRKO staff, Montana State 

University, and the NPS Natural 

Sounds and Night Skies Division 

(NSNSD) worked together to 

assess seasonal as well as diurnal 

soundscape characteristics at a 

site 200 m (656 ft) south and 

west of the ranch house (Figure 

52). Several acoustic instruments 

were used, including a Larson 

Davis 831 sound level meter, a 

calibrated digital audio recorder, 

a HOBO anemometer, and digital 

data logging system. Sound 

pressure levels were graphed for 

all 12 months during the survey. 

Montana State University also 

created a website where samples from the audio recordings can be heard: 

http://www.coe.montana.edu/ee/rmaher/audio_monitor/grko.htm. 

4.10.5 Current Condition and Trend

Characteristics of Sounds 

Types of Sounds 

NPS (2012b) documented both natural and anthropogenic sounds within the ranch. Natural sounds 

can be divided into biologic and geologic categories. Biologic sounds include horses, cattle, birds, 

coyotes (Canis latrans), frogs, and insects. The ranch has several working horses (draft, quarter) that 

are used daily to perform chores throughout the ranch. Some geologic sounds included flowing 

water, rustling grass, wind, and storms. Common anthropogenic sounds at GRKO included highway 

traffic from I-90, which occurred almost all the time, railroad traffic, and ranching activity (trucks 

and tractors, cowboys performing their daily activities, etc.). Most of the railroad traffic during 

monitoring was for remediation purposes, and was transporting contaminated soil from a nearby 

portion of the Clark Fork Superfund site (NPS 2012b). Currently, typical railroad traffic consists of 

Figure 52. The location of the sampling site in relation to the 

Ranch House and GRKO Visitor Center (reproduced from NPS 

2012b).
199 

two trains through the ranch per day (Johnson, written communication, 17 October 2014). Other 

anthropogenic sounds that could be heard on the ranch were airplanes, sirens from the city, car horns 

honking, and the back-up warning beeps from vehicles (park and public). Some of these 

anthropogenic sounds are expected and contribute to the cultural experience, while others are noncontributing. Non-contributing sounds are those that would not have occurred during the ranching era 

(i.e., late 19th and early 20th centuries). 

NPS (2012b) also documented diurnal and seasonal tendencies in sounds. Higher activity and sound 

levels from dawn until dusk were caused by animals on the farm, wildlife, and an increase in

anthropogenic sounds, such as the cowboys, cars, trains, and planes. Low activity was seen after 

dusk, with some geologic sounds still occurring such as wind, water, and storms, as well as the 

occasional car, plane, and train. 

Sound Level (Loudness) 

NPS (2012b) documented monthly sound levels including minimum, average, and maximum sound 

pressure levels (1 sec Leq[dBA]) from March 2009 to March 2010 (Figure 2). Average sound levels 

varied throughout the seasons; two examples of sound level graphs from different seasons are shown 

below (Figure 53). During the winter, the average sound level tended to remain below 40 dBA, 

whereas in summer months the average sound level regularly surpassed 40 dBA. Maximum sound 

levels rarely exceeded 80 dBA during most of the year; however, during the summer months they 

occasionally approached 90 dBA. Sound levels, on average, were higher in late summer (July, 

August). The loudest sound (95 dBA) came from a natural occurrence (thunder clap) in the month of 

July (Figure 53).
200 

Figure 53. Sound pressure level graphs from the months of July and January at GRKO (from NPS 

2012b).

Threats and Stressor Factors 

GRKO park staff identified several threats to the ranch’s cultural soundscape. The threats include 

increased airport traffic, increased train traffic, increased interstate traffic (semis), Superfund 

remediation activities, ranch construction activities, and increased development outside of the park. 

The Deer Lodge-City-County airport is a major threat to GRKO soundscape. The airport is less than 

1.6 km (1 mi) away from the southern border of the ranch (Figure 54). According to AirNav (2014), 

there was an average of 78 aircraft operations a week in 2013. Local general aviation was the most 

common operation, occurring 43% of the time; approximately 37%, 12%, and 7% of operations were 
201 

transient general aviation, air taxi, and military operations, respectively. In 2012, there was a 

proposal to establish the Deer Lodge-City-County airport as Class E (controlled) airspace (DOT 

2012). The expansion of the airport may cause an increased number of annual aircraft operations that 

cause natural and cultural sounds to be drowned out or even decrease (NPS 2008, 2012b). In 

addition, individuals with private jets and helicopters have purchased land near GRKO that was once 

a large ranch (NPS 2012b). This may increase air travel over the ranch.

Increased traffic, 

both train and 

interstate, is 

another threat to 

the soundscape in 

GRKO. Train 

tracks run through 

the eastern portion 

of the park, while 

the interstate runs 

near the eastern 

border (Figure 54). 

Train traffic has 

increased 

considerably due to 

the transportation 

of contaminated 

soil from the 

Milltown Dam 

remediation site 

(NPS 2012b). In 

the next 2 years, Superfund remediation activities will be taking place along the Clark Fork within 

GRKO. Anthropogenic sounds will increase during this time, as the cleanup will involve heavy 

construction equipment and trucks. This increased activity is estimated to last approximately 18 

months (Johnson, written communication, 17 October 2014). 

Increased development near the park is another threat to soundscape. In the past 10-20 years, 

commercial and residential development has occurred just east of the ranch, particularly around the I90 exit ramp. This contributes to the increase in traffic and general anthropogenic sounds, as well as 

noise from machinery during construction. 

Data Needs/Gaps

There are no long-term soundscape data for GRKO. NPS (2012b) conducted a baseline monitoring 

report for the park from March 2009 to March 2010. The continuation of annual measurements of 

sound levels and sound recordings is essential in the management of GRKOs cultural soundscape. An 

Figure 54. Location of the airport, railroad, and interstate in relation to GRKO.
202 

additional focus on the frequency and duration of non-contributing sounds or the percent of time they 

are audible would also be useful.

It may be helpful for GRKO to create a soundscape management plan or integrate soundscape into 

other planning documents. This would clearly outline contributing and non-contributing sounds, and 

set acceptable levels for the loudness, frequency, and duration of non-contributing sounds. Separate 

targets could be set for day and nighttime hours and for different seasons. Several parks in the NPS 

have completed these plans or written soundscape sections in other management plans and could be 

used as models (Denali National Park and Preserve [NPS 2006], Guadalupe Mountains National Park 

[NPS 2009], Zion National Park [NPS 2010]). 

Overall Condition 

Characteristics of Sounds 

The project team defined the Significance Level for characteristics of sounds as a 3. Many of the 

sounds heard at GRKO contribute to the cultural experience expected on a ranch, such as livestock, 

ranch hands working, bird song, and wind rustling in the grass. Other sounds, including airplanes and 

interstate traffic, would not be expected in a ranch setting. Interstate traffic is audible at almost all 

hours at the ranch. NPS (2012b) data indicated the average sound level is often below 40 dBA in the 

winter months and frequently above 40 dBA in the summer months. Occasional levels exceeding 90 

dBA are common in the summer months. While maximum sound levels regularly exceeded the 60 

dBA reference condition, average sound levels only rarely passed this threshold; NPS (2012b) did 

not indicate whether these louder sounds were from contributing or non-contributing sources. Based 

on the data that is currently available, this measure is assigned a Condition Level of 1. 

Weighted Condition Score 

A Weighted Condition Score of 0.33 was assigned to GRKO soundscape, which is on the boundary 

between good condition and moderate concern. Given the serious concern over increases in unnatural 

anthropogenic sounds such as airplanes and increased traffic on the railroad and interstate, the overall 

condition of soundscape at GRKO is considered of moderate concern with a declining trend. 

Soundscape 

Measures Significance 

Level

Condition 

Level WCS = 0.33 

Characteristics of 

Sounds (Sound 

Level, Sound Type)

3 1 
203 

4.10.6 Sources of Expertise

Christine Ford, GRKO Integrated Resources Program Manager 
204 

4.10.7 Literature Cited

AirNav LLC (2014). FAA information effective 03 April 2014. Deer Lodge-City_County Airport. 

http://www.airnav.com/airport/38S (accessed 30 July 2014). 

Department of Transportation (DOT). 2012. Proposed rules. Federal Register 77(137):41939-41940. 

http://www.gpo.gov/fdsys/pkg/FR-2012-07-17/pdf/2012-17282.pdf (accessed 30 July 2014). 

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, Office of Noise Abatement and Control, Washington, D.C. 

National Park Service (NPS). 1994. Report on effects of aircraft overflights on the National Park 

System. National Park Service, Fort Collins, Colorado. 

National Park Service (NPS). 2000. Directors order #47: Soundscape preservation and noise 

management. http://www.nps.gov/policy/DOrders/DOrder47.html (accessed 7 April 2014). 

National Park Service (NPS). 2006. Denali National Park and Preserve: Final backcountry 

management plan. National Park Service, Denali Park, Alaska.

National Park Service (NPS). 2008. Grant-Kohrs Ranch National Historic Site: Foundation for 

planning and management. National Park Service, Deer Lodge, Montana.

National Park Service (NPS). 2009. Resource stewardship strategy: Guadalupe Mountains National 

Park. National Park Service, Guadalupe Mountains National Park, Texas. 

National Park Service (NPS). 2010. Soundscape management plan: Zion National Park. 

http://www.nps.gov/zion/parkmgmt/upload/ZNP-Soundscape-Plan_Sep_2010.pdf (accessed 7 

August 2014) 

National Park Service (NPS). 2012a. Effects of noise. http://www.nature.nps.gov/sound/effects.cfm 

(accessed 27 August 2014). 

National Park Service (NPS). 2012b. Baseline sound monitoring at Grant Kohrs Ranch NHS. Final 

Report. Montana State University, Bozeman, Montana.
205 

4.11 Viewscape

4.11.1 Description

For this assessment, viewscape refers to the visible natural and cultural features on the landscape in 

GRKO. 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 from 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. Analyzing layers that identify areas of undesirable impacts on the landscape 

within viewsheds 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 31. Westward view of the mountains from a trail on the southeast side of GRKO (Photo by Sarah 

Gardner, SMUMN GSS 2013).

Multiple studies indicate that people prefer natural compared to developed landscapes (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. At GRKO, 

cultural landscape viewing is a primary visitor activity. GRKO natural vistas include open fields with 
206 

foothills and mountains in the distance (John Milner Associates et al. 2004). Cultural views include 

complexes of historical structures and equipment, corrals, and ranching operations (John Milner 

Associates et al. 2004). 

4.11.2 Measures

• Change in land use cover type inside the park (internal viewscape) 

• Change in land use cover type outside the park (external viewscape) 

• Change at selected photo points 

4.11.3 Reference Conditions/Values

The reference condition for viewscape is the condition of views and vistas contributing to cultural 

landscape significance, as documented in the GRKO cultural landscape report (John Milner 

Associates et al. 2004). 

4.11.4 Data and Methods

GRKO park staff provided historic aerial photos of GRKO from 6 different years over time. These

photos were from 1947, 1960, 1972, 1979, 1983, and 2001. All of the aerial photos cover only a 

portion of the park and its surroundings, but do not all cover the same area with the exception of the 

2013 NAIP imagery (retrieved from the NRCS Geospatial Data Gateway), which covers the entire 

United States (NRCS GDG 2014). As a result, only 3 years (1947, 1972, 2013) were used to display 

any changes in 

development in and 

surrounding GRKO over 

time. Aerial photos from 

before (1947), during 

(1972), and after (2013) 

park establishment were 

used to illustrate historic 

conditions and post-park 

establishment conditions. 

There were three areas (A, 

B, C) south and east of the 

park that were analyzed

(Figure 55). 

Historic photos from the 

early 1900s were provided 

by GRKO, to compare with

photos from similar 

vantage points taken in 

2002 and 2014. The photos 

Figure 55. Locations of the three areas (A, B, C) with the most visible 

change in development between 1947 and 2013. 
207 

from 2002 were obtained from GRKO’s cultural landscape report (John Milner Associates et al. 

2004). Photos from 2014 were taken by park staff to aid in this assessment. 

John Milner Associates et al. (2004) prepared a cultural landscape report (CLR) for GRKO. The 

report includes a landscape history and description of existing conditions. There are nine landscapes 

described in this report, each with a vista representing that landscape. The landscapes include the 

home ranch complex, east feed lot/Warren Hereford Ranch, Grant-Kohrs Residence, Warren 

Residence, pasture and hayfields, upland pasture, riparian woodland, railroad corridor, and 

development zone. Descriptions of each landscape are also included. Photo points were added to the 

report and were coupled with two photos (one from the late 1800s to early 1900s and another from 

2002) to compare change over time. 

Park staff identified six observation points and four trails of interest within the park for analysis in 

this NRCA: four comparative points from the CLR (12, 13, 22, and 36), the Ranch House back 

porch, the River Bridge, Outer Loop Road, Bridge Road, Ridge Road, and the old County Road 

(Figure 56). For each of these points or lines, 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. For line features, a polyline was created; the Viewshed Tool uses each 

vertex in the line to determine the viewshed of the feature as a whole. The DEM used was the 1/3-arc 

second National Elevation 

Dataset (NED) DEM. 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). 

In summary, two raster 

layers were developed for 

this analysis: an internal 

viewshed layer and an external viewshed layer. The internal viewshed layer represents the area of the 

park visible from the 10 selected viewing areas in the park. The external viewshed layer represents 

the areas outside the park boundary that are visible from high-use viewing areas inside the park. 

Figure 56. Locations of the 10 selected viewing areas in GRKO.
208 

4.11.5 Current Condition and Trend

A composite viewshed was created by combining the 10 high-use viewing areas in the park in an 

effort to define the most viewable areas of the study region. This analysis was combined with a 10-m 

DEM used in 

the viewshed 

analysis to 

produce an 

output defining 

the most 

viewable areas 

of the region 

(Figure 57).

However, the 

viewable area is 

limited, as some 

of the 

viewsheds 

would have 

returned 

viewable areas 

beyond the 

extent of the 

DEM. Figure 57

displays the 

composite 

viewshed, 

which displays 

which areas in 

and around the 

park cannot be 

seen, areas that 

can only be 

viewed from 

one vista, and 

areas that can 

be seen from 

multiple vistas. 

Change in Land Use Cover Type Inside the Park (Internal Viewscape)

Ten observation points were used to determine the internal viewshed of GRKO. The resulting total 

visible area from the observation points was 495 ha (1,223 ac), about 78% of the park’s total area. 

Most of the area not visible from these points is near the southwest border and in the northern portion 

of the park. 

Figure 57. Composite viewshed using vistas in GRKO.
209 

The primary 2011 National Landcover Database (NLCD) landcover classes viewable within GRKO 

are Pasture/Hay and Grassland/Herbaceous, at 25% each (Table 60; Jin et al. 2013). The Pasture/Hay 

class is dominated by grasses, legumes, and grass-legume mixtures. Grazing and production of hay 

crops are the uses for the Pasture/Hay classification (MRLC 2014). Graminoids dominate the 

Grassland/Herbaceous class. This herbaceous vegetation accounts for approximately 80% of the total 

vegetation in the landcover class. These areas “are not subject to intensive management such as 

tilling, but can be utilized for grazing” (MRLC 2014, p. 1). Figure 58 displays the visible land cover

classifications in and around GRKO. 
210 

Figure 58. Landcover classification of visible areas in and around GRKO (Jin et al. 2013).
211 

Table 60. 2011 NLCD viewable landcover composition in GRKO (Jin et al. 2013).

Landcover Classification Hectares Percent Land Cover

Pasture/Hay 165.7 25

Grassland/Herbaceous 159.39 25

Not Visible 143.1 22

Woody Wetlands 86.8 13

Shrub/Scrub 71.7 11

Developed, Open Space 24.8 4

Developed, Low Intensity 3.9 <1

Open Water 2.61 <1

Evergreen Forest 0.3 <1

Analysis of NLCD change 

data indicates very little 

change within the internal 

viewshed from 2001 to 

2011; approximately 32 ha 

(79 ac) changed over that 

time (about 6% of total 

visible area from the 

observation points) (Table 

61). Only three land cover 

classifications changed in 

the park between 2001 and 

2011 (Pasture/Hay, 

Shrub/Scrub, Woody 

Wetlands). The largest 

area of change occurred 

near the western border, 

changing from the 

Pasture/Hay classification 

to Grasslands/Herbaceous 

classification. All areas 

that changed in the park 

were converted to the 

Grasslands/Herbaceous 

classification. Figure 59 

displays the changes in the 

park’s internal landcover 

between 2001 and 2011. Figure 59. Internal viewshed analysis. Visible landcover change in 

GRKO between 2001 and 2011 (Jin et al. 2013).
212 

Table 61. NLCD landcover change in GRKO between 2001 and 2011 (Jin et al. 2013).

Landcover Change Type Hectares Percent Visible Areas

Visible, but No Change 484 94

Pasture/Hay to Grassland/Herbaceous 28 6

Shrub/Scrub to Grassland/Herbaceous 3 <1

Woody Wetlands to Grassland/Herbaceous <1 <1

Change in Land Use Cover Type Outside the Park (External Viewscape)

Similar to the internal viewshed, the external viewshed changed little between 2001 and 2011 

according to the NLCD change product. Within 25 km (15.5 mi) of the park, 43,137 ha (106,593 ac) 

were identified as visible from the viewpoints established for the park; of these, approximately 730 

ha (1,804 ac) experienced a change in landcover classification (about 2%). A majority of this change 

(419 ha [1,035 ac]) was from Evergreen Forest to Shrub/Scrub (Figure 60). The Shrub Scrub 

landcover class includes, “areas dominated by shrubs; less than 5 meters tall with shrub canopy 

typically greater than 20% of total vegetation. This class includes true shrubs, young trees in an early 

successional stage, or trees stunted from environmental conditions” (MRLC 2014, p. 1). About 116 

ha (287 ac) of area changed to Grassland/Herbaceous landcover within 24 km (62 mi) of the park 

boundary. Approximately 17 ha (42 ac) of the visible area changed to developed area, with much of 

this developed area being the High Intensity designation (i.e., areas where people reside or work in 

high numbers, more than 80% impervious surfaces [MRLC 2014]). Unlike the internal viewshed of 

the park, the primary NLCD cover class in the external viewshed is the Evergreen Forest designation. 

Appendix L provides a complete listing of designation changes between 2001 and 2011. 

Aerial photos were used to display the change in development in and around GRKO. The three areas 

that were used displayed the most change in development between 1947 and 2013 (Figure 55). 

Area A

Over the last 65 years, development occurred in and around the eastern border of the park. The 

changes that occurred inside the park between 1947 and 1972 included the addition of the Warren 

Hereford complex (square corrals, Warren barn, sales barn, bull corral, and office building) (Figure 

61). Between 1972 and 2013 the visitor center and walking path from the visitor center to the ranch 

house complex was created. The major change that occurred outside the park was the expansion of 

North Main Street, looping east toward Interstate 90, between 1972 and 2013. Residential and 

commercial buildings were developed after the addition of this road. More residential development 

occurred south and east of Little Joe E-70 Park. 
213 

Figure 60. External viewshed analysis. Visible land cover change in areas surrounding GRKO between 

2001 and 2011 (Jin et al. 2013).
214

Figure 61. Aerial photos of Area A in 1947 (left), 1972 (middle), and 2013 (right). The yellow and red polygons represent areas within Area A that 

changed from 1947 to 1972 and from 1972 to 2013, respectively.
215 

Area B

Development occurred around the southern border of the park. Most of the changes in development 

between 1947 and 1972 were residential expansion. Residential areas continued to expand 

throughout the northern portion of Area B between 1972 and 2013. A lumber yard (located in the 

southern portion of Area B) may have been present in 1947; however, it is more prevalent in the 

1972 photo and has expanded greatly by 2013. Figure 62 displays the changes in development in 

Area B in 1947 (left), 1972, (middle), and 2013 (right). 

Figure 62. Aerial photos of Area B in 1947 (left), 1972 (middle), and 2013 (right). The yellow and red 

polygons represent areas within Area B that changed from 1947 to 1972 and from 1972 to 2013, 

respectively. The dark gray shaded areas are not visible from the selected viewpoints

Area C

Development also occurred to the southeast of the park. In 1947, this area was relatively open with 

patches of residential areas. By 1972, most of the open fields were filled in with residential homes. 

Cottonwood City Park, an elementary school, and a junior high school were also built (located just 

north of the park’s track). By 2013, barely any open fields remained due to the construction of more 

residential homes. Figure 63 displays the changes in development in Area C in 1947 (left), 1972, 

(middle), and 2013 (right).
216

Figure 63. Aerial photos of Area C in 1947 (left), 1972 (middle), and 2013 (right). The yellow and red polygons represent areas within Area C that 

changed from 1947 to 1972 and from 1972 to 2013, respectively. The dark gray shaded areas are not visible from the selected viewpoints.
217 

Change at Selected Photo Points 

Comparative Point 12 

This vista consists of the 

south side of the ranch 

house and thoroughbred 

barn. Photo 32 displays the 

view from comparative 

point 12 in the early 1900s 

(top left), 2002 (top right), 

and 2014 (bottom). There 

have been several changes 

in viewscape at 

comparative point 12 from 

1900 to 2014. Between the 

early 1900s and 2002, the 

vegetation blocking the 

view of the fence in the 

foreground and white 

building in the background 

thinned out considerably. 

Cottonwood trees seem to 

dominate the vegetation in

the background in 2002 

and are still present in 

2014. Shrubs seen in the 

field in 2002 have grown 

several feet by 2014. All 

historic structures 

remained constant 

throughout the time period 

with the exception of 

changes made to the fence by 2014. Figure 64 displays the location of each selected photo point and 

the direction that photo is facing. 

Figure 64. The location of each selected photo point in GRKO, and the 

direction each photo is facing.
218 

Photo 32. The view from comparative point 12 in the early 1900s (top left), 2002 (top right), and 2014 

(bottom) (NPS photos). 
219 

Comparative Point 13 

This vista contains the general view of the ranch. There have been several changes in viewscape at 

comparative point 13 from 1900 to 2014 (Photo 33). A visible footpath was present in the early 

1900s, but that path was no longer distinguishable by 2002. This cultural viewscape was not 

compromised by power lines in the early 1900s. In 2002, the power lines in front of the ranch house 

are blocked by trees; however, the vegetation blocking the power lines from view were removed by 

2014. Several power lines are visible from this vista. Vegetation in the field seems to have only 

changed by natural succession between 2002 and 2014. 

Photo 33. The view from comparative point 13 in the early 1900s (top left), 2002 (top right), and 2014 

(bottom) (NPS photos).
220 

Comparative Point 22 

This vista looks west toward the Lower Yards. There has been little change in viewscape at this vista. 

Throughout the years the road has become more pronounced. In the early 1900s, the road seemed to 

be more of a dirt trail. By 2002, gravel was put down to make the trail more permanent and easily 

accessible to motorized vehicles as well as horses. The cultural structures have remained constant 

between the early 1900s and 2014. There are no pronounced changes in vegetation at this vista. 

Photo 34 displays the view from comparative point 22 in the early 1900s (top left), 2002 (top right), 

and 2014 (bottom). 

Photo 34. The view from comparative point 22 in the early 1900s (top left), 2002 (top right), and 2014 

(bottom) (NPS photos).
221 

Comparative Point 36 

This vista is of the Warren Hereford Ranch sign and barn from the administrative entrance. Photo 35 

displays the view from comparative point 36 in the early 1900s (top left), 2002 (top right), and 2014 

(bottom).There were a few changes in viewscape at this vista. Throughout the years, additions were 

made to the entrance and fence line, which do not appear to adversely affect the cultural viewscape. 

There seems to be little change to the vegetation, but two trees were removed between the 1900s and 

2002. Power lines can easily be seen in the 2002 and 2014 photos. The presence of cars and the 

parking lot may also take away from cultural view in the 2014 photo. 

Photo 35. The view from comparative point 12 in the early 1900s (top left), 2002 (top right), and 2014 

(bottom) (NPS photos).
222 

RE 20

This vista is a westward-facing view of Stuart Field. The vista has not changed much between 2002 

and 2014. A photo from the early 1900s was not available for comparison at this vista. The top posts 

on the fence gates are the only noticeable change in the structure between 2002 and 2014. The path 

that worked its way through Stuart Field in 2002 is not visible in 2014. The vegetation has not 

changed much between 2002 and 2014. This vista does not seem to have been adversely affected by 

development. Photo 36 displays the view from vista RE 20 in 2002 (left) and 2014 (right). 

Photo 36. The view from vista RE 20 in 2002 (left) and 2014 (right) (NPS photos).

G 01

This vista is a view of the North Meadows. There was little to no change in cultural viewscape at this 

vista. The fence has had no visible change between 2002 and 2014. The vegetation throughout the 

photo has not changed. The vegetation to the left of the fence seems to be denser in 2014, but this 

could be due to the time of year the photo was taken. Overall, the viewscape from this vista looks 

unaffected by noncontributing features. Photo 37 displays the view from vista G 01 in 2002 (left) and 

2014 (right). 

Photo 37. The view from vista G 01 in 2002 (left) and 2014 (right) (NPS photos).
223 

M 13 

This vista is of Kohrs Ditch Road. There was little to no change in cultural viewscape at this vista. 

The road has become more pronounced and filled in with gravel since 2002. The tree line to the left 

of the road seems to have filled in since 2002. Overall, the viewscape from this vista looks unaffected 

by noncontributing features. Photo 38 displays the view from vista M 13 in 2002 (left) and 2014 

(right). 

Photo 38. The view from vista M 13 in 2002 (left) and 2014 (right) (NPS photos).

O 16

This vista is the view from Little Gulch Field looking east towards the ranch complex. Vegetation 

composition and height seem to be the main change at this vista. The taller vegetation in the 2014 

picture may be a result of the time of year the photo was taken. Developed areas were visible in 2002 

and remain visible in 2014. The developed area has not noticeably expanded during the time 

difference. Overall, the viewscape from this vista looks unaffected by newly-developed, 

noncontributing features. Photo 39 displays the view from vista O 16 in 2002 (left) and 2014 (right). 

Photo 39. The view from vista O 16 in 2002 (left) and 2014 (right) (NPS photos).
224 

N 22 

This vista is of the Upland Pasture area. The unpaved trail that was present in 2002 remains unpaved 

in 2014. The vegetation seems to be similar (in height and density) in 2002 and 2014. There are no 

noncontributing features visible from this vista. Overall, the viewscape from this vista has 

experienced little change. Photo 40 displays the view from vista N22 in 2002 (left) and 2014 (right).

Photo 40. The view from vista N 22 in 2002 (left) and 2014 (right) (NPS photos).

P 13 

This vista is of a 91 m (300 ft) long slough (fed by three natural springs) located to the west of the 

river. Developed areas to the east of the park can be seen in both years. There does not seem to be a 

visible change in development. Riparian vegetation conceals a large portion of development from 

this vista. Aquatic and terrestrial vegetation has not changed much from 2002 to 2014. Overall, this 

vista does not seem to have changed much over the last 12 years. Photo 41 displays the view from 

vista P 13 in 2002 (left) and 2014 (right). 

Photo 41. The view from vista P 13 in 2002 (left) and 2014 (right) (NPS photos).
225 

E 01 

This is a view of the barrow pits wetland in the park. A power line was the only non-contributing 

feature at this vista, and it has been there since 2002. The body of water seems to have widened 

between 2002 and 2014 (Photo 42), although this may be natural variation. The vegetation in the area 

has not changed much in height or distribution. The beaver lodge in the 2002 photo cannot be seen in 

the 2014 photo because these are similar vantage points of the same vista, not the exact same 

location. Overall, the vista has not been altered nor has it been affected by additional noncontributing features since 2002. 

Photo 42. The view from vista E 01 in 2002 (left) and 2014 (right) (NPS photo).

Threats and Stressor Factors 

GRKO park staff identified several threats that impact the park’s cultural and natural viewscape. 

Those threats include gravel mining located south of the park, invasive species, Superfund 

remediation activities, development, and the conspicuousness of non-contributing features.

Development is a major concern to viewscape in GRKO. According to McChristian (1977), modern 

development occurring on the west slope of the valley is a major threat to the cultural viewscape. The 

park is located just west of the city of Deer Lodge. It is difficult not to see noncontributing features 

from within the park, and the city continues to develop, as seen in the external viewshed analysis 

using NLCD data. 

The conspicuousness of non-contributing features is another threat to the GRKO viewscape. 

Noncontributing features include any manmade structure that might detract from the cultural 

structures in the park. Non-contributing features inside the park include power lines and poles 

established within the last 25 years, blue watering troughs, the gravel parking area, the parking area 

by the visitor center, and the asphalt side walk leading from the visitor’s center to the home ranch 

complex (John Milner Associates et al. 2004). Noncontributing features that can be seen from the 

park include the city structures, such as the arches associated with McDonald’s fast food restaurant 

(less than a mile away). Most development is occurring to the south and east of the park. A scenic 

easement in the northern section of the park protects the cultural viewscape to the north (John Milner 

Associates et al. 2004). There is another easement (Five Valleys Trust Easement) to the west of the 
226 

park, located on the Rock Creek Ranch, which was established in 2006 (Smith, written 

communication, 14 November 2014). 

Gravel mining occurring to the south of the park is a threat to the viewscape at GRKO. There is an 

active gravel mine located south of Taylor Field within the Deer Lodge airport (Smith, written 

communication, 14 November 2014). Sand and gravel mining degrade the aesthetic feel of 

viewscapes (Ayenagbo et al. 2011). Abandoned mines may have mounds of aggregate left over, 

making the viewscape look unnatural and disturbed. Some abandoned mines do naturalize but 

vegetation succession takes time and there is no guarantee that natural plant communities will grow 

back (TOARC 2014). Mining can also degrade air quality by generating particulates (i.e., dust), 

which may decrease the visibility of the viewscape (Blodgett 2004). 

Invasive plant species are a threat to the GRKO viewscape. Invasive species, not intentionally 

planted, are considered noncontributing features that adversely affect the historical and cultural 

vegetative composition (John Milner Associates et al. 2004). These species can produce different 

colors and textures on the landscape than the native plants and intentionally cultivated grasses.

Superfund remediation activities will impact the GRKO viewscape starting in late 2015. Remediation 

will completely alter the riparian corridor, removing vegetation along with contaminated soils. The 

taller vegetation in this area blocks a majority of the developed city areas from view at the vistas 

located on the west side of the river. Large, unvegetated areas may be visible for months at a time 

due to this removal. The heavy equipment used in these activities will also likely be visible from 

portions of the ranch. The restored area will be replanted with a variety of grasses, shrubs, and trees 

to restore it to a natural setting. The estimated duration for the remediated area to fully recover is 

greater than 10 years (Johnson, written communication, 14 November 2014). 

Data Needs/Gaps

The data gap that exists is the lack of historic photos. Only four of the 12 selected photo points have 

historic photos from the early 1900s. Unfortunately, these may be difficult or impossible to obtain at 

this stage. Additional historic aerial photos (e.g., from the 1990s or mid-2000s) could be helpful in 

documenting development just outside the park that has impacted its viewscape.

Overall Condition 

Change in Land Use Cover Type Inside the Park (Internal Viewscape)

The Significance Level for change in land use cover type inside the park was defined as a 3. The 

internal viewscape analysis using NLCD data indicated very little change within the internal 

viewshed from 2001 to 2011. Approximately 32 ha (79 ac) changed over that time, which accounts 

for 6% of total visible area from the selected observation points. There were only three land cover 

classifications that changed in the park between 2001 and 2011 (Pasture/Hay, Shrub/Scrub, Woody 

Wetlands). All areas that changed in the park shifted to the Grasslands/Herbaceous classification. As 

a result, the Condition Level of this measure is 0, indicating no concern. 

Change in Land Use Cover Type Outside the Park (External Viewscape)
227 

The Significance Level for change in land use cover type outside the park was also defined as a 3. 

Similar to the internal viewshed, the external viewshed changed little between 2001 and 2011. Of the 

43,137 ha (106,593 ac) visible from selected viewpoints within 25 km of the park, approximately 730 

ha (1,804 ac) experienced a change in classification (about 2%). Some of the visible area directly 

west of the park that experienced change was converted to low intensity developed area. As a result, 

the Condition Level of this measure is 1, indicating low concern. 

Change at Selected Photo Points

The Significance Level for change at selected photo points was also defined as a 3. Most of the 

selected photo points displayed little change over time. Those points with photos that date back to the 

early 1900s, however, documented the addition of noncontributing features. Those features include 

power lines and poles, gravel parking lots, cars, and more developed roads. As a result, the Condition 

Level of this measure is 1, indicating low concern. 

Weighted Condition Score 

The Weighted Condition Score for the component is 0.22, indicating viewscape is in good condition 

overall. The external viewscape and aerial photos display a growing city of Deer Lodge. This 

increase in development surrounding GRKO suggests a declining trend for viewscape. 

Viewscape

Measures Significance 

Level

Condition 

Level WCS = 0.22 

Change in Land Use 

Cover Type Inside the 

Park (Internal 

Viewscape)

3 0 

Change in Land Use 

Cover Type Outside the 

Park (External 

Viewscape)

3 1 

Change at Selected 

Photo Points 3 1 

4.11.6 Sources of Expertise

Jason Smith, GRKO Natural Resource Specialist
228 

4.11.7 Literature Cited

Ayenagbo, K., J. N. Kimatu, J. Gondwe, and W. Rongcheng. 2011. The transportation and marketing 

implications of sand and gravel and its environmental impact in Lome-Togo. Journal of 

Economics and International Finance 3(3):125-138. 

Blodgett, S. 2004. Environmental impacts of aggregate and stone mining. Center for Science in 

Public Participation. 

http://www.csp2.org/files/reports/Environmental%20Impacts%20of%20Sand%20and%20Gravel

%20Operations%20in%20New%20Mexico.doc.pdf (accessed 25 June 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. 

John Milner Associates, Rivanna Archaeological Consulting, Susan Maxman and Partners 

Architects. 2004. Cultural landscape report. Grant-Kohrs Ranch National Historic Site, Deer 

Lodge, Montana. 

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. 

McChristian, D. C. 1977. Ranchers to rangers: An administrative history of Grant-Kohrs Ranch 

National Historic Site. Rocky Mountain Cluster, National Park Service. 

http://www.nps.gov/history/history/online_books/grko/adhi/adhi7b.htm (accessed 21 August 

2014). 

Multi-Resolution Land Characteristics Consortium (MRLC). 2014. National Land Cover Database 

2006 product legend. http://www.mrlc.gov/nlcd06_leg.php (accessed 21 August 2014). 

Natural Resource Conservation Services (NRCS), Geospatial Data Gateway (GDG). 2014. 2013 

NAIP imagery. United States Department of Agriculture. http://datagateway.nrcs.usda.gov/

(accessed 15 September 2014). 

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., and H. W. Harshaw 

(eds.). Forests and landscapes: Linking ecology, sustainability and aesthetics. CABI Publishing, 

New York, New York. 

The Ontario Aggregate Resource Corporation (TOARC). 2014. Management of abandoned aggregate 

properties program (MAAP). http://www.toarc.com/maap-1/about-maap.html (accessed 25 June 

2014). 
229 

4.12 Hydrology

4.12.1 Description

The Clark Fork River is an important resource for GRKO. The river and its hydrogeologic system is 

a primary resource at GRKO and it also protects a small portion of the upper Clark Fork River 

drainage (Thornberry-Ehrlich 2007). The river is integral to many of the on-going ecological 

processes within the ranch, as well as playing an important role in current ranching operations 

(Schweiger et al. 2014). GRKO also holds multiple water-right claims to use surface water from the 

river and its tributaries for flood irrigation (John Milner Associates et al. 2004). 

The Clark Fork River near the Idaho border is 

the largest stream in Montana (MT DNRC 

2004). Its headwaters are located in west-central 

Montana at the confluence of Silver Bow and 

Warm Spring Creeks (Figure 65). GRKO is

located along a 238 km (148 mi) reach of the 

Clark Fork that stretches from its headwaters 

near Butte, Montana to the former headwaters of 

the Milltown Reservoir near Bonner, Montana 

just upstream from Missoula, Montana (Dodge 

et al. 1996). This reach drains a watershed 

(Upper Clark Fork) of approximately 4,856 km2 

(875 mi2) (Hornberger et al. 1997). From its 

headwaters, the Clark Fork flows generally 

northward through the wide and meandering 

floodplain of the Deer Lodge Valley with an 

average gradient of 3.8 m/km [0.7 ft/mi] 

(Schweiger et al. 2014). Primary surface water 

use within the watershed includes irrigation, 

stock watering, light industry, hydroelectric 

power generation, and habitat for trout fisheries. 

Land use within the watershed consists 

primarily of cattle production, logging, mining 

and recreation (Dodge et al. 1996). Large-scale 

mining and smelting had historically been a 

major land use, but are now largely discontinued (Dodge et al. 1996). 

GRKO is located along a 5.5 km (3.4 mi) section of the Clark Fork River within the Upper Clark 

Fork watershed (Figure 66). The Ranch is located downstream from the town of Deer Lodge between 

Cottonwood Creek to the south and Fred Burr Creek to the north (Figure 66). Within the boundaries 

of GRKO there are six small tributary creeks and nine natural springs that feed into the Clark Fork 

River (John Milner Associates et al. 2004). The Clark Fork bisects GRKO north to south. The 

Figure 65. Location of Clark Fork River in western 

Montana.
230 

domestic buildings and buildings associated 

with cattle ranching operations are located to the

east while the west side of the river consists of 

pastures and hayfields. 

GRKO is located along a reach of the Clark 

Fork River that has been given a beneficial use 

classification of C-1 (MT DEQ 2012). This is

defined as suitable for the following uses: 

primary contact recreational use (bathing, 

swimming, and recreation); growth and 

propagation of salmonid fishes and their 

associated aquatic life, waterfowl, and 

furbearers; and agricultural and industrial water 

supply (MT DEQ 2006). This reach is also on 

the 303(d) list for the State of Montana (MT 

DEQ 2012). It is designated as not supporting 

for aquatic life, cold water fishery, and primary 

contact recreational use. This is primarily the 

result of impairment from mine tailings, causing 

elevated copper, lead, and zinc concentrations, 

and agriculture and municipal point-source 

discharge, which have resulted in elevated 

nitrogen, phosphorus, and sediment 

concentrations (MT DEQ 2014a). 

4.12.2 Measures

• Stream discharge 

• Irrigation flow inputs 

• Timing and amount of precipitation 

• Depth to groundwater 

4.12.3 Reference Conditions/Values

The reference condition for stream discharge is defined as the average hydrograph conditions that 

were derived for the period of 1980-2012 by Schweiger et al. (2014). The reference condition for 

precipitation is the historic record from a cooperative weather station located near Deer Lodge, MT. 

The reference condition for depth to groundwater is based on a report on water resources conditions 

at GRKO by Woessner and Johnson (2001). A reference condition could not be established for 

irrigation flow inputs. 

Figure 66. Location of Clark Fork River at GRKO.
231 

4.12.4 Data and Methods

The information for this assessment was gathered primarily from hydrologic data developed by 

several prior studies on the contamination to the surface water and ground water from the Clark Fork 

Superfund Site (e.g., Hornberger et al. 1997, Schweiger et al. 2014). Stream discharge information 

for stream gauge 12324200, located in the Clark Fork River near Deer Lodge, Montana was obtained 

from the USGS Water Information System website 

(http://waterdata.usgs.gov/mt/nwis/inventory?search_site_no=12324200). This station has a 

continuous record of discharge data from water year 1979 to the present. Precipitation data was 

obtained from the Western Regional Climate Center website 

(http://www.ncdc.noaa.gov/oa/ncdc.html) for the Deer Lodge 3W station. Historic data was also 

available for another station at Deer Lodge, Montana that was incorporated to analyze the period of 

record. 

4.12.5 Current Condition and Trend

Stream Discharge 

Discharge monitoring data is available from a USGS stream gage station located in the Clark Fork 

River near Deer Lodge, MT (Station Number 12324200). A continuous discharge record is available 

from water year 1979 to the present. A hydrograph based on mean monthly discharge over this 

period is shown in Figure 67. The hydrograph for the gauging station reflects the general conditions 

found in the Clark Fork River above Missoula, Montana. Stream discharge remains relatively stable 

from fall to early winter (October - January) with little variation in monthly discharge during the 

period of record for these months (Hornberger et al. 1997). During the months of February and 

March, stream flow begins to increase as a result of increased runoff from snow melt in the lower 

elevations (Hornberger et al. 1997). The months of April and May mark a transitional period between 

winter and summer. Precipitation can be in the form of rain or snow, but it tends to contribute little to 

overall stream flow, as the ground is generally thawed and the water can infiltrate (Hornberger et al.

1997). Stream flow increases during this period as a result of snow melt in the mid-elevations and 

can be augmented by some high-elevation snow melt (Hornberger et al. 1997). Peak flow can occur 

during this period, if temperatures are warmer than normal and the snow pack melts earlier than 

normal (Hornberger et al. 1997). Peak flow generally occurs in late May or early June, as a result of 

rainfall and snow melt in the high-elevations. Stream discharge declines during July and August as a 

result of warmer daily temperatures and less frequent and less intense precipitation events, and also 

because of irrigation withdrawals (Hornberger et al. 1997). The combination of the end of the 

irrigation season and late summer precipitation events result in increased discharge levels in 

September (Hornberger et al. 1997). 

Schweiger et al. (2014) created a 30-year normal (1980 - 2010) discharge dataset for the gaging 

station at Deer Lodge. This data, and data for every water year on record, are summarized in Table 

62. Mean annual discharge during the 30-year period averaged 2,507 cubic meters per second (cms) 

(88,538 cubic feet per second [cfs]). Minimum daily mean discharge was 1.7 cms (61 cfs) with a 

maximum daily discharge of 67.7 cms (2,390 cfs). The highest peak flow on record (67.7 cms [2,390 

cfs]) occurred on 23 May 1981 (USGS 2014b). The lowest peak flow recorded was 0.6 cms (22 cfs) 
232 

this occurred on two occasions, 22 April 1988 and 8 June 1991 (USGS 2014b). Figure 68 is a graph 

of the daily flows for the period of record. There is a slightly negative trend (i.e., a decrease in flow) 

over the historical record. A previous study (Schweiger et al. 2014) calculated this as a marginal (p = 

0.13) negative trend of 0.05 cms/year (1.72 cfs/year). 

Figure 67. Hydrograph of mean monthly discharge rates of the Clark River from USGS Gage Station 

12324200 located near Deer Lodge, MT.

Figure 68. Daily discharge rates (Oct 1978 - present) of the Clark River from USGS Gage Station 

12324200 located near Deer Lodge, MT. 

0

2

4

6

8

10

12

14

16

Mean Monthly Discharge (cms)

Month

0

10

20

30

40

50

60

70

80

Daily Discharge (cms)

Date

Daily Discharge

Linear Trend
233 

Table 62. Discharge data from the Clark Fork River (Deer Lodge USGS station 12324200) near GRKO

(USGS 2014b). All results are in cms with cfs equivalents in parenthesis.

Water Year

Total 

Discharge

Minimum

Discharge

Maximum

Discharge

Date of 

Maximum 

Discharge Median

Standard 

Deviation

1979 2735 (96572) 1.9 (68) 17.1 (605) May 25 8.1 (287) 114

1980 3942 (139200) 2.9 (104) 45.9 (1620) June 16 7.4 (263) 300

1981 4144 (146360) 2.6 (92) 67.7 (2390) May 23 9.1 (320) 321

1982 4513 (159370) 2.8 (100) 40.2 (1420) June 25 9.5 (334) 297

1983 3525 (124500) 3.6 (126) 25 (884) July 11 9.7 (344) 99

1984 3577 (126331) 2.7 (94) 45 (1590) June 22 8.9 (315.5) 185

1985 2428 (85730) 0.7 (25) 13.3 (469) May 4 7.4 (260) 110

1986 2824 (99712) 0.9 (32) 45.6 (1610) February 25 7.2 (256) 175

1987 2036 (71887) 1.7 (60) 12.5 (440) May 28 5.9 (210) 74

1988 1604 (56637) 0.6 (22) 11.1 (391) April 22 4.6 (161.5) 84

1989 1898 (67027) 1.2 (42) 24.3 (858) March 10 4.6 (161) 104

1990 1893 (66834) 0.8 (29) 13.9 (490) May 31 5.5 (195) 70

1991 1914 (67576) 0.6 (22) 26.2 (924) June 8 5 (177) 125

1992 1352 (47758) 0.7 (26) 8 (284) November 6 4 (142) 58

1993 2559 (90383) 2.5 (88) 16.9 (596) June 18 5.7 (203) 123

1994 2144 (75714) 0.7 (26) 12.6 (445) May 13 6.6 (233) 101

1995 2833 (100037) 1.6 (55) 33.4 (1180) June 7 6.2 (220) 172

1996 3389 (119680) 1.4 (50) 32 (1130) June 11 7.7 (272.5) 217

1997 4801 (169550) 4.5 (160) 56.1 (1980) June 14 8.8 (312) 377

1998 3197 (112899) 2.4 (85) 30.9 (1090) July 4 8.1 (287) 157

1999 2604 (91976) 1.5 (52) 22.5 (796) June 4 7 (246) 128

2000 1612 (56928) 0.7 (24) 7.1 (251) November 26 5.6 (196.5) 72

2001 1563 (55183) 0.9 (31) 7.9 (279) June 4 4.8 (170) 54

2002 1662 (58692) 1.7 (59) 12.1 (429) June 10 4.7 (165) 57

2003 2177 (76884) 1 (36) 28.9 (1020) June 1 5.4 (189) 143

2004 1499 (52932) 0.8 (27) 7.6 (267) March 9 4.4 (156) 53

2005 2034 (71818) 2.1 (73) 22.2 (785) June 18 4.5 (158) 126

2006 2016 (71187) 1 (35) 16.4 (578) June 11 5.5 (194) 98

2007 2160 (76273) 1.4 (50) 27.6 (974) June 7 5.7 (200) 130

2008 2648 (93499) 1.8 (64) 27.1 (957) June 5 5.8 (206) 165

2009 3343 (118055) 2.3 (80) 32.3 (1140) June 1 7.5 (264) 208

2010 3198 (112943) 3.4 (120) 41.6 (1470) June 17 6.9 (245) 203

2011 4655 (164388) 4.2 (150) 55.5 (1960) June 14 8 (283) 431

2012 2848 (100563) 2.2 (78) 22.1 (781) June 6 8.2 (288) 123

2013 1876 (66241) 1.6 (55) 9.9 (349) May 30 5.7 (200) 63

2014 2917 (103023) 2.7 (96) 21.2 (748) June 28 6.2 (219) 133

Historic 

(1980-2010) 2507 (88,538) 1.7 (61) 67.7 (2,390) May 28 6.4 (226) 140

A study was conducted in 2009 (KirK 2010) where discharge (among several other parameters) was 

measured for Cottonwood Creek. A total of 15 flow monitoring sites were established for this study, 

with four sites along Cottonwood Creek (KirK 2010). The location of the four sites is shown in 

Figure 69. Flow measurements were taken between 21 April and 19 October 2009 and the results for 

the four stations on Cottonwood Creek are shown in Table 63. As can be seen in Table 63 and in 

Figure 70, flows where highest in April, peaking in May and dropping to less than 0.5 cms in June. 
234 

Figure 69. Flow monitoring points along Cottonwood Creek (KirK 2010).

Table 63. Stream flow in Cottonwood Creek. All results are in cms with cfs equivalents in parenthesis

(KirK 2010). 

Date C-1 C-2 C-4 C-A 

21-Apr-09 0.64 (22.53)

22-Apr-09 0.92 (32.51) 1.37 (48.27)

8-May-09 0.49 (17.42) 0.45 (15.96) 0.56 (19.94) 0.51 (17.94)

21-May-09 1.92 (67.81) 1.79 (63.31)

22-May-09 1.91 (67.3) 1.99 (70.22)

22-May-09

28-May-09 3.85 (136.02) 3.72 (131.29) 4.28 (151.08)

29-May-09 4.7 (166.02)

29-Jun-09 0.16 (5.71) 0.17 (5.94) 0.16 (5.6) 0.76 (26.98)

5-Aug-09 0.08 (2.77) 0.06 (2.28) 0.17 (5.95) 0.26 (9.03)

19-Oct-09 0.09 (3.05) 0.08 (2.88) 0.03 (1.09) 0.07 (2.64)
235 

Figure 70. Flow rates for Cottonwood Creek (21 April through 19 October 2009 [KirK 2010]).

Irrigation Flow Inputs

Irrigation is the largest consumer of water in Montana, accounting for 97% of the total water 

withdrawals and 94% of the total water consumed (MT DEQ 2014b). Several geographic, climatic 

and agricultural factors affect when irrigation occurs, but in general the irrigation season starts in 

mid- April and continues through mid-September (MT DNRC 2004). Natural flow patterns in the 

Clark Fork are affected by the cumulative impacts of upstream water uses (MT DNRC 2004). In the 

Upper Clark Fork, tributaries and the main stem of the Clark Fork exhibit reduced flows in the 

summer months. This can be attributed to the combination of irrigation diversions and natural factors 

(MT DNRC 2004). On the other 

hand, depending on water use 

practices and local physical features, 

return flow, especially from flood 

irrigation can augment late season 

natural streamflow (MT DNRC 

2004). Nimick (1993) reported that 

stream flow data indicated that 

ground-water inflow to the Clark 

Fork is significant, primarily in the 

reach between Racetrack and 

Garrison, and that irrigation-return 

flow is probably the main source of 

this water. GRKO holds several 

water rights claims for diverting 

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

Flow Rate (cms)

Date

C-1

C-2

C-4

C-A

Figure 71. Flow rate in the Westside Ditch 2 ft. parshall flume 

within GRKO for the 2012 season.

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

14-May21-May28-May

4-Jun

11-Jun18-Jun25-Jun

2-Jul9-Jul

16-Jul23-Jul30-Jul

6-Aug

13-Aug20-Aug27-Aug

3-Sep

10-Sep17-Sep24-Sep

1-Oct8-Oct

Flow Rate (cms)

Date
236 

water for irrigation use from the Clark Fork River, Cottonwood Creek, Johnson Creek and Taylor 

Creek (MT WRB 2014). It also holds additional ground water and surface water rights for domestic 

and stock watering use (MT WRB 2014). 

Figure 71 shows the flow rates for the Westside Ditch for the 2012 irrigation season. Accurate flow 

rates were not available for all irrigation sources. Average flow for this period was 0.17 cms (6.1 

cfs). Peak flow of 0.3 cms (10.6 cfs) occurred on two occasions, 15 May and 6 June (NPS 2012). 

Timing and Amount of Precipitation 

The climate in the Clark Fork River basin results from influences of moist air masses stemming from 

the Pacific Ocean (MT DNRC 2004). Compared to the rest of Montana, GRKO experiences patterns 

of relatively abundant precipitation and mild winters, with the occasional extended cold periods, and 

hot, dry periods in summer (MT DNRC 2004). Table 64 summarizes the 30-year normal temperature 

and precipitation values for the station located near Deer Lodge, MT. Over this period, annual 

precipitation averaged 27 cm (10.62 in) (NCDC 2014). Mean monthly precipitation was highest in 

May and June and declined through late summer into fall (Figure 72). Total monthly precipitation is 

shown in Figure 73. Missing data periods in the graph correlate to months where five or more days of 

precipitation data were missing. These months were not used in the analysis. Over the period of 

record the total monthly precipitation has remained relatively stable, yet slightly increasing as is 

indicated by the trend line on the graph. In terms of total annual precipitation, analysis of data from 

1950 through 2010 shows a positive linear trend of 13% per century (Gonzalez 2014). 

Table 64. 1980-2010 normals for Deer Lodge 3W (NCDC 2014).

Mean Temperature °C (°F) 5.1 (41.2)

Mean Maximum Temperature °C (°F) 13.3 (56)

Mean Minimum Temperature °C (°F) -3.1 (26.5)

Mean Total Precipitation cm (in) 27 (10.62)
237 

Figure 72. 1980-2010 normal precipitation for Deer Lodge, MT (Cooperative Weather Station Deer Lodge 

3W) (NCDC 2014). 

Figure 73. Monthly total precipitation for the period of record for Cooperative Weather Station Deer 

Lodge 3W. Months with more than five days missing were not used in analysis. 

0

2

4

6

8

10

12

14

16

Monthly Total Precipitation (cm)

Date

Linear Trend

0.0

1.0

2.0

3.0

4.0

5.0

6.0

January February March April May June July August September October November December

Mean Monthly Precipitation (cm)

Month
238 

Depth to Groundwater 

Groundwater supplies in the Clark Fork basin are found in two basic types; basin fill aquifers or 

fractured bedrock aquifers (MT DNRC 2004). GRKO is located within a basin fill aquifer (MT 

DNRC 2004). These can be either shallow and unconfined or deep and confined and can range from 

several hundred to several thousand feet thick (MT DNRC 2004). Specifically, GRKO is located 

within the Northern Rocky Mountains Intermontane Basins aquifer system, which is an 

unconsolidated sand and gravel aquifer (USGS 2014a). Basin fill aquifers can range from being 

limited in extent and productivity to highly productive and dependable (MT DNRC 2004). Recharge 

in these aquifers can come from sources such as the infiltration of water from precipitation or 

snowmelt or excess irrigation water (MT DNRC 2004). These types of aquifers can be diminished by 

discharge to streams, evaporation, and withdrawals from pumping (MT DNRC 2004). 

At GRKO, groundwater occurs near the ground 

surface (Moore and Woessner 2001, Woessner 

and Johnson 2001). Previous studies at GRKO, 

using monitoring well and piezometer data, have 

found that the water table within the floodplain 

portion is within about 1.5 m (5 ft) of the ground 

surface. Under the gravel terraces to the east, the 

water table is generally 3 - 6 m (10 - 20 ft) 

below the surface, and can be up to 9 m (30 ft) 

or more below the surface for the upper portions 

of the west side fields (Moore and Woessner 

2001, Woessner and Johnson 2001). The city 

sewer line runs underneath a portion of GRKO. 

In order to limit groundwater infiltration into the 

line, the City of Deer Lodge has recently sliplined the sewer line and sealed the manholes. It 

is unknown what, if any affect this could have 

on the depth to groundwater (Johnson, written 

communication 8 December 2014). Figure 74

shows the location of select monitoring wells, 

and general direction of groundwater flow. This 

flow is generally from the uplands areas towards 

the floodplain area. On the west side of the river 

the groundwater flow is towards the northeast 

and on the east side of the river the groundwater 

flows in a northwesterly direction (Woessner 

and Johnson 2001). 

For the Upper Clark Fork, when not affected by irrigation, groundwater levels are generally highest 

during the spring runoff and then gradually decline until the next spring (Nimick 1993). Groundwater 

Figure 74. Groundwater dynamics at GRKO (GRKO 

GIS 2007).
239 

will also show short-term rises in response to rainfall or snowmelt events (Nimick 1993). This 

general pattern can be seen at GRKO in Figure 75. 

Figure 75. Depth to groundwater for selected monitoring wells at GRKO (Reproduced from WET 2012).

Threats and Stressor Factors 

GRKO staff identified several potential threats and stressors to the surface water and groundwater 

resources in the park. These include human alteration to the river, dewatering, climate change, and 

drought. 

Climate change is a growing concern and threat to steam hydrology at GRKO as well as across the 

western United States. Changes to stream hydrology in the western United States have been well 

documented and these changes are expected to continue (Barnett et al. 2008). Projected increases in 

temperature will cause earlier snow melt in the upper elevations, resulting in earlier peak flows and 

reduced summer flows (Dettinger et al. 2004). 

Periods of drought can threaten the supplies of water for irrigated crops and community drinking 

water supplies (MT DES 2013). Rangeland and irrigated agricultural lands do not exhibit the effects 

of drought as quickly as non-irrigated cultivated cropland (MT DES 2013). Drought conditions 

diminish groundwater resources which can lead to reduced pumping capacity, dry wells and 
240 

degraded water quality (MT DES 2013). A rare spring drought occurred in 1992 and, coupled with 

early irrigation withdrawals, resulted in a rapid decrease in stream discharge and some of the lowest 

flows on record for the months of May and June (Hornberger et al. 1997). 

The Palmer Hydrological Drought Index (PHDI) can be used to show hydrological (long-term 

cumulative) drought and wet conditions, as it more accurately reflects groundwater conditions and 

surface water conditions (NCDC 2013). Figure 76 shows the PHDI for the state of Montana. The 

state has experienced severe and extreme drought between 10% and 20% of the time over the last 

100 years (MT DES 2013). Drought conditions can result in low water levels, causing changes in 

water quality, temperature and sediment loading.

Figure 76. Palmer Hydrologic Drought Index (PHDI) for Montana. Graph was created and downloaded 

from time series data from the National Climatic Data Center (Reproduced from NCDC 2014). 

The supply of ground and surface water can be affected by several factors. These include evaporation 

of surface water, timing and degree of precipitation events, ground water discharge to streams, and 

from withdrawals from pumping (MT DNRC 2004). The largest consumer of groundwater within the 

Upper Clark Fork basin is public water supply and irrigation. However, the bulk of water used in 

irrigation comes from surface water diversions (MT DNRC 2004). Groundwater is growing in 

importance as the source of a potable water supply. One study showed that the municipal and 

residential population grew in the Upper Clark Fork basin on the average about 1% a year during a 

ten-year period prior to 2004 (MT DNRC 2004). At this rate, the Upper Clark Fork will have a 

population of almost 68,000 by the year 2020. At the water use rates exhibited during 2004, this 

would translate into a daily groundwater flow rate of approximately 0.1 cms (5 cfs) (MT DNRC 
241 

2004). Currently, the basin contains approximately 48,970 irrigated ha (121,000 ac) and the projected 

demand for future water use by irrigation depends on two factors (MT DNRC 2004). The first being 

the amount of irrigable lands remaining in the basin and secondly the ability to store surface supplies 

or to find hydrologically unconnected groundwater (MT DNRC 2004). 

Alterations in flow will affect the rate of channel migration and stream bank erosion in a dynamic 

system like the Clark Fork River (Moore et al. 2002, Parmar 2008). Studies conducted at GRKO 

have shown that the erosion and deposition rates are approximately balanced, resulting in no net 

measurable loss of land (Moore et al. 2002). Increased flow rates due to anthropogenic disturbances 

(or precipitation) upstream of GRKO have the potential to disrupt this balance (Moore et al. 2002). 

Efforts are in place to minimize anthropogenic impacts to river flow (EPA 2004). Powell County 

regulates the land use and building activities within the 100 year floodplain (EPA 2004). 

Construction and land use changes within the floodplain can result in increased river flow from 

runoff. Also the stream bank and riparian re-vegetation components of the Clark Fork Superfund Site 

remediation plan address the erosional concerns associated with the slickens deposits (EPA 2004). 

The remediation/restoration efforts for the Clark Fork Superfund Site started in 2012, with the 

portion within GRKO slated to begin in 2015 (Johnson, written communication, 8 December 2014). 

Data Needs/Gaps

Data or studies describing groundwater resources in the Upper Clark Fork basin are available for 

only select locations (MT DNRC 2004). When it does exist, it tends to have limited information on 

sustainable yields, flow patterns, influences by existing users and other information that would aid in 

the development of planning and management programs (MT DNRC 2004). More scientific research 

is needed to understand the interaction between surface water and groundwater in order to evaluate 

water availability for new wells and the potential impacts of improving irrigation efficiency (MT 

DNRC 2004). Currently there is a study being conducted by Montana Tech to determine surface and 

groundwater flow connections in the area of GRKO’s historic buildings (Smith, written 

communication, 5 January 2014). Also, it is unclear whether climate change is having a measurable 

impact on the Clark Fork in GRKO (Schweiger et al. 2014). In general in the northern and central 

Rockies, streamflow has shifted toward earlier peak runoff, which has been attributed to more 

precipitation falling as rain rather than snow and earlier snowmelt (Mote et al. 2005, Knowles et al. 

2006). The midpoint of annual discharge and the date of highest flows at GRKO are trending later in 

the year than during the historic period of record (Schweiger et al. 2014). This would suggest that the 

hydrograph is shifting forward in time due to delayed runoff. There is also a suggestion that the 

GRKO hydrograph is becoming more variable. More data is needed in order to determine if this shift 

is due to climate change (Schweiger et al. 2014). Additional data on the other sources of irrigation 

inputs would be necessary to accurately determine a condition level for the irrigation input measure. 
242 

Overall Condition 

Stream Discharge 

The measure of stream discharge was assigned a Significance Level of 3, as it is a fundamental 

hydrologic variable which has significant influence on many river conditions. The timing and 

amount of stream flow, coupled with its interaction with other elements of river habitat, is a critical

component and determinant of the condition of rivers (Schweiger et al. 2014). Data from the USGS 

gaging station at Deer Lodge shows that over the period of record there has been a slight decline in 

discharge. Also, the timing of peak flow has tended to be later in the year than the historic average. 

Due to these factors, a Condition Level of 1 was assigned. 

Irrigation Flow Inputs

Irrigation flow input was assigned a Significance Level of 3. GRKO has multiple water-right claims 

to divert surface water from the Clark Fork River and its tributaries for flood irrigation (John Milner 

Associates et al. 2004). Accurate flow records were not available for all these sources of diversion. 

Due to this, a Condition Level was not assigned.

Timing and Amount of Precipitation

The Significance Level for the precipitation measure was a 3. No significant trends can be seen in the 

data from the weather station near the park. The Condition Level for this measure is 0, indicating no 

concern. 

Depth to Groundwater 

The Significance Level for depth to groundwater was a 3. Limited data is available on the depth to 

groundwater at GRKO. There is also limited data on what constitutes a sustainable yield for 

groundwater (MT DNRC 2004). Due to these factors, a Condition Level was not assigned. 

Weighted Condition Score 

A Weighted Condition Score was not calculated for hydrology at GRKO, since condition could not 

be assigned for two of the four measures. It is not appropriate to assign trends in the overall condition 

of the hydrologic regime of the Clark Fork River at GRKO based solely on the one available data 

source. The only measure that exhibited any trend was total stream discharge.
243 

Hydrology 

Measures Significance 

Level

Condition 

Level WCS = N/A 

Stream Discharge 3 1 

Irrigation Flow Inputs 3 n/a

Timing and Amount of 

Precipitation 3 0 

Depth to Groundwater 3 n/a

4.12.6 Sources of Expertise

Jeffery Johnson, GRKO CERCLA Project Manager

Jason Smith, GRKO Natural Resource Specialist
244 

4.12.7 Literature Cited 

Barnett, T. P., D. W. Pierce, H. G. Hidalgo, C. Bonfils, B. D. Santer, T. Das, G. Bala, A. W. Wood, 

T. Nozawa, A. A. Mirin, and others. 2008. Human-induced changes in the hydrology of the 

western United States. Science 319:1080-1083. 

Dettinger, M., K. Redmond, and D. Cayan. 2004. Winter orographic precipitation ratios in the Sierra 

Nevada large-scale atmospheric circulations and hydrologic consequences. Journal of 

Hydrometeorology 5:1102-1116. 

Dodge, K. A., M. I. Hornberger, and E. V. Axtmann. 1996. Water-quality, bed-sediment, and 

biological data (October 1994 through September 1995) and statistical summaries of data for 

streams in the Upper Clark Fork Basin, Montana. USGS Open-File Report 96-432. U.S. 

Geological Survey, Helena, Montana. 

Environmental Protection Agency (EPA). 2004. Clark Fork River Operable Unit of the Milltown 

Reservoir/Clark Fork Superfund Site, Record of Decision Part 2: Decision summary. U.S. 

Environmental Protection Agency, Helena, Montana. 

Grant-Kohrs Ranch NHS GIS Program (GRKO GIS). 2007. Groundwater monitoring wells at GrantKohrs Ranch National Historic Site, Montana. National Park Service, Deer Lodge, Montana. 

Gonzalez, P. 2014. Climate trends, Grant-Kohrs Ranch National Historic Site, Montana. Climate 

change trends. Published Report-2217692. National Park Service Climate Change Response 

Program, Washington, D.C. 

Hornberger, M. I., J. H. Lambing, S. N. Luoma, and E. V. Axtmann. 1997. Spatial and temporal 

trends of trace metals in surface water, bed sediment, and biota of the Upper Clark Fork Basin, 

Montana, 1985-95. USGS Open-File Report 97-669. U.S. Geological Survey, Menlo Park, 

California. 

KirK Engineering and Natural Resources, Inc. 2010. Cottonwood Creek flow monitoring and fish 

barrier study. Watershed Restoration Coalition of the Upper Clark Fork, Deer Lodge, Montana. 

Knowles, N., M. D. Dettinger, and D. R. Cayan. 2006. Trends in snowfall versus rainfall in the 

western United States. Journal of Climate 19:4545-4559. 

Montana Disaster and Emergency Services (MT DES). 2013 State of Montana multi-hazard 

mitigation plan and statewide hazard assessment: 2013 update. 

http://letsmitigatemontana.com/draft-pdm-plan/ (accessed 10 November 2014). 

Montana Department of Environmental Quality (MT DEQ). 2006. Surface water quality standards 

and procedures. Chapter 30, subchapter 6 in Administrative rules of Montana: Environmental 

quality. Montana Department of Environmental Quality, Helena, Montana. 

Montana Department of Environmental Quality (MT DEQ). 2012. Montana 2012 final water quality 

integrated report. Montana Department of Environmental Quality, Helena, Montana. 
245 

Montana Department of Environmental Quality (MT DEQ). 2014a. 2014 water quality information: 

Clark Fork River, Powell County. 

https://svc.mt.gov/deq/dst/#/app/cwaic/report/cycle/2014/auid/MT76G001_030 (accessed 23 

February 2015). 

Montana Department of Environmental Quality (MT DEQ). 2014b. Climate change and water. 

http://deq.mt.gov/ClimateChange/NaturalResources/Water/WaterUses.mcpx (accessed 8 

November 2014). 

Montana Department of Natural Resources and Conservation, Water Resources Division (MT 

DNRC). 2004. Clark Fork River Basin water management plan. 

http://dnrc.mt.gov/wrd/water_mgmt/clarkforkbasin_taskforce/water_mgmt_plan.asp (accessed 12 

November 2014). 

Montana Department of Natural Resources and Conservation, Water Rights Bureau (MT WRB). 

2014. Water rights query system. http://nris.mt.gov/dnrc/waterrights/default.aspx (accessed 8

November 2014). 

Moore, J. N., and W. W. Woessner. 2001. Geologic, soil water and groundwater report - 2000 Grant 

Kohrs Ranch National Historic Site. National Park Service, Deer Lodge, Montana. 

Moore, J. N., B. Swanson, and C. Wheeler. 2002. Geochemistry and fluvial geomorphology report - 

A draft report to the Grant-Kohrs Ranch National Historic Site. National Park Service, Deer 

Lodge, Montana. 

Mote, P. W., A. F. Hamlet, M. P. Clark, and D. P. Lettenmaier. 2005. Declining mountain snowpack 

in western North America. Bulletin of the American Meteorological Society 86:39-49. 

National Climatic Data Center (NCDC). 2013. U.S. Palmer Drought Indices. 

http://www.ncdc.noaa.gov/oa/climate/research/prelim/drought/palmer.html (accessed 4 

December 2014). 

National Climatic Data Center (NCDC). 2014. Statistical weather and climate information. 

http://www.ncdc.noaa.gov/oa/ncdc.html (accessed 10 November 2014). 

National Park Service (NPS). 2012. 2012 GRKO Westside ditch 2 ft parshall flume measurements. 

Unpublished data received from Jason Smith, 19 September 2014. 

Nimick, D. A. 1993 Hydrology and water chemistry of shallow aquifers along the Upper Clark Fork, 

Western Montana. USGS Water Resources Investigations Report 93-4052. Montana Bureau of 

Mines and Geology, Helena, Montana.

Parmar, N. 2008. Bank erosion and channel migration of the Clark Fork River at Grant-Kohrs Ranch 

N.H.S., Western Montana. Thesis. University of Montana, Missoula, Montana. 
246 

Schweiger, E. W., L. O’Gan, D. Shorrock, and M. Britten. 2014. Stream ecological integrity at 

Grant-Kohrs National Historic Site: Rocky Mountain Inventory and Monitoring Network 2008-

2010 stream monitoring report. Natural Resources Technical Report NPS/ROMN/NRTR - 

2014/881. National Park Service, Fort Collins, Colorado. 

Thornberry- Ehrlich, T. 2007. Grant- Kohrs Ranch National Historic Site geologic resource 

evaluation report. Natural Resource Report NPS/NRPC/GRD/NRR—2007/004. National 

Park Service, Denver, Colorado. 

United States Geological Survey (USGS). 2014a. The National Map small-scale collection. 

http://nationalmap.gov/small_scale/ (accessed 10 November 2014). 

U.S. Geological Survey (USGS). 2014b. National Water Information System: Web Interface – USGS 

12324200 Clark Fork at Deer Lodge MT. 

http://waterdata.usgs.gov/mt/nwis/inventory?search_site_no=12324200 (accessed 12 November 

2014). 

Water and Environmental Technologies (WET). 2012. Groundwater monitoring report - Deer Lodge 

effluent irrigation project, 2012 irrigation season. Water and Environmental Technologies, Butte, 

Montana. 

Woessner, W. W., and M. M. Johnson. 2001. Water resources characterization report 2000 and 2001 

field seasons - Grant-Kohrs Ranch National Historic Site. National Park Service, Deer Lodge, 

Montana. 
247 

4.13 Soils

4.13.1 Description

Soils are a vital part of the ecosystem, supporting plant growth, cycling nutrients, providing habitat 

for a variety of micro- and macro-organisms, and influencing water retention, percolation, and 

purification (NPS 2010). Soil conditions can provide insight into ecosystem processes and 

productivity and can determine vegetative composition and structure; as a result, the ROMN 

recognized surface soils as an indicator of terrestrial ecosystem integrity (Manier et al. 2011). Soils 

are particularly important in a ranch setting, as they provide the nutrients required by crops and 

forage plants. 

The soils at GRKO are derived 

from alluvium (loose sediments 

deposited by water flow) and 

range from deep, coarse loams 

along the Clark Fork River, to 

shallow, poorly developed soils 

in the upland grasslands (NPS 

2013a, Rice et al. 2012). For 

over a century, the ranch’s 

riparian area has been subjected 

to metal contaminants washing 

downstream from the historic 

mining districts around 

Anaconda and Butte, MT. Many 

of these wastes were washed 

downstream along the Clark 

Fork River floodplain by large 

floods in the early 1900s 

(Kapustka 2002, Ramsey et al. 

2005a). Sediments deposited 

during these floods raised the 

level of the floodplain by a 

meter or more (Ramsey et al. 

2005a). Mining wastes were 

unevenly distributed and further 

agitated by subsequent floods 

and channel migration, leading 

to extensive spatial variation in contaminant concentration within the soils (Ramsey et al. 2005a). 

Small patches in the GRKO riparian area, called “slickens” (Figure 77), are so contaminated that they 

are devoid of vegetation and contain surface accumulations of heavy metal salts (Ramsey et al. 

2005a; Photo 43). The primary soil contaminants from mining waste include arsenic, cadmium, 

copper, lead, and zinc (Kapustka 2002). 

Figure 77. The Clark Fork floodplain and slickens areas at 

GRKO.
248 

Photo 43. An unvegetated slickens area along the Clark Fork in GRKO; note the white crust of heavy 

metals salts (Photo by Sarah Gardner, SMUMN GSS 2013).

4.13.2 Measures

• Soil chemistry

• Soil aggregate stability

• Bulk density 

• Soil microbial composition and respiration 

Soil Chemistry

Measures of soil chemistry that will be used in this assessment are pH, organic matter content, and 

nutrient levels. Soil pH influences the availability of nutrients to plant life. A pH below 7 indicates 

acidity; acidic soils can limit nutrient availability (Manier et al. 2011). Conversely, low pH levels can 

make toxic metals more available for plant uptake (Ramsey et al. 2005a). Soil organic matter is the 

percent of the soil that consists of dead plant and animal tissues in varying stages of decomposition 

(Manier et al. 2011). Organic matter content affects nutrient availability, soil structure (e.g., 

stability), pH, and water holding capacity (Sollins et al. 1999). High levels of organic matter, in 

combination with a near-neutral pH, can also reduce the bioavailability of toxic metals, reducing 

harmful effects to plants (Ramsey et al. 2005a). 

Nutrient levels in the soil are directly linked to productivity (e.g., plant biomass) and can be an 

indicator of ecosystem processes such as nutrient cycling and decomposition (Manier et al. 2011). 

Three of the most important nutrients, particularly in an agricultural setting, are nitrogen (N), 

phosphorous (P), and potassium (K). These nutrients are critical for plant growth, such as crop and 
249 

forage production. Nutrient levels can be maintained in the soil by incorporating animal manure, 

“green manure” (plant material intentionally grown to be returned to and enrich the soil), or other 

organic wastes (e.g., straw, crop residue, wood ash) (Olson and Leinard 2013). Legumes such as 

alfalfa and clover fix atmospheric nitrogen, converting it to a form that is usable by other plants. 

While most Montana soils are naturally high in potassium (with the exception of sandy soils and 

those high in organic matter), they are typically low in available phosphorous (Olson and Leinard 

2013). 

Soil Aggregate Stability

Soil aggregate stability estimates soil integrity, in terms of its ability to bind into cohesive units 

(Shorrock et al. 2010). More stable or cohesive soils are generally more resistant to erosion (Manier 

et al. 2011). However, if stability is extremely high, it may indicate soil compaction, which can 

negatively impact water infiltration and plant growth. Soil stability is strongly influenced by organic 

matter, which binds the soil particles and also varies with soil texture (Shorrock et al. 2010). As a 

result, only soils of similar textures (i.e., similar ratios of sand, silt, and clay) can be compared for 

stability. At GRKO, all soils are similar enough in texture that stability estimates are comparable 

throughout the park (Shorrock et al. 2010). 

Bulk Density 

Bulk density, a measure of soil mass per volume, is an indicator of soil structure or strength (Manier 

et al. 2011). Bulk densities are influenced by soil texture and organic matter content, and range from 

0.6 to 1.8 g/cc (Manier et al. 2011). Soils with high silt and clay content (i.e., smaller particles) 

typically show higher densities than coarser textured soils. High densities often suggest soil 

compaction, which impacts plant growth and reduces the porosity required for the transport of water 

and gases (e.g., oxygen). In finer-textured soils, a bulk density above 1.4 g/cc may limit root 

penetration and water storage (NPS 2013a). 

Soil Microbial Composition and Respiration 

Soil microbes play an important role in ecological processes such as organic matter decomposition 

and nutrient cycling (e.g., nitrogen and carbon) (Menta 2012). Soil respiration is a measure of CO2

production by these microorganisms during their normal activities and can indicate soil health 

(Ramsey et al. 2005a). Soil activity plays a key role in nutrient availability, which in turn influences 

plant growth and overall productivity (Gannon and Rillig 2002). When soil microbe communities are 

altered and/or respiration is low, nutrients may accumulate in forms that are unavailable to plant life. 

Soil microbial respiration is influenced by moisture, temperature, nutrient availability, and heavy 

metal contamination (Gannon and Rillig 2002, Ramsey et al. 2005a). 

4.13.3 Reference Conditions/Values

Reference conditions for soils can vary depending on the desired use of the land (e.g., crop 

production, grazing, recreation, etc.). Since GRKO is a working ranch, the NRCA project team 

looked for values recommended for agriculture or crop production, if available. In the case of pH, the 

suitable range for most crops is between 6 and 7.5 (Dinkins and Jones 2013). For organic matter 

content, 2% is considered normal for Montana soils (Dinkins and Jones 2013). With regard to 

nutrients, recommended nitrogen levels vary with crop yield goals. Most hayfields at GRKO have a 
250 

yield goal of 2 tons/acre (4.5 metric tons/ha). With a primary crop of grass, the recommended 

nitrogen level for this yield is 25 mg/kg (50 lbs/ac) (Jacobsen et al. 2005). Phosphorus and potassium 

recommendations are not dependent on yield goals; optimal levels are above 16 ppm (1 ppm = 1 

mg/kg) for phosphorus, and above 250 ppm for potassium (although levels above 800 ppm can be 

toxic) (Dinkins and Jones 2013). For soil aggregate stability, the reference condition will be a 

stability class range of 4.5-5.5 (see current condition section for explanation of stability classes). 

Suitable bulk densities vary by soil texture, with finer soils experiencing negative impacts at lower 

densities. Since very little soil at GRKO is finer than a silty clay loam (NPS 2013a), the reference 

condition for bulk density will be <1.5 g/cm3

, which is considered the density at which root 

restriction would occur in silty clay loams (NRCS 2001). No reference conditions have been 

established for soil microbial composition and respiration. 

4.13.4 Data and Methods

A soil survey and map for the park were completed by the NRCS from 1989-1991 (NPS 2013a, b; 

Figure 78). Data gathered included soil pH, organic matter content, and moist bulk density. 
251 

Figure 78. GRKO soil map (above) and description of soil map units (NPS 2013b).
252 

The ROMN started gathering soils data at GRKO in 2006 as part of their vegetation and soils 

monitoring program (Manier et al. 2011). The goals of this program, regarding soils, are to 

Determine the status and trend in soil condition in grassland, shrubland, and woodlands of 

each park based on measures of 1) dynamic properties such as soil stability, extent of nonvegetated soils, and erosion and 2) inherent properties including physical texture, 

composition and soil chemistry (Manier et al. 2011, p. 11). 

Data gathered includes chemical properties (e.g., pH, nutrients, organic matter) and physical 

properties such as bulk density and soil aggregate stability (Manier et al. 2011). Twentycentimeter-deep soil samples collected in the field were sent to a lab for analysis of all parameters 

with the exception of soil aggregate stability, which was measured in the field according to 

methods outlined by Herrick et al. (2005). This test involves placing a fragment of soil (ped) into 

a sieve and submerging it in water for a period of time to determine how long it holds its structure. 

Units that remain intact for longer periods of time are considered more stable and are assigned to 

a higher stability class (Manier et al. 2011). Stability classes and descriptions are described in 

Table 65 below. Sampling and analysis protocols for other parameters are described in further 

detail in Shorrock et al. (2010) and Manier et al. (2011). Data from 2006-2012 (ROMN 2006-

2012) were downloaded from the NPS Integrated Resource Management Applications (IRMA) 

portal at https://irma.nps.gov/App/.

Table 65. Soil stability classes according to methods described by Herrick et al. (2005) (adapted from 

Manier et al. 2011).

Stability class Criteria for classification

1 50% of structure lost within 5 seconds of immersion (melts and falls through sieve)

2 50% of structural integrity lost 5-30 seconds after immersion

3 50% of structural integrity lost 30 seconds – 5 minutes after immersion, or <10% of soil 

remains after 5 dipping cycles

4 10-25% of soil remains after 5 dipping cycles

5 25-75% of soil remains after 5 dipping cycles

6 75-100% of soil remains after 5 dipping cycles

Additional information on soil chemistry was obtained from soil test reports; tests were conducted 

by Agvise Laboratories of North Dakota on soil samples collected by GRKO staff from various 

hayfields on the ranch (Agvise 2008, 2010, 2013). Samples were submitted from eight fields in 

2008, one field in 2010, and nine fields in 2013. Parameters analyzed include nutrients (nitrate, 

phosphorus, and potassium), organic matter content, and pH. 

Soil microbial composition and respiration were studied at GRKO in 2000 and 2001 by Gannon 

and Rillig (2002). Fifteen sites were sampled in 2000 and 30 in 2001, although three sites had to 

be excluded in 2001 due to flooding during part or all of the study season (Gannon and Rillig 

2002). Differences in microbial composition were estimated using phospholipid fatty acid (PLFA) 

analysis. PLFA structure varies between groups of prokaryote and eukaryote microorganisms; a 

component analysis of fatty acid concentrations in a soil sample can detect changes in relative 

abundance within the microbial community (Ramsey et al. 2005b). Additional analyses of these 
253 

data were conducted by Ramsey et al. (2005a, b). Rice and Ray (1984) focused primarily on metal 

contamination of soils but briefly addressed soil microbe activity. 

4.13.5 Current Condition and Trend

Soil Chemistry

pH and Organic Matter 

Soils in western Montana tend to be neutral to slightly acidic (Dinkins and Jones 2013). Over the past 

decade, studies at GRKO have found soil pH values ranging from 4.2 to 8.8 (Table 66). Lower 

values, indicating more acidic soils, are typically from highly contaminated sites where heavy metals 

have influenced pH (Gannon and Rillig 2002). Tetratech (2012) obtained two samples with a pH 

below 4, both from depths of more than 45 cm (18 in). Over the 4 years of data collection by ROMN, 

mean soil pH has been 6.9, which is nearly neutral and falls within the reference range of 6.0-7.5 

chosen for this assessment.

Table 66. pH measurements from GRKO.

# of samples Range Mean

Moore and Woessner (2001) 141 4.3-8.8 --

Gannon and Rillig (2002) 40 4.2-8.3 6.7

Hayfield soil tests 

 (Agvise 2008, 2010, 2013) 18 6.6-8 7.4

Tetratech (2012) -- 3.3-9.2 --

NPS (2013) -- 4.5-8.4* --

ROMN 2009 24 5.6-8.1 6.9

ROMN 2010 18 5.7-7.7 6.6

ROMN 2011 24 6.3-7.7 6.9

ROMN 2012 24 6.5-7.9 7.2

ROMN Overall 90 5.6-8.1 6.9

*This range is for only the top horizon of each soil type, typically 15-23 cm (6-9 in).

Moore and Woessner (2001) found that lower pH readings are more common in the riparian area, 

where higher levels of metal contamination from mine wastes are present (Figure 79). 
254 

Figure 79. Map of soil pH in 2000 by sampling location (data from Moore and Woessner 2001).

Organic matter content of soils in GRKO is generally above the 2% that is considered average for 

Montana. Over 4 years of sampling by the ROMN, organic matter content has ranged from 0.9%-

23.8%, with a mean of 7.6% (Table 67). According to the soil survey (NPS 2013a), the surface layer 

of two soil types found in the park (Bohnly in map unit 109 and Gregson in map unit 444) contains 

28-70% organic matter.
255 

Table 67. Organic matter content measurements from GRKO.

# of samples Range Mean

Gannon and Rillig (2002) 55 0.9-17.7% 6.6%

Hayfield soil tests

 (Agvise 2008, 2010, 2013) 17 4.9-17.2% 8.8%

NPS (2013)* -- 1-70% --

ROMN 2009 24 2.6-21.9% 8.2%

ROMN 2010 18 1.5-14.5% 5.6%

ROMN 2011 24 3.1-18.7% 6.8%

ROMN 2012 24 0.9-23.8% 9.7%

ROMN Overall 90 0.9-23.8% 7.6%

*This range is for only the top horizon of each soil type, typically 15-23 cm (6-9 in).

Nutrients (N, P, K) 

Soil nutrient levels are highly 

variable throughout GRKO. 

Samples from several of the 

park’s hayfields (Figure 80) 

showed considerable variation, 

both between fields and over 

time (Figure 81). West fields 3 

and 4, near the Clark Fork, 

generally yielded the highest 

nutrient levels while upland 

fields tended to have lower 

nutrient levels.

Figure 80. GRKO hayfields with soil sample test results.
256 

Figure 81. Soil nutrient levels from sampled GRKO hayfields in 2008 and 2013 (Agvise 2008, 2013). All 

samples were taken from the top 15 cm (6 in) of the soil. Note that Upper and Lower Taylor were sampled 

as one unit in 2008 and separately in 2013.

0

10

20

30

40

50

60

Taylor

(upper &

lower)

Upper

Taylor

Lower

Taylor

West

F-1

West

F-2

West

F-3

West

F-4

Little

Gulch

Big

Gulch

Stuart

mg/kg

Nitrogen

2008

2013

0

5

10

15

20

25

30

35

40

Taylor

(upper &

lower)

Upper

Taylor

Lower

Taylor

West

F-1

West

F-2

West

F-3

West

F-4

Little

Gulch

Big

Gulch

Stuart

mg/kg

Phosphorus

2008

2013

0

100

200

300

400

500

600

700

800

Taylor

(upper &

lower)

Upper

Taylor

Lower

Taylor

West

F-1

West

F-2

West

F-3

West

F-4

Little

Gulch

Big

Gulch

Stuart

mg/kg

Potassium

2008

2013
257 

During ROMN sampling, which occurred throughout the park, nitrogen ranged from 1.2- 286.8 

mg/kg, with a mean of 44.6 mg/kg (Table 68). The range within just the sampled hayfields was 

smaller at 2.5-27.5 mg/kg with a mean of 9.3 mg/kg. The recommended nitrogen level, given 

GRKO’s crop yield goals, is 25 mg/kg. However, lower levels may be acceptable in areas that are not 

managed for crops. As with most Montana soils, GRKO samples were low in phosphorus and high in 

potassium. Mean annual phosphorus levels were variable, with 2 years above the recommended 16 

mg/kg (or ppm) and 2 years below; the mean over all 4 years of sampling was below 16 mg/kg 

(Table 68). Mean potassium levels were above the recommended 250 mg/kg in all but one year of 

ROMN sampling. 

Table 68. Nutrient measurements from GRKO. Unless otherwise listed, measurements are in mg/kg.

Nitrogen as NO3 (mg/kg) Phosphorus (mg/kg) Potassium(mg/kg)

Range Mean Range Mean Range Mean

Hayfield soil tests

(Agvise 2008, 

2010, 2013)

5-55 lb/ac

(~2.5-27.5 mg/kg)

18.5 lb/ac 

(~9.3 mg/kg) 8-34 18.4 106-730 382.6

ROMN 2009 3.3-148.2 46.2 0.07-1.28 0.30 224.6-874.8 452.1

ROMN 2010 16.4-286.8 99.8 8.6-32.4 16.7 204.4-636.4 411.8

ROMN 2011 1.2-100.4 14.4 3.7-16.2 8.9 110.1-807.0 380.2

ROMN 2012 2.3-55.6 18.1 6.0-60.0 20.1 63.8-706.5 226.2

ROMN Overall 1.2-286.8 44.6 0.07-60 11.5 63.8-874.8 367.6

Shorrock et al. (2010) noted that nutrient levels were considerably higher at two plots in the GRKO 

riparian area. Floodplain soils are often nutrient rich due to their location in a depositional 

environmental (i.e., river flooding can deposit new, nutrient rich sediments and organic matter) 

(Shorrock et al. 2010). 

Soil Aggregate Stability

The ROMN protocol samples soil aggregate stability at two depths: surface (top 1 cm) and 

subsurface (2 cm deep) (Manier et al. 2011). Most soils at GRKO are fairly stable and not 

particularly vulnerable to erosion (Shorrock et al. 2010). Over 7 years of sampling, mean surface 

stability ranged from 3.9 to 5.3 with a mean of 4.7 (Table 69). Subsurface stability was slightly lower 

with a range of 3.3 to 4.9 and a mean of 4.3. The surface stability mean falls within the selected 

reference condition range of 4.5-5.5, while the subsurface score is just below this range. Given that 

subsurface soils are less exposed and therefore less vulnerable to erosion, this lower value is not a 

particular concern. 
258 

Table 69. Soil aggregate stability measurements from GRKO.

# of samples Mean - Surface Mean - Subsurface

ROMN 2006 191 4.1 3.6

ROMN 2007 91 4.6 4.9

ROMN 2008 45 3.9 3.3

ROMN 2009 91 4.6 4.9

ROMN 2010 150 5.3 4.6

ROMN 2011 150 5.0 4.2

ROMN 2012 180 5.1 4.6

Overall 898 4.7 4.3

The ROMN has also noticed differences in soil stability depending on ground cover (vegetated vs. 

bare ground) (Shorrock et al. 2010). In 2009, surface soil stability at sites with canopy cover was one 

point higher than at sites with no canopy cover. Subsurface soil stability was more than 1.5 points 

higher at sites with canopy cover (Shorrock et al. 2010). 

Bulk Density 

ROMN sampling has not indicated that any soils at GRKO are compacted to the point of negatively 

impacting the vegetation community (Shorrock et al. 2010). During 4 years of study, bulk densities 

have ranged from 0.68 to 1.66 g/cm3

 with a mean of 1.1 g/cm3 (Table 70). All annual means were 

within the selected reference condition of <1.5 g/cm3

. 

Table 70. Bulk density measurements (g/cm3) from GRKO.

# of samples Range (g/cm3) Mean (g/cm3)

NPS (2013)* 1.1-1.55 --

ROMN 2009 24 0.79-1.66 1.15

ROMN 2010 17 0.94-1.43 1.13

ROMN 2011 24 1.01-1.42 1.21

ROMN 2012 24 0.68-1.27 1.01

ROMN Overall 89 0.68-1.66 1.1

*This range is for only the top horizon of each soil type, typically 15-23 cm (6-9 in).

Soil Microbial Composition and Respiration 

The earliest study to explore soil microbe activity at GRKO was Ray and Rice (1984). Bioassays 

were performed on three soil samples from a slickens area and three samples from an adjacent 

vegetated area. Tests showed that soil microbial enzyme activity was reduced by 85% in the slickens 

areas, suggesting that heavy metal contamination depressed soil microbial activity (Rice and Ray 

1984). 

Gannon and Rillig (2002) conducted a more thorough study of soil microbial composition and 

respiration at GRKO in 2000-2001. Measured in micromoles (μM) of CO2 per square meter per 

second, respiration over the 2 years ranged from 0.15 to 12.27 μM/m2

/s with a mean of 3.28 μM/m2/s

(Table 71). Respiration rates declined from September to November in 2000, demonstrating that 

temperature influences microbial activity.
259 

Table 71. Microbial respiration measurements (μM/m2/s) from plots at GRKO (Gannon and Rillig 2002).

Date Sample plots Range Mean

2000 15

 14 September 0.30-12.27 5.23

 26 September 0.20-5.94 2.32

 10 October 0.15-4.09 1.97

 2 November 0.20-2.54 0.81

2001 22

 7 June 0.32-8.41 3.43

 22 June 1.60-9.21 4.57

 2 July 1.00-10.28 4.67

 24 September 0.36-7.89 3.27

Overall 0.15-12.27 3.28

Gannon and Rillig (2002) found connections between microbial respiration and pH, organic matter, 

soil moisture, and metal contamination. Sites with the highest respiration typically had high organic 

matter content and low heavy metal levels (Gannon and Rillig 2002). Heavy metal contamination 

often lowers soil pH levels, and as a result, respiration generally declines with lower pH (i.e., more 

acidic soils). However, the relationship between metal contamination and respiration was not linear; 

rather, heavy metals appeared to limit the maximum level of respiration that could be achieved. In 

other words, 

While at every metal concentration a number of environmental factors are acting upon 

respiration rates as measured in the field, the potential to achieve a high rate clearly decreases 

with increased metal index. This means that with increasing metal concentration, metals 

become a more and more dominant effect with respect to determining respiration (Gannon 

and Rillig 2002, p. 26). 

Gannon and Rillig (2002) also determined, through PLFA analysis, that soil microbial community 

composition is significantly altered by heavy metal contamination. 

Ramsey et al. (2005b) further analyzed Gannon and Rillig’s (2002) microbial community 

composition data from September-October 2000. In September, microbial PLFAs ranged from 50- 

362 nmol/g with a mean of 156 362 nmol/g. October PLFAs yielded a mean of 141 nmol/g with a 

range of 60-226 nmol/g (Ramsey et al. 2005b). Data showed that high metal contamination levels 

caused a decline in both microbial biomass and microbial community richness (as estimated by 

PLFA peak number) (Figure 82). As metal levels increased, the microbial community appeared to 

shift from primarily Gram-negative bacteria and Actinomycetes to Gram-positive bacteria and fungi. 

However, these microbial declines may not be a direct effect of metal contamination, but rather due 

to low plant productivity and, therefore, low organic material inputs in contaminated areas (Ramsey 

et al. 2005b). 
260 

Figure 82. Soil microbial biomass (left) and community richness (right) at GRKO both decline as metal 

contamination increases (from Ramsey et al. 2005b).

Threats and Stressor Factors 

Threats to the soils of GRKO include erosion, contamination from historic mining activity, 

remediation activities, improper grazing and /or irrigation, and removal of vegetation (e.g., haying). 

The mining wastes that triggered the Superfund designation in the Upper Clark Fork region are a 

serious concern at GRKO, particularly the heavy metal contamination and associated increases in 

acidity (Thornberry-Ehrlich 2007). Heavy metal contamination not only has the potential to affect the 

health of humans and animals, it also can impact plant health and productivity as well as soil 

microbial community structure and respiration (i.e., nutrient cycling) (Gannon and Rillig 2002, 

Kapustka 2002, Ford and Beyer 2014). Ford and Beyer (2014) established heavy metal criteria levels 

for soils at mining sites to protect wildlife and livestock from adverse exposure (Table 72). Above 

these levels, animals may experience toxic effects. 

Table 72. Wildlife soil criteria for selected wildlife and livestock; metal levels are given in mg/kg (Ford and 

Beyer 2014). 

Arsenic Cadmium Copper Lead Zinc

deer mouse 583 18 601 191 1,437

white-tailed deer 517 15 279 1,627 1,238

mourning dove 134 9 689 133 634

mallard 646 25 1,008 637 1,896

cattle 355 20 281 1,127 1,600

horse 431 21 2,013 142 1,674

Several studies have explored soil metal contamination at GRKO over the past three decades and 

have collected samples with metal levels above the criteria recommended in Table 72. The earliest 

report is Rice and Ray (1984), who sampled soils in the early 1980s. This study found mean arsenic 

levels in the riparian area that exceeded criteria for the mourning dove and mean copper levels that 

exceeded criteria for all species listed above except horses (Table 73). Rice and Ray (1984) also 

illustrates that metal contamination is highest in the riparian area (nearest to the river, which is the 

source of most contaminants), moderate in the pastures/hayfields, and low in the uplands. Moore and 

Woessner (2001) found mean levels of four metals (arsenic, copper, lead, and zinc) that exceeded 

criteria for at least one of the species in Table 72. However, only mean copper levels exceeded 
261 

criteria in the surface soils, where most animals are likely to come in contact with metals (Table 73). 

According to Moore and Woessner (2001), the concentrations of all five metals sampled were greater 

than five times the baseline levels they established for the ranch (see Moore and Woessner 2001 for 

details on baseline calculation). They also found, in agreement with Rice and Ray (1984), that 

contamination levels were highest in the riparian area (see Figure 83), and that the total volume of 

contaminated soil ranged from 293,000 m3

 to 1,660,000 m3 (72.4-410.2 ac) (Moore and Woessner 

2001). 

Table 73. Mean metal contaminant levels in GRKO soils in mg/kg (or ppm, since 1 mg/kg = 1ppm).

Ranges are listed in parentheses, when available. Numbers in red exceed one or more of the criteria in 

Table 72 while numbers in bold exceed criteria for cattle.

Arsenic Cadmium Copper Lead Zinc

Rice and Ray (1984)

 Riparian 176 5.0 1,630

 Meadow (Pastures) 49 2.2 184

 Benches (Uplands) 30 1.6 75

Moore & Woessner (2001)

 Soil profiles 190

(10-1,600)

4.0

(1.0-20)

1,300

(3.0-15,000)

200

(8.0-1,600)

820

(14-4,500)

 Surface soils 46

(13-940)

2.4

(1.0-12)

420

(29-8,400)

77

(16-920)

610

(43-3,200)

Kapustka (2002) 315

(26-880) 

2,343

(120-7,100) 

1,487

(109-2,900) 
262 

Figure 83. Map of soil arsenic concentrations in 2000 by sampling location (data from Moore and 

Woessner 2001). Note that 1 ppm = 1 mg/kg.

Kapustka (2002) found that GRKO soils were toxic to plants (i.e., phytotoxic), in both field plots and 

laboratory studies. As the metal concentrations in the soils increased, total plant biomass and root 

biomass both decreased, with plant mortality occurring in some cases. According to a phytotoxicity 

scoring system established by Kapustka (2002), seven soil samples from GRKO were classified as 

severely phytotoxic, 12 as highly phytotoxic, 24 as moderately or mildly phytotoxic, and only two 

samples as non-phytotoxic. 

More recently, Tetratech (2012) sampled 576 soil pits within GRKO to determine the extent of metal 

contamination (Figure 84). For their purposes, any sample with total contaminants of concern (As, 

Ca, Cu, Pb, Zn) levels above 800 mg/kg were considered contaminated. Tetratech (2012) found that 

approximately 400 of the 576 soil pits contained soils above the 800 mg/kg level. Nearly 150 pits 
263 

contained soils with arsenic levels above the criteria for cattle, while just over 250 pits had lead 

levels above the criteria for mourning doves (Zenaida macroura), deer mice (Peromyscus spp.), and 

horses (Tetratech 2012).

In the coming years, a massive remediation effort will take place along the Clark Fork within GRKO 

boundaries in an effort to remove much of this mining contamination from the site. Areas targeted 

will be those within the 100-year channel migration zone where the cumulative contaminants of 

concern exceed 800 mg/kg and the depth of contamination is 61 cm (24 in) or greater. This will 

involve removing approximately 296,110 m3 (387,297 yd3

) of soil to an average depth of 0.7 m (2.3 

ft) (Johnson, written communication, 17 October 2014). These areas will be backfilled with clean soil 

and “uncontaminated rooting medium” to support native plant revegetation and return the flood plain 

to a 2-year flood level (NPS 2007, p. 3-2). While the removal of this contamination will benefit 

GRKO in the long run, it will cause a temporary disturbance that will heavily impact the park’s soils 

within the remediation zone. 
264 

Figure 84. Tetratech (2012) soil pit locations 

(left). Above are close-up images of two areas 

(highlighted in orange boxes on larger map) 

showing the depth (in inches - red numbers) to 

which contamination exceeds the 800 mg/kg 

level (Tetratech 2012).
265 

Overgrazing can cause soil compaction and the loss of vegetation that protects soils from erosion (da 

Silva et al. 2003, EPA 2003). Soil compaction can also destroy soil microbial biota and degrade their 

habitat (Menta 2012). Trampling along streambanks accelerates bank erosion, which can alter stream 

morphology and increase sedimentation, negatively impacting water quality (Armour et al. 1991). 

The removal of vegetation through hay harvest can negatively impact soils by removing carbon and 

nitrogen from the nutrient pools (Franzluebbers et al. 2000). 

Data Needs/Gaps

Further information is needed on soil microbial community composition and respiration in GRKO in 

order to assess this measure’s condition and any trends over time. Additional research into how the 

soil microbial community and its condition influence other park resources, particularly vegetation, 

would also be useful. Park managers are also interested in how grazing (high intensity, short duration 

grazing, specifically) impacts soil microbes (Smith, written communication, 5 May 2015). Continued 

ROMN monitoring of soil properties will help identify any changes in condition over time that are a 

cause for concern. 

Overall Condition 

Soil Chemistry

The soil chemistry measure was assigned a Significance Level of 3. Most soils within GRKO have 

pH levels within the 6-7.5 range considered suitable for crops. However, some soils in the riparian 

areas that have been contaminated with mining waste show pH readings below 4.5, which can inhibit 

plant growth. Additionally, heavy metal contaminant concentrations exceed levels known to impact 

plants and animals. Soil organic matter levels are above the 2% considered normal for Montana, 

averaging 7.6% over 4 years of ROMN sampling. Soil nutrient levels (N, P, K) are highly variable 

over the ranch. According to ROMN sampling, mean nitrogen levels were well above the 

recommended 25 mg/kg during 2 years of sampling (2009, 2010), but below that level in the 

remaining 2 years (2011, 2012). Several hayfield soil tests also showed nitrogen below the 

recommended level. Typical of Montana soils, some GRKO soils showed phosphorous levels below 

the recommended 16 mg/kg. Potassium levels were more consistently above the recommended 250 

mg/kg, with only one annual mean from ROMN sampling just below this level. In summary, much of 

the soil sampling at GRKO has shown soil chemistry measurements that meet reference conditions. 

However, some areas are cause for concern (e.g., low pH in riparian/slickens areas, low nutrients in 

hayfields). As a result, this measure is assigned a Condition Level of 2, indicating moderate concern. 

Soil Aggregate Stability

This measure was assigned a Significance Level of 3. Most soils at GRKO are considered fairly 

stable (Shorrock et al. 2010). While the overall mean surface soil stability from 7 years of ROMN 

sampling (4.7) falls within the reference condition range of 4.5-5.5, two annual means (2006, 2008) 

and the overall mean for subsurface soil samples (4.3) are below this range. Therefore, soil aggregate 

stability is assigned a Condition Level of 1 (low concern). 

Bulk Density
266 

Bulk density was assigned a Significance Level of 3. Since all annual means and nearly all sample 

ranges from ROMN monitoring over 4 years are within the selected reference condition of <1.5 

g/cm3

, this measure received a Condition Level of 0, indicating no concern. 

Soil Microbial Composition and Respiration

This measure was also assigned a Significance Level of 3. While some data exists regarding the soil 

microbial community at GRKO, not enough is known to assess its current condition. A Condition 

Level could not be assigned. 

Weighted Condition Score 

The Weighted Condition Score for soils at GRKO is 0.33. This is on the border between the low 

concern and moderate concern ranges. Given that isolated areas of soil are so highly contaminated 

with mining wastes and are clearly impacting soil chemistry and microbial activity, this resource is 

considered of moderate concern. 

Soils

Measures Significance 

Level

Condition 

Level WCS = 0.33 

Soil Chemistry 3 2 

Soil Aggregate 

Stability 3 1 

Bulk Density 3 0 

Microbial 

Composition and 

Respiration

3 n/a

4.13.6 Sources of Expertise

Jason Smith, GRKO Natural Resource Specialist 

Jeff Johnson, GRKO CERCLA Project Manager
267 

4.13.7 Literature Cited

Agvise Laboratories. 2008. Soil test reports: Grant-Kohrs Ranch. Agvise Laboratories, Northwood, 

North Dakota. 

Agvise Laboratories. 2010. Soil test report: Grant-Kohrs Ranch. Agvise Laboratories, Northwood, 

North Dakota. 

Agvise Laboratories. 2013. Soil test reports: Grant-Kohrs Ranch. Agvise Laboratories, Northwood, 

North Dakota. 

Armour, C. L., D. A. Duff, and W. Elmore. 1991. The effects of livestock grazing on riparian and 

stream ecosystems. Fisheries 16(1):7-11. 

da Silva, A. P., S. Imhoff, and M. Corsi. 2003. Evaluation of soil compaction in an irrigated shortduration grazing system. Soil and Tillage Research 70:83-90. 

Dinkins, C. P., and C. Jones. 2013. Interpretation of soil test reports for agriculture (MT200702AG). 

Montana State University Extension, Bozeman, Montana. 

Environmental Protection Agency (EPA). 2003. National management measures to control nonpoint 

source pollution from agriculture. EPA 841-B-03-004. Environmental Protection Agency, 

Washington, D.C. 

Ford, K. L., and W. N. Beyer. 2014. Soil criteria to protect terrestrial wildlife and open-range 

livestock from metal toxicity at mining sites. Environmental Monitoring and Assessment 

186:1899-1905. 

Franzluebbers, A. J., J. A. Stuedemann, H. H. Schomberg, and S. R. Wilkinson. 2000. Soil organic C 

and N pools under long-term pasture management in the southern Piedmont U.S.A. Soil Biology 

and Biochemistry 32:459-478. 

Gannon, J. E., and M. Rillig. 2002. Relationship of heavy metal contamination to soil respiration. 

National Park Service, Deer Lodge, Montana. 

Herrick, J. E., J. W. Van Zee, K. M. Havstad, L. M Burkett and W. G. Whitford. 2005. Monitoring 

manual for grassland, shrubland and savanna ecosystems. USDA-ARS Jornada Experimental 

Range, Las Cruces, New Mexico, and University of Arizona Press, Tucson, Arizona. 

Jacobsen, J., G. Jackson, and C. Jones. 2005. Fertilizer guidelines for Montana crops. Montana State 

University Extension, Bozeman, Montana. 

Kapustka, L. A. 2002. Phytotoxicity tests on soils from the Grant-Kohrs Ranch National Historic 

Site, Deer Lodge, Montana. National Park Service, Deer Lodge, Montana.
268 

Manier, D., D. Shorrock, E. W. Schweiger, I. Ashton, B. Frakes, M. Britten, D. Pillmore, and J. 

Burke. 2011. Rocky Mountain Network vegetation composition structure and soils monitoring 

protocol: Small park grasslands, shrublands, and woodlands; Version 1.0. Natural Resource 

Report NPS/ROMN/NRR-2011/383. National Park Service, Fort Collins, Colorado. 

Menta, C. 2012. Soil fauna diversity – function, soil degradation, biological indices, soil restoration. 

Pages 59-94 in Biodiversity conservation and utilization in a diverse world. G. A. Lameed (ed.). 

http://www.intechopen.com/books/biodiversity-conservation-and-utilization-in-a-diverse-world 

(accessed 15 July 2014). 

Moore, J. N., and W. W. Woessner. 2001. Geologic, soil water and groundwater report - 2000 Grant 

Kohrs Ranch National Historic Site. National Park Service, Deer Lodge, Montana. 

National Park Service (NPS). 2007. Federal restoration plan for Grant-Kohrs Ranch National 

Historic Site. National Park Service, Deer Lodge, Montana. 

National Park Service (NPS). 2010. Vegetation composition, structure, and soils: Small parks. 

Resource brief. National Park Service, Rocky Mountain Network, Fort Collins, Colorado. 

National Park Service (NPS). 2013a. Grant-Kohrs Ranch National Historic Site, Montana: Soil 

survey – DRAFT. National Park Service, Fort Collins, Colorado. 

National Park Service (NPS). 2013b. Soil map unit distribution of Grant-Kohrs Ranch National 

Historic Site, Montana. National Park Service, Fort Collins, Colorado. 

Natural Resources Conservation Service (NRCS). 2001. Rangeland soil quality – compaction. 

http://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/nrcs142p2_051912.pdf (accessed 15 

July 2014). 

Olson, B., and B. Leinard. 2013. BMP Report: Grant-Kohrs Ranch National Historic Site. National 

Park Service, Deer Lodge, Montana. 

Ramsey, P. W., M. C. Rillig, K. P. Feris, J. N. Moore, and J. E. Gannon. 2005a. Mine waste 

contamination limits soil respiration rates: A case study using quantile regression. Soil Biology 

and Biochemistry 37:1177-1183. 

Ramsey, P. W., M. C. Rillig, K. P. Feris, N. S. Gordon, J. N. Moore, W. E. Holben, and J. E. 

Gannon. 2005b. Relationship between communities and processes; new insights from a field 

study of a contaminated ecosystem. Ecology Letters 8:1201-1210. 

Rice, P. M., and P. C. Ray. 1984. Floral and faunal survey and toxic metal contamination study of the 

Grant-Kohrs Ranch National Historic Site. National Park Service, Deer Lodge, Montana.
269 

Rice, P. M., E. W. Schweiger, W. Gustafson, C. Lea, D. Manier, D. Shorrock, B. Frakes, and L. 

O’Gan. 2012. Vegetation classification and mapping project report, Grant-Kohrs Ranch National 

Historic Site. Natural Resource Report NPS/ROMN/NRR—2012/589. National Park Service, 

Fort Collins, Colorado. 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2006. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2006. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2007. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2007. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2008. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2008. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2009. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2009. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2010. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2010. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2011. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2011. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Rocky Mountain Inventory and Monitoring Network (ROMN). 2012. Vegetation composition, 

structure, and soils (VCSS) yearly master database - 2012. Microsoft Access database. Obtained 

from https://irma.nps.gov/App/ (accessed 16 July 2014). 

Shorrock, D. E., I. Ashton, M. Britten, J. Burke, D. Pillmore, and E. W. Schweiger. 2010. Vegetation 

composition structure and soils monitoring at Grant-Kohrs Ranch National Historic Site: 2009 

annual data report. Natural Resource Data Series NPS/ROMN/NRDS—2010/087. National Park 

Service, Fort Collins, Colorado. 

Sollins, P., C. Glassman, E. A. Paul, C. Swanston, K. Lajtha, J. W. Heil, and E. T. Elliott. 1999. Soil 

carbon and nitrogen: pools and fractions. Pages 89-105 in Standard soil methods for long-term 

ecological research. G. P. Robertson (ed). Oxford University Press, Cary, North Carolina. 

TetraTech. 2012. Clark Fork site data summary report: Reach A, phases 15 and 16. Montana 

Department of Environmental Quality, Remediation Division, Helena, Montana. 
270 

Thornberry- Ehrlich, T. 2007. Grant- Kohrs Ranch National Historic Site geologic resource 

evaluation report. Natural Resource Report NPS/NRPC/GRD/NRR—2007/004. National Park 

Service, Denver, Colorado.
271 

273 

Chapter 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 74 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 74. Identified data gaps or needs for the featured components.

Component Data Gaps/Needs

Grazing  Full Rangeland Health Assessments

 Future repetition of range condition assessments and similarity indices

Riparian Area  Repetition of vegetation surveys/research following Superfund 

remediation (including ecological effect size, NRCS Riparian Health 

Assessments, and Greenline Assessments)

 Update of National Wetland Inventory data using more recent aerial 

imagery

Pastures/Hayfields  Utilize a “nutrient budget” to track all nutrients applied to hayfields and 

pastures

 Establish a plan for managing “Effluent Fields” since the city’s effluent 

water is no longer available for irrigation

Uplands (grasslands, nonirrigated)

 Additional community surveys in order to calculate ecological effects sizes

(will be aided by development of NRCS Ecological Site Descriptions)

 Full Rangeland Health Assessments

 Future repetition of range condition assessments and similarity indices

Birds  Establishment of an annual survey with increased yearly sampling (>1 

survey/year) and a spatially balanced bird protocol would allow for density 

and occupancy estimates

 More winter bird surveys, in addition to Christmas Bird Counts

Periphyton  Continued yearly monitoring efforts to accumulate long-term data for the 

sediment increaser model

 Study how periphyton are impacted by the initial disturbance of Superfund 

remediation and by the subsequent “improved” (e.g., less contaminated) 

conditions
274 

Table 74. Identified data gaps or needs for the featured components. (continued)

Component Data Gaps/Needs

Aquatic Macroinvertebrates  Continued yearly monitoring efforts to accumulate long-term data for the 

RIVPACS model and MMI

 Study how aquatic macroinvertebrates are impacted by the initial 

disturbance of Superfund remediation and by the subsequent “improved” 

(e.g., less contaminated) conditions

Air Quality  No air quality monitors within the distance (16 km [10 mi]) necessary to 

accurately represent conditions in the park

Water Quality  Limited data for groundwater quality

 Limited data for total suspended sediment (TSS) of surface waters and no 

data for coliform bacteria specific to park surface waters 

 Study how Superfund remediation efforts impact water quality parameters 

in both the short and long-term 

Soundscape  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

Viewscape  Additional analysis of historic aerial photos (e.g., from the 1990s or mid2000s) to further document development just outside the park that has 

impacted its viewscape

Hydrology  Limited information on irrigation flow inputs and groundwater resources 

(e.g., depth to groundwater, flow patterns, sustainable yields)

 Research into the interaction between surface water and groundwater and 

the influence of irrigation

 Additional study to determine if and how climate change is affecting 

GRKO hydrology

Soils  Further information on soil microbial community composition and 

respiration, as well as research into how the soil microbial community and 

its condition influence other park resources, particularly vegetation

 Research into the impacts of grazing (high intensity, short duration) on 

soils and soil microbes

 Continued ROMN monitoring of soil properties to help identify any 

changes in condition

Several of the park’s data needs involve continuing recently established monitoring programs, to 

accumulate sufficient data for identifying any trends over time (e.g., periphyton, aquatic 

macroinvertebrates, soils, soundscape). Other components, such as birds, would benefit from more 

consistent sampling efforts (both timing and methodology), as funding allows. 

5.2 Component Condition Designations

Table 75 displays the conditions assigned to each resource component presented in Chapter 4 

(definitions of condition graphics are located in Table 76 following Table 75). It is important to 
275 

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 75) 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 historical data, a clear 

understanding of reference condition (i.e., what is considered desirable or natural) for some 

measures, or even current information. Condition could not be determined for three of the 13 selected 

components: grazing, uplands, and hydrology. 

For featured components with available data and fewer information gaps, assigned conditions varied. 

Six components are considered in good condition: pastures and hayfields, birds, periphyton, aquatic 

macroinvertebrates, air quality, and viewscape. However, periphyton and aquatic macroinvertebrates 

scores were at the edge of the good condition range, and any small decline in the community could 

shift them into the moderate concern range. Four components (riparian area, water quality, 

soundscape, and soils) were of moderate concern, and no components were considered to be of 

significant concern. 

Table 75. Summary of current condition and condition trend for featured NRCA components.

Component WCS Condition

Ecosystem Extent and Function

Disturbance Regimes

Grazing N/A

Biological Composition

Ecological Communities

Riparian Area 0.54

Pastures/Hayfields 0.33

Uplands (Grasslands, non-irrigated) N/A
276 

Table 75. Summary of current condition and condition trend for featured NRCA components. (continued)

Component WCS Condition

Birds

Birds 0.22

Freshwater Biota

Periphyton 0.33

Aquatic Macroinvertebrates 0.33

Environmental Quality

Air quality 0.13

Water quality 0.39

Soundscape 0.33

Viewscape 0.22

Physical Characteristics

Geologic & Hydrologic

Hydrology (Surface and Groundwater 

Dynamics) N/A

Soils 0.33
277 

Table 76. Description of symbology used for individual component assessments.

Condition Status Trend in Condition Confidence in 

Assessment

Warrants 

Significant Concern Condition is Improving High

Warrants 

Moderate Concern Condition is Unchanging Medium

Resource is in Good 

Condition Condition is Deteriorating Low

An open (uncolored) circle indicates that current condition is unknown or indeterminate; 

this condition status is typically associated with unknown trend and low confidence 

(explanation is required if a trend symbol or a medium/high confidence band is shown)

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. 
278 

5.3 Park-wide Condition Observations 

Vegetation Communities/Grazing

The vegetation communities of GRKO are vital resources for the park, particularly given their 

integral role in providing grass and hay for livestock on the working ranch and as a backdrop of the 

cultural landscape. The park’s pastures and hayfields are in good condition and stable, while the 

riparian area is of moderate concern. A trend could not be determined for the riparian area, as some 

measures seemed stable but others did not have enough data to detect any change over time (e.g., 

Greenline Assessment, NRCS Riparian Health Assessment). The riparian area will be heavily 

impacted by Superfund remediation activities, with extensive soil removal and re-vegetation in the 

near future. The condition of GRKO’s upland grasslands could not be determined due to a scarcity of 

data for the selected measures. Invasive plants are a serious threat to the uplands, but there is 

currently no evidence that upland grassland conditions are of significant concern. 

The condition of grazing is largely dependent on the condition of the vegetation communities 

utilized. Two methods commonly used to assess grazed lands were selected as measures for this 

component: Range Condition/Similarity Index and Rangeland Health (Pellant et al. 2005). Recently 

calculated Range Condition scores and similarity indices, which focus on vegetative composition, 

suggest that GRKO’s grazing areas are in good condition. Full Rangeland Health Assessments, 

which take into account other ecosystem characteristics (e.g., soil condition, ecological processes), 

have not been completed for GRKO’s lands. As a result an overall condition was not determined for 

the grazing component. Ecological Site Descriptions, which are in the initial stages of development 

by the NRCS, will aid in assessing grazing land conditions in the future (NRCS 2015). 

Other Biotics

Other biotic components included in the NRCA were birds, periphyton, and aquatic 

macroinvertebrates. Birds were considered in good condition with a stable trend. This is a good sign 

for the park overall, as bird populations often serve as indicators of an ecosystem’s health (Morrison 

1986, Hutto 1998, NABCI 2009). Periphyton and aquatic macroinvertebrates also received a “good 

condition” designation but, as mentioned above, were on the border of the moderate concern range. 

Consistent monitoring of these communities was recently initiated and continuation of those efforts 

will allow for more accurate assessment of their condition. 

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 and 

water quality. GRKO’s air quality appears to be in good condition; however, the nearest monitoring 

stations are outside the range of what the NPS ARD considers representative of park conditions (16 

km [10 mi]). Monitoring stations closer to GRKO would be needed to confirm that interpolated and 

estimated data used in this NRCA accurately reflects conditions in the park. 

Clark Fork water quality, including within GRKO, has been heavily impacted by historic mining 

contamination from upstream. Metals in the water and sediment of the park have been a significant 
279 

concern for management. The current condition of water quality is of moderate concern but with an 

improving trend. Upcoming Superfund remediation efforts along the Clark Fork within GRKO will 

remove much of the historic contamination, which will likely further improve condition. However, 

the disturbance from these remediation activities may cause a temporary decrease in water quality. 

The park’s viewscape is currently in good condition, with little change occurring inside the park but 

noticeable development outside park boundaries to the south and east. Soundscape is of moderate 

concern due to increased air, train, and road traffic around the park. This increased traffic suggests a 

deteriorating trend for the component. 

Physical Characteristics

An overall condition could not be assigned for GRKO’s hydrology, primarily due to limited 

information on irrigation flow inputs (i.e., how much water is diverted from the river for irrigation) 

and depth to groundwater. For those measures with enough data for analysis (stream discharge, 

annual precipitation), concern was low. This suggests there is currently no significant cause for 

concern regarding hydrology at the park. 

The park’s soils are currently of moderate concern, largely due to the lingering effects of historic 

mining contamination in the riparian area. Although soil physical properties (bulk density, aggregate 

stability) and organic matter content are of no or low concern, heavy metal contaminant 

concentrations in some areas exceeded levels known to impact plants and animals (Moore and 

Woessner 2001, Kaputska 2002, TetraTech 2012). This contamination appears to have negatively 

impacted pH levels and soil microbial activity (Gannon and Rillig 2002). As with water quality, 

upcoming Superfund remediation efforts will improve soil conditions in the riparian area in the longterm but may first cause a short-term disturbance and decline in conditions. 

Park-wide Threats and Stressors

Several threats and stressors influence the condition of multiple resources within GRKO. These 

include invasive plant species, mining contamination, and the related Superfund remediation 

activities. Many non-native plant species that occur in the park were introduced as hay species and 

pasture grasses and are now considered “contributing features” on the cultural landscape, as they 

represent the history of ranching in the area (John Milner Associates et al. 2004). However, other 

non-natives are considered invasive and are a significant concern at GRKO. Invasive species can 

alter plant community composition and ecological processes (e.g., water and nutrient cycling) and 

contribute to biodiversity and habitat losses (Lacey et al. 1989, NPS 2008). They also threaten the 

cultural landscape the park was set aside to protect and can reduce forage quality (Manier et al. 

2011). Recent efforts to reduce invasive species at GRKO have been largely effective, particularly in 

the riparian area (see Appendix E), but further work and continued vigilance will be necessary to 

minimize their impact.

Mining contamination has affected many park resources, including vegetation communities, soils, 

and water quality. Some “slickens” patches in the riparian area are so contaminated that they are 

completely devoid of vegetation (Rice and Hardin 2002). This contamination is what led to the 

designation of the Upper Clark Fork as a Superfund site in 1992 (NPS 2007). Remediation efforts to 
280 

remove much of this contamination have been occurring in stages upstream (south) of GRKO for 

several years. Remediation activities are scheduled to begin soon in GRKO and will involve the 

removal of nearly 300,000 m3

 of contaminated soil from the Clark Fork riparian area. These areas 

will be backfilled with clean soil to support native plant revegetation and return the floodplain to a 2-

year flood level (NPS 2007). While this will help restore the health of the riparian area in the longterm, the removal and initial restoration efforts will cause disturbance that will temporarily impact 

nearly every resource in the park, including vegetation, wildlife, water quality, soils, and even 

soundscape and viewscape. 

Overall Conclusions 

As outlined in Chapter 2, GRKO’s management objectives include providing opportunities for 

visitors to understand the cattle industry and its evolution, and managing natural resources in a way 

that complements the historical context of the ranch and cattle ranching operations (NPS 1993). 

GRKO also strives towards sustainable ranching, which “maintains and improves grassland and 

riparian health, supports vigorous livestock and wildlife populations that result in economic success, 

educational opportunity and community benefit beyond a single generation” (NPS 2011). Balancing 

these objectives, which sometimes may conflict, can be a challenge. This NRCA found that six of the 

13 selected components (resources) are currently in good condition and none are of significant 

concern. Components that are of moderate concern are primarily influenced by threats and stressors 

outside the control of park managers. These results suggest that GRKO is successfully meeting its 

sustainable ranching and natural resource management goals. 
281 

5.4 Literature Cited

Gannon, J. E., and M. Rillig. 2002. Relationship of heavy metal contamination to soil respiration. 

National Park Service, Deer Lodge, Montana. 

Hutto, R. L. 1998. Using landbirds as an indicator species group. Pages 75-92 in Avian conservation: 

Research and management. Island Press, Washington, D.C. 

John Milner Associates, Rivanna Archaeological Consulting, Susan Maxman and Partners 

Architects. 2004. Cultural landscape report. National Park Service, Deer Lodge, Montana. 

Kaputska, L. A. 2002. Phytotoxicity tests on soils from the Grant-Kohrs Ranch National Historic 

Site, Deer Lodge, Montana. National Park Service, Deer Lodge, Montana. 

Lacey, J. R., C. B. Marlow, and J. R. Lane. 1989. Influence of spotted knapweed (Centaurea 

maculosa) on surface runoff and sediment yield. Weed Technology 3(4):627-631. 

Manier, D., D. Shorrock, E. W. Schweiger, I. Ashton, B. Frakes, M. Britten, D. Pillmore, and J. 

Burke. 2011. Rocky Mountain Network vegetation composition structure and soils monitoring 

protocol: Small park grasslands, shrublands, and woodlands; Version 1.0. Natural Resource 

Report NPS/ROMN/NRR-2011/383. National Park Service, Fort Collins, Colorado. 

Moore, J. N., and W. W. Woessner. 2001. Geologic, soil water and groundwater report - 2000 Grant 

Kohrs Ranch National Historic Site. National Park Service, Deer Lodge, Montana. 

Morrison, M. L. 1986. Bird populations as indicators of environmental change. Current Ornithology 

3:429-451. 

National Park Service (NPS). 1993. Grant-Kohrs Ranch National Historic Site: Environmental 

impact statement for a general management plan and development concept plan. National Park 

Service, Deer Lodge, Montana. 

National Park Service (NPS). 2007. Federal restoration plan for Grant-Kohrs Ranch National 

Historic Site. National Park Service, Deer Lodge, Montana. 

National Park Service (NPS). 2008. Exotic plant management team: 2008 annual report. National 

Park Service, Biological Resources Management Division, Fort Collins, Colorado. 

National Park Service (NPS) 2011. Grant-Kohrs Ranch: Sustainable ranching. 

http://www.nps.gov/grko/learn/management/upload/Sustainable-Ranching-2-28-11.pdf (accessed 

17 February 2015). 

Natural Resources Conservation Service (NRCS). 2015. Ecological Site Descriptions. 

http://www.nrcs.usda.gov/wps/portal/nrcs/main/national/technical/ecoscience/desc/ (accessed 6 

May 2015). 

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. 
282 

Pellant, M., P. Shaver, D. A. Pyke, and J. E. Herrick. 2005. Interpreting indicators of Rangeland 

Health, version 4. Technical Reference 1734-6. U.S. Department of the Interior, Bureau of Land 

Management, National Science and Technology Center, Denver, Colorado. 

Rice, P. M., and J. Hardin. 2002. Riparian plant community structure at Grant-Kohrs Ranch. National 

Park Service, Deer Lodge, Montana. 

TetraTech. 2012. Clark Fork site data summary report: Reach A, phases 15 and 16. Montana 

Department of Environmental Quality, Remediation Division, Helena, Montana. 
283 

Appendices 

Appendix A. Non-native plants species documented in GRKO (NPS 2014). Note that not all non-native species are 

invasive. Species in bold have been designated as “contributing features” of the cultural landscape (John Milner 

Associates et al. 2004).

Scientific Name Common Name Scientific Name Common Name

Achillea ptarmica sneezeweed Polygonum convolvulus black bindweed

Rhaponticum repens*^ Russian knapweed Polygonum persicaria ladysthumb

Artemisia biennis biennial wormwood Rumex acetosella sheep sorrel

Carduus nutans musk thistle Rumex crispus curly dock

Centaurea stoebe*^ spotted knapweed Rumex obtusifolius bitter dock

Cirsium arvense*^ Canada thistle Lonicera x bella Bell's honeysuckle

Cirsium vulgare bull thistle Medicago lupulina black medick

Hieracium umbellatum narrowleaf hawkweed Medicago sativa alfalfa

Lactuca sativa garden lettuce Melilotus officinalis sweetclover

Lactuca serriola prickly lettuce Onobrychis viciifolia sainfoin

Sonchus arvensis field sowthistle Trifolium pratense red clover

Sonchus arvensis ssp.

uliginosus moist sowthistle Trifolium repens white clover

Tanacetum vulgare*^ common tansy Vicia cracca bird vetch

Taraxacum officinale dandelion Betula pendula European white birch

Tragopogon dubius yellow salsify Galeopsis tetrahit hemp nettle

Tragopogon pratensis meadow salsify Glechoma hederacea ground ivy

Callitriche stagnalis pond water-starwort Syringa vulgaris common lilac

Cynoglossum officinale*^ houndstongue Campanula rapunculoides creeping bellflower

Myosotis scorpioides forget-me-not Linaria vulgaris*^ yellow toadflax

Alyssum alyssoides pale madwort Plantago major common plantain

Alyssum desertorum desert madwort Verbascum thapsus common mullein

Barbarea vulgaris yellowrocket Euphorbia esula*^ leafy spurge

Camelina microcarpa littlepod falseflax Agropyron cristatum crested wheatgrass

Capsella bursa-pastoris shepherd's purse Agrostis stolonifera redtop

Lepidium chalapensis lenspod hoarycress Alopecurus pratensis meadow foxtail

Lepidium draba*^ whitetop; hoary cress Bromus inermis smooth brome

Lepidium appelianum hairy whitetop Bromus arvensis field brome

Descurainia sophia herb sophia; flixweed Bromus tectorum* cheatgrass

Hesperis matronalis dames rocket Dactylis glomerata orchard grass

Lepidium latifolium*^ perennial pepperweed Echinochloa crus-galli barnyard grass

Lepidium perfoliatum clasping pepperweed Elymus repens quackgrass

Cerastium fontanum ssp.

vulgare

common mouse-ear 

chickweed 

Elymus trachycaulus ssp.

trachycaulus slender wheatgrass

Rorippa sylvestris creeping yellowcress Lolium pratense meadow fescue

Sisymbrium altissimum tall tumblemustard Phalaris arundinacea reed canarygrass

Sisymbrium loeselii tumblemustard Phleum pratense timothy

Thlaspi arvense field pennycress Poa compressa Canada bluegrass

Amaranthus blitoides mat amaranth Poa pratensis Kentucky bluegrass

Chenopodium album lambsquarters Setaria viridis green bristlegrass

Chenopodium glaucum oakleaf goosefoot Nasturtium officinale watercress

Bassia scoparia* kochia; burningbush Ranunculus repens creeping buttercup

Salsola paulsenii barbwire Russian thistle Ranunculus acris*^ tall buttercup

Salsola tragus prickly Russian thistle Malus sp. apple

Gypsophila paniculata* baby's breath Potentilla recta*^ sulfur cinquefoil
284 

Scientific Name Common Name Scientific Name Common Name

Thinopyrum intermedium intermediate wheatgrass Convolvulus arvensis*^ field bindweed

Silene latifolia ssp. alba bladder campion Hyoscyamus niger black henbane

Silene vulgaris maidenstears Solanum dulcamara climbing nightshade

Polygonum arenastrum oval-leaf knotweed

* - Northern Rocky Mountains EPMT priority species for GRKO (NPS 2011b)

^ - State of Montana noxious weed 
285 

Appendix B. Ecological Effect Size Examples

by Peter Rice, University of Montana Research Ecologist 

Ecological effect size (A) is a whole community level parameter that quantifies the deviation of 

current in-situ Grant-Kohrs plant communities from the desired Potential Natural Community (PNC). 

The Montana Riparian Wetland Association (MRWA) developed a riparian & wetlands plant 

community classification system (Hansen et al. 1995) which provides the reference standard data for 

the PNCs expected on the Grant-Kohrs Ranch. Ecological effect size (A) is derived from ocular 

canopy cover estimates for every individual species in the sample plots. In our application, the 

calculated A ranges from 0 to 1; the larger the value of A, the greater the deviation of the species 

composition of the sample plot from the PNC. 

Toxic metal contamination of the Grant-Kohrs riparian soils caused the plant species composition to 

be altered from the PNC as a function of differential toxic metal susceptibility and tolerance among 

the plant species. In the examples in Table B-1, we see that the ecological effect size (A) for the 

deviation of the GRKO Geyer Willow community type from the MRWA PNC reference condition is 

0.088 and 0.143 for the Water Birch community type (Table B-1). Both example cases are very 

highly statistically significant (p<0.001). Moreover plant ecologists consider ecological effect sizes 

of 0.1 to 0.3+ calculated from numerous plots to be ecologically important. Vegetation ecological 

effect sizes greater than 0.4 are rare in natural systems, unless there are disturbance forces that 

remove and replace large portions of the in-situ vegetation.

Table B-1. Ecological effect size (A) deviation of two Grant-Kohrs riparian plant communities from the 

desired Potential Natural Community (MRWA PNC; Hansen et al. 1995).

Community Type Common Name Number of Plots

Ecological Effect 

Size 

MRWA PNC GK A P<X

SALGEY GEYER WILLOW 67 43 0.088 <0.001

BETOCC WATER BIRCH 20 28 0.143 <0.001

The extent of the ecological effect size or deviation from PNC can be portrayed graphically by 

ordination techniques (Figure B-1 and Figure B-2). In the graphic portrayal we contrast the GRKO 

plots with their respective PNC reference plots. Only plant species present in at least 20% of sampled 

plots (i.e., constancy ≥20%) were included in this ordination. Each point represents a single plot. The 

point or plot position in the ordination coordinate system, like ecological effect size, is also 

determined by the ocular canopy cover estimates for every individual species in that sample plot. 

Plots that are closer together are more similar in overall species composition. Plots that are 

increasingly separated in the coordinate system are increasingly dissimilar in species composition. As 

a group, the Grant Kohrs plant community plots are clearly different from the desired PNC group. 

Stress values of 20 or less suggest that the graphic can be visually interpreted with confidence. (Note 

that ordinations are actually three-dimensional and the full degree of separation between plots is not 

visible in the two-dimensional graphs below.) 
286 

Figure B-1. NMS ordinations of Geyer Willow (SALGEY) plots on the Grant-Kohrs Ranch contrasted with 

the Potential Natural Community as defined by the Montana Riparian and Wetland Association standard 

reference plots (Three-Dimensional Ordination, Stress 18.4).

Figure B-2. NMS ordinations of riparian Water Birch (BETOCC) plots on the Grant-Kohrs Ranch 

contrasted with the Potential Natural Community as defined by the Montana Riparian and Wetland 

Association standard reference plots (Three-Dimensional Ordination, Stress 12.5).

0

0

40 80

40

80

SALGEY (Constancy=>20%)

Axis 1

Axis 2

Data Set

MRWA

GK
287 

By re-grading the riparian flood plain topographic elevations, replacing contaminated soils, and 

replanting as part of Superfund remediation efforts, the NPS is acting to restore the metal impacted 

plant communities on the Ranch to a more natural condition. The various MRWA PNC reference 

plots provide an all species numerical standard for that goal and calculation of ecological effect size 

provides a quantitative measure of progress towards the natural restoration goal.
288 

Appendix C. Plant species documented throughout Montana in the 19 riparian community types that 

occur within GRKO (see Table 11) by Hansen et al. (1995), in GRKO riparian areas by Rice and Hardin 

(2002) or Rice and Smith (2011). The final column indicates all species documented by Hansen et al. 

(1995) that have been confirmed within GRKO (NPS 2014c), both in and outside the riparian zone. 

Columns under Hansen et al. (1995) indicate if a species was found in riparian community types 

dominated by (or named for) trees and shrubs or community types dominated by herbaceous vegetation.

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Trees

Abies lasiocarpa subalpine fir x x

Acer negundo boxelder x

Betula papyrifera paper birch x

Elaeagnus angustifolia* Russian olive x

Fraxinus pennsylvanica green ash x x 

Juniperus scopulorum Rocky Mountain juniper x x x 

Larix occidentalis western larch x 

Picea sp. spruce sp. x x 

Pinus contorta lodgepole pine x x 

Pinus flexilis limber pine x

Pinus ponderosa ponderosa pine x

Populus angustifolia narrowleaf cottonwood x 

Populus deltoides Great Plains cottonwood x

Populus tremuloides quaking aspen x x x

Populus balsamifera ssp.

trichocarpa

black cottonwood x x x x

Pseudotsuga menziesii Douglas fir x

Salix alba golden willow x

Salix amygdaloides peach-leaf willow x

Thuja plicata western redcedar x

Shrubs

Acer glabrum Rocky Mountain maple x

Alnus incana mountain alder x x x

Amelanchier alnifolia western serviceberry x x

1 x

Arctostaphylos uva-ursi kinnikinnick x

Artemisia cana silver sagebrush x

Artemisia frigida fringed sagebrush x x

Artemisia tridentata big sagebrush x

Betula glandulosa bog birch x x

Betula occidentalis water birch x x x

Celastrus scandens American bittersweet x

Chrysothamnus viscidiflorus green rabbitbrush x x 

Clematis ligusticifolia western virgin’s bower x
289 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Clematis occidentalis Columbia clematis x

Cornus canadensis bunchberry x

Cornus sericea red-osier dogwood x x x x

Crataegus douglasii black hawthorn x

Crataegus succulenta succulent hawthorn x

Dasiphora fruticosa shrubby cinquefoil x x x x

Dryas drummondii yellow mountain-avens x 

Elaeagnus commutata silverberry x 

Ericameria nauseosa gray rabbitbrush x x 

Gutierrezia sarothrae broom snakeweed x x

Juniperus communis common juniper x

Juniperus horizontalis creeping juniper x

Kalmia microphylla small-leaved laurel x 

Ledum glandulosum Labrador tea x x

Linnaea borealis twinflower x

Lonicera involucrata twinberry honeysuckle x x 

Lonicera utahensis Utah honeysuckle x x

Mahonia repens creeping Oregongrape x x

Parthenocissus quinquefolia Virginia creeper x 

Parthenocissus vitacea woodbine x

Philadelphus lewisii mock orange x

Prunus americana wild plum x

Prunus virginiana common chokecherry x x x

Rhamnus alnifolia alder buckthorn x

Rhus aromatica fragrant sumac x

Ribes americanum black currant x

Ribes aureum golden currant x x

Ribes cereum wax currant x 

Ribes sp. currant sp. x x x x 

Ribes hudsonianum stinking currant x 

Ribes inerme whitestem gooseberry x

Ribes lacustre swamp currant x

Ribes missouriense Missouri gooseberry x

Ribes odoratum buffalo currant x

Ribes oxyacanthoides Canadian gooseberry x x x

Ribes viscosissimum sticky currant x

Rosa acicularis prickly rose x x

Rosa arkansana prairie rose x

Rosa woodsii woods rose x x x x 

Rubus idaeus wild raspberry x x x
290 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Rubus parviflorus thimbleberry x

Salix bebbiana Bebb willow x x x x 

Salix boothii Booth willow x x x x

Salix brachycarpa short-fruited willow x

Salix candida hoary willow x x

Salix commutata undergreen willow x 

Salix drummondiana Drummond willow x x x x

Salix eriocephala diamond willow x

Salix exigua sandbar willow x x x x

Salix sp. willow x 

Salix farriae Farr willow x

Salix geyeriana Geyer willow x x x x 

Salix lucida ssp. lasiandra Pacific willow x x x x 

Salix lutea yellow willow x x x x

Salix planifolia planeleaf willow x x

Salix pseudomonticola mountain willow x

Salix wolfii Wolf’s willow x x 

Sambucus sp. elderberry sp. x

Shepherdia argentea thorny buffaloberry x

Shepherdia canadensis Canada buffaloberry x

Solanum dulcamara* climbing nightshade x x

Sorbus scopulina Cascade mountain-ash x

Spiraea betulifolia shiny-leaf spiraea x

Spiraea douglasii Douglas’s spiraea x

Symphoricarpos albus common snowberry x

Symphoricarpos occidentalis western snowberry x x x

Tamarix chinensis* salt cedar x

Toxicodendron rydbergii western poison ivy x

Vaccinium membranaceum thin-leaf huckleberry x

Vaccinium occidentale western blueberry x

Vaccinium scoparium whortleberry x

Viburnum edule low-bush cranberry x

Vitis riparia river-bank grape x

Graminoids

Achnatherum occidentale western needlegrass x x

Achnatherum richardsonii Richardson’s 

needlegrass

x x

Agropyron cristatum* crested wheatgrass x x

Agrostis pallens dune bentgrass x

Agrostis exarata spike bentgrass x x

Agrostis humilis alpine bentgrass x x 
291 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Agrostis idahoensis Idaho bentgrass x x

1 x

Agrostis scabra rough bentgrass x x

Agrostis stolonifera* redtop x x x x

Agrostis capillaris* colonial bentgrass x 

Alopecurus aequalis short-awned foxtail x x x 

Alopecurus magellanicus alpine foxtail x x

Alopecurus geniculatus* water foxtail x

Alopecurus pratensis* meadow foxtail x x x x

Andropogon gerardii big bluestem x

Aristida purpurea var.

longiseta

red threeawn x x

Beckmannia syzigachne slough grass x x x x

Bouteloua gracilis blue grama x x

Bromus anomalus nodding brome x

Bromus marginatus mountain brome x x

Bromus ciliatus fringed brome x x

Bromus inermis* smooth brome x x x x 

Bromus arvensis* field brome x x 

Bromus hordeaceus* soft brome x

Bromus tectorum* cheatgrass x x 

Calamagrostis canadensis bluejoint reedgrass x x x

1 x 

Calamovilfa longifolia prairie sandreed x 

Calamagrostis purpurascens purple reedgrass x 

Calamagrostis stricta narrow-spiked reedgrass x x x

Calamagrostis stricta ssp.

inexpansa

northern reedgrass x

Carex amplifolia bigleaf sedge x

Carex aperta Columbia sedge x

Carex aquatilis water sedge x x x x

Carex atherodes awned sedge x x x x

Carex athrostachya slender-beaked sedge x x

Carex aurea golden sedge x x

Carex bebbii Bebb’s sedge x x 

Carex buxbaumii Buxbaum’s sedge x x 

Carex canescens gray sedge x x 

Carex capillaris hair sedge x x 

Carex concinnoides northwestern sedge x 

Carex crawei Craw’s sedge x x 

Carex cusickii Cusick’s sedge x x 

Carex deweyana Dewey’s sedge x
292 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Carex diandra lesser-panicled sedge x

Carex disperma soft-leaved sedge x

Carex douglasii Douglas’ sedge x x x x

Carex sp. sedge sp. x x x x

Carex filifolia threadleaf sedge x

Carex flava yellow sedge x

Carex haydeniana Hayden’s sedge x 

Carex inops sun sedge x 

Carex hoodia Hood’s sedge x

Carex idahoa Idaho sedge x

Carex illiota sheep sedge x 

Carex interior inland sedge x x

Carex lasiocarpa slender sedge x x

Carex lenticularis lentil-fruit sedge x x 

Carex leptalea bristle-stalked sedge x x

Carex limosa mud sedge x x

Carex livida pale sedge x 

Carex microptera small-winged sedge x x x x

Carex multicostata manyrib sedge x

Carex nebrascensis Nebraska sedge x x x x 

Carex viridula green sedge x x

Carex pachystachya thick-headed sedge x x

Carex parryana Parry’s sedge x 

Carex magellanica poor sedge x

Carex pellita (formerly 

lanuginosa)

woolly sedge x x x x

Carex praegracilis clustered field sedge x x x x

Carex praticola meadow sedge x x

Carex raynoldsii Raynold’s sedge x

Carex retrorsa retrorse sedge x

Carex rostrata beaked sedge x x x x 

Carex saxatilis russet sedge x

Carex sartwellii Sartwell’s sedge x

Carex scirpoidea single-spike sedge x x x

Carex scopulorum Holm’s Rocky Mountain 

sedge

x x 

Carex simulata short-beaked sedge x x x

Carex sprengelii Sprengel’s sedge x 

Carex stipata sawbeak sedge x x x x

Carex vesicaria inflated sedge x x

Catabrosa aquatica brook grass x x 

Cinna latifolia drooping woodreed x
293 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Dactylis glomerata* orchard grass x x x

Danthonia californica California oatgrass x

Danthonia intermedia timber oatgrass x

Deschampsia cespitosa tufted hairgrass x x x x 

Dichanthelium acuminatum Pacific panicgrass x

Dulichium arundinaceum three-way sedge x

Echinochloa crus-galli * barnyard grass x x

Eleocharis acicularis needle spike-rush x

Eleocharis compressa flatstem spikerush x

Eleocharis palustris common spikesedge x x x x

Eleocharis pauciflora few-flowered spike-rush x

Elymus canadensis Canada wildrye x x

Elymus caninus* bearded wheatgrass x x x 

Elymus glaucus blue wildrye x x 

Elymus lanceolatus ssp. 

lanceolatus

thickspike wheatgrass x x 

Elymus repens* quackgrass x x x x

Elymus virginicus Virginia wildrye x 

Eriophorum chamissonis chamisso’s cotton-grass x 

Eriophorum angustifolium many-spiked cottongrass

x

Festuca idahoensis Idaho fescue x x

Festuca occidentalis western fescue x x x 

Festuca rubra red fescue x 

Festuca subulata bearded fescue x 

Glyceria borealis northern mannagrass x x

Glyceria elata tall mannagrass x

Glyceria grandis American mannagrass x x x x 

Glyceria striata fowl mannagrass x x 

Hesperostipa comata needle-and-thread x x

Hierochloe odorata sweetgrass x x x

Hordeum brachyantherum meadow barley x x

Hordeum jubatum foxtail barley x x x x

Juncus alpinoarticulatus northern rush x

Juncus articulatus jointed rush x x

Juncus balticus Baltic rush x x x x

Juncus bufonius toad rush x x

Juncus effusus common rush x x

Juncus ensifolius dagger-leaf rush x x 

Juncus filiformis thread rush x x

Juncus hallii Hall’s rush x x
294 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Juncus interior inland rush x

Juncus longistylis long-styled rush x x

Juncus nevadensis Sierra rush x 

Juncus nodosus knotted rush x x x

Juncus regelii Regel’s rush x

Juncus tenuis slender rush x x 

Juncus torreyi Torrey’s rush x

Koeleria macrantha prairie junegrass x x x

Leymus cinereus basin wildrye x x

Lolium pratense* meadow fescue x x x 

Luzula campestris* field woodrush x 

Luzula parviflora small-flowered woodrush x x

Muhlenbergia andina foxtail muhly x x

Muhlenbergia asperifolia alkali muhly x x x

Muhlenbergia filiformis pullup muhly x x 

Muhlenbergia racemosa marsh muhly x 

Nassella viridula green needlegrass x x

Oryzopsis micrantha littleseed ricegrass x

Pascopyrum smithii western wheatgrass x x x x

Phalaris aquatica* bulbuous canarygrass x

Phalaris arundinacea* reed canarygrass x x x x 

Phleum alpinum alpine timothy x x

Phleum pratense * common timothy x x x x

Phragmites australis common reed x

Poa compressa* Canada bluegrass x x x x

Poa cusickii Cusick's bluegrass x x x

Poa interior inland bluegrass x

Poa palustris fowl bluegrass x x

Poa pratensis* Kentucky bluegrass x x x x

Poa secunda Sandberg bluegrass x x x 

Polypogon monspeliensis* annual rabbitsfoot grass x

Pseudoroegneria spicata bluebunch wheatgrass x x x

Puccinellia nuttalliana Nuttall alkaligrass x

Schedonorus pratensis* meadow fescue x x

Schoenoplectus acutus hardstem bulrush x x

Schoenoplectus americanus American bulrush x x

Schoenoplectus fluviatilis river bulrush x

Schoenoplectus maritimus cosmopolitan bulrush x x 

Scirpus microcarpus small-fruited bulrush x x x 

Scirpus pallidus pale bulrush x x
295 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Schoenoplectus pungens sharp bulrush x x

Schoenoplectus 

tabernaemontani

softstem bulrush x x x

Scolochloa festucacea* common rivergrass x

Setaria viridis green bristlegrass x x

Spartina gracilis alkali cordgrass x x x 

Spartina pectinata prairie cordgrass x x 

Thinopyrum intermedium* intermediate wheatgrass x x 

Trisetum wolfii Wolf’s trisetum x x

Forbs

Achillea millefolium common yarrow x x x x 

Aconitum columbianum Columbian monkshood x x 

Actaea rubra red baneberry x x

Agastache urticifolia nettle-leaf giant-hyssop x

Agoseris glauca pale agoseris x x x

Agrimonia striata striate agrimony x

Alisma plantago-aquatica* American waterplantain x

Allium brevistylum short-style onion x

Allium cernuum nodding onion x x 

Allium geyeri Geyer’s onion x

Allium schoenoprasum wild chives x x x x

Ambrosia psilostachya western ragweed x

Ambrosia trifida giant ragweed x

Anaphalis margaritacea pearly everlasting x 

Androsace spp. fairy-candelabra x x 

Anemone cylindrica candle anemone x 

Anemone multifida cliff anemone x x

Angelica arguta sharptooth angelica x x

Antennaria anaphaloides tall pussytoes x x 

Antennaria corymbosa meadow pussytoes x x

Antennaria parlinii plainleaf pussytoes x

Antennaria umbrinella pussytoes x x x x 

Antennaria microphylla littleleaf pussytoes x x

Apocynum androsaemifolium spreading dogbane x

Apocynum cannabinum Indianhemp x x

Arabis sp. rockcress x x

Arabis glabra tower mustard x 

Aralia nudicaulis wild sarsaparilla x

Arctium lappa* great burrdock x 

Arctium minus* lesser burdock x 

Arenaria serpyllifolia* thyme-leaf sandwort x 
296 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Argentina anserina silverweed cinquefoil x

1 x

Arnica amplexicaulis clasping arnica x

Arnica chamissonis meadow arnica x x

Arnica fulgens orange arnica x

Arnica latifolia broadleaf arnica x

Arnica rydbergii Rydberg’s arnica x

Artemisia campestris green sagewort x x

Artemisia dracunculus wild tarragon x

Artemisia ludoviciana cudweed sagewort, 

white sagebrush

x x x

Asarum caudatum wild ginger x

Asclepias speciosa showy milkweed x x x

Asclepias verticillata whorled milkweed x

Asclepias viridiflora green milkweed x 

Asparagus officinalis* asparagus x 

Asperugo procumbens* madwort x

Astragalus agrestis field milk-vetch x

Astragalus alpinus alpine milk-vetch x

Astragalus canadensis Canada milk-vetch x 

Astragalus miser weedy milk-vetch x

Atriplex patula* spreading orache x x

Barbarea orthoceras American wintercress x

Bassia scoparia* kochia x x

Berteroa incana* hoary alyssum x

Bidens cernua nodding beggartick x x x

Butomus umbellatus* flowering-rush x 

Callitriche hermaphroditica autumnal water-starwort x

Caltha leptosepala elkslip marshmarigold x

Calystegia sepium hedge bindweed x

Camelina microcarpa smallseed falseflax x x

Camassia quamash common camas x

Camissonia breviflora short-flowered eveningprimrose

x

Campanula rapunculoides creeping bellflower x x

Campanula rotundifolia bluebell x x

Canadenthus modestus new world aster x

Capsella bursa-pastoris* shepherd's purse x x x

Cardamine breweri Brewer’s bittercress x 

Carum carvi* caraway x

Carduus nutans* musk thistle x x x

Cardamine pensylvanica Pennsylvania x x 
297 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

bittercress

Castilleja miniata scarlet paintbrush x 

Castilleja sulphurea sulphur paintbrush x

Centaurea stoebe ssp. 

micranthos*

spotted knapweed x x x x 

Cerastium arvense field chickweed x x

Cerastium fontanum ssp.

vulgare*

common mouse-ear 

chickweed

x x

Chamerion angustifolium fireweed x x x x

Chamerion latifolium alpine fireweed x

Chenopodium album lambsquarters x x x

Chenopodium glaucum* oakleaf goosefoot x x x

Chenopodium rubrum red goosefoot x 

Cicuta douglasii western water hemlock x x 

Cicuta maculata spotted water-hemlock x x

Circaea alpina enchanter’s nightshade x

Cirsium arvense* Canada thistle x x x x 

Cirsium canescens platte thistle x x

Cirsium flodmanii Flodman’s thistle x x

Cirsium scariosum meadow thistle x x

Cirsium undulatum wavyleaf thistle x x

Cirsium vulgare* bull thistle x x x x

Cleome serrulata Rocky Mountain 

beeplant

x x

Collomia linearis narrow-leaf collomia x x x

Convolvulus arvensis* field bindweed x x

Conyza canadensis Canadian horseweed x

Coptis occidentalis western goldthread x

Corydalis aurea golden smoke x

Coreopsis tinctoria plains coreopsis x

Crepis runcinata meadow hawksbeard x x x x

Cynoglossum officinale* houndstonge x x x

Delphinium sp. larkspur sp. x x

Descurainia pinnata pinnate tansymustard x 

Descurainia incana mountain tansymustard x x

1 x

Descurainia sophia* flixweed x x

Dianthus armeria* deptford pink x

Dodecatheon jeffreyi tall mountain shooting 

star

x 

Dodecatheon pulchellum dark-throat shootingstar x x x x

Draba stenloba slender draba x

Drosera anglica great sundew x
298 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Drosera linearis linear-leaved sundew x

Drymocallis glandulosa sticky cinquefoil x

Echinocystis lobata wild cucmber x

Elodea canadensis broad waterweed x x

Elodea nuttallii Nuttall’s waterweed x

Epilobium ciliatum fringed willowherb x x x x

Epilobium glaberrimum smooth willow-herb x x

Epilobium minutum chaparral willowherb x x x 

Epilobium palustre marsh willowherb x x x

Epilobium brachycarpum autumn willow-herb x 

Erigeron acris bitter fleabane x

Erigeron lonchophyllus spearleaf fleabane x x

Erigeron peregrinus subalpine daisy x x 

Erigeron speciosus showy fleabane x

Eriogonum umbellatum sulfur buckwheat x x

Erysimum cheiranthoides wormseed wallflower x x 

Erysimum repandum treacle mustard x

Eucephalus engelmannii Engelmann’s aster x

Euphorbia esula* leafy spurge x x x 

Eurybia conspicua showy aster x

Eurybia integrifolia thickstem aster x x

Eurybia sibirica Arctic aster x

Euthamia occidentalis western goldenrod x x

Filago arvensis* field filago x

Floerkea proserpinacoides false mermaid x x

Fragaria vesca woodland strawberry x x

Fragaria virginiana Virginia strawberry x x

Gaillardia aristata common gaillardia x x

Galium aparine cleavers x x 

Galeopsis tetrahit hemp nettle x x

Galium boreale northern bedstraw x x x x

Galium trifidum small bedstraw x x x x 

Galium triflorum sweetscented bedstraw x x

Gentiana affinis prairie gentian x x 

Gentiana calycosa explorer’s gentian x

Gentianopsis detonsa smaller fringed gentian x x

Geranium richardsonii white geranium x 

Geranium viscosissimum sticky geranium x x

Geum aleppicum yellow avens x

Geum macrophyllum large-leaved avens x x x x

Geum rivale purple avens x x

Geum triflorum old man’s whiskers x x
299 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Glycyrrhiza lepidota American licorice x x x

Grindelia squarrosa curly-cup gumweed x x x 

Hackelia deflexa nodding stickseed x 

Hackelia floribunda showy stickseed x 

Helenium autumnale common sneezeweed x x

Helianthus nuttallii Nuttall’s sunflower x x x x 

Helianthus petiolaris prairie sunflower x 

Helianthus pauciflorus stiff sunflower x 

Heracleum lanatum cow-parsnip x x x x

Heterotheca villosa hairy golden aster x x

Hippuris vulgaris common mare's-tail x x

Humulus lupulus common hop x

Hydrophyllum spp. waterleaf spp. x x

Hypericum perforatum* St. John’s wort x x

Hyoscyamus niger* black henbane x x

Impatiens aurella orange balsam x x

Iris missouriensis Rocky Mountain iris x x x x

Iris pseudacorus* paleyellow iris x 

Lactuca biennis tall blue lettuce x

Lactuca serriola* prickly lettuce x x x

1 x

Lactuca tatarica var. 

pulchella

blue lettuce x x

Lathyrus ochroleucus cream-flowered peavine x

Lemna minor duckweed x x x x

Lepidium appelianum * globepod hoarycress x x

Lepidium draba* whitetop x x

Lepidium latifolium* perennial pepperweed x x

Lepidium perfoliatum* clasping pepperweed x x

Lepidium virginicum tall pepperweed x

Leucanthemum vulgare* oxeye daisy x x

Ligusticum canbyi Canby’s licorice-root x

Ligusticum tenuifolium slender-leafed licoriceroot

x x 

Linaria dalmatica* dalmation toadflax x

Linum perenne* blue flax x x x x

Linum rigidum yellow flax x

Linaria vulgaris* yellow toadflax, butter 

and eggs

x x x

Lithospermum ruderale western gromwell x

Lobularia maritima* sweet alyssum x

Lupinus argenteus silvery lupine x

Lupinus sericeus silky lupine x x x

Lycopus americanus cut-leaved water 

horehound

x
300 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Lycopus asper rough bugleweed x

Lygodesmia juncea skeletonweed x x

Lysimachia ciliata fringed loosestrife x x

Lysimachia thyrsiflora yellow loosestrife x x

Maianthemum racemosum feathery false lily of the 

valley

x

Maianthemum stellatum starry false Solomon’s 

seal

x x x x

Medicago lupulina* black medick x x x

Medicago sativa* alfalfa x x x

Melilotus officinalis* sweet-clover x x x x

Mentha arvensis wild mint x x x x

Menyanthes trifoliata buckbean x x

Mertensia ciliata mountain bluebell x x 

Mimulus guttatus common monkeyflower x x

Minuartia nuttallii Nuttall’s sandwort x

Mirabilis albida white four-o’clock x

Mitella breweri Brewer’s miterwort x 

Mitella stauropetala side-flowered miterwort x

Moehringia lateriflora bluntleaf sandwort x

Moehringia macrophylla bigleaf sandwort x x

Monarda fistulosa horsemint x 

Myosotis arvensis* field forget-me-not x

Myosotis laxa small-flowered forgetme-not

x x 

Myosotis scorpioides* common forget-me-not x x x x

Myriophyllum spicatum* Eurasian water milfoil x

Nasturtium officinale* watercress x x x 

Nepeta cataria* catnip x

Nuphar polysepala spatter-dock x 

Oenothera villosa hairy evening primrose x x x

Opuntia polyacantha plains pricklypear x x

Orthocarpus luteus yellow owl-clover x

Osmorhiza berteroi mountain sweet-cicely x x

1 x

Osmorhiza depauperata blunt-fruit sweet-cicely x

Osmorhiza occidentalis western sweet-cicely x

Osmorhiza purpurea purple sweet-cicely x 

Oxytropis spp. locoweed spp. x x 

Packera cana woolly groundsel x x

Packera pauciflora alpine groundsel x x

Packera pseudaurea var. 

pseudaurea

streambank groundsel x 

Packera subnuda few-leaved or Buek’s 

groundsel

x
301 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Parnassia fimbriata fringed grass-ofparnassus

x

Parnassia palustris northern grass-ofparnassus

x x 

Parietaria pensylvanica Pennsylvania pellitory x 

Pedicularis groenlandica elephant’s head x x

Penstemon confertus yellow penstemon x

Penstemon procerus var. 

procerus

pincushion beardtongue x x x 

Penstemon rydbergii Rydberg’s penstemon x

Perideridia gairdneri Gardner’s yampah x x

Petasites sagittatus arrowleaf sweet coltsfoot x x

Phacelia hastata silverleaf phacelia x 

Phacelia procera tall phacelia x

Physalis heterophylla clammy groundcherry x

Physostegia parviflora purple dragonhead x x 

Plantago eriopoda saline plantain x x x

Plantago major* common plantain x x x x

Platanthera dilatata white bog orchid x x x x

Platanthera hyperborean northern green bog 

orchid

x 

Polygonum amphibium water smartweed x x x x

Polygonum austiniae Austin’s knotweed x

Polygonum aviculare* prostrate knotweed x x x x 

Polygonum bistortoides American bistort x x

Polygonum convolvulus* black bindweed x x

Polygonum hydropiper* marshpepper smartweed x 

Polygonum lapathifolium curlytop knotweed x x x x

Polemonium occidentale western polemonium x x

Polygonum persicaria* ladysthumb x x 

Polemonium pulcherrimum skunk-leaved 

polemonium

x x 

Polygonum douglasii ssp.

johnstonii

Johnston’s knotweed x

Potentilla anserina common silverweed x x x x

Potentilla argentea* silvery cinquefoil x

Potamogeton diversifolius diverse-leaved 

pondweed

x 

Potentilla diversifolia diverse-leaved cinquefoil x x

Potentilla gracilis slender cinquefoil x x x x

Potamogeton gramineus grass-leaved pondweed x 

Potentilla norvegica Norwegian cinquefoil x

Potentilla palustris purple cinquefoil x x

Potentilla paradoxa bushy cinquefoil x 
302 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Potamogeton pectinatus fennel-leafed pondweed x

Potamogeton pusillus baby pondweed x 

Potamogeton richardsonii Richardson’s pondweed x

Potentilla rivalis brook cinquefoil x

Prosartes trachycarpa wartberry fairy-bell x

Prunella vulgaris heal all x x 

Pediomelum esculentum Indian breadroot x

Pyrrocoma integrifolia entire-leaved 

goldenweed

x x

Pyrola asarifolia pink wintergreen x x 

Pyrola elliptica white wintergreen x

Ranunculus sp. buttercup x x x

Ranunculus acriformis sharpleaf buttercup x x x

Ranunculus aquatilis water buttercup x x x

Ranunculus cymbalaria alkali buttercup x x x

Ranunculus flammula creeping buttercup x

Ranunculus gmelinii lesser yellow water 

buttercup

x x x 

Ranunculus macounii Macoun’s buttercup x x

Ranunculus hyperboreus Arctic buttercup x x

Ranunculus pensylvanicus Pennsylvania buttercup x x 

Ranunculus repens* creeping buttercup x x x

Ranunculus sceleratus celery-leaved buttercup x x x

Ranunculus longirostris longbeak buttercup x x 

Ratibida columnifera prairie coneflower x

Rhaponticum repens* Russian knapweed x x

Rorippa calycina persistent yellowcress x

Rorippa curvisiliqua western yellowcress x x

Rorippa curvipes blunt-leaf yellowcress x x

Rorippa palustris marsh yellowcress x x

Rorippa sylvestris* creeping yellowcress x x x x 

Rubus pubescens dwarf red blackberry x

Rudbeckia laciniata tall coneflower x

Rudbeckia occidentalis western coneflower x 

Rumex acetosella* sheep sorrel x x x

Rumex crispus* curly dock x x x x

Rumex maritimus golden dock x x x x

Rumex obtusifolius* bitter dock x x 

Rumex aquaticus var. 

fenestratus

western dock x x

Rumex salicifolius var. 

mexicanus

willow dock x x x

Sagittaria cuneata arumleaf arrowhead x 

Sagittaria latifolia broadleaf arrowhead x
303 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Salsola tragus* prickly Russian thistle x x

Sanicula marilandica Maryland sanicle x

Saxifraga odontoloma brook saxifrage x

Saxifraga oregana Oregon saxifrage x 

Scutellaria galericulata marsh skullcap x x x x

Sedum lanceolatum lance-leaved stonecrop x

Senecio hydrophiloides tall groundsel x x 

Senecio hydrophilus water ragwort x x

Senecio integerrimus lambstongue groundsel x x x

Senecio serra tall ragwort x x 

Senecio sphaerocephalus ballhead ragwort x

Senecio triangularis arrowleaf groundsel x x 

Silene csereii* bladder campion x

Silene douglasii Douglas’s catchfly x

Silene latifolia ssp. alba* bladder campion x x x 

Silene menziesii Menzies’ campion x

Sisymbrium altissimum* tall tumblemustard x x

1 x 

Sisyrinchium idahoense blue-eyed grass x x x x 

Sisymbrium loeslii* tumblemustard x x x

Sium suave hemlock waterparsnip x x x x

Solidago canadensis Canada goldenrod x x x x 

Solidago gigantea giant goldenrod x x

Solidago missouriensis Missouri goldenrod x x x

Solanum rostratum buffalobur nightshade x 

Sonchus arvensis* perennial or field 

sowthistle

x x x x

Sonchus asper* prickly sowthistle x

Sonchus oleraceus* common sowthistle x

Sparganium angustifolium narrowleaf bur-reed x 

Spirodela polyrhiza common duckmeat x

Spiranthes romanzoffiana hooded ladies tresses x

Stachys palustris swamp hedge-nettle x x x

1 x

Stellaria americana American chickweed x 

Stellaria calycantha northern starwort x

Stellaria longipes longstalk starwort x x x x

Stellaria umbellata umbrella starwort x x 

Stenotus lanuginosus wooly mock goldenweed x x

Streptopus amplexifolius clasping-leaved twisted 

stalk

x

Swertia perennis felwort x x 

Symphyotrichum campestre western meadow aster x x 

Symphyotrichum chilense Pacific aster x x x

1 x 

Symphyotrichum ciliolatum Lindley’s aster x
304 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Symphyotrichum eatonii Eaton’s aster x

Symphyotrichum falcatum white prairie aster x x x

Symphyotrichum foliaceum leafy aster x x

Symphyotrichum 

lanceolatum ssp. hesperium

white panicle aster x x x x

Symphyotrichum boreale northern bog aster x x

Symphyotrichum laeve smooth blue aster x x x

Symphyotrichum 

oblongifolium

aromatic aster x

Symphyotrichum 

spathulatum

western mountain aster x x x x

Symphyotrichum ericoides 

var. pansum 

white heath aster x x x x 

Tanacetum vulgare* common tansy x x x

Taraxacum laevigatum* rock dandelion x

Taraxacum officinale* common dandelion x x x x 

Thalictrum alpinum alpine meadowrue x

Thalictrum dasycarpum Purple meadowrue x x x 

Thalictrum fendleri Fendler’s meadowrue x x

Thalictrum occidentale western meadowrue x x x

Thalictrum sparsiflorum fewflower meadowrue x

Thalictrum venulosum veiny meadowrue x

Thermopsis montana mountain goldenbanner x 

Thermopsis rhombifolia prairie thermopsis x

Thlaspi arvense* field pennycress x x x

Triantha glutinosa sticky tofieldia x 

Tragopogon dubius* western salsify x x x x

Tragopogon pratensis meadow salsify x x

Trifolium aureum* hop clover x x 

Trifolium longipes longstalk clover x x x x

Triglochin maritimum seaside arrow-grass x x x x

Triglochin palustris marsh arrow-grass x

Trifolium pratense* red clover x x x x 

Trifolium repens* white clover x x x x

Typha angustifolia narrow-leaved cattail x 

Typha latifolia broadleaf cattail x x x x

Urtica dioica stinging nettle x x x x

Utricularia minor lesser bladderwort x 

Utricularia macrorhiza common bladderwort x x

Vaccaria hispanica* cow herb x

Valeriana dioica northern valerian x

Valeriana edulis tobacco root x x x x

Veronica americana American speedwell x x
305 

Scientific name Common name Hansen et al. (1995) Rice & 

Hardin 

(2002)

NPS 

(2014c)

Tree/shrub Herbaceous Riparian in 

GRKO

Veronica anagallis-aquatica water speedwell x x x x

Verbascum blattaria* moth mullein x

Veratrum californicum California false hellebore x

Veronica catenata chain speedwell x x

Verbena hastata blue verbena x 

Veronica officinalis* common speedwell x

Veronica peregrina purslane speedwell x

Veronica scutellata marsh speedwell x x

Verbena stricta hoary verbena x

Verbascum thapsus* common mullein x x x 

Veronica wormskjoldii American alpine 

speedwell

x 

Vicia americana American vetch x x x x

Viola canadensis Canada violet x

Viola sp. violet sp. x x

Viola macloskeyi small white violet x

Viola nephrophylla northern bog violet x x

Viola nuttallii Nuttall’s violet x

Viola orbiculata round-leaved violet x

Viola palustris marsh violet x 

Xanthium strumarium common or rough 

cocklebur

x 

Zigadenus elegans mountain death camas x x x

Zizia aptera heart-leaved alexanders x x x

Zizia aurea golden alexanders x

Ferns & allies

Athyrium filix-femina common ladyfern x

Equisetum arvense field horsetail x x x x

Equisetum fluviatile swamp horsetail x x x x

Equisetum hyemale scouringrush horsetail x x x x

Equisetum laevigatum smooth scouring-rush x x x x

Equisetum palustre marsh horsetail x 

Equisetum pratense meadow horsetail x x

Equisetum sylvaticum woodland horsetail x

Equisetum variegatum variegated horsetail x x 

Lycopodium spp. club-moss x

Pteridium aquilinum western brackenfern x

* Non-native species

1 Species documented in the riparian area by Rice and Smith (2011) but not Rice and Hardin (2002).
306 

Appendix D. NRCS riparian health assessment worksheets for GRKO.
307 
308 
309 
310 
311 
312 
313 
314 
315 
316 
317 
318 
319 
320 
321 

Appendix E. Invasive Species Monitoring

Introduction

This report compares the results of non-native invasive plant surveys performed at GRKO in 2003, 

2012, and 2013. Their purpose was to identify and map the distribution of non-native plant species 

that were of concern to park resource managers or were known to be invasive in other areas (Wood 

and Rew 2005). The 2003 survey was part of a larger inventory and mapping project initiated by the 

Intermountain Region (IMR) of the NPS (Wood and Rew 2005). The goals of the IMR project are to 

develop a database to assist resource managers with invasive plant management and control, to 

provide a baseline dataset for long term monitoring efforts, and to facilitate data sharing within the 

NPS and with external agencies (Wood and Rew 2005). The goals of the resource managers at 

GRKO were to develop maps of the location of non-native invasive plant species to assist with their 

management and restoration actions, to prioritize mapping in those habitats with an increased risk of 

invasion, particularly the upland ranges and the Clark Fork River riparian area, and to search for 

potential new invaders (Wood and Rew 2005). Several years after the 2003 survey, the Northern 

Rocky Mountains Exotic Plant Management Team (NRM EPMT) initiated control efforts to reduce 

invasive plant infestations within GRKO (NPS 2011). Thus, an additional goal of the 2012 and 2013 

surveys was to document the effects of invasive species control efforts.

Site Description

Grant-Kohrs Ranch is located in Deer Lodge, Montana and occupies 607 ha (1,500 ac) of irrigated 

pasture, upland rangelands, and riparian area along the Clark Fork River. The NPS manages GRKO 

as an active cattle ranch and an interpretive site open to the public (Wood and Rew 2005). The ranch 

has a number of buildings and corrals, along with several roads, irrigation ditches, and fenced areas 

(Wood and Rew 2005). 

Disturbance History

Currently the ranch is comprised of relatively intact upland grasslands along with irrigated mesic 

pastures that are managed for hay production and/or grazing (Wood and Rew 2005). A rail line and 

right-of-way area operated and managed by Burlington Northern/Santa Fe Railroad runs through the 

ranch. A borrow pit created from the excavations used to build the railroad grade is located at the 

north end of the ranch, and functions as a wetland (Wood and Rew 2005). GRKO is bisected by the 

Clark Fork River with approximately 51 ha (126 ac) of fenced riparian area located along the river 

(Wood and Rew 2005). The reach of the Clark Fork flowing through GRKO is part of the Clark Fork 

River Operable Unit of the Milltown Reservoir Sediments National Priority Superfund Site. Natural 

and anthropogenic hydrological processes have resulted in the deposition of high levels of heavy 

metals in the riparian area from upstream mining and smelting operations (Wood and Rew 2005). 

Justification for Action

The NPS considers the invasion of non-native plant species (exotics, non-indigenous species, 

invasive species, or weeds) as one of the most serious threats that faces the lands they manage (NPS

2009). These non-native invasive species are considered the second greatest threat to biodiversity 

after habitat destruction (Randall 1996). Because these species have characteristics that allow them to 
322 

rapidly invade new areas and out-compete existing native plant communities, they are often referred 

to as invasive species (Westerbrooks 1998). 

Invasive species are not necessarily noxious weeds. A noxious weed can be defined as any plant 

species that has been designated by a federal, state or county government as injurious to public 

health, agriculture, recreation, wildlife or property (Sheley et al. 1999). The State of Montana, in its 

County Weed Control Act (CNWCA), defines a noxious weed as a “...plant of foreign origin that 

can directly or indirectly injure agriculture, navigation, fish or wildlife, or public health” (Montana 

Weed Control Association 2009). Their control is required by the CNWCA (7-22-2101 MCA) and is 

usually administered within county districts. The CNCWA also requires weed management plans to 

incorporate all appropriate methods, including education, prevention, mechanical methods, biological 

controls, cultural methods, and general land management practices (MDA 2013). Currently there are 

32 plant species on the Montana state noxious weed list (Montana Weed Control Association 2009). 

A summary of the noxious weed status and applicable priority status for each of the non-native 

species found during the three GRKO surveys is listed in Table E-1. 

Table E-1. Noxious weed status of species identified in field surveys (Wood and Rew 2005, NPS 2012, 

Krogstad and Kamerman 2013, MSU 2014). 

Scientific Name Common Name MT Noxious Weed List MT Priority Status

Bromus tectorum cheatgrass 3

Centaurea stoebe spotted knapweed x 2B

Cirsium arvense Canada thistle x 2B

Convolvulus arvensis field bindweed x 2B

Cynoglossum officinale houndstongue x 2B

Euphorbia esula leafy spurge x 2B

Gypsophila paniculata babysbreath

Lepidium draba whitetop x 2B

Lepidium latifolium perennial pepperweed x 2A

Linaria dalmatica Dalmatian toadflax x 2B

Linaria vulgaris yellow toadflax x 2B

Potentilla recta sulfur cinquefoil x 2B

Ranunculus acris tall buttercup x 2A

Rhaponticum repens Russian knapweed x 2B

Tanacetum vulgare common tansy x 2B

Thlaspi arvense field pennycress

Priority 1A - These species have a very limited presence or are not present in the state. When detected management 

criteria requires prevention, education, and eradication. No Priority 1A species were identified in the field inventories.

Priority 1B - These species have a limited presence in the state. When present management criteria requires eradication 

or containment, with prevention and education elsewhere. No Priority 1B species were identified in the field inventories.

Priority 2A - These species are commonly found in isolated areas of the state. Management criteria requires containment 

and suppression where common; and eradication, prevention, and education where less abundant. 

Priority 2B - These species are abundant in the state, and widespread in many counties. Management criteria requires 

containment and suppression where abundant and widespread; and eradication, prevention and education where less 

abundant.

Priority 3 - These species are not identified as noxious weeds, but as regulated plants that have the potential to have 

significant negative impacts. Research, education, prevention, and control programs, where appropriate, are 

recommended to minimize the spread of these weeds. Control of these species is not mandated.
323 

Vegetation Community Survey History

Prior to the IMR non-native survey conducted in 2003, several studies had addressed the vegetation 

community and the presence of non-native plants in GRKO (Wood and Rew 2005). In 1983, the 

University of Montana (UM) performed an inventory of vascular plant species in GRKO (Rice and 

Ray 1984). This study included a checklist of native and non-native plants, but did not address 

species location or frequency. This inventory was also part of a larger assessment of toxic metal 

contamination of the soil and biota of the Clark Fork River riparian area (Rice et al. 1984). During 

the years 2000-2002, researchers from the UM updated the earlier plant inventory and also classified 

the species found as either native or non-native (Rice and Hardin 2002b). In 2002, Rice and Hardin 

(2002a) also conducted a survey of the riparian vegetation along the Clark Fork River within the 

ranch. This study compared the riparian communities in the Superfund site to similar uncontaminated 

riparian communities in Western Montana. Riparian communities were classified and mapped and 

data were collected on the riparian community structure and species composition. However, nonnative species were not specifically identified (Rice and Hardin 2002a). 

IMR Non-native Invasive Plant Survey

Non-native invasive plant surveys were conducted in GRKO in 2003, 2012 and 2013. These surveys 

were designed and conducted as part of the IMR non-native species project and also to address the 

GRKO resource managers’ management concerns and goals (Wood and Rew 2005). The 2003 

survey was conducted by Montana State University (MSU) during the period of 30 June – 7 July and 

9-10 September (Wood and Rew 2005). In 2012, surveys were conducted between 3 July and 2 

August (NPS 2012). The 2013 survey was conducted between 6 June and 8 August (Krogstad and 

Kamerman 2013). To address the specific concerns of GRKO, a methodology was created that used 

three different sampling protocols (Wood and Rew 2005). The specific protocol is discussed in Wood 

and Rew (2005), but in general surveys were conducted along transects within the GRKO 

management units. The locations of these units are shown in Figure E-1. The primary protocol was to 

collect data along transects, using Global Positioning System (GPS) receivers to record the 

occurrences of non-native invasive species (Wood and Rew 2005). The second protocol involved the 

delineation of transects in areas that were too topographically difficult to sample intensively. In these 

cases, the transects followed the landscape or geographical features (Wood and Rew 2005). A third 

method was used in the areas of least interest to GRKO resource managers or in areas where the 

invasive plant density throughout the survey unit made it difficult to accurately delineate them into 

distinct populations (Wood and Rew 2005). In these instances, the area was sampled by one of two 

methods. If possible, the area was sampled by one of the two methods described above, or by visual 

observations (Wood and Rew 2005). 

For all methods, whenever a non-native invasive species infestation was observed, it was delineated 

as either a point, polygon, or gross area (polygon) feature (Wood and Rew 2005). Small patches were 

generally mapped as point features and the length and width of the patch was recorded. The larger 

patches of infestation were mapped as either a polygon or gross area polygon. The difference being 

polygon features encompassed a distinct plant population and the gross area polygon feature mapped 

the general occurrence of the invasive species and a percent distribution within that area was 

recorded for use in calculating area (Wood and Rew 2005). 
324 

Figure E-1. Management Units (or field names) at GRKO as of 2003.

Area Infested with Non-native Invasive Plant Species

The surveys conducted in 2003, 2012 and 2013 covered approximately 343 ha (849 ac). A 

comparative summary of the 2003 and 2012 surveys, including cumulative infested area and total 

infested area, is shown in Table E-2 and graphically in Figure E-2. Due to differences in 

methodology, it may be inaccurate to directly compare results from the 2013 survey. The cumulative 

infested area includes any overlaps where a number of species might occupy portions of the same 

mapped patch or point, but each is considered as a unique infestation (Wood and Rew 2005). The 

total area infested was calculated by removing the overlapping areas in the calculation, so that even if 

a number of species infests the same physical space, the area infested is counted only once (Wood 
325 

and Rew 2005). The results of the 2003 and 2012 surveys show that overall there has been a 

significant reduction in the area of the infestations on the ranch. As shown in Table E-2 and Figure 

E-2, the cumulative area decreased from approximately 256 ha (632 ac) in 2003 to only 119 ha (293 

ac) in 2012. The total infested area dropped from 223 ha (550 ac) to 106 ha (261 ac). 

Figure E-2. Comparison of the 2003 and 2012 field surveys in terms of area surveyed, cumulative 

infested area, total infested area and uninfested area (Wood and Rew 2005, NPS 2012). Results from the 

2013 survey are not included because direct comparisons may be inaccurate due to differences in 

methodology.

Table E-2. Summary of non-native invasive species field inventory results (Wood and Rew 2005, NPS 

2012). 

Hectares (acres)

2003 2012

Survey Area 343.5 (848.9) ~340 (~840)1

Cumulative Infested Area 255.7 (631.8) 118.7 (293.2)

Total Infested Area 222.4 (549.5) 105.5 (260.6)

Uninfested Area 121.1 (299.3) 238.1 (588.3)

1 Total area surveyed in 2012 was similar to 2003 but likely not exact. 

Non-native Invasive Plant Species Composition at GRKO

A total of 16 non-native invasive plant species were recorded in GRKO during the 2003 and 2012 

surveys (Figure E-3) and their infestation levels are provided in Table E-3. Of these, only cheatgrass, 

0

100

200

300

400

500

600

700

800

900

2003

2012

Area (acres)

Survey area

Cumulative Infested Area

Total Infested Area

Uninfested Area
326 

babysbreath (Gypsophila paniculata), and field pennycress are not on the noxious weed lists for the 

State of Montana (Table E-1). Cheatgrass is a regulated Priority 3 species in Montana, and 

babysbreath is listed as a noxious weed in nearby counties in Montana (Deerlodge and Silver Bow). 

The area infested declined from the 2003 levels for the majority of species; however, four species 

were recorded in 2012 that had not been documented in 2003. Again, due to differences in 

methodology, it may be inaccurate to directly compare results from the 2013 survey to the 2003 and 

2012 results. However, 2013 results are summarized separately in Table E-5. A summary of all three

surveys’ findings for each species is provided in the remainder of this appendix. 

Figure E-3. Comparison of cumulative areas for non-native invasive species identified during field 

surveys (Wood and Rew 2005, NPS 2012, Krogstad and Kamerman 2013). Results from the 2013 survey 

are not included because direct comparisons may be inaccurate due to differences in methodology.
327 

Table E-3. Composition of non-native invasive plant species identified during 2003 and 2012 field 

inventories (Wood and Rew 2005, NPS 2012). 

Cumulative Area Infested

hectares (acres)

Number of Observed 

Infestations

Species 2003 2012 2003 2012

Bromus tectorum -- 38.31 (94.67) -- 49

Centaurea stoebe 53.37 (131.87) 37.12 (91.72) 219 71

Cirsium arvense 91.54 (226.19) 6.45 (15.93) 100 78

Convolvulus arvensis 28.34 (70.04) 9.60 (23.73) 34 15

Cynoglossum officinale 0.08 (0.19) 1.58 (3.90) 16 5

Euphorbia esula 16.35 (40.40) 0.33 (0.82) 26 31

Gypsophila paniculata 16.88 (41.71) 0.05 (0.12) 70 5

Lepidium draba 12.02 (29.69) 0.12 (0.30) 60 61

Lepidium latifolium 12.14 (30.00) 0.18 (0.44) 56 48

Linaria dalmatica -- < 0.005 (<0.01) -- 1

Linaria vulgaris 15.21 (37.58) 0.06 (0.14) 38 18

Potentilla recta -- 16.66 (41.18) -- 19

Ranunculus acris 9.68 (23.93) 6.26 (15.46) 5 7

Rhaponticum repens 0.06 (0.16) 0.02 (0.04) 4 1

Tanacetum vulgare 0.01 (0.03) < 0.005 (<0.01) 8 3

Thlaspi arvense -- 1.92 (4.75) -- 65

Totals 255.68 (631.79) 118.66 (293.21) 636 477

Table E-4. Distribution of non-native invasive species identified during 2003 and 2012 field inventories 

(Wood and Rew 2005, NPS 2012). 

Percent Cumulative Area Infested Percent Observed Infestations

Species 2003 2012 2003 2012

Bromus tectorum -- 32.3% -- 10.3%

Centaurea stoebe 20.9% 31.3% 34.4

%

14.9%

Cirsium arvense 35.8% 5.4% 15.7

%

16.4%

Convolvulus arvensis 11.1% 8.1% 5.3% 3.1%

Cynoglossum officinale < 0.1% 1.3% 2.5% 1.0%

Euphorbia esula 6.4% 0.3% 4.1% 6.5%

Gypsophila paniculata 6.6% < 0.1% 11.0

%

1.0%

Lepidium draba 4.7% 0.1% 9.4% 12.8%

Lepidium latifolium 4.7% 0.1% 8.8% 10.1%

Linaria dalmatica -- < 0.1% -- 0.2%

Linaria vulgaris 5.9% < 0.1% 6.0% 3.8%

Potentilla recta -- 14.0% -- 4.0%

Ranunculus acris 3.8% 5.3% 0.8% 1.5%

Rhaponticum repens < 0.1% < 0.1% 0.6% 0.2%

Tanacetum vulgare < 0.1% < 0.1% 1.3% 0.6%

Thlaspi arvense -- 1.6% -- 13.6%

2013 Totals ~340 (~840) 18.7 (46.3) 4.6 

(11 4)

338.9 (837.5)
328 

Table E-5. Summary of 2013 non-native invasive plant survey results (Krogstad and Kamerman 2013). 

Species

Cumulative Area 

Infested

hectares (acres)

Number of 

Observed 

Infestations

Percent 

Cumulative 

Area Infested

Percent 

Observed 

Infestations 

Centaurea stoebe 2.08 (5.13) 129 11.1% 11.8%

Cirsium arvense 2.24 (5.53) 129 11.9% 11.8%

Convolvulus arvensis 1.72 (4.25) 24 9.2% 2.2%

Cynoglossum officinale < 0.005 (<0.01) 4 < 0.1% 0.4%

Euphorbia esula 5.74 (14.18) 154 30.6% 14.1%

Gypsophila paniculata 0.67 (1.66) 46 3.6% 4.2%

Lepidium draba 2.57 (6.34) 242 13.7% 22.1%

Lepidium latifolium 1.48 (3.66) 175 7.9% 16.0%

Linaria vulgaris 0.49 (1.22) 76 2.6% 6.9%

Potentilla recta < 0.005 (<0.01) 1 < 0.1% < 0.1%

Ranunculus acris 1.76 (4.35) 114 9.4% 10.4%

Totals 18.75 (46.32) 1094 --- ---

Cheatgrass (Bromus tectorum) 

Montana does not list cheatgrass as a noxious weed, but the state has identified it as a Priority 3, 

regulated plant (MSU 2014). Plants with this designation have the potential to have significant 

negative impacts. While control of these species is not mandated, research, education, prevention, 

and control programs are recommended to minimize spread (MSU 2014). 

Cheatgrass plants range from 15 to 61 cm (6 to 24 in) tall (Menalled et al. 2012). In early growth 

stages, leaves are brownish-green while at maturity the plant is red-brown in color and has erect, 

slender stems (Menalled et al. 2012). Leaf sheaths are flat, twisted blades with long, narrow leaves, 

and small soft hairs cover the entire plant (Menalled et al. 2012, Montana Weed Control Association 

2014). At maturity, cheatgrass has purple colored branched clusters of seed heads and slender 

extensions (awns) on the seeds (Montana Weed Control Association 2014). The awns stick to 

clothing and the hair and fur of animals, one of the vectors the plant utilizes for seed dispersal 

(Menalled et al. 2012). Cheatgrass is a prolific seed producer, with seeds remaining viable for two to 

three years (Menalled et al. 2012). Cheatgrass is extremely adaptable and can be found growing on 

all exposures and all types of topography (Montana Weed Control Association 2014). It infests 

heavily grazed rangeland, roadsides, burned areas and other disturbed areas quickly (Montana Weed 

Control Association 2014). It can also invade undisturbed areas and out-compete native vegetation 

(Montana Weed Control Association 2014). 

The field survey conducted by Wood and Rew (2005) in 2003 did not include cheatgrass as a target 

species and therefore no occurrences of the species were mapped. During the 2012 survey it 

accounted for nearly a third of the cumulative infested area mapped (NPS 2012). Forty-nine patches 

of cheatgrass covering nearly 38 ha (95 ac) were mapped (Table E-3). The majority of the 

infestations were found west of the Clark Fork River (Figure E-4). Seven patches were 0.4 ha (1 ac) 

or larger (NPS 2012). The largest of these patches, approximately 10.5 ha (26 ac), was located in 
329 

pastureland (Upper Northwest Range). Another patch of approximately 6.5 ha (16 ac) was also 

located in this pasture. A large infestation, covering approximately 10 ha (25 ac) was also found in 

the railroad remnant area. The remaining large patches were located in pastureland; a 4.3 ha (10.6 ac) 

patch in River Ridge Road, 5.5 ha (13.5 ac) and 0.6 ha (1.5 ac) patches in Gravel Pit Range, a 0.4 ha 

(1 ac) patch in Taylor Ridge Range and 1,214 m2 (0.3 ac) and 1,618 m2

 (0.4 ac) patches in VC North 

and South (NPS 2012). The remaining 40 patches were mapped as point infestations, and with the 

exception of one (along west side road), all were less than 405 m2

 (0.1 ac). This patch in the upland 

area along the west side road was measured at just over 405 m2

 (0.1 ac) (NPS 2012). The other 

patches were found in a mixture of pasture and hayland, and one was found along Taylor Creek (NPS 

2012). The 2013 field efforts did not survey for cheatgrass, so no infestations were mapped 

(Krogstad and Kamerman 2013). 

Figure E-4. Location of cheatgrass infestations found during the three field surveys. Note that the 2013 

field efforts did not survey for cheatgrass, so no infestations were mapped.

Spotted knapweed (Centaurea stoebe) 

Montana classifies spotted knapweed as a noxious weed (MDA 2013). The state has designated it as 

a Priority 2B species (MDA 2013). Control of 2B species requires eradication or containment of 

existing infestations coupled with education and prevention measures (MSU 2014). 
330 

Spotted knapweed is a short-lived perennial species that can grow as tall as 1.2 m (4 ft) in height 

(Montana Weed Control Association 2014). It has slender, many-branched stems with a single flower 

at the end of each branch (Duncan et al. 2011). Stems and leaves are normally blue-green in color 

(Montana Weed Control Association 2014). The flowers are normally a pinkish-purple, but can also 

be light purple or white. The flower heads are surround by bracts (small leaf-like structures) that give 

a “spotted” appearance to the flower head (Duncan et al. 2011). Spotted knapweed is a prolific seed 

producer, with one plant producing up to 300 flower heads and up to 140,000 seeds (Montana Weed 

Control Association 2014). Spotted knapweed prefers disturbed areas with sunny arid conditions in 

coarse soils. It is most often found in sunny areas with well drained or gravel/sandy soils (Montana 

Weed Control Association 2014). It is highly adaptable and shade tolerant, allowing it to grow in 

both moist and dry conditions (Montana Weed Control Association 2014). 

Spotted knapweed was one of the most abundant non-native invasive plants mapped at GRKO during 

all three field surveys (Table E-4). In the 2003 survey, only Canada thistle was mapped in greater 

numbers or cumulative area (Table E-3). A total of 219 instances were mapped in 2003 (Figure 5). 

Of this total, the vast majority were mapped as point features (201) ranging in size from a single 

plant to 0.6 ha (1.5 ac) (Wood and Rew 2005). Eighteen instances were mapped as polygon features, 

all but two being less than 2.8 ha (7 ac) (Wood and Rew 2005). The Burlington Northern railroad and 

right-of-way was infested through the length of the ranch, covering nearly 14.9 ha (36.8 ac) (Wood 

and Rew 2005). The other large area, totaling 8.6 ha (21.2 ac), was located in the Railroad Remnant 

and KM Flats (Wood and Rew 2005). Due to their particularly dense nature, some of the areas in the 

Railroad Remnant and KM Flats area were also mapped as point features. Other areas with 

significant numbers of small infestations mapped as point features included the Gravel Pit Range, 

Ridge Road Range, Taylor Ridge Range, Upper Northwest Range, Upper Taylor Field, and the VC 

North and South Fields. A number of infestations were found in the riparian area, generally close to 

the river along gravel bars (Wood and Rew 2005). 
331 

Figure E-5. Location of spotted knapweed infestations found during the three field surveys.

Results of the 2012 survey showed significant declines in both the number of spotted knapweed 

infestations mapped and in cumulative area infested (Table E-3). As was the case in 2003, it was still 

the second most abundant invasive plant mapped. A total of 71 infestations were mapped during the 

2012 survey (NPS 2012). The majority of these were small patches mapped as point features (66), all 

of which were less than 405 m2 (0.1 ac) with one exception, a 1,618 m2 (0.4 ac) infestation on a 

hillside in the Taylor Ridge Range (NPS 2012). As can been seen in Figure E-5, the point infestations 

mapped in 2012 were basically in the same locations as in 2003, but the number of infestations had 

been reduced. However, a few new infestations were found, mostly in the North Meadows Field 

(NPS 2012). The large KM Flat infestation found in 2003 had been reduced to three smaller point 

infestations (Figure E-5). The railroad and railroad right-of-way remained infested throughout the 

ranch. While the overall cumulative area infested in this area remained relatively unchanged from the 

2003 survey, the denser patches that had been separately delineated as points in 2003 had been 

reduced enough by 2012 to not warrant a separate point delineation (NPS 2012). The infestations in 

the northern portion of the Taylor Ridge Range (Figure E-5) that were mapped as a 1.4 ha (3.4 ac) 

polygon along with a few small point infestations in 2003, was mapped as a single polygon 

infestation of approximately 6.7 ha (16.5 ac) (NPS 2012). Additionally, two new polygon infestations 
332 

were mapped in the Pump House 1 (4.6 ha [11.4 ac]) and L Barn Field 93.1 ha [7.7 ac]), areas that 

were not present in 2003 (NPS 2012). 

In the 2013 field survey, spotted knapweed was still one of the more abundant invasive species found 

(Table E-5). The number of infestations increased from 2012 levels (perhaps due to a longer survey 

period) but the cumulative area infested was reduced (Krogstad and Kamerman 2013). The large 

infestations that had been previously mapped as polygons were reduced to only a few infestations 

that were mapped as points. The railroad and railroad right-of-way showed no signs of spotted 

knapweed (Figure E-5). The increase in the number of point infestations mainly was the result of new 

detections in the Effluent Fields and the fact that the polygon infestation in the L Barn Field had been 

replaced by a large number of point infestations (Krogstad and Kamerman 2013). 

Canada thistle (Cirsium arvense) 

Montana lists Canada thistle as a noxious weed (MDA 2013). The state has designated it as a Priority 

2B species (MDA 2013), requiring eradication or containment of existing infestations coupled with 

education and prevention measures (MSU 2014). 

Canada thistle can grow up to 1.2 m (4 ft) tall and develops a deep and extensive root system. Leaves 

are lance-shaped and deeply loped, with yellowish spines on the edges. Its flowers resemble spotted 

knapweed in that they are pink to purple in color. Plants produce both male and female flowers, with 

the male flower heads resembling globes while the female flowers are flask-shaped. Each female 

flower produces a single seed with a papery cover that is easily dispersed by wind. Both male and 

female flowers must be present for the plant to go to seed. A single plant can produce over 3,000 

seeds annually. Canada thistle reproduces by seed dispersal, but spreads primarily through horizontal 

roots (Montana Weed Control Association 2014). Canada thistle is generally found in open areas 

with moderate moisture. It often invades areas where water levels fluctuate, such as stream banks or 

irrigation ditches. It is also commonly found in fallow fields, abandoned lots, pastures, road ditches 

and right-of-ways, railway embankments and right-of-ways, and abandoned gravel pits (Montana 

Weed Control Association 2014). 
333 

Figure E-6. Location of Canada thistle infestations found during the three field surveys.

Canada thistle was the most abundant non-native invasive plant mapped at GRKO in 2003, both in 

cumulative area and number of mapped infestations (Wood and Rew 2005). In terms of infested area, 

it was nearly double the area infested by spotted knapweed with less than half the number of mapped 

infestations (Table E-3). It was found along irrigation ditches, creeks, and around the borrow pit 

wetland (Figure E-6). In all, 100 infestations were mapped covering 91.5 ha (226 ac) (Table E-3). 

The majority of these were mapped as point infestations, with 14 being large enough to be mapped as 

polygon features (Wood and Rew 2005). These larger infestations ranged in size from 0.4 – 23.5 ha 

(1 - 58 ac) (Wood and Rew 2005). The largest of these were located in the Lower Taylor Field (23.5 

ha [58 ac]), the riparian area (20 ha [49.5 ac]), and along the Westside and Hartz irrigation ditches 

(15.9 ha [39.4 ac]) (Wood and Rew 2005). Other large infestations were found in Big Gulch (13.4 ha 

[33.2 ac]) and the Kohrs-Manning Ditch (9.7 ha [23.9 ac]) (Wood and Rew 2005). The infestations 

mapped as point features were primarily found along the Westside and Kohrs-Manning Ditches, the 

railroad right-of-way and railroad remnant area, Little Gulch, and VC North and South (Wood and 

Rew 2005). 

The results of the 2012 field survey showed that while Canada thistle was still the most abundant 

invasive species in terms of number of infestations, it only accounted for approximately 5.5% of the 
334 

total cumulative infested area (Table E-3; NPS 2012). This was a significant decline from 

infestations representing 36% of the total in the 2003 field survey (Table E-4). A total of 78 

infestations were mapped in 2012, only four of which were mapped as polygon features, ranging in 

size from 0.12 ha – 2.8 ha (0.3 ac - 7 ac) (NPS 2012). The large infestations in Lower Taylor and the 

riparian areas had been reduced to a few point infestations (Figure E-6). The large infestation in Big 

Gulch had been reduced in size to a patch of 2.8 ha (7 ac) and a few point features (NPS 2012). One 

new infestation was mapped in the Lower Yards Field covering just under 2.8 ha (7 ac) (NPS 2012). 

The infestation along the Westside Ditch had been reduced to a few point infestation (NPS 2012). 

For the remaining infestations mapped as point features, reductions were seen in most areas, 

including the Kohrs-Manning Ditch, Little Gulch, VC North and South, the railroad and railroad 

right-of-way and the railroad remnant area. A few new infestations were mapped in 2012, primarily 

in the North Meadows, Pump House 3 and Effluent Field areas (Figure E-6). 

During the 2013 field survey, all 129 infestations of Canada thistle were mapped as point features 

(Figure E-6). Canada thistle was still one of the more abundant invasive species mapped, comprising 

approximately 12% of both the cumulative area infested and number of infestations identified during 

the 2013 field survey (Table E-5). Only 20 of the mapped infestation were larger than 405 m2

 (0.1 

ac). They ranged in size from 405 m2

 – 809 m2 (0.1 ac - 0.2 ac) (Krogstad and Kamerman 2013). The 

infestations in the North Meadows, Lower Yards Fields, and VC North and South were not present in 

2013. The number of infestations in Lower Taylor, Railroad Remnant, Stuart Field and Effluent Field 

were reduced. The 2013 survey also found an increase in the number of mapped observations in Big 

Gulch, Pump House 1, 2 and 3, L Barn Field and Westside Ditches (Krogstad and Kamerman 2013). 

Field bindweed (Convolvulus arvensis) 

Montana lists field bindweed as a noxious weed and has designated it as a Priority 2B species (MDA 

2013). Control of 2B species requires eradication or containment of existing infestations coupled 

with education and prevention measures (MSU 2014). 

Field bindweed is a perennial vine with an extensive root system that grows both laterally and 

vertically, creating a dense mat system beneath the soil surface. It grows along the ground until it 

encounters an obstacle to climb, where it will climb and form dense infestations. Its roots are cordlike and white and produce buds which form new shoots. Field bindweed has dark green smooth 

arrow-shaped leaves. Flowers are white and pink in color, bell-shaped and about 2.5 cm (1 in) in 

diameter. Field bindweed produces pear-shaped seeds, but reproduces primarily through its root 

system (Montana Weed Control Association 2014). Field bindweed can be found in most disturbed 

areas or disturbed habitats. It prefers sunny areas and uses its vine system to move into sunlight 

(Montana Weed Control Association 2014). 

The 2003 field inventory identified 34 field bindweed infestations (Table E-3). This accounted for 

roughly 5% of the total number of infestations and 11% of the cumulative infested area (Table E-4). 

Thirty of these infestations were comprised of point features that were under 0.4 ha (1 ac) in size 

(Wood and Rew 2005). Only seven of these point infestations were greater than 405 m2

 (0.1 ac), 

ranging in size from 405 m2

 – 3,237 m2 (0.1 ac - 0.8 ac) (Wood and Rew 2005). Four infestations 

were mapped as polygon features, ranging in size from 1.6 ha to 14.6 ha (4 ac to 36 ac) (Wood and 
335 

Rew 2005). Large areas of field bindweed infestation were found along the Westside Ditch (9.1 ha 

[22.5 ac]), Lower Taylor Field (14.7 ha [36.2 ac]) and Little Gulch (3.5 ha [8.6 ac]) (Figure 7). The 

smaller infestations mapped as point features were found in several areas, the majority being in the 

Kohrs and Westside Ditches, Upper Taylor Range, and Taylor Ridge Range areas (Wood and Rew 

2005). 

Figure E-7. Location of field bindweed infestations found during the three field surveys.

The results of the 2012 field survey showed a decline in both the number of infestations and the 

cumulative area infested (Table E-3). In 2012, field bindweed accounted for only 3% of the total 

number of infestations and 8% of the cumulative area infested on the ranch (Table E-4). Thirty-four 

infestations were identified with only two being large and dense enough to map as a polygon feature. 

One of the polygon infestations was in Little Gulch, where the 3.5 ha (8.6 ac) patch mapped in 2003 

had expanded to 6.2 ha (15.4 ac) (NPS 2012). The other was a 3.3 ha (8.1 ac) patch in Taylor Ridge 

Range (NPS 2012). The infestation along the Westside Ditch was not present, nor was the large 

infestation in Lower Taylor (Figure E-7). All of the infestations mapped as point features, except 

one, were less than 40 m2

 (0.01 ac) (NPS 2012). The one larger point feature was 525 m2 (0.13 ac) in 

size and located in the Taylor Ridge Range (NPS 2012). The location of the infestations mapped 
336 

during 2012 was similar to 2003. New infestations were found in Pump House 3 and 4 and the 

Effluent Field (NPS 2012). 

The 2013 survey showed a continued decline in the cumulative infested area but a slight increase in 

the number of infestations mapped. While field bindweed was on the lower end of the scale in terms 

of number of occurrences, it still was one of the more abundant non-native invasive species in terms 

of cumulative area infested (Table E-5). Twenty-four infestations were mapped in 2013, all as point 

features, ranging in size from 405 m2

 – 809 m2 (0.1 ac - 0.2 ac) (Krogstad and Kamerman 2013). The 

point infestations mapped in 2012 in Ridge Road Range, Pump House 3 and 4, VC North and South, 

and Effluent Field were not present (Figure E-7). The large infestation in Little Gulch was reduced to 

a small patch of approximately 809 m2 (0.2 ac) (Krogstad and Kamerman 2013). The 2013 inventory 

also identified infestations in Upper Taylor and Pump House 1, which were not present in the 2003 

survey (Krogstad and Kamerman 2013). 

Houndstongue (Cynoglossum officinale) 

Montana has classified houndstongue as a noxious weed (MDA 2013). The state has designated it as 

a Priority 2B species (MDA 2013). Houndstongue is a biennial forb with a deep tap-root (Montana 

Weed Control Association 2014). In its first year it forms a basal rosette with broad oblong leaves up 

to 25.4 cm (1 ft) in length and 7.6 cm (3 in) wide. It forms stems in its second year and can grow up 

to 101 cm (4 ft) in height. It produces five-petaled reddish-purple flowers with four triangular 

rounded seeds. These seeds easily attach to animals, humans and vehicles (Montana Weed Control 

Association 2014). Houndstongue prefers well-drained, relatively sandy/gravelly soils. It is often 

found in disturbed areas such as trails, roadsides and abandoned cropland, rangeland, pastureland and 

riparian areas (Kedzie-Webb and Sheley 2009). 

The 2003 field survey mapped 16 patches covering approximately 809 m2

 (0.2 ac) (Table E-3). It 

accounted for 2.5% of the total number of observations and less than 0.1% of the cumulative infested 

area (Table E-4). The majority of the houndstongue infestations were found close to the railroad 

right-of-way, railroad remnant area or Johnson Creek areas (Figure E-8). All houndstongue 

infestations were less than 405 m2

 (0.1 ac) (Wood and Rew 2005). 
337 

Figure E-8. Location of houndstongue infestations found during the three field surveys.

The 2012 field survey found only five infestations; however, the cumulative infested area increased 

from the 2003 level (Table E-3). This was due to the mapping of one large infestation of almost 1.6 

ha (4 ac) in the railroad remnant area (NPS 2012). Four smaller patch infestations were mapped in 

the Johnson Creek area. All were less than 40 m2

 (0.01 ac) (Wood and Rew 2005). Of the locations 

where infestations were mapped in 2003, only those in the Johnson Creek and railroad remnant areas 

remained (Wood and Rew 2005). 

The 2013 survey identified only four small infestations covering less than 40 m2

 (0.01 ac) (Table E5). They were all located within the railroad right-of-way area (Figure E-8) and were not present in 

the 2012 survey (Krogstad and Kamerman 2013). 

Leafy spurge (Euphorbia esula) 

Montana lists leafy spurge as a noxious weed and has designated it as a Priority 2B species (MDA

2013), requiring eradication or containment of existing infestations coupled with education and 

prevention measures (MSU 2014). 
338 

Leafy spurge is a deep-rooted perennial that can grow up to 0.91 m (3 ft) in height (Montana Weed 

Control Association 2014). The leaves and stems of leafy spurge are bluish green and produce a 

yellow-green flower arranged in clusters of seven to ten. The roots have pink buds which develop 

into new shoots. The plant also produces seed capsules containing grayish-brown oblong seeds 

(Montana Weed Control Association 2014). Leafy spurge is a highly adaptable plant that grows in a 

variety of dry and moist habitats and in a variety of soil conditions (Goodwin et al. 2001, Montana 

Weed Control Association 2014). It is commonly found in abandoned cropland, pasture, rangeland, 

or along waterways or irrigation ditches (Goodwin et al. 2001, Montana Weed Control Association 

2014). 

Figure E-9. Location of leafy spurge infestations found during the three field surveys.

During the 2003 field inventory, leafy spurge was abundant in the riparian area (Figure E-9). Four 

nearly contiguous polygons totaling just over 15.8 ha (39 ac) were mapped along the Clark Fork 

River (Wood and Rew 2005). Another ten infestations, totaling just under 0.4 ha (1 ac) were also 

mapped as small point features in this area (Wood and Rew 2005). In all, 99% of the 16.3 ha (40.4 

ac) infested were found in the riparian area (Table E-3). Other leafy spurge infestations were mainly 

confined to the borrow pit, Johnson Creek, Gravel Pit Range, Taylor Ridge Range, Big Gulch and 

along the Westside road (Wood and Rew 2005). Five infestations, all under 40 m2

 (0.01 ac), were 
339 

mapped in the borrow pit area (Wood and Rew 2005). Single infestations, also under 40 m2

 (0.01 ac), 

were mapped in the Johnson Creek, Gravel Pit Range, and Big Gulch (Figure E-9). Two slightly 

larger patches of 243 m2

 and 162 m2 (0.06 ac and 0.04 ac) were mapped along the Westside road 

(Wood and Rew 2005). Another slightly larger infestation (607 m2

 [0.15 ac]) was located in the 

Taylor Ridge Range (Wood and Rew 2005). 

The inventory conducted in 2012 showed a marked reduction in the area infested by leafy spurge, 

although the number of mapped infestations increased slightly (Table E-3). The inventory found less 

than 0.4 ha (1 ac) of GRKO infested with leafy spurge (NPS 2012). The infestation in the riparian 

area had been reduced to four small point infestations covering less than 60 m2

 (0.015 ac) (NPS 

2012). The number of infestations in the borrow pit area had also been reduced from five to two 

small infestations (NPS 2012). The number of infestations in the Gravel Pit Range also had 

decreased from 2003 levels (NPS 2012). Figure E-9 shows that infestations were found in other 

areas of the ranch in 2012 where they were not present in 2003. In addition, some of the areas 

infested in 2003 showed an increase in number of infestations. In Big Gulch, the number of 

infestations increased from one to three, but the total area infested remained relatively unchanged at 

<40 m2

 (0.01 ac) (NPS 2012). The number of infestations also increased along the railroad tracks and 

in the railroad remnant area. This area went from having only one mapped instance in 2003 (<40m2

[< 0.01 ac]) to ten infestations covering 202 m2

 (0.05 ac) in 2012 (NPS 2012). New infestations were 

mapped in the Upper Northwest Range, Little Gulch, North Meadows, Stuart Annex and Pump 

House 4 fields. The infestations in the Pump House 4 field included the only infestation mapped as a 

polygon in 2012, a 0.3 ha (0.7 ac) patch in the northeast corner of the field (NPS 2012). 

The results of the 2013 survey found a greater number of infestations and a greater total area infested

than in 2012 (Table 5). This was primarily from the increased number of infestations found in the 

riparian area. Although the 2013 survey mapped only point infestations, the pattern of infestation in 

the riparian area was very similar to that found during the 2003 survey (Figure E-9). Of the 154 

infestations mapped in 2013, 72% (111) were in the riparian area. These infestations ranged in size 

from <40 m2

 to 809 m2 (<0.01 ac to 0.2 ac) with 82 of these being greater than 40 m2 (0.01 ac) 

(Krogstad and Kamerman 2013). Of the infestations greater than 40 m2

, 87% of those were between 

405 m2 and 809 m2

 (0.1 ac and 0.2 ac) (Krogstad and Kamerman 2013). Other significant changes 

included an increase in the number of infestations found in the Westside Ditch and in the Pump 

House 1, 2, and 3 fields (Krogstad and Kamerman 2013). A few areas showed a decrease in the 

number of infestations, including areas along the railroad tracks, and in North Meadows, Taylor 

Ridge Range, and Little Gulch. The 2013 survey also found infestations in VC North and South, 

Taylor Creek, Johnson Creek and Johnson Creek feedlot areas that had not been present in either of 

the previous surveys (Krogstad and Kamerman 2013). 

Babysbreath (Gypsophila paniculata) 

Although the State of Montana does not classify babysbreath as a noxious weed, it is on county 

noxious weed lists for neighboring Deer Lodge and Silver Bow counties (Wood and Rew 2005). It 

was included in the survey as ranch managers were concerned about its spread on the ranch from a 
340 

potential downwind source in the Deer Lodge cemetery, located south of the ranch (Wood and Rew 

2005). 

Babysbreath is a perennial herb with a deep penetrating root system. It has a smooth stem, with linear 

leaves that are opposite one another. Babysbreath has many branches and grows to almost 0.91 m (3 

ft) in height. The plant develops flower buds in its third year, and then produces clusters of white 

flowers; it spreads primarily through seed production. Babysbreath is found in a variety of habitats, 

including roadsides, ditches, pasture and rangeland areas (British Columbia Ministry of Agriculture 

2014). 

The 2003 survey found babysbreath predominantly infesting the upland range sites (Figure E-10). 

Overall, nearly 17 ha (42 ac) were infested (Table E-3). The largest density of infestation was found 

in the Gravel Pit Range (Wood and Rew 2005). This density made it difficult to map unique patches, 

so the entire unit was mapped as a gross area and unique patches were mapped within this area when 

they had a higher than average canopy cover (Wood and Rew 2005). Within the gross area, one 

polygon with 30% canopy cover was mapped along the road at the south end of the range and 

extended up into the old gravel pit (Figure E-10). Seven additional infestations were mapped in the 

Gravel Pit Range, all but one 93,642 m2

 [0.9 ac]) were less than 80 m2 ( 0.02 ac) (Wood and Rew 

2005). The total area infested in the Gravel Pit Range was 4.4 ha (10.9 ac) (Wood and Rew 2005). 

The next largest infestation was found in the Taylor Ridge Range. Two large patches and 17 smaller 

point patches were mapped. The total area infested was approximately 10.9 ha (27 ac), with the two 

large patches accounting for 10.5 ha (26 ac) (Wood and Rew 2005). Additional smaller patch 

infestations were found in the Upper Northwest Range (1,214 m2

 [0.3 ac]), Ridge Road Range (0.4 

ha [1 ac]) and Little Gulch (162 m2

 [0.04 ac]) (Wood and Rew 2005). Other infestations, comprised 

mainly of isolated individual plants, were found in the Taylor Creek, Lower Taylor, and Big Gulch 

areas, Westside Ditches, on a gravel bar in the riparian area, and two large plants next to the walkway 

from the Visitor Center to the Kohrs House (Wood and Rew 2005). 
341 

Figure E-10. Location of babysbreath infestations found during the three field surveys.

The survey conducted in 2012 showed a decline in the infestations of babysbreath in terms of 

numbers and total area (Table E-3). None of the large infestations found in 2003 were evident in the 

2012 survey (Figure E-10). Five small patches were mapped, two in the Taylor Ridge Range, and one 

each in the Lower Taylor, Ridge Road Range and Upper Northwest Range (NPS 2012). 

The 2013 survey showed both an increase in the number and total area of infestations from 2012 

(Table E-5). However, it still was significantly below the original findings in 2003. The majority of 

the sightings (63%) were found in the Ridge Road Range and Gravel Pit Range (Krogstad and 

Kamerman 2013). The number of infestations had increased from one (<40 m2

 [0.01 ac]) to 13 (0.4 

ha [1 ac]) in the Ridge Road Range. Sixteen new infestations, totaling 2,023 m2

 (0.5 ac), were found 

once again in the Gravel Pit Range (Krogstad and Kamerman 2013). The remaining infestations were 

found in Little Gulch, Upper Northwest Range, Big Gulch and Taylor Ridge Range and, with the 

exception of Little Gulch (809 m2

 [0.2 ac]), all were under 40 m2 (0.01 ac) in area (Krogstad and 

Kamerman 2013). 
342 

Whitetop (Lepidium draba; formerly Cardaria draba) 

The state of Montana lists whitetop as a noxious weed and has designated it as a Priority 2B species 

(MDA 2013). Whitetop is a perennial that can grow up to 0.6 m (2 ft) in height and has an extensive 

root system that deeply penetrates both laterally and vertically (Montana Weed Control Association 

2014). It has basal and stem leaves covered with soft white hairs (Graves-Medeley et al. 2011). 

Flowers are white with four petals and form in clumps at the end of the stems. They have a flattopped appearance and tend to turn cream colored as the plant matures. Seed capsules are flat, heartshaped and contain two reddish-brown seeds in a pod. Whitetop can produce around 3,000 seeds 

annually, and reproduces by seed or by shoots from its roots (Montana Weed Control Association 

2014). Whitetop prefers open unshaded areas with moist soils or areas of moderate rainfall (Montana 

Weed Control Association 2014). This tendency results in it being found in habitats such as irrigated 

cropland and pastures, ditches, or the edges of riparian areas. Undisturbed habitats, including 

excessively grazed areas, waste areas and open grasslands are also preferred habitats (Montana Weed 

Control Association 2014). 

In the 2003 survey, most whitetop infestations were mapped in or near irrigated pastures or in 

developed/disturbed areas (Figure E-11). A total of 60 infestations covering approximately 12.1 ha 

(30 ac) (Table E-3) were identified during the field survey (Wood and Rew 2005). All but one of 

these patches were mapped as point features, and were less than 809 m2

 (0.2 ac) in size (Wood and 

Rew 2005). One large patch (11.3 ha [28 acres]) of whitetop was mapped along the southern edge of 

Lower Taylor Field (Wood and Rew 2005). 
343 

Figure E-11. Location of whitetop infestations found during the three field surveys.

The results of the 2012 field survey (Table E-3) show the number of mapped infestations remained 

basically the same as in 2003, but the area infested was reduced (NPS 2012). As was the case in 

2003, the majority of the infestations were found in irrigated areas. The large patch found in Lower 

Taylor Field in 2003 was reduced to 10 small patches covering a total area of less than 405 m2

 (0.1 

ac) (NPS 2012). The number of patches in Big Gulch and Little Gulch was reduced, but slightly 

increased in the Ridge Road Range (Figure E-11). Other notable changes in whitetop distribution 

were a decline in the number of infestations in the riparian area, and an increase in the number of 

patches in the Pump House 4 and Effluent Field areas. 

The number of infestations mapped in 2013 was much higher than those observed in 2012. This is 

possibly due to the difference in the sampling protocol used in the 2013 survey. Whitetop was the 

most abundant non-native invasive species found, comprising 22% of all infestations, but only 

comprised 14% of the cumulative infested area (Table E-5). Only about a third of the infestations 

mapped in 2013 were larger than 405 m2 (0.1 ac) (Krogstad and Kamerman 2013). The largest of 

these was approximately 3,238 m2

 (0.8 ac) while the rest ranged from 405 m2 to 809 m2 (0.1 to 0.2 

ac) (Krogstad and Kamerman 2013). The cumulative area infested was also greater than in 2012, as 

would be expected due to the larger number of infestation mapped. The 2013 survey did show a 
344 

reduction in the number of infestations in the Big Gulch, Little Gulch, Ridge Road Range, Taylor 

Ridge Range and Upper Northwest Range, Effluent Field and VC North and South area (Figure E11). However, there was an increase in the number of infestations found in irrigated areas (Lower 

Taylor Field Pump House 1, 2, 3, and 4 Fields) and the riparian and Westside Ditch areas (Krogstad 

and Kamerman 2013). 

Perennial pepperweed (Lepidium latifolium) 

Montana classifies perennial pepperweed as a noxious weed (MDA 2013). The state has designated it 

as a Priority 2A species (MDA 2013). Control of 2A species requires eradication or containment of 

existing infestations where less abundant, with the management actions prioritized by local weed 

districts (MSU 2014). 

Perennial pepperweed is a perennial that has multiple branching brittle stems and generally grows to 

0.3 m - 0.9 m (1 - 3 ft) high but can reach heights of up to 2.4 m (8 ft) (Montana Weed Control 

Association 2014). The leaves of the plant are bright green to grayish-green in color, serrated and can 

be up to 0.3 m (1 ft) in length and 7.6 cm (3 in) wide, although the leaves tend to be less serrated as 

they extend from the stem (Montana Weed Control Association 2014). The plant produces small, 

white four-petaled flowers in dense clusters. Seeds are found in small flattened pods that contain two 

seeds each that are dropped at irregular intervals (Montana Weed Control Association 2014). The 

plant mainly spreads from its extensive brittle root systems, but also spreads as stems break off and 

scatter seeds (Montana Weed Control Association 2014). Perennial pepperweed prefers wet and 

sunny conditions, but is also adaptable to drier conditions (Montana Weed Control Association 

2014). This flexibility allows it to occur in seasonally inundated areas, riparian areas, and stream and 

river banks as well as along roadsides, railroads. It is also commonly found in pastures and croplands 

(Montana Weed Control Association 2014). 

The 2003 survey mapped 12 ha (30 ac) that were infested with perennial pepperweed (Table E-3). 

This included three large infestations that were located in the riparian area and along the KohrsManning Ditch (Figure E-12). The two large infestations in the riparian area were approximately 3.6 

ha (9 ac) and 1.8 ha (4.4 ac) in size (Wood and Rew 2005). An additional 24 point infestations were 

mapped covering 2,833 m2 (0.7 ac) (Wood and Rew 2005). The third large infestation was found in 

the Kohrs-Manning Ditch and covered approximately 4.96 ha (12.25 ac) (Wood and Rew 2005). 

Also mapped in this area was one point infestation that covered approximately 1,011 m2 (0.25 ac) 

(Wood and Rew 2005). These infestations comprised nearly 90% (10.8 ha) (26.7 ac) of the total area 

infested with perennial pepperweed (Wood and Rew 2005). Seven point infestations were found in 

the railroad right-of-way and railroad remnant areas, totaling just under 2,023 m2

 (0.5 ac) and six 

small patches were found in the borrow pit wetland, totaling 2,428 m2 (0.6 ac) (Wood and Rew 

2005). The remaining perennial pepperweed occurrences were found along Center Road, where 

approximately 0.5 ha (1.25 ac) were infested, and in the VC North and South area (1,214 m2

 [0.3 ac]) 

(Wood and Rew 2005). Perennial pepperweed was also found in Big Gulch, Stuart Field, Lower 

Yard Corral and Swamp, but these were very small infestations (less than 40 m2

 [0.01 ac]) (Wood 

and Rew 2005). 
345 

Figure E-12. Location of perennial pepperweed infestations found during the three field surveys.

The 2012 survey showed a small decrease in the number of mapped instances but the total area 

infested was considerably lower (Table E-3). The infestation in the riparian area had been reduced to 

only five small infestations covering >405 m2 (0.1 ac) (NPS 2012). The infestations found in the 

Kohrs-Manning Ditch, Borrow Pit, railroad right-of-way and remnant areas, Stuart Field, Center 

Road, VC North and South, Lower Yard Corral and Lower Yard Swamp areas were not present in 

the 2012 survey (Figure E-12). One less infestation was found in Big Gulch than in 2003, but the 

total area infested was still less than 405 m2 (0.1 ac) (NPS 2012). Most notable were infestations 

found in the Upper Northwest Range, Taylor Ridge Range, Ridge Road Range, Gravel Pit Range, 

Lower Taylor, Pump House 4, and L Barn Field areas that were not present in the 2003 survey 

(Figure E-12). Within Taylor Ridge Range, eight infestations were found covering approximately 

809 m2

 (0.2 ac) (NPS 2012). Fourteen instances were mapped in the Gravel Pit Range covering 526 

m2

 (0.13 ac), and the four instances found in the L Barn Field covered 405 m2 (0.1 ac) (NPS 2012). 

All the other instances were very small (less than 40 m2

 [0.01 ac]) (NPS 2012). 

The 2013 survey showed an increase in the number of infestations from 2012 (Table E-5). The area 

infested also rose slightly, but on average, it increased only about 40 m2 (0.01 ac) per infestation. The 
346 

majority of the infestations were found in the northern half of the ranch, similar to the 2003 survey 

(Figure E-12). The riparian area, North Meadows, and Pump House 4 had the majority of the 

infestations. Over 70%, or 1.1 ha (2.6 ac), of the total area infested was in these three areas (Krogstad 

and Kamerman 2013). The riparian area had 47 infestations covering 2,023 m2

 (0.5 ac), North 

Meadow had 21 covering 0.45 ha (1.1 ac), and Pump House 4 had 30 patches covering just over 0.44 

ha (1 ac) (Krogstad and Kamerman 2013). The remaining infestations were primarily located in and 

around the L Barn Field, Lower Yard Corral and Swamp, VC North and South, and the Effluent 

Field. 

Dalmatian toadflax (Linaria dalmatica) 

Montana lists Dalmatian toadflax as a noxious weed and has designated it as a Priority 2B species 

(MDA 2013). Dalmatian toadflax is a short-live perennial herb that produces snapdragon-like yellow 

flowers (Jacobs and Sing 2006, Montana Weed Control Association 2014). It has a deep tap root, but 

also produces lateral roots that can extend out 3 m - 3.7 m (10 ft -12 ft) (Montana Weed Control 

Association 2014). It has a woody stem that can grow up to a height of 1.2 m (4 ft) (Montana Weed 

Control Association 2014). Seeds are produced in small capsules that contain small dark seeds with 

“papery” wings (Montana Weed Control Association 2014). Dalmatian toadflax spreads by both root 

and seeds, with the seeds being viable for up to ten years (Montana Weed Control Association 2014). 

It prefers full sunlight on coarse-textured well-drained soils, and is typically found in areas such as 

along roadsides, transitional forest-grassland areas, pastures and rangelands (Montana Weed Control 

Association 2014). 

Dalmatian toadflax was not found during either the 2003 (not on the target species list) or 2013 field 

surveys, only in the 2012 survey (Figure E-13). The 2012 survey found one isolated plant in the 

Effluent Field (NPS 2012). 
347 

Figure E-13. Location of Dalmatian toadflax infestations found during the three field surveys. Note that 

Dalmation toadflax was not on the target species list for the 2003 survey.

Yellow toadflax (Linaria vulgaris) 

The state of Montana classifies yellow toadflax as a noxious weed and has designated it as a Priority 

2B species (MDA 2013), requiring eradication or containment of existing infestations coupled with 

education and prevention measures (MSU 2014). 

Yellow toadflax is a perennial plant with an extensive horizontal root system, multiple stems and 

grows to a height of 0.3 m - 0.6 m (1ft - 2 ft) (Montana Weed Control Association 2014). Seedlings 

resemble leafy spurge, but do not produce the milky sap when broken (Montana Weed Control 

Association 2014). Yellow toadflax has numerous pale green to gray-green leaves, which are pointed 

at both ends, but have smooth margins (Montana Weed Control Association 2014). It produces snapdragon like flowers in dense clusters of 15-20. These flowers are pale to bright yellow with a 

downward pointing yellow spur (Montana Weed Control Association 2014). It produces brown, oval 

seed capsules that are winged and contain several seeds. It can produce up to 30,000 seeds annually 

and reproduces by seed or through its root system (Montana Weed Control Association 2014). 

Yellow toadflax prefers well-drained sandy or gravel soils that remain somewhat moist (Montana 
348 

Weed Control Association 2014). It is commonly found in a variety of areas including rangeland and 

pastureland (Montana Weed Control Association 2014). 

The 2003 survey found yellow toadflax mainly in the moister areas of the ranch, but was 

predominantly found in the riparian area (Figure E-14). In total, 38 infestations covering 

approximately 15.4 ha (38 ac) were mapped (Table E-3). Of these, 31 of them were found in the 

riparian area (Wood and Rew 2005). This included nine large clumped infestations, ranging from 0.4 

ha - 4.5 ha (1 ac - 11 ac) in size (Wood and Rew 2005). This accounted for 98% of the total infested 

area (Wood and Rew 2005). The remaining occurrences were found in the borrow pit (4), railroad 

right-of-way (2) and VC North and South (1) (Wood and Rew 2005). 

Figure E-14. Location of yellow toadflax infestations found during the three field surveys.

In 2012, the area infested with yellow toadflax was reduced to almost 405 m2 (0.1 ac), although there 

were still quite a few instances found during the survey (Table E-3). All of the occurrences were 

found in the riparian area, but none of the large clumped infestations mapped in 2003 were present 

(Figure E-14). All the infestations were mapped as small patches and were less than 161.9 m2

 (0.04 

ac) in size. Of the 18 infestations mapped, all but three were less than 40.5 m2

 (0.01 ac) in size (NPS 

2012). 
349 

In 2013, the number of infestations and the total area infested both increased (Table E-5). As was the 

case in 2012, all the infestations were found in the riparian area (Figure E-14). There was 

considerable increase in the number of infestations mapped. These infestations were all quite small, 

but it still did show an increase in the total area infested (Krogstad and Kamerman 2013). Only four 

of the infestations mapped were larger than 405 m2

 (0.1 ac) (Krogstad and Kamerman 2013). 

Sulphur cinquefoil (Potentilla recta) 

Montana lists sulphur cinquefoil as a noxious weed and has designated it as a Priority 2B species 

(MDA 2013). Sulphur cinquefoil is a perennial forb with a single woody taproot, that grows up to 0.9 

m (3 ft) in height (Montana Weed Control Association 2014). Its leaves are palmate with five to 

seven toothed leaflets (Montana Weed Control Association 2014). The leaves are 5 cm -10 cm (2 in - 

4 in) long and are more numerous at the base of the plant (Montana Weed Control Association 2014). 

Its flowers have five yellow petals with notched tips and a darker yellow center (Montana Weed 

Control Association 2014). Sulphur cinquefoil produces comma-shaped dark brown seeds with 

narrow winged edges. It can spread either by seed or by its root system (Montana Weed Control 

Association 2014). It prefers full sunlight and has adapted to a wide variety of soil conditions. It is 

commonly found in grasslands and roadsides (Montana Weed Control Association 2014). 

The original survey in 2003 did not identify any sulphur cinquefoil; however, it was found in both 

the 2012 and 2013 surveys (Table E-3). All of the infestations mapped in 2012 were less than 405 m2

(0.1 ac) except for one large infestation in Lower Taylor (Figure E-15). This one infestation was 

approximately 16.6 ha (41 ac) in size, accounting for almost all of the total infested area (NPS 2012). 

Nine small infestations were found in the Lower Yard Fields. One occurrence was 40.5 m2

 (0.01 ac) 

in size and all the others were less than 40.5 m2

 (0.01 ac) (NPS 2012). Three instances were mapped 

in Pump House 4; two were less than 40.5 m2

 (0.01 ac) and the third was 121.4 m2 (0.03 ac) in size 

(NPS 2012). Two instances were found in North Meadows, 364 m2 and 202 m2 (0.09 ac and 0.05 ac) 

in size respectively (NPS 2012). One instance each was found in the Effluent Fields, Stuart Field, 

Pump House 3 and the riparian area. All of these were less than 40.5 m2

 (0.01 ac) in size, except for 

the infestation found in Pump House 3, which was 81 m2

 (0.02 ac) in size (NPS 2012). 
350 

Figure E-15. Location of sulphur cinquefoil infestations found during the three field surveys.

The 2013 survey did not find and of the infestations mapped in 2012 (Figure E-15). Only one small 

occurrence (> 40.5 m2

) (> 0.01 ac) near the Johnson Creek feedlot was mapped during the survey 

(Krogstad and Kamerman 2013). 

Tall buttercup (Ranunculus acris) 

The state of Montana lists tall buttercup as a noxious weed (MDA 2013). It has been designated as a 

Priority 2A species (MDA 2013). Control of 2A species requires eradication or containment of 

existing infestations where less abundant with the management actions prioritized by local weed 

districts (MSU 2014). 

Tall buttercup is a perennial with 0.3-0.9 m (1-3 ft) stems (Montana Weed Control Association 

2014). These stems are hollow and often branch near the top of the plant. Leaves are palmately 

divided; the lower leaves have long petioles with hairy surfaces, while the upper leaves are smaller 

and usually three-lobed (Montana Weed Control Association 2014). The plant has a five-petaled 

yellow flower, each producing yellowish egg-shaped, flat seeds (Montana Weed Control Association 

2014). Tall buttercup is adapted to a variety of habitats, but prefers moist soils such as wet lowlands 

and woodlands (Montana Weed Control Association 2014). It is commonly found in pastures, open 
351 

areas and along roadsides (Montana Weed Control Association 2014). Infestations will decrease in 

dry years, but rebound and expand during wet years (Montana Weed Control Association 2014). 

During the 2003 survey tall buttercup was found in Stuart Field (Figure E-16). This was the first 

recorded instance of tall buttercup on the ranch (Wood and Rew 2005). A total of five instances of 

tall buttercup were identified during the 2003 survey (Table E-3). The largest infestation occurred in 

Stuart Field (8.9 ha [22 ac]) and a 0.8 ha (2 ac) infestation was also mapped in the Stuart Field Annex 

(Wood and Rew 2005). The remaining three infestations were small patches (less than 121 m2

 [0.03 

ac]) located to the south of the main infestation near Cottonwood Creek (Wood and Rew 2005). 

Figure E-16. Location of tall buttercup infestations found during the three field surveys.

The survey conducted in 2012 showed a slight decrease in the total area infested, but a slight increase 

in the number of infestations as compared to the 2003 results (Table E-3). The infestations found 

during 2003 were not present in 2012 but new infestations were found (Figure E-16). The largest 

infestation was a 6.1 ha (15 ac) patch found in the Lower Yards Field (NPS 2012). The remaining 

occurrences were smaller patches found in Lower Taylor, Upper Taylor, riparian area and Pump 

House 4. These were under 40 m2

 (0.01 ac) in size, except for the two patches in Pump House 4 

(NPS 2012). These covered 283 m2 (0.07 ac) and 162 m2

 (0.04 ac) respectively (NPS 2012). 
352 

The 2013 survey showed an increase in the number of observations of tall buttercup infestation, but 

they were very small, so the total area infested was lower (Table E-5). As can be seen in Figure E-16, 

the majority of these occurrences were centrally located around the Lower Yard Field, Lower Yards 

Swamp, Lower Yards Corral, Stuart Field, Johnson Creek and North Meadows areas. This area 

accounted for nearly 80% of the total occurrences and nearly 95% of the area infested (Krogstad and 

Kamerman 2013). The largest infestations in terms of numbers and area were found in Johnson 

Creek and Lower Yards Field. In Lower Yards Field a total of 16 patches were found and in Johnson 

Creek a total of 19 patches were found (Krogstad and Kamerman 2013). Nine patches each were 

found in North Meadows, Lower Taylor, and the riparian area. The infestation in the riparian area 

was approximately 809 m2

 (0.2 ac) in size, while the other two were less than 405 m2 (0.1 ac) 

(Krogstad and Kamerman 2013). The other infestation in Stuart Field Annex consisted of seven 

patches covering 2,833 m2

 (0.7 ac) (Krogstad and Kamerman 2013). 

Russian knapweed (Rhaponticum repens; formerly Acroptilon repens) 

Montana classifies Russian knapweed as a noxious weed and has designated it as a Priority 2B 

species (MDA 2013). Russian knapweed is a rhizomatous, deep-rooted perennial forb that grows to 

about 61 cm (2 ft) tall. It has thin, stiff stems covered with soft, short hairs. Flowers are light pink to 

purple in color. Two characteristics distinguish Russian knapweed from other knapweed species. 

First, the flower head bracts have light thin hairs, a papery, translucent tip and are green at the base. 

Second, it has a rhizomatous root system instead of a taproot. The leaves of the rosettes are narrow at 

the base and widen towards the tip (Duncan et al. 2011). Seed production for Russian knapweed is 

highly variable, but in general less than other knapweeds. Optimal conditions can result in up to 

1,200 seeds per plant (Duncan et al. 2011). Russian knapweed relies on vector distribution for seed 

dispersal. Vehicles, contaminated crop seed, hay, gravel, road fill, wildlife and domestic livestock are 

common vectors of dispersal (Duncan et al. 2011). Seeds can also be spread by rivers and other 

waterways. Seed longevity is in the range of two to nine years, and once established, patches 

normally spread by rhizomatous growth (Duncan et al. 2011). Mature plants can spread rapidly, 

covering as much as 7 m (23 ft) over two growing seasons (Duncan et al. 2011). Russian knapweed 

typically invades disturbed areas and not healthy natural habitats (Montana Weed Control 

Association 2014). It is adapted to a wide range of habitats including pastureland, cropland, 

rangeland, and roadsides (Duncan et al. 2011, Montana Weed Control Association 2014). It has a 

tolerance for poorly drained, saline, alkaline soils that extends its range to irrigation ditches, flood 

plains and river corridors (Duncan et al. 2011). 

During the 2003 field inventory, four small infestations of Russian knapweed were mapped, all on 

the west side of the Clark Fork River (Figure E-17). The cumulative area infested with Russian 

knapweed (Table E-3) was approximately 647 m2

 (0.16 ac), with the majority of this area represented 

by one patch located in the Taylor Ridge Range. Another patch, slightly less than 162 m2

 (0.04 ac), 

was located in pastureland (Big Gulch). The remaining two infestations, both less than 40 m2

 (0.01 

ac), were located in upland range habitat along the westside road and in the riparian area. Overall, 

infestations of Russian knapweed comprised less than 0.1% of the cumulative infested area (Table E4) identified during the 2003 survey (Wood and Rew 2005). 
353 

Figure E-17. Location of Russian knapweed infestations found during the three field surveys.

In 2012, only one infestation of Russian knapweed was mapped by the survey (Figure E-17). This 

infestation was located in pastureland (Pump House 3) and was relatively small, measuring just 162 

m2

 (0.04 ac) (Table E-3). Table E-4 shows that the 2012 results are similar to the 2003 results, with 

Russian knapweed comprising less than 0.01% of the cumulative infested area (NPS 2012). The 

number of infestations and the cumulative area infested was reduced by 75% from 2003 to 2012. 

Field surveys conducted in 2013 did not identify any Russian knapweed infestations (Krogstad and 

Kamerman 2013). However, NPS staff did observe the species in the park during 2014 (Smith, 

written communication, February 2015). 

Common tansy (Tanacetum vulgare) 

Montana lists common tansy as a noxious weed (MDA 2013). Montana has designated it as a Priority 

2A species (MDA 2013). Control of 2A species requires eradication or containment of existing 

infestations where less abundant with the management actions prioritized by local weed districts 

(MSU 2014). 

Common tansy is a perennial forb with an extensive root system that can grow to a height of 1.5 m (5 

ft) (Montana Weed Control Association 2014). It has dark green leaves that can be 25 cm (10 in) 
354 

long and up to 7.6 cm (3 in) wide (Montana Weed Control Association 2014). Common tansy has 

yellow to yellow-orange flowers that form in dense flat clusters. It produces a grayish tan ribbed 

seed. It spreads through seed dispersal and by its root system (Montana Weed Control Association 

2014). Common tansy prefers moist soils, and can be commonly found along roadsides and railroad 

right-of-ways, stream banks, rangeland and irrigated pasture (Montana Weed Control Association 

2014). 

Figure E-18. Location of common tansy infestations found during the three field surveys.

The 2003 survey mapped eight infestations of common tansy (Figure E-18). All the patches were 

small, measuring less than 40 m2

 (0.01 ac) (Wood and Rew 2005). Seven infestations were located in 

the riparian area with a total infested area of approximately 81 cm2

 (0.02 ac) (Wood and Rew 2005). 

The remaining infestation was found in Stuart Annex. 

The survey conducted in 2012 mapped only three occurrences of common tansy, all located in the 

riparian area (Figure E-18). As was the case in 2003, these were very small infestations; however, 

they were smaller in 2012, with none larger than 4 m2

 (43 ft2) in size (NPS 2012). No instances of 

common tansy were noted during the 2013 survey (Krogstad and Kamerman 2013). However, the 

species was observed in the park during 2014 (Smith, written communication, February 2015). 
355 

Field pennycress (Thlaspi arvense) 

Field pennycress is not listed as a noxious weed by the state of Montana (MDA 2013) and it is also 

not listed as a noxious species by any county in Montana (MSU 2014). 

Field pennycress is an annual that can grow up to 61 cm (24 in) in height (Koundinya and Hansen 

2012). It has both a slender taproot and a fibrous lateral root system (Alaska Natural Heritage 

Progam 2010). Its leaves are stalkless, up to 3.8 cm (1.5 in) long and 1.3 cm (0.5 in) wide, with an 

ear-like lobe at the base and large-toothed to wavy margins (Alaska Natural Heritage Progam 2010). 

It produces small white four-petaled flowers in clusters at the end of stalks (Koundinya and Hansen 

2012). It can be commonly found in areas such as open disturbed areas, roadsides, railroads and 

riparian areas (Koundinya and Hansen 2012). 

Field pennycress was only mapped on the ranch during the 2012 survey (Figure E-19). It was not on 

the list of dominant species that was used during the 2003 survey (Wood and Rew 2005) and was not 

surveyed for in 2013 due to its low management priority (Smith, written communication, February 

2015). The 2012 survey mapped 1.92 ha (4.75 ac) of field pennycress (Table 3). This was made up of 

mostly small patches, but two larger patches were mapped in the Westside Ditch and Effluent Field 

(NPS 2012). The largest of these (1.5 ha [3.6 ac]) was located in the Westside Ditch and a 3,237 m2

(0.8 ac) patch was mapped in the Effluent Field (NPS 2012). The remaining infestations were all 

very small, less than 405 m2

 (0.1 ac) in size (NPS 2012). 
356 

Figure E-19. Location of field pennycress infestations found during the three field surveys. Note that the 

2003 and 2013 field efforts did not survey for this species, so no infestations were mapped. 
357 

Literature Cited

Alaska Natural Heritage Progam. 2010. Field pennycress. University of Alaska - Anchorage, 

Anchorage, Alaska. 

British Columbia Ministry of Agriculture. 2014. Baby’s breath. 

http://www.agf.gov.bc.ca/cropprot/babysbreath.htm (accessed 31 December 2014). 

Duncan, C., J. Story, R. Sheley, H. Parkinson, J. Mangold. 2011. Biology, ecology, and management 

of Montana knapweeds. Montana State University Extension, Bozeman, Montana. 

Goodwin, K., R. Sheley, R. Nowierski, and R. Lym. 2001. Leafy spurge: Biology, ecology and 

management. USDA Agricultural Research Service, Sidney, Montana. 

Graves-Medeley, M., J. Mangold, and K. Goodwin. 2011. Biology, ecology, and management of 

whitetop. Montana State University Extension, Bozeman, Montana. 

Jacobs, J., and S. Sing. 2006. Ecology and management of Dalmatian toadflax. Invasive Species 

Technical Note No. MT-3. Montana State University Extension, Bozeman, Montana. 

Kedzie-Webb, S., and R. L. Sheley. 2009. Houndstongue: Identification, biology and integrated 

management. Montana State University Extension, Bozeman, Montana. 

Koundinya, V., and R. Hansen. 2012. Pennycress. 

http://www.agmrc.org/commodities__products/grains__oilseeds/pennycress/ (accessed 31 

December 2014). 

Krogstad, L., and R. Kamerman. 2013. 2013 Non-native plant survey at Grant-Kohrs Ranch National 

Historic Site. Montana State University, Bozeman, Montana. 

Menalled, F., J. Mangold, and E. Davis. 2012. Cheatgrass : Identification, biology and integrated 

management. Montana State University Extension, Bozeman, Montana. 

Montana Department of Agriculture (MDA). 2013. Montana noxious weed list. Montana Department 

of Agriculture, Helena, Montana.

Montana State University (MSU). 2014. Montana noxious weed information. 

http://www.msuextension.org/invasiveplantsMangold/noxioussub.html (accessed 31 December 

2014). 

Montana Weed Control Association. 2009. Weed control and management. 

http://www.mtweed.org/weed-control-management/ (accessed 31 December 2014). 

Montana Weed Control Association. 2014. Weed ID. http://www.mtweed.org/weed-identification/

(accessed 31 December 2014). 

National Park Service (NPS). 2009. Invasive species.....What are they and why are they a problem? 

http://www.nature.nps.gov/biology/invasivespecies/ (accessed 31 December 2014). 
358 

National Park Service (NPS). 2011. Northern Rocky Mountains invasive plant management plan. 

National Park Service, Fort Collins, Colorado. 

National Park Service (NPS). 2012. 2012 Non-native plant survey at Grant-Kohrs Ranch National 

Historic Site. National Park Service, Deer Lodge, Montana. 

Randall, J. A. 1996. Weed control for preservation of biological diversity. Weed Technology 10:370-

383. 

Rice, P. M., G. J. Ray, J. J. Bromenshenk, and P .C. Tourangeau. 1984. Floral and faunal survey and 

toxic metal contamination study of the Grant-Kohrs Ranch National Historic Site. Report for 

National Park Service. University of Montana, Missoula, Montana. 

Rice, P. M., and G. J. Ray. 1984. Baseline plant inventory of the Grant-Kohrs Ranch. Report for 

National Park Service. University of Montana, Missoula, Montana. 

Rice, P. M., and J. Hardin. 2002a. Riparian plant community structure at Grant-Kohrs Ranch. Report 

for National Park Service. University of Montana, Missoula, Montana. 

Rice, P. M., and J. Hardin. 2002b. Vascular plant survey of Grant-Kohrs Ranch National Historic 

Site. Report for National Park Service. University of Montana, Missoula, Montana. 

Sheley, R. L., J. K. Petroff, and M. M. Borman. 1999. Introduction. Pages 1-3 in R. L. Sheley and J. 

K. Petroff, editors. Biology and Management of Noxious Rangeland Weeds. Oregon State 

University Press, Corvallis, Oregon. 

Westbrooks, R. 1998. Invasive plants, changing the landscape of America: Fact book. Federal 

Interagency Committee for the Management of Noxious and Exotic Weeds (FICMNEW), 

Washington, D.C. 

Wood, S. D., and D. L. J. Rew. 2005. Non-native plant survey at Grant-Kohrs Ranch National 

Historic Site. Montana State University, Bozeman, Montana.
359

Appendix F. Species of conservation concern that have been identified in GRKO. 

Common Name

Global 

Rank

State 

Rank Federal Status

MT PIF 

Status

CFWCS 

Status

alder flycatcher G5 S3B II-I

American dipper III

American white pelican G4 S3B III III

bald eagle G5 S3 USFWS - DM II I-III

Barrow's goldeneye II

black rosy-finch II

black tern II

black-billed cuckoo G5 S3B II II-I

black-crowned night-heron G5 S3B III II-I

black-necked stilt G5 S3B III III-II

bobolink G5 S3B III III

Brewer's blackbird III

Brewer's sparrow G5 S3B BLM II II-III

brown creeper G5 S3 I II

burrowing owl G4 S3B USFS, BLM I I-III

calliope hummingbird II

Caspian tern II

Cassin's finch G5 S3 III II-III

Cassin's vireo III

chipping sparrow III

Clark's nutcracker G5 S3 III III

clay-colored sparrow III

common loon G5 S3B USFS, BLM I I-III

common tern II

cordilleran flycatcher II

downy woodpecker III

ferruginous hawk G4 S3B BLM II II-III

Franklin's gull G4 G5 S3B BLM II II
360

Common Name

Global 

Rank

State 

Rank Federal Status

MT PIF 

Status

CFWCS 

Status

golden-crowned kinglet III

gray catbird III

gray-crowned rosy-finch G5

S2B, 

S5N II

great blue heron G5 S3 III

green-tailed towhee III

Hammond's flycatcher II

harlequin duck G4 S2B USFS, BLMII-III

hooded merganser II

horned grebe G5 S3B II II

killdeer III

lark bunting II

lark sparrow III

lazuli bunting II

least flycatcher III

Lewis's woodpecker G4 S2B II II

long-billed curlew G5 S3B BLM III-II

MacGillivray's warbler III

marbled godwit II

northern goshawk G5 S3 USFS, BLM II II-I

northern harrier III

olive-sided flycatcherI

peregrine falcon G4 S3 USFWS - DM, USFS, BLM II II-III

pinyon jay G5 S3 II-III

red crossbill III

red-headed woodpecker G5 S3B II II

red-naped sapsucker II

red-winged blackbird III

rufous hummingbird III
361

Common Name

Global 

Rank

State 

Rank Federal Status

MT PIF 

Status

CFWCS 

Status

sharp-shinned hawk III

short-eared owl III

song sparrow III

Swainson's hawk III

Townsend's solitaire III

Townsend's warbler III

trumpeter swan G4 S3 BLM II I-III

varied thrush III

veery G5 S3B III II-III

warbling vireo III

white-faced ibis G5 S3B BLM II II-I

willet III

Williamson's sapsucker II

willow flycatcher II

Wilson's phalarope III

winter wren G5 S3 II II-III

yellow-headed blackbird III

(G) = Global

(S) = State

(B) = State rank modifier indicating breeding for a migratory species.

(N) = A state rank modifier referring to a non-breeding population of the species.

G5/S5 = Common, widespread, and abundant (although it may be rare in parts of its range). Not vulnerable in most of its range. 

G4/S4 = Uncommon but not rare (although it may be rare in parts of its range), and usually widespread. Apparently not vulnerable in most of its range, but possibly cause for 

long-term concern.

G3/S3 = Potentially at risk because of limited and/or declining numbers, range, and/or habitat, even though it may be abundant in some areas.

G2/S2 = At risk because of very limited and/or declining numbers, range, and/or habitat, making it vulnerable to global extinction or extirpation in the state.

BLM = Bureau of Land Management Sensitive Species.

USFWS (DM) = Recovered, delisted, and monitored species under the Endangered Species Act of 1973 as defined by the U.S. Fish and Wildlife Service.

USFS = U.S. Forest Service Sensitive Species or Species of Concern. 
362 

Appendix G. Bird species identified as present or probably present in GRKO.

Common Name

NPS 

(2014)

Rice and 

Ray (1984)

Giroir 

and 

Beason 

(2005)

Larson 

(2011)

Atkinson 

and 

Smucker 

(2013)

CBC

(2006-

2012)

alder flycatcher X

American avocet X

American coot X X

American crow X X X X X

American dipper X X

American goldfinch X X X X

American kestrel X X X X

American pipit X

American robin X X X X X

American tree sparrow X X

American white pelican X

American wigeon X X

American bittern X

Anna's hummingbird X

ash-throated flycatcher X

Baird's sandpiper X

bald eagle X X

band-tailed pigeon X X

bank swallow X X X

barn swallow X X X X

Barrow's goldeneye X X

belted kingfisher X X X

black rosy-finch X

black tern X

black-bellied plover X

black-billed cuckoo X X

black-billed magpie X X X X X

black-capped chickadee X X X X X X

black-crowned night-heron X

black-headed grosbeak X X X

black-necked stilt X

blue jay X

blue-winged teal X X X

bobolink X X X X X

Bohemian waxwing X X

Bonaparte's gull X

Brewer's blackbird X X X X

Brewer's sparrow X
363 

Common Name

NPS 

(2014)

Rice and 

Ray (1984)

Giroir 

and 

Beason 

(2005)

Larson 

(2011)

Atkinson 

and 

Smucker 

(2013)

CBC

(2006-

2012)

brown creeper X X

brown-headed cowbird X X X X

bufflehead X

Bullock's oriole X X

burrowing owl X

California gull X X

calliope hummingbird X

Canada goose X X X X

canvasback X

Caspian tern X

Cassin's finch X

Cassin's vireo X

cedar waxwing X X X X

chipping sparrow X X

cinnamon teal X

Clark's nutcracker X X

clay-colored sparrow X X

cliff swallow X X X

common goldeneye X X

common grackle X X X X

common loon X

common merganser X X

common nighthawk X X

common raven X X X X X

common redpoll X X

common tern X

common yellowthroat X X X X

Cooper's hawk X X

cordilleran flycatcher X

dark-eyed junco X X X

double-crested cormorant X X

downy woodpecker X X X

dusky flycatcher X

eared grebe X

eastern kingbird X X X X

herring gull X

Eurasian collared-dove X

European starling X X X X X

evening grosbeak X X
364 

Common Name

NPS 

(2014)

Rice and 

Ray (1984)

Giroir 

and 

Beason 

(2005)

Larson 

(2011)

Atkinson 

and 

Smucker 

(2013)

CBC

(2006-

2012)

ferruginous hawk X

Franklin's gull X

gadwall X X

golden eagle X X

golden-crowned kinglet X

gray catbird X X

gray jay X X

gray partridge X X

gray-crowned rosy-finch X X

great blue heron X X X X

great egret X

great horned owl X X

greater scaup X

greater white-fronted goose X

greater yellowlegs X

green-tailed towhee X

green-winged teal X X

gyrfalcon X

hairy woodpecker X X

Hammond's flycatcher X

harlequin duck X

Harris's sparrow X

hermit thrush X

hoary redpoll X

hooded merganser X

horned grebe X

horned lark X X X X X

house finch X X X

house sparrow X X X

house wren X X X

killdeer X X X X X X

lapland longspur X X

lark bunting X

lark sparrow X X

lazuli bunting X

least flycatcher X X

least sandpiper X

lesser scaup X X

lesser yellowlegs X
365 

Common Name

NPS 

(2014)

Rice and 

Ray (1984)

Giroir 

and 

Beason 

(2005)

Larson 

(2011)

Atkinson 

and 

Smucker 

(2013)

CBC

(2006-

2012)

Lewis's woodpecker X

Lincoln's sparrow X

long-billed curlew X X X

long-billed dowitcher X

long-eared owl X

long-tailed duck X

MacGillivray's warbler X X

mallard X X X X X X

marbled godwit X

marsh wren X X

merlin X X

mountain bluebird X X

mountain chickadee X X X

mourning dove X X X X X

northern flicker X X X X X X

northern goshawk X X

northern harrier X X X X X

northern mockingbird X

northern pintail X

northern pygmy-owl X X

northern rough-winged swallow X X X X

northern saw-whet owl X

northern shoveler X X

northern shrike X

northern waterthrush X X

olive-sided flycatcher X

orange-crowned warbler X

osprey X X X

pectoral sandpiper X

peregrine falcon X

pied-billed grebe X X

pine grosbeak X X

pine siskin X X

pinyon jay X

prairie falcon X X

red crossbill X X

red-breasted merganser X X

red-breasted nuthatch X

redhead X
366 

Common Name

NPS 

(2014)

Rice and 

Ray (1984)

Giroir 

and 

Beason 

(2005)

Larson 

(2011)

Atkinson 

and 

Smucker 

(2013)

CBC

(2006-

2012)

red-headed woodpecker X

red-naped sapsucker X X

red-necked grebe X

red-necked phalarope X

red-tailed hawk X X X X X X

red-winged blackbird X X X X X X

ring-billed gull X

ring-necked duck X

ring-necked pheasant X

rock pigeon X X X

rock wren X

Ross's goose X

rough-legged hawk X

rough-winged hawk X

ruby-crowned kinglet X

ruddy duck X X

rufous hummingbird X

rusty blackbird X

Sabine's gull X

sanderling X

sandhill crane X X X

savannah sparrow X X X X

Say's phoebe X

scarlet tanager X

semipalmated plover X

semipalmated sandpiper X

sharp-shinned hawk X X

short-eared owl X

snow bunting X X

snow goose X

snowy egret X

solitary sandpiper X

song sparrow X X X X X X

sora X X

spotted sandpiper X X X

spotted towhee X

Steller's jay X

stilt sandpiper X

Swainson's hawk X X
367 

Common Name

NPS 

(2014)

Rice and 

Ray (1984)

Giroir 

and 

Beason 

(2005)

Larson 

(2011)

Atkinson 

and 

Smucker 

(2013)

CBC

(2006-

2012)

Swainson's thrush X

swamp sparrow X

Townsend's solitaire X X

Townsend's warbler X

tree swallow X X X X X

trumpeter swan X

tundra swan X X

turkey vulture X

varied thrush X

veery X

vesper sparrow X X X X

violet-green swallow X

Virginia rail X

warbling vireo X

western bluebird X

western grebe X

western kingbird X X X

western meadowlark X X X X

western sandpiper X

western tanager X

western wood-pewee X X X X

whimbrel X

white-breasted nuthatch X

white-crowned sparrow X X

white-faced ibis X

white-throated sparrow X

white-throated swift X

white-winged crossbill X

wild turkey X

willet X

Williamson's sapsucker X

willow flycatcher X X X X

Wilson's phalarope X

Wilson's snipe X X X X X

Wilson's warbler X

winter wren X

wood duck X X

yellow warbler X X X X

yellow-breasted chat X
368 

Common Name

NPS 

(2014)

Rice and 

Ray (1984)

Giroir 

and 

Beason 

(2005)

Larson 

(2011)

Atkinson 

and 

Smucker 

(2013)

CBC

(2006-

2012)

yellow-headed blackbird X X X

yellow-rumped warbler X
369 

Appendix H. Species observed in GRKO based on each survey method during Atkinson and Smucker 

(2013).

Species 

Point 

Count

Nest 

Found

Mist 

Net

Area 

Search

American avocet X

American crow X X

American goldfinch X X

American kestrel X

American robin X X X X

American white pelican X

American wigeon X

bald eagle X

bank swallow X X

barn swallow X X

belted kingfisher X

black-billed magpie X X X X

black-capped chickadee X X X X

black-headed grosbeak X X

blue-winged teal X

bobolink X X

Brewer's blackbird X

brown-headed cowbird X X X

Bullock's oriole X X

California gull X X

calliope hummingbird X X

Canada goose X

canvasback X

Cassin's vireo X X

cedar waxwing X X

chipping sparrow X X

cinnamon teal X

clay-colored sparrow X X

common grackle X X X

common merganser X

common nighthawk X X

common raven X X

common yellowthroat X X X X

cordilleran flycatcher X X

dark-eyed junco X

double-crested cormorant X X

downy woodpecker X X

dusky flycatcher X X

eastern kingbird X X X
370 

Species 

Point 

Count

Nest 

Found

Mist 

Net

Area 

Search

Eurasian collared-dove X

European starling X X

evening grosbeak X

fox sparrow X

gadwall X

gray catbird X X

gray partridge X

great blue heron X X

great horned owl X

greater yellowlegs X

hairy woodpecker X

Hammond's flycatcher X X

hermit thrush X X

horned lark X X

house finch X X

house wren X X

killdeer X X

lazuli bunting X X

least flycatcher X X

lesser scaup X

Lincoln's sparrow X X

long-billed curlew X X

Macgillivray's warbler X X X

mallard X X

marsh wren X X

merlin X

mountain bluebird X

mountain chickadee X X X

mourning dove X X

northern flicker X X X X

northern harrier X X

northern rough-winged swallow X X X

northern shoveler X

northern waterthrush X X

orange-crowned warbler X X

osprey X

pine siskin X X

red-breasted nuthatch X X

red-eyed vireo X X

red-naped sapsucker X X

red-tailed hawk X X
371 

Species 

Point 

Count

Nest 

Found

Mist 

Net

Area 

Search

red-winged blackbird X X X

ring-billed gull X

ruby-crowned kinglet X X

rufous hummingbird X X

sandhill crane X X

savannah sparrow X X X X

song sparrow X X X

sora X

spotted sandpiper X X

Swainson's thrush X X

Tennessee warbler X X

Townsend's warbler X X

tree swallow X X

veery X X

vesper sparrow X X X

violet-green swallow X

warbling vireo X

western meadowlark X X

western tanager X X

western wood-pewee X X X

willow flycatcher X X X

Wilson's snipe X X

Wilson's warbler X X

wood duck X

yellow warbler X X X X

yellow-headed blackbird X

yellow-rumped warbler X X
372 

Appendix I. Species distribution and abundance during the Giroir and Beason (2005) survey in GRKO.

Species Grassland Riparian Total

Canada goose 1 1

wood duck 4 4

gadwall 1 1

mallard 1 1

ruddy duck 1 1

osprey 1 1

red-tailed hawk 1 1

American kestrel 1 1 2

sora 1 1

killdeer 3 8 11

spotted sandpiper 8 8

long-billed curlew 7 7

Wilson's snipe 14 14

mourning dove 2 9 11

red-naped sapsucker 2 2

downy woodpecker 1 1

northern flicker 7 7

western wood-pewee 3 3

willow flycatcher 1 20 21

least flycatcher 1 1

western kingbird 1 1

eastern kingbird 5 5

black-billed magpie 18 18

American crow 3 16 19

common raven 2 2

horned lark 19 19

tree swallow 1 1

northern rough-winged swallow 4 1 5

bank swallow 7 7

cliff swallow 1 1

black-capped chickadee 2 2

house wren 10 10

marsh wren 11 11

American robin 4 4

gray catbird 10 10

European starling 20 20

cedar waxwing 1 1

yellow warbler 25 25

northern waterthrush 6 6

common yellowthroat 1 14 15
373 

Species Grassland Riparian Total

clay-colored sparrow 1 1

vesper sparrow 27 1 28

savannah sparrow 30 46 76

song sparrow 18 18

black-headed grosbeak 3 3

bobolink 3 8 11

red-winged blackbird 1 22 23

western meadowlark 29 21 50

yellow-headed blackbird 10 10

Brewer's blackbird 9 9

common grackle 1 8 9

brown-headed cowbird 1 31 32

Bullock's oriole 4 4

American goldfinch 2 2

Total # of Individuals 145 412 557
374 

Appendix J. Species abundance during the Larson (2011) survey of the grassland/agricultural habitats in 

GRKO.

Species # of Individuals % of Observations

savannah sparrow 156 31

bobolink 57 11

western meadowlark 43 9

brown-headed cowbird 29 6

red-winged blackbird 28 6

vesper sparrow 28 6

American robin 14 3

Wilson's snipe 14 3

American crow 12 2

killdeer 12 2

black-billed magpie 11 2

song sparrow 9 2

European starling 6 1

tree swallow 5 1

eastern kingbird 4 < 1

sandhill crane 4 < 1

chipping sparrow 3 < 1

common grackle 3 < 1

dark-eyed junco 3 < 1 

horned lark 3 < 1

northern rough-winged swallow 3 < 1

red-tailed hawk 3 < 1

western wood-pewee 3 < 1

willow flycatcher 3 < 1

yellow warbler 3 < 1

alder flycatcher 2 < 1

American kestrel 2 < 1

barn swallow 2 < 1

black-capped chickadee 2 < 1

house wren 2 < 1

northern flicker 2 < 1

rock dove 2 < 1

Swainson's hawk 2 < 1

western bluebird 2 < 1

Brewer's blackbird 1 < 1

Canada goose 1 < 1

common raven 1 < 1

common yellowthroat 1 < 1

house finch 1 < 1

house sparrow 1 < 1
375 

Species # of Individuals % of Observations

lark sparrow 1 < 1

mallard 1 < 1

northern harrier 1 < 1

osprey 1 < 1

white-crowned sparrow 1 < 1

western kingbird 1 < 1

unidentified bird 2 < 1

unidentified swallow 2 < 1

unidentified Empid. Flycatcher 1 < 1

unidentified falcon 1 < 1

unidentified gull 1 < 1

Total 489 100
376 

Appendix K. Species distribution and abundance during the Atkinson and Smucker (2013) survey in 

GRKO.

Species Grassland/Agriculture Riparian/Wetland Total

double-crested cormorant 1 1

great blue heron 2 2

mallard 3 1 4

blue-winged teal 1 1

lesser scaup 1 1

northern harrier 1 1

red-tailed hawk 1 1

sandhill crane 1 1

killdeer 1 1

spotted sandpiper 2 2

long-billed curlew 2 1 3

Wilson's snipe 4 7 11

California gull 1 1 2

mourning dove 1 1

common nighthawk 2 2

northern flicker 1 2 3

western wood-pewee 2 2

willow flycatcher 1 1 2

eastern kingbird 1 1 2

black-billed magpie 10 21 31

common raven 5 1 6

horned lark 1 1

tree swallow 7 1 8

northern rough-winged swallow 3 10 13

barn swallow 2 3 5

black-capped chickadee 2 2 4

mountain chickadee 1 1

mountain bluebird 2 2

American robin 1 1

European starling 2 1 3

yellow warbler 6 10 16

MacGillivray's warbler 2 2

common yellowthroat 2 5 7

vesper sparrow 14 14

savannah sparrow 46 26 72

song sparrow 4 4

black-headed grosbeak 1 3 4

bobolink 4 1 5

red-winged blackbird 25 15 40

western meadowlark 15 11 26
377 

Species Grassland/Agriculture Riparian/Wetland Total

common grackle 1 1

brown-headed cowbird 3 9 12

Total # of Individuals 175 146 321
378 

Appendix L. NLCD landcover class composition and change (2001-2011) within GRKO external 

viewshed (gray indicates class with actual change).

Landcover Class Hectares Percent Visible Cover

Evergreen Forest to Evergreen Forest 17227 40

Shrub/Scrub to Shrub/Scrub 12217 28

Grassland/Herbaceous to Grassland/Herbaceous 7514 17

Pasture/Hay to Pasture/Hay 3572 8

Developed, Open Space to Developed, Open Space 623 1

Evergreen Forest to Shrub/Scrub 419 1

Cultivated Crops to Cultivated Crops 404 1

Developed, Low Intensity to Developed, Low Intensity 403 1

Woody Wetlands to Woody Wetlands 214 <1

Evergreen Forest to Grassland/Herbaceous 116 <1

Barren Land to Barren Land 114 <1

Developed, Med Intensity to Developed, Medium Intensity 102 <1

Pasture/Hay to Grassland/Herbaceous 43 <1

Shrub/Scrub to Evergreen Forest 32 <1

Grassland/Herbaceous to Pasture/Hay 29 <1

Grassland/Herbaceous to Shrub/Scrub 20 <1

Cultivated Crops to Grassland/Herbaceous 19 <1

Shrub/Scrub to Grassland/Herbaceous 17 <1

Grassland/Herbaceous to Evergreen Forest 11 <1

Developed, High Intensity to Developed, High Intensity 10 <1

Woody Wetlands to Pasture/Hay 7 <1

Shrub/Scrub to Pasture/Hay 5 <1

Open Water to Open Water 4 <1

Pasture/Hay to Woody Wetlands 3 <1

Deciduous Forest to Deciduous Forest 2 <1

Developed, Low Intensity to Developed, High Intensity 1 <1

Grassland/Herbaceous to Woody Wetlands 1 <1

Developed, Open to Developed, Medium Intensity 1 <1

Barren Land to Grassland/Herbaceous 1 <1

Developed, Open Space to Developed, Low Intensity 1 <1

Developed, Low Intensity to Developed, Medium Intensity 1 <1

Grassland/Herb to Developed, Medium Intensity 1 <1

Grassland/Herb to Developed, High Intensity 1 <1

Developed, Open Space to Developed, High Intensity <1 <1

Grassland/Herbaceous to Developed, Open Space <1 <1

Developed, Med Intensity to Developed, High Intensity <1 <1

Woody Wetlands to Grassland/Herbaceous <1 <1

Grassland/Herb to Emergent Herb Wetlands <1 <1
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