Sensitivity of Alpine and Subalpine 

Lakes to Acidification from Atmospheric 

Deposition in Grand Teton National Park 

and Yellowstone National Park, Wyoming

By Leora Nanus, Donald H. Campbell, and Mark W. Williams

Prepared in cooperation with the

Grand Teton National Park,

Yellowstone National Park, and the

Greater Yellowstone Inventory and Monitoring Network

Scientific Investigations Report 2005–5023

U.S. Department of the Interior

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

Gale A. Norton, Secretary

U.S. Geological Survey

Charles G. Groat, Director

U.S. Geological Survey, Reston, Virginia: 2005

For sale by U.S. Geological Survey, Information Services

Box 25286, Denver Federal Center

Denver, CO 80225

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Telephone: 1-888-ASK-USGS

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

endorsement by the U.S. Government.

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

to reproduce any copyrighted materials contained within this report.

Suggested citation:

Nanus, Leora, Campbell, Donald H., and Williams, Mark W., 2005, Sensitivity of alpine and subalpine lakes to 

acidification from atmospheric deposition in Grand Teton National Park and Yellowstone National Park, Wyoming: 

U.S. Geological Survey Scientific Investigations Report 2005–5023, 37 p.
iii

Contents

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

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

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

Acknowledgments ................................................................................. 2

Description of Data Used in the Logistic Regression Models ....................................... 2

Lake Acid-Neutralizing Capacity Data ............................................................ 2

Basin Boundary Delineation ........................................................................ 4

Physical Basin Characteristics Data ............................................................ 4

Land-Surface Characteristics ............................................................... 4

Atmospheric Factors ........................................................................ 9

Description of Logistic Regression Modeling Technique .......................................... 9

Logistic Regression Model Calibration and Application ............................................. 10

Grand Teton National Park ........................................................................ 10

Yellowstone National Park ........................................................................ 11

Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition ...... 11

Grand Teton National Park ........................................................................ 11

Yellowstone National Park ........................................................................ 12

Comparison between Grand Teton National Park and Yellowstone National Park ......... 12

Summary ................................................................................................... 19

Selected References .................................................................................... 19

Appendix ................................................................................................... 21

Figures

1. Graph showing frequency of lakes in acid-neutralizing capacity (ANC) 

concentration bins for Grand Teton National Park .......................................... 3

2. Graph showing frequency of lakes in acid-neutralizing capacity (ANC)

concentration bins for Yellowstone National Park .......................................... 3

 3–11. Maps showing:

 3. Location of lakes greater than 1 hectare in Grand Teton National Park ............ 5

 4. Location of lakes greater than 1 hectare in Yellowstone National Park ............ 6

 5. Elevation in Grand Teton and Yellowstone National Parks ........................... 7

 6. Geochemical rankings in Grand Teton and Yellowstone National Parks ............ 8

 7. Probability greater than 60 percent of lake sensitivity in Grand Teton 

 National Park to atmospheric deposition using an acid-neutralizing 

 capacity concentration bin of 0–50 microequivalents per liter ........................ 14

 8. Probability greater than 60 percent of lake sensitivity in Grand Teton 

 National Park to atmospheric deposition using an acid-neutralizing 

capacity concentration bin of 0–100 microequivalents per liter ..................... 15
iv

 9. Probability greater than 60 percent of lake sensitivity in Grand Teton 

 National Park to atmospheric deposition using an acid-neutralizing 

 capacity concentration bin of 0–200 microequivalents per liter ..................... 16

 10. Probability greater than 60 percent of lake sensitivity in Yellowstone 

 National Park to atmospheric deposition using an acid-neutralizing 

 capacity concentration bin of 0–100 microequivalents per liter ..................... 17

 11. Probability greater than 60 percent of lake sensitivity in Yellowstone 

 National Park to atmospheric deposition using an acid-neutralizing 

 capacity concentration bin of 0–200 microequivalents per liter ..................... 18

Tables

1. Predicted number and percentage of lakes in Grand Teton National 

Park by probability of an acid-neutralizing capacity concentration 

bin of 0–50 microequivalents per liter ...................................................... 11

2. Predicted number and percentage of lakes in Grand Teton National 

Park by probability of an acid-neutralizing capacity concentration 

bin of 0–100 microequivalents per liter ...................................................... 12

3. Predicted number and percentage of lakes in Grand Teton National 

Park by probability of an acid-neutralizing capacity concentration 

bin of 0–200 microequivalents per liter ...................................................... 12

4. Predicted number and percentage of lakes in Yellowstone National 

Park by probability of an acid-neutralizing capacity concentration 

bin of 0–100 microequivalents per liter ...................................................... 13

5. Predicted number and percentage of lakes in Yellowstone National 

Park by probability of an acid-neutralizing capacity concentration 

bin of 0–200 microequivalents per liter ...................................................... 13

 6. Lakes greater than 1 hectare in Grand Teton National Park, 

including lake-identification number, lake name, latitude, longitude, 

elevation of lake outlet, lake area, and associated probabilities at 

acid-neutralizing capacity concentration bins of 0–50, 0–100, and 

0–200 microequivalents per liter ............................................................ 23

 7. Results of univariate logistic regression analyses for Grand Teton 

National Park at acid-neutralizing capacity concentration bins of 0–50, 

0–100, and 0–200 microequivalents per liter and explanatory variable 

definitions and units ........................................................................... 26

 8. Results of univariate logistic regression analyses for Yellowstone 

National Park at acid-neutralizing capacity concentration bins of 0–100 

and 0–200 microequivalents per liter and explanatory variable definitions 

and units ....................................................................................... 27

 9. Results of multivariate logistic regression analyses for Grand Teton 

National Park ................................................................................. 28

 10. Lakes greater than 1 hectare in Yellowstone National Park, 

including lake-identification number, lake name, latitude, longitude, 

elevation of lake outlet, lake area, and associated probabilities at 

acid-neutralizing capacity concentration bins of 0–100 and 

0–200 microequivalents per liter ............................................................ 30

 11. Results of multivariate logistic regression analyses for Yellowstone 

National Park ................................................................................. 37
v

Conversion Factors and Abbreviations

Multiply By To obtain

meter (m) 3.281 foot (ft)

kilometer (km) 0.6214 mile (mi)

hectare (ha) 2.471 acre

kilogram (kg) 2.205 pound (lb)

liter (L) 0.264 gallon (gal)

millimeter per year (mm/yr) 0.0393 inches per year (in/yr)

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

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).

Additonal Abbreviations

kg/ha/yr kilograms per hectare per year

μeq/L microequivalents per liter

ANC acid-neutralizing capacity

DEM Digital Elevation Model

USEPA U.S. Environmental Protection Agency

GC Geochemical Class (geochemical ranking)

GIS Geographical Information System

NADP National Atmospheric Deposition Program

NWIS National Water Information System

PRISM Parameter-elevation Regressions on Independent Slopes Model

STORET Data Storage and Retrieval System
Abstract

The sensitivity of 400 lakes in Grand Teton and 

Yellowstone National Parks to acidification from atmospheric deposition of nitrogen and sulfur was estimated based 

on statistical relations between acid-neutralizing capacity 

concentrations and basin characteristics to aid in the design 

of a long-term monitoring plan for Outstanding Natural 

Resource Waters. Acid-neutralizing capacity concentrations 

that were measured at 52 lakes in Grand Teton and 23 lakes 

in Yellowstone during synoptic surveys were used to calibrate the statistical models. Three acid-neutralizing capacity 

concentration bins (bins) were selected that are within the 

U.S. Environmental Protection Agency criteria of sensitive to 

acidification; less than 50 microequivalents per liter (μeq/L) 

(0–50), less than 100 μeq/L (0–100), and less than 200 μeq/L 

(0–200). The development of discrete bins enables resource 

managers to have the ability to change criteria based on the 

focus of their study. Basin-characteristic information was 

derived from Geographic Information System data sets. The 

explanatory variables that were considered included bedrock 

type, basin slope, basin aspect, basin elevation, lake area, 

basin area, inorganic nitrogen deposition, sulfate deposition, 

hydrogen ion deposition, basin precipitation, soil type, and 

vegetation type. A logistic regression model was developed 

and applied to lake basins greater than 1 hectare in Grand 

Teton (n = 106) and Yellowstone (n = 294).

A higher percentage of lakes in Grand Teton than in 

Yellowstone were predicted to be sensitive to atmospheric 

deposition in all three bins. For Grand Teton, 7 percent of 

lakes had a greater than 60-percent probability of having acidneutralizing capacity concentrations in the 0–50 bin, 36 percent of lakes had a greater than 60-percent probability of having acid-neutralizing capacity concentrations in the 0–100 bin, 

and 59 percent of lakes had a greater than 60-percent probability of having acid-neutralizing capacity concentrations in the 

0–200 bin. The elevation of the lake outlet and the area of the 

basin with northeast aspects were determined to be statistically 

significant and were used as the explanatory variables in the 

multivariate logistic regression model for the 0–100 bin. For 

Yellowstone, results indicated that 13 percent of lakes had a 

greater than 60-percent probability of having acid-neutralizing 

capacity concentrations in the 0–100 bin, and 27 percent of 

lakes had a greater than 60-percent probability of having acidneutralizing capacity concentrations in the 0–200 bin. Only the 

elevation of the lake outlet was determined to be statistically 

significant and was used as the explanatory variable for the 

0–100 bin.

The lakes that exceeded 60-percent probability of having 

an acid-neutralizing capacity concentration in the 0–100 bin, 

and therefore had the greatest sensitivity to acidification from 

atmospheric deposition, are located at elevations greater than 

2,790 meters in Grand Teton, and greater than 2,590 meters in 

Yellowstone.

Introduction

Atmospheric deposition of nitrogen and sulfur and the 

effects of climate change on water quality and quantity in 

high-elevation lakes are issues that are a concern for Grand 

Teton and Yellowstone National Parks (herein referred to as 

“Grand Teton” and “Yellowstone”). Physical characteristics 

of high-elevation basins, such as thin, rocky soils; sparse 

vegetation; and a short growing season in Grand Teton and 

Yellowstone make them susceptible to damage from atmospheric contaminants. Deposition of nitrogen to high-elevation 

lakes has the potential to change the nutrient status of aquatic 

ecosystems through nitrogen saturation, increasing vulnerability to episodic acidification from atmospheric deposition. 

Current (2005) atmospheric deposition rates and proposed 

changes in atmospheric emissions, including increasing emissions from powerplants and energy production near Grand 

Teton and Yellowstone, have the potential to further alter the 

chemistry of these aquatic ecosystems.

Previous studies have documented strong relations 

between acid-neutralizing capacity (ANC) concentrations and 

certain basin characteristics (Melack and others, 1985; Nishida 

and Schnoor, 1989; Hooper and others, 1990; Clow and 

Sueker, 2000; Rutkowski and others, 2001; and Leora Nanus 

Sensitivity of Alpine and Subalpine Lakes to Acidification 

from Atmospheric Deposition in Grand Teton National 

Park and Yellowstone National Park, Wyoming

By Leora Nanus, Donald H. Campbell, and Mark W. Williams
2 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

and D.W. Clow, U.S. Geological Survey, written commun., 

2004). ANC is the measure of the amount of acid necessary to 

neutralize the bicarbonate, carbonate, alumino-hydroxy complexes, and other bases in a water sample and is determined 

using acidimetric Gran analysis (Kanciruk and others, 1987).

Compilation of historical water-quality data that have 

been collected in Grand Teton (Woods and Corbin, 2003a) and 

Yellowstone (Woods and Corbin, 2003b) indicates that few 

chemical data are available for Outstanding Natural Resource 

Waters in Yellowstone, particularly high-elevation lakes. 

Gulley and Parker (1985) conducted a limnological survey of 

70 small lakes and ponds in Grand Teton and determined that 

the lakes were very dilute and very poorly buffered, indicating that they could be extremely susceptible to acidification 

caused by the atmospheric deposition of contaminants. Of the 

17 high-elevation lakes sampled throughout Grand Teton and 

Targhee National Forest in 1996, 14 had ANC concentrations 

less than 200 microequivalents per liter (μeq/L), within the 

U.S. Environmental Protection Agency (USEPA) criteria of 

sensitive to acidification (M.W. Williams and K.A. Tonnessen, 

University of Colorado and National Park Service, written 

commun., 1997). Corbin (2004) sampled high-elevation lakes 

in Grand Teton in 2002 and determined that most lakes had 

ANC concentrations less than 100 μeq/L.

Atmospheric deposition maps (for 1992 through 1999) 

of the Rocky Mountains show regions of high atmospheric 

deposition in the northern Rocky Mountains (Nanus and others, 2003), including parts of Wyoming and Montana. High 

inorganic nitrogen deposition (3.5 to 4.5 kg/ha/yr inorganic 

N), sulfate deposition (4.0 to 8.0 kg/ha/yr SO4-S), and relatively high hydrogen ion deposition (0.10 to 0.25 kg/ha/yr H+

) 

rates are occurring in Grand Teton and Yellowstone (Nanus 

and others, 2003).

Surface-water monitoring is needed in Grand Teton and 

Yellowstone to assess current conditions of aquatic ecosystems 

and evaluate the long-term effects of atmospheric deposition 

of contaminants on these aquatic ecosystems. To address this 

need, the National Park Service (NPS), Greater Yellowstone 

Inventory and Monitoring Network is designing a long-term 

monitoring plan for Outstanding Natural Resource Waters in 

Grand Teton and Yellowstone that will focus monitoring efforts 

on lakes most sensitive to atmospheric deposition. Differences 

in environmental settings, such as topography, hydrology, geology, and vegetation types of high-elevation lake basins between 

Grand Teton and Yellowstone (Zelt and others, 1999), support 

the need for a water-quality assessment in each park. To address 

this need, the U.S. Geological Survey (USGS), in cooperation with the NPS, is using a scientifically based approach to 

identify those systems most sensitive to atmospheric deposition 

of contaminants. The study described in this report identifies 

and quantifies the extent of lakes that are sensitive to changes 

such as eutrophication, fertilization, and acidification from 

atmospheric deposition. Results from the study described in this 

report will be used to aid in the design of a long-term monitoring plan for Outstanding Natural Resource Waters within Grand 

Teton and Yellowstone.

Purpose and Scope

The purpose of this report is to identify lakes in Grand 

Teton and Yellowstone that are sensitive to acidification from 

atmospheric deposition of contaminants. This report describes 

the development of multivariate, logistic regression models for 

estimating lake sensitivity. Sensitive lakes are defined as lakes 

with a greater than 60-percent probability of having an ANC 

concentration less than 200 μeq/L, USEPA’s criteria of sensitive to acidification. Using Geographical Information System 

(GIS) tools and spatial statistics, physical basin characteristics 

data, including land-surface characteristics and atmospheric 

factors such as precipitation and atmospheric deposition of 

contaminants, were derived for use as explanatory variables in 

the logistic regression models. The logistic regression models were calibrated using ANC concentration data. Discrete 

ANC concentration bins were developed for use in the logistic 

regression analyses to give managers the ability to vary their 

sensitivity criteria based on the focus of their study.

Acknowledgments

The authors thank Sue O’Ney of Grand Teton National 

Park, Cathie Jean of the Greater Yellowstone Inventory and 

Monitoring Network, and Kathy Tonnessen of the National 

Park Service, Rocky Mountain Cooperative Ecosystem Studies 

Unit for their support of this project. This report was greatly 

improved by colleague reviewers Kathy Tonnessen of the 

National Park Service and Alisa Mast of the U.S. Geological 

Survey. The authors also thank Ann Rodman of Yellowstone 

National Park for GIS data.

Description of Data Used in the 

Logistic Regression Models

Only previously analyzed water-quality data and previously generated GIS data were used in the logistic regression 

models described in this report. The GIS data were used for 

basin boundary delineation of lakes and quantification of 

physical basin characteristics.

Lake Acid-Neutralizing Capacity Data

ANC concentration data for alpine/subalpine lakes in 

Grand Teton and Yellowstone were compiled. Data sources 

include the USGS National Water Information System (NWIS), 

the Federal Data Storage and Retrieval System (STORET), 1996 

Grand Teton data from Tonnessen and Williams (M.W. Williams

and K.A. Tonnessen, University of Colorado and National 

Park Service, written commun., 1997), 1999 Grand Teton and 

Yellowstone data from the USGS (Clow and others, 2002), and 

2002 Grand Teton data (Corbin, 2004). STORET data included 

ANC concentrations from a limnological study conducted in 

Grand Teton by Gulley and Parker (1985), and the USEPA 
Western Lake Survey in Grand Teton and Yellowstone (Kanciruk

and others, 1987; Landers and others, 1987; Silverstein and others, 1987).

Selection criteria applied to the data sets for use in the 

study described in this report included only data from alpine 

and subalpine lakes that were sampled from July through the 

first week of October, lakes that were greater than 1 hectare 

(ha) in area and less than 4 ha in area, and ANC concentration 

data were available. The lake-size selection criteria was used 

to avoid inclusion of small tarns and ponds in the data set as 

well as really large lakes, and is in keeping with the selection criteria used for the Western Lake Survey (Kanciruk and 

others, 1987; Landers and others, 1987; Silverstein and others, 

1987). A total of 52 lakes in Grand Teton and 23 lakes in 

Yellowstone met the selection criteria.

The ANC concentration data that met the selection 

criteria were classified into the three ANC concentration 

bins (bins) that are within the USEPA’s criteria of sensitive to 

acidification: less than 50 μeq/L (0–50), less than 100 μeq/L 

(0–100), and less than 200 μeq/L (0–200) (figs. 1 and 2). ANC 

concentrations less than 50 μeq/L would be more appropriate 

for evaluating chronic acidification risk, though ANC concentrations less than 100 μeq/L likely would include lakes that 

may have episodic acidification. Thus, for Grand Teton, ANC 

concentration data were classified into bins of 0–50 μeq/L, 

0–100 μeq/L, and 0–200 μeq/L to calibrate logistic regression models. For Yellowstone, no lakes had ANC concentrations less than 50 μeq/L, so only bins of 0–100 μeq/L and 

0–200 μeq/L were used.

EXPLANATION

0

5

10

15

20

25

30

35

40

0-50 0-100 0-200 Greater than 200

ANC CONCENTRATION, IN MICROEQUIVALENTS PER LITER

NUMBER OF LAKES 

> 200

Acid-neutralizing capacity,

 in microequivalents per

 liter

0–200

0–100

0–50

> 200

0–200

0–100

0-100 0-200 Greater than 200

ANC CONCENTRATION, IN MICROEQUIVALENTS PER LITER

0

2

4

6

8

10

12

14

16

NUMBER OF LAKES 

EXPLANATION

Acid-neutralizing capacity,

 in microequivalents per

 liter

Figure 1. Frequency of lakes in acid-neutralizing capacity (ANC) concentration bins for Grand Teton 

National Park.

Figure 2. Frequency of lakes in acid-neutralizing capacity (ANC) concentration bins for Yellowstone 

National Park.

Description of Data Used in the Logistic Regression Model 3
4 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

Water-quality data were examined to determine if the data 

sets could be combined for sites with multiple years of ANC 

concentration data from one data set or multiple data sets. It 

was determined that ANC concentrations were not variable 

across the ANC concentration bins either temporally or for 

different data sets, and that the data sets could be combined. 

ANC concentrations range from 18 to 1,600 μeq/L in Grand 

Teton and 54 to 1,621 μeq/L in Yellowstone. Water-quality 

data for Yellowstone Lake and Jackson Lake were not used to 

calibrate the regression models because of the larger size of 

these lakes compared to the other lakes included in the study; 

however, the two large lakes were included in the total lake 

population to which the results of the modeling were applied.

Basin Boundary Delineation

Lake coverages at a scale of 1:24,000 (U.S. Geological

Survey, 2000b) were used to identify lakes with a surface area 

of 1–4 ha. One hundred and six lakes in Grand Teton (fig. 3

and table 6; tables 6–11 are in the appendix at the back of the 

report), and 294 lakes in Yellowstone (fig. 4 and table 10), had 

lake areas of 1–4 ha and were included in the study. By using a 

10-m digital elevation model (DEM) (U.S. Geological Survey, 

2000a) for Grand Teton and Yellowstone and the lake outlets, 

the basin boundaries for the lake watersheds were delineated 

in ArcGrid (Environmental Systems Research Institute, 1999). 

All grid cells that contribute flow to the specified lake outlet, 

also known as the basin pour point, were included within the 

basin. Basin boundary delineations were rigorously checked 

in GIS by overlaying the basin boundary on the DEM and 

hydrology coverage. Sixty-six percent of lakes in Grand Teton 

and 36 percent of lakes in Yellowstone that were included in 

the study were headwater lakes, defined as having no tributary 

basins entering the lake.

Physical Basin Characteristics Data

Physical basin characteristics data from a variety of 

data sets were quantified for each basin by using GIS tools 

and spatial statistics. A total of 45 (for Grand Teton; table 7) 

and 37 (for Yellowstone; table 8) variables of physical basin 

characteristics were quantified for testing as explanatory 

variables in the regression models. Each of the variables was 

considered to be a possible factor in controlling the ANC of 

the lake, and therefore the sensitivity of the lake to eutrophication, fertilization, and acidification from atmospheric deposition. The explanatory variables tested in the logistic regression 

models are defined in tables 7 (for Grand Teton) and 8 (for 

Yellowstone).

Land-Surface Characteristics

Land-surface characteristics were derived from GIS 

data sets including a 1:24,000 lake coverage (U.S. Geological

Survey, 2000b), a 10-m DEM (U.S. Geological Survey, 

2000a), a 1:62,500-scale bedrock-geology coverage for 

Grand Teton (National Park Service, 1992), a 1:125,000-scale 

bedrock-geology coverage for Yellowstone (National Park 

Service, 1988), a 1:24,000-scale soils coverage for Grand 

Teton (National Park Service, 1994a), a 1:62,500-scale soils 

coverage for Yellowstone (National Park Service, 1997), a 

1:62,500-scale vegetation coverage for Grand Teton (National 

Park Service, 1994b), a 10-m vegetation grid for Yellowstone 

(National Park Service, 1990), a 1:125,000-scale precipitation grid for Grand Teton (Spatial Climate Analysis Service, 

2000), a 1:125,000-scale precipitation grid for Yellowstone 

(National Park Service, 1999), a 1:125,000-scale hydrogen iondeposition grid (Nanus and others, 2003), a 1:125,000-scale 

inorganic nitrogen-deposition grid (Nanus and others, 2003), 

and a 1:125,000-scale sulfate-deposition grid (Nanus and others, 2003).

The range in elevation for Grand Teton is 1,927 to 

4,185 m (fig. 5), and Yellowstone is 1,566 to 3,460 m (fig. 5). 

Grand Teton has a larger percentage of high-elevation terrain 

compared to Yellowstone (fig. 5). For each lake basin, the 

10-m DEM was used to calculate mean elevation and slope 

and to derive other physical parameters including lake-outlet 

elevation, maximum elevation, basin area, lake/basin area, percentage of steep slopes (slopes > 30 degrees), and percentage 

of aspect (by 45-degree increments) (tables 7 and 8). Aspect of 

0 degree is north, 90 degrees is east, 180 degrees is south, and 

270 degrees is west.

The lithologies for Grand Teton and Yellowstone were 

grouped into six different geochemical classes (hereinafter 

referred to as “geochemical ranking”) that were ranked from low 

to high on the basis of buffering capacity of the bedrock (Leora 

Nanus and D.W. Clow, U.S. Geological Survey, written commun., 2004). The geochemical rankings (GC) are as follows:

 GC 1 Class 1, Low buffering capacity: gneiss, 

 quartzite, schist, granite;

 GC 2 Class 2, Moderate buffering capacity: andesite, 

 dacite, diorite, phyllite;

 GC 3 Class 3, High buffering capacity: basalt, gabbro, 

 wacke, argillite, undifferentiated volcanic rocks;

 GC 4 Class 4, Very high buffering capacity: amphibolite, 

 hornfels, paragneiss, undifferentiated metamorphic 

 rocks;

 GC 5 Class 5, Extremely high buffering capacity: 

 metacarbonate, marine sedimentary rocks, marble, 

 calcium silicate and basic intrusive rocks; and

 GC 6 Class 6, Unknown buffering capacity.

The grouped geochemical-ranking coverage is shown in 

fig. 6. The predominant geochemical rankings, based on the 

potential buffering capacity of the bedrock for Grand Teton, 

are GC 1, GC 3, and GC 4, and for Yellowstone they are GC 3 

and GC 4. The large amount of GC 1 in Grand Teton indicates 

that the buffering capacity of the bedrock is lower in Grand 

Teton than in Yellowstone. The percentage of areal coverage 
Figure 3. Location of lakes greater than 1 hectare in Grand Teton National Park.

Montana

Wyoming

Idaho

Yellowstone 

National Park

Grand Teton 

National Park

44o08'

 43o35'

110o35'

73

46

38

42

57

50

56

49

51 53

67

71

60

55

41

45

78

74

40

58

89

79

61

68

44

75

86

36

43

37

87

65

77

70

52

85

63

72

48

76

83

47

80

82

91

90

92

66

84

81

12

25

106

31

93

101

102

99

4

 6

97

21

9

29

98

23

24

95

7

20

19

30

28

34

10

18

32

104

13

96

35

26

94

39

59 62

Jackson

Lake

11 69

88

54

64

5

105

8

14

27

1

100

33

22

Grand Teton

National Park

103

 3

18

1516

2

Lake location and ID number

 EXPLANATION

 Roads

 Park boundary

1

Base from U.S. Geological Survey digital data

Universal Transverse Mercator projection

Zone 12

0 5

5

2.5 7.5 10 MILES

0 10 15 20 KILOMETERS

Description of Data Used in the Logistic Regression Model 5
6 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

45o00'

111o00'

110o35'

110o00'

44o08'

210

234

257

211

90

224

134

164

100

290

229

120

170

258

279

295

287

112

216

48

269

195

4

286

92

28

165

166

238

74

208

88

171

119

191

106

51

189

30

209

101

160

278

303

188

14

78

3

132

95

197

298 304

6

66

7 8

236

65

16

5

151

248

124

262

107

20

149 145

1

84

29

47

250

213

259

109

38

293

111

225

266

60

231

273

116

61

233

114

138

276

54

53 41

296

13

56

265

72

146

253

77

97

289

139

80

35

24

227

199

82

9

104

36

136

25

186

11 10

110

123

85

93

73

69

76

57

179

31 32

117

207

68

182

21

156

49

300

19

291

15

86

302

292

204

37 44

33

75

217

246

12

152

98

176

67

192

17

228

34

282

108

96

169

184

27

163

18

270

40

271

274 275

153

222

294

155

113

283

142

118

230

261

172

277

185

251

223

143

115

130

202

260

2

22

63

 23

39

46

 59 58 55

50

70

79 83

89 91

99 103 102

121 122 125 128

137

140 147 144 148

150

154

159

174

 26

45 42 52 43

64 62

71

87 81

94

105

126

 141

135

161 168 175

178

127

131 133 129

167

173

187

196 190

193

200 198

194

215 218 219 221 220

226

249

243

240242 247

245

255

Yellowstone

Lake

252

288

284 280

285

281

305 306

268

272

264 263

267

297

301 307

299

Yellowstone 

National Park

Montana

Wyoming

Idaho

Yellowstone 

National Park

Grand Teton 

National Park

0 5 2.5 7.5 10 MILES

0 5 10 15 20 KILOMETERS

Lake location and ID number

 EXPLANATION

 Roads

 Park boundary

1

Base from U.S. Geological Survey digital data

Universal Transverse Mercator projection

Zone 12

Figure 4. Location of lakes greater than 1 hectare in Yellowstone National Park.
0 1 5 0 20 Miles

Yellowstone 

National Park

Grand Teton 

National Park

 EXPLANATION

 Park Boundary

High : 4,200

Low :1,500

Elevation (meters)

Montana

Wyoming

Idaho

Yellowstone 

National Park

Grand Teton 

National Park

0 10 20 30 40 KILOMETERS

0 5 10 15 20 MILES

44 08' o

45 00' o

 43 35' o

111 00' o 110 35' o 110 00' o

'

Base from U.S. Geological Survey digital data

Universal Transverse Mercator projection

Zone 12

Figure 5. Elevation in Grand Teton and Yellowstone National Parks.

Description of Data Used in the Logistic Regression Model 7
8 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

Wyoming

Montana

Idaho

Yellowstone 

National Park

Grand Teton 

National Park

Grand Teton

National Park

Yellowstone 

National Park

0 10 20 30 40 KILOMETERS

0 5 10 15 20 MILES

GC 1: Low buffering capacity

GC 2: Moderate buffering capacity

GC 3: High buffering capacity

GC 4: Very high buffering capacity

GC 5: Extremely high buffering capacity

GC 6: Unknown buffering capacity

 EXPLANATION

 Park boundary

Geochemical rank based on buffering 

 capacity of the bedrock 

45 00'

111 00' o

110 35'

110 00' o

o

o

44 08'

 43 35'

o

o

Base from U.S. Geological Survey digital data

Universal Transverse Mercator projection

Zone 12

Figure 6. Geochemical rankings in Grand Teton and Yellowstone National Parks.
of the six geochemical rankings in each basin was calculated in GIS by overlaying the delineated boundaries on the 

geochemical-ranking coverage.

Soil type for Grand Teton and Yellowstone was grouped 

for each individual park based on preexisting soils classifications into 17 different types for Grand Teton (table 7) and 

5 different types for Yellowstone (table 8) (Ann Rodman, 

National Park Service, written commun., 2004).

Vegetation type was classified into low, medium, and 

high classes based on sensitivity to deposition of contaminants (tables 7 and 8). High sensitivity includes agricultural 

or unvegetated terrain such as snow, ice, rock, and water. 

Medium sensitivity includes forest and tundra, and low 

sensitivity includes subalpine meadow.

Atmospheric Factors

Atmospheric factors, including precipitation amount and 

atmospheric deposition rates of inorganic nitrogen, sulfate, 

and hydrogen ion, also were included as explanatory variables 

in the logistic regression models. The mean-annual precipitation variable for each basin was derived from a 30-year

(1961–90) average annual precipitation grid (Parameterelevation Regressions on Independent Slopes Model; PRISM; 

Spatial Climate Analysis Service, 2000). Within the study area, 

mean-annual precipitation, by lake basin, ranged from a low of 

530 mm/yr to a high of 4,720 mm/yr.

Atmospheric deposition of hydrogen ion, inorganic 

nitrogen, and sulfate has the potential to alter the chemistry of 

aquatic ecosystems, through nitrogen saturation and episodic 

acidification, thus increasing the sensitivity of lakes to future 

acidification from atmospheric deposition in Grand Teton 

and Yellowstone. Mean-annual deposition of hydrogen ion, 

inorganic nitrogen, and sulfate were calculated for each basin. 

Within the study area, mean annual atmospheric deposition 

ranges are as follows: hydrogen ion deposition ranges from 

0.03 to 0.1 kg/ha/yr hydrogen ion, 0.2 to 4.3 kg/ha/yr inorganic nitrogen, and 0.7 to 6.8 kg/ha/yr sulfate (Nanus and 

others, 2003). The variability in solute deposition was largely 

controlled by precipitation amount (Nanus and others, 2003).

Description of Logistic Regression 

Modeling Technique

Multivariate logistic regression for each ANC concentration bin was used to identify lakes with a high probability 

of sensitivity to acidic deposition. Logistic regression differs 

from linear regression in that the result is the probability of 

being above or below a threshold, rather than a predicted 

value (Helsel and Hirsch, 1993). The large variability in 

ANC concentrations in Grand Teton and Yellowstone is 

such that predicting the probability for a lake to be within a 

discrete ANC concentration bin (0–50 μeq/L, 0–100 μeq/L, 

and 0–200 μeq/L) is a good approach and supports the use of 

logistic regression over other statistical analyses.

The probability equation is:

Logit (P) = e

bo bx +

1 e

bo bx +

+

-------------------------- (1)

where

Logit (P) is probability that ANC concentration is 

within a specified ANC concentration bin;

e is natural logarithm;

bo is constant;

and

bx is vector of slope coefficients and explanatory variables.

Basin characteristics (45 for Grand Teton and 37 for 

Yellowstone) were used as explanatory variables, and ANC 

concentrations at 52 lakes in Grand Teton and 23 lakes in 

Yellowstone were used as the dependent variable to calibrate 

the regression models. First, all explanatory variables were 

tested independently using univariate logistic regression, 

and the explanatory variables that have significant influence 

(p-value < 0.1) were included in an initial multivariate logistic 

regression analysis. Only explanatory variables that were significant (p-value < 0.05) in the initial multivariate analysis were 

included in the final multivariate logistic regression models. 

The resultant multivariate logistic regression models are highly 

significant (p-value < 0.05), compared with an intercept-only 

model that contains none of the explanatory variables. Once the 

final multivariate logistic regression models were calibrated, the 

resultant probability equations for each ANC concentration bin 

were applied to all lakes greater than 1 ha in Grand Teton and 

Yellowstone. Thus, the model was applied to lakes with ANC 

data (that were used to calibrate the models) and lakes without 

data to determine the probability for a lake to be in an ANC 

concentration bin. To enable further evaluation of the logistic 

regression model for each ANC concentration bin, model-based 

predicted probabilities were compared to measured concentrations by using the Hosmer-Lemeshow Goodness-of-Fit (Hosmer

and Lemeshow, 1989). For example, Somers’ D is used to 

determine the strength and direction of relation between pairs of 

variables (SAS Institute, 1990). Its values range from –1.0 (all 

pairs disagree) to 1.0 (all pairs agree). The c-statistic is another 

measure of rank correlation of ordinal variables (SAS Institute, 

1990). It is justified so that it ranges from 0 (no association) 

to 1 (perfect association). It is a variant of Somers’ D index. 

The wald statisitic can be used to determine significance of the 

coefficients (SAS Institute, 1990). The wald statistic is based on 

chi-square distribution and is the square of the ratio of the coefficient to its standard error.

Lakes with a high probability (greater than 60 percent) of 

having an ANC concentration within the predefined bins were 

identified as potentially sensitive. These results were subdivided 

further into four probability ranges: probability that the estimated ANC concentration is in a bin is equal to or greater than 

Description of Data Used in the Logistic Regression Model 9
10 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

90 percent; probability that the estimated ANC concentration is 

in a bin ranges from 80 to 90 percent; probability that the estimated ANC concentration is in a bin ranges from 70 to 80 percent; and probability that the estimated ANC concentration is in 

a bin ranges from 60 to 70 percent. The classification grouping 

described above was repeated for each ANC concentration bin: 

0–50 μeq/L, 0–100 μeq/L, and 0–200 μeq/L in Grand Teton, and 

0–100 μeq/L and 0–200 μeq/L in Yellowstone.

Logistic Regression Model Calibration 

and Application

Grand Teton National Park

In Grand Teton, 52 lakes between 1–4 ha that had 

available ANC concentration data for July through October 

were used to calibrate the logistic regression models for each 

ANC concentration bin. After each model was calibrated for 

the ANC concentration bins (0–50 μeq/L, 0–100 μeq/L, and 

0–200 μeq/L), the model was applied to the 106 lakes in Grand 

Teton that are greater than 1 ha (fig. 3 and table 6). This section of the report describes the model calibration and application for each bin in Grand Teton. Results of the univariate and 

multivariate logistic regression analysis for Grand Teton are 

presented in tables 7 and 9.

For Grand Teton, results of the lake-sensitivity classification using multivariate logistic regression indicate that the 

fraction of basin that is composed of soil type 9, LeightonMoran Wolcott association soils (p-value = 0.0035), and the 

percent area of the basin with steep slopes (slopes greater than 

30 degrees) (p-value = 0.0276) were the only physical basin 

characteristics that were significant at the 95-percent confidence interval (p-value < 0.05) using an ANC concentration 

bin of 0–50 μeq/L (table 9). As the area of the basin with steep 

slopes and the area of the basin with soil type 9 increases, the 

buffering capacity of the basin decreases as a result of thin 

soils and resistant bedrock, and the probability that ANC concentrations are in the 0–50 μeq/L bin increases. The HosmerLemeshow Goodness-of-Fit, which compares the measured 

concentrations of the response variable to the predicted concentrations obtained from models with and without the variable 

in question, indicates a good model fit to the calibration data. 

Measured ANC concentrations were compared to predicted 

ANC concentrations by randomly grouping the lakes with 

measured ANC into 10 groups with an equal number of lakes. 

These random groupings of 10 percent were used to evaluate model agreement between measured and predicted ANC 

concentration. In Grand Teton, measured ANC concentrations 

of 0–50 μeq/L compared to predicted in random groupings of 

10 percent, showed good agreement with a r-squared value 

equal to 0.66 (table 9). The c statistic, a variant of Somers’ D

index that measures rank correlation (SAS Institute, 1990), is 

equal to 0.90, indicating good association.

The following probability equation was applied to the 

106 delineated basins:

Logit (P) = e

�– 9.702 soil_9 8.624 + � � + 13.761 steep slope � ��

1 e�– 9.702 soil_9 8.624 + � � + 13.761 steep slope � �� +

------------------------------------------------------------------------------------------------------------ (2)

where Logit (P) and e are defined as in equation 1.

For an ANC concentration bin of 0–100 μeq/L, results 

indicate that the elevation of the lake outlet (p-value = 0.0005) 

and the area of the basin with northeastern aspects (asp45) 

(p-value = 0.0272) are significant at the 95-percent confidence interval (p-value < 0.05). As the elevation of lake outlet 

increases and the area of the basin with northeastern aspects 

decreases, the probability that ANC concentration is in the 

0–100 μeq/L bin increases. High-elevation watersheds with 

northeastern aspects have deep, seasonal snowpacks that have 

high rates of runoff during snowmelt and limited water/soil 

interaction, limiting the potential buffering capacity of the 

basin. Thus, elevation of lake outlet and the area of the basin 

with northeastern aspects were used as explanatory variables in 

the multivariate logistic regression model (table 9). Measured 

ANC concentrations 0–100 μeq/L compared to predicted in 

random groupings of 10 percent in Grand Teton, showed good 

agreement with a r-squared value equal to 0.61 (table 9). The 

c statistic is equal to 0.88, indicating good association.

The following probability equation was applied to the 

106 delineated basins:

Logit (P) = e

�– 0.004 min_elev 9.455 + � � – 8.318 asp45 � ��

1 e + �– 0.004 min_elev 9.455 + � � – 8.318 asp45 � �� --------------------------------------------------------------------------------------------------- (3)

where Logit (P) and e are defined as in equation 1.

For an ANC concentration bin of 0–200 μeq/L, only 

bedrock type GC 1, with low to no buffering capacity (p-value =

0.0003), was statistically significant at the 95-percent confidence 

interval (p-value < 0.05), such that as the area of the basin with 

GC 1 increases, the probability that ANC concentration is in 

the 0–200 bin increases. Thus, GC 1 was used as the explanatory variable in the model. Measured ANC concentrations 

0–200 μeq/L compared to predicted in groupings of 10 percent 

in Grand Teton, showed very good agreement with a r-squared 

value equal to 0.99 (table 9). The c statistic is equal to 0.86, 

indicating good association.

The following probability equation was applied to the 

106 delineated basins:

 Logit (P) = e

�–2.546 4.883 GC 1 + � ��

1 e�–2.546 4.883 GC 1 + � �� +

----------------------------------------------------------- (4)

where Logit (P) and e are defined as in equation 1.
Yellowstone National Park

In Yellowstone, 23 lakes, or 8 percent of lakes greater 

than 1 ha, met the selection criteria, and ANC data were 

used to calibrate the logistic regression models. Results of 

the univariate and multivariate logistic regression analysis 

for Yellowstone are presented in tables 8 and 11. Results 

for Yellowstone lakes with probabilities of being within the 

ANC concentration bins (0–100 μeq/L and 0–200 μeq/L) are 

presented in table 10. Two hundred and ninety-four lakes in 

Yellowstone are greater than 1 ha and were included in this 

study (fig. 4 and table 10).

For an ANC concentration bin of 0–100 μeq/L in 

Yellowstone, only elevation of lake outlet (min_elev, tables 8 

and 11) (p-value = 0.052) was significant at the 95-percent 

confidence interval, such that as elevation of lake outlet 

increases the probability that ANC concentration is 0–100 

μeq/L increases. Thus, elevation of lake outlet was used as the 

explanatory variable in the final multivariate logistic regression model. The Hosmer-Lemeshow Goodness-of-Fit indicates 

a good model fit to the calibration data. Measured ANC concentrations 0–100 μeq/L compared to predicted ANC concentrations 0–100 μeq/L in groupings of 10 percent in Yellowstone, showed good agreement with a r-squared value equal to 

0.61 (table 11). The c statistic is equal to 0.95, indicating good 

association. The following probability equation was applied to 

the 294 delineated basins.

 Logit (P) = e

�–40.149 0.005 min_elev + � ��

1 e�–40.149 0.005 min_elev + � �� +

--------------------------------------------------------------------- (5)

where Logit (P) and e are defined as in equation 1.

For an ANC concentration bin of 0–200 μeq/L, the elevation of lake outlet (p-value = 0.091) and the bedrock type 

with high buffering capacity (GC 3) (p-value = 0.053) were 

significant at the 95-percent confidence interval, such that as 

elevation of lake outlet increased and the amount of the basin 

with bedrock type GC 3 increased, the probability for an ANC 

concentration to be 0–200 μeq/L increases. Thus, elevation of 

lake outlet and bedrock type GC 3 were used as the explanatory variables in the multiple logistic regression models. 

Measured ANC concentrations less than 200 μeq/L compared 

to predicted in groupings of 10 percent in Yellowstone showed 

agreement with a r-squared value equal to 0.54 (table 11). The 

c statistic is equal to 0.78, indicating good association.

The following probability equation was applied to the 

294 delineated basins with unknown lake chemistry:

Logit (P) = e

–14.901 0.002· � + � � min_elev + 3.080 GC 3 � ��

1 e –14.901 0.002· � + � � min_elev + 3.080 GC 3 � �� +

---------------------------------------------------------------------------------------------------- (6)

where Logit (P) and e are defined as in equation 1.

Sensitivity of Alpine and Subalpine 

Lakes to Acidification from Atmospheric 

Deposition

Grand Teton National Park

The probabilities associated with each basin provide an 

indication of the lake sensitivity to acidification from atmospheric deposition. Results for Grand Teton lakes with probabilities of being in an ANC concentration bin are presented 

in table 6. Results indicated that 7 percent of the lakes had a 

greater than 60-percent probability of having ANC concentrations 0–50 μeq/L and 0 percent of the lakes had a greater 

than 80-percent probability of having ANC concentrations 

0–50 μeq/L (table 1). Lakes with a greater than 60-percent 

probability of an ANC concentration bin of 0–50 μeq/L are 

located in areas with steep slopes and soil type 9 in western 

and southwestern Grand Teton (fig. 7).

Results indicated that 36 percent of lakes had a greater 

than 60-percent probability of having ANC concentrations 

less than 100 μeq/L, and 14 percent of lakes had a greater 

than 80-percent probability of having ANC concentrations 

0–100 μeq/L (table 2). Lakes with a greater than 60-percent 

probability of lake sensitivity with respect to atmospheric 

deposition for an ANC concentration bin of 0–100 μeq/L are 

shown in fig. 8. Lakes with greater than 80-percent probability that ANC concentration is less than 100 μeq/L are located 

in western and southwestern Grand Teton. The same lakes 

that are significant in Grand Teton for the 0–50 ANC bin are 

significant at the 0–100 ANC bin.

Table 1. Predicted number and percentage of lakes in Grand 

Teton National Park by probability of an acid-neutralizing capacity

concentration bin of 0–50 microequivalents per liter.

[Total number of lakes used in the calculation of percentage of lakes in Grand 

Teton National Park is 106; μeq/L, microequivalents per liter; %, percent; 

ANC, acid-neutralizing capacity]

Probability of ANC 

concentration less 

than 50 μeq/L

Number 

of lakes 

Percentage 

of lakes 

Greater than 10% 25 24%

Greater than 20% 20 19%

Greater than 30% 14 13%

Greater than 40% 12 11%

Greater than 50% 8 8%

Greater than 60% 7 7%

Greater than 70% 5 5%

Greater than 80% 0 0%

Greater than 90% 0 0%

Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition 11
12 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

Results indicate that 59 percent of lakes had a greater 

than 60-percent probability of having ANC concentrations 

less than 200 μeq/L, and 46 percent of lakes had a greater 

than 80-percent probability of having ANC concentrations 

0–200 μeq/L (table 3). Lakes with a greater than 60-percent 

probability of lake sensitivity with respect to atmospheric 

deposition for an ANC concentration bin of 0–200 μeq/L are 

shown in fig. 9. Lakes with an 80- to 100-percent probability 

that ANC concentration is less than 200 μeq/L are located 

throughout western and southwestern Grand Teton.

Yellowstone National Park

Results for Yellowstone lakes with probabilities 

of being in an ANC concentration bin are presented in 

table 10. Results indicated that 13 percent of lakes had a 

greater than 60-percent probability of having ANC concentrations 0–100 μeq/L, and 9 percent of lakes had a greater 

than 80-percent probability of having ANC concentrations 

0–100 μeq/L (table 4). Lakes with a greater than 60-percent 

probability of lake sensitivity with respect to atmospheric 

deposition for an ANC concentration bin of 0–100 μeq/L 

are shown in fig. 10. Lakes with 80- to 100-percent probability that ANC concentration is less than 100 μeq/L are 

located throughout eastern and northwestern Yellowstone. 

The exception is unnamed lake (261) in southwestern 

Yellowstone.

Results indicated that 27 percent of lakes had a 

greater than 60-percent probability of having ANC concentrations 0–200 μeq/L, and 13 percent of lakes had a 

greater than 80-percent probability of having ANC concentrations less than 200 μeq/L (table 5). Lakes with a 

greater than 60-percent probability of lake sensitivity with 

respect to atmospheric deposition for an ANC concentration bin of 0–200 μeq/L are shown in fig. 11. Lakes with 

greater than or equal to 90-percent probability that ANC 

concentration is 0–200 μeq/L are located throughout eastern and central Yellowstone. The exception is unnamed lake 

(261) in southwestern Yellowstone. Lakes with greater than 

80-percent probability that ANC concentration is less than 

200 μeq/L are located throughout central, southeastern, and 

southwestern Yellowstone.

Comparison between Grand Teton 

National Park and Yellowstone National 

Park

For comparison of results between Grand Teton and 

Yellowstone, an ANC concentration bin of 0–100 μeq/L 

was selected because it was the lowest ANC concentration 

bin used for the multivariate logistic regression analysis that 

was common to both parks. The results of the modeling in 

Grand Teton and Yellowstone indicate that the identification 

of lakes can be based on a greater than 60-percent probability of having an ANC concentration bin 0–100 μeq/L. 

A higher percentage of lakes in Grand Teton (36 percent) 

were determined to be sensitive to deposition of contaminants 

than in Yellowstone (13 percent) for the 0–100 μeq/L ANC 

bin.

For Grand Teton and Yellowstone, the elevation 

of the lake outlet was significantly correlated with ANC 

concentration such that as elevation increased, ANC 

concentration decreased. In Grand Teton, the area of the 

basin with northeast aspects also was significant. Results 

Table 2. Predicted number and percentage of lakes in Grand 

Teton National Park by probability of an acid-neutralizing capacity

concentration bin of 0–100 microequivalents per liter.

[Total number of lakes used in the calculation of percentage of lakes in Grand 

Teton National Park is 106; μeq/L, microequivalents per liter; %, percent; 

ANC, acid-neutralizing capacity]

Probability of 

ANC concentration 

less than 100 μeq/L

Number 

of lakes 

Percentage 

of lakes 

Greater than 10% 81 76%

Greater than 20% 61 58%

Greater than 30% 55 52%

Greater than 40% 54 51%

Greater than 50% 44 42%

Greater than 60% 38 36%

Greater than 70% 30 28%

Greater than 80% 15 14%

Greater than 90% 6 5%

Table 3. Predicted number and percentage of lakes in Grand 

Teton National Park by probability of an acid-neutralizing capacity 

concentration bin of 0–200 microequivalents per liter.

[Total number of lakes used in the calculation of percentage of lakes in Grand 

Teton National Park is 106; μeq/L, microequivalents per liter; %, percent; 

ANC, acid-neutralizing capacity]

Probability of 

ANC concentration 

less than 200 μeq/L

Number 

of lakes

Percentage 

of lakes

Greater than 10% 75 71%

Greater than 20% 71 67%

Greater than 30% 67 63%

Greater than 40% 64 60%

Greater than 50% 64 60%

Greater than 60% 63 59%

Greater than 70% 57 54%

Greater than 80% 49 46%

Greater than 90% 29 27%
of this study indicate that the lakes that exceeded 60-percent 

probability of having an ANC concentration of less than 

100 μeq/L, and therefore at risk to atmospheric deposition, 

are located at elevations greater than 2,790 m in Grand Teton 

and greater than 2,590 m in Yellowstone. Rutkowski and 

others (2001) used a GIS-based model to assess surfacewater sensitivity to atmospheric deposition in Wilderness 

Areas of Nevada, Idaho, Utah, and Wyoming, and determined 

that elevation and bedrock geology were significant predictors of low ANC surface waters.

Atmospheric deposition of inorganic nitrogen, sulfate, and acidity was not significantly correlated with ANC 

concentrations, which may be because deposition is fairly 

similar among these sites. However, very high-risk basins 

include lakes where ANC concentrations are low and atmospheric deposition of contaminants is relatively high. Lakes 

with a greater than 60-percent probability of having an 

ANC concentration less than 100 μeq/L in Grand Teton and 

Yellowstone were within the following ranges for average 

annual atmospheric deposition: 0.05–0.15 kg/ha/yr hydrogen ion, 1.0–3.5 kg/ha/year inorganic nitrogen, 2–8 kg/ha/yr 

sulfate. Summit lake and unnamed lake (261) in southwestern Yellowstone were located in an area with deposition of 

2–2.5 kg/ha/year inorganic nitrogen.

The uncertainty associated with the combined use of 

GIS modeling and multivariate logistic regression is difficult 

to quantify. The best available NPS GIS data for Grand Teton 

and Yellowstone were used in this study; however, finer resolution GIS data, not currently (2005) available, may improve 

the model. Differences in the resolution of the geology and 

soils GIS data between Grand Teton and Yellowstone may 

have influenced the comparison results. Additionally, the 

physical geology, including the presence of major geologic 

contacts or faults within each lakes basin influences ANC 

concentration to an unknown degree and was not included as 

a variable in this study. Environmental variables other than 

those included in this study also may contribute to variability in some lake ANC concentrations and can be difficult to 

quantify; these variables could include recreational use, fire, 

and thermal activity.

The GIS and logistic regression modeling approach 

described in this report can be used as a cost-effective tool to 

help resource managers identify lakes likely to be sensitive to 

atmospheric deposition of contaminants and develop longterm monitoring programs. The sensitivity for both Grand 

Teton and Yellowstone lakes indicate a need for long-term 

monitoring, to identify seasonal variability and episodic acidification. In the future, it may be prudent to use the probability 

estimates to identify one to two alpine lakes in each park with 

a lake area of 1–4 ha that could be monitored by collecting 

samples each season for a minimum of 5 years. These intensive monitoring sites also could include climate stations for 

precipitation sample collection. The combination of intensive 

lake-chemistry and precipitation-chemistry data at one to 

two alpine lakes in each park would allow resource managers 

to observe short-term and long-term variability in inorganic 

nitrogen and sulfate deposition. Additionally, three to four 

lakes could be sampled once annually for at least 10 years to 

monitor long-term change. These could include lakes with the 

highest probability for ANC concentrations less than 50 μeq/L 

in Grand Teton and less than 100 μeq/L in Yellowstone, and 

with good spatial distribution within each park.

Table 4. Predicted number and percentage of lakes in 

Yellowstone National Park by probability of an acid-neutralizing 

capacity concentration bin of 0–100 microequivalents per liter.

[Total number of lakes used in the calculation of percentage of lakes 

in Yellowstone National Park is 294; μeq/L, microequivalents per liter; 

%, percent; ANC, acid-neutralizing capacity]

Probability of 

ANC concentration 

less than 100 μeq/L

Number 

of lakes

Percentage 

of lakes

Greater than 10% 101 34%

Greater than 20% 88 30%

Greater than 30% 73 25%

Greater than 40% 55 19%

Greater than 50% 43 15%

Greater than 60% 38 13%

Greater than 70% 29 10%

Greater than 80% 26 9%

Greater than 90% 16 5%

Table 5. Predicted number and percentage of lakes in 

Yellowstone National Park by probability of an acid-neutralizing 

capacity concentration bin of 0–200 microequivalents per liter.

[Total number of lakes used in the calculation of percentage of lakes 

in Yellowstone National Park is 294; μeq/L, microequivalents per liter; 

%, percent; ANC, acid-neutralizing capacity]

Probability of 

ANC concentration 

less than 200 μeq/L

Number 

of lakes 

Percentage 

of lakes 

Greater than 10% 207 70%

Greater than 20% 164 56%

Greater than 30% 132 45%

Greater than 40% 115 39%

Greater than 50% 97 33%

Greater than 60% 80 27%

Greater than 70% 60 20%

Greater than 80% 39 13%

Greater than 90% 15 5%

Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition 13
14 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

76

28

10

13

94

14

1

Grand Teton

National Park

 Roads

 Park boundary

 60–70

Percent probability that alkalinity

 concentration is less than 50

 microequivalents per liter

 70–80

EXPLANATION

Montana

Wyoming

Idaho

Yellowstone 

National Park

Grand Teton 

National Park

0 2.5 5 7.5 10 MILES

0 5 10 15 20 KILOMETERS

44 08' o

 43 35' o

110 35' o

Base from U.S. Geological Survey digital data

Universal Transverse Mercator projection

Zone 12

Figure 7. Probability greater than 60 percent of lake sensitivity in Grand Teton National Park to atmospheric 

deposition using an acid-neutralizing capacity concentration bin of 0–50 microequivalents per liter.
42

49

67

55

41

74

61

44

86

43

87

70

63

72

76

83

47

90

92

84

97

23

24

28

10

32

104

13

94

62

8

14

27

1

100

33

22

Grand Teton

National Park

103

 90–100

 Roads

 Park boundary

 80–90

 70–80

 60–70

Percent probability that alkalinity

 concentration is less than 100 

 microequivalents per liter

5

EXPLANATION

Montana

Wyoming

Idaho

Yellowstone 

National Park

Grand Teton 

National Park

 10 MILES

5

2.5 7.5

0 10 15 20

0

KILOMETERS

110 35' o

45 00' o

 43 35' o

Base from U.S. Geological Survey digital data

Universal Transverse Mercator projection

Zone 12

Figure 8. Probability greater than 60 percent of lake sensitivity in Grand Teton National Park to atmospheric 

deposition using an acid-neutralizing capacity concentration bin of 0–100 microequivalents per liter.

Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition 15
16 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

57

50

49 53

67

71

55

74

58

79

61

86

87

70

63

72

76

83

47

80

82

90

92

84

81

25

31

93

102

99

4

 6

97

29

98

23

95

30

28

34

10

104

13

35

94

59

62

11

88

105

8

14

27 1

100

33

22

Grand Teton

National Park

103

 3

17

16 15

2

Montana

Wyoming

Idaho

Yellowstone 

National Park

Grand Teton 

National Park

45 00'

 43 35'

110 35'

o

o

o

 90–100

 Roads

 Park boundary

 80–90

 70–80

 60–70

Percent probability that alkalinity

 concentration is less than 200 

 microequivalents per liter

EXPLANATION

5 10 MILES

5

2.5 7.5

0 10 15 20

0

KILOMETERS

Base from U.S. Geological Survey digital data

Universal Transverse Mercator projection

Zone 12

Figure 9. Probability greater than 60 percent of lake sensitivity in Grand Teton National Park to atmospheric 

deposition using an acid-neutralizing capacity concentration bin of 0–200 microequivalents per liter.
4

74

189

209

3

6 7 8

5

145

1

109

293

273

114

72

227

104

85

73

21

192

282

40

113

283

261

277

260

2

 23

70

83

89

144

71

193 190

Yellowstone 

National Park 

Montana

Wyoming

Idaho

Yellowstone 

National Park

Grand Teton 

National Park

44 08'

45 00'

111 00'

o 110 35'

110 00' o

o

o

o

0 5 2.5 7.5 10 MILES

0 5 10 15 20 KILOMETERS

 90–100

 Roads

 Park boundary

 80–90

 70–80

 60–70

Percent probability that alkalinity

 concentration is less than 100 

 microequivalents per liter

EXPLANATION Base from U.S. Geological Survey digital data

Universal Transverse Mercator projection

Zone 12

Figure 10. Probability greater than 60 percent of lake sensitivity in Yellowstone National Park to atmospheric deposition 

using an acid-neutralizing capacity concentration bin of 0–100 microequivalents per liter.

Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition 17
18 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

189

190

193

150

134

170

112

166

191

106

209

101

188

3

132

6 8

5

151

145

1

213

109

293

225

273

116

114

146 139

227

199

104

136

110

117 123

207

21

156

204

217

98

176

192

282

184

153

222

113

283

118

230

261

172

277

185

223

143

130

260

 23

102

137

144

178

221

140 141

154

128 126

127

131

99

79

81

175

291

196

Yellowstone 

National Park 

Montana

Wyoming

Idaho

Yellowstone 

National Park

Grand Teton 

National Park

44 08'

45 00'

111 00' o

110 35' o

110 00' o

o

o

0 5 2.5 7.5 10 MILES

0 5 10 15 20 KILOMETERS

 90–100

 Roads

 Park boundary

 80–90

 70–80

 60–70

Percent probability that alkalinity

 concentration is less than 200 

 microequivalents per liter

EXPLANATION

Base from U.S. Geological Survey digital data

Universal Transverse Mercator projection

Zone 12

Figure 11. Probability greater than 60 percent of lake sensitivity in Yellowstone National Park to atmospheric 

deposition using an acid-neutralizing capacity concentration bin of 0–200 microequivalents per liter.
Summary

The sensitivity of lakes in Grand Teton and Yellowstone 

National Parks to atmospheric deposition of contaminants was 

estimated based on statistical relations between ANC concentrations and basin characteristics. This study combined the use 

of Geographic Information System (GIS) modeling and multivariate logistic regression using the best available GIS and 

water-quality data for alpine/subalpine lakes in Grand Teton 

and Yellowstone National Parks. The result is the identification of a subset of lakes with a high probability of having low 

ANC concentrations and thus greater sensitivity to atmospheric deposition of nitrate, sulfate, and hydrogen ion.

Relations between ANC concentrations and basin characteristics were explored. ANC concentrations that were measured at 52 lakes in Grand Teton and 23 lakes in Yellowstone

during synoptic surveys were used to calibrate the statistical 

models. Basin characteristics were derived from GIS including topography, geology, vegetation, and soils. Multivariate 

logistic regression models were developed, and the resultant 

probability equations for ANC concentrations less than 50, 

100, and 200 microequivalents per liter were applied to lake 

basins greater than 1 hectare in Grand Teton (106 lakes) and 

Yellowstone (294 lakes). A higher percentage of lakes in 

Grand Teton (36 percent) than in Yellowstone (13 percent) 

were predicted to be sensitive to atmospheric deposition. The 

lakes that exceeded 60-percent probability of having an ANC 

concentration less than 100 μeq/L and, therefore, had the 

greatest sensitivity to atmospheric deposition of contaminants, 

are located at elevations greater than 2,790 meters (m) in 

Grand Teton, and greater than 2,590 m in Yellowstone.

The GIS and logistic regression modeling approach can 

be used as a cost-effective tool to help resource managers 

identify lakes likely to be sensitive to atmospheric deposition 

of contaminants and develop long-term monitoring programs 

within the parks.

Selected References

Clow, D.W., Striegl, R., Nanus, L., Mast, M.A., Campbell, 

D.H., and Krabbenhoft, D.P., 2002, Chemistry of selected 

high-elevation lakes in seven National Parks in the Western United States: Water, Air, and Soil Pollution, Focus 2, 

p. 139–164.

Clow, D.W., and Sueker, J.K., 2000, Relations between 

basin characteristics and streamwater chemistry in alpine/

subalpine basins in Rocky Mountain National Park, Colorado: Water Resources Research, v. 36, no. 1, p. 49–61.

Corbin, J.A., 2004, Effects of atmospheric deposition on water 

quality in high alpine lakes of Grand Teton National Park, 

Wyoming: University of Montana, M.S. thesis, 58 p.

Environmental Systems Research Institute (ESRI), 1999, 

Using Grid with Arc/Info, v. 2: U.S.A, ESRI, Inc.

Gulley, D.D., and Parker, M., 1985, A limnological survey 

of 70 small lakes and ponds in Grand Teton National Park: 

University of Wyoming, Department of Zoology and Physiology, 306 p.

Helsel, D.R., and Hirsch, R.M., 1993, Statistical methods 

in water resources: New York, Elsevier, 522 p.

Hooper, R.P., West, C.T., and Peters, N.E., 1990, Assessing the response of Emerald Lake, an alpine watershed 

in Sequoia National Park, California, to acidifcation during snowmelt by using a simple hydrochemical model: 

U.S. Geological Survey Water-Resources Investigations 

Report 90–4000, 68 p.

Hosmer, D.W., and Lemeshow, S., 1989, Applied logistic 

regression: New York, Wiley and Sons, 392 p.

Kanciruk, P., Gentry, M., McCord, R., Hook, L., Eilers, J., 

and Best, M.D., 1987, National surface water survey: 

Western Lake Survey, Phase 1, Data Base Dictionary: 

Oak Ridge, Tennessee, Oak Ridge National Laboratory, 

ORNL/TM–10307, 90 p.

Landers, D.H., Wilers, J.M., Brakke, D.F., Overton, W.S., 

Kellar, P.E., Silverstein, M.E., Schonbrod, R.D., Crewe, 

R.E., Linthurst, R.A., Omernik, J.M., Teague, S.A., 

and Meier, E.P., 1987, Western Lake Survey, Phase 1, 

Characteristics of lakes in the Western United States, 

v.1—Population descriptions and physio-chemical 

relationships: U.S. Environmental Protection Agency 

EPA–600/3–86/054a.

Melack, J.M., Stoddard, J.L., and Ochs, C.A., 1985, Major 

ion chemistry and sensitivity to acid precipitation of Sierra 

Nevada lakes: Water Resources Research, v. 21, no. 1, 

p. 27–32.

Nanus, Leora, Campbell, D.H., Ingersoll, G.P., Clow, D.W., 

and Mast, M.A., 2003, Atmospheric deposition maps for 

the Rocky Mountains: Atmospheric Environment, v. 37, 

p. 4881–4892.

National Park Service, 1988, Bedrock geology of Yellowstone 

National Park, Wyoming, Montana, Idaho: Miscellaneous 

Geologic Investigations, Map 1–711; scale 1:125,000.

National Park Service, 1990, Post 1988 cover types of 

Yellowstone National Park, Wyoming, Montana, Idaho, 

10-m: Boulder, Colorado, Robert Rinehart, Inc. Publishers.

National Park Service, 1992, Geology of Grand Teton 

National Park and surrounding area: Miscellaneous Geologic Investigations, Map 1–2031, scale 1:62,500.

Selected References 19
20 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

National Park Service, 1994a, Soils of Grand Teton National 

Park and Teton County, Wyoming: U.S. Department of 

Agriculture-Soil Conservation Service, scale 1:24,000.

National Park Service, 1994b, Combined habitat and cover 

types for Grand Teton National Park: Grand Teton National 

Park, GIS lab, scale 1:62,500.

National Park Service, 1997, Soils of Yellowstone National 

Park, Wyoming, Montana, Idaho: Yellowstone National 

Park, Center for Resources, scale 1:62,500.

National Park Service, 1999, Precipitation (30-year average) of Yellowstone National Park, Wyoming, Montana, 

Idaho: Yellowstone National Park, Center for Resources, 

scale 1:125,000.

Nishida, A.I., and Schnoor, J.L., 1989, Steady state model to 

determine lake resources at risk to acid deposition in the 

Sierra Nevada, California: California Air Resources Board 

Report, contract A7–32–036, 189 p.

Rutkowski, T., Baron, J., S., Merrill, S., 2001, Assessing 

surface water sensitivity to atmospheric deposition in wilderness areas of Nevada, Idaho, Utah, and Wyoming: U.S. 

Forest Service Report, 46 p.

SAS Institute, 1990, SAS/STAT user’s guide, version 6, 

4th ed.: Cary, North Carolina, 1,686 p.

Silverstein, M.E., Drouse, S.K., Engels, J.L, Faber, M.L., and 

Mitchell-Hall, T.E, 1987, National surface water survey, 

Western Lake Survey (Phase I-Synoptic Chemistry) Quality 

Assurance Plan: Las Vegas, Nevada, U.S. Environmental 

Protection Agency, EPA–600/8–87/026.

Spatial Climate Analysis Service, 2000, Parameter-elevation 

Regressions on Independent Slopes Model (PRISM): 

Oregon State University, http://www.ocs.oregonstate.edu/

prism/.

U.S. Geological Survey, 2000a, EROS data center, National 

Elevation Dataset, 30-meter DEM quadrangle: Reston, 

Virginia.

U.S. Geological Survey, 2000b, EROS data center, Hydrography Dataset, scale 1:24,000: Reston, Virginia.

Woods, S.W., and Corbin, J., 2003a, Vital signs water quality 

monitoring for the Greater Yellowstone Network, Grand 

Teton National Park: NPS Technical Report, 282 p.

Woods, S.W., and Corbin, J., 2003b, Vital signs water quality 

monitoring for the Greater Yellowstone Network, Yellowstone National Park: NPS Technical Report, 32 p.

Zelt, R.B., Boughton, G., Miller, K.A., Mason, J.P., and 

Gianakos, L.M., 1999, Environmental setting of the Yellowstone River basin, Montana, North Dakota, and Wyoming: 

U.S. Geological Survey Water-Resources Investigations 

Report 98–4269, 112 p.
Appendix
Appendix 23

Table 6. Lakes greater than 1 hectare in Grand Teton National Park, including lake-identification number, lake name, latitude, 

longitude, elevation of lake outlet, lake area, and associated probabilities at acid-neutralizing capacity concentration bins of 

0–50, 0–100, and 0–200 microequivalents per liter.

[DD, decimal degrees; Elev, elevation of lake outlet above North American Vertical Datum of 1988; m, meters; ha, hectare; μeq/L, microequivalents per liter; 

%, percent]

Lake number 

(see fig. 3 for 

location)

Lake name Latitude 

(DD)

Longitude 

(DD)

Elev 

(m)

Lake 

area 

(ha)

Probability

0–50 μeq/L 0–100 μeq/L 0–200 μeq/L

1 Amphitheater Lake 43.72 –110.78 2,956 1.87 64.69% 82.06% 91.19%

2 Arrowhead Lake 43.77 –110.75 2,790 0.23 51.95% 13.30% 91.19%

3 Bearpaw Lake 43.82 –110.73 2,088 4.59 12.01% 10.63% 76.17%

4 Bradley Lake 43.71 –110.75 2,141 27.11 27.89% 7.05% 85.95%

5 Christian Pond 43.87 –110.56 2,084 12.66 0.02% 5.16% 25.27%

6 Cirque Lake 43.83 –110.83 2,929 24.93 4.13% 43.72% 91.19%

7 Cow Lake 43.82 –110.56 2,083 6.43 0.02% 11.08% 7.48%

8 Coyote Lake 43.63 –110.87 3,110 1.62 4.81% 93.51% 63.92%

9 Cygnet Pond 43.9 –110.61 2,084 7.59 0.02% 16.91% 7.57%

10 Delta Lake 43.73 –110.77 2,748 2.77 72.59% 62.60% 91.18%

11 Dudley Lake 43.88 –110.78 2,512 3.83 41.86% 6.30% 91.00%

12 Emma Matilda Lake 43.88 –110.53 2,095 359.25 0.02% 1.23% 24.15%

13 Forget Me Not Lakes 43.65 –110.87 2,921 1.62 3.81% 72.66% 91.06%

14 Forget Me Not Lakes 43.65 –110.87 2,964 0.12 74.62% 91.92% 91.19%

15 Forget Me Not Lakes 43.64 –110.87 2,967 0.1 74.62% 41.84% 91.19%

16 Forget Me Not Lakes 43.64 –110.87 2,950 0.37 3.10% 23.91% 84.16%

17 Grizzly Bear Lake 43.8 –110.81 2,810 5.18 4.14% 48.93% 91.19%

18 Halfmoon Lake 43.82 –110.42 2,064 2.12 0.02% 0.66% 7.80%

19 Hechtman Lake 44.04 –110.79 2,394 3.02 44.95% 44.46% 7.27%

20 Hedrick Pond 43.75 –110.59 2,047 6.37 0.02% 11.32% 7.51%

21 Heron Pond 43.88 –110.63 2,065 8.72 0.02% 10.14% 7.70%

22 Holly Lake 43.79 –110.79 2,868 2.89 7.72% 84.00% 91.19%

23 Iceflow Lake 43.72 –110.82 3,247 9.39 20.97% 92.41% 90.87%

24 Indian Lake 43.63 –110.88 2,988 7.38 1.55% 87.54% 51.23%

25 Jenny Lake 43.76 –110.73 2,067 489.58 6.12% 4.89% 67.44%

26 Kelly Warm Spring 43.63 –110.61 2,037 0.26 0.02% 13.93% 7.27%

27 Kit Lake 43.71 –110.83 3,145 1.26 1.19% 95.92% 79.82%

28 Lake of the Crags 43.77 –110.77 2,916 4.47 78.93% 68.58% 91.19%

29 Lake Solitude 43.79 –110.84 2,755 15.08 18.47% 55.89% 90.00%

30 Lake Taminah 43.7 –110.8 2,761 5.46 16.94% 52.80% 88.41%

31 Leigh Lake 43.81 –110.73 2,094 413.49 6.30% 5.13% 67.55%

32 Marion Lake 43.62 –110.92 2,812 2.11 2.64% 83.93% 7.51%

33 Mica Lake 43.78 –110.84 2,913 3.85 7.77% 72.55% 91.19%

34 Mink Lake 43.81 –110.84 2,715 3.83 14.67% 6.56% 72.41%

35 Moose Pond 43.74 –110.74 2,065 0.61 10.92% 17.37% 80.56%

36 Noname-1 44.12 –110.76 2,310 1.13 0.02% 37.49% 7.27%

37 Noname-2 44.09 –110.7 2,100 1.09 0.02% 23.35% 7.27%

38 Noname-3 44.09 –110.68 2,070 4.63 0.02% 5.19% 7.27%

39 Noname-4 44.08 –110.68 2,070 1.88 0.02% 9.58% 7.27%

40 Noname-5 44.07 –110.78 2,459 1.29 0.15% 22.88% 7.27%

41 Noname-6 44.06 –110.71 2,067 1.69 0.11% 76.16% 7.27%

42 Noname-7 44.05 –110.72 2,067 3.28 0.03% 76.16% 7.27%

43 Noname-8 44.01 –110.86 2,581 1.13 0.02% 76.16% 7.27%
24 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

44 Noname-9 43.96 –110.84 2,797 1.15 0.15% 76.16% 31.21%

45 Noname-10 43.93 –110.63 2,072 3.27 0.02% 6.52% 11.57%

46 Noname-11 43.93 –110.62 2,108 10.76 0.02% 19.10% 9.92%

47 Noname-12 43.93 –110.74 2,969 1.26 5.70% 80.67% 87.75%

48 Noname-13 43.92 –110.49 2,231 1.34 0.02% 11.87% 9.05%

49 Noname-14 43.91 –110.76 2,932 4.57 1.78% 73.69% 64.83%

50 Noname-15 43.91 –110.82 2,758 6.21 0.64% 52.35% 87.11%

51 Noname-16 43.91 –110.62 2,097 4.42 0.02% 13.21% 17.62%

52 Noname-17 43.91 –110.56 2,127 1.71 0.09% 11.75% 8.44%

53 Noname-18 43.91 –110.79 3,059 4.25 2.29% 82.96% 83.86%

54 Noname-19 43.91 –110.63 2,084 1.31 0.02% 5.80% 8.14%

55 Noname-20 43.91 –110.83 2,908 3.56 1.07% 56.45% 87.07%

56 Noname-21 43.9 –110.53 2,124 5.9 0.02% 10.09% 7.88%

57 Noname-22 43.9 –110.83 2,967 6.44 2.15% 45.55% 89.28%

58 Noname-23 43.9 –110.81 2,915 2.53 1.34% 46.89% 87.03%

59 Noname-24 43.9 –110.83 3,067 1.38 1.25% 57.20% 91.19%

60 Noname-25 43.89 –110.48 2,104 3.74 0.02% 12.36% 8.56%

61 Noname-26 43.89 –110.79 2,794 2.36 3.88% 61.01% 82.56%

62 Noname-27 43.89 –110.47 2,961 1.41 1.52% 77.85% 88.86%

63 Noname-28 43.89 –110.8 2,988 1.41 3.03% 65.44% 71.06%

64 Noname-29 43.89 –110.48 2,157 1.02 0.02% 25.60% 7.51%

65 Noname-30 43.88 –110.58 2,086 1.93 0.02% 1.23% 7.27%

66 Noname-31 43.87 –110.57 2,085 1.04 0.02% 16.18% 7.27%

67 Noname-32 43.87 –110.84 2,919 3.91 5.69% 89.15% 73.08%

68 Noname-33 43.87 –110.73 2,078 2.35 0.02% 16.41% 9.37%

69 Noname-34 43.87 –110.72 2,072 1.48 0.02% 3.55% 10.63%

70 Noname-35 43.86 –110.81 2,942 1.75 8.08% 74.41% 90.08%

71 Noname-36 43.85 –110.87 2,958 3.86 0.13% 10.51% 89.19%

72 Noname-37 43.84 –110.87 2,988 1.36 2.32% 65.60% 91.19%

73 Noname-38 43.84 –110.71 2,066 15.52 0.02% 4.35% 20.88%

74 Noname-39 43.84 –110.83 2,814 3.19 10.05% 79.79% 90.79%

75 Noname-40 43.83 –110.58 2,120 2.29 0.02% 23.50% 7.27%

76 Noname-41 43.83 –110.82 3,011 1.26 63.42% 93.21% 91.19%

77 Noname-42 43.83 –110.72 2,087 1.85 0.02% 16.69% 9.90%

78 Noname-43 43.82 –110.61 2,098 3.21 0.02% 26.09% 8.08%

79 Noname-44 43.81 –110.78 2,376 2.45 30.98% 19.41% 77.24%

80 Noname-45 43.8 –110.86 2,929 1.19 4.13% 43.72% 91.19%

81 Noname-46 43.8 –110.81 2,097 1.04 26.08% 4.83% 91.19%

82 Noname-47 43.79 –110.83 2,898 1.18 7.99% 56.17% 67.96%

83 Noname-48 43.78 –110.79 2,799 1.26 5.35% 67.67% 90.51%

84 Noname-49 43.78 –110.8 2,967 1.04 4.72% 79.11% 91.19%

85 Noname-50 43.78 –110.62 2,035 1.45 0.02% 11.63% 7.27%

86 Noname-51 43.77 –110.84 3,060 2.28 9.20% 80.11% 91.19%

Table 6. Lakes greater than 1 hectare in Grand Teton National Park, including lake-identification number, lake name, latitude, 

longitude, elevation of lake outlet, lake area, and associated probabilities at acid-neutralizing capacity concentration bins of 

0–50, 0–100, and 0–200 microequivalents per liter.—Continued

[DD, decimal degrees; Elev, elevation of lake outlet above North American Vertical Datum of 1988; m, meters; ha, hectare; μeq/L, microequivalents per liter; 

%, percent]

Lake number 

(see fig. 3 for 

location)

Lake name Latitude 

(DD)

Longitude 

(DD)

Elev 

(m)

Lake 

area 

(ha)

Probability

0–50 μeq/L 0–100 μeq/L 0–200 μeq/L
Appendix 25

87 Noname-52 43.76 –110.84 2,929 2.03 2.35% 75.75% 91.07%

88 Noname-53 43.75 –110.84 2,918 1.59 3.68% 43.64% 87.67%

89 Noname-54 43.71 –110.74 2,143 2.48 0.02% 1.83% 37.08%

90 Noname-55 43.68 –110.82 3,118 1.14 1.27% 93.50% 91.19%

91 Noname-56 43.65 –110.73 1,962 1.14 0.02% 13.67% 7.27%

92 Noname-57 43.63 –110.86 3,066 1.05 20.68% 76.16% 82.05%

93 Phelps Lake 43.64 –110.79 2,023 184.72 5.57% 7.28% 63.02%

94 Ramshead Lake 43.77 –110.76 2,894 1.05 77.97% 68.93% 91.19%

95 Rimrock Lake 43.65 –110.84 3,023 6.46 26.50% 47.22% 80.10%

96 Schoolroom Lake 43.72 –110.84 3,067 0.94 1.23% 44.69% 26.34%

97 Snowdrift Lake 43.7 –110.82 3,051 22.18 2.88% 77.73% 85.41%

98 South Boundary Lake 44.13 –110.75 2,248 6.65 0.02% 1.62% 91.19%

99 String Lake 43.78 –110.73 2,094 29.55 4.51% 5.52% 63.60%

100 Surprise Lake 43.72 –110.77 2,906 0.94 41.78% 85.18% 91.19%

101 Swan Lake 43.88 –110.63 2,062 26.24 0.02% 10.97% 7.78%

102 Taggart Lake 43.7 –110.75 2,104 46.33 31.18% 6.59% 85.34%

103 Talus Lake 43.9 –110.8 2,947 8.52 1.15% 69.18% 86.00%

104 Timberline Lake 43.68 –110.81 3,141 2.03 47.94% 88.39% 91.19%

105 Trapper Lake 43.83 –110.73 2,107 1.36 23.99% 10.18% 77.37%

106 Two Ocean Lake 43.91 –110.53 2,102 238.72 0.02% 7.92% 11.65%

Table 6. Lakes greater than 1 hectare in Grand Teton National Park, including lake-identification number, lake name, latitude, 

longitude, elevation of lake outlet, lake area, and associated probabilities at acid-neutralizing capacity concentration bins of 

0–50, 0–100, and 0–200 microequivalents per liter.—Continued

[DD, decimal degrees; Elev, elevation of lake outlet above North American Vertical Datum of 1988; m, meters; ha, hectare; μeq/L, microequivalents per liter; 

%, percent]

Lake number 

(see fig. 3 for 

location)

Lake name Latitude 

(DD)

Longitude 

(DD)

Elev 

(m)

Lake 

area 

(ha)

Probability

0–50 μeq/L 0–100 μeq/L 0–200 μeq/L
26 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

Table 7. Results of univariate logistic regression analyses for Grand Teton National Park at acid-neutralizing capacity concentration 

bins of 0–50, 0–100, and 0–200 microequivalents per liter and explanatory variable definitions and units. 

[μeq/L, microequivalents per liter; ha, hectare; m2, meters squared; sed., sedimentary rocks; kg/ha/yr, kilograms per hectare per year; N, nitrogen; SO4, sulfate; 

S, sulfur; mm/yr, millimeters per year]

Variable p-value Definition and units 0–50 μeq/L 0–100 μeq/L 0–200 μeq/L

lkarea 0.246 0.12 0.304 Area of lake (ha*10,000 or m2)

lkperim 0.139 0.071 0.107 Perimeter of lake (ha*10,000 or m2)

wsarea 0.219 0.063 0.103 Area of basin area (ha*10,000 or m2)

lk_wsare 0.532 0.965 0.249 Lake area/basin Area

lake_per 0.206 0.604 0.076 Lake area/perimeter of lake

head 0.551 0.33 0.686 Headwater lake yes(1) or no(0)

GC 1 0.153 0.011 0 Fraction of basin that is gneiss, quartzite, schist, or granite

GC 2 0.986 0.986 0.981 Fraction of basin that is andesite, dacite, diorite, or phyllite

GC 3 0.628 0.457 0.318 Fraction of basin that is basalt, gabbro, wacke, argillite, or volcanics

GC 4 0.222 0.019 0.003 Fraction of basin that is amphibolite, hornfels, paragneiss, metamorphics

GC 5 0.756 0.685 0.273 Fraction of basin that is metacarbonate, marine sed., marble, calcium silicate 

and basic intrusive rocks

max_slp 0.475 0.356 0.039 Maximum slope of watershed

mean_slp 0.115 0.085 0.004 Mean slope of basin

min_elev 0.051 0.001 0.005 Lake outlet elevation

max_elev 0.158 0.172 0.008 Maximum elevation of basin

meanelev 0.069 0.008 0.001 Mean elevation of basin

stpslpe 0.076 0.095 0.006 Fraction of slopes greater than 30 degrees

asp45 0.06 0.047 0.944 Fraction of basin with aspect 0–45 degrees

asp4590 0.752 0.888 0.083 Fraction of basin with aspect 45–90 degrees

asp90135 0.792 0.778 0.381 Fraction of basin with aspect 90–135 degrees

asp135180 0.287 0.641 0.56 Fraction of basin with aspect 135–180 degrees

asp180225 0.848 0.238 0.813 Fraction of basin with aspect 180–225 degrees

asp225270 0.343 0.62 0.229 Fraction of basin with aspects of 225–270 degrees

asp270315 0.614 0.254 0.844 Fraction of basin with aspect 270–315 degrees

asp315360 0.297 0.375 0.277 Fraction of basin with aspect 315–360 degrees

med_veg 0.496 0.013 0.008 Fraction of basin that is forest or tundra 

low_veg 0.821 0.067 0.149 Fraction of basin that is subalpine meadow

high_veg 0.687 0.132 0.031 Fraction of basin that is agriculture or unvegetated (snow, rock, ice, water)

mean_n 0.75 0.30 0.03 Mean annual inorganic N deposition in basin (kg/ha/yr inorganic N)

mean_so4 0.497 0.158 0.028 Mean annual sulfate deposition in basin (kg/ha/yr SO4-S)

mean_h 0.876 0.491 0.047 Mean annual hydrogen ion deposition in basin (kg/ha/yr H+)

mean_ppt 0.371 0.049 0.003 Mean annual precipitation of basin (mm/yr)

soil_1 0.697 0.027 0.006 Fraction of basin that is rock outcrop/rubble land/water

soil_2 0.951 0.927 0.925 Fraction of basin that is of gravelly loam

soil_3 0.916 0.912 0.903 Fraction of basin that is loam other than gravelly loam

soil_5 0.973 0.959 0.959 Fraction of basin that is Buffork-Adel Association

soil_6 0.969 0.954 0.961 Fraction of basin that is Buffork-Tongue_River-Clayburn 

soil_7 0.879 0.875 0.203 Fraction of basin that is Cryaquolis-Cryofibrists-Comp.

soil_9 0.06 0.374 0.189 Fraction of basin that is Leighton-Moran_Wolcott_association

soil_10 0.97 0.97 0.957 Fraction of basin that is Perceton-Bufork_association

soil_12 0.649 0.121 0.059 Fraction of basin that is Taglake_Sebud association

soil_14 0.986 0.986 0.981 Fraction of basin that is Tineman Association

soil_15 0.967 0.948 0.958 Fraction of basin that is Youga_tineman Association

soil_16 0.986 0.986 0.981 Fraction of basin that is Uhl_rockman Association

soil_17 0.958 0.937 0.157 Fraction of basin that is Unknown Soils
Appendix 27

Table 8. Results of univariate logistic regression analyses for Yellowstone National Park at acid-neutralizing capacity concentration 

bins of 0–100 and 0–200 microequivalents per liter and explanatory variable definitions and units.

[μeq/L, microequivalents per liter; ha, hectare; m2, meters squared; kg/ha/yr, kilograms per hectare per year; N, nitrogen, SO4, sulfate, S, sulfur, mm/yr, millimeters

per year]

Variable p-value Definition and units 0–100 μeq/L 0–200 μeq/L

lkarea 0.867 0.589 Area of lake (ha*10,000 or m2)

lkperim 0.637 0.423 Perimeter of lake (ha*10,000 or m2)

wsarea 0.394 0.322 Area of basin area (ha*10,000 or m2)

lk_wsare 0.695 0.132 Lake area/basin area

lake_per 0.911 0.611 Lake area/perimeter of lake

head 0.950 0.187 Headwater lake yes(1) or no(0)

GC 1 0.708 0.580 Fraction of basin that is gneiss, quartzite, schist, or granite

GC 2 0.649 0.479 Fraction of basin that is andesite, dacite, diorite, or phyllite

GC 3 0.456 0.072 Fraction of basin that is basalt, gabbro, wacke, argillite, or volcanics

GC 4 0.377 0.305 Fraction of basin that is amphibolite, hornfels, paragneiss, or metamorphics

GC 6 0.922 0.914 Fraction of basin that is unknown buffering capacity of bedrock

mx_slp 0.061 0.156 Maximum slope of watershed

mean_slp 0.309 0.619 Mean slope of basin

min_elev 0.052 0.134 Lake outlet elevation

max_elev 0.515 0.689 Maximum elevation of basin

meanelev 0.093 0.368 Mean elevation of basin

stpslpe 0.279 0.520 Fraction of slopes greater than 30 degrees

asp45 0.445 0.680 Fraction of basin with aspect 0–45 degrees

asp4590 0.432 0.551 Fraction of basin with aspect 45–90 degrees

asp90135 0.497 0.817 Fraction of basin with aspect 90–135 degrees

asp135180 0.967 0.574 Fraction of basin with aspect 135–180 degrees

asp180225 0.297 0.247 Fraction of basin with aspect 180–225 degrees

asp225270 0.202 0.172 Fraction of basin with aspects of 225–270 degrees

asp270315 0.877 0.394 Fraction of basin with aspect 270–315 degrees

asp315360 0.495 0.167 Fraction of basin with aspect 315–360 degrees

med_veg 0.507 0.461 Fraction of basin that is forest or tundra 

low_veg 0.620 0.255 Fraction of basin that is subalpine meadow

high_veg 0.872 0.855 Fraction of basin that is agriculture or unvegetated (snow, rock, water)

mean_no3 0.950 0.267 Mean annual inorganic N deposition in basin (kg/ha/yr inorganic N)

mean_so4 0.882 0.959 Mean annual sulfate deposition in basin (kg/ha/yr SO4-S)

mean_h 0.953 0.485 Mean annual acid deposition in basin (kg/ha/yr H+)

mean_ppt 0.661 0.843 Mean annual precipitation of basin (mm/yr)

soil_1 0.278 0.074 Fraction of basin that is inceptisols

soil_2 0.684 0.176 Fraction of basin that is mollisols

soil_3 0.688 0.533 Fraction of basin that is thermal

soil_4 0.587 0.361 Fraction of basin that is bedrock

soil_5 0.878 0.810 Fraction of basin that is water
28 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

Table 9. Results of multivariate logistic regression analyses for Grand Teton National Park.

(A) Acid-neutralizing capacity (ANC) concentration bin of 0–50 microequivalents per liter (μeq/L).

[μeq/L, microequivalents per liter; (n), total number of lakes; (1), lakes in ANC bin 0–50 μeq/L; (0), lakes with ANC > 50 μeq/L; soil_9, fraction that is leightonmoran_wolcott_association; stpslpe, fraction of slopes > 30 degrees]

Logit (P) = e

�–8.624 9.702 soil_9 + � � + 13.761 stpslpe � ��

1 e�–8.624 9.702 soil_9 + � � + 13.761 stpslpe � �� +

---------------------------------------------------------------------------------------------------------

(B) Acid-neutralizing capacity (ANC) concentration bin of 0–100 microequivalents per liter.

[μeq/L, microequivalents per liter; (n), total number of lakes; (1), lakes in ANC bin 0–100 μeq/L; (0), lakes with ANC > 100 μeq/L; min_elev; lake outlet 

elevation; asp45, fraction of basin with aspect 0–45 degrees]

Logit (P) = e

�–9.455 0.004 min_elev + � � – 8.318 asp45 � ��

1 e�–9.455 0.004 min_elev + � � – 8.318 asp45 � �� +

----------------------------------------------------------------------------------------------------------

variable (1) (0) (n)

Likelihood ratio 

p-value

score 

p-value 

parameter 

estimate

standard 

error

wald 

chi-square p-value Somers’ D c statistic

intercept –9.455 3.041 9.665 0.0019

min_elev 23 29 52 <0.0001 <0.0001 0.004 0.001 12.136 0.0005 0.76 0.88

asp45 –8.318 3.766 4.878 0.0272

variable (1) (0) (n)

Likelihood ratio 

p-value

score 

p-value

parameter 

estimate

standard 

error

wald 

chi-square p-value Somers’ D c statistic

intercept –8.624 2.871 9.022 0.0027

soil_9 9 43 52 0.0001 0.0018 9.702 3.320 8.538 0.0035 0.80 0.90

stpslpe 13.761 5.158 7.116 0.0276

Goodness-of-Fit y = 0.6706x + 0.3306

R2 = 0.66

0

0.5

1

1.5

2

2.5

3

3.5

4

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5

Measured ANC Concentrations Less Than 50 microequivalents per liter

Predicted A

N

C

Concentrations

Less Than 50 microequivalents

per liter

Goodness-of-Fit y = 0.6074x + 0.7635

R2 = 0.61

0

0.5

1

1.5

2

2.5

3

3.5

4

0 1 2 3 4 5

Measured ANC Concentrations Less Than 100 microequivalents per liter

Predicted A

N

C

Concentrations

Less Than 100 microequivalents

per liter
Appendix 29

Table 9. Results of multivariate logistic regression analyses for Grand Teton National Park.—Continued

(C) Acid-neutralizing capacity concentration (ANC) bin of 0–200 microequivalents per liter. 

[μeq/L, microequivalents per liter; (n), total number of lakes; (1), lakes in ANC bin 0–200 μeq/L; (0), lakes with ANC > 200 μeq/L; GC 1, fraction of basin that 

is gneiss, quartzite, schist, or granite]

Logit (P) = e

�–2.546 4.883 GC 1 + � ��

1 e�–2.546 4.883 GC 1 + � �� +

----------------------------------------------------------------

variable (1) (0) (n)

Likelihood ratio 

p-value

score 

p-value

parameter 

estimate

standard 

error

wald 

chi-square p-value Somers’ D c statistic

intercept 37 15 52 <0.0001 <0.0001 –2.546 1.054 5.834

GC 1 4.883 1.344 13.189 0.0003 0.73 0.86

Goodness-of-Fit y = 0.9568x + 0.2009

R2 = 0.99

0

2

4

6

8

10

12

14

16

18

0 2 4 6 8 10 12 14 16 18

Measured ANC Concentrations Less Than 200 microequivalents per liter

Predicted A

N

C

Concentrations

Less Than 200 microequivalents

per liter
30 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

Table 10. Lakes greater than 1 hectare in Yellowstone National Park, including lake-identification number, lake name, latitude, 

longitude, elevation of lake outlet, lake area, and associated probabilities at acid-neutralizing capacity concentration bins of 

0–100 and 0–200 microequivalents per liter.

[DD, decimal degrees; Elev, elevation of lake outlet above North American Vertical Datum of 1988; m, meters; ha, hectare; μeq/L, microequivalents per liter; 

%, percent]

Lake 

number 

(see fig. 4 

for location)

Lake name Latitude 

(DD)

Longitude 

(DD)

Elev 

(m)

Lake area 

(ha)

Probability

0–100 μeq/L 0–200 μeq/L

1 Noname-1 45.09 –111.01 2,785 2.04 96.89% 95.95%

2 Sedge Lake 45.06 –110.98 2,699 1.42 88.94% 53.52%

3 Noname-2 45.05 –111.00 2,627 3.76 72.39% 72.40%

4 Crescent Lake 45.06 –110.99 2,614 5.96 68.21% 30.26%

5 Unnamed lake 45.05 –110.97 2,676 2.57 84.84% 73.48%

6 High Lake 45.05 –110.93 2,674 3.16 84.47% 92.84%

7 Unnamed lake 45.04 –111.00 2,655 2.68 80.34% 53.42%

8 Unnamed lake 45.04 –110.97 2,591 2.66 60.01% 69.78%

9 Noname-3 45.03 –110.75 1,662 1.03 0.00% 0.30%

10 Rainbow Lake 45.02 –110.74 1,792 1.86 0.00% 0.92%

11 Sportsman Lake 45.01 –110.9 2,349 1.89 3.26% 9.42%

12 Noname-4 45.01 –110.74 1,960 1.23 0.01% 1.67%

13 Slide Lake 45.00 –110.69 1,737 2.57 0.00% 0.60%

14 Crevice Lake 45.00 –110.57 1,687 7.57 0.00% 0.29%

15 Big Beaver Pond 44.99 –110.71 1,938 1.45 0.01% 2.51%

16 Cache Lake 44.98 –110.8.0 2,450 5.21 14.09% 15.20%

17 Noname-5 44.97 –110.72 2,255 1.17 0.77% 7.12%

18 Noname-6 44.97 –110.26 2,219 1.04 0.44% 4.92%

19 Noname-7 44.97 –110.64 2,284 1.49 1.20% 6.83%

20 Geode Lake 44.97 –110.48 1,823 4.4.0 0.00% 3.41%

21 Noname-8 44.97 –110.14 2,838 1.52 98.61% 96.91%

22 Unnamed pond 44.97 –110.45 1,797 1.24 0.00% 0.55%

23 Noname-9 44.97 –110.14 2,839 1.11 98.64% 96.94%

24 Unnamed pond 44.97 –110.46 1,773 2.22 0.00% 0.47%

25 Noname-10 44.97 –110.62 2,219 1.99 0.44% 4.92%

26 Unnamed pond 44.97 –110.45 1,779 1.2 0.00% 0.48%

27 Noname-11 44.96 –110.5.0 1,991 1.07 0.01% 5.68%

28 McBride Lake 44.96 –110.25 2,007 10.92 0.02% 1.62%

29 Unnamed pond 44.96 –110.41 2,013 3.99 0.02% 1.68%

30 Noname-12 44.96 –110.62 2,210 8.36 0.38% 9.00%

31 Noname-13 44.96 –111.03 2,225 1.64 0.48% 5.68%

32 Noname-14 44.95 –110.6 2,011 1.61 0.02% 3.88%

33 Fawn Lake 44.95 –110.79 2,373 1.34 4.66% 10.57%

34 Unnamed reservoir 44.94 –110.7 2,015 1.11 0.02% 1.86%

35 Floating Island Lake 44.94 –110.45 2,010 2.28 0.02% 2.23%

36 Unnamed pond 44.93 –111.01 2,331 2.03 2.47% 10.91%

37 Noname-15 44.93 –110.99 2,335 1.35 2.66% 17.52%

38 Junction Lake 44.93 –110.38 1,904 3.84 0.00% 1.55%

39 Unnamed pond 44.93 –110.31 1,889 1.25 0.00% 0.93%

40 Small Lake 44.92 –110.9 2,765 1.02 95.79% 49.42%

41 Unnamed pond 44.92 –110.35 1,886 2.73 0.00% 0.86%

42 Noname-16 44.92 –110.76 2,325 2.11 2.26% 8.37%
Appendix 31

43 Unnamed pond 44.92 –110.35 1,886 1.92 0.00% 0.86%

44 Noname-17 44.92 –110.28 2,102 1.38 0.07% 2.68%

45 Noname-18 44.92 –110.78 2,321 1.09 2.12% 8.21%

46 Noname-19 44.92 –110.72 2,227 2.22 0.50% 5.17%

47 Noname-20 44.92 –110.76 2,320 3.97 2.11% 8.18%

48 Swan Lake 44.91 –110.73 2,215 15.49 0.42% 4.83%

49 Hals Lake 44.91 –110.79 2,335 1.52 2.66% 8.82%

50 Ruddy Duck Pond 44.91 –110.37 2,199 3.73 0.32% 4.44%

51 Trumpter Lake 44.91 –110.36 1,862 9.01 0.00% 1.29%

52 Unnamed pond 44.91 –110.71 2,219 2.44 0.44% 4.91%

53 Unnamed pond 44.91 –110.68 2,190 2.73 0.28% 4.24%

54 Unnamed pond 44.91 –110.7 2,211 2.77 0.39% 4.73%

55 Unnamed pond 44.91 –110.67 2,199 2.65 0.32% 4.44%

56 Noname-21 44.91 –110.34 1,885 2.57 0.00% 0.85%

57 Unnamed pond 44.91 –110.38 1,893 1.66 0.00% 1.04%

58 Noname-22 44.91 –110.73 2,217 1.06 0.42% 4.86%

59 Noname-23 44.91 –110.76 2,301 1.09 1.57% 7.45%

60 Divide Lake 44.91 –111.05 2,201 3.54 0.33% 7.57%

61 Lost Lake 44.9 –110.43 2,046 2.95 0.03% 3.95%

62 Buck Lake 44.9 –110.12 2,113 2.36 0.08% 2.84%

63 Noname-24 44.9 –110.28 2,067 5.25 0.04% 2.23%

64 Noname-25 44.9 –110.29 2,074 3.41 0.05% 2.31%

65 Trout Lake 44.9 –110.12 2,119 5.25 0.09% 7.34%

66 Noname-26 44.89 –110.29 2,077 5.88 0.05% 8.09%

67 Noname-27 44.89 –110.77 2,303 1.18 1.62% 7.52%

68 Unnamed lake 44.87 –110.16 2,029 1.52 0.02% 2.66%

69 Unnamed lake 44.87 –110.85 2,567 1.67 50.73% 25.21%

70 Unnamed lake 44.87 –110.92 2,750 1.91 94.74% 47.41%

71 Unnamed lake 44.87 –110.86 2,592 1.29 60.35% 27.83%

72 Unnamed lake 44.86 –110.91 2,790 2.54 97.09% 52.70%

73 Noname-28 44.86 –110.86 2,688 1.76 87.19% 39.22%

74 Gallatin Lake 44.85 –110.88 2,688 9.92 87.24% 39.26%

75 Noname-29 44.84 –110.37 2,243 1.32 0.64% 7.15%

76 Noname-30 44.84 –110.92 2,309 1.66 1.77% 8.32%

77 Ace of Hearts Lake 44.84 –110.65 2,464 2.41 17.03% 43.47%

78 Obsidian Lake 44.83 –110.71 2,356 7.56 3.64% 49.60%

79 Noname-31 44.83 –110.66 2,468 2.16 17.86% 68.99%

80 Unnamed lake 44.83 –110.76 2,270 2.32 0.97% 27.84%

81 Noname-32 44.83 –110.67 2,473 1.17 19.08% 63.60%

82 Noname-33 44.82 –110.68 2,391 2.07 6.13% 30.05%

83 Middle Trilobite Lake 44.82 –110.84 2,674 2.97 84.53% 37.44%

84 Trilobite Lake 44.82 –110.83 2,544 4.04 41.85% 22.96%

Table 10. Lakes greater than 1 hectare in Yellowstone National Park, including lake-identification number, lake name, latitude, 

longitude, elevation of lake outlet, lake area, and associated probabilities at acid-neutralizing capacity concentration bins of 

0–100 and 0–200 microequivalents per liter.—Continued

[DD, decimal degrees; Elev, elevation of lake outlet above North American Vertical Datum of 1988; m, meters; ha, hectare; μeq/L, microequivalents per liter; 

%, percent]

Lake 

number 

(see fig. 4 

for location)

Lake name Latitude 

(DD)

Longitude 

(DD)

Elev 

(m)

Lake area 

(ha)

Probability

0–100 μeq/L 0–200 μeq/L
32 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

85 Echo Lake 44.82 –110.87 2,699 1.77 89.04% 40.67%

86 Noname-34 44.82 –110.8 2,384 1.44 5.48% 11.14%

87 Noname-35 44.81 –110.72 2,250 1.01 0.71% 19.34%

88 Beaver Lake 44.81 –110.73 2,251 9.65 0.72% 19.21%

89 Rosa Lake 44.81 –110.87 2,748 1.03 94.60% 47.17%

90 Grizzly Lake 44.8 –110.77 2,288 60.03 1.29% 30.31%

91 Noname-36 44.8 –110.76 2,401 1.99 7.04% 12.08%

92 Lake of the Woods 44.8 –110.71 2,362 11.06 3.97% 59.72%

93 Noname-37 44.77 –110.85 2,533 1.76 37.52% 21.88%

94 North Twin Lake 44.77 –110.73 2,301 4.3 1.57% 33.34%

95 South Twin Lake 44.77 –110.73 2,295 7.05 1.43% 36.64%

96 Noname-38 44.76 –111.07 2,008 1.1 0.02% 2.18%

97 Unnamed lake 44.76 –111.05 2,010 2.4 0.02% 2.39%

98 Noname-39 44.76 –110.77 2,418 1.23 9.00% 71.77%

99 Noname-40 44.75 –110.76 2,413 1.14 8.47% 76.21%

100 Grebe Lake 44.75 –110.55 2,445 53.13 13.25% 56.32%

101 Cascade Lake 44.75 –110.52 2,435 12.09 11.54% 69.65%

102 Noname-41 44.75 –110.69 2,341 2.46 2.92% 68.50%

103 Nymph Lake 44.75 –110.72 2,283 5.41 1.19% 39.67%

104 Noname-42 44.74 –110.18 2,711 3.05 90.68% 94.07%

105 Noname-43 44.74 –110.71 2,285 1.14 1.22% 43.82%

106 Wolf Lake 44.74 –110.58 2,438 13.59 11.99% 70.93%

107 Noname-44 44.74 –110.7 2,288 6.63 1.27% 52.29%

108 Noname-45 44.74 –110.23 2,543 1.65 41.16% 45.80%

109 Mirror Lake 44.73 –110.16 2,727 5.77 92.58% 92.53%

110 Ribbon Lake 44.72 –110.44 2,382 2.79 5.34% 67.71%

111 Wapiti Lake 44.71 –110.25 2,569 5.65 51.20% 35.68%

112 Ice Lake 44.72 –110.62 2,405 25.35 7.46% 60.47%

113 Noname-46 44.71 –110.15 2,638 1.27 75.69% 91.47%

114 Unnamed lake 44.71 –110.36 2,594 4.39 61.15% 89.46%

115 Clear Lake 44.71 –110.47 2,382 1.05 5.34% 29.41%

116 Unnamed lake 44.71 –110.77 2,299 4.68 1.53% 63.43%

117 Solfatara Lake 44.69 –110.58 2,503 2.41 27.24% 74.17%

118 Noname-47 44.68 –110.69 2,553 1.2 45.25% 87.18%

119 Wrangler Lake 44.68 –110.43 2,393 13.99 6.27% 21.32%

120 Wapiti Lake 44.67 –110.27 2,505 39.1 28.01% 19.43%

121 Noname-48 44.67 –110.23 2,528 2.64 35.64% 23.76%

122 Turn Lakes 44.66 –110.26 2,505 31.65 28.01% 22.39%

123 Noname-49 44.67 –110.36 2,489 2.68 23.29% 82.81%

124 Noname-50 44.67 –110.48 2,340 7.26 2.86% 34.18%

125 Noname-51 44.67 –110.47 2,344 1.44 3.04% 20.20%

126 Cygnet Lake #1 44.66 –110.61 2,527 2.4 35.42% 77.91%

Table 10. Lakes greater than 1 hectare in Yellowstone National Park, including lake-identification number, lake name, latitude, 

longitude, elevation of lake outlet, lake area, and associated probabilities at acid-neutralizing capacity concentration bins of 

0–100 and 0–200 microequivalents per liter.—Continued

[DD, decimal degrees; Elev, elevation of lake outlet above North American Vertical Datum of 1988; m, meters; ha, hectare; μeq/L, microequivalents per liter; 

%, percent]

Lake 

number 

(see fig. 4 

for location)

Lake name Latitude 

(DD)

Longitude 

(DD)

Elev 

(m)

Lake area 

(ha)

Probability

0–100 μeq/L 0–200 μeq/L
Appendix 33

127 Cygnet Lake #2 44.66 –110.61 2,527 1.95 35.42% 77.47%

128 Cygnet Lake #3 44.66 –110.61 2,527 2.83 35.42% 77.87%

129 West Tern Lake 44.66 –110.27 2,505 13.44 28.01% 19.43%

130 Noname-52 44.66 –110.58 2,536 1.03 38.64% 86.10%

131 Cygnet Lake #4 44.66 –110.61 2,527 2.17 35.42% 79.51%

132 Cygnet Lake #5 44.66 –110.61 2,527 10.64 35.53% 80.00%

133 Unnamed lake 44.65 –110.27 2,512 2.92 30.07% 19.98%

134 White Lake 44.65 –110.27 2,509 67.59 29.08% 63.25%

135 Noname-53 44.65 –110.26 2,518 1.39 32.11% 20.51%

136 Unnamed pond 44.65 –110.39 2,490 3.04 23.37% 61.35%

137 Unnamed pond 44.64 –110.37 2,529 1.18 36.08% 65.22%

138 Harlequin Lake 44.64 –110.89 2,094 4.29 0.06% 16.91%

139 Noname-54 44.64 –110.5 2,394 3.56 6.41% 68.52%

140 Unnamed pond 44.64 –110.37 2,539 1.91 39.78% 86.29%

141 Unnamed pond 44.64 –110.37 2,542 1.87 40.81% 86.46%

142 Noname-55 44.63 –110.92 2,076 1.24 0.05% 29.61%

143 Noname-56 44.63 –110.27 2,551 1.06 44.43% 82.39%

144 Unnamed lake 44.62 –110.05 2,749 4.45 94.64% 95.12%

145 Frost Lake 44.61 –110.03 2,897 6.29 99.45% 97.74%

146 Noname-57 44.62 –110.73 2,358 3.8 3.74% 70.38%

147 Noname-58 44.61 –110.44 2,394 1.14 6.41% 11.72%

148 Noname-59 44.61 –110.43 2,399 1 6.86% 11.98%

149 Noname-60 44.61 –110.43 2,393 6.57 6.27% 11.64%

150 Noname-61 44.61 –110.73 2,301 2.7 1.57% 63.66%

151 Mary Lake 44.6 –110.63 2,510 7.34 29.57% 74.98%

152 Unnamed pond 44.59 –110.69 2,228 1.84 0.51% 24.09%

153 Noname-62 44.58 –110.62 2,530 1.4 36.30% 77.36%

154 Noname-63 44.58 –110.64 2,522 1.03 33.48% 82.31%

155 Noname-64 44.57 –110.81 2,200 1.29 0.33% 50.44%

156 Noname-65 44.57 –110.77 2,281 2.28 1.16% 61.16%

158 Noname-66 44.56 –110.38 2,357 1.52 3.71% 9.82%

159 Noname-67 44.56 –110.82 2,199 1.17 0.32% 4.44%

160 Indian Pond 44.55 –110.32 2,364 10.84 4.12% 33.78%

161 Big Bear Lake 44.55 –111.01 2,437 1.28 11.74% 49.15%

162 Noname-68 44.55 –110.35 2,358 12.08 3.72% 9.83%

163 Big Bear Lake 44.55 –111.01 2,438 1.58 11.94% 50.53%

164 Turbid Lake 44.54 –110.25 2,388 63.7 5.86% 48.40%

165 Beach Springs Lake 44.55 –110.29 2,358 15.72 3.74% 57.44%

166 Dryad Lake 44.54 –110.51 2,530 15.49 36.52% 81.47%

167 Unnamed lake 44.54 –110.83 2,202 1.76 0.34% 4.50%

168 Feather Lake 44.54 –110.83 2,201 6.67 0.33% 4.48%

169 Hot Lake 44.54 –110.78 2,244 1.64 0.65% 56.23%

Table 10. Lakes greater than 1 hectare in Yellowstone National Park, including lake-identification number, lake name, latitude, 

longitude, elevation of lake outlet, lake area, and associated probabilities at acid-neutralizing capacity concentration bins of 

0–100 and 0–200 microequivalents per liter.—Continued

[DD, decimal degrees; Elev, elevation of lake outlet above North American Vertical Datum of 1988; m, meters; ha, hectare; μeq/L, microequivalents per liter; 

%, percent]

Lake 

number 

(see fig. 4 

for location)

Lake name Latitude 

(DD)

Longitude 

(DD)

Elev 

(m)

Lake area 

(ha)

Probability

0–100 μeq/L 0–200 μeq/L
34 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

170 Beach Lake 44.54 –110.57 2,483 37.05 21.55% 76.57%

171 Goose Lake 44.54 –110.84 2,201 14.28 0.33% 25.11%

172 Noname-69 44.53 –110.64 2,538 1.13 39.55% 86.25%

173 Unnamed lake 44.53 –110.83 2,197 2.31 0.31% 4.40%

174 Lower Basin Lake 44.53 –110.82 2,587 3.5 58.28% 27.24%

175 Crater Lake #4 44.53 –110.87 2,286 1.4 1.24% 61.70%

176 Unnamed lake 44.53 –110.87 2,283 1.83 1.19% 61.35%

177 Bridge Bay 44.53 –110.43 2,357 10.33 3.67% 10.55%

178 Noname-70 44.52 –110.57 2,483 2.34 21.55% 70.90%

179 Noname-71 44.52 –110.58 2,489 2.47 23.12% 41.54%

182 Gooseneck Lake 44.51 –110.84 2,234 2.29 0.55% 54.89%

184 Noname-72 44.49 –110.22 2,558 1.61 47.03% 87.45%

185 Noname-73 44.5 –110.79 2,444 1.1 12.98% 79.05%

186 Noname-74 44.49 –110.42 2,393 2.96 6.27% 11.64%

187 Noname-75 44.49 –110.42 2,376 1.4 4.90% 10.74%

188 Sylvan Lake 44.47 –110.16 2,564 11.79 49.41% 67.70%

189 Delacy Lake (West) 44.47 –110.71 2,593 13.23 60.69% 86.41%

190 Delacy Lake (East) 44.47 –110.7 2,593 10.2 60.69% 86.68%

191 Mallard Lake 44.47 –110.77 2,454 13.95 14.80% 77.29%

192 Noname-76 44.47 –110.67 2,605 1.77 64.82% 89.96%

193 Unnamed pond 44.47 –110.72 2,614 2.76 68.01% 90.39%

194 Noname-77 44.47 –110.61 2,538 5.86 39.32% 22.33%

196 Noname-78 44.47 –110.72 2,571 1.2 52.04% 88.19%

197 Chickadee Lake 44.46 –110.61 2,534 10.13 38.08% 22.02%

198 Unnamed lake 44.46 –110.61 2,547 1.56 42.67% 23.16%

199 Teal Lake 44.46 –110.75 2,568 3.19 50.96% 86.48%

200 Nuthatch Lake 44.45 –110.61 2,547 5.36 42.67% 23.16%

202 Noname-79 44.45 –110.62 2,553 1.03 45.25% 23.81%

204 Noname-80 44.43 –110.74 2,413 2.09 8.44% 72.32%

206 Noname-81 44.42 –110.45 2,357 3.91 3.67% 9.79%

207 Scaup Lake 44.43 –110.76 2,411 2.37 8.18% 72.27%

208 Noname-82 44.42 –110.57 2,373 14.66 4.72% 59.29%

209 Summit Lake 44.41 –110.94 2,605 12.33 64.82% 87.07%

210 Shoshone Lake 44.37 –110.69 2,374 2860.28 4.79% 52.06%

211 Delusion Lake 44.39 –110.45 2,383 229.83 5.46% 11.43%

212 Noname-83 44.4 –110.5 2,354 2.28 3.52% 14.15%

213 Pocket Lake 44.39 –110.74 2,486 5.85 22.28% 82.53%

214 Noname-84 44.39 –110.25 2,355 1.57 3.56% 9.69%

215 Noname-85 44.38 –110.45 2,388 2.15 5.86% 11.39%

216 Hidden Lake 44.38 –110.45 2,388 23.77 5.86% 11.39%

217 Noname-86 44.38 –111.04 2,544 1.96 41.85% 86.64%

218 Noname-87 44.37 –110.47 2,393 1.11 6.27% 11.64%

Table 10 Lakes greater than 1 hectare in Yellowstone National Park, including lake-identification number, lake name, latitude, 

longitude, elevation of lake outlet, lake area, and associated probabilities at acid-neutralizing capacity concentration bins of 

0–100 and 0–200 microequivalents per liter.—Continued

[DD, decimal degrees; Elev, elevation of lake outlet above North American Vertical Datum of 1988; m, meters; ha, hectare; μeq/L, microequivalents per liter; 

%, percent]

Lake 

number 

(see fig. 4 

for location)

Lake name Latitude 

(DD)

Longitude 

(DD)

Elev 

(m)

Lake area 

(ha)

Probability

0–100 μeq/L 0–200 μeq/L
Appendix 35

219 Unnamed lake 44.37 –110.48 2,401 5.39 7.04% 12.08%

220 Unnamed lake 44.37 –110.45 2,386 11.94 5.66% 11.25%

221 Noname-88 44.37 –111.03 2,548 1.22 43.14% 86.84%

222 Noname-89 44.37 –111.06 2,396 1.31 6.56% 71.01%

223 Noname-90 44.36 –110.52 2,429 1.07 10.56% 77.69%

224 Riddle Lake 44.35 –110.54 2,412 72.18 8.25% 15.62%

225 Noname-91 44.35 –110.68 2,374 5.54 4.79% 65.58%

226 Noname-92 44.35 –110.55 2,412 1.09 8.36% 12.78%

227 Glade Lake 44.34 –110.08 2,942 3.23 99.72% 94.76%

228 Madison Lake 44.34 –110.86 2,502 1.68 27.15% 53.60%

229 Alder Lake 44.33 –110.31 2,360 48.66 3.84% 14.07%

230 Noname-93 44.33 –110.76 2,375 1.18 4.81% 69.55%

231 Buffalo Lake 44.32 –111.07 2,342 5.15 2.96% 52.48%

232 Noname-94 44.32 –110.2 2,359 1.23 3.81% 9.91%

233 Noname-95 44.32 –110.29 2,373 4.39 4.72% 20.82%

234 Lewis Lake 44.3 –110.62 2,371 1122.15 4.55% 46.42%

236 Noname-96 44.31 –110.61 2,371 7.92 4.55% 31.21%

237 Noname-97 44.31 –110.2 2,359 7.62 3.77% 9.88%

240 Noname-98 44.31 –110.19 2,359 1.76 3.77% 9.88%

241 Noname-99 44.31 –110.21 2,358 1.39 3.74% 9.85%

242 Noname-100 44.3 –110.19 2,359 5.36 3.77% 9.88%

243 Noname-101 44.3 –110.19 2,359 9.29 3.77% 25.86%

244 Noname-102 44.3 –110.21 2,358 8.91 3.72% 9.83%

245 Noname-103 44.3 –110.16 2,362 1.12 3.99% 12.33%

246 Unnamed lake 44.3 –110.37 2,458 1.85 15.73% 41.46%

247 Noname-104 44.3 –110.16 2,363 1.05 4.01% 39.88%

248 Noname-105 44.3 –110.2 2,358 7.31 3.72% 28.21%

249 Noname-106 44.29 –110.18 2,359 3.42 3.77% 9.88%

250 Aster Lake 44.3 –110.55 2,489 5.94 23.12% 18.08%

251 Noname-107 44.29 –110.24 2,368 1.08 4.37% 43.75%

252 Noname-108 44.29 –110.24 2,385 1.03 5.61% 51.75%

253 Noname-109 44.29 –110.16 2,359 2.45 3.77% 9.88%

255 Noname-110 44.29 –110.16 2,363 3.62 4.04% 10.10%

257 Heart Lake 44.27 –110.48 2,272 884.68 1.00% 19.93%

258 Trail Lake 44.27 –110.17 2,363 35.19 4.01% 37.77%

259 Outlet Lake 44.27 –110.39 2,371 5.81 4.53% 19.94%

260 Noname-111 44.25 –110.22 2,702 1.01 89.49% 82.47%

261 Noname-112 44.25 –110.83 2,670 1.14 83.77% 92.73%

263 Noname-113 44.24 –110.97 2,133 1.61 0.11% 41.43%

264 Noname-114 44.23 –110.96 2,143 1.54 0.13% 42.74%

265 Little Robinson Lake 44.23 –111.03 1,978 3.83 0.01% 4.40%

266 Lake Wyodaho 44.23 –110.98 2,067 5.34 0.04% 33.20%

Table 10. Lakes greater than 1 hectare in Yellowstone National Park, including lake-identification number, lake name, latitude, 

longitude, elevation of lake outlet, lake area, and associated probabilities at acid-neutralizing capacity concentration bins of 

0–100 and 0–200 microequivalents per liter.—Continued

[DD, decimal degrees; Elev, elevation of lake outlet above North American Vertical Datum of 1988; m, meters; ha, hectare; μeq/L, microequivalents per liter; 

%, percent]

Lake 

number 

(see fig. 4 

for location)

Lake name Latitude 

(DD)

Longitude 

(DD)

Elev 

(m)

Lake area 

(ha)

Probability

0–100 μeq/L 0–200 μeq/L
36 Sensitivity of Alpine and Subalpine Lakes to Acidification from Atmospheric Deposition

267 Noname-115 44.23 –110.94 2,167 1.8 0.20% 46.02%

268 Noname-116 44.22 –111.03 1,977 3.74 0.01% 1.38%

269 Ranger Lake 44.21 –110.96 2,122 22.56 0.10% 24.29%

270 Noname-117 44.21 –110.12 2,382 1.53 5.36% 11.06%

271 Noname-118 44.21 –111.02 1,951 1.51 0.01% 1.21%

272 Noname-119 44.21 –111.03 1,953 1.13 0.01% 1.22%

273 Unnamed lake 44.2 –110.24 2,627 4.83 72.39% 83.98%

274 Noname-120 44.21 –110.83 2,314 1.41 1.91% 51.03%

275 Noname-121 44.2 –110.11 2,383 1.41 5.43% 11.11%

276 Basin Creek Lake 44.2 –110.52 2,252 4.29 0.73% 5.81%

277 Noname-122 44.18 –110.24 2,835 1.1 98.55% 96.87%

278 Noname-123 44.18 –111.06 1,977 10.45 0.01% 14.93%

279 Noname-124 44.17 –111.04 1,971 34.03 0.01% 9.14%

280 Noname-125 44.18 –111.02 1,960 1.05 0.01% 6.71%

281 Noname-126 44.17 –111.05 1,977 4.37 0.01% 13.29%

282 Noname-127 44.17 –110.17 2,994 1.66 99.88% 98.64%

283 Noname-128 44.17 –110.27 2,784 1.25 96.82% 95.92%

284 Noname-129 44.17 –111.07 1,977 5.66 0.01% 12.08%

285 Noname-130 44.16 –111.03 1,963 3.27 0.01% 22.13%

286 Robinson Lake 44.16 –111.07 1,977 16.9 0.01% 13.10%

287 Lilypad Lake 44.16 –111.01 1,953 26.94 0.01% 8.20%

288 Unnamed Lake 44.16 –111.08 1,974 1.2 0.01% 23.19%

289 Forest Lake 44.16 –110.63 2,262 3.58 0.85% 38.17%

290 Beula Lake 44.15 –110.76 2,256 53.01 0.78% 11.90%

291 Noname-131 44.16 –110.81 2,317 2.2 2.00% 65.57%

292 Noname-132 44.15 –110.84 2,180 2.1 0.24% 45.75%

293 Mariposa Lake 44.15 –110.24 2,729 5.67 92.80% 84.96%

294 Noname-133 44.15 –111.02 1,943 1.31 0.01% 11.09%

295 Hering Lake 44.14 –110.76 2,257 30.72 0.80% 5.98%

296 Noname-134 44.14 –110.97 1,971 3.93 0.01% 22.84%

297 Noname-135 44.14 –110.74 2,285 1 1.23% 6.87%

298 Phoneline Lake 44.14 –111.05 1,935 10.01 0.01% 12.38%

299 Unnamed lake 44.14 –110.66 2,097 1.48 0.07% 25.50%

300 Unnamed lake 44.13 –110.55 2,497 2.25 25.40% 18.72%

301 Noname-136 44.13 –110.75 2,247 1.96 0.68% 5.68%

302 Noname-137 44.13 –110.65 2,095 2.15 0.06% 3.44%

303 Winegar Lake 44.13 –110.96 1,963 11.93 0.01% 9.01%

304 Tanagar Lake 44.13 –110.68 2,124 9.59 0.10% 25.44%

305 Noname-138 44.13 –110.96 1,962 1.29 0.01% 21.99%

306 Noname-139 44.13 –110.97 1,977 1.34 0.01% 23.43%

307 South Boundary Lake 44.13 –110.75 2,247 6.68 0.68% 5.66%

308 Yellowstone Lake 2,353 34496 3.47% 18.20%

Table 10. Lakes greater than 1 hectare in Yellowstone National Park, including lake-identification number, lake name, latitude, 

longitude, elevation of lake outlet, lake area, and associated probabilities at acid-neutralizing capacity concentration bins of 

0–100 and 0–200 microequivalents per liter.—Continued

[DD, decimal degrees; Elev, elevation of lake outlet above North American Vertical Datum of 1988; m, meters; ha, hectare; μeq/L, microequivalents per liter; 

%, percent]

Lake 

number 

(see fig. 4 

for location)

Lake name Latitude 

(DD)

Longitude 

(DD)

Elev 

(m)

Lake area 

(ha)

Probability

0–100 μeq/L 0–200 μeq/L
Appendix 37

Table 11. Results of multivariate logistic regression analyses for Yellowstone National Park.

(A) Acid-neutralizing capacity (ANC) concentration bin of 0–100 microequivalents per liter.

[μeq/L, microequivalents per liter; (n), total number of lakes; (1), lakes in ANC bin 0–100μeq/L; (0), lakes with ANC > 100μeq/L; min_elev; lake outlet 

elevation]

Logit (P) = e

�–40.149 0.005 min_elev + � ��

1 e�–40.149 0.005 min_elev + � �� +

---------------------------------------------------------------------------

variable (1) (0) (n)

Likelihood ratio 

p-value

score 

p-value

parameter 

estimate

standard 

error

wald 

chi-square p-value Somers’ D c statistic

intercept –40.149 20.276 3.921 0.048

min_elev 3 20 23 0.0036 0.0110 0.005 0.003 3.764 0.052 0.90 0.95

(B) Acid-neutralizing capacity (ANC) concentration bin of 0–200 microequivalents per liter.

[μeq/L, microequivalents per liter; (n), total number of lakes; (1), lakes in ANC bin 0–200 μeq/L; (0), lakes with ANC > 200 μeq/L; min_elev; lake outlet 

elevation; GC 3, fraction of basin that is basalt, gabbro, wacke, argillite, or volcanics]

Logit (P) = e

�–14.901 0.002 min_elev + � � + 3.080 GC 3 � ��

1 e�–14.901 0.002 min_elev + � � + 3.080 GC 3 � �� +

------------------------------------------------------------------------------------------------------------

variable (1) (0) (n)

Likelihood ratio 

p-value p-value

parameter 

estimate

standard 

error

wald 

chi-square p-value Somers’ D c statistic 

intercept –14.901 7.863 3.591 0.058

min_elev 8 15 23 0.0238 0.0383 0.002 0.001 2.862 0.091 0.56 0.78

geochem 3 3.080 1.594 3.733 0.053

Goodness-of-Fit

y = 0.5780x + 0.1133

R2= 0.61

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

0 0.5 1 1.5 2 2.5

Measured ANC Concentrations Less Than 100 microequivalents per liter

Predicted A

N

C

Concentrations

Less Than 100 microequivalents

per liter

Goodness-of-Fit y = 0.5129x + 0.3543

R2 = 0.54

0

0.5

1

1.5

2

2.5

3

0 0.5 1 1.5 2 2.5 3

Predicted A

NC

Concentrations Less Than

200 microequivalents per liter

Measured ANC Concentrations Less Than 200 microequivalents per liter