Bighorn National Forest 

N 

SHERIDAN

COUNTY

Buffalo

Greybull 

Lovell

Sheridan 

Worland

14

14

16 

JOHNSON

COUNTY

MONTANA

WYOMING

BIG HORN

COUNTY

WASHAKIE

COUNTY

Wyoming

ALT

United States

Department

of Agriculture

Forest Service

Rocky Mountain

Research Station

General Technical

Report RMRS-GTR-140

September 2005

Historic Range of Variability for 

Upland Vegetation in the 

Bighorn National Forest, Wyoming

Carolyn B. Meyer

Dennis H. Knight

Gregory K. Dillon
Meyer, Carolyn B.; Knight, Dennis H.; Dillon, Gregory K. 2005. Historic range of variability for upland 

vegetation in the Bighorn National Forest, Wyoming. Gen. Tech. Rep. RMRS-GTR-140. Fort Collins, CO: 

Department of Agriculture, Forest Service, Rocky Mountain Research Station. 94 p.

Abstract

An approach for synthesizing the results of ecological research pertinent to land management is the analysis of 

the historic range of variability (HRV) for key ecosystem variables that are affected by management activities. This 

report provides an HRV analysis for the upland vegetation of the Bighorn National Forest in northcentral Wyoming. 

The variables include live tree density, dead tree (snag) density, canopy cover, abundance of coarse woody debris, 

species diversity, fire return intervals, the abundance of various diseases, the proportion of the landscape in different land cover types, and the degree of patchiness in the landscape. The variables were examined at the stand and 

landscape scales, using information available in the literature and USFS databases. High-elevation landscapes were 

considered separately from low-elevation landscapes. Much of the report pertains to forests dominated by lodgepole pine, subalpine fir, and Engelmann spruce at high elevations, and by ponderosa pine, aspen, and Douglas-fir at 

lower elevations. We defined the HRV reference period for the BNF as approximately 1600 to 1890.

Keywords: aspen, bark beetles, canopy gaps, coarse woody debris, comandra blister rust, Douglas-fir, dwarf mistletoe, Engelmann spruce, fire effects, forest fragmentation, insects in forests, landscape ecology, lodgepole pine, 

mistletoe, mountain pine beetle, ponderosa pine, roads, spruce beetle, subalpine fir, subalpine forests, timber 

harvesting effects, white pine blister rust, wind in forests

The Authors

Carolyn B. Meyer is on the faculty of the Department of Botany at the University of Wyoming, Laramie, WY. Much 

of her research focuses on spatial and temporal variation of ecological phenomena. She received a B.S. degree in 

natural resources from Humboldt State University, in 1983, an M.S. degree in wildlife biology from the University of 

Wyoming in 1985, and a Ph.D. in ecology from the University of Wyoming in 1999.

Dennis H. Knight is professor emeritus in the Department of Botany at the University of Wyoming, Laramie, WY. 

He retired in 2001 after 35 years on the faculty. He taught courses in ecology and forest management, and much of 

his research focused on the effects of natural and human-caused disturbances on Rocky Mountain coniferous forests. In 1999 he contracted with the Rocky Mountain Regional Office of the Forest Service to prepare historic range 

of variability analyses for the upland vegetation of the Medicine Bow, Bighorn, and Shoshone National Forests in 

Wyoming. He received a B.S. degree in biology from Augustana College, Sioux Falls, South Dakota in 1959, and the 

Ph.D. in plant ecology from the University of Wisconsin-Madison in 1964.

Gregory K. Dillon is a GIS specialist with the Forest Service at the Rocky Mountain Research Station, Fire Sciences 

Laboratory, Missoula, MT. His current work is focused on predictive mapping of biophysical settings in the 

United States for the LANDFIRE project. He received a B.S. degree in geography from James Madison University, 

Harrisonburg, Virginia in 1995, and an M.A. degree in geography from the University of Wyoming in 1998.

Cover photo: Scattered Engelmann spruce and lodgepole pine along Tongue River 

on road to Bald Mt. City looking S.W. at 8,500 feet altitude on July 21, 1900. Photo 

by Harvard Professor of Dendrology John G. Jack.

You may order additional copies of this publication by sending your 

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i

Executive Summary

The challenges of ecosystem management have led to an increased emphasis on incorporating the results of science 

in the decision-making process. One approach for accomplishing this objective is through analyzing the historic 

range of variability (HRV) for key ecosystem variables affected by management activities. Such analyses provide a 

means of synthesizing the scientific literature. The rationale for HRV analyses is that the chances of sustainable forest 

management are greater if the variation in managed ecosystems includes the range of conditions expected at various scales in ecosystems that are relatively uninfluenced by humans. This report provides an HRV analysis for the 

Bighorn National Forest (BNF) of northcentral Wyoming.

By definition, HRV analyses require the identification of specific variables and an estimation of how those variables 

fluctuated, at more than one scale, prior to the advent of resource extraction and management by EuropeanAmericans. A complete list of the variables that we examined is found in table 7 on page 78. Examples include live 

tree density, dead tree (snag) density, canopy cover, abundance of coarse woody debris, species diversity, fire return 

intervals, the abundance of various diseases, the proportion of the landscape in different land cover types, and the 

degree of patchiness in the landscape. We examined variables at two scales, namely, the stand and the landscape. 

For this report we separated high-elevation landscapes from low-elevation landscapes. Much of the report pertains 

to forests dominated by lodgepole pine, Engelmann spruce, and subalpine fire at high elevations, and ponderosa 

pine, Douglas-fir, and aspen at lower elevations. Our analysis emphasizes forests rather than grasslands and shrublands because more historical information is available for the forests.

Two significant challenges for HRV analyses are (1) selecting a “reference period” for comparison to present day 

conditions, and (2) making decisions with very little data about the range of variability of a variable during the reference period. We defined the HRV reference period for the BNF as approximately 1600 to 1890, as some data sets on 

fire history go back several centuries and the influence of European-Americans in the BNF was minimal until about 

1890. We also compared BNF ecosystems to comparable ecosystems in natural areas relatively uninfluenced by 

management activities, such as Yellowstone National Park. When data were lacking, our approach was to first make 

plausible though qualitative judgments about the conditions that must have existed in the reference period based on 

recent studies of plant adaptations and current knowledge about ecosystem structure and function. This approach 

is an example of deductive science. There will always be some uncertainty in such conclusions, but our conclusions were evaluated and supported by a panel of six anonymous peer reviewers. For each of our conclusions about 

whether a stand or landscape variable is within the HRV or trending away from that norm in managed landscapes, 

and the BNF as a whole, we indicate whether our confidence level is low, moderate, or high.

Our report describes how the forests of the BNF have developed with regular disturbances, and how the kinds and 

frequency of disturbances have changed in some areas due to modern management practices. About 18% of the 

forested area has been harvested for timber (high- and low-elevation landscapes combined). Roughly 12% has been 

harvested on two occasions. The effects of fire suppression and livestock grazing are more widespread.

Based on our understanding of BNF ecosystems, we have attempted to draw conclusions about whether or not certain ecosystem variables are now beyond their HRV for the period 1600-1890, or trending in that direction. Our 

conclusions can be summarized as follows:

At high elevations the following variables estimated at the stand scale appear to be within the HRV (confidence level 

is indicated in parentheses):

• Fire return interval (moderate) and intensity (high)

• Insect outbreaks (moderate)

• Abundance of diseases, except for dwarf mistletoe in some areas (low)

• Blowdowns (high)

• Tree, sapling, and seedling density (high)

• Plant species diversity (low)

• Understory plant density and cover (high)

• Age- and size-class structure of most stands (moderate)

• Forest floor depth (high)

Similarly, the following variables estimated at the landscape scale appear to be within the HRV at high elevations:

• Fire intensity (high)

• Insect outbreaks (moderate)

• Abundance of diseases except for dwarf mistletoe (low)

• Blowdowns (high)

• Tree, sapling and seedling density (moderate)

• Understory density and cover (moderate)
ii

• Plant species diversity (low)

• Forest floor depth (moderate)

• Number and proportion of land cover types (high)

• Forest/non-forest ratio (high)

At low elevations, the following stand variables appear to be within the HRV:

• Insect outbreaks (low)

• Abundance and composition of diseases, except where the introduced white pine blister rust occurs 

(moderate)

• Blowdowns (high)

• Tree species diversity (high)

• Snag density and abundance of coarse woody debris, except where timber harvesting has occurred 

(moderate and low, respectively)

Similarly, the following landscape variables appear to be within the HRV at low elevations:

• Insect outbreaks (low)

• Abundance and composition of diseases, except where the introduced white pine blister rust occurs 

(moderate)

• Blowdowns (high)

• Tree species diversity (high)

• Proportion of landscape with old trees (moderate)

• Proportion of land with high densities of snags and coarse woody debris (low)

• Proportion of land in different land cover types (low)

For aspen stands, the following variables appear to be within the HRV at high and low elevations and at both the 

stand and landscape scales:

• Insect outbreaks (moderate)

• Disease abundance (low), except near campgrounds

• Blowdowns (high)

Very little information is available for drawing conclusions about the HRV of grassland, meadow, and shrubland 

variables on the BNF. However, fire size, return interval, and intensity appear to be within the HRV, probably at both 

the stand and landscape scales (low confidence).

In contrast, the following variables appear to have exceeded their HRV in some areas affected by management activities:

Within stands at high elevations affected by timber harvest (~20% of the high-elevation forests on the 

BNF)

1. Canopy cover probably is lower and the size and density of canopy gaps probably are higher in harvested 

stands than the HRV for these variables in unmanaged forests of comparable age and site conditions due to 

selective and shelterwood cuts, thinning, and fewer standing-dead trees (moderate confidence).

2. Where timber harvesting has occurred, snag density and the amount of coarse woody debris are lower than 

the HRV for unmanaged stands of comparable age and site conditions (high confidence). Whole-tree yarding can accentuate this variation by concentrating coarse woody debris and slash at landings in a way that 

has not occurred previously.

3. Due to some methods of slash treatment, the intensity of soil scarification is beyond the HRV in some areas 

(high confidence). Burning can remove the forest floor, but the depth of soil disturbance typically is less 

than following mechanical harvesting. Similarly skid trails probably have compacted soils beyond their 

HRV, at least temporarily.

4. Age- and size-structure of managed stands within ravines or on some north or leeward slopes is skewed 

toward smaller and younger trees than would have occurred during the HRV period, because of harvesting 

where fires would have been less likely to burn (moderate confidence).

5. Dwarf mistletoe abundance is probably above its HRV in stands subjected to partial timber harvests, but 

may be below its HRV in clearcut stands (low confidence).

Across forested landscapes at high elevations

6. The estimated rotation times for harvesting of timber from forests judged suitable for harvesting are generally shorter, on average, than the estimated site-specific mean intervals between natural disturbances in 

high-elevation forests. On the area where timber harvesting has occurred, old-growth forest has been reduced, particularly in areas that have had long fire-free intervals, such as in valley bottoms and on some 
iii

north or leeward slopes. Thus, in such areas, ecosystem characteristics that depend on periods of forest 

growth longer than 140 years may be lost, resulting in less old-growth forest on the landscape. The proportions of other age-classes are within the HRV, except for the now more abundant mid-successional forests 

in harvested areas (moderate confidence).

7. The average snag density and coarse woody debris biomass across the landscape have been reduced below the HRV (high confidence). The loss of some old-growth forests and the suppression of fires that create 

abundant snags have reduced the percentage of the forested landscape that contains high density snags/

coarse woody debris to a level that is below the HRV (moderate confidence).

8. The rate of patch formation and the size of disturbances across high elevation landscapes are outside the 

HRV (high confidence). Timber harvest produces patches more frequently than natural disturbances, and 

mid-sized patches are over-represented. Natural fires produce many small patches and a few very large 

patches at high elevations. Fire frequency, size, and extent also have been reduced below the HRV due to 

fire suppression (low confidence).

9. The percentage of the landscape with low canopy cover probably is higher than the HRV due to partial 

cutting and thinning (low confidence).

10. Due to roads and clearcutting, the amount of edge is now higher and the amount of interior forest is lower 

than prior to the 1900s in parts of the BNF where timber harvesting has occurred (moderate confidence). 

Correlated with this and fire suppression is a decline in the maximum patch size, the development of a 

more simple patch shape, and a higher, more uniform level of landscape patchiness than would have occurred during the reference period (high confidence).

11. Some kinds of mechanical slash treatment have led to a higher level of mineral soil disturbance than 

would have occurred during the HRV reference period (high confidence).

12. Dwarf mistletoe may be somewhat above its HRV on the landscape scale due to the tie-hacking, selective 

cutting, fire suppression, and thinning that has occurred on the forest (low confidence).

Within stands at low elevations affected by harvest, fire suppression, and livestock grazing

13. Fire suppression, livestock grazing, and possibly climate change have led to the development of low-elevation forest stands with higher densities of young trees, greater canopy cover, less understory plant cover, 

and deeper forest floors than usually occurred on many sites before 1890 (see table 7 for confidence levels 

associated with each variable). Understory composition also has changed where introduced plants occur.

14. By removing large trees and downed wood from the system, wood harvesting has lowered the abundance 

of snags and coarse woody debris in managed stands of low-elevation forests (moderate confidence). 

Harvesting also has led to an increase in sapling density and a reduction in the average diameter of 

trees, thus creating younger, more uniform-sized stands than existed before harvest (moderate confidence). 

However, only about 1% of such forests have been subjected to harvesting thus far. Where harvesting 

and effective fire suppression have not occurred, snags and coarse woody debris probably are within the 

HRV.

15. Mean fire return interval has become longer than the HRV due to fire suppression (moderate confidence). 

Consequently, there is a trend for tree distribution to be more uniform and to have tree invasion into some 

meadows.

16. White pine blister rust outbreaks cause some stand variables to exceed the HRV in affected stands, as this 

disease is not native (high confidence).

Across forested landscapes at low elevations

17. The sizes of most fires have declined due to fire suppression, and the mean fire interval, tree/sapling density, tree canopy cover, and amount and continuity of fuels is above the HRV in a larger proportion of the 

BNF than during the reference period (moderate confidence).

18. Understory plant density and cover have declined below the HRV (low confidence) and forest floor depth 

has increased above the HRV in a larger proportion of the landscape than during the reference period 

(moderate confidence).

19. White pine blister rust was absent during the HRV reference period but is present today (high confidence).

20. The age- and size-class structure of trees (moderate) is different from the HRV.

Aspen woodlands

21. In some areas, livestock or native ungulate grazing and browsing have reduced aspen densities and affected the understory vegetation to a point where these variables are beyond their HRV (high confidence). 

These changes are confounded with the introduction of exotic plants.

22. Fire suppression has reduced fire size and lengthened fire return intervals, thereby enabling an increase in 

conifer density in some areas to a level that is higher than the HRV (moderate confidence).
23. Due to human wounding of trees in recreational areas, some stands have an incidence of disease that is 

beyond the HRV (low confidence).

Non-forest vegetation

24. Some meadows, grasslands, and shrublands are probably grazed more, or have been in the past, than 

during the HRV period, with the potential for an increase in soil erosion and forb and shrub abundance 

(moderate confidence). Deviations from the HRV are also caused by the presence of exotic plants that 

displace native species and cause changes in other ecosystem properties (high confidence).

Frequently there has been a lack of data for the ecosystem variables we have addressed in this report (table 7). Such 

variables can be identified as priorities for future research or monitoring. Research will also be required if decisions about the severity of a potential problem cannot be made without more information or if ways of restoring the 

HRV for important variables cannot be identified. Our report ends with a brief discussion of issues related to forest 

health.

iv
Acknowledgments

Funding was provided by the Division of Renewable Resources, Rocky Mountain Region, U.S. Forest Service (USFS 

Agreement 1102-0003-98-043 with the University of Wyoming). The following managers and scientists provided valuable assistance, and six anonymous reviewers, coordinated by the Ecological Society of America, provided 

helpful comments in their evaluations of this report:

• Claudia Regan, Regional Office, U.S. Forest Service, and Department of Forest Sciences,

 Colorado State University

• Bernie Bornong, Bighorn National Forest

• Rick Laurent, Bighorn National Forest

• DeeDee Arzy, Bighorn National Forest

• David Anderson, Bighorn National Forest

• Pam Ziesler, Bighorn National Forest

• David Myers, Bighorn National Forest

• Bob Daniels, Bighorn National Forest

• R. Scott Gall, Bighorn National Forest

• Ron Stellingwerf, Bighorn National Forest

• Dave Beard, Bighorn National Forest

• Bill Biastoch, Bighorn National Forest

• Chris Thomas, Bighorn National Forest

• Bryce Bohn, Bighorn National Forest

• Harold Golden, Bighorn National Forest

• Judy von Ahlefeldt, retired, Medicine Bow National Forest

• Greg Hayward, Regional Office, U.S. Forest Service, and Department of Zoology and

 Physiology, University of Wyoming

• Kurt Allen, Regional Office, U.S. Forest Service

• Bert Jellison, Wyoming Game and Fish Department

• Thomas T. Veblen, Department of Geography, University of Colorado

• William H. Romme, Department of Forest Sciences, Colorado State University

• Walt Fertig, Wyoming Natural Diversity Database, University of Wyoming

• Gary Beauvais, Wyoming Natural Diversity Database, University of Wyoming

• George Jones, Wyoming Natural Diversity Database, University of Wyoming

• William A. Reiners, Wyoming Geographical Information Sciences Center and Department of

 Botany, University of Wyoming

• William L. Baker, Department of Geography, University of Wyoming

• Stephen T. Jackson, Department of Botany, University of Wyoming

• Stephen T. Gray, Department of Botany, University of Wyoming

• Jodi Norris, Department of Botany, University of Wyoming

• Christopher L. Fastie, Department of Biology, Middlebury College

v
Contents

Executive Summary ............................................................................................................... i

Acknowledgments ....................................................................................................vi

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

2. Methods ........................................................................................................................... 4

3. The Bighorn National Forest ............................................................................................ 6

3.1 Physical Setting .......................................................................................................... 6

3.2 Ecological Setting ..................................................................................................... 10

3.3 Cultural Setting ......................................................................................................... 14

3.3.1 Historic Period (1600-1890) .............................................................................. 14

3.3.2 European-American Settlement and National Forest 

 Administration (1890-1945) .................................................................................... 15

3.3.3 Post-World War II (1945 to present) ................................................................... 16

4. Dominant Plant Distribution and Successional Patterns Along Ecological Gradients ..... 21

4.1 Dominant Plant Distribution Patterns ........................................................................ 21

4.2 Successional Patterns ................................................................................................ 24

4.2.1 Succession in high-elevation forests ................................................................... 24

4.2.2 Succession in low-elevation forests .................................................................... 25

4.2.3 Succession in aspen woodlands ......................................................................... 25

4.2.4 Succession in non-forest vegetation ................................................................... 25

5. Historic Range of Variability for Disturbances Compared to Existing Conditions .......... 26

5.1 Fire ........................................................................................................................... 26

5.1.1 Fire in high-elevation forests .............................................................................. 27

5.1.2 Fire in low-elevation forests ............................................................................... 38

5.1.3 Fire in aspen woodlands .................................................................................... 42

5.1.4 Fire in non-forest vegetation .............................................................................. 43

5.2 Insects ...................................................................................................................... 43

5.2.1 Insects in high-elevation forests ......................................................................... 43

5.2.2 Insects in low-elevation forests .......................................................................... 45

5.2.3 Insects in aspen woodlands ............................................................................... 47

5.2.4 Insects in non-forest vegetation .......................................................................... 48

5.3 Disease ..................................................................................................................... 48

5.3.1 Disease in high-elevation forests ........................................................................ 48

5.3.2 Disease in low-elevation forests and woodlands ................................................ 51

5.3.3 Disease in aspen and non-forest vegetation ....................................................... 51

5.4 Wind ........................................................................................................................ 52

5.4.1 Wind in high-elevation forests ........................................................................... 52

5.4.2 Wind in low-elevation forests and aspen woodlands ......................................... 52

6. Historic Range of Variability for Stand and Landscape Structure 

 Compared to Present Conditions .................................................................................... 54

6.1 Stand Structure ......................................................................................................... 54

6.1.1 Stand structure of high-elevation forests ............................................................. 54

6.1.2 Stand structure in low-elevation forests and woodlands ..................................... 61

6.1.3 Stand structure in aspen woodlands ................................................................... 64

6.1.4 Stand structure in non-forest vegetation ............................................................. 64

vi
6.2 Landscape Structure ................................................................................................. 65

6.2.1 High-elevation landscapes ................................................................................. 66

6.2.2 Landscape structure at low-elevations (including aspen and 

 non-forest vegetation) ............................................................................................. 76

7. Summary of Probable HRV Deviations ........................................................................... 77

8. Literature Cited .............................................................................................................. 82

Appendix A—Problems known to be associated with using data in the Bighorn 

National Forest RIS and fire databases. ............................................................................ 93

vii
USDA Forest Service RMRS-GTR-140. 2005 1

1. Introduction

Managers of public lands are now charged with achieving the societal goals of conserving biological diversity 

and maintaining ecosystem services while contributing 

to national needs for various other natural resources—an 

endeavor commonly referred to as ecosystem management (Covington and DeBano 1994; Grumbine 1994; 

Kaufmann and others 1994; Christensen and others 

1996; Vogt and others 1997; Landres and others 1999). 

The proponents of ecosystem management recognize 

that our current knowledge of ecosystems is incomplete 

(Christensen and others 1996) but that resource managers should use the best scientific information available. 

An analysis of the historic range of variability (HRV) 

for key ecosystem variables is one means of synthesizing the available ecological information for an area. In 

this report we present an HRV analysis for the Bighorn 

National Forest (BNF) in northcentral Wyoming.

One example of how attitudes about resource management have changed in the last 50 years is greater emphasis 

on resilience rather than stability (in terms of resistance 

to change; Holling and Meffe 1996). Ecosystems have 

developed with constant change and fluctuation (Botkin 

1990; Landres and others 1999; and others), with disturbances such as those caused by fire and insect epidemics 

having influenced ecosystems for millennia in the Rocky 

Mountain region (Knight 1987; Fall 1997). Managers 

are now using the variability caused by natural disturbances and other phenomena as a guideline. Kaufmann 

and others (1994) concluded, “. . . the most sound basis 

for ecosystem management is to assure that the variation characterizing [managed] ecosystems includes the 

range of conditions that are expected at various scales 

in ecosystems uninfluenced by humans.” The focus is on 

variability, not stability.

Various terms have been used in previous reports 

on variability, including “range of natural variability” 

(Swanson and others 1993), “natural variation” (Holling 

and Meffe 1996), “reference conditions” (Kaufmann and 

others 1994), “reference variability” (Manley and others 

1995), and “historic range of variability” (Morgan and 

others 1994). We have adopted the term “historic range 

of variability” (HRV) because it avoids the potential 

problems associated with the word “natural.” Regardless 

of the language, we interpret HRV as the spatial and 

temporal variation in various ecosystem characteristics 

when the influences of European-Americans were minimal. For our analysis, we focused on the period from 

1600 to 1890. Historical evidence suggests that timber 

harvesting and livestock grazing did not begin in the 

BNF until after 1890 (Martorano and others 1985).

We adopted four principles as guidelines. First, variables should be evaluated over at least two spatial scales. 

The variability that occurs in small tracts of land, commonly referred to as “stands,” is quite different from 

that which occurs over larger areas, referred to as “landscapes.” Stands are tracts of forest or other vegetation 

that are relatively homogeneous in terms of environment, 

plant species composition, and disturbance history. They 

generally occupy an area ranging from a few hectares 

to several hundred hectares. In contrast, “landscapes” 

are large, usually ranging from several km2 to several 

thousand km2 or more, and they have considerable heterogeneity. The HRV of some variables, such as dead 

standing trees (snags), is typically higher at the stand 

scale than at the landscape scale (fig. 1). Of course, some 

variables are not amenable to discussion in a practical 

way at both scales. For example, the proportion of a 

landscape in different cover types is not meaningful at 

the stand scale.

Just as there is more than one stand in a landscape, 

there are several landscape types in a National Forest. 

HRV

 Stand Landscape National Forest Region

Range

Mean

High 

Low 

Figure 1—Illustration of the decline in the 

HRV of a hypothetical variable as the spatial scale increases. The variation in the 

mean HRV of a variable is always less 

than the range between the maximum and 

minimum for the entire period.
2 USDA Forest Service RMRS-GTR-140. 2005

For this report, we separated high-elevation landscapes 

from low-elevation landscapes. We also evaluated the 

following general vegetation types separately: lodgepole pine/spruce-fir forest (referred to as high-elevation 

forest), Douglas-fir/ponderosa pine/limber pine forest 

(referred to as low-elevation forest), aspen woodlands, 

and non-forest vegetation (e.g., meadows and shrublands). Because the BNF timber and fire databases were 

often not separated into these vegetation types, our 

interpretation for the HRV of some landscape-level variables (e.g., fire regimes and mean shape of disturbance 

patches) required assumptions that we identify later in 

this report. Our analysis emphasizes forests rather than 

meadows and shrublands because much more historical 

information is available for the forests.

The second principle is that HRV analyses should 

consider variability in space as well as time. This principle is difficult to apply because historical data are rarely 

available for more than one or two watersheds or landscapes. However, it is possible to characterize spatial 

variability in vegetation patterns across watersheds on 

the BNF, as it exists today, and to compare that variability to the range of expected conditions during the HRV 

period based on our current understanding of ecosystem 

dynamics. By necessity, HRV analyses must often be deductive in nature—drawing conclusions about specific 

variables based on general knowledge about ecosystems.

The third principle affecting HRV analyses is that the 

effects of climate change should be distinguished from 

the effects of human activities. There is no question 

that the climate has changed since the Rocky Mountain 

glaciers began to recede about 10,000 years ago. It also 

is clear that the climate of the 1600s, 1700s, and much 

of the 1800s was different from the present time (Millar 

and Woolfenden 1999). Working on the west side of 

the BNF, Gray (2003) and Gray and others (2004) concluded from tree-ring data that, while the mean annual 

precipitation was about the same during the 1600s and 

1700s as it is today, there are now fewer extended wet 

and dry periods than in previous centuries and the extremes of the wet and dry periods in the 1900s are less. 

Moreover, preliminary research suggests that the climate of the Bighorn Mountains began to warm in the 

late 1800s (C. Fastie, unpublished data). While the HRV 

estimates of some ecosystem variables for the reference 

period 1600-1890 may be less applicable to present conditions because the climate has changed, we believe they 

still provide a useful context for management decisions. 

Distinguishing the effects of climate change from the effects of European-Americans is a difficult but important 

challenge for HRV reports.

The fourth principle is that “variability” can be characterized in several ways. To illustrate, variability can be 

thought of as the absolute range of an ecosystem variable 

or parameter, in which case extreme and rare conditions 

are often included (fig. 2). Alternatively, the HRV can 

be based on an estimate of the range of means (or frequency) for a variable over several consecutive periods 

of time, an approach that ignores extremes (fig. 3). HRV 

analyses based on average conditions tend to produce a 

narrower range than when considering extremes (fig. 1). 

A third approach involves the calculation of the standard 

deviation. Unfortunately, data availability and sample 

sizes are rarely, if ever, adequate for statistical analyses. 

In this report, we use primarily the range of means approach, conceptually if not quantitatively.

To characterize the HRV, a reference period must be 

specified to which the last century or so can be compared. 

Manley and others (1995) indicated that it would be ideal if the period could cover an evolutionary time scale 

(i.e., as long as possible within the past 10,000 years or 

so), but we selected a period of 290 years, between 1600 

to 1890 Martorano and others 1985). It would be good 

to consider a longer, evolutionary time scale, but climate 

change and glaciation in the BNF during the last 10,000 

years or more would create extremely broad ranges of 

variability that would be difficult to apply to present day 

management decisions. Also, it is difficult enough to estimate variability during the last few centuries.

An evolutionary perspective is adopted in our report, 

but in a different sense than implied by Manley and others (1995). Some of our interpretations are based on the 

prevailing consensus about the environmental conditions that must have led to the development of certain 

adaptations exhibited by the dominant plants of the BNF 

today. Such adaptations surely influence where species 

Decade

16801720

176018001840

1880

1920

19602000

Stand or landscape variable

0

5

10

15 HRV period

Existing conditions (post-European settlement)

Figure 2—Illustration of the historic range for a hypothetical 

variable, which incorporates extremes from 0 to 11 in the 

above example. If HRV is defined as the historic absolute 

range, then existing conditions in this example (ranging 

from 0 to 2) fall within the HRV. 
USDA Forest Service RMRS-GTR-140. 2005 3

survive today. For example, the thick bark of ponderosa 

pine (Pinus ponderosa) suggests that the environment 

where it occurs, or has occurred in the past, is characterized by periodic surface fires. Similarly, the thin bark 

and serotinous cones of lodgepole pine (Pinus contorta) 

suggest that the tree is characterized by periodic standreplacing crown fires.

Estimates of HRV are inevitably limited by our ability 

to interpret the nature of past ecosystems and determine 

what is “natural” or “normal” (Swanson and others 1993; 

Holling and Meffe 1996). Because ecosystems change 

dramatically during the time span of a few centuries, we 

only capture a “snapshot” if our reference period is not 

long enough (Swanson and others 1993). For such reasons, estimates of HRV are not a panacea. Rather, they 

serve as one of several tools to aid managers in achieving 

the societal goal of conserving biological diversity while 

providing the benefits of various natural resources.

By considering the HRV for tangible, meaningful variables during defined time periods, land managers have 

an improved context in which to evaluate their decisions 

(Manley and others 1995). If a management activity pushes an ecosystem variable to a higher or lower level then 

ever before, based on the kind of evidence included in 

HRV reports such as this one, then there is reason to evaluate the environmental impacts of that activity—or even 

consider adopting a different approach. When quantitative 

data are not available, the goal of specifying variability must be done using qualitative information. For some 

observers, this approach is not satisfactory. However, 

deductive analyses can provide insights that are not available in any other way and which improve the chance that 

management decisions will not impede an ecosystem’s 

inherent resilience following the inevitable disturbances 

that will occur, whether caused by fire, wind, insects and 

pathogens, or humans.

Landres and others (1999) concluded that, properly 

done, HRV analyses provide context and guidance for 

managing ecological systems. They also emphasized, 

however, that it is appropriate and unavoidable for HRV 

reports to include professional judgments, even though 

based on limited data. Given that fact, they recommended that the authors of such reports should specify their 

assumptions and value judgments. Briefly, our assumptions and judgments are (1) there is much yet to be learned 

about how to manage National Forests within the context 

of ecosystem management, (2) there is value in the periodic evaluation of traditional management approaches to 

determine if they are appropriate for meeting an objective, (3) some parts of a National Forest are suitable for 

the careful production of commodities, while others are 

not—a policy that has been implemented for many years 

through the designation of, for example, lands suitable 

and not suitable for timber harvesting—and (4) decisions 

about the management of specific areas cannot be based 

solely on a single report such as this one.

HRV analyses also should not be viewed as a step toward creating “pristine” conditions (Swanson and others 

1993; Allen and Hoekstra 1994). Ecosystems may, in 

fact, be sustainable outside the HRV for a variable if society is able and willing to engineer functions once carried 

out naturally (Allen and Hoekstra 1994). The question remains, however, whether or not we know enough to create 

substitutes for natural processes now done by the thousands of organisms representing innumerable species that 

occupy any ecosystem—and can afford to pay for them. 

Moreover, National Forests already have some features 

that are unprecedented and clearly outside the HRV, such 

as roads, dams, and exotic species (Swanson and others 

1993). Restoration of the HRV may not be practical or desirable, or even possible, in some situations.

In this report for the BNF, we have attempted to provide (1) an estimate of the HRV for key elements of 

terrestrial ecosystems, including quantitative ranges for 

specific variables whenever possible, and (2) a comparison of our HRV analysis with current conditions on the 

Decade 1680

1720

1760

1800

1840

1880

1920

1960

2000

Stand or landscape variable

0

5

10

15

Period 1 Period 2 Period 3 Period 4 

X = 6.2 

SD=3.8

X = 1.9 

SD=1.6

X = 1.5 

SD=1.2

X = 2.8 

SD=1.7

X = 0.6 

SD=0.4

X = 0.8 

SD=0.5

Period 5 Period 6 

HRV period Existing conditions

Figure 3—Illustration of the range of historic means for a 

variable which ignores extremes. If HRV and existing conditions (EC) are defined as the range of means, the range of 

EC in this example (0.6-0.8) falls outside the HRV (1.5-6.2). 

Also illustrated is a comparison of the range of standard 

deviations (SD) of the variable, where the SD of the existing conditions (0.4-0.5) falls outside the SD for the historic 

conditions (1.2-3.8) during a series of consecutive time periods. We used the range of means (mean = average for 

each period) and, occasionally, standard deviations (SD = 

how variable the values are for the period) as the definition for HRV in this report, conceptually if not quantitatively. 

Using a t-test on the means with α = 0.05, the HRV of our 

example does not differ significantly from the EC (P = 0.11), 

probably due to the low sample sizes of n = 4 and n = 2.
4 USDA Forest Service RMRS-GTR-140. 2005

BNF or conditions since European-Americans arrived. 

Our focus is on upland vegetation dynamics and plantrelated ecosystem variables at the stand and landscape 

scales. After describing our methods, we describe the 

physical, ecological, and cultural characteristics of the 

BNF before proceeding with an HRV analysis for key 

variables in high-elevation landscapes, low-elevation 

landscapes, aspen woodlands, and non-forest vegetation. 

Our conclusions about human-caused deviations from 

the HRV are summarized in the Executive Summary, table 7, and section 7.

As noted, we emphasize forests over meadows, 

grasslands, and shrublands because far more data are 

available for forested areas. Grazing certainly affects a 

large proportion of the BNF, but interpreting the historic 

development and variability of grassland and shrubland 

variables for our reference period (1600-1890) is almost 

impossible without a tree-ring record to provide insights 

into the past. Also, more ecosystem research has been 

done on forests than on non-forested areas, thereby providing a better basis for predicting the HRV through a 

deductive analysis. The HRV of riparian vegetation is of 

great importance and considerable interest but beyond 

the scope of our report.

2. Methods

Manley and others (1995) suggested that estimating 

HRV for biological systems should include the following steps: (1) determine key ecosystem elements (i.e., 

components, structures, and processes), (2) identify 

measurable environmental indicators for these elements 

(e.g., tree density and mean disturbance return interval), 

and (3) estimate values for the indicators over the selected HRV reference period. We tried to be more inclusive 

than exclusive in selecting key elements, as the importance of some ecosystem features or processes may be 

latent until the ecosystem is subjected to some kind of 

stress (Holling and Meffe 1996).

The challenge of HRV analyses is to make decisions 

about variables during the HRV period based on very 

little data. HRV studies are a relatively new endeavor 

and methods are changing rapidly as we gain new information on the best approaches to use. We used several 

approaches. First, we made plausible, though qualitative, 

judgments about the conditions that must have existed in 

the past based on recent quantitative studies of plant adaptations and current knowledge about ecosystem structure 

and function. Knowledge about the organisms that exist 

in an ecosystem today provides clues about environmental conditions that probably existed in the past, and the 

general principles of ecosystem structure and function 

provide a basis for drawing tentative conclusions, deductively, about a specific area. Our conclusions can be 

considered as hypotheses requiring further testing in the 

future. Each conclusion is followed by an indication of 

our confidence level (low, moderate, and high).

Second, we made judgments about the past from different kinds of historical records, such as contained in 

tree rings and the journals and photographs of early explorers. Specifically, we used (1) historic records and 

studies covering approximately the last century that provided quantitative or semi-quantitative information; (2) 

historical accounts, which provided mostly qualitative 

information back to the 1800s; and (3) reconstructive 

studies from tree rings, pollen analysis, and other methods that provide the only quantitative information for 

periods prior to the 1800s (Kaufmann and others 1998).

Finally, valuable information was obtained from studies on the long-term dynamics of ecosystems in modern 

reference areas that have not been heavily influenced 

by humans, such as wilderness areas and some National 

Parks in the region. The research done in Yellowstone 

National Park (YNP) has been especially useful. The 

climate is similar to the BNF, though YNP is generally 

cooler and more moist. The geological history is different, but the predominant vegetation is similar. Using data 

from any area as a proxy for another must be done with 

caution, but to ignore such pertinent information needlessly limits the applicability of research. Of course, no 

landscape is entirely free from human influences. Native 

Americans have caused some changes for thousands of 

years, and even our largest National Parks have been affected by the technological impacts that now characterize 

the earth.

Our analysis is based primarily on the compilation and 

synthesis of information on upland vegetation from published and unpublished sources relating to the history and 

ecology of the BNF specifically and the Rocky Mountain 

region in general. Funds were inadequate for initiating 

new field work or for incorporating an analysis of wetland 

vegetation. Information was derived from all available 

sources, including journals, books, USDA Forest Service 

publications, BNF reports, and BNF databases. Several 

sources were especially useful in quantifying historic and present conditions specific to the BNF, namely 

the Resource Information System (RIS) and the fire database of the BNF. Both databases are maintained at the 

Supervisor’s Office in Sheridan, Wyoming. While there 

are some limitations to using these databases (Appendix, 

table A-1), they provide the most comprehensive source 

of spatial information. We also used maps of disturbance patterns across the landscape that had been derived 

from satellite imagery by the Wyoming Game and Fish 
USDA Forest Service RMRS-GTR-140. 2005 5

Department. Finally, we conducted interviews of BNF 

personnel and others to gain a better understanding of the 

management and ecology of the BNF.

For this report, we have drawn conclusions about 

whether existing conditions have changed from conditions during the HRV reference period, from about 1600 

to 1890, due to the management activities of EuropeanAmericans. We define existing conditions (EC) as 

conditions occurring during any period after 1890, though 

primarily during the last half-century. In general, we defined HRV as the range of means of a variable for several 

consecutive time periods during the period 1600 to 1890 

(fig. 3). We concluded that a change from the HRV probably had occurred if we felt there was evidence to suggest 

that the range of means for the variable over a series of 

similar, consecutive time periods during the HRV period 

probably would be different from the existing conditions 

(fig. 3).

Unfortunately, only one mean is usually reported in 

the literature for the HRV period, if that, rather than the 

several required to obtain a range of means. In those 

cases, we estimated whether or not the mean during existing conditions probably differed by more than about 

75% from the mean during the HRV period (fig. 4). If a 

defensible argument could be made, we concluded that 

existing conditions are outside the HRV. This conclusion, based on only one mean, would not be possible if 

conditions varied substantially from half-century to halfcentury, or if they varied hardly at all. Future research is 

required to evaluate the accuracy of the assumptions associated with our approach.

The above examples assume data for the HRV period 

are available for the BNF. In reality, pertinent HRV data 

are usually available only in Yellowstone National Park 

and other areas nearby where a considerable amount of 

research has been done. To partially offset this deficiency, we substituted “proxy” data for actual data on the 

BNF during the HRV period, as follows:

(1) We used data collected for the HRV period from studies in other places in the Rocky Mountains.

(2) For many analyses, we used existing conditions (20th

century) in Yellowstone National Park as the conditions on the BNF during the HRV period. The 

Park’s vegetation has been less strongly influenced 

by European-American activities and probably reflects disturbances and environmental influences 

that occurred in the Bighorn Mountains. In most 

cases involving fire regimes, we used Yellowstone 

data for the period in which fire suppression was 

not attempted in the Park.

(3) We used the existing pattern (20th century) of “natural” disturbances, such as blowdowns and standreplacing fires, as the pattern that must have existed during the HRV period for comparison to patterns created by new kinds of disturbances such 

as extensive timber harvesting. Recognizing that 

humans have surely modified some of the natural disturbances (e.g., by suppressing some fires), 

we only used this method when the human modification of natural disturbance patterns was thought 

to be small relative to the landscape modifications 

caused by European-Americans.

(4) We substituted space for time in some landscape 

analyses. In other words, the range of conditions at 

a point in time across all watersheds was assumed 

to reflect the range of conditions during the HRV 

period. This assumes that the timing and patterns 

of disturbances in different watersheds are uncorrelated and that each watershed is a snapshot of 

conditions that occurred in just one of the watersheds in the past. This is not a strong assumption 

because events such as large fires often cross watershed boundaries. Also, different soils, topography, and climate cause differences in the vegetation of watersheds. Consequently, we used this approach rarely and only when our conclusions could 

be supported by other information.

For the qualitative analyses, we used the same approach outlined above but we substituted our knowledge 

of ecosystem processes and the effects of human developments to estimate the direction and magnitude of any 

Figure 4—When only one mean is reported for the historic period, no range of means can be determined. In such cases, 

to be considered a deviation from the HRV, a mean for existing conditions must be substantially higher or lower than 

the HRV mean. In this example, the HRV would have to be 

less than + 75% of the historic mean of 3.1 to have the EC 

mean (0.7) fall outside the HRV (1.5-6.2), using the same 

data as in fig. 3. 

Decade

1680

1720

1760

18001840

1880

19201960

2000

Stand or landscape variable

0

5

10

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HRV 

Period

X = 3.1 X = 0.7

Existing 

Conditions
6 USDA Forest Service RMRS-GTR-140. 2005

changes from the HRV. We describe the justification for 

each decision.

For each variable, we attempted to address (1) its 

HRV at the stand and landscape scale, (2) its spatial 

variability across the landscape as well as its temporal 

variability, when such data were available, (3) the influence of climate change, and (4) our confidence level 

(low, medium, and high) in concluding whether the variable under existing conditions is within or beyond the 

HRV. Our conclusions and confidence levels are summarized in table 7, which is part of our summary for this 

report (section 7).

Because it is easy to misinterpret how HRVs are applied to the stand and landscape scales, we provide the 

following two illustrations for clarification. At the stand 

scale, the HRV focuses on changes through time, which 

ecological theory suggests would differ for every stand 

even if two stands are within the same vegetation type. 

A continuum of HRVs should be expected, just as there 

is a continuum of species composition. No two stands 

are exactly alike because of differences, however slight, 

in topography, soils, climate, disturbance history, seed 

availability, sprouting capacity of surviving plants, rate 

of successional development, and other factors. We cannot consider all the various stand types in our analyses, 

but general statements about changes in HRV through 

time are possible. For example, we can say that most 

pre-commercial thinning prescriptions would lower 

canopy cover and increase the number of canopy gaps 

beyond the HRV in each stand that is thinned, at least for 

several decades, because no ecosystem processes mimic 

such an activity. Thus, the HRV of canopy cover for each 

stand averaged through those several decades would be 

reduced. When such a directional pattern is true of most 

but not all stands, we acknowledge the exceptions.

At the landscape scale, we looked for changes in patterns over time. However, we also averaged the variable 

across all stands to assess the HRV over a large spatial 

scale. As a result, the HRV narrows as the scale changes from the stand level to the landscape level (fig. 1). For 

example, a stand may have many snags after a crown 

fire, but then none at all (or very few) if the snags fall before new snags are formed. Thus, the snag densities for 

the individual stand could range from zero to extremely abundant. By contrast, it is highly unlikely that all of 

the snags across a landscape would fall before new ones 

are formed, or that all live trees in the landscape would 

be converted to snags by a fire. Thus, snag density at the 

landscape scale would range from moderately low to 

moderately high. There would always be some snags in 

the landscape.

A logical conclusion from this discussion is that the 

HRV for a variable is dependent on the amount of land 

area being considered. In other words, the probability 

of finding a stand or landscape with zero snags declines 

as the size of the stand increases. This is true simply 

because the probability of tree mortality somewhere in 

the area increases as the number of trees increases.

Regrettably, data for specific variables at the landscape scale are less common than for individual stands. 

Therefore, we sometimes used variables such as the percent of the landscape in stands that probably have high 

snag density. This approach supplements our landscapelevel, qualitative estimate of snag density.

3. The Bighorn National Forest

3.1 Physical Setting

The Bighorn National Forest (BNF) is located in 

northcentral Wyoming (fig. 5) and covers 447,500 ha 

(1,105,325 acres). The Forest occurs over most of the 

Bighorn Mountains, a relatively isolated mountain range 

that rises from rolling plains at 900-1200 m (2952-3936 

ft) up to 4009 m (13,187 ft) on Cloud Peak (USDA 

Forest Service 1985). On the eastern and western forest boundaries, the flanks of the mountains drop steeply 

to the surrounding Bighorn and Powder River Basins. 

High peaks rise from a plateau (at 2400-2800 m [7872-

9184 ft]) in the southcentral portion of the mountain 

range (fig. 6). The glaciated peaks of granite slope off to 

gently rolling and timbered drainages, all of which contribute water to the Yellowstone River (fig. 7). The Forest 

is characterized by several spectacular canyons through 

sedimentary strata on the west slope, large expanses of 

non-forested vegetation on fine-textured soils derived 

from sedimentary strata, extensive forested land in the 

north and south, and the large Cloud Peak Wilderness 

Area, much of which is above treeline. Many lakes occur in glaciated areas.

The anticlinal mountains were formed during the 

Laramide Orogeny and are composed primarily of igneous 

and sedimentary rocks with a Precambrian granite foundation (fig. 8). Much of the sedimentary rock has eroded 

away to expose the granite, but the northern and southern 

ends of the mountains are still overarched by sedimentary strata (sandstone, shale, dolomite, limestone). Because 

the central granitic block was uplifted to higher elevations, its peaks were glaciated during the Pleistocene. The 

Cloud Peak Wilderness is now centered on these peaks. 

No glaciers reached below 1990 m (6527 ft) and the lower 

ends of the canyons retain their angular, preglacial form. 
USDA Forest Service RMRS-GTR-140. 2005 7

Tilted sedimentary rock layers form steep flatirons and escarpments on the eastern and western flanks.

Soils derived from the granite are acidic, shallow, 

coarse-textured, and low in nutrients. Shale-derived 

soils are deep, fine-textured, high in nutrients, and acidic to neutral. Soils derived from interbedded limestone, 

sandstone, and dolomite are of intermediate texture, basic, and high in nutrients (Despain 1973; Nesser 1986).

As with other portions of the Rocky Mountains, the 

climate of the BNF varies greatly with elevation and topographic position (fig. 9). The lowlands east and west 

of the Bighorns are dry, with a mean annual precipitation from 28 to 38 cm (11-15 inches) on the plains to the 

east and 13 to 18 cm (5-7 inches) in the drier Bighorn 

Basin to the west. In the mountains, precipitation averages about 38 cm (15 inches) at the lower limits of tree 

growth on the eastern foothills and increases to about 63 

cm (25 inches) at higher elevations (Nesser 1986). At the 

highest elevations, cumulative snowfall is 400-500 cm 

(157-197 inches) from October to May, with an average 

snowpack depth of 178 cm (70 inches). Temperatures 

range from –40o C to 43oC, with an annual mean of 8oC 

at Hyattville in the foothills at 1371 m (4497 ft) to 1oC 

at Burgess Junction on the plateau at 2458 m (8085 ft). 

Frost can occur during any month of the year at higher 

elevations. Mean annual air temperature decreases about 

1.5oC per 300-m (984-ft) increase in elevation (Nesser 

1986). South slopes are considerably warmer and drier 

than north slopes or creek bottoms, causing great spatial variability in the distribution of different vegetation 

types. The western side of the BNF receives less precipitation than the eastern side because it lies within the rain 

shadow of the higher Absaroka Mountains to the west as 

well as the rain shadow of the Bighorn Mountains, which 

intercepts moisture caused by upslope air circulation 

from the east (fig. 9). Cloud Peak also appears to create a 

rain shadow to the southeast (Despain 1973).

Historically, the Rocky Mountain region has experienced great climatic and geological changes over time 

scales of millions of years (table 1). Driven by these 

Bighorn National Forest 

N 

SHERIDAN

COUNTY

Buffalo

Greybull 

Lovell

Sheridan 

Worland

14

14

16 

JOHNSON

COUNTY

MONTANA

WYOMING

BIG HORN

COUNTY

WASHAKIE

COUNTY

Wyoming

ALT

Figure 5—Location of the Bighorn National 

Forest in northcentral Wyoming.
8 USDA Forest Service RMRS-GTR-140. 2005

Figure 6—Elevation contours in meters on the 

Bighorn National Forest. Source: U.S. Geological 

Survey

Figure 7—Stream network and numbered watersheds on the Bighorn National Forest. Source: 

U.S. Geological Survey
USDA Forest Service RMRS-GTR-140. 2005 9

Figure 8—Land type associations (based on soils, topography, and geology) on the Bighorn National Forest. Source: Integrated 

Resources Inventory Center 1999
10 USDA Forest Service RMRS-GTR-140. 2005

changes, the vegetation of the region also changed. By 

the beginning of the Quaternary period, approximately 

2 million years ago, many of the species present today 

were in place (Tidwell 1975). From approximately 2 million to 10,000 years ago, during the Pleistocene epoch, 

several glacial advances and retreats (table 1) affected 

both the topography and vegetation in the center of the 

Bighorn Mountains (Nesser 1986). Since the end of the 

Pleistocene around 10,000 years ago, shifts in climate 

have continued, often triggering changes in the spatial and 

elevational distribution of many plant species (table 1).

The dramatic changes in climate have important implications for HRV analyses. Foremost, by considering 

variation observed in the past 300 years we are considering only a short period in the history of BNF ecosystems. 

Soils, for example, surely develop over a longer time 

period. Moreover, future climatic conditions may be different from those of the past, even without the potential 

for human-caused global warming.

3.2 Ecological Setting

Various classification systems have been applied to the 

upland vegetation of the BNF (table 2). On a broad scale, 

the vegetation is classified as part of the Southern Rocky 

Mountain Steppe-Open Woodland-Coniferous Forest 

Province (Bailey and others 1994). At an intermediate 

scale, the vegetation can be classified by the dominant 

overstory species, which is the approach adopted for the 

BNF. Using this intermediate system, the most dominant 

forest cover types are lodgepole pine and Engelmann 

spruce-subalpine fir (Picea engelmannii-Abies lasiocarpa) (fig. 10). Ponderosa pine, aspen (Populus 

tremuloides), limber pine (Pinus flexilis), and Douglas-fir 

(Pseudotsuga menziesii) forests and woodlands are more 

common at low-elevations, but are much less abundant 

(fig. 10). Grasslands (meadows) are scattered throughout the BNF but are more common in the north where 

fine-textured soils are more widespread. Forb-dominated 

Bighorn National Forest Yellowstone National Forest

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J F M A M J J A S O N D J F M A M J J A S O N D

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Lower Timberline, East Side

Eaton Ranch, 1402 m

Subalpine Fir Zone

Burgess Jct., 2450 m

Northeast entrance,

Yellowstone NP, 2240 m

West Yellowstone, MT 2031 m Yellowstone Park, WY 1902 m

Figure 9—Climate diagrams showing mean temperature and precipitation at four weather stations in and near the Bighorn 

National Forest (from Hoffman and Alexander 1976) and three stations in Yellowstone National Park (from Steele and others 1983).
USDA Forest Service RMRS-GTR-140. 2005 11

Table 1—Chronology of some major geologic and climatic events in Wyoming and Colorado, as summarized by Knight (1994a) and 

von Ahlefeldt and Speas (1996). Mybp = million years before present; ybp = years before present.

Time Climate/Geology Vegetation

350 mybp Tropical climate; submerged under saltwater Tropical

300 mybp Swamps, lagoons, tidal flats Clubmosses, horsetails, and ferns in swamps; 

 pine, spruce, and fir on upland

100 mybp Ancestral Rocky Mountains leveled, still near equator

245-66 mybp Overthrust belt formed (about 66 mybp); climate still Magnolia, palm, fig, breadfruit, 

(Mesozoic era) tropical sassafras, cinnamon, sweetgum, and willow 

 in wetlands; conifers, ginkgo, and cycads on 

 uplands

66-50 mybp Mountains of BNF uplifted during Laramide orogeny; Flowering plants more common in upland 

 drifting apart of continents; climate still tropical, forests, species include: alder, beech, birch, 

 snow rare, much wetter than today black locust, chestnut, cottonwood, cyprus, 

 dogwood, elm, fir, ginkgo, hickory, maple, 

 oak, pine, redwood, spruce, sweetgum, 

 sycamore, walnut, and willow; palm and 

 breadfruit also present

50-36 mybp Tremendous erosion, volcanism, and basin filling

10 mybp Regional uplifting creating present mountain landscape

7-5 mybp Increased aridity, creation of rainshadows Demise of some forests, giving rise to shrublands 

 and grasslands; drought tolerant species 

 persisted or immigrated; numbers of xerophytic 

 plants increased in grasslands, fires became 

 more frequent, leading to demise of trees and 

 spread of grassland; woodlands restricted to 

 ravines, valley bottoms, and ridges

660,000 ybp Volcanism (creating Yellowstone plateau); climate 

 cooling, heavy snows, further cooling and formation 

 of glaciers

2 mybp – 10,000 ybp Six glacial advances and retreats; flooding, creation Coniferous forests, shrublands, and grasslands 

(Pleistocene epoch) of outwash plains, loess, and soil development (many broad-leaved trees now regionally 

 extinct)

127,000 ybp Interglacial period Douglas-fir and limber pine common in 

 Yellowstone 

15,000 ybp Glacial advance; temperatures 10-13o C colder than Trees in Yellowstone confined to a narrow 

 today; permafrost elevational band; lowlands tundra-like 

11,500 ybp Temperatures 5-6o C cooler than today; retreat of Upper treeline about 600 m (1968 ft) lower 

 glacial ice than today in Yellowstone; gradually colonized

 by Engelmann spruce, and later by subalpine 

 fir and whitebark pine in some areas 

 (11,000-9500 ybp)

9500 ybp Continued warming Establishment of lodgepole pine at higher 

 elevations and Douglas-fir in foothills in 

 Yellowstone

9000-7000 ybp Upper treeline at its lowest in Colorado Front 

 Range 

7000-4000 ybp Altithermal period, comparatively warm and Expansion of sagebrush, greasewood, juniper, 

 dry conditions and grasses; spruce and fir retreated to higher 

 elevations; elevational range of spruce and fir 

 reduced

4000 ybp – present Neoglacial period of gradual cooling Expansion of forests to previous elevational 

 ranges; ponderosa pine expanded into the 

 Bighorn Mountains during the last 2000 years 

 (Jodi Norris, personal communication).

Ca. 1350 – 1500 AD Characterized by cooler temperatures, but also Probable glacial advances in the mountains 

and 1700 – 1900 AD long, severe droughts (Gray 2003; Gray and 

 others 2004)

1850 AD – present Generally warmer and wetter; 20th century warmer Increased tree recruitment near upper treeline 

 than previous 1000 yrs, but less severe droughts (Hessl and Baker 1997), in subalpine meadows 

 than in previous centuries (Gray and others 2004) (Jakubos and Romme 1993) and in montane 

 forests (Savage and others 1996)
12 USDA Forest Service RMRS-GTR-140. 2005

areas (mapped with willows in fig. 10) are mostly in the 

alpine and subalpine meadows. Shrublands containing 

mountain big sagebrush (Artemisia tridentata ssp. vaseyana) are common. Juniper (Juniperus osteosperma) and 

shrublands dominated by curlleaf mountain mahogany 

(Cercocarpus ledifolius) can be found on the BNF, but 

they are more common in the foothills outside the Forest 

boundary.

More detailed vegetation classifications have been 

developed for the BNF. As in other parts of the Rocky 

Mountains (Moir 1969; Loope and Gruell 1973; Whipple 

and Dix 1979; Despain 1983, 1990; Lotan and Perry 

1983; Peet 1988), large areas are dominated by forests 

of lodgepole pine (fig. 10). Compared to the Medicine 

Bow National Forest in southeastern Wyoming, there 

is a lower tree basal area per hectare in the spruce-fir 

zone and more of the lodgepole pine stands on the BNF 

are self-perpetuating rather than seral to Engelmann 

spruce and subalpine fir (Hoffman and Alexander 1976, 

Despain 1973). Hoffman and Alexander (1976) described six principle forest series on the BNF, based 

on overstory dominants, and 15 habitat types, based 

on overstory dominants and understory indicator species (after Daubenmire and Daubenmire 1968; table 2). 

Proponents of the habitat type approach contend that, 

while the spatial distribution of each tree species is controlled by factors such as elevation and topographic 

position, the understory species are better indicators of 

soils and microclimatic conditions. Also, such classifications focus on the potential natural vegetation given long 

periods without disturbance, rather than the actual vegetation at the present time.

Because of concerns about protecting riparian habitats, 

Girard and others (1997) developed a detailed classification system for riparian vegetation on the BNF that 

included 53 plant communities. Each community was 

placed into the following broader classification based on 

the dominant riparian species: sedge (Carex sp.), grass, 

Booth’s willow (Salix boothii), Geyer’s willow (Salix 

geyeriana), planeleaf willow (Salix planifolia), wolf’s 

willow (Salix wolfii), other willows (Salix spp.), shrubby 

cinquefoil (Potentilla fruticosa), narrowleaf cottonwood 

(Populus angustifolia), aspen (Populus tremuloides), 

lodgepole pine, and Engelmann spruce.

About 62% of the BNF is forested (USDA Forest 

Service 1994) and rock type has a strong effect on the 

location of forests (Despain 1973). On sedimentary substrates, forests cover less than 50% of the area and are 

composed of Douglas-fir or Engelmann spruce and subalpine fir. On granitic substrates, forests cover over 80% 

of the land area and are dominated by lodgepole pine 

at mid-elevations and Engelmann spruce and subalpine 

fir at higher elevations (Despain 1973). The environmental preferences of some shrubs, forbs, and grasses 

species are described by Despain (1973) and Hoffman 

and Alexander (1976).

Thirty-seven percent of BNF forests have been judged 

suitable for timber harvesting (102,645 ha [253,533 

acres]; BNF data). About 25% of this suitable land was 

subjected to tie hacking from 1893 to 1939 (R. Laurent, 

Table 2—Vegetation of the Bighorn National Forest, as classified at various levels of detail. Source: BNF

This report BNF (dominant species) Hoffman and Alexander 1976

High-elevation forests Engelmann spruce-subalpine fir 3 subalpine fir habitat types

1 Engelmann spruce habitat type

Lodgepole pine 2 lodgepole pine habitat types

Low-elevation forests and woodlands Ponderosa pine 5 ponderosa pine habitat types

2 Douglas-fir habitat types

Douglas-fir 

Limber pine

Rocky Mountain juniper

Aspen and riparian forests Aspen 1 aspen habitat type

Cottonwood

Willow

Non-forest vegetation (grasslands, Grasslands: fescue, oatgrass, tufted 

shrublands, and forblands, including hairgrass, bluegrass, wheatgrass, needle 

alpine vegetation) and thread, kobresia, bluejoint reedgrass, 

rushes, sedges, general

Shrublands: sagebrush, mountain 

mahogany, bitterbrush, skunkbrush, 

shrubby cinquefoil, general

Forbland: forb willow, general 
USDA Forest Service RMRS-GTR-140. 2005 13

Figure 10—Vegetation cover types on the Bighorn National Forest. Source: BNF
14 USDA Forest Service RMRS-GTR-140. 2005

BNF archaeologist, and B. Bornong, BNF ecologist, personal communication). Another 15% of the suitable land 

has been subjected to harvesting by European-Americans 

since 1940 (BNF data; excluding previously tie-hacked 

forests). Thus the total area known to be affected by harvesting is about 40% (though this estimate drops slightly 

when numbers are adjusted to account for the fact that 

some old harvests occurred on unsuitable land—about 

5900 ha [14,573 acres]). About 23% of the tie hacked 

forests were harvested again after 1940. Including these 

tie hacked forests, harvests after World War II had affected about 21% of the suitable land base by 1998.

When discussing each variable, we addressed four 

broad landscape types: (1) high-elevation forests (i.e., 

spruce-fir/lodgepole pine forests in the upper montane 

and subalpine, 49% of the BNF); (2) montane forests 

and woodlands at lower elevations, 12% of the BNF 

(i.e., Douglas-fir, ponderosa pine, limber pine); (3) aspen woodlands, 1% of the BNF; and (4) non-forest 

vegetation, namely, upland grasslands, forblands, shrublands, and juniper woodlands (24% of the BNF). The 

remainder of the Forest is wetlands or barren habitats 

with little or no vegetation. Note that high-elevation 

forests are not defined by an elevation boundary, but 

rather are all spruce-fir or lodgepole forests on the BNF. 

Similarly low-elevation forests are all of the Douglas-fir, 

ponderosa pine, or limber pine forests/woodlands. These 

landscapes could be broken into smaller classification 

units, as there certainly are important ecological distinctions between different habitat types and community 

types within each of the general forest types. However, 

the differences blur over the long time periods of HRV 

analyses. Furthermore, because of successional relationships between lodgepole pine, subalpine fir, and 

Engelmann spruce, and in some areas between Douglasfir and ponderosa pine, it is difficult to discuss the HRV 

separately for each overstory cover type.

3.3 Cultural Setting

For centuries humans have lived and traveled 

throughout the area that is today the BNF (Murray 

1980). Consequently, managers have inherited the legacies of past land uses and are not starting with a “blank 

slate” (Romme and others 2000). This is important 

for several reasons. First, our ability to interpret preEuropean-American conditions will be limited by events 

caused by Native Americans during the last several centuries or more. Also, it is difficult to distinguish events that 

were “natural” from those caused by Native Americans. 

In fact, it may be necessary and even desirable to include 

some human influences as a factor affecting the HRV. 

However, many of the unprecedented human influences 

of European-Americans have left legacies that present 

unique challenges for managers. Because human land 

uses on the BNF have changed over time, we provide a 

brief summary of three periods that relate to natural resource management.

3.3.1 Historic Period (1600-1890)

The first and earliest time period is from about 1600 

to 1890, a period when European-Americans had not yet 

impacted the area to any extent (Martorano and others 

1985). During the early years of this period, the Shoshoni 

and Comanche tribes occupied the Bighorn Basin and 

Bighorn Mountains (Murray 1980), practicing a mixed 

hunting/foraging lifestyle. The mountains were most 

likely used during the summer to escape the heat at low 

elevations, to hunt or trap the abundant bison and elk, and 

to obtain medicinal and food plants. As evidenced by the 

Medicine Wheel constructed during this period (sometime after 1620) on the west side of the Bighorns, the 

mountains were also used for ceremonial purposes (R. 

Laurent, BNF archeologist, personal communication).

By 1812 the Crows (or Absaroka) had obtained horses 

and guns and were in control of the Bighorn Mountains. 

The Cheyenne and Arapaho later fought the Crows and 

succeeded in gaining some control of the land (Scott 

1981). With the decline of bison in the east, the Dakota 

(Sioux) tribe also began to move into the region, forming an alliance with the Cheyenne and Arapaho and 

forcing the Crow and other tribes to retreat. Thus, the 

Bighorn Mountains were part of an Indian “war” ground 

between 1830 and 1860. Away from a tribes’ established 

hunting territory, war zones probably provided a refuge 

for the hunted game species (Scott 1981; Martin and 

Szuter 1999). For short periods in the fall, tribes from 

the west, such as the Shoshone, would use the area as a 

hunting ground, but hostilities prevented long-term use. 

The impacts of these early inhabitants on the landscape 

are largely unknown, but, except for a few intentional or 

unintentional fires, impacts were likely minor and probably were limited primarily to foothills, riparian areas, 

and travel routes. Grasslands and big game animals were 

abundant in the mountains, and so intentional Indian-set 

fires were probably not as common as in other parts of 

the Rocky Mountains (R. Laurent, BNF archeologist, 

personal communication) where fire was helpful for creating openings that would attract game. Notably, Baker 

(2002) concluded that, for Rocky Mountain landscapes 

in general, Native Americans had little effect on fire regimes in lodgepole and spruce-fir forests.

In general, Native American influences probably had less impact than those of others that gained 
USDA Forest Service RMRS-GTR-140. 2005 15

control of the region (R. Laurent, personal communication). Native Americans usually harvested small trees 

that would meet their needs, such as for lodge poles, and 

impacts from their harvesting were undoubtedly minor. 

Native Americans could have started fires that burned 

over large areas, and this may have been their greatest 

influence on the landscape, but such fires also were ignited by lightning.

Beginning in the early 1800s, trappers and adventurers began to explore the Rocky Mountain West. Human 

land uses probably remained fairly minor during this 

time, primarily because travelers in the region would 

follow routes around rather than through the mountains. 

Forts and camps were also on the plains rather than in 

the mountains (Murray 1980; Conner 1940), although 

some wood was cut from low-elevation forests. Conner 

(1940) reported that, following the Battle of the Little 

Big Horn of 1876, the Sioux Indians retreated into the 

Bighorn Mountains and set a large forest fire. However, 

the age of the trees in the area does not support this claim. 

More likely, the fire occurred on the adjacent plains (R. 

Laurent, BNF archeologist, personal communication).

Because of the low density of beaver in the area, fur 

trading in the Bighorn Mountains was relatively minor 

(Martorano and others 1985). Numerous prospectors entered the Bighorns but none stayed long. In the 1870s, 

after most of the bison were gone (last one seen in the 

early 1880s; Murray 1980), the Bozeman and Oregon 

Trails brought cattle and sheep ranching into the nearby 

plains and settlements such as Sheridan, Story, Buffalo, 

and Tensleep sprang up. Grazing and sawmill operations 

did not begin inside the present BNF boundaries until 

the mid-1880s (Martorano and others 1985).

3.3.2 European-American Settlement and 

National Forest Administration (1890-1945)

The second period of human occupation, 1890 to 1945, 

began with the arrival of large numbers of EuropeanAmericans. In the 1890s, livestock grazing increased 

and lumber mills and gold mining towns (such as Bald 

Mountain), were established within the area that would 

become the BNF (Martorano and others 1985). Due to 

poor results, most mines closed less than a decade later. Mining activity was marginal thereafter. From 1893 to 

the 1920s, the cutting of railroad ties (tie hacking), posts, 

poles, and fuelwood was practiced in low and high-elevation forests (Murray 1980; Martorano and others 

1985). Tie hacking occurred on about 25,500 ha (62,985 

acres) of the forest, with some of the harvesting resembling small, 0.2 ha [0.5 acre] clearcuts. Elsewhere the 

harvesting was more selective (R. Laurent, BNF archeologist, personal communication). Northern watersheds of 

the Tongue River, Wolf Creek, Sheep Creek, Big Goose 

Creek, and Little Bighorn River were affected (drainages 

2, 3, and 4 on fig. 7; Granum 1990).

In the mid-1920s to late 1930s, tie hacking was extensive in two high-elevation watersheds in the southern 

BNF—Clear Creek and Sourdough Creek watersheds 

(drainages 7 and 8 on fig. 7; USDA Forest Service 

1997). Lodgepole pine trees of 28-45 cm (10-18 inches) 

diameter at breast height (dbh) (usually over 150 years 

old; Jack 1900) were often selectively cut for railroad 

ties, which left only trees too large or too small for ties 

and trees that had defects. About half of the wood in a 

tree was “wasted” (Martorano and others 1985), and selective cutting left trees of less value for lumber until 

the next disturbance (Howe 1997). The rate of timber 

harvesting gradually dwindled in the 1940s until after 

World War II (USDA Forest Service 1985).

To deliver logs to sawmills from high elevations, water 

was diverted from streams into large wooden tie flumes 

built above streams (Granum 1990). Later, in the 1920s, 

dams were built on some streams to provide streamflow 

adequate to float logs downstream. Riparian vegetation 

was undoubtedly damaged during this time (Martorano 

and others 1985; USDA Forest Service 1997).

The frequency of human-caused fires probably 

increased with the arrival of European-Americans, primarily due to accidents associated with saw mills and 

the dwellings of the workers. Ember-producing wood 

stoves were used for heat during the winter. In the summer of 1898, about 21,000 ha (51,870 acres) of the 

forests burned, 9,000 ha (22,860 acres) of which were 

purportedly caused by a shepherd’s campfire near Piney 

and Little Goose Creeks (Town 1899). The causes of 

other fires that year are unknown (although Town reported rumors that Indians had set them).

From 1890 to the early 1900s, the native herbivores 

(elk, deer, bighorn sheep, pronghorn antelope, and bison) and furbearers (pine marten, beaver) were hunted 

for eastern markets and sport (Dary 1986). Some species were driven to near extinction; the elk disappeared. 

Populations of native predators, such as wolves, mountain 

lion, lynx, and grizzly bear, were also decimated during 

this time by poisoning and shooting. Simultaneously, 

domestic livestock grazing was extensive and uncontrolled until 1899. Town (1899) estimated 3000 cattle 

and 450,000 sheep on the Forest Reserve in 1898. There 

were many more by 1900, when Jack (1900) concluded that the BNF was badly overgrazed south of the 13th

standard parallel.

Concerns about grazing, timber harvesting, fire, and 

water quality led to the establishment of the Bighorn 

Forest Reserve in 1897 by President William McKinley. 
16 USDA Forest Service RMRS-GTR-140. 2005

Year

190019101920

1930

19401950

19601970

1980

1990

Population estimates of elk and deer

0

5000

10000

15000

20000

25000

30000

35000

40000

elk

mule and white-tailed deer

Year

190019101920

1930

19401950

19601970

1980

1990

Population estimates of bighorn sheep

0

100

200

300

400

500

600

700

800

900

1000 bighorn sheep

before aerial census increase in census 

sophistication for deer 

only adult elk 

from 1983 on

Figure 11—Population estimates for elk and deer (left axis), 

and bighorn sheep (right axis), on the Bighorn National 

Forest. Source: USDA Forest Service 1984, 1994; and 

1909-1929 annual wildlife reports for the BNF 

Year

1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

Million board feet

0

5

10

15

20

25

Figure 12—Wood harvested (million board feet) each year 

on the Bighorn National Forest from 1905 to 2002. Source: 

BNF

More careful attention was given to finding the best 

ways to avoid depleting and destroying valuable natural 

resources (Pinchot 1907). Because fire was personified 

as the “enemy” to forest managers, fire suppression became a primary objective (Town 1899; Conner 1940). 

Grazing permits also were required and sheep grazing 

was reduced to 150,500 head in 1899. However, the 

number of sheep permitted to graze on the Reserve increased again to 374,734 in 1904, and the number of 

cattle permits increased from 3000 to over 30,000 during 

the same period. The number of sheep often exceeded 

permitted levels. Uneven livestock distribution led to 

overgrazing in some areas but not elsewhere. In 1907, 

approximately 16,000 ha (39,520 acres) of the Forest 

(22% of the grasslands) were used by cattle and 24,000 

ha (59,280 acres) (34% of the grasslands) were used by 

sheep (Conner 1940, Martorano and others 1985). The 

Reserve became Bighorn National Forest in 1905, but 

over a decade passed before grazing became more tightly controlled and various kinds of range improvements 

were attempted (including fencing and the provision of 

water). Grazing continued to increase until 1919, when 

the number of livestock was reduced to about 117,000 

sheep and between 36,000 and 48,500 cattle. In 1931, 

sheep grazing was 126,765 head for a 2.5 month season and cattle use was 32,352 head for 3.5 months. By 

2002 the number of cattle was slightly lower (28,025) 

but sheep use had declined by nearly 90%, to 13,830 

animals.

Demand for tourism increased in the 1910s and 1920s 

and resort hotels and dude ranches flourished, such as 

Arrowhead Lodge, Dome Lake Club, Eaton Ranch, and 

Paradise Guest Ranch (BNF Historical Files). Roadbuilding became a major activity on the Forest, primarily 

to assist tourism and fire-fighting (Martarano and others 

1985). Wildlife management improved and elk were reintroduced beginning in 1909 (fig. 11).

3.3.3 Post-World War II (1945 to present)

The post-World War II period was characterized by 

new technology that rapidly increased the rate of human 

modifications of the landscape. The rate of timber harvesting was slow in the 1940s and 1950s (fig. 12), but 

large clearcuts were common in the 1960s and 1970s 

(fig. 13). New levels of prosperity created larger markets for timber than ever before and the creation of new 

stands of rapidly growing, economically valuable trees 

became a common goal (Langston 1995). The cutting 

of larger trees was encouraged. Gasoline-powered sawmills, some that were portable, had been in use since the 

1920s, and they now became more common. Also, additional road construction occurred in the 1950s, making 

more of the forest accessible for fire-fighting and timber 

harvest. By 1960, aerial techniques improved dramatically attempts to suppress fires (Martorano and others 

1985). Desires to harvest older stands with slow tree 

growth and remove stands that had been affected by tie 

hacking (in which the poorest quality trees were left 

to reproduce) made clearcutting an attractive practice. 

Throughout the National Forest System at this time, the 

old forests commonly were viewed as decadent, with the 

best prescription thought to be a clearcut to establish a 
USDA Forest Service RMRS-GTR-140. 2005 17

Figure 13—Location of different timber harvest types on the Bighorn National Forest. (A) All harvest types except tie hacking. (B) Clearcuts by decade (next page). Some areas had been affected by fire before they were 

cut. See fig. 7 for watershed boundaries and appendix A for problems known to be associated with the map 

polygons. Source: BNF
18 USDA Forest Service RMRS-GTR-140. 2005

Figure 13—Continued.
USDA Forest Service RMRS-GTR-140. 2005 19

Decade

1940 1950 1960 1970 1980 1990

Mean patch size (ha)

0

10

20

30

40

50

200

300

400

500

600

700

800 Clearcuts

All fires

Intense fires

1940 1950 1960 1970 1980 1990

Maximum patch size (ha)

0

100

200

300

400

500

4000

6000

8000

10000

12000 Clearcuts

All fires

Decade

Figure 14—Mean and maximum patch sizes of clearcuts compared to fires on the Bighorn National Forest by decade. 

A clearcut patch was defined as an area clearcut over a 

month period that created one contiguous patch. An intense 

fire had flame lengths >0.6 m (2 ft). To convert hectares to 

acres, multiply by 2.47. Source: BNF; fires for top graph 

from 1970-1996 fire database; data for bottom graph from a 

map of fires for each decade 

Timber harvest activity on Bighorn NF

pre-1960 1960 1970 1980 1990

Hectares

clearcut

seed tree

shelterwood

selection

thinning

Hectares

Site activity on Bighorn NF

7000

6000

5000

4000

3000

2000

1000

0

7000

6000

5000

4000

3000

2000

1000

0

pre-1960 1960 1970 1980 1990

salvage

reforestation

site preparation

(mechanical or burn)

reduced fuels

(pile burn)

Figure 15—Area on the Bighorn National Forest affected by 

timber harvesting and other related activities by decade 

from 1940 to 1999. Data prior to 1960 are incomplete and 

do not include tie-hacking. To convert hectares to acres, 

multiply by 2.47. Source: BNF

new stand of rapidly growing trees that could be more 

easily subjected to thinning and other management activities (Langston 1995).

Ten of the 12 major watersheds on the BNF have 

been subjected to logging in the past 40 years (fig. 13). 

Almost half of this logging was in the form of dispersed 

clearcuts. Clearcuts averaged 22 ha (54 acres) in the 

1960s, but were smaller in the 1980s and 1990s, averaging 8 ha (20 acres) (fig. 14). Shelterwood, group, 

and individual selection silvicultural systems became 

popular in the 1970s (fig. 15), though such methods 

sometimes increased the chances of windthrow (USDA 

Forest Service 1994).

The target rotation time for high-elevation clearcuts 

typically has ranged from 60 to 180 years on the BNF 

(USDA Forest Service 1985). Most of the timber was 

harvested in high-elevation forests dominated by lodgepole pine, Engelmann spruce and subalpine fir. At 

lower elevations, some Douglas-fir was logged (580 ha 

[1433 acres], or about 3% of total wood harvested), but 

ponderosa pine and limber pine have been harvested on 

only about 14 ha (35 acres) (0.0007% of wood harvested) on the BNF. Harvest rotation times for low-elevation 

forests were set at 80 to 100 years in 1985 (USDA Forest 

Service 1985). Tree regeneration, especially in sprucefir forests on sedimentary soils, often has not met the 

standards of the National Forest Management Act and 

thus, tree planting was and is required on about 30% of 

the land harvested in the BNF (USDA Forest Service 

1994; fig. 15). To reduce fuels or prepare sites for regrowth, thinning has occurred on 5.5% of the forested 

area and prescribed burning has occurred in about 2% of 

the forests (fig. 15).

Domestic grazing has declined in the region during 

the last 60 years, due largely to a dramatic reduction 

in sheep grazing (Cochrane and others 1988), from 

126,765 head in 1931 to 13,830 in 2002. The number 

of cattle grazing on the BNF was similar in the 1980s to 

the 1930s (33,000). Wild herbivores such as deer and elk 

increased during the early part of this period (up to the 

1960s; fig. 11). Bighorn sheep have been re-introduced 

periodically (fig. 11), but in 1999 their population was 

down to 20, probably due to disease transmission from 

domestic sheep (B. Bornong, BNF ecologist, personal 

communication). Moose were introduced in the 1950s, 

reaching a population of over 400 by 1994 (USDA 
20 USDA Forest Service RMRS-GTR-140. 2005

Forest Service 1994). Deer peaked in the 1960s and then 

declined, possibly caused by lower winter habitat quality resulting from fire suppression, tree encroachment, 

and other habitat alterations (Leege and Hickey 1971; 

Hobbs and Spowart 1984; B. Jellison, Wyoming Game 

and Fish Department biologist, personal communication). In 1984, winter carrying capacity on the Forest for 

deer and elk was estimated to be only 1053 and 544, respectively (USDA Forest Service 1985). Many animals 

migrate off the BNF during the winter. Winter rather 

than summer habitat tends to limit the ungulate populations in the region (Davis 1977).

Although levels of timber harvest have declined in 

the last decade (fig. 15), many human influences still affect the BNF. Imprints of timber harvesting over the last 

50 years are conspicuous in some areas (fig. 13), and 

clearcut or group selection harvesting is still common 

(though with greater sensitivity to wildlife and aesthetic 

values). The road system is now extensive in most watersheds away from the Cloud Peak Wilderness and steep 

canyons (fig. 16). Notably, an important effect has been 

the influence of people from throughout the nation who 

are engaged in a wide range of recreational activities. 

Due to accessibility and the popularity of outdoor recreation, such influences can have widespread impacts.

Figure 16—Location of roads on 

the Bighorn National Forest. 

Source: BNF
USDA Forest Service RMRS-GTR-140. 2005 21

4. Dominant Plant Distribution 

and Successional Patterns Along 

Ecological Gradients

4.1 Dominant Plant Distribution Patterns

Vegetation zones on the BNF are distributed as in other parts of the Rocky Mountains. At the lower elevations 

(1324-1846 m [4356-6072 ft]), ponderosa pine forests 

or savannas occur in the foothills (fig. 10 and Despain 

1973), extending down to the alluvial fans where they 

are bordered by grasslands and woodlands. Ponderosa 

pine forests are nearly absent on the drier, western flanks 

of the range, where a well-developed juniper-sagebrush 

plant association replaces the ponderosa pine or is situated between the pine and the grasslands below. On the 

western flanks, the lowest closed forest type is Douglasfir, which grows along the north-facing sides of canyons. 

Curlleaf mountain-mahogany is common on rocky, calcareous soils in the foothills of the mountains, though 

mostly outside the Forest boundary. At slightly higher 

elevations on the eastern flanks of the Bighorns, from 

2000 to 2300 m (6560-7544 ft) elevation, Douglas-fir 

forests become more common, occurring between the 

Figure 17—Relationship of forest community types, elevation, and substrate in the Bighorn Mountains. The curves were 

smoothed with a moving average (n = 3). After Despain (1973).

lodgepole pine forests above and ponderosa pine woodlands below. Higher on the mountain, from 2150 to 2900 

m (7052-9512 ft), lodgepole pine is common and creates 

an almost continuous forest on soils derived from granite 

(fig. 17). Above the lodgepole pine, from 2500 to 2900 m 

(8200-9512 ft), forests dominated by Engelmann spruce 

and subalpine fir are more common where tree growth is 

possible. The lodgepole pine and spruce-fir forests that 

occur at mid- to high-elevations are commonly known 

as upper montane or subalpine forests. Interspersed with 

the forests are extensive subalpine meadows, and above 

the subalpine forests is a large alpine zone, especially in 

the Cloud Peak Wilderness.

Soils strongly affect plant community composition on 

the BNF. Woodlands dominated by juniper and curlleaf 

mountain-mahogany are common on very shallow, sedimentary soils or fractured bedrock in the dry foothills 

above the Bighorn Basin (fig. 17; Despain 1973; Knight 

and others 1987). The mountain-mahogany communities 

are most common on calcareous soils derived from dolomite, red shales, and sandstones. Douglas-fir thrives on 

soils derived from limestone or dolomite and is rare on 

soils derived from granite (fig. 17 and Despain 1973). In 

lower parts of the Douglas-fir zone, limber pine ranges 

from a minor to a dominant overstory species on the dry, 
22 USDA Forest Service RMRS-GTR-140. 2005

rocky and often sedimentary soils of windswept ridges 

and the sides of canyons where other species are not able 

to survive (Despain 1973; Nesser 1986). Limber pine 

tends to be found on exposed ridges and south-facing 

slopes, partially because the Clark’s nutcracker prefers 

such habitats for its food caches—which are composed primarily of limber pine seed (Tomback 1983). 

Spruce-fir forests are best developed in the northern part 

of the Forest, especially on shales (figs. 8 and 10, and 

Despain 1973). Lodgepole pine is more common on 

granitic soils and only infrequently is associated with 

Engelmann spruce and subalpine fir on soils derived 

from sandstone (figs. 8 and 10, and Despain 1973).

An interesting feature of the Bighorn Mountains is 

the numerous sharp boundaries between grassland and 

forest, particularly in the northern part of the forest 

(Despain 1973). Such boundaries appear to be caused 

by differences in soil texture, with forests occurring on 

the more coarse soils and meadows on finer textured 

soils. The physical location of many mountain meadows and grasslands appears to be quite stable (Despain 

1973). In some instances, however, changing climatic 

conditions or other factors have allowed tree seedling 

establishment on areas that were historically dominated by grasses and forbs (Jack 1900; Bornong 1996a). 

Similarly, lodgepole pine has invaded some subalpine 

meadows in Yellowstone National Park (Jakubos and 

Romme 1993). Also, Douglas-fir is invading meadows 

in southwestern Montana (Arno and Gruell 1986), and 

subalpine fir and Engelmann spruce seedlings are becoming established near treeline in Rocky Mountain 

National Park in Colorado (Hessl and Baker 1997). Of 

course, the converse could be true as well, with climatic conditions following forest disturbances leading to 

the development (at least temporarily) of a mountain 

meadow. While edaphic conditions appear to be very 

important in causing forest/meadow boundaries, climate 

change appears to be influential as well.

The extensive montane grasslands of the BNF tend to 

occur on fine-textured sedimentary soils, mostly at lowelevations with low precipitation (<2300 m [7544 ft]) 

or at high-elevations too cold or snow-covered for too 

long to support continuous forests (>2750 m [9020 ft]; 

Jack 1900; Despain 1973). Idaho fescue (Festuca idahoensis) is the most common grass from 1840 m (6035 

ft) to about 3000 m (9840 ft) (timberline). Bluebunch 

wheatgrass (Elymus spicatum) dominates the grasslands 

at lower elevations. Both grasses also can be found with 

curlleaf mountain-mahogany and big sagebrush. The 

relatively high precipitation on the east slope has resulted in more forest there than on the west side, even on 

sedimentary substrates (Despain 1973).

Aside from elevation and soils, the distribution of 

lodgepole pine, subalpine fir, and Engelmann spruce 

is affected by moisture availability. Most precipitation 

falls in early spring in the Bighorn Mountains and is not 

evenly distributed (fig. 9). Consequently, less moisture 

is available in the critical summer months, when seedling establishment of Engelmann spruce and subalpine 

fir is limited because of a need for at least 2.5 cm (1 inch) 

of precipitation per month or 1.3 cm (0.5 inch) per week 

during the growing season (Alexander and Nobel 1971; 

Alexander and Sheppard 1984). Even at higher elevations, this level of precipitation often does not occur on 

the BNF. Near Powder River Pass, only 24% of the weeks 

in July and August from 1979-1995 had more than 1.3 

cm (0.5 inch) precipitation per week (Bornong 1996b).

Topographic position also affects moisture availability and thus species distributions. Spruce-fir forest 

is typical on the more mesic sites throughout the BNF, 

such as in ravine bottoms or on north slopes, while 

lodgepole pine is common on drier sites (Despain 1973). 

Small patches of spruce-fir forests occur in ravines at 

lower elevations, where cold air drainage occurs and the 

potential evapotranspiration is low. High-elevation landscapes often have abrupt changes in topography, with 

steep slopes causing many subalpine forests to occur in 

small patches (Knight 1994b; Knight and Reiners 2000). 

Occasionally white spruce (Picea glauca) occurs in the 

subalpine forests, though it is quite rare compared to in 

the Black Hills to the east.

Aspen is not abundant on the BNF (Despain 1973), occurring primarily as small, clonal groves at middle and 

low elevations (but with some extensive groves north of 

Burgess Junction). Aspen is most common on the more 

moist sites characterized by deeper, fine-textured soils 

(Hoff 1957). Aspen reproduction typically is asexual, with new shoots produced from root sprouts (Barnes 

1966; Bartos and others 1991). This, combined with the 

way aspen is able to persist in the understory of some mature forests, explains why aspen tends to develop where 

it occurred previously. Seedlings, though rare, do occur when severe disturbances such as fire are followed 

by the extended moist conditions required for seedling 

establishment (McDonough 1985; Romme and others 

1997). Because of such requirements, sexual reproduction is thought to be episodic (DeByle and Winokur 1985; 

Romme and others 1997). There is considerable genetic 

diversity between clones, with some clones better adapted for high elevations and some responding differently 

to weather conditions than others (Jelinkski and Cheliak 

1992). For example, it is not uncommon to see two adjacent aspen stands (clones) in the fall, one with yellow 

leaves and the other with green leaves.
USDA Forest Service RMRS-GTR-140. 2005 23

In riparian habitats on the western slopes, narrowleaf 

cottonwood (Populus angustifolia) and Rocky Mountain 

maple (Acer glabrum) are common, particularly on soils 

derived from limestone. Only a few isolated stands of 

narrowleaf cottonwood occur on the east slopes of the 

BNF, primarily along the Tongue River and in Crazy 

Woman Canyon.

As with the forests and grasslands, the distribution 

of the various shrublands on the BNF is controlled by 

climate, elevation, and topographic position. Mountain 

big sagebrush (Artemisia tridentata ssp. vaseyana), 

for example, often occurs where moisture is available 

but the soils are well drained and temperatures are not 

too cold (Burke and others 1989). As mentioned, curlleaf mountain-mahogany (Cercocarpus ledifolius) is 

found primarily on rocky, sedimentary substrata (Knight 

1994a). Bitterbrush (Purshia tridentata) is often mixed 

with mountain big sagebrush in the foothills, especially 

where snow accumulates, such as in ravines. At higher 

elevations, in association with sub-irrigated wet meadows, shrublands dominated by mountain silver sagebrush 

(Artemisia cana ssp. viscidula) and shrubby cinquefoil 

(Potentilla fruticosa) are common. Willow-dominated 

shrublands (Salix spp.) are common in riparian zones.

Other vegetation types are found only at high elevations. Where the subalpine and alpine zones merge, 

subalpine fir and Engelmann spruce trees form dwarfed, 

shrubby patches referred to as krummholz. Just above 

this, the alpine vegetation is dominated by grasses, shrubs, 

and forbs that are able to withstand the severe environment characterized by high winds, low humidity, cold 

soil temperatures, high ultraviolet radiation, short growing season, low soil moisture, and great daily temperature 

fluctuations (Bliss 1956; Knight 1994a). The extensive 

alpine zone is one of the primary attractions of the Cloud 

Peak Wilderness, which covers about 13% of the BNF.

Plant species distributions have been changing for 

thousands of years and likely will continue to change 

in the future (table 1). For example, investigators have 

found evidence in the pollen record that the relative abundance and distribution of lodgepole pine, Engelmann 

spruce, and subalpine fir at both the stand and landscape 

scales has shifted due to climate change (Hansen 1940; 

Fall 1997; Whitlock 1993). Recent research suggests 

that ponderosa pine arrived in the Bighorn Mountains as 

recently as 2500 years ago (J. Norris, S. T. Jackson, and 

J. L. Betancourt, paleoecologists, personal communication). As noted previously, HRV reports must, to every 

extent possible, separate climatic effects from management effects.

Some recent changes in vegetation distribution might 

have occurred due to climate change. For example, as 

noted, lodgepole pine, subalpine fir, and Engelmann 

spruce have been observed as saplings in formerly open meadows in the region (Patten 1969; Schimpf 

and others 1980; Pearson and others 1987; Jakubos 

and Romme 1993; Hessl and Baker 1997). Such forest 

encroachment occurs on the BNF (Jack 1900; Bornong 

1996a), although not commonly (Despain 1973); and 

juniper appears to be expanding its range and becoming more dense in the western foothills (mostly outside 

the BNF boundary). Some of these examples of forest encroachment have been attributed, at least in part, 

to warmer and wetter conditions that began in the late 

1800s (fig. 18). Of note, temperature in the BNF was 

higher in the year 2000 than it has ever been during 

the HRV period from 1600 to 1890, or even earlier to 

1200 AD (fig. 19). Nevertheless, the invasion of mountain meadows by trees, due to climate change, probably 

has not been widespread because of the relatively strong 

influence of soil characteristics in maintaining the forest/meadow boundaries of the BNF.

1.7

0.3

1

1500 1600 1700 1800 1900 2000

Temperature Precipitation

Year AD

Ring-width index

Figure 18—Tree-ring-based reconstructions at upper treeline for temperature 

(Powder River Pass) and lower treeline 

for precipitation (west side) in the Bighorn 

Mountains. Values >1 are wetter or warmer 

than average; values <1 are drier or colder 

than average. A cubic spline has been applied and is a mathematical equation that 

smooths the raw data in 25-year periods, 

which helps remove trends unrelated to 

climate. Source: C. Fastie, unpublished, 

and Gray and others 2004
24 USDA Forest Service RMRS-GTR-140. 2005

1.6

0.4

1

1500 1600 1700 1800 1900 2000

Year AD

Ring-width index

1200 1300 1400

Figure 19—Tree-ring-based reconstruction 

of temperature from 1200 AD to the present, before and after application of the 

25-year cubic spline in an Engelmann 

spruce forest at Powder River Pass, 

at tree line, in the Bighorn Mountains. 

Values >1 are warmer than average; values <1 are colder than average. Source: 

C. Fastie, unpublished data

4.2 Successional Patterns

4.2.1 Succession in high-elevation forests

Because of its relative intolerance for the forest understory environment, lodgepole pine traditionally has been 

considered a pioneer or seral species to forests dominated by Engelmann spruce and subalpine fir (Baker 

1949; Lotan and Perry 1983; Lotan and others 1985; 

Parker and Parker 1994). As mentioned, however, some 

of the BNF is too dry to support spruce-fir forests and 

lodgepole pine perpetuates itself in some areas (Despain 

1973). Very old lodgepole pine trees have been found 

in what appear to be stable forests (about 500-year-old 

trees in the North Fork of the headwaters of the Powder 

River; Bornong 1996a). Reproduction occurs in these 

stands after the creation of canopy gaps (Despain 1983). 

In some mesic areas, Engelmann spruce and subalpine 

fir together may be the pioneer species following a disturbance, such as Doyle (1997, 2004) observed in Grand 

Teton National Park. In such situations, regeneration can 

be very slow (Jack 1900; B. Bornong, BNF ecologist, 

personal communication). Although subalpine fir is the 

most shade-tolerant and has the greatest potential to become the dominant species, it is usually a co-dominant 

with Engelmann spruce because spruce lives considerably longer (fir lives up to about 200 years; spruce over 

500 years). On limestone/dolomite substrates at the 

higher end of the elevational range of Douglas-fir, the 

Douglas-fir rather than lodgepole pine can be seral to 

spruce and fir (Despain 1973).

Lodgepole pine is well-adapted to disturbances because it often bears cones that remain closed for many 

years, thereby storing large numbers of seed on a single tree. Known as serotinous cones, they open primarily 

when exposed to higher than normal temperatures, such 

as during a fire or when the cones are near the soil surface (which is warmer than the canopy). Significantly, 

not all lodgepole pine produce serotinous cones and the 

proportion of “closed” and “open” cone trees is highly 

variable (Lotan and Perry 1983; Muir and Lotan 1985; 

Muir 1993; Tinker and others 1994). The resistance of 

lodgepole pine seedlings to cold and dryness (Cochran 

and Bernsten 1973), combined with a history punctuated 

by disturbances over the last 150 years, help explain the 

prevalence of lodgepole pine on the BNF today (33% of 

the BNF land area; fig. 10).

Because there is great variability in rates of forest development, deciding when a subalpine forest reaches “old 

growth” conditions can be difficult. The time required for 

a spruce-fir forest to develop after a fire may range from 

just over 150 years to over 1000 years (Billings 1969; 

Mueggler 1976; Romme and Knight 1981). Villalba and 

others (1994) define “old growth” subalpine forests in 

Colorado as those with at least some trees greater than 

300 years old. Important components of old-growth forest, such as relatively large trees, numerous snags, and 

relatively high amounts of coarse woody debris, may require several centuries to develop (Rebertus and others 

1992). Mehl (1992) also developed criteria for defining old-growth forests in the Rocky Mountain region, 

but he did not specify that Rocky Mountain old-growth 

forests should be at least 300 years old. Instead, he concluded that the stands should be 150 to 200 years old, 

depending on species, and have large trees for the species and site, high variation in tree sizes and spacing, 

presence of standing and downed dead trees, decadence 

in the form of broken or deformed tops or bole and root 

decay, multiple canopy layers, gaps in the tree canopy, 

and understory patchiness. He provides minimum oldgrowth criteria for different forest cover types, which 

BNF managers are currently using when defining oldgrowth forests.

The BNF’s forest inventory is not yet complete (only 

50% of spruce-fir stands and 67% of lodgepole pine 

stands have been surveyed), so it is not now certain what 
USDA Forest Service RMRS-GTR-140. 2005 25

proportion of the forests are classified appropriately as 

“old-growth.” The inventory incorporates Mehl’s age 

and size criteria, which are that spruce-fir stands should 

be >200 years with trees >41 cm (16 inches) dbh, and 

lodgepole should be >150 years with trees >25 cm (10 

inches) dbh. When the entire forest was classified with 

photo interpretation using tree crown size, only 5% of 

the forested land was classified as old-growth. This estimate probably will change when the old-growth forest 

inventory is completed.

The HRV for succession and successional processes 

during the reference period for both individual stands 

and the landscape surely would have been quite broad. 

Different sites on any specific burn can experience different successional trajectories, resulting in doghair stands 

of lodgepole pine in some areas, stands of average or below average tree density elsewhere, and a full variety of 

combinations of invading aspen, spruce, fir and lodgepole pine across the landscape (Stahelin 1943; Turner 

and others 1997; Reed and others 1999). Moreover, 

secondary succession initiated today could have quite 

different trajectories than 200-300 years ago because of 

the warmer and sometimes wetter climatic conditions 

of the last century (fig. 18). Franklin and Laven (1989) 

stress that forest development is not unidirectional, as 

moderate disturbances such as a minor wind storm or 

surface fires can set back succession to an earlier stage 

or create alternative pathways of succession, even at 

high elevations. Such disturbances probably are more 

common in warmer environments.

4.2.2 Succession in low-elevation forests

Douglas-fir and ponderosa pine are the dominants of 

late-successional forests at low elevations on the BNF 

(Hoffman and Alexander 1976). Sometimes Douglas-fir 

replaces ponderosa pine as the stand matures, but most 

ponderosa pine stands are dominated by ponderosa pine 

saplings in the understory (Despain 1973). Unlike areas 

in the Colorado Front Range, lodgepole pine is generally not seral to Douglas-fir on the Bighorn Mountains, 

because of the separation of the two species by soil 

type (Despain 1973). Occasionally, limber pine has 

been viewed as a seral species (Hoffman and Alexander 

1976), though it also tends to occur on sites where the 

other species are less tolerant.

Based on the criteria of Mehl (1992), old-growth 

definitions for low-elevation forests are as follows: 

Douglas-fir >200 years and >46 cm (18 inches) dbh, 

and ponderosa pine >200 years and >41 cm (16 inches) 

dbh. The photo interpretation for the BNF shows only 

1% of the forests in Douglas-fir old-growth and another 

1% in ponderosa pine old-growth (USDA Forest Service 

1985). Again, these estimates may change substantially 

when the old-growth inventory for the BNF is completed.

The warmer and sometimes drier conditions in recent 

years can lead to changes in the successional trajectory at lower elevations as well as at high elevations, 

particularly due to changes that have occurred in stand 

structure (see section 6.1). Large conflagrations in the 

future due to both warming and increases in tree density and fuel loading (see section 6.2.2 for low-elevation 

landscapes) could set back some stands to earlier successional stages than would have occurred during the 

HRV period. Such landscape level changes in the proportions of late-successional forest are discussed in 

more detail in the Landscape Structure section of this 

report (section 6.2).

4.2.3 Succession in aspen woodlands

Aspen can be seral or relatively stable depending on site conditions and historical factors (Mueggler 

1985), but typically it is thought of as a pioneer species 

(Bartos and Campbell 1998). Usually a few aspen persist in the understory of coniferous forests and produce 

an abundance of new sprouts when the next stand-replacing disturbance occurs. Notably, while young aspen 

sprouts within a clone share the same root system with 

the mature canopy dominants, they typically are unable 

to survive in the understory. The clones (genets) of aspen are thought to be very long-lived, perhaps thousands 

of years, though individual trees (ramets) produced in 

the clone often do not live more than 100 or 125 years 

(Veblen and Lorenz 1991; Mehl 1992). Some ramets 

may live much longer. Aspen dynamics is discussed further in subsequent sections.

4.2.4 Succession in non-forest vegetation

As with forests on the BNF, the composition and 

structure of non-forest vegetation varies considerably 

during the time period of a century or more. In areas 

where big sagebrush was dominant, vegetation changes were probably quite dramatic after fire during the 

HRV reference period because the sagebrush is incapable of sprouting. When a fire occurs, grasses and forbs 

become the dominants for periods of several decades. 

Eventually, big sagebrush reestablishes with new seedlings, which is a common successional pattern. Some 

grasses, such as bluebunch wheatgrass, also may have 

declined following hot fires (or heavy spring grazing) (Knight 1994a). In contrast, some shrubs, such 

as snowbush ceanothus (Ceanothus velutinus), require 

the heat of fire to break seed dormancy (Zavitkovski 

and Newton 1968). Sufficiently long drought periods 
26 USDA Forest Service RMRS-GTR-140. 2005

during the past century could cause shifts in species 

composition.

The effects of warmer climate may have been more 

than counteracted by fire suppression activities in the 

last century, with the net result being an increase in the 

frequency of succession from grasslands to shrubland, 

especially shrublands dominated by big sagebrush. 

Whether or not the increase is beyond the HRV is uncertain because there is no evidence to support such a 

conclusion. In recent decades, the Forest Service has 

conducted prescribed burns to reduce the extensive invasion of woody plants such as big sagebrush (Cook and 

others 1994), thereby restoring what many consider to 

be a natural process to the landscape (i.e., one that was 

common during the HRV reference period).

Two other factors must be considered when addressing succession in non-forest vegetation—the effects of 

livestock grazing, which was especially intense in the 

early 1900s, and the invasion of exotic plants that has 

occurred throughout the last century. The effects of 

grazing are discussed later in this report, but in general, 

range management practices are better now than at the 

turn of the century and rangeland condition is probably 

better than at that time. This has occurred through natural successional processes, including the accumulation 

of biomass and favorable shifts in species composition. Undoubtedly, where exotic plants have become 

common, the recovery patterns have been different. 

Unfortunately, there has been essentially no research 

on this topic in Wyoming National Forests. The work 

of Stohlgren and his associates (Stohlgren and others 

1999a, 1999b) is pertinent. They found that habitats in 

the Rocky Mountains of Colorado with high native species diversity often are the habitats where exotic plant 

invasion is most likely. In general, the presence of exotic plants is likely to push many stand variables beyond 

their historic range of variability.

5. Historic Range of Variability for 

Disturbances Compared to Existing 

Conditions

A variety of natural disturbances occur in the Rocky 

Mountains, but fire is the predominant one (Clements 

1910; Brown 1973; Romme and Knight 1981; Fahey and 

Knight 1986; Despain and Romme 1991). Occasional 

windstorms and insect or disease epidemics can be 

important as well, but fire has shaped the vegetation mosaic for thousands of years by causing clearly defined 

disturbances on a variety of scales. The successional 

trajectories described in the previous section have been 

initiated over and over, creating a diverse landscape mosaic. We discuss each disturbance type separately in 

this report, but the various disturbances have been interactive. For example, a windstorm that topples a large 

number of trees may increase the probability of an insect epidemic or fire in some areas (Schmid and Frye 

1977; Lindemann and Baker 2001), and new edges between burned and unburned stands create environments 

favorable for the windthrow of both dead and live trees 

as well as the spread of certain insects and pathogens 

(Knight 1994a).

Today, the frequency, size, and intensity of historic 

disturbances, and the forests that develop after different kinds of disturbances, often have been altered by 

management activities. In this section we examine these 

changes in more detail and attempt to characterize the 

HRV for the major disturbances. Then we compare the 

HRV of disturbances to existing conditions.

5.1 Fire

The evidence of historical fires is recorded by the annual rings of trees that survive fire events (fire scars) or of 

trees that become established within a few years after the 

fire (e.g., Romme and Knight 1981; Kipfmueller 1997; 

Baker and Kipfmueller 2000). Evidence can also be obtained from charcoal and pollen deposited in bog and 

lake sediments (Mehringer and others 1977; Millspaugh 

and Whitlock 1995; Whitlock and Millspaugh 1996; 

Fall 1997; Kipfmueller and Baker 1998a, 2000). Using 

these techniques, it is clear that the frequency, size, and 

intensity of fire disturbances have been altered in some 

areas by management activities.

When separated by forest type, ponderosa pine forests on the BNF currently have the greatest number of 

fires. On average, 15 fires started per year per 100,000 

ha (247,000 acres) in ponderosa pine forest since 1970. 

In contrast, only five fires started per year per 100,000 

ha in the spruce-fir/lodgepole pine forests (BNF data). 

Various other studies also indicate that low-elevation 

forests burn more frequently than forests dominated by 

lodgepole pine or spruce-fir (compare Tables 3 and 4). 

Of course, low intensity surface fires are typical of the 

low-elevation forests (ponderosa pine and Douglas-fir), 

while intense crown fires are more common at high elevations. The fire regimes of high and low elevations 

should be considered separately, but some of the fire 

data were not easily separated in this way. For example, many of the quantitative fire and landscape analyses 

for high-elevation forests are based on the entire BNF. 

Because the forested area is 80% at high elevations, this 
USDA Forest Service RMRS-GTR-140. 2005 27

deficiency is not serious when considering the HRV at 

high elevations.

5.1.1 Fire in high-elevation forests

As lodgepole pine is often seral to Engelmann spruce 

and subalpine fir, the historic variability of lodgepole 

pine forests and spruce-fir forests is closely linked. 

Thus, the fire regimes for the two forest types are discussed together. In this section we compare the HRV for 

fire-related variables to existing conditions.

Fire intensity. Fire intensity in high-elevation forests 

varies according to weather, fuel, and site conditions. 

In certain cases, low intensity surface fires may occur 

(Brown 1973; Arno 1976; Franklin and Laven 1989; 

Kipfmueller 1997), but often such fires become standreplacing crown fires if spruce, fir, and lodgepole pine 

are present. Thus, high-elevation forests are affected primarily by stand-replacing fires.

Fire return interval. Fire frequency in high-elevation forests can be estimated using mean fire intervals 

(MFI) at two spatial scales: within a stand and across a 

landscape. Perhaps the most useful of such data to managers, as a guide to determining harvest rotation times, 

are estimates that focus on the fire return interval of 

stand-replacing fires (fire-free period) within a particular 

stand. A common approach to estimating such site-specific fire return intervals involves age-class sampling and 

the evaluation of stand structure and fuel accumulation 

(e.g., Billings 1969; Romme and Knight 1981; Romme 

1980a, 1982; Romme and Despain 1989; Kipfmueller 

and Baker 1998a, 2000). As a stand ages, the amount 

and continuity of fuels increases and stand-replacing 

fires become more likely. Based on this approach, the 

fire-free interval for a particular stand of subalpine forest varies commonly from 150 to 700 years (table 3). Of 

course, shorter intervals have been observed as well.

Average fire return intervals have also been estimated by counting the rings on fire-scarred trees (Hawkes 

1980; Bornong 1996a; Kipfmueller 1997; Kipfmueller 

and Baker 1998a). Such estimates are often low because 

Table 3—Examples of ranges for average fire intervals in high-elevation forests, as estimated by various investigators. These ranges 

represent the typical amount of time between successive fire events in an individual stand. MBNF = Medicine Bow National 

Forest, YNP = Yellowstone National Park, BNF = Bighorn National Forest (not available for pre- and post-settlement periods).

 Fire return

Forest type / interval estimate Type of fire

Study location (years) event Basis of estimates

Billings (1969) Spruce-fir / MBNF up to 600-700 stand-replacing stand age structure

Arno (1980) Subalpine forest; N. Rockies 150-350 stand-replacing stand age structure

Romme (1980a, 1982) Lodgepole, fir, spruce; YNP 300+ stand-replacing stand age structure and fuel

 accumulation

Romme and Knight (1981) Spruce-fir; MBNF 300-500+ stand-replacing stand age structure and fuel

 accumulation

Romme and Despain (1989) Lodgepole, fir, spruce; YNP 200-400 stand-replacing stand age structure and fuel

 accumulation

Hawkes (1980) Lodgepole, fir, spruce, 90-304 1 all empirical calculations 

 larch; Alberta based on fire scarred trees

Kipfmueller (1997) Lodgepole, fir, spruce; MBNF 39-149 2 all empirical point-scale 

 calculations based on 73 

 fire scarred trees

Bornong (1996a) Lodgepole habitat type; BNF 593 all empirical point-scale 

 calculations based on 15 

 apparently fire scarred 

 trees

Bornong (1996a) Spruce-fir; BNF 883 all empirical point-scale 

 calculations based on four 

 apparently fire scarred 

 trees

1 This range represents overall averages calculated for forests at different elevations and topographic positions, including: (1) lower subalpine/lower 

elevation (90-101 years); (2) upper subalpine/upper elevation (153-304 years); (3) north aspects (187 years); and (4) south, east, and west aspects 

(93-104 years). 2 This range represents four different methods for calculating point-scale MFI: (1) the interval between stand origin date and first scar (82 years); 

(2) the interval between scars on the same tree (39 years); (3) the interval between the last scar and the present (149 years); and (4) the overall 

average of all intervals (129 years for 54 different stands in the Rock Creek Basin). 3 Based on overall average of all intervals (8 different stands in North Fork of the Powder River Watershed); some scars may have been caused by 

insects.
28 USDA Forest Service RMRS-GTR-140. 2005 Table 4—Some fire return intervals reported for stands of ponderosa pine and Douglas-fir in the Rocky Mountains. The range in parentheses is the range in interval sizes for one stand or area and is not the range of means, because it considers extremes (see text for explanation). When the mean shifted by more than 75% between pre- and post-settlement, we considered the mean fire return intervals to be outside the HRV, which was true for the first three studies in this table. Mean fire return interval estimate (years) Type of Study Forest type / location Pre-settlement Post-settlement fire event Basis of estimates Brown and others 2000 Ponderosa pine/Laramie Range, WY median = 26-33.5 >86 – 88 surface fire scar analysis (Ashenfelder Basin) (8–82) Brown and others 1999 Ponderosa pine-Douglas-fir Central widespread fires widespread fires surface fire scar analysis Colorado 1496-1851: 59.2 1880-1996: >116 (27-128+) Fisher and others 1987 Ponderosa pine/Devils Tower 1600-1770: 27 >1900: 42 surface fire scar analysis Nat’l Mon., WY 1770-1900: 14 overall: 19 Dieterich 1980 Ponderosa pine/northern Arizona (2-35) ---- surface fire scar analysis Goldblum and Veblen 1992 Ponderosa pine-Douglas-fir/ before 1859: 31.8 1859-1920: 8.1 surface fire scar analysis Boulder, CO >1920: 28 Brown 1994; Brown and Sieg 1996 Ponderosa pine Jewel Cave 20-32 (5-79) ---- surface fire scar analysis Nat’l Mon., SD Laven and others 1980 Ponderosa pine Roosevelt Nat’l before 1840: 66 (5-157) 1906-1973: 27.3 surface fire scar analysis Forest, CO 1840-1905: 17.8 (3–161) (8-46) Shinneman and Baker 1997 Ponderosa pine Black Hills < 250-300+ ---- crown fires historical Nat’l Forest, SD observations; stand ages McCune 1983 Douglas-fir Montana 60 ---- not specified Arno and Gruell 1986 Douglas-fir Montana 35-40 ---- not specified Houston 1973 Douglas-fir Yellowstone Nat’l 20-25 ---- surface fire scar analysis Park, WY
USDA Forest Service RMRS-GTR-140. 2005 29

they consider the occurrence of low-intensity surface 

fires as well as stand-replacing fires. Using this approach, 

fire return intervals for high-elevation forests in the central and northern Rockies range from 39 to 304 years, 

depending on site characteristics, species composition, 

and the method of calculation (table 3). The longest firefree intervals probably are associated with mesic sites 

found in ravines, at high elevations, on leeward or north 

slopes, and on unusually dry sites where fires may not 

occur at all (Billings 1969, Hawkes 1980, Romme and 

Knight 1981, Tinker and others 1994). Notably, Baker 

and Kipfmueller (2000) could not find a relationship 

between old forests and topographic position in the 3241 

ha (8005 acres) watershed they studied in the Medicine 

Bow National Forest.

The second way of characterizing fire frequency is to 

calculate the MFI for a large landscape that encompasses 

many stands, rather than just one stand (e.g., Veblen and 

others 1994; Wadleigh and Jenkins 1996; Kipfmueller 

1997; Kipfmueller and Baker 1998a). This landscapelevel MFI is calculated simply as the arithmetic mean 

of intervals between all known fire events within a given landscape, even though different portions of the area 

burn each time (Romme 1980b). The MFI for a high-elevation watershed on the BNF during the HRV period 

was estimated to average 13 and 32 years for lodgepole pine and spruce-fir forests, respectively (Bornong 

1996a; fig. 20). Because this statistic is area dependent, 

larger study areas typically have more fire events, leading to lower MFI estimates (Arno and Peterson 1983; 

Kipfmueller 1997). While MFI estimates from different 

areas are difficult to compare unless standardized on a 

per unit area basis, MFI is useful as an index of changes 

in fire ignition over time within one location.

Fire size and extent. Insights into the size of fire 

events and the occurrence of large fires can be gained 

by considering both long-term and recent fire histories 

in Yellowstone National Park (YNP), which is similar in 

latitude, topography and vegetation to the BNF and has 

remained relatively undisturbed by human influences. 

Thus, despite geologic differences, it provides a reasonable reference area—indeed, one of the only reference 

areas that is appropriate for the BNF and where a considerable amount of research has been done.

At the landscape scale, Despain and Romme (1991) 

reconstructed the fire history for a 129,600 ha (320,112 

acres) study area in southcentral YNP (approximately 

one-fifth the size of the BNF). Although fire has apparently occurred in every decade, they found that large scale, 

stand-replacing fires have occurred during four main periods since 1690 AD: 1690-1710, 1730-1750, 1860-1870, 

and 1988 (fig. 21). Similarly, Barrett (1994) found that 

major fires occurred over four periods within 81,000 ha 

(200,070 acres) in northeastern YNP (1740-1750, 1770s, 

1820-1830, and 1980s; fig. 21), but not always during the 

same decades identified by Despain and Romme. The 

periods identified by both studies often corresponded to 

very dry or very warm periods (fig. 18).

During each major fire period, a large proportion of 

the entire area burned (7-26% in the decade with the 

maximum area burned in southcentral YNP, 11-58% in 

northeastern YNP), creating extensive, relatively evenaged forests. Despain and Romme (1991) concluded for 

YNP that (1) such even-aged cohorts progress into later 

successional stages and become increasingly susceptible to burning as fuel loading and continuity increase, 

and (2) the same area burns again after another 200-400 

years whenever weather conditions permit. Lightning 

ignitions are frequent (fig. 22) but usually do not burn 

more than a few hectares (Despain and Romme 1991). 

Most of the area burned during a century is attributable 

to only a few large fires (figs. 23 and 24).

Since 1972, the fire management policy in YNP has 

been to allow lightning-caused fires to burn in most instances, providing a proxy for possible dynamics in the 

HRV period. Only during a few years from 1972-1988 

were weather conditions dry enough to allow more than 

100 ha (247 acres) to burn (fig. 24).

Considering the area burned per year during the period of no fire suppression from 1972-1987 in YNP, three 

important trends in fire size emerge: (1) the area burned 

in a single year is highly variable, (2) the mean area 

burned per year is toward the low end of the range, and 

(3) the median, possibly a better indicator of a typical 

year because of the skewed distribution, is only 12 ha 

per million hectares (fig. 23). The 1988 fires are one of 

the five major fire events of the past 300 years, and they 

burned more land area than the other large fires combined over several decades (figs. 21 and 24). Possibly 

this was due to the warmer conditions in the latter half 

of the century than had occurred during the HRV period. 

The driving factors that create the fire regime in most of 

YNP and the BNF appear to be weather conditions and 

the type and distribution of fuel (Despain and Romme 

1991).

Using YNP as an HRV proxy. When determining if 

the YNP fire regime can be used as a proxy for the highelevation forest of the BNF, differences between the 

climate and vegetation types of the two areas must be 

considered. The BNF tends to be somewhat drier and 

warmer than YNP (fig. 9), which could create flammable 

conditions more frequently; but the BNF also has less 

forested area and less land in highly flammable forest 

(Despain 1990), which reduces fire potential. The mean 
30 USDA Forest Service RMRS-GTR-140. 2005

number of fire starts per year is similar between the two 

areas (fig. 22). Similar to YNP, the majority of the forests in the BNF are high-elevation forests. Both YNP and 

BNF had relatively large fires in 1988, but only about 

1600 ha (3952 acres) burned on the BNF per 100,000 

ha (247,000 acres) of land that year, compared to 44,200 

ha per 100,000 ha of land in YNP (fig. 24). Despite major fire suppression efforts, the largest fire on the BNF 

in 1988 (5300 ha [13,090 acres]), started by lightning, 

Figure 20—Mean (black square) and range (line) of fire intervals across the landscape for a watershed on the Medicine 

Bow National Forest (Rock Creek, 3241 ha [8005 acres]) and for a watershed on the Bighorn National Forest (watershed 

9 in fig. 7; 4162 ha [10,280 acres]) during the reference period (HRV) and existing conditions (EC). Unlike the BNF, the 

Medicine Bow National Forest had a settlement period after Europeans arrived but before fire suppression (SET) that was 

characterized by frequent fires (short fire-return intervals), compared to the HRV period. Fire intervals lengthened again 

during post-settlement (EC) with fire suppression, but were still shorter than during the HRV period. In contrast, comparable influences by European-Americans occurred later in the BNF, and large fires became less frequent than the HRV 

in the lodgepole pine forests, probably due to fire suppression. Mean clearcut intervals on the BNF were shorter than fire 

intervals and thus are shown for comparison. Note: Fires >9 ha (22 acres) include all cover types. LP=lodgepole pine; 

SP=spruce-fir. Source: Kipfmueller 1997 for the MBNF and Bornong 1996a for the BNF

probably stopped primarily due to insufficient fuel as it 

headed up into the rocky Cloud Peak Wilderness (fig. 25). 

The topography in the southern portion of the BNF may 

limit fire size more than in much of YNP.

Due to more rocky barriers and less continuous forests, one might think that the BNF never had the very 

large fires that burned in YNP during the HRV period. 

Yet, YNP had the same number of large fires as the BNF 

from 1900 to 1970 when fire suppression was practiced 

All fires lodge

pole

All fires spruce

fir

All fires lodge

pole

Fires >9 ha

Clearcuts
USDA Forest Service RMRS-GTR-140. 2005 31

Year

1680 1700 1720 1740 1760 1780 1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000

% forested area burned

or clearcut

0

10

20

40

60

Southcentral Yellowstone NP stand-replacing fires

Bighorn National Forest fires >9 ha (existing conditions only, after 1909)

Bighorn National Forest clearcuts (existing conditions only)

 

 

1680 1700 1720 1740 1760 1780 1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000

% lodgepole pine area

burned or clearcut

0

10

20

40

60

 

Northeastern Yellowstone NP stand-replacing fires

Bighorn National Forest fires >9 ha (existing conditions only, after 1909)

Bighorn National Forest clearcuts (existing conditions only)

Year

HRV EC

Figure 21—Comparison of the historic range of variability of area burned per decade in Yellowstone National Park (proxy for 

BNF) to more recent conditions for area burned or clearcut per decade in the Bighorn National Forest. Top graph is for all forests; bottom graph is for lodgepole pine forests only. EC = existing conditions after European-Americans arrived. Data are 

summed by decade, not individual years. To illustrate, the 1988 fires in YNP are part of the 1980 dataset. Source: Romme 

and Despain 1989 for southcentral YNP, Barrett 1994 for northeastern YNP, and BNF data.

Number of fires starts/year/100,000 ha 

0 2 4 6 8 10 12 14

lightning

total

lightning

total

YNP

EC BNF

HRV

Proxy

Figure 22—Mean (dots) and range (lines) of number of fire starts per year on the 

Bighorn National Forest compared to Yellowstone National Park, our HRV reference 

area. From 1930 to 1970, 57% of the YNP fires were started from lightning (Taylor 

1973 cited in Houston 1973), but the range of the number of lighting-caused fires is 

unknown. EC = existing conditions after European-Americans arrived. Source: BNF 

fire database for the periods 1909-1936 and 1970-96, and Despain and Romme 

(1991) for YNP from 1972-1988
32 USDA Forest Service RMRS-GTR-140. 2005

Area burned (ha/million ha) per year

0 2000 4000 6000 8000 10000

YNP

BNF

(EC)

(HRV

Proxy)

Median = 81

Mean = 578

Median = 12

Mean = 1,138

Figure 23—Area burned per year per million hectares within the entire Bighorn National Forest (BNF) and an area within 

Yellowstone National Park (HRV proxy) without fire suppression between 1972 and 1987 (YNP data from Despain and 

Romme 1991). EC = existing conditions, i.e., 1972-1987. Note: If the1988 fires in YNP had been included, the YNP range 

would extend to 441,890 ha and the mean (41,810 ha) would shift to the right, further increasing the difference between the 

BNF and YNP means.

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

Area (ha) burned or clearcut 

per 100,000 ha

0

500

1000

1500

2000

YNP fires (HRV proxy) 

BNF fires

BNF clearcuts

44,189 ha - YNP

0-99

100-199200-299300-399400-499500-599

600-699700-799

00-899

900-999

1000-19992000-29993000-3999

4000-4999

5000-5999

6000-6999

7000-7999

8000-8999

9000-9999

>10000

Number of years in 1900-2000 period

0

20

40

60

80

100

 

 

 

YNP fires (1900 - 1990)

BNF fires (1909 - 1939, 1970 - 1996)

BNF clearcuts (1946 - 1998)

Area (ha) burned or clearcut/year/100,000 ha

Year

Figure 24—Area burned or clearcut each year during the last century (1900-1996) on the entire Bighorn National Forest (BNF), 

compared to area burned in all of Yellowstone National Park (YNP) during a similar period (top graph). Most fires occurring 

during the last century were of small size (0-99 ha), as were clearcuts (bottom graph). Fire suppression was practiced in YNP 

for all but the period from 1972 to 1987. The BNF has less forested area to burn (62%) than YNP (80%) and less flammable 

forest (about 41% on BNF in flammable LP2, LP3, and LP of Despain (1990) classifications, compared to 63% on YNP), but 

a slightly drier climate. Data from small fires (<9 ha [22 acres]) on the BNF from 1940-1969 are missing. Those years are not 

used in the lower graph, but results for the remaining years were standardized to 100 years (as were clearcuts). The area 

burned includes all fires, not just stand-replacing fires. Source: Balling and others 1992 for YNP, and BNF data.
USDA Forest Service RMRS-GTR-140. 2005 33

Figure 25—Location of large fires (>9 ha [22 acres]) on the Bighorn National Forest for each decade from 1909 

to 1996. The largest fires shown on this map burned about 5000 ha (12,350 acres). Source: BNF
34 USDA Forest Service RMRS-GTR-140. 2005

Forest ages in Bighorn NF (EC)

Stand origin dates <1700 Area (10,000 hectares)

0

1

2

3

4

5

6

300+

Forest ages in Little Firehold Watershed, YNP (HRV proxy)

Area (1,000 hectares) 0

1

2

3

4 1778

1978

1988

Stand age

Stand age

1700-49 1750-99 1800-49 1850-99 1900-49 1950-99

250-99 200-49 250-99 100-49 250-99 0-49

300+ 250-99 200-49 250-99 100-49 250-99 0-49

Figure 26—Forest stand age and origin dates 

on the Bighorn National Forest, based on 

data from about 60% of the forests, compared 

to stand age for forests in the Little Firehole 

Watershed in Yellowstone National Park. In 

YNP, the forest areas in different age classes are shown during three years (1778, 1978, 

and 1988). These data came from maps of the 

reconstructed forest developed by Romme 

(1979) and from our estimates using 1988 satellite imagery of the park. In the upper graph, 

the lighter part of the stacked bar is the area 

clearcut that would have been in older age 

classes without clearcutting. We divided the 

total clearcut area into thirds and placed them 

in the three oldest age classes. Although not 

shown, the clearcut area would also have to 

be subtracted from the youngest age class 

to represent conditions without clearcutting. 

Source: BNF data and Romme 1979

in both areas (three fires that were >500 ha/100,000 ha 

[>500 acres/100,000 acres]), suggesting that large-fire 

dynamics may be comparable (fig. 24).

Clearly, however, there is insufficient information on 

the behavior of large fires without fire suppression on the 

BNF to state conclusively that the HRV for the YNP reference area is adequate for evaluating HRV fire size and 

frequency in the BNF. Notably, evaluation of the stand 

ages of the BNF suggests extensive and large fires did 

create large areas of more or less even-aged lodgepole 

pine forest during the HRV period on the drier portions 

of the BNF (figs. 26 and 27).

To further examine the similarity between YNP and 

the BNF, we examined stand age in lodgepole pine forests over time and found that the majority of the forest 

on the BNF originated in the 1890s (fig. 27). Although 

some of the burned areas were ignited by early settlers, 

many large areas had burned before that time (figs. 27 

and 28). Estimated lodgepole pine stand ages during the 

HRV period on the BNF (fig. 27), compared to lodgepole pine/spruce-fir forests in YNP (fig. 26), suggest that 

large fires occur periodically in both areas and that differences between YNP and the BNF in topography and 

forested area are not sufficient to negate the use of YNP 

as a proxy for the BNF.

Changes from HRV. Due to insufficient data, we 

could not evaluate quantitatively the changes in fire 

regimes that might have occurred at the stand level. 

However, our qualitative assessment suggests that the 

mean fire return interval of stand-replacing fires in the 

last 100 years is still within the range of means during 

the HRV period, despite fire suppression efforts (table 

3; moderate confidence (Morgan and others 1996). Fire 

intensity probably has not changed either, as the forests 

are still dominated by stand-replacing fires (high confidence).

At the landscape scale, a study of lodgepole pine 

above 2670 m elevation in the North Fork of the Powder 

River (Bornong 1996a) found the mean landscape-level 

fire interval (MFI) more than doubled after EuropeanAmericans arrived (after 1877) (fig. 20). For his analysis, 

Bornong combined fire scars of trees that survived standreplacing fires (at the edge of eight stands). His mean of 

current fire intervals since European-Americans arrived 

was greater than 75% of the HRV mean, indicating that 

the current intervals probably are longer than the HRV 

(low confidence). Recent fire records for the BNF suggest that fires still play an important role on the BNF, but 

fire suppression efforts have lengthened the MFI during 

the last 50 years.
USDA Forest Service RMRS-GTR-140. 2005 35

Year of stand origin

1550 1600 1650 1700 1750 1800 1850 1900 1950 2000

Hectares

0

2000

4000

6000

8000

10000

12000 Lodgepole (67%)

Spruce-fir (50%)

Douglas-fir (29%)

Hectares

0

100

200

300

400

500

600

Ponderosa pine (26%)

Limber pine (34%)

Aspen (28%)

Year of stand origin

1550 1600 1650 1700 1750 1800 1850 1900 1950 2000

HRV

EC

Figure 27—Stand origin dates for forests on 

the Bighorn National Forest. Percentages 

in the legend indicate the relative amount 

of forest area within each forest type surveyed for age. Note that for non-seral 

forests, origin dates do not indicate time 

since last stand-replacing disturbance, 

but rather the date the majority of the 

present trees became established. Note 

also that vertical axes differ between the 

two graphs. Source: BNF

Comparing the BNF to YNP, the mean and standard 

deviation of total area burned per decade on the BNF 

currently is lower than what appears to be the historical 

conditions in YNP (1690-1890; fig. 29). Additionally, the 

average area burned per year per unit area on the BNF 

was about half the area burned during years when fire 

suppression was not practiced in YNP, even when 1988 

was excluded (1972-1987; fig. 23). Construction of fire 

breaks in the BNF probably facilitated the reduction of 

fire sizes. Moreover, mop-up efforts can completely extinguish any potential for flare-ups several days later. In 

contrast, unregulated fires during the HRV period, such 

as in YNP, can wane and then flare up again, enlarging 

the original area burned and creating very large disturbances. Recent clearcuts without much tree growth can 

also act as fire breaks, plus roads increase accessibility 

for fire suppression crews. Both factors must have contributed to the reduction in the number and size of fires 

on the BNF to below the HRV (high confidence).

Because many fires are apparently put out quickly, 

any increase in ignition from human activities may not 

be important when balanced against the effects of aggressive fire suppression, climate change, and fuels, as 

discussed previously. The median size of all fires on the 

BNF was larger than the median size of fires in YNP 

during the era of suppressing fires, wherever they occurred (fig. 23). Definitive conclusions are not possible, 

but the data suggest, contrary to prevailing thought, that 

fire suppression plus removal of fuels by timber harvest 

on the high-elevation forests of the BNF may have reduced the number of large fires but not the mid-sized 

fires (fig. 30).

On a broader geographic scale, fire suppression and 

clearcuts (which can act as fuel breaks) appear to be 

less important than climate change and fuel buildup in 

determining the extent of the largest fires. Weather (or 

fuel) conditions on the BNF may not have been conducive to large fires during the early and mid-1900s, when 

conditions on the Bighorns were relatively wet (figs. 18 

and 19). By the late 1900s, temperatures had become 

the warmest since 1200 AD. Possibly for this reason, 

the area burned each year in the National Forests in all 

eleven western states more than doubled from the mid1900s (1950-60) to more recent years (the late 1980s 

and 1990s), despite more sophisticated fire-fighting 

techniques (Pyne 1997).
36 USDA Forest Service RMRS-GTR-140. 2005

Figure 28—Origin dates for stands that have been aged on the Bighorn National Forest (about 60% of the forests). 

No stands have been identified for the period 1576-1600. Source: BNF
USDA Forest Service RMRS-GTR-140. 2005 37

1680

1720

1760

1800

1840

1880

1920

1960

2000

% forested area burned

0

5

10

15 Yellowstone National Park (proxy for HRV period)

Bighorn National Forest (EC)

1.0 

0.9

0.8 

0.9

2.4 

1.9

1.5 

1.2

1.9 

1.6

Mean = 6.2 

SD = 3.8

Figure 29—The historic range of means for percent of forested area burned each decade is 

1.5 to 6.2 in Yellowstone National Park (used as an HRV proxy for BNF). Means shown are 

for each 50-year period, starting in 1690. The range of means for the Existing Conditions 

(EC) in the Bighorn National Forest is 0.8 to 1.0 for the 50-year periods, which suggests that 

the forested area burned on the BNF is outside the HRV, probably due to fire suppression. 

The standard deviation was the same for the two periods we examined for existing conditions on the BNF. This SD (0.9) was lower than the historic range of standard deviations for 

forest area burned (1.2-3.8). Based on BNF data and data in Despain and Romme 1989.

Number/year/100,000 ha

0 5 10 15

Size class (ha)

Two Ocean and Mirror Plateaus YNP fires

(under natural fire regime,1972-1988 = HRV proxy)

BNF fires (under suppressed 

fire regime, 1970-1996 = existing conditions)

BNF Clearcuts (1946-1998 = existing conditions)

0 - 0.9

1 - 4.9

5 - 50

> 50 Figure 30—Mean (box or circle) and range 

(line) of number of fires and clearcuts of 

various size classes that occurred per year 

across the landscape in spruce-fir and 

lodgepole pine forests for the entire Bighorn 

National Forest (BNF), compared to fires 

that occurred on the Two Ocean and Mirror 

Plateaus in Yellowstone National Park 

(YNP) under a nearly natural fire regime. 

Percent of spruce-fir and lodgepole pine 

forest is similar between the two areas, although YNP has additional whitebark pine 

forest. Absolute ranges are shown, but 

based on the means, more large fires (5-

50 and >50 ha [12-124 and >124 acres]) 

tend to occur in YNP, which we used as 

an HRV proxy for the BNF, than for existing conditions with fire suppression on the 

BNF. However, the number of clearcuts of 

size 1-4.9 and 5-50 ha (2.5-12 and 12-124 

acres) is much higher than the number of 

fires of the same size in either YNP or the 

BNF. Based on BNF data and Despain 

1990 for YNP (1970-1996)
38 USDA Forest Service RMRS-GTR-140. 2005

It is also possible that the reduced incidence of large 

fire on the BNF during much of the last century (fig. 

30) has occurred because many high-elevation forests 

on the BNF have been in a relatively inflammable stage 

of succession, rather than because of fire suppression 

or timber harvesting. Today, many stands are still only 

about 100-150 years old (fig. 26), and they probably will 

become more flammable over the next 100 years, as various reports on forest health predict. However, research 

suggests that large stand-replacing fires are more likely 

to occur because of weather conditions than fuel accumulations (Bessie and Johnson 1995; Weir and others 

1995). Romme and Despain (1989) suggest that, while 

extensive fires could have occurred in YNP since about 

1930 based on fuels, they did not burn until 1988 because of weather conditions. The relatively low amounts 

of fuel on the BNF at the present time must have some 

influence on fire occurrences, but probably not as much 

effect as more frequent periods of drought with strong 

winds. Baker (2002) also recognized the importance of 

climatic conditions, concluding that climate, fuels and 

elevation are linked in determining the frequency and 

extent of fires in the Rocky Mountain region.

Dealing with the large-scale disturbances caused by 

fire in high-elevation forests presents a challenge to 

forest managers. On one hand, disturbances of the magnitude of the 1988 Yellowstone fires appear to have had 

very important ecological effects (e.g., Christensen and 

others 1989), and preventing such events in the future, if 

that is possible, could have unknown consequences for 

biological diversity. On the other hand, the large land 

area involved with such disturbances also is an extreme 

in the HRV that the public hesitates to support (Swanson 

and others 1993; Manley and others 1995). Managers 

must consider such issues when deciding whether to 

manage high-elevation forests within the HRV.

Though the data suggest that fire suppression on a 

partially-harvested landscape reduces fire sizes, this conclusion is still quite controversial. Many fires, whether 

started by lightning or humans, certainly have been put 

out. However, without the wind and drought that accompanies the large fires that cannot be extinguished, the 

suppressed fires might not have burned over a large area 

anyway. There is little basis for arguing that fire suppression in YNP from 1872 to 1972 had a big effect on the 

magnitude of the 1988 fires there, except at lower elevations in the Douglas-fir woodlands in the northern part 

of the park (where fire history is more similar to the ponderosa pine forests). We have no records of fires during 

the reference period burning as much land area on the 

BNF during a single year as occurred in 1988 in YNP, 

but just as much land burned in YNP during two decades 

around 1700 (Romme and Despain 1989). Whether or 

not fire suppression in YNP and the BNF has been effective in high-elevation forests is still debatable. More 

research is needed to be confident.

It is probable that big fires will once again burn across 

the BNF, regardless of modern fire suppression technology and silvicultural practices designed to reduce fuel 

loadings. In unmanaged forests, stand-replacing fires 

may occur in the same stand, on average, every 200-400 

years, and they may burn over a large proportion (5-

25%) of the landscape approximately once each century. 

Where landscape patterns and stand structures are modified by humans, as in the BNF, such intervals may be 

more difficult to predict. Harvesting often is done with 

the objective of reducing fuel loads and flammability as 

well as providing a source of wood. However, as noted, 

wild fires that burn large areas probably are determined 

as much by drought and wind as by fuel loadings, if not 

more so (Clark 1990; Johnson and Larsen 1991; Bessie 

and Johnson 1995; Weir and others 1995; Baker 2002). 

Where there are enough live trees to be economical for 

timber harvesting, there probably is enough fuel to carry 

a stand-replacing fire under conditions of drought and 

high winds.

Another controversial issue is the frequency of 

surface fires burning through the understory of high-elevation coniferous forests, thinning some of the trees 

in the process and thereby altering stand structure in a 

way that could be emulated with selective harvesting. 

The abundance of low branches on spruce and fir suggests that such fires would be rare where these species 

are common. However, the lower branches of lodgepole pine are shed by the tree, creating a relatively open 

understory. Surface fires in lodgepole pine have been 

observed, and because of the thin bark, some trees are 

killed. Others survive but develop fire scars, sometimes 

multiple scars. Data presented in table 3, and in Lotan 

and others (1985), suggest that surface fires may have 

burned through lodgepole pine forests in the BNF at intervals as short as 40 to 80 years—considerably shorter 

than the 200+ intervals usually reported for YNP. Our 

impression is that stand-replacing crown fires are most 

common in all high-elevation forests, but that some are 

burned periodically by surface fires—especially on the 

edges of crown fires where flame lengths (a measure of 

fire intensity) are shorter.

5.1.2 Fire in low-elevation forests

Fire intensity. Ponderosa pine and Douglas-fir woodlands comprise about 10% of the BNF (9% Douglas-fir 

and 1% ponderosa pine), occurring at low-elevations. 

The most common fire regime in these woodlands during 
USDA Forest Service RMRS-GTR-140. 2005 39

the HRV reference period probably was characterized by 

frequent, low-intensity surface fires that kill most of the 

small trees but few of the older, thick-barked trees—thus 

maintaining relatively low tree density. Historic accounts 

in other parts of the Rocky Mountains describe “open 

and park-like” stands of ponderosa pine with understories rich in grasses, such as in the American Southwest 

(Cooper 1960) and in Colorado (Veblen and Lorenz 

1991). Photographs from the 1920s to 1950s show open, 

park-like stands of ponderosa pine forests on the east 

slope of the Bighorn Mountains (historic photos on file 

at the BNF). Notably, some lumber was taken from these 

ponderosa stands in the late 1800s (Jack 1900), which 

may have contributed to the low tree-density observed 

in photos taken after that time.

In addition to surface fires, there is evidence of fires 

that kill groups of trees, creating openings. Kaufmann 

and others (2000) refer to a fire regime with both fire 

types as a mixed-fire severity pattern. The mixed-fire 

severity pattern probably occurred on the BNF during 

the HRV period. As discussed below, stand-replacing 

fires could have occurred also, especially in mesic areas 

where tree density can be relatively high.

Fire return interval. Mean fire return interval estimates 

for stands at low elevations in portions of the Black Hills 

and Front Range of Colorado have generally been on the 

order of 15-45 years (Laven and others 1980; Fisher and 

others 1987; Goldblum and Veblen 1992; Brown 1994; 

Brown and Sieg 1996), compared to less than 10 years in 

the Southwest (Weaver 1951, Dieterich 1980, Fule and 

others 1997). In Wyoming, ponderosa pine fire scars indicate that, during the HRV reference period, a median 

fire interval of 26 to 33 years occurred in the stands of 

the Laramie Range (Brown and others 2000), and that 

a mean fire interval (MFI) of 14 to 27 years occurred 

at Devil’s Tower National Monument (Fisher and others 

1987; table 4). The range of fire intervals during the HRV 

period can be quite broad in Wyoming and Colorado 

(table 4 and fig. 31). For example, a range of 3-161 years 

was estimated by Laven and others (1980) in Colorado. 

In a paper urging caution when interpreting fire history 

data, Baker and Ehle (2001, 2003) concluded that such 

ranges are biased toward shorter intervals.

Fire return intervals vary widely among studies partly because of differences in methodology (Veblen 2000) 

and partly because of differences in climate, fuel conditions and topographic position. Most likely, warmer and 

drier sites (or years) experience more frequent fires than 

areas where (or when) conditions are cooler. Veblen and 

others (2000) conducted a detailed study of tree rings in 

the ponderosa pine forests of the Colorado Front Range, 

finding that alternating wet and dry periods with a 5-year 

periodicity are conducive to fire spread. Wet periods, believed to be caused by El Niño conditions, allowed the 

production of fine fuels that increased flammability during subsequent dry periods associated with La Niña. The 

effect of the El Niño/La Niña oscillation, however, may 

not be as strong in areas north of the Colorado Front 

Range (Veblen 2000). Another factor causing variability 

could be livestock grazing, which reduces the abundance 

of fine fuels and the likelihood of a fire extending into 

adjacent forests.

Because most of the ponderosa pine in the Bighorn 

Mountains is on land outside the BNF boundary, the 

predominant forest type at low elevations within the 

National Forest is dominated by Douglas-fir (9% of 

the BNF). Houston (1973) found a MFI of 20-25 years 

in Douglas-fir stands during the HRV period in YNP. 

Where Douglas-fir and ponderosa pine stands are located near each other in Colorado, fire intervals for stands 

of Douglas-fir appear to be slightly longer (Goldblum 

and Veblen 1992), possibly due to the occurrence of 

Douglas-fir on somewhat more mesic sites.

A factor complicating our ability to interpret what 

may be natural in lower elevation forests and woodlands 

is the role that humans have had in influencing the fire 

Years

0 20 40 60 80 100

HRV

EC

Figure 31—Return intervals for surface 

fires in stands of ponderosa pine in 

the Ashenfelder Basin, Medicine Bow 

National Forest, southeastern Wyoming. 

The HRV line represents the HRV for 

fire return intervals prior to 1912, and 

the black circle on the HRV line is an 

estimate of the median interval during 

that same period. The value during the 

existing conditions (EC) period is essentially time since last fire because 

no fires had occurred since the last fire 

in the early 1900s when the data were 

gathered. Based on data in Brown and 

others 2000
40 USDA Forest Service RMRS-GTR-140. 2005

regime. Prior to the arrival of European-Americans, fires 

set by Native Americans probably were most common 

at lower elevations (e.g., Barrett and Arno 1982; Gruell 

1983) and were inseparable from “natural” fires (Martin 

and Sapsis 1992). Fisher and others (1987) found evidence that fire in ponderosa pine at nearby Devil’s Tower 

National Monument became more frequent from 1770 

to 1900 (mean interval = 14 years) than it had been from 

1600-1770 (mean interval = 27 years), possibly, they 

concluded, because of the expansion of Sioux Indians 

into the area after 1770 (table 4).

Fire size. Fire size and intensity probably is directly 

proportional to the length of the fire-free interval, with 

more large, severe fires occurring where or when fire 

intervals (or climate oscillations) are longer and there 

has been more time for fuels to accumulate. At nearby 

Devil’s Tower National Monument (Fisher and others 1987), fires caused by individual lightning strikes 

(i.e., spot fires) were historically common, but typically they would damage only one or two trees before 

burning out due to weather conditions or fuel discontinuity. Larger fires were less frequent, occurring only at 

times when weather and fuel conditions facilitated fire 

spread. In the Southwest, where summer conditions are 

typically warmer and drier than Wyoming, large surface 

fires in the 1800s averaged only 1,300 ha (3211 acres) 

(Swetnam 1990). In parts of the Black Hills, the fires apparently could be larger and more intense (Shinneman 

and Baker 1997), like those in lodgepole pine forests. 

Historic fires in the Black Hills may have been as large 

as 20,000 ha (49,400 acres) (Dodge 1876), or even 

60,000 ha (148,200 acres) (Shinneman and Baker 1997, 

based on Graves 1899)—although, with one exception, 

fires since 1890 have been less than 9,000 ha (22,230 

acres). The exception was the intense, stand-replacing 

Jasper Fire in 2002 that burned about 33,850 ha (83,610 

acres). Notably, the few ponderosa pine woodlands and 

savannas in the BNF and nearby are patchy. This could 

have limited the spread of fire to smaller areas than in 

the Black Hills, except where the trees were separated 

by flammable grasslands.

Changes from HRV. Surface fires are much easier to 

suppress than the crown fires that develop so rapidly at 

higher elevations, and thus the change in fire regime from 

the HRV tends to be more noticeable at low elevations. 

The mean fire return interval for low-elevation ponderosa 

pine stands at Devil’s Tower appears to have lengthened 

from a range of 14 to 27 years before 1900 to 42 years after 

1900, possibly due to fire suppression (Fisher and others 1987, table 4). Fire intervals also are thought to have 

lengthened beyond the HRV in the nearby Ashenfelder 

Basin just north of Laramie Peak in the Medicine Bow 

National Forest during the last century, with the last fires 

recorded by Brown and others (2000) occurring in 1911 

and 1909 at two sites within the Basin (fig. 31). The resultant 86- and 88-year intervals since the last fire are four 

and six years longer than any recorded at these sites in the 

1800s. In Colorado, Brown and others (1999) found evidence to suggest that widespread fires on low-elevation 

forests occurred on average every 59 years, but that such 

fires did not occur after European-American settlement 

in the late 1800s. The results of Brown and others showed 

that the number of widespread fires per unit area (fire frequency) in the past century did not fall within the range 

of mean fire frequency during the HRV period. This kind 

of evidence suggests that fire suppression has been effective and that fire size as well as mean fire return interval 

has exceeded the HRV in low-elevation forests (moderate 

confidence).

Similar to high-elevation forests, the fire regime on 

the BNF at the lower elevations since 1970 has been 

dominated by numerous small fires with relatively few 

widespread fires (figs. 32 and 33). From 1970-1996, 93% 

of all fires in the forests at low elevations on the BNF 

were <4 ha, while only two fires were larger than 125 ha 

(309 acres) and none were larger than 400 ha (988 acres) 

(BNF fire data). Unfortunately, the historical fire sizes in 

the less extensive, patchy ponderosa pine and Douglasfir stands of the Bighorn Mountains is not known.

With some exceptions (e.g., Goldblum and Veblen 

1992; also see table 4), fire suppression apparently has 

lengthened the mean fire return interval at the stand 

scale in many ponderosa pine forests in the Rocky 

Mountains in general (moderate confidence). Extremely 

long intervals still occurred in the HRV period, however, because the ranges of post-settlement intervals often 

fall within the ranges of pre-settlement intervals (table 

4). Probably the same pattern has occurred in Douglasfir stands on the BNF, although data comparing pre- and 

post-European-American settlement are lacking (table 4). Some research suggests that such ranges are too 

narrow and are biased toward shorter intervals (Baker 

and Ehle 2001), but frequent, low-intensity fires probably characterized the scattered low-elevation forests and 

woodlands of the BNF. Grazing removes herbaceous fuels and, after the introduction of livestock, could have 

further increased the duration of fire intervals. Because 

the 20th century probably was warmer than the HRV reference period, fire intervals should be shorter than the 

HRV, not longer, based on climate alone.

At the landscape scale, no data are available on fire 

frequency in the BNF during the HRV period. However, 

surface fires were probably pervasive throughout the 

low-elevation forests and attempts at fire suppression 
USDA Forest Service RMRS-GTR-140. 2005 41

have become increasingly more effective. Thus, mean 

fire return interval at the landscape scale probably is also 

outside the HRV (moderate confidence).

The extent of area burned per year also probably was 

reduced below the HRV on low-elevation forests of the 

BNF (low confidence). The total area burned on lowelevation forests during the entire period from 1970 to 

1996 on the BNF was no more than 2000 ha (4940 acres) 

(of 53,676 ha [132,580 acres] of low-elevation forest; 

BNF Fire database). In general, because of successful 

fire suppression in lowland forests, many areas of ponderosa pine in the Rocky Mountains that were once 

maintained in savannas have changed into dense forests during the past century. Such forests now have high 

densities of small diameter trees (Covington and Moore 

1994; Knight 1994a; Fule and others 1997). Historic 

photos throughout the 1900s show that ponderosa pine 

woodlands in the BNF have increased in density as well. 

Additional factors such as livestock grazing may have 

contributed to this increase in density by reducing the 

competition for tree seedlings from grasses and forbs, as 

was found in Utah (Madany and West 1983). However, 

trampling may have offset such increases. Unique climatic conditions during the early 1900s (especially the 

wet, warm conditions from 1910-1920) also may have 

played a role in the increase of ponderosa pine density 

and fuel loadings (Savage and others 1996). As a result, 

intense stand-replacing fires in low-elevation forests 

generally have become more common in recent years, 

regionally, than they were during the 18th and 19th centuries (Agee 1997). Significantly, two large crown fires 

occurred in ponderosa pine forests in the Laramie Peak 

area of the Medicine Bow National Forest in 2002—the 

Hentzel Fire that burned 6016 ha (14,855 acres) and the 

Reese Fire that burned 7633 ha (18,848 acres).

Some surface fires are now prescribed on the BNF for 

low-elevation forests and non-forested vegetation types 

(B. Bornong, BNF ecologist, personal communication), 

and such burns can help restore the fire regime to the 

HRV. Without such surface fires, stand-replacing fires 

will occur. Stand-replacing fires probably are outside 

the HRV for all of the ponderosa pine woodlands and 

0-.1 .11-4 4.1-40 41-120 121-403 404-2020 >2020

Number fires or clearcuts per year

0

2

4

6

10

12

14

16

18

20

22 number of fires

0-.1 .11-4 4.1-40 41-120 121-403 404-2020 >2020

0

50

100

150

200

250

Area averaged over 

time period (ha/year)

8

number of clearcuts

Size class of burn (ha)

area burned

area clearcut

Size class of burn (ha)

Figure 32—Number (top) and area (bottom) of individual fires and clearcuts 

per year by size class (from the 

Bighorn National Forest). Note that 

the data are not standardized per unit 

area. Source: BNF 1970 – 1996 for 

fires and 1946 – 1998 for clearcuts
42 USDA Forest Service RMRS-GTR-140. 2005

some of the Douglas-fir woodlands on the BNF (high 

confidence).

5.1.3 Fire in aspen woodlands

Extensive fires during the 1800s appear to have created large stands of aspen in Colorado (Veblen and Lorenz 

1986) and on the west slope of the Sierra Madre in southcentral Wyoming (burned in 1841). It is unclear if these 

large stands developed largely from sprouts (ramets) or 

seedlings (genets) and what trees dominated the vegetation prior to the fires (Severson 1963; von Ahlefeldt 

and Speas 1996). On the BNF, fire has probably played 

a similarly important role in the establishment of new 

aspen stands (Brown and DeByle 1989; Romme and 

others 1997).

Fire frequency. Mean fire return intervals for aspen 

groves during the HRV period probably are essentially 

the same as for the other forest types with which they occur. Aspen is not considered to be highly flammable, but 

the stands often burn when the adjacent coniferous forest burns (DeByle and others 1987, 1989). Veblen and 

others (1994) found fire return intervals in aspen forests of 160 and 240 years (mean = 202) in Colorado, 

which was similar to some nearby conifer stands in the 

same area. Lightning-caused ignitions in aspen stands 

are probably rarer than in adjacent coniferous forests. If 

fires are of high intensity, some aspen root systems may 

be killed, thus favoring development of conifer stands 

(Parker and Parker 1983). However, the relatively mesophytic herbaceous understory in many aspen stands 

probably enables cooler fires than in adjacent stands of 

conifers. Such fires favor the development of large numbers of aspen root sprouts even though the aboveground 

part of the older trees (shoots or ramets) is killed (Veblen 

and Lorenz 1991). The abundance of aspen surely has 

fluctuated with the frequency, size and intensity of fires 

driven by climatic conditions, although grazers may also 

have had an effect (see sections 4.2.3, 6.1.3, and 6.2.2).

Changes from HRV. Most aspen stands that were surveyed on the BNF appear to have originated during two 

periods, namely, 1880 to 1920 and 1980 to the 1990s 

(fig. 27). The extensive fire disturbances during the late 

Size class (ha)

Number of fires/year

0

1

2

3

7

8

Lodgepole

Non-forest

Spruce-fir

Number of fires/year

0

1

2

3

7

8

High-elevation areas

0-.1 0.11-4 4.1-40 41-120 121-403 404-2020 >2020

Low-elevation areas

Douglas-fir

Non-forest

Ponderosa pine

Limber pine

Size class (ha)

0-.1 0.11-4 4.1-40 41-120 121-403 404-2020 >2020

Figure 33—Number of individual fires per 

year by size class and vegetation type on 

the Bighorn National Forest. Note that the 

number of fires per year is not standardized 

per hectare. Source: BNF for 1970-1996
USDA Forest Service RMRS-GTR-140. 2005 43

1800s (1870-1890) and early 1900s may have caused aspen seedlings or sprouts to establish at that time, but it 

is difficult to determine if they were previously common 

because aspen shoots (the ramets) often live only about 

100 years (although much older stems have been found 

and the aspen root system lives much longer and is capable of sprouting). Fire suppression since the mid-1900s 

probably has reduced fire frequency and extent because 

aspen regeneration has declined in some areas (Shepperd 

and others 2001). Bornong (1996a) documented a recent 

decline in the extent of aspen in the watershed of the 

North Fork of the Powder River, where clones are now 

usually less than one hectare in size. Across the Rocky 

Mountains, there is considerable variability in aspen regeneration, with stands in Utah apparently declining 

(Bartos and Campbell 2001) more so than in some other 

areas (Shepperd and others 2001).

The cause of the recent aspen regeneration by sprouting in some parts of the BNF after 1980 is likely due to 

mechanical treatment (clearfelling) as well as the increase 

in fires in the late 1980s (fig. 24). The stand age data for 

aspen are limited (28% surveyed) and the age distribution data (fig. 27) may be biased. However, similar to the 

adjacent coniferous forests, the mean fire interval probably is longer and the mean fire extent is lower in aspen 

forests today, at both the stand and landscape scales, than 

during the HRV reference period (moderate confidence).

5.1.4 Fire in non-forest vegetation

As noted previously, the composition and structure of non-forest cover types are affected by fire, 

especially where the non-sprouting big sagebrush occurs and where the natural fire regime has been altered 

by fire suppression and grazing. The Forest Service has 

conducted prescribed burns to reduce encroachment of 

woody plants (Cook and others 1994), which may help 

maintain the fire regime of some areas within the HRV. 

Although fire suppression may be causing increases in 

shrub cover and tree encroachment, such changes probably are not yet beyond the HRV at the stand or landscape 

level (low confidence). Fires are still very frequent in 

non-forested habitats and individual fires have burned 

up to 400 ha (988 acres) during the period 1970 to 1996 

(BNF fire database; fig. 33).

Cheatgrass (Bromus tectorum) is rare on the BNF (S. 

Gall, BNF Range Conservationist, personal communication). Rapid increases in cheatgrass could cause an 

increase in the mean fire return interval of some sites to 

beyond the HRV and a decline in the abundance of some 

native plants (Knight 1994a; Morgan and others 1996) 

(high confidence). More so than in forest vegetation, 

dramatic changes in non-forest vegetation could occur 

in the future if exotic plants become widespread.

5.2 Insects

Mortality caused by native insects has been an important form of disturbance in the high-elevation forests 

of the Rocky Mountains for millennia. The spruce beetle (Dendroctonus rufipennis) and mountain pine beetle 

(Dendroctonus ponderosae) are capable of reaching epidemic population sizes in spruce-fir, lodgepole pine, and 

ponderosa pine forests. As with fire, historic epidemics can be detected in the annual growth-ring patterns 

of trees, providing insight into pre-settlement dynamics 

(e.g., Veblen and others 1994). No studies of this nature 

have been done on the BNF, and therefore our current 

understanding of the HRV for insect populations since 

the 1600s must be derived from general observations 

during the last 100 years and from studies conducted 

elsewhere.

5.2.1 Insects in high-elevation forests

Mountain pine beetle. Based on historical reports that 

date back 100 years, the mountain pine beetle and other associated bark beetles (e.g., Ips spp.) do not appear 

to be a significant factor in the lodgepole pine forests 

of the BNF, at least after European-Americans arrived. 

Referring to conditions during the European-American 

settlement period, a 1906 report on the Bighorn Reserve 

(Coolidge 1906) states that “insects have never made 

serious or extensive ravages on lodgepole pine in this reserve. Bark borers kill or assist in killing scattered trees, 

but their work is unimportant.” Recent investigations 

have found that cold, high-elevation environments like 

much of the BNF may inhibit mountain pine beetle epidemics, apparently due to higher mortality of dormant 

larvae under the bark (Amman and others 1977; Amman 

1989). Indeed, few lodgepole pine trees have been affected at high elevations on the BNF (USDA Forest Service 

1985). Nevertheless, beetle epidemics may occur from 

time to time in some warmer, low- to middle-elevation lodgepole pine forests, particularly in older stands 

(Amman and others 1977; Amman 1978, 1989).

The mountain pine beetle survives in the phloem of the inner bark throughout most of its life cycle 

(McCambridge and others 1979). While healthy trees 

can often defend themselves by producing resin to expel the beetle, trees that are stressed or damaged may 

lack this ability. Once a tree becomes infested, it typically dies within a year, primarily because the blue-stain 

fungus introduced by the mountain pine beetle impedes 
44 USDA Forest Service RMRS-GTR-140. 2005

the flow of water and nutrients through the sapwood 

(Christiansen and others 1987).

Mountain pine beetle epidemics typically start in large 

diameter trees that are diseased or stressed. Therefore, 

most outbreaks occur in stands that are at least 80 years 

old, with trees at least 20 cm (7.8 inches) dbh (Koch 

1996; Schmid and Mata 1996). Typically, the larger 

trees are killed in groups of 100 or more (Schmid and 

Mata 1996). The result is to reduce the average tree 

diameter in a stand while creating small to large openings (Schmid and Mata 1996). By killing large trees, 

mountain pine beetle epidemics increase the number of 

standing dead trees that can become snags, which eventually fall and become coarse woody debris, thereby 

improving habitat quality for a number of species (Balda 

1975; Amman and others 1977). Also, the canopy gaps 

stimulate the growth of understory plants and small trees 

(Stone and Wolfe 1996), which creates a ladder of fuel 

from the forest floor to the canopy as they grow taller. Hence, flammability increases because of the beetles. 

Notably, the total productivity of the forest can return 

to pre-epidemic levels within 10-15 years (Romme and 

others 1986).

Hazard ratings have been developed for the mountain 

pine beetle based on tree diameter, age, and location by 

latitude and elevation (Amman and others 1977). Stands 

with diameters of <18 cm (<7 inches) dbh, 18-20 cm (7-

8 inches) dbh, and >20 cm (>8 inches) dbh are of low, 

moderate, and high susceptibility, respectively. Stands 

<60 years, 60-80 years, and >80 years are considered to 

be of low, moderate, and high susceptibility, respectively; and stands with elevations >2590, 2290-2590, and 

<2290 m are of low, moderate, and high susceptibility, 

respectively. Thus, older stands of large lodgepole pine 

on the eastern side of the BNF, where elevations are lower, are of highest susceptibility.

The historic frequency and severity of mountain 

pine beetle epidemics during the HRV period vary 

considerably in the Rocky Mountains, depending on environmental conditions such as elevation and climate. 

On the scale of an entire National Forest (landscapescale), an epidemic may occur every 20 to 40 years 

(Johnson 1995; Schmid and Mata 1996). Return intervals for an individual stand are longer (50-100 years). 

The duration of individual epidemics may vary from 

one to 10 years, with the average being six (Schmid and 

Mata 1996). Epidemic severity appears to be highest in 

the northern Rockies, where millions of trees have been 

killed in a single year (Klein and others 1979), although 

outbreaks also have been large in Colorado (Schmid and 

Mata 1996). At the latitude of the BNF, Amman and others (1977) estimated that lodgepole pine forests up to 

2500 m (8200 ft) elevation are susceptible to only 25 to 

50% mortality, while those above 2500 m would likely 

incur less than 25% mortality. Some research suggests 

that infestation risks may be even lower where grouse 

whortleberry (Vaccinium scoparium) is common in the 

understory (Amman 1977), which is true for large areas 

in the BNF.

The fact that mountain pine beetle epidemics are more 

frequent at lower elevations suggests a relationship with 

warmer temperatures. Thus, it is plausible to suggest that 

epidemics have been more common with climate warming during the last century (fig. 19) and that they will 

become more common if this warming trend continues.

Spruce beetle. As with the mountain pine beetle, the 

spruce beetle has not been an important cause of disturbance on the BNF during the last 100 years (Allen and 

Harris 1999), though it has caused heavy spruce mortality in Colorado and central New Mexico (e.g., Baker 

and Veblen 1990; Veblen and others 1991a and b; Veblen 

and others 1994). The two largest recorded outbreaks in 

Colorado occurred in the mid- to late-1800s (Sudworth 

1900; Baker and Veblen 1990) and in the 1940s (Hinds 

and others 1965).

As no specific information is available for the BNF, 

our estimates for the HRV of spruce beetle epidemics 

are based primarily on studies and observations from 

Colorado and New Mexico. The 1940s epidemic, which 

killed 99% of overstory spruce trees across more than 

282,800 ha (698,516 acres) on the White River National 

Forest in Colorado, is believed to be an extreme example (Hinds and others 1965; Schmid and Mata 1996). 

Historically, it appears that spruce beetle epidemics kill 

anywhere from 5 to 99% of large spruce trees (greater 

than 10 cm dbh) over areas ranging from small patches to thousands of hectares (Schmid and Mata 1996). 

Based on tree-ring records in a part of the White River 

National Forest, Veblen and others (1994) estimated that 

the average return interval for spruce beetle epidemics 

on the landscape was 116 years (range = 111-122 years), 

with a longer period of 259 years required for a single 

stand to be affected. Because the spruce beetle typically 

does not attack trees less than 70 years old, epidemics 

are not likely in stands that have had a stand-replacing 

disturbance in less than that amount of time (Veblen and 

others 1994).

Susceptibility of spruce stands on the BNF to future 

spruce beetle epidemics is uncertain. Endemic populations are normally found in windthrown or otherwise 

fallen spruce trees (i.e., logging residue). The 1940s 

epidemic in Colorado was triggered by an extensive 

blowdown in 1939 (Hinds and others 1965). However, 

the large blowdowns on the BNF in the mid-1900s and 
USDA Forest Service RMRS-GTR-140. 2005 45

early 1990s have not led to the expected spruce beetle 

outbreaks (1953 BNF historical report; Allen and Harris 

1999). It is possible that an outbreak could still result 

from the 1993 blowdown, but that is unlikely after a 

lapse of 10 years (K. Allen, Entomologist, Forest Health 

Management, U.S. Forest Service, personal communication). Forest susceptibility to spruce beetle epidemics 

has not been defined as precisely as for mountain pine 

beetles, but Schmid and Frye (1976) outlined the following four characteristics of highly susceptible stands: (1) 

average dbh >41 cm (16 inches), (2) basal area >34 m2/

ha (>148 ft2/acre), (3) >65% spruce in the canopy, and 

(4) locations in well drained creek bottoms. The effects 

of a spruce beetle epidemic on the BNF would likely 

be similar to a mountain pine beetle epidemic, with the 

creation of snags, coarse woody debris, and fuel continuity. Flammability would increase as well. Because the 

spruce beetle does not attack subalpine fir, a rapid shift 

in tree species abundance occurs that may persist until 

the next crown fire or wind storm (Schmid and Hinds 

1974).

Western balsam bark beetle and “fir decline.” In conjunction with other disease agents, the western balsam 

bark beetle (Dryocoetes confusus) appears to be causing widespread mortality of subalpine fir throughout the 

Rocky Mountains (Allen and Harris 1999). It is a native 

insect like the mountain pine beetle and spruce beetle, 

but it attacks subalpine fir primarily. Root disease pathogens such as Armillaria (Armillaria spp.) and Annosus 

(Heterobasidon annosum) may contribute to what has 

been referred to as a regionwide decline in subalpine 

fir (Morrison 1981; Wargo and Shaw 1985). To date, 

the exact cause and disease agents responsible for the 

mortality of subalpine fir are unknown (western balsam 

bark beetle and Armillaria are suspects), but the decline 

is obvious in numerous and extensive areas on the BNF 

(Allen and Harris 1999). Affected areas typically are circular patches of several dead and dying trees, with some 

that have fallen over. Young seedlings and saplings growing in the area are also dead and surrounding trees have 

poor growth (Shaw and Kile 1991). Because so little is 

known about the cause of the fir decline, interpreting its 

HRV has not been done.

Other insects. Numerous other insects are known 

to occur in the high-elevation forests of Wyoming and 

Colorado, such as the pandora moth (Coloradia pandora) (Schmid and Mata 1996) and the western spruce 

budworm (Choristoneura occidentalis) (Allen and Harris 

1999), but they are not presently viewed as a problem in 

high-elevation forests on the BNF.

Changes from HRV. Given that insect outbreaks were 

rare before clearcutting and continue to be rare, there is 

no evidence that the frequency of mountain pine beetle or spruce beetle outbreaks is outside the HRV on the 

BNF (moderate confidence). It is unknown if the suspected causes of the fir decline (western balsam bark 

beetle and associated root diseases) are outside the 

HRV, but the spread of this disturbance is of concern to 

BNF managers (C. Thomas, BNF silviculturist, personal communication). Schmid and Mata (1996) suggested 

that insect populations and their effects in the southern 

Rocky Mountains are currently within their respective HRVs, with some important caveats. Specifically, 

measurements of epidemics are imprecise, making the 

comparison of past, present, and future epidemics difficult. However, it is clear that the insects affecting 

Rocky Mountain forests are native, and probably they 

have reached epidemic population sizes from time to 

time throughout the post-glacial history of these forests. 

Human influences such as silvicultural treatments can 

slow the spread of outbreaks, but fire suppression could 

have the opposite effect. Both management activities, 

combined with climate change, could cause epidemic 

frequency and severity to move either below or above 

historic levels in the future (Schmid and Mata 1996).

5.2.2 Insects in low-elevation forests

As at higher elevations, the primary insects affecting 

low-elevation forests on the BNF are the mountain pine 

beetle and the western spruce budworm (Allen and Harris 

1999). The Douglas-fir beetle (Dendroctonus pseudotsuga) may be present in scattered areas, though its effects 

so far have been relatively minor (Allen and Harris 

1999). The introduced gypsy moth (Lymantria dispar) 

has been observed in Wyoming, but no populations of 

this insect are known to have persisted in the state (K. 

Allen, Entomologist, Forest Health Management, U.S. 

Forest Service, personal communication).

Mountain pine beetle. A fluctuating population of 

mountain pine beetles has killed large numbers of ponderosa pine along the east face of the Bighorns, with 

serious outbreaks in the 1950s and the 1970s when an 

estimated 6,000 or more trees were killed. From 1961-

65, trees were treated with chemicals to reduce mountain 

pine beetle infestations (Allen and Harris 1999). Areas 

of concern in the 1980s include the Sand Turn, Story, 

Red Grade, and Hospital tracts (USDA Forest Service 

1985). The majority of the infested trees in these areas 

were not on the BNF but the epidemic was of considerable concern to local residents. Additionally, many 

limber pine trees were killed by the beetles in Tensleep 

Canyon from 1991 to 2000 (C. Thomas, BNF silviculturist, personal communication).
46 USDA Forest Service RMRS-GTR-140. 2005

As in lodgepole pine forests, epidemics in stands of 

ponderosa pine often start when the beetles kill small 

groups of 3 to 10 of the larger trees (Schmid and Mata 

1996). If sufficient stresses are present in the “starter 

trees” (e.g., old age, water stress, or disease), the epidemic may spread across the landscape, killing groups of 

over 100 trees (Schmid and Mata 1996). The results of 

such outbreaks can cover large areas of the landscape, 

reduce the average tree diameter in a stand, and create 

small canopy gaps as well as large openings (Schmid 

and Mata 1996). As beetle-killed trees become snags and 

downed logs, they contribute to structural diversity (and 

therefore habitat diversity), at the same time providing 

fuel for the next fire (Lundquist 1995a; Schmid and Mata 

1996). Other species not susceptible to mountain pine 

beetle, such as Douglas-fir, may become more dominant 

(Schmid and Mata 1996). Based on the hazard rating 

developed for the Black Hills (Schmid and Mata 1992; 

Schmid and others 1994), large, old trees (18-33 cm dbh) 

in dense stands with >28 m2 of basal area per hectare are 

very susceptible to mountain pine beetle outbreaks.

Too little research in the BNF or nearby has been 

done to estimate epidemic frequency and severity, but 

mountain pine beetle outbreaks in the Southern Rocky 

Mountains have been more severe and more frequent in 

ponderosa pine than lodgepole pine—perhaps because 

of warmer winters at lower elevations where ponderosa 

pine occurs. On the landscape scale, Schmid and Mata 

(1996) estimated that an epidemic occurred in Colorado 

every 11 to 20 years in ponderosa pine landscapes 

during the HRV period. Beal (1943) found that the epidemics often coincided with periods of dry climatic 

conditions. Return intervals for an individual stand, however, are probably longer, with epidemics occurring once 

every 50 to 100 years (Johnson 1995; Schmid and Mata 

1996). Duration of an individual epidemic at the landscape scale varies from 2 to 5 years for short-lived 

epidemics to 7 to 14 years for long-term outbreaks 

(Schmid and Mata 1996).

The severity of mountain pine beetle epidemics also 

can vary considerably. In extreme cases, outbreaks result in the mortality of over a million trees in a single 

year (McCambridge and others 1979). In the Black 

Hills, historical reports indicate that 50,000 ha of mostly ponderosa pine were killed by a mountain pine beetle 

epidemic in 1895 (Shinneman and Baker 1997).

Western spruce budworm. The western spruce budworm is the most destructive defoliator in western 

forests. Its main hosts include Douglas-fir, with spruce 

and subalpine fir of lesser preference (Van Sickle 1985, 

Schmid and Mata 1996). In the spring, the larvae feed 

on buds and new needles, after which the adult moths 

disperse into other trees (mostly in July and August). 

Heavy outbreaks can completely defoliate overstory 

trees in 4 to 5 years. Defoliation reduces growth rates, 

reproduction, kills tree tops, and eventually kills whole 

trees. In contrast to mountain pine beetle, the smaller, 

suppressed trees are killed first, resulting in a higher average stand dbh but less total basal area (in live trees).

The frequency of western spruce budworm epidemics on the BNF at the stand or landscape scale in the past 

century is generally unknown. In Colorado and New 

Mexico, where most research on this insect has been 

done, the average outbreak intervals during the HRV 

period are similar to existing conditions there, ranging 

from 20 to 33 years (Swetnam and Lynch 1989, 1993) 

in individual stands. The epidemics last an average of 11 

years (Lynch and Swetnam 1992; Swetnam and Lynch 

1993). Records for the northwestern part of the BNF indicate that the budworm defoliated about 640 ha (1581 

acres) of Douglas-fir forest in 1985 and 400 ha (988 

acres) in 1994 (2.5% of the Douglas-fir over 10 years). 

Outbreaks have also been observed over approximately 

3000 ha (7410 acres) of ponderosa pine woodlands near 

Buffalo, Wyoming.

Douglas-fir beetle. As with other bark beetles, the 

Douglas-fir beetle produces one new generation of young 

per year, with most new attacks by the flying adults occurring in the late spring to early summer (McMillin and 

Allen 2000). Broods develop under the bark and overwinter as either adults or larvae. Attacks of this beetle 

are most successful on the large-diameter, mature trees 

in high-density stands that contain a high proportion of 

Douglas-fir in the overstory (Schmitz and Gibson 1996). 

McMillin and Allen (2000) found that three factors, 

namely, total basal area, Douglas-fir basal area, and the 

percentage of the stand that is Douglas-fir, were most 

important in determining the level of tree mortality.

Typically, the Douglas-fir beetle reproduces in scattered trees that are highly stressed, such as windfall, 

defoliated or fire-scorched trees (Lessard and Schmid 

1990; McMillin and Allen 2000). If enough stressed 

trees are available, beetles can increase and infest nearby 

healthy trees (Furniss and others 1981). Thus, Douglasfir beetle epidemics frequently occur after extensive fires, 

which create large areas of weakened Douglas-fir trees 

(McMillin and Allen 2000). Such epidemics have not yet 

been observed on the BNF, possibly because extensive 

fires in Douglas-fir forests have not occurred there.

The Douglas-fir beetle can cause widespread mortality of Douglas-fir in the Southern Rocky Mountains. 

Outbreaks have been observed to occur every 15 to 35 

years in the same stand and they last from 5 to 10 years 

(Hadley and Veblen 1993; Schmid and Mata 1996). 
USDA Forest Service RMRS-GTR-140. 2005 47

Outbreak frequencies at the scale of larger landscapes are 

unknown, but 7569 ha (18,695 acres) on the Shoshone 

National Forest (5% of the Douglas-fir on the Forest) 

were infested from 1992 to 1999 (an estimated 37,548 

trees killed; McMillin and Allen 2000).

Changes from HRV. For low-elevations forests, ponderosa pine has likely evolved with the influence of the 

mountain pine beetle, as it has with the influence of fire. 

In the past 50 years, however, fire suppression has created densities of young trees not often seen in previous 

centuries (as discussed previously and below). Such increased densities can contribute to water and nutrient 

stress, thereby reducing tree vigor and potentially increasing the susceptibility of some stands to mountain 

pine beetle epidemics. Given the influences of fire suppression, it is possible that the severity of ponderosa pine 

infestations in the latter half of the past century have increased. Intervals between outbreaks on the landscape 

have been about 10 to 20 years in recent decades on the 

BNF. Such levels are close to estimates during the HRV 

period in Colorado, so we conclude tentatively that outbreaks are probably still within the HRV on the BNF 

(low confidence). Even if the return interval for beetle 

outbreaks is shorter than the HRV, the cause could be the 

warm and dry conditions of the 1980s. If true, then the 

most recent epidemics may be natural events rather then 

events caused by management activities. Timber harvest 

essentially has not occurred in the ponderosa pine forests of the BNF. Therefore, harvesting could not have 

affected the HRV of insect outbreak frequency or severity in that forest type.

Fire suppression could also have increased the frequency of western spruce budworm outbreaks, but, on 

the other hand, silvicultural practices such as clearcutting 

could have the opposite effect. Relative to high-elevation forests, less clearcutting occurs in Douglas-fir forests 

(fig. 34). Therefore, harvesting probably has had a small 

effect on the frequency of budworm epidemics in that 

forest type (low confidence). Western spruce budworm 

outbreak frequencies across the landscape are unknown, 

but at the stand level, the average outbreak intervals during the HRV period in Colorado and New Mexico are 

similar to existing conditions in those states, ranging 

from 20 to 33 years (Swetnam and Lynch 1989, 1993) and 

lasting for an average of 11 years (Lynch and Swetnam 

1992; Swetnam and Lynch 1993). Thus, western spruce 

budworm incidence on the BNF is probably also within 

the HRV (low confidence).

Fire suppression and the low level of harvest in 

Douglas-fir forests (1%) may be increasing the susceptibility of Douglas-fir forests to the Douglas-fir beetle 

on the BNF. Douglas-fir beetle presently occurs only in 

scattered areas and large outbreaks have not been recorded. Even if outbreaks occur in the future, they probably 

will not create conditions that are beyond the HRV (moderate confidence), as they occur quite frequently in other 

parts of the Rocky Mountain region.

5.2.3 Insects in aspen woodlands

Various insect species defoliate aspen trees, but 

two are of special concern—the forest tent caterpillar (Malacosoma disstria) and the large aspen tortrix 

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Figure 34—Number (bars) and area (lines) of individual 

clearcuts by size class and vegetation type on the Bighorn 

National Forest. A clearcut patch was defined as an area 

clearcut during a month-long period that created one contiguous patch. Note that the data are not standardized per 

hectare. Source: BNF data for 1946-1998
48 USDA Forest Service RMRS-GTR-140. 2005

(Choristoneura conflicta) (Allen and Harris 1999). Both 

can affect large areas over longer periods than most other insects, though epidemics for these two insects have 

not been reported for the BNF. After the overwintering 

eggs hatch, the larvae of the tent caterpillar feed on the 

growing leaves. When population sizes are high, this 

caterpillar quickly defoliates entire trees and stands. The 

trees may produce new leaves, but infestation for several 

years in a row is lethal. When this happens, new aspen groves develop by sprouting or the conifer saplings 

in the understory grow into the canopy more rapidly. 

Epidemics occur every 10 to 20 years in northern New 

Mexico and southern Colorado, with a single epidemic 

lasting for up to 10 years or longer (Hinds 1976). The 

tortrix similarly has larvae that feed at the time of leaf 

expansion, but they also feed on buds. This insect can 

reach epidemic population sizes that persist for two to 

three years in some areas (Allen and Harris 1999).

In general, there is no basis to conclude that the characteristics of insect outbreaks in aspen stands are beyond 

their HRV (moderate confidence).

5.2.4 Insects in non-forest vegetation

Insects causing epidemics on non-forest vegetation 

have not been reported in any BNF documents that we 

have seen, nor have we found information on such events 

in other parts of the Rocky Mountains that would enable 

an HRV interpretation.

5.3 Disease

Pathogens such as comandra blister rust (Cronartium 

comandrae), dwarf mistletoe (Arceuthobium americanum), various root diseases (Armillaria spp., 

Heterobasidion annosum), broom rusts (Melampsorella 

carophyllacearum and Chrysomyxa arctostaphyli), western gall rust (Peridermium harknessii), and 

heart rots are all native elements of the BNF and other Rocky Mountain forests (Johnson 1995; Allen and 

Harris 1999). They often have the effect of reducing tree 

growth in a stand, or even causing localized mortality. 

Consequently, along with insects, they are commonly 

viewed as detrimental to “forest health.” Despite negative effects on short-term productivity, plant pathogens 

have been widely recognized for their positive contributions to biological diversity and various ecosystem 

processes (Gill and Hawksworth 1964; Hawksworth 

1975; Tinnen and others 1982; Dinoor and Eshed 1984; 

Tinnen 1984; Johnson 1995).

5.3.1 Disease in high-elevation forests

Comandra blister rust. The most widespread tree disease in high-elevation forests on the BNF is comandra 

blister rust, which is a native fungus that attacks lodgepole pine (Lundquist 1993). On six permanent plots on 

the BNF, 18% of the lodgepole pine trees were infected 

in 1995, of which 30% had severe infections and topkill (Allen and Harris 1999). At the landscape scale on 

the BNF, Lundquist (1993) found that 77% of the townships he surveyed from the roadside in 1991 had infected 

lodgepole pine stands, and 20% of the townships had severely infected stands (two or more infected stands per 

1.6 km [1 mile] of road; fig. 35). Infections were scattered throughout the BNF, but the most severe infections 

were on the east side at high elevations.

Comandra blister rust requires proximity of two host 

plants, lodgepole pine and comandra (Comandra umbellata). The spores are spread by wind from the comandra 

(also known as bastard toadflax) to infect pine needles 

and shoots. The fungus can eventually form a girdling 

canker that causes topkill and reduces tree growth thereafter (Geils and Jacobi 1991). Trees with topkill usually 

are at least 80-90 years old (K. Allen, Entomologist, 

Forest Health Management, U.S. Forest Service, personal communication). The younger trees (up to 80 years) 

are more susceptible to death than older trees because 

a smaller diameter provides a greater chance of the infection developing into stem-girdling cankers (Johnson 

1986a; Geils and Jacobi 1990). The canopy opens when 

trees are topkilled, enabling smaller lodgepole pines and 

other species to grow into the canopy (Krebill 1965). 

Sometimes a lower branch forms a new leader, creating 

a fork or crook in the trees.

From 1910 to 1945, the incidence of comandra blister 

rust increased dramatically, apparently due to unusually 

warm, moist summers (Krebill 1965). In the mid-1900s, 

Andrew and Harrison (1959) reported that about 25% 

of the lodgepole pine stands in Wyoming were infected. 

During the HRV period, the disease may have occurred at 

relatively low levels during cool periods and at higher levels during warm, moist periods, such as the early 1500s, 

early 1700s, and at the present time (figs.18 and 19).

Dwarf mistletoe. The second-most widespread disease at the present time on the BNF is dwarf mistletoe, 

a parasitic vascular plant that grows primarily on lodgepole pine, ponderosa pine, and limber pine in Wyoming. 

Several species are involved, but Arceuthobium americanum appears to be most common on BNF tree species 

(Hawksworth 1958; Hawksworth and Wiens 1972). The 

effects of dwarf mistletoe on a host tree include slowed 

growth, spike tops, witches brooms, dead branches and 
USDA Forest Service RMRS-GTR-140. 2005 49

Figure 35—Distribution by township of various diseases surveyed on the Bighorn National Forest in 1991. After Lundquist 

1993.
50 USDA Forest Service RMRS-GTR-140. 2005

eventual tree death. It can develop on trees of all sizes, but 

incidence of the disease is greatest in larger trees and it 

appears to spread most rapidly in uneven-aged landscapes 

(Kipfmueller and Baker 1998). While its effects can be 

negative for silviculture and the safety of forest visitors, 

mistletoe can also be beneficial for nesting birds and other animals (Hawksworth and Johnson 1989). Working in 

ponderosa pine forests, Bennetts and others (1996) found 

that bird abundance and diversity was greater in stands infected with mistletoe.

During an extensive roadside survey on the BNF in the 

1980s, Johnson (1986b) found 36% of surveyed stands 

were infected with mistletoe. Later, in 1991, Lundquist 

(1993) found 71% of surveyed townships had at least 

one stand with mistletoe infections (6% had severe infections; fig. 35). Although infections occurred throughout 

the BNF, most of the severe infections were in the south. 

The symptoms of mistletoe infection usually were most 

severe in localized areas. Notably, the severity level of 

dwarf mistletoe varied more from place to place than all 

the other major diseases on the Forest (Lundquist 1993). 

Kipfmueller and Baker (1998b) stressed that a “healthy 

lodgepole pine forest” probably has always had varying 

levels of dwarf mistletoe infection, and that some old 

forests are not infected.

Historically, the geographic spread of heavy infection 

centers was most likely limited by stand-replacing fires. 

Where such fires kill all infected trees, they essentially 

eliminate dwarf mistletoe from the stand until re-infection 

occurs, which can take several years to decades depending on the size of the fire because of the slow rate of 

growth and spread of the mistletoe plant (Hawksworth 

and Wiens 1972). However, the relationship between fire 

and dwarf mistletoe is complex. Where infected trees 

survive a fire, the mistletoe can infect new seedlings, 

creating new infection centers during the early stages of 

succession (Kipfmueller and Baker 1998b). In the earliest 

surveys of the Rocky Mountains, Mason (1915) described 

the distribution of severe mistletoe damage as scattered 

and localized. Although precise levels of dwarf mistletoe 

infection in the 1800s are not known, it probably has been 

present on the BNF at all levels of severity for centuries or 

longer (Kipfmueller and Baker 1998b).

Other diseases. Broom rust (Chrysomyxa arctostaphyli or Melampsorella caryophyllacearum), which 

infects fir and spruce, is another pathogen of importance 

(Lundquist 1993; fig. 35). However, this disease and 

others seem to have minor effects on the high-elevation 

forests of the BNF. An exception is Armillaria, which in 

combination with the western balsam bark beetle may 

cause patch mortality in subalpine fir (fig. 35), as discussed in section 5.2.1 on insects.

While the combined effects of minor diseases and 

their interaction with large and small disturbance agents 

(including porcupines, which feed on tree bark) undoubtedly contribute to a variety of ecological processes, very 

little is known about such interactions. Overall, diseases 

are important elements of subalpine forests in the BNF. 

Most stands are likely to have numerous pathogens 

as concurrent members of the biological community 

(Lundquist 1993), which contributes to the biodiversity 

of an area (Lundquist 1995a).

Changes from HRV. Dwarf mistletoe can spread in 

young as well as older trees, but incidence levels are 

higher when stands have larger trees. Dwarf mistletoe 

also increases when landscapes contain stands with uneven-aged trees and small clearcuts or group-selection 

cuts (Johnson 1995). Such conditions occur on portions of the BNF. Some older stands with large trees 

are present (at least 10% of current forests; see fig. 21) 

that probably would not have existed today without fire 

suppression (taking into consideration that much of the 

Forest is in young, less flammable stages). Tie-hacking 

and selection harvests, which produce the more susceptible uneven-aged stands, make up about 9% of the land 

on the BNF (15% of the forested area), and small clearcut patches (<8 ha [<20 acres]) were commonly created 

in the 1980s and 1990s (figs. 13 and 14; Harris and others 

1997)). Working in the Medicine Bow National Forests, 

Selmants and Knight (2003) found that as many as 25% 

of the lodgepole pine trees in stands developing after 

clearcutting could become infected within 40 years.

By contrast, other areas on the BNF probably have 

reduced incidences of dwarf mistletoe. For example, the 

large clearcuts (>8 ha [>20 acres]) common in the 1960s 

(figs. 13 and 14) may have slowed the spread of dwarf 

mistletoe. Some younger stands in the high-elevation 

forests would have been older without clearcuts (4% of 

the forest, fig. 26), and now they are less susceptible. 

Of course, large, natural, even-aged stands are common 

on the landscape even without timber harvest, keeping 

dwarf mistletoe at lower levels in large areas.

Because the extent of clearcutting has not fully counteracted the more extensive effects of partial cutting and 

fire suppression on the BNF, dwarf mistletoe incidence 

is probably above its HRV at the landscape scale (low 

confidence). Incidences in local uneven-aged stands 

where dwarf mistletoe occurs, and that would have been 

even-aged without harvest (group or individual selection 

cuts and tie-hacking), are probably beyond their HRV at 

the stand scale (low confidence). Similarly, mistletoe in 

stands that are older due to fire suppression or younger 

due to clearcuts may be above and below the HRV, respectively (low confidence).
USDA Forest Service RMRS-GTR-140. 2005 51

Comandra blister rust attacks stressed trees of any 

age, and such stress can increase with high tree densities. It is a common perception that fire suppression 

has increased tree densities and stress in high-elevation 

forests, but there is little evidence to support that. Standreplacing fires dominate the high-elevation forests, and 

even light fires can kill the thin-barked trees that inhabit 

those forests (lodgepole pine, Engelmann spruce, subalpine fir). Because fire suppression probably has not 

increased tree density or stress at high elevations, the 

severity and distribution of comandra blister rust and 

other diseases, except for dwarf mistletoe, probably are 

still within the HRV (low confidence), especially on the 

landscape scale and given the current relatively warm 

climatic conditions that probably support the moderate 

levels of infection seen on the BNF. Other less prominent diseases are probably also within the HRV (low 

confidence).

5.3.2 Disease in low-elevation forests and 

woodlands

Blister rusts. Various diseases also are present in the 

low-elevation forests and woodlands of the BNF, particularly two blister rusts. Comandra blister rust infects 

ponderosa pine as well as lodgepole pine, but little is 

known about its occurrence in ponderosa pine on the 

BNF (Allen and Harris 1999). The second, white pine 

blister rust (Cronartium ribicola), was introduced to 

North America and has infected some stands of limber pine. It was apparently introduced to the Tongue 

River drainage of the BNF in the early 1960s (Lundquist 

1993). Like comandra blister rust, the white pine blister 

rust requires an intermediate host to complete its life cycle, namely, currant or gooseberry (Ribes spp.) (Krebill 

and Hoff 1995; Allen and Harris 1999). Wind-dispersed 

spores from the shrubs infect pine needles and eventually create cankers that girdle and kill branches, if not the 

whole tree. Based on limited surveys, most of the forest 

has low incidence levels of white pine blister rust (landscape-level), although many limber pine trees have been 

killed by the disease in Ten Sleep Canyon (Lundquist 

1993; Allen and Harris 1999). More surveys are needed 

to identify hotspots and the spread of the disease. White 

pine blister rust can have serious impacts on limber 

pine forests over time, such as in Montana and southern 

Alberta, where over a third of the limber pine trees at the 

landscape scale are dead and 90% of the remaining live 

trees are infected (Kendall 1998).

Other diseases. Other diseases in low-elevation forests include western gall rust, Armillaria root disease 

(Armillaria mellea), red rot (Dichomitus squalens), 

Schweinitz root rot (Phaeolus schweinitzii), and limb 

rust (Peridermium filamentosum) (Lundquist 1993, 

Lundquist 1995a). While such diseases can cause localized mortality and damage to various tree species, 

none of them, individually, appears to have much effect on the BNF as a whole. Rather, it is the combined 

effects of diseases and other disturbance agents that influence stand structure and composition (e.g., Lundquist 

1995a). Notably, dwarf mistletoe is not common on ponderosa pine in the BNF, though it is common in southern 

Wyoming and in Colorado. The rarity of dwarf mistletoe on the ponderosa pine of the BNF may be due to 

geographic isolation or factors that either make the trees 

more resistant to mistletoe invasion or provide an environment not suitable for mistletoe (Hawksworth and 

Wiens 1972).

Changes from HRV. With the exception of white 

pine blister rust, the diseases found in the low-elevation forests of the BNF are native and probably 

have not been greatly affected by human influences. 

Silvicultural treatments probably have been too limited 

in the BNF to increase or reduce the spread of disease 

across the landscape. Our observations suggest that the 

native diseases in low-elevation forests currently appear to be within their HRV at the stand and landscape 

level (moderate confidence). However, the presence of 

an exotic disease such as the white pine blister rust 

creates conditions that definitely are beyond the HRV 

(high confidence).

5.3.3 Disease in aspen and non-forest 

vegetation

Aspen is affected by root diseases, canker-causing 

fungi, and a heartrotting fungus (Phellinus tremulae) 

(Allen and Harris 1999). Cankers form in wounds caused 

by animals, humans, or other agents; and heartrotting 

fungi colonize the sapwood and produce a fruiting conk 

(Hinds 1976; Walters and others 1982). Conversion of 

young aspen stands to older stands, a result of fire suppression, may be increasing the occurrence of diseases at 

the stand, landscape, and regional scales (Hinds 1985), 

although clearfelling has been used to offset such increases where that seems desirable (Johnson and others 

1995). Human activities in developed recreational areas 

may increase tree wounding (Johnson 1985), thereby 

increasing infection rates beyond the HRV in such localities (low confidence). However, disease infection rates 

in other aspen stands and across the landscape are probably within the HRV (low confidence).

With regard to non-forested vegetation, essentially 

nothing is known about the ecological effects of diseases and their HRV.
52 USDA Forest Service RMRS-GTR-140. 2005

5.4 Wind

5.4.1 Wind in high-elevation forests

Wind speeds are highly variable in the Rocky 

Mountains, ranging from very strong at ridge crests to 

light in some valleys and on the lee sides of peaks (Martner 

1986). Based on cursory observations, the BNF appears 

to have more storms capable of windthrow than most other National Forests in the northern Rockies (Howe 1997). 

The wind can blow down trees in small clumps (i.e., one 

to several trees) or topple whole stands of trees over 

thousands of hectares (Alexander 1964; Veblen and others 1991a). Large blowdowns typically produce a long, 

linear disturbance pattern oriented in the BNF in a southwest-northeast direction (fig. 36). Most severe storms that 

cause blowdowns on the BNF come from the southwest 

(B. Bornong, BNF ecologist, personal communication). 

The wind follows a straight path but the actual blowdown 

is not continuous, with patches of downfall separated by 

2 to 3 km (1.2-1.9 miles) or more. Many large trees are 

snapped off at 6 to 9 m (20-30 ft), but some are uprooted. 

Small trees may remain standing.

In 1991, about 670 ha of forest blew down in the 

northcentral portion of the BNF. Two years later about 

1212 ha of trees were blown down farther north, north 

of Highway 14 (USDA Forest Service 1994). About 

nine long, linear patches on the landscape were produced from blowdowns between 1955 and 1998 (long, 

linear yellow or blue patches in fig. 36), covering a total of about 1896 ha (4683 acres) (0.4 % of landscape) 

and averaging 211 ha (521 acres) per patch. The actual 

area affected by blowdowns in total was probably greater than that estimate because it included only patches 

identifiable on satellite imagery. Of the 1896 ha (4683 

acres) identifiable on the imagery, 405 ha (1000 acres) 

were partial blowdowns, in which many large trees were 

left standing (fig. 36). The mean recurrence interval for 

such windstorms on the BNF is unknown.

Elsewhere, in 1987 a windstorm leveled 6000 ha 

(14,820 acres) of forest in the Teton Wilderness (Knight 

1994a), and in 1997 winds of 200-250 km/hr (124-155 

miles/hr) toppled over 10,000 ha (24,700 acres) of forest on the western slope of the Routt National Forest in 

northern Colorado (Baker and others 2001; Lindemann 

and Baker 2001, 2002). 

Blowdowns interact with other kinds of disturbances. 

To illustrate, a dense pile of fine fuels is created when 

windfall occurs, greatly enhancing flammability. Also, as 

discussed above, there is the potential for an outbreak of 

spruce beetles on downed spruce trees (although the potential appears to be low on the BNF, based on historical 

records of the past 100 years). Standing trees weakened 

by fire, insects, and disease may be more susceptible to 

blowdown. Many trees in a stand are not toppled during 

blowdowns, making the effect more similar to a selective 

harvest than a clearcut (Lindemann and Baker 2001).

Recent studies of the Routt-Divide blowdown in northcentral Colorado indicate that various features of the 

physical environment and the vegetation determine where 

blowdowns are likely to occur. Physical factors seemed to 

be most influential, especially wind exposure, elevation, 

and aspect (Lindemann and Baker 2002). Unexpectedly, 

soil permeability, soil water-holding capacity, and distance to natural edges were not significantly correlated 

with the blowdown pattern. The effect of cover type varied with elevation. At lower elevations, aspen forests 

were less susceptible to blowdown and spruce-fir forests 

were more susceptible. At higher elevations, closer to the 

Continental Divide, younger stands were less susceptible 

than older stands (Baker and others 2001). These results 

suggest that both topography and vegetation structure can 

influence the extent and pattern of damage, but that the effects vary with elevation and wind intensity.

Changes from HRV. Blowdown has been a common 

disturbance following timber harvests, particularly for 

shelterwood (2- and 3-step canopy removal) and group 

selection cuts and on the leeward side of clearcut edges 

where trees are exposed (Alexander 1964; USDA Forest 

Service 1994; Vaillancourt 1995). However, clearcut, 

shelterwood, or group selection harvests have affected 

only 11% of the forested landscape at high elevations; 

clearcuts alone have affected only about 4% (BNF data). 

Consequently, the effects of harvest on blowdown frequency or extent surely must have been small. We can 

safely say that blowdowns, like fire, have always been 

and always will be an important factor in shaping landscape patterns and stand structure of high-elevation 

forests, and that current blowdown frequencies probably 

are within the HRV (high confidence).

5.4.2 Wind in low-elevation forests and aspen 

woodlands

No major blowdowns have been observed in the lowelevation forests or aspen groves on the BNF. Yet, just as 

in high-elevation forests, wind can have various effects 

on forests of ponderosa pine, Douglas-fir, and limber 

pine. As at higher elevations, the presence of predisposing factors such as disease, insects, and fire will affect the 

size of disturbance (Alexander 1986; Lundquist 1995a; 

Shinneman and Baker 1997). Limber pine often occurs 

on very windy sites, but its “limber” branches probably 

are an adaptation to reduce breakage.

In the Black Hills, Graves (1899) found evidence for 

one tornado in the 19th century; and another occurred in 
USDA Forest Service RMRS-GTR-140. 2005 53

Figure 36—Location of landscape disturbances on the Bighorn National Forest from 1955 to 1998. The linear patch

es in yellow are blowdowns. Source: Wyoming Game and Fish Department LANDSAT-derived database.
54 USDA Forest Service RMRS-GTR-140. 2005

1940 (Shinneman and Baker 1997). The more recent tornado leveled 1.5 million board feet of ponderosa pine. 

Aspen is also easily affected by blowdowns, as it has 

relatively weak stems and brittle branches (Veblen and 

Lorenz 1991).

Changes from HRV. Because only a few blowdowns 

have been documented in the low-elevation forests 

and in stands of aspen on the BNF, the differences between existing conditions and the HRV are unknown. 

However, timber harvest is not common in the low-elevation forests (<2% of low-elevation forests) and aspen 

woodlands, and the current conditions affecting blowdown frequency and extent in both cover types must be 

similar to conditions during the HRV period (high confidence). Wind is another natural phenomenon that will 

always be a potential disturbance agent in low-elevation 

forests and woodlands, as it is at higher elevations.

6. Historic Range of Variability for 

Stand and Landscape Structure 

Compared to Present Conditions

Of the numerous human influences on upland vegetation, three have had the most significant impact—fire 

suppression, timber harvest, and livestock grazing. In 

this section we focus on the effects of these human impacts on variables associated with stand structure and 

landscape structure. Fire suppression and livestock 

grazing could have affected large portions of the BNF. 

Timber harvesting, in contrast, has affected only about 

18% of the forested land area. As in the previous section 

on disturbances, our discussion includes conclusions on 

whether or not the variables probably are exceeding or 

remaining within the apparent historic range of variability.

6.1 Stand Structure

Stand and landscape structure both change through 

time as well as in space because of natural and humancaused influences. In this section we focus mainly on 

stands that have been harvested for timber or subjected 

to fire suppression, assessing probable changes through 

time within individual stands rather than comparing 

changes at the landscape scale. Landscape structure, 

which includes unharvested and harvested stands, is discussed in section 6.2.

If tie hacking, commercial thinning, and salvage 

harvests are included, the proportion of the forests 

affected by harvesting is approximately 18%. About 

4.7% was harvested using the shelterwood system, 3.3% 

by clearcutting, 0.4% with the seed tree approach, and 

0.3% by selection harvesting. Most of the clearcuts have 

been concentrated in three watersheds (watersheds 3, 7, 

and 8 in fig. 7; see fig. 13 also). Today, it is estimated 

that 5% of the forested land is old-growth (based on photo interpretation as described in section 4.2.1), but this 

estimate is preliminary because the old-growth inventory has not been completed.

As described previously, about 21% of the forests 

classified as suitable for harvesting in 1985 (37% of the 

forested land) have been harvested since 1940 and 9% 

have been clearcut. If tie hacking is included in harvest 

estimates, 40% of suitable lands have been harvested 

since the late 1800s. Thus, many more hectares could 

be subjected to silvicultural treatments in the future, including about 20,000 ha (50,800 acres) that already have 

been harvested for railroad ties. (In the plan currently 

being developed, the proportion of forested land classified as suitable for harvesting probably will be about 

185,000 acres, down from the 260,000 acres estimated 

in 1985 ; B. Bornong, BNF planner, personal communication).

The 40% of suitable lands (11% of the BNF as a whole, 

and 18% of the forests) that are known to have been 

harvested at least once, of which nearly half was for railroad ties, is the focus of our stand structure analysis for 

high-elevation forests. High-elevation forests classified 

as “unsuited for timber harvest” probably have experienced few changes at the stand scale that were caused 

by European-American activities. Fire suppression can 

change the proportions of the landscape in different successional stages (discussed in sections 4.2 and 6.2), as 

well as tree density at lower elevations, but we do not 

believe that fire suppression thus far has greatly affected the internal structure of high-elevation forest stands 

on the BNF (e.g., tree density at high elevations is not 

increased beyond the HRV relative to the age of the 

stand). In evaluating how management activities might 

have caused some variables to exceed their HRV, we 

focus on the effects of timber harvesting on stands at 

higher elevations and the effects of fire suppression at 

lower elevations (where very little harvesting has occurred). Stand variables are considered in this section; 

landscape changes are discussed in section 6.2.

6.1.1 Stand structure of high-elevation forests

The occurrence of fire at high elevations appears to 

have declined over the past century, but the amount of 

land affected by timber harvesting has increased. Some 
USDA Forest Service RMRS-GTR-140. 2005 55

effects of timber harvesting are similar to those of fire, 

insects, disease and wind storms, but others are different. For example, canopy gaps of varying sizes are 

created after both types of disturbances. In contrast, 

silvicultural treatments are designed partially, if not entirely, to manipulate stand structure in a way that favors 

the growth of certain species. Natural processes involved with forest development and succession do not 

lead to maximizing the rate of tree growth, or even total forest productivity (tree growth plus understory plant 

production). Instead, plant adaptations tend to facilitate persistence and the production of seed rather than 

growth rates. Consequently, our evaluation of many of 

the variables discussed below is based on the recognition of such fundamental differences between natural 

processes and silvicultural treatments.

Our focus in this section is on the following stand 

structure variables that are potentially affected by timber harvesting: tree density, regeneration time, seedling 

and sapling density, percent canopy cover, the density of 

canopy gaps, the density and cover of understory plants, 

plant species diversity, age- and size- class structure 

(the number of trees in a series of age classes and size 

classes), forest floor depth, the extent of disturbed mineral soil, the density of snags, and the amount of coarse 

woody debris. Small-scale patches in the canopy of one 

to several hundred square meters, such as those created 

by the death of one or a few trees, are considered part 

of the stand structure. Larger gaps are considered when 

discussing landscape structure (section 6.2).

As noted, there are essentially no data on stand structure for the HRV period (1600-1890). HRV analyses are 

still possible, but they must be based on a qualitative 

review of what is known about how current stand structure changes during succession and from one place to 

another, along with our impressions of what the forests 

must have been like prior to the arrival of EuropeanAmericans, based on the journals of early explorers and 

information about the biology of the dominant species. 

This analysis cannot be site specific, but the information 

we provide is necessary when developing site-specific 

management plans.

Based on the information we reviewed in sections 

4 and 5, and the nature of silvicultural practices on the 

BNF, we draw the following conclusions about variables 

pertaining to stand structure in forests dominated by 

lodgepole pine, Engelmann spruce, and subalpine fir:

Tree density. The naturally occurring number of trees 

per hectare is highly variable through space and time, 

ranging from a few hundred mature trees in open stands 

to over 15,000 per hectare (6073 per acre) in 100-yearold doghair stands of lodgepole pine. Various studies 

have shown that high lodgepole pine seedling densities are partially a function of the number of serotinous 

trees in a stand and fire intensity (Franklin and Laven 

1989; Anderson and Romme 1991; Turner et al 1997). 

Ten years following the 1988 fires in YNP, tree seedling density ranged from essentially no seedlings to very 

high densities (sometimes exceeding 100/m2 [9/ft2]) in 

different stands across the landscape. We have observed 

the same on the BNF. With succession, densely stocked 

stands may be thinned by natural mortality, but many 

doghair stands persist for well over 100 years—probably until the next stand-replacing disturbance, after 

which the area may develop low-density stands. When 

thinning is done for enhancing tree growth, the goal in 

the Bighorn National Forest is to have approximately 

750 trees per hectare (304 per acre) (C. Thomas, BNF 

silviculturist, personal communication). Thus, timber 

harvesting and associated thinning result in stand densities that are within the HRV (high confidence).

Regeneration time and seedling/sapling density. 

Concerning forest regeneration, some characteristics of 

clearcuts are similar to conditions created by large fires, 

such as the creation of an open environment for seedling establishment. Lodgepole pine has proven to be 

well-adapted for establishment and regeneration in the 

patches created by both fire and harvesting. In some areas, Engelmann spruce and subalpine fir can also invade 

after these disturbances (Doyle and others 1998). On 

most sites with lodgepole pine present before the disturbance, subsequent regeneration by this species has been 

very good (especially at <2900 m [<9512 ft] elevation). 

In fact, lodgepole pine often regenerates so prolifically after a clearcut that precommercial thinning has been 

recommended after about 20 years (Grasso and others 

1981; Geils and Jacobi 1991).

Notably, seedling establishment is much slower above 

2900 m (9512 ft) on the BNF (Jack 1900) and elsewhere 

(Stahelin 1943). High-elevation clearcuts often are subjected to high winds that blow snow into downwind 

forests. Consequently, new seedlings and saplings in the 

harvested areas often die, apparently because of the lack 

of snow protection from winter desiccation and high-intensity solar radiation (Knight 1994a). Livestock grazing 

also can retard seedling establishment (C. Thomas, BNF 

silviculturist, personal communication). Snags and 

coarse woody debris provide micro-environments favorable for snow accumulation along with shade and less 

intense wind, all of which favor new tree establishment.

From the late 1940s to the present, some BNF 

clearcuts have been in high-elevation spruce-fir forests 

(BNF data; fig. 34). Slash treatments that leave relatively low amounts of coarse woody debris could reduce 
56 USDA Forest Service RMRS-GTR-140. 2005

mean seedling densities from the mean for this variable 

during the HRV period, because the coarse woody debris provides some protection for seedlings. However, 

regeneration is often slow on rocky or sedimentary soils 

relative to granitic soils, whether after fire or harvest (B. 

Bornong, BNF ecologist, personal communication). The 

high natural variation in seedling density from site to 

site and the presently variable conditions for seedling 

establishment are probably still within the HRV (high 

confidence).

Management activities or prescribed fire have been 

used to facilitate tree regeneration and to reduce flammability through the removal of excessive slash. The 

Intermission Fire on the BNF in 1988 was sufficiently 

hot, due to the abundant slash, that much of the seed 

source burned (Howe 1997). In contrast, several onehectare patches that had reduced fuel loadings through 

slash treatment did not burn or burned less intensively and 

had good regeneration. However, hot fires in Yellowstone 

National Park also burned a significant amount of seed 

in the 1988 fires (Turner and others 1997). Apparently, 

conditions that create fires that burn much of the stored 

seed are still within the HRV.

Percent canopy cover and rate of gap formation. By 

thinning forests to maximize tree growth, silviculturists 

create a canopy that may be more open than would have 

occurred otherwise. When stands are thinned naturally, 

the canopy is opened up less than is usually done for silvicultural purposes. This assumes that surface fires and 

outbreaks of insects and diseases do not thin forests on 

the BNF in a comparable way as selective harvesting. 

Surface fires kill some of the trees in small groups, as do 

insects and diseases, but the dead trees (snags) remain in 

the forest. Unlike thinning, selective harvesting includes 

tree removal that probably lowers mean percent canopy cover below the HRV in forests of comparable age 

and site conditions (moderate confidence). Such effects 

may last no more than about 20 years, as the canopies of 

the remaining trees normally expand to fill the openings 

that were created, or new trees grow into the gaps from 

below. Group selection harvests would create somewhat 

larger canopy gaps (0.1 to 0.4 ha) that would take longer to fill.

Shelterwood harvesting removes about one-third of 

the trees at intervals of about 10 to 30 years, producing 

large gaps that temporarily create uneven-aged forests. 

Once the overstory is completely removed (after 10 to 

30 years, possibly longer), the stand becomes essentially even-aged. Some of the gaps from shelterwood cuts 

may mimic partial blowdowns or insect outbreaks for 

short periods, but the process of removing part and then 

all of the canopy trees creates gaps faster than during the 

HRV period because insect epidemics or fire typically 

have a within-stand turnover time that is considerably 

longer (at least 50 to 100 years). Thus, shelterwood cutting also produces canopy cover patterns that are not 

within the HRV.

Density of canopy gaps. As mentioned above, trees 

are gradually dying in the most healthy of natural forests, creating canopy gaps or openings in the forest 

canopy. Also, if a sufficiently large group of neighboring trees die, perhaps 10-20, a root gap is created as well 

as a canopy gap (Parsons and others 1994). Light penetration to the forest floor increases if a canopy gap is 

created, and competition for water and nutrients is greatly reduced if a root gap (large or small) is created. Both 

enhance the growth of the remaining trees as well as understory plants (including saplings). Indirectly, canopy 

and root gaps affect age-class structure, size-class structure, species diversity, and the abundance of some kinds 

of animals and other organisms.

Silvicultural systems that include group selection and 

thinning can create densities of canopy and root gaps 

that are similar to those found in unmanaged forests, and 

individual selection harvests create small gaps that are 

similar to natural gaps caused by the death of a single 

tree or several neighboring trees—though there is the 

difference of standing dead trees, as discussed previously. Shelterwood systems create larger, temporary gaps. 

Overall, the average number of gaps in a managed forest 

is likely to be higher than the HRV (moderate confidence) because of the motivation of managers to enable 

most of the remaining trees to grow faster.

Density and cover of understory plants. If managed 

forests have lower canopy cover or a higher density of 

canopy gaps than unmanaged forests, then the density and cover of understory plants usually will be higher. 

However, timber harvesting can leave an abundance of 

slash that could suppress some understory plants, as 

could surface soil compaction or other changes caused 

by the machinery that might be used. Species composition can be affected by slash treatments that disrupt the 

soil profile, which reduces the sprouting capacity of some 

understory plants and can be favorable for the invasion 

of new species (Selmants and Knight 2003), especially 

those with wind-borne propagates. For example, the machinery used for yarding, as well as for piling, burning, 

roller chopping, and tractor walking, can scarify the soil 

in ways that favor the establishment of lodgepole pine 

and Engelmann spruce seedlings. However, such scarification may also slow the recovery of some understory 

plants, such as grouse whortleberry, as suggested by von 

Ahlefeldt and Speas (1996) and the results of Selmants 

and Knight (2003) in the Medicine Bow National Forest. 
USDA Forest Service RMRS-GTR-140. 2005 57

Thus, species composition and abundance may be altered 

in ways that would not have occurred during the HRV 

reference period.

Grazing probably has not yet affected the understory 

plants significantly because high-elevation spruce-fir or 

lodgepole pine forests on the BNF are not heavily grazed 

(S. Gall, BNF range conservationist, personal communication). However, grazing has been reported to affect 

tree seedling success in regenerating stands (C. Thomas, 

personal communication). Such potential impacts of 

grazing should be quantified. Sheep often entered highelevation timbered areas in the late 1800s (Jack 1900), 

but it is difficult to know about the long-term effects on 

the forest understory.

Exotic plants can invade both managed and burned 

forests, but they apparently do not persist in 30- to 50-

year-old post-harvest stands on the Medicine Bow 

National Forest (Selmants and Knight 2003). The same 

is probably true for the BNF. Exotic plants often are common in road ditches, but, in the Medicine Bow National 

Forest, they apparently have not yet invaded the adjacent 

forests in large numbers (Dillon 1998).

Some plant species may be more sensitive to timber harvesting than to fire, wind storms, or other natural 

disturbances, and, of course, road building associated 

with harvesting decimates the native vegetation where 

the road bed was located and often provides habitat for 

introduced, weedy species. However, given that the density and cover of understory plants is highly variable in 

natural stands as well as in managed stands, there is no 

indication, to date, that timber harvesting would push 

variables associated with the understory vegetation beyond the HRV (high confidence).

Plant species diversity. All tree species present in the 

1700s and 1800s apparently are still very common on 

the BNF. High grading, which occurred earlier in the 20th

century, may leave a relatively high number of trees with 

less desirable wood characteristics, such as subalpine fir, 

or other species with malformed or small trees. More 

recently the practice of clearcutting may have increased 

the abundance of lodgepole pine, though fire could have 

caused the same shift. Nevertheless, within-stand tree 

species diversity is variable and probably within the 

HRV (moderate confidence), particularly since no new 

tree species have been introduced.

Research is insufficient to indicate the degree to 

which management activities during the last century 

have changed the genetic diversity of stands. If fire suppression has been effective, or becomes more effective 

in the future, the abundance of serotinous trees in managed forests may eventually decline below the HRV. To 

counteract such an effect, some management practices 

on the BNF are specifically designed to select for cone 

serotiny (Howe 1997).

The total species diversity of organisms that exist in 

any ecosystem is determined in part by disturbances, 

but timber harvesting, with the concomitant removal of 

coarse woody debris and the effects of machinery and 

slash disposal practices, is a new kind of disturbance 

to which some species may not be adapted. Also, some 

plants may be interior forest species that have been extirpated locally because of depth-of-edge effects associated 

with patch cutting (fragmentation), such as some species 

of orchids and herbaceous ericads (Dillon 1998; Baker 

and Dillon 2000). The cover of grouse whortleberry declines in proportion to the intensity of slash treatment, 

but it tends to persist in post-harvest stands and gradually increases in abundance, based on research done in the 

Medicine Bow National Forest (Selmants and Knight 

2003). Understory vegetation of post-harvest stands 

dominated by lodgepole pine at lower elevations appears 

to recover more rapidly than in stands of spruce and fir 

at higher elevations (Selmants and Knight 2003). Some 

plant species may be rare and easily extirpated from 

an area (e.g., Festuca hallii disappeared after 1898 in 

the head of Clear Creek). Some stands (about 5,900 ha 

[14,573 acres] or 5.8% of suitable land) have been subjected to at least two entries for the harvesting of many 

large trees, with the first one (tie-hacking) occurring 

around the turn of the century. In such stands, the species that are present today may be the species that can 

tolerate timber harvesting practices. Additional study is 

required to determine which species cannot.

Significantly, the species diversity in some areas may 

have increased because of the invasion of exotic plants. 

However, while the presence of such species increases the number of total species, one potential effect of 

exotics is to reduce the abundance of native species. 

Insufficient research has been done in Wyoming to determine the net effect of introduced species on species 

diversity and other variables in National Forests.

In general, there are few introduced plants in highelevation forests in Wyoming, and a relatively small 

proportion of the forests (20%, excluding low-elevation 

forests) has been subjected to harvesting thus far. Thus, 

we conclude that native plant diversity probably is not 

lower or higher than the HRV in high-elevation stands 

(low confidence). Significant changes could have occurred locally, especially in areas of severe disturbance 

and where exotic plants or other organisms have become 

abundant. Where that is the case, several ecosystem variables are beyond their HRV.

Size- and age-class structure of stands. A full range 

of size- and age-class structures must have existed 
58 USDA Forest Service RMRS-GTR-140. 2005

within individual stands throughout time during the HRV 

period (figs. 27 and 28; the proportion of the landscape 

in forests of different ages is discussed in section 6.2). 

They would have ranged from young to older even-aged 

stands of lodgepole pine, many having developed after 

fires in the 1600s and 1700s, to uneven-aged stands that 

had not burned for centuries and were dominated primarily by Engelmann spruce and subalpine fir (and possibly 

some lodgepole pine and aspen). The fires would have 

killed many of the big trees from time to time, and they 

probably burned over large areas (possibly over 25% of 

the BNF; 44% of YNP was subjected to varying degrees 

of fire in 1988; Balling and others 1992). Consequently, 

tree size would have ranged from uniformly small trees 

after the stand was recently burned to very large trees 

coexisting with small trees when the stand had not been 

disturbed for long periods.

Since the late 1800s, both human-caused fire and timber harvest have converted areas with large, old trees 

to stands of younger, smaller trees, with the important exception that timber harvesting could extend into 

areas that had not burned for centuries (such as on leeward slopes or in ravines, both of which are thought to 

burn less frequently). When timber harvesting in such 

rarely burned areas does not provide sufficient time to 

allow the regrowth of old trees, the age- and size-class 

structure is probably outside the HRV (moderate confidence). Across the rest of the landscape (i.e., where 

disturbances were more common historically), the variety of age and size-class structures with and without 

clearcutting, at the stand level, is probably within the 

HRV—as both clearcutting and intense fires would 

create the kind of size-class structure characteristic of 

even-aged stands, and currently, the forest stands have 

not been cut more frequently than the rate at which fires 

have burned stands (moderate confidence). Similarly, 

insect epidemics, partial blowdowns and partial cutting 

could create a structure characteristic of uneven-aged 

stands. However, because the planned rotation times are 

shorter than natural fire return intervals (see section 6.2.1 

on disturbance return intervals and rate at which new 

patches are formed), the average harvested stand expected in the future will not be able to achieve old-growth 

characteristics, and thus stand age and size structure 

may eventually exceed the HRV.

Forest floor depth. High-elevation forests in the Rocky 

Mountains are characterized by an abrupt boundary 

between the mineral soil and the forest floor, which is comprised mostly of fine and coarse litter in varying stages of 

decomposition. The abrupt boundary is caused by periodic fires that burn the forest floor and expose much of the 

mineral soil. A new forest floor gradually accumulates 

because of slow decomposition (Fahey 1983), but the litter does not become well incorporated into the mineral 

soil because of the absence of earthworms.

In addition to time since disturbance, the variation in 

forest floor depth is caused partially by the fact that, on 

slopes, litter often moves downslope due to gravity and 

flowing water, which creates deeper forest floors on toe 

slopes than nearer the ridge tops. Moreover, fallen logs 

often accumulate detritus on their upper side, and squirrels create middens of cone scales under some trees. 

Usually the forest floor of unmanaged stands is about 

2-6 cm (1-15 inches) thick, but the range of forest floor 

depth during the HRV period is much broader, ranging 

over time from essentially no forest floor to a forest floor 

that can be several decimeters thick.

Forest managers often recommend that much of the 

forest floor be scarified or removed, thereby creating a 

better seed bed for new tree establishment (Alexander 

1966, 1987); or they tend to suppress fires, which minimizes disturbance to the forest floor, thereby allowing 

for a continuation of forest floor thickening until the 

next fire that cannot be controlled. Under a variety of 

such treatments, harvested forests in lodgepole pine 

have forest floors averaging 2-3 cm thick and range from 

no forest floor to one with a depth of several decimeters 

(Maxwell and Ward 1976), which surely falls within the 

HRV (high confidence).

Mineral soil exposed, disrupted, or compacted. In 

general, the litter on the forest floor is important for 

minimizing soil erosion because it increases the rate 

of infiltration during periods of snowmelt and rainfall. Less surface runoff is associated with less soil 

erosion. However, exposed mineral soil is thought to 

improve the chances of successful establishment for 

lodgepole pine and spruce seedlings (Alexander 1987). 

The machinery used for yarding and slash treatments, 

such as roller chopping, tractor walking and piling and 

burning, scarify the soil in ways that favor the establishment of seedlings, similar to a natural fire (which 

can expose the mineral soil just as a timber harvesting 

operation can).

A notable difference between the two kinds of disturbances is the depth to which the mineral soil under 

the forest floor is disrupted (Bockheim and others 1975; 

Halpern and Franklin 1990; Dion 1998). Scarification 

by a bulldozer blade or the blades of a roller chopper 

often disrupts soil structure to a greater depth than does 

a fire, which often burns the litter without breaking up 

the mineral soil (though some erosion may occur). In 

the process of mechanical scarification, the surface roots 

of surviving trees and understory plants may be broken, 

which leads to higher mortality of plants than would 
USDA Forest Service RMRS-GTR-140. 2005 59

be expected for plants that survive a fire (Selmants and 

Knight 2003). An example of a plant in which scarification may slow recovery is grouse whortleberry. In 

contrast, though fires typically burn plant shoots, the 

soil temperature typically is not high enough to kill the 

roots except under patches where fuels have accumulated. Thus, most plants other than conifers survive fires 

because they are capable of sprouting from underground 

tissues that are not affected.

Soil displacement and compaction also occur after 

logging to greater extents than after fire. For example, on two clearcuts on the BNF, 25 to 52% of the soil 

was displaced (duff and top soil removed), mostly from 

machine piling of slash (Nesser 1990). On one of the 

clearcuts, 16% of the soil was compacted (a loss of 

>10% porosity compared to an undisturbed site), mostly 

under skid trails. Natural disturbance processes do not 

create skid trails or such levels of compaction and soil 

displacement. Mass movement events such as landslides 

can displace soil, but only on steep slopes. Logging can 

create such disturbances on gentle slopes. It seems clear 

that mechanized yarding, slash treatment, and scarification can create a disturbance that rarely occurs following 

a fire, with the consequence that the HRV for surface 

soil disruption is exceeded (high confidence).

Snag density. The importance of dead trees as a component of wildlife habitat is widely accepted (Hutto and 

others 1992; Hutto 1995; Bull and others 1997; Parks 

and others 1997; Hagan and Grove 1999). Reflecting 

this fact, BNF management prescriptions now call for 

leaving five to seven snags per ha that are >25.4 cm (10 

inches) dbh (USDA Forest Service 1985). Still, in areas 

that have been subjected to clearcutting (3% of the forested land on the BNF), there are far fewer snags right 

after the cut and in post-harvest mature forests than prior to the arrival of European-Americans (Harris 1999). 

Every natural disturbance, with the possible exception 

of wind, creates dead standing trees. For example, a 

fire typically leaves a forest of standing dead snags; a 

clearcut leaves few. Another fire can burn through a stand 

(called a reburn) not long after a previous fire, removing 

some of the standing or fallen snags (Lotan and others 

1985) and reducing snags to low densities. However, reburns are uncommon because young forests tend to be 

relatively inflammable due to the removal of so much 

of the fuels by the last fire. Also, removal of large, living trees during timber harvest leads to a decline in the 

number of snags in the future. Early photographs in unlogged areas often show an abundance of snags, giving 

the “salt and pepper” effect in black and white photos. 

Native Americans did not remove many snags during the 

HRV period because they probably used standing dead 

trees infrequently, especially those of large size.

In sum, with the advent of thinning, partial cutting, 

stand improvement, firewood gathering (not quantified), 

salvage harvesting, and wood harvesting in general, the 

rate at which old snags are replaced with new snags has 

been reduced at the stand level. Because most snags fall 

after 25 years (Lotan and others 1985), the range of conditions within a stand for actual snag density would be 

zero to abundant—which clearly is within the range of 

historical conditions. However, the mean snag density 

in post-harvest stands would be lower than the range of 

means for snag densities during the HRV reference period (high confidence).

Coarse woody debris. As noted, natural disturbances 

do not remove bolewood. Even an intensive fire leaves 

most of the wood in the form of snags, and most of it becomes coarse woody debris within two decades (Lotan 

and others 1985). A reburn can occur, but there is still 

considerable woody debris remaining in the stand. 

The leaves, branches, and smaller wood are consumed 

by fires, but Tinker and Knight (2000) found that only 

about 8% of the wood >7.5 cm (3 inches) was burned 

after an intense fire in YNP. After a century or more, the 

downed wood becomes incorporated into the surface 

soil (Graham and others 1994), giving the impression 

that there is little coarse woody debris. However, the residual of log decay is still present under the forest floor. 

Raking reveals the decomposed logs. New woody debris is added as the larger trees die and fall, one by one 

during stand development or in large numbers during a 

windstorm or after the next fire.

One detailed study has been done on the temporal and 

spatial dynamics of coarse woody debris in Wyoming 

forests. Tinker and Knight (2001, 2003) worked in the 

Medicine Bow National Forest and Yellowstone National 

Park, but the results are relevant to the BNF. They found 

a wide range of coarse woody debris cover and mass 

on cutover stands (11.4-26.8 m2 [123-288 ft2] and 15-

35 Mg/ha [7-16 tons/acre]). Using a simulation model, 

Tinker and Knight concluded that such amounts provide lower coarse woody debris after several clearcuts 

than after the same number of fires on comparable sites, 

suggesting that mean coarse woody debris amounts in 

harvested stands are lower than the HRV. They also 

found that the time required for coarse woody debris to 

cover 100% of the ground surface area after a fire was 

much less than after clearcutting (fig. 37). Only when 

slash amounts left on the ground were doubled from average amounts left using current management practices 

was the time required similar for a clearcut and fire 

(in other words, 200% of current coarse woody debris 
60 USDA Forest Service RMRS-GTR-140. 2005

amounts in slash could keep practices within the HRV 

on some sites). Coarse woody debris can be found elsewhere on the landscape, such as on land classified as 

unsuitable for harvesting, but the coarse woody debris 

dynamics of individual stands—the focus of this section—is changed beyond the HRV by harvesting (high 

confidence).

The consequences of deviations from the HRV for 

coarse woody debris are still poorly understood, but 

both standing and downed tree boles provide important habitat for some species of fungi and a variety of 

insects, all of which can be important sources of food 

for vertebrates (Harmon and others 1986; Hagan and 

Grove 1999); and the organic compounds derived from 

decomposing wood undoubtedly influence future soil 

productivity. Coarse woody debris is also known to be 

important for diversifying the structure of streams.

Could a changing climate have altered snag and 

coarse woody debris dynamics from the HRV reference 

period? As discussed previously, information available for the climate of the reference period suggests 

that it was somewhat cooler and was sometimes drier 

and sometimes moister. When moist conditions favored 

tree growth and density, then there may have been more 

snags and coarse woody debris during the reference period than there are now. However, such conditions also 

would have favored decomposition, causing a more 

rapid loss rate for both snags and coarse woody debris. 

We conclude tentatively that the change in climate would 

not have had a significant net effect on snag and coarse 

woody debris abundance. Further research is required to 

verify this conclusion.

Thus, harvesting is fundamentally different from 

any kind of natural disturbance and produces a forest 

that is beyond the HRV for dead standing trees (snags), 

coarse woody debris, and probably the ecosystem processes associated with structural features dependent on 

big pieces of wood (high confidence). Moreover, variation from natural disturbances has resulted from some 

machine yarding, where whole-trees are brought to the 

landing before delimbing. This results in a concentration 

of slash and residual coarse woody debris on landings. 

Following natural disturbances, this material would be 

distributed more evenly throughout the stand. Salvage 

operations after blowdowns or fires also reduce the 

amount of coarse woody debris. 

In summary for high-elevation forest stands, the HRV 

for many variables appears to be quite broad and many 

stand-scale variables remain within what we believe is 

their HRV in managed forests. Stand variables that are 

possibly beyond their HRV are canopy cover and gaps, 

mineral soil affected, snag density, and the amount of 

coarse woody debris.

Simulation year

0

200% Slash

Fires

100% Slash

50% Slash

500

2000

100

1500

0

300

3500

0

2500

50004004500

0

60005500

Figure 37—Time required for 100% of the forest floor 

to have been affected by coarse woody debris following fires and clearcuts, with different amounts of 

slash left behind after harvesting. Horizontal bars 

indicate the range of years required for coarse 

woody debris (CWD) to have covered 100% of 

the forest floor. The ranges were estimated using 

a series of stochastic model simulations for fires 

(HRV conditions) and for clearcuts (existing conditions), both with 100-year mean return intervals. 

Slash cover from clearcuts was 100% (average), 

half (50%), and double (200%) average amounts of 

slash usually left on site in recent clearcuts on the 

Medicine Bow National Forest. The time required 

for the forest floor to be completely covered under 

the natural fire regimes ranged from 1125-1350 

years. In contrast, 100% clearcut slash simulations 

required 1800-3600 years to completely cover 

the forest floor, and 50% clearcut slash simulations required 3000-5600 years. Leaving double 

the amount of CWD in slash (200%), the simulations suggested that 1100-2150 years would be 

required for 100% of the forest floor to have had 

the influence of CWD. This computer simulation 

study suggests that leaving double the amount of 

CWD in slash could possibly bring CWD to within 

the HRV. Source: Tinker and Knight 2001.
USDA Forest Service RMRS-GTR-140. 2005 61

6.1.2 Stand structure in low-elevation forests 

and woodlands

Only 3% of the timber harvested on the BNF thus far 

has been in low- elevation forests, with most of that in 

forests dominated by Douglas-fir. There has been essentially no timber harvesting in ponderosa pine forests, 

and only a few hectares with limber pine have had timber sales. As in other National Forests, the low-elevation 

forests as a whole have changed more due to fire suppression, and possibly livestock grazing, than to timber 

harvesting. In this section, we address the changes in 

stand structure that have occurred due to these activities 

in low-elevation forests since the late 1800s, and whether or not various stand variables are beyond their HRV.

Tree and Sapling Density. Tree density is the most frequently addressed variable in comparisons of early and 

modern conditions in low-elevation Rocky Mountain 

forests. Studies in the Southwest and the Front Range 

of Colorado have focused primarily on stands of ponderosa pine, with the results suggesting that the stands 

would have been more open prior to fire suppression by 

European-Americans (e.g., Progulske 1974 and Veblen 

and Lorenz 1991). Reconstructions from fire scars 

and other sources indicate that such stands often were 

maintained for hundreds of years by frequent, low intensity surface fires (White 1985; Covington and Moore 

1994; and others). Notably, some research suggests that 

crown fires also occurred in stands of ponderosa pine 

(Shinneman and Baker 1997), most likely on more mesic 

sites where tree density could have been higher. Indeed, 

“dense” stands were described in the 1800s by several 

explorers in the nearby Black Hills area (Dodge 1876; 

Newton and Jenny 1880; Graves 1899), probably on more 

mesic sites, and such stands probably were characterized 

by infrequent, stand-replacing fires. The pre-1900 canopy cover was 50 to 80% in such areas (Graves 1899). 

Working in the Black Hills, McAdams (1995) estimated 

that pre-European tree densities ranged widely, from 15 

to 1600 trees/ha (37-395 trees/acre). Similarly, Ehle and 

Baker (2003) reported ponderosa pine densities of 70 to 

3,000 trees/ha (28-1215 trees/acre) for Rocky Mountain 

National Park in northern Colorado.

Based on this evidence, Shinneman and Baker (1997) 

concluded that some ponderosa pine stands periodically 

would become susceptible to crown fires similar to those 

in forests at higher elevations. However, the thick bark 

of ponderosa pine, and the way that terminal clusters of 

needles on saplings often protect the buds from fires, 

would appear to be adaptations to frequent surface fires.

Whether dominated by Douglas-fir, ponderosa pine, or 

limber pine, some areas throughout the Rocky Mountains 

formerly dominated by open stands now have doghair 

stands with several thousand trees per hectare (Covington 

and Moore 1994; Knight 1994a; Knight 1994b; Savage 

and others 1996), mostly likely because of fire suppression and the elimination of Native American fires. 

Historic photos from the Black Hills, Northern Rockies, 

and to the south indicate that many stands of ponderosa 

pine and Douglas-fir were very open (Progulske 1974; 

Gruell 1985; Veblen and Lorenz 1986, 1991; Johnson 

1987) and that low-elevation tree density in many Rocky 

Mountain areas has increased greatly since the beginning 

of successful fire suppression. Indeed, historic photos 

indicate that BNF low-elevation forests that once were 

open now have become more dense (Wyoming State 

Historical Society 1976). Selective cutting can create 

open stands again, but this has not occurred in low-elevation forests on the BNF. Most of the harvests, though 

few in number, have been clearcuts that occurred in the 

1960s. Since the 1980s, harvests at low elevations have 

mostly been shelterwood cuts (BNF data). Neither silvicultural system restores the low tree-density structure 

that many believe was most prevalent on the BNF during 

the HRV reference period.

Livestock grazing also may have affected low-elevation forest structure, as this land use practice has been 

widespread in the BNF. Indeed, reference areas unaffected by livestock are difficult to find. A comparison 

of historic and modern photographs of a BNF ponderosa pine savanna that was grazed in the past (but not 

currently) shows an increase in tree density (Wyoming 

State Historical Society 1976). Livestock grazing could 

facilitate this increase in density by removing sufficient herbaceous vegetation to reduce competition for 

young tree seedlings. However, insufficient information is available at this time to distinguish an increase 

in tree density due to fire suppression from an increase 

due to grazing. Large numbers of cattle and sheep (or elk 

and deer) could cause damage to seedlings and saplings, 

which would reduce tree density.

In summary, we conclude that the few stands at low 

elevations on the BNF that would have escaped fires 

probably are still within the HRV for tree density (high 

confidence). However, tree density in the majority of 

low-elevation stands probably has increased substantially above the HRV (high confidence). By contrast, the 

regeneration of Douglas-fir following clearcutting has 

been slow at the upper elevation limits of Douglas-fir on 

the BNF (B. Bornong, BNF ecologist, personal communication). This slow regeneration may not be outside the 

HRV for this species at the limits of its range.

Plant species diversity, canopy cover and gaps, and 

understory composition and cover. No data are available 
62 USDA Forest Service RMRS-GTR-140. 2005

to suggest that plant species diversity is either within or 

beyond the HRV, whether for trees or understory plants. 

Dramatic shifts in tree species composition (and tree species diversity) surely have not occurred on the BNF (high 

confidence), though Fule and others (1997), working in 

the Southwest, found that trees less adapted to fire than 

ponderosa pine have become more important in many 

stands. Notably, Douglas-fir can eventually replace ponderosa pine as succession proceeds in relatively moist 

areas where fires are suppressed or occur at long return 

intervals (Goldblum and Veblen 1992).

As trees and saplings become more dense, canopy 

cover increases and there is a concomitant reduction in 

the amount of understory cover (Moir 1966; McPherson 

1992). Also, shade-tolerant species become more abundant as canopy cover increases. In areas where tree 

density has increased or where harvesting has not been 

used to thin the trees, it seems probable that the species 

composition of the understory vegetation would have 

changed and the average amount of understory vegetation would have declined. The range of means for such 

variables is probably beyond the HRV (low confidence). 

As discussed for high-elevation forests in section 6.1.1, 

the presence of exotic plants could cause further changes 

in the understory vegetation. Such plants are more likely to become a problem at low elevations than higher in 

the mountains.

Unfortunately, changes in herbaceous species composition due to domestic grazing are difficult to detect 

by comparing historic to present-day photographs, 

which makes the determination of their HRV essentially 

impossible. Indeed, livestock grazing was so widespread for so many years on the BNF that the long-term 

effects are difficult to identify, even for trained observers. Because of livestock grazing, some understory plant 

species may be quite rare today, overall cover may be 

less, and some soils that were degraded by livestock may 

not have been restored (based on studies in the Central 

Rockies by Thilenius 1975, Turner and Paulsen 1976, 

and Fleischner 1994).

It is interesting to speculate on the effects that management activities might have on genetic diversity. A 

change in fire regime could reduce the fitness (ability to 

produce offspring that bear seed) of trees at low-elevations because bark thickness is heritable and repeated 

surface fires over time probably select for trees with 

thick bark. Without the selection pressure of repeated 

surface fires, the insulative quality of the bark of ponderosa pine and Douglas-fir could be reduced below the 

HRV over the long term (Howe 1997). We suspect, however, that such adaptations for surface fires are still well 

represented in the gene pool.

Size and age structure of trees. The increased tree 

and sapling density resulting from fire suppression at 

low elevations slows the rate at which most trees reach 

large sizes; and with many more young trees, the average age of the trees in the stands is less. In ponderosa 

pine, the mountain pine beetle also reduces the average 

tree diameter by selectively killing more of the larger, 

older trees. Of course, the beetles create canopy gaps 

and large openings in which new trees become established. Overall, however, the average tree size and age 

structure of unharvested low-elevation stands probably 

are beyond the HRV (moderate confidence).

For harvested stands, clearcutting on the BNF skews 

age and size distributions toward young trees and creates 

more even-aged stands. In contrast, natural disturbances, such as the western spruce budworm and fire, tend to 

have the opposite effect—an increase in the mean dbh 

per tree because the smaller, suppressed trees are killed 

first, leaving the larger ones, and through the more rapid 

growth of surviving trees. Less stand basal area results 

because the augmented growth rates do not compensate 

for the trees that fall due to the disturbance. Even partial 

cutting tends to skew age toward young trees and does 

not mimic the effects of insects and fire. Thus, age and 

size structure in harvested Douglas-fir stands is probably 

beyond the HRV.

In the Front Range of Colorado, harvesting specifically designed to improve forest health, vigor, and 

appearance also produces a greater uniformity in density 

and age structure (Myers 1974; Alexander 1986). Various 

cutting methods have been proposed that could produce 

more stand structures typical of the HRV reference period, but, as discussed for high-elevation forests, their 

effects differ from those of natural processes in notable 

ways (less coarse woody debris and snags; Alexander 

1986; Lundquist 1995a; Romme and others 2000). Such 

experimentation has not yet been done on the BNF (C. 

Thomas, BNF silviculturist, personal communication).

Spatial distribution of trees. An important pre-1900 

characteristic of ponderosa pine forests appears to be 

the aggregation or clumped distribution of tree cohorts 

(a group of trees of the same species and age) in some 

areas at low elevations. Historical observations and reconstructions of open-grown ponderosa pine in the 

Southwest indicate that trees grew in clumps or patches 

of less than 0.4 ha (1 acre) with 3 to 44 trees (Cooper 

1960; White 1985; Moore and others 1993). Covington 

and Moore (1994) found that age structure within and 

between clumps varied depending on scale. Such patterns could occur at low elevations in the BNF as well, 

though Ehle and Baker (2003) found that dense, evenaged stands were common in Rocky Mountain National 
USDA Forest Service RMRS-GTR-140. 2005 63

Park in northern Colorado. Further research is necessary 

to determine if the distribution patterns observed farther 

to the south also apply to the BNF woodlands.

Although the spatial distribution of both ponderosa 

pine and Douglas-fir forests on the BNF during the HRV 

period is unknown, we suspect that the distribution of 

ponderosa pine now is greater and more uniform than 

the HRV (moderate confidence), based on historic photographs. Also, the warmer conditions in recent years, 

relative to our HRV reference period, indicate that fire 

frequency and forest openness should be higher than during the HRV period. Yet, fire suppression is causing the 

opposite to occur. This observation further strengthens 

the argument that many characteristics of low-elevation 

forests are outside the HRV.

Forest floor depth. The short return interval of surface 

fires in low-elevation forests would probably keep the 

depth of the forest floor quite thin. Thus, it is plausible 

to assume that the forest floor did not become as deep as 

in high-elevation forests, where the fire return interval 

was much longer. Fire suppression probably is causing 

the development of deeper layers of litter than normally would be expected, pushing this variable beyond the 

HRV (high confidence), thereby increasing flammability 

(along with increased tree density and more continuous fuels). Because frequent surface fires typically keep 

the forest floor litter amounts small, harvesting in such 

forests may be further increasing the forest floor depth 

beyond the HRV if much of the slash is left in place.

Snags and coarse woody debris. Lundquist (1995a, 

1995b) studied the diversity of snags and coarse woody 

debris in ponderosa pine forests in the nearby Black 

Hills. He identified 10 classes of snags and five classes 

of logs, finding that different types of disturbance create 

different types of snags and logs. For example, the stems 

of beetle-killed trees tend to break, leaving a relatively 

short snag, while trees killed by root rot are commonly 

uprooted and become coarse woody debris on the forest floor. No snags are created. Based on this research in 

the Black Hills, timber harvest in the small area where 

it occurs at low elevations on the BNF probably tends 

to (1) reduce the number and diversity of snag types 

and (2) distribute log types among the five classes more 

evenly on the forest floor. This evidence, combined with 

old photographs in Wyoming that show a much larger 

number of dead trees in low-elevation forests than occurs 

today, suggests that snags and downed wood are now 

lower than the HRV (moderate confidence) in the managed ponderosa pine and Douglas-fir woodlands, due to 

harvesting (including casual fire-wood cutting). Some 

coarse woody debris is burned by fires in low-elevation 

forests, possibly more than observed by Tinker (1999) in 

high-elevation forests because of frequent surface fires. 

Thus, with regard to coarse woody debris, low-elevation 

forests where timber harvesting has occurred may not be 

as far from the HRV as high-elevation forests.

Considering that most of the low-elevation forests on 

the BNF have not been harvested, but have been subjected to fire suppression, the bigger effect of management 

on snags and coarse woody debris at lower elevations 

may be less frequent fire. Fire tends to create snags, but 

insect and disease epidemics can do the same. In the absence of fire (or harvesting), are pathogens likely to be 

more abundant? That is a contention of some concerned 

about forest health problems in western landscapes, but 

it is not clear if this is occurring on the BNF. Our opinion 

is that there is not yet an unusually high or low number 

of dead trees (snags) due to fire suppression (moderate 

confidence).

With regard to coarse woody debris, periodic surface fires could consume downed and decaying wood 

on the forest floor. With less frequent fires, this wood 

could persist for a longer time, and if coarse woody debris inputs remain constant, then coarse woody debris 

may increase. We suspect, however, that fire suppression has not occurred frequently enough to raise the 

amount of coarse woody debris to above the HRV because of slowed fire consumption (low confidence). This 

opinion is based partly on the considerable longevity 

of the trees that dominate the low elevation landscapes 

(ponderosa pine, Douglas-fir, and limber pine) and the 

fact that pathogenic problems are still rather localized 

where these species occur. A notable exception may be 

Tensleep Canyon, where the exotic white pine blister 

rust has caused what appears to be an unusually high 

level of limber pine mortality.

In summary, a combination of human influences and 

probably climate change has caused many structural 

characteristics of low-elevation stands of conifers to exceed their HRV in other parts of the Rocky Mountains. 

The same probably has occurred on the BNF. Great attention has been given to this situation, often in the context 

of “forest health” discussions. Low-elevation forests on 

the BNF cover a relatively small proportion of the terrain and provide a rather small amount of the wood that 

is harvested. Only about 2% of the low-elevation forests 

have been subjected to harvesting. However, the effects 

of fire suppression probably have been more widespread 

at low elevations. Also, this is where the effects of the 

exotic white pine blister rust are most evident. Attention 

should be given to the potential adverse consequences 

of the unusual conditions now found in this forest type, 

where they occur.
64 USDA Forest Service RMRS-GTR-140. 2005

6.1.3 Stand structure in aspen woodlands

Following a disturbance, aspen often becomes 

more abundant, invading primarily from root sprouts. 

Seedlings can be abundant at times, such as after the 

1988 fires in some parts of YNP (Romme and others 

1997). With fire suppression and natural succession, 

conifers are now becoming co-dominants with aspen 

in some areas, to the point that managers have begun 

harvesting or burning aspen to maintain this highly valued species in the landscape (BNF data; B. Bornong, 

BNF ecologist, personal communication; Bartos 2001; 

Campbell and Bartos 2001). In other areas, stands of aspen have not been invaded by conifers. Both invaded and 

non-invaded stands probably occurred on the BNF during the HRV reference period, but the average number of 

conifers in aspen stands probably is increasing.

The addition of conifers can change the understory 

because plant growth under aspen is typically quite abundant, compared to coniferous forests, partially because 

of the relatively open, seasonal canopies of aspen stands 

that allow light to reach the forest floor. Notably, such 

forests support a high diversity of birds relative to other areas (Merrill and others 1993). Loose and Anderson 

(1995) found that woodpecker nests are more common 

in aspen forests than in other forest types, particularly in large aspen that are >18 cm (7 inches) dbh and 

have heart rot or dead tops (average dbh 26.7 cm [10.5 

inches]; range 18-45 cm [7-18 inches]), and Struempf 

(1999) found higher nest survival in aspen than in conifer forests. Good forage and ground cover for a variety 

of animals is provided. Of course, aspen contributes 

significantly to the aesthetic quality of an area wherever 

it occurs.

Variables pertaining to aspen stand structure probably 

have not exceeded their HRV due to timber harvesting 

because there has been very little harvesting of aspen on 

the BNF (about 25 ha [62 acres] in the 1950s and 1960s 

were clearcut; BNF data). However, in the 1980s, numerous groves were clearfelled to stimulate aspen root 

sprouting. Such efforts were successful in many areas. 

When the bolewood is left on site during clearfelling, 

this management could mimic some aspects of the effect 

of fire. When bolewood is removed, the abundance of 

coarse woody debris and snags would be reduced below 

the HRV in the affected stands.

The most widespread influence of humans on aspen 

stands in the BNF may be through livestock grazing and 

the introduction of non-native plants, both of which could 

be changing the understory vegetation in still unknown 

ways. Less than one-quarter of the stands cut for regeneration have been fenced and protected from grazing (B. 

Bornong, personal communication). Consequently, assuming wild herbivores did not graze as heavily in aspen 

stands as domestic livestock do today (van Vuren 1982; 

Kay and Wagner 1996), grazing may be slowing tree regeneration and reducing the typically lush understory 

vegetation. Another cause of variation in this ecosystem 

is the presence of Kentucky bluegrass (Poa pratensis), 

which has invaded most aspen stands on the BNF and 

causes change in the understory species composition.

In summary, because of very little timber harvesting, and the fact that some stands probably would have 

changed to coniferous forest through succession during the HRV reference period, it can be argued that 

the variables pertaining to modern day aspen stands 

are probably within their HRV on the BNF. However, 

we are hesitant to draw this conclusion because of the 

effects of long-term grazing in these forage-rich habitats and the widespread presence of introduced plants, 

such as Kentucky bluegrass. Stand variables pertaining 

to the trees probably are within their HRV (moderate 

confidence), but variables pertaining to understory vegetation, including conifer density, probably are not (high 

confidence when non-native species are present; moderate confidence in other situations).

6.1.4 Stand structure in non-forest vegetation

Exotic plants are becoming more widespread in nonforested areas (i.e., grasslands, meadows and shrublands) 

on the BNF (USDA Forest Service 1998; S. Gall, BNF 

range conservationist, personal communication). In some 

areas, grasslands have been invaded by Kentucky bluegrass, Canada thistle (Cirsium arvense), houndstongue 

(Cynoglossum officinale), Orchard grass (Dactylis glomerata), common timothy (Phleum pratense), Japanese 

brome (Bromus japonicus), and crested wheatgrass 

(Agropyron desertorum). Notably, cheatgrass is not a 

problem at the present time. Kentucky bluegrass is the 

most extensive introduced plant, particularly in intermediate moisture zones where it can outcompete native 

species (Girard and others 1997). This grass is found in 

every grazing allotment and in all aspen stands (S. Gall, 

personal communication). Timothy is found in <5% 

of the allotments, but where it occurs, it forms large 

patches. Some non-native species were seeded in road 

rehabilitation sites. In stands with exotic species, the 

species composition and diversity is definitely outside 

the HRV (high confidence).

Both the composition and structure of non-forest 

cover types are also affected by grazing. However, herbivory has been a natural process in non-forest vegetation. 

Before European-Americans arrived, bison and other 

herbivores grazed the montane grasslands in Wyoming 
USDA Forest Service RMRS-GTR-140. 2005 65

(Dorn 1986), and many of the plants dominating the different kinds of non-forest vegetation evolved adaptations 

for such herbivory (Mack and Thompson 1982). Since 

then, however, the characteristics of herbivory have been 

altered by the introduction of domestic livestock. In 

the late 1800s and early 1900s, sheep and cattle grazing 

were intense and poorly controlled--probably exceeding 

the levels of ungulate herbivory during the HRV period 

(moderate confidence). However, because population 

estimates of herbivores from the 1600 to 1890 HRV period are not available, confident comparisons of herbivory 

levels at that time and today are impossible. Jack (1900) 

documented and photographed the damage from livestock 

grazing in the BNF in the late 1800s. Comparisons of such 

early photos to 1975-76 suggests that the initial heavy 

grazing caused forbs to replace grasses, as well as stream 

downcutting and less coverage by willows and sedges in 

riparian areas. Based on the 1900 photographs, it appears 

that some topsoil has eroded since 1900. Because such 

heavy grazing intensities are no longer allowed, some of 

the vegetation is now recovering.

Although the numbers of livestock have declined during the last several decades, today the BNF is still one 

of the most heavily grazed National Forests in the region. Possibly over a third of the rangelands are less 

than satisfactory, based on percentages of plant species 

that are increasers compared to decreasers (S. Gall and 

D. Beard, BNF range conservationists, personal communication). The dominant grassland type affected by 

grazing on the BNF is the Idaho fescue community, 

where livestock grazing has caused loss of ground cover, loss of litter, increased soil compaction, and changes 

to stand structure and species composition, including increases in non-native species. Exotic species also have 

increased in riparian zones (Beetle 1956; Girard and 

others 1997), where the elimination of the litter layer 

warms and dries the soil, encouraging the growth and reproduction of certain plants at the expense of others. In 

the 1950s, grazing reduced grass and grass-like species 

by 15%. Consequently, forbs increased (Beetle 1956), 

although some forbs such as larkspur (Delphinium spp.) 

declined (S. Gall, personal communication). Wild herbivores may have also caused such damage, but, unlike 

domestic stock, wildlife are less likely to concentrate for 

long periods within specific areas (van Vuren 1982) and 

they cause less damage to riparian areas because they 

have a more dispersed grazing behavior than livestock. 

Livestock are more concentrated because they are fenced 

and only in the last 10-15 years has rotation grazing been 

implemented on the BNF. Grazing can also promote 

the spread of big sagebrush in some areas, which, once 

established, is competitive with grasses and may persist 

for many years.

Overall, exotic species today, and the intense grazing 

levels on the BNF during the last century, probably have 

pushed the structure and species composition of grasslands, forblands, and shrublands beyond their HRV (high 

confidence). Prescribed fire or chaining are sometimes 

used to reduce big sagebrush (B. Bornong, BNF ecologist, 

personal communication), which might help restore HRV 

conditions when that seems desirable, but there is now 

the potential of exotic plants growing where such control 

practices are attempted. Fire suppression may have allowed woody plants to occupy meadows and shrublands 

in some areas, but we doubt this change has been as significant as introduced plants and livestock grazing.

Our discussion is relatively brief for non-forest vegetation types because much less is known about them. 

In contrast to forests, it is difficult if not impossible to 

learn about their disturbance history (no tree rings, and 

old photographs reveal less information), and many ecosystem variables are more difficult to measure than in 

forests. To illustrate, much of the biomass and important ecosystem processes occur belowground. Moreover, 

successional changes are more difficult to interpret than 

in forests. With more careful management of livestock 

and wildlife, some variables could be restored to within their HRV—to the extent that is possible without the 

eradication of exotic plants such as Kentucky bluegrass. 

Monitoring various soil variables and variables associated with plant species composition, including the 

abundance of introduced plants, will help provide information required for judging sustainability

6.2 Landscape Structure

The spatial and temporal variability of some stand 

variables, with and without European-American influence, can also be considered at the landscape scale. In 

addition, stand-replacing fires, wind storms, and some 

insect epidemics cause natural landscape changes that 

are obvious from aerial photographs and satellite images. Changes in landscape patterns are known to influence 

the movement of animals, water, and nutrients, as well 

as the spread of disturbances.

In this section, we first address forest stand structure 

variables at the landscape scale in relation to the HRV 

(specifically, tree density, canopy cover, number and rate 

of formation of gaps, understory cover, age structure, forest floor depth, mineral soil disruption, snag density, and 

coarse woody debris). Then we discuss variables specific 

to the landscape scale, namely, the number and proportion of different vegetation types, the ratio of forest to 
66 USDA Forest Service RMRS-GTR-140. 2005

non-forest, the proportion in different classes of successional stages, the amount of land in edge and interior 

forest habitat, patchiness and patch shape, the proportion in high-density classes for snags and coarse woody 

debris, and disturbance return intervals.

As with our stand-level analysis, this section emphasizes high- and low-elevation landscapes. Aspen and 

non-forest vegetation are included as part of the discussion of these two, more general landscape categories.

6.2.1 High-elevation landscapes

The high-elevation, forested landscapes encountered 

by early explorers in the 1800s in northcentral Wyoming 

must have had large areas of even-aged cohorts of trees 

(stands) that originated following large crown fires. 

However, the landscapes probably were patchy due to 

uneven burning (Foster and others 1998). Large fires 

would burn for several weeks or months, with greater 

intensity some days than others. Winds would shift from 

time to time, causing the flames to move in different directions. Spotting would occur, and typically the flames 

would move more slowly downhill. More mesic areas, 

such as in ravines or on north slopes, were less likely 

to burn. Uneven-aged stands of older trees, including 

old-growth forests, would have occurred in mesic areas 

where, by chance, there had not been a stand-replacing 

fire for several centuries (Romme and Knight 1981).

Large, infrequent fires cause fragmentation of the 

forest just as timber harvesting can. Landscape fragmentation is a complex phenomenon (Buskirk and others 

2000) that has received considerable attention. For this 

analysis we define it as an increase in the number of abrupt 

transitions on a landscape between forest and non-forest 

or young-forest (whether caused by humans, fires, or 

wind) that reduce the area of interior forest and increase 

the area affected by edges. Where the topography is 

comparatively flat outside the Cloud Peak Wilderness, 

extensive forest stands can develop that are accessible 

for timber harvesting and susceptible to fragmentation 

(Tinker and others 1998), particularly in the southern part 

of the BNF (fig. 13). The northern half has always been 

more fragmented because of the natural parks that occur 

on fine-textured soils (forests commonly are on coarsetextured soils).

To evaluate changes in stand variables across the landscape due to management, the scale of management 

activities must first be considered. We focus on timber 

harvesting and fire suppression as the major management 

activities that could move stand structure variables averaged across the landscape beyond the HRV. As noted 

previously, the HRV for a variable generally becomes narrower as the size of the land area increases (see fig. 1).

We base our estimates of landscape HRVs on our 

more lengthy discussions in the previous stand structure 

section and on the average of values (mean) estimated 

across the landscape through time. To illustrate, consider that 10 years following the 1988 fires in YNP, tree 

seedling density ranged from essentially no seedlings 

to very high densities (exceeding 100/m2 [9/ft2]) across 

different stands (Turner and others 1997). Information 

on this spatial variability among different stands is lost 

when the stand-level values for a variable are averaged, 

but there is still the potential for change in the average 

values through time. If the stands did not change over 

time, the landscape-level average would remain at a constant value. However, stands do change, and therefore 

the temporal variability in average values can be used to 

describe the historic range of variability.

Many characteristics of stand structure surely had high 

variability through time during the HRV period. Average 

tree seedling density and adult tree density across landscapes were probably quite different in years following 

large fires than in years with few fires. To illustrate, serotinous lodgepole pine cones release abundant seeds 

following fires, which can lead to high seedling densities in many stands, increasing average seedling (and 

eventually sapling and tree) density across the landscape 

as a whole. In other years, densities could be lower in 

most stands, perhaps because of slower seed dispersal 

from non-serotinous cones, such as might occur after 

insect epidemics that cause high levels of tree mortality. Similarly, the density, species diversity, and cover of 

understory plants change as succession occurs in stands 

(e.g., intermediate stages have high tree canopy cover 

and sparse understory vegetation). Thus, the temporal 

variability of the average density and cover of understory vegetation probably would be moderately high. The 

same is true of canopy gap density and cover. The range 

of the averages of these variables would be expected to 

be from moderately low to moderately high values—

never very low to very high because that would require 

all stands on the landscape, at one time, to have very low 

or very high values. That would be unlikely.

Similarly, stand age structure averaged over the landscape probably had a moderate range of values during 

the HRV period (figs. 38 and 39). Stand age must have 

ranged from very young to quite old over time, and from 

predominantly even-aged to predominantly unevenaged—the result of infrequent stand-replacing fires and 

long periods of succession combined with other natural 

disturbances that would affect both stand and landscape 

composition. The average of the stands on a landscape 

would range from moderately young and even-aged to 

moderately older and uneven-aged. For the same reason, 
USDA Forest Service RMRS-GTR-140. 2005 67

Figure 38—Change in proportions of 

land cover types on the Bighorn 

National Forest between 1931 and 

1994. Source: Dayharsh 1931 and 

BNF data.

Figure 39—Historic range of variability of percentages in different successional stages of lodgepole/spruce-fir forests within one 

watershed in Yellowstone National Park (HRV proxy that includes the effects of the 1988 fires, from Romme 1982 and recent 1988 data), compared to existing conditions on the Bighorn National Forest (BNF, far right). See table 6 for definitions of 

early, middle and late successional stages. The distribution of percentages of each stage for each of the 12 watersheds on 

the Bighorn National Forest on the figure are shown using boxplots (median is the line in the box; box ends are 25th and 75th 

percentiles, and bar caps are 10th and 90th percentiles and dots are minimum and maximum). Existing conditions for late successional stages on 11 of the 12 BNF watersheds do not fall within the range of means during three 50-year HRV periods in 

YNP (1740-1890). Similarly, existing conditions of middle successional stages on the same 11 watersheds (all but the small 

watershed 9, see fig. 41) do not fall within the range of means during that historic period. Even if the recent 50-year period 

(1938-1988) in YNP is added as a 4th HRV period (because it includes the 1988 fires, which were of magnitudes expected 

during the historic period), the range of means in YNP does not change for these mid and late-successional stages and thus 

the conclusions are the same.

1750 1800 1850 1900 1950

Percent of forested area 

0

20

40

60

80

100

0

20

40

60

80

100

BNF

1999

Little Firehole Watershed, YNP - 7,500 ha (1738-1988)

Middle

Early

Late

Early

Middle

Late

3 HRV periods EC

Range of

 HRV period 

 means 

Actual percentages 
68 USDA Forest Service RMRS-GTR-140. 2005

forest floor depth must have had a moderate range of 

values because it is shallow or absent immediately after 

a hot crown fire but deep in stands that have not burned 

for a century or more, such as in old-growth forests.

In contrast, mineral soil disruption and compaction 

surely were very limited in spatial extent throughout the 

HRV period, because machinery was not used to assist 

with timber harvesting. Thus, the variability in average 

soil disruption and compaction should have been narrow. 

Snag density and the abundance of coarse woody debris 

must have varied greatly across the landscape, from near 

zero in mid-successional stands to abundant after fires 

or disease and common in stands of old-growth forest; 

but, similar to the other variables, with a narrower range 

(moderately high to moderately low) at the landscape 

scale than at the stand scale (see fig. 1).

Change from the HRV of landscape variables. The 

magnitude of the percentage of the landscape affected 

by management activities must be evaluated to assess 

the change from the HRV of landscape variables. On 

high elevation landscapes, the percentage of BNF 

forests that have been subjected to some form of harvesting is about 20%. Specifically, the proportions of 

the total forested land area at high elevations in shelterwood cuts, clearcuts, selection cuts, and seed tree cuts 

are 5.7%, 4.1%, 0.4%; and 0.5%, respectively (similar data in section 6.1 are for high- and low-elevation 

landscapes combined). About 8.7% has been tiehacked without re-harvest (11% if re-harvested stands 

are included). The forested area that has been thinned 

(commercial and pre-commercial) is 5.5% (BNF data). 

Forests that might have burned but were not due to fire 

suppression, and thus are older, comprise an estimated 

10% of the landscape. Under existing conditions, tree 

densities would still fall within the moderately broad 

HRV because, even though trees have been partially or 

completely removed on about 20% of the landscape, 

fires may have removed half of that anyway if fire suppression had not been practiced (moderate confidence). 

Also, because new tree establishment on harvested areas is usually quite good, seedling and sapling density 

in harvested landscapes probably falls within the fairly 

broad HRV (moderate confidence). Canopy gap density 

and cover may be slightly below the HRV, but after 20 

years these variables return to more natural conditions 

(moderate confidence). Understory density and cover, 

forest floor depth, and plant diversity averaged across 

the landscape probably are not outside the HRV (moderate confidence).

Stand variables averaged at the landscape scale that 

could be beyond their HRV, because about 20% of the 

high-elevation landscape has been affected by timber 

harvesting, may be the abundance of older forests, mineral soil disruption or compaction, snag density, and 

the abundance of coarse woody debris. Timber harvesting tends to reduce the land area in old-growth forests; 

and with the advent of mechanical harvesting, the soil 

would have been subjected to mineral soil disruption or 

compaction in ways that would not have occurred during the HRV period. Even though mechanized yarding 

and slash treatment have been used on a small portion of 

the BNF, the average amount of disruption/compaction 

would be higher than the HRV because the HRV would 

have been narrow. Mean snag density averaged over the 

landscape may be below the HRV because burned areas 

are often salvage logged and snags are removed for firewood (firewood collection affects areas other than the 

20% harvested). Also, bolewood is removed, thereby 

preventing future development of as many snags in harvested areas. Similarly, coarse woody debris abundance 

is probably below the HRV because much of the wood 

has been removed from the landscape and not allowed to 

decay on site, as occurred for millennia prior to the arrival of European-Americans.

Number and proportion of land-cover types. The proportion of the landscape in different vegetation cover 

types can give additional insights into landscape changes 

through time. Just as Romme (1982) found for YNP, all 

major land-cover types present in modern times on the 

BNF probably were present during the HRV period. The 

number of land cover types (landscape richness) probably has not changed beyond the HRV (high confidence). 

Also, the proportions of different cover types are naturally dynamic (fig. 38) and probably are within the HRV 

(high confidence). Evidence suggests that the lodgepole 

pine type on the BNF has become less abundant in the 

last century while the spruce-fir type has increased (fig. 

38), because of the maturing of the forest after heavy 

forest fires in the late 1800s (fig. 26) and some successful attempts at fire suppression. We would expect the 

opposite to occur with timber harvesting, which would 

increase the amount of lodgepole pine. About 10% of 

the forested BNF landscape has been clearcut or cut using the shelterwood system, yet this has not increased 

the prevalence of lodgepole pine relative to spruce and 

fir. Clearly, the effects of climate and harvesting on 

lodgepole pine abundance appears to be small relative to 

the effects of successional processes.

While aspen stands do not occupy a large area on the 

BNF, they contribute significantly to the overall diversity 

of the landscape. Aspen occur in high- and low-elevation 

landscapes, but mostly at low elevations on the BNF. 

Therefore, extent of aspen on the landscape is discussed 

under low-elevation landscapes.
USDA Forest Service RMRS-GTR-140. 2005 69

The grassland cover type may have declined relative 

to sagebrush on the landscape during the decades preceding 1985. The 15% decline in grasslands and 4% 

increase in sagebrush (fig. 38) documented for the whole 

BNF (no data are available for just the high-elevation 

landscapes) may have been due to fire suppression, but, 

given the variability in proportion of other cover types 

over time, sagebrush cover probably is within its HRV 

(moderate confidence). Prescribed burning since the 

1980s may be reducing the rate of sagebrush invasion 

into grassland.

Forest/non-forest ratio. Because of forest encroachment into meadows and shrublands, and natural 

reforestation following fire and timber harvesting, the 

proportion of the BNF in forested vegetation has increased substantially since the late 1800s, from 35% in 

1898 to 62% at present—an increase of 27% (USDA 

Forest Service 1994). The accuracy of the early 1898 and 

1900 estimates used for this comparison (Town 1899; 

Jack 1900) is probably low, but it seems clear that the 

area in forests has increased substantially (even between 

1931 and 1993, when an increase of 9% occurred; USDA 

Forest Service 1994). The current variability of forest/

non-forest percentages across watersheds is also high, 

from 40 to 90%. Much of this spatial variability is due to 

distribution patterns discussed in section 4.1, including 

those caused by varying topography and soils. The HRV 

may have been broader than today because fire suppression might have narrowed this range. Nevertheless, due 

to the variability of local climatic conditions over the 

past 500 years, the present ratio of forest to non-forest 

land is most likely within the HRV on high-elevation 

landscapes (high confidence).

Proportion of forests in different successional stages and old-growth. The vegetation mosaic of Rocky 

Mountain landscapes is known to vary greatly through 

time, primarily because of large-scale fires and other 

natural disturbances. In YNP, Romme and Knight (1981) 

found that the amount of land area in forests of early, 

middle, and late successional stages varied temporally 

and that it was unlikely that the subalpine forests of YNP 

as a whole are in a “shifting mosaic steady-state.” In the 

middle and late 1700s, young forests dominated more 

land area; but in the mid-1900s, old forests were more 

common in the same area (fig. 39; Romme and Knight 

1981; Romme 1982). Such shifts in the landscape mosaic surely have ecological effects on species composition, 

biodiversity, nutrient cycling, and other ecological phenomena.

A similar shifting mosaic must have occurred during 

the HRV period at high-elevations in the BNF. To evaluate this quantitatively, the present vegetation on the BNF 

was divided into successional stages (using information 

on habitat structure in the BNF data) and compared to the 

HRV in YNP (table 5). The inventory of old-growth forest on the BNF is not yet complete, but, based on present 

estimates of habitat structural stages (BNF data), current 

old-growth forest percentages on the BNF fell below 

HRV levels of old-growth forest (LP3) from 1735 to 

1985 on 129,600 forested ha in YNP (fig. 40). The lowest 

old-growth percentage ever observed in YNP during that 

period was 15%; the BNF classified only 5% of its forests as old-growth in 1994 (USDA Forest Service 1994, 

based on aerial photo interpretation). Averaged over the 

last 30 years (making the estimate more comparable to 

the YNP estimate), the mean percentage in old-growth 

on the BNF is probably closer to 7%, which is still below the range of means over 30-year periods during the 

HRV period (see fig. 40). The BNF’s current definition 

of old-growth is probably more liberal (includes more 

hectares) than the one used in YNP, which suggests further that old-growth is below the HRV on the BNF.

Notably, the effect of the 1988 fires is not included 

in this assessment. To include the 1988 fires, we divided the successional stages into early (0-40 years, middle 

(about 40-200 years), and late stages (>200 years, late 

includes transitional stages to spruce-fir, not just oldgrowth), as Romme (1982) had done in YNP’s Little 

Firehole watershed (table 6). We estimated percentages 

of each successional stage just after the 1988 fires in that 

watershed using satellite imagery, adding the 1988 data 

to Romme’s (1982) data (fig. 39). Similar to the effects 

of excluding the 1988 fires (see fig. 40), we found that 

late-successional stages were less common and mid-successional stages more common in many watersheds in 

the BNF than the YNP HRV proxy—1738 to 1988 on 

the Little Firehole watershed (fig. 39). Even with inclusion of the 1988 fires as part of the HRV period, older 

forests in the Little Firehole watershed were never below 7%. Comparable values for old forests in some BNF 

watersheds were lower than that (fig. 41; specifically, 

watersheds 3, 4, 5, 6, 7 and 10).

The Little Firehole watershed is not the best reference 

area for comparison to BNF watersheds because two of 

the BNF watersheds that had fewer late successional 

stages than YNP had no timber harvesting (watersheds 

5 and 6). These two watersheds had experienced large 

fires in the late 1800s during the HRV period, which naturally reduced older forest percentages. Thus, the high 

level of mid-successional stages and low old-growth in 

these specific areas is probably within the HRV.

The observation that late successional stages of all 

BNF watersheds are either lower or at the low end of 

the HRV, based on research done in YNP, suggests that 
70 USDA Forest Service RMRS-GTR-140. 2005

the percentage in some heavily clearcut watersheds is 

probably beyond the HRV (fig. 41). Because large-fire 

dynamics in the BNF appear to be similar to YNP, one 

would expect at least one watershed to have at least medium amounts (about 40%) of late successional stage 

forest. Apparently, due to the extensive fires in the late 

1800s on the BNF, the BNF was already at a low point in 

amounts of old-growth. The additional harvesting (9% affected by shelterwood cuts, clearcuts, and seed tree cuts) 

appears to have pushed old-growth or late-successional 

stage percentages below the HRV and mid-successional 

stages above the HRV (moderate confidence).

Forest planning that promotes the harvest of larger, 

slow-growing trees of old forests, and an ability to harvest 

such forests on north slopes and ravines where fires might 

not have burned as often, may help to explain why the 

amount of old forest today in some watersheds appears 

much lower than at any time during the YNP reference period. Fire history studies and more complete old-growth 

inventories are needed on the BNF to support or refute the 

conclusion that old-growth forest is below the HRV and 

that mid-successional stages are above the HRV.

Landscape proportion in low canopy cover. Thinning 

or partial cutting of stands may raise the proportion of low 

canopy cover, mid-successional forest on the landscape 

(<40% canopy cover) beyond the HRV. Such forests are 

relatively abundant on the BNF landscape (14% of landscape with low-density forest; fig. 41), partially because 

of management and partially from natural conditions. 

About 6% of high-elevation forests were thinned or selectively cut, but only about 4% were thinned in the last 

20 years. Only those thinned in the last 20 years may 

still have open canopies, as the branches of neighboring 

trees gradually fill in gaps created by harvesting. Thus, 

Table 5—Successional stage characterizations for lodgepole pine and spruce-fir forests, used when comparing Yellowstone National Park 

(YNP) to Bighorn National Forest. 

Bighorn National Forest (BNF)—from RIS database

Yellowstone National Park (YNP) –Romme and Despain 1989 and USDA Forest Service 1994

 Years Years after standafter stand- replacing fire (from 

Successional Stage replacing fire Characteristics Successional stage USDA BNF 1994)

Lodgepole seedlings/ 0 to 40 Vegetative sprouting of herbaceous Grass-forb-shrub-seedling about 0 to 40 years

saplings (LP0) plants; lodgepole pine seedling (structural stage 1 and 2)

 establishment; fuel consists of

 large, dead tree boles, does not

 ignite easily or support intense fires

Immature lodgpole (LP1) 40 to 150 Canopy closure; stands are relatively Sapling-pole about 40 to 100 

 dense with little groundlayer (structural stage 3) years

 vegetation; period of tree growth, 

 competition, and thinning; fuels are 

 discontinuous from forest floor to 

 canopy, do not burn readily and fires 

 die in absence of wind

Mature lodgepole (LP2) 150 to 300 Tree growth, competition, and Mature (structural stage 4) about 100 to 300 

 thinning decrease; canopy more years

 open; groundlayer denser and more 

 diverse; mixed understory of lodge-

 pole, spruce, and fir common; dead, 

 woody fuels increase but still some-

 what resistant to fire, most fires will 

 die out in absence of wind

Lodgepole, spruce-fir >300 years Canopy mortality increases; under- Old-growth1 Trees are usually

(LP3) story trees reach 2-3 m (7-10 ft) tall (structural stage 5) >300 years, but can

 and penetrate gaps; fuels and organic be >200 years. 

 materials build up, burn relatively Lodgepole may be as

 easily when weather conditions are young as 150 years; 

 right, burn more or less continuously this category still 

 and intensely; last stage before next needs to be verified 

 stand-replacing fire event in south- in the field.

 central YNP.

1 Old-growth on the BNF is based on structure as well as age, as defined by Mehl (1992). Because all of the old-growth on the BNF has not yet been 

inventoried, conclusions from these data must be tentative.
USDA Forest Service RMRS-GTR-140. 2005 71

Figure 40—Historic range of variability of percentages in different successional stages of lodgepole pine/spruce-fir forests within 

several watersheds of Yellowstone National Park compared to existing conditions on the Bighorn National Forest (BNF, far 

right). The HRV proxy excludes the effect of 1988 fires (Romme and Despain 1989). See table 5 for definitions of successional stages. Existing conditions on the BNF fall within the range of means within five 30-year periods (from 1740 to 1890), 

except for the late successional stage (LP3, HRV = 18-22%, EC = 5%) and mature stage (LP2, HRV = 17-40%, EC = 49%). 

Note that if the effect of the 1988 fires were added, the upper limit of the HRV range of means probably would have extended 

upward for LPO and the lower limit downward for LP3 and LP2.

Table 6—Community type definitions used in comparisons of the Little Firehole River watershed vegetation in Yellowstone National 

Park and the vegetation of 12 Bighorn National Forest watersheds.

YNP successional stage Age of stand (Romme 1982) BNF successional stage (from BNF data)2

(Romme 1982)1

Early successional stages 0-40 years Grass-forb-shrub-seedling (<3 cm dbh)

Middle successional stages 40–200 years Sapling-pole, mature (3–23 cm dbh, >40% canopy cover)

Late successional stages >200 years Very large mature (>23 cm dbh)

Riparian forest -- Riparian forest

Steep slope, sparse forests -- Low density sapling-pole, mature forest (<40% canopy cover)

Meadow -- Non-forest

1 Only lodgepole and spruce-fir vegetation types occur in the study area. 2 Romme’s classifications are based on stand ages (different than in table 5) that were matched by searching for the successional stage or size structure 

on the BNF that matched the correct stand age. Very large mature trees were almost always >200 years old in the BNF database. However, this 

approach ignores old trees >200 years that are small, such as those in doghair stands (table 5 better captures those trees). The emphasis of this 

approach is on late-successional stage structure that includes large trees. Such large trees provide important habitat for many species.

nearly one-third of the stands with low canopy cover 

appear to have resulted from management activities, a 

landscape trait that probably is beyond the HRV (low 

confidence)—even with the prevalence of dwarf mistletoe infections on the forest (which still leave snags that 

provide some canopy cover). Considerable uncertainty 

is involved with this conclusion because of the lack of 

information on the amount of forested land where trees 

could have been thinned due to surface fires, insects or 

pathogens during the HRV period.

Landscape proportions in high-density classes for 

snags and coarse woody debris. Snag and coarse woody 

debris density is often highest in recently burned forests 

(Tinker 1999) and in old-growth forests (Mehl 1992). 

When the percentage of the landscape in such forests is 

below the HRV, the numbers of snags and the amount of 
72 USDA Forest Service RMRS-GTR-140. 2005

Figure 41—Forest successional stages on the Bighorn Forest. Proportions of forests in late successional stages are shown for 

each watershed, numbered 1 to 12 (see fig. 7 for watershed boundaries). Late successional stages include stands with very 

large, old pine; transitional, old trees; and very large, old spruce, fir, or Douglas-fir. Source: BNF.
USDA Forest Service RMRS-GTR-140. 2005 73

coarse woody debris on the landscape also is probably 

below the HRV. Fire suppression has reduced the area of 

recently burned forests by at least 10%, and timber harvesting has reduced the area of old-growth forests. Both 

observations suggest that areas with high snag densities 

are less common than during the HRV period (moderate 

confidence).

Edge, interior forest habitat, patch shape, and patchiness. The spatial configuration of the landscape patches 

has been changed due to timber harvesting. Whereas 

fires and blowdowns produce many small patches and a 

few large patches, clearcuts produce a few small patches 

and many mid-size (4-40 ha [10-99 acres]) patches (figs. 

30, 32, 34, and 36). Hence, in contrast to the large, contiguous, even-aged cohorts that would have developed 

after fires during the HRV period, clearcut harvesting 

has tended to produce smaller patches at any given time 

(mostly dominated by lodgepole pine; fig. 34), which 

are dispersed throughout the high-elevation, forested landscape. In this sense, clearcuts “perforate” areas 

of interior forest (Forman 1995) and do not perpetuate 

large areas of even-aged forest, as would have occurred 

with fire and blowdowns (fig. 36).

Also, although edges were certainly created between 

areas of different burn intensities, human-created edges (around clearcuts and along roads) usually are more 

abrupt. The effects of such edges on plants and animals 

that require interior forest conditions or security cover can be detrimental (Murcia 1995; Beauvais 1997). 

Fragmentation apparently has not affected bird species 

diversity significantly on the BNF (Merrill and others 

1993), but loss of the interior-dependent wildlife species is of regional concern (Beauvais 2000). For these 

reasons, many investigators have argued that timber 

harvesting and other human activities cause the fragmentation of high-elevation forests, both on the BNF 

(Tinker and others 1998) and elsewhere in the Rocky 

Mountains (Baker 1994; Reed and others 1996a, 1996b; 

R.L. Knight and others 2000, Tinker et al. 2003).

Using a LANDSAT-derived database in Arc/Info 

(fig. 36), we compared a number of landscape patterns 

of clearcuts across watersheds on the BNF to the more 

natural patterns produced by fires and blowdowns in 

the last 43 years on the BNF, to quantify timber harvest 

effects. We used the program FRAGSTATS (McGarigal 

and Marks 1995) to quantify the patterns of the patches created by these disturbances. Rather than evaluating 

the patterns of the entire landscape (as was done in another study on the BNF by Tinker and others 1998), 

we focused on the configuration of just the disturbance 

patches shown in fig. 36. The mean of pattern variables 

created by clearcuts (e.g., edge density and percentage of 

land in clearcut) averaged across watersheds fell within 

the range of patterns from fires, but some individual watersheds had more edge per ha and total land in patches 

caused by clearcuts than ever occurred with fire or wind 

(fig. 42). On average, clearcuts were smaller, had less 

complex (convoluted) shapes, less variation in patch size, 

and smaller maximum patch sizes than natural patches 

(figs. 14 and 42). These patch variables probably are beyond their respective HRVs (moderate confidence).

Thus, the watersheds with heavy cutting have more 

homogeneous patch sizes than before, and the level of 

patchiness probably has exceeded the HRV for those watersheds (moderate confidence), assuming high-elevation 

fire and blowdown patterns in the last half century are 

somewhat similar to the HRV. This assumption is violated for fire patterns, since current fire sizes are, on average, 

smaller than fire sizes during the HRV period due to fire 

suppression. However, because fire sizes were actually 

bigger during the HRV period, the contrast in patch sizes 

is even more evident (large for fire, small for clearcuts). 

Tinker et al. (2003) similarly found clearcutting created 

more, smaller patches with less variability in size and more 

edge per hectare on landscapes of the Targhee National 

Forest, Wyoming when compared to the HRV in a nearby 

Yellowstone National Park landscape.

When we compared patterns of shelterwood cuts 

(which begin as partial cuts) to patterns of partial blowdowns in the last 43 years, using the same database (fig. 

36), shelterwood cuts in some watersheds had more 

edge per patch area, more total area, and a larger area 

in the biggest patch than the HRV of partial blowdowns 

(fig. 43). All partial blowdowns may not have been detected on the LANDSAT imagery, but shelterwood cuts 

probably are still more abundant on the landscape than 

the partial blowdowns. Additionally, shelterwood cuts 

are not equivalent to partial blowdowns because the rest 

of the trees are removed within 10 to 30 years (and bolewood is removed in the former). Possibly, some partial 

blowdown areas have complete blowdown or insect attack that destroys the rest of the trees in the future, but in 

general, the 2 to 3-step shelterwood system is a new kind 

of disturbance. The patterns that are created are beyond 

the HRV (moderate confidence). Other disturbances in 

the past 43 years (from insects or disease) apparently 

did not create large enough patches to be detected on the 

LANDSAT imagery.

Tinker and others (1998) looked at the effects of roads 

and clearcuts on landscape patterns on the BNF (the extensive road network is shown in fig. 16 and a map of 

clearcuts is in fig. 13). They found that both roads and 

clearcuts appeared to (1) reduce core area (interior area 

of patch with edge depth of 50 m [164 ft]) of all land 
74 USDA Forest Service RMRS-GTR-140. 2005

Figure 42—Mean (box or circle) averaged over 12 watersheds and range (line) of variables describing landscape patterns of 

disturbance patches that were created on the Bighorn National Forest by fires, blowdowns, and clearcuts between 1955 

and 1998, calculated using data in fig. 36. SD = standard deviation (measure of variability), “complex shape” = area-weighted shape index, and “to neighbor” = distance to nearest neighboring disturbance patch. Watershed size ranges from 4162 

to 57,067 ha (10,280-14,095 acres). Means were similar for amount of land and edge in disturbance patches and distance 

between neighboring patches, but patches formed by fire or blowdowns had more complex shapes and larger and more variable patch sizes. However, the range extended higher for amount of land and edge in clearcut patches than patches formed 

by fire or blowdowns, an indication that some watersheds had a much higher amount of disturbance than caused by fires or 

blowdowns. Because the complex shape index rarely exceeds 20, the relative difference between means is larger than it appears on the graph.

Figure 43—Mean (circle or square) and range 

(line) of characteristics of “partial” disturbance 

patches created by blowdowns or shelterwood 

cuts between 1955 and 1998, averaged over 

the 12 watersheds on the Bighorn National 

Forest using data from fig. 36. The “biggest 

patch %” value is the percent of watershed 

composed of the largest partial disturbance 

patch. Much more land has been affected by 

partial cutting (shelterwood cuts) than by partial blowdowns.

0 10 15 20

biggest patch % partial blowdown

shelterwood cut

biggest patch %

edge (m/ha)

edge (m/ha)

% land

% land

5
USDA Forest Service RMRS-GTR-140. 2005 75

cover types, (2) increase edge and edge convolution, (3) 

reduce patch size, and (4) increase patch diversity on the 

landscape. In two of the twelve watersheds, clearcuts 

and roads reduced the area of interior forest lower than 

values before roads and timber harvests. Considering that 

the numerous meadows and shrublands on the BNF give 

the landscape a rather high amount of natural edge and 

relatively low amount of interior forest (fig. 10; Knight 

and Reiners 2000), timber harvesting appears to have 

reduced the amount of already limited interior forests, 

probably to a point that is beyond the HRV (moderate 

confidence).

Compared to historic fires, clearcutting affects a 

much smaller area on the BNF (fig. 21), but harvesting 

every year in similar patch sizes creates a pattern on the 

landscape over time that is different than would have occurred during the reference period. For example, on the 

Medicine Bow National Forest in southeastern Wyoming, 

Tinker and Baker (2000) found that if practices observed 

from 1985-1993 continue over time, the spatially variable landscape patterns created by fire would cease to 

exist. In their place would be a patchwork of more or 

less equal sized patches with staggered age distributions. 

All age classes would continue to be represented on the 

landscape, but patches of the same age class would become small and isolated rather than large and contiguous 

(high confidence). Tinker and Baker concluded that future landscape structure will have little resemblance to 

conditions in the 1700s and 1800s if the practices observed from 1985-1993 continue (which included the 

rather unusually small patch-cuts associated with the 

Coon Creek Project on the Medicine Bow National 

Forest). Other studies of landscape patterns created by 

clearcut harvesting and road building have reached the 

same conclusion (Reed and others 1996a, 1996b; Miller 

and others 1996; Tinker and others 1998). Such studies 

make assumptions that timber harvesting will continue with the same approach as in the past on all suitable 

lands. This assumption may be unrealistic, because size 

and amount of area harvested have changed over time 

(figs. 12 and 14), but the studies show that fragmentation 

has steadily increased.

Disturbance return intervals and rate at which new 

patches are formed. Another aspect of silvicultural 

practices that can be compared to disturbances during 

the reference period is the return interval for successive disturbances at a site. Currently, the 1985 BNF 

Management Plan (pages II-232) specifies the rotation 

age for clearcutting in subalpine/montane landscapes at 

60 to 180 years for lodgepole pine, 100 to 240 years in 

spruce-fir, 80 to120 years for aspen, and 100+ years for 

other cover types. For two- and three-step shelterwood 

cuts, the rotation ages are 100 to 240 years for stands 

dominated by Engelmann spruce and subalpine fir, 90 

to 180 years for lodgepole pine, and 80+ for other cover types. If a mean return interval for stand-replacing 

fires of 150 to 300 years (spruce-fir typically would be 

on the long-end of the range) is assumed for individual 

stands during the HRV (Arno 1980; Romme and Knight 

1981; Romme and Despain 1989), then the silvicultural 

rotation ages in general tend to be somewhat shorter, depending on fire-return interval at specific sites.

The timing of thinning and partial harvests on the 

BNF also are different from natural disturbance frequency. For example, both mountain pine beetles and 

spruce beetles typically affect stands that are at least 

70 to 80 years old. In contrast, precommercial thinning, 

which sometimes has the same effect as beetles in reducing competition and increasing growth of surviving 

trees, is often prescribed for 20- or 35-year-old stands. 

Thinning 90- to 100-year-old stands was the standard 

practice in the 1970s and early 1980s. Monitoring has 

shown that this practice has not been economically effective for increasing tree growth and that it creates 

excessive slash (B. Bornong, BNF ecologist, personal communication). Because of the current thinning of 

young stands and shelterwood cutting, which involves 

two or three cuts per rotation, the landscape disturbance frequency is higher than with natural processes, 

especially with the addition of the concomitant roadbuilding and maintenance.

The result of the above changes in the site-specific 

return interval for disturbances is a change in the rate at 

which new patches are formed across the landscape. For 

example, in one BNF watershed, the mean clearcut return 

interval across the landscape (not in one site) was shorter 

with timber harvest than the mean interval for all fires that 

occurred prior to and after 1877 (fig. 20). The increased 

harvest return rate results in the increased patchiness on 

the landscape that is occurring in some heavily-cut watersheds (watersheds 1, 2, 3, 4, 7, 8, 9, 10, and 11 in fig. 

7; fig. 13). Thus, it is likely that the rate at which new 

landscape patches are formed now exceeds the HRV 

(high confidence).

In summary, the general conclusion is that EuropeanAmericans have made a significant imprint on 

high-elevation landscapes through timber harvesting 

on about 20% of the high-elevation forests on the BNF. 

Since the late 1800s, a large amount of old-growth forest has been cut, probably lowering the amount of this 

forest type to below the HRV. A large number of roads 

now exist also, contributing to a level of fragmentation that probably exceeds the HRV in locations where 

forests occur over large, flatter areas. The affected forests occur primarily north and south of the Cloud Peak 

Wilderness.
76 USDA Forest Service RMRS-GTR-140. 2005

6.2.2 Landscape structure at low-elevations 

(including aspen and non-forest vegetation)

Because the majority of forested area on the BNF occurs at high-elevation (81%), the data for the BNF enable 

conclusions that are largely pertinent to high elevations. 

It is clear, however, that the low elevation landscape 

patterns are different. Fire suppression probably has impacted the low-elevation landscape more than timber 

harvesting, as less than 2% of the low-elevation forests 

have been harvested (BNF data for 2001)—about 1% 

shelterwood cuts and 1% mostly clearcuts. As in the previous section, we first examine stand structure variables 

at the landscape scale; and then we discuss variables that 

apply to landscape mosaics.

Forest stand structure at the landscape scale. Most 

of the low-elevation landscape probably had grasslands, 

shrublands and relatively open forests during the HRV 

reference period because of frequent surface fires and 

the patchy distribution of soils and microclimate in the 

topographically variable foothills where ponderosa pine, 

Douglas-fir, and limber pine could survive. However, 

there probably were always some stands that escaped the 

surface fires, resulting in higher tree and sapling density, 

lower understory plant densities, and fewer and smaller canopy gaps than in neighboring stands that burned 

more frequently (Romme and others 2000). When 

the few forested stands were averaged with the abundant woodlands and shrublands, and projected through 

time during the HRV period, tree and sapling density 

on low-elevation landscapes probably ranged from low 

to moderately low. With the open canopy cover, density 

of grasses and forbs in the understory probably ranged 

from moderately high to high. Forest floor depth did 

not accumulate, due to the frequent fires, and the HRV 

probably remained fairly narrow at low values. 

Average size and age of trees was probably moderate to 

moderately high. It is impossible to quantify variables 

such as these at the present time.

Where fire suppression has been effective, tree and 

sapling densities and canopy cover averaged across the 

landscape are now relatively high, while canopy gap 

area and the cover of understory vegetation are relatively low. On average, tree size and age probably have 

declined due to larger numbers of young trees. Overall, 

where fire suppression has been effective, tree and sapling density (and thus fuel continuity), mean age and 

size of trees, forest floor depth, and some understory vegetation variables are probably outside the HRV 

(moderate confidence). Snag density and coarse woody 

debris could be relatively low in areas subjected to timber harvesting, but as most of the landscape has not 

been harvested (only about 2% of the landscape at low 

elevations), the majority of the low-elevation forest 

probably still has snag density and coarse woody debris amounts within the HRV (low confidence). Species 

diversity across the landscape is relatively high and relatively constant through time because of the great variety 

of environments and successional stages in the BNF, 

and because diversity probably has not been affected in 

an adverse way at the landscape scale by management 

practices (moderate confidence).

Proportion of landscape in different land cover types. 

The proportion in different land cover types in low-elevation landscapes has changed between 1931 and 1994 

(fig. 38). Specifically, the amount of forested area has increased about 4%, with Douglas-fir increasing by about 

6% and ponderosa pine declining by about 2%. Aspen 

was not extensive in the 1930s on the BNF, nor is it today with < 1% land cover (fig. 38), and thus, detecting 

change is difficult. The abundance of aspen probably is 

not outside the HRV (low confidence). Notably, in comparing historic and modern photographs taken on the 

BNF, it is clear that up to half of the aspen stands in some 

photographs died between 1900 and 1975 (Wyoming 

State Historical Society 1976).

As discussed in section 6.1.3, aspen cover has declined in some areas due to a variety of factors (DeByle 

1979; Veblen and Lorenz 1986; Kay 1990, 1993; Kay 

and Wagner 1996; Baker and others 1997; Hessl 2002; 

and several papers in Shepperd and others 2001). 

Livestock and large ungulates are possibly causing declines in aspen in the small area where it occurs on the 

BNF, particularly on low-elevation winter ranges, but 

other causes of aspen decline may be as important. To 

help offset declines in aspen, clearfelling was used in the 

1980s to regenerate some aspen stands (about 200 ha), 

and many of the new shoots (ramets) have now grown 

into the sapling-pole stage (BNF data; USDA Forest 

Service 1994).

With regard to the non-forest vegetation at low elevations, there would have been some fluctuation in the 

abundance of grassland and shrublands during the HRV 

reference period due to the effects of fire and the varying sprouting capacity of the different shrub species, as 

discussed in section 5.1.4 Fire suppression may have 

caused the land area in shrublands to become relatively 

high. However, we have no basis for concluding that this 

variable is beyond its HRV (low confidence).

In sum, we believe the proportion of the different vegetation types is still within the HRV on low-elevation 

landscapes in the BNF (low confidence).

Forest patch sizes and configuration. The low-elevation landscapes of the BNF during the HRV period 

probably were composed of distinct and separate stands 

of Douglas-fir, ponderosa pine and limber pine (with 
USDA Forest Service RMRS-GTR-140. 2005 77

variation in age-structure within each stand). Such 

landscapes probably resulted largely from topographic 

control, but fires also would have created openings of 

various sizes (Kaufmann and others 2000). Today, due 

to fire suppression, some areas are more homogeneous 

than during the reference period (moderate confidence).

Using BNF data, we found that clearcutting practices 

(mostly in the 1960s) increased mid-sized patches (4-40 

ha [10-99 acres], fig. 34) over and above the HRV under 

natural fire regimes (fig. 33) in low-elevation Douglasfir forests, which are the most abundant low-elevation 

forests on the BNF. Timber harvesting occurred on a 

small percentage of the landscape, but, in the small areas where wood was removed, the distribution pattern of 

the openings created by harvesting is probably beyond 

the HRV for comparable openings created by fire and 

other disturbances (low confidence).

Proportion of landscape dominated by old trees. 

Because only a small percentage of the Douglas-fir has 

been harvested (1%), timber harvest has probably not 

yet reduced the percentage of the low-elevation landscape in old trees below the HRV (moderate confidence). 

However, the available preliminary data indicate that 

only 1% of the land area with Douglas-fir is classified 

as old-growth (BNF data). Because little harvesting has 

occurred at low elevations, we are hesitant to postulate 

a cause for such apparent low proportions. Old-growth 

forests certainly could be lost in the future if suitable 

lands are harvested at the planned rotation rate. Fire suppression could cause more of the low-elevation forests to 

have old trees. However, this practice has been in effect 

for too short a time for that to happen.

Timber harvest has reduced the number of old trees in 

other Rocky Mountain low-elevation landscapes. For example, on an unlogged landscape of ponderosa pine and 

Douglas-fir in Colorado, about one-third of the sampled 

tree patches contained old trees (>300 years), whereas a 

nearby logged landscape had only one-fifth of the patches with old trees (Kaufmann and others 2000). Notably, if 

old trees are defined as >200 years rather than >300 years 

in the Colorado study, then old-growth was as common 

on the logged landscape. The number of patches with 

>200-year-old trees comprised half the patches and were 

similar between the logged and unlogged areas. The harvested landscape used for the Colorado study also had 

more dense trees and fewer openings than the unharvested one. The oldest and largest trees had been cut, leaving 

a more dense forest with smaller trees.

Proportion of landscape with high-densities of snags 

and coarse woody debris. Areas with extensive cutting for 

firewood or lumber would have reduced snags and coarse 

woody debris across the landscape. Wood harvesting 

(at least since 1940) has not yet been extensive at low elevations on the BNF. Therefore, we cannot conclude that 

harvesting has reduced the percentage of the landscape 

with high density snags and coarse woody debris below 

the HRV (high confidence). Coarse woody debris at low 

elevations may have been less than at high elevations 

during the reference period, because of frequent surface fires that provided more frequent opportunities for 

its combustion, but we doubt that the proportion of land 

with coarse woody debris and snags is outside the HRV 

(low confidence). Of course, outbreaks of insects or various diseases can lead to rapid increases in coarse woody 

debris at both high and low elevations.

Overall, management strategies that recognize the 

long-term, historic importance of fire, insects, and other 

natural disturbances—and aim to maintain large trees 

and snags—will most likely allow low-elevation forests 

to stay within their HRV (Romme and others 2000).

7. Summary of Probable HRV 

Deviations

Based on the literature and data that we reviewed, and 

our understanding of the ecology of the BNF, it seems 

clear that human-caused deviations from the HRV are 

occurring in some areas, primarily because they are 

subjected to timber harvesting, fire suppression, and 

livestock grazing. Does this matter? An answer is beyond the scope of this report. However, deviations from 

the HRV, where they appear to be occurring, should be 

evaluated through monitoring and research to determine 

if the deviations could lead to undesirable consequences.

As our report describes, forest disturbances on the BNF 

are not new. Indeed the forests have evolved with regular 

disturbances, and the historical record indicates that significant human-caused disturbances have occurred since 

the late 1800s. Moreover, many forested areas have been 

subjected to numerous episodes of burning during the 

HRV period. Still, only about 18% of the forested area 

has been harvested on the BNF (high and low-elevation 

forests combined). Roughly 12% has been harvested on 

two occasions. In contrast, the effects of fire suppression 

and livestock grazing have been widespread.

Based on our understanding of BNF ecosystems, 

we have attempted to draw conclusions about whether 

or not certain ecosystem variables are now beyond the 

HRV they experienced during the period 1600-1890, or 

trending in that direction (table 7).
78 USDA Forest Service RMRS-GTR-140. 2005

Table 7—Summary of variables describing upland vegetation characteristics on the Bighorn National Forest relative to their estimated 

historic range of variability (HRV) from about 1600 to 1890, with an indication of our confidence in making each comparison at 

the stand (S) and landscape (L) scales. Stand characteristics are evaluated for areas modified by human activities only. Landscape 

characteristics are evaluated across the landscape for parts or all of the BNF. For our discussion of each variable, refer to the pages 

listed in the column on the right. At high elevations, stand scale analyses focus on harvested areas, whereas at low elevations the stand 

scale analyses focus on unharvested stands. This is because very little timber has been harvested at low elevations and fire suppression 

has had a greater effect there.

Within Outside Pages with

Variable HRV HRV Confidence discussion of variable

High-elevation forests

Disturbances

Mean return interval for stand-replacing fires S L S Moderate, L-Low 26-38, 66-75

Fire intensity S,L High 26-38, 66-75

Fire size L Low 26-38, 66-75

Insect epidemics S,L Moderate 43-45

Dwarf mistletoe abundance S,L Low 48-51

All other diseases S,L Low 48-51

Wind S,L High 52-53

Stand structure at high elevations

Density of trees in all age and size classes S,L S-High, L-Moderate 54-55, 66-68

Regeneration time and seedling/sapling density S,L S- High, L-Moderate 55-56, 66-68

Tree canopy cover and the density and size of canopy gaps S,L S-Moderate, L-Low 56, 66-68

Understory plant density and cover S,L S-High, L-Moderate 56-57, 66-68

Diversity of all plants S,L Low 57, 66-68

Age and size-class structure of trees in most stands S L Moderate 57-58, 66-68

Age- and size-class structure of trees on some north slopes, S Moderate 57-58

 leeward slopes and ravines

Forest floor depth S,L S-High, L-Moderate 58, 68

Mineral soil affected S,L High 58

Snag density S,L High 59-60

Coarse woody debris S,L High 59-60

Landscape features at high elevations

Proportion of landscape in low canopy cover L Low 70-71

Number and proportion of different land cover types L High (moderate 68-69

 for sagebrush)

Forest/non-forest land area ratio L High 69

Proportion of forest land in old-growth and mid-successional L Moderate 69-70

 stages

Proportion of land with high snag and CWD densities L Moderate 71-73

Proportion of land in edge, interior forest, and patchy forest L Moderate 73-75

Rate at which new, uniformly distributed, small- to mid-sized L High 75

 patches are formed

Low-elevation forests

Disturbances

Mean return interval for surface fires S,L Moderate 38-43, 61-65

Fire size L Moderate 38-43, 61-65

Insect epidemics S,L Low 45-48, 61-65

White pine blister rust S,L High 51

Other diseases S,L Moderate 51

Wind S,L High 52-54

Stand structure at low elevations 

Tree density and canopy cover S,L S-High, L-Moderate 61-63, 76

Tree species diversity S,L High 61-62, 76

Understory plant composition and cover S,L Low 61-62, 76

Size- and age-class structure S,L Moderate 62, 76

Spatial distribution of trees S, L Moderate 62-63, 76

Forest floor depth S,L S-High, L-Moderate 63, 76

Snag densitya S,L S-Moderate, L-Low 63, 76

Coarse woody debrisa S,L Low 63, 76
USDA Forest Service RMRS-GTR-140. 2005 79

Table 7—Continued.

Within Outside Pages with

Variable HRV HRV Confidence discussion of variable

Low-elevation forests—Continued.

Landscape features at low elevations

Proportion of landscape with high-density trees and high L Moderate 76-77

 fuel continuity

Proportion of landscape with low understory plant cover L Moderate 76-77

 and relatively deep forest floors

Proportion of landscape dominated by old trees L Moderate 77

Proportion of landscape with high-densities of snags and L Low 77

 coarse woody debris

Proportion of landscape in different cover types L Low 76

Forest patch sizes and configuration L Moderate 76-77

Aspen woodlands

Insect epidemic frequency S,L Moderate 47-48

Blowdown frequency S,L High 52-54

Fire size and mean return interval at stand and landscape S,L Moderate 42-43

 scales

Disease abundance S,L S near Low 51

 recreation 

 areas

Tree density S,L Moderate 64

Conifer density in understory S, L Moderate 64

Understory plant composition with exotic plant species S, L High 64

 present

Representation in landscape L Moderate 76

Non-forest vegetation Little information available for drawing 25-26, 43, 48, 51,

conclusions about specific variables, but 64-65, 76-77

see summary and text for discussion

a

Stands that were harvested at low elevations would have snag and coarse woody debris density below the HRV (moderate confidence), but such stands 

are uncommon on the BNF.

At high elevations the following variables estimated 

at the stand scale appear to be within the HRV (confidence level is indicated in parentheses):

• Fire return interval (moderate) and intensity (high)

• Insect outbreaks (moderate)

• Abundance of diseases, except for dwarf mistletoe in 

some areas (low)

• Blowdowns (high)

• Tree, sapling, and seedling density (high)

• Plant species diversity (low)

• Understory plant density and cover (high)

• Age- and size-class structure of most stands (moderate)

• Forest floor depth (high)

Similarly, the following variables estimated at the 

landscape scale appear to be within the HRV at high elevations:

• Fire intensity (high)

• Insect outbreaks (moderate)

• Abundance of diseases except for dwarf mistletoe 

(low)

• Blowdowns (high)

• Tree, sapling and seedling density (moderate)

• Understory density and cover (moderate)

• Plant species diversity (low)

• Forest floor depth (moderate)

• Number and proportion of land cover types (high)

• Forest/non-forest ratio (high)

At low elevations, the following stand variables appear to be within the HRV:

• Insect outbreaks (low)

• Abundance and composition of diseases, except where 

the introduced white pine blister rust occurs (moderate)

• Blowdowns (high)

• Tree species diversity (high)
80 USDA Forest Service RMRS-GTR-140. 2005

• Snag density and abundance of coarse woody debris, 

except where timber harvesting has occurred (moderate and low, respectively)

Similarly, the following landscape variables appear to be 

within the HRV at low elevations:

• Insect outbreaks (low)

• Abundance and composition of diseases, except 

where the introduced white pine blister rust occurs 

(moderate)

• Blowdowns (high)

• Tree species diversity (high)

• Proportion of landscape with old trees (moderate)

• Proportion of land with high densities of snags and 

coarse woody debris (low)

• Proportion of land in different land cover types (low)

For aspen stands, the following variables appear to be 

within the HRV at high and low elevations and at both 

the stand and landscape scales:

• Insect outbreaks (moderate)

• Disease abundance (low), except near campgrounds

• Blowdowns (high)

• Tree density (moderate)

Very little information is available for drawing conclusions about the HRV of grassland, meadow, and 

shrubland variables on the BNF. However, fire return interval, size, and intensity appear to be within the HRV, 

probably at both the stand and landscape scales (low 

confidence).

In contrast, the following variables probably are beyond their HRV:

Within stands at high elevations affected by timber 

harvest (about 20% of the high-elevation forests on 

the BNF):

1. Canopy cover probably is lower and the size and density of canopy gaps probably is higher in harvested 

stands than the HRV for these variables in unmanaged forests of comparable age and site conditions 

due to selective and shelterwood cuts, thinning, and 

fewer standing-dead trees (moderate confidence).

2. Snag density and the amount of coarse woody debris are 

lower than the HRV for unmanaged stands of comparable age and site conditions (high confidence). 

Whole-tree yarding can accentuate this variation 

by concentrating coarse woody debris and slash at 

landings in a way that has not occurred previously.

3. Due to some methods of slash treatment, the intensity of soil scarification is beyond the HRV in some 

areas (high confidence). Burning can remove the 

forest floor, but the depth of soil disturbance typically is less than following mechanical harvesting. 

Similarly skid trails probably have compacted soils 

beyond their HRV, at least temporarily.

4. Age- and size-structure of managed stands within ravines or on some north or leeward slopes is skewed 

toward smaller and younger trees than would have 

occurred during the HRV period, because of harvesting where fires would have been less likely to 

burn (moderate confidence).

5. Dwarf mistletoe abundance is probably above its HRV 

in stands subjected to partial timber harvests, but it 

could be less than its HRV in clearcut stands (low 

confidence).

Across forested landscapes at high elevations:

6. The estimated rotation times for harvesting of timber from forests judged suitable for harvesting are 

generally shorter, on average, than the estimated 

site-specific mean intervals between natural disturbances in high-elevation forests. On the area where 

timber harvesting has occurred, old-growth forest 

has been reduced, particularly in areas that have 

had long fire-free intervals, such as in valley bottoms and on some north or leeward slopes. Thus, in 

such areas, ecosystem characteristics that depend 

on periods of forest growth longer than 140 years 

may be lost, resulting in less old-growth forest on 

the landscape. The proportions of other age-classes are within the HRV, except for the now more 

abundant mid-successional forests in harvested areas (moderate confidence).

7. The average snag density and coarse woody debris 

biomass across the landscape have been reduced 

below the HRV (high confidence). The loss of some 

old-growth forests and the suppression of fires that 

create abundant snags have reduced the percentage 

of the forested landscape that contains high density 

snags/coarse woody debris to a level that is below 

the HRV (moderate confidence).

8. The rate of patch formation and the size of disturbances across high elevation landscapes are outside the HRV (high confidence). Timber harvest 

produces patches more frequently than natural disturbances, and mid-sized patches are over-represented. Natural fires produce many small patches and a few very large patches at high elevations. 

Fire frequency, size, and extent also have been reduced below the HRV due to fire suppression (low 

confidence).
USDA Forest Service RMRS-GTR-140. 2005 81

9. The percentage of the landscape with low canopy cover probably is higher than the HRV due to partial 

cutting and thinning (low confidence).

10. Due to roads and clearcutting, the amount of edge 

is now higher and the amount of interior forest is 

lower than prior to the 1900s in parts of the BNF 

where timber harvesting has occurred (moderate 

confidence). Correlated with this and fire suppression is a decline in the maximum patch size, the 

development of a more simple patch shape, and a 

higher, more uniform level of landscape patchiness 

than would have occurred during the reference period (high confidence).

11. Some kinds of mechanical slash treatment have led 

to a higher level of mineral soil disturbance than 

would have occurred during the HRV reference period (high confidence).

12. Dwarf mistletoe may be somewhat above its HRV on 

the landscape scale due to the tie-hacking, selective cutting, fire suppression, and thinning that has 

occurred on the forest (low confidence).

Within stands at low elevations affected by harvest, 

fire suppression, and livestock grazing:

13. Fire suppression, livestock grazing, and possibly climate change have led to the development of lowelevation forest stands with higher densities of 

young trees, greater canopy cover, less understory plant cover, and deeper forest floors than usually occurred on many sites before 1890 (see table 7 

for confidence levels associated with specific variables). Understory composition also has changed 

where introduced plants occur.

14. By removing large trees and downed wood from the 

system, wood harvesting has lowered the abundance of snags and coarse woody debris in managed stands of low-elevation forests (moderate 

confidence). Harvesting also has led to an increase 

in sapling density and a reduction in the average 

diameter of trees, thus creating younger, more 

uniform-sized stands than existed before harvest 

(moderate confidence). However, only about 1% 

of such forests have been subjected to harvesting 

thus far. Without harvesting and with fire suppression, snags and coarse woody debris probably are 

still within the HRV, as noted previously.

15. Mean fire return interval has become longer than 

the HRV due to fire suppression (moderate confidence). Consequently, there is a trend for tree distribution to be more uniform and to have tree invasion into some meadows.

16. White pine blister rust outbreaks cause some stand 

variables to exceed the HRV in affected stands, as 

this disease is not native (high confidence).

Across forested landscapes at low elevations:

17. The sizes of most fires have declined due to fire suppression, and the mean fire interval, tree/sapling 

density, tree canopy cover, and amount and continuity of fuels is above the HRV in a larger proportion of the BNF than during the reference period 

(moderate confidence).

18. Understory plant density and cover have declined 

below the HRV (low confidence) and forest floor 

depth has increased above the HRV in a larger 

proportion of the landscape than during the reference period (moderate confidence).

19. White pine blister rust was absent during the HRV 

reference period, but is present today (high confidence).

20. The age- and size-class structure of trees is beyond 

the HRV (moderate).

Aspen woodlands

21. In some areas, livestock or native ungulate grazing 

and browsing have reduced aspen densities and affected the understory vegetation to a point where 

these variables are beyond their HRV (high confidence). These changes are confounded with the introduction of exotic plants.

22. Fire suppression has reduced fire size and lengthened 

fire return intervals, thereby enabling an increase 

in conifer density in some areas to a level that is 

higher than the HRV (moderate confidence).

23. Due to human wounding of trees in recreational areas, some stands have an incidence of disease that 

is beyond the HRV (low confidence).

Non-forest vegetation

24. Some meadows, grasslands, and shrublands are probably grazed more, or have been in the past, than 

during the HRV period, with the potential for an 

increase in soil erosion and forb and shrub abundance (moderate confidence). Deviations from 

the HRV are also caused by the presence of exotic plants that displace native species and cause 

changes in other ecosystem properties (high confidence).

Frequently there has been a lack of pertinent, quantitative data for the ecosystem variables we have addressed 

in this report. Such variables should be considered when 

identifying priorities for future research or monitoring. 
82 USDA Forest Service RMRS-GTR-140. 2005

Research will also be required if decisions about the 

severity of a problem cannot be made without more information or if ways of restoring the HRV for important 

variables cannot be identified.

Much has been learned about ecosystem structure and 

function, but the kinds of influences to which National 

Forests are now subjected are different and are occurring 

more rapidly than ever before—and in a cumulative way. 

Human experience with modern forest management has 

been too short to speak with confidence about sustainability, but HRV analyses can help achieve that goal. Our 

report, which focuses primarily on upland vegetation, 

should be supplemented with HRV reports on riparian ecosystems, aquatic ecosystems, and the population 

dynamics of plant and animal species thought to be potentially threatened by management activities.

Attitudes during the last century have set in motion 

changes that have pushed some ecosystem variables outside their HRV. The unusually high density of ponderosa 

pine in some areas is an example of how negative attitudes toward fire have influenced the landscape. Timber 

harvesting is sometimes promoted as a way of solving 

problems thought to be associated with fire suppression 

and the resultant development of what appear to be unhealthy forests. However, sick and dying trees surely 

have always been a part of the BNF—sometimes over 

large areas. Such trees create habitat for organisms that 

cannot survive on or around healthy trees. The biological 

diversity of an ecosystem, which assures their long-term 

survival without human intervention, is higher because 

of periodic waves of mortality that oscillate through the 

landscape.

For some observers of management practices, forests with an abundance of diseases and insects should 

be treated by harvesting slow growing or dying trees. 

That may be desirable in some situations, but such 

judgments should be preceded by analyses to determine whether or not fire suppression has been effective 

and is responsible for an increase in pathogens on specific sites, and whether or not the “treatment” creates 

more problems than it resolves. A stand of healthy 

trees surely is the goal of a tree farm on private land, 

but widespread stands of rapidly growing trees over 

much of a National Forest, where the pathogens are 

essentially all native, would not be within the HRV. 

Similarly, to harvest a forest to the point where it could 

not burn also would exceed the HRV for some ecosystem variables.

In general, a continuing challenge is to determine if 

there are options for reducing the undesirable effects 

that can be associated with extracting wood, suppressing fires, and grazing livestock while providing the other 

resources and amenities that are desired from National 

Forests. Considering the HRV for key variables can be 

useful in achieving that goal.

8. Literature Cited

Agee, J. K. 1997. Fire management for the 21st century. In: 

Kohm, K. A.; Franklin, J. F., eds. Creating a forestry for 

the 21st century: the science of ecosystem management. 

Washington, DC: Island Press: 191–201.

Alexander, R. R. 1964. Minimizing windfall around clear 

cuttings in spruce-fir forests. Forest Science. 10: 130–142.

Alexander, R. R. 1966. Establishment of lodgepole pine 

reproduction after different slash disposal treatments. 

Res. Note RM-62. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and 

Range Experiment Station.

Alexander, R. R. 1986. Silvicultural systems and cutting 

methods for ponderosa pine forests in the Front Range of 

the Central Rocky Mountains. Gen. Tech. Rep. RM-128. 

Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Forest and Range Experiment 

Station.

Alexander, R. R. 1987. Ecology, silviculture, and management 

of the Engelmann spruce-subalpine fir type in the Central 

and Southern Rocky Mountains. Agric. Handb. 659. Fort 

Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Forest and Range Experiment 

Station.

Alexander, R. R.; Noble, D. L. 1971. Effects of watering 

treatments on germination, survival, and growth of 

Englemann spruce: a greenhouse study. Gen. Tech. 

Rep. RM-182. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and 

Range Experiment Station.

Alexander, R. R.; Sheppard, W. D. 1984. Silvical characteristics 

of Engelmann spruce. Gen. Tech. Rep. RM-114. Fort 

Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Forest and Range Experiment 

Station.

Allen, K. K.; Harris, J. L. 1999. Insects and diseases of the 

Bighorn National Forest. Report on file at: U.S. Department 

of Agriculture, Forest Service, Bighorn National Forest, 

Sheridan, WY.

Allen, T. F. H.; Hoekstra, T. W. 1994. Toward a definition of 

sustainability. In: Covington, W. W.; DeBano, L. F., tech. 

coords. Sustainable ecological systems: implementing an 

ecological approach to land management; 1993 July 12–

15; Flagstaff, AZ. Gen. Tech. Rep. RM-247. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station: 98-107.

Amman, G. D. 1977. The role of the mountain pine beetle 

in lodgepole pine ecosystems: impact on succession. 

In: Mattson, W. J., ed. The role of arthropods in forest 

ecosystems. New York: Springer-Verlag: 3–18

Amman, G. D. 1978. Biology, ecology and causes of outbreaks 

of the mountain pine beetle in lodgepole pine forests. In: 

Kibbee, D. L.; Berryman, A. A.; Amman, G. D.; Stark, 

R. W., eds. Theory and practice of mountain pine beetle 
USDA Forest Service RMRS-GTR-140. 2005 83

management in lodgepole pine forests. Proceedings of a 

meeting; 1978 25–27 April; Pullman, WA. Moscow, ID: 

University of Idaho: 39–53

Amman, G. D., comp. 1989. Symposium on the management 

of lodgepole pine to minimize losses to the mountain 

pine beetle. Gen. Tech. Rep. INT-262. Ogden, UT: U.S. 

Department of Agriculture, Forest Service, Intermountain 

Experiment Station.

Amman, G. D.; McGregor, M. D.; Cahill, D. B.; Klein, W. H. 

1977. Guidelines for reducing losses of lodgepole pine to 

the mountain pine beetle in unmanaged stands in the Rocky 

Mountains. Gen. Tech. Rep. INT-36. Ogden, UT: U.S. 

Department of Agriculture, Forest Service, Intermountain 

Forest and Range Experiment Station.

Anderson, J. E.; Romme, W. H. 1991. Initial floristics in 

lodgepole pine (Pinus contorta) forests following the 1988 

Yellowstone fires. International Journal of Wildland Fire. 

1: 119–124.

Andrew, E. A.; Harrison, M. D. 1959. Cronartium comandrae

in Wyoming. Plant Disease Reporter. 43: 418–419.

Arno, S. F. 1976. The historical role of fire on the Bitterroot 

National Forest. Res. Pap. INT-187. Ogden, UT: U.S. 

Department of Agriculture, Forest Service, Intermountain 

Forest and Range Experiment Station.

Arno, S. F. 1980. Forest fire history in the Northern Rockies. 

Journal of Forestry. 78: 460–465.

Arno, S. F.; Gruell, G. E. 1986. Douglas fir encroachment into 

mountain grasslands in southwestern Montana. Journal of 

Range Management. 39: 272–276.

Arno, S. F.; Petersen, T. D. 1983. Variation in estimates of 

fire intervals: a closer look at fire history on the Bitterroot 

National Forest. Res. Pap. INT-301. Ogden, UT: U.S. 

Department of Agriculture, Forest Service, Intermountain 

Research Station.

Bailey, R. G.; Avers, P.; King, T.; McNab, W. 1994. Ecoregions 

and subregions of the United States. Washington, DC: U.S. 

Department of Agriculture, Forest Service. Map included.

Baker, F. S. 1949. A revised tolerance table. Journal of 

Forestry. 47: 179–181.

Baker, W. L. 1994. Landscape structure measurements for 

watersheds in the Medicine Bow National Forest using 

GIS analysis. Report by Department of Geography and 

Recreation, University of Wyoming, to the Routt-Medicine 

Bow National Forest, Laramie, WY.

Baker, W. L. 2002. Indians and fire in the Rocky Mountains: 

the wilderness hypothesis renewed. In: Vale, T. R., ed. Fire, 

native peoples, and the natural landscape. Covelo, CA: 

Island Press: 41–76.

Baker, W. L.; Dillon, G. K. 2000. Plant and vegetation 

responses to edges in the Southern Rocky Mountains. 

In: Knight, R. L.; Smith, F. W.; Buskirk, S. W.; Romme, 

W. H.; Baker, W. L., eds. Forest fragmentation in the 

Southern Rocky Mountains. Niwot, CO: University Press 

of Colorado: 221–245.

Baker, W. L.; Ehle, D. S. 2001. Uncertainty in surface-fire 

history: the case of ponderosa pine forests in the Western 

United States. Canadian Journal of Forest Research. 31: 

1205-–1226.

Baker, W. L.; Ehle, E. S. 2003. Uncertainty in fire history 

and restoration of ponderosa pine forests in the Western 

United States. In: Omi, P. N.; Joyce, L. A., eds. Fire, 

fuel treatments, and ecological restoration: conference 

proceedings; 2002 April 16–18. Proc. RMRS-P-2. Fort 

Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station: 319–330.

Baker, W. L.; Flaherty, P. H.; Lindemann, J. D.; Veblen, T. 

T.; Eisenhart, K. S.; Kulakowski, D. W. 2001. Effect of 

vegetation on the impact of a severe blowdown in the 

Southern Rocky Mountains, USA. Forest Ecology and 

Management. 168: 63–75.

Baker, W. L.; Kipfmueller, K. F. 2000. Spatial ecology of 

pre-EuroAmerican fires in a Southern Rocky Mountain 

subalpine forest landscape. Professional Geographer. 53: 

248–262.

Baker, W. L.; Monroe, J. A.; Hessl, A. E. 1997. The effects 

of elk on aspen in the winter range in Rocky Mountain 

National Park. Ecography. 20: 155–167.

Baker, W. L.; Veblen, T. T. 1990. Spruce beetles and fires in the 

nineteenth-century subalpine forests of western Colorado. 

Arctic and Alpine Research. 22: 65–80.

Balda, R. P. 1975. The relationship of secondary cavity 

nesters to snag densities in Western coniferous forests. 

Albuquerque, NM: USDA Forest Service Southwest 

Wildlife Habitat Technical Bulletin No. 1.

Balling, R. C., Jr.; Meyer, G. A.; Wells, S. G. 1992. Relation 

of surface climate and burned area in Yellowstone National 

Park. Agricultural and Forest Meteorology. 60: 235–293.

Barnes, B. V. 1966. The clonal growth habit of American 

aspens. Ecology. 47: 439–447.

Barrett, S. W. 1994. Fire regimes on andesitic mountain terrain 

in Northeastern Yellowstone National Park, Wyoming. 

International Journal of Wildland Fire. 4: 65–76.

Barrett, S. W.; Arno, S. F. 1982. Indian fires as an ecological 

influence in the Northern Rockies. Journal of Forestry. 80: 

647–651.

Bartos, D. L. 2001. Landscape dynamics of aspen and conifer 

forests. In: Shepperd, W. D.; Binkley, D.; Bartos, D. L.; 

Stohlgren, T. J.; Eskew, L. G., comps. Sustaining aspen in 

Western landscapes: symposium proceedings. Proc. RMRSP-18. Fort Collins, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Research Station: 5–14.

Bartos, D. L.; Campbell, R. B., Jr. 1998. Decline of quaking 

aspen in the Interior West: examples from Utah. Rangelands. 

20: 17–24.

Bartos, D. L.; Mueggler, W. F.; Campbell, R. B., Jr. 1991. 

Regeneration of aspen by suckering on burned sites in 

western Wyoming. Res. Pap. INT-448. Ogden, UT: U.S. 

Department of Agriculture, Forest Service, Intermountain 

Research Station.

Beal, J. . 1943. Relation between tree growth and outbreaks of 

the Black Hills beetle. Journal of Forestry. 41: 359–366.

Beauvais, G. P. 1997. Mammals in fragmented forests in the 

Rocky Mountains: community structure, habitat selection, 

and individual fitness. Laramie: University of Wyoming. 

Dissertation.

Beauvais, G. P. 2000. Mammalian responses to forest 

fragmentation in the Central and Southern Rocky 

Mountains. In: Knight, R. L.; Smith, F. W.; Buskirk, S. W.; 

Romme, W. H.; Baker, W. A., eds. Forest Fragmentation in 

the Southern Rocky Mountains. Niwot: University Press of 

Colorado: 177–219.

Beetle, A. A. 1956. Range survey in Wyoming’s Big Horn 

Mountains. Wyoming Agricultural Experiment Station 

Bulletin 341.

Bennetts, R. E.; White, G. C.; Hawksworth, F. G.; Severs, 

S. E. 1996. The influence of dwarf mistletoe on bird 
84 USDA Forest Service RMRS-GTR-140. 2005

communities in Colorado ponderosa pine forests. Ecological 

Applications. 6: 899–909.

Bessie, W. C.; Johnson, E. A. 1995. The relative importance 

of fuels and weather on fire behavior in subalpine forests. 

Ecology. 76: 747–762.

Billings, W. D. 1969. Vegetational pattern near alpine 

timberline as affected by fire-snowdrift interactions. 

Vegetatio. 19: 192–207.

Bliss, L. C. 1956. A comparison of plant development in 

microenvironments of arctic and alpine tundras. Ecological 

Monographs. 26: 303–337.

Bockheim, J. G.; Ballard, T. M.; Willington, R. P. 1975. 

Soil disturbance associated with timber harvesting in 

southwestern British Columbia. Canadian Journal of Forest 

Research. 5: 285–290.

Bornong, B. R. 1996a. A fire history study conducted on 

the North Fork of the Powder River, Bighorn National 

Forest, Wyoming. Report on file at: U.S. Department of 

Agriculture, Forest Service, Bighorn National Forest, 

Forest Supervisor’s Office, Sheridan, WY.

Bornong, B. R. 1996b. Silvicultural certification prescription. 

Report on file at: U.S. Department of Agriculture, Forest 

Service, Bighorn National Forest, Forest Supervisor’s 

Office, Sheridan, WY.

Botkin, D. B. 1990. Discordant harmonies, a new ecology 

for the twenty-first century. New York: Oxford University 

Press.

Brown, J. K. 1973. Fire cycles and community dynamics 

in lodgepole pine forests. In: Baumgartner, D. M., ed. 

Management of lodgepole pine ecosystems. Vol. 1. 

Pullman, WA: Washington State University: 429–456.

Brown, J. K.; DeByle, N. V. 1989. Effects of prescribed fire on 

biomass and plant succession in western aspen. Res. Pap. 

INT-412. Ogden, UT: U.S. Department of Agriculture, 

Forest Service, Intermountain Research Station.

Brown, P .M. 1994. Fire history of the Southern Black Hills, 

South Dakota. Final report for cooperative agreement 

No. 28-C3-776. Fort Collins, CO, and Rapid City, SD: 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station.

Brown, P. M.; Kaufmann, M. R.; Shepperd, W. D. 1999. Longterm, landscape patterns of past fire events in a montane 

ponderosa pine forest of central Colorado. Landscape 

Ecology. 14: 513–532.

Brown, P. M.; Ryan, M. G.; Andrews, T. G. 2000. Historical 

surface fire frequency in ponderosa pine stands in research 

natural areas, Central Rocky Mountains and Black Hills, 

USA. Natural Areas Journal. 20: 133–139. 

Brown, P. M.; Sieg, C. H. 1996. Fire history in interior 

ponderosa pine communities of the Black Hills, South 

Dakota, USA. International Journal of Wildland Fire. 6: 

97–105.

Bull, E. L.; Parks, C. G.; Torgersen, T. R. 1997. Trees and 

logs important to wildlife in the Interior Columbia River 

Basin. Gen. Tech. Rep. PNW-GTR-391. Portland, OR: 

U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station.

Burke, I. C.; Reiners, W. A.; Olson, R. K. 1989. Topographic 

control of vegetation in a mountain big sagebrush steppe. 

Vegetatio. 84: 77–86.

Buskirk, S. W.; Romme, W. H.; Smith, F. W.; Knight, R. L. 

2000. An overview of forest fragmentation in the Southern 

Rocky Mountains. In: Knight, R. L.; Smith, F. W.; 

Buskirk, S. W.; Romme, W. H.; Baker, W. A., eds. Forest 

fragmentation in the Southern Rocky Mountains. Niwot: 

University Press of Colorado: 3–15.

Campbell, R. B.; Bartos, D. L. 2001. Aspen ecosystems: 

objectives for sustaining biodiversity. In: Shepperd, W. 

D.; Binkley, D.; Bartos,, D. L.; Stohlgren, T. J.; Eskew, 

L. G., comps. Sustaining aspen in Western landscapes: 

symposium proceedings. Proc. RMRS-P-18. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station: 299–308.

Christiansen, E.; Waring, R. H.; Berryman, A. A. 1987. 

Resistance of conifers to bark beetle attack: searching for 

general relationships. Forest Ecology and Management. 

22: 89–106.

Christensen, N. L.; Agee, J. K.; Brussard, P. F.; Hughes, J.; 

Knight, D. H.; Minshall, G. W.; Peek, J. M.; Pyne, S. J.; 

Swanson, F. J.; Thomas, J. W.; Wells, S.; Williams, S. E.; 

Wright, H. A. 1989. Interpreting the Yellowstone fires of 

1988: ecosystem responses and management implications. 

BioScience. 39: 678–685.

Christensen, N. L.; Bartuska, A. M.; Brown, J. H.; Carpenter, 

S.; D’Antonio, C.; Francis, R.; Franklin, J. F.; MacMahon, 

J. A.; Noss, R. F.; Parsons, D. J.; Peterson, C. H.; Turner, M. 

G.; Woodmansee, R. G. 1996. The report of the Ecological 

Society of America on the scientific basis for ecosystem 

management. Ecological Applications. 6: 665–691.

Clark, J. S. 1990. Fire and climate change during the last 750 

years in northwestern Minnesota. Ecological Monographs. 

60: 135–159.

Clements, F. E. 1910. The life history of lodgepole burn 

forests. U.S. Department of Agriculture, Forest Service 

Bulletin 79.

Cochran, P. H.; Bernsten, C. M. 1973. Tolerance of lodgepole 

pine and ponderosa pine seedlings to low night temperatures. 

Forest Science. 19: 272–280.

Cochrane, T.; Murray, R. A.; Karamanski, T. J. 1988. Narrative 

history of the Shoshone National Forest. Chicago, IL: 

Loyala University, Mid-American Research Center.

Conner, J. F. 1940. History of the Bighorn National Forest 

and the vicinity. Forest Supervisor’s Report. Sheridan, WY: 

U.S. Department of Agriculture, Forest Service, Bighorn 

National Forest.

Cook, J. G.; Hershey, T. J.; Irwin, L. L. 1994. Vegetative 

response to burning on Wyoming mountain-shrub big game 

ranges. Journal of Range Management. 47: 296–302.

Coolidge, P. T. 1906. Silvical report on the Bighorn National 

Forest. Internal report. Sheridan, WY: U.S. Department of 

Agriculture, Forest Service, Bighorn National Forest.

Cooper, C. F. 1960. Changes in vegetation, structure, and 

growth of southwestern pine forest since white settlement. 

Ecological Monographs. 30: 129–164.

Covington, W. W.; DeBano, L. F., tech. coords. 1994. 

Sustainable ecological systems: implementing an ecological 

approach to land management. Gen. Tech. Rep. RM-247. 

Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Forest and Range Experiment 

Station.

Covington, W. W.; Moore, M. M. 1994. Southwestern 

ponderosa forest structure: changes since Euro-American 

settlement. Journal of Forestry. 92: 39–47.

Dary, D. 1986. Entrepreneurs of the Old West. Lincoln: 

University of Nebraska Press.
USDA Forest Service RMRS-GTR-140. 2005 85

Daubenmire, R. F.; Daubenmire, J. B. 1968. Forest vegetation 

of eastern Washington and northern Idaho. Tech. Bull. 60. 

Pullman: Washington Agriculture Experiment Station.

Davis, P. R. 1977. Cervid response to forest fire and 

clearcutting in southeastern Wyoming. Journal of Wildlife 

Management. 41: 785–788.

Dayharsh, V. J. 1931. Silvicultural notes. Unpublished data 

on file at: U.S. Department of Agriculture, Forest Service, 

Bighorn National Forest, Sheridan, WY.

DeByle, N. V. 1979. Potential effects of stable versus fluctuating 

elk populations in the aspen ecosystem. In: Boyce, M. S.; 

Hayden-Wing, L. D., eds., North American elk: ecology, 

behavior and management. Laramie: University of 

Wyoming Press: 13–19.

DeByle, N. V.; Bevins, C. D.; Fischer, W. C. 1987. Wildfire 

occurrence in aspen in the Interior Western United States. 

Western Journal of Applied Forestry. 2: 73–76.

DeByle, N. V.; Urness, P. J.; Blank, D. L. 1989. Forage quality 

in burned and unburned aspen communities. Res. Pap. INT404. Ogden, UT: U.S. Department of Agriculture, Forest 

Service, Intermountain Research Station.

DeByle, N. V.; Winokur, R. P., eds. 1985. Aspen: ecology 

and management in the Western United States. Gen. Tech. 

Rep. RM-119. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and 

Range Experiment Station.

Despain, D. G. 1973. Vegetation of the Big Horn Mountains, 

Wyoming, in relation to substrate and climate. Ecological 

Monographs. 43: 329–355.

Despain, D. G. 1983. Nonpyrogenous climax lodgepole pine 

communities in Yellowstone National Park. Ecology. 64: 

231–234.

Despain, D. G. 1990. Yellowstone vegetation: consequences 

of environment and history in a natural setting. Boulder, 

CO: Roberts Rinehart Publishers.

Despain, D. G.; Romme, W. H. 1991. Ecology and management 

of high-intensity fires in Yellowstone National Park. Tall 

Timbers Fire Ecology Conference. 17: 43–58.

Dieterich, J. M. 1980. Chimney Spring forest fire history. 

Res. Pap. RM-220. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and 

Range Experiment Station.

Dillon, G. K. 1998. Effects of road edges on vegetation 

structure and composition in Rocky Mountain conifer 

forests. Laramie: University of Wyoming. Thesis.

Dinoor, A.; Eshed, E. 1984. The role and importance of 

pathogens in natural plant communities. Annual Review of 

Phytopathology. 22: 443–466.

Dion, A. 1998. Vegetation response to slash treatment and soil 

disturbance after clearcutting in a Rocky Mountain conifer 

forest. Laramie: University of Wyoming. Thesis.

Dodge, I. R. 1876. The Black Hills: a minute description of 

the routes, scenery, soil, climate, timber, gold, geology, 

zoology, etc. New York: James Miller, Publisher.

Dorn, R. D. 1986. The Wyoming landscape, 1805–1878. 

Cheyenne, WY: Mountain West Publishing.

Doyle, K. M. 1997. Fire, environment, and early forest 

succession in a heterogeneous Rocky Mountain landscape, 

northwestern Wyoming. Laramie: University of Wyoming. 

Dissertation.

Doyle, K. M. 2004. Early post-fire forest succession in the 

heterogeneous Teton landscape. In: Wallace, L. L., ed. After 

the fires: the ecology of change in Yellowstone National 

Park. New Haven, CT: Yale University Press: 235–278.

Doyle, K. M.; Knight, D. H.; Taylor, D. L.; Barmore, W. J.; Jr.; 

Benedict, J. M. 1998. Seventeen years of forest succession 

following the Waterfalls Canyon Fire in Grand Teton 

National Park, Wyoming. International Journal of Wildland 

Fire. 8: 45–55.

Ehle, D. S.; Baker, W. L. 2003. Disturbance and stand dynamics 

in ponderosa pine forests in Rocky Mountain National 

Park, USA. Ecological Monographs. 73: 543–566.

Fahey, T. J. 1983. Nutrient dynamics of aboveground detritus 

in lodgepole pine (Pinus contorta ssp. latifolia) ecosystems. 

Ecological Monographs. 53: 51–72.

Fahey, T. J.; Knight, D. H. 1986. Lodgepole pine ecosystems. 

BioScience. 36: 610–617.

Fall, P. L. 1997. Fire history and composition of the subalpine 

forest of western Colorado during the Holocene. Journal of 

Biogeography. 24: 309–325.

Fisher, R. F.; Jenkins, M. J.; Fisher, W. F. 1987. Fire and the 

prairie-forest mosaic of Devils Tower National Monument. 

American Midland Naturalist. 117: 250–257.

Fleischner, T. L. 1994. Ecological costs of livestock grazing 

in Western North America. Conservation Biology. 8: 629–

644.

Forman, R. T. T. 1995. Land mosaics; the ecology of 

landscapes and regions. Cambridge, UK: Cambridge 

University Press.

Foster, D. R.; Knight, D. H.; Franklin, J. F. 1998. Landscape 

patterns and legacies resulting from large, infrequent forest 

disturbances. Ecosystems. 1: 497–510.

Franklin, T. L.; Laven, R. D. 1989. Fire influences on Central 

Rocky Mountain lodgepole pine stand structure and 

composition. Tall Timbers Fire Ecology Conference. 17: 

183–196.

Fule, P. Z.; Covington, W. W.; Moore, M. M. 1997. Determining 

reference conditions for ecosystem management of 

Southwestern ponderosa pine forests. Ecological 

Applications. 7: 895–908.

Furniss, M. M.; Livingston, R. L.; McGregor, D. M. 1981. 

Development of a stand susceptibility classification for 

Douglas-fir beetle. In: Hedden, R. L.; Barras, S. J.; Coster, 

J. E. Symposium proceedings, hazard rating systems in 

forest pest management; 1980 July 31–August 1. Gen. 

Tech. Rep. WO-27. Washington, DC: U.S. Department of 

Agriculture, Forest Service: 115–128.

Geils, B. W.; Jacobi, W. R. 1990. Development of comandra 

blister rust on lodgepole pine. Canadian Journal of Forest 

Research. 20: 159–165.

Geils, B. W.; Jacobi, W. R. 1991. Rating a lodgepole pine forest 

for potential losses to comandra blister rust. In: Hiratsuka, 

Y.; Samoil, J. K.; Blenis, P. V.; Crane, P. E.; Laishley, B. L., 

eds. Rusts of pine. Proceedings of the 3rd IUFRO Rusts of 

Pine Working Party conference. Information Report NORX-317. Edmonton, Alberta: Forestry Canada, Northwest 

Region, Northern Forestry Centre: 403–408.

Gill, L. S.; Hawksworth, F. G. 1964. Dwarf mistletoe of 

lodgepole pine. Forest Pest Leaflet 18. Fort Collins, CO: 

U.S. Department of Agriculture, Forest Service.

Girard, M.; Wheeler, D. L.; Mills, S. B. 1997. Classification 

of riparian communities on the Bighorn National Forest. 

R2-RR-97-02. U.S. Department of Agriculture, Forest 

Service.
86 USDA Forest Service RMRS-GTR-140. 2005

Goldblum, D.; Veblen, T. T. 1992. Fire history of a ponderosa 

pine/Douglas-fir forest in the Colorado front range. Physical 

Geography. 13: 133–148.

Graham, R. T.; Harvey, A. E.; Jurgensen, M. F.; Jain, T. B.; 

Tonn, J. R.; Page-Dumroese, D. S. 1994. Managing coarse 

woody debris in forests of the Rocky Mountains. Res. Pap. 

INT-RP-477. Ogden, UT: U.S. Department of Agriculture, 

Forest Service, Intermountain Research Station.

Granum, R. M. 1990. History of the Tongue River tie flume, 

Bighorn Mountains, 1893–1913. Sheridan County, WY: 

Library Foundation, Inc.

Grasso, D. N.; Thybony, S.; Rosenberg, R.; Rosenberg, 

E. 1981. Cultural resource overview—Medicine Bow 

National Forest. Vol. 1. High Plains Consultant Contract 

No. 53-82X9-1-12.2 Laramie, WY: U.S. Department of 

Agriculture, Forest Service.

Graves, H. S. 1899. The Black Hills Forest Reserve. In: The 

nineteenth annual report of the survey, 1897–1898. Part V. 

Forest Reserves. Washington, DC: U.S. Geological Survey: 

67–164.

Gray, S. T. 2003. Long-term climate variability and its 

implications for ecosystems and natural resource 

management in the Central Rocky Mountains. Laramie: 

University of Wyoming. Dissertation.

Gray, S. T.; Fastie, C. L.; Jackson, S. T.; Betancourt, J. L. 

2004. Tree-ring-based reconstruction of precipitation in 

the Bighorn Basin, Wyoming since 1260 AD. Journal of 

Climate. 17: 3855–3865.

Gruell, G. E. 1983. Fire and vegetative trends in the Northern 

Rockies: interpretations from 1871–1982 photographs. 

Gen. Tech. Rep. INT-158. Ogden, UT: U.S. Department 

of Agriculture, Forest Service, Intermountain Forest and 

Range Experiment Station.

Gruell, G. E. 1985. Indian fires in the Interior West: a 

widespread influence. In: Lotan, J. E.; Kilgore, B. M.; 

Fischer, W. C.; Mutch, R. W., tech. coords. Symposium 

and workshop on wilderness fire; 1983 November 15–18; 

Missoula, MT. Gen. Tech. Rep. INT-182. Ogden, UT: U.S. 

Department of Agriculture, Forest Service, Intermountain 

Forest and Range Research Station: 68–74.

Grumbine, R. E. 1994. What is ecosystem management? 

Conservation Biology. 8: 27–38.

Hadley, K. S.; Veblen, T. T. 1993. Stand response to western 

spruce budworm and Douglas-fir beetle outbreaks, Colorado 

Front Range. Canadian Journal of Forest Research. 23: 

474–491.

Hagan, J. M.; Grove, S. L. 1999. Coarse woody debris. Journal 

of Forestry. 97: 6–11.

Halpern, C. B.; Franklin, J. F. 1990. Physiognomic 

development of Pseudotsuga forests in relation to initial 

structure and disturbance intensity. Journal of Vegetation 

Science. 1: 475–482.

Hansen, H. P. 1940. Ring growth and dominance in a sprucefir association in southern Wyoming. American Midland 

Naturalist. 23: 442–447.

Harmon, M. E.; Franklin, J. F.; Swanson, F. J.; Sollins, P.; 

Gregory, S. V.; Lattin, J. D.; Anderson, N. H.; Cline, S. P.; 

Aumen, N. G.; Sedell, J. R.; Lienkaemper, G. W.; Cromack, 

K.; Cummins, K. W. 1986. Ecology of coarse woody debris 

in temperate ecosystems. Advances in Ecological Research. 

15: 133–302.

Harris, J. L.; Allen, K. K.; Juntti, T. 1997. Insect and disease 

survey, Ramshorn analysis area, Wind River Ranger 

District, Shoshone National Forest. Biological Evaluation 

R2-98-04. Rapid City, SD: U.S. Department of Agriculture, 

Forest Service, Forest Health Management, Renewable 

Resources, Rapid City Service Center.

Harris, R. B. 1999. Abundance and characteristics of snags in 

western Montana forests. Gen. Tech. Rep. RMRS-GTR-31. 

Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station.

Hawkes, B. C. 1980. Fire history of Kananaskis Provincial 

Park—mean fire return intervals. In: Stokes, M. A.; 

Dieterich, J. H., tech. coords. Proceedings of the fire 

history workshop; 1980 October 20–24; Tucson, AZ. Gen. 

Tech. Rep. RM-81. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and 

Range Experiment Station: 42–45.

Hawksworth, F. G. 1958. Survey of lodgepole pine dwarf 

mistletoe on the Roosevelt, Medicine Bow, and Bighorn 

National Forests. Res. Pap. RM-35. Fort Collins, CO: 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station.

Hawksworth, F. G. 1975. Dwarf mistletoe and its role in 

lodgepole pine ecosystems. In: Baumgartner, D., ed. 

Management of lodgepole pine ecosystems symposium. 

Pullman: Washington State University: 342–358.

Hawksworth, F. G.; Johnson, D. W. 1989. Biology and 

management of dwarf mistletoe in lodgepole pine in the 

Rocky Mountains. Gen. Tech. Rep. RM-169. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station.

Hawksworth, F. G.; Weins, D. 1972. Biology and classification 

of dwarf mistletoes. Agric. Handb. 401. Washington, DC: 

U.S. Department of Agriculture, Forest Service.

Hessl, A. 2002. Aspen, elk, and fire: the effects of human 

institutions on ecosystem processes. BioScience. 52: 

1011–1022.

Hessl, A. E.; Baker, W. L. 1997. Spruce and fir regeneration 

and climate in the forest-tundra ecotone of Rocky Mountain 

National Park, Colorado, USA. Arctic and Alpine Research. 

29: 173–183.

Hinds, T. E. 1976. Aspen mortality in Rocky Mountain 

campgrounds. Res. Pap. RM-164. Fort Collins, CO: 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station.

Hinds, T. E.; Hawksworth, F. G.; Davidson, R. W. 1965. Beetlekilled Engelmann spruce: its deterioration in Colorado. 

Journal of Forestry. 63: 536–542.

Hobbs, N. T.; Spowart, R. A. 1984. Effects of prescribed 

fire on nutrition of mountain sheep and mule deer during 

winter and spring. Journal of Wildlife Management. 48: 

551–560.

Hoff, C. 1957. A comparison of soil, climate, and biota of 

conifer and aspen communities in the Central Rocky 

Mountains. American Midland Naturalist. 58: 115–140.

Hoffman, G. R.; Alexander, R. R. 1976. Forest vegetation of the 

Bighorn Mountains, Wyoming: a habitat type classification. 

Res. Pap. RM-170. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and 

Range Experiment Station.

Holling, C. S.; Meffe, G. K. 1996. Command and control 

and the pathology of natural resource management. 

Conservation Biology. 10: 328–337.

Houston, D. B. 1973. Wildfires in Northern Yellowstone 

National Park. Ecology. 54: 1111–1117.
USDA Forest Service RMRS-GTR-140. 2005 87

Howe, G. E. 1997. Bighorn National Forest genetics service 

visit. Report on file at: U.S. Department of Agriculture, 

Forest Service, Bighorn National Forest, Supervisor’s 

Office, Sheridan, WY.

Hutto, R. L. 1995. Composition of bird communities following 

stand-replacement fires in Northern Rocky Mountain (USA) 

conifer forests. Conservation Biology. 9: 1041–1058.

Hutto, R. L.; Hejl, S. J.; Preston, C. R.; Finch, D. M. 1992. 

Effects of silvicultural treatments on forest birds in 

the Rocky Mountains: implications and management 

recommendations. In: Finch, D. M.; Stangel, P. W., eds. 

Status and management of Neotropical migratory birds. Gen. 

Tech, Rep. RM-229. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and 

Range Experiment Station: 386–391.

Jack, J. G. 1900. Forest and grazing conditions in the Bighorn 

Reserve, Wyoming. Report on file at: U.S. Department 

of Agriculture, Forest Service, Bighorn National Forest, 

Sheridan, WY.

Jakubos, B.; Romme, W. H. 1993. Invasion of subalpine 

meadows by lodgepole pine in Yellowstone National Park. 

Arctic and Alpine Research. 25: 382–390.

Jelinkski, D. E.; Cheliak, W. M. 1992. Genetic diversity and 

spatial subdivision of Populus tremuloides (Salicaceae) in 

a heterogeneous landscape. American Journal of Botany. 

79: 728–736.

Johnson, D. W.; Beatty, J. S.; Hinds, T. E. 1995. Cankers on 

western quaking aspen. Forest Insect and Disease Leaflet 

152. U.S. Department of Agriculture, Forest Service. 

Johnson, D. W. 1985. Forest pest management training 

manual. Golden, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Region, Forest Pest 

Management.

Johnson, D. W. 1986a. Comandra blister rust. Forest Insect 

and Disease Leaflet 62. U.S. Department of Agriculture, 

Forest Service.

Johnson, D. W. 1986b. A summary of dwarf mistletoe program 

activities in the Rocky Mountain Region 1970–1986. Tech. 

Rep. R2-36. Golden, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Region, Timber, Forest 

Pest and Cooperative Forestry Management.

Johnson, D. W. 1995. Ecology and management of forest 

insects and diseases on the Medicine Bow National Forest. 

Draft white paper. Lakewood, CO: U.S. Department of 

Agriculture, Forest Service, Region 2, Forest Insect and 

Disease Methods Group.

Johnson, E. A.; Larsen, C. P. S. 1991. Climatically induced 

change in fire frequency in the Southern Canadian Rockies. 

Ecology. 72: 194–201.

Johnson, K. L. 1987. Rangeland through time: a photographic 

study of vegetation change in Wyoming 1870–1986. 

Laramie: University of Wyoming, Agricultural Experiment 

Station.

Kaufmann, M. R.; Graham, R. T.; Boyce, D. A., Jr.; Moir, W. 

H.; Perry, L.; Reynolds, R. T.; Bassett, R. L.; Mehlhop, 

P.; Edminster, C. B.; Block, W. M.; Corn, P. S. 1994. An 

ecological basis for ecosystem management. Gen. Tech. 

Rep. RM-GTR-246. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service , Rocky Mountain Forest and 

Range Experiment Station.

Kaufmann, M. R.; Huckaby, L. S.; Regan, C. M.; Popp, J. 1998. 

Forest reference conditions for ecosystem management in 

the Sacramento Mountains, New Mexico. Gen. Tech. Rep. 

RMRS-GTR-19. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research 

Station.

Kaufmann, M. R.; Regan, C. M.; Brown, P. M. 2000. 

Heterogeneity in ponderosa pine/Douglas-fir forests: age 

and size structure in unlogged and logged landscapes of 

central Colorado. Canadian Journal of Forest Research. 30: 

698–711.

Kay, C. E. 1990. Yellowstone’s northern elk heard: A critical 

evaluation of the “natural regulation” paradigm. Logan: 

Utah State University. Dissertation.

Kay, C. E. 1993. Aspen seedlings in recently burned areas in 

Grand Teton and Yellowstone National Parks. Northwest 

Science. 67: 94–104.

Kay, C. E.; Wagner, F. H. 1996. Response of shrub aspen 

to Yellowstone’s 1988 wildfire: implications of “natural 

regulation” management. In: Greenlee, J., ed. The 

ecological implications of fire in Greater Yellowstone: 

second biennial conference on the Greater Yellowstone 

Ecosystem. Fairfield, WA: International Association of 

Wildland Fire: 107–112.

Kendall, K. C. 1998. White bark pine, limber pine: regional 

trends of biological resources—Rocky Mountains. In: Mac, 

M. J.; Opler, P. A.; Puckett-Haeker, C. E.; Doran, P. D., eds. 

Status and trends of the nation’s biological resources. Vol. 

2. West Glacier, MT: U.S. Geological Survey, Biological 

Resources Division, Glacier Field Station Science Center: 

483–487.

Kipfmueller, K. F. 1997. A fire history of a subalpine forest in 

southeastern Wyoming. Laramie: University of Wyoming, 

Department of Geography and Recreation. Thesis.

Kipfmueller, K. F.; Baker, W. L. 1998a. A comparison of three 

techniques to date stand-replacing fires in lodgepole pine 

forests. Forest Ecology and Management. 104: 171–177.

Kipfmueller, K. F.; Baker, W. L. 1998b. Fires and dwarf 

mistletoe in a Rocky Mountain lodgepole pine ecosystem. 

Forest Ecology and Management. 108: 77–84.

Kipfmueller, K. F.; Baker, W. L. 2000. A fire history of a 

subalpine forest in south-eastern Wyoming, USA. Journal 

of Biogeography. 27: 71–85.

Klein, W. H.; Bennett, D. D.; Young, R. W. 1979. A pilot survey 

to measure annual mortality of lodgepole pine caused by 

mountain pine beetle. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Intermountain Region and 

Methods Application Group, Forest Pest and Disease 

Management.

Knight, D. H. 1987. Parasites, lightning and the vegetation 

mosaic in wilderness landscapes. In: Turner, M. G., ed. 

Landscape heterogeneity and disturbance. New York: 

Springer-Verlag: 59–83.

Knight, D .H. 1994a. Mountains and plains: the ecology of 

Wyoming landscapes. New Haven, CT: Yale University 

Press.

Knight, D. H. 1994b. Dynamics of subalpine forests. In: 

Hayward, G. D.; Verner, J., eds. Flammulated, boreal, and 

great gray owls in the United States: a technical conservation 

assessment. Gen. Tech. Rep. RM-253. Fort Collins, CO: 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station: 128–138.

Knight, D. H.; Jones, G. P.; Akashi, Y.; Myers, R. W. 1987. 

Vegetation ecology in the Bighorn Canyon National 

Recreation Area. Laramie: University of Wyoming, 

Department of Botany.
88 USDA Forest Service RMRS-GTR-140. 2005

Knight, D. H.; Reiners, W. A. 2000. Natural patterns in 

Southern Rocky Mountain landscapes and their relevance 

to forest management. In: Knight, R. L.; Smith, F. W.; 

Buskirk, S. W.; Romme, W. H.; Baker, W. A.; eds. Forest 

fragmentation in the Southern Rocky Mountains. Niwot: 

University Press of Colorado: 15–30.

Knight, R. L.; Smith, F. W.; Buskirk, S. W.; Romme, W. 

H.; Baker, W. L., eds. 2000. Forest fragmentation in the 

Southern Rocky Mountains. Niwot: University Press of 

Colorado.

Koch, P. 1996. Lodgepole pine commercial forests: an essay 

comparing the natural cycle of insect kill and subsequent 

wildfire with management for utilization and wildlife. Gen. 

Tech. Rep. INT-GTR-342. Ogden, UT: U.S. Department 

of Agriculture, Forest Service, Intermountain Research 

Station.

Krebill, R. G. 1965. Comandra rust outbreaks in lodgepole 

pine. Journal of Forestry. 63: 519–522.

Krebill, R. G.; Hoff, R. J. 1995. Update on Cronartium 

ribicola in Pinus albicaulis in the Rocky Mountains, USA. 

In: Kaneko, S.; Katsuya, K.; Kakishima, M.; Ono, Y., eds. 

Proceedings of the 4th IUFRO Rusts of Pines Working Party 

conference, Tsukuba: 119–126.

Landres, P. B.; Morgan, P.; Swanson, F. J. 1999. Overview of the 

use of natural variability concepts in managing ecological 

systems. Ecological Applications. 9: 1179–1188.

Langston, N. 1995. Forest dreams, forest nightmares: the 

paradox of old growth in the Inland West. Seattle: University 

of Washington Press.

Laven, R. D.; Omi, P. N.; Wyant, J. G.; Pinkerton, A. S. 1980. 

Interpretations of fire scar data from a ponderosa pine 

ecosystem in the Central Rocky Mountains, Colorado. In: 

Proceedings of the fire history workshop. Gen. Tech. Rep. 

RM-81. Fort Collins, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Forest and Range 

Experiment Station: 46–49.

Leege, T. A.; Hickey, W. O. 1971. Sprouting of northern 

Idaho shrubs after prescribed burning. Journal of Wildlife 

Management. 44: 372–380.

Lessard, E. D.; Schmid, J. M. 1990. Emergence, attack 

densities, and host relationships for the Douglas-fir 

beetle (Dendroctonus pseudotsugae Hopkins) in northern 

Colorado. Great Basin Naturalist. 50: 333–338.

Lindemann, J. D.; Baker, W. L. 2001. Attributes of blowdown 

patches from a severe wind event in the Southern Rocky 

Mountains, USA. Landscape Ecology. 16: 313–325.

Lindemann, J. D.; Baker, W. L. 2002. Using GIS to analyse a 

severe forest blowdown in the Southern Rocky Mountains. 

International Journal of Geographical Information Science. 

16: 377–399.

Loope, L. L.; Gruell, G. E. 1973. The ecological role of fire in 

the Jackson Hole area, northwestern Wyoming. Quaternary 

Research. 3: 425–443.

Loose, S. S.; Anderson, S. H. 1995. Woodpecker habitat 

use in the forests of southeast Wyoming. Journal of Field 

Ornithology. 66: 503–511.

Lotan, J. E.; Brown, J. K.; Neuenswander, L. F. 1985. Role 

of fire in lodgepole pine forests. In: Baumgartner, D. M.; 

Krebill, R. G.; Arnott, J. T.; Weetman, G. F., eds. Lodgepole 

pine: the species and its management. Pullman: Washington 

State University, Cooperative Extension Service: 133–

152.

Lotan, J. E.; Perry, D. A. 1983. Ecology and regeneration of 

lodgepole pine. Agriculture Handbook 606. Washington, 

D.C.: U.S. Department of Agriculture, Forest Service.

Lundquist, J. E. 1993. Large scale spatial patterns of conifer 

dseases in the Bighorn Mountains, Wyoming. Res. 

Note RM-523. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and 

Range Experiment Station.

Lundquist, J .E. 1995a. Pest interactions and canopy gaps in 

ponderosa pine stands in the Black Hills, South Dakota, 

USA. Forest Ecology and Management. 74: 37–48.

Lundquist, J. E. 1995b. Characterizing disturbance in managed 

ponderosa pine stands in the Black Hills. Forest Ecology 

and Management. 74: 61–74.

Lynch, A. M.; Swetnam, T. W. 1992. Old-growth mixed 

conifer and western spruce budworm in the Southern Rocky 

Mountains. In: Kaufmann, M. R.; Moir, W. H.; Bassett, 

R. L.; tech. eds. Old-growth forests in the Southwest and 

Rocky Mountain Regions. Proceedings of a workshop; 

1992 March 9–13; Portal, AZ. Gen. Tech. Rep. RM-213. 

Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Forest and Range Experiment 

Station: 66–68.

Mack, R. N.; Thompson, J. N. 1982. Evolution in steppe with 

few large, hoofed mammals. American Naturalist. 119: 

757–773.

Madany, M. H.; West, N. E. 1983. Livestock grazing-fire 

regime interactions within montane forests of Zion National 

Park, Utah. Ecology. 64: 661–667.

Manley, P. N.; Brogan, G. E.; Cook, C.; Flores, M. E.; Fullmer, 

D. G.; Husare, S.; Jimerson, T. M.; Lux, L. M.; McCain, M. 

E.; Rose, J. A.; Schmitt, G.; Schuyler, J. C.; Skinner, M. 

J. 1995. Sustaining ecosystems: a conceptual framework. 

Publ. R5-EM-TP-001. San Francisco, CA: U.S. Department 

of Agriculture, Forest Service, Pacific Southwest Region.

Martin, P. S.; Szuter, C. R. 1999. War zones and game sinks 

in Lewis and Clark’s West. Conservation Biology. 13: 36–

45.

Martin, R. E.; Sapsis, D. B. 1992. Fires as agents of biodiversity: 

pyrodiversity promotes biodiversity. In: Harris, R.; Erman, 

D. E.; Kerner, H. M., tech. coords. Proceedings of the 

symposium on biodiversity of northwestern California. 

Report 29. Berkeley: University of California, Wildland 

Resources Center: 150–157.

Martner, B. E. 1986. Wyoming climate atlas. Lincoln: 

University of Nebraska Press.

Martorano, M. A.; Burns, G. R.; Alpert, A. M.; Killam, D. 

G. 1985. Cultural resource overview: Bighorn National 

Forest, Wyoming. Semi-final draft report by Goodson and 

Associates, Inc., Lakewood, CO, submitted to Bighorn 

National Forest, Sheridan, WY.

Mason, D. T. 1915. The life history of lodgepole pine in the 

Rocky Mountains. Bulletin 154. Washington, DC: U.S 

Department of Agriculture.

Maxwell, W. G.; Ward, R. R. 1976. Photo series for quantifying 

forest residues in the ponderosa pine type, ponderosa pine 

and associated species type, lodgepole pine type. Gen. 

Tech. Rep. PNW-52. Portland, OR: U.S. Department of 

Agriculture, Forest Service, Pacific Northwest Research 

Station.

McAdams, A. G. 1995. Changes in ponderosa pine forest 

structure in the Black Hills, South Dakota, 1874–1995. 

Flagstaff: Northern Arizona University. Thesis.
USDA Forest Service RMRS-GTR-140. 2005 89

McCambridge, W. F.; Amman, G. D.; Trostle, G. C. 1979. 

Mountain pine beetle. Insect and Disease Leaflet 2. 

Washington, DC: U.S Department of Agriculture, Forest 

Service.

McCune, B. 1983. Fire frequency reduced two orders of 

magnitude in the Bitterroot Canyons, Montana. Canadian 

Journal of Forest Research. 13: 212–218.

McDonough, W. 1985. Sexual reproduction, seeds, and 

seedlings. In: DeByle, N. V.; Winokur, R. P., eds. Aspen: 

ecology and management in the Western United States. Gen. 

Tech. Rep. RM-119. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and 

Range Experiment Station: 25–28

McGarigal, K.; Marks, B. J. 1995. FRAGSTATS: Spatial 

pattern analysis program for quantifying landscape 

structure. Gen. Tech. Rep. PNW-GTR-351. Portland, OR: 

U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station.

McMillin, J. D.; Allen, K. K. 2000. Impacts of Douglas-fir 

beetle on overstory and understory conditions of Douglasfir stands, Shoshone National Forest, Wyoming. Tech. 

Rep. R2-64. Golden, CO: U.S. Department of Agriculture, 

Forest Service.

McPherson, G. R. 1992. Comparison of linear and nonlinear overstory-understory models for ponderosa pine: a 

conceptual framework. Forest Ecology and Management. 

55: 31–34.

Mehl, M. S. 1992. Old-growth descriptions for the major forest 

cover types in the Rocky Mountain Region. In: Kaufmann, 

M. R.; Moir, W. H.; Bassett, R. L., tech. coords. Old-growth 

forests in the Southwest and Rocky Mountain Regions: 

proceedings of a workshop. Gen. Tech. Rep. RM-213. 

Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Forest and Range Experiment 

Station: 106–120.

Mehringer, P. J., Jr.; Arno, S. F.; Petersen, K. L. 1977. Postglacial 

history of lost trail pass bog, Bitterroot Mountains, Montana. 

Arctic and Alpine Research. 9: 345–368.

Merrill, E.; Hak, J.; Beauchaine, S. 1993. Forest fragmentation 

and bird diversity in the Bighorn National Forest, Wyoming. 

EMAP-01-93, Project # R-82-1748. Report on file at: 

Wyoming Game and Fish Department, Sheridan, WY.

Millar, C. I.; Woolfenden, W. B. 1999. The role of climate 

change in interpreting historical variability. Ecological 

Applications. 9: 1207–1216.

Miller, J. R.; Joyce, L. A.; Knight, R. L.; King, R. M. 1996. 

Forest roads and landscape structure in the Southern Rocky 

Mountains. Landscape Ecology. 11: 115–127.

Millspaugh, S. H.; Whitlock, C. 1995. A 750-year fire history 

based on lake sediment records in Central Yellowstone 

National Park, USA. The Holocene. 5: 283–292.

Moir, W. H. 1966. Influence of ponderosa pine on herbaceous 

vegetation. Ecology. 47: 1045–1048.

Moir, W. H. 1969. The lodgepole pine zone in Colorado. 

American Midland Naturalist. 81: 87–98.

Moore, M. M.; Covington, W. W.; Fule, P. Z. 1993. Spatial 

change in southwestern ponderosa pine since settlement. 

Bulletin of the Ecological Society of America. 74: 365.

Morgan, P.; Aplet, G. H.; Haufler, H. B.; Humphries, H. C.; 

Moore, M. M.; Wilson, W. D. 1994. Historical range of 

variability: a useful tool for evaluating ecosystem change. 

Journal of Sustainable Forestry. 2: 87–111.

Morgan, P.; Bunting, S. C.; Black, A. E.; Merrill, T.; Barrett, 

S. 1996. Fire regimes in the Interior Columbia River Basin: 

past and present. Report submitted to: Intermountain Fire 

Sciences Laboratory, Intermountain Research Station, 

Missoula, MT.

Morrison, D. J. 1981. Armillaria root disease: a guide to 

disease diagnosis, development and management in 

British Columbia. Information Report BC-X-203. Victoria, 

BC: Canadian Forestry Service, Pacific Forest Research 

Centre.

Mueggler, W. F. 1976. Type variability and succession in 

Rocky Mountain aspen. In: Utilization and marketing 

as tools for aspen management in the Rocky Mountains: 

proceedings of a symposium. Gen. Tech. Rep. RM-29. 

Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Forest and Range Experiment 

Station: 16–19.

Mueggler, W. F. 1985. Vegetation associations. In: DeByle, N. 

V.; Winokur, R. P., eds. Aspen: ecology and management 

in the Western United States. Gen. Tech. Rep. RM-119. 

Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Forest and Range Experiment 

Station: 45–56.

Muir, P. S. 1993. Disturbance effects on structure and tree 

species composition of Pinus contorta forests in western 

Montana. Canadian Journal of Forest Research. 23: 1617–

1625.

Muir, P. S.; Lotan, J. E. 1985. Disturbance history and serotiny 

of Pinus contorta in western Montana. Ecology. 66: 1658–

1668.

Murcia, C. 1995. Edge effects in fragmented forests: 

implications for conservation. Trends in Ecology and 

Evolution. 10: 58–62.

Murray, R. A. 1980. Multiple use in the Big Horns: the story 

of the Bighorn National Forest. Volume 1. Narrative history 

and notes. Report submitted to: Bighorn National Forest, 

Sheridan, WY.

Myers, C. A. 1974. Multipurpose silviculture in ponderosa 

pine stands of the montane zone of central Colorado. 

Res. Pap. RM-132. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and 

Range Experiment Station.

Nesser, J. A. 1986. Soil survey of Bighorn National Forest, 

Wyoming: parts of Big Horn, Johnson, Sheridan, and 

Washakie Counties. U.S. Department of Agriculture, Soil 

Conservation Service. Washington, D.C.: Government 

Printing Office.

Nesser, J. A. 1990. Monitoring soil physical conditions: 

sawsite timber sale, Bighorn National Forest. Report on 

File at: U.S. Department of Agriculture, Forest Service, 

Bighorn National Forest, Sheridan, WY.

Newton, H.; Jenny, W. P. 1880. Report of the geology and 

resources of the Black Hills of Dakota. Washington, DC: 

U.S. Geographical and Geological Survey, Rocky Mountain 

Region. U.S. Government Printing Office.

Parker, A. J.; Parker, K. C. 1983. Comparative successional 

roles of trembling aspen and lodgepole pine in the Southern 

Rocky Mountains. Great Basin Naturalist. 43: 447–455.

Parker, A. J.; Parker, K. C. 1994. Structural variability of 

mature lodgepole pine stands on gently sloping terrain in 

Taylor Park Basin, Colorado. Canadian Journal of Forest 

Research. 24: 2020–2029.
90 USDA Forest Service RMRS-GTR-140. 2005

Parks, C. G.; Bull, E. L.; Torgersen, T. R. 1997. Field guide 

for the identification of snags and logs in the Interior 

Columbia River Basin. PNW-GTR-390. Portland, OR: 

U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station.

Parsons, W. F. J.; Knight, D. H.; Miller, S. L. 1994. Root gap 

dynamics in lodgepole pine forest: nitrogen transformations 

in gaps of different size. Ecological Applications. 4: 354–

362.

Patten, D. T. 1969. Succession from sagebrush to mixed 

conifer forest in the Northern Rocky Mountains. American 

Midland Naturalist. 82: 229–240.

Pearson, J. A.; Knight, D. H.; Fahey, R. J. 1987. Biomass 

and nutrient accumulation during stand development in 

Wyoming lodgepole pine forests. Ecology. 68: 1966–

1973.

Peet, R. K. 1988. Forests of the Rocky Mountains. In: Barbour, 

M. G.; Billings, W. D., eds. North American terrestrial 

vegetation. New York: Cambridge University Press: 63–

101.

Pinchot, G. 1907. The use of the National Forests. Washington, 

DC: U.S. Department of Agriculture, Forest Service, 

Government Printing Office.

Progulske, D. R. 1974. Yellow ore, yellow hair, and yellow 

pine: a photographic study of a century of forest ecology. 

South Dakota Agricultural Experimental Station Bulletin 

616: 1–169.

Pyne, S. J. 1997. America’s fires: management on wildlands 

and forests. Durham, NC: Forest History Society.

Rebertus, A. J.; Veblen, T. T.; Roovers, L. M.; Mast, J. N. 1992. 

Structure and dynamics of old-growth Engelmann sprucesubalpine fir in Colorado. In: Kaufmann, M. R.; Moir, W. 

H.; Bassett, R. L.; tech. coords. Old-growth forests in the 

Southwest and Rocky Mountain Regions: proceedings of 

a workshop. Gen. Tech. Rep. RM-213. Fort Collins, CO: 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station: 139–153.

Reed, R. A.; Finley, M. E.; Romme, W. H.; Turner, M. G. 

1999. Aboveground net primary production and leaf-area 

index in early postfire vegetation in Yellowstone National 

Park. Ecosystems. 2: 88–94.

Reed, R. A.; Johnson-Barnard, J.; Baker, W. L. 1996a. The 

contribution of roads to forest fragmentation in the Rocky 

Mountains. Conservation Biology. 10: 1098–1106.

Reed, R. A.; Johnson-Barnard, J.; Baker, W. L. 1996b. 

Fragmentation of a forested Rocky Mountain landscape, 

1950–1993. Biological Conservation. 75: 267–277.

Romme, W. H. 1979. Fire and landscape diversity in subalpine 

forests of Yellowstone National Park. Laramie: University 

of Wyoming. Dissertation.

Romme, W. H. 1980a. Fire frequency in subalpine forests of 

Yellowstone National Park. In: Stokes, M. A.; Dieterich, J. 

H., tech. coords. Proceedings of the fire history workshop; 

1980 October 20–24; Tucson, AZ. Gen. Tech. Rep. RM-81. 

Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Forest and Range Experiment 

Station: 27–30.

Romme, W. H. 1980b. Fire history terminology: report of the 

ad hoc committee. In: Stokes, M. A.; Dieterich, J. H., tech. 

coords. Proceedings of the fire history workshop; 1980 

October 20–24; Tucson, AZ. Gen. Tech. Rep. RM-81. 

Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Forest and Range Experiment 

Station:135-137.

Romme, W. H. 1982. Fires and landscape diversity in 

subalpine forests of Yellowstone National Park. Ecological 

Monographs. 52: 199–221.

Romme, W. H.; Despain, D. G. 1989. Historical perspective on 

the Yellowstone fires of 1988. BioScience. 39: 695–699.

Romme, W. H.; Floyd, M. L.; Hanna, D.; Redders, J. S. 2000. 

Using natural disturbance regimes as a basis for mitigating 

impacts of anthropogenic fragmentation. In: Knight, R. 

L.; Smith, F. W.; Buskirk, S. W.; Romme, W. H.; Baker, 

W. L., eds. Forest fragmentation in the Southern Rocky 

Mountains. Niwot: University Press of Colorado: 377–

400.

Romme, W. H.; Knight, D. H. 1981. Fire frequency and 

subalpine forest succession along a topographic gradient in 

Wyoming. Ecology. 62: 319–326.

Romme, W. H.; Knight, D. H.; Yavitt, J. B. 1986. Mountain 

pine beetle outbreaks in the Rocky Mountains: regulators 

of primary productivity? American Naturalist. 127: 484–

494.

Romme, W. H.; Turner, M. G.; Gardner, R. H.; Hargrove, W. 

W.; Tuskan, G. A.; Despain, D. G.; Renkin, R. A. 1997. 

A rare episode of sexual reproduction in aspen (Populus 

tremuloides Michx.) following the 1988 Yellowstone fires. 

Natural Areas Journal. 17: 17–25.

Savage, M.; Brown, P. M.; Feddema, J. 1996. The role 

of climate in a pine forest regeneration pulse in the 

Southwestern United States. Ecoscience. 3: 310–318.

Schimpf, D. J.; Henderson, J. A.; MacMahon, J. A. 1980. 

Some aspects of succession in the spruce-fir forest zone of 

northern Utah. Great Basin Naturalist. 40: 1–26.

Schmid, J. M.; Frye, R. H. 1977. Stand ratings for spruce beetles. 

Res. Note RM-309. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and 

Range Experiment Station.

Schmid, J. M.; Hinds, T. E. 1974. Development of spruce-fir 

stands following spruce beetle outbreaks. Res. Pap. RM131. Fort Collins, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Forest and Range 

Experiment Station.

Schmid, J. M.; Mata, S. A. 1992. Stand density and mountain 

pine beetle-caused tree mortality in ponderosa pine stands. 

Res. Note RM-515. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and 

Range Experiment Station.

Schmid, J. M.; Mata, S. A. 1996. Natural variability of specific 

forest insect populations and their associated effects in 

Colorado. Gen. Tech. Rep. RM-GTR-275. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station.

Schmid, J. M., Mata, S. A.; Obedzinski, R. A. 1994. Hazard 

rating ponderosa pine stands for mountain pine beetles 

in the Black Hills. Res. Note RM-529. Fort Collins, CO: 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station.

Schmitz, R. F.; Gibson, K. E. 1996. Douglas-fir beetle. Forest 

Insect and Disease Leaflet 5. Washington, D.C.: U.S. 

Department of Agriculture, Forest Service.

Scott, S. S. 1981. An Indian history of the Big Horn Mountains 

and vicinity. Appendix II. Archaeology Files MP 81-07. 
USDA Forest Service RMRS-GTR-140. 2005 91

Sheridan, WY: U.S. Department of Agriculture, Forest 

Service, Bighorn National Forest.

Selmants, P. C.; Knight, D. H. 2003. Understory plant species 

composition 30-50 years after clearcutting in southeastern 

Wyoming coniferous forests. Forest Ecology and 

Management. 185: 175–289.

Severson, K. E. 1963. A description and classification by 

composition of the aspen stands in the Sierra Madre 

Mountains, Wyoming. Laramie: University of Wyoming.

Shaw, C. G., III; Kile, G. A. 1991. Armillaria root disease. 

Agric. Handb. 691. Washington, DC: U.S. Department of 

Agriculture, Forest Service.

Shepperd, W. D.; Binkley, D.; Bartos, D. L.; Stohlgren, T. J.; 

Eskew, L. G., comps. 2001. Sustaining aspen in Western 

landscapes: symposium proceedings. Proc. RMRS-P-18. 

Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station.

Shinneman, D. J.; Baker, W. L. 1997. Nonequilibrium 

dynamics between catastrophic disturbances and oldgrowth forests in ponderosa pine landscapes of the Black 

Hills. Conservation Biology. 11: 1276–1288.

Stahelin, R. 1943. Factors influencing the natural restocking 

of high altitude burns by coniferous trees in the Central 

Rocky Mountains. Ecology. 24: 19–30.

Steele, R.; Cooper, S. V.; Ondov, D. M.; Roberts, D. W.; 

Pfister, R. D. 1983. Forest habitat types of eastern Idahowestern Wyoming. Gen. Tech. Rep. INT-144. Ogden, UT: 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station.

Stohlgren, T. J.; Binkley, D.; Chong, G. W.; Kalkhan, M. A.; 

Schell, L. D.; Bull, K. A.; Otsuki, Y.; Newman, G.; Bashkin, 

M.; Son, Y. 1999a. Exotic plant species invade hot spots of 

native plant diversity. Ecological Monographs. 69: 25–46.

Stohlgren, T. J.; Schell, L. D.; Vanden Heuvel, B. 1999b. 

How grazing and soil quality affect native and exotic 

plant diversity in Rocky Mountain grasslands. Ecological 

Applications. 9: 45–64.

Stone, W. E.; Wolfe, M. L. 1996. Response of understory 

vegetation to variable tree mortality following a mountain 

pine beetle epidemic in lodgepole pine stands in northern 

Utah. Vegetatio. 122: 1–12.

Struempf, H. 1999. Nesting bird community response to 

natural habitat variation in aspen forests of the Central 

Rocky Mountains. Laramie: University of Wyoming. 

Thesis.

Sudworth, G. B. 1900. White River Plateau Timber Land 

Reserve. Twentieth annual report of the United States 

Geological Survey, Part V—Forest Reserves. Washington, 

DC: Government Printing Office: 117–179.

Swanson, F. J.; Jones, J. A.; Wallin, D. O.; Cissel, J. H. 

1993. Natural variability—implications for ecosystem 

management. In: Jensen, M. E.; Bourgeron, P. S., eds. 

Ecosystem management: principles and Applications. 

Vol. II. Eastside forest health assessment. Gen. Tech. 

Rep. PNW-GTR-318. Portland, OR: U.S. Department of 

Agriculture, Forest Service, Pacific Northwest Experiment 

Station: 89–103.

Swetnam, T. W. 1990. Fire history and climate in the 

Southwestern United States. In: Krammes, J. S., tech. 

coord. Effects of fire management of Southwestern natural 

resources. Gen. Tech. Rep. RM-191. Fort Collins, CO: 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station: 6–17.

Swetnam, T. W.; Lynch, A. M. 1989. A tree-ring reconstruction 

of western spruce budworm history in the Southern Rocky 

Mountains. Forest Science. 35: 962–986.

Swetnam, T. W.; Lynch, A. M. 1993. Multicentury, regionalscale patterns of western spruce budworm outbreaks. 

Ecological Monographs. 63: 399–424.

Taylor, D. L. 1973. Some ecological implications of forest fire 

control in Yellowstone National Park, Wyoming. Ecology. 

54: 1394–1396.

Thilenius, J. F. 1975. Alpine range management in the Western 

United States: principles, practices and problems—the 

status of our knowledge. Res. Pap. RM-157. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station.

Tidwell, W. D. 1975. Common fossil plants of Western North 

America. Provo, UT: Brigham Young University Press.

Tinker, D. B. 1999. Coarse woody debris in Wyoming 

lodgepole pine forests. Laramie: University of Wyoming. 

Dissertation.

Tinker, D. B.; Baker, W. L. 2000. Using the LANDLOG 

model to analyze the fragmentation of a Wyoming forest 

by a century of clearcutting. In: Knight, R. L.; Smith, F. W.; 

Buskirk, S. W.; Romme, W. H.; Baker, W. L., eds. Forest 

fragmentation of the Southern Rocky Mountains. Niwot: 

University Press of Colorado: 337–358.

Tinker, D. B.; Knight, D. H. 2000. Coarse woody debris 

following fire and logging in Wyoming lodgepole pine 

forests. Ecosystems. 3: 472–483.

Tinker, D. B.; Knight, D. H. 2001. Temporal and spatial 

dynamics of coarse woody debris in harvested and 

unharvested lodgepole pine forests. Ecological Modelling. 

141: 125–149.

Tinker, D. B.; Knight, D. H. 2003. Snags and coarse woody 

debris: an important legacy of forests in the Greater 

Yellowstone Ecosystem. In: Wallace, L. L., ed. After the 

fires: the ecology of change in Yellowstone National Park. 

New Haven, CT: Yale University Press: 279–298.

Tinker, D. B.; Resor, C. A. C.; Beauvais, G. P.; Kipfmueller, 

K. F.; Fernandes, C. I.; Baker, W. L. 1998. Watershed 

analysis of forest fragmentation by clearcuts and roads in a 

Wyoming forest. Landscape Ecology. 13: 149–165.

Tinker, D. B.; Romme, W. H.; Despain, D. G. 2003. Historic 

range of variability in landscape structure in subalpine 

forests of the Greater Yellowstone Area, USA. Landscape 

Ecology. 18: 427-439.

Tinker, D. B.; Romme, W. H.; Hargrove, W. W.; Gardner, R. 

H.; Turner, M. G. 1994. Landscape-scale heterogeneity 

in lodgepole pine serotiny. Canadian Journal of Forest 

Research. 24: 897–903.

Tinnen, R. O. 1984. The effect of dwarf-mistletoe on forest 

community ecology. In: Hawksworth, F. G.; Scharpf, R. 

F., eds. Biology of dwarf mistletoes: proceedings of the 

symposium. Gen. Tech. Rep. RM-111. Fort Collins, CO: 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station: 117–122.

Tinnen, R. O.; Hawksworth, F. G.; Knutson, D. J. 1982. Witches 

brooms formation in conifers infected by Arceuthobium 

spp.: an example of parasitic impact upon community 

dynamics. American Midland Naturalist. 107: 351–259.

Tomback, D. F. 1983. Nutcrackers and pines: coevolution or 

coadaptation? In: Nitecki, M. H., ed. Coevolution. Chicago, 

IL: University of Chicago Press: 179–223.
92 USDA Forest Service RMRS-GTR-140. 2005

Town, F. E. 1899. Bighorn Forest Reserve. In Walcott, C. 

D., comp. Nineteenth annual report of the United States 

Geological Survey to the Secretary of Interior 1897–98. 

Part V—Forest Reserves. Washington, DC: U.S. Geological 

Survey: 165–190.

Turner, G. Y.; Paulsen, H. A., Jr. 1976. Management of 

mountain grasslands in the Central Rockies: the status 

of our knowledge. Res. Pap. RM-161. Fort Collins, CO: 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station.

Turner, M. G.; Romme, W. H.; Gardner, R. H.; Hargrove, W. 

W. 1997. Effects of fire size and pattern on early postfire 

succession in subalpine forests of Yellowstone National 

Park, Wyoming. Ecological Monographs. 67: 411–433.

USDA Forest Service. 1985. Land and resource management 

plan, Bighorn National Forest. Sheridan, WY.

USDA Forest Service. 1994. Amended land and resource 

management plan (draft). Final supplemental environmental 

impact statement. Volume I: Chapters I-V and Appendices. 

Sheridan, WY: Bighorn National Forest.

USDA Forest Service. 1997. Clear Creek and Crazy Woman 

Creek landscape analysis. Report on file at: Bighorn 

National Forest, Sheridan, WY.

USDA Forest Service 1998. Bighorn National Forest noxious 

weed management, environmental assessment. Sheridan, 

WY: Bighorn National Forest.

Vaillancourt, D. A. 1995. Structural and microclimatic edge 

effects associated with clearcutting in a Rocky Mountain 

forest. Laramie: University of Wyoming. Thesis.

Van Sickle, G. A. 1985. Effects of infestations on trees and 

stands. In: Brookes, M. H.; Colbert, J. J.; Mitchell, R. G.; 

Stark, R. W., eds. Managing trees and stands susceptible to 

western spruce budworm. Tech. Bull. 1695. Washington, 

D.C.: U.S. Department of Agriculture, Forest Service, 

Cooperative State Research Service.

Van Vuren, D. 1982. Comparative ecology of bison and cattle 

in the Henry Mountains, Utah. In: Nelson, L.; Peek, J. M.; 

Dalke, P. D., eds. Proceedings of the wildlife-livestock 

relationships symposium. Moscow: University of Idaho, 

Forest, Wildlife, and Range Experiment Station: 449–457.

Veblen, T. T. 2000. Disturbance patterns in Southern 

Rocky Mountain forests. In: Knight, R. L.; Smith, F. W.; 

Buskirk, S. W.; Romme, W. H.; Baker, W. A., eds. Forest 

fragmentation in the Southern Rocky Mountains. Niwot: 

University Press of Colorado: 31–54.

Veblen, T. T.; Donnegan, J.; Kitzberger, T. 2000. Climatic and 

human influences on fire regimes in ponderosa pine forests 

in the Colorado Front Range. Ecological Application. 10: 

1178–1195.

Veblen, T. T.; Hadley, K. S.; Nel, E. M.; Kitzberger, T.; Reid, 

M.; Villalba, R. 1994. Disturbance regime and disturbance 

interactions in a Rocky Mountain subalpine forest. Journal 

of Ecology. 82: 125–135.

Veblen, T. T.; Hadley, K. S.; Reid, M. S. 1991a. Disturbance 

and stand development of a Colorado subalpine forest. 

Journal of Biogeography. 18: 707–716.

Veblen, T. T.; Hadley, K. S.; Reid, M. S.; Rebertus, A. J. 1991b. 

The response of subalpine forests to spruce beetle outbreak 

in Colorado. Ecology. 72: 213–231.

Veblen, T. T.; Lorenz, D. C. 1986. Anthropogenic disturbance 

and recovery patterns in montane forests, Colorado Front 

Range. Physical Geography. 7: 1–24.

Veblen, T. T.; Lorenz, D. C. 1991. The Colorado Front Range: 

a century of ecological change. Salt Lake City: University 

of Utah Press.

Villalba, R.; Veblen, T. T.; Ogden, J. 1994. Climatic influences 

on the growth of subalpine trees in the Colorado Front 

Range. Ecology. 75: 1450–1462.

Vogt, K. A.; and others, eds. 1997. Ecosystems: balancing 

science with management. New York: Springer-Verlag.

von Ahlefeldt, J. P.; Speas, C. 1996. Biophysical and historical 

aspects of species and ecosystems of the Medicine Bow 

National Forest. Specialist Report. Laramie, WY: U.S. 

Department of Agriculture, Forest Service, Medicine Bow 

National Forest.

Wadleigh, L.; Jenkins, M. J. 1996. Fire frequency and the 

vegetative mosaic of a spruce-fir forest in northern Utah. 

Great Basin Naturalist. 56: 28–37.

Walters, J. W.; Hinds, T. E.; Johnson, D. W.; Beatty, J. 

1982. Effects of partial cutting on diseases, mortality, 

and regeneration of Rocky Mountain aspen stands. Res. 

Pap. RM-240. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and 

Range Experiment Station.

Wargo, P. M.; Shaw, C. G., III. 1985. Armillaria root rot: the 

puzzle is being solved. Plant Diseases. 69: 826–832.

Weaver, H. 1951. Fire as an ecological factor in the 

southwestern ponderosa pine forests. Journal of Forestry. 

49: 93–98.

Weir, J. M. H.; Chapman, K. J.; Johnson, E. A. 1995. 

Wildland fire management and the fire regime in the 

Southern Canadian Rockies. In: Brown, J. K.; Mutch, 

R. W.; Spoon, C. W.; Wakimoto, R. H., tech. coords. 

Proceedings: symposium on fire in wilderness and park 

management. Gen. Tech. Rep. INT-GTR-320. Ogden, UT: 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station: 275–280.

Whipple, S. A.; Dix, R. L. 1979. Age structure and successional 

dynamics of a Colorado subalpine forest. American 

Midland Naturalist. 101: 142–148.

White, A. S. 1985. Presettlement regeneration patterns in a 

southwestern ponderosa pine stand. Ecology. 66: 589–

594.

Whitlock, C. 1993. Postglacial vegetation and climate of 

Grand Teton and Southern Yellowstone National Parks. 

Ecological Monographs. 63: 173–198.

Whitlock, C.; Millspaugh, S. H. 1996. Testing the assumptions 

of fire-history studies: an examination of modern charcoal 

accumulation in Yellowstone National Park, USA. The 

Holocene. 6: 7–15.

Wyoming State Historical Society. 1976. Rediscovering the 

Bighorns: a pictorial study of 75 years of ecological change. 

Sheridan: Wyoming State Historical Society in cooperation 

with the Bighorn National Forest.

Zavitkovski, J.; Newton, M. 1968. Ecological importance of 

snowbrush (Ceonothus velutinus) in the Oregon Cascades. 

Ecology. 49: 1132–1144.
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Appendix A—Problems known to be associated with using data in the Bighorn

 National Forest RIS and Fire databases.

Fire database (1970-1996) Location of the start point for each fire is mapped in the GIS. These data 

were used to locate fires by vegetation type. However, the fire may have 

started in one vegetation type but burned most extensively in another, and 

that information is not recorded, just the type where it started. Also, the 

program that BNF personnel used to plot the points in the GIS 

occasionally shifted the location of the point from the start point to 

the center of the township section in which the fire started. Therefore, the 

location of some of the fires may be inaccurate, although the shift would 

not be large enough to make comparisons between high and low 

elevations inaccurate. Additionally, the vegetation type of the fire was 

recorded as the vegetation class following the fire, not before the fire. To 

avoid some of these problems, we attempted to use the cover type 

recorded with each fire in the database, but the coding system has 

changed over the years.

Large fire database (1909-1996) The spatial extents of large fires from 1909 to 1996 were originally 

drawn on topographic maps. The polygons were crude on early maps and 

became more refined by the 1980s. The smallest mapped fire was 9 ha 

(22 acres), but that does not necessarily mean all fires >9 ha were always 

mapped. It is unknown if the mappers used a size criteria when deciding 

which large fires to map. Also, a couple large fires in the late 1980s, 

recorded in the above fire database, have not been mapped out spatially; 

these two fires were <540 ha (1334 acres).

RIS database Stand ages were calculated as follows: Cores were taken at breast height, 

and then 15 years were added to the number of rings counted to the pith 

for softwoods, 4 years were added for hardwoods, and 30 years for spruce 

to account for growth to breast height. Error of +10% in age was 

acceptable. Each forest stand had 1 sample point per 4 ha (10 acres) and 

a minimum of 5 points per stand. At each point, the first two live trees 

in the northward direction that were >12.5 cm dbh were measured for 

age. The age was averaged over trees and plots. Only certain proportions 

of stands in each forest type were sampled (fig. 27 for percentages).

RIS database Mean patch size of clearcuts was based on the size of clearcuts that 

foresters recorded in the GIS database, not on the mapped polygon size. 

Many clearcuts were smaller than the polygon in the GIS, and the 

map of clearcuts shows more area cut than actual area (31% more) 

because the entire polygon is shown. When clearcuts occurred in the 

same month and same polygon, they were considered one clearcut event. 

However, if clearcuts occurred in the same month and were in adjacent 

polygons, they remained separate, even though ideally they should be 

joined. Thus, the size of the clearcut patches may be underestimated 

somewhat (but total area is correct). Similar to the fire database, the 

vegetation type for a clearcut is the one after the clearcut occurred, not 

before.
94 USDA Forest Service RMRS-GTR-140. 2005

RIS database The seral stage map appears very approximate and sometimes appears to 

conflict with the tree size map. It seems to be acceptable for broad-scale 

landscape patterns.

RIS database Cover type classifications were conducted by separate teams across the 

Forest, resulting in some inconsistencies. A new (IRI) database improves 

on these greatly. However, at the Forest-level of analysis, the differences 

among the RIS and IRI maps are small. The IRI database was not fully 

available at the time of the preparation of this report.

Romme (1979, 1982), Romme and As Tables 5 and 6 demonstrate, the classifications used in YNP were 

Despain (1989) data compared to only roughly comparable to the classifications that could be developed 

BNF data from the RIS database. Ages associated with structural stages are very 

approximate, based on the best estimate of the BNF silviculturalists 

(USDA Forest Service 1994). Also, area of the landscape in each of 

Romme’s classifications by seral stage (fig. 26) was estimated using a dot 

grid on his maps in his 1979 dissertation and by crudely estimating areas 

burned during the 1988 fires by examining a 1988 satellite image of the 

park.
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