Historical and Current Forest

and Range Landscapes in the

Interior Columbia River Basin

and Portions of the Klamath

and Great Basins

Part 1: Linking Vegetation Patterns and

Landscape Vulnerability to Potential Insect

and Pathogen Disturbances

United States

Department of

Agriculture

Forest Service

Pacific Northwest

Research Station

United States

Department of the

Interior

Bureau of Land

Management

General Technical

Report

PNW-GTR-458

September 1999
Authors

PAUL F. HESSBURG is a research plant pathologist and R. BRION SALTER is a GIS analyst, Pacific

Northwest Research Station, Forestry Sciences Laboratory, 1133 N. Western Avenue, Wenatchee, WA

98801; BRADLEY G. SMITH is a quantitative ecologist, Pacific Northwest Region, Deschutes National

Forest, 1645 Highway 20 E., Bend, OR 97701; SCOTT D. KREITER is a GIS analyst, Wenatchee,

WA; CRAIG A. MILLER is a geographer, Wenatchee, WA; CECILIA H. McNICOLL was a plant ecologist, Intermountain Research Station, Fire Sciences Laboratory, and is currently at Pike and San Isabel

National Forests, Leadville Ranger District, Leadville, CO 80461; and WENDEL J. HANN was the

regional ecologist, Northern Region, Intermountain Fire Sciences Laboratory, and is currently the

National Landscape Ecologist stationed at White River National Forest, Dillon Ranger District,

Silverthorne, CO 80498.
Historical and Current Forest and 

Range Landscapes in the Interior 

Columbia River Basin and Portions 

of the Klamath and Great Basins

Part 1: Linking Vegetation Patterns and Landscape 

Vulnerability to Potential Insect and Pathogen Disturbances

Paul F. Hessburg, Bradley G. Smith, Scott D. Kreiter, Craig A. Miller, 

R. Brion Salter, Cecilia H. McNicoll, and Wendel J. Hann

Interior Columbia Basin Ecosystem Management Project: 

Scientific Assessment

Thomas M. Quigley, Editor

U.S. Department of Agriculture 

Forest Service

Pacific Northwest Research Station 

Portland, Oregon 

General Technical Report PNW-GTR-458

September 1999
Abstract

Hessburg, Paul F.; Smith, Bradley G.; Kreiter, Scott D.; Miller, Craig A.; Salter, R. Brion;

McNicoll, Cecilia H.; Hann, Wendel J. 1999. Historical and current forest and range landscapes 

in the interior Columbia River basin and portions of the Klamath and Great Basins. Part I: Linking

vegetation patterns and landscape vulnerability to potential insect and pathogen disturbances. Gen.

Tech. Rep. PNW-GTR-458. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station. 357 p. (Quigley, Thomas, M., ed., Interior Columbia Basin Ecosystem

Management Project: scientific assessment).

Management activities of the 20th century, especially fire exclusion, timber harvest, and domestic livestock grazing, have significantly modified vegetation spatial patterns of forests and ranges in the interior

Columbia basin. Compositional patterns as well as patterns of living and dead structure have changed.

Dramatic change in vital ecosystem processes such as fire, insect, and pathogen disturbances, succession,

and plant and animal migration is linked to recent change in vegetation patterns. Recent change in vegetation patterns is also a primary reason for current low viability and threatened, endangered, or sensitive

status of numerous native plant and animal species. Although well intentioned, 20th-century management practices have not accounted for the larger patterns of living and dead vegetation that enable forest

ecosystems to function in perpetuity and maintain their structure and organization through time, or for

the disturbances that create and maintain them. Knowledge of change in vegetation patterns enhances

resource manager and public awareness of patterns that better correspond with current climate, site conditions, and native disturbance regimes, and improves understanding of conditions to which native terrestrial species have already adapted. 

In this study, we characterized recent historical and current vegetation composition and structure of 337

randomly sampled subwatersheds (9500 ha average size), in 43 of 164 total subbasins (404 000 ha average size), selected by stratified random draw on all ownerships within the interior Columbia River basin

and portions of the Klamath and Great Basins (collectively referred to as the basin). We compared landscape patterns, vegetation structure and composition, and landscape vulnerability to 21 major insect and

pathogen disturbances of historical and current vegetation coverages. For each selected subwatershed, we

constructed historical and current vegetation maps from interpretations of 1932-66 and 1981-93 aerial

photos, respectively. Areas with homogeneous vegetation composition and structure were delineated as

patches to a minimum size of 4 ha. We then attributed cover types (composition), structural classes

(structure), and series-level potential vegetation types (site potential) to individual patches within subwatersheds by modeling procedures. We characterized change in vegetation spatial patterns by using an

array of class and landscape pattern metrics and a spatial pattern analysis program. Finally, we translated

change in vegetation patterns to change in landscape vulnerability to major forest pathogen and insect

disturbances. Change analyses results were reported for province-scale ecological reporting units. 

Forest and range ecosystems are significantly altered after their first century of active management, but

there is reason for guarded optimism. Large areas remain relatively unchanged and intact, such as can be

found on the east side of the Cascade Range in Washington and in the central Idaho mountains, and

these areas may provide an essential “nucleus” for conservation strategies and ecosystem restoration.

Strategies for improving the health of basin ecosystems can build on existing strengths. Improved understanding of change in vegetation patterns, causative factors, and links with disturbance processes will

assist managers and policymakers in making informed decisions about how to address important ecosystem health issues. 

Keywords: Landscape characterization, ecological assessment, vegetation patterns, interior Columbia

River basin, Klamath Basin, Great Basin, ecosystem health, vegetation pattern-disturbance process interactions, insect and disease disturbance, landscape ecology, ecosystem processes, potential natural vegetation modeling, vegetation change, fire effects.
Preface

The Interior Columbia Basin Ecosystem Management Project (ICBEMP) was initiated by the Forest

Service and the Bureau of Land Management to respond to several critical issues including, but not limited to, forest and rangeland health, anadromous fish concerns, terrestrial species viability concerns, and

the recent decline in traditional commodity flows. The charter given to the project was to develop a scientifically sound, ecosystem-based strategy for managing the lands of the interior Columbia River basin

administered by the Forest Service and the Bureau of Land Management. 

The Science Integration Team was organized to develop a framework for ecosystem management, a

broad-scale assessment of the socioeconomic and biophysical systems in the basin, and an evaluation of

alternative management strategies. The broad-scale assessment of the biophysical systems consisted of

two parts: (1) a multiscale characterization of biophysical environments of the basin (Jensen and others

1997), and (2) a broad-scale landscape assessment of change in vegetation patterns and disturbance

regimes of the basin (Hann and others 1997). In addition to the broad-scale landscape assessment, a

midscale assessment was conducted to validate the results of the broad-scale assessment at a scale appropriate to observing the vegetation pattern-disturbance process interactions. This paper is one of a series

of four papers developed to document the results of that mid-scale assessment.

The Science Integration Team, although organized functionally, worked hard at integrating the research

approaches, analyses, and conclusions. It was the collective effort of the team that provided depth and

understanding to the work of the project. The Science Integration Team leadership included deputy

team leaders Russel Graham and Sylvia Arbelbide; landscape ecology—Wendel Hann, Paul Hessburg,

and Mark Jensen; aquatic—Jim Sedell, Kris Lee, Danny Lee, Jack Williams, Lynn Decker; economic—

Richard Haynes, Amy Horne, and Nick Reyna; social science—Jim Burchfield, Steve McCool, and Jon

Bumstead; terrestrial—Bruce Marcot, Kurt Nelson, John Lehmkuhl, Richard Holthausen, and Randy

Hickenbottom; and broad-scale spatial analysis—Becky Gravenmier, John Steffenson, and Andy Wilson.

Thomas M. Quigley

Editor

United States

Department of

Agriculture

Forest Service

Interior Columbia

Basin Ecosystem

Management Project

United States

Department of

the Interior

Bureau of Land

Management
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Summary

In this midscale assessment, we have quantified change in vegetation patterns and landscape vulnerability to fire, insect, and pathogen disturbances over the most recent 50 to 60 years based on a stratified

random sample of 337 subwatersheds (9500 ha average size) distributed in 43 subbasins (404 000 ha

average size), on all public and private ownerships within the interior Columbia River basin (the basin).

Change analyses results were reported by province-scale ecological reporting units (ERUs). In the assessment, we have compared landscape patterns, structure, composition, and vulnerability to insect and

pathogen disturbances of historical and current vegetation coverages. Forest and rangeland vegetation

composition and structure were remotely sensed from resource aerial photographs taken from 1932 to

1966 (historical), and from 1981 to 1993 (current). Areas with homogeneous vegetation composition

and structure were delineated as patches, with a minimum patch size of 4 ha. Cover types, structural

classes, and potential vegetation types (PVTs) were modeled for each forest or range patch by using raw

photointerpreted attributes and topographic or biophysical data from other digital sources of comparable

scale and image resolution.

Each patch was assigned a vulnerability rating for three to seven vulnerability factors associated with

each of 21 different potential forest insect and pathogen disturbances: one defoliator disturbance, seven

bark beetle disturbances, four dwarf mistletoe disturbances, six root disease disturbances, two rust disturbances, and one stem decay disturbance. Patch vulnerability factors were taken from the published 

literature or were based on the expert opinions and experiences of field pathologists and entomologists

with regional or localized experience in specific geographic areas. Vulnerability factors were unique for

each host-pathogen or host-insect interaction modeled and included such items as site quality (differences in site potential), host abundance, canopy layers, host age or host size, stand vigor, stand density,

connectivity of host patches, topographic setting, and type of visible logging disturbance.

Vegetation maps, patch attributes, and derived cover type, structural class, and PVT attributes formed

the basic data set from which all subsequent pattern analyses were accomplished. Individual patches were

described by their composition, structure, and PVT from selected photointerpreted attributes. We used

percentage of area, mean patch size, and patch density metrics to describe changes in area and connectivity of patch types in subwatersheds of an ERU. Change from historical to current conditions was estimated as the mean difference between historical and current conditions, not as the percentage of change

from historical conditions, to avoid the bias of establishing the historical condition as an essential reference. For each ERU, means, mean standard errors, and confidence intervals were estimated by using

methods for simple random samples with subwatersheds as sample units. Statistically significant (P≤0.2)

change was determined by examining the 80-percent confidence interval around the mean difference for

the ERU.

We supplemented this statistical test with two additional analyses that enabled us to evaluate the potential ecological significance of patch type change in area or connectivity of area. First, we approximated

the historical range of variation by calculating the historical sample median 75-percent range for each

metric, and we compared the current sample median value with this estimate of the historical range.

Second, we characterized the most significant changes in absolute area of a patch type within a sample

by using transition analysis. Ecologically significant change was ultimately determined after examining

each of the three pieces of information.

Physiognomic Types

Forest cover increased in the Blue Mountains, Columbia Plateau, Southern Cascades, and Upper Snake

ERUs, where our results suggested that effective fire prevention, suppression, and exclusion resulted in

expansion of forests into areas that previously were bare ground or shrubland or into former herbland

areas previously maintained by fire or created by early logging. 
Forest cover declined in the Upper Klamath ERU, and our analysis indicated that timber harvest activities during the sample period caused the observed depletion of forest area. Connectivity of forests

increased in the Central Idaho Mountains and Upper Snake ERUs. The Central Idaho Mountains ERU

contains large areas of congressionally or administratively designated wilderness or roadless areas, and it

is likely that increased connectivity occurred as a result of fire exclusion. Connectivity of forests declined

significantly in the Upper Klamath ERU where evidence of timber harvest was widespread. Forests of

the Upper Klamath are naturally quite fragmented. Forested slopes often are separated by broad grassy

valley bottoms and dry southerly aspects. Timber harvest apparently accentuated this characteristic.

Woodland area increased in the Blue Mountains, Columbia Plateau, Northern Cascades, Northern

Great Basin, Owyhee Uplands, Snake Headwaters, and Upper Klamath ERUs and declined in no ERUs,

thereby suggesting that fire suppression, fire exclusion, and grazing enabled expansion at the expense of

declining herblands and shrublands. Perhaps most dramatic of all changes in physiognomic conditions

was the across-the-board regional decline in area of shrublands. Shrubland area declined in all ERUs but

the Southern Cascades, which had little to begin with. Ecologically significant reduction was observed 

in the Blue Mountains, Central Idaho Mountains, Columbia Plateau, Northern Great Basin, Owyhee

Uplands, and Snake Headwaters ERUs, and no ERU exhibited increased shrubland area. Transition

analyses indicated that losses to native shrublands resulted from various factors, including forest or

woodland expansion as observed in the Blue Mountains and Northern Great Basin ERUs, cropland

expansion as observed in the Northern Great Basin ERU, and conversion to seminative or nonnative

herbland as observed in the Owyhee Uplands or Snake Headwaters ERU.

Herbland area increased significantly in the Central Idaho Mountains, Northern Great Basin, Owyhee

Uplands, Snake Headwaters, and Southern Cascades ERUs and did not decline in any ERU. In the

Central Idaho Mountains, herbland area increased by about 1 percent, and increases were primarily to

colline and montane bunchgrass cover types. But in the Northern Great Basin, herbland area rose at the

expense of shrublands; historical shrubland area fell by more than 15 percent of the land area of the

ERU. Half of the lost shrubland area is currently occupied by juniper woodland, and the balance of the

area currently supports montane bunchgrasses or exotic grass and forb cover. Herbland and shrubland

area followed a similar pattern in the Owyhee Uplands. Across the basin, most increase in herbland area

was the result of expanding colline exotic grass and forb cover with the conversion of shrublands.

Forest and Range Cover Types

Predicted shifts from early seral forest species, such as ponderosa pine, western larch, lodgepole pine,

western white pine, and sugar pine, to late seral species, such as grand fir, white fir, subalpine fir,

Engelmann spruce, and western hemlock, were evident in several ERUs. In some, the shift from seral 

to late seral climax species was at least partially masked by steep climatic gradients. For example, in the

Northern Cascades ERU, Douglas-fir is seral in subalpine fir, western hemlock, and Pacific silver fir

PVTs but to the east is climax or late seral in the Douglas-fir PVT.

Of all forested ERUs, the most pronounced shifts from early to late seral cover types occurred in the

Northern Glaciated Mountains. Western larch cover declined significantly in the Central Idaho

Mountains, Columbia Plateau, and Northern Glaciated Mountains ERUs, and ponderosa pine cover

decreased in the Northern Cascades, Northern Glaciated Mountains, Upper Clark Fork, and Upper

Klamath ERUs. Ponderosa pine cover increased in the Southern Cascades as a result of regrowth of

forests clearcut just before the period of our historical photo coverage. Lodgepole pine cover declined in

the Snake Headwaters ERU, and in six other ERUs. Western white pine cover decreased in the Northern

Glaciated Mountains ERU as a consequence of white pine blister rust, mountain pine beetle mortality,

and selective harvesting and increased slightly in the Northern Cascades as a result of recent reforestation

efforts. Whitebark pine-subalpine larch cover declined in the Central Idaho Mountains, Northern
Glaciated Mountains, Snake Headwaters, and Upper Clark Fork ERUs and increased in the Blue

Mountains and Northern Cascades ERUs. Decline in whitebark pine cover likely was the result of 

ongoing blister rust and mountain pine beetle mortality. 

In contrast, Douglas-fir cover increased significantly in the Blue Mountains, Columbia Plateau, and

Northern Cascades ERUs; grand fir-white fir cover increased in the Northern Cascades and Northern

Glaciated Mountains; Pacific silver fir cover increased in the Northern Cascades ERU; Engelmann

spruce-subalpine fir cover increased in the Northern Glaciated Mountains, Snake Headwaters, Southern

Cascades, and Upper Clark Fork ERUs; and western hemlock-western redcedar cover increased in the

Columbia Plateau, and Northern Glaciated Mountains ERUs. Engelmann spruce-subalpine fir cover

declined significantly in the Blue Mountains, and Engelmann spruce-subalpine fir and western hemlockwestern redcedar cover both decreased in the Northern Cascades. We believe the noted increases in

shade-tolerant cover types are the direct result of effective fire suppression and exclusion and selective

timber harvest.

Among woodland cover types, juniper cover significantly increased in the Blue Mountains, Columbia

Plateau, Northern Great Basin, Owyhee Uplands, Snake Headwaters, and Upper Klamath ERUs 

and decreased in no ERU where it was a major cover type. Oregon white oak cover increased in the

Northern Cascades ERU. Fire exclusion and grazing may be primary causes of the observed increases,

but we were unable to test this hypothesis directly.

Significant reductions in shrubland cover types were noted in virtually every ERU, but effects were most

dramatic where shrublands accounted for more than one-quarter of the land area of an ERU. The largest

reductions in shrub cover types occurred in the Columbia Plateau, Northern Great Basin, Owyhee

Uplands, and Upper Snake ERUs. Significant declines in shrub cover types also were observed in the

Blue Mountains, Snake Headwaters, and Upper Klamath ERUs. In general, the greatest losses to shrublands were associated with forest or woodland expansion as observed in the Blue Mountains and

Northern Great Basin ERUs, cropland expansion as observed in the Northern Great Basin ERU, 

and conversion to seminative or nonnative herbland as observed in the Owyhee Uplands or Snake

Headwaters ERUs. Most shrubland cover in the Blue Mountains, Columbia Plateau, Owyhee Uplands,

and Upper Snake ERUs resides below lower treeline, and in each case, the most significant losses 

of shrub cover occurred in these colline settings. Shrublands of the Northern Great Basin, Snake

Headwaters, and Upper Klamath primarily occupy montane settings. Cover types of these elevation 

settings suffered the greatest losses.

In general, herbland cover increased throughout the basin as a result of declining shrubland area, but

several important cover type losses also were noteworthy. Bunchgrass cover declined significantly in several ERUs, notably the Columbia Plateau, Northern Cascades, Northern Glaciated Mountains, Upper

Clark Fork, and Upper Klamath. Bunchgrass cover increased in the Central Idaho Mountains, Northern

Great Basin, Snake Headwaters, and Upper Snake ERUs. Exotic grass and forb cover increased in 9 of

13 ERUs. Significant increases in exotics in either colline or montane settings occurred in the Blue

Mountains, Columbia Plateau, Northern Cascades, Northern Great Basin, Owyhee Uplands, Snake

Headwaters, and Upper Clark Fork ERUs. Ecological reporting units most affected by expansion of

exotics were, in ascending order, the Columbia Plateau, Northern Great Basin, and Owyhee Uplands.

Finally, postlogging grass-forb cover increased in all forested ERUs.

Cropland area increased dramatically in two ERUs, the Upper Klamath and the Upper Snake. Cropland

area declined in the Blue Mountains. Area in irrigated pastures increased in several ERUs, but only the

increase observed in the Northern Glaciated Mountains was significant. Urban and rural developed area

increased in half of the ERUs during the sample period; the increase was significant in the Central Idaho

Mountains, Northern Cascades, Southern Cascades, and Upper Snake ERUs.
Forest and Range Structural Classes

In general, the structure of current forests of sampled ERUs was simpler when compared with historical

forests, but causal links with management are difficult to establish because the amount of fire suppression or total timber harvest, for instance, was not directly measurable or quantifiable. Still, structural

changes observed were consistent with management activities implicated as primary factors in the overall

simplification of structural complexity of basin forests: namely, timber harvest, fire suppression, fire

exclusion, and domestic livestock grazing. In future work, we will compute landscape metrics by using

structural classes as patch types to further quantify patterns of structural change.

Area in forest stand-initiation structures declined significantly in four of nine forest-dominated ERUs

and increased significantly in one, the Blue Mountains. Area in stand-initiation structures declined in

the Central Idaho Mountains, Lower Clark Fork, Northern Glaciated Mountains, and Upper Clark Fork

ERUs. Area in old-forest structures declined in most forested ERUs, but the most significant declines

occurred in the Blue Mountains, Northern Cascades, Snake Headwaters, and Upper Klamath ERUs. In

general, area in intermediate (not new and not old forest) structural classes (stem exclusion, understory

reinitiation, and young multistory) increased in most forested ERUs; the most notable increases occurred

in the Blue Mountains, Central Idaho Mountains, Columbia Plateau, Lower Clark Fork, Northern

Glaciated Mountains, Snake Headwaters, Southern Cascades, and Upper Clark Fork ERUs. Area in

intermediate structural classes actually declined in the Upper Klamath ERU, where most evidence suggested extensive past harvesting.

Area of open or closed shrub structure declined in every ERU where the shrubland physiognomic type

comprised more than 0.5 percent of the area. The most significant loss of shrub structure in the basin

was the loss of open low-medium structures (primarily sagebrushes, rabbitbrush, and bitterbrush).

Significant reductions in open low-medium shrub structures were noted in the Blue Mountains,

Columbia Plateau, Northern Great Basin, Owyhee Uplands, and Snake Headwaters ERUs. Significant

reduction in closed low-medium shrub structure was noted in the Columbia Plateau ERU. Open herbland area increased in most ERUs where significant reduction in open low-medium shrub structure

occurred. We speculate that range management activities to improve forage production for domestic

livestock were responsible for much of the noted change.

Forest Vulnerability to Insect and Pathogen Disturbances

Forest landscapes have changed significantly in their vulnerability to major insect and pathogen disturbances. Changes have occurred in response to management practices common in the 20th century.

Management practices have significantly increased vulnerabilities in some subbasins and ERUs, and

decreased them in others. Vulnerability changes at the ERU scale often were insignificant or masked

owing to high variation among sampled subwatersheds. High variability among subwatersheds within

ERUs was a function of large geographic extent, high variability in vegetative communities and biophysical conditions, and variable climatic and disturbance regimes. We learned that analysis of change in vulnerability to various pathogen and insect disturbances is best accomplished at a subwatershed scale,

given change among similar subwatersheds at a subregional scale.

Change analyses indicated that forests of the Blue Mountains ERU were influenced quite predictably by

timber harvesting, fire suppression and exclusion, and livestock grazing. Timber harvest minimized oldforest area and area with remnant large trees to a fraction of the historical area and reduced the availability of medium and large trees in all structures. Medium and large trees were harvested from all major

cover types including ponderosa pine, grand fir-white fir, Engelmann spruce-subalpine fir, and Douglasfir. In the absence of frequent fires and under the influence of selective harvesting and grazing, Douglasfir cover expanded, forest structures became more layered, grass and shrub understories were replaced by

conifer understories, and forests and woodlands expanded in areas that were formerly grasslands and

shrublands.
In the Blue Mountains, area vulnerable to western spruce budworm did not change significantly; a relatively large proportion of the ERU was vulnerable in the historical coverage, and a similar proportion 

is vulnerable in the existing condition. But were defoliation to occur under existing conditions, growth

and mortality effects likely would be more pronounced. Area vulnerable to Douglas-fir beetle has

increased because Blue Mountains landscapes in the existing condition have increased cover, connectivity, size of Douglas-fir, and stand densities. Area vulnerable to western pine beetle (type 1) disturbance

of mature and old ponderosa pine fell because medium and large ponderosa pine were selectively harvested from old and other forest structures. Area vulnerable to mountain pine beetle (type 1) disturbance

of lodgepole pine declined as a result of declining area where lodgepole pine occurs as a major seral

species in mixed types. Area vulnerable to fir engraver and spruce beetle disturbance also declined as 

a result of timber harvest, extended drought, and bark beetle outbreaks.

Area vulnerable to Douglas-fir dwarf mistletoe increased with expanded area of Douglas-fir and

increased canopy layering and contiguity of host patches. In contrast, area vulnerable to ponderosa pine

and western larch dwarf mistletoes declined as a result of reduced area of ponderosa pine and western

larch overstory cover. Even with declining area of grand fir, white fir, and subalpine fir overstory cover,

area vulnerable to S-group annosum root disease likely increased. We believe this is true because the

total area occupied by host species increased (but hosts now more often occur in intermediate and lower

crown classes), a large percentage of the total forest area has been entered for timber harvest, and freshly

cut stumps provide avenues for spread of this disease to new patches. Area and connectivity of area vulnerable to laminated root rot disturbance increased primarily as a result of increased cover and connectivity of Douglas-fir patches, but also as a result of increased area occupied by true firs.

Few significant changes in vulnerability were in evidence in the Central Idaho Mountains. For the most

part, vulnerability characterizations indicated that the primary management influence during the sample

period was exclusion of fire. Shade-tolerant true firs increased slightly in area and dominance, and

insects and pathogens that specialize in attacking true firs were modestly favored by that increase. Area

vulnerable to western spruce budworm increased but the change was not significant; a large proportion

of the ERU area (49.4 percent) was highly vulnerable in the historical coverage, and a similar proportion

(51.1 percent) is vulnerable in the existing condition. Area vulnerable to fir engraver and S-group annosum root disease disturbance also increased.

Our analyses suggested that dry and mesic forests of the Columbia Plateau have been influenced in a

predictable manner by selective harvesting, fire suppression, and fire exclusion. Area highly vulnerable 

to western spruce budworm disturbance increased during the sample period; increased vulnerability was

associated with increased area of Douglas-fir cover and increased area of Douglas-fir and grand fir in

multilayered understories, both predicted consequences of fire exclusion and selective harvesting.

Selective harvesting reduced area in old-forest structures and reduced the abundance of medium and

large trees in all structures. Consequently, we observed a modest decline in vulnerability to western pine

beetle (type 1) disturbance of mature and old ponderosa pine. Area vulnerable to western pine beetle

(type 2) and mountain pine beetle (type 2) disturbance of immature, high-density ponderosa pine

increased during the sample period as a result of expanded area of ponderosa pine cover in young multistory structures. Area highly vulnerable to fir engraver increased as a result of increased area with grand

fir understories. Area highly vulnerable to S-group annosum also increased because grand fir and western

hemlock in mixed species cover types, and occurring as understory species, increased during the sample

period, as did area in these types with visible logging entry. Area vulnerable to white pine blister rust

(type 1) disturbance of western white pine declined; decline was likely the result of white pine blister

rust and mountain pine beetle mortality and selective harvesting.
Analysis of cover type and structural class changes and vulnerability characterizations indicate that significant harvesting has occurred in highly productive forests of the Lower Clark Fork ERU, but fire exclusion perhaps has had the greatest effect on conditions we observe today. In our small sample, area with

medium and large trees increased during the sample period, and area in the 90- to 100- percent crown

cover class and in multilayered canopies increased. Each change is a predictable consequence of fire suppression and exclusion, especially in an area where stand-replacing fire historically played such a significant role.

Area vulnerable to western spruce budworm increased but the change was not significant; a large proportion of the ERU (56.8 percent) was highly vulnerable in the historical condition, and a similar proportion

(65 percent) is vulnerable in the existing condition. The 8.2-percent increase was not statistically significant because of the small sample size; further sampling is needed to establish the trend. In the absence of

fire, lodgepole pine-dominated landscapes of the Lower Clark Fork aged and became more synchronous

in their vulnerability to bark beetle and fire disturbances. With increased overstory and understory grand

fir cover developing during the sample period, vulnerability to fir engraver disturbance also increased, but

the 8.7-percent increase again was not statistically significant because of our small sample size. Similarly,

area vulnerable to Armillaria root disease increased, but the change was not significant.

Results of vulnerability characterizations for the Northern Cascades ERU indicated that the primary

effect of management during the sample period was probably timber harvest followed by fire suppression

and exclusion. Area occupied by old-forest structures and medium and large trees declined significantly

during the sample period, as did area of ponderosa pine cover. Area of Douglas-fir cover increased, but

area of medium and large Douglas-fir declined. These results explain much of the change we observed in

vulnerability to pathogen and insect disturbances. Vulnerabilities to western pine beetle (type 1) disturbance of mature and old ponderosa pine and Douglas-fir beetle disturbance both declined with the loss

of medium and large hosts. Connectivity of vulnerable areas also declined, indicating that remaining distributions of medium and large ponderosa pine and Douglas-fir are relatively fragmented.

Area and connectivity of area vulnerable to western pine beetle (type 2) and mountain pine beetle (type

2) disturbance of immature, high-density ponderosa pine also declined owing to reduced area of ponderosa pine cover in young and middle-aged structures. Area vulnerable to western (ponderosa pine)

dwarf mistletoe disturbance declined with the loss of ponderosa pine overstories through harvesting. In

contrast, area vulnerable to S-group annosum root disease disturbance increased during the sample period. The observed increase in high-vulnerability area was associated with increased area and stature of

grand fir and Pacific silver fir cover and increased area with visible logging entry.

Fire exclusion and timber harvest acted together to produce the changes in vulnerability we observed in

the Northern Glaciated Mountains ERU. In our historical vegetation coverage, no visible logging entry

was apparent for 91 percent of the forested area. In the current condition, signs of visible logging activity

were apparent for 26 percent of that area. But old-forest area and area with remnant large trees did not

decline during the sample period. Furthermore, area occupied by medium and large trees actually

increased. We speculate that because stand-replacing fires once were common in the ERU, regrowth 

of forest in the absence of fire apparently offset some of the effects of harvesting at the ERU scale.

Predicted effects of fire exclusion also were observed: increased crown cover, increased canopy layering,

and increased cover by shade-tolerant understory conifers.

Area vulnerable to western spruce budworm increased with increasing cover of grand fir and subalpine 

fir and increased canopy layering. In the absence of fire, lodgepole pine-dominated landscapes of the

Northern Glaciated Mountains became more synchronous in their vulnerability to mountain pine beetle

and fire disturbances. Area and connectivity of area vulnerable to spruce beetle disturbance increased with

increased area and stature of spruce in the Engelmann spruce-subalpine fir cover type. As expected, area

vulnerable to ponderosa pine and western larch dwarf mistletoes declined with the reduction of ponderosa
pine and western larch cover. Area vulnerable to Armillaria root disease and S-group annosum root disease increased with the increasing dominance of shade-tolerant overstories and understories; area and connectivity of area vulnerable to white pine blister rust (type 1) disturbance of western white pine declined

as a result of white pine blister rust and mountain pine beetle mortality and selective harvesting.

Fire exclusion and, to a lesser extent, timber harvest interacted to produce the changes in vulnerability

that we observed in the Snake Headwaters ERU. In the historical vegetation condition, no visible logging entry was apparent in any of the forested area. In the current condition, signs of visible current or

past logging were apparent for 2 percent of the area. Old-forest area and area with remnant large trees

declined during the sample period, but changes were not statistically significant. Area occupied by medium and large trees also declined. Overall, increased area with visible logging could not account for some

of the changes in vulnerability we observed. Area and connectivity of area vulnerable to western spruce

budworm disturbance increased dramatically during the sample period; increase was associated with

increased area of Engelmann spruce-subalpine fir cover in multilayered structural arrangements. Area

and connectivity of area vulnerable to Douglas-fir beetle disturbance also increased. Because total area in

old-forest structures declined, most of the increased area likely was associated with increased abundance

of Douglas-fir larger than 22.7 cm d.b.h. in structural classes other than old forest.

Area vulnerable to mountain pine beetle (type 1) disturbance of high-density lodgepole pine fell by 5.4

percent, and area of lodgepole pine cover declined by 4.3 percent. These results suggest that the area of

small to medium lodgepole pine in both pure and mixed compositions declined during the sample period. We know that before and during the period of our sample, large areas of Snake Headwaters lodgepole pine forest were attacked and killed by the mountain pine beetle. But these results suggest that

salvage and regeneration efforts influenced less than half of that area at best. Beetle disturbance and fire

exclusion resulted in cover type conversion of some areas to Engelmann spruce and subalpine fir. These

changes were corroborated by transition analyses. Area vulnerable to Armillaria root disease and S-group

annosum root disease increased significantly with increasing dominance of shade-tolerant overstories and

understories.

Analyses of vegetation change and characterizations of disturbance vulnerability indicated that the

Southern Cascades have been influenced quite significantly and predictably by timber harvesting and 

fire exclusion. Area of old single-story and old multistory forest structures more than doubled during 

the sampling period, but area with remnant large trees associated with structures other than old forest

declined, albeit nonsignificantly, by 42 percent. Area occupied by medium and large trees associated

with all forest structures increased by 10 percent during the sample period. But average area in the forest

physiognomic type also rose by 10 percent, mainly as a result of regrowth of large areas being clearcut

harvested before our historical vegetation condition. We speculate that the large harvested area likely 

was dominated by patches with large ponderosa pine trees and old single-story structures.

In the Southern Cascades, area vulnerable to western spruce budworm disturbance increased; the

increase was associated with increased area of multilayered, shade-tolerant understories. But area vulnerable to budworm disturbance amounts to little more than 10 percent of the area of the ERU, even in the

existing condition. Area vulnerable to Douglas-fir beetle and Douglas-fir dwarf mistletoe disturbances

declined because area and connectivity of patches with medium and large Douglas-fir in old forest and

other structures declined. Area vulnerable to mountain pine beetle (type 1) disturbance of high-density

lodgepole pine declined and area of the lodgepole pine cover remained unchanged. As was the case in

the Blue Mountains, these results suggest that area of lodgepole pine in historically mixed compositions

declined during the sample period as a result of mountain pine beetle outbreaks and the exclusion of

regenerative fires. Area vulnerable to Armillaria root disease and laminated root rot disturbance increased

with expanded area of subalpine fir, grand fir, and Douglas-fir in pure and mixed species compositions;

expanded area of shade-tolerant understories; and increased crown cover of host species.
Forest vegetation of the Upper Clark Fork ERU has been radically altered by timber harvest and, to a

lesser extent, fire suppression and exclusion. Most especially, the grain of Upper Clark Fork landscapes

has been refined. In our historical vegetation coverage, 12 percent of the forest area exhibited remotely

sensed visible signs of logging; in the existing condition, 37 percent of the forest area exhibited visible

signs of logging. During the sample period, forest and woodland area affected by regeneration and selective harvesting jumped from 10 to 20 percent of the forest area. Overall, the level of timber harvest had

little effect on old-forest area or area with remnant large trees. It was apparent from the area of standinitiation structures in our historical vegetation coverage, that fire played a major role in regenerating

forests, and it is likely that large areas of young and intermediate structure were historically typical for

these landscapes. Area with medium and large trees remained relatively unchanged despite the level of

timber harvest. In the absence of fires and under the influence of selective harvesting, forest crown cover

declined, forest structures became less layered, and large areas developed grass and shrub understories

where conifer understories once were more typical. Even area with visible dead trees and snags declined

during the sample period.

Among forested ERUs, the Upper Clark Fork was one those most heavily influenced by past timber harvest. It was not surprising that most vulnerability changes were declines. Area and connectivity of area

vulnerable to Douglas-fir beetle disturbance declined owing to reduced crown cover of large and medium Douglas-fir across all forest structural classes. Area vulnerable to western pine beetle (type 1) disturbance of mature and old ponderosa pine declined as a consequence of reduced area in the ponderosa

pine cover type and reduced crown cover of medium and large ponderosa pine across all forest structural

classes.

Area vulnerable to western pine beetle (type 2) and mountain pine beetle (type 2) disturbance of immature, high-density ponderosa pine also declined as a result of reduced area in the ponderosa pine cover

type and reduced area of stem-exclusion, understory reinitiation, and young multistory structures with

ponderosa pine in pure or mixed compositions. In contrast, area and connectivity of area vulnerable to

fir engraver disturbance increased during the sample period. High-vulnerability area increased primarily

as a result of increased area in the subalpine fir-Engelmann spruce cover type in all forest structural 

classes except stand initiation. Vulnerability to dwarf mistletoe disturbances of Douglas-fir, ponderosa

pine, and western larch declined during the sample period. The observed decline was the result of significantly reduced patch area and contiguity with medium and large hosts in multilayered structures.

In the historical vegetation condition, more than one-half (53 percent) of all forest cover in the Upper

Klamath ERU was ponderosa pine and 23 percent of all forest structure was old forest; 38 percent of 

all forest structures had at least 10 percent or more crown cover of large trees. In the existing condition,

49 percent of all forest cover is ponderosa pine and 21 percent is old forest; 36 percent of all forest

structures have at least 10 percent or more crown cover of large trees, but crown cover of medium and

large trees has been substantially reduced. Selection cutting reduced the crown cover of medium and

large trees for 31 percent of the forest area. Much like the Upper Clark Fork, in the absence of fires and

under the influence of heavy selective harvesting, forest crown cover declined, forest structures became

less layered, and large areas developed grass and shrub understories where conifer understories once were

more typical. Forest area declined by an average of 3 percent; likewise, area with visible dead trees and

snags declined during the sample period. Among forested ERUs, the Upper Klamath was probably the

second most heavily influenced by past timber harvest, and as with the Upper Clark Fork, most vulnerability changes were declines.
Introduction 1

Methods

Study Area 5

Overview of Biophysical Environments 5

Northern Rocky Mountain Forest Province 5

Cascade Province 7

Great Plains-Palouse Dry Steppe Province 7

Middle Rocky Mountain Province 8

Intermountain Semidesert Province 8

Intermountain Semidesert Province 9

Sierran Province 9

Southern Rocky Mountain Province 10

Sampling Design 10

Software tools 10

Land and hydrologic unit sampling framework 11

Subbasin stratification and subwatershed selection 11

Vegetation Mapping 39

Forest vegetation classification 41

Range vegetation classification 55

Vegetation and Landscape Pattern Analysis 64

Raster size determination 64

Sample statistics 64

Spatial statistics 67

Landscape pattern analyses 68

Forest Landscape Vulnerability to Insect and Pathogen Disturbances 69

Disturbance agents 69

Vulnerability factors 70

Modeling change 71

Ecological Reporting Units 71

Rationale 71

Development 72

Contents
Results 75

Vegetation 75

Blue Mountains ERU 75

Central Idaho Mountains ERU 85

Columbia Plateau ERU 107

Lower Clark Fork ERU 109

Northern Cascades ERU 110

Northern Glaciated Mountains ERU 114

Northern Great Basin ERU 117

Owyhee Uplands ERU 118

Snake Headwaters ERU 120

Southern Cascades ERU 122

Upper Clark Fork ERU 124

Upper Klamath ERU 126

Upper Snake ERU 129

Landscape Patterns 131

Blue Mountains ERU 133

Central Idaho Mountains ERU 133

Columbia Plateau ERU 134

Lower Clark Fork ERU 134

Northern Cascades ERU 135

Northern Glaciated Mountains ERU 136

Northern Great Basin ERU 136

Owyhee Uplands ERU 137

Snake Headwaters ERU 138

Southern Cascades ERU 139

Upper Clark Fork ERU 139

Upper Klamath ERU 139

Upper Snake ERU 140

Forest and Woodland Area With Medium and Large Trees 140

Blue Mountains ERU 142

Central Idaho Mountains ERU 143

Columbia Plateau ERU 143

Lower Clark Fork ERU 143

Northern Cascades ERU 144

Northern Glaciated Mountains ERU 144

Northern Great Basin ERU 145

Owyhee Uplands ERU 145
Snake Headwaters ERU 145

Southern Cascades ERU 145

Upper Clark Fork ERU 146

Upper Klamath ERU 146

Upper Snake ERU 147

Forest and Woodland Crown Cover, Canopy Layers, and Cover of Understory Tree Species 147

Blue Mountains ERU 160

Central Idaho Mountains ERU 161

Columbia Plateau ERU 161

Lower Clark Fork ERU 161

Northern Cascades ERU 162

Northern Glaciated Mountains ERU 162

Northern Great Basin ERU 162

Owyhee Uplands ERU 163

Snake Headwaters ERU 163

Southern Cascades ERU 163

Upper Clark Fork ERU 163

Upper Klamath ERU 164

Upper Snake ERU 164

Dead Tree and Snag Abundance 165

Area Affected by Visible Logging Activity 165

Riparian and Wetland Area 173

Vulnerability of Forest Landscapes to Potential Insect and Pathogen Disturbances 175

Blue Mountains ERU 175

Central Idaho Mountains ERU 181

Columbia Plateau ERU 196

Lower Clark Fork ERU 200

Northern Cascades ERU 200

Northern Glaciated Mountains ERU 202

Northern Great Basin ERU 206

Owyhee Uplands ERU 206

Snake Headwaters ERU 206

Southern Cascades ERU 207

Upper Clark Fork ERU 208

Upper Klamath ERU 209

Upper Snake ERU 210
Discussion 211

Detecting Ecosystem Change 211

Vegetation Composition and Structure 213

Physiognomic types 213

Forest and woodland cover types 223

Shrubland and herbland cover types 229

Nonrange-nonforest and other anthropogenic cover types 230

Forest and woodland structure 233

Shrubland and herbland structure 254

Landscape Patterns 255

Richness, diversity, and evenness 256

Contagion and interspersion 257

Edge contrast 258

Pattern changes among ERUs 258

Forest Vulnerability to Insect and Pathogen Disturbances 260

Blue Mountains ERU 261

Central Idaho Mountains ERU 264

Columbia Plateau ERU 268

Lower Clark Fork ERU 268

Northern Cascades ERU 270

Northern Glaciated Mountains ERU 270

Snake Headwaters ERU 275

Southern Cascades ERU 275

Upper Clark Fork ERU 277

Upper Klamath ERU 279

Ecological Regionalization 279

Additional Validation and Research 281

Validation 281

Vegetation research 282

Insect and pathogen research 283

Conclusion 287

Acknowledgments 291

English Conversions 295

References 297

Appendix 1: Attributes of Forest and Nonforest Patches 311

Appendix 2: Table 32 315

Appendix 3: Table 33 337
Tables

Table 1—Stratum membership of subbasins sampled in the midscale ecological assessment of the 

interior Columbia River basin 14

Table 2—Bailey province and Omernik ecoregion membership of sampled subbasins of the 

midscale ecological assessment of the interior Columbia River basin 16

Table 3—Photo years of resource aerial photography used to sample recent historical and 

current vegetation conditions of subbasins in the midscale ecological assessment of the interior

Columbia River basin 40

Table 4—Photointerpreted and derived patch attributes of sampled subwatersheds in the 

midscale ecological assessment of the interior Columbia River basin 42

Table 5—Descriptions of forest structural classes modeled in the midscale ecological assessment 

of the interior Columbia River basin 46

Table 6—Classification rules for forest structural classes modeled for sampled subwatersheds 

in the midscale ecological assessment of the interior Columbia River basin 47

Table 7—Classification rules for forest cover types modeled for sampled subwatersheds in the 

midscale ecological assessment of the interior Columbia River basin 48

Table 8—Common and scientific names and abbreviations of species 49

Table 9—Elevation classes used to model forest potential vegetation types in the midscale 

ecological assessment of the interior Columbia River basin 53

Table 10—Aspect classes used to model forest potential vegetation types in the midscale 

ecological assessment of the interior Columbia River basin 53

Table 11—Descriptions of herbland and shrubland structure classes modeled for sampled

subwatersheds in the midscale ecological assessment of the interior Columbia River basin 54

Table 12—Classification rules for herbland and shrubland structural classes modeled for 

sampled subwatersheds in the midscale ecological assessment of the interior 

Columbia River basin. 55

Table 13—Classification rules for herbland and shrubland cover types modeled for sampled 

subwatersheds in the midscale ecological assessment of the interior Columbia River basin 56

Table 14—Classification rules for woodland structural classes modeled for sampled subwatersheds 

in the midscale ecological assessment of the interior Columbia River basin 57

Table 15—Definitions of range potential vegetation types modeled for sampled subwatersheds in 

the midscale ecological assessment of the interior Columbia River basin. 58

Table 16—Classification rules for herbland, shrubland, and woodland potential vegetation 

types modeled for sampled subbasins in the midscale ecological assessment of the interior 

Columbia River basin 61

Table 17—FRAGSTATS indices used to quantify connectivity and spatial patterns of patch types 

in sampled subbasins in the midscale ecological assessment of the interior Columbia River basin 65

Table 18—Edge contrast weights used in calculating the FRAGSTATS metric—area weighted 

mean edge contrast index (AWMECI) in pattern analyses of patch types of sampled subwatersheds 

in the midscale ecological assessment of the interior Columbia River basin 68
Table 19—Landscape metric results for 13 ecological reporting units in the midscale assessment 

of the interior Columbia River basin where patch types were cover type-structural class doublets 132

Table 20—Percentage comparison of areas of remnant large trees, old single story, and old 

multistory forest structures for ecological reporting units in the midscale assessment of the interior

Columbia River basin 141

Table 21—Percentage comparison of area of medium and large trees for ecological reporting 

units in the midscale assessment of the interior Columbia River basin 142

Table 22—Percentage comparison of areas of forest and woodland in 5 total crown cover classes 

for ecological reporting units in the midscale assessment of the interior Columbia River basin 148

Table 23—Percentage comparison of areas of forest and woodland with 1, 2, or more than 

2 canopy layers for ecological reporting units in the midscale assessment of the interior 

Columbia River basin 149

Table 24—Percentage comparison of area of forest and woodland understory species classes for 

ecological reporting units in the midscale assessment of the interior Columbia River basin 154

Table 25—Percentage comparisons of historical and current areas of grass-forb-shrub-bare 

ground and conifer or hardwood understories for ecological reporting units in the midscale 

assessment of the interior Columbia River basin 160

Table 26—Percentage comparison of area of forest and woodland in dead tree and snag 

abundance classes for ecological reporting units in the midscale assessment of the interior 

Columbia River basin 164

Table 27—Percentage comparison of area of forest and woodland in visible logging activity classes 

for ecological reporting units in the midscale assessment of the interior Columbia River basin 168

Table 28—Comparison of riparian-wetland area abundance in ecological reporting units in the 

midscale assessment of the interior Columbia River basin. 173

Table 29—Historical and current percentages of area for physiognomic types, cover types, and 

structural classes of 13 ecological reporting units in the midscale assessment of the interior 

Columbia River basin 214

Table 30—“Jackknife” estimates of total patch-type richness and dominance (N2) for 13 ecological

reporting units in the midscale assessment of the interior Columbia River basin where patch types 

were cover type-structural class doublets 257

Table 31—Insect and pathogen disturbance vulnerability changes in 13 ecological reporting 

units in the midscale assessment of the interior Columbia River basin. 262

Table 32—Historical and current percentage of area, patch density, and mean patch size for 

physiognomic types, cover types, and structural classes of sampled subwatersheds in the ERUs 

of the midscale ecological assessment of the interior Columbia River basin 315

Table 33—Historical and current percentage of area, patch density, and mean patch size for 

insect and pathogen disturbance vulnerability classes of sampled subwatersheds of the ERUs 

of the midscale ecological assessment of the interior Columbia River basin 337
Figures

Figure 1—Interior Columbia River basin assessment area with Bailey province boundaries 6

Figure 2—Hierarchical organization of subwatersheds (6th code HUCs), watersheds (5th code 

HUCs), and subbasins (4th code HUCs) in the interior Columbia River basin and portions of 

the Klamath and Great Basins 12

Figure 3—Sampled subbasins of the midscale assessment of the interior Columbia River basin 

(see also table 2). The assessment area included the portion of the Columbia River basin occurring 

in the United States east of the crest of the Cascade Range. Subbasins in the upper reaches of the

Klamath River basin and the Northern Great Basin also were included to fully represent conditions 

in eastern Oregon and Washington, Idaho, and western Montana 19

Figure 4—Map groupings of subbasins sampled in the midscale ecological assessment of the 

interior Columbia River basin. Subbasins were separated for ease of mapping into 18 groups. 

Sampled watersheds are shown by subbasin group in figures 5 to 22. 20

Figure 5—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other 

ownerships sampled in the Methow and Wenatchee subbasins of Washington for the midscale 

ecological assessment of the interior Columbia River basin 21

Figure 6—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other 

ownerships sampled in the Kettle, Sanpoil, and Pend Oreille subbasins of Washington for the 

midscale ecological assessment of the interior Columbia River basin 22

Figure 7—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other 

ownerships sampled in the Upper Coeur d’Alene and Yaak subbasins of Idaho and Montana for 

the midscale ecological assessment of the interior Columbia River basin 23

Figure 8—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other 

ownerships sampled in the Lower Flathead, Swan, and Blackfoot subbasins of Montana for the 

midscale ecological assessment of the interior Columbia River basin 24

Figure 9—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other 

ownerships sampled in the Upper Yakima, Naches, and Lower Yakima subbasins of Washington 

for the midscale ecological assessment of the interior Columbia River basin 25

Figure 10—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other 

ownerships sampled in the Palouse subbasin of Idaho and Washington for the midscale ecological 

assessment of the interior Columbia River basin 26

Figure 11—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other 

ownerships sampled in the Lochsa, Flint Rock, and Bitterroot subbasins of Idaho and Montana 

for the midscale ecological assessment of the interior Columbia River basin 27

Figure 12—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other 

ownerships sampled in the Upper and Lower John Day subbasins of Oregon for the midscale 

ecological assessment of the interior Columbia River basin 28

Figure 13—Subwatersheds on USDA Forest Service, Bureau of Land Management, and 

other ownerships sampled in the Upper Grande Ronde, Wallowa, and Lower Grande Ronde 

subbasins of Oregon and Washington for the midscale ecological assessment of the interior 

Columbia River basin 29
Figure 14—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other 

ownerships sampled in the Burnt and South Fork Clearwater subbasins of Oregon and Idaho for 

the midscale ecological assessment of the interior Columbia River basin 30

Figure 15—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other 

ownerships sampled in the Lower Crooked, Upper Deschutes, and Little Deschutes subbasins 

of Oregon for the midscale ecological assessment of the interior Columbia River basin 31

Figure 16—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other 

ownerships sampled in the Silvies and Donner und Blitzen subbasins of Oregon for the midscale 

ecological assessment of the interior Columbia River basin 32

Figure 17—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other 

ownerships sampled in the South Fork Salmon, Boise-Mores, and Upper Middle Fork Salmon 

subbasins of Idaho for the midscale ecological assessment of the interior Columbia River basin 33

Figure 18—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other 

ownerships sampled in the Lemhi and Medicine Lodge subbasins of Idaho for the midscale 

ecological assessment of the interior Columbia River basin 34

Figure 19—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other 

ownerships sampled in the Lower Henry’s, Palisades, and Snake Headwaters subbasins of Idaho 

and Wyoming for the midscale ecological assessment of the interior Columbia River basin 35

Figure 20—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other 

ownerships sampled in the Upper Klamath Lake and Lost subbasins of Oregon and California 

for the midscale ecological assessment of the interior Columbia River basin 36

Figure 21—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other 

ownerships sampled in the Crooked Rattlesnake and Upper Owyhee subbasins of Oregon, Idaho, 

and Nevada for the midscale ecological assessment of the interior Columbia River basin 37

Figure 22—Subwatersheds on USDA Forest Service, Bureau of Land Management, and 

other ownerships sampled in the Big Wood and Lake Walcott subbasins of Idaho 

for the midscale ecological assessment of the interior Columbia River basin. 38

Figure 23—Ecological reporting units (ERUs) of the interior Columbia River basin broadscale and midscale assessments. Shaded areas denote subbasins sampled within

each ERU. 73

Figure 24—Composite of ecological reporting units (A) and Bailey’s province-elevation strata 

(B) for subbasins sampled in the midscale assessment of the interior Columbia River basin. 

Shaded areas denote sampled subbasins 74

Figure 25—Historical and current distribution of physiognomic types expressed as a percentage 

of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate 

the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between 

historical and current conditions 76

Figure 26—Historical and current distribution of forest and woodland cover types expressed as a 

percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error 

bars indicate the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) 

difference between historical and current conditions 78
Figure 27—Historical and current distribution of forest cover types expressed as a percentage 

of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate 

the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between 

historical and current conditions 80

Figure 28—Historical and current distribution of forest cover types expressed as a percentage 

of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate 

the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between 

historical and current conditions 82

Figure 29—Historical and current distribution of herbland and shrubland cover types expressed 

as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin. 

Error bars indicate the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) 

difference between historical and current conditions 86

Figure 30—Historical and current distribution of herbland and shrubland cover types expressed 

as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error 

bars indicate the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions 88

Figure 31—Historical and current distribution of shrubland cover types expressed as a percentage 

of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate 

the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between 

historical and current conditions 90

Figure 32—Historical and current distribution of herbland and nonforest-nonrange cover types

expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River 

basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate a significant 

(P≤0.2) difference between historical and current conditions 92

Figure 33—Historical and current distribution of herbland cover types expressed as a percentage 

of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate 

the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between 

historical and current conditions 94

Figure 34—Historical and current distribution of anthropogenic and other nonforest-nonrange 

cover types expressed as a percentage of total area on all ownerships in ERUs of the interior 

Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks 

indicate a significant (P≤0.2) difference between historical and current conditions 96

Figure 35—Historical and current distribution of anthropogenic and other nonforest-nonrange 

cover types expressed as a percentage of total area on all ownerships in ERUs of the interior 

Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks 

indicate a significant (P≤0.2) difference between historical and current conditions 98

Figure 36—Historical and current distribution of forest structural classes expressed as a percentage 

of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate 

the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between 

historical and current conditions. Structural class codes are SI = stand initiation; SEOC = stem 

exclusion, open canopy; SECC = stem exclusion, closed canopy; UR = understory reinitiation; 

YMS = young multistory; OMS = old multistory; and OSS = old single story 100
Figure 37—Historical and current distribution of woodland structural classes expressed as a 

percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error 

bars indicate the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) 

difference between historical and current conditions. Structural class codes are SI = stand initiation; SE = stem exclusion; UR = understory reinitiation; YMS = young multistory; OMS = old 

multistory; and OSS = old single story 102

Figure 38—Historical and current distribution of herbland, shrubland, and other structural classes

expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River 

basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate a significant 

(P≤0.2) difference between historical and current conditions. Structural class codes are OH = open 

herb; CH = closed herb; OLS = open low-medium shrub; CLS = closed low-medium shrub; 

OTS = open tall shrub; CTS = closed tall shrub; and Other = nonforest-nonrange and anthropogenic type structures 104

Figure 39—Historical and current distribution of forest and woodland total crown cover classes

expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River 

basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate a significant 

(P≤0.2) difference between historical and current conditions 150

Figure 40—Historical and current distribution of forest and woodland canopy layer classes expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin.

Error bars indicate the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) 

difference between historical and current conditions 152

Figure 41—Historical and current distribution of forest and woodland understory species classes

expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River 

basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate a significant 

(P≤0.2) difference between historical and current conditions. The understory species class “other”

includes grass-forb, shrub, and bare ground understories and those comprised of Shasta red fir, 

incense-cedar, western white pine, limber pine, pinyon pine, and beargrass 156

Figure 42—Historical and current distribution of forest and woodland understory species classes

expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River 

basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate a significant 

(P≤0.2) difference between historical and current conditions. The understory species class “other”

includes grass-forb, shrub, and bare ground understories and those comprised of Shasta red fir, 

incense-cedar, western white pine, limber pine, pinyon pine, and beargrass 158

Figure 43—Historical and current distribution of forest and woodland dead tree and snag abundance classes expressedas a percentage of total area on all ownerships in ERUs of the interior 

Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate 

a significant (P≤0.2) difference between historical and current conditions. Dead tree and snag classes

were none apparent, < 10 percent of trees dead or snags, 10 to 39 percent of trees dead or snags, 

40 to 70 percent of trees dead or snags, and > 70 percent of trees dead or snags 166

Figure 44—Historical and current distribution of forest and woodland apparent logging entry classes

expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River 

basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate a significant 

(P≤0.2) difference between historical and current conditions. Logging entry classes were no logging 

apparent, regeneration harvest, selective harvest, thinned, patch clearcut, and nonforestnonwoodland 170
Figure 45—Historical and current distribution of riparian and wetland area expressed as a percentage 

of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the

standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between 

historical and current conditions 174

Figure 46—Historical and current distribution of western spruce budworm and Douglas-fir 

beetle disturbance vulnerability classes expressed as a percentage of total area on all ownerships in 

ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean 

estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.

Insect disturbance abbreviations are WSB = western spruce budworm and DFB = Douglas-fir beetle.

Vulnerability class codes are low, moderate, and high 176

Figure 47—Historical and current distribution of western pine beetle type-1 and type-2 disturbance vulnerability classes expressed as a percentage of total area on all ownerships in ERUs of the 

interior Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks

indicate a significant (P≤0.2) difference between historical and current conditions. Insect disturbance

abbreviations are WPB1=western pine beetle (type 1) of mature and old ponderosa pine, and

WPB2=western pine beetle (type 2) of immature and high density ponderosa pine. Vulnerability 

class codes are low, moderate, and high 178

Figure 48—Historical and current distribution of mountain pine beetle type-1 and type-2 disturbance vulnerability classes expressed as a percentage of total area on all ownerships in ERUs of the 

interior Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks

indicate a significant (P≤0.2) difference between historical and current conditions. Insect disturbance

abbreviations are MPB1=mountain pine beetle (type 1) of high-density lodgepole pine, and

MPB2=mountain pine beetle (type 2) of immature and high-density ponderosa pine. Vulnerability 

class codes are low, moderate, and high 182

Figure 49—Historical and current distribution of fir engraver and spruce beetle disturbance 

vulnerability classes expressed as a percentage of total area on all ownerships in ERUs of the interior

Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate 

a significant (P≤0.2) difference between historical and current conditions. Insect disturbance abbreviations are FE = fir engraver and SB = spruce beetle. Vulnerability class codes are low, moderate, 

and high 184

Figure 50—Historical and current distribution of Douglas-fir and western larch dwarf mistletoe 

disturbance vulnerability classes expressed as a percentage of total area on all ownerships in ERUs 

of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate.

Asterisks indicate a significant (P≤0.2) difference between historical and current conditions. 

Pathogen disturbance abbreviations are DFDM = Douglas-fir dwarf mistletoe and WLDM = 

western larch dwarf mistletoe. Vulnerability class codes are low, moderate, and high 186

Figure 51—Historical and current distribution of ponderosa pine and lodgepole pine dwarf 

mistletoe disturbance vulnerability classes expressed as a percentage of total area on all ownerships 

in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean 

estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.

Pathogen disturbance abbreviations are PPDM = ponderosa pine dwarf mistletoe and LPDM = 

lodgepole pine dwarf mistletoe. Vulnerability class codes are low, moderate, and high 188
Figure 52—Historical and current distribution of Armillaria root disease and laminated root rot 

disturbance vulnerability classes expressed as a percentage of total area on all ownerships in ERUs 

of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate.

Asterisks indicate a significant (P≤0.2) difference between historical and current conditions. 

Pathogen disturbance abbreviations are AROS = Armillaria root disease and PHWE = laminated 

root rot. Vulnerability class codes are low, moderate, and high 190

Figure 53—Historical and current distribution of S- and P-group annosum root disease disturbance 

vulnerability classes expressed as a percentage of total area on all ownerships in ERUs of the interior

Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate 

a significant (P≤0.2) difference between historical and current conditions. Pathogen disturbance 

abbreviations are HEAN-S = S-group annosum root disease and HEAN-P = P-group annosum root 

disease. Vulnerability class codes are low, moderate, and high 192

Figure 54—Historical and current distribution of tomentosus and Schweinitzii root and butt rot 

disturbance vulnerability classes expressed as a percentage of total area on all ownerships in ERUs 

of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate.

Asterisks indicate a significant (P≤0.2) difference between historical and current conditions. Pathogen

disturbance abbreviations are TRBR = tomentosus root and butt rot and SRBR = Schweinitzii root 

and butt rot. Vulnerability class codes are low, moderate, and high 194

Figure 55—Historical and current distribution of white pine blister rust type-1 and type-2 

disturbance vulnerability classes expressed as a percentage of total area on all ownerships in ERUs 

of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate.

Asterisks indicate a significant (P≤0.2) difference between historical and current conditions. Pathogen

disturbance abbreviations are WPBR1 = white pine blister rust (type 1) of western white and sugar 

pine and WPBR2 = white pine blister rust (type 2) of whitebark pine. Vulnerability class codes are 

low, moderate, and high 198

Figure 56—Historical and current distribution of rust-red stringy rot disturbance vulnerability 

classes expressed as a percentage of total area on all ownerships in ERUs of the interior 

Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks 

indicate a significant (P≤0.2) difference between historical and current conditions. RRSR = 

rust-red stringy rot. Vulnerability class codes are low, moderate, and high 204

Figure 57—Historical and current maps of physiognomic types: (A) subwatershed 21 in the 

Lower Grande Ronde subbasin of the Blue Mountains ERU, and (B) subwatershed 0402 in the 

Upper Klamath subbasin of the Upper Klamath ERU 220

Figure 58—Historical and current maps of physiognomic types: (A) subwatershed o16 in the 

Lower Crooked subbasin of the Columbia Plateau ERU, and (B) subwatershed 0802 in the 

Upper Owyhee subbasin of the Owyhee Uplands ERU 222

Figure 59—Historical and current maps of physiognomic types in subwatershed 45 in the 

Little Deschutes subbasin of the Southern Cascades ERU 223

Figure 60—Historical and current maps of forest and woodland cover types in subwatershed 

09 in the Pend Oreille subbasin of the Northern Glaciated Mountains ERU 224

Figure 61—Historical and current maps of forest and woodland cover types in subwatershed 

2002 in the Palouse subbasin of the Columbia Plateau ERU 225
Figure 62—Historical and current maps of forest and woodland cover types in subwatershed 60 

in the Lower Yakima subbasin of the Northern Cascades ERU 226

Figure 63—Historical and current maps of forest and woodland cover types: (A) subwatershed 45 in the Little Deschutes subbasin of the Southern Cascades ERU, and (B) subwatershed 0308 in the Snake Headwaters subbasin of the Snake Headwaters ERU 227

Figure 64—Historical and current maps of forest and woodland cover types: (A) subwatershed 55 in the Methow subbasin of the Northern Cascades ERU, and (B) subwatershed 06 in 

the Wenatchee subbasin of the Northern Cascades ERU 228

Figure 65—Historical and current maps of forest and woodland cover types in subwatershed 2701 in the Lower John Day subbasin of the Columbia Plateau ERU 230

Figure 66—Historical and current maps of shrubland and herbland cover types in subwatershed y3 in the Upper Yakima subbasin of the Northern Cascades ERU 231

Figure 67—Historical and current maps of shrubland and herbland cover types in subwatershed 0402 in the Donner und Blitzen subbasin of the Northern Great Basin ERU 232

Figure 68—Historical and current maps of shrubland, herbland, and anthropogenic cover types 

in subwatershed 0203 in the Lake Walcott subbasin of the Upper Snake ERU 233

Figure 69—Historical and current maps of shrubland, herbland, and anthropogenic cover types in 

subwatershed 0701 in the Lower Flathead subbasin of the Northern Glaciated Mountains ERU 234

Figure 70—Broadscale (1-km2 pixels) map of current potential vegetation groups within the 

interior Columbia River basin assessment boundary. See Hann and others (1997) for map 

development procedures 236

Figure 71—Broadscale (1-km2 pixels) map of (A) historical and (B) current fire regimes within 

the interior Columbia River basin assessment boundary. See Hann and others (1997) for map 

development procedures. Lethal = stand-replacing fire that kills > 70 percent of the overstory tree 

basal area; nonlethal = fire that kills < 20 percent of the overstory tree basal area; mixed = fire that 

kills 20 to 70 percent of the overstory tree basal area; and rarely burns = fire seldom occurs. Very 

frequent = 0- to 25-year mean fire-return interval; frequent = 26- to 75-year mean fire-return 

interval; infrequent = 76- to 150-year mean fire-return interval; very infrequent = 151- to 300-year

mean fire-return interval; and extremely infrequent = > 300-year mean fire-return interval 238

Figure 72—Historical and current maps of forest and woodland structural classes in subwatershed 21 in the Lower Grande Ronde subbasin of the Blue Mountains ERU 240

Figure 73—Broadscale (1-km2 pixels) map of current predicted road density classes within the 

interior Columbia River basin assessment boundary. See Hann and others (1997) for map 

development procedures. None = 0 to 0.01 km/km2; very low = 0.01 to 0.06 km/km2; low = 

0.06 to 0.43 km/km2; moderate = 0.43 to 1.06 km/km2; high = 1.06 to 2.92 km/km2; and 

very high = > 2.92 km/km2 241

Figure 74—Broadscale (1-km2 pixels) map of historical potential vegetation groups within the 

interior Columbia River basin assessment boundary. See Hann and others (1997) for map 

development procedures 242
Figure 75—Historical and current maps of forest and woodland structural classes in subwatershed 2701 in the Lower John Day subbasin of the Columbia Plateau ERU 244

Figure 76—Historical and current maps of forest and woodland structural classes in subwatershed 1401 in the Upper Coeur d’Alene subbasin of the Lower Clark Fork ERU 245

Figure 77—Historical and current maps of forest and woodland structural classes in subwatershed 09 in the Pend Oreille subbasin of the Northern Glaciated Mountains ERU 248

Figure 78—Historical and current maps of forest and woodland structural classes in subwatershed 0903 in the Lost subbasin of the Upper Klamath ERU 253

Figure 79—Historical and current maps of shrubland and herbland structural classes in subwatershed 1101 in the Lower John Day subbasin of the Columbia Plateau ERU 254

Figure 80—Historical and current maps of vegetation vulnerability to (A) Douglas-fir beetle 

disturbance in subwatershed 40C in the Silvies subbasin of the Blue Mountains ERU, and (B) 

mountain pine beetle type 1 disturbance in subwatershed 40 in the Wallowa subbasin of the 

Blue Mountains ERU 263

Figure 81—Historical and current maps of vegetation vulnerability to (A) fir engraver disturbance 

in subwatershed L2 in the Lower Grande Ronde subbasin of the Blue Mountains ERU, and 

(B) spruce beetle disturbance in subwatershed u28 in the Upper Grande Ronde subbasin of the 

Blue Mountains ERU 265

Figure 82—Historical and current maps of vegetation vulnerability to (A) Douglas-fir dwarf 

mistletoe disturbance in subwatershed 29 in the Wallowa subbasin of the Blue Mountains ERU, 

and (B) Schweinitzii root and butt rot disturbance in subwatershed 0901 in the Burnt subbasin 

of the Blue Mountains ERU 266

Figure 83—Historical and current maps of vegetation vulnerability to (A) fir engraver disturbance in subwatershed 0703 in the South Fork Clearwater subbasin of the Central Idaho Mountains

ERU, and (B) western pine beetle type 1 disturbance in subwatershed 1303 in the Lower John Day 

subbasin of the Columbia Plateau ERU 267

Figure 84—Historical and current maps of vegetation vulnerability to (A) western pine beetle 

type 2 disturbance in subwatershed 1903 in the Lower John Day subbasin of the Columbia Plateau

ERU, and (B) mountain pine beetle type 2 disturbance in subwatershed 2002 in the Palouse 

ubbasin of the Columbia Plateau ERU 269

Figure 85—Historical and current maps of vegetation vulnerability to (A) western pine beetle 

type 2 disturbance in subwatershed 10 in the Naches subbasin of the Northern Cascades ERU, 

and (B) mountain pine beetle type 2 disturbance in subwatershed 55 in the Methow subbasin 

of the Northern Cascades ERU 271

Figure 86—Historical and current maps of vegetation vulnerability to (A) western dwarf mistletoe 

disturbance in subwatershed 35 in the Wenatchee subbasin of the Northern Cascades ERU, and 

(B) spruce beetle disturbance in subwatershed 0801 in the Lower Flathead subbasin of the 

Northern Glaciated Mountains ERU 272

Figure 87—Historical and current maps of vegetation vulnerability to (A) western larch dwarf 

mistletoe disturbance in subwatershed 0202 in the Swan subbasin of the Northern Glaciated 

Mountains ERU, and (B) Armillaria root disease disturbance in subwatershed 20 in the Kettle 

subbasin of the Northern Glaciated Mountains ERU 273
Figure 88—Historical and current maps of vegetation vulnerability to (A) white pine blister rust 

type 1 disturbance in subwatershed 09 in the Pend Oreille subbasin of the Northern Glaciated

Mountains ERU, and (B) western spruce budworm disturbance in subwatershed 1102 in the 

Palisades subbasin of the Snake Headwaters ERU 274

Figure 89—Historical and current maps of vegetation vulnerability to (A) S-group annosum 

root disease disturbance in subwatershed 0305 in the Snake Headwaters subbasin of the 

Snake Headwaters ERU, and (B) laminated root rot disturbance in subwatershed 30 in the 

Upper Deschutes subbasin of the Southern Cascades ERU 276

Figure 90—Historical and current maps of vegetation vulnerability to (A) Douglas-fir beetle 

disturbance in subwatershed 0103 in the Blackfoot subbasin of the Upper Clark Fork ERU, and 

(B) Douglas-fir dwarf mistletoe disturbance in subwatershed 0902 in the Flint Rock subbasin of 

the Upper Clark Fork ERU 278
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1

A biological system, whether individual or ecological, can be considered healthy when its inherent

potential is realized, its condition is stable, its

capacity for self repair when perturbed is preserved, and minimal external support [from] management is needed....Stability is not the stability

implied in the Clementsian view of the community;

rather it is compatible with the widespread recognition that biological systems are metastable

(sensu Botkin 1990).

Our ability to change the world [now] outpaces the

ability of biological systems to respond to those

changes. Even our minds and our language evolve

too slowly to deal with the rate of environmental

degradation....Our success as a world society

depends on an environmental revolution—on our

ability, that is, to change our vocabulary and our

perceptions so that we can indeed protect ecological integrity.

No clear standard has been developed to measure

biological condition, however, or to define the

nature and extent of degradation. The lack of 

a standard has, by default, resulted in society’s 

ignoring the status of [human] life support systems. No single innovation can reverse that trend.

Recognizing the problem as a serious social issue

fosters dialogue to define our goals—to define 

the level of ecological health we can accept as a

society. Hence we must develop a rational approach

to the definition of ecological health, methods to

measure that health, and mechanisms to incorporate protection of ecological health into society’s

decision-making processes.

James R. Karr (1992)

Forest and range ecosystems of the interior West

are exceedingly rich and diverse owing to great

variety in climate, geology, landforms, hydrology,

flora, fauna, and ecological processes (Bailey

1995, Franklin and Dyrness 1973, Hann and

others 1997, Jensen and others 1997, Lee and

others 1997, Marcot and others 1997). Recurring

disturbances, such as those caused by fires,

insects, pathogens, and wind, are essential to

maintaining this diversity (Agee 1990, 1993,

1994; Arno 1976, 1980; Edmonds and Sollins

1974; Gara and others 1985; Hagle and others

1994, 1995; Hall 1976; Harvey and others 1992,

1995; Hessburg and others 1994; Martin 1988;

Turner 1987, 1989; Wickman 1992). Terrestrial

plant communities range from dry, short grass

prairies and sagebrush shrublands, to cool and

moist western hemlock and western redcedar

forests, and high-elevation whitebark pine and

subalpine larch forests, krummholz, and heath.1

Alpine tundras, rock barrens, and glaciers comprise many of the highest elevations.

Landscape patterns and ecological characteristics

of these various communities are closely related 

to their fire, insect, and pathogen ecology. Even

though broad landscape patterns of life forms and

physiognomic types arise from broad differences

in topography and physiography, lithology, geomorphic processes, climate regime, and large-scale 

1 Scientific names of all species are given in table 8.

Introduction
disturbances, fine and medium grain2 patterns

within the general framework of coarse patterning

are the result of environmental gradients, patchscale and gap disturbance, stand development,

and succession processes. 

Native fire regimes range from frequent, nonlethal

surface fires typical in dry forests of the ponderosa

pine and Douglas-fir series,3 to moderately infrequent, mixed-severity fires characteristic of mesic

and moist forests of the grand fir, western hemlock, and western redcedar series, and infrequent,

lethal, stand-replacing fires typical in cold subalpine forests.

Native insect and pathogen disturbance regimes

also are variable in their frequency, severity, duration, and spatial extent. Pandemic bark beetle and

defoliator outbreaks, for example, occur relatively

infrequently in any given geographic area (once 

or twice a century at most), and such outbreaks

often are synchronous with climatic extremes and

cycles of geographically dominant vegetation

structure or composition resulting from other

major pattern-forming agents or events. But bark

beetle, defoliator, or pathogen disturbance associated with local and endemic populations is ongoing, blending seamlessly with succession and

stand-development processes; for example, dwarf

mistletoes and root pathogens bring about the

mortality of individual large trees over a span 

of several decades to several centuries, but their

effects on composition and structure of landscapes can be quite spectacular because of their

wide distribution, longevity, and degree of host

specialization. For the most part, it is appropriate

to think of native forest pathogens and insects as

agents of succession (sensu Byler and others 1996,

Hagle and Williams 1995, Hagle and others

1995), selectively killing or reducing the growth

and vigor of a particular tree species or size class,

and thereby bringing about discernible transitions

in composition and structure at patch and landscape scales.

Oliver and Larson (1990) present an ordered progression of stand-development phases resulting

from stand dynamics and disturbance processes,

but in the interior West, insect, pathogen, and

fire disturbances bring about a nonsequential progression of transitions (O’Hara and others 1996).

Insect, pathogen, and fire disturbances are, in

fact, so common and varied in their effects on

vegetation structure and composition that both

seral status and structural development may be

advanced or retarded by individual disturbances

or complex interactions among disturbances (see

also Keane and others 1996).

Declining health of forest ecosystems in the interior West has been the subject of much study,

concern, and controversy in recent years (for

example, see Agee 1994, Byler and others 1994,

Byler and Zimmer-Grove 1990, Everett and 

others 1994, Gast and others 1991, Harvey and

others 1995, Hessburg and others 1994, Huff and

others 1995, Lehmkuhl and others 1994, Monnig

and Byler 1992, O’Laughlin and others 1993,

Wickman 1992). Land-use practices of the last

100 years have altered disturbance regimes, spatial

and temporal patterns of vegetation, and reduced

ecosystem resilience in the face of ongoing disturbance. Concern over “declining forest health”

centers around the human perception that past

forest management activities have had a deleterious effect on forest ecosystem structure and functioning. The perception is founded on the widely

held social value that forest (and rangeland) ecosystems ought to appear natural and be allowed 

to function naturally. In that context, significant

departure from native conditions in the appearance of forests, in attributes of disturbance

regimes (such as disturbance frequency, duration,

2

2 The grain of a given landscape is a function of the average

size and size range of patches comprising that landscape; for

example, a landscape with a coarse grain is comprised of relatively large patches ranging in size from hundreds to perhaps

thousands of hectares. A landscape of fine grain is comprised

of many small patches ranging from a fraction of a hectare to

several hectares. The grain of any given landscape depends

on the scale at which agents of pattern formation operate

locally and the scale of observation.

3 A series is a conceptual grouping of related plant associations having the same predicted dominant climax species;

the series takes the name of the dominant species. A plant

association is a potential vegetation type in a hierarchical classification scheme directly beneath the series level; the plant

association takes the name of a predicted climax community

type. A community type is a conceptual synthesis of all plant

communities having similar structure and floristic composition with no successional status implied; it is simply an

assemblage of plants that live together, interact, and compete

among themselves (Daubenmire and Daubenmire 1968,

Driscoll and others 1984).
3

distribution, intensity, and extent), and in other

vital ecosystem processes (such as succession,

species migration, speciation, extinction) is

indicative of unnatural or deviant functioning 

and uncertain outcomes. Hence, by virtue of the

perceived deviant functioning and unease with

expanding uncertainty, a negative connotation is

applied to changing ecosystems in the notion of

“declining ecosystem health.”

Fire suppression, timber harvest, and livestock

grazing have contributed most to increased forest

ecosystem vulnerability to insect, pathogen, and

wildfire disturbance (Agee 1994, Everett and others 1994, Gast and others 1991, Hann and others

1997, Hessburg and others 1994, Johnson and

others 1994, Lehmkuhl and others 1994, Martin

and others 1976). These conditions are not pervasive, however, and some forests remain in relatively healthy4 and productive condition.

Many studies focusing at the stand level have

characterized fuel loading (Fischer 1981; Maxwell

and Ward 1976, 1980) and fire behavior characteristics (Anderson 1982, Brown and See 1981,

Fahnestock 1976, Ward and Sandberg 1981) for 

a broad range of forest structural conditions

occurring across an equally broad range of potential vegetation types. Likewise, numerous hazard

rating systems have been devised to assess the susceptibility of stands of varying structure, composition, age, vigor, and density to bark beetle

disturbance (for example, see Amman and others

1977; Amman and Anhold 1989; Berryman

1978, 1982; Cole 1978; Cole and Cahill 1976;

Crookston and others 1977; Mahoney 1978;

McGregor 1978; Miller and Keen 1960; Mitchell

1987; Mitchell and others 1983a, 1983b; Roe

and Amman 1970; Safranyik and others 1974,

1975; Schenk and others 1980; Shore and others

1989; Stuart 1984; Waring and Pitman 1980) or

defoliator infestation (Carlson and others 1985;

Heller and Kessler 1985; Stoszek and Mika 1984,

1985; Wulf and Carlson 1985). Stand structural

and compositional conditions most conducive to

damage by dwarf mistletoes and root pathogens

have been characterized, modeled, and articulated

as well (Dixon and Hawksworth 1979; Edminster

1978; Edminster and others 1991; Geils and

Mathiasen 1990; Hadfield and others 1986;

Hawksworth and Johnson 1989; Hawksworth

and others 1995; Knutson and Tinnin 1980;

Myers and others 1971, 1976; Parmeter 1978;

Robinson and Sutherland 1995; Stage and others

1990; Strand and Roth 1976). But little is known

of the effects of cumulative stand-level shifts in

forest composition and structure over long time

spans on landscape composition, structure, and

patterns. Even less is known about the effects of

shifting landscape patterns on fire, insect, and

pathogen disturbance processes or their interactions.

This paper is the first part of a two-part study

conducted under the aegis of the Interior

Columbia Basin Ecosystem Management Project

(ICBEMP). Here, we report on a midscale scientific assessment of vegetation change in terrestrial

landscapes of the interior West and associated

change in landscape vulnerability to potential

insect and pathogen disturbances. Part II (Ottmar

and others, in prep.) will evaluate change in

ground fuel conditions, potential fire behavior,

and related smoke production associated with

reported vegetation change. Our assessment area

included the interior Columbia River basin east 

of the crest of the Cascade Range in the Western

United States and portions of the Klamath and

Great Basins in Oregon (collectively, the basin).

Our study had five objectives:

1. To characterize current structure and composition of a representative sample of forest and

range landscapes distributed throughout the

basin.

2. To compare existing vegetation conditions

(1981-93) to the oldest historical vegetation

conditions (1932-66) we could reconstruct at a

comparable scale. This was done with the hope

of better understanding directions, rates, and

magnitudes of vegetation change occurring

4 In this paper, we say that a forest is healthy when its inherent potential is realized, its condition is metastable, and its

capacity for self-repair when perturbed is preserved. Inherent

potential is the product of biophysical environment, climate,

associated disturbance and other ecological processes. A

metastable condition involves continuous yet bounded

change; change is bounded in its nature and magnitude due

to dominant features of environment, climate, and disturbance regimes.
during the first century of active resource management and exploitation. Our sampling period, although less than 100 years, corresponded

well with the period of most intensive timber

harvest, road construction, and fire suppression; a period of intermediate or declining

intensity in range management; and a period

of comparable climate regime.

3. To link historical and current vegetation patterns with landscape vulnerability to potential

insect and pathogen disturbances to better

understand patterns and disturbance vulnerability relations and more directly characterize

some effects of historical management practices.

4. To link historical and current landscape vegetation characteristics throughout the basin with

fuel conditions, potential fire behavior, and

related smoke production. Our rationale was

twofold: these links would enable us to better

understand causal connections among historical management activities, such as selective

harvesting, fire exclusion, and domestic livestock grazing, and current conditions for

potential fire behavior and smoke production;

and they would assist us in evaluating current

air quality and human health tradeoffs associated with wild and prescribed fires.

5. To synthesize and summarize our findings so

that our information might provide regional

and subregional contexts for Federal and other

management agencies to formulate ecologically

sound management strategies for terrestrial

ecosystems.

We speculate on possible relations between historical land use and our results, considerations for

future management, and research and validation

questions that can be answered with further

analysis of these and supporting data.

4
5

Study Area

In this study, we sampled environments and vegetation conditions representative of each of the

major forest and range provinces of the basin. We

characterized recent historical and current vegetation composition and structure of each of these

sampled environments and compared landscape

patterns, vegetation structure and composition,

and landscape vulnerability to major insect and

pathogen disturbances of historical and current

vegetation coverages. The study area included all

of Washington and Oregon east of the crest of the

Cascade Range, nearly all of Idaho, and portions

of northwestern Montana, western Wyoming,

northern California, northern Utah, and northern

Nevada (fig. 1). The following Bailey provinces

(from Bailey 1989, 1994a, 1994b, 1995) were

included in the study area: Northern Rocky

Mountain Forest—M333, Cascade—M242,

Great Plains-Palouse Dry Steppe—331, Middle

Rocky Mountain—M332, Intermountain

Semidesert—342, Intermountain Semidesert and

Desert—341, Sierran—M261, and Southern

Rocky Mountain—M331.

Overview of 

Biophysical Environments

In this section (adapted from Bailey 1995), we

briefly describe broad, province-scale differences

in environments of the basin to provide a general

overview of biological and physical environment

and climatic conditions of the study area. At the

end of this “Methods” section, we introduce ecological reporting units (ERUs), province-scale

land units used as statistical pooling strata for

reporting results of change analysis. Ecological

reporting units were developed as land units 

useful for generalizing results of all broad-scale

and midscale basinwide ecological, social, and

economic assessments. Because ERUs do not represent purely biophysical environments, we briefly

review differences in province-scale ecological

land units of the basin. Refer to Jensen and others

(1997) for an indepth, multiscale discussion of

basin biophysical and hydrologic environments.

Northern Rocky Mountain Forest

Province—Landforms of the Northern Rocky

Mountain Forest Province (fig. 1) consist primarily of high, glaciated mountains separated by

broad, flat valleys. Winters can be severe with a

heavy snow pack. Dry growing seasons result

from strongly influential westerly air masses; climatic regimes are maritime where Pacific Coast

influence dominates and continental elsewhere.

Precipitation averages 51 to 102 cm annually and

is concentrated in fall, winter, and spring. Forests

are mixed coniferous and deciduous, with

Douglas-fir and cedar-hemlock often dominating.

Elevation belts are clearly indicated by lifeform

changes. Alpine5 environments are barren and

tundralike;6 subalpine7 belts are dominated by

Engelmann spruce, subalpine fir, or mountain

hemlock forests as in the Bitterroot Mountain

5 Alpine environments occur above upper treeline and below

the snow line in mountainous regions. With the exception of

subalpine (often called alpine) larch, conifers are unable to

persist in these environments in an upright growth form.

6 Barren treeless environments are found north of the Arctic

Circle and above the upper tree line of high mountains

(alpine tundra). Tundra environments are characterized by

very low winter temperatures and short cool summers; soils

display a permafrost layer beneath the uppermost layers

affected by summer melt. Tundra vegetation is dominated by

lichens, mosses, sedges, low shrubs, and subshrubs.

7 Subalpine environments occur near the upper treeline. For

much of the year, these environments are snow covered,

cold, and often harsh. For most coniferous species, the subalpine zone defines the upper elevation range of conifers.

Methods
6

Figure 1—Interior Columbia River basin assessment area with Bailey province boundaries.
7

Range. Western hemlock and western redcedar

forests characterize montane settings in association with Douglas-fir, western white pine, western

larch, grand fir, and to a lesser extent ponderosa

pine. Lower montane8 and colline9 environments

are dominated by grasses and sagebrush.

Soils are cool and moist Inceptisols and are often

shallow and stony, but unlike elsewhere in the

Rocky Mountains, these factors play a minor role

in the distributions of forests. Foothill soils tend

to be quite productive as a result of rich loess10

and ash deposits.

Cascade Province—This province is bisected

by the study area boundary (fig. 1). We adapted

the description so that it pertains to the portion

of the province within the basin study area.

Dominant landforms of the Cascade Province 

are the result of widespread volcanic activity.

Rugged mountains of the northern Cascades of

Washington also have been repeatedly glaciated.

Terrain in the north is steep and highly dissected

with relatively narrow valley bottoms except

where glaciated. Maritime climatic regimes dominate throughout because of the close proximity

and influence of Pacific Coast air masses. Precipitation is heavy at the crest and declines rapidly

to the east due to rain shadow effects. Annual

precipitation at the crest is 380 cm; eastern foothills receive as little as 51 cm precipitation annually. Fog partially compensates for droughty summer seasons. Most precipitation occurs as snow. 

Vegetation patterns in the northern and southern

extremes of the province are distinctly different.

At the northern end, alpine environments are

glaciated or barren close to the Cascade crest and

are tundralike to the east. Subalpine belts are

dominated by mountain hemlock forests and treeislands intermixed with heath shrublands at the

crest. Subalpine fir and Engelmann spruce intermixed with subalpine herblands dominate to the

east. Whitebark pine and subalpine larch occur

sporadically throughout. Pacific silver fir, western

hemlock, Douglas-fir, and noble fir characterize

montane forests at the crest; to the east, grand fir,

Douglas-fir, western larch, and ponderosa pine

dominate. Ponderosa pine and sagebrush steppe11

characterize the lower montane and colline elevation belts found mainly to the east.

At the southern end of the province, alpine belts

are tundralike and barren. Mountain hemlock

and lodgepole pine dominate subalpine forests

intermixed with barren herblands. Shasta red fir

provides the transition to montane forest types

dominated by grand fir or white fir, Douglas-fir,

and ponderosa pine. Lodgepole pine forms extensive forests in this belt on flat ground. Ponderosa

pine, western juniper, and sagebrush dominate

lower montane and colline settings.

Andisols are extensive and often overlay volcanic

ash. Moist Inceptisols are widely distributed west

of the Cascade crest, but soils east of the crest are

dry and erosive as a result of deposition of unconsolidated volcanic ash. 

Great Plains-Palouse Dry Steppe

Province—Landforms of the Palouse dry steppe

region (fig. 1) consist of rolling plains and loesscovered basalt tablelands ranging in elevation

from 370 to 1800 m. Plains are flat or rolling and

frequently dissected by valleys and canyons. The

Palouse short grass prairies lie in the rainshadow

of the Cascade Range in Washington, where summers are hot and dry. Throughout the Great

Plains, winters are cold and dry; but on the

Palouse steppe, precipitation reaches its maximum

in the winter. Precipitation ranges from 26 cm in

8 Montane environments are relatively cool, moist upland

habitats occurring above the lower treeline, where coniferous

vegetation often dominates. Lower montane environments

are among the driest forested settings. They occur immediately above the lower tree line. Upper montane environments

support coniferous vegetation favoring cool to cold and

moist to wet growing conditions.

9 Colline environments occur immediately below the lower

treeline.

10 Loess, in this usage, refers to soil accumulations derived of

fine, unconsolidated, wind-blown volcanic ash and glacial

till. In other areas, loess accumulations are the result of aeolian (wind blown) deposits and may be alluvial (silty deposits

initially transported by water), colluvial (deposits initially

transported by gravity), or lacustrine (lake bottom) in origin.

11 Steppe refers to semiarid, treeless environments where

shrub or herbaceous species comprise the dominant vegetative cover.
the northern portion of the province to more

than 64 cm in the south, with maximum rainfall

occurring during summer. Evaporation usually

exceeds precipitation; when precipitation occurs,

it often comes as hail storms and blizzards.

At the time of this assessment, much of the native

herbland vegetation of the Palouse region had

already been converted to dryland agriculture.

What remains, except for remnant shrublands 

and relict12 juniper woodlands, are small isolated

islands comprised of native short grasses, such as

bluebunch wheatgrass, Idaho fescue, and bluegrasses, and often other nonnative grasses and

forbs. Soils are derived of rich loess accumulations

deposited during periods of glacial recession.

Mollisols are common, but humus depth is typically minimal because vegetation is sparse.

Middle Rocky Mountain Province—The

Middle Rocky Mountains Province is comprised

of the Blue Mountains, Salmon River Mountains,

and the basins and ranges of southwestern

Montana (fig. 1). Central Idaho and the Salmon

River Mountains developed from granitic intrusions that collectively make up what is known as

the Idaho Batholith. Terrain is deeply dissected in

the batholith with much evidence of weathered

granitic substrates. In southwestern Montana,

basin and range landforms are mountains with

broad alluvial plains at their bases. Most of 

the highest peaks throughout the province have

been influenced by repeated glaciation. The Blue

Mountains in the western portion of the province

are comprised of uplifted basalts originating from

repeated overland flows associated with the

Columbia River Basalt Group.

Climate within the province is strongly influenced

by maritime air flows up the Columbia mainstem

from the Pacific Ocean, but continental influences also are apparent in the southwestern portion of the province, especially in the John Day

and Malheur basins. Precipitation in montane

forests occurs mostly as snow, and interior valleys

tend to be dry and semiarid. Valleys receive less

than 51 cm of precipitation annually, but mountainous regions may get up to 77 cm.

Clear zones of vegetation by elevation belt are evident. Alpine settings are tundra. Whitebark pine,

subalpine fir, and Engelmann spruce dominate

subalpine belts. Lower montane forests are dominated by ponderosa pine, and midmontane environments are comprised chiefly of Douglas-fir

and grand fir in the more moderate aspects and

elevation settings. Lodgepole pine and grasses

dominate the basins and ranges in the eastern and

southeastern portions of the province. Colline

semidesert environments are dominated by sagebrush and short grasses.

Soils of the alluvial fans and interior valleys are

Mollisols, which support sagebrushes and grasses.

Above 610 m, forest soils are Alfisols except where

glaciated or with steep slopes; Inceptisols predominate in the latter locations.

Intermountain Semidesert Province—The

Intermountain Semidesert Province (fig. 1),

which includes the Columbia River and Snake

River plains in eastern Oregon and Washington,

southern Idaho, and the Wyoming basin, is the

largest province of the basin study area and spans

more than 412 000 km2. Landforms consist of

flat to rolling plains and tablelands. Above 762 m,

plateaus are surrounded by folded and faulted lava

ridges, which make up most of the lava fields of

the region. In the southern portion of the province, intermountain basins and isolated mountain ranges meet strongly dissected plateaus.

Climate of the high plateaus is cool and semiarid.

Average annual precipitation ranges from a low of 

25 cm in the rangelands just east of the Cascade

Range, to 51 cm farther east; accumulations are

somewhat evenly distributed throughout fall, winter, and spring. Winters are long and cold, and

summers are hot and dry. Because of the higher

elevation of the Wyoming basin, its climate is

cooler than that of the rest of the province, and

average precipitation is typically lower, ranging

from 13 to 36 cm annually. Summers there are

short, hot, and dry, and winters can be quite

severe.

Steppe vegetation is dominated by sagebrushes,

shadscale, and short grasses. In central Oregon, a

large area of western juniper-dominated woodland

is apparent where annual precipitation exceeds 25

to 30 cm. Colline valley bottoms are lined with

8

12 Relict, in this usage, refers to a persistent remnant of a

formerly widespread western juniper woodland existing in

isolated areas.
9

willows and sedges, and those of the intermountain valleys support greasewood and other alkalitolerant shrubs and herbs. Moist alkali flats also

commonly support greasewood cover types. In

eastern Washington, areas that once were dominated by bunchgrass herblands now support

extensive dryland wheat farms.

Rich alluvial deposits are widespread throughout

this province in broad flood plains and at the

bases of the Cascade and central Idaho mountains. Dry lake beds are numerous as are dune

and loess deposits. Aridisols dominate throughout

the province in basin and lowland areas. Mollisols

are typical in the higher elevations. Soils of the

Wyoming basin, also Aridisols, are alkaline

enriched with lime and gypsum, and hardpans13

often form naturally or with cultivation. Entisols

make up much of the Bighorn basin soils.

Intermountain Semidesert and Desert

Province—This province enters the basin assessment area at its southern edge in Nevada (fig. 1).

Great Basin and northern Colorado Plateau physiographies comprise most of the area. Really a

misnomer, the Great Basin consists of many

smaller basins with no outlet to the sea. Landforms are varied with mountains rising sharply

from semiarid shrub-covered plains. Mountains

are well vegetated, but conifer forests are few and

limited to the uppermost elevations of high

mountains. Summers are hot, and winters are

moderate. Annual precipitation averages 13 to 49

cm, much of which accumulates as snow. Almost

no rain falls during summer, except occasionally

in the mountains. Spring seasons are typically

long because mild temperatures come early to the

Great Basin, especially in the lower elevations.

Alkaline soil conditions are widespread, and most

vegetation is semitolerant of alkali. Lower elevations are dominated with sagebrush often associated with bitterbrush, shadscale, saltbush,

rabbitbrush, hopsage, and horsebrush. In the

most alkali areas, greasewood and saltgrass cover

types dominate. In areas currently sagebrush

dominated, steppe grasses such as those of the

Palouse Prairie once were more abundant.

Current widespread distribution of sagebrushes

may be the result of repeated historical overgrazing combined with fire suppression. At higher 

elevations above a conspicuous shrubland belt,

pinyon pine and juniper woodlands dominate.

Above the woodlands, ponderosa pine dominates

exposed slopes and Douglas-fir the higher, more

sheltered settings. Subalpine environments, when

occurring, are comprised of subalpine fir and

Engelmann spruce. Exact composition of forested

settings differs considerably from mountain range

to mountain range, presumably the result 

of differing migration rates. As in the preceding

province, soils of basin and lowland areas are

Aridisols, and Entisols line some flood plains in

narrow bands. Salt flats14 and playas15 are typical

in the lower elevations of basins with interior

drainage.

Sierran Province—The Sierran Province is

comprised of the southern extremity of the

Cascade Range in Oregon, the northern Coast

Range in southwest Oregon, the Klamath

Mountains of southern Oregon and northern

California, and the Sierra Nevada of east-central

California. Of this large area, only the Klamath

Mountains and southern Cascades are included in

the basin assessment area (fig. 1). Landforms of

the province consist of steep to precipitous mountains separated by valleys with long and relatively

steep elevation gradients. The Sierra Nevada drop

off abruptly to the Great Basin region to the east,

and more gradually to the west. Within the basin

assessment area, only alpine environments of the

Klamath Mountains are glaciated, and subalpine

and alpine environments are rugged.

Air masses from the Pacific Coast influence the

climate of most of the region. Within the study

area, average annual precipitation ranges from 

25 to 178 cm with rain and snow occurring in

roughly equal proportion. Dense, mixed coniferous forests occupy the montane zone (900 to

2100 m) where the greatest total precipitation

13 A hardpan is a compacted layer in the B-horizon of a soil

typically rich in deposited salts, and restricting drainage and

root penetration. The B-horizon is an upper subsoil layer

with an accumulation of clay, humus, iron, and various

oxides as a result of leaching and translocation from upper

layers.

14 Salt flats are salt-covered, flat-floored, ancient lake beds

remaining after an inland lake has evaporated.

15 Playa is the flat bottom of an undrained desert basin that

at times becomes a shallow lake.
occurs. Subalpine settings receive as much as 100

to 125 cm of precipitation, with most occurring 

as snow.

Elevation zones are distinctly marked by lifeform

and vegetation changes. Montane forests within

the assessment area are dominated by ponderosa

at lower elevations, and Douglas-fir, sugar pine,

incense-cedar, Shasta red fir, and white fir in middle and upper elevations. Subalpine forests are

composed of Shasta red fir, mountain hemlock,

lodgepole pine, western white pine, and an occasional whitebark pine. Below lower treeline, ponderosa pine gives way to juniper woodlands. On

mountain slopes where the coastal influence is

greatest, soils are Ultisols, whereas dry Alfisols are

more typical in lower montane and colline environments. Alluvial and fluvial soils are typically

Entisols.

Southern Rocky Mountain Province—In

the Southern Rocky Mountain province, only the

Snake River headlands in southeastern Idaho and

western Wyoming reside within the basin assessment area (fig. 1). Landforms include glaciated

high mountains with peaks of 4300 m or more,

intermontane parks (herblands and shrublands) or

depressions at intermediate elevations (< 1800 m),

and semiarid valleys at lower elevations. Climate is

dry, resulting primarily from continental air masses. Primary factors of influence to climate are prevailing westerly winds and the north-south orientation of major ranges. The west slope of the

Rocky Mountains within this province area

receives considerably more moisture than the 

eastern slope. Average annual precipitation ranges

from 25 cm at the lowest elevations to as much as

100 cm in the high mountains where most precipitation occurs as snow.

Distinct vegetation zones are the direct result of

elevation and latitude gradients, prevailing winds,

and the degree of slope exposure. North aspects

and narrow valleys support vegetation associated

with the coldest environments for growth and

survival. Alpine settings are tundra or barren; subalpine environments are dominated by subalpine

fir and Engelmann spruce. Lodgepole pine and

aspen are important early seral components of

montane and subalpine environments. Montane

environments are dominated by Douglas-fir and

ponderosa pine; ponderosa pine is especially

prominent in the lowest and driest montane settings, and Douglas-fir is restricted to more

mesic16 and sheltered environments. Foothill

colline environments within the assessment area

are comprised of mixed conifer woodlands, sagebrush, scrub oak, maple, mountain-mahogany, or

bitterbrush shrublands, and herblands. Aridisols

are characteristic of foothills environments,

Mollisols and Alfisols are characteristic of lower

and mid-montane settings, and steep glaciated

slopes typically have Inceptisols.

Sampling Design

Software tools—In this section, we describe the

computing hardware and software we used and its

application in this project to provide an analytical

context for the subsequent descriptions of methods. We used various commercially available computer hardware and software products to complete

this assessment, including geographical information systems (GIS); packages for statistical, spatial,

and ecological data analysis; relational databases

and spreadsheets; and programming language

compilers for custom, inhouse software. These

programs were used on several hardware-operating

system platforms, including Sun® workstations

and X-terminals with Solaris® (Sun’s Unix operating system) and personal computers with OS/2®

and DOS/Windows® operating systems.17

This assessment was a map-based characterization

of landscape patterns and ecological processes

across space and time. We used two GISs to

manipulate and analyze digital maps: ARC/INFO

(ESRI 1995) was the principal GIS used for most

analyses, and GRASS (USACERL 1992) was used

in analyses leading to sample stratification.

ARC/INFO was used with a wide variety of maps

to manipulate, combine, and query coverages to

derive data sets for further analysis with other

10

16 Mesic pertains to environmental conditions of moderate

moisture or water supply; applies to organisms that occupy

habitats displaying intermediate levels of soil moisture or

water availability.

17 The use of trade or firm names in this publication is for

reader information and does not imply an endorsement by 

the U.S. Department of Agriculture of any product or service.
11

software. We used ARC/INFO’s macroprogramming language (AML) to develop and run inhouse spatially explicit models, such as our insect

and pathogen vulnerability characterizations

(Hessburg and others, in press), and potential fire

behavior models (Ottmar and others, in prep.).

Spatial and statistical analyses were done to characterize change in patterns and to quantify statistical and ecological significance of those changes.

FRAGSTATS (McGarigal and Marks 1995) was

used to compute a variety of class and landscape

pattern metrics directly from ARC/INFO data

tables; FRAGSTATS is distributed with a source

code for Unix operating environments. We modified the FRAGSTATS source code by incorporating additional metrics and correcting computational errors of several algorithms. S-PLUS

(MathSoft Inc. 1993) is a statistical package that

reads ARC/INFO data files directly. We used it to

summarize ARC/INFO and FRAGSTATS outputs. Summaries were displayed in tabular and

graphic formats.

A spatially explicit context was not required for

some analyses. Data were generated by ARC/

INFO and exported into a Paradox® relational

database or Excel® spreadsheet. Ad hoc queries

were used to generate summaries and reports.

Paradox also was used to derive or model other

attributes, such as potential vegetation type

described later in this section (see also Smith and

others, in prep). An ecological data analysis package, EcoAid,18 which reads Paradox data files

directly, was used to conduct some ordination and

cluster analyses. Other inhouse programs that

read from or wrote to Paradox files also were written for computations not available in conventional software packages. These programs are available

through the first and second authors.

Land and hydrologic unit sampling framework—To provide insight into managementinduced cause-and-effect relations between

terrestrial and aquatic ecosystems, it is preferable

that ecological characterizations classify environments as terrestrial (both biological and physical

dimensions) and hydrologic, at scales appropriate

to observing the patterns, processes, and interactions of interest. If, for example, an analysis is

conducted to evaluate effects of roads on the distribution of native trout life histories in an area,

land areas ought to be hydrologic domains sufficiently large to represent a nearly full complement

of trout life histories. If that were not the case, it

would be difficult to separate effects of stream

network size from the effects of roads on bull

trout life histories. For reasons such as these, we

chose large sample units, unique in their hydrology, climate, geology, vegetation, and landform.

The ECOMAP land unit hierarchy (ECOMAP

1993) provided a framework for ecological land

units used in this assessment; the U.S. Geological

Survey (USGS) hydrologic unit hierarchy (Seaber

and others 1987) provided an initial framework

for hydrologic units. Both were used to stratify

watersheds of the basin for sampling and characterization.

The USGS hydrologic unit hierarchy supplied a

nested, four-level classification of watersheds of

similar size and scale for the entire United States.

The fourth level in that hierarchy (subbasin or 4th

Hydrological Unit Code [HUC]) was used to initially stratify watersheds of the interior Columbia

River basin assessment area for sampling. In addition, results from the Eastside Forest Ecosystem

Health Assessment (Everett and others 1994,

Lehmkuhl and others 1994) indicate that smaller

hydrologic units of 4000 to 8000 or more ha

were suitable for characterizing, on a sampling

basis, patterns and changes in structural attributes

(both composition and configuration) of vegetation within 4th code HUCs. Complete hydrologic

unit coverages of this scale for the entire interior

Columbia River basin were lacking in the existing

USGS hierarchy. Consequently, two additional

nested levels (5th code HUCs or watersheds, and

6th code HUCs or subwatersheds) were developed

within the established fourth level of the hierarchy for this assessment (fig. 2). Refer to Jensen

and others (1997), for a description of watershed

and subwatershed delineation methods.

Subbasin stratification and subwatershed

selection—Subbasins were selected from a formal stratification of all subbasins in the basin by

18 EcoAid is an inhouse software package for analyzing ecological data sets. Copies are available on request from the 

second author.
their Bailey province membership and similarity

of area in 304.8-m elevation zones. Subbasin areas

in each elevation zone were derived in a GIS by

using a 90-m digital elevation model (DEM)

resampled to 1-km cell size. Similarity analyses

employed the percent similarity (PS) algorithm

(Pielou 1984) shown below:

where

xi= the measure of attribute i in subbasin x, and

yi= the measure of attribute i in subbasin y.

The generated pixel data were treated like any

ecological data set consisting of sample units (subbasins) with species abundances (pixel counts

within each province-elevation class). The intent

was to classify groups of similar subbasins. A

smaller set of subbasins was then randomly drawn

from within each group, from which subwatersheds were randomly selected. Each group contained similar subbasins where the attributes of

similarity were the province-elevation classes.

Because provinces were, by definition, relatively

homogeneous ecological land units at that scale

(ECOMAP 1993), this was a reasonable method

of stratification. A recursive analysis was used;

each analysis cycle consisted of several steps:

12

Figure 2—Hierarchical organization of subwatersheds (6th code HUCs), watersheds (5th code HUCs), and subbasins (4th code

HUCs) in the interior Columbia River basin and portions of the Klamath and Great Basins.

PS = 200

∑min(xi,yi )

∑xi +∑yi

,
13

1. The clustering procedure TWINSPAN (twoway indicator species analysis) was used to

divide the data in four to eight groups (Hill

1979).

2. Two similarity index tables were developed

from the PS algorithm (Pielou 1984). The first

table was a subbasin-by-subbasin comparison.

The PS uses abundance data to weight the

importance of each attribute; for example, two

subbasins with similar attributes that have similar abundance values will have higher similarity values than two subbasins also having similar attributes but divergent abundance values.

The second table was a cluster-by-cluster comparison using TWINSPAN output. These values represented averages of all the within- or

among-group similarity values from the first

table. Assessment of cluster homogeneity for

presence or absence of attributes was possible

with this table.

3. We used the similarity analysis described above 

to further refine membership of each cluster.

We repeated the process for each cluster

defined above, applying steps 1 and 2 for each

cluster, and stopped when further division produced clusters too small to be useful, or when

further subdivision was not ecologically meaningful.

Sixteen subbasin strata were the result of stratification (table 1). Strata contained 4 to 18 subbasins, of which 2 to 4 were randomly selected

without replacement from each stratum for sampling. We duplicated the sampling intensity used

in the Eastside Forest Ecosystem Health Assessment (Everett and others 1994, Lehmkuhl and

others 1994) and allocated that intensity across

each stratum in proportion to stratum size.

Subbasins previously selected for the Eastside

Forest Ecosystem Health Assessment were included in the sample as these data were readily available; subwatersheds within these subbasins also

were selected randomly. In all, 43 subbasins were

sampled. Table 2 lists sampled subbasins by Bailey

province, Omernik ecoregion, and state. Figure 3

displays the locations of all sampled subbasins in

the basin study area. Figure 4 shows selected subbasins as they were grouped for mapping, and figures 5 to 22 display subwatersheds within subbasin groupings.

Subwatersheds were randomly selected for vegetation mapping until at least 15 percent of the area

of each selected subbasin was represented. We

researched availability of recent historical aerial

photography for each selected subwatershed at the

Cartographic Branch of National Archives offices

in Washington, DC, and Salt Lake City. For a few

subbasins, historical aerial photographic coverages

of randomly selected subwatersheds were either

unavailable or incomplete. In most cases, subwatersheds lacking adequate coverage were those

comprised primarily of private lands or rangelands. As a general rule, if a subwatershed contained in excess of 55 to 60 percent private land,

historical photography would be absent or of

insufficient coverage to characterize vegetation

conditions. Subwatersheds with insufficient photo

coverage were randomly replaced as they were

encountered in the draw with others having sufficient coverage. If historical photography was

available for a random selection of subwatersheds

comprising less than 15 percent of the subbasin

area, a new subbasin was randomly selected from

within the same stratum.

Availability of the most current resource aerial

photography was researched at appropriate local

offices of the Forest Service, Bureau of Land

Management, or state departments of forestry 

or natural resources. Ultimately, 337 subwatersheds were sampled in 43 subbasins, and historical and current vegetation maps were constructed

for each sampled subwatershed from remotely

sensed attributes. 

One concern with using subwatersheds of differing area in vegetation pattern analyses is the wellknown correlation of some landscape pattern

attributes with landscape area (O’Neill and others

1988, Turner 1989). Lehmkuhl and Raphael

(1993) show that sample estimates of landscape

attributes change asymptotically rather than 

linearly with landscape area. We used sample subwatersheds averaging at least 4000 ha to avoid

bias associated with small sampling units. When

subwatersheds smaller than 4000 ha were encountered in the sample, they were joined with an

adjacent subwatershed to form a larger logical

hydrologic unit.

Text resumes on page 39
14

Table 1—Stratum membership of subbasins sampled in the midscale ecological assessment of the interior

Columbia River basin

4th code 4th code

Stratum Subbasin name HUC Stratum Subbasin name HUC

1 Goose Lake 18020001 6 Middle Columbia-Hood 17070105

1 Lost 18010204 6 Naches 17030002

1 Upper Klamath 18010206 6 Similkameen 17020007

1 Upper Klamath Lake 18010203 6 Sprague 18010202

2 Chief Joseph 17020005 6 Upper Columbia-Entiat 17020010

2 Clearwater 17060306 6 Upper Deschutes 17070301

2 Coeur d’Alene Lake 17010303 6 Upper Yakima 17030001

2 Colville 17020003 6 Wenatchee 17020011

2 Franklin D. Roosevelt Lake 17020001 6 Williamson 18010201

2 Hangman 17010306 7 Gros Ventre 17040102

2 Kettle 17020002 7 New Fork 14040102

2 Little Spokane 17010308 7 Snake Headwaters 17040101

2 Lower Kootenai 17010104 7 Upper Green 14040101

2 Lower Spokan 17010307 8 American Falls 17040206

2 Okanogan 17020006 8 Blackfoot 17040207

2 Pend Oreille 17010216 8 Greys-Hobock 17040103

2 Pend Oreille Lake 17010214 8 Idaho Falls 17040201

2 Priest 17010215 8 Lake Walcott 17040209

2 Sanpoil 17020004 8 Lower Henry’s 17040203

2 Upper Spokane 17010305 8 Palisades 17040104

3 Banks Lake 17020014 8 Portneuf 17040208

3 Lower Crab 17020015 8 Salt 17040105

3 Lower Snake 17060110 8 Teton 17040204

3 Middle Columbia Lake-Wallula 17070101 8 Willow 17040205

3 Moses Coulee 17020012 9 Alvord Lake 17120009

3 Upper Columbia-Priest Rapids 17020016 9 Beaver-South Fork 17070303

3 Upper Crab 17020013 9 Donner und Blitzen 17120003

4 Palouse 17060108 9 Goose 17040211

4 Lower Snake-Tucannon 17060107 9 Guano 17120008

4 Rock 17060109 9 Harney-Malheur Lakes 17120001

4 Walla Walla 17070102 9 Lake Abert 17120006

5 Lower Crooked 17070305 9 Raft 17040210

5 Lower John Day 17070204 9 Salmon Falls 17040213

5 Trout 17070307 9 Silver 17120004

5 Umatilla 17070103 9 Silvies 17120002

5 Willow 17070104 9 South Fork Owyhee 17050105

6 Klickitat 17070106 9 Summer Lake 17120005

6 Lake Chelan 17020009 9 Thousand-Virgin 16040205

6 Little Deschutes 17070302 9 Warner Lakes 17120007

6 Lower Deschutes 17070306 9 Upper Quinn 16040201

6 Lower Yakima 17030003 10 Bruneau 17050102
15

Table 1—Stratum membership of subbasins sampled in the midscale ecological assessment of the interior

Columbia River basin (continued)

4th code 4th code

Stratum Subbasin name HUC Stratum Subbasin name HUC

6 Methow 17020008 10 Bully 17050118

10 Burnt 17050202 12 South Fork Payette 17050120

10 C.J. Strike Reservoir 17050101 12 South Fork Salmon 17060208

10 Crooked-Rattlesnake 17050109 12 Upper Selway 17060301

10 East Little Owyhee 17050106 13 Big Wood 17040219

10 Jordan 17050108 13 Camas 17040220

10 Lower Boise 17050114 13 Little Wood 17040221

10 Lower Malheur 17050117 13 Lower Middle Fork Salmon 17060206

10 Lower Owyhee 17050110 13 Upper Middle Fork Salmon 17060205

10 Middle Owyhee 17050107 13 Upper Salmon 17060201

10 Middle Snake-Payette 17050115 14 Bitterroot 17010205

10 Middle Snake-Succor 17050103 14 Fisher 17010102

10 Upper Malheur 17050116 14 Flathead Lake 17010208

10 Upper Owyhee 17050104 14 Lower Clark Fork 17010213

10 Upper Snake-Rock 17040212 14 Lower Flathead 17010212

10 Weiser 17050124 14 Lower North Fork Clearwater 17060308

10 Willow 17050119 14 Middle Clark Fork 17010204

11 Brownlee Reservoir 17050201 14 Moyie 17010105

11 Hell’s Canyon 17060101 14 South Fork Coeur d’Alene 17010302

11 Imnaha 17060102 14 St. Joe 17010304

11 Lower Grande Ronde 17060106 14 Stillwater 17010210

11 Lower Snake-Asotin 17060103 14 Upper Coeur d’Alene 17010301

11 Middle Fork John Day 17070203 14 Upper Kootenai 17010101

11 North Fork John Day 17070202 14 Upper North Fork Clearwater 17060307

11 Powder 17050203 14 Yaak 17010103

11 Upper Crooked 17070304 15 Blackfoot 17010203

11 Upper Grande Ronde 17060104 15 Flint-Rock 17010202

11 Upper John Day 17070201 15 Middle Fork Flathead 17010207

11 Wallowa 17060105 15 North Fork Flathead 17010206

12 Little Salmon 17060210 15 South Fork Flathead 17010209

12 Lochsa 17060303 15 Swan 17010211

12 Lower Salmon 17060209 16 Beaver-Camas 17040214

12 Lower Selway 17060302 16 Big Lost 17040218

12 Middle Fork Clearwater 17060304 16 Birch 17040216

12 Middle Fork Payette 17050121 16 Lemhi 17060204

12 Middle Salmon-Chamberlain 17060207 16 Little Lost 17040217

12 Boise-Mores 17050112 16 Medicine Lodge 17040215

12 North and Middle Forks Boise 17050111 16 Middle Salmon Panther 17060203

12 North Fork Payette 17050123 16 Pahsimeroi 17060202

12 Payette 17050122 16 Upper Clark Fork 17010201

12 South Fork Boise 17050113 16 Upper Henry’s 17040202

12 South Fork Clearwater 17060305
16

Table 2—Bailey province and Omernik ecoregion membership of sampled subbasinsa of the midscale 

ecological assessment of the interior Columbia River basinb

4th code

Subbasinc HUC Samples State Bailey province Omernik ecoregion

(1) Pend Oreille 17010216 8 WA M333—Northern Rocky Northern Rockies

Mountain

(2) Kettle 17020002 5 WA M333—Northern Rocky Northern Rockies

Mountain

(3) San Poil 17020004 6 WA M333—Northern Rocky Northern Rockies

Mountain

(4) Methow 17020008 17 WA M242—Cascade Cascades

(5) Wenatchee 17020011 11 WA M242—Cascade Cascades

(6) Upper Yakima 17030001 10 WA M242—Cascade Cascades

(7) Naches 17030002 9 WA M242—Cascade East-side Cascades

slopes and foothills

(8) Lower Yakima 17030003 8 WA M242—Cascade Columbia basin

(9) Palouse 17060108 7 WA 331—Great Plains- Columbia basin

Palouse Dry Steppe

(9) Palouse 17060108 2 ID 331—Great Plains- Columbia basin

Palouse Dry Steppe

(10) Lower Grande Ronde 17060106 9 OR M332—Middle Rocky Blue Mountains

Mountain

(11) Upper Grande Ronde 17060104 9 OR M332—Middle Rocky Blue Mountains

Mountain

(12) Wallowa 17060105 7 OR M332—Middle Rocky Blue Mountains

Mountain

(13) Burnt 17050202 6 OR M332—Middle Rocky Blue Mountains and

Mountian Snake River basin 

and high desert

(14) Upper John Day 17070201 11 OR M332—Middle Rocky Blue Mountains

Mountain and 342—

Intermountain Semidesert

(15) Lower John Day 17070204 16 OR M332—Middle Rocky Columbia basin and

Mountain and 342— Blue Mountains

Intermountain Semidesert

(16) Lower Crooked 17070305 6 OR M332—Middle Rocky Blue Mountains and

Mountain and M242— Snake River basin

Cascade and high desert and

east-side Cascades

slopes and foothills

(17) Upper Deschutes 17070301 10 OR M242—Cascade East-side Cascades

slopes and foothills

(18) Little Deschutes 17070302 6 OR M242—Cascade East-side Cascades

slopes and foothills

(19) Silvies 17120002 4 OR M332—Middle Rocky Blue Mountains and

Mountain Snake River basin

and high desert
17

Table 2—Bailey province and Omernik ecoregion membership of sampled subbasinsa of the midscale ecological assessment of the interior Columbia River basinb (continued)

4th code

Subbasinc HUC Samples State Bailey province Omernik ecoregion

(20) Donner und Blitzen 17120003 4 OR 342—Intermountain Snake River basin

Semidesert and high desert

(21) Crooked Rattlesnake 17050109 7 OR 342—Intermountain Snake River basin

Semidesert and high desert

(22) Lost 18010204 5 OR M261-Sierran East-side Cascades

slopes and foothills

and Snake River

basin and high desert

(22) Lost 18010204 4 CA M261-Sierran East-side Cascades

slopes and foothills

and Snake River

basin and high desert

(23) Upper Klamath Lake 18010203 4 OR M261—Sierran and East-side Cascades

M242—Cascade slopes and foothills

(24) Big Wood 17040219 6 ID 342—Intermountain Northern Rockies and

Semidesert and M332— Snake River basin and

Middle Rocky Mountain high desert

(25) Blackfoot (Montana) 17010203 16 MT M332—Middle Rocky Northern Rockies and

Mountain Montana valley and

Foothill prairies

(26) Bitterroot 17010205 8 MT M332—Middle Rocky Northern Rockies and

Mountain and M333— Montana valley and

Northern Rocky Mountain Foothill prairies

(27) Boise-Mores 17050112 3 ID M332—Middle Rocky Northern Rockies and

Mountain Snake River basin and

high desert

(28) Flint Rock 17010202 7 MT M332—Middle Rocky Northern Rockies and

Mountain Montana valley and

Foothill prairies

(29) Lake Walcott 17040209 9 ID 342—Intermountain Snake River basin and

Semidesert high desert and

Northern Great Basin

and range

(30) Lemhi 17060204 6 ID M332—Middle Rocky Northern Rockies and

Mountain Snake River basin and

high desert

(31) Lochsa 17060303 7 ID M333—Northern Rocky Northern Rockies

Mountain and M332—

Middle Rocky Mountain

(32) Lower Flathead 17010212 14 MT M333—Northern Rocky Northern Rockies and

Mountain Montana valley and

Foothill prairies

(33) Lower Henry’s 17040203 3 ID M331—Southern Rocky Middle Rockies and

Mountain and 342— Snake River basin and

Intermountain Semidesert high desert

(33) Lower Henry’s 17040203 1 WY M331—Southern Rocky Middle Rockies and

Mountain Snake River basin and

high desert
18

Table 2—Bailey province and Omernik ecoregion membership of sampled subbasinsa of the midscale ecological assessment of the interior Columbia River basinb (continued)

4th code

Subbasinc HUC Samples State Bailey province Omernik ecoregion

(34) Medicine Lodge 17040215 5 ID 342—Intermountain Northern Rockies and

Semidesert and M332— Snake River basin and

Middle Rocky Mountain high desert

(35) Palisades 17040104 5 ID M331—Southern Rocky Middle Rockies

Mountain

(35) Palisades 17040104 1 WY M331—Southern Rocky Middle Rockies

Mountain

(36) Snake Headwater 17040101 8 WY M331—Southern Rocky Middle Rockies

Mountain

(37) South Fork Clearwater 17060305 6 ID M332—Middle Rocky Northern Rockies and

Mountain Columbia basin

(38) South Fork Salmon 17060208 7 ID M332—Middle Rocky Northern Rockies

Mountain

(39) Swan 17010211 4 MT M333—Northern Rocky Northern Rockies

Mountain

(40) Upper Owyhee 17050104 12 ID 342—Intermountain Snake River basin 

Semidesert and high desert and 

Northern Great Basin

and range

(41) Upper Coeur d’Alene 17010301 5 ID M333—Northern Rocky Northern Rockies

Mountain

(42) Upper Middle Fork 17060205 9 ID M332—Middle Rocky Northern Rockies

Mountain

(43) Yaak 17010103 4 MT M333—Northern Rocky Northern Rockies

Mountain

a 337 subwatersheds were sampled in 43 subbasins.

b See also figure 3.

c Numbers in parentheses identify subbasins shown in figure 3.
19

Figure 3—Sampled subbasins of the midscale assessment of the interior Columbia River basin (see also table 2). The assessment

area included the portion of the Columbia River basin occurring in the United States east of the crest of the Cascade Range.

Subbasins in the upper reaches of the Klamath River basin and the Northern Great Basin also were included to fully represent

conditions in eastern Oregon and Washington, Idaho, and western Montana.
20

Figure 4—Map groupings of subbasins sampled in the midscale ecological assessment of the interior Columbia River basin.

Subbasins were separated for ease of mapping into 18 groups. Sampled watersheds are shown by subbasin group in figures 

5 to 22.
21

Figure 5—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the Methow

and Wenatchee subbasins of Washington for the midscale ecological assessment of the interior Columbia River basin.
22

Figure 6—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the Kettle,

Sanpoil, and Pend Oreille subbasins of Washington for the midscale ecological assessment of the interior Columbia River basin.
23

Figure 7—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the Upper

Coeur d'Alene and Yaak subbasins of Idaho and Montana for the midscale ecological assessment of the interior Columbia River

basin.
24

Figure 8—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the Lower

Flathead, Swan, and Blackfoot subbasins of Montana for the midscale ecological assessment of the interior Columbia River basin.
25

Figure 9—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the Upper

Yakima, Naches, and Lower Yakima subbasins of Washington for the midscale ecological assessment of the interior Columbia

River basin.
26

Figure 10—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the Palouse

subbasin of Idaho and Washington for the midscale ecological assessment of the interior Columbia River basin.
27

Figure 11—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the

Lochsa, Flint Rock, and Bitterroot subbasins of Idaho and Montana for the midscale ecological assessment of the interior

Columbia River basin.
28

Figure 12—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the Upper

and Lower John Day subbasins of Oregon for the midscale ecological assessment of the interior Columbia River basin.
29

Figure 13—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the Upper

Grande Ronde, Wallowa, and Lower Grande Ronde subbasins of Oregon and Washington for the midscale ecological assessment

of the interior Columbia River basin.
30

Figure 14—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the Burnt

and South Fork Clearwater subbasins of Oregon and Idaho for the midscale ecological assessment of the interior Columbia River

basin.
31

Figure 15—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the Lower

Crooked, Upper Deschutes, and Little Deschutes subbasins of Oregon for the midscale ecological assessment of the interior

Columbia River basin.
32

Figure 16—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the Silvies

and Donner und Blitzen subbasins of Oregon for the midscale ecological assessment of the interior Columbia River basin.
33

Figure 17—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the South

Fork Salmon, Boise-Mores, and Upper Middle Fork Salmon subbasins of Idaho for the midscale ecological assessment of the

interior Columbia River basin.
34

Figure 18—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the Lemhi

and Medicine Lodge subbasins of Idaho for the midscale ecological assessment of the interior Columbia River basin.
35

Figure 19—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the Lower

Henry's, Palisades, and Snake Headwaters subbasins of Idaho and Wyoming for the midscale ecological assessment of the 

interior Columbia River basin. 
36

Figure 20—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the Upper

Klamath Lake and Lost subbasins of Oregon and California for the midscale ecological assessment of the interior Columbia River

basin. 
37

Figure 21—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the

Crooked Rattlesnake and Upper Owyhee subbasins of Oregon, Idaho, and Nevada for the midscale ecological assessment of 

the interior Columbia River basin. 
38

Figure 22—Subwatersheds on USDA Forest Service, Bureau of Land Management, and other ownerships sampled in the Big

Wood and Lake Walcott subbasins of Idaho for the midscale ecological assessment of the interior Columbia River basin.
39

Vegetation Mapping

Landscape ecology is founded primarily on the

notion that landscape structure and composition

strongly influence ecological processes (Forman

and Godron 1986; Li 1990; O’Neill and others

1988; Turner 1989, 1990; Turner and Gardiner

1991; Urban and others 1987). Populations of

terrestrial vertebrate species, for example, differ by

the area and connectivity of their habitats. Thus,

characterizing trends in landscape structural

attributes (both composition and configuration) 

is prerequisite to the study of change in landscape

function. In this study, vegetation was mapped for

recent historical (1930s to 1960s) and existing

conditions (1985 to 1993) to evaluate trends in

spatial patterns of structural attributes. Vegetation

mapping and subsequent spatial analysis relied on

high-quality, comparable (in photo scale and resolution) aerial photography of historical and current vegetation conditions (table 3).

Vegetation patches were delineated to a minimum 

size of 4 ha by using stereo aerial photography,

both color and black and white. Photo scale

ranged from 1:12,000, for recent color resource

photography, to 1:63,360 high-resolution “real

color” or black and white photography. Some

1:30,000 color infrared (Wratten 12 filter) photography also was used where color or black and

white photography was unavailable. Higher

stereoscopic magnification was used with decreasing photo scale to provide comparable resolution

of attributes. Vegetation patches were defined by

using an array of patch attributes (appendix 1)

useful in characterizing (1) vertical and horizontal

structure and composition of vegetation, (2) fuel

conditions, (3) potential fire behavior attributes,

(4) potential smoke production attributes, and (5)

patch and landscape vulnerability to potential

pathogen and insect disturbances.

Following is an abbreviated list of remotely sensed

attributes: (1) total tree crown cover; (2) overstory

tree crown cover; (3) understory tree crown cover,

computed by subtraction; (4) clumpiness of tree

cover; (5) clump density of tree cover; (6) average

clump size of tree cover; (7) degree of crown differentiation among overstory tree crowns; (8)

number of canopy layers; (9) riparian or wetland

status; (10) nonforest type; (11) type of visible

logging entry; (12) overstory size class; (13)

understory size class; (14) overstory species or

species mix; (15) understory species or species

mix; (16) dead tree and snag abundance; (17) elevation belt; and (18) overstory canopy cover of

nonforest types. Items 1-9 and 11-16 were interpreted for forest patches; items 9, 10, and 11, and

17-18 applied to nonforest patches. Items 1-3

were estimated to the nearest 10 percent.

Independent attributes were defined instead of

being directly interpreted structural descriptions,

such as “old-growth” or “ponderosa pine-mature

sawtimber,” so that attributes could be used independently or in combinations for a wider variety

of analyses. Vegetation patches were mapped for

historical and existing conditions by using the

same attributes, standards, equipment, working

conditions, and photointerpreters. Existing conditions were interpreted and mapped first. We

obtained experienced photointerpreters who had

local knowledge of vegetation conditions, landforms, and management history to interpret the

aerial photography and to map and attribute vegetation patches. Photointerpreters were encouraged to field-verify vegetation signatures they were

unsure of, and existing inventory and stand exam

data were consulted, where available, to confirm

visual interpretations.

Vegetation patches were delineated by withinpatch uniformity of structure and composition. 

A single class change of any attribute (appendix 1)

prompted delineation of a new patch, provided

that the 4-ha minimum patch size limitation was

satisfied. Patches were delineated on stereo aerial

photo pairs with the aid of high-quality mirrored

scanning stereoscopes with variable ocular magnification, then transferred to Mylar® overlays on

georeferenced 1:24,000 (7.5-minute quadrangle)

orthophotographs. Apparent riparian vegetation

areas were delineated first within the effective

area19 of each photo pair. Mylar overlay maps

were digitally scanned, edited and edge-matched

by using LTplus raster-to-vector conversion 

19 For any aerial photograph that is one of an overlapping

series in a flight strip among adjacent and overlapping flight

strips, the central part of the photograph, where overlaps with

adjacent photographs occur, enables stereo interpretation.
40

Table 3—Photo years of resource aerial photography used to sample recent historical and current vegetation

conditions of subbasins in the midscale ecological assessment of the interior Columbia River basin

Span, Subbasin percentage Subbasin percentage

Code Subbasin name historical 1930s 1940s 1950s 1960s current 1980s 1990s

BFM Blackfoot (Montana) 1934-53 63 37 1988-90 63 37

BOM Boise-Mores 1962-66 100 1988 100

BTR Bitterroot 1936-58 83 17 1986-87 100

BUR Burnt 1954-60 83 17 1989 100

BWD Big Wood 1943-59 33 67 1988 100

CRT Crooked-Rattlesnake 1954-63 14 86 1989 100

DUB Donner und Blitzen 1958 100 1989 100

FLR Flint Rock 1947 100 1990-91 100

KET Kettle 1944 100 1985-92 40 60

LCR Lower Crooked 1943-51 33 67 1987-91 33 67

LDS Little Deschutes 1943-59 50 50 1988-91 92 8

LFH Lower Flathead 1934-55 86 14 1990 100

LGR Lower Grande Ronde 1939-64 33 44 17 6 1987-91 78 22

LHE Lower Henry's 1941-60 75 25 1991-93 100

LJD Lower John Day 1937-51 50 50 1985-91 88 12

LMH Lemhi 1960 100 1991-93 100

LOC Lochsa 1937-62 29 42 29 1990 100

LST Lost 1942 100 1984 100

LWC Lake Walcott 1950-58 100 1988 100

LYK Lower Yakima 1949 100 1988-91 87 13

MDL Medicine Lodge 1941-60 80 20 1987-93 20 80

MET Methow 1954-56 100 1981-92 18 82

NAC Naches 1938-49 11 89 1991-92 100

PEN Pend Oreille 1932-35 100 1985-86 100

PLS Palouse 1932-51 22 78 1990-92 100

PSD Palisades 1956-60 100 1988-90 33 67

SFC South Fork Clearwater 1959-60 17 83 1991 100

SFS South Fork Salmon 1962 100 1987-88 100

SHW Snake Headwaters 1955-56 100 1987-93 63 37

SIL Silvies 1956 100 1989 100

SPO San Poil 1936-44 50 50 1991-92 100

SWN Swan 1934-54 75 25 1992 100

UCD Upper Coeur d' Alene 1933-55 80 20 1990-91 100

UDS Upper Deschutes 1943-59 30 70 1987-91 20 80

UGR Upper Grande Ronde 1939-55 88 13 1987 100

UJD Upper John Day 1951-56 100 1990-91 100

UKL Upper Klamath Lake 1952-57 100 1985-92 63 37

UMS Upper Middle Fork Salmon 1959-62 11 89 1988-91 44 56

UOW Upper Owyhee 1930-63 8 92 1984-91 67 33

UYK Upper Yakima 1942-59 67 33 1985-92 89 11

WAL Wallowa 1939-56 14 36 50 1980-91 57 43

WEN Wenatchee 1949 100 1992 100

YAA Yaak 1950-63 50 50 1990-92 100

Span,
41

software, and imported into the ARC/INFO GIS

where they were merged with tabular data files.

The final product was a vector ARC/INFO map

coverage with each polygon (patch) coded with

the raw photointerpreted and derived attributes

discussed below (see table 4 for a complete list

and description of interpreted and derived patch

attributes).

Forest vegetation classification—Patch

attributes were interpreted for all forest and range

vegetation in the sampled subwatersheds. Photointerpreted attributes and structural derivations

using those raw attributes provided the basis for

analysis. Patches comprised of agricultural cropland and urban or rural developments were interpreted as nonforest and nonrange but could be

evaluated independently as anthropogenic20 types

when coupled with the raw photointerpreted

nonforest type attribute. Three primary vegetation

attributes were derived from remotely sensed data 

and mapped for all polygons: structural class

(SC), cover type (CT), and potential vegetation

type (PVT), a midscale measure of site potential

and climatic climax vegetation. Structural classes

and cover types of nonforest and nonrange and

anthropogenic types were classified as other.

Forest structure—Oliver and Larson (1990)

describe four stand-development phases: stand

initiation (si), stem exclusion, understory reinitiation (ur), and old growth. We added three

additional structural classes to account for standdevelopment characteristics of interior forest 

conditions with their frequent disturbances (see

also O’Hara and others 1996). We subdivided

Oliver and Larson’s stem-exclusion phase into

open canopy and closed canopy conditions. Forest

patches classified as stem exclusion-open canopy

(seoc) were primarily those where the occurrence

of new tree stems was limited by moisture or was

the result of stocking control, prescribed underburning, or surface fires. Forest patches classified

as stem exclusion-closed canopy (secc) were those

where the occurrence of new tree stems was predominantly limited by light.

We subdivided Oliver and Larson’s old-growth

stage into single-story and multistory conditions.

Old-forest patches classified as single story (ofss)

were those resulting from frequent low-intensity

surface fires, or other management, with large

trees dominating the overstory. Old-forest patches

classified as multistory (ofms) were those lacking

frequent lethal disturbance to overstory or understory vegetation and also had large trees dominating the overstory.

One additional structural class, young-forest 

multistory (yfms) was modeled to represent stand

development resulting from frequent harvest or

lethal disturbance to the overstory. With the addition of these structural classes, we also converted

Oliver and Larson’s (1990) ordered classes to a set

of unordered classes, whose temporal sequence at

a given scale was a function of biophysical environment conditions and disturbance history

(O’Hara and others 1996). Development of forest

structure in the interior West is not the result 

of an ordered sequence of developmental events

but the consequence of often unpredictable disturbances occurring at a variety of scales, broad to

fine, that can either advance or retard succession

by altering composition or structure. We provide

structural class definitions for forest patches in

table 5 and rules for classifying forest structures

from continuous data in table 6. 

Agee (1990, 1993) defines stand-replacing fires 

in the Pacific Northwest as those causing more

than 70 percent mortality of overstory trees. We

defined old-forest structures as those dominated

by large tree structure; that is, ≥ 30 percent crown

cover is displayed by trees larger than 63.5 cm in

diameter at breast height (d.b.h.). Other structural

classes that were not old forest could display up 

to 30 percent crown cover by large trees. We did

so to allow remnant large trees surviving standreplacement fires to be factored into definitions 

of structural classes that were not old forest.

Indeed, many non-old-forest structures that have

experienced mixed-severity or stand-replacement

fires exhibit some characteristics of late successional patches, including large snags, down coarse

woody debris accumulation, and complex understories, even though large trees may not dominate

forest cover.

20 Anthropogenic, as used in this paper, is defined in

Webster’s New Collegiate Dictionary, 1981, G & C Merriam

Co., Springfield, MA as, of, relating to, or influenced by the

impact of man on nature.

Text resumes on page 47
42

Table 4—Photointerpreted and derived patch attributes of sampled subwatersheds in the midscale ecological

assessment of the interior Columbia River basina

Derived or

No. Attribute name Code Description interpreted

1 Area AREA Patch area in square meters D

2 Perimeter PERIMETER Length of patch boundary in meters D

3 Polygon number PGON# Unique polygon (patch) number within each subwatershed I

4 Acres ACRES Patch area expressed in acres D

5 Subbasin SUB_BASIN Subbasin name (see also table 1) I

6 Subwatershed SUBWATERSHED Subwatershed number (6th code HUC number), see figures 3 to 20 I

7 Total crown cover TOTL_CC Total crown cover estimated to the nearest 10 percent, forest patches I

8 Overstory crown cover OS_CC Overstory tree crown cover estimated to the nearest 10 percent, forest patches I

9 Understory crown cover US_CC TOTL_CC minus OS_CC I

10 Clumpiness CLMP Indicates presence of clumpy tree cover, forest patches I

11 Clump density CLMP_DENS Relative density of clumpy tree cover, forest patches I

12 Clump size CLMP_SIZE Average size of tree clumps where tree cover is clumpy, forest patches I

13 Crown differentiation CRWN_DIFF Degree of differentiation among overstory tree crowns, forest patches I

14 Canopy layers CNPY_LYRS Estimated number of tree canopy layers of forest patches, forest patches I

15 Riparian or wetland RIPR_WET Riparian or wetland status, forest or nonforest patches I

16 Nonforest type NON_FRST Nonforest-nonrange or other anthropogenic type I

17 Logging type LOG_TYPE Indicates apparent logging entry and type of harvest, forest patches I

18 Percent in small clearcuts LOG_P_CC Percentage of patch area in small clearcuts estimated to nearest 10 percent I

19 Overstory density DENS_OS Overstory trees/acre taken from inventory data where available, forest patches I

20 Understory density DENS_US Understory trees/acre taken from inventory data where available, forest patches I

21 Overstory size class SIZE_OS Overstory size class, forest patches I

22 Understory size class SIZE_US Understory size class, forest patches I

23 Forest overstory species SPP_OS Overstory species or species mix, forest patches I

24 Forest understory species SPP_US Understory species or species mix, forest patches I

25 Dead trees and snags DEAD_SNAG Dead tree and snag abundance, forest patches I

26 Elevation belt ELEV_BELT Elevation belt of nonforest types I

27 Elevation ELEVATION Elevation class (1,000 ft) that comprises most of the patch area D

28 Aspect ASPECT Aspect class that comprises most of the patch area D

29 Slope SLOPE Slope class that comprises most of the patch area D

30 Elevation percent ELEV_PCT Percentage of patch area in the dominant elevation class D

31 Aspect percent ASPECT_PCT Percentage of patch area in the dominant aspect class D

32 Slope percent SLOPE_PCT Percentage of patch area in the dominant slope class D

33 Nonforest overstory species NON_FRST_SPP_OS Nonforest (range or other) overstory species I

34 Nonforest total canopy cover NON_FRST_TCC Total canopy cover of nonforest types I

35 Nonforest, trees present NON_FRST_TCOV Indicates presence of sparse tree cover in a nonforest patch I

36 Cover type COVER Modeled cover type D

37 Potential vegetation type SERIES Modeled forest or range potential vegetation type (PVT) D

38 Broadscale PVT-code SERIES_CODE Potential vegetation type numeric codes used in broadscale analyses D

39 PVT percent SERIES_PCT Percentage of patch area comprised of modeled D potential vegetation type D

40 Structural class STRUCTURE_2 Modeled structural class D

41 AROS-site quality AROS_SQ Armillaria root disease (AROS)-patch vulnerability factor = site quality D

42 AROS-host abundance AROS_HA Armillaria root disease-patch vulnerability factor = host abundance D

43 AROS-canopy structure AROS_CS Armillaria root disease-patch vulnerability factor = canopy structure D

44 AROS-host age AROS_AGE Armillaria root disease-patch vulnerability factor = host age D

45 AROS-host continuity AROS_C Armillaria root disease-patch vulnerability factor = continuity of host patches D

46 AROS-sum of factor ratings AROS_SUM Armillaria root disease-patch vulnerability factor = sum of factor ratings D

47 AROS-patch rating AROS_HAZ Armillaria root disease-patch vulnerability rating D

48 DFB-site quality DFB_SQ Douglas-fir beetle (DFB)-patch vulnerability factor = site quality D

49 DFB-host abundance DFB_HA Douglas-fir beetle-patch vulnerability factor = host abundance D

50 DFB-canopy structure DFB_CS Douglas-fir beetle-patch vulnerability factor = canopy structure D

51 DFB-host age DFB_AGE Douglas-fir beetle-patch vulnerability factor = host age D

52 DFB-stand density DFB_D Douglas-fir beetle-patch vulnerability factor = stand density D

53 DFB-host continuity DFB_C Douglas-fir beetle-patch vulnerability factor = continuity of host patches D

54 DFB-sum of factor ratings DFB_SUM Douglas-fir beetle-patch vulnerability factor = sum of factor ratings D

55 DFB-patch rating DFB_HAZ Douglas-fir beetle-patch vulnerability rating D

56 AROS-site quality AROS_SQ Armillaria root disease (AROS)-patch vulnerability factor = site quality D

57 AROS-host abundance AROS_HA Armillaria root disease-patch vulnerability factor = host abundance D
43

Table 4—Photointerpreted and derived patch attributes of sampled subwatersheds in the midscale ecological

assessment of the interior Columbia River basina (continued)

Derived or

No. Attribute name Code Description interpreted

58 AROS-canopy structure AROS_CS Armillaria root disease-patch vulnerability factor = canopy structure D

59 AROS-host age AROS_AGE Armillaria root disease-patch vulnerability factor = host age D

60 AROS-host continuity AROS_C Armillaria root disease-patch vulnerability factor = connectivity of host patches D

61 AROS-sum of factor ratigs AROS_SUM Armillaria root disease-sum of factor ratings D

62 AROS-patch rating AROS_HAZ Armillaria root disease-patch vulnerability rating D

63 DFB-site quality DFB_SQ Douglas-fir beetle (DFB)-patch vulnerability factor = site quality D

64 DFB-host abundance DFB_HA Douglas-fir beetle-patch vulnerability factor = host abundance D

65 DFB-canopy structure DFB_CS Douglas-fir beetle-patch vulnerability factor = canopy structure D

66 DFB-host age DFB_AGE Douglas-fir beetle-patch vulnerability factor = host age D

67 DFB-stand density DFB_D Douglas-fir beetle-patch vulnerability factor = stand density D

68 DFB-host continuity DFB_C Douglas-fir beetle-patch vulnerability factor = connectivity of host patches D

69 DFB-sum of factor ratings DFB_SUM Douglas-fir beetle-sum of factor ratings D

70 DFB-patch rating DFB_HAZ Douglas-fir beetle-patch vulnerability rating D

71 DFDM-site quality DFDM_SQ Douglas-fir dwarf mistletoe (DFDM)-patch vulnerability factor = site quality D

72 DFDM-host abundance DFDM_HA Douglas-fir dwarf mistletoe-patch vulnerability factor = host abundance D

73 DFDM-canopy structure DFDM_CS Douglas-fir dwarf mistletoe-patch vulnerability factor = canopy structure D

74 DFDM-host age DFDM_AGE Douglas-fir dwarf mistletoe-patch vulnerability factor = host age D

75 DFDM-host continuity DFDM_C Douglas-fir dwarf mistletoe-patch vulnerability factor = connectivity of host patches D

76 DFDM-sum of factor ratings DFDM_SUM Douglas-fir dwarf mistletoe-sum of factor ratings D

77 DFDM-patch rating DFDM_HAZ Douglas-fir dwarf mistletoe-patch rating D

78 FE-site quality FE_SQ Fir engraver (FE)-patch vulnerability factor = site quality D

79 FE-host abundance FE_HA Fir engraver-patch vulnerability factor = host abundance D

80 FE-canopy structure FE_CS Fir engraver-patch vulnerability factor = canopy structure D

81 FE-host size FE_HS Fir engraver-patch vulnerability factor = host size D

82 FE-stand density FE_D Fir engraver-patch vulnerability factor = stand density D

83 FE-host continuity FE_C Fir engraver-patch vulnerability factor = connectivity of host patches D

84 FE-sum of factor ratings FE_SUM Fir engraver-sum of factor ratings D

85 FE-patch rating FE_HAZ Fir engraver-patch rating D

86 LPDM-site quality LPDM_SQ Lodgepole pine dwarf mistletoe (LPDM)-patch vulnerability factor = site quality D

87 LPDM-host abundance LPDM_HA Lodgepole pine dwarf mistletoe-patch vulnerability factor = host abundance D

88 LPDM-canopy structure LPDM_CS Lodgepole pine dwarf mistletoe-patch vulnerability factor = canopy structure D

89 LPDM-host age LPDM_AGE Lodgepole pine dwarf mistletoe-patch vulnerability factor = host age D

90 LPDM-host continuity LPDM_C Lodgepole pine dwarf mistletoe-patch vulnerability factor = connectivity of 

host patches D

91 LPDM-sum of factor ratings LPDM_SUM Lodgepole pine dwarf mistletoe-sum of factor ratings D

92 LPDM-patch rating LPDM_HAZ Lodgepole pine dwarf mistletoe-patch rating D

93 MPB1-site quality MPB1_SQ Mountain pine beetle type1 (MPB1)-patch D

94 MPB1-host abundance MPB1_HA Mountain pine beetle type1-patch vulnerability factor = host abundance D

95 MPB1-host size MPB1_HS Mountain pine beetle type1-patch vulnerability factor = host size D

96 MPB1-stand density MPB1_D Mountain pine beetle type1 -patch vulnerability factor = stand density D

97 MPB1-stand vigor MPB1_V Mountain pine beetle type1-patch vulnerability factor = stand vigor D

98 MPB1-host continuity MPB1_C Mountain pine beetle type1-patch vulnerability factor = connectivity of host patches D

99 MPB1-sum of factor ratings MPB1_SUM Mountain pine beetle type1-sum of factor ratings D

100 MPB1-patch rating MPB1_HAZ Mountain pine beetle type1-patch rating D

101 MPB2-site quality MPB2_SQ Mountain pine beetle type2 (MPB2)-patch vulnerability factor = site quality D

102 MPB2-host abundance MPB2_HA Mountain pine beetle type2-patch vulnerability factor = host abundance D

103 MPB2-host age MPB2_AGE Mountain pine beetle type2-patch vulnerability factor = host age D

104 MPB2-stand density MPB2_D Mountain pine beetle type2 -patch vulnerability factor = stand density D

105 MPB2-stand vigor MPB2_V Mountain pine beetle type2-patch vulnerability factor = stand vigor D

106 MPB2-host continuity MPB2_C Mountain pine beetle type2-patch vulnerability factor = connectivity of host patches D

107 MPB2-sum of factor ratings MPB2_SUM Mountain pine beetle type2-sum of factor ratings D

108 MPB2-patch rating MPB2_HAZ Mountain pine beetle type2-patch rating D

109 PHEAN-site quality PHEAN _SQ P-group annosum root disease (PHEAN)-patch vulnerability factor = site quality D

110 PHEAN-host abundance PHEAN _HA P-group annosum root disease-patch vulnerability factor = host abundance D

111 PHEAN-canopy structure PHEAN _CS P-group annosum root disease-patch vulnerability factor = canopy structure D

112 PHEAN-host age PHEAN _AGE P-group annosum root disease-patch vulnerability factor = host age D

113 PHEAN-disturbance history PHEAN_DH P-group annosum root disease-patch vulnerability factor = logging disturbance 

history D
44

Table 4—Photointerpreted and derived patch attributes of sampled subwatersheds in the midscale ecological

assessment of the interior Columbia River basina (continued)

Derived or

No. Attribute name Code Description interpreted

114 PHEAN-host continuity PHEAN_C P-group annosum root disease-patch vulnerability factor = connectivity of host patches D

115 PHEAN-sum of factor ratings PHEAN_SUM P-group annosum root disease-sum of factor ratings D

116 PHEAN-patch rating PHEAN_HAZ P-group annosum root disease-patch rating D

117 PHWE-site quality PHWE_SQ Laminated root rot (PHWE)-patch vulnerability factor = site quality D

118 PHWE-host abundance PHWE_HA Laminated root rot-patch vulnerability factor = host abundance D

119 PHWE-canopy structure PHWE_CS Laminated root rot-patch vulnerability factor = canopy structure D

120 PHWE-host age PHWE_AGE Laminated root rot-patch vulnerability factor = host age D

121 PHWE-host continuity PHWE_C Laminated root rot-patch vulnerability factor = connectivity of host patches D

122 PHWE-sum of factor ratings PHWE_SUM Laminated root rot-sum of factor ratings D

123 PHWE-patch rating PHWE_HAZ Laminated root rot-patch vulnerability rating D

124 PPDM-site quality PPDM_SQ Western dwarf mistletoe (PPDM)-patch vulnerability factor = site quality D

125 PPDM-host abundance PPDM_HA Western dwarf mistletoe-patch vulnerability factor = host abundance D

126 PPDM-canopy structure PPDM_CS Western dwarf mistletoe-patch vulnerability factor = canopy structure D

127 PPDM-host age PPDM_AGE Western dwarf mistletoe-patch vulnerability factor = host age D

128 PPDM-host continuity PPDM_C Western dwarf mistletoe-patch vulnerability factor = connectivity of host patches D

129 PPDM-sum of factor ratings PPDM_SUM Western dwarf mistletoe-sum of factor ratings D

130 PPDM-patch rating PPDM_HAZ Western dwarf mistletoe-patch vulnerability rating D

131 RRSR-site quality RRSR_SQ Rust-red stringy rot (RRSR)-patch vulnerability factor = site quality D

132 RRSR-host abundance RRSR_HA Rust-red stringy rot-patch vulnerability factor = host abundance D

133 RRSR-canopy structure RRSR_CS Rust-red stringy rot-patch vulnerability factor = canopy structure D

134 RRSR-host age RRSR_AGE Rust-red stringy rot-patch vulnerability factor = host age D

135 RRSR-disturbance history RRSR_DH Rust-red stringy rot-patch vulnerability factor = logging disturbance history D

136 RRSR-sum of factor ratings RRSR_SUM Rust-red stringy rot-sum of factor ratings D

137 RRSR-patch rating RRSR_HAZ Rust-red stringy rot-patch rating D

138 SB-site quality SB_SQ Spruce beetle (SB)-patch vulnerability factor = site quality D

139 SB-host abundance SB_HA Spruce beetle-patch vulnerability factor = host abundance D

140 SB-topographic setting SB_TS Spruce beetle-patch vulnerability factor = topographic setting D

141 SB-host size SB_HS Spruce beetle-patch vulnerability factor = host size D

142 SB-stand density SB_D Spruce beetle-patch vulnerability factor = stand density D

143 SB-host continuity SB_C Spruce beetle-patch vulnerability factor = connectivity of host patches D

144 SB-sum of factor ratings SB_SUM Spruce beetle-sum of factor ratings D

145 SB-patch rating SB_HAZ Spruce beetle-patch rating D

146 SHEAN-site quality SHEAN_SQ S-group annosum root disease (SHEAN)-patch vulnerability factor = site quality D

147 SHEAN-host abundance SHEAN_HA S-group annosum root disease-patch vulnerability factor = host abundance D

148 SHEAN-canopy structure SHEAN_CS S-group annosum root disease-patch vulnerability factor = canopy structure D

149 SHEAN-host age SHEAN_AGE S-group annosum root disease-patch vulnerability factor = host age D

150 SHEAN-disturbance history SHEAN_DH S-group annosum root disease-patch vulnerability factor = logging disturbance history D

151 SHEAN-host continuity SHEAN_C S-group annosum root disease-patch vulnerability factor = connectivity of host patches D

152 SHEAN-sum of ratings SHEAN_SUM S-group annosum root disease-sum of factor ratings D

153 SHEAN-patch rating SHEAN_HAZ S-group annosum root disease-patch rating D

154 SRBR-site quality SRBR_SQ Schweinitzii root and butt rot (SRBR)-patch vulnerability factor = site quality D

155 SRBR-host abundance SRBR_HA Schweinitzii root and butt rot-patch vulnerability factor = host abundance D

156 SRBR-host age SRBR_AGE Schweinitzii root and butt rot-patch vulnerability factor = host age D

157 SRBR-host continuity SRBR_C Schweinitzii root and butt rot-patch vulnerability factor = connectivity of host patches D

158 SRBR-sum of factor ratings SRBR_SUM Schweinitzii root and butt rot-sum of factor ratings D

159 SRBR-patch rating SRBR_HAZ Schweinitzii root and butt rot-patch rating D

160 TRBR-host abundance TRBR_HA Tomentosus root and butt rot (TRBR)-patch vulnerability factor = host abundance D

161 TRBR-host age TRBR_AGE Tomentosus root and butt rot-patch vulnerability factor = host age D

162 TRBR-topographic setting TRBR_TS Tomentosus root and butt rot-patch vulnerability factor = topographic setting D

163 TRBR-host continuity TRBR_C Tomentosus root and butt rot-patch vulnerability factor = connectivity of host patches D

164 TRBR-sum of factor ratings TRBR_SUM Tomentosus root and butt rot-sum of factor ratings D

165 TRBR-patch rating TRBR_HAZ Tomentosus root and butt rot-patch rating D

166 WLDM-site quality WLDM_SQ Western larch dwarf mistletoe (WLDM)-patch vulnerability factor = site quality D

167 WLDM-host abundance WLDM_HA Western larch dwarf mistletoe-patch vulnerability factor = host abundance D

168 WLDM-canopy structure WLDM_CS Western larch dwarf mistletoe-patch vulnerability factor = canopy structure D

169 WLDM-host age WLDM_AGE Western larch dwarf mistletoe-patch vulnerability factor = host age D

170 WLDM-host continuity WLDM_C Western larch dwarf mistletoe-patch vulnerability factor = connectivity of host patches D

171 WLDM-sum of factor ratings WLDM_SUM Western larch dwarf mistletoe-sum of factor ratings D
45

Table 4—Photointerpreted and derived patch attributes of sampled subwatersheds in the midscale ecological

assessment of the interior Columbia River basina (continued)

Derived or

No. Attribute name Code Description interpreted

172 WLDM-patch rating WLDM_HAZ Western larch dwarf mistletoe-patch rating D

173 WPB1-site quality WPB1_SQ Western pine beetle type1 (WPB1)-patch vulnerability factor = site quality D

174 WPB1-host abundance WPB1_HA Western pine beetle type1-patch vulnerability factor = host abundance D

175 WPB1-host age WPB1_AGE Western pine beetle type1-patch vulnerability factor = host age D

176 WPB1-stand density WPB1_D Western pine beetle type1-patch vulnerability factor = stand density D

177 WPB1-host continuity WPB1_C Western pine beetle type1-patch vulnerability factor = connectivity of host patches D

178 WPB1-sum of factor ratings WPB1_SUM Western pine beetle type1-sum of factor ratings D

179 WPB1-patch rating WPB1_HAZ Western pine beetle type1-patch vulnerability rating D

180 WPB2-site quality WPB2_SQ Western pine beetle type1 (WPB2)-patch vulnerability factor = site quality D

181 WPB2-host abundance WPB2_HA Western pine beetle type1-patch vulnerability factor = host abundance D

182 WPB2-host age WPB2_AGE Western pine beetle type1-patch vulnerability factor = host age D

183 WPB2-stand vigor WPB2_V Western pine beetle type1-patch vulnerability factor = stand vigor D

184 WPB2-stand density WPB2_D Western pine beetle type1-patch vulnerability factor = stand density D

185 WPB2-host continuity WPB2_C Western pine beetle type1-patch vulnerability factor = connectivity of host patches D

186 WPB2-sum of factor ratings WPB2_SUM Western pine beetle type1-sum of factor ratings D

187 WPB2-patch rating WPB2_HAZ Western pine beetle type1-patch vulnerability rating D

188 WPBR1-site quality WPBR1_SQ White pine blister rust (WPBR1)-patch vulnerability factor = site quality D

189 WPBR1-host abundance WPBR1_HA White pine blister rust-patch vulnerability factor = host abundance D

190 WPBR1-host size WPBR1_HS White pine blister rust-patch vulnerability factor = host age D

191 WPBR1-sum of ratings WPBR1_SUM White pine blister rust-sum of factor ratings D

192 WPBR1-patch rating WPBR1_HAZ White pine blister rust-patch vulnerability rating D

193 WPBR2-site quality WPBR2_SQ White pine blister rust (WPBR2)-patch vulnerability factor = site quality D

194 WPBR2-host abundance WPBR2_HA White pine blister rust-patch vulnerability factor = host abundance D

195 WPBR2-host size WPBR2_HS White pine blister rust-patch vulnerability factor = host age D

196 WPBR2-sum of ratings WPBR2_SUM White pine blister rust-sum of factor ratings D

197 WPBR2-patch rating WPBR2_HAZ White pine blister rust-patch vulnerability rating D

198 WSB-site quality WSB_SQ Western spruce budworm (WSB)-patch vulnerability factor = site quality D

199 WSB-host abundance WSB_HA Western spruce budworm-patch vulnerability factor = host abundance D

200 WSB-canopy structure WSB_CS Western spruce budworm-patch vulnerability factor = canopy structure D

201 WSB-host age WSB_AGE Western spruce budworm-patch vulnerability factor = host age D

202 WSB-stand density WSB_D Western spruce budworm-patch vulnerability factor = stand density D

203 WSB-stand vigor WSB_V Western spruce budworm-patch vulnerability factor = stand vigor D

204 WSB-host continuity WSB_C Western spruce budworm-patch vulnerability factor = connectivity of host patches D

205 WSB-sum of factor ratings WSB_SUM Western spruce budworm-sum of factor ratings D

206 WSB-patch rating WSB_HAZ Western spruce budworm-patch rating D

207 Consumption-wet cond. CONS_W Modeled fuel consumption under wet burn conditions D

208 Consumption-dry cond. CONS_D Modeled fuel consumption under dry burn conditions D

209 Consumption-normal cond. CONS_N Modeled fuel consumption under normal or average burn conditions D

210 Intensity-wet cond. INT_W Modeled fireline intensity under wet burn conditions D

211 Intensity-dry cond. INT_D Modeled fireline intensity under dry burn conditions D

212 Intensity-normal cond. INT_N Modeled fireline intensity under normal or average burn conditions D

213 Flame length-wet cond. FLAME_W Modeled flame length under wet burn conditions D

214 Flame length-dry cond. FLAME_D Modeled flame length under dry burn conditions D

215 Flame length-normal cond. FLAME_N Modeled flame length under normal or average burn conditions D

216 Fire rate of spread-wet RATE_W Modeled fire rate of spread under wet burn conditions D

217 Fire rate of spread-dry RATE_D Modeled fire rate of spread under dry burn conditions D

218 Fire rate of spread-normal RATE_N Modeled fire rate of spread under normal or average burn conditions D

219 Risk of crown fire-wet RCF_W Modeled risk of crown fire under wet burn conditions D

220 Risk of crown fire-dry RCF_D Modeled risk of crown fire under dry burn conditions D

221 Risk of crown fire-normal RCF_N Modeled risk of crown fire under normal or average burn conditions D

222 Smoke emissions-wet SMOKE_W Modeled smoke emissions under wet burn conditions D

223 Smoke emissions-dry SMOKE_D Modeled smoke emissions under dry burn conditions D

224 Smoke emissions-normal SMOKE_N Modeled smoke emissions under normal or average burn conditions D

225 Fuel loading FUEL Ground fuel loading D

226 Aerial photo year PHOTO_YEAR Time period of source aerial photography (1930 to 1993) I

a See appendix 1 for descriptions of photointerpreted attributes, and Hessburg and others (in press) for characterization rules for 

modeling patch and landscape vulnerability to pathogen and insect disturbances.
46

Table 5—Descriptions of forest structural classes modeled in the midscale ecological assessment of the 

interior Columbia River basin

Structural class Definition Description

Stand initiation Growing space is reoccupied 1 canopy stratum (may be broken or

following a stand-replacing continuous); 1 cohorta seedlings or

disturbance (e.g., fire, harvest), saplings; grasses, forbs, shrubs may 

typically by early seral species be present with early seral trees

Stem exclusion open canopy Occurrence of new tree stems is 1 broken canopy stratum; 1 cohort;

moisture limited; crowns are open trees excluding new stems through

growing; canopy is broken; may be competition; poles, small, or

maintained by frequent under- medium trees; understory shrubs,

burning or density management grasses, forbs may be present

Stem exclusion closed canopy Occurrence of new tree stems Continuous closed canopy; 1 or

is mostly light limited; crowns more canopy strata; 1 cohort; lower

abrading, canopy is closed strata, if present, are same age as

upper strata; poles, small, or

medium trees; understory shrubs,

grasses, forbs may be present

Understory reinitiation Second cohort established under Broken overstory canopy; ≥ 2

older, typically early seral overstory; canopy strata; 2 cohorts; overstory

mortality in the overstory creates is poles, small, or medium trees;

growing space for new trees in the understory is seedlings, saplings, 

understory or poles

Young-forest multistory Several cohorts have established Broken overstory canopy; > 2

under the influence of management canopy strata; > 2 cohorts; large

or fires with mixed lethal and trees are absent in the overstory;

nonlethal effects, or by insect and stands are characterized by diverse

disease group killing; early seral horizontal and vertical distributions

overstory large trees are generally of trees and tree sizes; seedlings,

absent as a result of harvesting or saplings, poles, small, and medium

other disturbance trees are present

Old-forest multistory Multicohort, multistrata stands with Broken overstory canopy; > 2

large, old trees canopy strata; > 2 cohorts; large

trees dominate in the overstory;

stands are characterized by diverse

horizontal and vertical distributions

of trees and tree sizes; all tree sizes

may be present

Old-forest single story Single-stratum stands of large, old Broken or continuous canopy of

trees. No or few young trees are large, old trees; 1 stratum, may 

present in the understory; parklike be single but usually multicohort; 

conditions resulting from nonlethal large trees dominate the overstory;

natural or prescribed underburning understory absent or seedlings or 

or other management are the saplings; grasses, forbs, or shrubs

dominant feature may be present in the understory

a Trees within a cohort share a common disturbance history; they are those initiated or released after a disturbance (natural or

artificial). Tree ages within a cohort may span several decades.
47

Forest composition—Existing vegetation cover

attributes were classified into cover types. Cover

types were estimated from overstory and understory species composition and total overstory and

understory crown cover attributes. Both pure and

mixed species cover conditions (appendix 1) were

interpreted for forest patches. Cover types were

based on the overstory species attribute when

overstory crown cover was ≥ 30 percent. Understory species composition determined the cover

type when overstory crown cover was ≤ 20 percent and understory crown cover exceeded overstory crown cover.

Forest cover type classes were modeled according

to Society of American Foresters (SAF) forest

cover type definitions (Eyre 1980). To facilitate

comparison of results, forest cover type classes 

of the midscale assessment were closely matched

with cover type classes used in the broad-scale

assessment of the basin (see Hann and others

1997). Examples of forest cover types of midscale

subwatersheds are ponderosa pine (SAF 237),

western larch (SAF 212), lodgepole pine (SAF

218), interior Douglas-fir (SAF 210), and

Engelmann spruce-subalpine fir (SAF 206). We

classified 17 forest cover types. We provide rules

for modeling all midscale forest cover types from

remotely sensed cover attributes in table 7. Common and scientific names and abbreviations of

species discussed in the text and tables are listed

in table 8. 

Cover type and structural class items were attributed to each patch; the type assigned to each

patch was the doublet of its cover type and 

structural class. Examples of patch types are

Douglas-fir-stand initiation, western larch-stem

exclusion-closed canopy, and ponderosa pine-old

forest-single story. In subsequent analysis, these

patch types become the unique elements of the

landscape mosaic and are the focus of change

analyses. 

Forest potential vegetation types—Environments highly similar in climate attributes, geology, landforms, and geomorphic and hydrologic

Table 6—Classification rules for forest structural classes modeled for sampled subwatersheds in the midscale

ecological assessment of the interior Columbia River basin

No. Structural class (code) Classification rule

1 Stand initiation (si) LgT_cca < 30 percent (i.e., = 0, 10, or 20 percent) and SSb_cc ≥ 10 percent and {[PT_cc 

+ SmT_cc + MedT_cc < 20 percent] or [PT_cc + SmT_cc + MedT_cc ≤ 60 percent and 

PT_cc + SmT_cc + MedT_cc ≥ 20 percent and SmT_cc + MedT_cc < 10 percent]}

2 Stem exclusion open LgT_cc < 30 percent (i.e., = 0, 10, or 20 percent) and SS_cc < 10 percent and PT_cc 

canopy (seoc) + SmT_cc + MedT_cc ≤ 70 percent

3 Stem exclusion closed LgT_cc < 30 percent (i.e., = 0, 10, or 20 percent) and SS_cc < 10 percent and PT_cc 

canopy (secc) + SmT_cc + MedT_cc > 70 percent

4 Understory reinitiation LgT_cc < 30 percent (i.e., = 0, 10, or 20 percent) and SS_cc ≥ 10 percent and PT_cc 

(ur) + SmT_cc + MedT_cc > 60 percent

5 Young-forest multistory LgT_cc < 30 percent (i.e., = 0, 10, or 20 percent) and SS_cc ≥ 10 percent and PT_cc 

(yfms) + SmT_cc + MedT_cc ≤ 60 percent and SmT_cc ≥ 10 percent or MedT_cc ≥ 10 percent

6 Old-forest multistory LgT_cc ≥ 30 percent and SS_cc + PT_cc + SmT_cc + MedT_cc > 20 percent

(ofms)

7 Old-forest single story LgT_cc ≥ 30 percent and SS_cc + PT_cc + SmT_cc + MedT_cc ≤ 20 percent

(ofss)

a cc = crown cover; crown cover was interpreted in 10-percent increments and class percentages were expressed as midpoints;

e.g., 10 percent = 5 to 14 percent, 20 percent = 15 to 24 percent.

b Tree sizes were estimated as SS–seedlings and saplings (< 12.7 cm d.b.h.), PT–poles (12.7 to 22.6 cm d.b.h.), SmT–small

trees (22.7 to 40.4 cm d.b.h.), MedT–medium trees (40.5 to 63.5 cm d.b.h.), and LgT–large trees (> 63.5 cm d.b.h.).

Text resumes on page 52
48

Table 7—Classification rules for forest cover types modeled for sampled subwatersheds in the midscale 

ecological assessment of the interior Columbia River basin

SAF cover 

Forest cover type type(s) Overstory species compositiona Understory species compositionb

Ponderosa pine SAF 237 Ponderosa pine,c ponderosa pine-Douglas-fir Grass-forb, shrub, bare ground, ponderosa 

pine, ponderosa pine-Douglas-fir 

Western larch SAF 212 Western larch, western larch-lodgepole pine, Grass-forb, shrub, or bare ground, western 

western larch-lodgepole pine-western larch-lodgepole pine

white pine, western larch-ponderosa pine, 

western larch-Engelmann spruce, western 

larch-western white pine

Lodgepole pine SAF 218 Lodgepole pine, lodgepole pine-Engelmann Grass-forb, shrub, bare ground, lodgepole 

spruce, lodgepole pine-white fir pine, lodgepole pine-Engelmann spruce, 

lodgepole pine-white fir, lodgepole pineponderosa pine

Douglas-fir SAF 210 Douglas-fir, Douglas-fir-western larch, Grass-forb, shrub, bare ground, DouglasDouglas-fir-aspen, Douglas-fir-western fir-western larch, Douglas-fir-lodgewhite pine, Douglas-fir-lodgepole pine, pole pine

Douglas-fir-grand fir 

Grand fir or white SAF 211 Grand fir or white fir, grand fir-Engelmann Grass-forb, shrub, bare ground, 

fir, or both SAF 213 spruce, grand fir-ponderosa pine, grand fir or white fir, grand fir-Douglas-fir 

grand fir-subalpine fir, incense-cedar,d white fir-Douglas-fir incense-cedar

grand fir-western white pine, grand firwestern larch

Pacific silver fir SAF 226 Pacific silver fir, noble fir Grass-forb, shrub, bare ground, Pacific

silver fir-grand fir, Pacific silver firDouglas-fir, Pacific silver fir

Engelmann spruce SAF 206 Engelmann spruce-subalpine fir, Grass-forb, shrub, bare ground, Engelmann

or subalpine fir, Engelmann spruce-Douglas-fir, spruce- subalpine fir, Engelmann spruceor both subalpine fir-Douglas-fir Douglas-fir

subalpine fir-western white pine, 

subalpine fir-lodgepole pine

Western hemlock SAF 224 Western hemlock or western redcedar Grass-forb, shrub, bare ground, western

or western redcedar, SAF 227 hemlock or western redcedar

or both SAF 228

Mountain hemlock SAF 205 Mountain hemlock, mountain hemlock- Grass-forb, shrub, bare ground, mountain

Douglas-fir, mountain hemlock-white fir, hemlock, mountain hemlock-Douglas-fir, 

incense-cedare mountain hemlock-white fir, mountain 

hemlock-lodge pole pine

Whitebark pine or SAF 208 Whitebark pine or subalpine larch, Grass-forb, shrub, bare ground, whitebark 

subalpine larch, subalpine fir-subalpine larch pine or subalpine larch

or both

Western white pine SAF 215f Western white pine or sugar pine, Grass-forb, shrub, bare ground, 

or sugar pine, sugar pine-subalpine fir-ponderosa pine western white pine and/or sugar pine

or both

Aspen-cottonwood- SAF 217 Hardwoods, maple, birch, aspen, Grass-forb, shrub, bare ground, hardwoods,

willow SAF 222 cottonwood, aspen-lodgepole pine maple, birch, aspen, cottonwood

SAF 235

SAF 233
49

Table 7—Classification rules for forest cover types modeled for sampled subwatersheds in the midscale 

ecological assessment of the interior Columbia River basin (continued)

SAF cover 

Forest cover type type(s) Overstory species compositiona Understory species compositionb

Western or Rocky SAF 238 Juniper Grass-forb, shrub, bare ground, juniper

Mountain juniper SAF 220

Shasta red fir SAF 207 Shasta red fir Grass-forb, shrub, bare ground, Shasta red 

fir

Pinyon-juniper SAF 239 Pinyon pine-juniper, pinyon pine Grass-forb, shrub, bare ground, pinyon 

pine-juniper, pinyon pine

Russian olive n/a Russian olive Grass-forb, shrub, bare ground

Limber pine SAF 219 Limber pine, limber pine-Douglas-fir, Grass-forb, shrub, bare ground, 

limber pine-subalpine fir limber pine, limber pine-Douglas-fir

a Compositions occurred in pure and mixed types. To be named in a photointerpreted overstory or understory species mix, a

species represented at least 20 percent of the total crown cover.

b Cover type classification of any forest patch was based on the photointerpreted overstory species attribute when overstory

crown cover was ≥ 30 percent. Understory species composition determined the cover type when overstory crown cover was

≥ 20 percent and understory crown cover was greater than overstory crown cover.

c Common and scientific names, and abbreviations of species discussed in the text and tables are listed in table 8.

d Forest patches with incense-cedar occurring as the dominant overstory species in combination with an understory species mix

of Douglas-fir-grand fir or Douglas-fir-white fir were classified to a grand fir-white fir cover type.

e Forest patches with incense-cedar occurring as the dominant overstory species in combination with an understory species of

mountain hemlock, mountain hemlock-white fir, or mountain hemlock-lodgepole pine were classified to a mountain hemlock

cover type.

f SAF 215 occurs only in Idaho, Montana, and Washington. The SAF (Eyre 1980) does not provide an explicit cover type for

sugar pine. Sugar pine is included in the mixed conifer types of the Sierra, Siskiyou, and Cascades ranges of southern Oregon

and California.

Table 8—Common and scientific names, and abbreviations of species

Common name Abbreviation Scientific name

Pathogens:

Annosum root disease HEAN Heterobasidion annosum (Fr.) Bref.

Armillaria root disease AROS Armillaria ostoyae (Romag.) Herink

Douglas-fir dwarf mistletoe DFDM Arceuthobium douglasii Engelm.

Laminated root rot PHWE Phellinus weirii (Murr.) Gilb.

Lodgepole pine dwarf mistletoe LPDM Arceuthobium americanum Nutt. ex Engelm.

P-group annosum root disease HEANp Heterobasidion annosum (Fr.) Bref.

Rust-red stringy rot (Indian paint fungus) RRSR Echinodontium tinctorium E. & E.

Schweinitzii root and butt rot SRBR Phaeolus schweinitzii (Fr.) Pat.

S-group annosum root disease HEANs Heterobasidion annosum (Fr.) Bref.

Tomentosus root and butt rot TRBR Inonotus tomentosus (Fr.) Teng.

Western dwarf mistletoe PPDM Arceuthobium campylopodum Engelm.

Western larch dwarf mistletoe WLDM Arceuthobium laricis (Piper) St. John 

White pine blister rust WPBR Cronartium ribicola Fisch.

Insects:

Douglas-fir beetle DFB Dendroctonus pseudotsugae Hopkins

Douglas-fir tussock moth DFTM Orgyia pseudotsugata (McDonnough)

Fir engraver FE Scolytus ventralis LeConte

Mountain pine beetle MPB Dendroctonus ponderosae Hopkins

Spruce beetle SB Dendroctonus rufipennis (Kirby)

Western pine beetle WPB Dendroctonus brevicomis LeConte

Western spruce budworm WSB Choristoneura occidentalis Freeman
50

Table 8—Common and scientific names, and abbreviations of species (continued)

Common name Abbreviation Scientific name

Trees:

Birch— Birch Betula spp.

Bog birch BEGL B. glandulosa Michx.

Paper birch BEPA B. papyrifera Marsh.

Water birch BEOC B. occidentalis Hook.

Blue spruce PIPU Picea pungens Engelm.

Cottonwood— Cottonwood Populus spp.

Black cottonwood POTRI P. trichocarpa Torr. & Gray.

Narrow-leaved cottonwood POAN P. angustifolia James

Douglas-fir PSME Pseudotsuga menziesii (Mirb.) Franco

Engelmann spruce PIEN Picea engelmannii Parry ex Engelm.

Grand fir ABGR Abies grandis (Dougl. ex D. Don) Lindl.

Hemlocks Tsuga spp.

Incense-cedar CADE Libocedrus decurrens Torr.

Juniper— Juniper Juniperus spp.

Rocky Mountain juniper JUSC J. scopulorum Sarg.

Utah juniper JUOS J. osteosperma (Torr.) Little

Western juniper JUOC J. occidentalis Hook.

Limber pine PIFL Pinus flexilis James

Lodgepole pine PICO Pinus contorta var. latifolia Engelm.

Maple— Maple Acer spp.

Bigleaf maple ACMA A. macrophyllum Pursh

Bigtooth maple ACGR A. grandidentatum Nutt.

Douglas maple ACGLDO A. glabrum var. douglasii (Hook.) Dippel

Rocky Mountain maple ACGLGL A. glabrum var. glabrum Torr.

Vine maple ACCI A. circinatum Pursh

Mountain hemlock TSME Tsuga mertensiana (Bong.) Carr.

Noble fir ABPR Abies procera Rehd.

Pacific silver fir ABAM A. amabilis Dougl. ex Forbes

Pinyon pine PIMO2 Pinus monophylla Torr. & Frem.

Ponderosa pine PIPO P. ponderosa Dougl. ex Laws.

Quaking aspen Aspen Populus tremuloides Michx.

Russian olive ELAN Elaeagnus angustifolia L.

Shasta red fir ABMA Abies magnifica A. Murr.

Subalpine fir ABLA2 A. lasiocarpa (Hook.) Nutt.

Sugar pine PILA Pinus lambertiana Dougl.

True firs Abies spp.

Western hemlock TSHE Tsuga heterophylla (Raf.) Sarg.

Western larch LAOC Larix occidentalis Nutt.

Western redcedar THPL Thuja plicata Donn ex D. Don

Western white pine PIMO Pinus monticola Dougl. ex D. Don

Whitebark pine PIAL P. albicaulis Engelm.

White fir ABCO Abies concolor (Gord. & Glend.) Lindl.

White spruce PIGL Picea glauca (Moench) Voss

Shrubs:

Alder— Alder Alnus spp. 

Basin big sagebrush ARTRTR Artemisia tridentata var. tridentata Nutt.

Bitterbrush PUTR Purshia tridentata (Pursh)

Bittercherry PREM Prunus emarginata (Dougl.) Walp. 

Bog birch BEGL Betula glandulosa Michx.

Common chokecherry PRVI Prunus virginiana L.

Common snowberry SYAL Symphoricarpos albus (L.) Blake

Currant Ribes spp.

Curlleaf mahogany CELE Cercocarpus ledifolius Nutt.
51

Table 8—Common and scientific names, and abbreviations of species (continued)

Common name Abbreviation Scientific name

Dogwood— Cornus spp.

Red-osier dogwood COST C. stolonifera Michx.

Dwarf sagebrush ARNO Artemisia nova Nutt.

Greasewood SAVE Sarcobatus vermiculatus (Hook.) Torr.

Long-leaved sagebrush ARLO Artemisia longifolia Nutt.

Low sagebrush ARAR Artemisia arbuscula Nutt.

Mallow ninebark PHMA Physocarpus malvaceus (Greene) Kuntze

Mountain big sagebrush ARTRVA Artemisia tridentata var. vaseyana Nutt.

Mountain heather Heather Phyllodoce spp. 

Mountain-mahogany CEMO Cercocarpus montanus Raf.

Mountain snowberry SYOR Symphoricarpos oreophilus Gray

Rabbitbrush Chrysothamnus spp.

Rose Rosa spp.

Russet buffaloberry Buffaloberry Sheperdia canadensis (L.) Nutt.

Salt desert shrub— Salt desert shrub

Greasewood SAVE Sarcobatus vermiculatus (Hook.) Torr.

Spiny hopsage GRSP Grayia spinosa

Spiny saltbush, shadscale ATCO Atriplex confertifolia (Torr. & Frem.) Wats.

Winterfat EULA Eurotia lanata (Pursh)

Scouler’s willow SASC Salix scouleriana Barratt

Serviceberry— Amelanchier spp.

Western serviceberry AMAL A. alnifolia Nutt.

Silver sagebrush ARCA Artemisia cana Pursh

Snowberry Snowberry Symphoricarpus spp.

Stiff sagebrush ARRI Artemisia rigida (Nutt.) Gray

Threetip sagebrush ARTRI A. tripartita Rydb.

Willow— Willow Salix spp.

Booth willow SABO S. boothii Bebb

Geyer willow SAGE S. geyeriana Anderss.

Hoary willow SACA S. candida Fluegge

Wolf’s willow SAWO S. wolfii Bebb

Wyoming big sagebrush ARTRWY Artemisia tridentata var. wyomingensis Nutt

Grasses and forbs:

Alkaligrass Pucinellia spp.

Alkali saltgrass DIST Distichlis stricta (Torr.) Rydb.

Arrowleaf balsamroot BASA Balsamorhiza sagitata (Pursh) Nutt.

Bluebunch wheatgrass AGSP Agropyron spicatum (Pursh) Scribn. & Smith

Bluejoint reedgrass CACA Calamagrostis canadensis (Michx.) Beauv.

Bluestem wheatgrass AGSM Agropyron smithii Rybd.

Bottlebrush squirreltail SIHY Sitanion hystrix (Nutt.) Smith

California brome-grass BRCA Bromus carinatus H. & A.

Cheat grass BRTE B. tectorum L.

Crested wheatgrass AGCR Agropyron cristatum (L.) Gaertn.

Cusick’s milkvetch ASCU Astragalus cusickii Gray

Douglas’ water-hemlock CIDO Cicuta douglasii (D.C.) Coult. & Rose

Fowl bluegrass POPA Poa palustris L.

Geyer’s sedge CAGE Carex geyeri Boott

Giant wildrye ELCI Elymus cinereus Scribn. & Merr.

Green fescue FEVI Festuca viridula Vasey

Hood’s sedge CAHO Carex hoodii Boott 

Hounds-tongue hawkweed HICY Hieracium cynoglossoides Arv.-Touv.
processes display similar area and distribution of

PVTs. In this study, we modeled and mapped forest potential vegetation types to better frame our

presentation and discussion of vegetation change

and to provide a basis to compare changes occurring in similar PVTs in differing geographic locations. Forest PVTs were modeled at approximately

the series level, as that level has been described in

habitat type and plant association classifications

throughout the Western United States. The dominant climatic “climax” coniferous species of each

forest patch was estimated by using remotely

sensed historical and current overstory and understory species composition and elevation, slope,

and aspect coverages generated from 90-m digital

elevation models of the sampled subbasins.

We created a complex vector map coverage for

each sampled subwatershed based on the intersection of a topographic theme, the current remotely

sensed vegetation coverage, and the historical vegetation coverage. The topographic theme included

elevation and aspect coverages constructed from

90-m DEMs. Elevation and aspect classification

rules are shown in tables 9 and 10, respectively.

Each polygon was assigned a uniform elevation

class (table 9) and a uniform aspect class (table

10). Each polygon in the complex coverage was

attributed by elevation class, aspect class, modal

slope, and each of the current and historical

remotely sensed attributes. Data were exported

from ARC/INFO to Paradox for analysis.

52

Table 8—Common and scientific names, and abbreviations of species (continued)

Common name Abbreviation Scientific name

Idaho fescue FEID Festuca idahoensis Elmer

Kentucky bluegrass POPR Poa pratensis L.

Leafy spurge EUES Euphorbia esula L.

Medusahead TACA Taeniatherum caput-medusae L.

Narrow-leaved skullcap SCAN Scutellaria angustifolia Pursh

Needlegrass STCO Stipa comata Trin. & Rupr.

Prairie junegrass KOCR Koeleria cristata Pers.

Red threeawn ARLO Aristida longiseta Steud.

Richardson’s needlegrass STRI Stipa richardsonii Link 

Rough fescue FESC Festuca scabrella Torr.

Rushes— Rushes Juncus spp.

Baltic rush JUBA J. balticus Willd.

Salmon River phlox PHCO Phlox colubrina Wherry & Const.

Sand dropseed SPCR Sporobolus cryptandrus (Torr.) Gray

Sandberg’s bluegrass POSA Poa sandbergii Vasey

Sedges— Sedges Carex spp.

Beaked sedge CARO C. rostrata Stokes

Short-beaked sedge CASI C. simulata Mack.

Small-winged sedge CAMI C. microptera Mack.

Nebraska sedge CANE C. nebrascensis Dewey

Water sedge CAAQ C. aquatilis Wahl.

Shaggy fleabane ERPU Erigeron pumilis Nutt.

Silky lupine LUSE Lupinus sericeus Pursh

Spotted knapweed CEMA Centaurea maculosa Lam.

Spurred lupine LULA Lupinus laxiflorus Dougl.

Starvation cactus OPPO Opuntia polyacantha Haw.

Thread-leaved sedge CAFI Carex filifolia Nutt.

Thurber’s needlegrass STTH Stipa thurberiana Piper

Timber oatgrass DAIN Danthonia intermedia Vasey

Tufted hairgrass DECA Deschampsia caespitosa (L.) Beauv.

Wildrye Wildrye Elymus spp.

Wyeth buckwheat ERHI Erigonum heracleoides Nutt. 

Yellowstar thistle CESO Centaurea solstitialis L. 
53

Potential vegetation analysis was done separately

for each subbasin; it involved three modeling

steps and a final map-review step. First, attribute

combinations were used to provisionally assign a

likely PVT. Assignments generally were based on

overstory and understory species identities (historical and current), but other attributes such as elevation, slope, aspect, presence of visible logging,

and riparian or wetland status, also were used.

These rules were effective for determining the forest PVT for polygons in dry, moist, or cold forest

environmental settings. They were not immediately useful in classifying PVTs for forest polygons

with vegetation dominated by early seral species.

For example, the presence of mountain hemlock

in either the overstory or understory (current or

historical) was sufficient to assign a polygon to

the mountain hemlock PVT. But in subwatersheds of the northern Cascade Range of

Washington, polygons with Douglas-fir as the

principal cover species were not assigned a PVT 

at this step because Douglas-fir can be early seral,

midseral, or climax depending on ecological site

conditions. These types of polygons were processed in subsequent steps.

In the second step, probability rules were developed from PVT assignments made in step 1 for

all possible elevation and aspect class combinations. We tallied the area of all assigned polygons

by PVT within combined elevation and aspect

classes and calculated the proportion of the total

assigned area within a subbasin comprised of each

PVT-elevation-aspect class combination. Unassigned polygons were then assigned a probable

PVT based on elevation, aspect, and occasionally,

early seral species identity and the result of a uniform random number generator. The PVT labels

for this step differed from those assigned in step 1

so that assignments in either step could be revisited. For example, in a particular subbasin with the

combination of elevation class = 3 and aspect class

= 1, the western hemlock-western redcedar PVT

occupied 50 percent of the assignable subbasin

area in step 1, the subalpine fir-Engelmann spruce

PVT occupied 25 percent of the assignable area,

and the Douglas-fir–white fir–grand fir PVT

occupied 25 percent of the assignable area. These

PVTs were assigned ranges of 1-50, 51-75, and

76-100, respectively. A random draw of 33

assigned an unassigned polygon of the same elevation-aspect class identity to the western hemlockwestern redcedar PVT in step 2.

Several PVTs were defined at a series-group level

(for example, the Douglas-fir–grand fir–white fir

PVT, the western hemlock-western redcedar PVT,

and the subalpine fir-Engelmann spruce PVT)

because of the limited resolution of remotely

sensed data. In step 3, these series-groups were

split into cool-moist and warm-dry subgroups by

using elevation and aspect rules derived from

published species distributions and plant association and habitat type manuals. A third cold-harsh

Table 9—Elevation classes used to model forest

potential vegetation types in the midscale ecological

assessment of the interior Columbia River basin

Elevation range

Class Minimum Maximum

Meters above sea level 

1 0 304.8

2 304.9 609.6

3 609.7 914.4

4 914.5 1219.2

5 1219.3 1524.0

6 1524.1 1828.8

7 1828.9 2133.6

8 2133.7 2438.4

9 2438.5 2743.2

10 2743.3 3048.0

11 3048.1 3352.8

12 3352.9 3657.6

13 3657.7 3962.4

Table 10—Aspect classes used to model forest

potential vegetation types in the midscale ecological assessment of the interior Columbia River basin

Aspect classa Aspect Range

-1 None Flat, slope less than 1 percent

1 N 351° to 80°a

2 E 81° to 170°

3 S 171° to 260°

4 W 261° to 350°

a All aspect values relative to true north.
subgroup was identified for the subalpine firEngelmann spruce PVT where elevation and

aspect conditions warranted. Once these three

steps were completed, an initial PVT map of the

subbasin was made. This was checked for reasonable pattern, location, and setting of PVTs. Step 2

above often would result in odd polygon assignments that became obvious when displayed on a

map. These were manually converted to the type

of the surrounding matrix. Many polygons were

small slivers resulting from initial creation of the

complex topographic theme. A smoothing algorithm was applied in ARC/INFO to merge these

slivers into larger adjacent units. Polygon boundaries were dissolved to homogeneous PVT areas,

and this became the final PVT map for the subbasin.

Forest PVTs of midscale subbasins were ponderosa pine, Douglas-fir–grand fir (or Douglasfir–white fir), western hemlock-western redcedar,

Pacific silver fir, mountain hemlock, subalpine firEngelmann spruce, whitebark pine-subalpine

larch, Shasta red fir, western juniper-Rocky

Mountain juniper, quaking aspen, Oregon white

oak, and edaphic lodgepole pine. A complete set

of classification rules for midscale forest PVT by

subbasin is provided in Smith and others (in

prep.). Time and resources did not allow field 

verification of forest PVTs in each subbasin, but

remotely sensed overstory and understory species

composition data were checked against inventory

and stand exam plot data where available.

54

Table 11—Descriptions of herbland and shrubland structure classes modeled for sampled subwatersheds in

the midscale ecological assessment of the interior Columbia River basin

Structural class Definition Description

Open herblanda Open canopy herbaceous A canopy of herbaceous vegetation with < 66 percent 

vegetation projected canopy cover; < 10 percent cover each of shrubs 

or trees; ≥ 1 stratum

Closed herblandb Closed canopy herbaceous A canopy of herbaceous vegetation with ≥ 66 percent 

vegetation projected canopy cover; < 10 percent cover each of shrubs 

or trees; ≥ 1 stratum

Open low-medium Dominated by an open A canopy of low (<50 cm) or medium-sized (50 cm to 2 m)

shrublandc d canopy of low or shrubs with < 66 percent projected canopy cover; shrubs

medium-sized shrubs dominate; tree cover < 10 percent; ≥ 2 strata, ≥ 2 cohorts 

possible

Closed low-medium Dominated by a closed A canopy of low (< 50 cm) or medium-sized (50 cm to 2 m)

shrublandc d canopy of low or shrubs with ≥ 66 percent projected canopy cover; shrubs 

medium-sized shrubs dominate; tree cover < 10 percent; ≥ 2 strata, ≥ 2 cohorts 

possible

Open tall shrublande Dominated by an open A canopy of tall (2 m to 5 m) shrubs with < 66 percent 

canopy of tall shrubs projected canopy cover; shrubs dominate; tree cover < 10 

percent; ≥ 2 strata, ≥ 2 cohorts possible

Closed tall shrublande Dominated by a closed A canopy of tall (2 m to 5 m) shrubs with ≥ 66 percent 

canopy of tall shrubs projected canopy cover; shrubs dominate; tree cover < 10 

percent; ≥ 2 strata, ≥ 2 cohorts possible

a Open: a canopy with < 66 percent projected canopy cover as remotely sensed by photointerpretation. The 66-percent canopy

cover threshold separating open and closed structures does not numerically correspond with canopy cover estimates for open

and closed conditions derived by using frame, point sampling, or line intercept survey methods.

b Closed: a canopy with 66 percent projected canopy cover.

c Low shrubs: shrubs that typically do not exceed 50 centimeters in height.

d Medium shrubs: shrubs > 50 centimeters tall and < 2 meters tall.

e Tall shrubs: shrubs > 2 meters tall but < 5 meters tall.
55

Range vegetation classification—

Herbland and shrubland structure—

Structural classes of herbland and shrubland vegetation patches were based on overstory species

composition, canopy cover of overstory species,

and the stature of overstory species. Herbland and

shrubland structure classes were open herbland,

closed herbland, open low-medium shrubland,

closed low-medium shrubland, open tall shrubland, and closed tall shrubland. We provide

descriptions of herbland and shrubland structural

classes in table 11; rules for classifying midscale

herbland and shrubland structure classes from

remotely sensed cover attributes are in table 12. 

Herbland and shrubland composition—In

addition to classifying herbland and shrubland

structural classes, we classified dominant cover

types. Dominant cover was estimated from nonforest overstory species, total canopy cover of

nonforest types, and elevation belt attributes.

Herbland and shrubland cover types were

described for colline, montane (lower and upper

montane), and subalpine-alpine elevation settings.

Both pure and mixed species cover conditions

were interpreted for herbland and shrubland

patches. Modeled cover types were bunchgrasses,

exotic grasses and forbs, moist herbs, low and

medium shrubs, tall shrubs, tall mountain shrubs,

wet-site shrubs, and subshrubs. Table 13 provides

classification rules for herbland and shrubland

cover types.

Table 12—Classification rules for herbland and shrubland structural classes modeled for sampled subwatersheds in the midscale ecological assessment of the interior Columbia River basin

Overstory canopy cover

Structural class Nonforest (herbland or shrubland) overstory speciesa (photointerpreted)

Percent 

Open herbland Native bunchgrasses (fescues, wildrye), annual grasses ≤ 66

(cheatgrass, medusahead), seeded wheatgrasses (crested 

wheatgrass), exotic forbs (knapweeds, leafy spurge, thistles), 

native moist site herbs (sedges, rushes)

Closed herbland Same as open herbland > 66 

Open low-medium shrubland Low sagebrushes (black sage, low sage), salt desert shrub, ≤ 66

low alpine shrubs (heathers), big sagebrushes (basin big sage, 

Wyoming sage), bitterbrush rabbitbrush

Closed low-medium shrubland Same as open low-medium shrubland > 66

Open tall shrubland Mountain-mahogany, curlleaf mahogany ≤ 66 

Closed tall shrubland Same as open tall shrubland > 66 

Open tall mountain shrubland Serviceberry, rose, snowberry, mountain maple, ≤ 66

Scouler's willow, buffaloberry, chokecherry, bittercherry, 

other mountain shrubs

Closed tall mountain shrubland Same as open tall mountain shrubland > 66 

Open wet-site tall shrubland Willow, alder, bog birch, dogwood, other wet-site, shrubs ≤ 66 

Closed wet-site tall shrubland Same as open wet-site tall shrubland > 66 

Open low subshrubs Beargrass ≤ 66 

Closed low subshrubs Same as open low subshrubs > 66 

a Refer also to appendix 1 for examples of nonforest (herbland and shrubland) overstory species representative of each photointerpreted grouping.
Woodlands—The woodland physiognomy was

classified for juniper, pinyon-juniper, and Oregon

white oak cover types only. For data capture purposes, photointerpretation initially treated forest

and woodland physiognomies as forest if total tree

crown of any patch was at least 10 percent. This

enabled us to obtain tree crown cover and overstory tree species information for both woodland

and forest structure classifications. Woodland

structure classification followed a logic similar to

that used for forest structural classes (see table 6).

Structure classes for woodland were stand initiation, stem exclusion, understory reinitiation,

young multistory, old multistory, and old single

story. Rules for classifying woodland structures

from continuous data are provided in table 14.

Herbland, shrubland, and woodland potential vegetation types—The PVTs of herbland,

shrubland, and woodland physiognomic conditions were modeled as broad habitat-type groups.

The dominant “climax” species of each rangeland

patch was estimated from remotely sensed attributes, digital elevation data, published range cover

type definitions, Bailey’s province and section

56

Table 13—Classification rules for herbland and shrubland cover types modeled for sampled subwatersheds

in the midscale ecological assessment of the interior Columbia River basin

Elevation belt(s) Herbland or shrubland overstory speciesa Cover type

Colline Native bunchgrasses (fescues, wildrye, alkali Colline bunchgrasses

Lower and upper montane grass, bottlebrush squirreltail, others) Montane bunchgrasses

Subalpine and alpine Subalpine and alpine bunchgrasses

Colline Annual grasses (cheatgrass, medusahead, Colline exotic grasses and forbs

others), seeded wheatgrasses-(crested Montane exotic grasses and forbs

Lower and upper montane wheatgrass, other seeded dryland grasses), Subalpine and alpine exotic

Subalpine and alpine exotic forbs-(knapweeds, leafy spurge, grasses and forbs

yellowstar thistle, others)

Colline Native moist site herbs (sedges, rushes, Colline moist herbs

Lower and upper montane moist site grasses, forbs, others) Montane moist herbs

Subalpine and alpine Subalpine and alpine moist herbs

Colline Low sagebrushes (black sage, low sage), salt Colline low-medium shrubs

desert shrub, big sagebrushes-(basin big

sage, Wyoming sage, mountain big sage,

Lower and upper montane silver sagebrush), bitterbrush, rabbitbrush Montane low-medium shrubs

Subalpine and alpine Low alpine shrubs (heathers), big Subalpine and alpine lowsagebrushes-(basin big sage, Wyoming medium shrubs

sage, mountain big sage, silver sagebrush),

bitterbrush, rabbitbrush

Colline Mountain-mahogany, curlleaf mahogany Colline tall shrubs

Lower and upper montane Montane tall shrubs

Subalpine and alpine Subalpine and alpine tall shrubs

Colline Serviceberry, rose, snowberry, mountain Colline tall mountain shrubs

Lower and upper montane maple, Scouler's willow, buffaloberry, Montane tall mountain shrubs

chokecherry, bittercherry

Colline Willow, alder, bog birch, dogwood, other wet- Colline wet-site shrubs

Lower and upper montane site shrubs Montane wet-site shrubs

Subalpine and alpine Subalpine and alpine wet-site shrubs

Lower and upper montane Beargrass Montane subshrubs

Subalpine and alpine Subalpine and alpine subshrubs

a Refer also to appendix 1 for examples of nonforest (herbland and shrubland) overstory species representative of each photointerpreted grouping.
57

boundaries (Bailey 1995, McNab and Avers

1994), and STATSGO (USDA 1993) broad-scale

soils, precipitation, and dominant range PVT digital maps. Remotely sensed attributes used were

nonforest type, nonforest overstory species, riparian and wetland status, elevation zones of nonforest types, dead tree and snag abundance, and

sparse tree cover of herbland and shrubland types.

Elevation, slope, and aspect coverages were generated from 90-m digital elevation models of sampled subbasins. We adopted range cover type

descriptions of the Society for Range Management (SRM; published in Shiflet 1994). All

attributes were used to establish likely SRM 

cover types (table 15).

Range PVTs were developed by assembling a

complex coverage in a GIS through successive

map intersections. To begin, the photointerpreted

historical vegetation map of sampled subwatersheds and an associated data file including the following attributes—cover type, structural class,

overstory and understory species, nonforest type,

nonforest overstory species, riparian and wetland

status, elevation zones of nonforest types, dead

tree and snag abundance, and sparse tree cover of

herbland and shrubland types—were intersected

with the remotely sensed current vegetation map

having the same associated attributes. This first

complex coverage then was intersected with

derived elevation, slope, and aspect maps. The

resultant coverage then was intersected with the

STATSGO digital soils map. Each small polygon

in the resultant map coverage contained the

attributes of the successive intersections.

From published STATSGO precipitation data,

dominant vegetation types associated with

STATSGO map units, and dominant habitat

types associated with SRM cover types and their

geographic distribution, polygons were classified

by range PVTs through a series of Paradox

queries. We derived 29 range PVTs. Examples

include bluebunch wheatgrass steppe; antelope

bitterbrush steppe; low sagebrush steppe (mesic

sites with juniper woodland); Wyoming big sagebrush steppe (hot sites); riverine cottonwood; 

fescue grassland (with conifers); mountain big

Table 14—Classification rules for woodland structural classes modeled for sampled subwatersheds in the

midscale ecological assessment of the interior Columbia River basin

No. Structural class (code) Classification rule

1 Woodland stand initiation (w_si) PT_cca + SmTb_cc + MedT_cc + LgT_cc 

< 10 percent and SS_cc ≥ 10 percent

2 Woodland stem exclusion (w_se) LgT_cc < 10 percent and PT_cc + SmT_cc 

+ MedT_cc ≥ 10 percent and SS_cc < 10 percent 

3 Woodland understory reinitiation (w_ur) LgT_cc < 10 percent and PT_cc + SmT_cc 

+ MedT_cc ≥ 10 percent and SS_cc ≥ 10 percent

4 Young multistory woodland (w_yms) LgT_cc < 10 percent, and SmT_cc 

+ MedT_cc 10 percent, and PT_cc 

≥ 10 percent, and SS_cc ≥ 10 percent

5 Old multistory woodland (w_oms) LgT_cc ≥ 10 percent, and SS_cc + PT_cc 

+ SmT_cc + MedT_cc ≥ 10 percent

6 Old single story woodland (w_oss) LgT_cc ≥ 10 percent, and SS_cc + PT_cc 

+ SmT_cc + MedT_cc < 10 percent

a cc = crown cover; crown cover was interpreted in 10-percent increments, and class percentages were expressed as midpoints;

e.g., 10 percent = 5 to 14 percent, 20 percent = 15 to 24 percent.

b Tree sizes were estimated as SS–seedlings and saplings (< 12.7 centimeter d.b.h.), PT–poles (12.7 to 22.6 centimeter d.b.h.),

SmT–small trees (22.7 to 40.4 centimeter d.b.h.), MedT–medium trees (40.5 to 63.5 centimeter d.b.h.), and LgT–large trees 

(> 63.5 centimeter d.b.h.).

Text resumes on page 64
58

Table 15—Definitions of range potential vegetation types modeled for sampled subwatersheds in the midscale ecological assessment of the interior Columbia River basin

Bailey's

province or

Potential vegetation type SRMa types Habitat types section Code

Alpine herbland with low shrubs na Habitat types not adequately na ahls

described to date

Antelope bitterbrush steppe SRM 101 PUTR/FEID,b PUTR/FESC,

SRM 302 PUTR/AGSP, PUTR/STCO na putr

Basin big sagebrush/wildrye steppe SRM 401 Habitat types not adequately

described to date na bsbw

Big greasewood/ryegrass SRM 422 SAVE/DIST, SAVE/AGSM,

SAVE/ELCI na sarp

Bluebunch wheatgrass steppe SRM 317 AGSP/POSA,c SPCR/POSA, na agst

SRM 318 ARLO/POSA, AGSP/OPPO,

SRM 319 AGSP/ERHI, AGSP/POSA/SCAN,

SRM 104 AGSP/POSA/ASCU,

SRM 105 AGSP/POSA/ERPU,

AGSP/POSA/PHCO,

AGSP/POSA/OPPO,

AGSP/SPCR/ARLO

Bluebunch wheatgrass steppe SRM 317 AGSP/POSA with conifers, na ags2

(with conifers) SRM 318 SPCR/POSA with conifers,

SRM 319 ARLO/POSA with conifers,

SRM 104 AGSP/OPPO with conifers,

SRM 105 AGSP/ERHI with conifers,

AGSP/POSA/SCAN with conifers,

AGSP/POSA/ASCU with conifers,

AGSP/POSA/ERPU with conifers,

AGSP/POSA/PHCO with conifers, 

AGSP/POSA/OPPO with conifers, 

AGSP/SPCR/ARLO with conifers

Curlleaf mountain-mahogany SRM 415 CELE/AGSP, CELE Province M332 cew1

(without sagebrush)

Curlleaf mountain-mahogany SRM 322 CELE/AGSP, CELE Province M331 cew2

(with sagebrush) Province 341

Province 342

Fescue grassland SRM 102 AGSP/FEID, FEID/HICY, na fesc

SRM 103 FEID/SYAL, STCO/POSA,

SRM 108 FEID/KOCR, FESC/AGSP,

SRM 304 FESC/FEID, FEID/AGSM,

SRM 307 FEID/CAFI, FEID/STRI,

SRM 311 FEVI/CAHO, FEVI/LULA,

SRM 312 FEID/AGSP/LUSE,

FEID/AGSP/BASA, 

FEID/AGSP/PHCO, FEID/DAIN,

FEID/CAHO, FEID/CAGE
59

Table 15—Definitions of range potential vegetation types modeled for sampled subwatersheds in the midscale ecological assessment of the interior Columbia River basin (continued)

Bailey's

province or Potential vegetation type SRMa types Habitat types section Code

Fescue grassland (with conifers) SRM 102 AGSP/FEID with conifers, na fes2

SRM 103 FEID/HICY with conifers,

SRM 108 FEID/SYAL with conifers,

SRM 304 STCO/POSA with conifers,

SRM 307 FEID/KOCR with conifers,

SRM 311 FESC/AGSP with conifers,

SRM 312 FESC/FEID with conifers,

FEID/AGSM with conifers,

FEID/CAFI with conifers, 

FEID/STRI with conifers,

FEVI/CAHO with conifers,

FEVI/LULA with conifers,

FEID/AGSP/LUSE with conifers,

FEID/AGSP/BASA with conifers,

FEID/AGSP/PHCO with conifers,

FEID/DAIN with conifers,

FEID/CAHO with conifers,

FEID/CAGE with conifers,

Low sagebrush steppe SRM 320 ARAR/AGSP, ARAR/FEID, na lsme

(mesic sites) SRM 321 ARNO/AGSP, ARNO/FEID,

SRM 405 ARAR/POSA, ARLO/FEID

SRM 406

Low sagebrush steppe (mesic SRM 412 ARAR/AGSP with JUOC, na lsmj

sites with juniper woodland) ARAR/FEID with JUOC

Low sagebrush steppe SRM 407 ARRI, ARRI/POSA na lsxe

(xeric sites) 

Low sagebrush steppe (xeric SRM 412 ARAR, ARNO, ARRI with JUOC na lsxj

sites with juniper woodland)

Mountain big sagebrush steppe SRM 412 ARTRVA/FEID with JUOC, na bsmj

(mesic sites with Juniper ARTRVA/SYOR/FEID with JUOC,

woodland) ARTRVA/FEID/AGSP with JUOC

Mountain big sagebrush steppe SRM 314 ARTRVA/FESC, ARTRVA/AGSP, Province M331 bsme

(northerly and easterly aspects, SRM 315 ARTRVA/FEID, ARTRVA/STCO, Province M332

mesic sites, > 20 percent slopes) SRM 316 ARTRVA/SYOR/AGSP, Province 333

ARTRVA/SYOR/FEID, 

ARTRVA/SYOR/CAGE

Mountain big sagebrush steppe SRM 317 ARTRVA/FEID with conifers, na bsmc

(northerly and easterly aspects, SRM 324 ARTRVA/FESC with conifers,

mesic sites, with conifers) ARTRVA/AGSP with conifers,

ARTRVA/SYOR/AGSP with conifers,

ARTRVA/SYOR/FEID with conifers,

ARTRVA/SYOR/CAGE with conifers

Mountain big sagebrush steppe SRM 314 ARTRVA/FESC, ARTRVA/AGSP, Province M331 bsml

(northerly and easterly aspects, SRM 315 ARTRVA/FEID, ARTRVA/STCO, Province M332

mesic sites, < 20 percent slopes) SRM 316 ARTRVA/SYOR/AGSP, Province 333

ARTRVA/SYOR/FEID,

ARTRVA/SYOR/CAGE
60

Table 15—Definitions of range potential vegetation types modeled for sampled subwatersheds in the midscale ecological assessment of the interior Columbia River basin (continued)

Bailey's

province or Potential vegetation type SRMa types Habitat types section Code

Mountain big sagebrush steppe SRM 402 ARTRVA/AGSP, ARTRVA/FEID, Province 342 bsmw

(southerly and westerly aspects, ARTRVA/STCO, Province 341

mesic sites) ARTRVA/SYOR/AGSP,

ARTRVA/SYOR/FEID,

ARTRVA/SYOR/CAGE,

ARTRVA/CAGE,

ARTRVA/PUTR/FEID,

ARTRVA/SYOR/BRCA

Mountain riparian low shrub na Habitat types not adequately described na mrls

Mountain riparian sedge na Habitat types not adequately described na mrsd

(without willows)

Mountain shrub SRM 419 SYAL/Rosa spp., PHMA/SYAL, na mtsh

SRM 420 Habitat types not adequately

SRM 421 described, most are probably early

seral stages of PIPO and PSME

habitat types.

Riparian graminoid SRM 308 FEID/DECA, DECA/Carex spp., na rigr

SRM 313 Carex spp., CANE/JUBA, DECA,

POPA, POPR

Riparian sedge (with willows) na SAGE/CARO, SAGE/POPA, na salx

SAGE/CACA, SAGE/POPR,

SABO/CARO, SABO/CACA,

SABO/POPR, SAWO/CAAQ,

SAWO/CARO, SAWO/CACA,

SAWO/DECA, SAWO/POPA, others

Riverine cottonwood na POTRI/CIDO, POAN/COST, na ctrv

POAN/POPR, POTRI/COST,

POTRI/POPR

Salt desert shrub SRM 414 GRSP/POSA, EULA/POSA na sdsh

Three-tip sagebrush steppe SRM 324 ARTRI/AGSP, ARTRI/FEID na ttsa

SRM 404

Wyoming big sagebrush steppe SRM 403 ARTRWY/AGSP, ARTRWY/POSA Section 342C wbsa

(warm to hot sites) ARTRWY/SIHY, ARTRWY/STTH, Section 342I

ARTRWY/STCO, ARTRTR/AGSP Section 341E

Wyoming big sagebrush steppe SRM 403 ARTRWY/AGSP, ARTRWY/POSA, not in: wbsc

(cool to cold sites) ARTRWY/SIHY, ARTRWY/STTH, Section 342C

ARTRWY/STCO, ARTRTR/AGSP, Section 342I 

ARTRTR/FEID Section 341E

na = not applicable.

a SRM types refers to rangeland cover type descriptions adopted by the Society for Range Management (Shiflet 1994).

b Common and scientific names and abbreviations of species discussed in the text and tables are listed in table 8.

c POSA (Poa sandbergia) is equivalent to POSE (Poa secunda).
61

Table 16—Classification rules for herbland, shrubland, and woodland potential vegetation types modeled for

sampled subbasins in the midscale ecological assessment of the interior Columbia River basin

Potential vegetation type Code Classification rule

Alpine herbland (with low shrubs) ahls (NF_typea = alpine meadow) and (Elev_belt = subalpine or alpine) and

(NF_spp_os_C = native moist-ste herbs or low alpine shrubs or beargrass) 

or (STATSGO_MapUnit_ID _Series = XETEb) 

Antelope bitterbrush steppe putr (NF_type = shrubland) and (NF_spp_os_C = big sagebrush/bitter brush) 

and (NF_spp_os_H = big sagebrush/bitterbrush) and (STATSGO_Map 

Unit_ID_Series = PUTR)

Basin big sagebrush/wildrye bsbw (NF_type = shrubland) and (NF_spp_os_C = native bunchgrasses or annual

steppe grasses or seeded wheatgrasses or exotic forbs or big sagebrush/bitterbrush) 

or (NF_spp_os_H = native bunchgrasses or annual grasses or seeded wheatgrasses or exotic forbs or big sagebrush/bitterbrush) and (STATSGO_Map 

Unit_ID _Series = ELCI)

Big greasewood/ryegrass sarp (NF_type = shrubland) and (Riparian_Wetland_Status = “yes”) and

(streambanks) (NF_spp_os_C = low sagebrush or other low shrubs) and (NF_spp_os_H = 

low sagebrush or other low shrubs) and (STATS GO_MapUnit_ID _Series 

= ATCO or SAVE) 

Bluebunch wheatgrass steppe agst (NF_type = grassland) and (ELEV_belt = colline or lower montane) and

(NF_spp_os_C = native bunchgrasses or annual grasses or seeded wheat

grasses or exotic forbs) and (NF_spp_os_H = native bunchgrasses or annual 

grasses or seeded wheatgrasses or exotic forbs) and (STATSGO_MapUnit_ 

ID _Series = AGSP)

Bluebunch wheatgrass steppe ags2 (NF_type = grassland) and [(NF_tree_cover = “yes”) or (DeadTree_Snag 

(with conifers) _Abundance ≥ 10 percent dead trees)] and (NF_spp_os_C = native bunchgrasses or annual grasses or seeded wheatgrasses or exotic forbs) and

(NF_spp_os_H = native bunchgrasses or annual grasses or seeded wheatgrasses or exotic forbs) or (STATSGO_MapUnit_ID _Series = AGSP)

Curlleaf mountain-mahogany cew1 (NF_type = shrubland) and (NF_spp_os_C = mahogany) and

(without sagebrush) (NF_spp_os_H = mahogany) and (STATSGO_MapUnit_ID _Series = 

CELE with no ARTRVA)

Curlleaf mountain-mahogany cew2 (NF_type = shrubland) and (NF_spp_os_C = mahogany) and

(with sagebrush) (NF_spp_os_H =mahogany) and (STATSGO_MapUnit_ID _Series = 

CELE with ARTRVA)

Fescue grassland fesc (NF_type = grassland) and (NF_spp_os_C = native bunchgrasses or annual

grasses or seeded wheatgrasses or exotic forbs) and (NF_spp_os_H = native

bunchgrasses or annual grasses or seeded wheatgrasses or exotic forbs) and

(STATSGO_MapUnit_ID_Series = FESC)

Fescue grassland (with conifers) fes2 (NF_type = grassland) and [(NF_tree_cover = “yes”) or (DeadTree_Snag_ 

Abundance ≥ 10 percent dead trees)] and (NF_spp_os_C = native bunchgrasses or annual grasses or seeded wheatgrasses or exotic forbs) and

(NF_spp_os_H = native bunchgrasses or annual grasses or seeded wheatgrasses or exotic forbs) and (STATSGO_MapUnit_ID _Series = FESC) 

Low sagebrush steppe lsme (NF_type = shrubland or grassland) and (NF_spp_os_C = native bunch-

(mesic sites) grasses or annual grasses or seeded wheatgrasses or exotic forbs or low sagebrushes) or (NF_spp_os_H = native bunchgrasses or annual grasses or 

seeded wheatgrasses or exotic forbs or low sagebrushes) and

(STATSGO_MapUnit _ID _Series = ARAR or ARNO)
62

Table 16—Classification rules for herbland, shrubland, and woodland potential vegetation types modeled for

sampled subbasins in the midscale ecological assessment of the interior Columbia River basin (continued)

Potential vegetation type Code Classification rule

Low sagebrush steppe lsmj (NF_type = shrubland or grassland) and (NF_spp_os_C = native bunch-

(mesic sites with juniper grasses or annual grasses or seeded wheatgrasses or exotic forbs or low sagewoodland) brushes) or (NF_spp_os_H = native bunchgrasses or annual grasses or seeded

wheatgrasses or exotic forbs or low sagebrushes) and (STATSGO_MapUnit 

_ID_Series = ARAR or ARNO) and (Subbasin_Codec = BUR or UDS or 

LDS or LCR or LFH or LHE or LJD or LST or LWC or MDL or PSD or 

SIL or SHW or UJD or UOW or DUB) and (F_spp_os = juniper )

Low sagebrush steppe lsxe (NF_type = shrubland) and (NF_spp_os_C = native bunchgrasses or annual

(xeric sites) grasses or seeded wheatgrasses or exotic forbs or low sagebrushes) or (NF_ 

spp_os_H = native bunchgrasses or annual grasses or seeded wheatgrasses or 

exotic forbs or low sagebrushes) and (STATSGO_MapUnit_ID _Series = 

ARAR or ARNO)

Low sagebrush steppe (xeric lsxj (NF_type = shrubland) and (NF_spp_os_C = native bunchgrasses or annual

sites with juniper woodland) grasses or seeded wheatgrasses or exotic forbs or low sagebrushes) or (NF_ 

spp_os_H = native bunchgrasses or annual grasses or seeded wheatgrasses or 

exotic forbs or low sagebrushes) and (STATSGO_MapUnit_ID _Series = 

ARAR or ARNO) and (Subbasin_Code =BUR or UDS or LDS or LCR or 

LFH or LHE or LJD or LST or LWC or MDL or PSD or SIL or SHW or 

UJD or UOW or DUB) and (F_spp_os = juniper)

Mountain big sagebrush bsmj (NF_type = grassland or shrubland) and (NF_spp_os_C = native

steppe (mesic sites with bunchgrasses or annual grasses or seeded wheatgrasses or exotic forbs or big 

juniper woodland) sagebrush/bitterbrush) or (NF_spp_os_H = native bunchgrasses or annual 

grasses or seeded wheatgrasses or exotic forbs or big sagebrush/bitterbrush) 

and (STATSGO_MapUnit_ID_Series = ARTRTR or ARTRVA) and

(Subbasin_Code = BUR or UDS or LDS or LCR or LFH or LHE or LJD or

LST or LWC or MDL or PSD or SIL or SHW or UJD or UOW or DUB) 

and (F_spp_os = juniper)

Mountain big sagebrush bsme (NF_type = grassland or shrubland) and (NF_spp_os_C = native bunchsteppe (northerly and grasses or annual grasses or seeded wheatgrasses or exotic forbs or big sageeasterly aspects, mesic brush /bitterbrush) or (NF_spp_os_H = native bunchgrasses or annual 

sites, > 20 percent slopes) grasses or seeded wheatgrasses or exotic forbs or big sagebrush/bitterbrush) 

and (STATSGO_MapUnit_ID_Series = ARTRTR or ARTRVA) and

(Subbasin_Code = BFM, BTR, BOM, BWD, FLR, UGR, LGR, WAL, 

KET, LMH, LOC, LYK, MET, NAC, PEN, PLS, SFC, SFS, SWN, UCD, 

UKL, UMS, UYK, WEN, YAA) and (Slope ≥ 20 percent) and (aspects = N 

or E)

Mountain big sagebrush bsmc (NF_type = grassland or shrubland) and [(NF_tree_cover = “yes”) or (Dead

steppe (northerly and Tree_Snag_Abundance ≥ 10 percent dead trees)] and (ELEV_belt = colline 

easterly aspects, mesic or lower montane) and (NF_spp_os_C = big sagebrush/bitter brush) and

sites, with conifers) (NF_spp_os_H = big sagebrush/bitterbrush) and (STATSGO_MapUnit 

_ID _Series = ARTRTR or ARTRVA) and (aspects = N or E)

Mountain big sagebrush bsml (NF_type = grassland or shrubland) and (NF_spp_os_C = native bunchsteppe (northerly and grasses or annual grasses or seeded wheatgrasses or exotic forbs or big sageeasterly aspects, mesic sites, brush/bitterbrush) or (NF_spp_os_H = native bunchgrasses or annual 

< 20 percent slopes) grasses or seeded wheatgrasses or exotic forbs or big sagebrush/bitterbrush) 

and (STATSGO_MapUnit_ID_Series = ARTRTR or ARTRVA) and (Slope 

< 20 percent) and (aspects = N or E)
63

Table 16—Classification rules for herbland, shrubland, and woodland potential vegetation types modeled for

sampled subbasins in the midscale ecological assessment of the interior Columbia River basin (continued)

Potential vegetation type Code Classification rule

Mountain big sagebrush bsmw (NF_type = grassland or shrubland) and (NF_spp_os_C = native bunchsteppe (southerly and grasses or annual grasses or seeded wheatgrasses or exotic forbs or big sagewesterly aspects, mesic brush/bitterbrush) or (NF_spp_os_H = native bunchgrasses or annual

sites) grasses or seeded wheatgrasses or exotic forbs or big sagebrush/bitterbrush) 

and (STATSGO_MapUnit_ID_Series = ARTRTR or ARTRVA) and

(Subbasin_Code = BUR or UDS or LDS or LCR or LFH or LHE or LJD 

or LST or LWC or MDL or PSD or SIL or SHW or UJD or UOW or 

DUB) and (aspects = S or W)

Mountain riparian low shrub mrls (NF_type = shrubland) and (Elev_belt = upper montane or subalpine or 

alpine) and (NF_spp_os_C = wet-site shrubs) and (STATSGO_MapUnit_ 

ID_Series =Salix spp.) 

Mountain riparian sedge mrsd (NF_type = wet meadow) and (NF_spp_os_C = native moist-site herbs) 

(without willows) and (STATSGO_MapUnit_ID _Series = Carex spp.) 

Mountain shrub mtsh (NF_type = shrubland) and (NF_spp_os_C = mountain shrubs) and

(STATSGO_MapUnit_ID _Series = SYAL, AMAL, Rosa spp.; SASC, 

PRVI, and ACGL)

Riparian graminoid rigr (NF_type = dry meadow) and (NF_spp_os_C = native bunchgrasses) or

(without shrubs) (STATSGO_MapUnit_ID _Series = DECA) 

Riparian sedge salx (NF_type = shrubland or wet meadow or stream channel & nonvegetated 

(with willows) flood plain) and (NF_spp_os_C = wet-site shrubs) and (Riparian_Wetland 

_Status = “yes”) and (Elev_belt = colline or lower montane) and

(STATSGO_MapUnit_ID_Series = Salix spp.) 

Riverine cottonwood ctrv (F_spp_os = cottonwood) and (Riparian_Wetland_Status = “yes”) and

(STATSGO_MapUnit_ID _Series = POTRI or POAN)

Salt desert shrub (playas) sdsh (NF_type = playa) and (NF_spp_os_C = low sagebrush or other low 

shrubs) and (NF_spp_os_H = low sagebrush or other low shrubs) and

(STATSGO_MapUnit_ID _Series = ATCO or SAVE)

Three-tip sagebrush steppe ttsa (NF_type = shrubland) and (NF_spp_os_C = native bunchgrasses or annual

grasses or seeded wheatgrasses or exotic forbs or big sagebrush/bitterbrush) 

or (NF_spp_os_H = native bunchgrasses or annual grasses or seeded wheatgrasses or exotic forbs or big sagebrush/bitterbrush) and (STATSGO_

MapUnit_ID _Series = ARTRI)

Wyoming big sagebrush wbsa (NF_type = shrubland) and (NF_spp_os_C = native bunchgrasses or annual 

steppe (warm to hot sites) grasses or seeded wheatgrasses or exotic forbs or big sagebrush/bitterbrush) 

or (NF_spp_os_H = native bunchgrasses or annual grasses or seeded wheatgrasses or exotic forbs or big sagebrush/bitterbrush) and (STATSGO_

MapUnit_ID_Series = ARTRWY) and (Subbasin_Code = CRT or BOM)

Wyoming big sagebrush wbsc (NF_type = shrubland) and (NF_spp_os_C = native bunchgrasses or annual

steppe (cold sites) grasses or seeded wheatgrasses or exotic forbs or big sagebrush/bitterbrush) 

or (NF_spp_os_H = native bunchgrasses or annual grasses or seeded wheatgrasses or exotic forbs or big sagebrush/bitterbrush) and (STATSGO_

MapUnit_ID _Series = ARTRWY) and (Subbasin_Code ≠ CRT or BOM)

a Abbreviations correspond with photointerpreted attributes (appendix 1) and STATSGO (USDA 1993) potential vegetation

map units: NF_type = nonforest type; NF_spp_os_C = nonforest overstory species-current condition; NF_spp_os_H = nonforest overstory species-historical condition; NF_tree_cover = tree cover of herbland and shrubland types; STATSGO_MapUnit

_ID_Series = dominant climax series; DeadTree_Snag_Abundance = dead trees and snags; Elev_belt = elevation zones of nonforest types.

b Common and scientific names, and abbreviations of all species mentioned in the text and tables are listed in table 8.

c Sampled subbasin names and corresponding 3 character alpha-codes are provided in table 3.
sagebrush steppe (northerly and easterly aspects,

mesic sites, with slopes > 20-percent); riparian

sedge (with willows); riparian sedge (without 

willows); curlleaf mountain-mahogany (without

sagebrush); and alpine herbland (with low

shrubs). Complete definitions for range PVTs are

given in table 15; generalized rules for modeling

range PVTs are provided in table 16.21

Nonforest-nonrange and anthropogenic

cover types—Several cover conditions were

interpreted from aerial photographs that did not

represent a forest, herbland, shrubland, or woodland physiognomic type. These were typically

nonforest or nonrange cover conditions or types

of human-caused origin. Cover types such as

these were attributed by their actual cover condition but were treated as the class “other” in some

analyses, unless otherwise indicated. Naturally

occurring nonforest-nonrange cover types were

rock, water (pond, lake, river), bare ground (dry

lake beds, playa), glacier, sand dune, and stream

channel and nonvegetated flood plains. Nonforest-nonrange cover types of anthropogenic origin

were bare ground (adjacent to roadcuts), bare

ground (burned or logged), bare ground (slumps

and erosion), urban and rural developments,

cropland, and irrigated pasture. During modeling

of forest and range PVTs, bare ground of human

origin was assigned to the forest or range PVT of

adjacent patches in similar elevation and aspects

settings by nearest neighbor analysis.

Vegetation and Landscape 

Pattern Analysis

Vegetation maps, patch attributes, derived cover

type, structural class, and PVT attributes formed

the basic data set from which all subsequent pattern analysis was accomplished. Individual patches were defined by both their derived attributes

and selected remotely sensed attributes (see

appendix 1).

Raster size determination—To quantify

change in landscape structural attributes and patterns of various patch types, we used raster versions of current and historical vegetation themes.

A raster format was chosen because several useful

class metrics (for example, mean nearest neighbor

distance [MNN], nearest neighbor coefficient of

variation [NNCV], and contagion [CONTAG])

were available in FRAGSTATS only for data in

raster format. Map themes stored in vector format

in ARC/INFO were converted to raster at a scale

appropriate for avoiding biases commonly associated with raster formats (McGarigal and Marks

1995). The appropriate cell size was determined

by calculating several class metrics (number of

patches [NP], mean patch size [MPS], patch size

coefficient of variation [PSCV], edge density

[ED], and mean shape index [MSI]) in vector 

and raster form, with cell sizes ranging from 10 

to 100 m (1 ha), in 10-m increments, and at 2.0

and 5.0 ha, and plotting each raster-derived metric value against the vector value. Raster bias was

relatively minor for the evaluated metrics at a cell

size of 40 m, and insignificant with smaller cell

sizes. We used 30-m raster versions for all spatial

pattern analysis. 

Sample statistics—We used percentage of area

(%LAND), mean patch size (MPS), and patch

density (PD; see metric descriptions in table 17)

in various patch types (for example, patch types

are ponderosa pine cover type, or old-forest single-story structural class) to objectively and graphically represent changes in area and connectivity

relations of patch types in subwatersheds of a

pooling stratum (ecological reporting unit, or

ERU; described at the end of “Methods”). We

estimated change from historical to current conditions as the mean difference between conditions,

not as the percentage of change from historical

conditions, to avoid the bias of establishing the

historical condition as an essential reference. For

the ERU pooling stratum, means, mean standard

errors, and confidence intervals were estimated by

using methods for simple random samples (Steel

and Torrie 1980) with subwatersheds as sample

units. Statistically significant (P≤0.2) change was

determined by examining the 80-percent confidence interval around the mean difference for the

ERU, which was estimated as the simple random

mean from pairwise comparisons of historical and

current subwatersheds. If the confidence interval

included zero, no significant change was recorded.

64

21 Classification rules for each of the 43 subbasins are on file

with Don Long, Rocky Mountain Research Station, Fire

Sciences Laboratory, P.O. Box 8089, Missoula, MT 59807.
65

Table 17—FRAGSTATS indices used to quantify connectivity and spatial patterns of patch types in sampled

subbasins in the midscale ecological assessment of the interior Columbia River basin

Acronym Scale Index name Descriptiona

%LAND Class Percentage of Percentage of a landscape composed of the corresponding 

landscape (%) patch type

LPI Class or Largest patch Percentage of a landscape composed of the largest patch of the 

landscape index (%) corresponding patch type 

PD Class or Patch density (no. per Number of patches in an area of 10 000 hectares

landscape 10 000 hectares)

MPS Class or Mean patch size Average patch size

landscape (hectares)

PSCV Class or Patch size coefficient Relative measure of patch size variability

landscape of variation (%)

ED Class or Edge density (meters Length of edge per hectare of the corresponding patch type

landscape per hectare)

AWMECI Class or Area-weighted mean Average patch edge contrast as a percentage of maximum 

landscape edge contrast index (%) contrast with patch edge contrasts weighted by patch area; 

equals 100 when all edge is maximum contrast; approaches 0 

when all edge is minimum contrast

AWMSI Class or Area-weighted mean Average patch shape complexity with patch shape index 

landscape shape index weighted by patch area; equals 1 when all patches are circular, 

increases as patch shapes become more complex

MNN Class or Mean nearest-neighbor Average distance to the nearest neighbor of the corresponding 

landscape distance (meters) patch type

NNCV Class or Nearest-neighbor Relative measure of nearest neighbor distance variability

landscape coefficient of variation

(%)

SHDI Landscape Shannon's diversity Measures proportional abundance of patch types and the 

index equitable distribution of patch type areas; increases with patch 

richness (PR) and equitability of area

RPR Landscape Relative patch Observed number of patch types within a landscape over a 

richness (%) realistic potential maximum number of patch types

PR Landscape Patch richness Observed number of patch types within a landscape boundary

MSIEI Landscape Modified Simpson's Observed distribution of area of patch types within a landscape 

evenness index over evenly distributed area of patch types

IJI Class or Interspersion and Observed interspersion of edge types over maximum possible

landscape juxtaposition index (%) interspersion; IJI approaches 0 when patch types are clumped, 

IJI approaches 100 when all patch types are equally adjacent to 

all other patch types

CONTAG Landscape Contagion index (%) Observed contagion over the maximum possible contagion 

for the given number of patch types; approaches 0 when the 

distribution of adjacencies among unique patch types becomes 

increasingly uneven; approaches 100 when all patch types are 

equally adjacent to all other patch types; measures patch type 

interspersion and patch dispersion
Evaluating the ecological significance of

changes—We supplemented this statistical test

with two additional analyses that enabled us to

evaluate the potential ecological significance of

patch type change in area or connectivity of area.

First, we approximated the historical range of

variation (Everett and others 1994, Morgan and

others 1994, Swanson and others 1994) by calculating the historical sample median 75-percent

range for each patch type metric, and we compared the current sample median value with this

estimate of the historical range. Second, we characterized the most significant changes in absolute

area of a patch type within a sample by using

transition analysis. Ecologically significant change

ultimately was determined by examining each of

the three pieces of information: the 80-percent

confidence interval, differences between current

median values and historical median 75-percent

ranges, and principal transitions between historical and current conditions.

Transition analysis estimated the percentage of

area in a pooling stratum that changed from any

one cover type or structural condition in the historical vegetation coverage to any other condition

in the current coverage, including transitions to

the same condition. If change was narrowly

focused to a few transition types, and those transitions were credible in light of known management history and successional and disturbance

regime changes, the transitions were provisionally

judged as ecologically significant. (Note that transition matrices were established from 30-m raster

coverages of patch types. The total number of

possible transition types within an ERU ranged

from 102 to 103.) Transition analysis enabled us 

to directly identify transitions responsible for the

changes we observed and detect statistically significant “nonsense” changes resulting from rasterization of historical and current vegetation coverages.

The median 75-percent range of the historical

condition was used to estimate the significant difference between current median values and the

typical range of historical conditions. If the median value of the current condition (for any metric

associated with any patch type) was outside the

median 75-percent range of the historical condition, and transition analysis determined that no

major transitions were nonsense changes, we

judged the difference to be ecologically significant. Nearly all changes evaluated as ecologically

significant were found to be statistically significant at P≤0.2 via examination of the 80-percent

confidence interval.

We chose the median 75-percent range instead of

the full 100-percent range as a meaningful measure of recent historical variation to portray typical

variation exclusive of extreme observations. Historical (and current) data distributions most often

were highly skewed and only rarely were distributed normally; hence, the sample median value

was a more accurate reflection of central tendency

than either the mean or mode. Most observations

clustered within the median 75- to 80-percent

range, and few observations accounted for differences between the range of the clustered observations and the full range. We reasoned that more

extreme variation usually results from either

66

Table 17—FRAGSTATS indices used to quantify connectivity and spatial patterns of patch types in sampled

subbasins in the midscale ecological assessment of the interior Columbia River basin (continued)

Acronym Scale Index name Descriptiona

N1 Landscape Hill’s Index N1 A transformation of SHDI, computed as eSHDI; rare patch 

types are weighted less in the calculation than in PR

N2 Landscape Hill's index N2 A transformation of SIDI, computed as 1/(1-SIDI); rare patch 

types are weighted less in the calculation than in N1

R21 Landscape Alatalo's evenness Measures evenness of patch types; computed as (N2-1) / (N1-1),

index where PR > 1; values approaching 0 indicate uneven 

distribution of patch type areas; values approaching 1 indicate 

even distribution of area for the given number of patch types

a See McGarigal and Marks (1995) for algorithms and complete descriptions of all indices except N1, N2, and R21.
67

unique contexts or environments or from rare

events. By imposing the contrast between current

median values and a typical range of historical

conditions, we retained the ability to detect conditions resulting from management activities, random chance, or perhaps climate change that was

unique or abnormal in some aspect. Indeed, a

similar rule is applied when we compare our own

human physical condition to a standard or set 

of norms. Although natural variation in human

anatomy and morphology includes supernumerary

digits, appendages, and teeth, or the noticeable

absence of common anatomical features, we compare our condition to a more narrowly defined

standard that excludes characteristics associated

with the most extreme variation in human populations. We do so because we are aware that these

rarer features often are associated with a certain

amount of disutility or dysfunction.

We noted earlier in this “Methods” section that

historical vegetation maps were developed from

the earliest available aerial photography. While

researching archived films, we learned that in

most cases, the first available continuous coverage

of historical photos usually predated the advent of

significant timber harvest in a subwatershed. As

indicated in our list of remotely sensed attributes

(appendix 1), we interpreted the extent and type

of visible logging activity and found this to be the

case. Historical photographic coverages represented a span of years from 1933 to 1966 (table 3).

When we evaluated the ecological significance of

vegetation change, we compared current median

values with a typical range of historical values: the

full range of historical observations minus the

most extreme outliers.

The ideal would be to sample vegetation conditions in subwatersheds at many different time

depths, over a period of similar climate regime to

obtain a representative sample of historical or

“natural” variation, but such a sample is expensive

and unavailable. In the ideal case, sampling over

multiple time depths would enable the observer

to characterize variation arising from the stochasticity of environments, disturbance regimes, and

climate regimes. We had a span of years rather

than a single year to represent historical vegetation conditions and thus could sample more variability in historical vegetation patterns resulting

from chance events and contexts, and could more

adequately represent natural variation, than had

we sampled a single historical year. 

Spatial statistics—We used the basic data set 

to quantify change in area and connectivity of

patch types and their spatial patterns in subwatersheds. We assessed change in area and connectivity relations of cover type and structural class

patch types by computing nine class metrics for

historical and current vegetation coverages and

testing for significant change. We evaluated

change in spatial patterns of cover type-structural

class patch types by computing 10 landscape pattern indices and testing for significant change

(table 17). Nine of the 10 landscape metrics were

used to evaluate changes in diversity, richness,

dominance, evenness, interspersion, and contagion of patch types. One area-weighted mean

edge contrast index (AWMECI) was computed;

mean edge contrast was defined by using weights

ranging from 0 to 1, with increasing weight representing greater edge contrast. Edge contrast

weights are provided in table 18. For those patches occurring at the boundary of a subwatershed,

the boundary was considered the patch edge for

the purpose of calculating area, shape, and other

class metrics, even though in reality some patches

continued beyond the subwatershed boundary.

All class and landscape metrics were computed 

for whole subwatersheds from 30-m raster versions of the vector ARC/INFO maps. We used

the FRAGSTATS program (McGarigal and Mares

1995) to quantify and contrast all historical and

current area and connectivity, and landscape pattern relations. Of the metrics available in

FRAGSTATS, a restricted set was used to quantify trends in subwatershed structural attributes and

spatial patterns. That set included the following

metrics by type: area (%LAND and LPI); patch

density, patch size and variability (MPS, PD, and

PSCV); edge (ED and AWMECI); shape

(AWMSI); nearest neighbor (MNN and NNCV);

diversity (SHDI, RPR, PR, and MSIEI); contagion (CONTAG); and interspersion (IJI). In

addition, three supplemental diversity metrics

were added to the FRAGSTATS source code and

computed: Hill’s Indices N1 and N2 (Hill 1973),

and R21, Alatalo’s evenness index (Alatalo 1981);

N1 and N2 also were used to derive R21.
Landscape pattern analyses—Pattern analyses

presented in this paper represent about one-quarter of the total analysis. Time and budget constraints and page limitations prevent a complete

presentation of analyses and results. We include

those analyses that we thought most essential and

that provided the greatest insight into changes

occurring in sampled subbasins. In this paper and

in Ottmar and others (in prep.), we summarize,

by ERUs as the pooling stratum, changes in area

and connectivity of the following patch types: (1)

physiognomic types; (2) forest cover types; (3)

herbland, shrubland, and woodland cover types;

(4) nonforest and nonrange cover types; (5) forest

structural classes; (6) herbland, shrubland, and

woodland structural classes; (7) disturbance vulnerability classes for 21 potential pathogen and

insect disturbances; (8) fuel loading classes; (9)

potential fuel consumption classes under wet, dry,

and normal (average) burning conditions; (10)

potential fireline intensity classes under wet, dry,

and normal burning conditions; (11) potential

flame length classes under wet, dry, and normal

burning conditions; (12) potential fire rate of

spread classes under wet, dry, and normal burning

conditions; (13) potential risk of crown fire classes under wet, dry, and normal burning conditions; (14) potential PM10 smoke emissions

under wet, dry, and normal burning conditions

(see Ottmar and others, in prep. for analysis of

items 8 to 14); (15) forests and woodlands with

large trees; (16) forests and woodlands with medium and large trees; (17) forest and woodland tree

crown cover; (18) forest and woodland dead tree

68

Table 18—Edge contrast weights used in calculating the FRAGSTATS metric area weighted mean edge contrast index (AWMECI) in pattern analyses of patch types of sampled subwatersheds in the midscale ecological assessment of the interior Columbia River basina

Forest (by structural classb)

Nonforest

Physiognomic and seoc and ur and

type nonrange Herbland Shrubland Woodland si secc yfms ofss ofms

Nonforest and

nonrange 0c 0.2 0.3 0.4 0.5 0.6 0.8 0.9 1

Herbland 0 0.2 0.3 0.4 0.6 0.7 0.8 0.9

Shrubland 0 0.2 0.3 0.5 0.6 0.7 0.8

Woodland 0 0.3 0.4 0.5 0.6 0.7

Forest si 0 0.3 0.4 0.5 0.6

Forest seoc and secc 0 0.3 0.4 0.5

Forest ur and yfms 0 0.3 0.4

Forest ofss 0 0.3

Forest ofms 0

a For FRAGSTATS, see McGarigal and Marks (1995).

b Forest structural classes are stand intiation (si); stem exclusion open canopy (seoc); stem exclusion closed canopy (secc); understory reinitiation (ur); young forest multistory (yfms); old forest single story (ofss); and old forest multistory (ofms). See also

tables 5 and 6 for forest structural class descriptions, definitions, and classification rules for continuous data.

c Range of possible values is 0 to 1, with increasing values representing greater edge contrast.
69

and snag abundance; (19) forest and woodland

visibly affected by logging; and (20) riparian and

wetland areas. The ERUs were used as pooling

strata to verify the broad-scale assessment findings

of Hann and others (1997) and to compare those

findings with findings contained herein. Later, we

will resummarize change by using more appropriate midscale pooling strata.

In addition to assessing change in area and connectivity relations of cover types and structural

classes, we assessed change in physiognomic conditions. Following is the disposition of remotely

sensed nonforest types (see appendix 1) to physiognomic types. Patches interpreted as wet meadow, alpine meadow, dry meadow, grasses and

forbs after logging, pasture, grassland, and grasses

and forbs after burning (wildfire or prescribed)

were classified as herbland; patches interpreted as

shrubland were classified as shrubland; and patches interpreted as rock, water, bare ground after

burning or logging, bare ground associated with

slumps and erosion, cropland, urban or rural

development, bare ground associated with roads

and highways, stream channels and nonvegetated

flood plains, dune, glacier, or bare ground associated with dry lake beds or as playa were classified

as nonforest-nonrange and other anthropogenic

types.

Other change analyses quantified but not summarized in this paper include (1) riparian and wetland area by forest and range cover type; (2)

riparian and wetland area by forest and range

cover type and PVT; (3) forest cover type by

structural class by PVT; (4) range cover type by

structural class by PVT; (5) forest cover type by

structural class; (6) range cover type by structural

class; (7) forest and woodland understory species

by cover type; (8) forest and woodland understory

species by cover type and PVT; (9) forest and

woodland total crown cover classes by cover type;

(10) forest and woodland total crown cover classes

by cover type and PVT; (11) patch clumpiness by

cover type; (12) patch clumpiness by cover type

and PVT; (13) patch clump density by cover type;

(14) patch clump density by cover type and PVT;

(15) patch clump size by cover type; (16) patch

clump size by cover type and PVT; (17) patch

overstory crown differentiation by cover type;

(18) patch overstory crown differentiation by

cover type and PVT; (19) patch canopy layers by

cover type; (20) patch canopy layers by cover type

and PVT; (21) patch visible logging activity class

by cover type; (22) patch visible logging activity

class by cover type and PVT; (23) patch dead tree

and snag abundance by cover type; and (24)

patch dead tree and snag abundance by cover type

and PVT. Resources allowing, results of these

analyses will be summarized for midscale pooling

strata and reported at a later time.

Forest Landscape Vulnerability to

Insect and Pathogen Disturbances

Here we summarize methods used to assess recent

change in vulnerability of forest vegetation to disturbances caused by the major forest insects and

pathogens of the basin (see Hessburg and others,

in press, for modeling procedures). Change in

potential vulnerability was characterized for each

of the 337 subwatersheds. Vulnerability characterizations modeled the potential susceptibility or

conduciveness of vegetation patterns to alteration

by insect or pathogen disturbance. Insect and

pathogen disturbances were modeled as succession

processes. Vulnerable subwatersheds displayed

vegetation patterns conducive to propagating 

a given pathogen or insect disturbance within and

among patches. Structural and compositional succession, as intended here, was the outcome of

pathogen infection or insect infestation of susceptible vegetation at patch or landscape scales.

Examples of growth and mortality effects leading

to succession are tree topkilling, tree mortality,

brooming, stem decay, tree collapse, butt rot,

windthrow, top breakage, and defoliation.

Disturbance agents—We characterized subwatershed vulnerability to 21 different forest

pathogen and insect disturbances. Forest pathogens and insects selected were those that frequently cause patch- and landscape-scale

disturbances resulting in measurable structural

and compositional change in the interval between

stand-replacing fires. Landscape vulnerability was

assessed for one defoliator disturbance, seven 

bark beetle disturbances, four dwarf mistletoe 

disturbances, four root disease disturbances, two

root and butt rot disturbances, two blister rust

disturbances, and one stem decay disturbance.
Vulnerability characterizations for two principal

defoliators, the western spruce budworm and the

Douglas-fir tussock moth, were collapsed into one

vulnerability rating, but vulnerability factors used

were most appropriate to the western spruce budworm. Vulnerability to bark beetle disturbance

was quantified separately for the Douglas-fir beetle, western pine beetle, mountain pine beetle, fir

engraver, and spruce beetle. Subwatershed vulnerability to western pine beetle disturbance was

addressed in two separate submodels: one (type 1)

for landscapes comprised of mature and old ponderosa pine, and another (type 2) for landscapes

comprised of immature and high-density ponderosa pine. Similarly, vulnerability to mountain

pine beetle disturbance was addressed by two submodels: one (type 1) for landscapes comprised of

high-density lodgepole pine, and another (type 2)

for landscapes comprised of immature, high-density ponderosa pine.

Subwatershed vulnerability to dwarf mistletoe disturbance was modeled separately for mistletoes of

western larch, Douglas-fir, ponderosa pine, and

lodgepole pine. Vulnerability to root disease disturbance was modeled separately for laminated

root rot, Armillaria root disease, S-group annosum

root disease, and P-group annosum root disease.

Vulnerability to root and butt rot disturbance was

modeled separately for tomentosus root and butt

rot and Schweinitzii root and butt rot. Vulnerability to white pine blister rust disturbance was

addressed in two separate submodels: one (type 1)

for western white pine and sugar pine cover types,

and another (type 2) for the whitebark pine-subalpine larch cover type. Finally, vulnerability to

stem decay disturbance was modeled for rust-red

stringy rot caused by the Indian paint fungus.

Vulnerability factors—We used patch composition, structure, logging disturbance, and physical

environment attributes to compare the vulnerability of vegetation of historical subwatersheds with

that of their current condition. Appendix 1 lists

attributes interpreted from historical and current

aerial photographs in the midscale assessment and

used to derive patch vulnerability. Patch vulnerability factors were unique for each host-pathogen

or host-insect interaction modeled and included

(1) site quality (differences in ecological site

potential), (2) host abundance, (3) canopy structure, (4) host size, (5) patch vigor, (6) patch

(stand) density. (7) connectivity of host patches,

(8) topographic setting, and (9) logging disturbance.

Site quality was modeled from plant series-level

PVTs as described in Hessburg and others (in

press) and Smith and others (in prep.). Site quality was used as a vulnerability factor because hosts

on poorer sites often are more vulnerable to a particular pathogen or insect disturbance than those

occurring on more productive sites; we used site

quality to capture some of those differences. Host

abundance was used to estimate the proportion of

a patch comprised of vegetation capable of hosting a particular pathogen or insect. Where differences in host susceptibility were known, hosts

were weighted. Host abundance was estimated

from the following photointerpreted attributes:

total crown cover, overstory crown cover, understory crown cover, overstory species, and understory species (appendix 1). Canopy structure was

used as a vulnerability factor to capture the influence of patch vertical structure on pathogen or

insect dispersal and was derived from the following photointerpreted attributes: canopy layers,

overstory species, and understory species.

Host size was used to indicate size of hosts and, in

some cases, to approximate host age, because host

age could not be directly estimated from photointerpretation. Host size was used for a few insects

because tree size thresholds or size ranges were

germane to estimating host vulnerability within

patches. Host size also was used because patch

structural attributes are more likely to change as 

a consequence of disturbance when hosts are large

than when hosts are small. Host size was estimated from the following photointerpreted attributes:

overstory species, understory species, overstory

size class, and understory size class.

Relative differences in patch vigor were represented by the overstory crown differentiation attribute

(appendix 1). Relative differences in stand density

were represented by using the total crown cover

attribute. Connectivity of host patches was estimated by computing the percentage of the area

within a specified dispersal radius comprised of

host patches at a scale of 30 m with raster coverages. Toe-slope topographic settings were modeled

by using the riparian status attribute and a 90-m

70
71

digital elevation model. Environmental attributes

such as site quality and topographic setting aided

in defining the influence of selected biophysical

conditions on vulnerability of vegetation to a disturbance agent. Logging disturbance was represented by type and apparent extent of harvest

(appendix 1).

Modeling change—In brief, the procedure for

quantifying subwatershed vulnerability to an

insect or pathogen disturbance in the midscale

assessment was as follows: (1) we rated patches in

each historical and current subwatershed vegetation coverage for all vulnerability factors specified

for each disturbance agent; (2) we summed factor

ratings for each patch—this sum was the patch

vulnerability rating; (3) we assigned a vulnerability class (low, moderate, or high) to each patch

according to the patch vulnerability rating; and

(4) we computed three FRAGSTATS metrics for

each patch type, where patch types were vulnerability classes %LAND—the percentage of area

within a patch type, MPS—the mean size in

hectares of patches within a patch type, and

PD—the estimated patch density, or number of

patches per 10 000-ha area (see McGarigal and

Marks [1995] for complete descriptions of

FRAGSTATS metrics). These metrics were used

to describe changes in area and connectivity of

area of vulnerability classes in subwatersheds of an

ERU. As described in Hessburg and others (in

press), change from historical to current conditions was estimated as the difference between historical and current conditions, not the percentage

of change from historical conditions. For the

ERU pooling stratum, means, mean standard

errors, and confidence intervals were estimated by

using methods for simple random samples (Steel

and Torrie 1980) with subwatersheds as sample

units. Statistically significant (P≤0.2) change was

determined by examining the 80-percent confidence interval around the mean difference for the

ERU, which was estimated as the simple random 

mean from pairwise comparisons of historical and 

current subwatersheds. If the confidence interval

included zero, no significant change was recorded.

We supplemented this statistical test with two

additional analyses described earlier, which

enabled us to evaluate the potential ecological significance of patch type change in area or connectivity of area. We approximated the historical

range of variation by calculating the historical

sample median 75-percent range for each patch

type metric, and we compared the current sample

median value with this estimate of the historical

range. We also characterized the most significant

changes in absolute area of a patch type within a

sample by using transition analysis. Ecologically

significant change was ultimately determined by

examining each of the three pieces of information.

Ecological Reporting Units

Rationale—In this project, the Forest Service

and Bureau of Land Management were charged

(see the ICBEMP charter in Haynes and others

1996) with developing an ecosystem approach to

guide assessment, planning, and management of

forest, range, and aquatic ecosystems on public

lands within the basin. Early in the assessment

work, it was apparent that assessment teams needed a common geographic framework useful to all

teams for reporting assessment results. Land units

were needed that were broadly homogeneous in

their biophysical and social ecosystem characteristics. A strategy was devised to logically subdivide

the basin study area into geographic areas to

report assessment results, focus management

opportunities, and provide a framework for

implementing planning decisions.

The Northwest Forest Plan (USDA and USDI

1994) used the term “province” to designate geographic areas in western Washington and Oregon

and northern California for analysis, planning,

and management purposes. Province boundaries

in this usage were delineated by using large watershed boundaries. McNab and Avers (1994) also

used the term “province” when mapping sections

of the United States; provinces formed the third

level in the national hierarchical framework of

ecological land units, and province boundaries

were not delineated by hydrography. To avoid further confusion, we adopted the term “ecological

reporting units” to refer to land units delineated

by both biophysical and socioeconomic criteria.

As Odum (1969) suggests, land use policy should

consider ecosystems as the foundation for determining the capacity of any land area to provide

goods and services for people. Furthermore,
ecosystems should be defined at scales appropriate

to ecological and social issues of interest. Ecological land units (sensu McNab and Avers 1994)

provide some of the needed defining characteristics of ecosystems. But ecosystems have terrestrial

and hydrologic dimensions, and ecological land

units as such, do not adequately incorporate the

hydrologic dimension of ecosystems. To that end,

we derived land units at a scale appropriate to

assessing the status of ecosystems given their 

biophysical and social contexts and the need 

to address corresponding issues in a common

environment.

Development—Digital map themes used to

develop ERUs included (1) the nested hierarchy

of subbasins (4th code HUCs), watersheds (5th

code HUCs), and subwatersheds (6th code

HUCs) described earlier (Jensen and others 1997,

Seaber and others 1987); (2) section (McNab and

Avers 1994) and subsection (Jensen and others

1997) biophysical environment maps; and (3)

county maps (USDI 1987).

Three maps were generated initially. The first

map represented reporting units primarily as biophysical environments; section and subsection

boundaries were adjusted to the nearest subwatershed boundary. A second map was created to represent reporting units based on socioeconomic

criteria with counties as basic mapping units.

Counties were grouped into geographic clusters

representative of dominant human uses of natural

resources. County clusters were evaluated against

several biophysical criteria, including precipitation

zones, dominant potential vegetation types, physiognomic types, and major landforms, to further

refine boundaries of county clusters and better

reflect dominant land uses (see Haynes and

Horne 1997).

A third map was developed that emphasized

broad geographic differences in hydrology based

on multivariate analysis of watershed characteristics and stream gauge data; it incorporated

province-scale differences in the zoogeography of

aquatic species. Subbasins having similar hydrologic characteristics and aquatic species assemblages were grouped and mapped (Jensen and

others 1997). Subbasin group boundaries were

adjusted toward the nearest section or subsection

boundary following subbasin boundaries.

All three mapping strategies resulted in highly

similar delineations with comparable numbers

and locations of map units. To create an ERU

map, the three maps were merged into a single

map by using subwatersheds as the mapping unit.

The final map was created as follows: (1) subbasins were aggregated that had > 65 percent of

their area within a section (section boundaries

were developed by aggregating subsections); (2)

subbasins with equal area in two very different

sections were split along subwatershed boundaries; and (3) subbasins with equal area in two

similar sections were grouped with those subbasins having similar base erosion values (Jensen

and others 1997). The resulting ERU map (fig.

23) adequately conserved the integrity of the

three original maps.

We used ERUs in midscale analyses as an initial

pooling stratum for summarizing results of statistical and spatial analysis of subwatershed trends.

This was done as a poststratification procedure

primarily to enable validation of broad-scale

assessment results (Hann and others 1997) and

provide consistency among the assessments in

reporting of results. Subsequent to this project,

we will report results of midscale analysis at the

ecological subregion level (see “Discussion”)

derived through hierarchical clustering and ordination techniques. Broad-scale assessment results

(Hann and others 1997), biophysical environment descriptions (Jensen and others 1997),

results of aquatic and riparian assessment analysis

(Lee and others 1997), terrestrial species analysis

(Marcot and others 1997), social assessment

analysis (McCool and others 1997), and economic analysis (Haynes and Horne 1997) also were

reported at this ERU scale. Figure 24 provides a

map for comparison of ERUs and our original

midscale subbasin sampling strata. Refer to Jensen

and others (1997) for a more complete discussion

of the rationale and development process for

ERUs.

72
73

Figure 23—Ecological reporting units (ERUs) of the interior Columbia River basin broad-scale and midscale assessments.

Shaded areas denote subbasins sampled within each ERU. 
74

Figure 24—Composite of ecological reporting units (A) and Bailey's province-elevation strata (B) for subbasins sampled in the

midscale assessment of the interior Columbia River basin. Shaded areas denote sampled subbasins. 
75

Vegetation

In this first section, we describe ecologically significant22 change in area and connectivity of

patch types, between historical and current vegetation conditions for physiognomic types, cover

types, and structural classes of sampled forest and

rangeland vegetation; results are summarized by

ERU. Ecologically significant change is the primary emphasis; appendix 2 (table 32) provides

complete tabular results of all vegetation change

analysis summarized in this section. Appendix 3

(table 33) shows change in insect and pathogen

disturbance vulnerability classes by ERU. Comparisons among ERUs are provided in the “Discussion” and related tables. We report significant

figures for conventional and spatial statistics to

one decimal place unless otherwise indicated.

Blue Mountains ERU—Subbasins sampled

within the Blue Mountains ERU (figs. 12 to 

14 and 16) included the Burnt (BUR), Lower

Grande Ronde (LGR), Silvies (SIL), Upper

Grande Ronde (UGR), Upper John Day (UJD),

and Wallowa (WAL). Among these subbasins, 

46 historical and current subwatershed pairs were

sampled. 

Physiognomic types—Area in the forest physiognomic type increased from an average of 62.8

to 74.2 percent of the area of the ERU, and area

in woodland increased from an average of 2.7 to

4.2 percent (fig. 25 and appendix 2) Shrubland

area declined from an average of 14.1 to 10.7 percent of the ERU area. Connectivity of woodlands

also increased significantly, with patch size

increasing from an average of 17.4 to 29.8 ha.

Patch density of herblands increased from an

average of 24 to 28.8 patches per 10 000 ha. No

significant change (hereafter, ns) in area of nonforest-non-range and other anthropogenic types

was evident, but patch density declined from an

average of 5.5 to 4.6 patches per 10 000 ha.

Cover types—

Forest—Area and connectivity of grand fir-white

fir and subalpine fir-Engelmann spruce cover

types declined, and that of the Douglas-fir cover

type increased (figs. 26 to 28 and appendix 2).

Average area of the grand fir-white fir cover type

declined from 15.3 percent to 8.4 percent, and

area of subalpine fir-Engelmann spruce declined

from an average of 6.3 percent to 4.4 percent.

Both declines likely were associated with severe

bark beetle outbreaks in those types during the

last decade (Gast and others 1991). Area of whitebark pine-subalpine larch cover increased by an

average of 0.7 percent from 0, and area of

Douglas-fir cover increased substantially from an

average of 7.7 percent to 17.1 percent. Average

patch density of Douglas-fir increased from 11.7

patches to 20.6 patches per 10 000 ha, and mean

patch size increased from an average of 54.4 ha to

107.7 ha. Change in Douglas-fir area and connectivity was the most significant occurring among

forest cover types of the Blue Mountains.

Changes in connectivity of grand fir-white fir and

subalpine fir-Engelmann spruce were nearly as

dramatic. Patch density of the grand fir-white fir

cover type increased from an average of 8 to 11

patches per 10 000 ha, and patch density of subalpine fir-Engelmann spruce increased from an

average of 2.3 to 3.8 patches per 10 000 ha.

22 Statistical significance was assessed at P≤0.2. As described

in “Methods,” we also used transition matrices and an estimate of the historical range of variation for each ERU along

with statistical significance to evaluate “ecological significance” referred to in this section.

Results

Text resumes on page 84
76

Historic

Current

0 20 40 60 80

 *

 *

 *

Other

Forest

Woodland

Shrubland

Herbland

BLUE MTNS.

0 20 40 60 80

 *

 *

 *

Other

Forest

Woodland

Shrubland

Herbland

CENTRAL IDAHO MTNS.

0 10 20 30 40

 *

 *

 *

Other

Forest

Woodland

Shrubland

Herbland

COLUMBIA PLATEAU

0 20 40 60 80 100

Other

Forest

Woodland

Shrubland

Herbland

LOWER CLARK FORK

0 20 40 60 80 100

 *

 *

Other

Forest

Woodland

Shrubland

Herbland

N. CASCADES

0 20 40 60 80 100

Other

Forest

Woodland

Shrubland

Herbland

N. GLACIATED MTNS.

0 20 40 60 80

 *

 *

 *

Other

Forest

Woodland

Shrubland

Herbland

N. GREAT BASIN

0 20 40 60 80 100

 *

 *

 *

Other

Forest

Woodland

Shrubland

Herbland

OWYHEE UPLANDS
77

Historic

Current

0 20 40 60 80

 *

 *

 *

Other

Forest

Woodland

Shrubland

Herbland

SNAKE HEADWATERS

0 20 40 60 80 100

 *

 *

Other

Forest

Woodland

Shrubland

Herbland

S. CASCADES

0 20 40 60 80 100

Other

Forest

Woodland

Shrubland

Herbland

UPPER CLARK FORK

0 20 40 60 80

 *

 *

 *

Other

Forest

Woodland

Shrubland

Herbland

UPPER KLAMATH

0 20 40 60 80

 *

Other

Forest

Woodland

Shrubland

Herbland

UPPER SNAKE

Figure 25—Historical and current distribution of physiognomic types expressed as a percentage of total area on all ownerships

in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate a

significant (P≤0.2) difference between historical and current conditions. 
78

Historic

Current

0 10 20 30 40

Douglas-fir 

Ponderosa pine 

Pinyon/juniper 

Rocky Mtn. juniper 

Western juniper/ 

wood/willow 

Aspen/cottonGrand/white fir 

 *

 *

 *

BLUE MTNS.

0 5 10 15 20 25

Douglas-fir 

Ponderosa pine 

Pinyon/juniper 

Rocky Mtn. juniper 

Western juniper/ 

wood/willow 

Aspen/cottonGrand/white fir 

CENTRAL IDAHO MTNS.

0 5 10 15 20 25 30

Douglas-fir 

Ponderosa pine 

Pinyon/juniper 

Rocky Mtn. juniper 

Western juniper/ 

wood/willow 

Aspen/cottonGrand/white fir 

 *

 *

 *

COLUMBIA PLATEAU

0 10 20 30 40 50 60

Douglas-fir 

Ponderosa pine 

Pinyon/juniper 

Rocky Mtn. juniper 

Western juniper/ 

wood/willow 

Aspen/cottonGrand/white fir 

LOWER CLARK FORK

0 5 10 15 20 25 30

Douglas-fir 

Ponderosa pine 

Pinyon/juniper 

Rocky Mtn. juniper 

Western juniper/ 

Oregon white oak 

Grand/white fir 

 *

 *

 *

 *

N. CASCADES

0 10 20 30 40

Douglas-fir 

Ponderosa pine 

Pinyon/juniper 

Rocky Mtn. juniper 

Western juniper/ 

wood/willow 

Aspen/cottonGrand/white fir 

 *

 *

N. GLACIATED MTNS.

0 5 10 15 20 25 30

Douglas-fir 

Ponderosa pine 

Pinyon/juniper 

Rocky Mtn. juniper 

Western juniper/ 

wood/willow 

Aspen/cottonGrand/white fir 

 *

N. GREAT BASIN

0 2 4 6 8 10 12

Douglas-fir 

Ponderosa pine 

Pinyon/juniper 

Rocky Mtn. juniper 

Western juniper/ 

wood/willow 

Aspen/cottonGrand/white fir 

 *

OWYHEE UPLANDS
79

Historic

Current

0 5 10 15 20 25

Douglas-fir 

Ponderosa pine 

Pinyon/juniper 

Rocky Mtn. juniper 

Western juniper/ 

wood/willow 

Aspen/cottonGrand/white fir 

 *

 *

SNAKE HEADWATERS

0 10 20 30 40

Douglas-fir 

Ponderosa pine 

Pinyon/juniper 

Rocky Mtn. juniper 

Western juniper/ 

wood/willow 

Aspen/cottonGrand/white fir 

S. CASCADES

0 10 20 30 40

Douglas-fir 

Ponderosa pine 

Pinyon/juniper 

Rocky Mtn. juniper 

Western juniper/ 

wood/willow 

Aspen/cottonGrand/white fir 

 *

UPPER CLARK FORK

0 10 20 30 40

Douglas-fir 

Ponderosa pine 

Pinyon/juniper 

Rocky Mtn. juniper 

Western juniper/ 

wood/willow 

Aspen/cottonGrand/white fir 

 *

 *

UPPER KLAMATH

012345

Douglas-fir 

Ponderosa pine 

Pinyon/juniper 

Rocky Mtn. juniper 

Western juniper/ 

wood/willow 

Aspen/cottonGrand/white fir 

UPPER SNAKE

Figure 26—Historical and current distribution of forest and woodland cover types expressed as a percentage of total area on all

ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks

indicate a significant (P≤0.2) difference between historical and current conditions.
80

Historic

Current

01234

western redcedar 

Western hemlock/ 

sugar pine 

Western white/ 

Lodgepole pine 

Western larch 

Pacific silver fir 

BLUE MTNS.

0 2 4 6 8 10 12

western redcedar 

Western hemlock/ 

sugar pine 

Western white/ 

Lodgepole pine 

Western larch 

Pacific silver fir 

 *

CENTRAL IDAHO MTNS.

01234

western redcedar 

Western hemlock/ 

sugar pine 

Western white/ 

Lodgepole pine 

Western larch 

Pacific silver fir 

 *

 *

COLUMBIA PLATEAU

0 5 10 15 20 25

western redcedar 

Western hemlock/ 

sugar pine 

Western white/ 

Lodgepole pine 

Western larch 

Pacific silver fir 

LOWER CLARK FORK

0 2 4 6 8 10 12

western redcedar 

Western hemlock/ 

sugar pine 

Western white/ 

Lodgepole pine 

Western larch 

Pacific silver fir 

 *

 *

 *

N. CASCADES

0 5 10 15 20

western redcedar 

Western hemlock/ 

sugar pine 

Western white/ 

Lodgepole pine 

Western larch 

Pacific silver fir 

 *

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

western redcedar 

Western hemlock/ 

sugar pine 

Western white/ 

Lodgepole pine 

Western larch 

Pacific silver fir 

N. GREAT BASIN

n/a

0 20 40 60 80 100

western redcedar 

Western hemlock/ 

sugar pine 

Western white/ 

Lodgepole pine 

Western larch 

Pacific silver fir 

OWYHEE UPLANDS

n/a
81

Historic

Current

0 5 10 15 20

western redcedar 

Western hemlock/ 

sugar pine 

Western white/ 

Lodgepole pine 

Western larch 

Pacific silver fir 

 *

SNAKE HEADWATERS

0 5 10 15 20 25 30

western redcedar 

Western hemlock/ 

sugar pine 

Western white/ 

Lodgepole pine 

Western larch 

Pacific silver fir 

S. CASCADES

0 5 10 15 20 25

western redcedar 

Western hemlock/ 

sugar pine 

Western white/ 

Lodgepole pine 

Western larch 

Pacific silver fir 

UPPER CLARK FORK

0.0 1.0 2.0 3.0

western redcedar 

Western hemlock/ 

sugar pine 

Western white/ 

Lodgepole pine 

Western larch 

Pacific silver fir 

UPPER KLAMATH

0.0 0.1 0.2 0.3 0.4

western redcedar 

Western hemlock/ 

sugar pine 

Western white/ 

Lodgepole pine 

Western larch 

Pacific silver fir 

UPPER SNAKE

Figure 27—Historical and current distribution of forest cover types expressed as a percentage of total area on all ownerships in

ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.
82

Historic

Current

0 2 4 6 8 10

Mtn. hemlock 

Limber pine 

subalpine larch 

Whitebark pine/ 

Shasta red fir 

subalpine fir 

ngelmann spruce/ 

 *

 *

 *

BLUE MTNS.

0 5 10 15 20 25 30

Mtn. hemlock 

Limber pine 

subalpine larch 

Whitebark pine/ 

Shasta red fir 

subalpine fir 

ngelmann spruce/ 

 *

CENTRAL IDAHO MTNS.

0.0 0.02 0.04 0.06

Mtn. hemlock 

Limber pine 

subalpine larch 

Whitebark pine/ 

Shasta red fir 

subalpine fir 

ngelmann spruce/ 

COLUMBIA PLATEAU

01234

Mtn. hemlock 

Limber pine 

subalpine larch 

Whitebark pine/ 

Shasta red fir 

subalpine fir 

ngelmann spruce/ 

 *

LOWER CLARK FORK

0 5 10 15 20

Mtn. hemlock 

Limber pine 

subalpine larch 

Whitebark pine/ 

Shasta red fir 

subalpine fir 

ngelmann spruce/ 

 *

 *

N. CASCADES

0 5 10 15 20

Mtn. hemlock 

Limber pine 

subalpine larch 

Whitebark pine/ 

Shasta red fir 

subalpine fir 

ngelmann spruce/ *

N. GLACIATED MTNS.

0 20 40 60 80 100

Mtn. hemlock 

Limber pine 

subalpine larch 

Whitebark pine/ 

Shasta red fir 

subalpine fir 

ngelmann spruce/ 

N. GREAT BASIN

n/a

0 20 40 60 80 100

Mtn. hemlock 

Limber pine 

subalpine larch 

Whitebark pine/ 

Shasta red fir 

subalpine fir 

ngelmann spruce/ 

OWYHEE UPLANDS

n/a
83

Historic

Current

0 10 20 30 40

Mtn. hemlock 

Limber pine 

subalpine larch 

Whitebark pine/ 

Shasta red fir 

subalpine fir 

ngelmann spruce/ 

 *

 *

SNAKE HEADWATERS

0 10 20 30 40

Mtn. hemlock 

Limber pine 

subalpine larch 

Whitebark pine/ 

Shasta red fir 

subalpine fir 

ngelmann spruce/ *

S. CASCADES

0 5 10 15 20 25

Mtn. hemlock 

Limber pine 

subalpine larch 

Whitebark pine/ 

Shasta red fir 

subalpine fir 

ngelmann spruce/ 

 *

 *

UPPER CLARK FORK

0 5 10 15

Mtn. hemlock 

Limber pine 

subalpine larch 

Whitebark pine/ 

Shasta red fir 

subalpine fir 

ngelmann spruce/ 

UPPER KLAMATH

0 20 40 60 80 100

Mtn. hemlock 

Limber pine 

subalpine larch 

Whitebark pine/ 

Shasta red fir 

subalpine fir 

ngelmann spruce/ 

UPPER SNAKE

n/a

Figure 28—Historical and current distribution of forest cover types expressed as a percentage of total area on all ownerships in

ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.
Mean patch sizes declined from an average of

136.2 to 54.7 ha, and from 64.8 to 40 ha, respectively. Although there was no significant change

in area of western larch, connectivity declined;

patch density of the existing condition (7.8 patches per 10 000 ha) was nearly double that of the

historical condition (3.8 patches).

In the Blue Mountains, the whitebark pine-subalpine larch cover type was minor among forest

cover types. But in the last 40 to 50 years, area in

this cover type increased by 0.7 percent from 0,

and mean patch size increased by 15.9 ha from 0.

Overall, connectivity of the whitebark pine-subalpine larch cover type increased. Total area occupied by the ponderosa pine cover type changed

little in the last 40 to 50 years, but connectivity

declined; patch density doubled over that period

from 12.2 to 24 patches per 10 000 ha. Juniper

increased in both area and connectivity; average

area increased from 2.7 percent to 4.2 percent 

of the ERU, and mean patch size increased from

17.6 to 29.6 ha. 

Shrubland—Colline low-medium shrub cover

type decreased in area from an average of 7.2 to

4.7 percent of the area of the ERU, and connectivity declined dramatically; patch density increased from an average of 2 to 266.4 patches 

per 10 000 ha, and mean patch size declined from

116.9 to 2.7 ha (figs. 29 to 31 and appendix 2).

Among shrubland cover types, change in area and

connectivity of colline low-medium shrublands

was most significant. Connectivity of montane

low-medium shrub cover also decreased, with

average patch size declining from 47.7 to 32.3 ha.

Herbland—Area in dry meadows declined significantly from 6.2 percent of the ERU area in the

historical condition to 5.3 percent in the existing

condition, and connectivity declined with increased patch density (figs. 29, 32, and 33 and

appendix 2). Patch density of dry meadows

increased from 11 to 14.6 patches per 10 000 ha.

Although there was no significant increase in area

of colline bunchgrasses, connectivity increased;

patch density declined from an average 1.6 to 

1.0 patch per 10 000 ha, and mean patch size

increased from 83.7 to 146.7 ha. In contrast, connectivity of montane bunchgrasses declined; patch

density increased from an average of 5.9 to 8.4

patches per 10 000 ha.

Area in colline exotic grasses and forbs increased

from an average of 0.3 percent of the ERU area in

the historical condition to 1.3 percent in the current condition. Connectivity of this cover type

increased as well; average patch size increased

from 6.3 ha to 34.4 ha during the sample period

(i.e., during the period between our historical and

current vegetation samples). Wet meadow area

declined; percentage of area fell from 0.2 to 0 percent of the ERU, patch density declined from 0.5

to 0.1 patch per 10 000 ha, and mean patch size

declined from 3.6 ha to an average of 0.2 ha.

Finally, patch area comprised of seral grasses and

forbs after logging entry (postlogging-grass-forbs)

increased, and connectivity of area declined. Area

increased from 0 to 0.1 percent, patch density

increased from 0.1 to 5.6 patches per 10 000 ha,

and mean patch size declined from an average of

1.8 to 0.1 ha.

Nonforest-nonrange and other anthropogenic cover

types—Cropland area declined significantly during

the sample period from an average of 2.3 to 1.8

percent of the area; connectivity of cropland area

also declined (figs. 34 and 35 and appendix 2).

Connectivity of pasture lands increased, with

patch density declining from 1.0 to 0.7 patch per

10 000 ha. Area and connectivity of patches of

bare ground burned after logging (postloggingbare ground-burned) also increased. Area increased 0.6 percent from 0, patch density rose

from 0 to 0.7 patch per 10 000 ha, and mean

patch size increased from an average of 5.3 to

10.5 ha.

Structural classes—

Forest—Much change was evident in the pattern

and distribution of forest structural classes; all but

one structural class changed significantly in area

(fig. 36 and appendix 2). Area in stand initiation

and young multistory structures increased, and

area in stem-exclusion open canopy, understory

reinitiation, old multistory, and old single-story

forest structures declined. Nearly all changes in

connectivity of forest structures were significant

reductions, with the exception of stand-initiation

structures. Patch density of stand-initiation structures increased from an average of 10.2 to 17.9

patches per 10 000 ha. Percentage of area in

stand-initiation structures increased from 3.9 to

6.5 percent of the ERU area during the sample

period. Area of stem-exclusion open canopy 

84
85

Text continues on page 106

structures declined from 14.3 to 9.6 percent of

the ERU area. Patch density and mean patch size

also declined significantly, from 29.6 to 25.7

patches per 10 000 ha, and from 51.5 to 41.5 ha,

respectively. Area in understory reinitiation structures declined from an average of 13.6 percent of

the ERU area in the historical condition to 11.2

percent. Area in young multistory structures

increased from an average 21.3 to 29.6 percent.

This increase likely ws associated with historical

selective harvest and removal cutting of medium

and large overstory trees of early seral species such

as ponderosa pine and Douglas-fir.

One of the most significant changes to forest

structure in the Blue Mountains was that occurring in old forests. Area in old multistory structures declined from an average of 2.2 to 1.0

percent of the ERU area. Area in old single-story

structures declined by nearly 63 percent, from 2.7

to 0.9 percent. In the historical vegetation map,

about 8 percent of Blue Mountains forests were

comprised of old multistory and old single-story

structures. Currently, 3 percent of the forest area

is comprised of old forest, a 64-percent reduction

in area.

Woodland—Area and connectivity of woodland

stem-exclusion structures increased. Percentage of

area increased from 2.4 to 4.0 percent of the ERU

area; patch density increased from an average of

4.8 to 6.0 patches per 10 000 ha, and mean patch

size increased from 14.9 to 28.6 ha (fig. 37 and

appendix 2). Understory reinitiation structures

exhibited reduced connectivity; patch density

declined from an average of 1.3 to 0.5 patch per

10 000 ha, and mean patch size declined from

9.7 to 4.6 ha. 

Shrubland—The most significant change occurring in shrubland structures was that exhibited by

open low-medium shrub structures (fig. 38 and

appendix 2). Area in this shrubland structure

declined from an average of 11 to 8.3 percent of

the area of the ERU. Connectivity of open lowmedium shrubs also declined; mean patch size

declined from an average of 96.6 to 61.0 ha.

Connectivity of closed low-medium shrub and

closed tall shrub structures also declined; mean

patch size of sampled subwatersheds declined

from an average of 19.8 to 12.1 ha and from 4.5

to 2.1 ha, respectively.

Herbland—Significant change also occurred in

herbland structures: open herbland area increased

from an average of 6.4 to 8.5 percent, and closed

herbland area declined from an average of 3.2 to

2.5 percent of the ERU area (fig. 38 and appendix 2). Connectivity of open herblands increased

with significantly increased patch density and

mean patch size; patch density increased from an

average of 7.6 to 9.8 patches per 10 000 ha, and

mean patch size increased from 40.8 to 67.3 ha.

Nonforest-nonrange and other types—Area in nonforest-nonrange and other anthropogenic types

declined from 11.1 to 10.0 percent, and patch

density increased from 17.2 to 21.1 patches per

10 000 ha, indicating an overall decline in connectivity of these types (fig. 38 and appendix 2).

Central Idaho Mountains ERU—Subbasins

sampled within the Central Idaho Mountains

ERU (figs. 11, 14, 17, 18, and 22) included the

Boise-Mores (BOM), Big Wood (BWD), Lemhi

(LMH), Lochsa (LOC), Medicine Lodge (MDL),

South Fork Clearwater (SFC), South Fork

Salmon (SFS), and Upper Middle Fork Salmon

(UMS). Among these subbasins, 43 historical and

current subwatershed pairs were sampled.

Physiognomic types—Area in the forest physiognomic type remained constant over the sample

period but connectivity of forests was enhanced;

mean patch size increased from an average of

2,983.7 to 3,457.6 ha, a 16-percent average

increase in size over historical conditions (fig. 25

and appendix 2). The most significant change in

area of any physiognomic type occurred in shrubland, where shrubland area declined from an average of 19.2 to 17.1 percent of the ERU area, an

11-percent loss of historical shrublands. Shrubland losses occurred in both forest and range environments. Loss of early seral shrub structures in

forest settings likely was the result of fire suppression. Change in shrubland connectivity was

insignificant at P≤0.2, but mean patch size

declined from an average of 218.6 to 158.3 ha,

which suggests more fragmented conditions.

Herbland area increased from an average of 3.2 

to 4.5 percent of the ERU area, but connectivity

of herblands declined. Patch density increased

from an average of 9.0 to 13.7 patches per 10 000

ha. Average area in nonforest-nonrange and other

anthropogenic types also increased from 4.2 to

4.9 percent of the ERU area.
86

Historic

Current

0 2 4 6 8 10

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

 *

 *

BLUE MTNS.

0 2 4 6 8 10 12

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs *

CENTRAL IDAHO MTNS.

0 10 20 30 40

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

 *

COLUMBIA PLATEAU

0.0 0.1 0.2 0.3 0.4 0.5

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

LOWER CLARK FORK

0.0 1.0 2.0 3.0

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

N. CASCADES

0.0 0.5 1.0 1.5 2.0

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

 *

N. GLACIATED MTNS.

0 10 20 30 40 50 60

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

 *

N. GREAT BASIN

0 20 40 60 80 100

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

 *

 *

OWYHEE UPLANDS
87

Historic

Current

0 5 10 15 20

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

 *

 *

SNAKE HEADWATERS

0.0 0.05 0.10 0.15 0.20

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

S. CASCADES

0.0 0.5 1.0 1.5

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

UPPER CLARK FORK

0 5 10 15 20 25

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

 *

 *

UPPER KLAMATH

0 20 40 60 80

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

 *

UPPER SNAKE

Figure 29—Historical and current distribution of herbland and shrubland cover types expressed as a percentage of total area on

all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate.

Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.
88

Historic

Current

0.0 0.2 0.4 0.6

mtn. shrubs 

Montane tall 

mtn. shrubs 

Colline tall 

tall shrubs 

Subalpine/alpine 

shrubs 

Montane tall 

Colline tall shrubs 

 *

 *

BLUE MTNS.

012345

mtn. shrubs 

Montane tall 

mtn. shrubs 

Colline tall 

tall shrubs 

Subalpine/alpine 

shrubs 

Montane tall 

Colline tall shrubs 

 *

CENTRAL IDAHO MTNS.

0.0 0.5 1.0 1.5

mtn. shrubs 

Montane tall 

mtn. shrubs 

Colline tall 

tall shrubs 

Subalpine/alpine 

shrubs 

Montane tall 

Colline tall shrubs 

COLUMBIA PLATEAU

01234

mtn. shrubs 

Montane tall 

mtn. shrubs 

Colline tall 

tall shrubs 

Subalpine/alpine 

shrubs 

Montane tall 

Colline tall shrubs 

LOWER CLARK FORK

0.0 0.1 0.2 0.3 0.4

mtn. shrubs 

Montane tall 

mtn. shrubs 

Colline tall 

tall shrubs 

Subalpine/alpine 

shrubs 

Montane tall 

Colline tall shrubs 

 *

 *

N. CASCADES

0.0 0.5 1.0 1.5

mtn. shrubs 

Montane tall 

mtn. shrubs 

Colline tall 

tall shrubs 

Subalpine/alpine 

shrubs 

Montane tall 

Colline tall shrubs 

 *

 *

N. GLACIATED MTNS.

0.0 0.2 0.4 0.6 0.8 1.0

mtn. shrubs 

Montane tall 

mtn. shrubs 

Colline tall 

tall shrubs 

Subalpine/alpine 

shrubs 

Montane tall 

Colline tall shrubs 

N. GREAT BASIN

0.0 0.5 1.0 1.5 2.0 2.5

mtn. shrubs 

Montane tall 

mtn. shrubs 

Colline tall 

tall shrubs 

Subalpine/alpine 

shrubs 

Montane tall 

Colline tall shrubs 

OWYHEE UPLANDS
89

Historic

Current

0 5 10 15 20

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

 *

 *

SNAKE HEADWATERS

0.0 0.05 0.10 0.15 0.20

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

S. CASCADES

0.0 0.5 1.0 1.5

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

UPPER CLARK FORK

0 5 10 15 20 25

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

 *

 *

UPPER KLAMATH

0 20 40 60 80

low-med. shrubs 

Subalpine/alpine 

med. shrubs 

Montane lowmed. shrubs 

Colline lowmoist herbs 

Subalpine/alpine 

herbs 

Montane moist 

olline moist herbs 

 *

UPPER SNAKE

Figure 30—Historical and current distribution of herbland and shrubland cover types expressed as a percentage of total area 

on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate.

Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.
90

Historic

Current

0.0 0.05 0.10 0.15 0.20

subshrubs 

Subalpine/alpine 

subshrubs 

Montane 

wet-site shrubs 

Subalpine/alpine 

site shrubs 

Montane wetsite shrubs 

Colline wetBLUE MTNS.

0.0 0.4 0.8 1.2

subshrubs 

Subalpine/alpine 

subshrubs 

Montane 

wet-site shrubs 

Subalpine/alpine 

site shrubs 

Montane wetsite shrubs 

Colline wet- 

 *

 *

CENTRAL IDAHO MTNS.

0.0 0.10 0.20 0.30

subshrubs 

Subalpine/alpine 

subshrubs 

Montane 

wet-site shrubs 

Subalpine/alpine 

site shrubs 

Montane wetsite shrubs 

Colline wet- *

COLUMBIA PLATEAU

0.0 0.5 1.0 1.5 2.0 2.5

subshrubs 

Subalpine/alpine 

subshrubs 

Montane 

wet-site shrubs 

Subalpine/alpine 

site shrubs 

Montane wetsite shrubs 

Colline wetLOWER CLARK FORK

0.0 0.5 1.0 1.5

subshrubs 

Subalpine/alpine 

subshrubs 

Montane 

wet-site shrubs 

Subalpine/alpine 

site shrubs 

Montane wetsite shrubs 

Colline wetN. CASCADES

0.0 0.2 0.4 0.6 0.8

subshrubs 

Subalpine/alpine 

subshrubs 

Montane 

wet-site shrubs 

Subalpine/alpine 

site shrubs 

Montane wetsite shrubs 

Colline wet- 

 *

 *

 *

N. GLACIATED MTNS.

0.0 0.5 1.0 1.5 2.0

subshrubs 

Subalpine/alpine 

subshrubs 

Montane 

wet-site shrubs 

Subalpine/alpine 

site shrubs 

Montane wetsite shrubs 

Colline wet- 

 *

N. GREAT BASIN

0.0 0.1 0.2 0.3 0.4 0.5

subshrubs 

Subalpine/alpine 

subshrubs 

Montane 

wet-site shrubs 

Subalpine/alpine 

site shrubs 

Montane wetsite shrubs 

Colline wetOWYHEE UPLANDS
91

Historic

Current

01234

subshrubs 

Subalpine/alpine 

subshrubs 

Montane 

wet-site shrubs 

Subalpine/alpine 

site shrubs 

Montane wetsite shrubs 

Colline wetSNAKE HEADWATERS

0 20 40 60 80 100

subshrubs 

Subalpine/alpine 

subshrubs 

Montane 

wet-site shrubs 

Subalpine/alpine 

site shrubs 

Montane wetsite shrubs 

Colline wetS. CASCADES

n/a

0.0 0.2 0.4 0.6 0.8 1.0

subshrubs 

Subalpine/alpine 

subshrubs 

Montane 

wet-site shrubs 

Subalpine/alpine 

site shrubs 

Montane wetsite shrubs 

Colline wet- 

 *

 *

UPPER CLARK FORK

0.0 0.2 0.4 0.6 0.8 1.0

subshrubs 

Subalpine/alpine 

subshrubs 

Montane 

wet-site shrubs 

Subalpine/alpine 

site shrubs 

Montane wetsite shrubs 

Colline wet- 

 *

UPPER KLAMATH

0.0 0.10 0.20

subshrubs 

Subalpine/alpine 

subshrubs 

Montane 

wet-site shrubs 

Subalpine/alpine 

site shrubs 

Montane wetsite shrubs 

Colline wetUPPER SNAKE

Figure 31—Historical and current distribution of shrubland cover types expressed as a percentage of total area on all ownerships

in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate a

significant (P≤0.2) difference between historical and current conditions.
92

Historic

Current

02468

Glacier 

Water 

forb 

Post-fire grass/ 

Alpine meadow 

Dry meadow 

marsh 

Wet meadow/ 

 *

 *

BLUE MTNS.

0.0 0.05 0.10 0.15 0.20

Glacier 

Water 

forb 

Post-fire grass/ 

Alpine meadow 

Dry meadow 

marsh 

Wet meadow/ 

CENTRAL IDAHO MTNS.

0.0 0.2 0.4 0.6

Glacier 

Water 

forb 

Post-fire grass/ 

Alpine meadow 

Dry meadow 

marsh 

Wet meadow/ 

 *

COLUMBIA PLATEAU

0123456

Glacier 

Water 

forb 

Post-fire grass/ 

Alpine meadow 

Dry meadow 

marsh 

Wet meadow/ 

LOWER CLARK FORK

0.0 0.5 1.0 1.5 2.0 2.5

Glacier 

Water 

forb 

Post-fire grass/ 

Alpine meadow 

Dry meadow 

marsh 

Wet meadow/ 

N. CASCADES

0.0 0.2 0.4 0.6 0.8

Glacier 

Water 

forb 

Post-fire grass/ 

Alpine meadow 

Dry meadow 

marsh 

Wet meadow/ 

 *

 *

N. GLACIATED MTNS.

0.0 0.010 0.020 0.030

Glacier 

Water 

forb 

Post-fire grass/ 

Alpine meadow 

Dry meadow 

marsh 

Wet meadow/ 

N. GREAT BASIN

0.0 0.05 0.10 0.15 0.20

Glacier 

Water 

forb 

Post-fire grass/ 

Alpine meadow 

Dry meadow 

marsh 

Wet meadow/ 

 *

OWYHEE UPLANDS
93

Historic

Current

0.0 0.5 1.0 1.5

Glacier 

Water 

forb 

Post-fire grass/ 

Alpine meadow 

Dry meadow 

marsh 

Wet meadow/ 

 *

SNAKE HEADWATERS

0.0 0.5 1.0 1.5 2.0 2.5

Glacier 

Water 

forb 

Post-fire grass/ 

Alpine meadow 

Dry meadow 

marsh 

Wet meadow/ 

 *

S. CASCADES

0.0 0.5 1.0 1.5

Glacier 

Water 

forb 

Post-fire grass/ 

Alpine meadow 

Dry meadow 

marsh 

Wet meadow/ 

UPPER CLARK FORK

01234

Glacier 

Water 

forb 

Post-fire grass/ 

Alpine meadow 

Dry meadow 

marsh 

Wet meadow/ 

UPPER KLAMATH

0.0 0.2 0.4 0.6 0.8

Glacier 

Water 

forb 

Post-fire grass/ 

Alpine meadow 

Dry meadow 

marsh 

Wet meadow/ 

UPPER SNAKE

Figure 32—Historical and current distribution of herbland and nonforest-nonrange cover types expressed as a percentage of total

area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.
94

Historic

Current

02468

exotic grass/forb 

Subalpine/alpine 

grass/forb 

Montane exotic 

grass/forb 

Colline exotic 

bunchgrass 

Subalpine/alpine 

bunchgrass 

Montane 

bunchgrass 

Colline 

 *

BLUE MTNS.

0.0 0.5 1.0 1.5 2.0

exotic grass/forb 

Subalpine/alpine 

grass/forb 

Montane exotic 

grass/forb 

Colline exotic 

bunchgrass 

Subalpine/alpine 

bunchgrass 

Montane 

bunchgrass 

Colline 

 *

 *

CENTRAL IDAHO MTNS.

0 2 4 6 8 10 12

exotic grass/forb 

Subalpine/alpine 

grass/forb 

Montane exotic 

grass/forb 

Colline exotic 

bunchgrass 

Subalpine/alpine 

bunchgrass 

Montane 

bunchgrass 

Colline 

 *

 *

 *

COLUMBIA PLATEAU

0.0 0.1 0.2 0.3 0.4

exotic grass/forb 

Subalpine/alpine 

grass/forb 

Montane exotic 

grass/forb 

Colline exotic 

bunchgrass 

Subalpine/alpine 

bunchgrass 

Montane 

bunchgrass 

Colline 

LOWER CLARK FORK

0.0 0.5 1.0 1.5 2.0

exotic grass/forb 

Subalpine/alpine 

grass/forb 

Montane exotic 

grass/forb 

Colline exotic 

bunchgrass 

Subalpine/alpine 

bunchgrass 

Montane 

bunchgrass 

Colline 

 *

 *

 *

N. CASCADES

0.0 1.0 2.0 3.0

exotic grass/forb 

Subalpine/alpine 

grass/forb 

Montane exotic 

grass/forb 

Colline exotic 

bunchgrass 

Subalpine/alpine 

bunchgrass 

Montane 

bunchgrass 

Colline *

N. GLACIATED MTNS.

0 2 4 6 8 10

exotic grass/forb 

Subalpine/alpine 

grass/forb 

Montane exotic 

grass/forb 

Colline exotic 

bunchgrass 

Subalpine/alpine 

bunchgrass 

Montane 

bunchgrass 

Colline 

 *

N. GREAT BASIN

0 2 4 6 8 10 12

exotic grass/forb 

Subalpine/alpine 

grass/forb 

Montane exotic 

grass/forb 

Colline exotic 

bunchgrass 

Subalpine/alpine 

bunchgrass 

Montane 

bunchgrass 

Colline 

 *

OWYHEE UPLANDS
95

Historic

Current

0123456

exotic grass/forb 

Subalpine/alpine 

grass/forb 

Montane exotic 

grass/forb 

Colline exotic 

bunchgrass 

Subalpine/alpine 

bunchgrass 

Montane 

bunchgrass 

Colline 

 *

 *

SNAKE HEADWATERS

0 20 40 60 80 100

exotic grass/forb 

Subalpine/alpine 

grass/forb 

Montane exotic 

grass/forb 

Colline exotic 

bunchgrass 

Subalpine/alpine 

bunchgrass 

Montane 

bunchgrass 

Colline 

S. CASCADES

n/a

012345

exotic grass/forb 

Subalpine/alpine 

grass/forb 

Montane exotic 

grass/forb 

Colline exotic 

bunchgrass 

Subalpine/alpine 

bunchgrass 

Montane 

bunchgrass 

Colline 

 *

 *

 *

UPPER CLARK FORK

012345

exotic grass/forb 

Subalpine/alpine 

grass/forb 

Montane exotic 

grass/forb 

Colline exotic 

bunchgrass 

Subalpine/alpine 

bunchgrass 

Montane 

bunchgrass 

Colline 

 *

 *

UPPER KLAMATH

0 2 4 6 8 10

exotic grass/forb 

Subalpine/alpine 

grass/forb 

Montane exotic 

grass/forb 

Colline exotic 

bunchgrass 

Subalpine/alpine 

bunchgrass 

Montane 

bunchgrass 

Colline *

UPPER SNAKE

Figure 33—Historical and current distribution of herbland cover types expressed as a percentage of total area on all ownerships

in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate a

significant (P≤0.2) difference between historical and current conditions. 
96

Historic

Current

01234

Dune 

nonveg. floodplain 

Stream channel/ 

Urban/rural 

Cropland 

Pasture 

 *

BLUE MTNS.

0.0 0.2 0.4 0.6

Dune 

nonveg. floodplain 

Stream channel/ 

Urban/rural 

Cropland 

Pasture 

 *

CENTRAL IDAHO MTNS.

0 5 10 15 20 25

Dune 

nonveg. floodplain 

Stream channel/ 

Urban/rural 

Cropland 

Pasture 

COLUMBIA PLATEAU

0.0 0.2 0.4 0.6 0.8

Dune 

nonveg. floodplain 

Stream channel/ 

Urban/rural 

Cropland 

Pasture 

LOWER CLARK FORK

0.0 1.0 2.0 3.0

Dune 

nonveg. floodplain 

Stream channel/ 

Urban/rural 

Cropland 

Pasture 

 *

N. CASCADES

02468

Dune 

nonveg. floodplain 

Stream channel/ 

Urban/rural 

Cropland 

Pasture 

 *

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

Dune 

nonveg. floodplain 

Stream channel/ 

Urban/rural 

Cropland 

Pasture 

N. GREAT BASIN

n/a

0.0 1.0 2.0 3.0

Dune 

nonveg. floodplain 

Stream channel/ 

Urban/rural 

Cropland 

Pasture 

OWYHEE UPLANDS
97

Historic

Current

0.0 0.2 0.4 0.6 0.8

Dune 

nonveg. floodplain 

Stream channel/ 

Urban/rural 

Cropland 

Pasture 

SNAKE HEADWATERS

0.0 0.1 0.2 0.3 0.4 0.5

Dune 

nonveg. floodplain 

Stream channel/ 

Urban/rural 

Cropland 

Pasture 

 *

S. CASCADES

0.0 0.5 1.0 1.5 2.0 2.5

Dune 

nonveg. floodplain 

Stream channel/ 

Urban/rural 

Cropland 

Pasture 

UPPER CLARK FORK

0 5 10 15 20

Dune 

nonveg. floodplain 

Stream channel/ 

Urban/rural 

Cropland 

Pasture 

 *

UPPER KLAMATH

0 5 10 15 20

Dune 

nonveg. floodplain 

Stream channel/ 

Urban/rural 

Cropland 

Pasture 

 *

 *

UPPER SNAKE

Figure 34—Historical and current distribution of anthropogenic and other nonforest-nonrange cover types expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of

the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.
98

Historic

Current

0.0 0.4 0.8 1.2

Rock 

Bare ground 

roadcut 

Bare groundslumps/erosion 

Bare groundGrass/forb-logged 

burned/logged 

Bare ground- 

 *

 *

BLUE MTNS.

012345

Rock 

Bare ground 

roadcut 

Bare groundslumps/erosion 

Bare groundGrass/forb-logged 

burned/logged 

Bare ground- 

 *

 *

CENTRAL IDAHO MTNS.

012345

Rock 

Bare ground 

roadcut 

Bare groundslumps/erosion 

Bare groundGrass/forb-logged 

burned/logged 

Bare groundCOLUMBIA PLATEAU

0.0 0.5 1.0 1.5 2.0

Rock 

Bare ground 

roadcut 

Bare groundslumps/erosion 

Bare groundGrass/forb-logged 

burned/logged 

Bare groundLOWER CLARK FORK

02468

Rock 

Bare ground 

roadcut 

Bare groundslumps/erosion 

Bare groundGrass/forb-logged 

burned/logged 

Bare ground- 

 *

 *

N. CASCADES

01234

Rock 

Bare ground 

roadcut 

Bare groundslumps/erosion 

Bare groundGrass/forb-logged 

burned/logged 

Bare ground- 

 *

 *

 *

N. GLACIATED MTNS.

0.0 0.5 1.0 1.5 2.0

Rock 

Bare ground 

roadcut 

Bare groundslumps/erosion 

Bare groundGrass/forb-logged 

burned/logged 

Bare groundN. GREAT BASIN

012345

Rock 

Bare ground 

roadcut 

Bare groundslumps/erosion 

Bare groundGrass/forb-logged 

burned/logged 

Bare groundOWYHEE UPLANDS
99

Historic

Current

01234

Rock 

Bare ground 

roadcut 

Bare groundslumps/erosion 

Bare groundGrass/forb-logged 

burned/logged 

Bare ground- *

SNAKE HEADWATERS

0 5 10 15 20

Rock 

Bare ground 

roadcut 

Bare groundslumps/erosion 

Bare groundGrass/forb-logged 

burned/logged 

Bare ground- 

 *

 *

S. CASCADES

01234

Rock 

Bare ground 

roadcut 

Bare groundslumps/erosion 

Bare groundGrass/forb-logged 

burned/logged 

Bare ground- 

 *

 *

 *

UPPER CLARK FORK

0.0 0.2 0.4 0.6 0.8

Rock 

Bare ground 

roadcut 

Bare groundslumps/erosion 

Bare groundGrass/forb-logged 

burned/logged 

Bare ground- 

 *

 *

 *

UPPER KLAMATH

0 2 4 6 8 10

Rock 

Bare ground 

roadcut 

Bare groundslumps/erosion 

Bare groundGrass/forb-logged 

burned/logged 

Bare ground- 

 *

UPPER SNAKE

Figure 35—Historical and current distribution of anthropogenic and other nonforest-nonrange cover types expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of

the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.
100

Historic

Current

0123456

OSS 

OMS 

YMS 

UR 

SE 

SI 

 *

 *

BLUE MTNS.

0.0 0.04 0.08 0.12

OSS 

OMS 

YMS 

UR 

SE 

SI 

CENTRAL IDAHO MTNS.

0 5 10 15

OSS 

OMS 

YMS 

UR 

SE 

SI 

 *

COLUMBIA PLATEAU

0 20 40 60 80 100

OSS 

OMS 

YMS 

UR 

SE 

SI 

LOWER CLARK FORK

n/a

0.0 0.2 0.4 0.6 0.8 1.0

OSS 

OMS 

YMS 

UR 

SE 

SI 

 *

 *

N. CASCADES

0.0 0.02 0.04 0.06

OSS 

OMS 

YMS 

UR 

SE 

SI 

N. GLACIATED MTNS.

0 5 10 15 20 25

OSS 

OMS 

YMS 

UR 

SE 

SI 

 *

N. GREAT BASIN

0 2 4 6 8 10

OSS 

OMS 

YMS 

UR 

SE 

SI 

 *

OWYHEE UPLANDS
101

Historic

Current

0.0 0.2 0.4 0.6

OSS 

OMS 

YMS 

UR 

SE 

SI 

SNAKE HEADWATERS

0.0 0.2 0.4 0.6 0.8 1.0

OSS 

OMS 

YMS 

UR 

SE 

SI 

S. CASCADES

0 20 40 60 80 100

OSS 

OMS 

YMS 

UR 

SE 

SI 

UPPER CLARK FORK

n/a

0 2 4 6 8 10 12

OSS 

OMS 

YMS 

UR 

SE 

SI 

 *

 *

UPPER KLAMATH

01234

OSS 

OMS 

YMS 

UR 

SE 

SI 

 *

 *

UPPER SNAKE

Figure 36—Historical and current distribution of forest structural classes expressed as a percentage of total area on all owner- ships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks indi- cate a significant (P≤0.2) difference between historical and current conditions. Structural class codes are SI = stand initiation;

SEOC = stem exclusion, open canopy; SECC = stem exclusion, closed canopy; UR = understory reinitiation; YMS = young multistory; OMS = old multistory; and OSS = old single story.
102

Historic

Current

0 10 20 30 40

OSS 

OMS 

YMS 

UR 

SECC 

SEOC 

SI 

 *

 *

 *

 *

 *

 *

BLUE MTNS.

0 5 10 15 20 25

OSS 

OMS 

YMS 

UR 

SECC 

SEOC 

SI 

 *

 *

CENTRAL IDAHO MTNS.

0 5 10 15

OSS 

OMS 

YMS 

UR 

SECC 

SEOC 

SI 

 *

COLUMBIA PLATEAU

0 10 20 30 40 50

OSS 

OMS 

YMS 

UR 

SECC 

SEOC 

SI 

 *

 *

 *

 *

LOWER CLARK FORK

0 5 10 15 20 25

OSS 

OMS 

YMS 

UR 

SECC 

SEOC 

SI 

 *

 *

N. CASCADES

0 5 10 15 20 25 30

OSS 

OMS 

YMS 

UR 

SECC 

SEOC 

SI 

 *

 *

 *

 *

N. GLACIATED MTNS.

0 2 4 6 8 10

OSS 

OMS 

YMS 

UR 

SECC 

SEOC 

SI 

N. GREAT BASIN

0.0 0.10 0.20 0.30

OSS 

OMS 

YMS 

UR 

SECC 

SEOC 

SI 

OWYHEE UPLANDS
103

Historic

Current

0 10 20 30 40

OSS 

OMS 

YMS 

UR 

SECC 

SEOC 

SI 

 *

 *

SNAKE HEADWATERS

0 10 20 30 40 50 60

OSS 

OMS 

YMS 

UR 

SECC 

SEOC 

SI 

 *

S. CASCADES

0 5 10 15 20 25

OSS 

OMS 

YMS 

UR 

SECC 

SEOC 

SI 

 *

 *

UPPER CLARK FORK

0 5 10 15 20 25 30

OSS 

OMS 

YMS 

UR 

SECC 

SEOC 

SI 

 *

 *

 *

UPPER KLAMATH

0.0 0.5 1.0 1.5 2.0 2.5

OSS 

OMS 

YMS 

UR 

SECC 

SEOC 

SI 

 *

UPPER SNAKE

Figure 37—Historical and current distribution of woodland structural classes expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks

indicate a significant (P≤0.2) difference between historical and current conditions. Structural class codes are SI = stand initiation; SE = stem exclusion; UR = understory reinitiation; YMS = young multistory; OMS = old multistory; and OSS = old single story.
104

Historic

Current

0 5 10 15

Other 

CTS 

OTS 

CLS 

OLS 

CH 

OH 

 *

 *

 *

 *

 *

BLUE MTNS.

0 5 10 15 20

Other 

CTS 

OTS 

CLS 

OLS 

CH 

OH 

 *

 *

 *

CENTRAL IDAHO MTNS.

0 5 10 15 20 25 30

Other 

CTS 

OTS 

CLS 

OLS 

CH 

OH 

 *

 *

 *

 *

COLUMBIA PLATEAU

0 2 4 6 8 10

Other 

CTS 

OTS 

CLS 

OLS 

CH 

OH 

LOWER CLARK FORK

0 5 10 15 20

Other 

CTS 

OTS 

CLS 

OLS 

CH 

OH 

 *

 *

 *

N. CASCADES

0 5 10 15

Other 

CTS 

OTS 

CLS 

OLS 

CH 

OH 

N. GLACIATED MTNS.

0 20 40 60 80

Other 

CTS 

OTS 

CLS 

OLS 

CH 

OH 

 *

 *

N. GREAT BASIN

0 20 40 60 80 100

Other 

CTS 

OTS 

CLS 

OLS 

CH 

OH 

 *

 *

 *

OWYHEE UPLANDS
105

Historic

Current

0 5 10 15

Other 

CTS 

OTS 

CLS 

OLS 

CH 

OH 

 *

 *

SNAKE HEADWATERS

0 5 10 15 20 25 30

Other 

CTS 

OTS 

CLS 

OLS 

CH 

OH 

 *

S. CASCADES

0 2 4 6 8 10

Other 

CTS 

OTS 

CLS 

OLS 

CH 

OH 

 *

 *

 *

UPPER CLARK FORK

0 5 10 15 20 25 30

Other 

CTS 

OTS 

CLS 

OLS 

CH 

OH 

 *

 *

 *

UPPER KLAMATH

0 20 40 60 80

Other 

CTS 

OTS 

CLS 

OLS 

CH 

OH 

 *

 *

UPPER SNAKE

Figure 38—Historical and current distribution of herbland, shrubland, and other structural classes expressed as a percentage of

total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean

estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions. Structural class codes are

OH = open herb; CH = closed herb; OLS = open low-medium shrub; CLS = closed low-medium shrub; OTS = open tall shrub;

CTS = closed tall shrub; and Other = nonforest-nonrange and anthropogenic type structures.
Cover types—

Forest—The Central Idaho Mountains ERU

exhibited relatively minimal change in forest cover

types (figs. 26 to 28 and appendix 2). Only western larch and whitebark pine-subalpine larch

cover types declined in area. For the latter, percentage of area decreased from an average of 5.1

to 2.5 percent of the ERU area. This change was

not statistically significant at P≤0.2, but we found

it ecologically significant when we considered

transition analyses and median 75-percent range

information. Average patch size for the cover type

also declined from 170.8 to 18.3 ha. The noted

loss of whitebark pine-subalpine larch cover

amounted to a 51-percent reduction from historical levels. Area of western larch cover also

declined from an average of 0.5 to 0.3 percent.

Douglas-fir area and connectivity of area increased but change in area was not significant.

Connectivity of Douglas-fir cover increased with

increased patch density; patch density increased

from an average of 16.0 to 19.2 patches per 

10 000 ha. Connectivity of lodgepole pine, 

ponderosa pine, aspen-cottonwood-willow, and

western hemlock-western redcedar cover types

declined.

Shrubland—There were few significant changes in

area, and nearly all changes in shrubland cover

types were losses (figs. 29 to 31 and appendix 2).

Colline low-medium shrub types exhibited dramatically reduced connectivity; patch density

increased from an average of 1.3 to 571.5 patches

per 10 000 ha, and mean patch size declined from

an average of 186.4 to 5.7 ha. This change in

connectivity of colline low-medium shrub types

was the most significant occurring in shrubland

cover types. Area and connectivity of montane

mahogany species declined. Percentage of area fell

from an average of 0.4 to 0.2 percent, and patch

density declined from an average of 1.3 to 0.5

patch per 10 000 ha. Montane tall and colline

wet-site shrub types exhibited reduced connectivity as well; mean patch sizes declined from 35.4 to

17.7 and from 3.9 to 1.7 patches per 10 000 ha,

respectively. Average area in the subalpine-alpine

subshrub cover type, although a minor type,

increased significantly, and connectivity also

increased. Transition analysis revealed that noted

increases in the subalpine-alpine subshrub and

subalpine fir-Engelmann spruce cover types partially compensated for losses observed in the

whitebark pine-subalpine larch cover type.

Herbland—Three significant increases in area were

apparent in central Idaho herblands: average area

in colline and montane bunchgrasses increased

during the sample period from 0.1 to 0.2 percent,

and from 0.7 to 1.2 percent of the ERU area,

respectively, and area in postlogging grasses and

forbs increased from 0 to 0.2 percent of the ERU

area (figs. 29, 32, and 33 and appendix 2). Connectivity of montane bunchgrasses increased with

mean patch size increasing from 6.4 to 11.0 ha.

Connectivity of postlogging-grasses and forbs

declined with declining mean patch size. Increase

in area of montane exotic grass and forbs cover

was not significant, but increased connectivity 

of this cover type was significant; patch density

increased from an average of 0.5 to 1.1 patches

per 10 000 ha. Connectivity of postfire-grasses

and forbs declined likely as a result of fire exclusion in forest settings; mean patch size declined

from 1.7 to 0.8 ha during the sample period. 

Nonforest-nonrange and other anthropogenic cover

types—Area in urban and rural developments

increased from an average of 0 to 0.3 percent of

the ERU area (figs. 34 and 35 and appendix 2).

Connectivity of this type also increased; patch

density increased from an average of 0.2 to 0.4

patch per 10 000 ha, and mean patch size increased from 1.8 to 7.7 ha. Connectivity of pasture lands also increased, with average patch size

increasing from 1.5 to 3.4 ha. Area of postlogging-bare ground-burned cover types increased

from an average of 0.2 to 0.7 percent of the ERU

area. Connectivity of this type also increased with

patch density, rising from 0.7 to 2.7 patches per

10 000 ha.

Structural classes—

Forest—The most significant changes among forest structures were those occurring to stand-initiation and understory reinitiation structures (fig. 36

and appendix 2). Area in stand-initiation structures declined from a 9.7-percent historical level

to 5.9 percent in the existing condition. Less than

three-quarters of the Central Idaho Mountains

ERU was historically or is currently comprised 

of forest. Of that forested area, 13.2 percent was

106
107

historically comprised of stand-initiation structures. Currently, 8 percent of the forested area is

comprised of stand-initiation structures, nearly a

40-percent reduction. This dramatic change is

likely attributable to the exclusion of stand-replacing fires associated with mixed severity and lethal

fire regimes. Connectivity of area in stand-initiation structures also declined. In the historical condition, average mean patch size of stand-initiation

structures was 61.1 ha. In the current condition,

mean patch size was 30.5 ha, which represents a

50-percent reduction. 

In contrast, area in understory reinitiation structures increased from an average of 16 to 21.4 percent. Connectivity of understory reinitiation

structures increased, with patch sizes increasing

from 102.1 to 151.7 ha. Connectivity of young

and old multistory structures declined significantly; mean patch size of young multistory structures

decreased from 75.1 to 62 ha, patch density of

old multistory structures increased from 1.8 to

2.7 patches per 10 000 ha, and mean patch size

declined from 32.6 to 9.3 ha. 

Woodland—No significant changes in area or connectivity of woodland structures were evident at

this reporting scale (fig. 37 and appendix 2). Total

woodland area was 0.1 percent of the total ERU

area in the historical condition, and 0 percent in

the current condition.

Shrubland—Among shrubland structures few

changes were significant. Only area of closed tall

shrub structures declined, with percentage of area

declining from 2.7 to 1.5 percent, a 44-percent

reduction over the sample period (fig. 38 and

appendix 2). Connectivity of open low-medium

and closed tall shrub structures declined. 

Herbland—Area in closed herbland structures

increased from a historical level of 1.7 percent to

2.2 percent in the existing condition, nearly a 30-

percent increase (fig. 38 and appendix 2).

Connectivity of open and closed herbland structures declined; patch density increases were 2.4 

to 3.6 and 4.8 to 6.5 patches per 10 000 ha,

respectively.

Nonforest-nonrange types—Nonforest-nonrange

and other anthropogenic types increased in both

area and connectivity of area (fig. 38 and appendix

2). Average area increased from 4.4 to 5.4 percent, and patch density increased by 23 percent,

from 12.8 to 15.8 patches per 10 000 ha.

Columbia Plateau ERU—Subbasins sampled

within the Columbia Plateau ERU (figs. 9, 10,

12, and 15) included the Lower Crooked (LCR),

Lower John Day (LJD), Lower Yakima (LYK),

Palouse (PLS), and Upper Yakima (UYK). Among

these subbasins, 38 historical and current subwatershed pairs were sampled. 

Physiognomic types—Vast areas of what were

formerly dry grasslands and dry shrublands have

been converted to dryland or irrigated agriculture

in the 20th century in the Columbia Plateau

ERU (fig. 25 and appendix 2). By the time of our

historical photointerpretation, most land cover

conversion had already taken place. Still, considerable change in physiognomic conditions was

evident. Forest area increased from an average of

26.1 to 29.1 percent of the ERU area, representing an 11-percent increase from the historical

condition, but average patch size declined from

1116.2 to 930 ha (ns).

Woodland area increased from a historical level of

6.7 percent to 12.2 percent in the existing condition, representing an 82-percent rise overall.

Woodland connectivity also increased, with mean

patch size more than tripling from an average of

69.9 ha in the historical condition to 220.6 ha 

in the existing condition. The most significant

decline in area of any physiognomic type occurred

in shrublands, where area declined from 32.2 to

23.4 percent, representing a 27-percent reduction

from historical levels. Decline in connectivity 

of shrublands was equally dramatic; mean patch

size fell from 842.8 to 265.9 ha, for an average

decrease of 576.9 ha. 

Cover types—

Forest—Area in ponderosa pine, Douglas-fir, and

western hemlock-western redcedar cover types

increased significantly (figs. 26 to 28 and appendix 2). Ponderosa pine cover increased from 19.2

to 21.4 percent, and area in the Douglas-fir cover

type increased from 3 to 3.9 percent of the ERU

area. Western hemlock-western redcedar cover

increased from 0.4 to 2.2 percent of the ERU

area, representing a fivefold increase. Western
larch, a relatively minor cover type, declined in

area by 90 percent from a 1-percent historical

level to 0.1 percent in the existing condition. As

expected with fire exclusion, connectivity of the

Douglas-fir and western hemlock-western redcedar cover types increased. Average patch density

of Douglas-fir cover increased by 50 percent,

from 2.4 to 3.6 patches per 10 000 ha. Average

patch density of western hemlock-western redcedar cover increased threefold, from 0.3 to 0.9

patch per 10 000 ha.

Woodland—Juniper cover increased by 85 percent, from an average of 6.5 percent in the historical condition, to 12 percent of the land cover in

the existing condition (fig. 26 and appendix 2).

Connectivity of juniper cover also increased significantly; average patch size increased from 60.6

to 208.4 ha. 

Shrubland—Only colline low-medium and colline 

wet-site shrub cover types declined in area. Colline low-medium shrub cover declined from 29.1

to 21.7 percent, for a 25-percent decrease (figs.

29 to 31 and appendix 2). Area in colline wet-site

shrubs declined by 50 percent, from 0.2 to 0.1

percent of the ERU area. Connectivity of colline

low-medium shrubs also declined. Patch density

increased from 5.2 to 1,405.2 patches per 10 000

ha for an average increase of 1,400.1 patches per

10 000 ha, and mean patch size declined from 

a historical level of 838.4 ha to 14.1 ha. In contrast, connectivity of montane low-medium shrub

cover increased. Connectivity of montane tall

shrub cover also declined, with mean patch sizes

dropping from 12.3 to 2.8 ha.

Herbland— Area in colline bunchgrass cover

declined from an 8.3-percent historical level to

6.9 percent of the ERU area (figs. 29, 32, and 33

and appendix 2). Area in montane bunchgrass

cover and colline exotic grasses and forbs increased. Montane bunchgrass cover increased

from 1.3 to 1.8 percent, and colline exotic cover

increased from 0.8 to 2.3 percent of the ERU

area, representing a threefold increase. Connectivity of colline exotic grass and forb cover also

increased; patch density increased from 2.4 to 

4.2 patches per 10 000 ha, and mean patch size

increased from an 11.3-ha historical level to 

29.3 ha. Connectivity of postlogging grasses and 

forbs declined; patch density increased twelvefold

from 0.2 to 2.4 patches per 10 000 ha, and mean

patch size declined by 98 percent.

Nonforest-nonrange and other anthropogenic cover

types—There were no significant changes in area

in this ERU (figs. 34 and 35 and appendix 2).

Connectivity of cropland cover increased; patch

density declined from 7.8 to 4.8 patches per 

10 000 ha, and mean patch size increased from

708.9 to 815.4 ha. Connectivity of urban and

rural development areas declined. Uniquely, area

in water cover increased significantly as did connectivity of that area. The Columbia Plateau ERU

is crisscrossed by ditches and canals constructed

by farmers, ranchers, and the Bureau of Reclamation for irrigation; it is rife with water-holding

“tanks” and ponds. Average area in water cover

increased by 44 percent from 0.3 to 0.4 percent

of the ERU area; average patch density of water

area increased by 64 percent from 0.5 to 0.9

patch per 10 000 ha; and average patch size

increased 26 percent from 13 to 16.4 ha (ns).

Finally, connectivity of exposed rock (such as

scree, talus, cliffs, rimrock) increased; mean patch

size increased from 4.5 to 9.6 ha.

Structural classes—

Forest—Among forest structures, there were many

changes but few were significant at P≤0.2 owing

to high inherent variability of conditions throughout the ERU (fig. 36 and appendix 2). The most

significant change in forest structure was that

occurring to young multistory structures; area

increased from 7.3 to 10.0 percent of the ERU

area, a 37-percent increase from recent historical

conditions: average patch size increased from 54.6

to 81.4 ha, a 48-percent increase from historical

conditions. 

Woodland—As noted earlier, area in woodland

increased by more than 5 percent of the area of

the ERU; that is, an 82-percent increase over historical levels (fig. 37 and appendix 2). Most of the

noted increase in area occurred in stem-exclusion

structures, which increased from 5.9 to 10.9 percent of the ERU area. Connectivity of stem-exclusion structures also increased; mean patch size

increased from 63.8 to 152.7 ha, a 139-percent

increase from historical conditions. No other significant structural changes were observed among

Columbia Plateau woodland structures.

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109

Shrubland—Among all forest and range structures, the most significant changes occurring during the sample period occurred to shrubland

structures, where area in all structural classes

declined (fig. 38 and appendix 2). It is important

to note here that changes to historical dry herblands of the Columbia Plateau have been equally

significant, but most native herblands had already

been lost to dryland wheat production before the

period of historical photointerpretation (see also

Hann and others 1997).

Area of open low-medium and closed low-medium shrub structures declined as did area of open

tall shrubs. Area of open low-medium shrubs

declined from 23.4 to 19.4 percent of the ERU

area, a 17-percent drop. Area of closed low-medium shrub structures declined from 6.9 to 3.3 

percent, a 53-percent drop. Connectivity of 

both low-medium shrub structural classes also

declined. Mean patch size of open low-medium

shrub structures declined from 435.1 to 172.9 ha,

representing a 60-percent reduction; patch density

of closed low-medium shrub structures declined

from 5.2 to 2.9 patches per 10 000 ha, a 43-percent drop from recent historical levels. Likewise,

connectivity of closed tall shrub structures

declined; mean patch size decreased from 14.7 

to 3.7 ha.

Herbland—Among open and closed herbland

structures, only area in open herbland structures

increased during the sample period (fig. 38 and

appendix 2). Although this increase was statistically significant, most native herblands have been

lost to agriculture, and the noted increase is relatively small in comparison. Area in open herbland

structures increased from 7.4 to 9.0 percent.

Connectivity of closed herb structures continued

to decline; mean patch size declined from 41.5 to

23.1 ha. 

Nonforest-nonrange and other types—No significant

change in area of nonforest-nonrange types was

observed but connectivity declined (fig. 38 and 

appendix 2). Patch density decreased from 11.8 

to 9.3 patches per 10 000 ha.

Lower Clark Fork ERU—The Upper Coeur

d’Alene (UCD) was the only subbasin sampled

within the Lower Clark Fork ERU (fig. 7); five

historical and current subwatershed pairs were

sampled.

Physiognomic types—Changes observed among

physiognomic types were not statistically significant because of the small sample size (fig. 25 and

appendix 2).

Cover types—

Forest—Few changes in area were observed among

forest cover types. Douglas-fir cover declined

from 26.4 to 21.1 percent (figs. 26 to 28 and

appendix 2). Although not statistically significant,

we gauged the change as ecologically significant

given results of transition analysis and comparison

to existing conditions with the historical median

75-percent range. Connectivity of the aspencottonwood-willow cover type increased; patch

density increased from 0.6 to 2.2 patches per 

10 000 ha, and mean patch size increased from 

3 to 14.2 ha. Connectivity of the western larch

cover type also increased; patch density increased

from 2.6 to 4.8 patches per 10 000 ha. Area of the

mountain hemlock cover type declined from 1.3

to 0.6 percent of the ERU area, a 54-percent drop,

and connectivity of the cover type declined; patch

density fell from 1.6 to 0.6 patch per 10 000 ha.

Shrubland—Shrubland area in this ERU is apparently small (< 2 percent of the area of the ERU)

based on our sample, and only one change in

shrubland cover types was significant: connectivity of montane wet-site shrubs declined (figs. 29 to

31 and appendix 2). Patch density increased from

4.2 to 8.8 patches per 10 000 ha, and mean patch

size fell from 63.9 to 20.0 ha (ns).

It is interesting that historical area of montane 

tall shrubs declined from 1.6 to 0.3 percent of 

the ERU area. This is not a statistically significant

change, but it would be worthwhile to explore

this relation in greater detail to determine

whether early seral shrub components of forest

communities have been minimized as a consequence of excluding stand-replacing fires from

montane settings. 
Herbland—Only one significant change was

noted among herbland cover types: connectivity

of the postfire grass and forb cover type declined

(figs. 29, 32, and 33 and appendix 2). Patch density fell from 8.8 to 0 patch per 10 000 ha, and

mean patch size dropped from 13.3 to 0 ha.

Historical area of this cover type was 2.9 percent

of the ERU area based on this small sample and

current area is zero, but the change was not statistically significant. As noted above, it would 

be worthwhile to explore this relation in greater

detail to determine whether early seral herb and

forb cover types of forest communities have been

minimized as a consequence of excluding standreplacing fires.

Nonforest-nonrange and other anthropogenic cover

types—Only one change was noted as significant:

connectivity of the postlogging bare groundburned cover type increased (figs. 34 and 35 and

appendix 2). Mean patch size increased from 0.8

to 6.3 ha.

Structural classes—

Forest—Many significant changes were in evidence among forest structures of the Lower Clark

Fork ERU (fig. 36 and appendix 2). In general,

structures associated with early seral forest development declined in area, and those associated

with midseral development increased. In the historical condition, one-third of the ERU was comprised of stand-initiation structures, based on our

sample; stand-initiation represented the dominant

structural condition. Area in stand-initiation

structures declined from 32.7 to 9.5 percent of

the ERU area, and connectivity declined as well;

mean patch size dropped from 208.3 to 24.2 ha.

Average area in stem exclusion-open canopy structures declined from 15.7 to 9.2 percent, and connectivity of this structure likewise declined. Patch

density fell from 28 to 23 patches per 10 000 ha,

and mean patch size dropped from 52.4 to 25.9

ha. In contrast, ERU area in stem exclusionclosed canopy structures substantially increased

from 10.3 to 17.6 percent, an increase of nearly

71 percent over historical conditions. Connectivity of stem exclusion-closed canopy structures

also increased with mean patch size by more than

doubling during the sample period. Mean patch

size increased from 31.8 to 64.4 ha.

Area in understory reinitiation structures increased from a historical level of 16.4 percent 

to 37.7 percent of the ERU area. The noted 

230-percent rise in area of understory reinitiation

structures precipitated replacement of stand initiation as the dominant structural feature of currentday Lower Clark Fork landscapes. Connectivity 

of understory reinitiation structures likewise

increased; average patch density increased from 

24 to 33.8 patches per 10 000 ha. Area in young

multistory structures increased from 14.3 to 

17.5 percent (ns), further indicating an overall

trend toward middle-aged, intermediate forests

across the ERU. Area of old single-story and old

multistory structures increased but changes were

not significant. Connectivity of old single-story

structures declined significantly, though; patch

density increased from 2.8 to 8.2 patches per 

10 000 ha, and mean patch size declined from

39.4 to 18.6 ha.

Shrubland—All changes in shrub structures indicated declining presence, but no changes in area

or connectivity were significant (fig. 38 and

appendix 2)

Herbland—No changes in herbland structure

were significant at this reporting scale (fig. 38 and

appendix 2).

Nonforest-nonrange and other anthropogenic types—

No change was significant at this reporting scale

(fig. 38 and appendix 2).

Northern Cascades ERU—Subbasins sampled

within the Northern Cascades ERU (figs. 5 and

9) included the Methow (MET), Wenatchee

(WEN), Naches (NAC), Upper Yakima (UYK),

and Lower Yakima (LYK). Among these subbasins, 48 historical and current subwatershed

pairs were sampled.

Physiognomic types—Many changes in area

and connectivity of physiognomic types were significant in the Northern Cascades ERU, but forest area and connectivity remained relatively

stable during the sample period (fig. 25 and

appendix 2). Woodland, though a minor type in

the ERU, increased in area by 100 percent; percentage of area increased from 0.3 to 0.7 percent

during the sample period. Connectivity of woodlands also increased; patch density rose from 1.1

110
111

to 1.8 patches per 10 000 ha, and mean patch

size doubled, increasing from 3.2 to 6.5 ha.

Shrubland area and connectivity both declined

but only the latter change was significant. Patch

density rose from 7.2 to 8.7 patches per 10 000

ha, and mean patch size declined (ns). Connectivity of herblands declined dramatically; patch

density increased from 7.6 to 11.0 patches per 

10 000 ha, representing a 43-percent rise over the

sample period, and mean patch size dropped from

78.5 to 55.0 ha. Finally, area and connectivity 

of nonforest-nonrange and other anthropogenic

types increased; area increased from 9.4 to 10.6

percent of the ERU area, and patch density increased from 13.5 to 19.0 patches per 10 000 ha. 

Cover types—

Forest—Significant change in area or connectivity

occurred in most forest cover types. Area of ponderosa pine cover declined from 16.5 to 13.2 percent of the area of the ERU (figs. 26 to 28 and

appendix 2). In the historical condition, ponderosa pine comprised 21 percent of all forest

cover (in the historical condition, 78.8 percent 

of the ERU area was comprised of the forest

physiognomic type). Currently, ponderosa pine

comprises 17 percent of forest cover, representing

an overall decline of 4 percent. Connectivity 

of ponderosa pine cover also fell dramatically:

patch density rose from 7.3 to 8.2 patches per 

10 000 ha, and mean patch size declined from 

an average of 241.3 to 156.1 ha. Concurrently,

area in Douglas-fir cover increased from 23.8 to

25.8 percent, and connectivity declined. Density

of Douglas-fir patches increased from 10.9 to

13.3 patches per 10 000 ha, and mean patch size

fell from an average of 294.1 to 254 ha (ns).

No change in area of the western larch cover type

was evident at this reporting scale, but connectivity of the type declined; patch density increased

from 1.2 to 1.7 patches per 10 000 ha, and mean

patch size remained relatively constant. Though 

a relatively minor cover type within the northern

Cascades ERU, area in the western white pinesugar pine cover type (western white pine in 

the northern Cascades) increased from 0.1 to 0.3

percent of the ERU area. Connectivity of western

white pine cover also increased; patch density 

rose from an average of 0.2 to 0.5 patch per 

10 000 ha, and mean patch size increased from

2.4 to 6.5 ha. Western white pine occurs as a

minor seral component in mixed coniferous

forests in the northern portion of the Cascade

Range. Noted increases likely were the result 

of management efforts in the Wenatchee and

Okanogan National Forests to deploy white pine

blister rust-resistant stock (personal observation,

senior author). Outplanting strategies have

emphasized both phenotypic and genotypic resistance in multiline arrangements and mixed species

plantings.

Area in the whitebark pine-subalpine larch cover

type increased from 3.3 to 4.7 percent of the

ERU area. Connectivity of the type also rose during the sample period; patch density increased

from 4.0 to 4.9 patches per 10 000 ha, and mean

patch size increased from 35.4 to 63.3 ha. Recent

observations from studies of subalpine forests of

the Wenatchee National Forest23 indicate that

mortality of whitebark pine due to white pine

blister rust is evident throughout the cover type,

but it is unknown whether mortality rate and disease progress match that observed in the Rocky

Mountains (Keane and Arno 1993).

Area in the Pacific silver fir and grand fir-white 

fir (grand fir in the Northern Cascades ERU)

cover types increased from 6.0 to 8.3 percent, and

from 1.0 to 2.2 percent, respectively. But connectivity of Pacific silver fir cover declined; patch

density increased from 4.0 to 359.8 patches per

10 000 ha, representing nearly a hundredfold

increase, and mean patch size declined from an

average of 61.5 to 3.6 ha, a 94-percent decrease

from the historical condition. In contrast, connectivity of grand fir cover rose from the historical

condition; patch density more than tripled,

increasing from 1.1 to 3.7 patches per 10 000 ha,

and mean patch size increased from 25.7 to 

33.6 ha, a 31-percent increase from the historical

condition.

Area and connectivity of subalpine fir-Engelmann

spruce cover both declined during the sample

period; area fell from an average of 16.8 to 13.6

percent of the ERU area. Patch density increased

23 Personal communication. 1997. Paul Flanagan, entomologist, U.S. Department of Agriculture, Forest Service,

Wenatchee National Forest, 215 Melody Lane, Wenatchee,

WA 98801.
slightly from 10 to 11.2 patches per 10 000 ha,

and mean patch size declined by almost half from

283.8 to 158.2 ha. Area and connectivity of western hemlock-western redcedar cover also declined

during the sample period. Area fell from 3 to 

2.4 percent, patch density increased from 1.3 to

2.2 patches per 10 000 ha, and mean patch size

declined from 62.9 to 40.2 ha. Finally, connectivity of mountain hemlock cover declined with

mean patch size dropping from 30.4 to 22.8 ha.

Woodland—Although a relatively minor cover

type in the ERU, area in Oregon white oak cover

increased from 0.6 to 0.9 percent of the ERU

area, and patch density rose from 2.1 to 2.8

patches per 10 000 ha (fig. 26 and appendix 2).

No significant change in western juniper cover

was evident at this reporting scale.

Shrubland—No change in area of shrubland cover

types was significant, but several changes in connectivity were significant (figs. 29 to 31 and

appendix 2). Connectivity of colline low-medium

shrub cover declined; patch density increased 

a hundredfold from 1.1 to 105.4 patches per 

10 000 ha, and mean patch size declined by 91

percent from an average of 12.7 to 1.1 ha.

Similarly, connectivity of montane low-medium

shrub cover declined but change was less striking;

mean patch size declined from an average of 5.5

to 4.2 ha. Connectivity of colline mahogany

species cover declined with patch density increasing eightfold. Connectivity of montane mahogany

species cover increased; patch density rose from 0

to 0.2 patch per 10 000 ha, and mean patch size

increased from 0.4 to 1.1 ha. Connectivity of

montane tall shrub cover declined with patch

density falling from 0.1 to 0 patch per 10 000 ha,

and mean patch size declined from 2.6 to 0.7 ha.

Herbland—Changes in herbland cover types

occurred with mixed results. Area and connectivity of montane exotic grasses and forbs increased;

area increased from 0.7 to 0.9 percent of the ERU

area, patch density declined from 0.9 to 0.7 patch

per 10 000 ha, and mean patch size rose from 8.2

to 12.8 ha (figs. 29, 32, and 33 and appendix 2).

Area in postlogging grass and forb cover also increased but connectivity declined; area increased

fourfold from 0.1 to 0.4 percent, patch density

increased from 0.2 to 19.2 patches per 10 000 ha,

and mean patch size fell from 1.6 to 0.2 ha. Harvest practices in recent decades favored extensive

partial cutting, and numerous small harvest units

likely account for these changes.

Area and connectivity of montane bunchgrass

cover both declined; area dropped from 1.0 to 0.7

percent of the ERU, and patch density increased

from 0.9 to 1.5 patches per 10 000 ha. Connectivity of colline bunchgrass cover also declined;

patch density rose from 0.7 to 1.9 patches per 

10 000 ha, and mean patch size fell from 13.7 to

6.7 ha. Of special interest, area and connectivity

of colline exotic grass and forb cover declined;

area dropped from 0.9 to 0.5 percent, and mean

patch size declined from 16.6 to 4.5 ha. Transition analysis indicated that loss in area of the

type was the result of many minor transitions to

other range cover types. It is quite possible that

severely degraded conditions of some herblands 

in the Northern Cascades ERU (caused by sheep

in the late 1880s and early 1900s; Wissmar and

others 1994a, 1994b) improved over the last half

of the 20th century with the advent of improved

grazing management, thereby producing the

observed decline in this cover type.

Nonforest-nonrange and other anthropogenic cover

types—Area and connectivity of urban and rural

developments increased during the sample period;

area rose from 0.1 to 0.3 percent of the ERU

area, patch density increased from 0.2 to 0.7

patch per 10 000 ha, and mean patch size rose

from an average of 4.6 to 9.0 ha (figs. 34 and 35

and appendix 2). Most increase in this type was

associated with fire-prone forest and range ecotones and dry and mesic forest PVTs. Such an

increase in the wildland-urban interface in the

Northern Cascades ERU will pose significant new

challenges to restoring fire regimes and expanding

cover of pyrophytic species.

Area and connectivity of pasturelands declined,

but the former change was not significant. Patch

density of pasture cover increased from 0.3 to 

0.4 patch per 10 000 ha, and mean patch size declined from 7.0 to 2.8 ha. Connectivity of postlogging-bare ground-slumps and erosion cover

declined with patch density, increasing from 2.9

to 3.5 patches per 10 000 ha. These changes indicate that new road construction or reconstruction

112
113

over the sample period has affected more areas,

but affected areas exhibit slightly less exposed soil.

Similarly, percentage of area in postlogging-bare

ground-burned cover increased from 0.5 to 1.5

percent of the ERU area, and connectivity of the

type declined; patch density increased from 0.8 to

5.7 patches per 10 000 ha.These changes indicate

that regeneration timber harvest type activities

have affected more areas over the sample period,

but each affected area exhibits less exposed soil

than was apparent from the historical vegetation

condition. Finally, connectivity of exposed rock

cover increased, with mean patch size rising from

62.4 to 84.2 ha. 

Structural classes—

Forest—Considering all structural classes of forest

and nonforest, changes among forest structures

were the most significant in the Northern

Cascades ERU (fig. 36 and appendix 2). Connectivity of all forest structures changed significantly,

and in most cases, connectivity declined. Area and

connectivity of understory reinitiation structures

increased; percentage of area increased from 17.5

to 19.5 percent in the historical condition, and

patch density increased from 15.7 to 19.5 patches

per 10 000 ha. Increase in understory reinitiation

structures was the only significant increase observed. Although the change was not statistically

significant, we gauged it as ecologically significant

given results of transition analysis and comparison

of existing conditions with the historical median

75-percent range. 

Area and connectivity of old single-story and

multistory structures declined. Percentage of area

in old single-story structures fell from 4.3 to 

2.4 percent, representing a 46-percent decline

from historical conditions. In the historical vegetation coverage, old single-story structures comprised 5.5 percent of the area of the forest

physiognomic condition: in the current vegetation

coverage, old single-story structures comprised 

3 percent of the area of forests. Mean patch size

declined by more than 52 percent from 81.9 to

38.9 ha. Percentage of area in old multistory

structures fell from 5.8 to 2.7 percent, representing a 54-percent decline from historical conditions. In the historical vegetation coverage, old

multistory structures comprised 7.4 percent of 

the area of forests, and in the current vegetation

coverage, old multistory structures comprised 

3.5 percent of the area of forests. Patch density of

old multistory structures increased from 4.5 to

4.9 patches per 10 000 ha (ns), and mean patch

size declined by 74 percent from 145.0 to 37.5 ha.

Connectivity of stand-initiation, stem-exclusion

open and closed canopy, and young multistory

structures declined with significant increases in

patch density, in all cases. Mean patch size declined for each structural class, but only declines

in stem-exclusion open canopy and young multistory structures were significant. In general, the

most significant changes among forest structures

were the significant declines in area of old-forest

structures and dramatically increased fragmentation of all structural classes except understory

reinitiation.

Woodland—Among woodland cover types, only

the Oregon white oak cover type is well distributed in the Northern Cascades ERU (fig. 37 and

appendix 2). Because the range of western juniper

does not extend into this ERU, the juniper cover

type is not represented. Area and connectivity of

oak stem-exclusion structures increased significantly during the sample period. Percentage of

area increased from 0.3 to 0.6 percent, patch density increased from an average of 1.0 to 1.7 patches per 10 000 ha, and mean patch size increased

from 2.3 to 6.3 ha. Overall, it appeared that oak

woodland structures encroached on other shrubland and herbland types. Results of transition

analysis reflected this general trend, but no single

transition was dominant. 

Shrubland—The shrubland physiognomic type

comprised less than 5 percent of the area of this

ERU (fig. 38 and appendix 2). Among shrubland

structures, no change in area of any structural

class was significant, but connectivity of most

shrub structures declined. Connectivity of open

and closed low-medium structures declined with

increasing patch density. Patch density of open

low-medium structures increased from 2.8 to 

3.3 patches per 10 000 ha, and patch density of

closed low-medium structures increased threefold

from 0.4 to 1.3 patches per 10 000 ha. Mean

patch size of open tall structures declined from

3.5 to 0.6 ha.

Herbland—The herbland physiognomic type

comprised less than 7 percent of the area of this

ERU in both the historical and current conditions
(fig. 38 and appendix 2). Among herbland structures, no change in area of any structural class was

significant, but connectivity of all herbland structures declined. Connectivity of open herbland

structures declined with increasing patch density;

patch density of open herb structures increased

from 1.4 to 2.0 patches per 10 000 ha, and patch

density of closed herb structures increased from

1.6 to 2.3 patches per 10 000 ha. Mean patch size

of open herb structures declined from 21.8 to

11.5 ha and mean patch size of closed herb structures declined from 14.3 to 6.5 ha. 

Nonforest-nonrange and other anthropogenic types—

Nonforest-nonrange types increased in area from 

an average of 14.3 to 15.2 percent of the ERU

area (fig. 38 and appendix 2). Connectivity of

these types declined, with patch density increasing

from 17.9 to 25.2 patches per 10 000 ha, and

mean patch size fell from 117.0 to 104.3 ha.

Northern Glaciated Mountains ERU—

Subbasins sampled within the Northern Glaciated

Mountains ERU (figs. 6 to 8) included the Lower

Flathead (LFH), Kettle (KET), Pend Oreille

(PEN), Sanpoil (SPO), Swan (SWN), and Yaak

(YAA). Among these subbasins, 41 historical and

current subwatershed pairs were sampled. 

Physiognomic types—No change in percentage 

of area of any physiognomic type was significant

in this ERU, but connectivity of shrubland, herbland, and nonforest-nonrange and other types

declined (fig. 25 and appendix 2). Patch density

of shrublands increased by 190 percent from an

average of 5 to 9.5 patches per 10 000 ha, and

mean patch size declined by 49 percent from 40.6

to 20.6 ha. Patch density of herblands increased

by 62 percent from 11.1 to 18.0 patches per 

10 000 ha, and mean patch size declined from

93.8 to 65.9 ha (ns). Patch density of nonforestnonrange and other anthropogenic types increased from an average of 12.4 to 17.9 patches

per 10 000 ha, and mean patch size declined from

86.4 to 58.6 ha (ns).

Cover types—

Forest—Many significant changes in area as well

as connectivity were noted among forest cover

types (figs. 26 to 28 and appendix 2). Percentage

of area of shade-tolerant cover species such as

grand fir-white fir (grand fir in the Northern

Glaciated Mountains), subalpine fir-Engelmann

spruce, and western hemlock-western redcedar

cover increased, and area in fire-tolerant and

shade-intolerant western larch and ponderosa 

pine cover declined. Area in the grand fir cover

type rose from 0 to 1.2 percent of the ERU.

Connectivity of grand fir cover also increased;

patch density rose from 0.1 to 2.3 patches per 

10 000 ha, and mean patch size increased by 

525 percent from 3.6 to 18.9 ha. Percentage of

area in subalpine fir-Engelmann spruce cover rose

from 11.5 to 13.2 percent of the ERU. Connectivity of subalpine fir-Engelmann spruce cover

declined; patch density rose by 80 percent from

6.1 to 11.0 patches per 10 000 ha, and mean

patch size fell by 22 percent from 177.6 to 

138.9 ha.

Percentage of area in western larch cover dropped

by 23 percent from 14.8 to 11.4 percent; connectivity of the type declined as well. Patch density

increased from 9.6 to 13.7 patches per 10 000 ha,

and mean patch size fell by 55 percent from

134.4 to 61.1 ha. Similarly, percentage of area in

ponderosa pine cover dropped by 15 percent from

13.4 to 11.4 percent of the ERU area; connectivity of the type declined as well. Patch density increased from 7.7 to 10.3 patches per 10 000 ha,

and mean patch size fell by 28 percent from

151.9 to 108.8 ha (ns). 

Percentage of area in western hemlock-western

redcedar cover increased from 0.7 to 2.8 percent

of the ERU area, a fourfold increase in the cover

type. Connectivity of hemlock-redcedar cover declined; patch density rose from 1.1 to 4.4 patches

per 10 000 ha, and mean patch size fell by 2.1 ha

from 19.1 ha (ns). Connectivity of the Douglasfir, lodgepole pine, and western white pine-sugar

pine (western white pine in this ERU) cover types

declined; patch density of Douglas-fir cover rose

from 16.1 to 23.0 patches per 10 000 ha, patch

density of lodgepole pine cover rose from 9.7 to

13.3 patches per 10 000 ha, and mean patch size

dropped from 68.8 to 52.4 ha. Percentage of area

in western white pine cover declined from 1.5 to 

0 percent; patch density of western white pine cover

declined from 0.6 to 0.2 patch per 10 000 ha, and

mean patch size fell by 92 percent from 21.5 to

1.7 ha. In the historical vegetation coverage, the

western white pine cover type comprised 2 percent

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115

of all forest cover in the Northern Glaciated

Mountains ERU. In the current vegetation coverage, the cover type comprised <0.1 percent of forest cover. Historical photo coverages of sampled

subwatersheds in the Kettle, Sanpoil, Pend

Oreille, Yaak, Swan, and Lower Flathead subbasins span the period of 1932 to 1963, with the

bulk of the aerial photography coming from the

1930s and 1940s (see table 3). Prior to that time,

significant partial cutting of western white pine

had occurred, and by the late 1930s and 1940s,

white pine blister rust already was causing widespread mortality (Monnig and Byler 1992). Our

estimates of the historical extent of this cover type

likely were conservative, but even at that, subsequent harvest and mortality due to white pine

blister rust have significantly minimized this 

ecologically and commercially important cover

species during the period of our sample.

Finally, connectivity of the aspen-cottonwoodwillow (includes maples and birches in this ERU)

cover type increased; patch density rose from 1.2

to 2.6 patches per 10 000 ha, and mean patch

size increased from 8 to 40.8 ha (ns).

Woodland—Woodland cover types represented a

small area in our sample of this ERU. No significant changes in area or connectivity were noted

(fig. 26 and appendix 2).

Shrubland—Shrubland cover types comprised

about 3 percent of the area of the ERU (figs. 29

to 31 and appendix 2). Although a small area,

many changes in area and connectivity of shrub

cover types were significant. Area and connectivity of montane low-medium shrub cover increased;

percentage of area increased from 0 to 0.1 percent

of the ERU area, patch density rose from 0 to 

0.2 patch per 10 000 ha, and mean patch size increased from 0 to 2.2 ha. These results suggested

that a modest recovery from earlier heavy sheep

and cattle grazing may be underway in midelevation shrub cover types. Connectivity of colline

low-medium shrub cover declined during the

sample period; patch density rose from 0.3 to 

5.4 patches per 10 000 ha, and mean patch size

declined from 1.8 to 0.1 ha. Connectivity of subalpine and alpine low-medium shrub cover also

declined; patch density rose from 1.4 to 2.0

patches per 10 000 ha, and mean patch size

declined from 8.4 to 5.1 ha (ns).

Area and connectivity of colline and montane

mahogany cover types declined during the sample

period. Percentage of area of colline mahogany

cover fell from 0.4 to 0 percent, patch density

dropped from 0.4 to 0 patch per 10 000 ha, 

and mean patch size declined from 7.2 to 0 ha.

Colline mahogany cover was undetected in the

current vegetation of sampled subwatersheds.

Likewise, percentage of area of montane mahogany cover fell from 0.2 to 0 percent, patch density dropped from 0.3 to 0 patch per 10 000 ha,

and mean patch size declined from 3.1 to 0 ha.

Montane mahogany cover also was undetected in

the current vegetation of sampled subwatersheds.

Area of colline wet-site shrub cover declined from

0.3 to 0.2 percent, and mean patch size declined

by 43 percent from 9.0 to 5.1 ha. Conversely,

area and connectivity of montane wet-site shrub

cover increased; percentage of area rose from 0.1

to 0.2 percent of the ERU area, patch density

increased from 0.3 to 0.6 patch per 10 000 ha,

and mean patch size nearly doubled increasing

from 4.7 to 8.6 ha. Connectivity of montane tall

shrub cover declined with patch density increasing

threefold from 1.0 to 3.4 patches per 10 000 ha.

Area of subalpine and alpine subshrubs (beargrass) increased 0 to 0.1 percent, patch density

increased from 0 to 10.0 patches per 10 000 ha,

and mean patch size fell from 2.2 to 0.1 ha.

Connectivity of montane subshrubs also declined

with mean patch size falling from 2.8 to 1.2 ha. 

Herbland—Few significant changes were noteworthy among herbland cover types (figs. 29, 32, and

33 and appendix 2). Connectivity of dry meadow

cover increased during the sample period; patch

density increased from 0.1 to 0.4 patch per 

10 000 ha, and mean patch size rose sevenfold

from 0.3 to 2.1 ha. Area and connectivity of

colline bunchgrasses declined; percentage of area

fell by 50 percent from 1.6 to 0.8 percent of the

ERU area. Patch density doubled from 0.7 to 

1.5 patches per 10 000 ha, and mean patch size

de-clined by 72 percent from 34.9 to 9.8 ha. Area

and connectivity of colline exotic grasses and

forbs both increased, but the change in area was

not significant. Patch density rose from 0.9 to 

1.9 patches per 10 000 ha, and mean patch size

increased from 11.8 to 14.0 ha. Area and connectivity of wet meadow cover increased. Percentage
of area rose from 0 to 0.1 percent; patch density

increased from 0.2 to 0.8 patch per 10 000 ha,

and mean patch size increased from 2 to 4.1 ha

(ns). Finally, area in postlogging grasses and forbs

increased and connectivity declined, indicating

increasing number and decreasing size of harvest

units during the sample period. Percentage of area

increased from 0.1 to 0.8 percent of the ERU

area; patch density rose thirtyfold from 0.7 to

21.2 patches per 10 000 ha, and mean patch size

fell from 4.1 to 0.2 ha. 

Nonforest-nonrange and other anthropogenic cover

types—Several changes among the nonforest nonrange and anthropogenic types are noteworthy

(figs. 34 and 35 and appendix 2). Cropland area

increased by 26 percent from 3.4 to 4.3 percent

of the ERU area, but the change was not significant at P≤0.2. Connectivity of cropland area

declined with patch density falling from 4.1 to

3.2 patches per 10 000 ha, and mean patch size

declined from 49 to 47.3 ha (ns). Area and connectivity of pasture lands increased; percentage 

of area increased by 21 percent from 1.4 to 

1.7 percent of the ERU area, patch density fell

from 1.4 to 1.1 patches per 10 000 ha (ns), and

mean patch size increased more than fourfold

from 11.2 to 49.1 ha. These results suggested that

additional native shrublands had been converted

to irrigated pasture during the sample period;

transition analysis confirmed the trend. Area in

urban and rural developments increased from 0.2

to 0.3 percent, but the change was not significant.

Connectivity of urban and rural development

areas increased significantly during the sample

period with patch density rising from 0.8 to 

1.3 patches per 10 000 ha, and mean patch size

doubled from 4.1 to 8.1 ha.

Percentage of area of exposed rock increased from

2.3 to 2.7 percent of the ERU area, but connectivity of rock area declined; patch density nearly

doubled, rising from 4.9 to 9.2 patches per 

10 000 ha, and mean patch size declined from

32.5 to 29.2 ha (ns). Finally, area and connectivity of postlogging-bare ground-burned cover

declined from 2.2 to 0.4 percent, patch density

rose from 1.3 to 3.1 patches per 10 000 ha, and

mean patch size declined from 24.9 to 7.2 ha

(ns). These results further suggest increasing number and decreasing size of harvest units during the

sample period. 

Structural classes—

Forest—Most changes in area and connectivity 

of forest structures were significant (fig. 36 and

appendix 2). Area in stand-initiation and young

multistory structures declined, and area in stemexclusion closed canopy and understory reinitiation structures increased. Nearly all changes in

connectivity reflected drastically increased fragmentation. Percentage of area in stand-initiation

structures fell from 16.9 to 9.4 percent of the

ERU area. In the historical vegetation condition,

stand-initiation structures comprised 21 percent

of all forest cover. In the current condition, standinitiation structures comprise 11.6 percent of forest cover, a 44-percent decline during the sample

period. Patch density increased from 18.3 to 

26.5 patches per 10 000 ha, and mean patch size

decreased by 63 percent, falling from 103.6 to

38.5 ha. These results indicated declining abundance of new forest structure as a consequence 

of excluding stand-replacing fires and increasing

number and decreasing size of harvest units during the sample period.

Conversely, area and connectivity of stem exclusion-closed canopy structures increased. Percentage of area rose from 7.2 to 12.8 percent, representing a 78-percent increase, patch density

increased from 8.6 to 15.0 patches per 10 000 ha,

and mean patch size rose from 61.2 to 71.4 ha

(ns). Connectivity of stem-exclusion open canopy

structures declined with patch density, rising from

18.0 to 27.8 patches per 10 000 ha, and mean

patch size declined by 35 percent from 75.3 

to 49.1 ha. Area in understory reinitiation structures increased from 18.4 to 23.3 percent of the

ERU, and connectivity of area declined; patch

density increased from 12.9 to 22.1 patches per

10 000 ha, and mean patch size declined from

170.6 to 150.7 ha (ns). Area and connectivity 

of young multistory structures both declined.

Percentage of area fell from 25.5 to 22.8 percent,

patch density increased by 46 percent, rising from

22.2 to 32.4 patches per 10 000 ha, and mean

patch size declined by 51 percent, falling from

218.1 to 106.3 ha, but the change was not significant at this reporting scale.

Declines in area of old single-story and multistory

structures were not significant at the scale of the

ERU, but connectivity of old multistory structures

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117

declined significantly. Patch density increased

from 0.5 to 1.2 patches per 10 000 ha, and mean

patch size declined from 22.7 to 7.8 ha. 

Shrubland—Only two changes in shrub structures

were significant at this scale: connectivity of closed

low-medium structures declined (patch density

rose from 0.6 to 1.3 patches per 10 000 ha), 

and mean patch size fell, from 5.6 to 4.5 ha (ns)

(fig. 38 and appendix 2). Connectivity of open

tall structures also declined; patch density rose

from 1.7 to 3.2 patches per 10 000 ha, and mean

patch size fell from 22.9 to 12.5 ha (ns).

Herbland—One change in herb structure was 

significant at this scale: connectivity of closed

structures declined; patch density rose from 6.9 

to 7.9 patches per 10 000 ha, and mean patch

size fell from 38.3 to 27.7 ha (ns) (fig. 38 and

appendix 2).

Nonforest-nonrange and other anthropogenic types—

These types changed significantly in both area

and connectivity (fig. 38 and appendix 2). Percentage of area of nonforest-nonrange and other

anthropogenic types increased by 10 percent, rising from 10.5 to 11.6 percent of the ERU, patch

density increased from 14.7 to 25.1 patches per

10 000 ha, and mean patch size increased by 

245 percent, rising from 90.3 to 221.4 ha, but

the change was not significant at this scale.

Northern Great Basin ERU—The Donner 

und Blitzen (DUB) subbasin was the only one

sampled within the Northern Great Basin ERU

(fig. 16); four historical and current subwatershed

pairs were sampled.

Physiognomic types—Changes in shrubland,

herbland, and woodland physiognomic types were

highly significant, and it is difficult to say which

change was most significant (fig. 25 and appendix

2). Area in woodland increased from 15.3 to 22.2

percent of the ERU, representing a 45-percent

increase during the sample period. Conversely,

percentage of area in shrubland declined from

72.8 to 57.6 percent of the ERU area, a 21-percent decline from historical conditions. Patch

density of shrublands rose from 11.8 to 21.0

patches per 10 000 ha (ns), and mean patch size

declined by 64 percent, falling from 934.1 to

337.1 ha. Herbland area and connectivity each

rose dramatically; area increased threefold, rising

from 3.9 to 12.2 percent of the ERU. Patch density of herblands increased from 15.0 to 21.5

patches per 10 000 ha (ns), and mean patch size

nearly tripled, increasing from 24.4 to 68.6 ha.

Patches interpreted as wet meadow, alpine meadow, dry meadow, grasses and forbs after logging,

pasture, grassland, and grasses and forbs after

burning (wildfire or prescribed) were classified

along with native herblands as “herbland.” Only 

7 percent of the ERU area is forested according 

to our small sample, and changes to area and 

connectivity of forest were insignificant.

Cover types—

Forest—No significant change in area or connectivity of a forest cover type was evident at the ERU

reporting scale (figs. 26 to 28 and appendix 2).

Woodland—Most woodlands in the Northern

Great Basin ERU are juniper woodlands (fig. 26

and appendix 2). Area of juniper cover increased

by 55 percent during the sample period; percentage of area rose from 14.1 to 21.8 percent. Mean

patch size increased from 139.9 to 180.4 ha, but

the change was not significant. 

Shrubland—Nearly all loss of shrubland cover

occurred in the montane low-medium cover type,

where area declined by 26 percent, falling from

51.2 to 37.7 percent (figs. 29 to 31 and appendix

2). Patch density of montane low-medium shrub

cover rose from 16.8 to 22.5 patches per 10 000

ha, and mean patch size declined from 316.1 to

248.1 ha, but neither change was significant at

this reporting scale. Connectivity of colline lowmedium shrub cover declined significantly; patch

density rose from 1.3 to 1411.3 patches per 

10 000 ha, and mean patch size declined modestly from 20.0 to 18.1 percent, but the change was

not significant. These results indicated that colline

low-medium shrub cover area changed little during the sample period, but that the area has

become highly fragmented. Area in montane wetsite shrub cover declined from 1.0 to 0.9 percent

of the ERU, patch density dropped from 5.3 to

4.0 patches per 10 000 ha, and mean patch size

declined from 8.7 to 5.5 ha (ns).

Herbland—Area and connectivity of montane

bunchgrass cover increased significantly; percentage of area rose from 1.1 to 5.5 percent of the
ERU area, patch density increased from 3.0 to 

5.3 patches per 10 000 ha (ns), and mean patch

size rose eightfold from 11.2 to 92.6 ha (figs. 29,

32 and 33 and appendix 2). Area and connectivity of colline exotic grass and forb cover also rose

sharply; percentage of area rose from 0 to 2.5 percent of the ERU, patch density increased from 

0 to 3.3 patches per 10 000 ha, and mean patch

size rose from 0 to 38.5 ha. Area of montane

moist-site herb cover doubled, increasing from

0.6 to 1.2 percent (ns), patch density increased

from 4.8 to 6.0 patches per 10 000 ha, and mean

patch size rose from 8.9 to 14.2 ha (ns).

Nonforest-nonrange and other anthropogenic cover

types—Area with this collection of types was small

in our sample, and observed changes were insignificant (figs. 34 and 35 and appendix 2).

Structural classes—

Forest—No change in area of forest structures was

significant at this scale, but connectivity of closed

canopy stem-exclusion structures increased (fig.

36 and appendix 2). Patch density increased from

2.5 to 3.8 patches per 10 000 ha, and mean patch

size rose from 22.5 to 31.7 ha (ns). 

Woodland—Area in stem-exclusion structures

increased significantly; percentage of area rose

from 15.3 to 22.2 percent, a 45-percent increase

in this structure (fig. 37 and appendix 2). Stem

exclusion was the only woodland structure classified in this ERU. Changes in patch density and

mean patch size of stem-exclusion structures were

insignificant. 

Shrubland—Area and connectivity of open lowmedium shrub structures declined quite significantly; percentage of area fell by 19 percent,

declining from 71.8 to 57.8 percent of the ERU

area; mean patch size fell from 903.8 to 346.1 ha,

for a 62-percent overall decline in mean patch size

during the sample period (fig. 38 and appendix

2). Transition analysis indicated that losses to

shrubland structure were primarily associated 

with woodland and herbland expansion.

Herbland—Area and connectivity of open herb

structures rose dramatically; percentage of area

increased threefold, rising from 3.4 to 10.1 percent, and mean patch size more than doubled, rising from 28.3 to 64.8 ha (fig. 38 and appendix 2).

Owyhee Uplands ERU—Subbasins sampled

within the Owyhee Uplands ERU (figs. 21 to 

22) included the Big Wood (BWD), Crooked

Rattlesnake (CRT), and Upper Owyhee (UOW).

Among these subbasins, 21 historical and current

subwatershed pairs were sampled. 

Physiognomic types—Many significant changes

occurred among physiognomic types (fig. 25 and

appendix 2). The most dramatic change in physiognomic types in the Owyhee Uplands ERU

occurred to shrublands, where area and connectivity both sharply declined. Percentage of area in

shrublands dropped from 88.8 to 81.0 percent.

Nearly 90 percent of the ERU was comprised of

shrublands in the historical condition; the observed decline reflected a net loss of 9 percent.

Connectivity of shrublands declined with patch

density, dropping from 7.9 to 5.7 patches per 

10 000 ha; mean patch size fell from an average

of 4695.3 to 3439.3 ha, a 27-percent decline in

average patch size. Herbland area increased more

than sevenfold from 1.0 to 7.4 percent of the

ERU area; patch density rose from 3.0 to 4.5

patches per 10 000 ha, and mean patch size

increased ninefold from 22.2 to 202.0 ha (ns).

Patches interpreted as wet meadow, alpine meadow, dry meadow, grasses and forbs after logging,

pasture, grassland, and grasses and forbs after

burning (wildfire or prescribed) were classified

along with native herblands as “herbland.”

Transition analyses indicated that loss of shrubland area was associated with expanded woodland and herbland area. Gain in herbland area

occurred primarily in open herbland structures

(see next page).

Woodland area rose from 5.5 to 7.6 percent; connectivity of woodlands also increased. Patch density of woodland declined by more than half from

9.0 to 4.4 patches per 10 000 ha, and mean patch

size increased from 15.9 to 64.4 ha. Increase in

woodland was likely the result of historical fire

exclusion and domestic livestock grazing practices

(see Hann and others 1997). Area in forest was

small in this ERU, and no significant change in

area or connectivity was observed. Connectivity 

of nonforest-nonrange and other anthropogenic

types increased during the sample period. Patch

density fell from 6.7 to 4.5 patches per 10 000 ha,

and mean patch size rose from 53.2 to 86.0 ha. 

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119

Cover types—

Forest—Only two forest cover types were observed

in our sample of this ERU: Douglas-fir and aspen

cottonwood-willow (figs. 26 to 28 and appendix

2). No significant change in area or connectivity

was noted for either cover type, but mean patch

size of aspen-cottonwood-willow cover declined

from 11.7 to 5.4 ha (ns). Because these hardwood

species reside primarily in riparian settings in this

ERU, this observation suggests that agricultural

and grazing practices may have minimized the

average extent of patches of this cover type.

Closer examination of this relation is warranted.

Woodland—Area and connectivity of the juniper

cover type increased during the sample period

(fig. 26 and appendix 2). Percentage of area

increased by 36 percent, rising from 5.5 to 7.5

percent of the ERU area, patch density fell from

9.0 to 4.4 patches per 10 000 ha, and mean patch

size rose fourfold from 15.8 to 64.3 ha.

Shrubland—Only one change in shrubland cover

types was significant: area and connectivity of

colline low-medium shrub cover declined during

the sample period (figs. 29 to 31 and appendix

2). Percentage of area dropped from 87.7 to 

79.3 percent, representing a 10-percent decline;

patch density increased sharply by more than

seven hundredfold from 8.9 to 7007.0 patches

per 10 000 ha, and average patch size fell from

4443.5 to 70.1 ha, for a 98-percent decline 

in mean patch size. 

Herbland—Among herbland cover types, two

changes were significant (figs. 29, 32, and 33 and

appendix 2). Most significant was the increase in

area and connectivity of colline exotic grass and

forb cover. Percentage of area of colline exotic

grass and forb cover rose thirtyfold from 0.2 

to 6.2 percent of the ERU area; patch density

increased from 0.6 to 2.0 patches per 10 000 ha,

and mean patch size increased more than thirtyfold from 5.8 to 195.8 ha. Area and connectivity

of colline moist-site herb cover also increased.

Percentage of area rose fivefold from 0.1 to 0.5

percent of the ERU area; patch density increased

sixfold from 0.1 to 0.6 patch per 10 000 ha, and

mean patch size climbed fourfold from 7.4 to

29.9 ha.

Nonforest-nonrange and other anthropogenic cover

types—Cropland area increased from 1.1 to 

1.4 percent, but the change was not significant 

at P≤0.2 (figs. 34 and 35 and appendix 2). But

cropland connectivity increased significantly during the sample period; patch density dropped

from 0.5 to 0.3 patch per 10 000 ha, and mean

patch size increased by 45 percent from 21.8 to

31.7 ha. Area of exposed rock declined from 2.8

to 1.9 percent (ns), and connectivity of exposed

rock area also declined. Mean patch size fell from

34.3 to 23.5 ha, suggesting substantial recent colonization of rock area by vegetation.

Connectivity of stream channel and nonvegetated flood-plain cover increased; patch density

dropped from 2.3 to 0.7 patch per 10 000 ha, 

for a 65-percent decline, and mean patch size

increased from 6.5 to 8.3 ha (ns). These observations suggest that current flood plains contain

fewer areas of exposed soil than occurred in the

historical vegetation coverage, but areas that occur

tend to be larger. Finally, connectivity of water

cover area increased with mean patch size, rising

from 2.9 to 4.2 ha and representing a 45-percent

increase in average patch size during the sample

period. Area of water cover also increased significantly, but we are not able to show the increase

because we rounded all values to one decimal

place. Increase in water cover area and connectivity likely is associated with creation by ranchers

of irrigation ditches, water holding “tanks,” and

stock ponds.

Structural classes—

Forest—No significant change in area or connectivity of forest structures was in evidence at this

reporting scale (fig. 36 and appendix 2).

Woodland—Among woodland structures, one

change was significant (fig. 37 and appendix 2).

Percentage of area of stem-exclusion structures

rose from 5.2 to 6.5 percent of the ERU area;

patch density declined from 8.8 to 5.3 patches

per 10 000 ha, and mean patch size rose nearly

threefold from 15.4 to 42.2 ha.

Shrubland—Several important changes were

observed among shrubland structures (fig. 38 and

appendix 2). Most noteworthy were changes in

area and connectivity of open low-medium shrub
structures. Percentage of area of open low-medium shrub structures declined by 9 percent, falling

from 85.1 to 77.2 percent of the ERU area; patch

density declined by 35 percent, dropping from

10.0 to 6.5 patches per 10 000 ha, and mean

patch size decreased by 30 percent from 4607.3

to 3232.1 ha. Connectivity of closed low-medium

structures sharply increased. Patch density fell

from 4.7 to 1.6 patches per 10 000 ha, and mean

patch size rose fourfold from 24.3 to 103.8 ha.

Area of open tall shrub structures increased from

0.8 to 1.4 percent of the ERU, nearly a twofold

rise.

Herbland—Area and connectivity of open herbland structures rose dramatically (fig. 38 and

appendix 2). Percentage of area increased from

0.3 to 6.4 percent of the ERU, a twentyfold rise

during the sample period; patch density rose from

1.9 to 3.5 patches per 10 000 ha, an 84-percent

increase. Mean patch size of open herbland structures rose nearly thirtyfold from 6.3 to 183.0 ha. 

Nonforest-nonrange and other types—Overall, area

in these types declined from 5.0 to 4.4 of the

ERU area but the change was not significant at

this reporting scale (fig. 38 and appendix 2).

Connectivity of nonforest-nonrange structures

increased significantly; patch density dropped

from 6.6 to 4.9 patches per 10 000 ha, and mean

patch size rose more than 50 percent from 63.2 to

96.0 ha.

Snake Headwaters ERU—Subbasins sampled

within the Snake Headwaters ERU (fig. 19)

included the Lower Henry’s (LHE), Palisades

(PSD), and Snake Headwaters (SHW). Among

these subbasins, 15 historical and current subwatershed pairs were sampled.

Physiognomic types—Three-quarters of the ERU is

comprised of forest. Changes to area and connectivity of forest were insignificant, but changes to

shrubland and herbland physiognomic types were

significant (fig. 25, and appendix 2). Area and

connectivity of shrublands declined; percentage 

of area declined from 16.3 to 13.9 percent, 

and mean patch size fell from 56.7 to 43.5 ha.

Conversely, area and connectivity of herbland

increased; percentage of area rose by over 

40 percent, from an average of 6.1 to 8.7 percent of the ERU area, and patch density increased 

37 percent, from 21.3 to 29.1 patches per 

10 000 ha. Connectivity of nonforest-nonrange

and other anthropogenic types increased; patch

density dropped from 7.6 to 5.2 patches per 

10 000 ha, and mean patch size rose from 26.6 

to 34.2 ha. 

Cover types—

Forest—Among forest cover types, several changes

were significant during the sample period (figs. 26

to 28 and appendix 2). Area of subalpine firEngelmann spruce and limber pine cover types

increased significantly, and area in aspen-cottonwood-willow and lodgepole pine cover declined.

Area of subalpine fir-Engelmann spruce cover

increased 29 percent from 24.3 to 31.4 percent of

the ERU area, and area of limber pine increased

57 percent, rising from 0.7 to 1.1 percent of the

ERU. Connectivity of limber pine cover also

increased; mean patch size increased from an 

average of 2.3 to 9.9 ha, representing a fourfold

increase in average patch size.

Aspen-cottonwood-willow cover declined from

8.8 to 5.7 percent of the ERU, a 35-percent drop,

and area of lodgepole pine cover fell from 15.6 to

11.3 percent of the ERU area. Connectivity of

aspen-cottonwood-willow cover declined with

reduced mean patch size; average patch size fell

from 38.3 to 26.2 ha. Despite declining area,

connectivity of lodgepole pine cover increased;

patch density fell from 19.1 to 15.4 patches per

10 000 ha, and mean patch size increased from

93.8 to 125.1 ha (ns). Connectivity of whitebark

pine-subalpine larch cover declined significantly;

patch density dropped from 6.0 to 4.1 patches

per 10 000 ha, and mean patch size declined 

from 57.0 to 37.8 ha (ns). Finally, connectivity 

of Douglas-fir cover increased; mean patch size

increased by 45 percent, rising from 96.3 to

139.3 ha.

Woodland—Although juniper is a relatively minor

cover species, its area rose from 0.2 to 0.3 percent; changes in connectivity of juniper cover

were not significant (fig. 26 and appendix 2).

Shrubland—Few significant changes were apparent among shrub cover types, and only the montane low-medium shrub cover type declined in

area (figs. 29 to 31 and appendix 2). Percentage

of area in montane low-medium shrub cover fell

120
121

by 18 percent from 13.0 to 10.7 percent of the

ERU area; changes in connectivity were not significant. Connectivity of montane mahogany

species cover increased during the sample period;

patch density rose from 0 to 0.4 patch per 

10 000 ha, and mean patch size increased from 0

to 2.4 ha. Connectivity of montane wet-site shrub

cover fell with declining mean patch size; average

patch size dropped from 66.1 ha to 49.1 ha during the sample period, a 26-percent decline.

Herbland—Area and connectivity of montane

bunchgrass cover increased, and area of montane

exotic grass and forb cover and subalpine-alpine

moist-site herb cover declined (figs. 29, 32, and

33 and appendix 2). Percentage of area in montane bunchgrass cover increased nearly twofold

from 2.2 to 4.3 percent of the ERU, and patch

density increased from 12.8 to 19.7 patches per

10 000 ha. Percentage of area in montane exotic

grass and forb cover rose from 0.2 to 0.7 percent,

and mean patch size increased sevenfold from 

5.9 to 41.7 ha (ns). Finally, area in montane

moist-site herb cover fell from an average of 1.5

to 1.1 percent of the ERU. 

Nonforest-nonrange and other anthropogenic cover

types—Few changes were significant among nonforest-nonrange types (figs. 34 and 35 and appendix 2). Area of postlogging-bare ground-burned

cover increased significantly, but we are not able

to show the increase because we rounded all values to one decimal place. Connectivity of this

cover type also increased. Patch density increased

from 0 to 0.3 patch per 10 000 ha, and mean

patch size rose from an average of 0 to 1.1 ha.

Connectivity of bare ground associated with 

roadcuts and sidecast (bare ground-roadcut) also

increased, with patch density rising from 0.4 to

0.8 patch per 10 000 ha. 

Structural classes—

Forest—Changes among forest structural classes

were highly significant (fig. 36 and appendix 2).

Stem-exclusion and old-forest structures declined

significantly in area; only area in young multistory structures increased. Percentage of area of

stem-exclusion open canopy structures dropped

from an average of 19.1 to 15.3 percent of the

ERU, and that of stem-exclusion closed canopy

structures fell from 7.9 to 4.8 percent. Connectivity of the latter also declined; patch density

declined by 30 percent from 19.7 to 13.8 patches

per 10 000 ha, and mean patch size dropped by

38 percent from 40.9 to 25.3 ha. Connectivity 

of stand-initiation structures increased during the

sample period; patch density rose from 14.9 to

19.8 patches per 10 000 ha (ns), and mean patch

size doubled from 26.5 to 50.1 ha.

The most substantial change among forest structures in the ERU was that occurring to young

multistory structures, which increased in area and

connectivity of area. Percentage of area increased

40 percent, rising from 22.0 to 30.9 percent of

the ERU during the sample period; patch density

increased by 46 percent from 23.9 to 34.8 patches per 10 000 ha, and mean patch size rose from

145.3 to 269.6 ha, an 86-percent increase. Area

of old multistory structures fell from 3.2 to 

1.8 percent of the ERU area, and area of old 

single-story structures fell from 2.0 to 1.3 percent. Connectivity of old multistory structures

also declined; mean patch size fell by 49 percent

from 27.5 to 13.9 ha during the sample period.

During the time represented by our remotely

sensed historical vegetation map, old multistory

structures comprised 4.3 percent of forest 

structure (the forest physiognomy represented

74.5 percent of the total ERU area); old singlestory structures comprised 2.7 percent of all forest

cover. In the existing condition, those values were

2.4 and 1.8 percent, respectively. Our sample of

the ERU indicated that 40 percent of the historical area of old-forest structures has been lost. 

Woodland—Area of stem-exclusion structures 

rose from 0.1 to 0.3 percent of the ERU, but the

change was not significant (fig. 37 and appendix

2). Connectivity of stem-exclusion structures

changed significantly; patch density rose from 0.4

to 0.6 patch per 10 000 ha, and mean patch size

rose from 1.2 to 7.3 ha (ns). No other change in

woodland structures was significant at this scale. 

Shrubland—Only one change in shrub structures

was significant; area of open low-medium shrub

structure declined by 25 percent, dropping from

9.3 to 7.0 percent of the ERU (fig. 38 and appendix 2).
Herbland—Only one change in herb structures

was significant; area and connectivity of open

herb structures increased (fig. 38 and appendix

2). Percentage of area increased more than

twofold, rising from 1.8 to 4.2 percent of the

ERU; patch density increased by 76 percent from

10.0 to 17.6 patches per 10 000 ha, and mean

patch size rose more than sevenfold from 12.6 

to 90.2 ha. 

Nonforest-nonrange and other anthropogenic types—

Connectivity of nonforest-nonrange types increased; patch density dropped from 7.7 to 

5.4 patches per 10 000 ha, and mean patch size

increased by more than 50 percent, rising from

25.1 to 37.9 ha (fig. 38 and appendix 2).

Southern Cascades ERU—Subbasins sampled

within the Southern Cascades ERU (fig. 15)

included the Little Deschutes (LDS) and Upper

Deschutes (UDS). Between these subbasins, 16

historical and current subwatershed pairs were

sampled. 

Physiognomic types—Many changes among

physiognomic types occurred in this ERU (fig. 25

and appendix 2). Two of the most significant

changes were highly correlated. Area of forest

increased from 80.5 to 88.3 percent of the ERU,

and area of nonforest-nonrange and other anthropogenic types declined from 18.4 to 8.1 percent.

Increase in forest area and decline in nonforestnonrange area was associated with forest regrowth

from extensive tractor logging of ponderosa pine

cover types conducted before the time of the historical photointerpretations. 

Woodland area rose from 0 to 0.4 percent during

the sample period. Although this change was not

statistically significant, we regarded it as ecologically significant, given results of transition analysis

and the comparison of existing conditions with

the historical median 75-percent range. Connectivity of woodland also increased; patch density

rose from 0 to 0.2 patch per 10 000 ha, and

mean patch size increased from 0.1 to 21.1 ha

(ns). As noted in many other ERUs, connectivity

of shrubland declined; patch density rose from

0.9 to 1.9 patches per 10 000 ha, and mean patch

size fell from 49.6 to 11.8 ha (ns). 

Herbland area and connectivity increased during

the sample period. Percentage of area climbed

more than fourfold, rising from an average of 0.6

to 2.7 percent of the ERU area, patch density rose

more than fivefold from 3.6 to 19.4 patches per

10 000 ha, and mean patch size remained stable.

Most increase in herbland was associated with

increased area in the postlogging-grass and forb

cover type. Less than 1 percent (0.5 percent) of

the area of the ERU was comprised of shrubland

in the historical condition. Percentage of area

remained relatively stable during the sample period, but connectivity of shrubland declined; patch

density increased from 0.9 to 1.9 patches per 

10 000 ha, and mean patch size fell from 49.6 to

11.8 ha (ns). Because shrublands were a relatively

minor type, they are not addressed further in this

section. 

Cover types—

Forest—Few significant changes in forest cover

types occurred during the sample period (figs. 26

to 28 and appendix 2). Area and connectivity of

subalpine fir-Engelmann spruce cover increased;

percentage of area rose from an average of 0 to

0.2 percent of the ERU area; patch density rose

from 0 to 0.4 patch per 10 000 ha, and mean

patch size increased from 0 to 8.9 ha. Area of

Shasta red fir increased from 0.2 to 0.4 percent,

but the change was not significant. Connectivity

of red fir declined significantly; patch density rose

from 0.1 to 1.3 patches per 10 000 ha, and mean

patch size fell from an average of 14.4 to 4.1 ha.

Area and connectivity of whitebark pine-subalpine larch cover increased; percentage of area

rose from 0 to 0.8 percent. Although the change

in area was not statistically significant, we regarded it as ecologically significant given results of

transition analysis and comparison of existing

conditions with the historical median 75-percent

range. Patch density of whitebark pine-subalpine larch cover rose from 0 to 0.3 patch per 

10 000 ha, and mean patch size increased from 

0 to 20.5 ha (ns).

Connectivity of lodgepole pine cover increased

significantly; patch density rose from 5.2 to 

7.3 patches per 10 000 ha, and mean patch size

remained stable. Connectivity of sugar pine-western white pine cover (both species occur in the

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123

Southern Cascades ERU) declined significantly;

patch density rose from 0.6 to 1.1 patches per 

10 000 ha, and mean patch size remained stable.

Area of ponderosa pine cover rose and connectivity declined during the sample period. Percentage

of area in ponderosa pine cover increased from

22.7 to 28.1 percent. The change in area was not

statistically significant at P≤0.2, but we regarded

it as ecologically significant given results of transition analysis and comparison of existing conditions with the historical median 75-percent range.

The observed increase in ponderosa pine cover

was associated with regrowth of forest (described

above). Connectivity of ponderosa pine decreased

significantly; patch density rose from 5.8 to 

10.9 patches per 10 000 ha, and mean patch size

declined. Connectivity of Douglas-fir cover also

declined; patch density doubled from 0.9 to 

1.8 patches per 10 000 ha, and mean patch size

declined.

Woodland—Juniper cover increased from 0 to 

0.4 percent, and mean patch size rose from 0 to

20.8 ha, but neither change was significant at

P≤0.2 (fig. 26 and appendix 2).

Herbland—Dry meadows comprised a relatively

small area of the ERU, but area and connectivity

of dry meadows both increased during the sample

period (figs. 29, 32, and 33 and appendix 2).

Percentage of area rose from 0 to 0.1 percent,

patch density rose from 0.4 to 0.8 patch per 

10 000 ha, and mean patch size remained stable.

Connectivity of wet meadows also increased;

patch density rose from 2.6 to 4.3 patches per 

10 000 ha, and mean patch size remained unchanged. Area in postlogging grass and forb cover

increased from an average of 0 to 1.6 percent of

the ERU, and patch density rose from 0 to 42.1

patches per 10 000 ha.

Nonforest-nonrange and other anthropogenic cover

types—Area and connectivity of urban and rural

developments increased; percentage of area rose

during the sample period from 0 to 0.3 percent 

of the ERU, patch density increased fourfold

from 0.1 to 0.4 patch per 10 000 ha, and mean

patch size increased more than fourfold from 4.1

to 18.6 ha (figs. 34 and 35 and appendix 2). As

noted above in the discussion of changes among

physiognomic types, the principal decline in 

nonforest-nonrange types was that occurring to

postlogging-bare ground-burned areas. Percentage 

of area declined during the sample period from

10.1 in the historical vegetation coverage to 

1.8 percent in the existing condition; decline was

associated with regrowth of ponderosa pine as

noted above. Patch density increased more than

threefold, rising from 2.8 to 10.6 patches per 

10 000 ha, and mean patch size dropped from

749.3 to 8.5 ha (ns), a 99-percent decline in average patch size from historical conditions. 

Structural classes—

Forest—Two changes in area were significant, but

most significant were changes to connectivity of

forest structures (fig. 36 and appendix 2). With

few exceptions, forest structures were more highly

fragmented in the current condition than in the

historical condition, with large changes noted to

both mean patch size and patch density. Area in

stand-initiation structures increased slightly, but

the change was not significant. Connectivity of

stand-initiation structures declined. Patch density

rose by more than 350 percent, from an average

of 6.8 to 24.3 patches per 10 000 ha, and mean

patch size dropped from 171.5 to 75.4 ha (ns).

Connectivity of stem-exclusion open canopy

structures also declined. Patch density more than

doubled from 8.6 to 19.2 patches per 10 000 ha,

and mean patch size dropped by 43 percent from

150.5 to 86.5 ha. In contrast, area and connectivity of stem-exclusion closed canopy structures

increased substantially; percentage of area rose

nearly tenfold from 0.5 to 4.8 percent as a result

of the regrowth of ponderosa pine; patch density

rose from 0.9 to 4.8 patches per 10 000 ha, and

mean patch size increased from 19.2 to 116.7 ha.

Area and connectivity of understory reinitiation

structures declined; percentage of area fell from

10.3 to 8.7 percent (ns); patch density rose from

5.6 to 9.2 patches per 10 000 ha, and mean 

patch size dropped by 54 percent from 232.6 to

106.6 ha. Connectivity of young multistory structures also declined. Patch density rose from 7.6 to

17.3 patches per 10 000 ha, and mean patch size

remained stable.

Area of old single-story structure increased during

the sample period. This likely occurred because a

considerable area of the sampled subbasins resides
in congressionally designated wilderness, is administratively withdrawn from the timber base, 

or is otherwise roadless and has not been entered

for timber harvest. The primary effect of management in these areas is that of forest aging with the

exclusion of most fire disturbances. Percentage of

area of old single-story structures rose from 1.6 to

3.7 percent of the ERU, a 131-percent increase

during the sample period, and patch density rose

from 1.1 to 2.9 patches per 10 000 ha.

Woodland—Area and connectivity of woodland

stem-exclusion structures increased (fig. 37 and

appendix 2). Percentage of area rose from 0 to 

0.4 percent, and patch density rose from 0 to 

0.2 patch per 10 000 ha. 

Shrubland—No changes in area or connectivity 

of shrubland structures were significant at this

reporting scale (fig. 38 and appendix 2).

Herbland—No changes in area or connectivity of

herbland structures were significant at this reporting scale (fig. 38 and appendix 2).

Nonforest-nonrange and other anthropogenic types—

As noted earlier, area and connectivity of nonforest-nonrange structures declined significantly (fig.

38 and appendix 2). Percentage of area fell from

an average of 19.5 to 11.2 percent of the ERU

area; patch density rose from 14.4 to 40.5 patches

per 10 000 ha, and mean patch size declined from

856.6 to 40.4 ha (ns). This decline of nonforest–

nonrange structures was associated with regrowth

of forest structures on postlogging-bare groundburned cover types.

Upper Clark Fork ERU—Subbasins sampled

within the Upper Clark Fork ERU (figs. 8 and

11) included the Blackfoot (BFM), Bitterroot

(BTR), and Flint Rock (FLR). Among these subbasins, 32 historical and current subwatershed

pairs were sampled.

Physiognomic types—Few changes in physiognomic conditions were noteworthy (fig. 25 and

appendix 2). More than 85 percent of the historical and current area of the ERU was forested.

Area and connectivity of forests remained relatively stable during the sample period. As with most

other ERUs, connectivity of shrubland and herbland declined; shrubland patch density rose from

3.7 to 4.6 patches per 10 000 ha, and mean patch

size fell from 60.5 to 31.4 ha (ns). Shrublands

comprised less than 3 percent of the historical or

current area. Herbland patch density rose from

13.8 to 18.2 patches per 10 000 ha, and mean

patch size fell from 33.6 to 28.7 ha (ns). Herblands comprised less than 6 percent of the historical or current area. Area and connectivity of

nonforest-nonrange and other anthropogenic

types increased during the sample period, but

change in area was not significant at P≤0.2. Patch

density rose from 8.0 to 10.5 patches per 10 000

ha, and mean patch size was relatively stable. 

Cover types—

Forest—Few changes in area of forest cover types

were significant at this reporting scale (figs. 26 to

28 and appendix 2). The most significant increase

was that occurring to area of subalpine firEngelmann spruce; percentage of area rose from

14.2 to 17.3 percent. Connectivity of subalpine

fir-Engelmann spruce cover declined; patch 

density increased from 13.6 to 16.5 patches per

10 000 ha, and mean patch size remained unchanged. Connectivity of western larch cover 

also declined; patch density rose from 3.8 to 

6.6 patches per 10 000 ha, a 74-percent increase,

and mean patch size remained unchanged.

Area of whitebark pine-subalpine larch cover

declined by 19 percent from 4.3 to 3.5 percent 

of the ERU area. The most significant decrease 

in area observed for any forest cover type was that

occurring to area of ponderosa pine; percentage 

of area declined from 12.3 to 9.5 percent of the

ERU area, a 23-percent decrease during the sample period. Connectivity of ponderosa pine cover

also declined; patch density remained relatively

stable, and mean patch size declined by 50 percent from 155.6 to 78.2 ha.

Area and connectivity of limber pine cover

increased but the change in area was not significant; percentage of area rose from 0 to 0.4 percent, patch density increased from 0.1 to 

0.3 patch per 10 000 ha, and mean patch size

increased from 3.4 to 7.7 ha (ns). Area of the

Douglas-fir cover type remained stable during the

sample period but connectivity declined; patch

density increased from 14.8 to 17.6 patches per

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125

10 000 ha, and mean patch size declined by 

37 percent, falling from 417.1 to 262.9 ha.

Finally, connectivity of mountain hemlock cover

increased; patch density increased from 0 to 

0.1 patch per 10 000 ha, and mean patch size

rose from 0 to 4.5 ha. 

Shrubland—Overall, area and connectivity of

shrub cover types declined in the Upper Clark

Fork ERU, but only a few changes were significant (figs. 29 to 31 and appendix 2). Areas of

montane mahogany species cover and montane

subshrub (beargrass) cover both declined. Percentage of area of montane mahogany species cover

fell from 0.1 to 0 percent, and connectivity

declined. Patch density of montane mahogany

cover fell from an average of 0.3 to 0 patch per 

10 000 ha, and mean patch size declined from an

average of 1.9 to 0.6 ha, for a 68-percent decrease

in average patch size. Percentage of area in montane subshrub cover likewise fell from 0.3 to 

0 percent, and connectivity declined. Patch density of montane subshrub cover declined by 87 percent, falling from 0.8 to 0.1 patch per 10 000 ha,

and mean patch size remained stable.

Connectivity of colline low-medium shrub cover

declined; patch density rose more than fortyfold

from 0.5 to 21.1 patches per 10 000 ha, and

mean patch size declined by 98 percent from 9.7

to 0.2 ha. Connectivity of montane low-medium

shrub cover increased during the sample period;

patch density increased from 0.5 to 0.7 patch per

10 000 ha, and mean patch size more than tripled

from 6.3 to 19.8 ha (ns). Connectivity of montane tall shrub cover likewise increased during the

sample period; patch density increased from 0.5

to 0.9 patch per 10 000 ha, and mean patch size

remained constant. Finally, area of subalpine and

alpine wet-site shrub cover, a relatively minor

cover component, increased, and connectivity

declined; percentage of area increased from 0 percent in the historical condition by an amount less

than 0.1 percent; patch density declined from 0.1

to 0 patch per 10 000 ha, and mean patch size

fell from 0.8 to 0 ha, for 100-percent declines in

patch density and average patch size. 

Herbland—Several changes in area and connectivity of herbland cover types were significant

(figs. 29, 32, and 33 and appendix 2). Area and

connectivity of montane bunchgrass cover declined. Percentage of area declined by 42 percent

during the sample period, dropping from 3.1 to

1.8 percent of the ERU area. Patch density of

montane bunchgrass cover fell from 8.4 to 

7.3 patches per 10 000 ha, and mean patch size

dropped from 23.9 to 13.6 ha, for a 43-percent

decline in average patch size. Area of montane

exotic grass and forb cover increased and connectivity declined. Percentage of area rose from 0.1 

to 0.2 percent of the ERU, representing a doubling in area. Patch density of montane exotic

grass and forb cover tripled, rising from 0.4 to 

1.2 patches per 10 000 ha, and mean patch size

remained relatively stable.

Connectivity of montane and subalpine-alpine

moist-site herb cover types increased; patch density increases were from 1.8 to 2.3, and from 0.1 

to 0.6 patch per 10 000 ha, respectively. Mean

patch sizes of both cover types also increased, 

but changes were not significant at P≤0.2. Finally,

area of herb cover resulting from harvest activities

(postlogging-grasses and forbs) increased but connectivity of that area declined. Percentage of area

of postlogging-grass and forb cover rose from 0 

to 0.9 percent of the ERU area; patch density increased more than one hundredfold from 0.3 to

40.5 patches per 10 000 ha, and mean patch size

fell by 79 percent from 1.9 to 0.4 ha. These latter

changes indicate that during the sample period,

harvest activities within the ERU affected many

more areas, but harvest units are typically smaller

today (79 percent smaller) than was apparent in

the historical photos.

Nonforest-nonrange and other anthropogenic cover

types—Area of urban and rural development

increased slightly, but the change was not significant (figs. 34 and 35 and appendix 2). Connectivity of urban and rural development areas increased; patch density doubled during the sample

period from 0.3 to 0.6 patch per 10 000 ha, and

mean patch size increased from 1.2 to 2.0 ha (ns).

Area and connectivity of postlogging-bare groundburned cover increased. Percentage of area rose

from 0.1 to 1.5 percent of the ERU area, representing a fifteenfold increase; patch density

increased more than fourfold from 0.5 to 2.3

patches per 10 000 ha, and mean patch size rose
fivefold from 3.1 to 15.9 ha. Finally, connectivity

of water cover increased; patch density rose from

1.5 to 1.8 patches per 10 000 ha, and mean patch

size remained constant.

Structural classes—

Forest—The most significant loss of area was associated with stand-initiation structures, which fell

by 30 percent, from 15.9 to 11.1 percent of the

ERU area (fig. 36 and appendix 2). Stand-initiation structures historically comprised 18 percent of forest structure; currently they comprise

13 percent of forest structure. Patch density of

stand-initiation structures remained constant and

mean patch size declined from 69.8 to 50.8 ha,

indicating declining connectivity. This loss in area

and connectivity of stand-initiation structures

most likely was associated with effective fire prevention and suppression and the substitution of

small regeneration cutting units for larger standreplacing fires.

Connectivity of stem-exclusion open canopy

structures also declined; patch density rose from

27.5 to 35.3 patches per 10 000 ha; mean patch

size declined by 28 percent, falling during the

sample period from 78.2 to 56.3 ha. In contrast,

area and connectivity of stem-exclusion closed

canopy structures increased; percentage of area

swelled by 26 percent, rising from 16.7 to 

21.1 percent of the ERU area, patch density

remained stable, and mean patch size rose by 

255 percent from 157.9 to 402.9 ha. Both area

and connectivity of understory reinitiation structures declined, but only the change in connectivity was significant. Percentage of area fell from

15.6 to 14.0 percent (ns); patch density rose from

16.3 to 19.8 patches per 10 000 ha, and mean

patch size declined by 30 percent, falling from 

an average of 97.6 to 68.6 ha.

Area of old multistory structures declined slightly

from 0.6 to 0.4 percent of the ERU, and area of

old single-story structures increased slightly from

0.2 to 0.3 percent, but neither change was significant at P≤0.2. Connectivity of old single-story

structures increased significantly. Patch density

rose from 0.5 to 1.0 patch per 10 000 ha (ns) and

mean patch size increased fourfold from 1.1 ha to

4.5 ha.

Shrubland—Only one significant decline in shrub

structure was observed: area of closed tall shrub

structures fell from 0.5 to 0.3 percent of the ERU

area (fig. 38 and appendix 2). No significant

change in connectivity of these structures was

observed. Connectivity of open tall shrub structures increased; patch density increased from 2.0

to 2.7 patches per 10 000 ha, and mean patch

size remained relatively constant. 

Herbland—Area and connectivity of closed herb

structures declined; percentage of area fell from

3.5 to 2.1 percent of the ERU area, patch density

remained stable, and mean patch size declined

from an average of 25.9 to 15.3 ha, for an average

decline of 41 percent (fig. 38 and appendix 2).

Nonforest-nonrange and other anthropogenic types—

Area and connectivity of these types increased

(fig. 38 and appendix 2). Percentage of area

increased by 49 percent, rising from 5.3 to 

7.9 percent of the ERU, patch density increased

by 68 percent, rising from 8.7 to 14.6 patches per 

10 000 ha, and mean patch size remained stable.

The observed rise in area and connectivity was

mostly driven by increasing area of postloggingbare ground-burned cover. 

Upper Klamath ERU—Subbasins sampled

within the Upper Klamath ERU (fig. 20) included the Lost (LST) and Upper Klamath Lake

(UKL). Between these subbasins, 12 historical

and current subwatershed pairs were sampled.

Physiognomic types—About one-half of the area 

of this ERU was forested in both the historical

and current vegetation coverages; shrublands

comprised one-fifth of the area; and herblands,

woodlands, and other nonforest-nonrange types

each comprised about one-tenth of the area 

(fig. 25 and appendix 2). Percentage of area of

forest declined by 6 percent, falling from 50.5 

to 47.5 percent of the ERU area. Connectivity of

forest also declined; patch density fell from 7.8 to

5.9 patches per 10 000 ha, and mean patch size

remained stable. Woodland area and connectivity

increased. Percentage of woodland area rose

sharply by 52 percent from 8.4 to 12.8 percent 

of the ERU area. Woodland patch density fell

from 10.6 to 9.0 patches per 10 000 ha, and

mean patch size increased threefold from 58.0 

to 189.2 ha.

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127

Shrubland area and connectivity both declined,

but neither change was significant. Percentage 

of area declined from 21.4 to 18.8 percent (ns);

patch density fell from 20.5 to 18.1 patches per

10 000 ha (ns), and mean patch size dropped

from 275.8 to 116.8 ha (ns). These seemingly

large changes were not statistically significant

because highly dissimilar subwatersheds were

pooled at this large reporting scale. Similarly,

herbland area and connectivity declined, but 

none of the changes was significant. Area and

connectivity of nonforest-nonrange and other

anthropogenic types both increased significantly.

Percentage of area of nonforest-nonrange climbed

by 32 percent from 9.1 to 12.0 percent; patch

density rose from 3.9 to 6.9 patches per 

10 000 ha, and mean patch size more than 

doubled, increasing from 160.2 to 338.7 ha.

Cover types—

Forest—Ponderosa pine comprised 53 percent of

the historical forest vegetation and 49 percent of

the current forest vegetation, for a net decline of

4 percent during the sample period (figs. 26 to 28

and appendix 2). Percentage of area of ponderosa

pine cover dropped from 26.7 to 23.5 percent of

the ERU area. Change in connectivity of ponderosa pine cover was not significant at this

reporting scale, but mean patch size fell from

387.3 to 256.7 ha. Connectivity of Douglas-fir

cover declined; patch density remained stable, and

mean patch size dropped by 68 percent from 31.9

to 10.3 ha. Connectivity of mountain hemlock

cover also declined; patch density remained stable,

and mean patch size dropped by 21 percent from

308.0 to 242.9 ha. No other change in area or

connectivity of forest cover types was significant

at this reporting scale. 

Woodland—Virtually all woodland identified

through photointerpretation was juniper woodland (fig. 26 and appendix 2). Area and connectivity of juniper woodlands increased significantly

during the sample period. Percentage of area

climbed by 52 percent, from 8.4 to 12.8 percent

of the ERU area, patch density declined from

10.6 to 8.9 patches per 10 000 ha, and mean

patch size rose threefold from 58 to 189.2 ha. 

Shrubland—Few changes among shrub cover

types were significant (figs. 29 to 31 and appendix 2). Area and connectivity of montane lowmedium shrub cover declined, but connectivity

changes were not significant at P≤0.2. Percentage

of area of montane low-medium shrub cover fell

by 19 percent, from 18.5 to 14.9 percent of the

ERU area. Connectivity of colline low-medium

shrub cover declined; patch density rose sharply

by nearly thirtyfold, from 4.7 to 139.0 patches

per 10 000 ha, and mean patch size plummeted

by 90 percent from 13.4 to 1.4 ha. Finally, area

and connectivity of montane wet-site shrub cover

declined significantly during the sample period.

Percentage of area fell from an average of 0.6 to

0.4 percent of the ERU area, patch density

declined from 1.5 to 0.8 patch per 10 000 ha,

and mean patch size dropped from 35.8 to 

29.5 ha (ns). 

Herbland—Many area and connectivity changes

were significant among herbland cover types (figs.

29, 32, and 33 and appendix 2). Area and connectivity of montane bunchgrass cover declined

significantly during the sample period. Percentage

of area fell from an average of 0.7 to 0.4 percent

of the ERU; patch density remained unchanged,

and mean patch size dropped by 65 percent, 

from an average of 26.3 to 9.1 ha. Area of colline

bunchgrass cover also declined during the sample

period. Percentage of area fell from 2.8 to 1.0 percent of the ERU, for a net loss of 64 percent of

the cover type area. Area of colline exotic grass

and forb cover increased from 0 to 0.4 percent of

the ERU area, but the change was not statistically

significant at P≤0.2. But connectivity of colline

exotic grass and forb cover increased significantly;

patch density rose from 0.1 to 0.4 patch per 

10 000 ha, and mean patch size increased from

1.5 to 18.8 ha (ns). Because of our relatively small

sample size of 12 subwatershed pairs, observed

changes in percentage of area and mean patch size

of colline exotic grass and forb cover were not significant at P≤0.2, but the changes suggest increasing area and connectivity of exotic grass and forb

cover in colline elevation settings and warrant a

closer look. 

Area and connectivity of colline moist-site herb

cover declined significantly during the sample

period. Percentage of area fell by 91 percent from

an average of 1.1 to 0.1 percent of the ERU area;

patch density remained unchanged, and mean

patch size dropped from an average of 49.2 to 
3.2 ha, for a net decline in mean patch size of 

93 percent. Connectivity of montane moist-site

herb cover also declined; patch density rose from

an average of 1.9 to 2.9 patches per 10 000 ha,

and mean patch size remained unchanged. Finally,

area of postlogging grass and forb cover increased

and connectivity of that cover declined. Percentage of area rose from 0 to 0.1 percent of the

ERU area, patch density climbed more than seventyfold from 0.1 to 7.4 patches per 10 000 ha,

and mean patch size plummeted from 1.9 to 

0.1 ha, for a net decline of more than 95 percent.

Nonforest-nonrange and other anthropogenic cover

types—Connectivity of most anthropogenic cover

types increased, and area in only a few significantly increased (figs. 34 and 35 and appendix 2).

The most dramatic increase in area was associated

with cropland cover; percentage of area rose

sharply by 50 percent from an average of 7.0 

to 10.5 percent of the ERU area. Connectivity 

of cropland area also increased; patch density

remained stable, but mean patch size climbed

from 187.0 to 384.8 ha, for a net rise in average

patch size of 106 percent. Connectivity of pasture

cover increased; patch density dropped from 0.3

to 0 patch per 10 000 ha, and mean patch size

rose from an average of 702.3 ha in the historical

condition to 898.1 ha in the existing condition

(ns).

Connectivity of urban and rural developments increased; patch density remained unchanged, and

mean patch size rose threefold from 1.2 to 3.8 ha.

Area and connectivity of postlogging-bare groundburned cover increased; percentage of area rose

from an average of 0 to 0.4 percent of the ERU

area, patch density rose from 0.1 to 2.9 patches

per 10 000 ha, and mean patch size remained

unchanged.

Structural classes—

Forest—Several changes in area and connectivity

of forest structures were significant (fig. 36 and

appendix 2). Area of stand-initiation structures

increased by 89 percent, but the observed change

in area was not statistically significant at P≤0.2;

percentage of area rose from an average of 1.9 

to 3.6 percent of the ERU area. Connectivity of

stand-initiation structures increased significantly;

patch density remained unchanged, and mean

patch size doubled from 31.2 to 62.1 ha. Because

half of the forest cover is ponderosa pine, we

would expect that the dominant disturbance

influence on vegetation patterns in the historical

condition would be nonlethal surface fires and

area in stand-initiation structures would be small,

as was observed. Increased connectivity of standinitiation structures likely is the result of expanding area of stand-replacing fires and regeneration

harvest.

Connectivity of stem-exclusion closed canopy

structures declined; patch density rose by 76 percent from an average of 2.1 to 3.7 patches per 

10 000 ha, and mean patch size remained unchanged. Area and connectivity of understory

reinitiation structures increased. Change in area

was not statistically significant at P≤0.2, but we

regarded the change as ecologically significant

given results of transition analysis and comparison

of existing conditions with the historical median

75-percent range. Percentage of area rose by 

45 percent from an average of 5.6 to 8.1 percent

of the ERU area; patch density increased by 

52 percent from an average of 6.9 to 10.5 patches

per 10 000 ha; and mean patch size rose nearly

sevenfold from an average of 42.9 to 292.3 ha,

but the change was not statistically significant at

P≤0.2. In contrast, area of young multistory

structures declined; percentage of area dropped 

22 percent from an average of 21.1 to 16.4 percent of the ERU area. Mean patch size of young

multistory structures dropped sharply from 401.1

to 163.9 ha, but the change was not statistically

significant at P≤0.2.

Perhaps the most significant changes to area and

connectivity of forest structure occurred to oldforest structures. Percentage of area of old multistory structures rose from 4.3 to 5.5 percent of

the ERU area (ns); patch density nearly doubled,

increasing from an average of 3.5 to 6.6 patches

per 10 000 ha, and mean patch size fell from 46.1

to 34.1 ha (ns). Area and connectivity of old single-story structures declined significantly. Percentage of area fell by 35 percent, declining from an

average of 7.4 to 4.8 percent of the ERU area.

Patch density of old single-story structures increased by 82 percent, from an average of 3.9 to

128
129

7.1 patches per 10 000 ha, and mean patch 

size fell by 67 percent, dropping from 69.6 to

22.7 ha. In the historical vegetation coverage, 

old multistory structures comprised 8.5 percent 

of forest structure; they currently comprise 

11.6 percent, but the difference is not statistically

significant. In the historical vegetation coverage,

old single-story structures comprised 14.5 percent

of forest structure; they currently comprise 

10 percent. Overall, old-forest structures comprised 23 percent of forest structure in the historical vegetation coverage. In the current coverage,

old-forest structures comprise 21.7 percent of 

forest structure.

Woodland—Nearly all changes in area and 

connectivity of woodland structures indicated

expanding woodlands (fig. 37 and appendix 2).

Area of stand-initiation, stem-exclusion, understory reinitiation, and old multistory structures

increased during the sample period, but the

observed change in area of old multistory structures was not significant. Percentage of area of

stand-initiation structure rose nearly threefold,

from 0.4 to 1.1 percent of the ERU area. Change

in area was not statistically significant at P≤0.2,

but we regarded the change as ecologically significant given results of transition analysis and comparison of existing conditions with the historical

median 75-percent range. Area of stem-exclusion

structure increased; percentage of area rose from

5.9 to 7.6 percent of the ERU area. Area and connectivity of understory reinitiation structure also

increased. Percentage of area rose nearly twofold

from 2 to 3.8 percent; patch density increased

from 2.8 to 3.4 patches per 10 000 ha, and mean

patch size rose more than sixtyfold from 5.3 to

330.1 ha (ns). 

Shrubland—No significant change in area of 

any shrub structure was apparent in the Upper

Klamath ERU (fig. 38 and appendix 2). The 

most substantial change occurring to area of

shrub structures was associated with open lowmedium structure; percentage of area declined

from 18.5 to 15.9 percent. Connectivity of closed

low-medium and open tall structures increased

significantly. Patch density of closed low-medium

structures fell from an average of 3.6 to 1.4 patches per 10 000 ha, and mean patch size rose threefold from 24.8 to 73.1 ha. Patch density of open

tall structures declined from 3.2 to 1.9 patches

per 10 000 ha, and mean patch size remained 

unchanged. Connectivity of closed tall structures

declined; patch density declined from 1.3 to 

0.6 patches per 10 000 ha, and mean patch size

dropped from an average of 9.2 to 4.3 ha, for 

a net decrease of 53 percent.

Herbland—Area of open and closed herbland

structures declined during the sample period (fig.

38 and appendix 2). Percentage of area of open

herbland fell by 63 percent from an average of 3.8

to 1.4 percent of the ERU area. Percentage of area

in closed herbland fell by 31 percent from an

average of 1.6 to 1.1 percent of the ERU area. 

Nonforest-nonrange and other anthropogenic types—

Area and connectivity of these types rose sharply

(fig. 38 and appendix 2). The observed increase in

area was associated with expanded cropland area

during the sample period. Percentage of area in

nonforest-nonrange and other anthropogenic

types rose by 31 percent from an average of 13.9

to 18.2 percent of the ERU area. Patch density

doubled, increasing from 4.5 to 9.1 patches per

10 000 ha, and mean patch size climbed sharply

by 85 percent, rising from an average of 340.8 to

630.1 ha.

Upper Snake ERU—Subbasins sampled within

the Upper Snake ERU (figs. 18 to 19 and 22)

included the Lower Henry’s (LHE), Lake Walcott

(LWC), and Medicine Lodge (MDL). Among

these subbasins, 15 historical and current subwatershed pairs were sampled.

Physiognomic types—According to our sample of

remotely sensed historical vegetation conditions,

three-quarters of the area of the Upper Snake

ERU was shrubland, 10 percent of the area was

herbland, 10 percent was comprised of nonforestnonrange and other anthropogenic types, and the

combined area of forest and woodland was about

5 percent (fig. 25 and appendix 2). The most substantial change in area of any physiognomic type

occurred in shrublands; percentage of area fell

from 73.8 to 68.5 percent, representing a net loss

of 7 percent of the historical area of the type. The

observed change in area was not statistically significant at P≤0.2, but we regarded the change as

ecologically significant given results of transition

analysis and comparison of existing conditions
with the historical median 75-percent range.

Native shrublands were lost primarily to expanding cropland area. Area of nonforest-nonrange

and other anthropogenic types increased by a corresponding amount owing to the noted increase

in croplands. Percentage of cropland area rose

from an average of 10.3 to 15.4 of the ERU area.

Although forests represented a relatively minor

area, forest area and connectivity both increased

significantly. Percentage of area rose from an average of 2.4 to 3.2 percent of the ERU, and mean

patch size increased by 60 percent, rising from

26.6 to 42.5 ha.

Cover types—

Forest—No change in area of any forest cover type

was significant, but connectivity of aspen-cottonwood-willow cover increased (figs. 26 to 28 and

appendix 2). Patch density remained unchanged,

and mean patch size increased from 5.5 to 7.0 ha.

Connectivity of Douglas-fir cover also increased;

patch density declined from an average of 2.7 to

1.3 patches per 10 000 ha, and mean patch size

increased threefold from an average of 13.0 to

39.8 ha (ns).

Woodland—Upper Snake ERU woodlands were

comprised of juniper and pinyon-juniper cover

types. No significant changes in area or connectivity were noted for either cover type (fig. 26 

and appendix 2).

Shrubland—Area and connectivity of colline lowmedium shrub cover declined sharply; percentage

of area fell by 12 percent from an average of 71.0

to 62.3 percent of the ERU area (figs. 29 to 31

and appendix 2). Patch density of colline lowmedium shrub cover increased nearly eight hundredfold, rising from 7.3 to 5,679.9 patches 

per 10 000 ha, and mean patch size declined by

98 percent, falling from an average of 3,639.5 to

56.8 ha.These data suggest that remaining colline

low-medium shrub cover is a highly fragmented

remnant of a once expansive cover type. Connectivity of colline tall shrub cover increased; patch

density declined by 38 percent from 5.8 to 

3.6 patches per 10 000 ha, and mean patch size

increased by 70 percent from an average of 29.9

to 50.9 ha. 

Herbland—Among herbland cover types, only

two changes were significant (figs. 29, 32, and 33

and appendix 2). Area of colline bunchgrass cover

increased; percentage of area rose by 40 percent

from 3.7 to 5.2 percent. Connectivity of colline

exotic grass and forb cover increased; patch density remained stable during the sample period, and

mean patch size increased about 21/2-fold from an

average of 29.3 to 75.4 ha. 

Nonforest-nonrange and other anthropogenic cover

types—Two changes were significant among

anthropogenic cover types: cropland area and

connectivity increased, as did area and connectivity of urban and rural developments (figs. 34 and

35 and appendix 2). Percentage of area of cropland rose more than fourfold from an average 

of 2.7 to 12.1 percent of the ERU area; patch

density remained stable, and mean patch size

increased fourfold, rising from an average of 52.1

to 229.4 ha. Likewise, percentage of area of urban

and rural developments rose from an average of 

0 to 0.2 percent of the ERU area; patch density

increased from 0.6 to 1.7 patches per 10 000 ha,

and mean patch size more than tripled, rising

from 1.1 to 3.8 ha.

Area of exposed rock (cliffs, scree slopes, talus,

rimrock, outcrops) declined; percentage of area

dropped from an average of 6.8 to 2.6 percent 

of the ERU area, a net loss of 62 percent of the

historical area of the cover type; patch density

remained stable; and mean patch size fell sharply

from an average of 1,884.0 to 182.3 ha (ns), for 

a net decline in average patch size of 90 percent

of the historical area. 

Structural classes—

Forest—Because forests were a relatively minor

physiognomic type in this ERU, changes among

forest structures were few (fig. 36 and appendix

2). Area of stand-initiation structure declined and

connectivity increased. Percentage of area fell

from an average of 0.8 to 0.3 percent of the ERU,

patch density declined from 4.9 to 1.7 patches

per 10 000 ha, and mean patch size remained

unchanged. Area and connectivity of stem-exclusion open canopy structures increased; percentage

of area rose from an average of 0.4 to 1.0 percent

of the ERU area, patch density remained stable,

and mean patch size rose from 6.9 to 11.9 ha.

130
131

Connectivity of young multistory structures also

increased; patch density declined from 2.7 to 1.2

patches per 10 000 ha, and mean patch size rose

threefold from an average of 7.5 to 22.6 ha (ns).

Woodland—As noted above, no significant change

in area or connectivity of woodland cover types

was observed, but structure of Upper Snake

woodlands did change significantly (fig. 37 and

appendix 2). Area and connectivity of stem-exclusion structures increased; percentage of area rose

threefold from an average of 0.7 to 2.0 percent of

the ERU area, patch density increased from 4.0 to

6.2 patches per 10 000 ha, and mean patch size

more than doubled, rising from an average of 8.7

to 17.9 ha. Area of understory reinitiation structures declined by a comparable amount; percentage of area fell from 1.8 to 0.8 percent of the

ERU. Connectivity of understory reinitiation

structures also declined with patch density

remaining unchanged and mean patch size declining from an average of 7.9 to 4.4 ha. 

Shrubland—Considering all forest and range

structures, shrub structures changed most significantly (fig. 38 and appendix 2). Area and connectivity of open tall structures increased; percentage

of area rose by 73 percent from an average of 3.0

to 5.2 percent of the ERU area, patch density was

unchanged, and mean patch size rose from an

average of 35.6 to 54.5 ha. Area and connectivity

of closed tall structures declined; percentage of

area fell from 0.7 to 0.4 percent of the ERU;

patch density dropped nearly 50 percent from 

4.0 to 2.1 patches per 10 000 ha, and mean patch

size declined from 13.3 to 2.5 ha (ns). 

Area of open and closed low-medium shrub structures declined, but connectivity of remaining

closed low-medium structure increased during 

the sample period. The observed loss of area of

both open and closed low-medium shrub structures was not statistically significant at P≤0.2, but

we regarded it as ecologically significant given primary transitions and comparison of the median

value in the existing condition with the historical

median 75-percent range. Percentage of area of

open low-medium shrub structure fell from 63.1 

to 57.8 percent, and percentage of area of closed

low-medium structure declined from 8.2 to 5.0

percent. Patch density of closed low-medium

structures declined by 74 percent, dropping from

11.1 to 2.9 patches per 10 000 ha, and mean

patch size rose threefold from 73.9 to 217.3 ha

(ns).

Herbland—No significant change in area or connectivity was noted for open or closed herb structures (fig. 38 and appendix 2).

Nonforest-nonrange and other anthropogenic types—

As noted above, area of nonforest-nonrange and

other anthropogenic types increased significantly

owing to expanding cropland area (fig. 38 and

appendix 2). Percentage of cropland area rose

from an average of 10.8 to 16.0 percent of the

ERU area (ns). The observed rise in area was not

statistically significant at P≤0.2 but was ecologically significant given primary transitions and historical median 75-percent range information. 

Landscape Patterns

In this second set of analyses, we evaluated the

effects on landscape vegetation patterns of management activities occurring during the period

between our historical and current vegetation

samples. Our null hypothesis was no significant

difference in landscape vegetation patterns between historical and current photointerpreted

vegetation conditions. We speculated that managed forest and range landscapes become structurally more complex, diverse, and fragmented as

a result of historical timber harvest and grazing

activities and effective exclusion of fire. We further speculated that forest landscapes comprised

of large wilderness and roadless area become less

diverse and exhibit increased connectivity owing

to the dominant role of effective fire prevention

and suppression strategies and grazing activities 

in these areas. Table 19 displays results of 10

landscape metrics summarized by ERU.

We describe significant change in each ERU for

an array of pattern metrics that highlight landscape-scale change in the kind and number of

unique patch types, the distribution and equitability of land area among patch types, the degree of dispersion of patch type area, the extent 

to which patch types are interspersed with and

juxtaposed against each other patch type, and the

degree of edge contrast occurring between edges
132

Table 19—Landscape metric results for 13 ecological reporting units in the midscale assessment of the 

interior Columbia River basin where patch types were cover type-structural class doublets

Ecological reporting units

Blue C. Idaho Col. L. Clark No. N. Glac. N. Great Owyhee Snake So. U. Clark Upper Upper

Landscape metrics Mts. Mts. Plateau Fork Cascade Mts. Basin Uplands Headw. Cascade Fork Klamath Snake

Richness and diversity:

RPR_hab 11.4 11.3 7.8 15.8 13.9 11.6 4.8 2.9 11.8 7.7 11.6 9.6 5.1

RPR_c 12.1 12.5 8.2 15.5 16.0 14.3 5.3 2.9 11.9 10.6 13.5 9.5 5.2

RPR_md 0.7 1.2* c 0.3 -0.3 2.0* 2.7* 0.5 0.0 0.1 3.0* 1.9* -0.1 0.1

PR_h 22.8 22.3 15.2 30.6 27.0 22.6 9.3 5.6 22.9 14.9 22.5 18.6 9.8

PR_c 23.5 24.7 15.8 30.0 31.0 27.9 10.3 5.6 23.0 20.6 26.1 18.5 10.1

PR_md 0.7 2.4* 0.6 -0.6 4.0* 5.3* 1.0 0.0 0.0 5.8* 3.7* -0.1 0.3

SHDI_h 2.1 2.2 1.5 2.5 2.5 2.2 1.3 0.4 2.3 1.7 2.4 1.8 1.0

SHDI_c 2.2 2.3 1.5 2.6 2.6 2.4 1.5 0.5 2.4 2.1 2.5 1.9 1.1

SHDI_md 0.0 0.1* 0.0 0.1 0.1* 0.2* 0.3* 0.1* 0.1* 0.3* 0.1* 0.0 0.0

N1_h 10.0 10.1 5.2 12.9 13.3 10.3 3.6 1.7 10.7 6.0 11.7 7.4 3.4

N1_c 9.9 10.6 5.5 14.5 15.1 12.7 4.6 2.0 11.6 9.2 12.3 8.2 3.4

N1_md -0.1 0.4* 0.2 1.6* 1.8* 2.3* 1.1* 0.3* 0.9* 3.1* 0.6 0.8 0.0

N2_h 6.8 7.0 3.8 8.2 9.4 7.2 2.6 1.4 7.7 4.5 8.6 5.2 2.4

N2_c 6.8 7.1 3.8 10.2 10.6 8.9 3.5 1.6 8.5 6.8 8.7 6.1 2.5

N2_md 0.0 0.1 0.1 2.0* 1.3* 1.6* 0.9* 0.2* 0.8* 2.3* 0.0 0.8* 0.0

Evenness:

MSIEI_hd 0.58 0.60 0.46 0.61 0.66 0.61 0.44 0.15 0.62 0.55 0.67 0.51 0.34

MSIEI_c 0.58 0.58 0.46 0.67 0.68 0.63 0.54 0.20 0.65 0.60 0.65 0.54 0.35

MSIEI_md 0.00 -0.01 0.00 0.06* 0.01* 0.02 0.11* 0.05* 0.03* 0.04 -0.03* 0.04 0.00

R21_h 0.64 0.64 0.63 0.62 0.67 0.65 0.65 0.44 0.66 0.69 0.71 0.62 0.61

R21_c 0.64 0.62 0.61 0.69 0.68 0.66 0.68 0.46 0.68 0.68 0.67 0.66 0.59

R21_md 0.00 -0.02* -0.01 0.07* 0.01 0.00 0.03* 0.01 0.02 -0.01 -0.04* 0.04* -0.02

Contagion and interspersion:

CONTAG_h 58.2 57.3 66.3 56.6 55.8 58.1 65.8 86.1 56.2 63.3 55.1 63.3 73.3

CONTAG_c 57.9 57.6 65.8 54.2 54.9 56.4 60.6 74.0 54.8 59.7 55.8 62.1 73.6

CONTAG_md -0.3 0.3 -0.5 -2.4* -0.9* -1.7* -5.2* -12.1* -1.4* -3.6* 0.7 -1.2 0.3

IJI_h 65.9 67.6 60.2 69.0 68.8 67.6 56.0 42.6 70.1 64.0 70.6 61.5 47.1

IJI_c 65.2 67.1 58.8 71.7 69.7 68.2 56.5 52.4 71.1 65.1 68.7 63.0 56.7

IJI_md -0.7 -0.6 -1.4 2.7 1.0* 0.6 0.6 9.8* 1.0 1.0 -1.9* 1.5 9.6*

Edge contrast:

AWMECI_h 37.8 37.3 28.0 33.5 38.8 35.5 24.7 10.5 41.1 37.3 34.7 33.9 17.3

AWMECI_c 38.5 38.3 29.0 38.6 39.1 37.7 24.8 11.4 41.2 40.4 35.3 33.6 18.9

AWMECI_md 0.7 1.1* 1.0 5.1* 0.3 2.2* 0.1 0.9* 0.1 3.1* 0.6 -0.3 1.6*

a RPR values represent percentage of relative patch richness where the observed number of patch types (cover type-structural

classes) in an ERU is scaled against a realistic maximum number of patch types possible across the entire basin assessment area.

PR values simply represent the total number of patch types present within an ERU. N1 is a transformation of SHDI; rare patch

types are weighted less than in PR. N2 also counts numbers of patch types like RPR, but N2 gives dominant patch types

increased weight and can be considered a count of the average number of dominant patch types in an ERU. With N2, rare

patch types are weighted less than in N1.

b Suffix h = average historical value among subwatersheds of an ERU; c = average current value among subwatersheds of an

ERU; and md = mean difference of pairwise comparisons of sampled subwatersheds within an ERU. RPR = relative patch richness; PR = patch richness; SHDI = Shannon-Weaver diversity index; N1 = Hill's index N1 = eSHDI; N2 = Hill's index N2 =

1/(1/SIDI); MSIEI = modified Simpson's evenness index; R21 = Alatalo's evenness index = (N2-1)/(N1-1); CONTAG = contagion index; IJI = interspersion and juxtaposition index; AWMECI = area-weighted mean edge contrast index (see also tables 17

and 18, and McGarigal and Marks 1995).

c * indicates statistical significance at P≤0.2.

d MSIEI is more sensitive to change in abundance among all patch types, whereas R21 is more sensitive to change in abundance

of the dominant patch types. Increases indicate that area distributed among patch types is increasingly even. Declines indicate

that some patch types are more abundant than others within an ERU. Significant figures are computed to 2 decimal places.
133

of differing patch types to emphasize changes and

reveal major differences in pattern attributes of

landscapes. In our analysis, landscape metrics

were computed for a broad variety of patch types,

such as physiognomic types, cover types, structural classes, cover-structure class doublets, potential

vegetation type-cover-structure class triplets, fuel

loading classes, fireline intensity classes, insect and

pathogen vulnerability classes, and so forth. Here,

we report only results of landscape pattern analyses where patch types are cover-structure class

doublets (for example, stand initiation-western

larch, old forest single-story-ponderosa pine, or

open structured-montane low-medium shrubs),

because this combination is most appropriate 

for understanding and visualizing simultaneous

change in patterns of structural and compositional attributes (table 19). We do not discuss changes

in Hill’s index N1, because that index is a simple

transformation of SHDI, and we discuss changes

in SHDI Index. N1 is shown because it was used

to compute R21, Alatalo’s evenness index. Conventional and spatial statistics were computed to

eight decimal places; we report significant figures

to one decimal place unless otherwise indicated. 

Blue Mountains ERU—No significant (P≤0.2)

change in any landscape metric was evident in the

Blue Mountains ERU, although trends for most

metrics were similar to those observed in other

ERUs having a history of widespread domestic

livestock grazing and timber management (table

19). Lack of significant difference for all metrics

was the result of high variability within and

among sampled subwatersheds pooled in this

ERU. To improve on this analysis and indeed

reveal masked changes in landscape pattern 

metrics, it would be appropriate to derive midscale statistical pooling strata that would partition

environmental variation by grouping subwatersheds similar in their climate and environmental

attributes.

The Blue Mountains ERU is roughly two-thirds

forest and one-third rangeland with large wilderness and roadless areas. Elsewhere in the basin,

landscape pattern trends in ERUs with significant

wildland area were clearly different from those

observed in ERUs comprised primarily of managed forests. In general, landscape patterns of

wilderness subwatersheds became less diverse and

less fragmented, while landscape patterns of managed subwatersheds became more diverse and

fragmented. This difference also was observed by

Lehmkuhl and others (1994). The magnitude of

landscape pattern change also was quite different

between forest- and range-dominated ERUs (table

19); we suspect the same is true at the subwatershed scale within the Blue Mountains ERU, and

additional investigation is warranted. Furthermore, landscape pattern changes more often were

significant at smaller scales where a homogenous

area was considered. We believe that landscape

pattern evaluations will have greater meaning and

become more revealing when they are conducted

for smaller ecological subregions comprised of

similar biophysical environments (see “Ecological

Regionalization,” below).

One additional observation is noteworthy; the

Blue Mountains ERU was one of only three

where the sign of the mean difference value for

both the contagion index (CONTAG) and the

interspersion index (IJI) was the same, but

changes were not significant at P≤0.2 (table 19).

Contagion and interspersion usually are inversely

related to each other. A high value for CONTAG

means that a landscape is contagious; that is, the

distribution of area within one or more patch

types is aggregated or clumped, and dispersion is

low. If the value of contagion declines, it means

that fewer, larger contiguous patches were replaced by more, smaller, dispersed patches, and

dispersion increased. In such cases, we would

often, but not always expect an increasing value

of IJI. 

Central Idaho Mountains ERU—Patch richness (the number of cover-structure patch types)

in the Central Idaho Mountains ERU increased

by more than 10 percent. The Shannon-Weaver

diversity index (SHDI; Shannon and Weaver

1949) indicated slightly but significantly increased patch type diversity, which was confirmed

by the noted increase in Hill’s index N1, but the

inverse of Simpson’s λ (N2) (Simpson 1949), an

indicator of diversity and changing dominance,

did not change significantly. The SHDI is more

sensitive to changes in richness than evenness;

Simpson’s λ and N2 are less sensitive to changes
in richness and the presence of rare patch types.

The value of Simpson’s λ represents the probability that any two patches selected at random will be

the same patch types; it is an expression of dominance exerted by individual patch types. One

minus that value expresses the probability that

any two patches selected at random will be different patch types; the higher the value, the greater

the diversity. The inverse of Simpson’s λ rescales

the solution for ease of interpretation; the higher

the number, the greater the diversity and the

lower the dominance of any one patch type. For

example, in table 19, the average historical value

of N2 (N2_h) for sampled subwatersheds in the

Central Idaho Mountains was 7.0, which is equal

to the inverse of Simpson’s λ (SIDI). So the value

of Simpson’s λ = 0.143, and 1 - Simpson’s λ =

0.857, indicating a low degree of dominance and

a high degree of diversity.

Evenness measures are attempts to assess how

equitably area is distributed among a given number of patch types. Both evenness measures

(MSIEI and R21) index relative change in the

distribution of “abundance,” or in this case area,

among patch types. Values for both evenness metrics declined, but only the decline in Alatalo’s

evenness index was significant at P≤0.2. Evenness

indices (table 19) indicated that the average distribution of area among patch types of subwatersheds in the historical condition was 60 and 64

percent of the maximum evenness for the given

number of patch types, respectively; the average

distribution of area among patch types of subwatersheds in the current condition was 58 and 62

percent of the maximum evenness for the given

number of patch types, respectively. Decline in

R21 indicated that the distribution of area among

cover-structure patch types became less even during the sample period, or some types became

more dominant (see also cover type and structural

class changes for the Central Idaho Mountains

ERU in appendix 2).

Finally, increase in AWMECI was quite significant; in fact, it was the sixth largest change occurring for that index among all ERUs. In this analysis, we based edge contrast difference mostly on

physiognomic and structural conditions, and we

minimized the effect of differing composition.

This was done in deference to edge-sensitive and

edge-dependent species, and their typically greater

sensitivity to structural rather than compositional

differences of edges; for example, we made stem

exclusion-Douglas-fir and stem exclusion-ponderosa pine equivalent conditions (see table 18 

for edge contrast weights). The noted increase in

area-weighted mean edge contrast indicated that

the percentage of edge that was maximum contrast edge increased by an amount equivalent to

1.1 percent of the total edge. Maximum contrast

edge would be like that occurring between oldforest multistory structures and urban developments or croplands.

Columbia Plateau ERU—No significant

(P≤0.2) change in any landscape metric was evident in the Columbia Plateau ERU, although

trends for most metrics were similar to those

observed in other ERUs having a history of

domestic livestock grazing and timber management (table 19). Lack of significant difference for

all metrics was the result of high inherent variability within and among sampled subwatersheds.

The Columbia Plateau is roughly two-thirds

rangeland and one-third forest. As was observed

in the Blue Mountains, the sign of the mean 

difference value for both the contagion index

(CONTAG) and the interspersion index (IJI) 

was the same, but values were not significant.

Lower Clark Fork ERU—Several landscape

metrics changed significantly within the Lower

Clark Fork ERU (table 19). Historical patch richness (PR_h) was the highest observed among all

ERUs, and current patch richness (PR_c) was the

second highest observed. Overall, there was an

average of 30 unique cover-structure patch types

in sampled subwatersheds representing the ERU

in both the historical and current samples. Patch

richness as indicated by RPR and PR did not

change significantly, but dominance and diversity

as indicated by the inverse of Simpson’s λ (N2)

increased significantly. The mean difference for

N2 was 2.0; that is, the average number of dominant patch types per subwatershed increased from

8.2 to 10.2. The mean difference value for N2

represented an average increase in dominance of

24.4 percent during the average historical level,

the third largest increase observed among all

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135

ERUs. Significant reductions in area of stand initiation (minus 23.3 percent) and stem exclusionopen canopy structures (minus 6.5 percent) and

significant rises in area of understory reinitiation

(21.3 percent) and stem exclusion-closed canopy

(7.3 percent) structures no doubt fueled the

observed increase in dominance (appendix 2).

Both evenness measures increased significantly

during the sample period. Evenness indices (R21

and MSIEI in table 19) indicate that the average

distribution of area among patch types of subwatersheds in the historical condition was 61 to 

62 percent of the maximum evenness for the

given number of historical patch types, and the

average distribution of area among patch types 

of subwatersheds in the current condition was 67

to 69 percent of the maximum evenness for the

given number of current patch types. Increases 

in both indices indicated that the distribution of

area among cover-structure patch types became

more even during the sample period, that historical Lower Clark Fork landscapes (which were 

primarily forested) were structurally and compositionally simpler, and patch type area was not

evenly distributed. This is reasonable given the

historical dominance of stand-replacing and

mixed-severity fires (Hann and others 1997) and

associated stand-initiation structures (appendix 2).

We compared area distributions of historical and

current cover-structure patch type combinations

to confirm that increased evenness was associated

with dominant patch types.

Contagion (CONTAG) decreased significantly

from 56.6 to 54.2 percent with no significant

change in IJI, thereby indicating increased dispersion without consistently increased interspersion.

We expected a reduced contagion value in this

ERU, because we observed significantly increased

dispersion of stand-initiation, stem exclusionopen canopy, and understory reinitiation structures during the sample period (see patch density

and mean patch size values of forest structures for

the Lower Clark Fork ERU in appendix 2). The

AWMECI increased significantly from 33.5 to

38.6 percent—the largest absolute increase among

all ERUs. The noted increase in mean edge contrast indicated that the percentage of edge that was

maximum contrast edge increased by an amount

equivalent to 5.1 percent of the total edge.

Northern Cascades ERU—Significant change

was evident in 8 of 10 landscape metrics. Absolute patch richness, as indicated by PR, increased

an average of 14.8 percent during the sample

period; relative patch richness (RPR), which computes the observed number of cover-structure

patch types over a realistic potential maximum

number of patch types, increased by a comparable

amount. Average current patch richness (PR_c)

was the highest observed among all ERUs. Likewise, the average current SHDI diversity value

(SHDI_c) was the highest value observed. The

mean difference value of the SHDI was 0.1, and

that of the inverse of Simpson’s λ (N2) was 1.3;

both increases were significant. The mean difference value of SHDI represented an average increase in patch type diversity of 4 percent over 

the average historical level. The mean difference

value of N2 represented an average increase in

dominance of 13.8 percent over the average historical level, and indicated that the average number of dominant patch types per subwatershed

increased from 9.4 to 10.6.

Of the two evenness indices used, significant

change was noted only for the modified MSIEI.

Values for MSIEI in the Northern Cascades indicated that the average distribution of area among

patch types of subwatersheds in the historical

condition was 66 percent of the maximum evenness for the given number of historical patch

types; the average distribution of area among

patch types of subwatersheds in the current condition was 68 percent of the maximum evenness

for the given number of current patch types (table

19). Although small, the noted increase indicated

that the distribution of area among cover-structure patch types of sampled subwatersheds became consistently more even during the sample

period. We compared area distributions of historical and current cover-structure patch type combinations to confirm that increased evenness was

associated with dominant patch types.

Contagion decreased significantly from 55.8 to

54.9 percent and IJI increased significantly from

68.8 to 69.7 percent. Observed CONTAG values

indicated that dispersion had dropped to 54.9

percent of the maximum possible dispersion given

the total number of patch types. Observed IJI values indicated that interspersion had increased to
69.7 percent of the maximum possible interspersion given the total number of patch types. These

changes suggested significantly reduced connectivity of cover-structure patch types or increasing

landscape fragmentation. We anticipated these

pattern changes because we observed significantly

increased patch density and reduced mean patch

size for most major cover types and structural

classes (see also appendix 2). Mean edge contrast

as indicated by the AWMECI, increased slightly,

but the change was not significant at P≤0.2. 

The historical edge contrast value for the ERU

(AWMECI_h) was the second highest value observed among all ERUs. The historical value of

38.8 percent indicated that of all the edge shared

among patch types, an amount equivalent to 

38.8 percent of all edge was maximum contrast

edge of the kind occurring at the boundary of a

stand-replacing fire. The mean difference value

(AWMECI_md) of 0.3 indicated that despite 

significant timber harvesting during the sample

period, current edge contrast (AWMECI_c) is

equivalent to historical.

Northern Glaciated Mountains ERU—

Significant change was evident in 7 of 10 landscape metrics in the Northern Glaciated Mountains. Absolute patch richness, as indicated by PR,

increased an average of 23.4 percent during the

sample period; relative patch richness increased by

a comparable amount. This was the second largest

richness increase among ERUs. Average current

patch richness (PR_c) was the third highest

observed among all ERUs. The mean difference

value of the SHDI was 0.2, and that of the inverse of Simpson’s λ (N2) was 1.6; both increases

were significant. The mean difference value of

SHDI represented an average increase in patch

type diversity of 9.1 percent over the average 

historical level. The mean difference value of N2

represented an average increase in dominance of

24 percent over the average historical level and

indicated that the average number of dominant

patch types per subwatershed increased from 7.2

to 8.9. This was the fourth largest increase in

dominance among ERUs.

As with many extensively managed forest ERUs,

both evenness measures increased during the sample period, but neither change was significant at

P≤0.2. Contagion decreased significantly from

58.1 to 56.4 percent with a corresponding but

insignificant increase in IJI. Observed CONTAG

values indicated that patch type dispersion had

dropped to 56.4 percent of the maximum possible dispersion given the total number of patch

types. The IJI values indicated that interspersion

had increased to 68.2 percent of the maximum

possible interspersion given the total number of

patch types, but the change was not significant 

at P≤0.2. We expected a reduced CONTAG value

in this ERU, because we observed significantly

increased patch density and reduced mean patch

size for most major cover types and structural

classes (see also appendix 2). Lack of significant

increase in IJI with decreasing contagion, meant

that patch type area in the average current condition was more dispersed than in the average historical condition, but patch area still tended to 

be clumpy or aggregated rather than highly interspersed and evenly juxtaposed with other patch

types. (Note: This interspersion index is not

affected by the number, size, contiguity or dispersion of patches per se, as is the contagion index.)

This means that building blocks for improving

contagion, or more specifically, reducing patch

density and increasing mean patch size, reside 

in existing landscapes of the ERU.

The AWMECI increased significantly from 35.5

to 37.7 percent; the third largest absolute increase

among all ERUs. The noted increase in mean

edge contrast indicated that the percentage of

edge that was maximum contrast edge increased

by an amount equivalent to 2.2 percent of the

total edge. We anticipated increasing edge contrast because we noted significantly increasing

patch density and edge density (not reported

here) for most major cover types and structural

classes. 

Northern Great Basin ERU—Significant

change was evident in 6 of 10 landscape metrics.

Absolute PR increased an average of 10.8 percent

during the sample period; relative patch richness

increased comparably, but neither change was significant at P≤0.2. Average current patch richness

(PR_c) was the second lowest observed among 

all ERUs. We would expect this because the

Northern Great Basin ERU is dominated by

shrubland and woodland patch types and lacks

patch type diversity contributed by forests.

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137

The mean difference value of the SHDI was 0.3,

and that of the inverse of Simpson’s λ (N2) was

0.9; both increases were significant (table 19).

The mean difference value of SHDI represented

an average increase in patch type diversity of 

23 percent over the average historical level. This

was the second largest increase in patch type

diversity among ERUs. A small richness change

contributed to great change in diversity in this

ERU because Northern Great Basin range landscapes are relatively simple to begin with. The

mean difference value of N2 represented an average increase in dominance of 35 percent over 

the average historical level. This was the second

largest increase in dominance among ERUs.

Change in N2 values between historical and 

current conditions indicated that the average

number of dominant patch types per subwatershed increased from 2.6 to 3.5.

Evenness of patch type area in Northern Great

Basin landscapes increased during the sample

period. Change in MSIEI values indicated that

the average distribution of area among patch

types of subwatersheds in the historical condition

was 44 percent of the maximum evenness for the

given number of historical patch types; and the

average distribution of area among patch types 

of subwatersheds in the current condition was 

54 percent of the maximum evenness for the

given number of current patch types. The R21

values indicated that the average distribution of

area among dominant patch types of subwatersheds in the historical condition was 65 percent

of the maximum evenness for the given number

of historical patch types; the average distribution

of area among dominant patch types of subwatersheds in the current condition was 68 percent of

the maximum evenness for the given number of

current patch types. Alatalo’s R21 metric is sensitive to changing distribution of area among dominant patch types, whereas the modified Simpson’s

evenness index reflects changing distribution of

area among all patch types regardless of their

dominance or rarity. Differences in average historical, average current, and mean difference values

for the two metrics suggested that increased richness (albeit nonsignificant) was associated with

relatively rare patch types; Alatalo’s R21 metric

may provide clearer insight into evenness changes

occurring during the sample period. We compared area distributions of historical and current

cover-structure patch type combinations to confirm this observation. Evenness results suggest

that historical Great Basin landscapes (which are

primarily rangeland) were structurally and compositionally simpler and patch type area was less

evenly distributed than it is today.

Contagion decreased significantly from 65.8 to

60.6 percent with a corresponding increase in IJI,

but the latter change was not significant at P≤0.2.

Significantly reduced CONTAG without significant change in IJI suggested increased dispersion

without consistently increased interspersion

among sampled subwatersheds. We expected a

reduced CONTAG value in this ERU because 

we observed significantly increased dispersion 

of shrubland cover types and structural classes

during the sample period (see patch density and

mean patch size values in appendix 2).

Owyhee Uplands ERU—Significant change

was evident in 7 of 10 landscape metrics in the

Owyhee Uplands. No change in relative or absolute patch richness was evident, but diversity

increased significantly. The mean difference value

of the SHDI was 0.1 and that of the inverse of

Simpson’s λ (N2) was 0.2; both increases were

significant (table 19). The mean difference value

of SHDI represented an average increase in patch

type diversity of 25 percent over the average historical level. This was the largest increase in patch

type diversity among ERUs. The mean difference

value of N2 represented an average increase in

dominance of 14.3 percent over the average historical level. This was the sixth largest increase in

dominance among ERUs. The observed change in

values of N2 during the sample period indicated

that the average number of dominant patch types

per subwatershed increased from 1.4 to 1.6.

Evenness of patch type area in Owyhee Uplands

landscapes remained relatively constant during the

sample period. Change in MSIEI values indicated

that the average distribution of area among patch

types of subwatersheds in the historical condition

was 15 percent of the maximum evenness for the

given number of historical patch types; and the
average distribution of area among patch types 

of subwatersheds in the current condition was 

20 percent of the maximum evenness for the

given number of current patch types. The R21

values also indicated increasing evenness, but the

change was not significant at P≤0.2. Differences

in average historical, average current, and mean

difference values for the two metrics suggested

that increased evenness was associated with relatively rare patch types. We compared area distributions of historical and current cover-structure

patch type combinations and confirmed this

observation.

Contagion decreased significantly from 86.1 to 

74 percent, and IJI increased significantly from

42.6 to 52.4 percent. Among all ERUs in the historical condition, range landscapes of the Owyhee

Uplands were the most contagious because they

were dominated by the fewest dominant coverstructure patch types (see also the value for N2_h

in table 19). Observed contagion values indicated

that dispersion had dropped to 74 percent of the

maximum possible dispersion given the total

number of patch types. Observed IJI values indicated that interspersion had increased to 52.4 percent of the maximum possible interspersion given

the total number of patch types. These changes

indicated significantly increased fragmentation 

of cover-structure patch types during the sample

period. We anticipated these changes in landscape metrics because we observed significantly

increased patch density and reduced mean patch

size of shrubland cover types and structural classes, which comprise more than 80 percent of the

area in both the historical and current vegetation

coverages (see also appendix 2).

The AWMECI increased significantly from 10.5

to 11.4 percent. The noted increase in edge contrast indicated that the percentage of edge that

was maximum contrast edge increased by an

amount equivalent to 0.9 percent of the total

edge. We anticipated increasing edge contrast

because we noted significantly increasing patch

density, edge density (not reported here) and

decreasing mean patch size for shrubland coverstructure patch types.

Snake Headwaters ERU—Significant change

was evident in 5 of 10 landscape metrics in the

Snake Headwaters. No change in relative or absolute patch richness was in evidence, but diversity increased significantly. The mean difference

value of the SHDI was 0.1, and that of the inverse of Simpson’s λ (N2) was 0.9; both increases

were significant (table 19). The mean difference

value of SHDI represented an average increase in

patch type diversity of 4.3 percent over the average historical level. The mean difference value of

N2 represented an average increase in dominance

of 10.4 percent over the average historical level.

This was the eighth largest increase in dominance

among ERUs. The observed change in values of

N2 during the sample period also indicated that

the average number of dominant patch types per

subwatershed increased from 7.7 to 8.5.

Evenness of patch type area in Snake Headwaters

landscapes also increased during the sample period. Change in MSIEI values indicated that the

average distribution of area among patch types 

of subwatersheds in the historical condition was

62 percent of the maximum evenness for the

given number of historical patch types; and the

average distribution of area among patch types 

of subwatersheds in the current condition was 

65 percent of the maximum evenness for the

given number of current patch types. The R21

values also indicated increasing evenness but the

change was not significant. We compared area

distributions of historical and current cover-structure patch type combinations to confirm that

increased evenness was associated with dominant

patch types. 

Contagion decreased significantly by 1.4 percent,

and IJI increased by 1.0 percent, but the latter

change was not significant at P≤0.2. Observed

contagion values indicated that dispersion had

dropped to 54.8 percent of the maximum possible dispersion given the total number of patch

types. Observed interspersion and juxtaposition

values indicated that interspersion of patch types

had increased to 71.1 percent of the maximum

possible interspersion given the total number of

patch types. These changes indicated significantly

increased fragmentation and shuffling of coverstructure patch types during the sample period.

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Southern Cascades ERU—The Southern 

Cascades displayed the greatest change in richness

and dominance of all ERUs. Significant change

was evident in 7 of 10 landscape metrics.

Absolute patch richness as indicated by PR, increased an average of 38 percent during the sample period; relative patch richness increased by a

comparable amount. The mean difference value

of the SHDI was 0.3 and that of the inverse of

Simpson’s λ (N2) was 2.3; both increases were

significant. The mean difference value of SHDI

represented an average increase in patch type

diversity of 17.6 percent over the average historical level. The mean difference value of N2 represented an average increase in dominance of 51.1

percent over the average historical level. The observed change in values of N2 during the sample

period indicated that the average number of dominant patch types per subwatershed increased

from 4.5 to 6.8.

Evenness did not change significantly according

to either MSIEI or R21, but CONTAG decreased

significantly by 3.6 percent with a corresponding

but statistically insignificant increase in IJI. Observed contagion values indicated that patch type

dispersion had dropped to 59.7 percent of the

maximum possible dispersion given the total

number of patch types. Observed IJI values indicated that interspersion had increased to 65.1 percent of the maximum possible interspersion given

the total number of patch types, but the change

was not significant at P≤0.2. We expected a

reduced contagion value in this ERU because 

we observed significantly increased patch density

and reduced mean patch size for most major

cover types and structural classes in the Southern

Cascades (appendix 2). The lack of significant

increase in IJI with decreasing CONTAG meant

that patch type area in the average current condition was more dispersed than in the average historical condition, but patch area still tended to 

be clumpy or aggregated rather than highly interspersed and evenly juxtaposed with other patch

types. This means that building blocks for reducing patch density and increasing mean patch size

still reside in existing forest landscapes.

The AWMECI increased significantly from 37.3

to 40.4 percent, the second largest absolute increase among all ERUs. The noted increase in

edge contrast indicated that the percentage of

edge in maximum contrast edge increased by 

an amount equivalent to 3.1 percent of the total

edge. 

Upper Clark Fork ERU—Significant change

was evident in 6 of 10 landscape metrics. Absolute PR increased an average of 16.4 percent during the sample period; relative PR increased comparably (table 19). The mean difference value of

the SHDI was 0.1, which represented an average

increase in patch type diversity of 4.2 percent over

the average historical level. There was no significant change in dominance as indicated by N2.

This was reflected in both evenness measures, as

both decreased significantly. The Upper Clark

Fork was the only ERU that experienced significant reductions in patch type evenness.

Contagion also did not change significantly, but

IJI decreased significantly by 1.9 percent. Observed historical and current values indicated that

interspersion had declined to 68.7 percent of the

maximum possible interspersion given the total

number of patch types. We observed no significant change in AWMECI.

Upper Klamath ERU—The Upper Klamath

ERU posted some of the smallest changes in richness and diversity among all ERUs, and among

the 10 computed landscape pattern metrics, only

two changes were significant. The inverse of

Simpson’s λ (N2) was the only diversity index 

to change significantly. The mean difference value

of N2 was 0.8, which represented an average increase in dominance of 15.4 percent over the

average historical level. The observed change in

values of N2 between the historical and current

conditions indicated that the average number of

dominant patch types per subwatershed increased

from 5.2 to 6.1 (table 19).

The only other landscape metric to change significantly was Alatalo’s evenness index, R21. Change

in R21 values indicated that the average distribution of area among patch types of subwatersheds

in the historical condition was 62 percent of the

maximum evenness for the given number of historical patch types; and the average distribution 

of area among patch types of subwatersheds in 

the current condition was 66 percent of the maximum evenness for the given number of current
patch types. We compared area distributions of

historical and current cover-structure patch type

combinations to confirm that increased evenness

was associated with dominant patch types.

Simultaneous examination of CONTAG, N2,

R21, and IJI metrics revealed that Upper Clark

Fork landscapes are dominated by several patch

types evenly distributed rather than contagiously

clumped, with a highest degree of patch type

interspersion and juxtaposition; that is, landscape

patterns were dominated by several well-mixed

patch types. 

Upper Snake ERU—Significant change was

evident in only 2 of 10 landscape metrics in the

Upper Snake. No change in richness, diversity,

dominance, evenness, or contagion was in evidence. Although there was no change in CONTAG, interspersion increased dramatically by 

9.6 percent. Observed historical and current values indicated that interspersion had increased to

56.7 percent of the maximum possible interspersion given the total number of patch types. The

noted increase in interspersion without a compensating decline in contagion (dispersion) could be

explained rather simply. Two-thirds of the area of

the ERU is comprised of open shrubland structures in colline settings, most of which are lowmedium shrub cover types (appendix 2). Patch

density and mean patch size of open low-medium

shrub structures did not change significantly, but

patch density of colline low-medium shrub cover

types increased radically, and mean patch size

plunged precipitously. Most of the area of open

structured-colline low-medium patch type is still

spatially aggregated, but many herbland and cropland patches of small area are currently interspersed. Change in the AWMECI reflects this

transition as well. The AWMECI increased significantly from 17.3 to 18.9 percent. The noted

increase in mean edge contrast indicated that the

percentage of edge in maximum contrast edge

increased by an amount equivalent to 1.6 percent

of the total edge. The resultant proportion of the

total edge that is currently the equivalent of maximum contrast edge is still a relatively low number

because edge contrast between shrubland and

herbland, or shrubland and cropland, is low (see

table 18 for edge contrast weights). 

Forest and Woodland Area With

Medium and Large Trees

In this third set of analyses, we evaluated the

effects of management activities on the distribution of medium and large trees in forest and

woodland settings. Our null hypothesis was no

significant difference in percentage of area with

medium and large trees between historical and

current photointerpreted vegetation conditions.

We conducted this analysis because we speculated

that managed forest and woodland landscapes

became structurally more intermediate, or more

crudely, “middle-aged,” and lacking in dominance

of large trees as a result of effective fire exclusion

and historical selection and regeneration timber

harvest activities that often targeted the largest

trees for removal. 

To be classified as old-forest structure in our classification (table 6), overstory crown cover of large

trees (trees > 63.5 cm d.b.h.) was at least 30 percent (that is, the overstory crown cover class was

at least 30 percent, actual crown cover was at 

least 25 percent, and the overstory size class was

large trees). Remember that remotely sensed total

and overstory crown covers were interpreted in

10-percent increments, and classes were expressed

as midpoints; for example, the 30-percent overstory crown cover class corresponded with the 

25- to 34-percent range of actual overstory crown

covers. In our classification of forest structures

other than old forest (table 6), we allowed large

trees to comprise an overstory crown cover class

of up to 20 percent (that is, ≤ 24 percent actual

crown cover), but large tree cover was generally

subordinate to other structural features that reflected more dominant effects of disturbance. For

example, if fire or timber harvest had replaced a

former ponderosa pine overstory of medium and

large trees with seedlings and saplings comprising

an actual crown cover of 82 percent and remnant

large trees comprising an actual crown cover of 

16 percent, the structure would be classified as

stand initiation, with 100 percent total crown

cover, 20 percent remnant large tree overstory

crown cover, and 80 percent understory seedling

and sapling crown cover.

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141

In appendix 2, we show change in area and connectivity of forest structural classes for each ERU.

But we also wanted to discover any change in the

disposition of medium (40.5 to 63.5 cm d.b.h.)

and large trees regardless of their structural affiliation. When we speak of structures that are not

old forest, we refer to large trees as “remnant large

trees,” because in these structures large trees typically occur as a remnant or residuum of a former

structural condition after a stand-replacing disturbance. Table 20 compares area of sampled historical and current subwatersheds with remnant large

trees, old single-story structure, and old multistory structure by ERU.

A number of “old-growth” definitions in use

today use 50.8 cm d.b.h. and even smaller diameters as the lower limit for large trees; 50.8 cm

d.b.h. is roughly the midpoint of our medium

tree size class (40.5 to 63.5 cm d.b.h.). It appears

that managers have at least two compelling arguments for using relatively small lower diameter

limits: (1) over the last 90 years, most of the

largest trees (pathologically old emergents much

larger than 50.8 cm) have been removed through

selective timber harvest; and (2) given what

remains, old forests as they are currently defined

appear to retain the greatest available measure of

structural and functional complexity of presettlement old forests. For these reasons, we ran an

additional analysis to determine the disposition 

of medium and large tree crown cover regardless

of structural affiliation. But we caution that it is

imprudent to revise or simplify definitions of 

old forest by reducing the lower diameter limit 

of large trees simply because much larger trees are

no longer available. The immeasurable biological

legacy associated with those largest trees is too

large to surrender with so simple a classification

assumption. Table 21 displays change in percentage of area of medium and large trees during the

sample period. Area occupied by medium and

large trees was divided into five crown cover 

Table 20—Percentage comparison of area of remnant large trees, old single story, and old multistory forest

structures for ecological reporting units in the midscale assessment of the interior Columbia River basin

Remnant large treesa Old multistory structure Old single-story structures

(large tree crown coverb (large tree crown cover (large tree crown cover

≤ 20 percent) ≥ 30 percent) ≥ 30 percent) 

Mean Mean Mean

Ecological reporting unit Historical Current differencec Historical Current differencec Historical Current differencec

Percent

Blue Mountains 3.7 1.9 -1.8* 2.2 1.0 -1.3* 2.7 0.9 -1.7*

Central Idaho Mountains 1.7 1.9 0.2 1.4 1.2 -0.3 1.8 1.7 -0.1

Columbia Plateau 1.3 2.1 0.8 2.3 1.2 -1.0 1.1 1.0 -0.1

Lower Clark Fork 0.4 0.0 -0.4 0.2 0.5 0.3 2.2 2.5 0.3

Northern Cascades 4.6 3.6 -1.0 5.8 2.7 -3.1* 4.3 2.4 -1.9*

Northern Glaciated Mountains 1.3 1.2 -0.1 0.5 0.4 -0.1 0.7 0.6 -0.1

Northern Great Basin 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Owyhee Uplands 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Snake Headwaters 1.5 1.4 -0.1 3.2 1.8 -1.4 2.0 1.3 -0.7

Southern Cascades 5.2 3.0 -2.2 0.7 1.4 0.7 1.6 3.7 2.1

Upper Clark Fork 0.7 0.6 -0.2 0.6 0.4 -0.2 0.2 0.3 0.1

Upper Klamath 7.7 6.7 -0.9 4.3 5.5 1.2 7.4 4.7 -2.6*

Upper Snake 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 -0.1

a Large trees were > 63.5 centimeters in diameter at breast height (d.b.h.).

b Crown cover values represent class midpoints: 10 percent crown cover = 5 to 14 percent actual crown cover; 20 percent crown

cover = 15 to 24 percent actual crown cover; 30 percent actual crown cover = 25 to 34 percent actual crown cover; etc. See also

table 6 for structural class and tree size class definitions.

c * indicates statistical significance at P≤0.2.
classes: < 10 percent (none), 10 to 30 percent, 

40 to 60 percent, > 60 percent; and total (≥ 10

percent).

Blue Mountains ERU—In the Blue

Mountains, area of old single-story and old multistory structures declined significantly during the

sample period (table 20 and appendix 2). Area

occupied by remnant large trees also declined significantly; percentage of area fell from a historical

level of 3.7 percent of the ERU to 1.9 percent. In

the historical condition, 62.8 percent of the ERU

area was forest. Of that area, 5.9 percent was

comprised of structures with remnant large trees,

3.5 percent was comprised of old multistory

structures, and 4.3 percent was comprised of old

single-story structures. About 13.7 percent of the

historical forest area of the ERU was comprised 

of old and other forest structures containing large

trees. In the current condition, 64.1 percent of

the ERU area was forest. Of that area, 3 percent

was comprised of structures with remnant large

trees, 1.6 percent was comprised of old multistory

structures, and 1.4 percent was comprised of old

single-story structures. About 6 percent of the

current forest area of the ERU was comprised of

old and other forest structures containing large

trees. The difference amounts to a net decline in

forest area with large trees of 56 percent.

Table 21 shows change in area ERU with medium

and large trees. Percentage of area with no medium and large trees (where overstory crown cover

class is < 10 percent, and actual large tree crown

cover < 5 percent) increased during the sample

period from 60.4 to 72.8 percent, and area in the

10- to 30-percent, 40- to 60-percent, and > 60-

percent medium and large tree crown cover classes

declined. Percentage of area in the 10- to 30-percent medium and large tree crown cover class fell

from 23.3 to 18.4 percent, and area in the 40- to

60-percent and > 60-percent crown cover classes

declined from 11.9 to 6.7 percent, and from 4.5

to 2.1 percent, respectively. Total area with medium and large trees fell by 31 percent during the

sample period.

142

Table 21—Percentage comparison of area of medium and large trees for ecological reporting units in the

midscale assessment of the interior Columbia River basin

Area with medium and large treesabc

Crown cover Crown cover Crown cover Crown cover

(< 10 percent) (10 to 30 percent) (40 to 60 percent) (> 60 percent) Total 

Ecological reporting unit H C MDd H C MDd H C MDd H C MDd H C MDd

Percent

Blue Mountains 60.4 72.8 12.4* 23.3 18.4 -4.8* 11.9 6.7 -5.2* 4.5 2.1 -2.4* 39.6 27.2 -12.4*

Central Idaho Mountains 76.5 74.2 -2.3* 12.9 10.9 -1.9* 8.4 9.3 0.8 2.2 5.6 3.4* 23.5 25.8 2.3*

Columbia Plateau 84.8 85.9 1.1 9.6 9.5 -0.1 5.2 2.7 -2.5* 0.4 1.9 1.5* 15.2 14.1 -1.1

Lower Clark Fork 78.3 63.3 -15.0* 5.5 3.8 -1.7 11.1 15.4 4.2* 5.1 17.6 12.5* 21.8 36.8 15.0*

Northern Cascades 58.1 62.1 4.0* 18.2 18.2 0.1 15.0 12.7 -2.3* 8.8 6.9 -1.8* 41.9 37.9 -4.0*

Northern Glaciated Mountains 78.0 75.8 -2.1 11.2 11.2 0.0 7.1 6.7 -0.4 3.8 6.3 2.5* 22.0 24.2 2.1

Northern Great Basin 99.6 97.9 -1.7 0.3 0.5 0.2 0.1 1.6 1.5 0.0 0.0 0.0 0.4 2.1 1.7

Owyhee Uplands 99.3 99.8 0.5* 0.7 0.2 -0.5* 0.1 0.0 0.0* 0.0 0.0 0.0 0.7 0.2 -0.5*

Snake Headwaters 71.3 73.4 2.1 13.2 13.2 0.1 11.5 11.4 -0.1 4.0 1.9 -2.0* 28.7 26.6 -2.1

Southern Cascades 59.7 55.7 -4.0 23.3 17.9 -5.4 15.1 18.9 3.8 2.0 7.5 5.5* 40.3 44.3 4.0

Upper Clark Fork 80.3 82.8 2.4 12.6 10.6 -2.0 4.0 4.5 0.5 3.0 2.1 -0.9 19.7 17.2 -2.4

Upper Klamath 56.7 72.6 15.9* 28.7 14.6 -14.1* 10.4 9.0 -1.4 4.2 3.8 -0.5 43.3 27.4 -15.9*

Upper Snake 98.7 98.1 -0.6* 0.8 0.6 -0.2 0.4 0.8 0.4* 0.1 0.6 0.5 1.3 1.9 0.6*

a Medium trees were 40.5 to 63.5 cm d.b.h.; large trees were > 63.5 cm d.b.h. See also table 6.

b Crown cover values represent class midpoints: 10 percent crown cover = 5 to 14 percent actual crown cover, 20 percent actual

crown cover = 15 to 24 percent actual crown cover, 30 percent actual crown cover = 25 to 34 percent actual crown cover, etc.

c H = historical; C = current; MD = mean difference of pairwise comparisons of historical and current subwatersheds.

d * indicates statistical significance at P≤0.2.
143

Central Idaho Mountains ERU—In the

Central Idaho Mountains, area of old single-story

and old multistory forest structures declined

slightly during the sample period (appendix 2 

and table 20), but change was not significant at

P≤0.2. Area occupied by remnant large trees

increased slightly, but again change was not 

statistically significant; percentage of area rose

from 1.7 to 1.9 percent. In the historical vegetation condition, 73.4 percent of the area of the

ERU was forest. Of that area, 2.3 percent was

comprised of structures with remnant large trees,

1.9 percent was comprised of old multistory

structures, and 2.4 percent was comprised of old

single-story structures. About 6.6 percent of the

historical forest area of the ERU was comprised 

of old and other forest structures containing large

trees. In the current condition, 73.5 percent 

of the area of the ERU was forest. Of that area,

2.6 percent was comprised of structures with remnant large trees, 1.6 percent was comprised of old

multistory structures, and 2.3 percent was comprised of old single-story structures. Of the current forest area of the ERU, 6.5 percent was

comprised of old and other forest structures containing large trees. 

Percentage of area with no medium and large

trees (< 10 percent overstory crown cover) decreased during the sample period from 76.5 to

74.2 percent, and area in the > 60-percent medium and large tree crown cover class rose (table

21). Percentage of area in the 10- to 30-percent

medium and large tree crown cover class fell from

12.9 to 10.9 percent, and area in the 40- to 60-

percent and > 60-percent medium and large tree

crown cover classes rose from 8.4 to 9.3 percent

(ns), and from 2.2 to 5.6 percent, respectively.

Total area with medium and large trees increased

by 9.8 percent during the sample period.

Columbia Plateau ERU—Area of old singlestory and old multistory structures declined (table

20 and appendix 2) during the sample period, 

but change was not significant at P≤0.2. Area

occupied by remnant large trees increased, but

again change was not statistically significant; 

percentage of area rose from 1.3 to 2.1 percent 

of the ERU area. In the historical condition, 

26.1 percent of the area of the Columbia Plateau

ERU was forest. Of that area, 5 percent was 

comprised of structures with remnant large trees,

8.8 percent was comprised of old multistory

structures, and 4.2 percent was comprised of old

single-story structures. About 18 percent of the

historical forest area of the ERU was comprised 

of old and other forest structures containing large

trees. In the current condition, 29.1 percent of

the area of the ERU was forest. Of that area, 

7.2 percent was comprised of structures with remnant large trees, 4.1 percent was comprised of old

multistory structures, and 3.4 percent was comprised of old single-story structures. Of the current forest area of the ERU, 14.7 percent was

comprised of old and other forest structures containing large trees. The difference amounts to a

net decline in forest area with large trees of 18 percent, but the difference is not significant at P≤0.2.

Percentage of area with no medium and large

trees (overstory crown cover < 10 percent) increased from 84.8 to 85.9 percent (ns), and 

area in the 40- to 60-percent medium and large

tree crown cover class declined from 5.2 to 

2.7 percent of the ERU area, and ERU area in 

the > 60-percent medium and large tree crown

cover class rose from 0.4 to 1.9 percent (table 21).

Percentage of area in the 10- to 30-percent medium and large tree crown cover class fell from 9.6

to 9.5 percent (ns). Total ERU area with medium

and large trees dropped by 7.2 percent during 

the sample period (ns).

Lower Clark Fork ERU—In the Lower Clark

Fork ERU, area of old single-story and old multistory structures increased slightly (table 20 and

appendix 2) during the sample period, but change

was not significant at P≤0.2. Area occupied by

remnant large trees declined slightly, but again

change was not statistically significant. Percentage

of area fell from 0.4 to 0 percent of the ERU. In

the historical condition, 91.7 percent of the area

of the ERU was forest according to our small

sample. Of that area, 0.4 percent was comprised

of structures with remnant large trees, 0.2 percent

was comprised of old multistory structures, and

2.4 percent was comprised of old single-story

structures. About 3 percent of the historical forest
area of the ERU was comprised of old and other

forest structures containing large trees. In the 

current condition, 94.5 percent of the area of 

the ERU was forest. Of that area, 0 percent was

comprised of structures with remnant large trees,

0.5 percent was comprised of old multistory

structures, and 2.6 percent was comprised of old

single-story structures. Of the current forest area

of the ERU, 3.1 percent was comprised of old

and other forest structures containing large trees.

Percentage of area with no medium and large

trees (overstory crown cover < 10 percent) decreased during the sample period from 78.3 

to 63.3 percent, and area in the 40- to 60-percent, and > 60-percent medium and large tree

crown cover classes rose from 11.1 to 15.4 percent, and from 5.1 to 17.6 percent, respectively

(table 21). Percentage of area in the 10- to 30-

percent medium and large tree crown cover class

fell from 5.5 to 3.8 percent (ns). Total area with

medium and large trees increased by 68.8 percent

during the sample period.

Northern Cascades ERU—In the Northern

Cascades ERU, area of old single-story and 

old multistory structures declined significantly

(P≤0.2) during the sample period (table 20 and

appendix 2). Area occupied by remnant large trees

also declined, but the change was not statistically

significant; percentage of area fell from 4.6 to 

3.6 percent. In the historical vegetation condition, 78.8 percent of the area of the ERU was forest. Of that area, 5.8 percent was comprised of

structures with remnant large trees, 7.4 percent

was comprised of old multistory structures, and

5.5 percent was comprised of old single-story

structures. About 18.7 percent of the historical

forest area of the ERU was comprised of old and

other forest structures containing large trees. In

the current condition, 78.2 percent of the area of 

the ERU was forest. Of that area, 4.6 percent was

comprised of structures with remnant large trees,

3.5 percent was comprised of old multistory

structures, and 3.1 percent was comprised of old

single-story structures. About 11.2 percent of the

current forest area of the ERU was comprised of

old and other forest structures containing large

trees. The difference amounts to a net decline 

in forest area with large trees of 40 percent.

Percentage of area with no medium and large

trees (crown cover < 10 percent) increased during

the sample period from 58.1 to 62.1 percent of

the ERU area, and area in the 40- to 60-percent,

and > 60-percent medium and large tree crown

cover classes declined (table 21). Percentage of

area in the 10- to 30-percent medium and large

tree crown cover class remained stable, and area 

in the 40- to 60-percent and > 60-percent medium and large tree crown cover classes declined

from 15.0 to 12.7 percent, and from 8.8 to 

6.9 percent, respectively. Total area with medium

and large trees fell by 9.5 percent during the 

sample period.

Northern Glaciated Mountains ERU—In

the Northern Glaciated Mountains ERU, area 

of old single-story and old multistory structures

declined slightly (table 20 and appendix 2) during

the sample period, but the change was not significant at P≤0.2. Area occupied by remnant large

trees also declined slightly, but the change was 

not statistically significant; percentage of area fell

from 1.3 to 1.2 percent of the ERU area. In the

historical vegetation condition, 81 percent of the

ERU area was forest. Of that area, 1.6 percent

was comprised of structures with remnant large

trees, 0.6 percent was comprised of old multistory

structures, and 0.9 percent was comprised of old

single-story structures. About 3.1 percent of the

historical forest area of the ERU was comprised 

of old and other forest structures containing large

trees. In the current condition, 80.8 percent of

the ERU area was forest. Of that area, 1.5 percent

was comprised of structures with remnant large

trees, 0.5 percent was comprised of old multistory

structures, and 0.7 percent was comprised of old

single-story structures. Of the current forest area

of the ERU, 2.7 percent was comprised of old

and other forest structures containing large trees.

Percentage of area with no medium and large

trees (overstory crown cover < 10 percent)

decreased during the sample period from 78.0 

to 75.8 percent, and area in the > 60-percent

medium and large tree crown cover class rose

from 3.8 to 6.3 percent (table 21). Percentage 

of area in the 10- to 30-percent and 40- to 60-

percent medium and large tree crown cover classes

remained stable. Total area with medium and

large trees increased by 9.5 percent (ns) during

the sample period.

144
145

Northern Great Basin ERU—Forests of 

the Northern Great Basin ERU occupied about 

7 percent of the land area, and large trees were

not present in any sampled subwatersheds in

either the historical or current conditions.

Medium tree crown cover was observed. Area

with medium tree crown cover increased during

the sample period, but the change was not statistically significant. Percentage of area with no

medium trees (overstory crown cover < 10 percent) decreased during the sample period from

99.6 to 97.9 percent (ns), and area in the 40- to

60-percent medium tree crown cover class rose

from 0.1 to 1.6 percent (ns). Percentage of area 

in the 10- to 30-percent medium tree crown

cover class increased slightly from 0.3 to 0.5 percent (ns). Total area with medium trees increased

fivefold (ns) during the sample period.

Owyhee Uplands ERU—Forests of the

Owyhee Uplands ERU occupied < 1 percent 

of the land area, and large trees were not present

in any sampled subwatersheds in either the historical or current vegetation conditions. Medium

tree crown cover was observed, but scarcely so.

Area with medium tree crown cover declined during the sample period. Percentage of area with no

medium trees (overstory crown cover < 10 percent) rose from 99.3 to 99.8 percent of the ERU

area, and area in the 10- to 30-percent crown

cover class fell from 0.7 to 0.2 percent. Total 

area with medium trees declined by 71 percent.

Snake Headwaters ERU—In the Snake

Headwaters ERU, area of old single-story and 

old multistory forest structures declined, but the

change was not significant at P≤0.2 (table 20 and

appendix 2). Area occupied by remnant large trees

also declined and the change was not significant;

percentage of area fell from 1.5 to 1.4 percent of

the ERU area. In the historical vegetation condition, 74.5 percent of the area of the ERU was 

forest. Of that area, 2 percent was comprised of

structures with remnant large trees, 4.3 percent

was comprised of old multistory structures, and

2.7 percent was comprised of old single-story

structures. About 9 percent of the historical forest 

area of the ERU was comprised of old and other

forest structures containing large trees. In the 

current condition, 73.8 percent of the area of 

the ERU was forest. Of that area, 1.9 percent 

was comprised of structures with remnant large

trees, 2.4 percent was comprised of old multistory

structures, and 1.8 percent was comprised of old

single-story structures. Of the current forest area

of the ERU, 6.1 percent was comprised of old

and other forest structures containing large trees.

Percentage of area with no medium and large

trees (overstory crown cover < 10 percent) increased from 71.3 to 73.4 percent of the ERU

area, but the change was not statistically significant (table 21). Percentage of area in the > 60-

percent medium and large tree crown cover class

fell from 4.0 to 1.9 percent of the ERU area.

Percentage of area in the 10- to 30-percent and

40- to 60-percent medium and large tree crown

cover classes remained stable. Total area with

medium and large trees declined by 7.3 percent

(ns). 

Southern Cascades ERU—Area of old singlestory and old multistory structures increased

(table 20 and appendix 2), but the change was

not significant at P≤0.2. Area occupied by remnant large trees declined, but again, the change

was not statistically significant; percentage of area

fell from 5.2 to 3.2 percent of the ERU area. In

the historical condition, 80.5 percent of the area

of the ERU was forest. Of that area, 6.5 percent

was comprised of structures with remnant large

trees, 0.9 percent was comprised of old multistory

structures, and 2 percent was comprised of old

single-story structures. About 9.4 percent of the

historical forest area of the ERU was comprised 

of old and other forest structures containing large

trees. In the current condition, 88.3 percent of

the area of the ERU was forest. Of that area, 

3.4 percent was comprised of structures with remnant large trees, 1.6 percent was comprised of old

multistory structures, and 4.2 percent was comprised of old single-story structures. Of the current forest area of the ERU, 9.2 percent was

comprised of old and other forest structures containing large trees.

Percentage of area with no medium and large

trees (overstory crown cover < 10 percent) declined during the sample period from 59.7 to

55.7 percent of the ERU area, and area in the 

> 60-percent medium and large tree crown cover
class rose from 2.0 to 7.5 percent of the ERU.

Percentage of area in the 10- to 30-percent medium and large tree crown cover class fell from 23.3

to 17.9 percent (ns), and area in the 40- to 60-

percent medium and large tree crown cover class

increased from 15.1 to 18.9 percent (ns). Total

area with medium and large trees increased by 

9.9 percent, but the change was not significant.

We note that considerable selection and regeneration harvest activity was visible in the aerial photographs representing the historical vegetation

condition. It is likely that combined historical 

old forest area and area with remnant large trees

was as much as 50 percent greater than what we

were able to portray. We discuss this further in

“Change in Area Affected by Visible Logging

Activity,” below. 

Upper Clark Fork ERU—In the Upper Clark

Fork ERU, area of old multistory structures

declined and area of old single-story structures

increased, but neither change was significant at

P≤0.2 (table 20 and appendix 2). Area occupied

by remnant large trees declined slightly, but the

change was not statistically significant; percentage

of area fell from 0.7 to 0.6 percent of the ERU

area. In the historical condition, 87.2 percent 

of the area of the ERU was forest. Of that area,

0.8 percent was comprised of structures with remnant large trees, 0.6 percent was comprised of old

multistory structures, and 0.2 percent was comprised of old single-story structures. About 1.6

percent of the historical forest area of the ERU

was comprised of old and other forest structures

containing large trees. In the current condition,

86.2 percent of the area of the ERU was forest.

Of that area, 0.7 percent was comprised of 

structures with remnant large trees, 0.5 percent

was comprised of old multistory structures, and

0.3 percent was comprised of old single-story

structures. Of the current forest area of the ERU,

1.5 percent was comprised of old and other forest

structures containing large trees.

There were no significant changes in area with

medium and large tree cover. Percentage of 

area with no medium and large trees (overstory

crown cover < 10 percent) increased from 80.3 to

82.8 percent of the ERU area, but the change was

not statistically significant. Percentage of area in

the > 60-percent medium and large tree crown

cover class fell from 3.0 to 2.1 percent (ns).

Percentage of area in the 10- to 30-percent medium and large tree crown cover class declined from

12.6 to 10.6 percent of the ERU area, and area 

in the 40- to 60-percent medium and large tree

crown cover class rose from 4.0 to 4.5 percent

(ns). Total area with medium and large trees

declined by 12.2 percent (ns) during the sample

period. Nearly all the observed change was associated with declining area occupied by medium

trees.

Upper Klamath ERU—In the Upper Klamath

ERU, area of old single-story structures decreased

from 7.4 to 4.7 percent of the ERU area, and area

of old multistory structures remained stable (table

20 and appendix 2). Area occupied by remnant

large trees also declined; percentage of area fell

from 7.7 to 6.7 percent (ns). In the historical

condition, 50.5 percent of the area of the ERU

was forest. Of that area, 15.2 percent was comprised of structures with remnant large trees, 

8.5 percent was comprised of old multistory

structures, and 14.7 percent was comprised of 

old single-story structures. About 38.4 percent 

of the historical forest area of the ERU was comprised of old and other forest structures containing large trees. In the current condition, 47.5

percent of the area of the ERU was forest. Of that

area, 14.1 percent was comprised of structures

with remnant large trees, 11.6 percent was comprised of old multistory structures, and 9.9 percent was comprised of old single-story structures.

About 35.6 percent of the current forest area of

the ERU was comprised of old and other forest

structures containing large trees.

Table 21 shows change in area with medium and

large trees. Percentage of area with no medium

and large trees (overstory crown cover < 10 percent) increased from 56.7 to 72.6 percent of the

ERU area, and area in the 10- to 30-percent, 

40- to 60-percent, and > 60-percent medium and

large tree crown cover classes declined. Percentage

of area in the 10- to 30-percent crown cover class

fell from 28.7 to 14.6 percent. Total area with

medium and large trees declined by 36.7 percent

during the sample period.

146
147

Upper Snake ERU—Forests of the Upper

Snake ERU occupied about 3 percent of the land

area, and large trees were present only in sampled

subwatersheds of the historical condition in trace

amounts. Medium tree crown cover was observed;

percentage of area with medium tree crown cover

increased during the sample period. Area with no

medium trees (overstory crown cover < 10 percent) decreased from 98.7 to 98.1 percent of 

the ERU area, and area in the 40- to 60-percent

medium tree crown cover class rose from 0.4 to

0.8 percent. Total area with medium trees increased by 46 percent during the sample period,

from 1.3 to 1.9 percent of the ERU area.

Forest and Woodland Crown Cover,

Canopy Layers, and Cover of

Understory Tree Species

In this section, we report results of analyses assessing change in total tree crown cover, number of

canopy layers, and cover of understory species to

evaluate several potential effects of fire exclusion

and timber harvest during the last half century.

Our null hypothesis was no significant difference

in tree cover, canopy layers, and cover of understory species during the interval between our historical and current photointerpreted vegetation

conditions. We speculated that fire prevention

and suppression activities and selective harvesting

caused an increase in total tree crown cover, canopy layers, and area in shade-tolerant, fire-intolerant understory species during decades when they

were featured management strategies.

Table 22 and figure 39 display change in percentage of area of five total crown cover classes during

the sample period. Total crown cover classes were

< 10 percent (nonforest and nonwoodland environmental settings), 10 to 30 percent total crown

cover; 40 to 50 percent total crown cover; 60 to

80 percent total crown cover; and 90 to 100 percent total crown cover. Table 23 and figure 40

display change during the sample period in percentage of area in three canopy layer classes. Canopy layer classes were one layer, two layers, and

more than two layers. Table 24 and figures 41 

and 42 display change during the sample period

in percentage of cover by understory species.

Understory species classes were (1) PIPO–ponderosa pine; (2) LAOC/PICO–western larch 

or lodgepole pine or both; (3) PSME/ABGR/

ABCO/ABAM–Douglas-fir or grand fir or 

white fir or Pacific silver fir and combinations; 

(4) TSHE/THPL–western hemlock or western

redcedar, or both; (5) TSME–mountain hemlock;

(6) ABLA2/ PIEN–subalpine fir or Engelmann

spruce, or both; (7) PIAL/LALY–whitebark 

pine or subalpine larch, or both; (8) hardwood;

(9) juniper; (10) other (including grass and forb,

shrub, and bare ground understories, and those

comprised of Shasta red fir, incense-cedar, western

white pine, limber pine, pinyon pine, or beargrass); and (11) nonforest-nonwoodland. 

Tree cover increased in 9 of 13 ERUs, and the 

observed increased was statistically significant 

in 8 of 13 ERUs (table 22). Tree cover increased

in the Blue Mountains, Central Idaho Mountains,

Columbia Plateau, Lower Clark Fork, Northern

Glaciated Mountains, Northern Great Basin,

Owyhee Uplands, Southern Cascades, and Upper

Snake ERUs and declined in the Snake Headwaters, Upper Clark Fork, and Upper Klamath

ERUs. Tree cover in the Northern Cascades ERU

did not change significantly.

Canopy layering increased significantly in 9 of 

13 ERUs. Canopy layering increased in the Blue

Mountains, Columbia Plateau, Lower Clark Fork,

Northern Glaciated Mountains, Northern Great

Basin, Owyhee Uplands, Snake Headwaters,

Southern Cascades, and Upper Snake ERUs and

declined in the Upper Clark Fork and Upper

Klamath ERUs (table 23). Canopy layering in the

Central Idaho Mountains and Northern Cascades

ERUs remained relatively constant at this reporting scale. Because these latter two ERUs are comprised of highly dissected mountain ranges with

steep terrain and steep environmental gradients, 

it is likely that differences in canopy layering may

be detected at smaller subregional scales. 

Forest area with shade-tolerant understories increased significantly in 7 of 13 ERUs. Area with

shade-intolerant understories declined significantly in two ERUs. Shade-tolerant understories (for

example, including such species as Douglas-fir,

grand fir, white fir, and subalpine fir) increased
significantly in the Blue Mountains, Central

Idaho Mountains, Columbia Plateau, Lower

Clark Fork, Northern Glaciated Mountains,

Snake Headwaters, and Upper Clark Fork ERUs.

Shade-intolerant understories (for example,

including ponderosa pine, western larch, and

lodgepole pine) declined in the Blue Mountains,

Central Idaho Mountains, Columbia Plateau,

Northern Cascades, Northern Glaciated

Mountains, Snake Headwaters, Upper Clark

Fork, and Upper Klamath ERUs, but declines

were significant at P≤0.2 only in the Northern

Glaciated Mountains and Upper Clark Fork

ERUs (table 24). 

148

Table 22—Percentage comparison of area of forest and woodland in 5 total crown cover classes for ecological reporting units in the midscale assessment of the interior Columbia River basin

Area

NonforestForest and woodland crown coverab nonwoodland 

crown cover

Ecological

reporting unit H C MDc H C MDc H C MDc H C MDc H C MDc

Percent

Blue Mountains 12.5 12.5 0.0 17.7 21.0 3.3* 27.5 29.4 2.0 7.8 5.4 -2.3* 34.6 31.6 2.9*

Central Idaho 

Mountains 8.9 8.3 -0.5 18.6 16.8 -1.8* 33.6 32.6 -1.0 12.3 15.9 3.6* 26.6 26.4 -0.2

Columbia Plateau 9.5 11.3 1.9 8.8 15.4 6.6* 10.5 9.9 -0.6 4.0 4.6 0.7* 67.2 58.8 -8.4*

Lower Clark Fork 6.3 2.7 -3.6* 21.5 9.7 -11.8* 44.2 38.6 -5.5 19.7 43.4 23.7* 8.3 5.5 -2.8

Northern Cascades 9.2 9.5 0.4 17.3 18.7 1.5 33.6 30.3 -3.3* 19.0 20.1 1.1 20.9 21.2 0.3

Northern Glaciated 

Mountains 9.2 8.7 -0.5 19.1 18.0 -1.1 31.2 29.9 -1.2 21.5 24.2 2.6 19.0 19.2 0.2

Northern Great Basin 7.1 10.5 3.4 11.5 15.6 4.1* 3.7 3.1 -0.6* 0.2 0.2 0.0 77.5 70.6 -6.9*

Owyhee Uplands 4.2 5.4 1.2* 1.3 2.2 1.0* 0.2 0.1 -0.1 0.0 0.0 0.0 94.3 92.3 -2.0*

Snake Headwaters 11.7 11.9 0.2 15.8 19.2 3.5* 35.7 35.4 -0.2 11.5 7.5 -4.0* 25.3 25.9 0.6

Southern Cascades 8.0 12.9 4.9* 37.1 36.6 -0.6 35.1 35.8 0.7 0.2 3.5 3.2* 19.5 11.3 -8.2*

Upper Clark Fork 7.4 9.5 2.1* 18.8 20.3 1.6 45.3 41.2 -4.1* 15.8 15.2 -0.6 12.8 13.8 1.0

Upper Klamath 11.8 10.9 -0.9 17.5 26.1 8.5* 27.4 19.9 -7.5* 2.1 3.4 1.2 41.1 39.7 -1.3

Upper Snake 1.7 1.7 0.0 1.9 2.4 0.5* 1.2 1.3 0.1 0.4 0.7 0.3 94.7 93.8 -0.9

a Crown cover values represent class midpoints: 10 percent crown cover = 5 to 14 percent actual crown cover, 20 percent actual

crown cover = 15 to 24 percent actual crown cover, 30 percent actual crown cover = 25 to 34 percent actual crown cover, etc.

b H = historical; C = current; MD = mean difference of pairwise comparisons of historical and current subwatersheds.

c * indicates statistical significance at P≤0.2.

10 to 30 percent 40 to 50 percent 60 to 80 percent 90 to 100 percent (< 10 percent)

Text resumes on page 160
149

Table 23—Percentage comparison of area of forest and woodland with 1, 2, or more than 2 canopy layers

for ecological reporting units in the midscale assessment of the interior Columbia River basin

Areaa

Canopy layers-forest and woodland

Nonforest1 layer 2 layers > 2 layers nonwoodland

Ecological reporting unit H C MDb H C MDb H C MDb H C MDb

Blue Mountains 16.0 12.5 -3.6* 37.8 39.5 1.7 11.6 16.4 4.9* 34.6 31.6 -2.9*

Central Idaho Mountains 24.7 24.4 -0.3 40.7 42.1 1.5 8.1 7.0 -1.0 26.6 26.4 -0.2

Columbia Plateau 14.3 17.6 3.3* 14.2 17.2 3.0 4.3 6.4 2.2* 67.2 58.8 -8.4*

Lower Clark Fork 38.7 30.0 -8.7* 52.9 61.8 8.9 0.1 2.7 2.6 8.3 5.5 -2.8

Northern Cascades 17.3 17.5 0.2 51.1 50.9 -0.2 10.7 10.4 -0.3 20.9 21.2 0.3

Northern Glaciated 20.7 22.6 1.9 54.6 48.0 -6.6* 5.7 10.2 4.5* 19.0 19.2 0.2

Mountains

Northern Great Basin 21.9 28.6 6.7* 0.6 0.8 0.2 0.0 0.0 0.0 77.5 70.6 -6.9*

Owyhee Uplands 3.3 4.4 1.1 2.1 3.0 0.9* 0.3 0.3 -0.0 94.3 92.3 -2.0*

Snake Headwaters 26.4 19.7 -6.7* 45.1 50.6 5.5 3.2 3.8 0.6 25.3 25.9 0.6

Southern Cascades 9.7 14.1 4.4 60.0 55.0 -5.0 10.7 19.6 8.9* 19.5 11.3 -8.2*

Upper Clark Fork 32.4 37.7 5.3* 41.0 37.2 -3.8* 13.8 11.4 -2.5* 12.8 13.8 1.0

Upper Klamath 10.8 14.5 3.7 38.2 39.8 1.6 10.0 6.0 -4.0 41.1 39.7 -1.3

Upper Snake 1.6 2.7 1.1* 3.4 3.3 -0.1 0.3 0.2 -0.1 94.7 93.8 -0.9

a H = historical; C = current; MD = mean difference of pairwise comparisons of historical and current subwatersheds.

b * statistically significant difference at P≤0.2; all values rounded to 1 decimal place.

Percent
150

Historic

Current

0 10 20 30 40

nonwoodland 

Nonforest/ 

90% - 100% 

60% - 80% 

40% - 50% 

10% - 30% 

 *

 *

 *

BLUE MTNS.

0 10 20 30 40

nonwoodland 

Nonforest/ 

90% - 100% 

60% - 80% 

40% - 50% 

10% - 30% 

 *

 *

CENTRAL IDAHO MTNS.

0 20 40 60 80

nonwoodland 

Nonforest/ 

90% - 100% 

60% - 80% 

40% - 50% 

10% - 30% 

 *

 *

 *

COLUMBIA PLATEAU

0 10 20 30 40 50 60

nonwoodland 

Nonforest/ 

90% - 100% 

60% - 80% 

40% - 50% 

10% - 30% 

 *

 *

 *

LOWER CLARK FORK

0 10 20 30 40

nonwoodland 

Nonforest/ 

90% - 100% 

60% - 80% 

40% - 50% 

10% - 30% 

 *

N. CASCADES

0 10 20 30 40

nonwoodland 

Nonforest/ 

90% - 100% 

60% - 80% 

40% - 50% 

10% - 30% 

N. GLACIATED MTNS.

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

90% - 100% 

60% - 80% 

40% - 50% 

10% - 30% 

 *

 *

 *

N. GREAT BASIN

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

90% - 100% 

60% - 80% 

40% - 50% 

10% - 30% 

 *

 *

 *

OWYHEE UPLANDS
151

Historic

Current

0 10 20 30 40

nonwoodland 

Nonforest/ 

90% - 100% 

60% - 80% 

40% - 50% 

10% - 30% 

 *

 *

SNAKE HEADWATERS

0 10 20 30 40 50

nonwoodland 

Nonforest/ 

90% - 100% 

60% - 80% 

40% - 50% 

10% - 30% 

 *

 *

 *

S. CASCADES

0 10 20 30 40 50

nonwoodland 

Nonforest/ 

90% - 100% 

60% - 80% 

40% - 50% 

10% - 30% 

 *

 *

UPPER CLARK FORK

0 10 20 30 40 50

nonwoodland 

Nonforest/ 

90% - 100% 

60% - 80% 

40% - 50% 

10% - 30% 

 *

 *

UPPER KLAMATH

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

90% - 100% 

60% - 80% 

40% - 50% 

10% - 30% 

 *

UPPER SNAKE

Figure 39—Historical and current distribution of forest and woodland total crown cover classes expressed as a percentage of

total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean

estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.
152

Historic

Current

0 10 20 30 40 50

nonwoodland 

Nonforest/ 

> 2 layers 

2 layers 

1 layer 

 *

 *

 *

BLUE MTNS.

0 10 20 30 40 50

nonwoodland 

Nonforest/ 

> 2 layers 

2 layers 

1 layer 

CENTRAL IDAHO MTNS.

0 20 40 60 80

nonwoodland 

Nonforest/ 

> 2 layers 

2 layers 

1 layer 

 *

 *

 *

COLUMBIA PLATEAU

0 20 40 60 80

nonwoodland 

Nonforest/ 

> 2 layers 

2 layers 

1 layer *

LOWER CLARK FORK

0 10 20 30 40 50 60

nonwoodland 

Nonforest/ 

> 2 layers 

2 layers 

1 layer 

N. CASCADES

0 10 20 30 40 50 60

nonwoodland 

Nonforest/ 

> 2 layers 

2 layers 

1 layer 

 *

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

> 2 layers 

2 layers 

1 layer 

 *

 *

N. GREAT BASIN

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

> 2 layers 

2 layers 

1 layer 

 *

 *

OWYHEE UPLANDS
153

Historic

Current

0 10 20 30 40 50 60

nonwoodland 

Nonforest/ 

> 2 layers 

2 layers 

1 layer *

SNAKE HEADWATERS

0 20 40 60 80

nonwoodland 

Nonforest/ 

> 2 layers 

2 layers 

1 layer 

 *

 *

S. CASCADES

0 10 20 30 40 50

nonwoodland 

Nonforest/ 

> 2 layers 

2 layers 

1 layer 

 *

 *

 *

UPPER CLARK FORK

0 10 20 30 40 50

nonwoodland 

Nonforest/ 

> 2 layers 

2 layers 

1 layer 

UPPER KLAMATH

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

> 2 layers 

2 layers 

1 layer *

UPPER SNAKE

Figure 40—Historical and current distribution of forest and woodland canopy layer classes expressed as a percentage of total area

on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate.

Asterisks indicate a significant (P≤0.2) difference between historical and current conditions. 
154

Table 24—Percentage comparison of area of forest and woodland understory species classes for ecological

reporting units in the midscale assessment of the interior Columbia River basin

Areaa

Western larch- Douglas fir-grand Western hemlockPonderosa pine lodgepole pine fir-Pacific silver fir western redcedar

Ecological reporting unit H C MDb H C MDb H C MDb H C MDb

Blue Mountains 18.0 19.4 1.3 4.1 3.4 -0.7 21.0 25.2 4.2* 0.0 0.0 0.0

Central Idaho Mountains 2.9 2.4 -0.4 11.6 11.0 -0.6 15.2 15.0 -0.2 0.6 0.7 0.1

Columbia Plateau 13.1 12.6 -0.5 0.9 1.1 0.2 2.0 2.9 0.9* 0.0 0.3 0.3

Lower Clark Fork 2.6 3.3 0.8 3.9 7.3 3.4 29.1 31.5 2.4 13.5 17.3 3.8*

Northern Cascades 8.9 7.5 -1.4 4.5 4.7 0.1 31.8 31.7 -0.1 1.1 1.4 0.4

Northern Glaciated 9.9 7.4 -2.5* 21.4 13.6 -7.8* 14.9 19.2 4.3* 2.1 5.6 3.5*

Mountains

Northern Great Basin 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Owyhee Uplands 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Snake Headwaters 0.0 0.1 0.1 13.5 9.0 -4.5 3.0 3.4 0.4 0.0 0.0 0.0

Southern Cascades 16.4 21.9 5.5 17.0 15.6 -1.3 7.1 10.0 2.9 0.0 0.0 0.0

Upper Clark Fork 7.8 5.8 -2.1* 32.5 24.0 -8.4* 5.4 8.4 3.1* 0.0 0.0 0.0

Upper Klamath 16.4 15.0 -1.4 3.0 2.4 -0.6 11.4 11.8 0.5 0.0 0.0 0.0

Upper Snake 0.0 0.0 0.0 0.2 0.3 0.1 0.4 1.2 0.8 0.0 0.0 0.0

Areaa

Mountain Subalpine fir- Whitebark pineHemlock Engelmann spruce subalpine larch Hardwood

H C MDb H C MDb H C MDb H C MDb

Blue Mountains 0.0 0.1 0.1* 3.9 5.3 1.4 0.0 0.0 0.0 0.2 0.2 0.0

Central Idaho Mountains 0.0 0.0 0.0* 14.7 16.6 1.8* 1.2 1.1 -0.1 0.3 0.3 0.0

Columbia Plateau 0.0 0.0 0.0 0.0 0.0 0.0* 0.0 0.0 0.0 0.2 0.2 0.0

Lower Clark Fork 0.9 0.8 -0.1 1.1 1.5 0.4* 0.0 0.0 0.0 0.0 0.0 0.0

Northern Cascades 0.4 0.7 0.2* 12.6 11.6 -1.0 0.7 1.4 0.8 0.6 0.8 0.2

Northern Glaciated Mountains 0.2 0.1 -0.1 10.3 10.8 0.5 0.0 0.0 0.0 0.1 0.9 0.8*

Northern Great Basin 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.7 0.1

Owyhee Uplands 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.1 0.0

Snake Headwaters 0.0 0.0 0.0 22.7 32.8 10.1* 0.3 0.4 0.1 8.6 7.9 -0.7

Southern Cascades 27.5 25.3 -2.2 0.7 0.7 -0.1 0.0 0.0 0.0 0.0 0.0 0.0

Upper Clark Fork 0.0 0.1 0.1 6.6 7.4 0.8 0.5 0.5 -0.1 0.2 0.2 0.1

Upper Klamath 4.9 3.1 -1.7 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.6 0.6

Upper Snake 0.0 0.0 0.0 0.2 0.0 -0.2 0.0 0.0 0.0 1.0 0.7 -0.3

Percent

Percent
155

Table 24—Percentage comparison of area of forest and woodland understory species classes for ecological

reporting units in the midscale assessment of the interior Columbia River basin (continued)

Areaa

NonforestJuniper Otherc nonwoodland

Ecological reporting unit H C MDb H C MDb H C MDb

Percent

Blue Mountains 1.5 2.1 0.7 16.6 12.6 -4.0* 34.7 31.7 -3.0*

Central Idaho Mountains 0.0 0.0 0.0 26.8 26.3 -0.5 26.6 26.4 -0.2

Columbia Plateau 2.3 6.5 4.2* 14.4 17.7 3.3* 67.2 58.8 -8.5*

Lower Clark Fork 0.0 0.0 0.0 40.8 32.8 -8.0* 8.3 5.5 -2.8

Northern Cascades 0.0 0.0 0.0 18.4 19.0 0.6 20.9 21.2 0.3

Northern Glaciated Mountains 0.0 0.1 0.1 22.0 23.1 1.1 19.0 19.2 0.2

Northern Great Basin 0.0 0.1 0.1 21.9 28.6 6.7* 77.5 70.6 -6.9*

Owyhee Uplands 2.2 3.2 0.9* 3.3 4.4 1.1 94.3 92.3 -2.0*

Snake Headwaters 0.0 0.0 0.0 26.5 20.5 -6.1* 25.3 25.9 0.6

Southern Cascades 1.8 0.1 -1.7 9.9 15.1 5.1 19.5 11.3 -8.2*

Upper Clark Fork 0.0 0.0 0.0 34.3 39.8 5.5* 12.8 13.8 1.0

Upper Klamath 8.5 9.0 0.5 14.7 18.0 3.4 41.1 39.7 -1.3

Upper Snake 1.9 1.3 -0.6 1.6 2.7 1.1* 94.7 93.8 -0.9

a H = historical; C = current; MD = mean difference of pairwise comparisons of historical and current subwatersheds.

b * statistically significant difference at P≤0.2; all values rounded to 1 decimal place. 

c The understory species class “other” includes grass-forb, shrub, and bare ground understories, and those comprised of Shasta

red fir, incense cedar, western white pine, limber pine, pinyon pine, and beargrass.
156

Historic

Current

0 5 10 15 20 25 30

ABLA2/PIEN 

TSME 

TSHE/THPL 

ABCO/ABAM 

PSME/ABGR/ 

LAOC/PICO 

PIPO 

 *

 *

BLUE MTNS.

0 5 10 15 20

ABLA2/PIEN 

TSME 

TSHE/THPL 

ABCO/ABAM 

PSME/ABGR/ 

LAOC/PICO 

PIPO 

 *

 *

CENTRAL IDAHO MTNS.

0 5 10 15 20

ABLA2/PIEN 

TSME 

TSHE/THPL 

ABCO/ABAM 

PSME/ABGR/ 

LAOC/PICO 

PIPO 

 *

 *

COLUMBIA PLATEAU

0 10 20 30 40

ABLA2/PIEN 

TSME 

TSHE/THPL 

ABCO/ABAM 

PSME/ABGR/ 

LAOC/PICO 

PIPO 

 *

LOWER CLARK FORK

0 10 20 30 40

ABLA2/PIEN 

TSME 

TSHE/THPL 

ABCO/ABAM 

PSME/ABGR/ 

LAOC/PICO 

PIPO 

 *

N. CASCADES

0 5 10 15 20 25

ABLA2/PIEN 

TSME 

TSHE/THPL 

ABCO/ABAM 

PSME/ABGR/ 

LAOC/PICO 

PIPO 

 *

 *

 *

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

ABLA2/PIEN 

TSME 

TSHE/THPL 

ABCO/ABAM 

PSME/ABGR/ 

LAOC/PICO 

PIPO 

N. GREAT BASIN

n/a

0 20 40 60 80 100

ABLA2/PIEN 

TSME 

TSHE/THPL 

ABCO/ABAM 

PSME/ABGR/ 

LAOC/PICO 

PIPO 

OWYHEE UPLANDS

n/a
157

Historic

Current

0 10 20 30 40

ABLA2/PIEN 

TSME 

TSHE/THPL 

ABCO/ABAM 

PSME/ABGR/ 

LAOC/PICO 

PIPO 

 *

SNAKE HEADWATERS

0 10 20 30 40

ABLA2/PIEN 

TSME 

TSHE/THPL 

ABCO/ABAM 

PSME/ABGR/ 

LAOC/PICO 

PIPO 

S. CASCADES

0 10 20 30 40

ABLA2/PIEN 

TSME 

TSHE/THPL 

ABCO/ABAM 

PSME/ABGR/ 

LAOC/PICO 

PIPO 

 *

 *

 *

UPPER CLARK FORK

0 5 10 15 20 25

ABLA2/PIEN 

TSME 

TSHE/THPL 

ABCO/ABAM 

PSME/ABGR/ 

LAOC/PICO 

PIPO 

UPPER KLAMATH

0.0 0.5 1.0 1.5 2.0 2.5

ABLA2/PIEN 

TSME 

TSHE/THPL 

ABCO/ABAM 

PSME/ABGR/ 

LAOC/PICO 

PIPO 

UPPER SNAKE

Figure 41—Historical and current distribution of forest and woodland understory species classes expressed as a percentage of

total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean

estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions. The understory species

class “other” includes grass-forb, shrub, and bare ground understories and those comprised of Shasta red fir, incense-cedar, western white pine, limber pine, pinyon pine, and beargrass. 
158

Historic

Current

0 10 20 30 40

nonwoodland 

Nonforest/ 

Other 

Juniper 

Hardwood 

PIAL-LALY 

 *

 *

BLUE MTNS.

0 10 20 30 40

nonwoodland 

Nonforest/ 

Other 

Juniper 

Hardwood 

PIAL-LALY 

CENTRAL IDAHO MTNS.

0 20 40 60 80

nonwoodland 

Nonforest/ 

Other 

Juniper 

Hardwood 

PIAL-LALY 

 *

 *

 *

COLUMBIA PLATEAU

0 10 20 30 40 50 60

nonwoodland 

Nonforest/ 

Other 

Juniper 

Hardwood 

PIAL-LALY 

 *

LOWER CLARK FORK

0 5 10 15 20 25

nonwoodland 

Nonforest/ 

Other 

Juniper 

Hardwood 

PIAL-LALY 

N. CASCADES

0 5 10 15 20 25 30

nonwoodland 

Nonforest/ 

Other 

Juniper 

Hardwood 

PIAL-LALY 

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

Other 

Juniper 

Hardwood 

PIAL-LALY 

 *

 *

N. GREAT BASIN

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

Other 

Juniper 

Hardwood 

PIAL-LALY 

 *

 *

OWYHEE UPLANDS
159

Historic

Current

0 10 20 30 40

nonwoodland 

Nonforest/ 

Other 

Juniper 

Hardwood 

PIAL-LALY 

 *

SNAKE HEADWATERS

0 5 10 15 20 25 30

nonwoodland 

Nonforest/ 

Other 

Juniper 

Hardwood 

PIAL-LALY 

 *

S. CASCADES

0 10 20 30 40 50

nonwoodland 

Nonforest/ 

Other 

Juniper 

Hardwood 

PIAL-LALY 

 *

UPPER CLARK FORK

0 10 20 30 40 50

nonwoodland 

Nonforest/ 

Other 

Juniper 

Hardwood 

PIAL-LALY 

UPPER KLAMATH

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

Other 

Juniper 

Hardwood 

PIAL-LALY 

 *

UPPER SNAKE

Figure 42—Historical and current distribution of forest and woodland understory species classes expressed as a percentage of

total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean

estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions. The understory species

class “other” includes grass-forb, shrub, and bare ground understories and those comprised of Shasta red fir, incense-cedar, western white pine, limber pine, pinyon pine, and beargrass. 
Blue Mountains ERU—In the Blue

Mountains ERU, forest and woodland tree cover

increased in previously nonwooded areas. Area

without tree cover (crown cover < 10 percent)

declined from 34.6 to 31.6 percent of the ERU

area, and area in the 40- to 50-percent crown

cover class increased from 17.7 to 21.0 percent of

the ERU (table 22 and fig. 39). Area in the 90- to

100-percent crown cover class declined from 7.8

to 5.4 percent. Canopy layering increased across

the ERU as well. Area with one canopy layer fell

from 16.0 to 12.5 percent, and area with more

than two canopy layers increased from 11.6 to

16.4 percent of the ERU area (table 23 and fig.

40). In the historical condition, 65.5 percent of

the ERU area was comprised of forest and woodland; 24 percent of that area was single canopy

layer forest or woodland. In the current condition, 68.3 percent of the ERU was comprised of

forest and woodland; 18.3 percent of that area

was single canopy layer forest or woodland. In 

the historical condition, 17.7 percent of the forest

and woodland area was comprised of canopies

with more than two layers. In the current condition, 24 percent of the forest and woodland area

was comprised of canopies with more than two

layers.

Understory area with Douglas-fir or grand fir or

white fir, or combinations (Pacific silver fir is

absent), increased significantly in the ERU; percentage of area rose from 21.0 to 25.2 percent of

the ERU. Understory area with mountain hemlock also increased significantly, but the change

was relatively minor (table 24 and figs. 41 and

42). Area with understories classified as “other”

(primarily grass and forb, shrub, or bare ground)

declined from 16.6 to 12.6 percent of the ERU.

These grass, forb, shrub, and bare ground understories currently support trees (table 25). In table

25, we see that area with grass-forb-shrub-bare

160

Table 25—Percentage comparisons of historical and current areas of grass-forb-shrub-bare ground and

conifer or hardwood understories for ecological reporting units in the midscale assessment of the interior

Columbia River basin

Areaa

Grass-forb-shrub- Nonforest- Conifer or hardwood

bare ground understories nonwoodland understories 

Ecological reporting unit H C MDb H C MDb H C MDb

Percent

Blue Mountains 16.6 12.6 -4.0* 34.6 31.6 -2.9* 48.8 55.7 6.9*

Central Idaho Mountains 26.6 26.1 -0.5 26.6 26.4 -0.2 46.8 47.5 0.7

Columbia Plateau 14.4 17.7 3.3* 67.2 58.8 -8.5* 18.4 23.6 5.1*

Lower Clark Fork 40.8 32.3 -8.5* 8.3 5.5 -2.8 50.9 62.1 11.2

Northern Cascades 18.4 19.1 0.7 20.9 21.2 0.3 60.7 59.7 -1.0

Northern Glaciated Mountains 21.7 23.1 1.4 19.0 19.2 0.2 59.3 57.7 -1.6

Northern Great Basin 21.9 28.6 6.7* 77.5 70.6 -6.9* 0.6 0.8 0.2

Owyhee Uplands 3.3 4.4 1.1 94.3 92.3 -2.0* 2.4 3.3 0.9*

Snake Headwaters 26.5 20.1 -6.4* 25.3 25.9 0.6 48.2 54.0 5.8*

Southern Cascades 9.9 14.1 4.2 19.5 11.3 -8.2* 70.6 74.6 4.0

Upper Clark Fork 34.3 39.8 5.5* 12.8 13.8 1.0 52.9 46.4 -6.5*

Upper Klamath 10.8 14.5 3.7 41.1 39.7 -1.3 48.1 45.7 -2.4

Upper Snake 1.6 2.7 1.1* 94.7 93.8 -0.9 3.7 3.5 -0.2

a H = historical; C = current; MD = mean difference of pairwise comparisons of historical and current subwatersheds.

b * indicates statistically significant difference at P≤0.2; all values rounded to 1 decimal place.
ground understories fell and area with conifer 

or hardwood understories (primarily conifer)

increased from 48.8 to 55.7 percent of the ERU

area. During the sample period, it is likely that

effective fire exclusion and grazing activities

allowed conifer understories to develop on 

11 percent of historical forest and woodland area.

Central Idaho Mountains ERU—In the

Central Idaho Mountains ERU, there was no 

net increase in forest or woodland area, but total

crown cover increased in existing forests and

woodlands. Area without tree cover remained

unchanged, but area in the 90- to 100-percent

crown cover class increased from 12.3 to 15.9 percent, and area in the 40- to 50-percent crown

cover class declined from 18.6 to 16.8 percent of

the ERU area (table 22 and fig. 39). No significant changes in canopy layers were evident at this

reporting scale (table 23 and fig. 40).

Understory area with subalpine fir-Engelmann

spruce cover increased significantly in the ERU;

percentage of area rose from 14.7 to 16.6 percent

of the ERU area (table 24 and figs. 41 and 42).

Understory area with mountain hemlock decreased significantly, but the change was relatively minor.

Columbia Plateau ERU—In the Columbia

Plateau ERU, forest and woodland tree cover

increased in previously nonwooded areas (table 22

and fig. 39). Area without tree cover (crown cover

< 10 percent) declined from 67.2 to 58.8 percent

of the ERU, and area in the 40- to 50-percent

crown cover class increased from 8.8 to 15.4 percent of the ERU. Area in the 90- to 100-percent

crown cover class increased from 4.0 to 4.6 percent of the ERU.

Canopy layering also increased in the ERU. 

Nonforest-nonwoodland area fell from 67.2 to

58.8 percent, thereby confirming previously noted

changes in forest and woodland area. Area with

one canopy layer increased; percentage of area

rose from 14.3 to 17.6 percent, and area with

more than two canopy layers increased from 4.3

to 6.4 percent of the ERU (table 23 and fig. 40).

Understory area with Douglas-fir-grand fir-white

fir (Pacific silver fir is absent) cover increased 

significantly in the ERU; percentage of area rose

from 2.0 to 2.9 percent of the ERU area. Understory area with subalpine fir-Engelmann spruce

cover also increased significantly, but the change

was relatively minor (table 24 and figs. 41 and

42). Area with understory juniper increased dramatically; percentage of area rose from 2.3 to 

6.5 percent of the ERU. Area with understories

classified as “other” (primarily grass-forb, shrub,

or bare ground) increased significantly from 14.4 

to 17.7 percent of the ERU. As noted in appendix 2, forest area in the Columbia Plateau ERU

increased by 3 percent, and woodland area increased by 5.5 percent of the ERU. The observed

increase in grass-forb, shrub, or bare ground

understory area likely was associated with forest

and woodland area expansion; that is, some historical herbland and shrubland areas are wooded

in the current condition. In table 25, we see that

nonforest-nonwoodland area fell from 67.2 to

58.8 percent, area with grass-forb-shrub-bare

ground understories rose from 14.4 to 17.7 percent, and area with conifer or hardwood understories (primarily conifer) increased from 18.4 to

23.6 percent of the ERU. During the sample 

period, it is likely that effective fire exclusion 

and grazing activities allowed conifer understories

to develop on 15.5 percent of historical forest and

woodland area.

Lower Clark Fork ERU—In the Lower 

Clark Fork ERU, forest and woodland tree cover

increased in previously nonwooded areas. Area in

the 10- to 30-percent crown cover class declined

from 6.3 to 2.7 percent of the ERU, and area 

in the 40- to 50-percent crown cover class also

declined, falling from 21.5 to 9.7 percent. Area 

in the 90- to 100-percent crown cover class rose

more than twofold from 19.7 to 43.4 percent of

the ERU area. In the historical vegetation condition, roughly one-quarter of forest patches in the

ERU exhibited a total crown cover ≤ 50 percent,

and more than three-quarters of forest patches

exhibited a total crown coverage ≤ 80 percent

(table 22 and fig. 39). In the current condition,

patches in the 90- to 100-percent crown cover

class were most abundant, representing more than

45 percent of the forest area of the ERU. Canopy

layering increased in the ERU as well; percentage

of area with one canopy layer fell from 38.7 to

30.0 percent of the ERU, area with two canopy

161
162

layers increased from 52.9 to 61.8 percent (ns)

(table 23 and fig. 40), and area with more than

two canopy layers increased from 0.1 to 2.7 percent of the ERU (ns).

Understory area with western hemlock-western

redcedar cover increased significantly in the ERU;

percentage of area rose from 13.5 to 17.3 percent

of the ERU (table 24 and figs. 41 and 42). Area

with understories as “other” (primarily grass-forb,

shrub, or bare ground) declined significantly from

40.8 to 32.8 percent of the ERU. These understories currently support trees. In table 25, we see

that nonforest-nonwoodland area fell from 8.3 to

5.5 percent (ns), area with grass-forb-shrub-bare

ground understories fell from 40.8 to 32.3 percent of the ERU, and area with conifer or hardwood understories (primarily conifer) increased

from 50.9 to 62.1 percent of the ERU (ns).

During the sample period, it is likely that effective fire exclusion allowed conifer understories to

develop on 12 percent of the historical forest area.

Northern Cascades ERU—Overall, there was

no significant trend in declining or increasing tree

cover in the ERU (table 22 and fig. 39). Area in

the 60- to 80-percent crown cover class fell from

33.6 to 30.3 percent (ns), but this decline was

evenly offset by increases in the 90- to 100-percent and 40- to 50-percent crown cover classes.

Neither were significant changes in canopy layers

evident at this reporting scale (table 23 and fig.

40). Understory area with mountain hemlock

cover increased significantly in the ERU; percentage of area rose from 0.4 to 0.7 percent of the

ERU (table 24 and figs. 41 and 42). Understory

area with ponderosa pine understory fell from 8.9

to 7.5 percent (ns). The Northern Cascades ERU

is large and diverse with a wide array of biophysical environmental settings. It is likely that differences in crown cover, canopy layering, and understory species cover may be detected at smaller

subregional scales.

Northern Glaciated Mountains ERU—No

significant changes were observed in tree cover 

at this reporting scale (table 22 and fig. 39). Area

in the 90- to 100-percent crown cover class increased from 21.5 to 24.2 percent, but the change

was not significant at P≤0.2. Canopy layering

increased significantly in the ERU. Area with two

canopy layers declined from 54.6 to 48.0 percent

of the ERU, and area with more than two canopy

layers rose from 5.7 to 10.2 percent (table 23 and

fig. 40).

Area with ponderosa pine or western larch-lodgepole pine understory cover declined significantly.

Percentage of area with ponderosa pine understories fell from 9.9 to 7.4 percent of the ERU,

and area with western larch-lodgepole pine understories dropped from 21.4 to 13.6 percent. Compensating increases were observed with Douglasfir–grand fir and western hemlock-western

redcedar understories (table 24 and figs. 41 and

42). Percentage of area with Douglas-fir–grand fir

understories increased from 14.9 to 19.2 percent

of the ERU area, and area with western hemlockwestern redcedar understory cover increased from

2.1 to 5.6 percent of the ERU. Hardwood understory area also increased.

Northern Great Basin ERU—In the Northern

Great Basin ERU, forest and woodland tree cover

increased in previously nonwooded areas (table 22

and fig. 39). Percentage of area without tree cover

(crown cover < 10 percent) declined from 77.5 to

70.6 percent of the ERU, and area in the 40- to

50-percent crown cover class increased from 11.5

to 15.6 percent. Percentage of area in the 60- to

80-percent crown cover class declined from 3.7 

to 3.1 percent. Concurrent with increasing forest

and woodland tree cover, area with one canopy

layer rose from 21.9 to 28.9 percent of the ERU

(table 23 and fig. 40).

Area with understories classified as “other” 

(primarily grass-forb, shrub, or bare ground)

increased significantly from 21.9 to 28.6 percent

of the ERU (table 24 and figs. 41 and 42). 

As noted in appendix 2, woodland area in the

Northern Great Basin ERU increased from 

15.3 to 22.2 percent of the ERU. The observed

increase in grass-forb, shrub, or bare ground

understory cover likely was associated with 

woodland area expansion; that is, some historical

herbland and shrubland areas are wooded in the

current condition (see also table 25). 
163

Owyhee Uplands ERU—In the Owyhee

Uplands ERU, woodland tree cover increased in

previously nonwooded areas. Percentage of area

without tree cover (crown cover < 10 percent)

declined from 94.3 to 92.3 percent of the ERU,

and percentage of area in the 10- to 30-percent

crown cover class increased from 4.2 to 5.4 percent (table 22 and fig. 39). Area in the 40- to 50-

percent crown cover class also increased, rising

from 1.3 to 2.2 percent of the ERU area. Canopy

layering also increased significantly in the ERU.

Percentage of area with two canopy layers increased from 2.1 to 3.0 percent of the ERU (table

23 and fig. 40). Area with understory juniper

cover also increased; percentage of area rose from

2.2 to 3.2 percent of the ERU (tables 24 and 25

and figs. 41 and 42).

Snake Headwaters ERU—In the Snake Headwaters ERU, there was no net increase in forest or

woodland area, but unlike most other ERUs, total

crown cover declined in existing forests and

woodlands (table 22 and fig. 39). Percentage 

of area without tree cover remained unchanged,

but area in the 90- to 100-percent crown cover

class fell from 11.5 to 7.5 percent of the ERU,

and percentage of area in the 40- to 50-percent

crown cover class rose from 15.8 to 19.2 percent

of the ERU. Canopy layering increased in the

ERU (table 23 and fig. 40). Percentage of area

with a single canopy layer declined from 26.4 

to 19.7 percent of the ERU and area with two

canopy layers increased from 45.1 to 50.6 percent

of the ERU (ns).

Percentage of area with western larch-lodgepole

pine understory cover fell from 13.5 to 9.0 percent of the ERU (ns), and area with subalpine firEngelmann spruce understory cover increased;

percentage of area rose from 22.7 to 32.8 percent

of the ERU, representing a 44-percent increase

during the sample period (table 24 and figs. 41

and 42). Percentage of area with understories classified as “other” (primarily grass-forb, shrub, or

bare ground) decreased significantly from 26.5 

to 20.5 percent of the ERU. These understories

currently support trees. In table 25, we see that

percentage of area with grass-forb-shrub-bare

ground understories fell by 6.4 percent, and area

with conifer or hardwood understories (primarily

conifer) increased by 5.8 percent, rising from 48.2

to 54.0 percent of the ERU area. It is likely that

fire exclusion and domestic livestock grazing practices enabled conifer understories to develop on

7.8 percent of historical forest and woodland area.

Southern Cascades ERU—Forest and woodland tree cover increased in previously nonwooded areas. Percentage of area without tree cover

(crown cover < 10 percent) fell sharply from 19.5

to 11.3 percent of the ERU, area in the 10- to

30-percent crown cover class increased from 

8.0 to 12.9 percent, and area in the 90- to 100-

percent crown cover class increased from 0.2 to

3.5 percent of the ERU (table 22 and fig. 39).

Perhaps the most significant change in canopy

layering occurring among all ERUs was that

observed for the Southern Cascades ERU. Nonforest-nonwoodland area fell sharply from 19.5 

to 11.3 percent of the ERU, and area with more

than two canopy layers increased by a compensating amount from 10.7 to 19.6 percent. Area 

with a single canopy layer also increased, but the

change was not significant; percentage of area rose

from 9.7 to 14.1 percent of the ERU. Area with

two canopy layers fell from 60.0 to 55.0 percent

but the change was not significant (table 23 and

fig. 40).

Upper Clark Fork ERU—There was no net

increase in forest or woodland area, but total

crown cover declined in existing forests and

woodlands (table 22 and fig. 39). Area without

tree cover remained unchanged, but percentage 

of area in the 60- to 80-percent crown cover class

fell from 45.3 to 41.2 percent of the ERU, and

area in the 10- to 30-percent crown cover class

rose from 7.4 to 9.5 percent. Canopy layering

also declined in the Upper Clark Fork ERU (table

23 and fig. 40). Percentage of area with two layers

and more than two layers declined significantly;

percentage of area fell from 41.0 to 37.2 percent,

and from 13.8 to 11.4 percent, respectively.

Percentage of area with a single canopy layer rose

sharply from 32.4 to 37.7 percent of the ERU.
164

The ERU area with ponderosa pine or western

larch-lodgepole pine understory cover declined

significantly. Percentage of area with ponderosa

pine understories fell from 7.8 to 5.8 percent, and

area with western larch-lodgepole pine understories dropped from 32.5 to 24.0 percent (table 24

and figs. 41 and 42). Area with Douglas-fir–grand

fir understory cover increased significantly in the

ERU; percentage of area rose from 5.4 to 8.4 percent of the ERU. Percentage of area with understories classified as “other” (primarily grass-forb,

shrub, or bare ground) increased from 34.3 to

39.8 percent of the ERU. In table 25, we see that

area with grass-forb-shrub-bare ground understories rose, and area with conifer or hardwood

understories (primarily conifer) declined. During

the sample period, it is likely that timber harvest

activities reduced conifer understories on 7 percent of the historical forest and woodland area.

Upper Klamath ERU—In the Upper Klamath

ERU, there was no net increase in forest or woodland area, but total crown cover declined in existing forests and woodlands (table 22 and fig. 39).

Percentage of area without tree cover remained

essentially unchanged, but area in the 60- to 80-

percent crown cover class fell from 27.4 to 19.9

percent, and area in the 40- to 50-percent crown

cover class rose sharply from 17.5 to 26.1 percent.

Canopy layering in the Upper Klamath generally

declined, but none of the observed changes was

significant at P≤0.2 (table 23 and fig. 40).

Upper Snake ERU—In the Upper Snake ERU,

forest tree cover increased slightly but significantly

in previously nonwooded areas (table 22 and fig.

39). Percentage of area without tree cover (crown

cover < 10 percent) remained unchanged, and

area in the 40- to 50-percent crown cover class

increased from 1.9 to 2.4 percent of the ERU

area. Concurrent with increasing tree cover, forest

area with a single canopy layer rose from 1.6 to

2.7 percent of the ERU (table 23 and fig. 40).

Percentage of area with understories classified 

as “other” (primarily grass-forb, shrub, or bare

ground) increased from 1.6 to 2.7 percent of the

ERU (see also table 25).

Table 26—Percentage comparison of area of forest and woodland in dead tree and snag abundance classes 

Areaa

No dead trees or < 10 percent of trees

snags apparent dead or snags

Ecological reporting unit H C MDb H C MDb

Percent

Blue Mountains 44.5 41.2 -3.3 20.1 20.2 0.1

Central Idaho Mountains 56.5 46.3 -10.2* 15.3 24.3 9.0*

Columbia Plateau 22.5 26.2 3.8* 10.2 2.7 2.5

Lower Clark Fork 66.0 62.7 -3.3 24.5 31.7 7.2

Northern Cascades 66.7 46.9 -19.8* 11.6 28.9 17.3*

Northern Glaciated Mountains 61.7 47.9 -13.8* 14.8 28.7 13.9*

Northern Great Basin 22.5 29.4 6.9* 0.0 0.0 0.0

Owyhee Uplands 4.9 6.4 1.4* 0.8 1.4 0.6

Snake Headwaters 51.8 34.2 -17.5* 22.0 23.7 1.6

Southern Cascades 76.8 76.9 0.1 3.7 9.9 6.2*

Upper Clark Fork 74.3 80.3 6.0* 10.6 5.2 -5.4*

Upper Klamath 21.7 24.1 2.4 36.7 34.1 -2.6*

Upper Snake 4.3 4.0 -0.3 1.0 1.7 0.8

a H = historical; C = current; MD = mean difference of pairwise comparisons of historical and current subwatersheds.

b * indicates statistically significant difference at P≤0.2; all values rounded to 1 decimal place.
for ecological reporting units in the midscale assessment of the interior Columbia River basin

Areaa

10 to 39 percent of 40 to 70 percent of trees > 70 percent of trees Nonforesttrees dead or snags dead or snags dead or snags nonwoodland

H C MDb H C MDb H C MDb H C MDb

Percent

0.8 5.3 4.5* 0.1 1.5 1.4* 0.0 0.1 0.1* 34.6 31.6 -2.9*

1.5 1.8 0.4 0.1 0.4 0.2* 0.0 0.8 0.8 26.6 26.4 -0.2

0.1 2.0 1.8* 0.0 0.2 0.2* 0.0 0.2 0.2 67.2 58.8 -8.4*

0.4 0.1 -0.3 0.9 0.0 -0.9 0.0 0.0 0.0 8.3 5.5 -2.8

0.5 2.6 2.1* 0.2 0.1 0.0 0.2 0.2 0.1 20.9 21.2 0.3

2.6 3.5 0.8 1.5 0.6 -0.9 0.4 0.1 -0.2 19.0 19.2 0.2

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 77.5 70.6 -6.9*

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 94.3 92.3 -2.0*

0.8 12.9 12.0* 0.0 1.2 1.2* 0.0 2.1 2.1* 25.3 25.9 0.6

0.0 1.4 1.3* 0.0 0.5 0.5 0.0 0.1 0.1* 19.5 11.3 -8.2*

1.8 0.2 -1.6* 0.1 0.1 0.0 0.4 0.3 -0.1 12.8 13.8 1.0

0.5 1.1 0.6 0.0 1.0 0.9 0.0 0.0 0.0 41.1 39.7 -1.3

0.0 0.2 0.2* 0.0 0.0 0.0 0.0 0.1 0.1 94.7 93.8 -0.9

Dead Tree and Snag Abundance

In this section, we report on changes in dead tree

and snag abundances to evaluate direct effects of

insect and pathogen infestation and mortality and

indirect effects of fire exclusion, dead tree salvage,

and timber harvest during the last half century.

Our null hypothesis was no significant difference

in dead tree and snag abundance between historical and current photointerpreted vegetation conditions. We speculated that fire prevention and

suppression activities, salvage logging, and selective

timber harvesting created increased abundance of

snags and dead trees in sapling, pole, and smalltree size classes. We further speculated that abundance of medium and large dead trees and snags

declined with widespread decline of live medium

and large trees (see also tables 20 and 21).

Table 26 and figure 43 display changes during the

sample period in percentage of area of five dead

tree and snag abundance classes. Dead tree and

snag classes were none apparent, < 10 percent of

trees dead or snags, 10 to 39 percent of trees dead

or snags, 40 to 70 percent of trees dead or snags,

and > 70 percent of trees dead or snags.

Dead tree and snag abundance increased significantly in the Blue Mountains, Central Idaho

Mountains, Columbia Plateau, North Cascades,

Northern Glaciated Mountains, Snake Headwaters, and Southern Cascades ERUs and

declined significantly in the Upper Clark Fork

and Upper Klamath ERUs. Two patterns of

change were observed. High concentrations of

dead trees within patches (≥ 10 percent of trees

dead or snags) were found in the Blue Mountains,

Snake Headwaters, and Southern Cascades ERUs,

but affected areas comprised less than 10 to 15

percent of the ERU area. In the Central Idaho

Mountains, Northern Cascades, and Northern

Glaciated Mountains ERUs, dead trees were less

concentrated within patches (< 10 percent of trees

dead or snags than in the aforementioned ERUs),

but this condition occurred over relatively large

areas of each ERU, affecting 10 to 20 percent of

the land area. 

165
166

Historic

Current

0 10 20 30 40 50

nonwoodland 

Nonforest/ 

> 70% 

40 to 70% 

10 to 39% 

< 10% 

None apparent 

 *

 *

 *

 *

BLUE MTNS.

0 20 40 60 80

nonwoodland 

Nonforest/ 

> 70% 

40 to 70% 

10 to 39% 

< 10% 

None apparent 

 *

 *

 *

CENTRAL IDAHO MTNS.

0 20 40 60 80

nonwoodland 

Nonforest/ 

> 70% 

40 to 70% 

10 to 39% 

< 10% 

None apparent 

 *

 *

 *

 *

COLUMBIA PLATEAU

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

> 70% 

40 to 70% 

10 to 39% 

< 10% 

None apparent 

LOWER CLARK FORK

0 20 40 60 80

nonwoodland 

Nonforest/ 

> 70% 

40 to 70% 

10 to 39% 

< 10% 

None apparent 

 *

 *

 *

N. CASCADES

0 20 40 60 80

nonwoodland 

Nonforest/ 

> 70% 

40 to 70% 

10 to 39% 

< 10% 

None apparent 

 *

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

> 70% 

40 to 70% 

10 to 39% 

< 10% 

None apparent 

 *

 *

N. GREAT BASIN

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

> 70% 

40 to 70% 

10 to 39% 

< 10% 

None apparent 

 *

 *

OWYHEE UPLANDS
167

Historic

Current

0 10 20 30 40 50 60

nonwoodland 

Nonforest/ 

> 70% 

40 to 70% 

10 to 39% 

< 10% 

None apparent 

 *

 *

 *

 *

SNAKE HEADWATERS

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

> 70% 

40 to 70% 

10 to 39% 

< 10% 

None apparent 

 *

 *

 *

 *

S. CASCADES

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

> 70% 

40 to 70% 

10 to 39% 

< 10% 

None apparent 

 *

 *

 *

UPPER CLARK FORK

0 10 20 30 40 50 60

nonwoodland 

Nonforest/ 

> 70% 

40 to 70% 

10 to 39% 

< 10% 

None apparent 

 *

UPPER KLAMATH

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

> 70% 

40 to 70% 

10 to 39% 

< 10% 

None apparent 

 *

UPPER SNAKE

Figure 43—Historical and current distribution of forest and woodland dead tree and snag abundance classes expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of

the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions. Dead tree and

snag classes were none apparent, < 10 percent of trees dead or snags, 10 to 39 percent of trees dead or snags, 40 to 70 percent of

trees dead or snags, and > 70 percent of trees dead or snags. 
Area Affected by 

Visible Logging Activity

In this section, we report on changes in area

affected by visible logging activity to evaluate

extent and effects of timber harvest activities during the sample period. Our null hypothesis was

no significant difference in percentage of area

within logging activity classes between historical

and current vegetation conditions. We hypothesized that area affected by selective and regeneration harvest activities would increase during the

sample period. Table 27 and figure 44 display

changes in percentage of area of five visible logging entry classes. Logging entry classes were no

logging apparent, regeneration harvest, selective

harvest, thinned, and small patch clearcut.

As would be expected, logging activity increased

significantly in all forested ERUs. Percentage of

area with no visible logging activity declined significantly in 6 of 13 ERUs, and increased in 3

herbland- and shrubland-dominated ERUs. The

most commonly increasing logging activity was

selective harvesting, which increased significantly

in the Blue Mountains, Columbia Plateau, Northern Cascades, Northern Glaciated Mountains,

Snake Headwaters, Southern Cascades, Upper

Clark Fork, and Upper Klamath ERUs and

declined in the Lower Clark Fork (ns) and Upper

Snake ERUs. In all but one forested ERU, selective harvesting had affected less than 10 percent

of the historical condition. But, in the Lower

Clark Fork ERU, nearly 22 percent of the area

had been affected by selective harvesting in the

historical condition. During the sample period,

apparent selective harvested area increased from

9.6 to 13.2 percent of the ERU in the Blue

Mountains, from 6.1 to 11.3 percent in the

Columbia Plateau, from 7.2 to 11.5 percent in

the Northern Cascades, from 4.5 to 11.4 percent

in the Northern Glaciated Mountains, from 0 to

0.3 percent in the Snake Headwaters, from 9.2 to

23.2 percent in the Southern Cascades, from 4.6

to 9.7 percent in the Upper Clark Fork, and from

7.0 to 19.3 percent in the Upper Klamath ERU.

168

Table 27—Percentage comparison of area of forest and woodland in visible logging activity classes for

Areaa

No logging apparent Regeneration harvest 

Ecological reporting unit H C MDb H C MDb

Percent

Blue Mountains 51.4 49.0 -2.5 3.9 5.1 1.2

Central Idaho Mountains 70.5 67.9 -2.6* 0.5 2.7 2.2*

Columbia Plateau 25.1 27.5 2.4 1.4 1.5 0.1

Lower Clark Fork 67.5 67.0 -0.6 2.3 9.5 7.2*

Northern Cascades 71.3 61.4 -9.9* 0.4 4.1 3.7*

Northern Glaciated Mountains 74.0 59.4 -14.6* 2.3 7.9 5.6*

Northern Great Basin 22.5 29.4 6.9* 0.0 0.0 0.0

Owyhee Uplands 5.7 7.7 2.0* 0.0 0.0 0.0

Snake Headwaters 74.7 72.4 -2.3 0.0 0.1 0.1*

Southern Cascades 65.1 54.7 -10.3* 5.5 7.5 2.0

Upper Clark Fork 77.0 63.8 -13.2* 5.5 11.6 6.1*

Upper Klamath 48.9 35.2 -13.7* 1.0 3.8 2.8*

Upper Snake 4.1 6.0 1.9* 0.0 0.0 -0.0

a H = historical; C = current; MD = mean difference of pairwise comparisons of historical and current subwatersheds.

b * indicates statistically significant difference at P≤0.2; all values rounded to 1 decimal place.
Area affected by regeneration harvests increased

most significantly in the Central Idaho Mountains, Lower Clark Fork, Northern Cascades,

Northern Glaciated Mountains, Upper Clark

Fork, and Upper Klamath ERUs. During the

sample period, apparent regeneration-harvested

area increased from 0.5 to 2.7 percent of the 

ERU in the Central Idaho Mountains, from 2.3

to 9.5 percent in the Lower Clark Fork, from 0.4

to 4.1 percent in the Northern Cascades, from

2.3 to 7.9 percent in the Northern Glaciated

Mountains, from 0 to 0.1 percent in the Snake

Headwaters, from 5.5 to 11.6 percent in the

Upper Clark Fork, and from 1.0 to 2.8 percent 

in the Upper Klamath ERU. Thinned and small

patch clearcut areas also increased significantly 

in about one-half of the ERUs, but affected areas

were considerably smaller than those affected by

regeneration and selective harvests.

In the Blue Mountains’ historical vegetation coverage, 65.5 percent of the land area of the ERU

was forested or woodland (appendix 2), 78.5 percent of the forest and woodland area exhibited 

no apparent sign of visible logging activity, and

21.4 percent of the forest and woodland area was

visibly logged (table 27). In our current vegetation coverage, 68.3 percent of the land area was

forested or in woodland, 71.7 percent of the forest and woodland area exhibited no apparent sign

of visible logging activity, and 28.4 percent of the

forest and woodland area was visibly logged.

Historically, 73.5 percent of the land area of the

Central Idaho Mountains ERU was forested or

woodland, 95.9 percent of the forest and woodland area exhibited no sign of visible logging

activity, and 3.8 percent of the forest and woodland area was visibly logged. In our current vegetation coverage, 73.5 percent of the land area was

again forested or in woodland, 92.4 percent of the

forest and woodland area exhibited no apparent

sign of visible logging activity, and 7.8 percent of

the forest and woodland area was visibly logged.

For the Columbia Plateau ERU, 32.8 percent of

the land area was forested or woodland in historical vegetation coverage, 76.5 percent of the forest

and woodland area exhibited no sign of visible

logging activity, and 24.4 percent of the forest

169

ecological reporting units in the midscale assessment of the interior Columbia River basin

Areaa

NonforestSelective harvest Thinned Patch clearcut nonwoodland

H C MDb H C MDb H C MDb H C MDb

Percent

9.6 13.2 3.5* 0.5 0.9 0.4 0.0 0.2 0.2* 34.6 31.6 -2.9*

2.3 2.5 0.2 0.0 0.4 0.3* 0.0 0.1 0.1* 26.6 26.4 -0.2

6.1 11.3 5.3* 0.2 0.8 0.6* 0.3 0.1 -0.2 67.2 58.8 -8.4*

21.8 16.4 -5.5 0.0 1.3 1.2 0.0 0.4 0.4 8.3 5.5 -2.8

7.2 11.5 4.3* 0.1 0.7 0.6* 0.0 1.1 1.1* 20.9 21.2 0.3

4.5 11.4 6.9* 0.0 0.7 0.7* 0.0 1.4 1.4* 19.0 19.2 0.2

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 77.5 70.6 -6.9*

0.0 0.0 -0.0 0.0 0.0 0.0 0.0 0.0 0.0 94.3 92.3 -2.0*

0.0 0.3 0.3* 0.0 0.0 0.0 0.0 1.3 1.3* 25.3 25.9 0.6

9.2 23.2 14.0* 0.7 2.8 2.1* 0.0 0.5 0.5* 19.5 11.3 -8.2*

4.6 9.7 5.1* 0.0 0.6 0.6* 0.0 0.5 0.5* 12.8 13.8 1.0

7.0 19.3 12.2* 2.0 1.9 0.0 0.0 0.1 0.1 41.1 39.7 -1.3

1.2 0.2 -1.1* 0.0 0.0 0.0 0.0 0.0 0.0 94.7 93.8 -0.9
170

Historic

Current

0 10 20 30 40 50 60

nonwoodland 

Nonforest/ 

Patch clearcut 

Thinned 

harvest 

Selective 

harvest 

Regeneration 

apparent 

No logging 

 *

 *

 *

BLUE MTNS.

0 20 40 60 80

nonwoodland 

Nonforest/ 

Patch clearcut 

Thinned 

harvest 

Selective 

harvest 

Regeneration 

apparent 

No logging 

 *

 *

 *

 *

CENTRAL IDAHO MTNS.

0 20 40 60 80

nonwoodland 

Nonforest/ 

Patch clearcut 

Thinned 

harvest 

Selective 

harvest 

Regeneration 

apparent 

No logging 

 *

 *

 *

COLUMBIA PLATEAU

0 20 40 60 80

nonwoodland 

Nonforest/ 

Patch clearcut 

Thinned 

harvest 

Selective 

harvest 

Regeneration 

apparent 

No logging 

 *

LOWER CLARK FORK

0 20 40 60 80

nonwoodland 

Nonforest/ 

Patch clearcut 

Thinned 

harvest 

Selective 

harvest 

Regeneration 

apparent 

No logging 

 *

 *

 *

 *

 *

N. CASCADES

0 20 40 60 80

nonwoodland 

Nonforest/ 

Patch clearcut 

Thinned 

harvest 

Selective 

harvest 

Regeneration 

apparent 

No logging 

 *

 *

 *

 *

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

Patch clearcut 

Thinned 

harvest 

Selective 

harvest 

Regeneration 

apparent 

No logging 

 *

 *

N. GREAT BASIN

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

Patch clearcut 

Thinned 

harvest 

Selective 

harvest 

Regeneration 

apparent 

No logging 

 *

 *

OWYHEE UPLANDS
171

Historic

Current

0 20 40 60 80

nonwoodland 

Nonforest/ 

Patch clearcut 

Thinned 

harvest 

Selective 

harvest 

Regeneration 

apparent 

No logging 

 *

 *

 *

SNAKE HEADWATERS

0 20 40 60 80

nonwoodland 

Nonforest/ 

Patch clearcut 

Thinned 

harvest 

Selective 

harvest 

Regeneration 

apparent 

No logging 

 *

 *

 *

 *

 *

S. CASCADES

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

Patch clearcut 

Thinned 

harvest 

Selective 

harvest 

Regeneration 

apparent 

No logging 

 *

 *

 *

 *

 *

UPPER CLARK FORK

0 10 20 30 40 50 60

nonwoodland 

Nonforest/ 

Patch clearcut 

Thinned 

harvest 

Selective 

harvest 

Regeneration 

apparent 

No logging 

 *

 *

 *

UPPER KLAMATH

0 20 40 60 80 100

nonwoodland 

Nonforest/ 

Patch clearcut 

Thinned 

harvest 

Selective 

harvest 

Regeneration 

apparent 

No logging 

 *

 *

UPPER SNAKE

Figure 44—Historical and current distribution of forest and woodland apparent logging entry classes expressed as a percentage

of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean

estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions. Logging entry classes

were no logging apparent, regeneration harvest, selective harvest, thinned, patch clearcut, and nonforest-nonwoodland.
and woodland area was visibly logged. In the 

current condition, 41.3 percent of the land area

was forested or in woodland, 66.6 percent of the

forest and woodland area exhibited no apparent

sign of visible logging activity, and 33.2 percent

of the forest and woodland area was visibly

logged. 

Historically, 93.6 percent of the land area of the

Lower Clark Fork ERU was forested or woodland,

72.1 percent of the forest and woodland area exhibited no apparent sign of visible logging activity, and 25.7 percent of the forest and woodland

area was visibly logged. In the current condition,

95.1 percent of the land area was forested or in

woodland, 70.5 percent of the forest and woodland area exhibited no apparent sign of visible

logging activity, and 29 percent of the forest and

woodland area was visibly logged.

For the Northern Cascades ERU historical vegetation coverage, 79.1 percent of the land area was

forested or in woodland, 90.1 percent of the forest and woodland area exhibited no apparent sign

of visible logging activity, and 9.7 percent of the

forest and woodland area was visibly logged. In

the current condition, 78.9 percent of the land

area was forested or in woodland, 77.8 percent 

of the forest and woodland area exhibited no

apparent sign of visible logging activity, and 22.1

percent of the forest and woodland area was visibly logged.

In the Northern Glaciated Mountains ERU, 

81 percent of the land area was forested or woodland in historical vegetation coverage, 91.4 percent of the forest and woodland area exhibited 

no apparent sign of visible logging activity, and

8.4 percent of the forest and woodland area was

visibly logged. In the existing condition, 80.8 percent of the land area was forested or in woodland,

73.5 percent of the forest and woodland area

exhibited no apparent sign of visible logging

activity, and 26.5 percent of the forest and woodland area was visibly logged.

Historically, 74.7 percent of the land area of the

Snake Headwaters ERU was forested or woodland, and no forest and woodland area exhibited

any sign of visible logging activity. In the current

condition, 74.1 percent of the land area was

forested or in woodland, 97.7 percent of the forest and woodland area exhibited no apparent sign

of visible logging activity, and 2.3 percent of the

forest and woodland area was visibly logged.

In the Southern Cascades ERU, 80.5 percent of

the land area was forested or woodland in historical vegetation coverage, 80.9 percent of the forest

and woodland area exhibited no apparent sign of

visible logging activity, and 19.1 percent of the

forest and woodland area was visibly logged. In

the current condition, 88.7 percent of the land

area was forested or in woodland, 61.7 percent of

the forest and woodland area exhibited no apparent sign of visible logging activity, and 38.3 percent of the forest and woodland area was visibly

logged.

Nearly 90 percent (87.2) of the land area of the

Upper Clark Fork ERU was forested or woodland

in historical vegetation coverage, 88.3 percent of

the forest and woodland area exhibited no apparent sign of visible logging activity, and 11.6 percent of the forest and woodland area was visibly

logged. In the current condition, 86.2 percent 

of the land area was forested or in woodland, 

74 percent of the forest and woodland area exhibited no apparent sign of visible logging activity,

and 26 percent of the forest and woodland area

was visibly logged.

Finally, in the Upper Klamath ERU historical

vegetation coverage, 58.9 percent of the land area

was forested or woodland, 83 percent of the forest

and woodland area exhibited no apparent sign of

visible logging activity, and 17 percent of the forest and woodland area was visibly logged. In the

existing condition, 60.3 percent of the land area

was forested or in woodland, 58.4 percent of the

forest and woodland area exhibited no apparent

sign of visible logging activity, and 41.6 percent

of the forest and woodland area was visibly

logged. 

172
173

Riparian and Wetland Area

In this section, we report on changes in distribution of riparian and wetland area to evaluate

extent and effects of timber harvest activities and

fire exclusion during the sample period. Our null

hypothesis was no significant difference in percentage of riparian or wetland area between historical and current vegetation conditions. We

speculated that riparian and wetland area within

forested ERUs declined as a result of increased

density and areal extent of forests and woodlands

and their dewatering effects on wet areas. We 

further speculated that riparian and wetland area

in nonforest also declined as a result of extensive

agricultural use of historical herbland and shrubland riparian areas and ditching efforts in wetlands. Table 28 and figure 45 display change 

in riparian and wetland area during the sample

period.

As was expected, riparian and wetland area

declined in ERUs with significant nonforest area,

but surprisingly, area increased in forested ERUs.

We suspect that the observed increase in riparian

and wetland area in forested ERUs was a function

of two unrelated factors. First, in the absence of

more regular fire disturbance to both riparian and

adjacent upslope environments, differences between valley bottom environments and adjacent

slopes had time to develop and be expressed over

a period of six or seven decades without fire.

Camp (1995) and Camp and others (1997) show 

that 74 percent of the riparian environments in

the Wenatchee Mountains of Washington display

the fire regime of adjacent side slopes. Second,

scale of photos of current vegetation conditions

was somewhat larger than that for the historical

conditions, and most historical photography was

black and white. Steps were taken to minimize

effects of these differences on remotely sensed

interpretations, but interpreters noted that interpreting vegetation attributes from black and

white, 1:20,000-scale, historical photographs 

was somewhat more difficult than interpreting

1:12,000-scale, current color photography. It 

is therefore possible that photointerpreters were

Table 28—Comparison of riparian-wetland area abundance in ecological reporting units in the midscale

assessment of the interior Columbia River basin

Areaa

Riparian or wetland area Not a riparian or wetland area 

Ecological reporting unit H C MDb H C MDb

Percent Percent

Blue Mountains 3.3 5.3 2.0* 96.7 94.7 -2.0*

Central Idaho Mountains 2.8 3.7 0.9* 97.2 96.3 -0.9*

Columbia Plateau 3.5 2.5 -1.0* 96.5 97.5 1.0*

Lower Clark Fork 3.3 3.6 0.3* 96.7 96.4 -0.3*

Northern Cascades 5.5 7.2 1.7* 94.5 92.8 -1.7*

Northern Glaciated Mountains 4.5 4.6 0.1 95.6 95.4 -0.1

Northern Great Basin 4.2 2.6 -1.5 95.8 97.4 1.5

Owyhee Uplands 1.5 1.1 -0.4 98.5 98.9 0.4

Snake Headwaters 5.9 6.5 0.5 94.1 93.5 -0.5

Southern Cascades 4.1 6.1 1.9* 95.9 93.9 -1.9*

Upper Clark Fork 8.0 7.5 -0.5 92.0 92.5 0.5

Upper Klamath 15.1 12.7 -2.4 84.9 87.3 2.4

Upper Snake 0.3 0.5 0.1 99.7 99.5 -0.1

a H = historical; C = current; MD = mean difference of pairwise comparisons of historical and current subwatersheds.

b * indicates statistically significant difference at P ≤ 0.2; all values rounded to 1 decimal place.
174

able to see more riparian and wetland areas in the

current photography. We believe that this source

of error was minimized, though, because highquality mirrored stereoscopes were used with adequate lighting and variable ocular magnification.

Riparian and wetland area increased significantly 

in the Blue Mountains, Central Idaho Mountains,

Lower Clark Fork, Northern Cascades, and

Southern Cascades ERUs and decreased significantly in the Columbia Plateau ERU. During 

the sample period, riparian and wetland area

increased from 3.3 to 5.3 percent of the ERU 

in the Blue Mountains, from 2.8 to 3.7 percent 

in the Central Idaho Mountains, from 3.3 to 

3.6 percent in the Lower Clark Fork, from 5.5 to

7.7 percent in the Northern Cascades, and from

4.1 to 6.1 percent in the Southern Cascades.

Riparian and wetland area declined from 3.5 to

2.5 percent of the ERU in the Columbia Plateau.

A general trend of declining riparian and wetland

area also was noted in the Northern Great Basin,

Owyhee Uplands, Upper Clark Fork, and Upper

Klamath ERUs, but changes were not significant

at this reporting scale.

Historic

Current

0 5 10 15 20

Upper Snake 

Upper Klamath 

Upper Clark Fork 

S. Cascades 

Snake Headwaters 

Owyhee Uplands 

N. Great Basin 

N. Glaciated Mtns. 

N. Cascades 

Lower Clark Fork 

Columbia Plateau 

Central Idaho Mtns. 

Blue Mtns. 

 *

 *

 *

 *

 *

 *

Riparian/Wetland Status

Figure 45—Historical and current distribution of riparian and wetland area expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions. 
175

Vulnerability of Forest 

Landscapes to Potential Insect 

and Pathogen Disturbances

In this section, we describe significant change in

area and connectivity of patch types between historical and current vegetation conditions, where

patch types were insect and pathogen disturbance

vulnerability classes (hereafter, vulnerability classes). Our null hypothesis was no significant difference in area or connectivity of area vulnerable to

insect and pathogen disturbances between historical and current vegetation conditions. We speculated that both significant increases and declines

in vulnerability would be observed as a consequence of timber harvest, domestic livestock grazing activities, and fire exclusion. All results are

summarized by ERU, and ecologically significant

change is the primarily emphasis. Appendix 3

provides complete tabular results of all analyses

summarized in this section. Comparisons among

ERUs are provided in the “Discussion.” 

Vulnerability to potential insect and pathogen 

disturbances changed less than expected because

variation among paired subwatershed samples was

considerable at the ERU scale. Large changes in

vulnerability to insect and pathogen disturbances

were common at the subwatershed scale, thereby

indicating that statistical pooling at the subwatershed scale was more appropriate for reporting

midscale trends in vulnerability.

Blue Mountains ERU—Subbasins sampled

within the Blue Mountains ERU (figs. 12 to 

14 and 16) included the Burnt (BUR), Lower

Grande Ronde (LGR), Silvies (SIL), Upper

Grande Ronde (UGR), Upper John Day (UJD),

and Wallowa (WAL). Among these subbasins, 

46 historical and current subwatershed pairs 

were sampled.

Insect disturbance vulnerabilities—

Defoliators—There was no significant change in

percentage of area vulnerable to western spruce

budworm disturbance at this reporting scale (fig.

46), but connectivity of vulnerable area declined

(appendix 3). Patch density of the high vulnerability class increased from 12.4 to 14.7 patches

per 10 000 ha, and mean patch size declined from

an average of 568.4 to 516.4 ha (ns). Loss of

grand fir and white fir cover and increased area 

in Douglas-fir cover were apparently compensating effects of management (appendix 2).

Barkbeetles—Area vulnerable to the Douglas-fir

beetle disturbance increased, and connectivity of

vulnerable area also increased. Percentage of area

in the high vulnerability class rose from 5.2 to 

7.8 percent of the ERU (fig. 46), patch density

increased from 4.5 to 8.9 patches per 10 000 ha

(appendix 3), and mean patch size remained

unchanged. Patch density of the moderate vulnerability class also increased from 17.7 to 22.8

patches per 10 000 ha, and mean patch size

remained unchanged. Percentage of area in the

low vulnerability class declined from 75.0 to 

69.8 percent. Increased area in the high vulnerability class was associated primarily with increased

area of Douglas-fir cover.

Area vulnerable to western pine beetle (type 1)

disturbance of mature and old ponderosa pine

declined (fig. 47); loss of area was observed in the

moderate vulnerability class where percentage of

area dropped from 18.8 to 16.5 percent of the

ERU. As noted earlier, there was little appreciable

loss of area in the ponderosa pine cover type, but

area of old multistory and old single-story structures declined, as did area of understory reinitiation and stem-exclusion open canopy structures

(appendix 2). Decline in area vulnerable to western pine beetle (type 1) was apparently associated

with declining abundance of medium and large

ponderosa pine in overstories associated with

understory reinitiation, stem-exclusion open

canopy, and old single-story and multistory forest

structures (tables 20 and 21). Patch density of the

moderate vulnerability class also increased from

11.3 to 15.2 patches per 10 000 ha, and mean

patch size dropped from 304.5 to 128.5 ha (ns),

indicating declining connectivity of host types.

Declining connectivity of the ponderosa pine

cover type also was observed (appendix 2).

Modeling rules for western pine beetle (type 2)

and mountain pine beetle (type 2) patch vulnerabilities were identical, and results of change analyses were likewise identical. Here and following,

Text resumes on page 180
176

Historic

Current

0 20 40 60 80

DFB high 

DFB mod. 

DFB low 

WSB high 

WSB mod. 

WSB low 

 *

 *

BLUE MTNS.

0 20 40 60 80

DFB high 

DFB mod. 

DFB low 

WSB high 

WSB mod. 

WSB low 

 *

CENTRAL IDAHO MTNS.

0 20 40 60 80 100

DFB high 

DFB mod. 

DFB low 

WSB high 

WSB mod. 

WSB low 

 *

 *

 *

 *

COLUMBIA PLATEAU

0 20 40 60 80 100

DFB high 

DFB mod. 

DFB low 

WSB high 

WSB mod. 

WSB low 

 *

 *

LOWER CLARK FORK

0 20 40 60 80

DFB high 

DFB mod. 

DFB low 

WSB high 

WSB mod. 

WSB low 

 *

N. CASCADES

0 20 40 60 80

DFB high 

DFB mod. 

DFB low 

WSB high 

WSB mod. 

WSB low 

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

DFB high 

DFB mod. 

DFB low 

WSB high 

WSB mod. 

WSB low 

N. GREAT BASIN

0 20 40 60 80 100

DFB high 

DFB mod. 

DFB low 

WSB high 

WSB mod. 

WSB low 

OWYHEE UPLANDS
177

Historic

Current

0 20 40 60 80 100

DFB high 

DFB mod. 

DFB low 

WSB high 

WSB mod. 

WSB low 

 *

 *

 *

 *

SNAKE HEADWATERS

0 20 40 60 80 100

DFB high 

DFB mod. 

DFB low 

WSB high 

WSB mod. 

WSB low 

 *

 *

S. CASCADES

0 20 40 60 80

DFB high 

DFB mod. 

DFB low 

WSB high 

WSB mod. 

WSB low 

 *

UPPER CLARK FORK

0 20 40 60 80 100

DFB high 

DFB mod. 

DFB low 

WSB high 

WSB mod. 

WSB low 

UPPER KLAMATH

0 20 40 60 80 100

DFB high 

DFB mod. 

DFB low 

WSB high 

WSB mod. 

WSB low 

 *

 *

 *

 *

UPPER SNAKE

Figure 46—Historical and current distribution of western spruce budworm and Douglas-fir beetle disturbance vulnerability

classes expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current

conditions. Insect disturbance abbreviations are WSB = western spruce budworm and DFB = Douglas-fir beetle. Vulnerability

class codes are low, moderate, and high.
178

Historic

Current

0 20 40 60 80 100

WPB2 high 

WPB2 mod. 

WPB2 low 

WPB1 high 

WPB1 mod. 

WPB1 low 

 *

 *

BLUE MTNS.

0 20 40 60 80 100

WPB2 high 

WPB2 mod. 

WPB2 low 

WPB1 high 

WPB1 mod. 

WPB1 low 

 *

 *

 *

CENTRAL IDAHO MTNS.

0 20 40 60 80 100

WPB2 high 

WPB2 mod. 

WPB2 low 

WPB1 high 

WPB1 mod. 

WPB1 low 

 *

 *

 *

 *

COLUMBIA PLATEAU

0 20 40 60 80 100

WPB2 high 

WPB2 mod. 

WPB2 low 

WPB1 high 

WPB1 mod. 

WPB1 low 

 *

 *

LOWER CLARK FORK

0 20 40 60 80 100

WPB2 high 

WPB2 mod. 

WPB2 low 

WPB1 high 

WPB1 mod. 

WPB1 low 

 *

 *

 *

 *

 *

N. CASCADES

0 20 40 60 80 100

WPB2 high 

WPB2 mod. 

WPB2 low 

WPB1 high 

WPB1 mod. 

WPB1 low 

N. GLACIATED MTNS.

0 20 40 60 80 100

WPB2 high 

WPB2 mod. 

WPB2 low 

WPB1 high 

WPB1 mod. 

WPB1 low 

N. GREAT BASIN

0 20 40 60 80 100

WPB2 high 

WPB2 mod. 

WPB2 low 

WPB1 high 

WPB1 mod. 

WPB1 low 

 *

 *

OWYHEE UPLANDS
179

Historic

Current

0 20 40 60 80 100

WPB2 high 

WPB2 mod. 

WPB2 low 

WPB1 high 

WPB1 mod. 

WPB1 low 

 *

 *

SNAKE HEADWATERS

0 20 40 60 80 100

WPB2 high 

WPB2 mod. 

WPB2 low 

WPB1 high 

WPB1 mod. 

WPB1 low 

S. CASCADES

0 20 40 60 80 100

WPB2 high 

WPB2 mod. 

WPB2 low 

WPB1 high 

WPB1 mod. 

WPB1 low 

 *

 *

 *

UPPER CLARK FORK

0 20 40 60 80 100

WPB2 high 

WPB2 mod. 

WPB2 low 

WPB1 high 

WPB1 mod. 

WPB1 low *

UPPER KLAMATH

0 20 40 60 80 100

WPB2 high 

WPB2 mod. 

WPB2 low 

WPB1 high 

WPB1 mod. 

WPB1 low 

UPPER SNAKE

Figure 47—Historical and current distribution of western pine beetle type-1 and type-2 disturbance vulnerability classes

expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the

standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.

Insect disturbance abbreviations are WPB1=western pine beetle (type 1) of mature and old ponderosa pine, and WPB2=western

pine beetle (type 2) of immature and high density ponderosa pine. Vulnerability class codes are low, moderate, and high.
180

we report them together. Percentage of area highly

vulnerable to western pine beetle (type 2) and

mountain pine beetle (type 2) disturbance of

immature, high-density ponderosa pine remained

unchanged during the sample period (figs. 47 

and 48). Patch density increased from 10.5 to

13.7 patches per 10 000 ha, and mean patch size

increased from 166.9 to 254.5 ha. These results,

and results from analysis of change in forest cover

types and structural classes indicated that young

and middle-aged patches vulnerable to this disturbance were only slightly more numerous in the

current vegetation condition than in the historical

condition, but the average size of highly vulnerable patches had increased by 52 percent. Conversely, area and connectivity of the moderate

vulnerability class declined; percentage of area 

fell from 30.6 to 26.0 percent of the ERU, patch

density rose by 30 percent from 20.6 to 26.7

patches per 10 000 ha, and mean patch size

declined by 45 percent from 259.7 to 141.8 ha.

Another significant change in area vulnerable 

to bark beetle disturbance was associated with

mountain pine beetle (type 1) disturbance of high

density lodgepole pine. Percentage of area in the

high vulnerability class fell from 6.7 to 5.1 percent, a 24-percent loss of vulnerable area during

the sample period (fig. 48). Because no significant

change in area of the lodgepole pine cover type

was observed where lodgepole pine was the principal cover species (appendix 2), these results suggest that the percentage of area of lodgepole pine

in mixed species cover types declined during the

sample period. As modeled, both pure and mixed

species cover types with lodgepole pine were host

types (see Hessburg and others, in press).

Area and connectivity of the fir engraver high vulnerability class declined (fig. 49); change was correlated with observed declines in grand fir-white

fir and subalpine fir-Engelmann spruce cover type

area (appendix 2). Percentage of area in the high

vulnerability class fell from 24.6 to 15.0 percent,

patch density rose from 9.0 to 12.4 patches per

10 000 ha, and mean patch size declined by 

67 percent from 428.3 to 142.2 ha (appendix 3).

Percentage of area in low and moderate vulnerability rose from 65.0 to 70.4 percent and from

10.3 to 14.6 percent of the ERU, respectively.

Mean patch size of low vulnerability areas declined from 1907.4 to 1409.0 ha, and mean

patch size of moderate vulnerability areas rose

from 65.3 to 81.4 ha, indicating that areas of fir

engraver host and nonhost type are more highly

fragmented in the current condition.

Finally, area and connectivity of the spruce beetle

high vulnerability class declined (fig. 49); change

was correlated with observed declines in subalpine

fir-Engelmann spruce cover type area (appendix

2). Percentage of area in the high vulnerability

class fell from 2.6 to 0.7 percent of the ERU, and

percentage of area in the low vulnerability class

rose from 63.3 to 66.0 percent. Observations of

Gast and others (1991) suggest that declining vulnerability to spruce beetle in the Blue Mountains

ERU was associated with spruce beetle outbreaks

of the last decade that already have claimed many

old Engelmann spruce patches observed in the

historical vegetation coverage.

Pathogen disturbance vulnerabilities—

Dwarf mistletoes—Area and connectivity of patches vulnerable to Douglas-fir dwarf mistletoe disturbance increased (fig. 50). Percentage of area

rose sharply by 63 percent from 10.1 to 16.5 percent, patch density more than doubled from 9.3

to 19.6 patches per 10 000 ha, and mean patch

size rose by 44 percent from 87.5 to 125.7 ha

(appendix 3). Increased area in the high vulnerability class was associated with expanded area of

the Douglas-fir cover type, increased canopy layering, and contiguity of host patches apparently

brought about by fire exclusion and selective harvesting.

Area and connectivity of patches vulnerable to

western (ponderosa pine) dwarf mistletoe disturbance declined (fig. 51). Percentage of area fell

from 10.4 to 8.1 percent of the ERU, patch density rose from 9.6 to 12.7 patches per 10 000 ha,

and mean patch size remained unchanged. Because no significant change in area of the ponderosa pine cover type was observed where

ponderosa pine was the principal cover species

(appendix 2), these results suggest that patch area

of ponderosa pine in mixed species cover types

with multilayered canopies declined significantly

during the sample period.
181

Connectivity of patches vulnerable to western

larch dwarf mistletoe disturbance declined

(appendix 3); patch density rose from 1.8 to 

3.6 patches per 10 000 ha, and mean patch size

declined from 16.0 to 9.8 ha. Area in the low 

vulnerability class increased from 95.9 to 96.5

percent.

Root diseases—Area and connectivity of patches

vulnerable to laminated root rot disturbance

increased during the sample period, but the

observed change in area was not significant at

P≤0.2 (fig. 52). Percentage of area rose from 

34.5 to 37.0 percent (ns), and mean patch size

increased from 376.7 to 572.4 ha (appendix 3),

indicating increased contiguity of susceptible host

patches. The observed increase in vulnerability

was primarily associated with increased area of 

the Douglas-fir cover type, which rose from 7.7 

to 17.1 percent of the ERU area (appendix 2).

Area and connectivity of patches vulnerable to 

S-group annosum disturbance declined (fig. 53).

Percentage of area declined from 24.3 to 16.9

percent of the ERU, patch density increased from

11.0 to 15.0 patches per 10 000 ha, and mean

patch size declined by 52 percent from 238.3 to

114.7 ha (appendix 3). The apparent change in

vulnerability of Blue Mountains landscapes to 

S-group annosum was associated with observed

declines in area of grand fir-white fir, and subalpine fir-Engelmann spruce cover types, where

these species represented the principal overstory

cover (appendix 2). But the story of change is

perhaps more complex than these results suggest.

Although it is apparent that a dramatic reduction

in dominance of overstory true firs has occurred,

grand fir, white fir, and subalpine fir have significantly increased in area where they occur as primary understory species occupying lower and

intermediate crown classes (see also Lehmkuhl

and others 1994). Because spores of this pathogen

readily infect freshly cut stumps, and because 

the majority of stands with true fir understories

have experienced timber harvest, we suggest 

that expression of S-group annosum root disease 

disturbance in the foreseeable future will be 

far greater than that occurring in our photointerpreted historical or current condition.

Connectivity of area vulnerable to P-group 

annosum also declined (fig. 53); patch density 

remained relatively stable, and mean patch size

declined from 110.7 to 75.2 ha. The observed

decline in connectivity was associated with reduced connectivity of patches with medium and

large ponderosa pine in pure and mixed compositions (table 21 and appendix 2).

Area vulnerable to tomentosus root and butt rot

disturbance declined, but we suggest that the

change is temporary and superficial; percentage 

of area fell from 4.4 to 2.5 percent of the ERU

(fig. 54). Spruce beetle outbreaks during the

1980s resulted in mortality of many old patches

of Engelmann spruce (Gast and others 1991).

With increasing age and declining vitality, remaining patches of mature and old spruce with

tomentosus (and other) root diseases eventually

will experience a period of heightened gap disturbance where trees collapse and are windthrown 

as a consequence of a resident root pathogen and

strong winds. Windthrown trees usually are infested by the spruce beetle. As patches subsequently regenerate, many again will be comprised

of Engelmann spruce in pure and mixed compositions, and tomentosus root disease inoculum

already will be resident in the patch.

Area and connectivity of patches vulnerable 

to Schweinitzii root and butt rot disturbance

increased during the sample period (fig. 54); 

percentage of area in the high vulnerability class

rose from 46.7 to 52.1 percent of the ERU, patch

density dropped from 12.7 to 10.5 patches per 

10 000 ha, and mean patch size increased by

149.1 ha from 807.1 ha (ns). The observed

increase in vulnerability was associated primarily

with increased cover and contiguity of Douglas-fir

(appendix 2). Percentage of area in the moderate

vulnerability class declined by a corresponding

amount. 

Central Idaho Mountains ERU—Subbasins

sampled within the Central Idaho Mountains

ERU (figs. 11, 14, 17, 18, and 22) included the

Boise-Mores (BOM), Big Wood (BWD), Lemhi

(LMH), Lochsa (LOC), Medicine Lodge (MDL),

South Fork Clearwater (SFC), South Fork

Salmon (SFS), and Upper Middle Fork Salmon

(UMS). Among these subbasins, 43 historical and

current subwatershed pairs were sampled.

Text resumes on page 196
182

Historic

Current

0 10 20 30 40 50 60

MPB2 high 

MPB2 mod. 

MPB2 low 

MPB1 high 

MPB1 mod. 

MPB1 low 

 *

 *

BLUE MTNS.

0 20 40 60 80

MPB2 high 

MPB2 mod. 

MPB2 low 

MPB1 high 

MPB1 mod. 

MPB1 low 

 *

 *

 *

CENTRAL IDAHO MTNS.

0 20 40 60 80 100

MPB2 high 

MPB2 mod. 

MPB2 low 

MPB1 high 

MPB1 mod. 

MPB1 low 

 *

 *

 *

 *

COLUMBIA PLATEAU

0 20 40 60 80 100

MPB2 high 

MPB2 mod. 

MPB2 low 

MPB1 high 

MPB1 mod. 

MPB1 low 

 *

 *

 *

 *

LOWER CLARK FORK

0 10 20 30 40 50 60

MPB2 high 

MPB2 mod. 

MPB2 low 

MPB1 high 

MPB1 mod. 

MPB1 low 

 *

 *

N. CASCADES

0 10 20 30 40 50 60

MPB2 high 

MPB2 mod. 

MPB2 low 

MPB1 high 

MPB1 mod. 

MPB1 low 

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

MPB2 high 

MPB2 mod. 

MPB2 low 

MPB1 high 

MPB1 mod. 

MPB1 low 

N. GREAT BASIN

0 20 40 60 80 100

MPB2 high 

MPB2 mod. 

MPB2 low 

MPB1 high 

MPB1 mod. 

MPB1 low 

 *

 *

OWYHEE UPLANDS
183

Historic

Current

0 20 40 60 80

MPB2 high 

MPB2 mod. 

MPB2 low 

MPB1 high 

MPB1 mod. 

MPB1 low 

 *

 *

 *

 *

SNAKE HEADWATERS

0 10 20 30 40 50 60

MPB2 high 

MPB2 mod. 

MPB2 low 

MPB1 high 

MPB1 mod. 

MPB1 low 

 *

S. CASCADES

0 10 20 30 40 50 60

MPB2 high 

MPB2 mod. 

MPB2 low 

MPB1 high 

MPB1 mod. 

MPB1 low 

 *

UPPER CLARK FORK

0 20 40 60 80 100

MPB2 high 

MPB2 mod. 

MPB2 low 

MPB1 high 

MPB1 mod. 

MPB1 low 

UPPER KLAMATH

0 20 40 60 80 100

MPB2 high 

MPB2 mod. 

MPB2 low 

MPB1 high 

MPB1 mod. 

MPB1 low 

UPPER SNAKE

Figure 48—Historical and current distribution of mountain pine beetle type-1 and type-2 disturbance vulnerability classes

expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the

standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.

Insect disturbance abbreviations are MPB1=mountain pine beetle (type 1) of high-density lodgepole pine, and MPB2=mountain

pine beetle (type 2) of immature and high-density ponderosa pine. Vulnerability class codes are low, moderate, and high. 
184

Historic

Current

0 20 40 60 80

SB high 

SB mod. 

SB low 

FE high 

FE mod. 

FE low 

 *

 *

 *

 *

 *

BLUE MTNS.

0 20 40 60 80

SB high 

SB mod. 

SB low 

FE high 

FE mod. 

FE low 

 *

 *

 *

 *

CENTRAL IDAHO MTNS.

0 20 40 60 80 100

SB high 

SB mod. 

SB low 

FE high 

FE mod. 

FE low 

 *

COLUMBIA PLATEAU

0 20 40 60 80 100

SB high 

SB mod. 

SB low 

FE high 

FE mod. 

FE low 

LOWER CLARK FORK

0 20 40 60 80

SB high 

SB mod. 

SB low 

FE high 

FE mod. 

FE low 

 *

 *

 *

N. CASCADES

0 20 40 60 80

SB high 

SB mod. 

SB low 

FE high 

FE mod. 

FE low 

 *

 *

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

SB high 

SB mod. 

SB low 

FE high 

FE mod. 

FE low 

N. GREAT BASIN

0 20 40 60 80 100

SB high 

SB mod. 

SB low 

FE high 

FE mod. 

FE low 

OWYHEE UPLANDS
185

Historic

Current

0 20 40 60 80

SB high 

SB mod. 

SB low 

FE high 

FE mod. 

FE low 

 *

 *

 *

SNAKE HEADWATERS

0 20 40 60 80 100

SB high 

SB mod. 

SB low 

FE high 

FE mod. 

FE low 

 *

 *

S. CASCADES

0 20 40 60 80

SB high 

SB mod. 

SB low 

FE high 

FE mod. 

FE low 

 *

UPPER CLARK FORK

0 20 40 60 80 100

SB high 

SB mod. 

SB low 

FE high 

FE mod. 

FE low 

 *

 *

 *

UPPER KLAMATH

0 20 40 60 80 100

SB high 

SB mod. 

SB low 

FE high 

FE mod. 

FE low 

UPPER SNAKE

Figure 49—Historical and current distribution of fir engraver and spruce beetle disturbance vulnerability classes expressed as a

percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of

the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions. Insect disturbance abbreviations are FE = fir engraver and SB = spruce beetle. Vulnerability class codes are low, moderate, and high. 
186

Historic

Current

0 20 40 60 80 100

WLDM high 

WLDM mod. 

WLDM low 

DFDM high 

DFDM mod. 

DFDM low 

 *

 *

 *

BLUE MTNS.

0 20 40 60 80 100

WLDM high 

WLDM mod. 

WLDM low 

DFDM high 

DFDM mod. 

DFDM low 

 *

 *

 *

 *

CENTRAL IDAHO MTNS.

0 20 40 60 80 100

WLDM high 

WLDM mod. 

WLDM low 

DFDM high 

DFDM mod. 

DFDM low 

 *

 *

 *

 *

COLUMBIA PLATEAU

0 20 40 60 80 100

WLDM high 

WLDM mod. 

WLDM low 

DFDM high 

DFDM mod. 

DFDM low 

LOWER CLARK FORK

0 20 40 60 80 100

WLDM high 

WLDM mod. 

WLDM low 

DFDM high 

DFDM mod. 

DFDM low 

N. CASCADES

0 20 40 60 80 100

WLDM high 

WLDM mod. 

WLDM low 

DFDM high 

DFDM mod. 

DFDM low 

 *

 *

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

WLDM high 

WLDM mod. 

WLDM low 

DFDM high 

DFDM mod. 

DFDM low 

N. GREAT BASIN

0 20 40 60 80 100

WLDM high 

WLDM mod. 

WLDM low 

DFDM high 

DFDM mod. 

DFDM low 

OWYHEE UPLANDS
187

Historic

Current

0 20 40 60 80 100

WLDM high 

WLDM mod. 

WLDM low 

DFDM high 

DFDM mod. 

DFDM low 

 *

 *

SNAKE HEADWATERS

0 20 40 60 80 100

WLDM high 

WLDM mod. 

WLDM low 

DFDM high 

DFDM mod. 

DFDM low 

 *

 *

 *

S. CASCADES

0 20 40 60 80 100

WLDM high 

WLDM mod. 

WLDM low 

DFDM high 

DFDM mod. 

DFDM low 

 *

 *

 *

UPPER CLARK FORK

0 20 40 60 80 100

WLDM high 

WLDM mod. 

WLDM low 

DFDM high 

DFDM mod. 

DFDM low 

UPPER KLAMATH

0 20 40 60 80 100

WLDM high 

WLDM mod. 

WLDM low 

DFDM high 

DFDM mod. 

DFDM low 

UPPER SNAKE

Figure 50—Historical and current distribution of Douglas-fir and western larch dwarf mistletoe disturbance vulnerability classes expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the

standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.

Pathogen disturbance abbreviations are DFDM = Douglas-fir dwarf mistletoe and WLDM = western larch dwarf mistletoe.

Vulnerability class codes are low, moderate, and high.
188

Historic

Current

0 20 40 60 80 100

LPDM high 

LPDM mod. 

LPDM low 

PPDM high 

PPDM mod. 

PPDM low 

 *

 *

 *

BLUE MTNS.

0 20 40 60 80 100

LPDM high 

LPDM mod. 

LPDM low 

PPDM high 

PPDM mod. 

PPDM low 

 *

 *

 *

CENTRAL IDAHO MTNS.

0 20 40 60 80 100

LPDM high 

LPDM mod. 

LPDM low 

PPDM high 

PPDM mod. 

PPDM low 

 *

 *

COLUMBIA PLATEAU

0 20 40 60 80 100

LPDM high 

LPDM mod. 

LPDM low 

PPDM high 

PPDM mod. 

PPDM low 

LOWER CLARK FORK

0 20 40 60 80 100

LPDM high 

LPDM mod. 

LPDM low 

PPDM high 

PPDM mod. 

PPDM low 

 *

 *

 *

 *

N. CASCADES

0 20 40 60 80 100

LPDM high 

LPDM mod. 

LPDM low 

PPDM high 

PPDM mod. 

PPDM low 

 *

 *

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

LPDM high 

LPDM mod. 

LPDM low 

PPDM high 

PPDM mod. 

PPDM low 

N. GREAT BASIN

0 20 40 60 80 100

LPDM high 

LPDM mod. 

LPDM low 

PPDM high 

PPDM mod. 

PPDM low 

OWYHEE UPLANDS
189

Historic

Current

0 20 40 60 80 100

LPDM high 

LPDM mod. 

LPDM low 

PPDM high 

PPDM mod. 

PPDM low 

 *

 *

 *

SNAKE HEADWATERS

0 20 40 60 80 100

LPDM high 

LPDM mod. 

LPDM low 

PPDM high 

PPDM mod. 

PPDM low 

S. CASCADES

0 20 40 60 80 100

LPDM high 

LPDM mod. 

LPDM low 

PPDM high 

PPDM mod. 

PPDM low 

 *

 *

 *

 *

UPPER CLARK FORK

0 20 40 60 80 100

LPDM high 

LPDM mod. 

LPDM low 

PPDM high 

PPDM mod. 

PPDM low *

UPPER KLAMATH

0 20 40 60 80 100

LPDM high 

LPDM mod. 

LPDM low 

PPDM high 

PPDM mod. 

PPDM low 

UPPER SNAKE

Figure 51—Historical and current distribution of ponderosa pine and lodgepole pine dwarf mistletoe disturbance vulnerability

classes expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current

conditions. Pathogen disturbance abbreviations are PPDM = ponderosa pine dwarf mistletoe and LPDM = lodgepole pine dwarf

mistletoe. Vulnerability class codes are low, moderate, and high.
190

0 10 20 30 40 50 60

PHWE high 

PHWE mod. 

PHWE low 

AROS high 

AROS mod. 

AROS low 

 *

BLUE MTNS.

0 10 20 30 40 50

PHWE high 

PHWE mod. 

PHWE low 

AROS high 

AROS mod. 

AROS low 

CENTRAL IDAHO MTNS.

Historic

Current

0 20 40 60 80 100

PHWE high 

PHWE mod. 

PHWE low 

AROS high 

AROS mod. 

AROS low 

 *

 *

COLUMBIA PLATEAU

0 20 40 60 80

PHWE high 

PHWE mod. 

PHWE low 

AROS high 

AROS mod. 

AROS low 

LOWER CLARK FORK

0 10 20 30 40 50 60

PHWE high 

PHWE mod. 

PHWE low 

AROS high 

AROS mod. 

AROS low 

 *

 *

 *

 *

N. CASCADES

0 10 20 30 40 50

PHWE high 

PHWE mod. 

PHWE low 

AROS high 

AROS mod. 

AROS low 

 *

 *

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

PHWE high 

PHWE mod. 

PHWE low 

AROS high 

AROS mod. 

AROS low 

N. GREAT BASIN

0 20 40 60 80 100

PHWE high 

PHWE mod. 

PHWE low 

AROS high 

AROS mod. 

AROS low 

OWYHEE UPLANDS
191

Historic

Current

0 20 40 60 80

PHWE high 

PHWE mod. 

PHWE low 

AROS high 

AROS mod. 

AROS low 

 *

 *

 *

SNAKE HEADWATERS

0 20 40 60 80

PHWE high 

PHWE mod. 

PHWE low 

AROS high 

AROS mod. 

AROS low 

 *

 *

 *

S. CASCADES

0 10 20 30 40 50 60

PHWE high 

PHWE mod. 

PHWE low 

AROS high 

AROS mod. 

AROS low 

 *

UPPER CLARK FORK

0 20 40 60 80 100

PHWE high 

PHWE mod. 

PHWE low 

AROS high 

AROS mod. 

AROS low 

 *

 *

UPPER KLAMATH

0 20 40 60 80 100

PHWE high 

PHWE mod. 

PHWE low 

AROS high 

AROS mod. 

AROS low 

UPPER SNAKE

Figure 52—Historical and current distribution of Armillaria root disease and laminated root rot disturbance vulnerability classes

expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the

standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.

Pathogen disturbance abbreviations are AROS = Armillaria root disease and PHWE = laminated root rot. Vulnerability class

codes are low, moderate, and high.
192

Historic

Current

0 20 40 60 80

HEAN-P high 

HEAN-P mod. 

HEAN-P low 

HEAN-S high 

HEAN-S mod. 

HEAN-S low 

 *

 *

BLUE MTNS.

0 20 40 60 80 100

HEAN-P high 

HEAN-P mod. 

HEAN-P low 

HEAN-S high 

HEAN-S mod. 

HEAN-S low 

 *

 *

 *

CENTRAL IDAHO MTNS.

0 20 40 60 80 100

HEAN-P high 

HEAN-P mod. 

HEAN-P low 

HEAN-S high 

HEAN-S mod. 

HEAN-S low 

 *

 *

 *

 *

COLUMBIA PLATEAU

0 20 40 60 80 100

HEAN-P high 

HEAN-P mod. 

HEAN-P low 

HEAN-S high 

HEAN-S mod. 

HEAN-S low 

LOWER CLARK FORK

0 20 40 60 80 100

HEAN-P high 

HEAN-P mod. 

HEAN-P low 

HEAN-S high 

HEAN-S mod. 

HEAN-S low 

 *

 *

 *

 *

N. CASCADES

0 20 40 60 80 100

HEAN-P high 

HEAN-P mod. 

HEAN-P low 

HEAN-S high 

HEAN-S mod. 

HEAN-S low 

 *

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

HEAN-P high 

HEAN-P mod. 

HEAN-P low 

HEAN-S high 

HEAN-S mod. 

HEAN-S low 

N. GREAT BASIN

0 20 40 60 80 100

HEAN-P high 

HEAN-P mod. 

HEAN-P low 

HEAN-S high 

HEAN-S mod. 

HEAN-S low 

OWYHEE UPLANDS
193

Historic

Current

0 20 40 60 80 100

HEAN-P high 

HEAN-P mod. 

HEAN-P low 

HEAN-S high 

HEAN-S mod. 

HEAN-S low 

 *

 *

SNAKE HEADWATERS

0 20 40 60 80 100

HEAN-P high 

HEAN-P mod. 

HEAN-P low 

HEAN-S high 

HEAN-S mod. 

HEAN-S low 

 *

S. CASCADES

0 20 40 60 80 100

HEAN-P high 

HEAN-P mod. 

HEAN-P low 

HEAN-S high 

HEAN-S mod. 

HEAN-S low 

 *

 *

 *

 *

UPPER CLARK FORK

0 20 40 60 80 100

HEAN-P high 

HEAN-P mod. 

HEAN-P low 

HEAN-S high 

HEAN-S mod. 

HEAN-S low 

 *

 *

UPPER KLAMATH

0 20 40 60 80 100

HEAN-P high 

HEAN-P mod. 

HEAN-P low 

HEAN-S high 

HEAN-S mod. 

HEAN-S low 

UPPER SNAKE

Figure 53—Historical and current distribution of S- and P-group annosum root disease disturbance vulnerability classes

expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the

standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.

Pathogen disturbance abbreviations are HEAN-S = S-group annosum root disease and HEAN-P = P-group annosum root disease. Vulnerability class codes are low, moderate, and high.
194

Historic

Current

0 20 40 60 80 100

SRBR high 

SRBR mod. 

SRBR low 

TRBR high 

TRBR mod. 

TRBR low 

 *

 *

 *

 *

BLUE MTNS.

0 20 40 60 80 100

SRBR high 

SRBR mod. 

SRBR low 

TRBR high 

TRBR mod. 

TRBR low 

 *

CENTRAL IDAHO MTNS.

0 20 40 60 80 100

SRBR high 

SRBR mod. 

SRBR low 

TRBR high 

TRBR mod. 

TRBR low 

 *

 *

COLUMBIA PLATEAU

0 20 40 60 80 100

SRBR high 

SRBR mod. 

SRBR low 

TRBR high 

TRBR mod. 

TRBR low 

 *

LOWER CLARK FORK

0 20 40 60 80 100

SRBR high 

SRBR mod. 

SRBR low 

TRBR high 

TRBR mod. 

TRBR low 

 *

 *

 *

 *

N. CASCADES

0 20 40 60 80 100

SRBR high 

SRBR mod. 

SRBR low 

TRBR high 

TRBR mod. 

TRBR low 

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

SRBR high 

SRBR mod. 

SRBR low 

TRBR high 

TRBR mod. 

TRBR low 

N. GREAT BASIN

0 20 40 60 80 100

SRBR high 

SRBR mod. 

SRBR low 

TRBR high 

TRBR mod. 

TRBR low 

OWYHEE UPLANDS
195

Historic

Current

0 20 40 60 80 100

SRBR high 

SRBR mod. 

SRBR low 

TRBR high 

TRBR mod. 

TRBR low 

 *

 *

SNAKE HEADWATERS

0 20 40 60 80 100

SRBR high 

SRBR mod. 

SRBR low 

TRBR high 

TRBR mod. 

TRBR low 

 *

S. CASCADES

0 20 40 60 80 100

SRBR high 

SRBR mod. 

SRBR low 

TRBR high 

TRBR mod. 

TRBR low 

UPPER CLARK FORK

0 20 40 60 80 100

SRBR high 

SRBR mod. 

SRBR low 

TRBR high 

TRBR mod. 

TRBR low 

 *

 *

UPPER KLAMATH

0 20 40 60 80 100

SRBR high 

SRBR mod. 

SRBR low 

TRBR high 

TRBR mod. 

TRBR low 

 *

UPPER SNAKE

Figure 54—Historical and current distribution of tomentosus and Schweinitzii root and butt rot disturbance vulnerability classes expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the

standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.

Pathogen disturbance abbreviations are TRBR = tomentosus root and butt rot and SRBR = Schweinitzii root and butt rot.

Vulnerability class codes are low, moderate, and high.
196

Insect disturbance vulnerabilities—

Defoliators—There were no statistically significant

changes in percentage of area or connectivity of

patches vulnerable to western spruce budworm

disturbance at this reporting scale (appendix 3).

Percentage of area in the high vulnerability class

rose from 49.4 to 51.1 percent (ns), and area in

the moderate vulnerability class declined from

18.9 to 16.9 percent (fig. 46).

Bark beetles—Percentage of area vulnerable to

western pine beetle (type 1) disturbance of mature

and old ponderosa pine remained relatively constant during the sample period, but connectivity

of vulnerable patches declined significantly owing

to the relatively limited area of the ponderosa

pine cover type. Patch density of the high vulnerability class rose from 1.6 to 2.8 patches per 

10 000 ha, and mean patch size remained unchanged. Mean patch size of the moderate vulnerability class declined from an average of 34.3 

to 20.1 ha.

Patch area vulnerable to the fir engraver disturbance increased during the sample period (fig.

49); percentage of area in the high vulnerability

class rose from 21.3 to 26.2 percent of the ERU,

and area in the moderate vulnerability class

declined by a corresponding amount (appendix 3). Connectivity of patches vulnerable to 

fir engraver disturbance increased; patch density

remained stable, and mean patch size rose from

156.7 to 254.6 ha. Enhanced connectivity of 

vulnerable patches was associated with increased

patch size and contiguity of subalpine fir patches

(appendix 2).

Pathogen disturbance vulnerabilities—

Dwarf mistletoes—Area and connectivity of patches vulnerable to western dwarf mistletoe disturbance declined during the sample period (fig. 51);

percentage of area fell from an average of 2.2 to

1.8 percent of the ERU, and mean patch size

declined from 17.2 to 11.4 ha (appendix 3).

Because no significant change in area of the 

ponderosa pine cover type was observed where

ponderosa pine was the principal cover species,

these results suggest that area of ponderosa pine

in mixed species cover types with multilayered

canopies declined during the sample period.

Root diseases—Connectivity of patches vulnerable to laminated root rot disturbance declined

(appendix 3); patch density in the high vulnerability class rose by 33 percent, from 14.5 to 19.3

patches per 10 000 ha, and mean patch size declined from 321.5 to 253.2 ha. Reduced connectivity of vulnerable patches was associated with

declining connectivity of host cover.

Area vulnerable to S-group annosum root disease

disturbance increased; percentage of area in the

high vulnerability class rose from an average of

36.2 to 38.9 percent of the ERU (fig. 53), and

area in the moderate vulnerability class declined

by a corresponding amount. Increase in vulnerable area was associated with expanding grand 

fir, Douglas-fir, subalpine fir-Engelmann spruce,

and western hemlock-western redcedar cover type

area (appendix 2) and increased area with visible

logging entry (table 27). In contrast, area and

connectivity of patches vulnerable to P-group

annosum root disease disturbance declined during

the sample period (fig. 53); percentage of area fell

from an average of 2.1 to 1.7 percent, and mean

patch size declined from 15.0 to 12.4 ha. As

noted earlier, because no significant change in

ponderosa pine-dominated cover was observed,

these results suggest that area of ponderosa pine

in mixed species cover types declined significantly

during the sample period.

Area and connectivity of patches vulnerable to

tomentosus root disease disturbance increased

(fig. 54). Percentage of area in the high vulnerability class increased by 18 percent, rising from an

average of 9.3 to 11.0 percent of the ERU, thereby indicating that area comprised of medium and

large Engelmann spruce increased during the

sample period. Patch density rose from 12.4 to

15.0 patches per 10 000 ha, and mean patch size

remained stable. 

Columbia Plateau ERU—Subbasins sampled

within the Columbia Plateau ERU (figs. 9, 10,

12, and 15) included the Lower Crooked (LCR),

Lower John Day (LJD), Lower Yakima (LYK),

Palouse (PLS), and Upper Yakima (UYK). Among

these subbasins, 38 historical and current subwatershed pairs were sampled.
197

Insect disturbance vulnerabilities—

Defoliators—Area vulnerable to western spruce

budworm disturbance increased during the sample period (fig. 46). Percentage of area in the high

vulnerability class increased by 29 percent, rising

from an average of 9.3 to 12.0 percent of the

ERU. In the Columbia Plateau, forests comprise

less than one-third of the area (appendix 2). In

the historical condition, 36 percent of the forested area was classified as high vulnerability area,

and in the current condition, 41 percent was classified as high vulnerability (appendix 3). Cover

type changes alone did not account for the

observed increase in vulnerability; increased 

vulnerability was associated with increased area 

of Douglas-fir cover in pure and mixed types

(appendix 2) and increased area of Douglas-fir

and grand fir in multilayered understories. 

Bark beetles—Area vulnerable to western pine beetle (type 1) disturbance of mature and old ponderosa pine declined (fig. 47), but the change was

not significant at P≤0.2. Percentage of area in the

high vulnerability class fell from an average of 4.6

to 2.9 percent of the ERU (ns). Connectivity of

area in the high vulnerability class declined significantly; mean patch size declined by 48 percent,

dropping from an average of 50.8 to 26.6 ha.

Area in the ponderosa pine cover type actually

increased during the sample period, rising from

19.2 to 21.4 percent, but area in old multistory

and old single-story structures declined (appendix

2). These results suggest that contiguity of patches

with medium and large ponderosa pine in mixed

species overstories declined (tables 20 and 21).

(Note that large tree structure was potentially

associated with all classified forest structures; see

also table 6.) Because total area in old forest structures declined by 1.1 percent (appendix 2), some

of the loss in connectivity of the high vulnerability class was associated with reduced abundance 

of scattered medium and large ponderosa pine in

structural classes other than old forest.

Area vulnerable to western pine beetle (type 2)

and mountain pine beetle (type 2) disturbance of

immature, high-density ponderosa pine increased

during the sample period (figs. 47 and 48). Percentage of area in the high vulnerability class rose

from an average of 14.9 to 17.1 percent of the

ERU, and area in the moderate vulnerability 

class rose from 9.8 to 11.8 percent of the ERU.

Increasing vulnerability was associated with

expanded area of ponderosa pine cover in young

and middle-aged structures (appendix 2).

Finally, area vulnerable to fir engraver disturbance

increased (fig. 49); percentage of area in the high

vulnerability class rose from 1.8 to 2.9 percent.

Area where grand fir was the principal cover

species actually declined by a small amount during the sample period (appendix 2), but area

where grand fir occurred in mixed species cover

types and as understory species cover increased 

as a probable result of fire exclusion and harvest

of seral species.

Pathogen disturbance vulnerabilities—

Root diseases—Area and connectivity of patches

vulnerable to S-group annosum root disease disturbance increased (fig. 53); percentage of area

climbed sharply, nearly sevenfold, rising from 

an average of 0.8 to 5.4 percent of the ERU. Area

in moderate and low vulnerability classes declined

significantly by a corresponding amount. Patch

density of high vulnerability areas rose from 1.3

to 2.2 patches per 10 000 ha, and mean patch

size increased more than eightfold from 15.6 to

132.1 ha. Increase in area of host cover types

alone did not account for the dramatic rise in 

vulnerable area. Our results indicated that area 

of grand fir and western hemlock in mixed species

cover types and occurring as understory species

increased during the sample period, as did area 

in these susceptible host types having visible logging entry.

Rusts—Area vulnerable to white pine blister rust

(type 1) disturbance of western white pine declined (fig. 55 and appendix 3); percentage of 

area in the high vulnerability class plummeted by

93 percent, declining from an average of 1.4 to

0.1 percent of the ERU. In similar fashion, mean

patch size declined from 45.6 to 4.3 ha, but the

change was not significant at P≤0.2. The observed

decline in high vulnerability area was likely the

result of more than eight decades of blister rust

mortality and selective harvest of western white

pine early in the 20th century. 
198

Historic

Current

0 20 40 60 80 100

WPBR2 high 

WPBR2 mod. 

WPBR2 low 

WPBR1 high 

WPBR1 mod. 

WPBR1 low 

 *

 *

BLUE MTNS.

0 20 40 60 80 100

WPBR2 high 

WPBR2 mod. 

WPBR2 low 

WPBR1 high 

WPBR1 mod. 

WPBR1 low 

CENTRAL IDAHO MTNS.

0 20 40 60 80 100

WPBR2 high 

WPBR2 mod. 

WPBR2 low 

WPBR1 high 

WPBR1 mod. 

WPBR1 low 

 *

 *

COLUMBIA PLATEAU

0 20 40 60 80 100

WPBR2 high 

WPBR2 mod. 

WPBR2 low 

WPBR1 high 

WPBR1 mod. 

WPBR1 low 

LOWER CLARK FORK

0 20 40 60 80 100

WPBR2 high 

WPBR2 mod. 

WPBR2 low 

WPBR1 high 

WPBR1 mod. 

WPBR1 low 

 *

 *

 *

N. CASCADES

0 20 40 60 80 100

WPBR2 high 

WPBR2 mod. 

WPBR2 low 

WPBR1 high 

WPBR1 mod. 

WPBR1 low 

 *

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

WPBR2 high 

WPBR2 mod. 

WPBR2 low 

WPBR1 high 

WPBR1 mod. 

WPBR1 low 

N. GREAT BASIN

0 20 40 60 80 100

WPBR2 high 

WPBR2 mod. 

WPBR2 low 

WPBR1 high 

WPBR1 mod. 

WPBR1 low 

OWYHEE UPLANDS
199

Historic

Current

0 20 40 60 80 100

WPBR2 high 

WPBR2 mod. 

WPBR2 low 

WPBR1 high 

WPBR1 mod. 

WPBR1 low 

 *

SNAKE HEADWATERS

0 20 40 60 80 100

WPBR2 high 

WPBR2 mod. 

WPBR2 low 

WPBR1 high 

WPBR1 mod. 

WPBR1 low 

 *

 *

S. CASCADES

0 20 40 60 80 100

WPBR2 high 

WPBR2 mod. 

WPBR2 low 

WPBR1 high 

WPBR1 mod. 

WPBR1 low 

 *

UPPER CLARK FORK

0 20 40 60 80 100

WPBR2 high 

WPBR2 mod. 

WPBR2 low 

WPBR1 high 

WPBR1 mod. 

WPBR1 low 

UPPER KLAMATH

0 20 40 60 80 100

WPBR2 high 

WPBR2 mod. 

WPBR2 low 

WPBR1 high 

WPBR1 mod. 

WPBR1 low 

 *

 *

UPPER SNAKE

Figure 55—Historical and current distribution of white pine blister rust type-1 and type-2 disturbance vulnerability classes

expressed as a percentage of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the

standard error of the mean estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions.

Pathogen disturbance abbreviations are WPBR1 = white pine blister rust (type 1) of western white and sugar pine and WPBR2

= white pine blister rust (type 2) of whitebark pine. Vulnerability class codes are low, moderate, and high.
200

Lower Clark Fork ERU—The Upper Coeur

d’Alene (UCD) was the only subbasin sampled

within the Lower Clark Fork ERU (fig. 7). Many

changes in area and connectivity of vulnerability

classes were observed, but few were significant at

P≤0.2 owing to the small sample size.

Insect disturbance vulnerabilities—

Defoliators—Area vulnerable to western spruce

budworm disturbance increased during the sample period, but the change was not significant 

at P≤0.2 (fig. 46); percentage of area in the high

vulnerability class rose from 56.8 to 65.0 percent

(ns). Further sampling and study are needed to

establish the trend.

Bark beetles—Area vulnerable to the mountain

pine beetle (type 1) disturbance of high density

lodgepole pine increased dramatically. Percentage

of area in the high vulnerability class rose more

than threefold from an average of 4.0 to 12.9 percent of the ERU (fig. 48). Area in the low vulnerability class declined from an average of 30.0 to

17.3 percent of the ERU, patch density rose 

nearly twofold from 28.8 to 49.4 patches per 

10 000 ha, and mean patch size fell from 150.1

to 36.4 ha. Our results indicated that total patch

area comprised of lodgepole pine in pure and

mixed compositions has changed little during the

sample period, but patches in the existing condition are comprised of larger and older host trees.

Area and connectivity of patches vulnerable to fir

engraver disturbance increased, but changes were

not significant at P≤0.2 (fig. 49). Percentage of

area in the high vulnerability class rose from an

average of 28.3 to 37.0 percent (ns), and mean

patch size increased from 129.7 to 171.8 ha (ns).

Further sampling and study are needed to establish the trend. 

Pathogen disturbance vulnerabilities—

Dwarf mistletoes—Area and connectivity of area

vulnerable to lodgepole pine dwarf mistletoe disturbance increased, but change in area was not

significant at P≤0.2 (fig. 51). Percentage of area in

the high vulnerability class rose more than tenfold

from an average of 0.2 to 2.6 percent of the ERU

(ns), and mean patch size increased more than

threefold from 9.1 to 31.2 ha. Further sampling

and study are needed to establish the trend.

Root diseases—Area vulnerable to Armillaria root

disease disturbance increased dramatically, but 

the change was not significant at P≤0.2 (fig. 52).

Percentage of area in the high vulnerability class

rose from 55.0 to 65.1 percent of the ERU (ns).

Further sampling is needed to establish the trend.

Northern Cascades ERU—Subbasins sampled

within the Northern Cascades ERU (figs. 5 and

9) included the Methow (MET), Wenatchee

(WEN), Naches (NAC), Upper Yakima (UYK),

and Lower Yakima (LYK). Among these subbasins, 48 historical and current subwatershed

pairs were sampled.

Insect disturbance vulnerabilities—

Bark beetles—Connectivity of patches vulnerable

to Douglas-fir beetle disturbance declined; patch

density rose from 6.2 to 8.2 patches per 10 000

ha, and mean patch size declined by 40 percent

from 149.9 to 89.2 ha (appendix 3). Connectivity

of patches in the moderate vulnerability class also

declined; patch density rose from 11.8 to 15.2

patches per 10 000 ha, and mean patch size declined from 376.5 to 274.8 ha. Percentage of area

in the low vulnerability class rose from 65.1 to

68.4 percent of the ERU (fig. 46). Overall, area

comprised of Douglas-fir cover increased, but

reduced area in the high vulnerability class was

the result of reduced patch area with medium and

large Douglas-fir in old forest and other structures

(tables 20 and 21).

Area and connectivity of area vulnerable to western pine beetle (type 1) disturbance of mature

and old ponderosa pine declined (fig. 47). Percentage of area in the high vulnerability class 

fell from an average of 3.7 to 1.8 percent of the

ERU, and mean patch size declined from 74.5 to

42.8 ha (appendix 3). Area and connectivity of

patches in the moderate vulnerability class also

declined; percentage of area fell from 11.8 to 8.9

percent, and mean patch size declined from 153.9

to 89.4 ha. Percentage of area in the low vulnerability class rose by a corresponding amount. The

observed decline in area of high vulnerability was

the result of significantly reduced area of ponderosa pine cover and reduced patch area with

medium and large ponderosa pine in old forest

and other structures (appendix 2).
201

Area and connectivity of area vulnerable to western pine beetle (type 2) and mountain pine beetle

(type 2) disturbance of immature, high density

ponderosa pine also declined (figs. 47 and 48).

Percentage of area in the high vulnerability class

fell from an average of 9.8 to 8.2 percent of the

ERU, and mean patch size declined from an average of 227.4 to 96.8 ha (appendix 3). Connectivity of patches in the moderate vulnerability class

also declined; patch density rose from 13.5 

to 17.4 patches per 10 000 ha, and mean patch

size declined from 631.7 to 369.6 ha. Decline in

area of high vulnerability was the result of significantly reduced area of ponderosa pine cover in

pure and mixed composition and young and 

middle-aged structures. 

Pathogen disturbance vulnerabilities—

Dwarf mistletoes—Area and connectivity of area

vulnerable to western (ponderosa pine) dwarf

mistletoe disturbance declined (fig. 51); percentage of area in the high vulnerability class fell from

5.6 to 3.9 percent of the ERU, patch density

remained unchanged, and mean patch size

declined by 51 percent from 87.0 to 42.5 ha

(appendix 3). Area and connectivity of area in 

the moderate vulnerability class also declined; 

percentage of area fell from 13.0 to 10.8 percent,

patch density rose from 7.1 to 9.2 patches per 

10 000 ha, and mean patch size declined by 

42 percent from 156.3 to 90.4 ha. The observed

decline in area of high vulnerability was the result

of significantly reduced area of ponderosa pine

cover and reduced patch area with medium and

large ponderosa pine in multilayered, pine-dominated structures. In many cases, ponderosa pine

overstories were absent in the current condition;

in others, pine-dominated understories gave way

to those dominated by shade-tolerant Douglas-fir

and grand fir.

Root diseases—Results of root disease analyses were

quite interesting in the Northern Cascades ERU.

Area and connectivity of patches vulnerable to

Armillaria root disease disturbance declined (fig.

52); percentage of area in the high vulnerability

class fell from 48.6 to 45.2 percent of the ERU,

patch density rose from 10.7 to 12.4 patches 

per 10 000 ha, and mean patch size declined by

17 percent from an average of 681.2 to 563.9 ha

(appendix 3). Rules for classifying patch vulnerability to root diseases (including root and butt

rots) rated patches with larger host trees as more

vulnerable to disturbance (that is, more vulnerable to change in structure and composition as a

consequence of disturbance) than those with

small host trees. The reason was simple: when

medium and large overstory host trees succumb

to root disease, canopy gaps develop, and patch

structure and composition are altered; when small

host trees are killed by root disease either in the

overstory or understory, there is little or no substantive alteration of structure or composition.

The observed decline in area of high vulnerability

to Armillaria root disease disturbance was the

result of declining area occupied by large host

trees, primarily Douglas-fir. Patches comprised of

hosts in the current vegetation condition will tend

to be less vulnerable to structural or compositional change until host species are large enough to

dominate patch structure and composition.

Area and connectivity of patches vulnerable to

laminated root rot disturbance declined similarly

(fig. 52); percentage of area in the high vulnerability class fell from an average of 41.7 to 39.2

percent of the ERU, patch density rose from 8.5

to 10.4 patches per 10 000 ha, and mean patch

size declined by 35 percent from an average of

837.9 to 541.1 ha (appendix 3). As noted above,

the observed decline in area of high vulnerability

to laminated root rot disturbance was the result 

of declining area occupied by large host trees, 

primarily Douglas-fir.

Area vulnerable to S-group annosum root disease

disturbance increased during the sample period

(fig. 53). Percentage of area in the high vulnerability class rose by 9 percent from an average of

29.6 to 32.2 percent of the ERU. The observed

increase in high vulnerability area was associated

with increased area and stature of grand fir and

Pacific silver fir cover (appendix 2) and increased

area with visible logging entry. Area and connectivity of patches vulnerable to P-group annosum

root disease disturbance declined (fig. 53); percentage of area in the high vulnerability class fell

by 21 percent from an average of 7.5 to 5.9 percent of the ERU, and mean patch size fell by 

34 percent from 114.1 to 74.9 ha. Area and 
202

connectivity of area in the moderate vulnerability

class also declined. The observed decline in area

of high vulnerability was the result of significantly

reduced area of the ponderosa pine cover type and

reduced patch area with medium and large ponderosa pine in single-layered and multilayered,

pine-dominated structures.

Area vulnerable to tomentosus root and butt rot

disturbance declined during the sample period

(fig. 54); percentage of area fell from an average

of 11.4 to 9.9 percent of the ERU. Decline in

vulnerable area was associated with the loss of

subalpine fir-Engelmann spruce cover and declining abundance of medium and large Engelmann

spruce. Similarly, area and connectivity of patches

vulnerable to Schweinitzii root and butt rot disturbance declined; percentage of area in the high

vulnerability class fell from an average of 61.2 to

57.2 percent of the ERU (fig. 54), patch density

rose from 5.9 to 7.6 patches per 10 000 ha, and

mean patch size dropped sharply by 32 percent

from 1855.9 to 1266.6 ha. The observed decline

in area of high vulnerability to Schweinitzii root

and butt rot disturbance was the result of declining area occupied by large host trees, primarily

Douglas-fir, ponderosa pine, and Engelmann

spruce. 

Rusts—Area and connectivity of patches vulnerable to white pine blister rust (type 1) disturbance

of sugar and western white pine (western white

pine in the Northern Cascades ERU) increased

(fig. 55); percentage of area in the high vulnerability class rose from 0.1 to 0.2 percent of the

ERU, and mean patch size increased from 2.2 to

6.7 ha. The slight but significant increase in area

in the high vulnerability class was likely the result

of management efforts by the Wenatchee and

Okanogan National Forests to outplant white

pine blister rust-resistant stock (personal observation of the senior author). Area and connectivity

of patches vulnerable to white pine blister rust

(type 2) disturbance of whitebark pine also

increased (fig. 55); percentage of area in the high

vulnerability class rose from an average of 0.4 to

0.9 percent of the ERU, patch density rose from

an average of 0.8 to 1.1 patches per 10 000 ha,

and mean patch size more than doubled, increasing from 11.5 to 24.5 ha (appendix 3). Increase

in high vulnerability area was associated with the

observed increase in percentage of area in the

whitebark pine-subalpine larch cover type (appendix 2).

Stem decays—Area vulnerable to rust-red stringy

rot gap disturbance increased during the sample

period (fig. 56). Percentage of area in the high

vulnerability class rose from an average of 0.6 to

1.1 percent of the ERU. The observed increase 

in high vulnerability area was associated with

increased area and stature of grand fir and Pacific

silver fir cover (appendix 2).

Northern Glaciated Mountains ERU—

Subbasins sampled within the Northern Glaciated

Mountains ERU (figs. 6 to 8) included the Lower

Flathead (LFH), Kettle (KET), Pend Oreille

(PEN), Sanpoil (SPO), Swan (SWN), and Yaak

(YAA). Among these subbasins, 41 historical and

current subwatershed pairs were sampled.

Insect disturbance vulnerabilities—

Defoliators—Area vulnerable to western spruce

budworm disturbance increased during the sample period (fig. 46). Percentage of area in the high

vulnerability class increased by 8 percent from

44.5 to 47.9 percent of the ERU. The observed

increase in high vulnerability area was associated

with increased area of grand fir and subalpine 

fir-Engelmann spruce cover (appendix 2). 

Connectivity of high vulnerability area declined;

patch density rose from 12.2 to 16.5 patches 

per 10 000 ha, and mean patch size declined by

64.4 ha from 806.8 ha (ns).

Bark beetles—Perhaps the most significant change

in area vulnerable to bark beetle disturbance was

associated with mountain pine beetle (type 1) disturbance of high density lodgepole pine. Percentage of area in the high vulnerability class rose by

23 percent from an average of 15.4 to 18.9 percent of the ERU (fig. 48). Patch density rose by

70 percent from an average of 9.3 to 15.8 patches

per 10 000 ha (appendix 3), and mean patch size

was unchanged. No significant change in area of

the lodgepole pine cover type was observed where

lodgepole pine was the principal cover species

(appendix 2), but our results suggested that 

current areas of lodgepole pine exhibit larger 

host size, poorer overstory crown differentiation,
203

higher total crown cover, and greater contiguity of

these characteristics than occurred in the historical condition. It appears that large areas became

synchronously more vulnerable to mountain pine

beetle (type 1) disturbance during the sample

period.

Area and connectivity of patches vulnerable to

spruce beetle disturbance increased (fig. 49); percentage of area in the high vulnerability class rose

from an average of 3.0 to 4.5 percent of the ERU,

patch density increased from 2.6 to 4.7 patches

per 10 000 ha, and mean patch size increased by

71 percent from 46.6 to 79.9 ha (appendix 3).

Increased area in high vulnerability patches was

associated with increased area and stature of

spruce in the subalpine fir-Engelmann spruce

cover type.

Pathogen disturbance vulnerabilities—

Dwarf mistletoes—Area and connectivity of patches vulnerable to western (ponderosa pine) dwarf

mistletoe disturbance declined (fig. 51); percentage of area in the high vulnerability class fell by

34 percent from an average of 3.8 to 2.5 percent

of the ERU area, patch density remained unchanged, and mean patch size declined by 72 

percent from an average of 57.1 to 16.0 ha

(appendix 3). The observed decline in area of

high vulnerability was the result of significantly

reduced area of ponderosa pine cover (appendix

2) and reduced patch area with medium and large

ponderosa pine in multilayered, pine-dominated

structures. In many patches, ponderosa pine overstories were absent in the current condition; in

others, pine-dominated understories gave way to

shade-tolerant Douglas-fir and grand fir.

Area vulnerable to western larch dwarf mistletoe

disturbance declined (fig. 50); percentage of area

in the high vulnerability class declined by 39 percent, falling from 6.9 to 4.2 percent, and mean

patch size declined from an average of 57.6 to

38.5 ha (appendix 3). Area and connectivity of

patches in the moderate vulnerability class also

declined. The observed decline in area of high

vulnerability was the result of significantly

reduced area of western larch cover, and reduced

patch area with medium and large western larch

in multilayered, larch-dominated structures

(appendix 2). In many patches, western larch

overstories were absent in the current condition;

in others, larch understories gave way to shadetolerant Douglas-fir, grand fir, subalpine fir, western hemlock, and western redcedar.

Root diseases—Area vulnerable to Armillaria root

disease disturbance increased (fig. 52) and connectivity of vulnerable patches declined (appendix

3). Percentage of area in the high vulnerability

class rose from an average of 37.3 to 40.7 percent

of the ERU, patch density rose from an average 

of 14.1 to 20.8 patches per 10 000 ha, and mean

patch size remained relatively stable. The observed

increase in area of high vulnerability was the

result of significantly increased area of grand fir

and subalpine fir-Engelmann spruce cover types.

Area and connectivity of patches vulnerable to 

S-group annosum root disease disturbance

increased (fig. 53); percentage of area in the high

vulnerability class rose by 34 percent from 20.0 

to 26.8 percent of the ERU, patch density more

than doubled from an average of 9.3 to 20.5

patches per 10 000 ha from 9.3 patches, and

mean patch size was unchanged. The observed

increase in area of high vulnerability was the

result of increased area of grand fir, subalpine firEngelmann spruce, and western hemlock-western

redcedar cover (appendix 2); increased patch area

with understories comprised of shade-tolerant

Douglas-fir, grand fir, subalpine fir, and western

hemlock; and increased area with visible logging

entry.

Area and connectivity of area vulnerable to

tomentosus root and butt rot disturbance also

increased (fig. 54); percentage of area in the high

vulnerability class rose from 7.1 to 9.0 percent,

patch density rose from 5.9 to 10.8 patches per

10 000 ha (appendix 3), and mean patch size was

unchanged. The observed increase in area of high

vulnerability was the result of increased area of

the subalpine fir-Engelmann spruce cover type

with medium and large Engelmann spruce.

Rusts—Area and connectivity of patches vulnerable to white pine blister rust (type 1) disturbance

of sugar and western white pine (western white

pine in the Northern Glaciated Mountains) declined significantly (fig. 55); percentage of area 
204

Historic

Current

0 20 40 60 80 100

RRSR high 

RRSR mod. 

RRSR low 

BLUE MTNS.

0 20 40 60 80 100

RRSR high 

RRSR mod. 

RRSR low 

 *

 *

CENTRAL IDAHO MTNS.

0 20 40 60 80 100

RRSR high 

RRSR mod. 

RRSR low 

 *

 *

 *

COLUMBIA PLATEAU

0 20 40 60 80

RRSR high 

RRSR mod. 

RRSR low 

LOWER CLARK FORK

0 20 40 60 80

RRSR high 

RRSR mod. 

RRSR low 

 *

N. CASCADES

0 20 40 60 80 100

RRSR high 

RRSR mod. 

RRSR low 

 *

 *

 *

N. GLACIATED MTNS.

0 20 40 60 80 100

RRSR high 

RRSR mod. 

RRSR low 

N. GREAT BASIN

0 20 40 60 80 100

RRSR high 

RRSR mod. 

RRSR low 

OWYHEE UPLANDS
205

Historic

Current

0 20 40 60 80 100

RRSR high 

RRSR mod. 

RRSR low 

SNAKE HEADWATERS

0 20 40 60 80

RRSR high 

RRSR mod. 

RRSR low 

S. CASCADES

0 20 40 60 80 100

RRSR high 

RRSR mod. 

RRSR low 

 *

 *

UPPER CLARK FORK

0 20 40 60 80 100

RRSR high 

RRSR mod. 

RRSR low 

UPPER KLAMATH

0 20 40 60 80 100

RRSR high 

RRSR mod. 

RRSR low 

UPPER SNAKE

Figure 56—Historical and current distribution of rust-red stringy rot disturbance vulnerability classes expressed as a percentage

of total area on all ownerships in ERUs of the interior Columbia River basin. Error bars indicate the standard error of the mean

estimate. Asterisks indicate a significant (P≤0.2) difference between historical and current conditions. RRSR = rust-red stringy

rot. Vulnerability class codes are low, moderate, and high.
206

in the high vulnerability class fell by 84 percent

from an average of 1.9 to 0.3 percent of the ERU.

Mean patch size declined by the same proportion,

falling from an average of 26.3 to 4.2 ha (appendix 3). The observed decline in high vulnerability

area was likely the result of more than eight decades of blister rust mortality and early selective

harvest of western white pine.

Stem decays—Area and connectivity of area vulnerable to rust-red stringy rot disturbance increased slightly; percentage of area in the high

vulnerability class rose from an average of 0 to 

0.2 percent of the ERU (fig. 56 and appendix 3).

The observed increase in area of high vulnerability was the result of increased area of grand fir and

subalpine fir-Engelmann spruce cover and increased patch area with understories comprised 

of shade-tolerant grand fir and subalpine fir.

Northern Great Basin ERU—The Donner

und Blitzen (DUB) is the only subbasin sampled

within the Northern Great Basin ERU (fig. 16);

four historical and current subwatershed pairs

were sampled. Forests of the ERU represented a

minor area and were comprised of aspen, cottonwood, and juniper. Hosts of the insects and

pathogens modeled were not present in the ERU. 

Owyhee Uplands ERU—Subbasins sampled

within the Owyhee Uplands ERU (figs. 21 and

22) included the Big Wood (BWD), Crooked

Rattlesnake (CRT), and Upper Owyhee (UOW).

Among these subbasins, 21 historical and current

subwatershed pairs were sampled. Forests of the

ERU represented a minor area and were comprised chiefly of aspen and cottonwood. Woodland cover was dominated by juniper. With the

exception of juniper, which is host to P-group

annosum root disease, hosts of the insects and

pathogens modeled were not present in the ERU.

Snake Headwaters ERU—Subbasins sampled

within the Snake Headwaters ERU (fig. 19)

included the Lower Henry’s (LHE), Palisades

(PSD), and Snake Headwaters (SHW). Among

these subbasins, 15 historical and current subwatershed pairs were sampled.

Insect disturbance vulnerabilities—

Defoliators—Area and connectivity of patches 

vulnerable to western spruce budworm disturbance increased during the sample period (fig.

46). Percentage of area in the high vulnerability

class rose from an average of 45.0 to 51.8 percent

of the ERU area, patch density remained unchanged, and mean patch size increased by 37

percent from an average of 333.1 to 455.5 ha

(appendix 3). The observed increase in high vulnerability area was associated with dramatically

increased area of subalpine fir-Engelmann spruce

cover in multilayered structural arrangements

(tables 23 and 24 and appendix 2).

Bark beetles—Area and connectivity of patches

vulnerable to Douglas-fir beetle disturbance increased during the sample period. Percentage of

area in the high vulnerability class increased by 

86 percent from an average of 2.1 to 3.9 percent

of the ERU (fig. 46), patch density increased from

5.1 to 7.1 patches per 10 000 ha, and mean patch

size increased by 80 percent from an average of

17.5 to 31.6 ha (appendix 3). Because total area

in old forest structures declined from 5.2 to 3.1

percent of the ERU (appendix 2), most of the

increased area in the high vulnerability class was

likely associated with increased abundance of

medium and large Douglas-fir in structural classes

other than old forest.

The most significant change in area vulnerable 

to bark beetle disturbance was associated with

mountain pine beetle (type 1) of high density

lodgepole pine. Percentage of area in the high vulnerability class fell by 16 percent from an average

of 34.6 to 29.2 percent of the ERU (fig. 48).

Percentage of area in the moderate vulnerability

class rose by a corresponding amount. Area of 

the lodgepole pine cover type declined during 

the sample period from 15.6 to 11.3 percent of

the ERU. These results suggest that area of polesized and larger lodgepole pine in both pure and

mixed compositions declined during the sample

period, perhaps as a consequence of historical

mountain pine beetle disturbance.
207

Connectivity of patches vulnerable to fir engraver

disturbance declined (fig. 49); patch density increased from an average of 10.8 to 18.1 patches

per 10 000 ha, and mean patch size declined by

38 percent from an average of 211.3 to 131.9 ha

(appendix 3). Percentage of area highly vulnerable

to fir engraver disturbance declined from an average of 19.3 to 16.1 percent of the ERU, but the

change was not significant at this reporting scale.

Area vulnerable to spruce beetle disturbance

declined significantly (fig. 49); percentage of area

in the high vulnerability class fell from 8.3 to 

7.6 percent of the ERU. Percentage of area in the

moderate vulnerability class fell from 39.2 to 35.3

percent. Area of subalpine fir-Engelmann spruce

cover increased by 30 percent during the sample

period from an average of 24.3 to 31.4 percent of

the ERU area. These results suggest that area of

medium and large Engelmann spruce in mixed

compositions declined during the sample period.

Pathogen disturbance vulnerabilities—

Dwarf mistletoes—Area and connectivity of patches vulnerable to Douglas-fir dwarf mistletoe disturbance increased (fig. 50). Percentage of area

rose from 4.1 to 6.4 percent of the ERU, representing a 56-percent increase from the historical

condition, and mean patch size sharply increased

more than twofold from 19.2 to 49.6 ha (appendix 3). Increased area in the high vulnerability

class was associated with expanded area of

Douglas-fir in mixed species compositions,

increased canopy layering, and contiguity of host

patches. Area and connectivity of patches vulnerable to lodgepole pine dwarf mistletoe declined

(fig. 51). Percentage of area in the high vulnerability class fell sharply by 32 percent from an

average of 30.8 to 20.9 percent of the ERU, and

mean patch size declined from 274.3 to 186.6 ha

(appendix 3). Area in the low and moderate vulnerability classes increased by a corresponding

amount. Area of lodgepole pine cover declined

during the sample period, but not enough to

account for the observed decline in high vulnerability area. Our results indicated that area in

lodgepole pine occurring in pure and mixed compositions and in multilayered structures declined

significantly during the sample period. 

Root diseases—Area and connectivity of patches

vulnerable to Armillaria root disease disturbance

increased significantly (fig. 52); percentage of area

increased by 54 percent from an average of 20.4

to 31.5 percent of the ERU area, and mean patch

size nearly doubled from 106.6 to 205.4 ha

(appendix 3). Increased area in the high vulnerability class was associated with expanded area of

subalpine fir and Douglas-fir in pure and mixed

species compositions, increased crown cover of

host species, and increased contiguity of host

patches. Area and connectivity of patches vulnerable to laminated root rot disturbance also

increased; percentage of area rose from 10.9 to

12.8 percent of the ERU, and mean patch size

increased from an average of 71.4 to 100.8 ha.

Area and connectivity of patches vulnerable to 

S-group annosum root disease disturbance increased (fig. 53). Percentage of area rose sharply

by 39 percent from an average of 22.0 to 30.6

percent of the ERU area, and mean patch size

increased from an average of 141.1 to 204.0 ha.

Area of the low and moderate vulnerability class

changed by a compensating amount. Increased

area in the high vulnerability class was associated

with expanded area of subalpine fir in pure and

mixed species compositions, increased crown

cover of host species, increased contiguity of host

patches, and increased area with visible logging

entry.

Southern Cascades ERU—Subbasins sampled

within the Southern Cascades ERU (fig. 15)

included the Little Deschutes (LDS), and Upper

Deschutes (UDS). Within these subbasins, 16

historical and current subwatershed pairs were

sampled.

Insect disturbance vulnerabilities—

Defoliators—Area vulnerable to western spruce

budworm disturbance increased; percentage of

area in the high vulnerability class increased by 

22 percent from an average of 10.1 to 12.3 percent of the ERU (fig. 46). Connectivity declined

significantly in all vulnerability classes (appendix

3), indicating that highly vulnerable areas were

fewer and larger historically, but today are more

numerous and interspersed.
208

Bark beetles—Area vulnerable to Douglas-fir beetle disturbance declined (fig. 46); percentage of

area fell by 94 percent from an average of 1.8 to

0.1 percent of the ERU. Decline in high vulnerability area was associated with reduced area and

connectivity of patches having large Douglas-fir

in structures other than old forest (table 20).

The most significant change in area vulnerable 

to bark beetle disturbance was associated with

mountain pine beetle (type 1) of high density

lodgepole pine. Percentage of area in the high 

vulnerability class fell from an average of 29.0 

to 24.9 percent of the ERU (ns); percentage of

area in the moderate vulnerability class rose from

34.9 to 39.5 percent (fig. 48). Area of the lodgepole pine cover type actually increased slightly

during the sample period from 19.4 to 20.6 percent, but the change was not significant at P≤0.2.

Our results suggest that area of lodgepole pine in

historically mixed compositions declined during

the sample period as a result of well-documented

mountain pine beetle outbreaks in central Oregon

(Mitchell 1987, Mitchell and Preisler 1991, and

references therein) and fire exclusion. 

Pathogen disturbance vulnerabilities—

Dwarf mistletoes—Area and connectivity of patches vulnerable to Douglas-fir dwarf mistletoe disturbance declined (fig. 50); percentage of area in

the high vulnerability class declined by 78 percent, from an average of 2.3 to 0.5 percent of the

ERU, and mean patch size declined by a similar

proportion from an average of 95.1 to 24.1 ha

(appendix 3). The observed decline in area of

high vulnerability was the result of significantly

reduced patch area and contiguity with medium

and large Douglas-fir in multilayered structures.

Root diseases—Area vulnerable to Armillaria root

disease disturbance increased (fig. 52). Percentage

of area rose 17 percent from an average of 10.9 

to 12.8 percent of the ERU, patch density

increased from an average of 3.5 to 6.1 patches

per 10 000 ha, and mean patch size declined from

230.0 to 171.4 ha (ns). Area vulnerable to laminated root rot disturbance also increased (fig. 52);

percentage of area rose by 14 percent from an

average of 31.1 to 35.4 percent of the ERU.

Increased area in Armillaria root disease and 

laminated root rot high vulnerability classes was

associated with expanded area of subalpine fir,

grand fir, and Douglas-fir in mixed species compositions, expanded area of shade-tolerant understories, and increased crown cover of host species

(table 24 and appendix 2).

Area and connectivity of patches vulnerable to 

P-group annosum root disease disturbance increased (fig. 53). Percentage of area rose 70 percent from an average of 13.8 to 23.4 percent of

the ERU area, patch density increased from 3.6 

to 5.8 patches per 10 000 ha, and mean patch

size increased by 51 percent from 541.6 to 

816.2 ha (ns). Increased area in the high vulnerability class was associated with regrowth of

ponderosa pine in pure and mixed species compositions, increased crown cover of host species, and

increased contiguity of host patches.

Upper Clark Fork ERU—Subbasins sampled

within the Upper Clark Fork ERU (figs. 8 and

11) included the Blackfoot (BFM), Bitterroot

(BTR), and Flint Rock (FLR). Among these subbasins, 32 historical and current subwatershed

pairs were sampled.

Insect disturbance vulnerabilities—

Bark beetles—Area and connectivity of patches

vulnerable to Douglas-fir beetle disturbance

declined during the sample period. Percentage of

area in the high vulnerability class fell by 40 percent from an average of 8.0 to 4.8 percent of 

the ERU (fig. 46), patch density increased from

5.4 to 10.0 patches per 10 000 ha, and mean

patch size declined by 61 percent from 114.6 to

44.4 ha. Loss of area in the high vulnerability

class was the result of reduced crown cover of

large and medium Douglas-fir across all forest

structural classes.

Another significant change in area vulnerable to

bark beetle disturbance was associated with western pine beetle (type 1) disturbance of mature

and old ponderosa pine. Percentage of area in 

the high vulnerability class declined sharply by 

83 percent from an average of 2.9 to 0.5 percent

of the ERU (fig. 47). Area of ponderosa pine

cover decreased from 12.3 to 9.5 percent of the

ERU (appendix 2). Loss of high vulnerability area

was primarily associated with reduced area in the

ponderosa pine cover type and reduced crown

cover of medium and large ponderosa pine across

all forest structural classes. 
209

Area vulnerable to western pine beetle (type 2)

and mountain pine beetle (type 2) disturbance 

of immature, high-density ponderosa pine also

declined during the sample period (figs. 47 and

48). Percentage of area in the high vulnerability

class fell from 9.9 to 8.1 percent, an 18-percent

loss of area during the sample period. Loss of high

vulnerability area was associated primarily with

reduced area in the ponderosa pine cover type and

reduced area of stem-exclusion, understory reinitiation, and young multistory structures with ponderosa pine in pure or mixed compositions.

Area and connectivity of patches vulnerable to fir

engraver disturbance increased during the sample

period (fig. 49); percentage of area in the high

vulnerability class rose by 24 percent from an

average of 7.8 to 9.7 percent of the ERU, patch

density increased from 6.4 to 8.7 patches per 

10 000 ha, and mean patch size increased from

88.0 to 111.0 ha (ns). High vulnerability area

increased as consequence of increased area in the

subalpine fir-Engelmann spruce cover type in all

forest structural classes but stand initiation.

Pathogen disturbance vulnerabilities—

Dwarf mistletoes—Area and connectivity of patches vulnerable to the Douglas-fir, ponderosa pine,

and western larch dwarf mistletoes disturbance

declined during the sample period (figs. 50 and

51). Percentage of area in the Douglas-fir dwarf

mistletoe high vulnerability class fell by 19 percent from an average of 16.2 to 13.2 percent of

the ERU (fig. 50), patch density increased 25 percent from an average of 12.3 to 15.4 patches per

10 000 ha, and mean patch size declined by 

50 percent from an average of 154.0 to 75.1 ha

(appendix 3). The observed decline in area of

high vulnerability was the result of significantly

reduced patch area and contiguity with medium

and large Douglas-fir in multilayered structures.

Area and connectivity of area vulnerable to western (ponderosa pine) dwarf mistletoe disturbance

also declined (fig. 51); percentage of area in the

high vulnerability class fell by 54 percent from 

an average of 5.0 to 2.3 percent of the ERU, and

mean patch size declined 59 percent from an

average of 50.2 to 20.4 ha. The observed decline

in area of high vulnerability was the result of significantly reduced patch area and contiguity with

medium and large ponderosa pine in multilayered

structures. Area and connectivity of patches vulnerable to western larch dwarf mistletoe disturbance followed a similar pattern (fig. 50).

Root diseases—Area and connectivity of patches

vulnerable to P-group annosum root disease disturbance declined (fig. 53); percentage of area 

in the high vulnerability class fell from 5.4 to 

4.0 percent of the ERU, patch density increased

from 3.3 to 4.5 patches per 10 000 ha, and mean

patch size declined from an average of 51.8 to

39.4 ha (ns). The observed decline in area of high

vulnerability was the result of reduced patch area

and contiguity with medium and large ponderosa

pine.

Upper Klamath ERU—Subbasins sampled

within the Upper Klamath ERU (fig. 20) included the Lost (LST) and Upper Klamath Lake

(UKL). Among these subbasins, 12 historical and

current subwatershed pairs were sampled.

Insect disturbance vulnerabilities—

Bark beetles—Area and connectivity of patches

vulnerable to western pine beetle (type 1) disturbance of mature and old ponderosa pine declined,

but only change in connectivity was significant

(fig. 47). Percentage of area in the high vulnerability class fell from an average of 5.7 to 4.5 percent of the ERU, patch density increased from

3.5 to 4.9 patches per 10 000 ha, and mean patch

size declined from 67.6 to 51.1 ha (ns). Decline

in connectivity of high vulnerability patches was

the result of significantly reduced area of ponderosa pine cover and reduced patch area with

medium and large ponderosa pine, especially in

old single-story forest structures (tables 20 and

21). 

Area and connectivity of patches vulnerable to fir

engraver disturbance increased during the sample

period; percentage of area in the high vulnerability class rose from an average of 17.1 to 18.0 percent of the ERU (fig. 49), patch density declined

from 3.7 to 2.0 patches per 10 000 ha (appendix

3), and mean patch size rose from 586.7 to 700.1

ha (ns). High vulnerability area increased as consequence of expanded area in the grand fir-white

fir and Shasta red fir cover types.
210

Pathogen disturbance vulnerabilities—

Root diseases—Area vulnerable to Schweinitzii 

root and butt rot disturbance declined sharply 

by 32 percent, falling from an average of 26.4 to

17.9 percent of the ERU (fig. 54). Decline in area

of high vulnerability to Schweinitzii root and butt

rot disturbance was the result of declining area

occupied by medium and large host trees, primarily Douglas-fir and ponderosa pine in old-forest

single-story and other forest structures (tables 20

and 21 and appendix 2).

Upper Snake ERU—Subbasins sampled within

the Upper Snake ERU (figs. 18, 19, and 22)

included the Lower Henry’s (LHE), Lake Walcott

(LWC), and Medicine Lodge (MDL). Among

these subbasins, 15 historical and current subwatershed pairs were sampled. Less than 5 percent

of the area of the ERU is comprised of forest

cover types. Forest settings are cold and dry,

occurring in upper montane and subalpine settings. Two significant vulnerability changes were

associated with increased area of Douglas-fir.

Insect disturbance vulnerabilities—

Defoliators—Area and connectivity of patches vulnerable to western spruce budworm disturbance

increased (fig. 46). Percentage of area in the high

vulnerability class rose from 1.6 to 2.1 percent,

representing a 31-percent increase from the historical condition. Patch density declined from 

1.1 to 0.5 patch per 10 000 ha, and mean patch

size increased threefold from an average of 32.4 

to 95.4 ha (appendix 3).

Pathogen disturbance vulnerabilities—

Dwarf mistletoes—Area and connectivity of patches vulnerable to Douglas-fir dwarf mistletoe increased but only the change in connectivity was

significant (fig. 50). Percentage of area in the high

vulnerability class rose from 0.6 to 1.5 percent of

the ERU (ns), patch density declined from 1.8 

to 1.1 patches per 10 000 ha, and mean patch

size more than tripled from an average of 5.3 to

18.8 ha, but the increase was not statistically significant at this scale. 

Root diseases—Area and connectivity of patches

vulnerable to Armillaria root disease increased, 

but only change in connectivity was statistically

significant (fig. 52). Patch density declined from

2.1 to 1.1 patches per 10 000 ha, and mean patch

size more than doubled from 9.2 to 21.0 ha (ns).

Connectivity of patches vulnerable to S-group

annosum root disease increased similarly (appendix 3); patch density declined from 2.3 to 0.9

patch per 10 000 ha, and mean patch size tripled

from 10.2 to 31.7 ha (ns).

Area and connectivity of patches vulnerable to

Schweinitzii root and butt rot disturbance increased. Percentage of area in the high vulnerability class rose from an average of 1.5 to 2.1 percent

(fig. 54), and mean patch size jumped from 20.4

to 57.8 ha (appendix 3). Area in the Douglas-fir

cover type increased most significantly in stemexclusion open canopy and young multistory

structures.
211

Discussion

Detecting Ecosystem Change

To detect significant vegetation change of forest

or rangeland ecosystems, vegetation attributes

must change similarly across sampled subwatersheds of a statistical pooling stratum. Despite 

our efforts to sample large landscapes to minimize

area bias in landscape metrics and a sampling

intensity of at least 15 percent of subbasin area,

our sample size was still relatively small given the

geographic extent and spatial heterogeneity of

subbasins within ERUs. Even though we detected

many significant changes at the ERU scale, we

learned that likelihood was high of falsely accepting that no difference exists between historical

and current conditions of some attributes of

ERUs. We suggest that much greater change has

occurred than we were able to detect at the scale

of the ERU, and that the change analysis will be

more potent and revealing where subwatersheds

of similar climate, biophysical environment, and

potential vegetation conditions are grouped for

analysis.

Ecological reporting units were developed by the

Science Team in response to an executive decision

to summarize results of all broad-scale ecological,

social, and economic assessments of the project by

province-scale units. That decision also dictated

that results of midscale analysis would be summarized by ERU rather than by our initial sample

strata. Summarization by ERUs enabled comparison of results between broadscale (Hann and others 1997) and midscale landscape assessments, but

it also pooled tremendous environmental variation and redistributed some of the sampled subwatersheds in a less than optimal manner.

Throughout the discussion, we suggest likely

causes of change based on our best interpretation

of the empirical evidence, but alternative explanations are possible for the changes we detected,

and these are worthy of further exploration. Some

changes we observed may be the result of random

chance, climate change, environmental, climate,

disturbance stochasticity, or interactions among a

variety of disturbance and successional processes.

Our remotely sensed current conditions were

fixed reasonably well in time within sampled subbasins, but historical vegetation conditions, which

provided the basis for change detection, were variable among subwatersheds, even within subbasins.

On balance, we believe that a variable historical

starting point was more desirable that a single 

historical starting point, because it gave us the

potential to observe greater variability in historical

vegetation attributes and patterns stemming from

climatic, environmental, and disturbance stochasticity, thereby strengthening our estimation of

ecologically significant change. Still, historical

fires, insect outbreaks, logging activities, wild

ungulate and domestic livestock grazing, other

disturbance factors, and differences in landscape

patterns of biophysical environments created

widely differing patterns of vegetation structure

and composition. Such differences in historical

conditions obscured our ability to detect some

changes at the ERU scale and even at smaller spatial scales, such as the subbasin. Differences associated with biophysical environmental conditions,

and to some extent management history, could be

minimized with regionalization—a multivariate

classification and environmental mapping procedure we will present below (see “Ecological

Regionalization”). 
212

Variation in historical conditions was the result 

of many factors. Perhaps greatest among them

was high variability in the variety and intensity 

of historical management activities. Within ERUs,

some entire historical subwatersheds were unlogged wilderness or unburned or burned wilderness, and others had been intensively managed. 

In landscape-scale studies such as this one (see

also Lehmkuhl and others 1994), amount, timing,

and kind of management activity are difficult if

not impossible factors to account for or control.

We expected to observe large differences in the

rate and type of change between subwatersheds

managed primarily for wilderness and those managed for multiple resource objectives. But it is

important not to carry the comparison too far.

Throughout the basin, most wilderness watersheds occur in upper montane and subalpine

environmental settings, and watersheds managed

for multiple uses typically occur in low and middle montane settings. Fundamental differences in

dominant potential vegetation types, disturbance

and climatic regimes, and other biophysical characteristics are enormous, as are differences in

response to management activities.

Throughout the basin, fire suppression, fire exclusion, and timber harvest of early seral species had

the effect of dramatically advancing forest succession on a collapsed time scale, in both species

composition and structural attributes. But in 

the current condition, other typical and essential

attributes of late seral forests often are absent,

including large, pathologically old live trees,

native epiphytic and hypogeous flora, large standing dead and down woody structures, and native

understory shrub and herbaceous communities.

As seen in wilderness and roadless areas, fire

exclusion alone produced a similar effect on succession, but it occurred over a longer time frame;

that is, the temporal scale was not collapsed. Fire

exclusion affected change by removing a disturbance agent that normally reset one or more ecosystem components episodically; for example, in

dry ponderosa pine ecosystems, exclusion of fire

precipitated accumulation of high tree densities

and woody residue volumes that were absent 

or rare under native fire regimes. At a landscape

scale, fire exclusion enabled the accumulation of

mid- and late-seral forests habitable by the northern spotted owl (Strix occidentalis), which is now

apparent east of the crest of the Cascades (Everett

and others 1997). Areas once dominated by early

seral species, such as ponderosa pine, and frequented by surface fires are now dominated by

grand fir and dwarf mistletoe-infested Douglas-fir

and are infrequently visited by stand-replacing

fires.

Effects of fire exclusion, although more subtle

than those produced by timber harvesting, differed substantially among sampled historical 

subwatersheds of an ERU. Reasons for this were

fairly obvious: fire regimes differ quite predictably

by PVT, PVTs differ somewhat predictably with

biophysical environmental setting, and subwatershed patterns of biophysical environments and

potential vegetation differ greatly. Exclusion of

fire for six to eight decades in settings historically

visited by frequent surface fires (every 0 to 25

years) would transform nonlethal surface fire

regimes to lethal crown fire regimes. But exclusion of fire for a similar period in settings historically visited by infrequent crown fires at intervals

averaging 150 to 300 years would have, by comparison, an as yet negligible effect on fire regime.

Other potential sources of variation included differences in quality and photo scale between historical and current aerial photographic coverages,

differences in quality and consistency of interpretations among photointerpreters, and differing

period length among sampled subwatersheds

within an ERU (see table 3). Quality control steps

were taken to minimize these sources of variation,

but the latter contributed nonetheless. Lack of

significant difference for some variables between

historical and current subwatershed conditions

also could be related to high inherent natural 

variability within and among subwatersheds.

Observations of significant change, or its lack, 

in the period between our historical and current

samples were not and should not be interpreted 

as effects from a pristine pre-European settlement

initial condition. We assumed in this study that

considerable change in forest and range vegetation

structure and composition had already taken 

place throughout the 58-million-hectare basin
213

assessment area before the time of our historical

starting point sample (Anderson and others 

1987; Antos 1977; Antos and Habeck 1981;

Arno 1976, 1980; Arno and Davis 1980; Arno

and Peterson 1983; Barrett and Arno 1982;

Barrett and others 1991; Bevins and Barney 1980;

Bork 1985; Christensen 1985, 1988; Cooper

1926, 1961a, 1961b; Daubenmire 1968;

Daubenmire and Daubenmire 1968; Davis 

and others 1980; Dickman and Cook 1989;

Fahnestock 1976; Finch 1984; Franklin and 

others 1971; Galbraith and Anderson 1991; 

Gara and others 1985; Geiszler and others 1980;

Gruell and others 1982; Hall 1976; Kauffman

1990; Keen 1937; Knudsen 1980; Martin and

others 1976; McNeil and Zobel 1980; Morris

1934a, 1934b; Nordin 1958; Oliver 1981; 

Oliver and Larson 1990; Pyne 1982; Savage 

and Swetnam 1990; Soeriaatmadja 1966; Stuart

and others 1989; Vale 1975; Weaver 1959, 1961;

Wischnofske and Anderson 1983; Wright and

Klemmedson 1965; Young and Evans 1981;

Young and others 1987). Rates, magnitudes, 

and locations of older historical changes are poorly known today and will continue to be poorly

understood in most areas of the basin. The historical photographs we used simply represented the

oldest photographic coverages of interpretable

quality and of continuous subwatershed coverage

available from the Forest Service, Bureau of Land

Management, or National Archives or held in 

private ownership. In this manner, we provide

previously unavailable quantitative estimates of

direction, rate, and partial magnitude of changes.

Near the start of the 20th century, the Forest

Service and Bureau of Land Management inherited highly altered forest and range ecosystems.

Grazing had radically changed rangeland vegetation structure and composition and forest understories, and forest burning by miners and sheep

herders was a relatively common occurrence

(Robbins and Wolf 1994, Wissmar 1994a, Woods

and Horstman 1996). Extensive logging on

Federal forest lands was uncommon in most areas

of the basin until after World War II. Throughout

the five decades of management and resource

extraction that followed, these ecosystems were

further altered, disturbed, and reconfigured.

Whether current conditions of any subwatershed

in our sample are nearly natural considering the

climatic regime, biophysical environmental conditions, and inherent disturbance regimes is as yet

unknown to us. Information we provide on the

partial magnitude and direction of change during

a relatively long period of comparable climate and

across a large geographic area contributes valuable

insights into rates of change that can be expected

both temporally and spatially. It also provides a

framework from which management alternatives

can be developed, tested, and monitored.

Vegetation Composition 

and Structure

Physiognomic types—Many predicted changes

in vegetative structure and composition of basin

forests and ranges associated with past management activities were largely borne out by our

analysis. Causal connections, however, were difficult to establish because the timing, duration, and

intensity of various management activities were

not directly measured; it also was not possible to

evaluate correlations between effects and potential

causative factors. Increased forest cover in the

Blue Mountains, Columbia Plateau, Southern

Cascades, and Upper Snake ERUs (table 29 and

appendix 2) suggested that effective fire exclusion

resulted in forest establishment on areas that were

previously bare ground or shrubland, or on herbland areas previously maintained by fire or created

by early logging. Figure 57, A, provides an example of increased forest cover in a subwatershed 

of the Lower Grande Ronde subbasin in the Blue

Mountains ERU. Significantly reduced forest

cover in the Upper Klamath ERU suggested that

timber harvest activities during the sample period

resulted in a net depletion of forest area. Cover

type and structure analysis corroborated this

observation. Figure 57, B, provides an example 

of reduced forest cover in a subwatershed of the

Upper Klamath subbasin in the Upper Klamath

ERU.

Text resumes on page 221
214

Table 29—Historical and current percentage of area for physiognomic types, cover types, and structural

classes of 13 ecological reporting units in the midscale assessment of the interior Columbia River basin

Change in percentage of area among ERUs

Blue Central Idaho Columbia Lower Northern

Mountainsab Mountainsab Plateauab Clark Forkab Cascadesab

Patch types H C MDc H C MDc H C MDc H C MDc H C MDc

Percent

Physiognomic types:

Forest 62.8 64.1 1.4* 73.4 73.5 0.2 26.1 29.1 3.0* 91.7 94.5 2.8 78.8 78.2 -0.6

Woodland 2.7 4.2 1.6* 0.1 0.0 0.0 6.7 12.2 5.5* -- -- -- 0.3 0.7 0.3*

Shrubland 14.1 10.7 -3.4* 19.2 17.1 -2.0* 32.2 23.4 -8.8* 1.9 0.6 -1.4 4.8 4.1 -0.7

Herbland 17.4 18.0 0.6 3.2 4.5 1.0* 12.7 14.0 1.4 5.4 3.2 -2.3 6.7 6.5 -0.3

Otherd 3.0 2.9 -0.1 4.2 4.9 1.0* 22.4 21.4 -1.0 0.9 1.8 0.8 9.4 10.6 1.2*

Cover types-forest and woodland:

Pacific silver fir -- -- -- -- -- -- -- -- -- -- -- -- 6.0 8.3 2.3*

Grand fir-white fir 15.3 8.4 -6.9* 9.6 10.2 0.5 1.1 0.4 -0.7 40.4 42.5 2.1 1.0 2.2 1.3*

Engelmann spruce-subalpine fir 6.3 4.4 -1.9* 22.7 24.1 1.4 0.0 0.0 0.0 2.5 2.2 -0.3 16.8 13.6 3.2*

Aspen-cottonwood-willow 0.1 0.1 0.0 1.1 0.8 -0.2 0.3 0.3 0.0 0.1 0.7 0.6 -- -- --

Oregon white oak -- -- -- -- -- -- -- -- -- -- -- -- 0.6 0.9 0.3*

Juniper 2.7 4.2 1.5* 0.1 0.0 0.0 6.5 12.0 5.5* -- -- -- 0.0 0.0 0.0

Western larch 2.6 2.2 -0.4 0.5 0.3 -0.2* 1.0 0.1 -0.9* 0.8 2.6 1.7 1.0 1.0 0.0

Whitebark pine-subalpine larch 0.0 0.7 0.7* 5.1 2.5 -2.5 -- -- -- -- -- -- 3.3 4.7 1.4*

Lodgepole pine 2.4 2.3 -0.1 9.7 9.5 -0.2 1.3 0.9 -0.4 2.1 1.8 -0.3 5.9 5.2 -0.6

Limber pine 0.0 0.0 0.0 0.4 0.4 -0.1 -- -- -- 0.0 0.0 0.0 -- -- --

Sugar pine-western white pine -- -- -- -- -- -- -- -- -- 0.3 0.6 0.2 0.1 0.3 0.1*

Ponderosa pine 28.4 28.9 0.5 6.0 5.9 -0.2 19.2 21.4 2.3* 3.0 5.1 2.1 16.5 13.2 -3.2*

Douglas-fir 7.7 17.1 9.4* 17.6 18.5 1.0 3.0 3.9 0.9* 26.4 21.1 -5.3 23.8 25.8 2.0*

Western hemlock with redcedar -- -- -- 0.9 1.3 0.4 0.4 2.2 1.9* 14.7 17.3 2.6 3.0 2.4 -0.6*

Mountain hemlock -- -- -- 0.0 0.0 0.0* 0.0 0.0 0.0 1.3 0.6 -0.7* 1.3 1.2 -0.1

Cover types-shrubland:

Colline low-medium 7.2 4.7 -2.5* 8.2 8.0 -0.3 29.1 21.7 -7.4* -- -- -- 1.6 1.8 0.2

Montane low-medium 6.0 5.4 -0.6 5.3 4.9 -0.4 1.3 0.9 -0.3 -- -- -- 0.3 0.4 0.1

Subalpine-alpine low-medium -- -- -- 0.5 0.4 -0.1 -- -- -- 0.2 0.1 -0.1 -- -- --

Colline mahogany species -- -- -- 0.0 0.0 0.0 0.4 0.1 -0.2 -- -- -- 0.2 0.0 -0.1

Montane mahogany species 0.4 0.2 -0.1* 0.4 0.2 -0.2* 0.0 0.0 0.0 -- -- -- 0.0 0.0 0.0*

Subalpine-alpine 

mahogany species -- -- -- 0.0 0.0 0.0 -- -- -- -- -- -- -- -- --

Colline tall 0.0 0.0 0.0 0.5 0.3 -0.3 0.3 0.1 -0.1 -- -- -- 0.0 0.0 0.0

Montane tall 0.1 0.0 -0.1* 3.7 3.2 -0.5 0.9 0.4 -0.6 1.6 0.3 -1.3 0.0 0.0 0.0*

Colline wet-site 0.0 0.1 0.0 0.1 0.1 -0.1 0.2 0.1 -0.1* 0.0 0.0 0.0 0.0 0.0 0.0

Montane wet-site 0.1 0.1 0.0 0.7 0.6 -0.1* 0.1 0.1 0.0 1.4 1.4 0.1 0.0 0.0 0.0

Subalpine-alpine wet-site -- -- -- 0.0 0.0 0.0 -- -- -- -- -- -- -- -- --

Montane subshrub -- -- -- 0.1 0.1 0.0 0.0 0.0 0.0 -- -- -- 0.9 0.3 -0.5

Subalpine-alpine subshrub -- -- -- 0.0 0.1 0.1* -- -- -- -- -- -- -- -- --

Cover types-herbland:

Alpine meadow 0.1 0.2 0.2 0.0 0.1 0.1 -- -- -- -- -- -- 0.7 0.8 0.1 

Dry meadow 6.2 5.3 -0.9* 0.0 0.1 0.1 0.1 0.0 -0.1 -- -- -- 1.7 1.5 -0.2

Colline bunchgrass 3.9 4.6 0.7 0.1 0.2 0.1* 8.3 6.9 -1.4* -- -- -- 1.0 1.2 0.2

Montane bunchgrass 3.4 3.5 0.1 0.7 1.2 0.6* 1.3 1.8 0.5* 0.1 0.2 0.1 1.0 0.7 -0.3*

Subalpine-alpine bunchgrass -- -- -- 0.0 0.0 0.0 -- -- -- -- -- -- -- -- --

Colline exotic grasses-forbs 0.3 1.3 1.0* 0.6 0.8 0.1 0.8 2.3 1.5* -- -- -- 0.9 0.5 -0.4*
215

Table 29—Historical and current percentage of area for physiognomic types, cover types, and structural

classes of 13 ecological reporting units in the midscale assessment of the interior Columbia River basin

(continued)

Change in percentage of area among ERUs

Blue Central Idaho Columbia Lower Northern

Mountainsab Mountainsab Plateauab Clark Forkab Cascadesab

Patch types H C MDc H C MDc H C MDc H C MDc H C MDc

Percent

Montane exotic grasses-forbs 1.3 1.2 -0.1 0.1 0.2 0.1 0.1 0.3 0.2 0.1 0.1 0.0 0.7 0.9 0.2*

Colline moist-site herbs 0.1 0.0 0.0 0.2 0.2 0.0* 0.1 0.2 0.1 -- -- -- 0.0 0.0 0.0

Montane moist-site herbs 0.7 0.5 -0.2* 0.7 0.6 0.0 0.5 0.5 0.1 0.2 0.2 -0.1 0.0 0.0 0.0

Subalpine-alpine 

moist-site herbs -- -- -- 0.0 0.1 0.1 -- -- -- -- -- -- -- -- --

Wet meadow 0.2 0.0 -0.2* -- -- -- 0.1 0.0 -0.1 0.0 0.0 0.0 0.2 0.1 -0.1

Postfire-grasses -- -- -- 0.1 0.0 -0.1 -- -- -- 2.9 0.0 -2.9 -- -- --

Postlogging grasses-forbs 0.0 0.1 0.1* 0.0 0.2 0.2* 0.0 0.0 0.0 0.4 0.9 0.5 0.1 0.4 0.4*

Cover type-agricultural-rural-urban:

Cropland 2.3 1.8 -0.5* 0.3 0.2 -0.1 18.1 17.9 -0.1 -- -- -- 1.7 1.6 -0.1

Pasture 1.0 1.0 0.0 0.1 0.1 0.1 1.1 1.4 0.3 0.4 0.4 0.0 0.3 0.2 -0.2

Urban-rural 0.1 0.1 0.0 0.0 0.3 0.2* 0.6 0.8 0.2 0.0 0.0 0.0 0.1 0.3 0.2*

Cover type-other:

Bare ground-road 0.0 0.0 0.0 0.0 0.0 0.0 -- -- -- -- -- -- -- -- --

Rock 0.6 0.7 0.1 3.4 3.6 0.1 0.4 0.5 0.1 0.5 0.3 -0.2 4.8 5.1 0.3

Postlogging-bare ground-burned 0.0 0.3 0.6* 0.2 0.7 0.5* 2.8 1.6 -1.2 0.0 1.1 1.1 0.5 1.5 0.9*

Postloggingbare ground-slumps 0.1 0.0 -0.1 0.0 0.0 0.0 0.0 0.1 0.1 -- -- -- 1.5 1.3 -0.2

Stream channelnonvegetated flood plain 0.0 0.0 0.0 0.0 0.1 0.0 0.3 0.0 -0.2 0.2 0.3 0.1 -- -- --

Water 0.1 0.1 0.0 0.1 0.1 0.0 0.3 0.4 0.1* 0.2 0.1 -0.1 0.8 0.8 0.0

Structural classes-forest:

Stand initiation 3.9 6.5 2.6* 9.7 5.9 -3.8* 2.3 2.8 0.5 32.7 9.5 -23.3* 9.2 10.4 1.3

Stem exclusion, open canopy 14.3 9.6 -4.7* 18.4 17.7 -0.8 6.7 7.8 1.1 15.7 9.2 -6.5* 13.2 13.2 0.0

Stem exclusion, closed canopy 5.0 5.0 0.0 7.7 8.5 0.8 3.8 3.6 -0.2 10.3 17.6 7.3* 7.6 7.9 0.3

Understory reinitiation 13.6 11.2 -2.4* 16.0 21.4 5.5* 3.1 3.3 0.2 16.4 37.7 21.3* 17.5 19.5 2.0

Young multistory 21.3 29.6 8.2* 18.4 17.1 -1.2 7.3 10.0 2.7* 14.3 17.5 3.2 21.2 22.0 0.8

Old multistory 2.2 1.0 -1.3* 1.4 1.2 -0.3 2.3 1.3 -1.0 0.2 0.5 0.3 5.8 2.7 -3.1*

Old single story 2.7 0.9 -1.7* 1.8 1.7 -0.1 1.1 1.0 -0.1 2.2 2.5 0.4 4.3 2.4 -1.9*

Structural classes-woodland:

Stand initiation 0.0 0.1 0.0 -- -- -- 0.1 0.3 0.2 -- -- -- 0.0 0.0 0.0

Stem exclusion 2.4 4.0 1.6* 0.1 0.0 0.0 5.9 10.9 5.0* -- -- -- 0.3 0.6 0.3*

Understory reinitiation 0.3 0.2 -0.1 -- -- -- 0.6 1.0 0.3 -- -- -- 0.0 0.0 0.0*

Young multistory -- -- -- -- -- -- 0.0 0.0 0.0 -- -- -- -- -- --

Old multistory 0.0 0.0 0.0 -- -- -- 0.0 0.0 0.0 -- -- -- 0.0 0.0 0.0

Old single story -- -- -- -- -- -- -- -- -- -- -- -- 0.0 0.0 0.0

Structural classes-shrubland:

Open low-medium 11.0 8.3 -2.7* 12.6 12.0 -0.5 23.4 19.4 -4.1* 0.2 0.1 -0.1 2.0 1.8 -0.2

Closed low-medium 2.3 1.8 -0.4 1.6 1.4 -0.2 6.9 3.3 -3.7* 0.0 0.0 0.0 0.8 0.8 0.0

Open tall 0.5 0.4 0.0 2.8 2.8 0.1 0.9 0.4 -0.6* 2.1 1.2 -0.9 0.0 0.0 0.0*

Closed tall 0.2 0.1 -0.1* 2.7 1.5 -1.2* 0.9 0.4 -0.6 1.0 0.7 -0.3 0.0 0.1 0.0*

Structural classes-herbland:

Open 6.4 8.5 2.1* 0.9 1.1 0.1 7.4 9.0 1.5* 0.2 0.1 -0.1 2.3 2.4 0.1

Closed 3.2 2.5 -0.7* 1.7 2.2 0.5* 3.8 3.2 -0.5 0.2 0.3 0.2 1.5 1.0 -0.5

Structural classes-other:

Nonforest-nonrange 11.1 10.0 -1.1* 4.4 5.4 1.1* 23.8 23.2 -0.6 4.7 3.2 -1.5 14.3 15.2 0.9*
216

Table 29—Historical and current percentage of area for physiognomic types, cover types, and structural

classes of 13 ecological reporting units in the midscale assessment of the interior Columbia River basin

(continued)

Change in percentage of area among ERUs

Northern Northern Owyhee Snake Southern

Glaciated Mountainsab Great Basinab Uplandsab Headwatersab Cascadesab

Patch types H C MDc H C MDc H C MDc H C MDc H C MDc

Percent

Physiognomic types:

Forest 81.0 80.8 -0.2 7.2 7.3 0.0 0.2 0.2 0.0 74.5 73.8 -0.7 80.5 88.3 7.8

Woodland 0.0 0.0 0.0 15.3 22.2 6.9* 5.5 7.6 2.1* 0.2 0.3 0.1* 0.0 0.4 0.4

Shrubland 3.1 2.5 -0.5 72.8 57.6 -15.2* 88.8 81.0 -7.8* 16.3 13.9 -2.4* 0.5 0.5 0.1

Herbland 7.4 8.1 0.7 3.9 12.2 8.3* 1.0 7.4 6.4* 6.1 8.7 2.6* 0.6 2.7 2.1*

Otherd 8.5 8.5 0.0 0.8 0.8 0.0 4.5 3.8 -0.6 3.0 3.3 0.4 18.4 8.1 -10.4*

Cover types-forest and woodland:

Pacific silver fir -- -- -- -- -- -- -- -- -- -- -- -- -- -- --

Grand fir-white fir 0.0 1.2 1.2* -- -- -- -- -- -- -- -- -- 5.9 6.5 0.6

Engelmann spruce-subalpine fir 11.5 13.2 1.7* -- -- -- -- -- -- 24.3 31.4 7.1* 0.0 0.2 0.2*

Shasta red fir -- -- -- -- -- -- -- -- -- -- -- -- 0.2 0.4 0.2*

Aspen-cottonwood-willow 0.3 1.9 1.6 8.4 7.7 -0.8 0.2 0.2 0.0 8.8 5.7 -3.1* 0.0 0.0 0.0

Juniper 0.0 0.0 0.0 14.1 21.8 7.7* 5.5 7.5 2.0* 0.2 0.3 0.1* 0.0 0.4 0.4

Western larch 14.8 11.4 -3.4* -- -- -- -- -- -- -- -- -- 0.0 0.0 0.0

Whitebark pine-subalpine larch 0.3 0.2 -0.1 -- -- -- -- -- -- 6.9 5.7 -1.3 0.0 0.8 0.8

Lodgepole pine 8.0 8.3 0.3 -- -- -- -- -- -- 15.6 11.3 -4.3* 19.4 20.6 1.2

Pinyon pine-juniper -- -- -- -- -- -- -- -- -- 0.0 0.0 0.0 -- -- --

Limber pine -- -- -- -- -- -- -- -- -- 0.7 1.1 0.4* -- -- --

Sugar pine-western white pine 1.5 0.0 -1.4* -- -- -- -- -- -- -- -- -- 0.3 0.3 0.0

Ponderosa pine 13.4 11.4 -2.0* -- -- -- -- -- -- 0.0 0.0 0.0 22.7 28.1 5.4

Douglas-fir 30.3 30.2 -0.1 -- -- -- 0.0 0.0 0.0 18.2 18.6 0.4 1.5 1.7 0.2

Western hemlock with redcedar 0.7 2.8 2.5* -- -- -- -- -- -- -- -- -- -- -- --

Mountain hemlock -- -- -- -- -- -- -- -- -- -- -- -- 30.5 29.7 -0.8

Cover types-shrubland:

Colline low-medium 0.1 0.1 0.0 20.0 18.1 -1.8 87.7 79.3 -8.5* 0.1 0.0 -0.1 -- -- --

Montane low-medium 0.0 0.1 0.1* 51.2 37.7 -13.5* -- -- -- 13.0 10.7 -2.3* -- -- --

Subalpine-alpine low-medium 1.1 0.8 -0.2 0.6 2.0 1.4 -- -- -- 0.1 0.3 0.2 -- -- --

Colline mahogany species 0.4 0.0 -0.4* -- -- -- 0.8 1.1 0.4 -- -- -- -- -- --

Montane mahogany species 0.2 0.0 -0.2* 0.4 0.4 0.0 -- -- -- 0.0 0.1 0.1 -- -- --

Colline tall 0.7 0.3 -0.4 -- -- -- 0.1 0.3 0.2 0.0 0.0 0.0 -- -- --

Montane tall 0.4 0.6 0.2 0.1 0.1 0.0 -- -- -- 2.1 2.1 -0.1 -- -- --

Colline wet-site 0.3 0.2 -0.1* -- -- -- 0.3 0.3 -0.1 -- -- -- -- -- --

Montane wet-site 0.1 0.2 0.1* 1.0 0.9 -0.1* -- -- -- 2.8 2.8 0.0 -- -- --

Subalpine-alpine wet-site 0.0 0.0 0.0 -- -- -- -- -- -- -- -- -- -- -- --

Montane subshrub 0.3 0.4 0.1 -- -- -- -- -- -- -- -- -- -- -- --

Subalpine-alpine subshrub 0.0 0.1 0.1* -- -- -- -- -- -- -- -- -- -- -- --

Russian olive -- -- -- -- -- -- 0.1 0.0 -0.1 -- -- -- -- -- --

Cover types-herbland:

Alpine meadow 0.0 0.0 0.0 -- -- -- -- -- -- -- -- -- 0.1 0.2 0.1

Dry meadow 0.0 0.0 0.0* -- -- -- -- -- -- -- -- -- 0.0 0.1 0.0*

Colline bunchgrass 1.6 0.8 -0.8* 0.0 0.5 0.5 0.2 0.2 0.0 0.0 0.0 0.0 -- -- --

Montane bunchgrass 1.6 1.9 -.2 1.1 5.5 4.5* -- -- -- 2.2 4.3 2.1* -- -- --

Subalpine-alpine bunchgrass 0.0 0.0 0.0 1.5 0.8 -0.7 -- -- -- 0.1 0.3 0.2 -- -- --

Colline exotic grasses-forbs 1.0 1.2 0.2 0.0 2.5 2.5* 0.2 6.2 6.1* -- -- -- -- -- --
217

Table 29—Historical and current percentage of area for physiognomic types, cover types, and structural

classes of 13 ecological reporting units in the midscale assessment of the interior Columbia River basin

(continued)

Change in percentage of area among ERUs

Northern Northern Owyhee Snake Southern

Glaciated Mountainsab Great Basinab Uplandsab Headwatersab Cascadesab

Patch types H C MDc H C MDc H C MDc H C MDc H C MDc

Percent

Montane exotic grasses-forbs 0.5 0.7 0.1 0.0 0.0 0.0 -- -- -- 0.2 0.7 0.5* -- -- --

Subalpine-alpine 

exotic grasses-forbs -- -- -- -- -- -- -- -- -- 0.0 0.1 0.1 -- -- --

Colline moist-site herbs 0.0 0.0 0.0 -- -- -- 0.1 0.5 0.4* -- -- -- -- -- --

Montane moist-site herbs 0.2 0.2 0.0 0.6 1.2 0.6 -- -- -- 1.5 1.1 -0.4* 0.0 0.1 0.1

Subalpine-alpine moist-siteherbs 0.0 0.0 0.0 0.1 0.0 -0.1 -- -- -- 0.0 0.0 0.0 -- -- --

Wet meadow 0.1 0.1 0.1* -- -- -- -- -- -- -- -- -- 0.5 0.6 0.0

Postlogging grasses-forbs 0.1 0.8 0.7* -- -- -- -- -- -- 0.0 0.1 0.1 0.0 1.6 1.6*

Cover type-agricultural-rural-urban:

Cropland 3.4 4.3 0.9 -- -- -- 1.1 1.4 0.3 0.3 0.1 -0.3 0.2 0.0 -0.1

Pasture 1.4 1.7 0.3* -- -- -- 0.5 0.5 0.0 -- -- -- -- -- --

Urban-rural 0.2 0.3 0.1 -- -- -- -- -- -- -- -- -- 0.0 0.3 0.3*

Cover types-other:

Bare ground 0.0 0.0 0.0 -- -- -- 0.0 0.0 0.0 -- -- -- -- -- --

Bare ground-road -- -- -- -- -- -- 0.0 0.0 0.0 0.0 0.1 0.0 -- -- --

Glacier 0.0 0.0 0.0 -- -- -- -- -- -- 0.1 0.0 -0.1 -- -- --

Rock 2.3 2.7 0.5* 0.8 0.7 -0.1 2.8 1.9 -0.9 1.7 2.1 -.5 5.2 4.1 -1.1

Postlogging-bare ground-burned 2.2 0.4 -1.7* -- -- -- 0.1 0.1 0.0 0.0 0.0 0.0* 10.1 1.8 -8.4*

Postlogging-bare ground-slumps 0.0 0.0 0.0 -- -- -- -- -- -- 0.1 0.0 -0.1 0.4 0.2 -0.2

Stream channelnonvegetated flood plain 0.1 0.1 0.0* -- -- -- 0.4 0.3 -0.1 0.1 0.1 0.1 0.0 0.0 0.0

Water 0.4 0.5 0.1 0.0 0.0 0.0 0.1 0.1 0.0* 0.9 0.9 0.1* 1.5 1.6 0.1

Structural classes-forest:

Stand initiation 16.9 9.4 -7.5* -- -- -- 0.0 0.0 0.0 6.4 7.0 0.6 9.1 9.9 0.8

Stem exclusion, open canopy 11.8 11.6 -0.2 6.5 6.0 -0.5 0.0 0.1 0.0 19.1 15.3 -3.8* 12.3 14.3 2.1

Stem exclusion, closed canopy 7.2 12.8 5.6* 0.7 1.3 -0.6 0.0 0.0 0.0 7.9 4.8 -3.1* 0.5 4.8 4.2*

Understory reinitiation 18.4 23.3 4.9* -- -- -- 0.4 1.1 0.7 13.8 12.6 -1.2 10.3 8.7 -1.7

Young multistory 25.5 22.8 -2.7* -- -- -- 0.1 0.1 0.0 22.0 30.9 8.9* 46.0 45.6 -0.4

Old multistory 0.5 0.4 -0.1 -- -- -- -- -- -- 3.2 1.8 -1.4* 0.7 1.4 0.7

Old single story 0.7 0.6 -0.1 -- -- -- -- -- -- 2.0 1.3 -0.7* 1.6 3.7 2.1

Structural classes-woodland:

Stand initiation -- -- -- -- -- -- 0.0 0.0 0.0 0.1 0.0 -0.1 -- -- --

Stem exclusion 0.0 0.0 0.0 15.3 22.2 6.9* 5.2 6.5 1.3* 0.1 0.3 0.2 0.0 0.4 0.4

Understory reinitiation 0.0 0.0 0.0 -- -- -- 0.3 1.1 0.8 0.0 0.0 0.0 -- -- --

Old multistory -- -- -- -- -- -- -- -- -- -- -- -- 0.0 0.0 0.0

Structural classes-shrubland:

Open low-medium 1.2 1.1 -0.2 71.8 57.8 -13.9* 85.1 77.2 -7.8* 9.3 7.0 -2.3* -- -- --

Closed low-medium 0.3 0.5 0.2 -- -- -- 2.7 2.1 -0.6 3.9 4.0 0.1 -- -- --

Open tall 1.2 0.8 -0.4 1.2 1.2 0.0 0.8 1.4 0.6* 2.9 2.6 -0.3 -- -- --

Closed tall 0.3 0.4 0.2 0.4 0.2 -0.1 0.3 0.3 0.0 2.1 2.3 0.2 -- -- --

Structural classes-herbland:

Open 1.4 1.5 0.1 3.4 10.1 6.7* 0.3 6.4 6.1* 1.8 4.2 2.4* 0.0 0.1 0.1

Closed 4.2 3.4 -0.8 0.0 0.5 0.5 0.1 0.5 0.4 2.3 2.3 0.1 -- -- --

Structural classes-other:

Nonforest-nonrange 10.5 11.6 1.1* 0.8 0.8 0.0 5.0 4.4 -0.6 3.1 3.5 0.3 19.5 11.2 -8.3*
218

Table 29—Historical and current percentage of area for physiognomic types, cover types, and structural

classes of 13 ecological reporting units in the midscale assessment of the interior Columbia River basin

(continued)

Change in percentage of area among ERUs

Upper Clark Forksab Upper Klamathab Upper Snakeab

Patch types H C MDc H C MDc H C MDc

Percent

Physiognomic types:

Forest 87.2 86.2 -1.0 50.5 47.5 -3.1* 2.4 3.2 0.9*

Woodland -- -- -- 8.4 12.8 4.4* 3.0 2.9 0.0

Shrubland 2.5 2.1 -0.4 21.4 18.8 -2.6 73.8 68.5 -5.3

Herbland 5.5 5.7 0.2 10.6 9.0 -1.6 10.6 9.9 -0.7

Otherd 4.8 6.0 1.2 9.1 12.0 2.9* 10.3 15.4 5.1

Cover types-forest and woodland:

Grand fir-white fir 0.0 0.1 0.1 7.8 8.1 0.3 -- -- --

Engelmann spruce-subalpine fir 14.2 17.3 3.1* 0.1 0.1 0.0 0.0 0.0 0.0

Shasta red fir -- -- -- 7.8 8.5 0.7 -- -- --

Aspen-cottonwood-willow 0.3 0.3 0.0 0.0 0.1 0.0 0.9 1.0 -.1

Juniper -- -- -- 8.4 12.8 4.4* 2.6 2.5 -0.1

Western larch 2.5 3.0 0.6 0.0 0.1 0.1 -- -- --

Whitebark pine-subalpine larch 4.3 3.5 -0.8* 0.0 0.0 0.0 -- -- --

Lodgepole pine 20.9 19.5 -1.3 1.4 1.7 0.3 0.1 0.2 0.1

Pinyon pine-juniper -- -- -- -- -- -- 0.4 0.5 0.1

Limber pine 0.0 0.4 0.3 -- -- -- -- -- --

Sugar pine-western white pine -- -- -- 0.0 0.0 0.0 -- -- --

Ponderosa pine 12.3 9.5 -2.9* 26.7 23.5 -3.2* -- -- --

Mountain hemlock 0.0 0.1 0.1 4.7 4.2 -0.5 -- -- --

Cover types-shrubland:

Colline low-medium 0.8 0.7 -0.1 1.8 2.9 1.1 71.0 62.3 -8.6*

Montane low-medium 0.4 0.7 0.2 18.5 14.9 -3.6* 0.3 0.5 0.2

Subalpine-alpine low-medium 0.2 0.2 -0.1 0.1 0.1 0.0 -- -- --

Colline mahogany species -- -- -- 0.0 0.1 0.1 0.4 0.0 -0.4

Montane mahogany species 0.1 0.0 -0.1* 0.1 0.1 0.0 0.1 0.1 0.0

Colline tall -- -- -- 0.0 0.0 0.0 3.4 5.1 1.6

Montane tall 0.2 0.2 -0.1 0.3 0.4 0.2 0.1 0.4 0.3

Colline wet-site 0.1 0.1 0.0 0.5 0.0 -0.5 0.1 0.1 0.0

Montane wet-site 0.6 0.6 0.0 0.6 0.4 -0.1* 0.0 0.0 0.0

Subalpine-alpine wet-site 0.0 0.0 0.0* -- -- -- -- -- --

Montane subshrub 0.3 0.0 -0.3* -- -- -- -- -- --

Subalpine-alpine subshrub 0.0 0.0 0.0 -- -- -- -- -- --

Cover types-herbland:

Alpine meadow 0.0 0.0 0.0 -- -- -- 0.0 0.0 0.0

Dry meadow -- -- -- 0.0 0.0 0.0 -- -- --

Colline bunchgrass 0.3 0.3 -0.1 2.8 1.0 -1.8* 3.7 5.2 1.5*

Montane bunchgrass 3.1 1.8 -1.4* 0.7 0.4 -0.3* -- -- --

Subalpine-alpine bunchgrass 0.1 0.0 0.0* -- -- -- -- -- --

Colline exotic grasses-forbs 0.1 0.2 0.0 0.0 0.4 0.4 4.6 4.0 -0.6

Montane exotic grasses-forbs 0.1 0.2 0.1* 0.0 0.0 0.0 -- -- --

Subalpine-alpine exotic grasses-forbs 0.1 0.0 -0.1 -- -- -- -- -- --

Colline moist-site herbs 0.0 0.0 0.0 1.1 0.1 -1.0* 0.1 0.2 0.0

Montane moist-site herbs 0.7 0.7 0.0 0.8 0.7 -0.1 -- -- --

Subalpine-alpine moist-site herbs 0.0 0.3 0.2 -- -- -- -- -- --
219

Table 29—Historical and current percentage of area for physiognomic types, cover types, and structural

classes of 13 ecological reporting units in the midscale assessment of the interior Columbia River basin

(continued)

Change in percentage of area among ERUs

Upper Clark Forksab Upper Klamathab Upper Snakeab

Patch types H C MDc H C MDc H C MDc

Percent

Wet meadow -- -- -- -- -- -- 0.0 0.0 0.0

Post fire-grasses 0.0 0.5 0.4 -- -- -- 0.4 0.2 -0.2

Postlogging grasses-forbs 0.0 0.9 0.9* 0.0 0.1 0.1* -- -- --

Cover types-agricultural-rural-urban:

Cropland 1.2 1.3 0.1 7.0 10.5 3.5* 2.7 12.1 9.4*

Pasture 0.4 0.4 0.0 4.4 5.3 0.9 0.1 0.2 0.2

Urban-rural 0.0 0.1 0.0 0.0 0.1 0.1 0.0 0.2 0.2*

Cover types-other:

Bare ground-road 0.0 0.0 0.0* 0.0 0.0 0.0* 0.1 0.1 0.0

Rock 2.5 2.4 -0.1 0.2 0.4 0.2 6.8 2.6 -4.1*

Postlogging-bare ground-burned 0.1 1.5 1.4* 0.0 0.4 0.4* -- -- --

Postlogging-bare ground-slumps 0.0 0.0 0.0 0.0 0.0 0.0 -- -- --

Sand dune -- -- -- -- -- -- 0.5 0.4 -0.1

Stream channel-nonvegetated flood plain 0.1 0.1 0.0 -- -- -- 0.1 0.0 -0.1

Water 0.8 0.7 -0.1 2.2 1.4 -0.8 0.1 0.1 0.0

Structural classes-forest:

Stand initiation 15.9 11.1 -4.8* 1.9 3.6 1.6 0.8 0.3 -0.5*

Stem exclusion, open canopy 18.5 18.2 -0.3 11.3 10.9 -0.4 0.4 1.0 0.6*

Stem exclusion, closed canopy 16.7 21.1 4.4* 1.2 1.6 0.3 0.1 0.1 0.0

Understory reinitiation 15.6 14.0 -1.5 5.6 8.1 2.5 2.5 1.6 -1.0

Young multistory 19.7 21.1 1.3 21.1 16.4 -4.7* 0.6 1.1 0.5

Old multistory 0.6 0.4 -0.2 4.3 5.5 1.2 0.0 0.0 0.0

Old single story 0.2 0.3 0.1 7.4 4.8 -2.6* 0.1 0.0 -0.1

Structural classes-woodland:

Stand initiation -- -- -- 0.4 1.1 0.7 0.4 0.2 -0.3

Stem exclusion -- -- -- 5.9 7.6 1.6* 0.7 2.0 1.3*

Understory reinitiation -- -- -- 2.0 3.8 1.8* 1.8 0.8 -1.1*

Old multistory -- -- -- 0.0 0.3 0.3 -- -- --

Structural classes-shrubland:

Open low-medium 1.2 0.8 -0.4 18.5 15.9 -2.6 63.1 57.8 -5.3

Closed low-medium 0.6 0.8 0.2 1.9 2.0 0.1 8.2 5.0 -3.2

Open tall 0.5 0.6 0.2 1.1 0.9 -0.2 3.0 5.2 2.3*

Closed tall 0.5 0.3 -0.3* 0.3 0.2 -0.1 0.7 0.4 -0.4*

Structural classes-herbland:

Open 1.1 1.3 0.2 3.8 1.4 -2.4* 8.1 9.1 1.0

Closed 3.5 2.1 -1.5* 1.6 1.1 -0.4* -.7 0.3 -0.4

Structural classes-other:

Nonforest-nonrange 5.3 7.9 2.6* 13.9 18.2 4.3* 10.8 16.0 5.1

a Ecological reporting units of the interior Columbia River basin. 

b H = historical; C = current; MD = mean difference of pairwise comparisons of historical and current subwatersheds.

c* indicates significant difference at P≤0.2.

d Other includes anthropogenic cover types and other nonforest and nonrange types.
220

Figure 57—Historical and current maps of physiognomic types: (A) subwatershed 21 in the Lower Grande Ronde subbasin of

the Blue Mountains ERU, and (B) subwatershed 0402 in the Upper Klamath subbasin of the Upper Klamath ERU.
221

Connectivity of forests (as a physiognomic condition) increased in the Central Idaho Mountains

and Upper Snake ERUs (appendix 2). The

Central Idaho Mountains ERU contains large

areas of congressionally or administratively designated wilderness or roadless areas. Across much 

of the area of this ERU, the primary management

activity has been fire prevention and suppression.

It is likely that increased connectivity of forests

has occurred as a consequence of fire exclusion.

Connectivity of forests declined significantly in

the Upper Klamath ERU where evidence of timber harvest was widespread.

Woodland area increased in virtually all ERUs

that had a significant woodland component in

our historical starting point condition, and in

some where woodland was apparently a minor

component (table 29). Woodland cover increased

significantly in the Blue Mountains, Columbia

Plateau, Northern Cascades, Northern Great

Basin, Owyhee Uplands, Snake Headwaters, and

Upper Klamath ERUs, suggesting that fire exclusion and grazing indeed enabled expansion at the

expense of declining herblands and shrublands

(see Hann and others 1997). Figure 58, A, provides an example of expanded woodland cover 

in a subwatershed of the Lower Crooked subbasin

in the Columbia Plateau ERU.

Perhaps most dramatic of all changes in physiognomic conditions was the across-the-board regional decline in area of shrublands. Shrubland

area declined in all ERUs but the Southern

Cascades, which had little to begin with (table

29); no ERU exhibited increased shrubland area.

Ecologically significant reduction was observed 

in the Blue Mountains, Central Idaho Mountains,

Columbia Plateau, Northern Great Basin,

Owyhee Uplands, and Snake Headwaters ERUs.

Transition analyses indicated that losses to native

shrublands resulted from various factors, including forest or woodland expansion as observed in

the Blue Mountains and Northern Great Basin

ERUs, cropland expansion as observed in the

Northern Great Basin ERU, and conversion to

seminative or nonnative herbland as observed 

in the Owyhee Uplands and Snake Headwaters

ERUs (see also fig. 58, A).

Herbland area increased significantly in the

Central Idaho Mountains, Northern Great Basin,

Owyhee Uplands, Snake Headwaters, and

Southern Cascades ERUs and declined in no

ERU (table 29). This observation is somewhat

misleading when viewed superficially: for example, in the Central Idaho Mountains, herbland

area apparently increased from an average of 3.2

to 4.5 percent of the ERU (appendix 2), and

increases were primarily to colline and montane

bunchgrass cover types (table 29); but in the

Northern Great Basin, herbland area rose from 

an average of 3.9 to 12.2 percent of the ERU. 

In the latter instance, historical shrubland area

declined by more than 15 percent of the ERU

area. Half of the lost shrubland area is currently

occupied by juniper woodland, 4.5 percent supports montane bunchgrass cover, and the remaining 2.5 percent currently supports exotic grass

and forb cover.

In the Owyhee Uplands, herbland area rose from

1.0 to 7.4 percent of the ERU, but shrubland 

area fell from 88.8 to 81.0 percent of the ERU

(appendix 2). Most increase in herbland area was

the result of expanding colline exotic grass and

forb cover with the conversion of shrublands.

Figure 58, B, provides an example of increased

herbland area in a subwatershed of the Upper

Owyhee subbasin in the Owyhee Uplands ERU.

Increased herbland area in the Snake Headwaters

ERU also was associated with declining shrubland

area. Increased herbland and forest area in the

Southern Cascades ERU was associated with

regrowth of vast dry ponderosa pine forests

clearcut early in the 20th century before the 

historical photos were taken.

Area in “other” nonforest-nonrange types

increased significantly in the Central Idaho

Mountains, Northern Cascades, and Upper

Klamath ERUs and declined in the Southern

Cascades ERU for reasons cited immediately

above. Figure 59 provides an example of recently

increased forest area and reduced nonforest-nonrange area in a subwatershed of the Little

Deschutes subbasin in the Southern Cascades

ERU. In the Central Idaho Mountains and

Northern Cascades ERUs, increased nonforest

and nonrange area was the result of expanded
222

Figure 58—Historical and current maps of physiognomic types: (A) subwatershed o16 in the Lower Crooked subbasin of the

Columbia Plateau ERU, and (B) subwatershed 0802 in the Upper Owyhee subbasin of the Owyhee Uplands ERU. 
urban and rural development and increased bare

ground area after logging (appendix 2). In the

Upper Klamath ERU, increased nonforest and

nonrange area was the result of expanded cropland area and increased bare ground area after

logging (fig. 57, B, and table 29).

Forest and woodland cover types—Predicted

shifts (Gast and others 1991; Harvey and others

1994, 1995; Hessburg and others 1994;

Lehmkuhl and others 1994; O’Laughlin and others 1993; Wickman 1992) from early-seral species

(such as ponderosa pine, western larch, lodgepole

pine, western white pine, and sugar pine) to lateseral species (such as grand fir, white fir, subalpine

fir, Engelmann spruce, western hemlock, and

western redcedar) were evident in several ERUs.

Of all forested ERUs, the most pronounced shifts

from early to late seral cover types occurred in the

Northern Glaciated Mountains (table 29). Figure

60 provides an example of declining area in early

seral species and increasing area in late seral

species cover types in a subwatershed of the Pend

Oreille subbasin in the Northern Glaciated

Mountains ERU.

Western larch cover declined significantly in the

Central Idaho Mountains, Columbia Plateau (fig.

61), and Northern Glaciated Mountains ERUs,

and ponderosa pine cover decreased in the

Northern Cascades (fig. 62), Northern Glaciated

Mountains, Upper Clark Fork, and Upper

Klamath ERUs. Figure 61 provides an example 

of reduced area of western larch cover in a subwatershed of the Palouse subbasin in the Columbia

Plateau ERU. Figure 62 provides an example of

significantly reduced area of ponderosa pine cover

in a subwatershed of the Lower Yakima subbasin

in the Northern Cascades ERU. Ponderosa pine

cover increased in the Southern Cascades from 

an average of 22.7 to 28.1 percent of the ERU 

as a result of regrowth of forests clearcut just prior

to the period of our historical photo coverage (for

example, see fig. 63, A). Lodgepole pine cover

223

Figure 59—Historical and current maps of physiognomic types in subwatershed 45 in the Little Deschutes subbasin of the

Southern Cascades ERU. 
declined significantly in the Snake Headwaters

ERU (see fig. 63, B), and in six other ERUs, but

the latter changes were not significant at P≤0.2.

Western white pine cover decreased significantly

in the Northern Glaciated Mountains ERU (fig.

60) as a consequence of blister rust and mountain

pine beetle mortality and increased slightly in the

Northern Cascades (see fig. 64, A). Whitebark

pine-subalpine larch cover declined in the Central

Idaho Mountains, Northern Glaciated Mountains, Snake Headwaters (see fig. 63, B), and

Upper Clark Fork ERUs, but only the change 

in the Upper Clark Fork ERU was significant at

P≤0.2; cover increased in the Blue Mountains and

Northern Cascades ERUs. Decline in whitebark

pine cover likely was the result of ongoing blister

rust and mountain pine beetle mortality (Hagle

and others 1989, Keane and Arno 1993, Keane

and Morgan 1994).

In the Northern and Southern Cascades ERUs,

western white pine and sugar pine occurred as 

relatively minor early seral species in mixed compositions. Large areas of pure type apparently

were uncommon. In the Northern Glaciated

Mountains ERU, large areas of pure type were 

relatively more common. Throughout the Inland

Northwest, western white pine and sugar pine

have long been prized as premium sawtimber

species for their rapid growth rate, long straight

boles, and superior physical properties and

machining characteristics.

Accounts of the earliest logging in the West describe widespread selective harvest of large western

white pine throughout northern Idaho, northwest

Montana, and the Cascade Range of Oregon and

Washington. The extent to which such selective

harvest affected five-needle pine reserves in the

Northern and Southern Cascades is poorly documented. Additionally, the fungus that causes

224

Figure 60—Historical and current maps of forest and woodland cover types in subwatershed 09 in the Pend Oreille subbasin of

the Northern Glaciated Mountains ERU. 
white pine blister rust was introduced to inland

Northwest forests over the last 90 years. Widespread blister rust mortality is prevalent throughout the entire range of western white pine, sugar

pine, whitebark pine, and limber pine. For these

reasons, our estimates of the historical area of

these cover types and other mixed types including

these species for the Northern and Southern

Cascades, Northern Glaciated Mountains, and

Lower Clark Fork ERUs were probably quite conservative. Our results suggest that finer scale plot

data and stand reconstructions are needed to

improve estimates of historical distribution and

abundance of five-needle pines. But focusing only

on improved quantitative estimates of decline in

reserves of five–needle pines misses the larger

point, which our data clearly illustrate: five-needle

pines have been decimated by blister rust, timber

harvest, and bark beetles, and that has significant

ecological and economic consequences for people.

Perhaps greatest among the risks associated with

declining five-needle pine reserves is reduced

genetic diversity where populations of western

white pine and sugar pine have been minimized

or eliminated. Across vast areas of the range of

western white pine and sugar pine, these species

occur as minor or associated early seral species. 

In many areas, such populations are now extinct

or minimized to a remnant. In northern Idaho

and northwest Montana, western white pine was 

a major early seral species across a significant forest area, especially within the western hemlock

and western redcedar zones (Cooper and others

1987). As a consequence of blister rust, other

coniferous species such as Douglas-fir and grand

fir have replaced western white pine in that role,

modifying successional trajectories and associated

fire, insect, and pathogen ecology.

225

Figure 61—Historical and current maps of forest and woodland cover types in subwatershed 2002 in the Palouse subbasin of the

Columbia Plateau ERU.
226

Figure 62—Historical and current maps of forest and woodland cover types in subwatershed 60 in the Lower Yakima subbasin

of the Northern Cascades ERU.
227

Figure 63—Historical and current maps of forest and woodland cover types: (A) subwatershed 45 in the Little Deschutes subbasin of the Southern Cascades ERU, and (B) subwatershed 0308 in the Snake Headwaters subbasin of the Snake Headwaters

ERU.
228

Figure 64—Historical and current maps of forest and woodland cover types: (A) subwatershed 55 in the Methow subbasin of the

Northern Cascades ERU, and (B) subwatershed 06 in the Wenatchee subbasin of the Northern Cascades ERU.
Douglas-fir cover increased significantly in 

the Blue Mountains, Columbia Plateau, and

Northern Cascades ERUs (see fig. 62); grand 

fir-white fir cover increased in the Northern

Cascades and Northern Glaciated Mountains 

(see fig. 60); Pacific silver fir cover increased in

the Northern Cascades ERU (see fig. 64, A);

Engelmann spruce-subalpine fir cover increased 

in the Northern Glaciated Mountains, Snake

Headwaters (see fig. 63, B), Southern Cascades,

and Upper Clark Fork ERUs; and western hemlock-western redcedar cover increased in the

Columbia Plateau (fig. 61), and Northern

Glaciated Mountains ERUs. Figure 61 provides

an example of dramatically increased area of western hemlock-western redcedar cover in a subwatershed of the Palouse subbasin in the Columbia

Plateau ERU. Engelmann spruce-subalpine fir

cover declined significantly in the Blue Mountains, and Engelmann spruce-subalpine fir (see

fig. 64, A) and western hemlock-western redcedar

cover decreased in the Northern Cascades. Figure

64, B, provides an example of reduced area and

connectivity of western hemlock-western redcedar

cover in a subwatershed of the Wenatchee subbasin in the Northern Cascades ERU. Our results

suggest that noted increases in shade-tolerant

cover types were the direct result of effective fire

prevention and suppression programs, selective

timber harvest, and fire exclusion and an indirect

consequence of the development of extensive road

networks, human settlement of interior valleys,

movement of Native American Indians onto reservations, and extensive domestic livestock grazing.

Change in area and connectivity of the Douglasfir cover type should be interpreted with caution

because Douglas-fir can be early seral, mid-seral,

or late-seral depending on the PVT: Douglas-fir 

is early seral in the western hemlock, subalpine fir,

and Pacific silver fir series, early and mid-seral in

the grand fir and white fir series, and late-seral in

the Douglas-fir series. Analysis is underway to

separate change in area and connectivity of

Douglas-fir and other cover types by PVT for

each ERU.

Among woodland cover types, juniper cover 

significantly increased in the Blue Mountains,

Columbia Plateau, Northern Great Basin,

Owyhee Uplands, Snake Headwaters, and Upper

Klamath ERUs (table 29) and did not decrease in

any ERU where it was a major cover type. Figure

65 provides an example of substantially increased

area of western juniper cover in a subwatershed 

of the Lower John Day subbasin in the Columbia

Plateau ERU. Oregon white oak cover increased

in the Northern Cascades ERU (see fig. 62). Fire

exclusion and grazing may be causes of the observed increase, but we were unable to directly

test this hypothesis.

Shrubland and herbland cover types—

Significant reductions in area and connectivity 

of shrubland cover types were noted in virtually

every ERU, but effects were most dramatic where

shrublands accounted for more than one-quarter

of the land area of an ERU (table 29). The largest

reductions in shrub cover types occurred in the

Columbia Plateau, Northern Great Basin, Owyhee Uplands, and Upper Snake ERUs. Significant

declines in shrub cover types also were observed

in the Blue Mountains, Snake Headwaters, and

Upper Klamath ERUs. In general, the most significant losses to shrublands were associated with

forest or woodland expansion as observed in the

Blue Mountains and Northern Great Basin ERUs,

cropland expansion as observed in the Northern

Great Basin ERU, and conversion to seminative

or nonnative herbland as observed in the Owyhee

Uplands or Snake Headwaters ERU.

Most shrubland cover in the Blue Mountains,

Columbia Plateau, Owyhee Uplands, and Upper

Snake ERUs resides below lower treeline, and in

each case, the most significant losses of shrub

cover occurred in these colline settings. Shrublands of the Northern Great Basin, Snake Headwaters, and Upper Klamath primarily occupy

montane settings. Cover types of these elevation

settings suffered the greatest losses.

In general, herbland cover increased throughout

the basin as a result of declining shrubland area,

but several important cover type losses were noteworthy. Bunchgrass cover declined significantly 

in several ERUs, notably the Columbia Plateau,

Northern Cascades, Northern Glaciated Mountains, Upper Clark Fork, and Upper Klamath

(table 29). Bunchgrass cover increased in the

229
Central Idaho Mountains, Northern Great Basin,

Snake Headwaters, and Upper Snake ERUs.

Exotic grass and forb cover increased in 9 of 13

ERUs. Significant increases in exotics in either

colline or montane settings occurred in the Blue

Mountains, Columbia Plateau, Northern

Cascades, Northern Great Basin, Owyhee

Uplands, Snake Headwaters, and Upper Clark

Fork ERUs. Figure 66 provides an example of

substantially increased area of exotic grass and

forb cover and reduced colline bunchgrass cover

in a subwatershed of the Upper Yakima subbasin

in the Northern Cascades ERU. Figure 67 provides an example of increased area of exotic grass

and forb cover, reduced montane low-medium

shrubland cover, and increased montane bunchgrass cover in a subwatershed of the Donner und

Blitzen subbasin in the Northern Great Basin

ERU. Ecological reporting units most affected 

by expansion of exotics were, in ascending order,

the Columbia Plateau, Northern Great Basin, and

Owyhee Uplands. Finally, postlogging grass-forb

cover increased in all forested ERUs and increased

significantly in all but the Lower Clark Fork and

Snake Headwaters ERUs. 

Nonforest-nonrange and other anthropogenic cover types—During the course of

our aerial photo research, we learned that early

historical photographs are rarely available for 

subwatersheds comprised primarily or entirely 

of private lands. We were usually able to obtain

adequate photographic coverage of a subwatershed when 30 percent or more of the land area

was publicly held. As a result, our analysis reflects,

at a minimum, change in area and connectivity 

of nonforest-nonrange and other anthropogenic

cover types when they occurred in subwatersheds

having substantial public land area. For this 

reason, we are concerned that some of our results

230

Figure 65—Historical and current maps of forest and woodland cover types in subwatershed 2701 in the Lower John Day subbasin of the Columbia Plateau ERU.
231

Figure 66—Historical and current maps of shrubland and herbland cover types in subwatershed y3 in the Upper Yakima subbasin of the Northern Cascades ERU.
may not truly represent changes occurring

throughout the total area of each cover type, 

and they therefore should be interpreted with

some caution.

Cropland area increased dramatically in two

ERUs: the Upper Klamath and the Upper Snake.

In the Upper Klamath, cropland area increased 

by 50 percent, rising from an average of 7.0 to

10.5 percent of the ERU; in the Upper Snake,

cropland area rose more than fourfold (448 percent) from an average of 2.7 to 12.1 percent of

the ERU. Figure 68 provides an example of substantially increased cropland area and reduced

shrubland and herbland area in a subwatershed 

of the Lake Walcott subbasin in the Upper Snake

ERU. Cropland area declined significantly only in

the Blue Mountains. Area in irrigated pastures increased in several ERUs, but only the increase

observed in the Northern Glaciated Mountains

was significant at P≤0.2 (see fig. 69). Urban and

rural developed area increased in half of the ERUs

during the sample period; increase was significant

in the Central Idaho Mountains, Northern

Cascades, Southern Cascades, and Upper Snake

ERUs. 

Postlogging of bare ground-burned area increased

significantly in several ERUs but, surprisingly,

declined in several others. Percentage of area

increased in the Blue Mountains, Central Idaho

Mountains, Northern Cascades, Snake Headwaters, Upper Clark Fork, and Upper Klamath

ERUs, and declined in the Northern Glaciated

Mountains and Southern Cascades ERUs. These

latter reductions suggested reduced slash burning

of postharvest fuels during the sample period and

regrowth of forests. 

232

Figure 67—Historical and current maps of shrubland and herbland cover types in subwatershed 0402 in the Donner und

Blitzen subbasin of the Northern Great Basin ERU.
Area of exposed rock declined in seven ERUs, 

but none so dramatically as the Upper Snake

where exposed rock area fell from an average of

6.8 to 2.6 percent of the ERU. Rock areas were

not converted directly to cropland as might be

superficially indicated in table 29 and appendix 2.

Transition analysis in the Upper Snake revealed

multiway transitions resulting in declining rock

area: areas of exposed rock were overgrown with

open-structured low-medium shrubs, but total

area in open low-medium shrubs transitioned to

open structured seminative and nonnative herblands, colline tall shrublands, and croplands to

result in a significant net decline.

Forest and woodland structure—In general,

the structure of current forests of sampled ERUs

was simpler when compared with historical

forests, but causal links with management are 

difficult to establish because the amount of fire

suppression or total timber harvest, for instance,

was not directly measurable or quantifiable. Still,

structural changes observed were consistent with

management activities implicated as primary factors in the overall simplification of the structural

complexity of basin forests; namely, timber 

harvest, fire suppression and exclusion, and grazing (Agee 1994, Everett and others 1994, Gast

and others 1991, Hessburg and others 1994,

Lehmkuhl and others 1994, O’Laughlin and 

others 1993).

Area in forest stand-initiation structures declined

significantly in four of nine chiefly forested ERUs

and increased significantly only in the Blue

Mountains (table 29 and appendix 2). Area in

stand-initiation structures declined significantly 

in the Central Idaho Mountains, Lower Clark

Fork, Northern Glaciated Mountains, and Upper

Clark Fork ERUs. Area in old-forest structures

declined in most forested ERUs, but the most significant declines occurred in the Blue Mountains,

Northern Cascades, Snake Headwaters, and

Upper Klamath ERUs. In general, area in the

233

Figure 68—Historical and current maps of shrubland, herbland, and anthropogenic cover types in subwatershed 0203 in the

Lake Walcott subbasin of the Upper Snake ERU. 
234

Figure 69—Historical and current maps of shrubland, herbland, and anthropogenic cover types in subwatershed 0701 in the

Lower Flathead subbasin of the Northern Glaciated Mountains ERU.
235

middle-aged, or more precisely, intermediate 

(not new and not old forest) structural classes

(stem exclusion, understory reinitiation, and

young multistory) increased in most forested

ERUs; the most notable increases occurred in 

the Blue Mountains, Central Idaho Mountains,

Columbia Plateau, Lower Clark Fork, Northern

Glaciated Mountains, Snake Headwaters,

Southern Cascades, and Upper Clark Fork ERUs.

Area in intermediate structural classes actually

declined in the Upper Klamath ERU, where most

evidence suggested extensive past harvesting.

Blue Mountains ERU—Forests of the Blue

Mountains ERU are comprised primarily of dry

and mesic potential vegetation types (see fig. 70

and Hann and others 1997). Historical fire regimes resulted in predominantly nonlethal surface

fires with frequent (26 to 75 years) to very frequent (0 to 25 years) return intervals (see fig. 71,

A and B, and Hann and others 1997). Nearly

one-half of historical forest cover was ponderosa

pine (table 29 and appendix 2). 

Evidence from this analysis suggests that fire

exclusion, timber harvest, and grazing each had 

a pronounced effect on current forest composition and structure. In the historical condition, 

we would have expected stand-initiation structures to occupy a relatively minor fraction of 

Blue Mountains forest landscapes, because surface

fire regimes with frequent fire return typically

regenerate forests continually via individual tree

and small group killing. Area in stand-initiation

structures increased from an average historical

level of 3.9 to 6.5 percent of the ERU in the current condition, most likely as a result of regeneration harvests and removal cuttings (table 27) that

occurred during the sample period. Figure 72

provides an example of increased area of standinitiation structures in a subwatershed of the

Lower Grande Ronde subbasin. In our historical

vegetation condition, old forests comprised 4.9

percent of the ERU area, or 7.8 percent of the

total forest. Selective harvests have diminished

that area to a small remnant (fig. 72). Decline in

area occupied by medium (40.5 to 63.5 cm d.b.h.)

and large (> 63.5 cm d.b.h.) trees was perhaps the

single greatest change occurring to all forest structures in the Blue Mountains (tables 21 and 22).

In the historical condition, 39.6 percent of the

ERU area (63 percent of forest area) was occupied

by forest structures comprised of medium and

large trees. In the current condition, 27.2 percent

of the ERU area (42 percent of the forest) is occupied by forest structures comprised of medium

and large trees.

For the Blue Mountains, we predicted that stem

exclusion-open canopy structures were common

in the historical vegetation coverage because environmental settings that support dry PVTs often

are severely moisture limited. Full site occupancy

with less than 100 percent crown cover is the

result of limited soil moisture, competition from

native early seral grasses and shrubs, and frequent

surface fires. Area in open-canopy, stem-exclusion

structures declined significantly during the sample

period. Results suggested that timber harvest, fire

exclusion, and domestic livestock grazing activities

were associated with the decline (see Oliver and

others 1994; Skovlin and Thomas 1995; Wissmar

and others 1994a, 1994b). Selective harvest of

medium and large trees in a management context 

of fire control and extensive sheep and cattle grazing would promote development of more total

crown cover (table 22), less grass-forb and shrub

understory cover and greater conifer understory

cover (table 25), increased vertical complexity of

forest canopies (table 23), and increased cover of

shade-tolerant understories (table 24). Each of

these changes was observed. In addition, extensive

grazing would minimize flashy fuel cover (Agee

1993, 1994), thereby increasing opportunities for

conifer understory development via reduced competition for site resources and reducing the likelihood of surface fires from natural or humancaused ignitions.

Area in understory reinitiation structures declined

for similar reasons. Repeated partial cutting in a

context of cattle grazing and fire exclusion created

increasing area of young multistory structure by

encouraging pulsed regeneration and release of

shade-tolerant conifers. During the sample period, area in young multistory structures increased

from one-third to one-half of the forest area (table

29 and appendix 2). We were surprised to find

such an extensive area in young multistory forest

structures in our historical coverage. We suggest
236

Figure 70—Broadscale (1-km2 pixels) map of current potential vegetation groups within the interior Columbia River basin

assessment boundary. See Hann and others (1997) for map development procedures.
237

three possible explanations: (1) ongoing insect,

pathogen, and fire disturbances exerted a greater

mortality influence on overstory structure than we

had anticipated, such that large tree structure was

not dominant; (2) some areas were affected by

partial cutting before the time of our historical

coverage, and we were not able to determine by

remote sensing any associated road, skid trail, or

harvest signature; and (3) some structures classified as young multistory by virtue of their size

may be older than they appear.

Blue Mountains woodlands are composed primarily of western juniper. During the sample period,

stem-exclusion structure increased sharply by 67

percent from an average of 2.4 to 4.0 percent of

the ERU. Connectivity of stem-exclusion structure also increased (appendix 2). We believe that

expansion of western juniper cover and the associated stem-exclusion structure was the result of fire

exclusion and grazing. Grazing minimized herbaceous competition and the possibility of surface

fires, and fire exclusion enabled uninhibited

expansion of juniper cover. 

Central Idaho Mountains ERU—Forests of

the Central Idaho Mountains are comprised primarily of cold and moist PVTs (see fig. 70 and

Hann and others 1997). Historical fire regimes

were predominantly of mixed severity with infrequent (76 to 150 years) to very infrequent (151

to 300 years) fire return intervals (see fig. 71, A

and B, and Hann and others 1997). Historical

forest cover was dominated by upper montane

and subalpine species such as Engelmann spruce,

subalpine fir, lodgepole pine, grand fir, and

Douglas-fir (table 29 and appendix 2). Our

results suggest that fire suppression and exclusion

were primary factors responsible for current forest

composition and structure. Road densities are

among the lowest of any forested ERU (see fig. 73

and Hann and others 1997), and wilderness and

roadless area is greatest of any forested ERU. In

our historical vegetation condition, we would

have expected stand-initiation structures to represent a relatively large fraction of Central Idaho

Mountains forest landscapes because mixed severity fires with infrequent fire return typically create

a mosaic of underburned and regenerated patches

of new forest. Area in stand-initiation structures

declined during the sample period by 39 percent,

from an average historical level of 9.7 percent of

the ERU to 5.9 percent. We believe the observed

decline occurred primarily as a result of effective

fire prevention and suppression efforts and 

secondarily as a consequence of fire exclusion.

Although timber harvest activities and road network development were evident, most of these

activities were associated with dry and moist 

forest settings of lower and middle montane 

environments or were in areas with extensive

lodgepole pine cover that had been attacked by

bark beetles and salvage logged or regenerated. 

A large, intact, interior core area of the ERU

comprised mainly of cool and cold upper montane and subalpine forests was mostly unroaded

and had not been entered for timber harvest.

In our historical vegetation condition, old forests

comprised 3.2 percent of the ERU area, or 4.4

percent of the total historical forest. Old-forest

area in the current condition was essentially

unchanged. Likewise, area with large trees,

whether in old forest or associated with other 

forest structures, was unchanged (table 20). Area

with medium and large trees increased significantly during the sample period (table 21). In the historical condition, 23.5 percent of the ERU area

(32 percent of the forest) was occupied by forest

structures comprised of medium and large trees.

In the current condition, 25.8 percent of the

ERU (35 percent of the forest) is occupied by 

forest structures comprised of medium and large

trees.

Area in understory reinitiation structures increased significantly during the sample period 

to become the dominant structural component 

of Central Idaho Mountains forests in the current

condition. We believe that the observed increase

in understory reinitiation structure was the result

of fire exclusion: areas regenerated by fire before

our historical coverage have regrown. In the

absence of fire, we predict a correlated decline 

in area and connectivity of early seral shrub 

and herb structures in forest potential vegetation

settings.
238
239

Figure 71—Broadscale (1-km2 pixels) map of (A) historical and (B) current fire regimes within the interior Columbia River

basin assessment boundary. See Hann and others (1997) for map development procedures. Lethal = stand-replacing fire that kills

> 70 percent of the overstory tree basal area; nonlethal = fire that kills < 20 percent of the overstory tree basal area; mixed = fire

that kills 20 to 70 percent of the overstory tree basal area; and rarely burns = fire seldom occurs. Very frequent = 0- to 25-year

mean fire-return interval; frequent = 26- to 75-year mean fire-return interval; infrequent = 76- to 150-year mean fire-return

interval; very infrequent = 151- to 300-year mean fire-return interval; and extremely infrequent = > 300-year mean fire-return

interval. 
Columbia Plateau ERU—Forests of the

Columbia Plateau ERU are comprised of dry 

and moist potential vegetation types. Historical

fire regimes were predominantly nonlethal with

very frequent (0 to 25 years) fire return intervals

(see fig. 70 and Hann and others 1997). The

majority of historical forest cover was ponderosa

pine and Douglas-fir (table 29 and appendix 2).

Before European settlement, the Columbia

Plateau contained the largest expanses of native

grasslands in the whole of the Columbia River

basin (see fig. 74 and Hann and others 1997).

During the period of settlement, even to the current day, these grasslands and shrublands have

been converted to dryland and irrigated agriculture and pasturelands (fig. 70). Presettlement

herblands burned frequently, and fires often

spread to lower and mid montane dry forests

(Arno 1980). With herbland conversion to agriculture, dry and mesic forests of the Columbia

Plateau became isolated from fires that had 

commonly originated in herbland and shrubland

settings. Fire prevention and suppression efforts

minimized the incidence of fires originating from

within, especially adjacent to human settlements.

In the absence of fires from once adjacent herblands, and in the context of aggressive fire suppression, forest area expanded by 11 percent,

from an average of 26.1 to 29.1 percent of 

the ERU, and juniper woodlands expanded by 

82 percent, from an average of 6.7 to 12.2 percent of the ERU. We expected to see significantly

increased total tree crown cover in forest settings

(table 22).

240

Figure 72—Historical and current maps of forest and woodland structural classes in subwatershed 21 in the Lower Grande

Ronde subbasin of the Blue Mountains ERU.
241

Figure 73—Broadscale (1-km2 pixels) map of current predicted road density classes within the interior Columbia River basin

assessment boundary. See Hann and others (1997) for map development procedures. None = 0 to 0.01 km/km2; very low =

0.01 to 0.06 km/km2; low = 0.06 to 0.43 km/km2; moderate = 0.43 to 1.06 km/km2; high = 1.06 to 2.92 km/km2; and very

high = > 2.92 km/km2. 
242

Figure 74—Broadscale (1-km2 pixels) map of historical potential vegetation groups within the interior Columbia River basin

assessment boundary. See Hann and others (1997) for map development procedures. 
243

Evidence from these analyses suggests that agriculture, fire exclusion, timber harvest, and grazing

each had an effect on existing forest structure. In

the historical condition, we expected stand-initiation structures to occupy a minor fraction of

Columbia Plateau forest landscapes because surface fire regimes continuously regenerated multicohort forests dominated by early seral species.

Historical area in stand-initiation structures was

2.3 percent of the ERU and remained stable during the sample period. In our historical vegetation

condition, old forests comprised 3.4 percent of

the ERU, or 13 percent of the total forest. Selective harvests have diminished that area to a small

remnant in the existing condition. Selective harvest of medium and large trees in a management

context of fire control and grazing would promote

development of more total crown cover (table

22), less grass-forb and shrub understory cover

and greater conifer understory cover (table 25),

increased vertical complexity of forest canopies

(table 23), and increased cover of shade-tolerant

understories (table 24). All but one of these

changes were observed; grass-forb and shrub

understory cover actually increased during the

sample period. Transition analysis revealed that

such increase was associated with expanding forest

and woodland in former native herbland and

shrubland areas (table 24 and appendix 2).

For the Columbia Plateau, we predicted that stem

exclusion-open canopy structures were common

in the historical condition because dry potential

vegetation types are typically moisture limited,

and surface fire regimes tend to maintain open

stand conditions and dry site climate. Area in

open canopy, stem-exclusion structures was 6.7

percent of the ERU in the historical condition

and remained stable during the sample period.

During the sample period, area in young multistory structures increased from 28 to 34 percent

of the forest area (table 29 and appendix 2).

Figure 75 provides an example of increased area

of young multistory structure in a subwatershed

of the Lower John Day subbasin. We were again

surprised to find such an extensive area in young

multistory forest structures in our historical 

coverage. As suggested for the Blue Mountains,

we believe that it is likely that ongoing insect,

pathogen, and fire disturbances exerted a greater

mortality influence on overstory structure than 

we had anticipated, such that large tree structure

was not dominant; that is, it did not exceed 24

percent crown cover. Large and medium trees 

are those most likely to be old and decadent or

declining in vigor, and such trees are the most

probable targets of tree-killing bark beetles that

favor vigor-depressed hosts. Dry ponderosa pine

forests often are afflicted with western dwarf

mistletoe and S-group annosum root disease,

pathogens of ponderosa pine of any age. Forests

such as these are especially sensitive to dry growing seasons, winter desiccation injury, and protracted droughts. Pine bark beetles have ample

opportunities to capitalize on hosts vigor-depressed from a variety of independent or interacting factors. It is also possible that some areas were

affected by partial cutting before the period of our

historical coverage, and we were not able to detect

the logging entry, and some structures classified 

as young multistory by virtue of their size may be

older than they appear.

Western juniper woodland cover in the Columbia

Plateau nearly doubled in the interval between

our historical and current vegetation conditions.

Nearly all change in woodland structure was associated with stem-exclusion structures, which increased from an average of 5.9 to 10.9 percent 

of the ERU (fig. 75). Connectivity of woodland

stem-exclusion structure also increased dramatically (appendix 2); mean patch size rose from

63.8 to 152.7 ha, representing a 239-percent rise

for the period. In the absence of fire and under

the influence of grazing, we expected increases 

in both the stem-exclusion and understory reinitiation structures (table 29).

Lower Clark Fork ERU—Forests of the Lower

Clark Fork are comprised primarily of moist

PVTs (see fig. 70 and Hann and others 1997).

Historical fire regimes were predominantly lethal

crown fires and of mixed severity with fire frequencies ranging broadly from very frequent (0 

to 25 years) to extremely infrequent (> 300 years)

(see fig. 71, A and B, and Hann and others

1997). Historical forest cover was dominated 

by grand fir, Douglas-fir, western hemlock, and

western redcedar (table 29 and appendix 2). Our
results suggest that timber harvest, fire suppression, and fire exclusion were primary factors

responsible for current forest composition and

structure. Road densities are high throughout the

ERU (see fig. 73 and Hann and others 1997),

and there is scant roadless area.

From our historical vegetation condition, we

expected stand-initiation structures to represent 

a large fraction of Lower Clark Fork forest landscapes, and indeed they did, because a sizable area

was burned just before and after the start of the

20th century. In the historical condition, standinitiation structures occupied 32.7 percent of the

ERU area (35.7 percent of the forested area). Area

in stand-initiation structures declined during the

sample period by 71percent, plummeting to an

average of 9.5 percent of the ERU in the current

condition. We believe the observed decline occurred primarily as a result of effective fire prevention and suppression efforts. Figure 76 provides an example of substantially reduced area of

stand-initiation structures in a subwatershed of

the Upper Coeur d’Alene subbasin. Also noteworthy, among ERUs, area affected by regeneration harvesting increased most significantly in the

Lower Clark Fork (table 27). While small staggered-setting clearcut and shelterwood harvest

units were increasing in abundance, area of standinitiation structure declined on nearly one-quarter

of the land area of the ERU. These results clearly

244

Figure 75—Historical and current maps of forest and woodland structural classes in subwatershed 2701 in the Lower John Day

subbasin of the Columbia Plateau ERU.
245

suggest that small, regularly sized and shaped

clearcut harvest units are not an adequate substitute for larger scale disturbance events that leave

coarse-grain patterns on affected landscapes.

In our historical vegetation condition, old forests

comprised 2.4 percent of the ERU area, or 2.6

percent of the total historical forest. Area of old

forest in the current condition was essentially

unchanged (table 29 and appendix 2). Likewise,

area with large trees, whether in old forest or associated with other forest structures, was unchanged

(table 20). Area with medium and large trees

increased significantly during the sample period

(table 21); we believe the observed increase was

associated with fire exclusion and subsequent 

succession and aging of forests. In the historical

condition, 21.8 percent of the ERU area (23.8

percent of the forest) was occupied by forest

structures comprised of medium and large trees.

In the current condition, 36.8 percent of the

ERU area (38.9 percent of the forest) was occupied by forest structures comprised of medium

and large trees.

Area in understory reinitiation structures increased quite significantly during the sample 

period to become the dominant structural feature

of Lower Clark Fork forests in the current condition. We believe, and transition analysis confirmed, that the observed increase in understory

reinitiation structure was the result of fire exclusion: areas regenerated by fire before our historical 

coverage have regrown.

Table 27 shows that at the starting point of our

historical vegetation coverage, nearly 22 percent

of the ERU area had been influenced by selective

harvest entry. In the current condition, area

Figure 76—Historical and current maps of forest and woodland structural classes in subwatershed 1401 in the Upper 

Coeur d'Alene subbasin of the Lower Clark Fork ERU. 
affected by selective harvesting fell to 16.4 percent, but the change was not statistically significant. Such extensive selective harvesting in a

management context of fire suppression would

promote development of more total crown cover

(table 22), less grass-forb and shrub understory

cover and greater conifer understory cover (table

25), increased vertical complexity of forest canopies (table 23), and increased cover of shade-tolerant understories (table 24). All these changes were

observed. 

Northern Cascades ERU—Forests of the

Northern Cascades are comprised primarily of

moist and cool to cold PVTs (see fig. 70 and

Hann and others 1997), with dry and mesic types

represented on the eastern fringe. Historical fire

regimes were predominantly of mixed severity

with infrequent (76 to 150 years) to frequent (26

to 75 years) fire return intervals (see fig. 71, A

and B, and Hann and others 1997). Surface fire

regimes represented a relatively modest area where

ponderosa pine was a major early seral species.

Fire return intervals in areas with surface fire

regimes were frequent (26 to 75 years) and very

frequent (0 to 25 years).

Forests of the Northern Cascades are among the

most varied in composition of all forests in the

basin, with most east- and west-slope Cascade

Range conifers represented. Historical forest cover

was dominated by Douglas-fir, Engelmann

spruce, subalpine fir, ponderosa pine, lodgepole

pine, Pacific silver fir, western hemlock, and western redcedar (appendix 2 and table 29). Results

from our analysis suggest that fire exclusion and

suppression and timber harvest were primary 

factors responsible for current forest composition

and structure.

Road densities are very low in upper montane 

and subalpine settings, increasing in density with

decreasing elevation (see fig. 73 and Hann and

others 1997). Wilderness and roadless areas are

associated with upper montane and subalpine settings. Change in area of forest structures in the

Northern Cascades was relatively minor in comparison with that observed in other forested

ERUs. But change in connectivity of forest structures was among the most significant (appendix

2). We speculate that the observed reduction in

grain of Northern Cascades forest landscapes was

the result of excluding fire, an agent of relatively

coarse grain pattern formation, and introducing

comparatively fine-grained selection cutting and

staggered setting regeneration harvests (Franklin

and Forman 1987).

Relative to fire disturbances, forest landscapes 

of the Northern Cascades appear to be more synchronous today than they were in the historical

condition (Ottmar and others, in prep.). Here

and elsewhere in the basin, many environments

that once supported mixed severity fire regimes

today support lethal crown fire regimes. Most

environments that once supported lethal crown

fire regimes still support lethal regimes, but it is 

as yet unknown whether fire behavior attributes

under a wildfire burn scenario are any longer

comparable with those of the historical condition.

In the Northern Cascades, fire-free intervals have

lengthened dramatically in nearly all environmental settings. Thus, in a management context of

active fire prevention and suppression, climatedriven fires predominate. Climate cycles ordinarily drive fire cycles, especially in areas dominated

by mixed and lethal crown fire regimes. But, in

the historical condition, depending on the condition of forests in any given landscape, the results

of an extended dry climatic period and its associated fires may have been large areas of old forest,

a variable patchwork of forest structural conditions, or large areas of young, early seral forest 

or shrubland. In the current condition, the likelihood of extensive stand replacement is high. 

From our historical vegetation condition, we

expected that stand-initiation structures would

represent a relatively large fraction of Northern

Cascades forest landscapes because mixed severity

fires typically regenerate patches of new forest.

Area in stand-initiation structures remained relatively constant during the sample period as a

result of regeneration harvests, patch clearcutting,

and removal cutting (table 27). In the historical

vegetation condition, old forests comprised 10.1

percent of the ERU area, or 12.8 percent of the

total forest area. Selective and regeneration harvests have diminished that area by one-half.

Decline in area occupied by medium and large

246
247

trees associated with all forest structures also was

significant (tables 20 and 21). In the historical

condition, an average of 41.9 percent of the ERU

(53 percent of the forest) was occupied by forest

structures comprised of medium and large trees.

In the current condition, 37.9 percent of the

ERU (48.5 percent of the forest) is occupied by

forest structures comprised of medium and large

trees.

Oregon white oak woodland cover increased by

50 percent during the interval between our historical and current vegetation coverages, and total

woodland area more than doubled, rising from

0.3 to 0.7 percent of the ERU. Nearly all change

in area of woodland structure was associated with

stem-exclusion structures, which increased from

an average of 0.3 to 0.6 percent of the ERU.

Connectivity of woodland stem-exclusion structure also increased; patch density rose from 1.0 to

1.7 patches per 10 000 ha, and mean patch size

rose nearly threefold from 2.3 to 6.3 ha. In the

absence of fire, and under the influence of grazing, we expected increases in both the stem-exclusion and understory reinitiation structures. 

Northern Glaciated Mountains ERU—

Forests of the Northern Glaciated Mountains are

comprised primarily of moist and dry PVTs (see

fig. 70, and Hann and others 1997), but cold

types are present throughout and are especially

dominant in the eastern portion of the ERU in

the North, Middle, and South Fork Flathead

River drainages. Historical fire regimes were 

predominantly of mixed severity in the eastern

two-thirds of the ERU, with fire return intervals

ranging from 0 to 300 years (see fig. 71, A and

B, and Hann and others 1997). Surface fire

regimes characterized the western third of the

ERU, including the Okanogan Highlands, from

the Okanogan River drainage east to the Kettle

and Sanpoil River drainages in Washington State,

and the Lower Flathead River area in northwestern Montana. Fire return intervals ranged from 

0 to 150 years. Historical forest cover was dominated by species such as Douglas-fir, western

larch, ponderosa pine, Engelmann spruce, subalpine fir, and lodgepole pine (table 29 and

appendix 2). Our results suggest that fire exclusion and suppression and timber harvest were 

primary factors responsible for current forest

composition and structure. Road densities are

high throughout forests of the ERU (see fig. 73

and Hann and others 1997), and wilderness and

roadless area of any consequence is present only

in the Swan River drainage and in the North,

Middle, and South Fork Flathead River drainages

on the eastern edge of the ERU.

Given the historical vegetation condition, we

expected stand-initiation structures to represent 

a relatively large fraction of Northern Glaciated

Mountains forest landscapes because of the large

area of mixed severity fire regimes. Area in standinitiation structures declined during the sample

period from an average historical level of 16.9 to

9.4 percent of the current ERU area. We believe

the observed decline occurred primarily as a result

of effective fire prevention and suppression efforts

and fire exclusion. In our starting point historical

coverage, stand-initiation structures occupied 21

percent of the forest area. In the current condition, stand-initiation structures occupied 12 percent of the forest area. Also noteworthy, area

affected by regeneration harvests increased more

than threefold from an average of 2.3 to 7.9 percent of the ERU (table 27). Small staggered-setting clearcut and shelterwood harvest units

increased in abundance, and area of stand-initiation structures precipitously declined.

In our historical vegetation condition, old forests

comprised 1.2 percent of the ERU, or 1.5 percent

of the total historical forest. Area of old forest in

the current condition was essentially unchanged.

Likewise, area with large trees, whether in old forest or associated with other forest structures, was

unchanged (table 20). Area with medium and

large trees increased significantly during the sample period (table 21). In the historical condition,

22 percent of the ERU area (27 percent of the

forest) was occupied by forest structures comprised of medium and large trees. In the current

condition, 24.2 percent of the ERU (30 percent

of the forest) was occupied by forest structures

comprised of medium and large trees.
Area in understory reinitiation structures increased significantly during the sample period 

to become the dominant structural feature of

Northern Glaciated Mountains forests in the 

current condition. We believe that the observed

increase in understory reinitiation structure is the

result of fire exclusion and selective harvesting

(table 27): areas regenerated by fire before the 

historical coverage have regrown, and partial cut

areas have partially regenerated. Area in stemexclusion closed canopy structures also increased

significantly. In the current condition, 87 percent

of forest structure is intermediate (stem-exclusion,

understory reinitiation, or young multistory), 

1 percent is old, and 12 percent is new forest. 

In appendix 2, we see that the connectivity of

most major forest cover types and structural classes declined significantly. In most cases, patch 

density increased, and mean patch size declined.

Our results suggest that these changes are characteristic of the combined effects of not only fire

exclusion but also regeneration and selective harvesting at scales differing from natural disturbance

patterns. Area and connectivity of most of the

major early seral species declined (timber harvest),

area of new forest structure declined, and area of

intermediate forest structure increased (fire exclusion and timber harvest). Figure 77 provides an

example of increased patch density and reduced

patch size of forest structures in a subwatershed 

of the Pend Oreille subbasin.

Northern Great Basin ERU—In the portion 

of the Northern Great Basin that we sampled,

forests were comprised primarily of hardwoods,

which occupy about 7 percent of the ERU land

area. Forest structure is open because growing

conditions are severely moisture limited. No

changes in forest structure were noteworthy, but

woodland structure did change significantly (table

29 and appendix 2). Woodlands in this ERU are

comprised of western juniper, and they are also

248

Figure 77—Historical and current maps of forest and woodland structural classes in subwatershed 09 in the Pend Oreille subbasin of the Northern Glaciated Mountains ERU. 
249

severely moisture limited. In our historical coverage, most woodlands were characterized as stemexclusion structure. Area in woodland stemexclusion structure increased by 45 percent from

an average of 15.3 to 22.2 percent of the ERU.

We were surprised that we did not observe a significant reduction in patch density and a significant rise in mean patch size. In fact, connectivity

of woodland structure did not change during the

sample period.

Owyhee Uplands ERU—According to our

sample, forests represent less than 1 percent of the

ERU area. No changes in forest structure were

significant or noteworthy, but woodland structure

did change significantly (table 29 and appendix

2). Woodlands in this ERU are comprised of

western juniper and are severely moisture limited.

In our historical coverage, most woodlands were

characterized as stem-exclusion structure. Area 

in woodland stem-exclusion structure increased

25 percent from an average of 5.2 to 6.5 percent

of the ERU. Total area of juniper cover increased

by 36 percent from a historical average of 5.5 to

7.5 percent of the ERU in the current condition.

Most of the increase was from stem-exclusion

structure. Patch density of stem-exclusion structure declined and mean patch size increased, as

was expected. Our results suggest that under the

influence of fire exclusion and grazing, most of

the observed increase in woodland structure was

associated with conversion of shrubland to woodland.

Snake Headwaters ERU—Forests of the Snake

Headwaters are comprised primarily of cold and

dry potential vegetation types (see fig. 70 and

Hann and others 1997). Historical fire regimes

were predominantly lethal crown fire with infrequent (76 to 150 years) to very infrequent (151

to 300 years) fire return intervals (see fig. 71, A

and B, and Hann and others 1997). Forest cover

was dominated by upper montane and subalpine

species. Nearly two-thirds (63 percent) of historical forest cover consisted of subalpine fir, Engelmann spruce, lodgepole pine, and whitebark pine

(table 29 and appendix 2). Montane environments were dominated by Douglas-fir and aspen.

Our results suggest that fire exclusion and timber

harvest were primary factors responsible for current forest composition and structure. Road densities are relatively low throughout much of the

ERU (see fig. 73 and Hann and others 1997),

and large wilderness and roadless areas are present

in the Snake Headwaters, Gros Ventre, Lower

Henry’s, Grey’s-Hobock, and Palisades subbasins.

In the historical condition, we would have expected stand-initiation structures to occupy a relatively small fraction of forest landscapes because fire

return intervals were quite long and forest regeneration appears to be primarily event driven rather

than continual. Area in stand-initiation structures

remained unchanged (table 29), but connectivity

of area increased (appendix 2). Area affected by

regeneration harvests and small patch clearcutting

increased from an average of 0 to 1.4 percent of

the ERU (table 27). It was apparent that area

affected by regeneration harvests increased during

the sample period, and area with no visible logging declined from an average of 74.7 to 72.4

percent of the ERU (the forested proportion of

the land area of the ERU); the change was not

statistically significant at P≤0.2 (table 27). In our

historical vegetation condition, old forests comprised 5.2 percent of the ERU area, or 7 percent

of the total forest. Harvesting had diminished

that area by 40 percent in the current condition

(table 20).

For the Snake Headwaters, we predicted that stem

exclusion-open canopy structures would be quite

common in the historical vegetation coverage

because both dry and cold PVTs of the area often

are moisture limited. Area in open and closed

canopy, stem-exclusion structures declined significantly during the sample period from an average of 19.1 to 15.3 percent and from 7.9 to 4.8

percent of the ERU, respectively. Results suggest

that harvest of lodgepole pine and mountain pine

beetle mortality were associated with the decline

(tables 21, 22, and 25 and appendices 2 and 3). 

A management context of fire exclusion would

have encouraged development of increased vertical complexity of forest canopies (table 23),

greater conifer understory cover (table 25), less

grass-forb and shrub understory cover, and

increased cover of shade-tolerant understories

(table 24). All these changes were observed.
During the sample period, area in young multistory structures increased from one-quarter to

nearly one-third of the forest area (table 29). We

were again surprised to find such an extensive area

in young multistory forest structures in our historical coverage. We suggest that two of three

aforementioned explanations apply: (1) ongoing

insect and pathogen disturbances in the interval

between fires exerted a greater influence on landscape structure than we had anticipated; and (2)

structures classified as young multistory by virtue

of their size are much older than they appear,

especially in the cold upper montane and subalpine environments of this ERU. 

Southern Cascades ERU—Forests of the

Southern Cascades are comprised primarily of

moist and dry potential vegetation types (see fig.

70 and Hann and others 1997), with cold types

well represented on the western fringe adjacent to

the crest of Cascade Range but accounting for less

than one-third of the area. Historical fire regimes

were predominantly nonlethal surface fire or of

mixed severity with fire return intervals mostly

ranging from 0 to 150 years (see fig. 71, A and B,

and Hann and others 1997). Surface fire regimes

represented a large area, especially where ponderosa pine was historically a major early seral

species. Very frequent (0 to 25 years) fire return

was common across more than half of the ERU 

in areas of surface and mixed severity fire.

As in the northern Cascades, forests of the southern Cascades are highly varied in composition,

with many east- and west-slope Cascade Range

conifers represented. Historical forest cover was

dominated by mountain hemlock, ponderosa

pine, lodgepole pine, grand fir, white fir, Douglasfir, and a wide assortment of other less abundant

species such as Shasta red fir, incense-cedar, sugar

pine, western white pine, Engelmann spruce, and

subalpine fir (table 29 and appendix 2). Our

results suggest that timber harvest, fire suppression, and fire exclusion were primary factors

responsible for current forest composition and

structure. Road densities are very high throughout

the ERU (see fig. 73 and Hann and others 1997).

Wilderness and roadless areas are relatively small

and are in subalpine and alpine environmental

settings along the Cascade crest. 

Change in area of forest structures was relatively

minor in comparison with observed changes in

other forested ERUs. Reduced connectivity of forest structures was quite significant (appendix 2).

We speculate that the observed reduction in grain

of Southern Cascades ERU forest landscapes was

the result of several interacting factors, including

extensive road network development (fig. 73 and

Hann and others 1997), selection cutting (table

27), and fire exclusion (see fig. 71, A and B).

In the historical vegetation condition, we expected that stand-initiation structures would represent

a relatively large fraction of Southern Cascades

forest landscapes because mixed severity fires typically regenerate variable-sized patches of new forest. Despite fire suppression efforts, area in standinitiation structures remained relatively constant

during the sample period as a result of regeneration harvests, patch clearcutting, and removal or

heavy selection cutting (table 27), but connectivity sharply declined (appendix 2). Patch density

increased sharply by 357 percent from 6.8 to 

24.3 patches per 10 000 ha, and mean patch size

declined by 56 percent from 171.5 to 75.4 ha.

Clearly, stand-replacement disturbances early in

the 20th century occurred at a much larger scale

than those witnessed today.

In our historical vegetation coverage, old forests

comprised 2.3 percent of the ERU area, or 2.9

percent of the total forest area. Area of old singlestory and old multistory forest structures more

than doubled during the sampling period (appendix 2), but area with remnant large trees associated with structures other than old forest (table 20)

declined by 42 percent from an average of 5.2 

to 3.0 percent of the ERU (ns). Area occupied 

by medium and large trees associated with all 

forest structures increased by 10 percent during

the sample period (table 21). In the historical

condition, 40.3 percent of the ERU area (50.1

percent of the forest area) was occupied by structures with medium or large trees. In the current

condition, 44.3 percent of the ERU (50.2 percent

of the forest) is occupied by forest structures comprised of medium or large trees. But average area

in the forest physiognomic type rose by 10 percent from an average of 80.5 to 88.3 percent of

the ERU, mainly as a result of regrowth of large

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251

areas clearcut harvested before our historical vegetation coverage. We speculate that this area likely

was dominated by patches with large ponderosa

pine trees and old single-story structures.

Considering the dominant cover types and PVTs

displayed in this ERU, we were surprised to see

the relatively minor area in stem-exclusion closed

canopy structures in the historical vegetation coverage. With regrowth of clearcut areas apparent in

the historical vegetation coverage, we expected to

see greater increase in area of this structure. About

20 percent of the ERU is currently comprised of

the lodgepole pine cover type; a comparable portion was present in the historical starting point

vegetation coverage (appendix 2). Much of the

area of the lodgepole pine cover type resides on

deep pumice flats where cold air ponding and

early or late hard frosts are a common occurrence. In these locations, lodgepole pine is often

described as an edaphic “climax” dominant. We

expected to observe a considerable area of closed

canopy stem-exclusion structure in these locations, but did not. We suspect that a rather simple explanation may account for the apparent

absence of this structure in our historical coverage: we know that large landscape-scale mountain

pine beetle outbreaks are responsible for coarseand medium-grain pattern changes in lodgepole

forests, but fine-grain, patch-scale mountain pine

beetle disturbances may be more common than

we suspected and may sum to highly significant

change in landscape patterns. We, and others,

perhaps have simplified our understanding of the

relation between lodgepole pine forests, mountain

pine beetles, and regenerative fires. Indeed, we

observed that 46 percent of the ERU (57 percent

of the forest) was comprised of young multistory

structures in the historical coverage, and a comparable amount was present in the current 

condition. Young multistory structure is the structure we expected in great abundance where finegrain disturbances are the norm and overstory

dominance of large trees is seldom achieved. 

Nearly all change in woodland was associated

with stem-exclusion structures that increased in

area from 0 to 0.4 percent of the ERU. Connectivity of woodland stem-exclusion structures also

increased. In the absence of fire, and under the

influence of domestic livestock grazing, we

expected increases in both the woodland stemexclusion and understory reinitiation structures. 

Table 27 shows that at the start of our historical

vegetation coverage, 9.2 percent of the ERU area

had been influenced by selective harvest entry. In

the current condition, area affected by selective

harvesting rose to an average of 23.2 percent of

the ERU. Such extensive selective harvesting in a

management context of fire prevention and suppression promotes development of more total tree

crown cover (table 22), increased vertical complexity of forest canopies (table 23), and increased

cover of shade-tolerant understories (table 24). 

All these changes were observed. 

Upper Clark Fork ERU—Forests of the Upper

Clark Fork are comprised primarily of cold and

dry PVTs (see fig. 70 and Hann and others 1997).

Historical fire regimes were predominantly nonlethal surface fire or of mixed severity with fire

return intervals typically ranging from 0 to 150

years (see fig. 71, A and B, and Hann and others

1997). Surface fire regimes represented a large

area, especially where ponderosa pine or Douglasfir historically were major early-seral species. Very

frequent (0 to 25 years) and frequent (26 to 75

years) fire return was common over more than

half of the ERU in areas prone to surface and

mixed severity fire.

Historical forest cover was dominated by species

such as Douglas-fir, lodgepole pine, Engelmann

spruce, subalpine fir, ponderosa pine, whitebark

pine, subalpine larch, and western larch (table 29

and appendix 2). Our results suggest that fire

exclusion and suppression and timber harvest

were primary factors responsible for current forest

composition and structure. Road densities are

moderately high throughout montane forests of

the ERU (see fig. 73 and Hann and others 1997),

and wilderness or roadless areas are small and in

subalpine and alpine environmental settings.

In the historical vegetation condition, we expected stand-initiation structures to represent a relatively large fraction of Upper Clark Fork forest

landscapes because of the large area of mixed

severity fire regimes with infrequent fire return

intervals. Area in stand-initiation structures
declined during the sample period by 30 percent

from a historical level of 15.9 to 11.1 percent of

the ERU in the current condition. Evidence suggests that the observed decline occurred primarily

as a result of fire suppression and fire exclusion.

In our historical coverage, stand-initiation structures occupied 18 percent of the forest area. In

the current condition, stand-initiation structures

occupied 12.9 percent of the forest area. Also

noteworthy, area affected by regeneration harvesting increased significantly from an average of 5.5

to 11.6 percent of the ERU (table 27). Small,

staggered-setting clearcut and shelterwood harvest

units increased in abundance, and area of standinitiation structures declined.

In the historical condition, old forests comprised

0.8 percent of the ERU, or 0.9 percent of the

total historical forest. Area of old forests in the

current condition was essentially unchanged.

Likewise, area with large trees, whether in old 

forest or associated with other forest structures,

was unchanged (table 20). Area with medium 

and large trees declined slightly during the sample

period (table 21), but the change was not significant. In the historical condition, 19.7 percent of

the ERU (22.6 percent of the forest) was occupied by forest structures comprised of medium

and large trees. In the current condition, 17.2

percent of the ERU (20 percent of the forest) 

was occupied by forest structures comprised of

medium and large trees.

Area in stem-exclusion closed canopy structures

increased significantly during the sample period

to become the codominant structural feature of

Upper Clark Fork forests in the current condition. Our results suggest that the observed

increase in stem-exclusion closed canopy structures is the result of fire exclusion and selective

harvesting (table 27): areas regenerated by fire

before our historical coverage have regrown. In

the current condition, 86 percent of forest structure is intermediate (stem exclusion, understory

reinitiation, or young multistory), 1 percent is

old, and 13 percent is new forest. In appendix 2,

we observe that the connectivity of most major

forest cover types and structural classes declined

significantly. In most cases, patch density increased, and average patch size declined. These

changes are characteristic of the combined effects

of fire exclusion and regeneration and selective

harvesting. Area and connectivity of major early

seral species cover declined (timber harvest), area

of new forest structure declined, and area of intermediate forest structure increased (fire exclusion

and timber harvest). 

Upper Klamath ERU—Forests of the Upper

Klamath ERU are comprised primarily of dry 

and mesic PVTs (see fig. 70 and Hann and others

1997). Historical fire regimes were predominantly

nonlethal surface fire with frequent (26 to 75

years) to very frequent (0 to 25 years) fire return

intervals (see fig. 71, A and B, and Hann and

others 1997). More than one-half of historical

forest cover was ponderosa pine (table 29 and

appendix 2). Results from our analysis suggest

that timber harvest, fire exclusion, and grazing

each had a pronounced effect on current forest

composition and structure.

In the historical condition, we expected stand-initiation structures to occupy only a minor fraction

of Upper Klamath forest landscapes because surface fire regimes with frequent fire return typically

regenerate forests continually via individual tree

and small group killing. Area in stand-initiation

structures increased from a historical level of 1.9

to 3.6 percent of the ERU (ns) as a result of

regeneration and selective harvests or removal 

cutting (table 27) that occurred during the sample

period. In the historical condition, old forests

comprised 11.7 percent of the ERU, or 23.2 percent of the total forest area. In the current condition, old forests comprised 10.3 percent of the

ERU, or 21.7 percent of the total forest area.

Selective harvests have diminished that area significantly (appendix 2). Decline in area occupied 

by medium and large trees was perhaps the single

greatest change occurring to all forest structures in

the Upper Klamath (tables 20 and 21). In the historical condition, 43.3 percent of the ERU (86

percent of the forest) was occupied by forest

structures comprised of medium and large trees.

In the current condition, 27.4 percent of the

ERU (58 percent of the forest) was occupied 

by forest structures with medium and large trees.

Selection cutting of medium and large trees in 

a management context of fire control and extensive cattle grazing would have promoted development of more total crown cover (table 22), less

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grass-forb and shrub understory cover and greater

conifer understory cover (table 25), increased vertical complexity of forest canopies (table 23), and

increased cover of shade-tolerant understories

(table 24). None of these changes was observed.

In addition, extensive grazing would have minimized flashy fuel cover (Agee 1994), increasing

opportunities for conifer understory development

via reduced competition and reducing the likelihood of surface fires from natural or humancaused ignitions. Our findings suggest that for 

the period of our sample, the primary management influence in the Upper Klamath ERU was

extensive and heavy timber harvest.

Area in young multistory structures declined for

similar reasons (fig. 78). Repeated heavy partial

cutting reduced forest crown cover (table 22),

canopy layering (table 23), and conifer understory

development (tables 24 and 25), thereby depleting area of young multistory structure (table 29).

Upper Klamath woodlands are composed chiefly

of western juniper. During the sample period,

area of stem-exclusion and understory reinitiation

structures increased sharply (appendix 2 and fig.

78). We believe that expansion of the western

juniper cover type and its associated stem-exclusion structure was the result of fire exclusion and

grazing. Grazing minimized herbaceous competition and the possibility of surface fires, and fire

exclusion enabled uninhibited expansion of 

juniper cover.

Upper Snake ERU—According to our sample,

forests comprise about 3 percent of the ERU area.

No changes in forest structures were particularly

noteworthy, but two changes were statistically 

significant: area in stand-initiation structures declined, and area in stem-exclusion open canopy

structures increased by a compensating amount.

We speculate that fire exclusion was primarily

responsible for the shift (see also tables 22, 23,

25, and 27).

Woodland structure also changed significantly

(table 29 and appendix 2). Woodlands in this ERU

are juniper and mixed pinyon and juniper, and

they are severely moisture limited. In our historical coverage, most woodlands were characterized

Figure 78—Historical and current maps of forest and woodland structural classes in subwatershed 0903 in the Lost subbasin of

the Upper Klamath ERU.
as understory reinitiation structure. Area in woodland understory reinitiation structures declined,

and area in stem-exclusion structures increased by

a compensating amount. We speculate that this

minor change in structure may have been associated with ongoing insect disturbance (table 25). 

Shrubland and herbland structure—Area 

of open or closed shrub structure declined in

every ERU where the shrubland physiognomic

type comprised more than 0.5 percent of the area.

The most significant loss of shrub structure

occurring in the basin was the loss of open lowmedium structures (primarily sagebrushes, rabbitbrush, and bitterbrush). Significant reductions in

open low-medium shrub structures were noted in

the Blue Mountains, Columbia Plateau, Northern

Great Basin, Owyhee Uplands, and Snake

Headwaters ERUs (table 29). Significant reduction in closed low-medium shrub structure was

observed in the Columbia Plateau ERU. Figure

79 provides an excellent illustration of increased

open herbland structure and reduced open and

closed low-medium shrub structure in a subwatershed of the Lower John Day subbasin in the

Columbia Plateau ERU. In general, the most significant losses to shrublands were associated with

forest or woodland expansion as observed in the

Blue Mountains and Northern Great Basin ERUs,

cropland expansion as observed in the Northern

Great Basin ERU, and conversion to seminative

or nonnative herbland as observed in the Owyhee

Uplands or Snake Headwaters ERUs.

Decline in shrubland area was the most significant change we observed during the sample 

period in the whole of the midscale assessment.

Change was most conspicuous in ERUs where

shrublands were a dominant physiognomic 

condition, such as in the Blue Mountains,

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Figure 79—Historical and current maps of shrubland and herbland structural classes in subwatershed 1101 in the Lower John

Day subbasin of the Columbia Plateau ERU. 
255

Columbia Plateau, Northern Great Basin,

Owyhee Uplands, and Upper Snake ERUs (table

29 and appendix 2). In the Blue Mountains,

shrublands occupied 14.1 percent of the area in

the historical condition. Shrubland area declined

by 24 percent to 10.7 percent of the ERU, and

most of the loss was to open low-medium structures. In the Columbia Plateau, shrublands occupied 32.2 percent of the area in the historical

condition. Shrubland area declined by 27 percent

to 23.4 percent of the ERU, and most of the 

loss was to open and closed canopy low-medium

shrub structures. In the Northern Great Basin,

shrublands occupied 72.8 percent of the area in

the historical condition. Shrubland area declined

by 21 percent to 57.6 percent of the ERU, and

virtually all the loss was to open low-medium

structures. In the Owyhee Uplands, shrublands

occupied 88.8 percent of the area in the historical

condition. Shrubland area declined during the

sample period by 9 percent to 81.0 percent of the

ERU, and most of the loss was to open low-medium structures. Finally, in the Upper Snake, shrublands occupied 73.8 percent of the area in the

historical condition. Shrubland area declined by 

7 percent to 68.5 percent of the ERU (ns), and

most of the loss was to open and closed canopy

low-medium structures. It is apparent that shrublands as a physiognomic condition, and that open

low-medium shrub structures in particular, have

been significantly diminished across the entire

basin. We speculate that such a dramatic and

expansive change must have produced equally 

significant and deleterious consequences for terrestrial species that rely on the presence of vast

unbroken shrubland areas. 

In general, open herbland area increased in most

ERUs where significant reduction in open lowmedium shrub structure occurred. We speculate

that active range management activities to improve domestic livestock forage production were

responsible for much of the noted expansion of

open herbland area.

Landscape Patterns

The size and scale of ERUs as a pooling stratum

preclude their use for project-level planning, 

but they are quite useful in providing context of

individual watersheds and displaying significant

province-scale change in vegetation patterns.

When conditions of any watershed are examined,

it is essential to understand the importance of various changes relative to the broader picture, not

only the type but also the degree of change. Information of the sort we have provided answers

questions on the rarity or uniqueness of any given

patch type within a subwatershed or larger domain, currently and historically. And it enables 

one to gauge how representative current landscape 

patterns are compared with recent historical conditions. Additionally, when determining landscape

changes, it is often difficult to understand the

marriage of management and environmental 

causes behind observed changes. Comparative

study of change in highly similar and differing

ERUs, given their management histories, biophysical environment composition, climatic conditions, and disturbance regimes, enables us to

better understand the relative contributions of

each factor to the observed changes. These observations aid the understanding of the past and help

to interpret or predict alternative management

and climate futures. An even richer contribution

to our understanding is the comparative study 

of landscape change at multiple scales, including

pooling strata as large as ERUs and using smaller

subregional strata and those in between. Such

multiscale analyses provide insight to the magnitude and effects of changes at several relevant

scales and contexts.

We conducted our landscape pattern analyses by

using cover type-structural class couplets as the

patch type because this combination is most intuitive for understanding simultaneous changes in

patterns of structural and compositional attributes

and terrestrial habitats. We first discuss change

occurring across all ERUs for a given subset of

metrics, and then we discuss changes across metrics by ERU.
Richness, diversity, and evenness—

Patch richness (PR), SHDI, and the inverse of

Simpson’s λ (N2) provide different views of the

diversity of cover-structure patch types across any

landscape. Richness simply tallies the number of

different patch types present without regard for

their relative abundance; a patch type represented

by a single patch counts as much as another patch

type comprising 95 percent of the subwatershed

area. The SHDI and N2 incorporate abundance

into the measurement of diversity, but N2 responds to abundance changes in the most dominant patch types. Relative patch richness (RPR)

rescales PR as a percentage of the total coverstructure patch types present in the basin (there

were 192 reasonable cover-structure patch types).

The SHDI (or its transformed equivalent N1) is

intermediate in responsiveness between RPR and

N2. In general, for the three measures of richness

and diversity (RPR and PR, SHDI and N1, and

N2), all ERUs displayed a positive mean difference with only two notable exceptions (table 19):

the Lower Clark Fork and Upper Klamath ERUs

exhibited minor declines in PR. We attributed

these declines to an extended history of widespread timber harvest activity. Five of thirteen

ERUs (the Central Idaho Mountains, Northern

Cascades, Northern Glaciated Mountains,

Southern Cascades, and Upper Clark Fork) 

displayed significant change in PR, generally 

on the order of a 15- to 30-percent increase.

Eight of thirteen ERUs displayed significantly

increased dominance and diversity (N2), thereby

indicating that patch type numbers were not only

increasing but also that new patch types were

occupying significant landscape area. Ecological

reporting units displaying an increase were the

Lower Clark Fork, Northern Cascades, Northern

Glaciated Mountains, Northern Great Basin,

Owyhee Uplands, Snake Headwaters, Southern

Cascades, and Upper Klamath.

Evenness measures are attempts to assess how

equitably area is distributed among a given 

number of patch types. Both evenness measures

(MSIEI and R21) index relative change in the

distribution of “abundance,” or in this case area,

among patch types. Many ERUs displayed

increased diversity, richness, and dominance 

during the sample period for the diversity measures we used. That typically results in a modest

increase in the evenness measures used, if any

change in evenness occurs at all. Our results 

confirmed this relation; the MSIEI and R21

increased significantly in six of eight ERUs 

displaying significantly increased diversity and

dominance. The Upper Clark Fork and the

Central Idaho Mountains were the only two

ERUs to decline in evenness; the Upper Clark

Fork declined significantly in both evenness measures. In the Central Idaho Mountains, few cover

type changes were significant, but the distribution

of area in forest structures became increasingly

uneven. Area in stand-initiation structures

declined from 9.7 to 5.9 percent of the ERU, 

and area in understory reinitiation structures

increased from an average of 16 to 21.4 percent

of the ERU. A similar pattern of change was evident in the Upper Clark Fork ERU; few cover

type changes were evident, but distribution of

area in stand initiation, closed canopy stem-exclusion, and young multistory forest structures

became increasingly uneven (appendix 2).

Landscape metrics (table 19) computed in

FRAGSTATS (McGarigal and Marks 1995) were

averaged across sampled subwatersheds; for example, the value of CONTAG_c computed for the

Northern Cascades ERU was derived by averaging

all CONTAG values of individual subwatersheds

in that ERU in the current condition. Hence, values for all metrics in the historical and current

condition reflect the average per subwatershed.

Some questions come to mind: What is the total

richness and diversity of patch types of each ERU?

and Have those values changed during the sample

period? Heltshe and Forrester (1983) describe a

“jackknife” estimator for richness that attempts to

estimate total richness for a geographic area of

interest. We applied this technique and a related

jackknife estimator for N2 (Burnham and

Overton 1979) to the historical and current patch

type data for each ERU to estimate difference in

richness and dominance for each ERU (table 30).

The jackknife technique results in estimates of the

total and the standard error. We used these statistics in simple two-way t-tests to test for significant change in richness or dominance across each

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ERU. All changes but one were insignificant at

the ERU scale. Eight ERUs displayed nonsignificant increase in richness.

Jackknife estimates of richness are very sensitive

to sample size and coverage. It is best in this

instance not to make comparisons among ERUs,

but comparisons between current and historical

values are appropriate. Jackknife estimates for 

N2 are not restricted in this way. The N2 values

across ERUs range from a low of 1 in the Owyhee

Uplands to 36 in the Northern Cascades. We

expect forest-dominated ERUs to display much

larger values of total N2 than range-dominated

ERUs because of the former’s greater PR and

diversity. 

Contagion and interspersion—Contagion

and IJI metrics were designed to quantify the

extent to which patches or pixels of differing

types intermix with one another. The IJI considers length of edge between contrasting patch

types, and CONTAG estimates patch-type 

dispersion and interspersion for data in raster 

format. Both metrics are rescaled as a percentage

of the maximum possible value, given the total

number of patch types, and range in value from 

0 to 100. As mean patch size increases, total edge

length tends to decrease. We then expect that

mean differences values for IJI and CONTAG

will differ in sign, although this is not always

true.

Seven of thirteen ERUs displayed significant

declines in CONTAG, and all significant mean

differences values were negative (table 19).

Ecological reporting units displaying a significant

decline were the Lower Clark Fork, Northern

Cascades, Northern Glaciated Mountains,

Northern Great Basin, Owyhee Uplands, Snake

Headwaters, and Southern Cascades. A negative

mean difference value of CONTAG indicated

that across a given ERU, cover-structure patches

became smaller during the sample period and

more dispersed. Three of six ERUs with nonsignificant mean difference values of CONTAG

Table 30—“Jackknife” estimates of total patch-type richness and dominance (N2) for 13 ecological reporting units in the midscale assessment of the interior Columbia River basin where patch types were cover

type-structural class doublets

Richness Dominance (N2)

Sampled

Ecological reporting unit watersheds Historical (s.e.)a Current (s.e.)a Historical (s.e.)b Current (s.e.)bc

Number

Blue Mountains 44 114 (6.0) 123 (4.3) 23 (3.5) 20 (2.4)

Central Idaho Mountains 43 142 (6.4) 135 (5.7) 32 (2.9) 29 (2.7)

Columbia Plateau 38 121 (7.7) 119 (5.5) 10 (1.7) 11 (1.7)

Lower Clark Fork 5 88 (9.5) 73 (2.9) 19 (1.6) 17 (1.8)

Northern Cascade Mountains 47 135 (5.1) 133 (3.8) 36 (4.5) 36 (3.8)

Northern Glaciated Mountains 41 127 (5.1) 136 (5.4) 25 (2.4) 26 (2.7)

Northern Great Basin 4 22 (2.6) 29 (3.6) 4 (0.4) 5 (0.6)

Owyhee Uplands 22 40 (6.0) 41 (4.1) 1 (0.2) 2 (0.3)*

Snake Headwaters 15 83 (5.4) 92 (5.9) 30 (3.2) 26 (3.1)

Southern Cascades 16 69 (5.7) 80 (8.1) 15 (1.3) 15 (2.6)

Upper Clark Fork 32 113 (5.8) 120 (4.9) 25 (1.9) 23 (2.2)

Upper Klamath 13 107 (7.0) 100 (5.7) 13 (3.9) 16 (3.0)

Upper Snake 15 67 (8.3) 71 (6.5) 3 (0.4) 3 (0.9) 

a Estimates of total richness and standard error (s.e.) were computed by using the methods of Heltshe and Forrester (1983).

Estimates for total richness were rounded to the nearest integer.

b Estimates of total dominance (N2) and its standard error were computed by using the methods of Burnham and Overton

(1979). Estimates for total dominance were rounded to the nearest integer.

c * indicates significant difference at P≤0.2.
also exhibited a negative sign. These results point

to a systematic basinwide decrease in contagion or

connectivity of cover-structure patch types. With

the exception of the Northern Great Basin and

Owyhee Uplands ERUs, the magnitude of

decrease was small relative to initial average 

historical values. 

Only 4 of 13 ERUs displayed significant mean

difference values for IJI; two were positive and

two were negative (table 19). The Owyhee

Uplands and Upper Snake ERUs were noteworthy

because the magnitude of mean difference values

for these two ERUs was especially large. Unlike

CONTAG, there was no consistent pattern across

ERUs for this metric, and most changes were

small. We concluded that interspersion changes 

as measured by this metric were minimal at this

reporting scale, and that changes in interspersion

and patch type juxtaposition may be better

observed at smaller scales where variability of biophysical environments is more readily controlled.

For example, IJI values of subwatersheds pooled

to subbasins indicated highly significant mean

differences.

Edge contrast—The AWMECI uses a set of

user-defined values ranging from 0 to 1 to represent relative edge contrast (table 18) between

patch types, weighted by area, to evaluate change

in edge contrast of a landscape or sample of landscapes. We based edge contrast on physiognomic

and structural conditions in deference to edgesensitive and -dependent terrestrial species, and

their typically greater sensitivity to structural differences of edges. An increase in area-weighted

mean edge contrast was indicated as the percentage of the total edge that was the equivalent of

maximum contrast edge. The greater the difference in structure or physiognomic condition (for

example, an old single-story forest patch adjacent

to open herbland), the greater the edge contrast

weight. Significant increase in AWMECI for a

given landscape or sample of landscapes indicated

that greater contrast in structural and physiognomic condition was occurring at patch edges. 

Six of thirteen ERUs displayed such a significant

increase. Most increases were relatively modest

except in the Lower Clark Fork ERU, where

increase in maximum contrast edge averaged 

5.1 percent of the total edge (table 19). 

Pattern changes among ERUs—The Blue

Mountains and Columbia Plateau ERUs displayed no significant change for any landscape

metric. The sign of insignificant change was generally consistent with change occurring in other

ERUs except as noted earlier for the contagion

and interspersion indices. When we ranked the

mean difference value for PR, SHDI, and N2 

and then averaged the three ranking values, the

Blue Mountains was 10th in overall change and

the Columbia Plateau ERU was 12th. The jackknife index value of total richness increased in

both ERUs, but insignificantly.

In the Central Idaho Mountains, significant

changes in richness and SHDI were consistent

with declining evenness as measured by R21.

More patch types appeared on the landscape, yet

the number of dominant types did not increase

significantly. The Central Idaho Mountains ERU

ranked seventh among ERUs in overall change 

in diversity and richness. Contagion and interspersion did not change significantly, but edge

contrast rose significantly, thereby indicating

increasing juxtaposition of dissimilar structural

and physiognomic types. Rank in edge contrast

change was fifth among ERUs.

The 24-percent rise in N2 was the only significant change in richness, dominance, and diversity

noted in the Lower Clark Fork ERU. We anticipated the corresponding rise in evenness values

(table 19). This ERU ranked sixth in overall

change in diversity and richness. Contagion also

increased significantly; in fact, the noted change

was the fourth largest observed, but interspersion

did not change significantly, perhaps owing to 

our small sample size after poststratification. The

Lower Clark Fork displayed the largest overall

increase in edge contrast of all ERUs, indicating 

a significant repatterning of structure and physiognomic condition and grain of the landscape.

Further evaluation is needed before these observation can be accepted as representative of the

Lower Clark Fork ERU at large because our sample was restricted to subwatersheds of the Upper

Coeur d’Alene subbasin, which may not adequately represent the ERU.

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259

The Northern Cascades ERU displayed one of the

highest jackknife values for total richness and the

highest value for the jackknifed N2 measure; significant increases were noted for all richness and

diversity metrics. We expected and observed little

or no change in evenness with across-the-board

increase in richness, dominance, and diversity

(table 19). The Northern Cascades ranked 

third in overall change in diversity and richness.

Change in contagion and interspersion was significant. Decreasing contagion indicated that 

similar patch types were less likely to be adjacent

to one another. Interspersion increase indicated

reduced patch sizes and reduced connectivity of

patch-type area. 

The Northern Glaciated Mountains ERU ranked

second in overall change in diversity and richness;

richness, dominance, and diversity all increased

significantly. Evenness did not change significantly given noted increases in PR, RPR, and N2.

The jackknife N2 index of total diversity placed

the Northern Glaciated Mountains in the third

highest position among ERUs. Decreasing contagion indicated that similar patch types were less

likely to be adjacent to one another; increase 

in edge contrast (AWMECI) was third largest

among ERUs. Fire exclusion, timber harvest, and

checkerboard ownerships in this ERU all contributed to the changes detected.

The Northern Great Basin and Owyhee Uplands

ERUs were among the least diverse in cover-structure patch types from both an average per subwatershed (table 19) and an ERU perspective (table

30). Yet the Northern Great Basin ERU ranked

fourth in overall change in diversity and richness.

Diversity (SHDI and N2) and dominance (N2)

both increased significantly, and as expected,

evenness as measured by both MSIEI and R21

measures increased significantly. Decrease in 

contagion was second only in magnitude to 

the decrease observed in the Owyhee Uplands.

The Owyhee Uplands ranked ninth overall in

richness and diversity changes. Diversity, dominance, and evenness increased in the manner

expected, but the Owyhee Uplands was the least

diverse among all ERUs from a total N2 perspective (table 30). Radically reduced contagion indicated that similar patch types were less likely than

ever to be adjacent to one another, and interspersion increase indicated that patch sizes and connectivity of patch type area had been substantially

reduced. Changes in contagion and interspersion

were the largest observed among all ERUs. Mean

edge contrast increased significantly, indicating

increasing juxtaposition of dissimilar structural

and physiognomic conditions. The magnitude 

of change in edge contrast was seventh highest

among ERUs. Given the diminutive historical

(10.5 percent) and current (11.4 percent) values 

of AWMECI as compared to values from forestdominated ERUs, this increase was especially 

significant. It likely reflects the well-known and

widespread conversion and fragmentation of

native shrublands by seminative and nonnative

grasslands.

The Snake Headwaters ERU ranked eighth 

overall in richness and diversity mean difference

changes. Diversity (SHDI and N2) and dominance (N2) both increased significantly, and 

as expected, evenness as measured by MSIEI

increased significantly. The Snake Headwaters

ERU was moderately diverse from a jackknife 

N2 perspective, but total diversity had declined,

albeit nonsignificantly, during the sample period.

Contagion decreased, indicating that landscapes

had become more fragmented and that similar

patch types were less likely to be adjacent to 

one another.

The Southern Cascades ERU exhibited the greatest overall increase in diversity and richness as

measured by ranked and averaged mean difference

values, displaying nearly a 40-percent increase in

patch richness alone. In fact, richness (PR and

RPR), diversity (SHDI and N2), and dominance

(N2) all increased significantly, and as expected,

evenness as measured by either R21 or MSIEI

remained relatively constant. As with most all

ERUs, contagion decreased, indicating that 

landscapes had become more fragmented and that

similar patch types were less likely to be adjacent

to one another; edge contrast increased significantly, indicating increasing juxtaposition of dissimilar structural and physiognomic conditions.

The magnitude of change in edge contrast was

second among ERUs.
The Upper Clark Fork ERU displayed significant

increases in richness and SHDI but not in dominance. Increased richness was a function of increased variety in cover type and structural class

combinations during the sample period. Increasing patch type richness was commonly observed

among forest-dominated ERUs. Results of transition analysis indicated that increase was most 

likely a consequence of timber harvest and fire

exclusion. The Upper Clark Fork ranked fifth in

overall change in richness and diversity as measured by ranked and averaged mean difference values. Large increases in richness led to a prediction

that evenness would be reduced, and significant

reductions were observed for both evenness metrics. The Upper Clark Fork was the only ERU

exhibiting a significant decrease in both indices

and the only ERU displaying a significant decline

in interspersion not accompanied by an increase

in contagion; the general trend among ERUs was

inverse change.

The Upper Klamath and Upper Snake ERUs displayed few changes in landscape patterns. The

Upper Klamath ranked 11th in overall change in

diversity and richness as measured by ranked and

averaged mean difference values. The N2 was the

only diversity and dominance measure to increase

significantly, and evenness of dominant patch

types as measured by R21 displayed the expected

increase. Increasing cropland area and juniper

cover in woodlands was the likely cause of increased dominance. Increasing evenness among

dominant patch types was most influenced by increasing evenness among forest structural classes.

The Upper Snake ERU ranked last in overall

change in richness and diversity. No change in

richness or diversity was in evidence. But interspersion increased significantly, with the second

largest change observed among all ERUs. Increased interspersion was most influenced by

sharply increased patch density and reduced 

mean patch size of colline low-medium shrublands (appendix 2). Surprisingly, change in contagion was insignificant, and the sign of change was

positive. Mean edge contrast also increased significantly, indicating increasing juxtaposition of dissimilar structural and physiognomic conditions.

The magnitude of change in edge contrast was

fourth largest among ERUs. Given the small historical (17.3 percent) and current (18.9 percent)

values of AWMECI as compared to values from

forest-dominated ERUs, this increase is especially

significant. It reflects the widespread replacement

and fragmentation of once vast native shrublands

by cropland and seminative and nonnative grasslands.

Forest Vulnerability to 

Insect and Pathogen Disturbances

We found that vulnerability characterizations and

associated change analysis revealed more of the

complexity and subtlety of change in forest vegetation patterns than was possible with direct

analysis of change in cover type, structural class,

or physiognomic condition alone (appendix 2).

This was true because vulnerability characterizations were based on raw interpreted data as well

as derived attributes (see table 4 and Hessburg

and others, in press). This difference enabled the

discovery of changes within cover types and structural conditions and the recognition that they are

truly varied rather than homogeneous as classifications tend to imply. Results of vulnerability

characterizations were a less-than-subtle reminder

that maps and classifications partially disguise the

truth about what is mapped or classified. We were

reminded that investigators must be wary of their

own and others’ maps and classifications—that

perhaps more information may be cloaked than

revealed.

Management practices significantly increased 

vulnerabilities in some subbasins and ERUs and

decreased them in others. Vulnerability changes at

the ERU scale often were insignificant or masked

owing to high variation among sampled subwatersheds. High variability among subwatersheds

within ERUs was a function of large geographic

extent, high variability in vegetative communities

and biophysical conditions, and variable climatic

and disturbance regimes. We have learned that to

detect change in vegetation patterns or associated

changes in landscape vulnerability to various

pathogen and insect disturbances, it is better to

consider change among subwatersheds highly 

260
261

similar in climatic regime and biophysical environment composition (see “Ecological Regionalization,” below). For these reasons, trends

reported in “Results” are apt to be highly conservative estimates for ERUs.

In this section, we discuss some of the major

changes in forest landscape vulnerability to insect

and pathogen disturbances. We concentrate on

the most significant changes and underlying probable causes. Because we were unable to directly

measure levels and areal extent of management

activities, we speculate on the most probable

management activities responsible for the changes

we observed and present evidence to support

those speculations. We do not discuss broad vulnerability trends for the Northern Great Basin,

Owyhee, and Upper Snake ERUs because of their

small forest area, but results of vulnerability characterizations for all ERUs are discussed in the

“Results,” summarized in appendix 3, and displayed in figures 46 to 56. Table 31 allows the

reader to review at a glance vulnerability changes

among ERUs; significant and nonsignificant

increases and decreases in vulnerability are indicated so that the reader can observe general trends

in vulnerability among ERUs in addition to significant change.

Blue Mountains ERU—Our analysis indicated

that forests of the Blue Mountains ERU have

been influenced quite significantly and predictably by timber harvesting, fire suppression,

fire exclusion, and grazing. In our historical vegetation coverage, 22 percent of the forest area

exhibited obvious visible signs of logging (table

27). In the current condition, 28 percent of the

forest area exhibited visible signs of logging.

Timber harvest reduced old-forest area and area

with remnant large trees to a fraction of the historical area (table 20) and, more significantly,

restricted availability of medium and large trees 

in all structures (table 21). Medium and large

trees were harvested from all major cover types

including ponderosa pine, grand fir-white fir,

Engelmann spruce-subalpine fir, and Douglas-fir

(appendix 2). In the absence of frequent fires and

under the influence of selective harvesting and

grazing, Douglas-fir cover expanded (table 29 and

appendix 2), forest structures became more layered (table 23), grass and shrub understories were

replaced by those comprised of shade-tolerant

conifers (tables 24 and 25), and forests and woodlands expanded substantially in areas formerly

grasslands and shrublands (appendix 2).

In the Blue Mountains, area vulnerable to western

spruce budworm did not change significantly; a

relatively large proportion of the ERU (38.2 percent) was highly vulnerable in the historical coverage, and a similar proportion (38.9 percent) is

vulnerable in the current condition. Furthermore,

increased area vulnerable to budworm disturbance

(ns) was associated with increased area of multilayered shade-tolerant understories (tables 23 and

24). At the ERU scale, it appears that a similar

area is vulnerable to defoliation, but were defoliation to occur under current conditions, growth

and mortality effects likely would be more pronounced. We believe that the lack of significant

change in area vulnerable to budworm disturbance was primarily due to high inherent variability among subwatersheds pooled at the scale of

the ERU. At a subbasin scale, we observed highly

significant differences in vulnerability to western

spruce budworm. Budworm vulnerability results

(appendix 3) and fire regime changes (fig. 71, 

A and B) shown by Hann and others (1997) also

suggest that a considerable amount of change in

vegetation conditions was already set in motion

during the 50 to 60 years before the start of the

historical coverage (see also table 3). Domestic

sheep and cattle grazing and selection cutting

(Oliver and others 1994; Wickman 1992;

Wissmar and others 1994a, 1994b) were the 

principal agents of change.

Area vulnerable to Douglas-fir beetle increased

during the sample period because Blue Mountains

landscapes in the current condition display

increased cover and connectivity of Douglas-fir

and increased stand densities. Figure 80, A, provides an example of increased area vulnerable to

Douglas-fir beetle disturbance in a subwatershed

of the Silvies subbasin.

Area vulnerable to western pine beetle (type 1)

disturbance of mature and old ponderosa pine

declined because medium and large ponderosa

pine were selectively harvested from old and other

forest structures (tables 20 and 21). We believe

that this decline in vulnerability has had and will
262

Table 31—Insect and pathogen disturbance vulnerability changes in 13 ecological reporting units in the

midscale assessment of the interior Columbia River basin

Ecological reporting units

Central Lower Nor. Nor. Upper

Blue Idaho Col. Clark Nor. Glac. Great Owyhee Snake So. Clark Upper Upper

Disturbance Agenta Mts. Mts. Plateau Fork Cascade Mts. Basin Uplands Headw. Cascade Fork Klamath Snake

WSB +b + + + + - - - na na + + + + - + +

DFB ++ + - + - + na na + + - - - - nc +

WPB1 nc + - na - - - na na na - - - - na

WPB2 + nc + + + - - - na na na + - - + na

MPB1 - - + + + + + + + na na - - - + - -

MPB2 + nc + + + - - - na na na + - - + na

FE - - + + + + + + + na na - + + + + + na

SB - - + na + - + + na na - - nc - na na

DFDM + + - - + - + na na + + - - - - - +

PPDM - - - - - + - - - - na na na + - - - na

WLDM - - na nc nc - - na na na na - - na na

LPDM nc + na + + - na na - - + - nc nc

AROS + + + + - - + + na na + + + + - + +

PHWE + + - - + - - + na na + + + + - - +

HEANs - - + + + + + + + + + na na + + + + + +

HEANp - - - - na - - + na na na + + - - + na

TRBR - - + + na na - - + + na na + nc + na na

SRBR + + - - - - - - na na - + - - - + +

WPBR1 na nc - - + + + - - na na na nc - na na

WPBR2 na nc na na + + nc na na - na - na na

RRSR - + na + + + + + na na na + + - na

a WSB = western spruce budworm; DFB = Douglas-fir beetle; WPB1 = western pine beetle - type 1 attack of mature and old

ponderosa pine; WPB2 = western pine beetle - type 2 attack of immature and overstocked ponderosa pine; MPB1 = mountain

pine beetle - type 1 attack of overstocked lodgepole pine; MPB2 = mountain pine beetle - type 2 attack of immature and overstocked ponderosa pine; FE = fir engraver; SB = spruce beetle; DFDM = Douglas-fir dwarf mistletoe; PPDM = ponderosa pine

dwarf mistletoe; WLDM = western larch dwarf mistletoe; LPDM = lodgepole pine dwarf mistletoe; AROS = Armillaria root 

disease; PHWE = laminated root rot; HEANs = S-group annosum root disease; HEANp = P-group annosum root disease;

TRBR = tomentosus root and butt rot; SRBR = Schweintizii root and butt rot; WPBR1 = white pine blister rust - type 1 on

western white pine/sugar pine; WPBR2 = white pine blister rust - type 2 on whitebark pine; RRSR = rust-red stringy rot. See

also appendix A.

b + + = significant increase at P≤0.2; + = nonsignificant increase; - - = significant decrease at P≤0.2; - = nonsignificant decrease;

“na” = not applicable; and nc = no change.
263

Figure 80—Historical and current maps of vegetation vulnerability to (A) Douglas-fir beetle disturbance in subwatershed 40C

in the Silvies subbasin of the Blue Mountains ERU, and (B) mountain pine beetle type 1 disturbance in subwatershed 40 in the

Wallowa subbasin of the Blue Mountains ERU.
264

continue to have important ecological ramifications. Ponderosa pine is the primary early seral

species naturally occurring in the ERU. As such,

it historically had the opportunity to achieve great

age and stature under presettlement disturbance

regimes, and large areas of the ERU (old forest or

otherwise) supported some amount of ponderosa

pine in the overstory. Ponderosa pine produces

snags of excellent quality and potentially long 

residence time (Bull 1983; Keen 1929, 1955).

Selective harvesting of live medium and large

ponderosa pine has depleted the current and

future availability of pine snags.

Area vulnerable to mountain pine beetle (type 1)

disturbance of high-density lodgepole pine declined, but area of the lodgepole pine cover type

did not change significantly. In the Blue Mountains, area where lodgepole pine comprises a pure

cover type is small in comparison with the area

where it occurs in mixed types. The observed

decline in vulnerability is indicative of declining

area where lodgepole pine occurs as a major early

seral species in mixed types. With the exclusion 

of stand-regenerating fires, ongoing mountain

pine beetle mortality has steadily removed lodgepole pine in many such stands (Schmitt and others 1991). Figure 80, B, provides an example of

reduced area vulnerable to mountain pine beetle

(type 1) disturbance in a subwatershed of the

Wallowa subbasin.

Area vulnerable to fir engraver and spruce beetle

disturbance also declined. In both cases, area of

host cover declined as a result of timber harvest 

or salvage, extended drought, and western spruce

budworm and prior bark beetle disturbance (Gast

and others 1991, Schmitt and others 1991).

Figure 81, A, illustrates reduced area vulnerable 

to fir engraver disturbance in a subwatershed of

the Lower Grande Ronde subbasin. Figure 81, B,

provides an example of reduced area vulnerable to

spruce beetle disturbance in a subwatershed of the

Upper Grande Ronde subbasin.

Area vulnerable to Douglas-fir dwarf mistletoe increased with expanded area of Douglas-fir cover

and increased canopy layering and contiguity of

host patches. In contrast, area vulnerable to ponderosa pine and western larch dwarf mistletoe disturbances declined; these declines were associated

with reduced area of ponderosa pine and western

larch overstory cover, respectively, from timber

harvest. Figure 82, A, provides an example of

increased area vulnerable to Douglas-fir dwarf

mistletoe disturbance in a subwatershed of the

Wallowa subbasin.

Even with declining area of grand fir, white fir,

and subalpine fir overstory cover, area vulnerable

to S-group annosum root disease likely increased.

We believe this is true because (1) the total area

occupied by host species actually increased (table

24), but hosts now more often occur in understories in intermediate and suppressed crown classes;

and (2) a large percentage of the forest has been

entered for timber harvest (table 27), and freshly

cut stumps provide avenues for spread of this disease to new patches (Hadfield and others 1986).

Area and connectivity of area vulnerable to laminated root rot disturbance increased primarily 

as a result of increased cover and connectivity of

Douglas-fir patches but also because of increasing

area occupied by understory true firs. Area and

connectivity of area vulnerable to Schweinitzii

root and butt rot disturbance increased as a result

of increased cover and connectivity of Douglas-fir

patches. Figure 82, B, displays increased area vulnerable to Schweinitzii root and butt rot disturbance in a subwatershed of the Burnt subbasin.

Central Idaho Mountains ERU—Few significant changes in vulnerability were in evidence in

the Central Idaho Mountains (table 31). For the

most part, vulnerability characterizations indicated that the primary influence during the sample

period was fire exclusion. Shade-tolerant true firs

increased slightly in area and dominance, and

insects and pathogens that specialize in attacking

true firs were modestly favored by that increase.

Area vulnerable to western spruce budworm

increased but the change was not significant at

this reporting scale; a large proportion of the

ERU area (49.4 percent) was highly vulnerable 

in the historical coverage, and a similar proportion (51.1percent) is vulnerable in the current

condition. Area vulnerable to fir engraver and 

S-group annosum root disease disturbance also

increased. Figure 83, A, provides an example of

increased area vulnerable to fir engraver disturbance in a subwatershed of the South Fork Clearwater subbasin.
265

Figure 81—Historical and current maps of vegetation vulnerability to (A) fir engraver disturbance in subwatershed L2 in the

Lower Grande Ronde subbasin of the Blue Mountains ERU, and (B) spruce beetle disturbance in subwatershed u28 in the

Upper Grande Ronde subbasin of the Blue Mountains ERU.
266

Figure 82—Historical and current maps of vegetation vulnerability to (A) Douglas-fir dwarf mistletoe disturbance in subwatershed 29 in the Wallowa subbasin of the Blue Mountains ERU, and (B) Schweinitzii root and butt rot disturbance in subwatershed 0901 in the Burnt subbasin of the Blue Mountains ERU. 
267

Figure 83—Historical and current maps of vegetation vulnerability to (A) fir engraver disturbance in subwatershed 0703 in the

South Fork Clearwater subbasin of the Central Idaho Mountains ERU, and (B) western pine beetle type 1 disturbance in subwatershed 1303 in the Lower John Day subbasin of the Columbia Plateau ERU. 
Columbia Plateau ERU—Our results indicated that dry and mesic forests of the Columbia

Plateau have been influenced in a predictable

manner by selective harvesting, fire suppression,

and fire exclusion. Area highly vulnerable to western spruce budworm disturbance increased during

the sample period from an average of 9.3 to 12.0

percent of the ERU (appendix 3). In the historical

condition, 36 percent of the forest area was vulnerable to western spruce budworm disturbance.

In the current condition, 41 percent of the forest area is vulnerable to budworm disturbance

(appendices 2 and 3). Increased vulnerability 

was associated with expanded area of Douglas-fir

cover (appendix 2 and table 29) and increased

area of Douglas-fir and grand fir in multilayered

understories (tables 23, 24, and 25), both predicted consequences of fire exclusion and selective

harvesting (table 27).

Selective harvesting reduced area in old forest

structures (table 20) and reduced abundance of

medium and large trees in all structures (table

21). Consequently, we observed a modest decline

in vulnerability to western pine beetle (type 1)

disturbance of mature and old ponderosa pine.

Figure 83, B, displays an example of reduced area

vulnerable to western pine beetle (type 1) disturbance in a subwatershed of the Lower John Day

subbasin. Area vulnerable to western pine beetle

(type 2) and mountain pine beetle (type 2) disturbance of immature, high-density ponderosa

pine increased during the sample period.

Increased vulnerability was associated with expanded area of ponderosa pine cover in young

multistory structures (appendix 2), a likely consequence of the combined effects of selective harvesting, fire exclusion and suppression, and

domestic livestock grazing. Figure 84, A and B,

provides illustrations of increased area vulnerable

to western pine beetle (type 2) and mountain

pine beetle (type 2) disturbances in subwatersheds

of the Lower John Day and Palouse subbasins,

respectively.

Area highly vulnerable to fir engraver disturbance

increased as a consequence of increased area of

grand fir understories. Area highly vulnerable to

S-group annosum also increased because grand fir

and western hemlock in mixed species cover types

and occurring as understory species increased during the sample period, as did area in these types

with visible logging entry. Area vulnerable to

white pine blister rust (type 1) disturbance of

western white pine declined; decline was likely

the result of blister rust mortality and early selective harvest of western white pine. 

Lower Clark Fork ERU—Analysis of cover

type and structural changes, and vulnerability

characterizations indicated that significant harvesting has occurred in highly productive forests

of this ERU (table 27), but fire exclusion and fire

suppression also have greatly affected conditions

we observe today. In our sample, area with medium and large trees increased during the sample

period (table 21), ERU area in the 90- to 100-

percent crown cover class increased by 23.7 percent (table 22), and ERU area in multilayered

canopies increased by more than 11 percent

(tables 23 and 24). Each change was a predictable

consequence of fire exclusion, especially in an area

where stand-replacing fire historically played such

a significant role.

Area vulnerable to western spruce budworm

increased but the change was not significant at

this reporting scale; a large proportion of the

ERU (56.8 percent) was highly vulnerable in 

the historical coverage, and a similar proportion

(65 percent) is vulnerable in the current condition. The 8.2-percent increase was not statistically

significant because of our small sample size; further sampling is needed to establish the trend.

In the absence of fire, lodgepole pine-dominated

landscapes of the Lower Clark Fork aged and

became more synchronous in their vulnerability

to bark beetle and fire disturbances. With increased overstory and understory grand fir cover

(appendix 2 and table 24) developing during the

sample period, vulnerability to fir engraver disturbance also increased (appendix 3 and table 31),

but the 8.7-percent increase was not statistically

significant because of our small sample size; further sampling is needed to establish the trend.

Similarly, area vulnerable to Armillaria root disease increased by 10 percent, but the change was

not significant because of our small sample size.

268
269

Figure 84—Historical and current maps of vegetation vulnerability to (A) western pine beetle type 2 disturbance in subwatershed 1903 in the Lower John Day subbasin of the Columbia Plateau ERU, and (B) mountain pine beetle type 2 disturbance in

subwatershed 2002 in the Palouse subbasin of the Columbia Plateau ERU. 
270

Northern Cascades ERU—Results of vulnerability characterizations for this ERU indicated

that the primary effect of management during the

sample period was probably timber harvest (table

27) followed by active fire suppression and fire

exclusion. Area occupied by old-forest structures

(table 20) and medium and large trees (table 21)

declined significantly during the sample period, as

did area of ponderosa pine cover (appendix 2 and

table 29). Area of Douglas-fir cover increased significantly, but area of medium and large Douglasfir declined. These results explain much of the

change we observed in vulnerability to pathogen

and insect disturbances.

Vulnerabilities to western pine beetle (type 1) disturbance of mature and old ponderosa pine and

Douglas-fir beetle disturbance both declined with

the loss of medium and large hosts. Connectivity

of highly vulnerable area also declined, indicating

that remaining distributions of medium and large

ponderosa pine and Douglas-fir are fragmented.

Area and connectivity of area vulnerable to western pine beetle (type 2) and mountain pine beetle

(type 2) disturbance of immature, high-density

ponderosa pine also declined owing to reduced

area of ponderosa pine cover in young (new) and

middle-aged (intermediate) structures. Figure 85,

A and B, provides illustrations of increased area

vulnerable to western pine beetle (type 2) and

mountain pine beetle (type 2) disturbances in

subwatersheds of the Naches and Methow subbasins, respectively.

Area vulnerable to western (ponderosa pine)

dwarf mistletoe disturbance declined with the loss

of ponderosa pine overstories (for example, see

fig. 86, A). In contrast, area vulnerable to S-group

annosum root disease disturbance increased during the sample period (fig. 53). The observed

increase in high-vulnerability area was associated

with increased area and stature of grand fir and

Pacific silver fir cover (appendix 2) and increased

area with visible logging entry (table 27).

Northern Glaciated Mountains ERU—

Results of our analysis indicated that fire suppression and exclusion and timber harvest together

produced the changes in vulnerability we

observed. In the historical vegetation coverage,

visible logging entry was apparent on 8.6 percent

of the forested area (table 27 and appendix 2). In

the current condition, visible logging activity was

apparent on 26.5 percent of the forested area. But

old-forest area and area with remnant large trees

did not decline during the sample period (table

20); furthermore, area occupied by medium and

large trees actually increased. We speculate that

because stand-replacing fires were once common

in the ERU, regrowth of forest in the absence of

fire apparently offset some of the effects of harvesting (note the substantial decline in area of

stand-initiation structures in appendix 2). Predicted effects of fire exclusion also were observed:

increased crown cover (table 22), increased

canopy layering (table 23), and increased cover 

of shade-tolerant understory conifers (table 24). 

Area vulnerable to western spruce budworm disturbance increased with increasing cover of grand

fir and subalpine fir and increased canopy layering. In the absence of fire, lodgepole pine-dominated landscapes became more synchronous in

their vulnerability to mountain pine beetle and

fire disturbances. Area and connectivity of area

vulnerable to spruce beetle disturbance also

increased (fig. 49) with increased area, size, and

stature of Engelmann spruce (see fig. 86, B).

As we would expect, area vulnerable to ponderosa 

pine and western larch dwarf mistletoe disturbances declined (appendix 3) with the reduction 

of ponderosa pine and western larch cover (table

29). Figure 87, A, illustrates reduced area vulnerable to western larch dwarf mistletoe disturbance

in a subwatershed of the Swan subbasin. Area vulnerable to Armillaria (see fig. 87, B) and S-group

annosum root diseases increased with increasing

dominance of shade-tolerant overstories and

understories (table 24 and appendix 2). Finally,

area and connectivity of area vulnerable to white

pine blister rust (type 1) disturbance of western

white pine declined (fig. 55 and appendix 3) as a

result of blister rust mortality and early selective

harvest of western white pine (see fig. 88, A). 

Text resumes on page 275
271

Figure 85—Historical and current maps of vegetation vulnerability to (A) western pine beetle type 2 disturbance in subwatershed 10 in the Naches subbasin of the Northern Cascades ERU, and (B) mountain pine beetle type 2 disturbance in subwatershed 55 in the Methow subbasin of the Northern Cascades ERU.
272

Figure 86—Historical and current maps of vegetation vulnerability to (A) western dwarf mistletoe disturbance in subwatershed

35 in the Wenatchee subbasin of the Northern Cascades ERU, and (B) spruce beetle disturbance in subwatershed 0801 in the

Lower Flathead subbasin of the Northern Glaciated Mountains ERU.
273

Figure 87—Historical and current maps of vegetation vulnerability to (A) western larch dwarf mistletoe disturbance in subwatershed 0202 in the Swan subbasin of the Northern Glaciated Mountains ERU, and (B) Armillaria root disease disturbance in

subwatershed 20 in the Kettle subbasin of the Northern Glaciated Mountains ERU.
274

Figure 88—Historical and current maps of vegetation vulnerability to (A) white pine blister rust type 1 disturbance in subwatershed 09 in the Pend Oreille subbasin of the Northern Glaciated Mountains ERU, and (B) western spruce budworm disturbance in subwatershed 1102 in the Palisades subbasin of the Snake Headwaters ERU.
275

Snake Headwaters ERU—Our results suggest

that fire suppression and exclusion, and to a lesser

extent timber harvest, interacted to produce the

changes in vulnerability we observed. In the historical vegetation coverage, no visible logging

entry was apparent for 100 percent of the forested

area (table 27 and appendix 2). In the current

condition, signs of visible current or past logging

were apparent for only 2 percent of the area. Oldforest area and area with remnant large trees declined during the sample period (table 20), but

changes were not statistically significant. Area

occupied by medium and large trees also declined.

Overall, increased area with visible logging could

not account for the changes in vulnerability we

observed.

Area and connectivity of area vulnerable to western spruce budworm disturbance increased dramatically during the sample period (fig. 46 and

appendix 3); increase was associated with increased area of Engelmann spruce-subalpine fir

cover in multilayered canopy arrangements (tables

23 and 24 and appendix 2). Figure 88, B, illustrates increased area vulnerable to western spruce

budworm disturbance in a subwatershed of the

Palisades subbasin. Area and connectivity of area

vulnerable to Douglas-fir beetle disturbance also

increased (appendix 3). Because total area in oldforest structures declined by 40 percent from an

average of 5.2 to 3.1 percent of the ERU (appendix 2), most of the increased area vulnerable to

Douglas-fir beetle disturbance likely was associated with increased abundance of Douglas-fir larger

than 22.9 cm d.b.h. in structural classes other

than old forest.

Area vulnerable to mountain pine beetle (type 1)

disturbance of high density lodgepole pine fell

from an average of 34.6 to 29.2 percent of the

ERU, and area of the lodgepole pine cover type

declined from 15.6 to 11.3 percent of the ERU.

Our results indicated that area of pole, small, and

medium lodgepole pine in both pure and mixed

compositions declined during the sample period.

We know that before and during the period of

our sample, large areas of lodgepole pine forest

were attacked and killed by the mountain pine

beetle. But these results suggest that salvage and

regeneration efforts influenced, at best, less than

half of that area (table 27). Beetle disturbance and

fire exclusion have resulted in cover type conversion of some areas to Engelmann spruce and subalpine fir. This change was corroborated by transition analysis. Area vulnerable to Armillaria root

disease and S-group annosum root disease increased significantly with increasing dominance 

of shade-tolerant overstories and understories

(table 24 and appendix 2). Figure 89, A, illustrates increased area vulnerable to S-group annosum root disease disturbance in a subwatershed 

of the Snake Headwaters subbasin.

Southern Cascades ERU—Our vegetation

analysis and disturbance vulnerability characterizations indicated that the Southern Cascades have

been influenced quite significantly and predictably by timber harvest, fire suppression, and

fire exclusion. In the historical vegetation coverage, 12 percent of the forest area exhibited visible

signs of logging (table 27). In the current condition, 38 percent of the forest area exhibited visible

signs of logging. During the sample period, forest

and woodland area affected by selective harvesting

alone jumped from less than 10 percent to nearly

one-quarter of the area. Overall, the level of timber harvest had little effect on old-forest area,

which increased modestly but nonsignificantly

during the sample period. Area with remnant

large trees declined, but the change was not significant (table 20).

Area with medium and large trees actually increased (table 21). In the absence of fires and

under the influence of selective harvesting, forest

crown cover increased (table 22), forest structures

became highly layered (table 23), and large areas

developed conifer understories (tables 24 and 25).

Expansion of forest area was the result of regrowth of forests cut before our historical vegetation coverage (appendix 2). These results explain

much of the change in vulnerability to pathogen

and insect disturbances that we observed.

In the Southern Cascades, area vulnerable to

western spruce budworm disturbance increased

significantly; increased area was associated with

increased area of multilayered shade-tolerant

understories (tables 23 and 24). But area vulnerable to budworm disturbance amounted to little
276

Figure 89—Historical and current maps of vegetation vulnerability to (A) S-group annosum root disease disturbance in subwatershed 0305 in the Snake Headwaters subbasin of the Snake Headwaters ERU, and (B) laminated root rot disturbance in

subwatershed 30 in the Upper Deschutes subbasin of the Southern Cascades ERU.
277

more than 10 percent of the ERU, even in the

current condition. Area vulnerable to Douglas-fir

beetle and Douglas-fir dwarf mistletoe disturbances declined because area and connectivity 

of patches with medium and large Douglas-fir 

in old forest and other structures declined. In

contrast, area vulnerable to mountain pine beetle

(type 1) disturbance of high-density lodgepole

pine declined by 14 percent from an average of

29.0 to 24.9 percent of the ERU, and area of the

lodgepole pine cover type remained unchanged.

As was the case in the Blue Mountains, our results

indicate that area of lodgepole pine in historically

mixed compositions declined during the sample

period as a result of mountain pine beetle outbreaks and exclusion of regenerative fires.

Area vulnerable to Armillaria root disease and

laminated root rot disturbance increased (fig. 52

and appendix 3); increased area was associated

with expanded area of subalpine fir, grand fir, and

Douglas-fir in pure and mixed species compositions, expanded area of shade-tolerant understories, and increased crown cover of host species.

Figure 89, B, illustrates increased area vulnerable

to laminated root disease disturbance in a subwatershed of the Upper Deschutes subbasin.

Upper Clark Fork ERU—Forest vegetation 

of the Upper Clark Fork ERU has been radically

altered by timber harvest and, to a lesser extent,

fire exclusion. In the historical vegetation coverage, 12 percent of the forest area exhibited visible

signs of logging (table 27 and appendix 2). In the

current condition, 37 percent of the forest area

exhibited visible signs of logging. During the

sample period, forest and woodland area affected

by regeneration and selective harvesting alone

jumped from 10 to 20 percent of the forest area.

Overall, the level of timber harvest had little

effect on old-forest area or area with remnant

large trees (table 20 and appendix 2).

It was apparent from the area of stand-initiation

structures in our historical vegetation coverage

that stand-replacement fires played a major role 

in regenerating and patterning forests, and it is

likely that large areas of new and intermediate

structure were typical historically for these landscapes. Indeed, in the historical condition, 15.9

percent of the ERU area or 18.2 percent of the

forest area was comprised of stand-initiation or

new forest structures, and 70.5 percent of the

ERU area or 80.8 percent of the forest area was

comprised of intermediate (stem exclusion,

understory reinitiation, and young multistory)

forest structures.

Area with medium and large trees remained

unchanged despite the level of timber harvest

(table 21). In the historical condition, 19.7 percent of the ERU area or 22.6 percent of the forest

area was comprised of forest patches with medium and large trees regardless of their structural

affiliation. In the current condition, 17.2 percent

of the ERU area or 20 percent of the forest area

was comprised of forest patches with medium and

large trees. In the absence of fires and under the

influence of selective harvesting forest crown

cover declined (table 22), forest structures became

less layered (table 23), and large areas developed

grass and shrub understories (tables 24 and 25)

where conifer understories once were more typical. Forest area declined by an average of 1 percent of the ERU, but the change was not statistically significant (appendix 2). Even area with

visible dead trees and snags declined significantly

during the sample period (table 26).

Among forested ERUs, the Upper Clark Fork was

one of those most heavily influenced by past timber harvest. It was not surprising that most vulnerability changes were declines (table 31 and

appendix 3). Area and connectivity of area vulnerable to Douglas-fir beetle disturbance declined

owing to reduced crown cover of large and medium Douglas-fir across all forest structural classes.

Figure 90, A, provides an example of reduced area

vulnerable to Douglas-fir beetle disturbance in 

a subwatershed of the Blackfoot subbasin. Area 

vulnerable to western pine beetle (type 1) disturbance of mature and old ponderosa pine also

declined as a result of reduced area in the ponderosa pine cover type and reduced crown cover

of medium and large ponderosa pine across all

forest structural classes.
278

Figure 90—Historical and current maps of vegetation vulnerability to (A) Douglas-fir beetle disturbance in subwatershed 0103

in the Blackfoot subbasin of the Upper Clark Fork ERU, and (B) Douglas-fir dwarf mistletoe disturbance in subwatershed 0902

in the Flint Rock subbasin of the Upper Clark Fork ERU.
279

Area vulnerable to western pine beetle (type 2)

and mountain pine beetle (type 2) disturbance of

immature, high-density ponderosa pine declined

as a result of reduced area in the ponderosa pine

cover type and reduced area of stem-exclusion,

understory reinitiation, and young multistory

structures with ponderosa pine in pure or mixed

compositions. In contrast, area and connectivity

of area vulnerable to fir engraver disturbance

increased during the sample period. High-vulnerability area increased primarily as a result of increased area in the subalpine fir-Engelmann

spruce cover type in all forest structural classes

but stand initiation.

Area vulnerable to Douglas-fir, ponderosa pine,

and western larch dwarf mistletoe disturbances

declined during the sample period. The observed

decline in area of high vulnerability was the result

of significantly reduced patch area and contiguity

with medium and large hosts in multilayered

structures (large trees in the overstory were

removed). Figure 90, B, illustrates reduced 

area vulnerable to Douglas-fir dwarf mistletoe 

disturbance in a subwatershed of the Flint Rock

subbasin.

Upper Klamath ERU—In the historical vegetation coverage, more than one-half (53 percent)

of all forest cover was ponderosa pine (appendix

2), 23 percent of all forest structure was old forest

(table 20), and 38 percent of all forest structures

had at least 10 percent or more crown cover of

large trees (table 20). In the current condition, 

49 percent of all forest cover is ponderosa pine,

21 percent of all forest structure is old forest, 

and 36 percent of all forest structures have at least

10 percent or more crown cover of large trees, but

crown cover of medium and large trees has been

substantially reduced (table 21). Selection cutting

reduced the crown cover of medium and large

trees across 31 percent of the forest area (16 percent of the ERU). Much like the Upper Clark

Fork, in the absence of fires and under the influence of heavy selective harvesting (table 27), 

forest crown cover declined (table 22), forest

structures became less layered (table 23), and

large areas developed grass and shrub understories

(tables 24 and 25) where conifer understories

were once more typical. Forest area declined by 

6 percent from an average of 50.5 to 47.5 percent

of the ERU (appendix 2). Likewise, area with visible dead trees and snags declined significantly

during the sample period (table 26). Among

forested ERUs, the Upper Klamath was probably

the second most heavily influenced by past timber

harvest after the Upper Clark Fork.

Few vulnerability changes were significant, but

one change was particularly revealing (table 31

and appendix 3). Area vulnerable to Schweinitzii

root and butt rot declined by 32 percent from

26.4 to 17.9 percent of the ERU. The observed

decline in area of high vulnerability was the result

of significantly reduced area in the ponderosa

pine cover type and reduced patch area and contiguity with medium and large overstory ponderosa

pine and Douglas-fir. Mean size of patches in the

low vulnerability class rose by 77 percent from an

average of 1551.8 to 2746.9 ha.

Ecological Regionalization

The midscale assessment was designed to evaluate

change in patterns of structural and compositional attributes and links between landscape pattern

change and associated change in insect, pathogen,

and fire (Ottmar and others, in prep.) disturbance

processes. Two criteria make midscale assessment

data particularly relevant to land management

planning: 

1. The scale of observation in our assessment is

equivalent to the scale at which management

occurs; that is, vegetation data were collected 

at a patch scale similar to the scale of the

“stand” used by managers to prescribe and

evaluate management treatments.

2. Historical and current conditions and changes

in conditions were characterized for areas

much larger than forest planning and watershed analysis areas. Midscale assessment findings provide valuable contextual or “big

picture” information for project planning,

watershed analysis, and landscape restoration 

at these spatial scales.

Based on stated purposes (Jensen and Everett

1994, and references therein; Overbay 1992),

ecosystem management activities in the 21st century likely will be motivated by the twin goals of

providing goods, services, and values for people
while conserving ecological integrity. By “conserving ecological integrity,” we mean that ecosystem

management designs do not intentionally encumber or minimize the capacity of any ecosystem to

maintain its structure and organization through

time, especially in the face of natural or human

disturbance. And when designs are recognized via

monitoring and evaluation that do not conserve

integrity, they are quickly replaced with improved

designs in a highly adaptive and learning mode.

To succeed at ecosystem management, it will be

important for land managers to understand the

various contexts of ecosystems they will manage.

Ecosystem management activities will be centered

on accomplishing human goals framed, and to

some extent redirected, by those larger ecological

contexts. Each watershed and landscape will play

a role in some larger context(s).

Forest and rangeland managers throughout the

basin will need a repeatable method to (1) accurately diagnose the degree of departure in watershed or landscape pattern conditions from natural

or more nearly representative conditions for their

specific biophysical environments, and (2) develop management and investment priorities for

allocating scarce resources. A mechanism is needed for differentiating high-priority areas from

low-priority areas for conservation, rehabilitation,

restoration, and production. Departure characterizations, such as we have provided, contribute critical reference information. They do not necessarily provide target or desired future conditions, 

but they do enable assessment of relative risks

associated with greater or lesser departures from

more typical or native biophysical environment

conditions.

We assume that Forest Service and Bureau of

Land Management administrative units within

the basin assessment area are interested in evaluating current vegetation conditions within their

boundaries to determine whether structure, composition, patterns, and associated disturbance

regimes are more or less typical or atypical of

what would occur within specific biophysical

environments under inherent disturbance regimes.

To do that, they must have the ability to differentiate typical from atypical, or more natural conditions from those less so. The diagnostic procedure

must be the same for neighboring yet dissimilar

watersheds in the same administrative area and

for highly similar watersheds in differing administrative areas.

In this midscale assessment, results of change

analysis were reported for province-scale ERUs,

which offered many challenges in interpretation.

High inherent variability of environments pooled

at that very large scale masked considerable

change, and it often was difficult to determine

where sample variation in an ERU ended and

change began. Grouping subwatersheds into 

“subregions” based on similarity of ecological

attributes (regionalization) would organize environmental variability, make change detection

more transparent, and refine estimates of historical variation in vegetation spatial patterns for each

environment.

The basin assessment area contains more than

7,500 subwatersheds, which are not entirely

unique. Many share similar biological and physical features such as geology, landform, hydrology,

major soil taxa, current and potential vegetation,

and climate. From available digital coverages of

broadscale potential vegetation and climate attributes, such as mean annual temperature, total

annual precipitation, and total annual solar radiation (for example, see Hann and others 1997,

Thornton and others 1997), we can group similar

subwatersheds in the basin into ecological subregions according to their similar composition of

attributes by using a multivariate “fingerprinting”

exercise.

Regionalization would employ both agglomerative

and divisive analytical procedures, such as hierarchical cluster analysis and two-way indicator

species analysis, to obtain and validate groupings.

The end result would be a map of all subwatersheds in the basin with each one assigned to a

particular ecological subregion. In this context,

ecological subregions are comprised of a spatially

disjunct population of similar subwatersheds. 

By grouping subwatersheds in this manner, we

assume that vegetation and disturbance patterns

are closely linked with climate and environment,

and that environmental composition of subwatersheds and other large landscapes can be

approximated by potential vegetation and climate

attribute fingerprinting.

280
281

Once a map of ecological subregions of the basin

is created, we can estimate historical variability of

conditions within each subregion. The subregion

map will provide the needed basis for poststratifying sampled subwatersheds and extrapolating

information from sampled subwatersheds of a

subregion to other subwatersheds of the same

subregion. Because it is difficult and costly to

sample historical vegetation structure, composition, and patterns continuously over large geographic areas, and in chronosequence over long

historical time frames, we can substitute a sampling of space (that is, we can sample many similar biophysical environments) for a sampling of

time (versus repeatedly sampling the same environments over many decades or centuries). If we

sample enough areas that are similar in their biophysical features, we should be able to observe a

cross-section or range of conditions typical for relatively short historical periods of similar climatic

regime (Pickett 1989, and references therein).

We can estimate typical ranges of historical conditions in subregions for patch types, such as physiognomic types, forest and rangeland cover types,

structural classes, successional stages, fuel condition classes, crown fire potential classes, fire

behavior attribute classes, and insect and pathogen disturbance vulnerability classes. This

approach assumes no all-pervasive influence that

differs from the historical sample period to the

present day. The typical range of historical conditions for subregions could be estimated by using a

median 75- or 80-percent range or other similar

range metric. We can then summarize the following by ecological subregion: mean, standard error,

and range estimates of the historical condition for

each patch type; class metrics, such as percentage

area, patch density, mean patch size, edge density,

and nearest neighbor distance; and other landscape pattern metrics that might be thought

essential or informative.

Information on the range of condition can be

used to diagnose departure in conditions of any

subwatershed within an ecological subregion. It 

is desirable to develop range-of-condition information for the earliest historical conditions

obtainable, because these are conditions under

which large land areas were least affected by management during any observable period, and area

and connectivity relations of patch types will likely be more rather than less typical of what would

normally occur in each biophysical setting under

a similar climatic regime. 

Additional Validation and Research

To complete the landscape characterizations and

analyses reported here, various methods were

used. Some were tried and true, others were based

on published theory or related applications, and

still others were based partially on established literature and empirical study and partially on field

experience and judgment. We believe that efforts

to assess and refine the accuracy of raw and

derived data and to validate new models and

maps generated by this study would give us and

the agencies benefitting directly from this work

improved insight into the reliability of our characterizations and findings and provide tremendous

future benefits for landscape analysis.

Validation—On this project, time and financial

resources were severely constrained, and efforts

were minimized to field verify interpreted attributes. This was done to meet short timelines and

control costs but at the potential expense of reliability. We made every attempt to ensure quality

and reliability in our data capture; to check for

errors in remotely sensed raw attributes as vegetation coverages were assembled and as new attributes were derived; to check for errors in programs,

scripts, and analysis protocols; and to run routine

error checks for inconsistencies and miscalculations. Despite these efforts, we were unable to

conduct field accuracy assessments of raw and

derived attributes because of constraints. We

believe that our data and methods are acceptably

reliable, but the reliability of each should be evaluated. To that end, we suggest the following as

priority validation needs:

• Assess the accuracy of the following abridged

list of photointerpreted forest patch attributes:

total and overstory crown cover, canopy layers,

riparian and wetland status, visible logging

entry, overstory and understory size class, overstory and understory species, and dead tree and
snag abundance; and nonforest attributes: nonforest overstory species, overstory crown cover,

and tree and shrub cover of herbland and

shrubland types.

• Assess the accuracy of derived forest and range

cover types, structural classes, and potential

vegetation types; correct classification errors

and revise map coverages as needed.

• Field verify by random sampling the patch vulnerability values for each insect and pathogen

disturbance modeled, fuel conditions, and

potential fire behavior and smoke production

attributes (see Ottmar and others, in prep.).

Vegetation research—To develop vegetation

management strategies (including no active management) and activities for ecosystems that conserve native species and natural processes and

their effects, resource managers will need to be

knowledgeable of the ecological ramifications of

natural and management disturbances on landscape patterns and processes. Future Forest

Service and Bureau of Land Management project

planning may call for more intensive ecological

characterization of planning areas than has

occurred previously.

This study is a first attempt at a midscale ecological assessment of the basin. It represents a first

characterization of the historical range variability

of ERUs, and a first characterization of recent

departure of forest and rangeland vegetation 

patterns and forest vulnerability to insect and

pathogen disturbances. At the close of the study,

many basic and applied research questions remain

unanswered. Further analysis of this landmark

data set will reveal new information useful to conservation and management of basin ecosystems.

We propose the following additional research that

can be accomplished by building on databases

and models established through this study:

• Develop an ecological regionalization of all

subwatersheds in the basin. Ecological subregions would provide a powerful basis for

extrapolating information on reference conditions and a much improved basis for change

detection analysis in either assessment or monitoring modes.

• Compute ranges of historical structure, composition, pattern, and disturbance vulnerability

conditions for each ecological subregion.

• Evaluate through similarity analysis, structural

and compositional change of current and historical subwatershed pairs to detect significant

compositional change and determine direction

and magnitude of change.

• Evaluate average similarity among all subwatershed pairs at several pooling scales, and test for

differences between average historical and average current similarity to detect compositional

trend of subwatersheds within a pooling stratum.

• Use compositional attribute data from the similarity analysis, above, to ordinate (DECORANA or CANOCO) and graphically display

patterns of change in attribute space.

• Examine and contrast variation in landscape

patterns and disturbance processes by PVT,

topographic and physiographic setting, and

management history.

• Evaluate pathways of vegetation change at a

subregion scale, through detailed analysis of

change in structure and composition and by

using transition analysis, to improve predictive

modeling of future landscape change.

• Evaluate the effects of recent change in spatial

patterns of composition and structure on spatial patterns of vulnerability to insect, pathogen, and fire disturbances.

• Develop reliable, continuous, field-verified,

midscale (1:24,000) ecological land unit and

PVT maps for public lands in the basin.

• For ecological subregions, classify habitat values of cover-structure patch types for all historical and current subwatershed pairs, initially

for threatened, endangered, sensitive, and 

candidate species and other terrestrial species

where habitat and environmental correlations

are reasonably well established. Use habitat and

environmental correlates associated with other

midscale GIS map coverages as needed to complete the classifications. For all pairs of midscale subwatersheds, evaluate and report trends

282
283

in area and connectivity of habitats. Quantify

effects of predicted habitat changes on wildlife

species diversity during the sample period.

Correlate predicted results with known status

of species, especially currently listed and candidate species.

• For ecological subregions, use historical and

current subwatershed vegetation conditions

and associated vulnerabilities to insect, pathogen, and fire disturbances as a basis for evaluating risks associated with alternative landscape

configurations or desired future conditions.

Rank subwatershed conditions within each

subregion according to their risk of crown fires,

disease, and insect disturbance vulnerabilities.

This would be especially useful to land management planning, watershed assessment, and

project planning efforts.

• Develop reliable, continuous, field-verified,

midscale (1:24,000) fire regime maps for ecological and units of the basin, and link map

units with potential fire behavior and smoke

emissions information. Correlate fire regimes

with biophysical environmental characteristics

and potential vegetation.

• Assess the relative contribution of social and

biophysical factors to landscape change. Also

assess interactions among factors by relating

landscape changes, their biophysical settings, 

or individually significant ecosystem elements

to social and biophysical drivers of change.

Significant ecosystem elements can be those

things people care a great deal about, elements

important to a great many species, or elements

that have experienced great change and are particularly vulnerable to more change.

• Determine the best approaches for extrapolating broadscale (Hann and others 1997) and

midscale landscape data from place to place.

For example, determine the extent to which

broadscale coverages can be used to guide

extrapolation from one place to the next at 

the midscale, and the extent to which midscale

coverages help to interpret past changes and

vulnerability to future changes in project areas

at the fine scale.

• Examine alternative approaches to characterizing natural or historical range variability in

vegetation spatial patterns.

• Examine the geographical and biophysical 

settings of nonforest types to determine why

some settings and types appear to be more

prone than others to change. 

• Develop alternative methods for characterizing

the spatial distribution, predictability, area, and

synergism among disturbance regimes and

patch dynamics that incorporate (1) the different agents of disturbance, their interactions,

their spatial patterning and extent; (2) disturbance effects on species richness, the distribution of dominance, community structure, 

and genetic diversity; (3) effects on filling 

and change within disturbed and undisturbed

patches; (4) relations among patches of a given

type and the matrix; and (5) flows of organisms, materials, and energy among patches

(refer to the rich theoretical foundation developed in Pickett and White [1985]).

• Use these midscale data to validate and extend 

the utility of vegetation and disturbance dynamics simulation models such as CRBSUM

(Keane and others 1996). The CRBSUM

model already has a framework for simulating

the effects of multiple agents of disturbance on

landscape patterns and could be readily extended to include contagious spread and other spatial characteristics of disturbance, particularly if

midscale vegetation change results were used to

develop and test the new subroutines and related hypotheses.

Insect and pathogen research—For human

valuation of ecosystem status, forest insect and

pathogen disturbances can be viewed as producing favorable or unfavorable results. From the

standpoint of ecological structures and functioning, disturbances at one level may provide great

variety in living and dead structure, and the

agents themselves are the key to many vital future

processes. At a much higher level of disturbance,

structure and process needs may be more than

satisfied at the expense of other forest values

important or essential to human needs.
In recent decades, resource managers have

attempted to actively manipulate stand- and 

landscape-level insect and disease conditions (that

is, the amount of insect or pathogen disturbance

they wanted to allow) by using direct suppression

and prevention strategies. Suppression activities

typically employed chemical insecticides or biological control agents such as bacteria or viruses;

prevention was accomplished through silvicultural

manipulations of stand-level species composition

and structure.

Little attention has been given to landscape vegetation patterns, processes, organisms, and interactions whose function is to naturally regulate

disturbances and the agents responsible for them.

For example, fires historically played a key role in

regulating the density and composition of forests,

especially dry and mesic forests. Fires were directly involved in determining where shade-tolerant

true firs and Douglas-fir would typically grow,

thereby shaping the population dynamics and 

disturbance regime characteristics of forest insects

such as the western spruce budworm and the

Douglas-fir tussock moth. Fires of varying intensity and extent determined, by influencing the

landscape patterns of hosts, where Armillaria

laminated root rot, and S- and P-group annosum

root diseases played a significant role in snag production, canopy gap development, and coarse

wood recruitment.

In addition, many forest insects and pathogens

capable of altering forest structure and composition have numerous natural enemies, and little is

known of the environmental factors, patch-scale

vegetation conditions, and landscape patterns

favoring their survival and prosperity. Critical

gaps exist in our knowledge of (1) insect and

pathogen population dynamics under managed,

unmanaged, and “natural” conditions; (2) regulatory processes, organisms, and interactions associated with natural insect and pathogen disturbances; (3) interactions among insect, pathogen,

and fire disturbance processes, climate, and management activities; and (4) functional roles of

insects and pathogens under managed, unmanaged, and “natural” scenarios. Important research

emphases follow:

• Develop decision-support tools for stand and

landscape management to predict insect and

pathogen responses to natural and management disturbances.

• Survey the natural enemies of native and

important nonnative pathogens and insects.

Learn their habitat requirements, associations,

and responses to changing landscape patterns

and environments; study immigration and

emigration processes, and habitat and environmental constraints.

• Examine the community ecology of native 

and important nonnative insects and

pathogens in each of the major forest plant

associations. Discover changes in functional

roles and dynamics along various successional

trajectories.

• Study the functional roles of the major native

and important nonnative root pathogens,

dwarf mistletoes, bark beetles, defoliators, stem

decays, and rusts in (1) forest succession, (2)

wildlife habitat development, (3) coarse wood

recruitment, and (4) carbon and nutrient

cycling in each of the major plant associations

of the basin.

• Experimentally examine options for developing

replacement wildlife microhabitat structures by

using native organisms and microbial successional processes in areas currently depauperate

of such structures (Parks and others 1996a,

1996b).

• Study the effects of the more extreme oscillations in climatic conditions on native insect

and pathogen population dynamics and associated disturbances for major plant-association

groups of the basin. Learn also how such oscillations affect their natural enemies.

• For each of the major plant-association groups

and their successional communities, study the

effects of conventional management practices

on insect and pathogen populations and their

natural enemies.

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285

• Evaluate conventional and new management

techniques to determine the extent to which

each can be used to modify forest structure and

composition (living and dead), while the beneficial roles of pathogens and insects and their

natural enemies are maintained and long-term

adverse effects on soils, streams, and native

species diversity are minimized.
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287

The primary utility of landscape assessments and

change analysis summaries is in understanding 

the characteristics of ecosystems that we manage

(Morgan and others 1994). Knowledge of landscape pattern change at regional, provincial, and

subregional scales provides critical context for

regional and forest planning and watershed analysis and project-level planning, and valuable

insight for ecological restoration, conservation,

and monitoring decisions and activities. Summaries of landscape pattern change provide

answers to simple but vital questions, such as

How important is the type and degree of change

noted in one place relative to the broader picture?

or How important is a particular patch type (for

example, ponderosa pine-old forest, single story)

within a given watershed, subbasin, or subregion?

Landscape change analysis provides an essential

empirical basis to evaluate the historical and current rarity of landscape pattern features and is an

aid in determining how representative current

patterns are in comparison with recent historical

conditions.

The basin assessment area is large, and we have

summarized a great many changes in vegetation

condition and associated change in vulnerability

to insect and pathogen disturbances. Ottmar and

others (in prep.) will similarly summarize change

in fire behavior attributes and potential smoke

emissions associated with these same vegetation

changes. But here we will focus on some of the

most important generalities lest we lose them in 

a sea of detail.

Most dramatic of all changes in physiognomic

conditions was the across-the-board regional

decline in shrubland area. The greatest declines

were to colline and montane low-medium shrub

cover types in both open and closed structural

conditions. Losses of native shrublands resulted

from a variety of factors, including forest and

woodland expansion as observed in the Blue

Mountains and Northern Great Basin ERUs,

cropland expansion as in the Northern Great

Basin ERU, and conversion to seminative and

nonnative herbland as in the Owyhee Uplands,

Snake Headwaters, and Southern Cascades ERUs.

Loss of historical dry herblands to agriculture was

equally dramatic but had already been sustained

by the start of our historical vegetation coverage

(Hann and others 1997). During our sample period, herbland area actually increased modestly, but

most increase was in the form of seminative or

nonnative herbland, and it was to the detriment

of native shrublands.

Forest cover increased substantially in several

ERUs at the expense of shrubland and herbland,

and woodland cover rose sharply in all ERUs

where woodland was more than a minor physiognomic condition. It was clear that the distribution

of forest and woodland physiognomies had been

altered and that this change could be observed at

subwatershed to regional scales; our results indicated that direct fire suppression, indirect exclusion of fire, and domestic livestock grazing were

primary influences.

Predicted shifts from early to late seral species

were evident in many ERUs. Most of the observed change in ponderosa pine, western larch,

and Douglas-fir cover was associated with decline

in area and connectivity of patches with medium

and large trees of these species. We also observed

precipitous decline in area and connectivity of

western white pine cover in northern Idaho and

northwestern Montana, the heart of the historical

Conclusions
range. Loss of white pine cover was attributable 

to early selective and regeneration harvesting and

mortality associated with white pine blister rust

infection and mountain pine beetle infestation.

Overstories and understories comprised of shadetolerant species were evident in many forested

ERUs; across the basin, forests are now more contagiously dominated by shade-tolerant conifers

than was true in the historical condition. Lacking

significant forest pattern restoration, we can

expect that insects and pathogens (for example,

the western spruce budworm, Douglas-fir tussock

moth, fir engraver, Douglas-fir dwarf mistletoe,

Armillaria root disease, and S-group annosum

root disease) favored by increased areal extent and

contiguity of patches of shade-tolerant conifers

will have an expanding role in shaping forest patterns by their direct disturbance influence, via

mortality inputs, and by indirect but substantial

influence on fire regimes.

Area in old-forest structures declined sharply in

all forested ERUs where they historically occupied

more than a minor area. The same was true of

remnant large trees associated with structural

classes other than old forest. But when we evaluated change in area with medium and large trees,

regardless of their structural affiliation (tables 20

and 21), we observed what we believe was the

most important change in structure in several

ERUs. In the Blue Mountains, Northern

Cascades, and Upper Klamath ERUs, decline 

in area with medium and large trees both overshadowed and augmented losses to historical 

old-forest area.

Our results suggested that 20th-century timber

harvest activities did not target old forest; instead,

timber harvest targeted medium- and large-sized

trees regardless of their structural affiliation. They

were most economical to harvest and most accessible, sawmills were tooled to handle them most

efficiently and economically, and timber sales

were most viable when offered volumes were in

the form of medium and large trees. Our results

indicated that medium and large trees were harvested wherever they stood; they were often but

not always associated with old forest.

There are at least two important ramifications 

of this observation. First, it has been broadly

assumed by forest managers and ecologists alike,

that large trees are principally associated with old

forest, where they obviously contribute important

living and dead structure. But our results indicate

that large (and medium) trees were, in several

ERUs, widely distributed in other forest structures

as a conspicuous remnant after stand-replacing

disturbance. In some cases, large trees comprised

as much as 24 percent of the crown cover of forest structures that were not old and, although

subordinate to other features, contributed important living and dead structure. Hence, many nonold-forest structures of historical forest landscapes

contributed some measure of late-successional

functionality and connectivity with old forest.

Second, in those ERUs where old-forest area and

area with large trees has been depleted, the present and future supply of medium and large dead

trees as snags and down logs has been substantially diminished. This is especially true of snags and

down logs of early seral species, such as ponderosa

pine, western larch, Douglas-fir, western white

pine, and sugar pine—all preferred commercial

species that have been the primary focus of 20thcentury harvest activities. Owing to the magnitude of the deficit, it is likely that terrestrial and

aquatic species and ecological processes requiring

medium and large dead tree structure may be

adversely influenced by this current and future

reduction, unless steps are taken to remedy the

shortfall through replacement.

Along with reduced area containing large overstory trees, we observed a marked reduction in landscape vulnerability to dwarf mistletoes of early

seral species such as ponderosa pine and western

larch. It was generally apparent from comparisons

of historical and current subwatersheds that timber harvest reduced or eliminated overstory crown

cover of large trees of early seral species while one

or more (often shade-tolerant) coniferous understory strata developed. 

As expected, we observed that area in stand-initiation (new forest) structures dramatically declined

in several ERUs (Central Idaho Mountains, Lower

Clark Fork, Northern Glaciated Mountains, and

288
289

Upper Clark Fork) where stand-replacing fires

once were relatively common events. Such reduction was evident despite widespread timber harvest activity. Along with declining area in

stand-initiation and old-forest structures, we

observed sharply increased area and connectivity

of intermediate forest structure, including stemexclusion, understory reinitiation, and young

multistory structures, across the basin.

Results from nearly all forested ERUs indicated

that the absence of fire by direct suppression or

exclusion has had profound effects on forest and

woodland area and connectivity at subwatershed

to regional scales. The history and legacy of fire

suppression and prevention programs is well documented, but the effect of fire exclusion has been

more difficult to pin down because many interacting factors played a role in excluding fire from

fire-dependent ecosystems. As a result, it is possible and even likely that the efficacy of fire prevention and suppression programs has been overstated, and the role of factors responsible for

exclusion of fire has been understated. Key factors

responsible for fire exclusion were the widespread

elimination of flashy fuels through extensive

domestic livestock grazing and overgrazing, especially in the first half of the 20th century (Hann

and other 1997, and references therein; Skovlin

and Thomas 1995; Wissmar and others 1994a,

1994b); reduced connectivity of fire-prone landscapes through placement of extensive road networks; settlement of fire-prone interior valleys

and subsequent conversion to agriculture by

European immigrants; and the movement onto

reservations of Native Americans, who frequently

used fire as a management tool (Robbins and

Wolf 1994, Woods and Horstman 1996).

Many direct effects of fire exclusion and fire suppression were observed in our results. In appendix

2 and figure 25, we show increased area and connectivity of forest and woodland physiognomies.

Total forest and woodland crown cover increased

in many forested ERUs (table 22 and fig. 39), as

did area with more than two canopy layers (table

23 and fig. 40). Area with conifer understories

increased (table 25), especially area with shadetolerant conifer understories (table 24 and fig.

41).

Throughout the basin, current forests and rangelands are more fragmented than were landscapes

of our historical condition. Whether patch types

are cover types, structural classes, or cover typestructural class couplets, patch densities are now

higher, mean patch sizes are smaller, the largest

patch of any given cover type or structural class 

is generally smaller, and edge density is greater.

These combined outcomes point to landscape

fragmentation and reduced patch type connectivity, primarily as a consequence of timber harvest

activities and road construction. Contagion, interspersion, and juxtaposition metrics displayed in

table 19 confirm the presence of highly fragmented landscapes in the current condition and point

to increased complexity in managed landscape

patterns. The converse appears to be true in roadless area and wilderness-dominated subwatersheds, where patch type connectivity generally

increased and landscape patterns were simplified.
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291

More than 400 people assisted us in making the

midscale assessment of the basin. Without their

hard work, long hours, humor, and commitment

over 3.5 years, this assessment would not have

taken place. We extend our thanks to Lynn Kaney

and Mike Stimak, who provided uncommon leadership for the entire aerial photo research, acquisition, interpretation, and vegetation mapping

effort. They organized, trained, and managed 

the workload of photointerpretive (PI) teams

throughout the basin in mapping more than 

3.2 million hectares of vegetation twice–once for

the historical condition, and once for the current

condition. Lynn and Mike managed team productivity, morale, and timelines, supervised editing of

line work at remote interpretive sites, inventoried

and archived all historical aerial photos, and

returned all borrowed current photography. They

also conducted quality control inspections in

Washington, Idaho, and Montana and provided 

a much needed cornerstone for the midscale data

capture.

Glen Truscott coordinated and administered the

Coeur d’Alene aerial photo research operation

from the photo research phase, through completion of all midscale photointerpretations, to final

photo storage. Glenn submitted and tracked all

requisitions, managed an enormous aerial photo

database, and shipped and received photos, supplies, maps, and orthophoto quads from interpretive sites all across the basin. He also took care of

an endless list of onerous administrative odds and

ends that led to successful completion of the 

project.

Marty Dumpis was responsible for onsite quality 

control inspection of PI teams in southern Idaho.

He also voluntarily filled the void in Boise of

reviewing, editing, and coordinating the flow of

thousands of manuscripts submitted by PI teams

for digitizing. Without his efforts there, the digitization process would have taken much longer. 

In addition to these activities, he lead a PI team

when midscale valley bottom map coverages were

developed, assisted with aerial photo research and

acquisition, and helped numerous Forest Service

units with the borrowing and returning of stereoscopes when their PI teams lacked quality equipment.

John Lampereur was important to the smooth

beginning of the aerial photointerpretation

process. He played a lead role in data capture

associated with the Eastside Forest Ecosystem

Health Assessment, and he applied his knowledge

and experience to our advantage. John helped

lead the photointerpretation effort in Oregon and

Washington by doing photo research and acquisition, training PI teams, and establishing the blueprint for the Coeur d’Alene operation. John also

was responsible for quality control inspections of

all PI teams in Oregon before returning to his

home unit.

Talent and in-kind support (hardware, software,

work space, clerical and administrative support,

phones, faxes, patience, and moral support) were

provided by Forest Service (FS) and Bureau of

Land Management (BLM) units throughout

Oregon, Washington, Idaho, and Montana. We

attempted to keep track of each of the major contributors; our most sincere apology if we have

missed anyone. For each task in the midscale

assessment, we list administrative units that supplied staff to complete work and names of those

who helped us. Our thanks and deep appreciation

to all.

Acknowledgments
Task 1—Delineation of subwatersheds and

watersheds within subbasins.

Units—ICBEMP Spatial Team, FS—Pacific

Northwest Regional Office, Idaho Water

Resources, Payette National Forest (NF), 

FS—Northern Regional Office, ICBEMP—

Landscape Ecology Team, Lolo NF, Bitteroot

NF, Nez Perce NF, Sawtooth NF, Clearwater

NF, Idaho Panhandle NF, Aerial Photography

Field Office (FSA)—Salt Lake City, UT,

Wasatch NF, Salmon NF, Montana Heritage

Program, and Boise NF.

People—Hal Anderson, Leigh Bailey, Bob

Barreiros, Bob Bond, Ken Brewer, Paul

Callahan, Ervin Cowley, Linda Davis, Gary

Decker, Darl Enger, Kim Foiles, Al Galbraith,

Nick Gerhardt, Dave Gruenhagen, Valdon

Hancock, Liz Hill, Dick Jones, Bob Kasun, Jay

Kurth, Cary Lorimar, Jan McCormick, Letty

Miller, Paul Newman, Mark Novak, Marilyn

O’Dell, Bill Ondrechen, Rick Patten, Brian

Paulson, Ann Puffer, Rick Reynolds, Betsy

Riefenberger, Bill Sabo, Kathy Schonn-Rollins,

Lisa Stern, John Thorton, John Waters, and

Andy Wilson.

Task 2—Midscale photogrammetric sampling

of vegetation (aerial photointerpretation).

Units—Nationwide Forestry Application

Program (NFAP)—Salt Lake City, FS—

Washington Office, Humboldt NF, Colville

BIA, Colville NF, BLM—Coeur D’Alene.

People—Jule Caylor, Thomas Dechert, Barry

Dutton, Ted Felt, Mike Hoppus, Lynn Kaney,

Brian Kelly, Will Koenitzer, Robert Long,

Larry Nall, Mike Stimak, and James Ward. 

Units—Farm Service Agency (FSA)—Aerial

Photo Field Office.

People—Steve Calchera, Mary Carlson,

Cindy Christensen, Doug Clark, Charlie

Clement, Ann Craig, Linda Dammaschke,

Ronald Dickson, Kathy Erickson, Mary

Faulkner, Jim Fisher, Tim Fullmer, Judy Gale,

Sherry Holyoak, Ken Koehler, Rebecca Larsen,

Bob Lear, Wayne London, Linda McDonald,

Sharon McIff, Valeen Merrill, Bonnie Mullen,

Mike Myers, David Parry, Amy Penechar,

Donna Pola, Marla Jo Porter, Jerry Roach, Rick

Rozsa, Mark Rymer, Mark Schneller, Brenda

Simpson, Jeanette Tolliver, and Wynn Zundel.

Units—Beaverhead NF, Deerlodge NF,

Bitterroot NF, BLM—Boise District, Boise NF,

BLM—Branch of Mapping Science—Denver

Federal Center, Bridger-Teton NF, BLM—

Burley District, BLM—Burns District,

Caribou NF, and Challis-Salmon NF.

People—Jones Amundson, Bob Arnold, John

G. Augsburger, Bill Baer, Gail Baer, Douglas

Basford, Tom Bills, Dorothy Bonner, Debra

Bowen, Art Burbank, Dean Burnham, Joan

Caffaney, Russ Camper, Kimberly Chipman,

Jim Clark, Mary Clark, Jack Cornelisse, Brad

Crompton, Larry Cunningham, Steve Davis,

Dan Dolata, John Dormus, Shana Driscoll,

Dennis Duehren, Russ Edelen, Phil

Eisenhauer, Susan Erwin, Donna Fornenell,

John Fowler, Kurtis Fruit, John Fuller, Gerhard

Gareis, Sylvia Gorski, Bill Goslin, Galen

Green, Ron Guitierrez, Melissa Habbit, Rick

Hall, Shelly Haaland, Brad Harris, Carol

Harvey, Wayne Hecker, Lenny Hinman, Ed

Horn, Susan Johnson, John Joy, Steve Kujula,

Curt Leet, Ruth Lewis, Nate Luibrand, Paul

Makela, Dave Marben, Melani May, Rob

Mickleson, Wanda Montgomery, Shawn

Muldoon, Penny Myers, Norm Nass, John

Petty, Bruce Schuelke, Paul Seronka, Marsha

Sine, Danny Rafferty, Steve Rawlings,

Constance Slusser, Charlie Tackman, Elroy

Taylor, Nancy Taylor-Grant, Jim Tharp, Ken

Thompson, Pete Van Wyhee, Ray Warburton,

and Brian Watts.

Units—Clearwater NF, Colville NF, BLM—

Coeur D’Alene District, BLM—Salmon

District, Cottonwood Resource Area,

Deschutes NF, Flathead NF, and Fremont NF.

People—Pete Bauer, Sonny Castille, Van

Davis, Glenn Elzinga, Jerry Haaland, Reed

Heckly, Jerry Hess, Beth Hodder-Koss, Crispin

Holland, Linda Jensen, Gary Kiefer, Mark

Klinke, Scott Lusk, Bill Marcure, Mitchell

Maxwell, Pat McKinnon, Sue McWilliams,

292
293

Ron Mellem, Chuck Morganstean, Brian

Palmer, Shawn Pardue, James Parker, Wes

Paulson, Robert Petersen, Don Polanski, H.E.

“Puff” Puffenberger, Lisa Rayner, Jim Rosetti,

Mary Rourke, Dave Schmitt, Kevin Searle,

Stephanie Snook, Heidi Trechsel, Andrea

Unruh, Geoff Vevera, Dave Wallace, Lonnie

Way, Bill Wulf, and Steve Zieroth.

Units—Helena NF, BLM—Idaho Falls

District, Idaho Panhandle NF.

People—Karen Aslett, Jeri Beck, Anita

Delcarlo, Donna Hawkins, Darwin Jeppesen,

Jack Kaiser, Pat Koelsch, Keith Leatherman,

Vicky MacLean, Charlie McKenna, Jon

Michelson, Dan Nelson, Craig Norris, Carl

Ritchie, John Ruebke, Sally Russell, Melanie

Scott, Sharon Scott, Mike Stoddard, Dan

Studer, Deena Teel.

Units—BLM—Idaho State Office, Kootenai

NF, Lolo NF, Malheur NF, BLM—Missoula

District, Garnet Resource Area, Nez Perce NF,

and Ochoco NF.

People—Sue Alley, Marilyn Allison, Dale

Applegate, Kendall Boyd, Dan Browder, Troy

Bunch, Tom Carlsen, Shirley Chase, Alexia

Cochrane, Paul Cuddy, Tom Daer, Steve

Dagger, Joe Denham, Tony Drahos, Tim

Drugmiller, Duane Ecker, Barbara Fontaine,

Dave Hayes, Buz Hettick, Dan Hinson, Myron

Holland, Debbie Job, Susan Johnson, Ella

Kidder, Kurt Kluegel, Dennis Leonard,

Marjorie Lubinski, Bill McArthur, Janice

McConnell, Jeff Mork, Mary Miles, Joe

Murphy, Dave Olsen, Brian Paulson, Rich

Prittie, Dan Rasmussen, Janet Reynolds, Rick

Reynolds, Alan Rodehorst, Stephanie Singer,

Mike Small, Larry Smith, Margaret Smith,

Karen Tamberg, Dan Thompson, Virginia

Wait-Hudiburgh, Craig Waldron, John

Weinert, Bill Yeager, Beverly Yelczyn, Michele

Wasienko, and Doug Wulff.

Units—Okanogan NF, BLM—Oregon State

Office, Payette NF, Sawtooth NF, BLM—

Shoshone District, Targhee NF, Umatilla NF,

BLM—Vale District, and Wallowa-Whitman

NF.

People—Ted Albert, Susan Alford, Donna

Aschenbrenner, John Ash, Julie Baird, Al

Bammann, Butch Bosley, Pam Braciszeski,

Clair Button, Lottie Child, Kathleen

Countryman, Eric Cruikshank, Greg Danly,

Lynn Danly, Ted Demetriades, Gary Dillavou,

Steve Donnelly, Pam Fahey, Jean Findley, Brian

Fischer, Ed Fischer, Glenn Fischer, Gerald

Garrett, Jerry Greer, Gerald Haasl, Chris

Hamilton, Matt Howard, Maureen Hyzer,

Nancy Johnson, Gary Kaiser, Lisa Kennedy,

Greg Knott, Daniel Little, Clark Lucas,

Michael Marsh, Michael Mauntel, Paul

McClain, Gene McLaughlin, Jack Melland,

Ray Mitchell, Toby Mix Kaylene Monson,

Dave Motanic, Annette Pepin, Sharon Phillips,

Mike Piazza, Charlotte Quarnberg, Jim

Reinholt, Richard Roberson, Tina Ruffing,

Philip Rumpel, Jon Sadowski, Mike Saras,

John Schelly, Jim Simpson, Rick Sorensen, Ken

Thacker, Laurie Thorp, John Townsley, Tim

Vugteveen, Sherry Watts, Jack Wendroth,

Doug Williams, Alissa Wilson, Walter Wood,

Gary Wright, and Teresa Wurschmidt.

Units—Winema NF, FS—Pacific Northwest

Reserach Station—Wenatchee FSL, FS—

Intermountain Research Station—Boise,

ICBEMP Spatial Team, and Wenatchee NF.

People—Steven Abate, Gary Alvarado, Tom

Anderson, Mike Andler, Paul Appel, Howard

Banks, Glynnis Bauer, Pierre Dawson, Glenn

Ferrier, Brent Foster, Suzanne Francoeur,

Dianna Gettinger, Ben Gonzales, William

Hatcher, Jerry Haugen, Becky Heath, Deb

Hennessey, Jerry Hunter, Mike Kaibel, Scott

Kreiter, Amy Jo Krommes, John Lane, Mike

Mathews, Craig Miller, Kevin Moore, Heather

Murphy, Pete Ohlsen, Andy Peavy, Jean

Postlethwaite, Cindy Raekes, Gary Raines,

Claire Reiter, Brion Salter, Greg Shannon,

Kevin Smith, Ginni Stoddard, and Steve

Trulove.

Task 3—Midscale potential vegetation type

(PVT) modeling.

Units—FS—Pacific Northwest Research

Station—Wenatchee FSL, FS—Intermountain

Research Station—Missoula Fire Lab, Lolo NF,

and FS—Rocky Mountain Regional Office.
People—Scott Kreiter, Paul Callahan, Marty

Dumpis, Cecilia McNicoll, Craig Miller,

Michelle Wasienko, and David Wheeler.

Task 4—Midscale photogrammetric valley bottom characterizations.

Units—Idaho Panhandle NF, Boise NF, FS—

Northern Regional Office, Flathead NF,

Colville NF, Humboldt NF, and Winema NF.

People—Dave Arbach, Vicki Bachurski,

Christopher Beebe, Van Davis, Marty Dumpis,

Dave Ensign, David Fredrickson, John Fuller,

Kathy Heffner, Dev Hill, Liz Hill, John

Hoffland, Kathy Hyde, John Ingebretson,

Jeffery Jones, Bob Kasun, Don Kole, John

Lane, Allen Layman, William Marcure, Larry

Meyer, Toby Mix, Zachary Mondry, Dave

Motanic, Shawn Muldoon, Tim Murphy, Craig

Norris, Sarah Pearson, Jim Pudelka, Carl

Ritchie, Ruth Robberson, Sally Russell, Bill

Schauer, Jim Sharp, Jim Skranak, Lisa Stern,

Dan Studer, Steve Trulove, Tim Vugteveen,

and Ray Warburton.

Task 5—Midscale historical and current vegetation and valley bottom maps—scanning, digitizing, line work editing, data entry, logistical

coordination, and manuscript preparation.

Units—Idaho Panhandle NF, Flathead NF,

NF Northern Regional Office, and Kootenai

NF.

People—Dennis Adams, Diane Amato, Jim

Barber, Julie Bartlett, Jeri Beck, Elizabeth

Behrends, Debbie Bozarth, Sue Bristol, Linda

Davis, Ron Deon, Alan Dohmen, Risa Devore,

Dan Frigard, Ben Greeson, Gerry Ann

Howlett, Michael Leigh, Mary Manning,

Anthony Matthews, Brad Mingay, Susan

Nicholas, Rosa Nygaard, Mary Ellen Pearce,

Peggy Polichio, Dale Schrempp, Mike Stimak,

Greg Tensmeyer, Debra Tirmenstein, Glen

Truscott, Randy Wakefield, and Barb Young.

Task 6—Photo acquisition and logistical 

support.

Units—FS—Pacific Northwest Regional

Office, ICBEMP—Administrative Team, 

FS—Northern Regional Office, NFAPSalt Lake City, FS—Washington Office,

Humboldt NF, Yakima BIA, NRCS—

Goldendale, WA, FSA—Spokane, Boise NF,

Colville NF, Humboldt NF, Lolo NF,

Wenatchee NF, FS—Inter-mountain Research

Station—Missoula Fire Lab, BLM—Coeur

D’Alene District, FS—Northeast Regional

Office—State and Private Forestry, and U.S.

Geological Survey—Spokane.

People—Vi Agnew, Dennis Adams, Diane

Amato, Kerry Arneson, Julie Bartlett, Elizabeth

Behrends, Elisa Benner, Brad Bleckwenn,

Susan Bristol, Carolyn Brooks, Suzanne

Burnside, Paul Callahan, Jule Caylor, Bill

Cook, John Cosolito, Roger Crystal, Mike

Daly, Linda Davis, Jan Deitz, Anita Del Carlo,

Ron Deon, Risa Devore, Cathy Dickinson,

Dale Dieter, Alan Dohmen, Dan Dolatta,

Marty Dumpis, Joe Encinas, Vicki English,

Leanne Eno, Carol Fisher, Dan Frigard, Dick

Gerhardus, Arlene Green, Barb Hansen, Jodi

Hastings, Kathy Heffner, Steve Hogue, Myron

Holland, Mike Hoppus, Patricia House, Gerry

Ann Howlett, Chris Jacobson, Lynn Kaney,

Julie Kincheloe, Mary Knutson, Don Kole,

Linda Lampman, John Lampereur, Sherri

Lionberger, Henry Logsdon, Robin Loper,

Laurene MacDonald, Anthony Matthews, Dan

Mayer, Janice McConnell, Jackie McGillivrary,

Judy McHugh, Cecilia McNicoll, Larry Meyer,

Craig Miller, Brad Mingay, Dan Misciagna,

Kenda Morgan, Terrie Morelli, Cindy

Muhlhausen, Jack O’Brien III, Brian Paulson,

Sarah Pearson, Ralph Perkins, Martin Prather,

Tim Raines, Georgene Reichert, Janet

Reynolds, Rick Reynolds, Danna Rode,

Victoria Roth, Susan Schilling, Dale Schrenpp,

Debra Scribner, Peggy Sherdian, Jim Skranak,

Lisa Stern, Mike Stimak, Suzi Sweeny, Bonnie

Thomson, Glen Truscott, Randy Wakefield,

Cathy Wallis, Michelle Wasienko, Peg Watry,

Rod Weeks, Doug Welbourn, Richard Wiest,

Andy Wilson, Gail Worden, and Barb Young.

We especially thank Penny Morgan, Al Harvey,

Don Goheen, and Tom Atzet for critical reviews

of an earlier draft of this manuscript.

294
295

When you know: Multiply by: To obtain:

centimeters 0.3937007874 inches

meters 3.280839895 feet

meters 0.04970960 chains

square meters 0.0002471054 acres

kilometers 0.6213711922 miles

square kilometers 247.1054 acres

hectares 2.471054073 acres

English Conversions
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311

Appendix 1

Attributes of Forest and Nonforest Patches

The following describes the attributes of forest and nonforest patches interpreted from aerial photographs in the midscale ecological assessment of the interior Columbia River basin.

Total crown cover and overstory crown cover—Total and overstory forest crown cover were 

estimated to the nearest 10 percent for all forest patches. Forest patches were defined as having at least

10 percent of their patch area under a forest canopy. A new patch was delineated by total crown cover

alone when two adjacent patches similar in all attributes differed in average total crown cover by at least

20 percent.

Clumpiness—This term refers to the horizontal “patchiness” of tree cover within a patch. Patches were

rated as (1) clumpy—yes or no; (2) if clumpy, clump distribution was widely scattered, moderately

dense, or dense (see below); and (3) average clump size was < 0.4 ha, 0.4 to 2.0 ha, or > 2.0 ha, but 

< 4.0 ha.

Widely scattered Moderately dense Dense

Crown differentiation—Degree of differentiation among overstory tree crowns was estimated as low

(< 30 percent difference), moderate (30 to 100 percent difference), and high (> 100 percent difference).

Visual templates are shown.

Low Moderate High

Canopy layers—Canopy layers were estimated as 1, 2, or > 2 layers visible.

Riparian or wetland—These terms indicated whether a patch resided within a riparian or wetland

setting and was used in conjunction with overstory vegetation to estimate forest and nonforest riparian

and wetland area.
312

Nonforest type—A vegetation patch was interpreted as nonforest when total crown cover was < 10

percent. Categories were rock, water (lake or pond), wet meadow or marsh (soils saturated year-round),

alpine meadow, dry meadow (soils saturated seasonally), grasses or forbs after logging, shrubland (with 

at least 5 percent shrub canopy cover), bare ground (burned or logged), bare ground (from slumps or

erosion), agriculture cropland, urban or rural development, pasture (irrigated grasses or forbs), grassland

(with at least 20 percent canopy cover), woodland (< 10 percent total crown cover and at least two trees

per acre), bare ground (from roadcuts or sidecast adjacent to highways), stream channel and nonvegetated flood plains, grass or forbs after wildfire, sand dune, glacier, and bare ground (dry lake beds, playa).

Visible logging entry—Visible logging was interpreted as no logging apparent, regeneration harvested

(clearcut, shelterwood, seedtree), selection harvested (overstory removal, final removal, selective harvest),

thinned (commercial or precommercial), or patch clearcut (clearcut patches were < 4 ha). If patch

clearcut, we estimated the percentage of patch area in clearcut patches to the nearest 10 percent.

Overstory and understory tree size classes—Tree sizes were estimated as seedlings and saplings 

(< 12.7 cm d.b.h.), poles (12.7 to 22.6 cm d.b.h.), small trees (22.7 to 40.4 cm d.b.h.), medium trees

(40.5 to 63.5 cm d.b.h.), and large trees (> 63.5 cm d.b.h.).

Overstory and understory species—Dominant overstory and understory species were recorded. To

be named as an overstory species in pure or mixed compositions, a species comprised at least 20 percent

of the basal area. To be named as an understory species in pure or mixed compositions, a species comprised at least 20 percent of the trees per hectare. 

Primary overstory species or species mixes were ponderosa pine; western larch; lodgepole pine; Douglasfir; grand fir or white fir, or both; Pacific silver fir; subalpine fir or Engelmann spruce, or both; western

hemlock or western redcedar, or both; mountain hemlock; whitebark pine or subalpine larch, or both;

western white pine or sugar pine; hardwoods (Oregon and Washington subbasins only); juniper; noble

fir; Shasta red fir; ponderosa pine and sugar pine; ponderosa pine and Douglas-fir; Douglas-fir and

mountain hemlock; lodgepole pine and Engelmann spruce; mountain hemlock and white fir; Douglasfir and Engelmann spruce; incense-cedar; western larch and lodgepole pine; Douglas-fir and western

larch; limber pine; blue spruce; pinyon pine; white spruce; maple; birch; aspen; cottonwood; Douglas-fir

and limber pine; pinyon pine and juniper; Douglas-fir and western white pine; grand fir and western

white pine; subalpine fir and western white pine; western larch and western white pine; western larch,

lodgepole pine, and western white pine; western larch and ponderosa pine; western larch and

Engelmann spruce; lodgepole pine and subalpine fir; lodgepole pine and Douglas-fir; lodgepole pine 

and grand fir; subalpine fir and limber pine; grand fir and Engelmann spruce; Douglas-fir and aspen;

lodgepole pine and aspen; subalpine fir and Douglas-fir; grand fir and ponderosa pine; grand fir and

subalpine fir; grand fir and western larch; Russian olive; subalpine fir and whitebark pine.

Primary understory species or species mixes were ponderosa pine; western larch and lodgepole pine;

Douglas-fir or grand fir or white fir or Pacific silver fir, or combinations; western hemlock or western

redcedar, or both; mountain hemlock; subalpine fir or Engelmann spruce, or both; hardwood (Oregon

and Washington subbasins only); juniper; grasses and forbs; shrubs; bare ground; lodgepole pine; ponderosa pine and lodgepole pine; ponderosa pine and Douglas-fir; grand fir or white fir; mountain hemlock and white fir; mountain hemlock and lodgepole pine; Douglas-fir and mountain hemlock;

lodgepole pine and Engelmann spruce; whitebark pine or subalpine larch, or both; Shasta red fir;

incense-cedar; western white pine; Douglas-fir and western larch; Douglas-fir and Engelmann spruce;

limber pine; blue spruce; pinyon pine; white spruce; maple; aspen; cottonwood; Douglas-fir and limber

pine; lodgepole pine and Douglas-fir; beargrass; and Pacific silver fir.
313

Dead trees and snags—Dead tree and snag abundance was estimated as none apparent, < 10 percent

of trees dead, 10 to 39 percent of trees dead, 40 to 70 percent of trees dead, and > 70 percent of trees

dead.

Elevation zones of nonforest types—Elevation zones were interpreted as colline (below lower timberline); lower montane (above lower timberline but not including such forest types as subalpine fir,

lodgepole pine, Engelmann spruce, mountain hemlock, Pacific silver fir, noble fir, or Shasta red fir);

upper montane (below upper timberline and including the forest types listed immediately above); subalpine (above upper timberline but with trees as islands or krummholz); and alpine (above upper treeline).

Nonforest overstory species—Dominant herbland and shrubland overstory species were recorded.

The primary species groups were native bunchgrasses (for example, wildrye, bluebunch wheatgrass,

Idaho fescue, alkali grass, bottlebrush squirreltail); annual grasses (for example, cheatgrass, medusahead);

seeded wheatgrasses (for example, crested wheatgrass, other seeded dryland grasses); exotic forbs (for

example, spotted knapweed, yellowstar thistle, leafy spurge); native moist site herbs (for example, sedges,

rushes); low sagebrush (for example, low sagebrush, salt desert shrub); low alpine shrubs (for example,

meadow heathers); sagebrush and bitterbrush (for example, basin big sagebrush, Wyoming sagebrush,

mountain big sagebrush, silver sagebrush, bitterbrush, rabbitbrush); mahoganies (for example, mountain

and curlleaf mahoganies); mountain shrubs (for example, serviceberry, rose, snowberry, Rocky Mountain

maple, Scouler's willow, buffaloberry, chokeberry, bittercherry); wet site shrubs (for example, willow,

alder, bog birch, dogwood); and beargrass.

Overstory canopy cover nonforest types—Canopy cover of herbland and shrubland patches was

estimated to the nearest 15 percent. A new patch was delineated by canopy cover alone when two adjacent patches were similar in all attributes and differed in average total canopy cover by at least 15 percent. Cover classes were estimated as 0 to 15 percent canopy cover, 16 to 33 percent cover, 33 to 66

percent cover, and > 66 percent cover.

Tree cover of herbland and shrubland types—Tree cover was identified, where present, in herbland and shrubland patches.
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Appendix 2

Table 32—Historical and current percentage of area, patch density, and mean patch size for physiognomic types, cover types, and structural classes of sampled subwatersheds in the ERUs of the

midscale ecological assessment of the interior Columbia River basin

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Blue Mountains ERU:

Physiognomic types—

Forest + nc 62.8 64.1 1.4* 9.3 137.6 -0.3 1984.3 1925.0 -59.3

Woodland + + 2.7 4.2 1.6* 5.9 6.2 0.3 17.4 29.8 12.5*

Shrubland - nc 14.1 10.7 -3.4* 7.9 7.9 0.0 128.0 90.3 -37.6

Herbland nc + 17.4 18.0 0.6 24.0 28.8 4.8* 89.5 103.8 14.3

Othere nc + 3.0 2.9 -0.1 5.5 4.6 -0.9* 37.7 45.9 8.2

Cover types-forest and woodland—

Grand fir-white fir - - 15.3 8.4 -6.9* 8.0 11.0 3.0* 136.2 54.7 -81.5*

Engelmann sprucesubalpine fir - - 6.3 4.4 -1.9* 2.3 3.8 1.5* 64.8 40.0 -24.8*

Aspen-cottonwood-willow nc nc 0.1 0.1 0.0 0.3 0.4 0.1 4.7 3.1 -1.6

Juniper + + 2.7 4.2 1.5* 5.8 6.3 0.5 17.6 29.6 12.0*

Western larch nc - 2.6 2.2 -0.4 3.8 7.8 4.1* 21.2 15.8 -5.4

Whitebark pinesubalpine larch + + 0.0 0.7 0.7* 0.0 0.4 0.4* 0.0 15.9 15.9*

Lodgepole pine nc nc 2.4 2.3 -0.1 4.6 5.6 1.0 29.1 29.1 0.0

Limber pine nc nc 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0 -0.6

Ponderosa pine nc - 28.4 28.9 0.5 12.2 24.0 11.8* 419.5 428.6 9.1

Douglas-fir + + 7.7 17.1 9.4* 11.7 20.6 8.9* 54.4 107.7 53.3*

Cover types-shrubland—

Colline low-medium - - 7.2 4.7 -2.5* 2.0 266.4 264.7* 116.9 2.7 -114.2*

Montane low-medium nc - 6.0 5.4 -0.6 4.8 5.0 0.2 47.7 32.3 -15.4*

Montane mahogany - nc 0.4 0.2 -0.1* 1.2 0.9 -0.3* 6.4 4.4 -2.0

Colline tall nc nc 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.3

Montane tall - nc 0.1 0.0 -0.1* 0.5 0.2 -0.4* 3.3 2.7 -0.6

Colline wet-site nc nc 0.0 0.1 0.0 0.1 0.2 0.1* 1.9 2.3 0.4

Montane wet-site nc nc 0.1 0.1 0.0 0.8 0.5 -0.3 4.0 5.4 1.4

Cover types-herbland—

Alpine nc nc 0.1 0.2 0.2 0.3 0.7 0.4* 2.9 2.3 -0.6

Dry-meadow - - 6.2 5.3 -0.9* 11.0 14.6 3.7* 24.5 24.6 0.2

Colline bunchgrass nc + 3.9 4.6 0.7 1.6 1.0 -0.6* 83.7 146.7 63.0*

Montane bunchgrass nc - 3.4 3.5 0.1 5.9 8.4 2.5* 27.4 23.5 -3.9

Colline exotic grasses-forbs + + 0.3 1.3 1.0* 0.6 0.4 -0.2 6.3 34.4 28.1*

Montane exotic grasses-forbs nc nc 1.3 1.2 -0.1 2.8 3.4 0.6 17.5 20.5 3.0

Colline moist-site nc nc 0.1 0.0 0.0 0.1 0.0 -0.1 6.5 2.6 -4.0

Montane moist-site - nc 0.7 0.5 -0.2* 2.7 2.1 -0.6 9.4 8.5 -0.9

Wet-meadow - - 0.2 0.0 -0.2* 0.5 0.1 -0.4 3.6 0.2 -3.4*

Postlogging grasses-forbs + - 0.0 0.1 0.1* 0.1 5.7 5.6* 1.8 0.1 -1.8*
316

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Cover types-agriculture-urban rural—

Cropland - - 2.3 1.8 -0.5* 3.2 1.7 -1.6* 34.7 33.7 -1.0

Pasture nc + 1.0 1.0 0.0 1.0 0.7 -0.3* 25.1 50.3 25.2

Urban-rural nc nc 0.1 0.1 0.0 0.2 0.2 0.0 4.4 4.1 -0.3

Cover types-other—

Bare ground-road nc nc 0.0 0.0 0.0 0.0 0.1 0.0 0.6 0.3 -0.3

Rock nc nc 0.6 0.7 0.1 1.6 1.6 0.0 9.3 8.9 -0.4

Postloggingbare ground-burned + + 0.0 0.3 0.6* 0.0 0.7 0.7* 5.3 10.5 5.2

Postloggingbare ground-slumps-erosion nc nc 0.1 0.0 -0.1 0.1 0.1 -0.1 3.3 0.7 -2.7

Stream channelnonvegetated flood plain nc nc 0.0 0.0 0.0 0.1 0.1 0.0 0.6 0.4 -0.2

Water nc + 0.1 0.1 0.0 0.4 0.4 0.0 7.8 10.7 2.9*

Structural classes-forest—

Stand initiation + + 3.9 6.5 2.6* 10.2 17.9 7.7* 34.1 41.8 7.6

Stem exclusion, open canopy - - 14.3 9.6 -4.7* 29.6 25.7 -3.9* 51.5 41.5 -10.0*

Stem exclusion, closed canopy nc nc 5.0 5.0 0.0 10.3 10.7 0.4 48.4 43.2 -5.3

Understory reinitiation - nc 13.6 11.2 -2.4* 15.7 16.8 1.0 90.8 83.5 -7.3

Young, multistory + nc 21.3 29.6 8.2* 25.9 27.8 1.9 112.3 130.5 18.2

Old, multistory - - 2.2 1.0 -1.3* 4.1 2.8 -1.3* 33.6 16.8 -16.8*

Old, single story - - 2.7 0.9 -1.7* 4.9 2.4 -2.5* 31.1 17.8 -13.3*

Structural classes-woodland—

Stand initiation nc nc 0.0 0.1 0.0 0.2 0.1 0.0 1.5 4.0 2.6

Stem exclusion + + 2.4 4.0 1.6* 4.8 6.0 1.2* 14.9 28.6 13.7*

Understory reinitiation nc - 0.3 0.2 -0.1 1.3 0.5 -0.8* 9.7 4.6 -5.1*

Old, multistory nc nc 0.0 0.0 0.0 0.0 0.1 0.1 0.2 1.2 0.9

Structural classes-shrubland—

Open low-medium - - 11.0 8.3 -2.7* 7.0 6.4 -0.6 96.6 61.0 -35.6

Closed low-medium nc - 2.3 1.8 -0.4 3.4 3.0 -0.4 19.8 12.1 -7.7*

Open tall nc nc 0.5 0.4 0.0 1.6 1.4 -0.2 9.9 12.4 2.4

Closed tall nc - 0.2 0.1 -0.1* 1.2 0.5 -0.7* 4.5 2.1 -2.4*

Structural classes-herbland—

Open + + 6.4 8.5 2.1* 7.6 9.8 2.2* 40.8 67.3 26.6*

Closed - nc 3.2 2.5 -0.7* 5.1 3.9 -1.2 33.2 31.0 -2.2

Structural classes-othere

—

Nonforest-nonrange - - 11.1 10.0 -1.1* 17.2 21.1 3.9* 74.5 69.0 -5.5
317

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No. /10 000 ha Hectares

Central Idaho Mountains: 

Physiognomic types—

Forest nc + 73.4 73.5 0.2 7.7 8.1 0.4 2983.7 3457.6 474.9*

Woodland nc nc 0.1 0.0 0.0 0.3 0.4 0.0 0.3 0.3 -0.1

Shrubland - nc 19.2 17.1 -2.0* 13.4 14.7 1.3 218.6 158.3 -60.3

Herbland + - 3.2 4.5 1.0* 9.0 13.7 4.7* 42.4 37.3 -5.1

Othere + nc 4.2 4.9 1.0* 12.4 13.8 1.4 32.2 39.3 7.0

Cover types-forest and woodland—

Grand fir-white fir nc nc 9.6 10.2 0.5 4.5 5.6 1.2 213.2 75.0 -138.2

Engelmann spruce-subalpine fir nc nc 22.7 24.1 1.4 13.0 14.4 1.4 231.1 350.5 119.4

Aspen-cottonwood-willow nc - 1.1 0.8 -0.2 1.8 2.4 0.6* 11.0 11.2 0.2

Juniper nc nc 0.1 0.0 0.0 0.3 0.4 0.0 0.3 0.3 -0.1

Western larch nc nc 0.5 0.3 0.0* 1.3 1.5 0.2 14.6 6.0 -8.6

Whitebark pine-subalpine larch - nc 5.1 2.5 -2.5 5.2 5.6 0.4 170.8 18.3 -152.6

Lodgepole pine nc - 9.7 9.5 -0.2 12.2 14.6 2.4* 53.6 47.5 -6.0

Limber pine nc nc 0.4 0.4 -0.1 0.7 0.4 -0.3 1.4 1.8 0.5

Ponderosa pine nc - 6.0 5.9 -0.2 3.7 4.9 1.2* 48.7 39.8 -8.9*

Douglas-fir nc + 17.6 18.5 1.0 16.0 19.2 3.2* 118.0 138.6 20.5

Western hemlock-western redcedar nc - 0.9 1.3 0.4 0.7 1.1 0.4* 10.4 8.4 -1.9*

Mountain hemlock nc + 0.0 0.0 0.0* 0.0 0.2 0.2* 0.3 1.1 0.8

Cover types-shrubland—

Colline low-medium nc - 8.2 8.0 -0.3 1.3 571.5 570.2* 186.4 5.7 -180.7*

Montane low-medium nc nc 5.3 4.9 -0.4 6.4 7.0 0.6 32.5 46.8 14.3

Subalpine-alpine low-medium nc nc 0.5 0.4 -0.1 1.2 1.8 0.6 11.7 8.3 -3.4

Colline mahogany species nc nc 0.0 0.0 0.0 0.1 0.1 0.0 0.7 0.5 -0.2

Montane mahogany species - - 0.4 0.2 -0.2* 1.3 0.8 -0.5* 5.2 4.1 -1.1

Subalpine-alpine mahogany species nc nc 0.0 0.0 0.0 0.1 0.0 0.0 0.5 0.2 -0.3

Colline tall nc nc 0.5 0.3 -0.3 0.5 0.4 -0.1 7.0 14.6 7.6

Montane tall nc - 3.7 3.2 -0.5 7.0 8.8 1.8 35.4 17.7 -17.7*

Colline wet-site nc - 0.1 0.1 -0.1 0.4 0.3 -0.1 3.9 1.7 -2.2*

Montane wet-site - nc 0.7 0.6 -0.1* 1.9 1.6 -0.3 12.2 16.0 3.8

Subalpine-alpine wet-site nc nc 0.0 0.0 0.0 0.0 0.1 0.1 0.1 1.0 0.9

Montane subshrub nc + 0.1 0.1 0.0 0.4 0.5 0.1 1.3 2.6 1.3*

Subalpine-alpine subshrub + + 0.0 0.1 0.1* 0.0 6.2 6.2* 0.0 0.1 0.1*

Cover types-herbland—

Alpine nc nc 0.0 0.1 0.1 0.0 0.0 0.0 0.0 3.5 3.5

Dry meadow nc nc 0.0 0.1 0.1 0.0 0.0 0.0 0.0 4.0 4.0

Colline bunchgrass + nc 0.1 0.2 0.1* 0.4 0.7 0.3 3.6 4.0 0.4

Montane bunchgrass + + 0.7 1.2 0.6* 3.3 4.3 1.0 6.4 11.0 4.6*

Subalpine-alpine bunchgrass nc + 0.0 0.0 0.0 0.1 0.1 0.0 0.6 1.2 0.6

Colline exotic grasses-forbs nc nc 0.6 0.8 0.1 0.5 0.6 0.1 10.8 10.9 0.1
318

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Montane exotic grasses-forbs nc + 0.1 0.2 0.1 0.5 1.1 0.6* 1.7 2.2 0.5

Colline moist-site nc nc 0.2 0.2 0.0* 0.2 0.2 0.0 3.7 6.0 2.3

Montane moist-site nc nc 0.7 0.6 0.0 2.2 3.0 0.8 9.9 8.4 -1.5

Subalpine-alpine moist-site nc nc 0.0 0.1 0.1 0.0 0.1 0.1 0.0 2.2 2.2

Postfire-grasses nc - 0.1 0.0 -0.1 0.1 0.0 -0.1 1.7 0.8 -0.9*

Postlogging-grasses-forbs + + 0.0 0.2 0.2* 0.3 4.3 4.0* 0.3 0.0 -0.2

Cover types-agriculture-rural-urban—

Cropland nc nc 0.3 0.2 -0.1 0.4 0.3 -0.1 9.9 8.3 -1.6

Pasture nc + 0.1 0.1 0.1 0.3 0.4 0.1 1.5 3.4 1.8*

Urban-rural + + 0.0 0.3 0.2* 0.2 0.4 0.3* 1.8 7.7 5.9*

Cover types-other—

Bare ground-road nc nc 0.0 0.0 0.0 0.1 0.1 0.0 1.2 1.1 -0.1

Rock nc nc 3.4 3.6 0.1 10.5 10.6 0.1 23.4 22.9 -0.5

Postlogging-bare ground-burned + + 0.2 0.7 0.5* 0.7 2.7 2.0* 4.5 6.8 2.3

Postloggingbare ground-slumps-erosion nc nc 0.0 0.0 0.0 0.1 0.1 0.0 0.2 0.6 0.3

Stream channelnonvegetated flood plain nc nc 0.0 0.1 0.0 0.2 0.3 0.1 2.0 3.3 1.4

Water nc nc 0.1 0.1 0.0 0.7 0.6 -0.1 1.9 2.4 0.4

Structural classes-forest—

Stand initiation - - 9.7 5.9 -3.8* 19.0 18.0 -1.0 61.1 30.5 -30.6*

Stem exclusion, open canopy nc nc 18.4 17.7 -0.8 26.1 29.0 2.9 87.6 77.6 -10.0

Stem exclusion, closed canopy nc - 7.7 8.5 0.8 16.7 19.8 3.1* 42.0 34.5 -7.5

Understory reinitiation + + 16.0 21.4 5.5* 20.6 21.0 0.4 102.1 151.7 49.5*

Young, multistory - - 18.4 17.1 -1.2 30.3 31.5 1.2 75.1 62.0 -13.1*

Old, multistory nc - 1.4 1.2 -0.3 1.8 2.7 0.9* 32.6 9.3 -23.4*

Old, single story nc nc 1.8 1.7 -0.1 4.7 4.8 0.2 16.2 12.5 -3.7

Structural-woodland

Stem exclusion nc nc 0.1 0.0 0.0 0.3 0.4 0.0 0.3 0.3 -0.1

Structural classes-shrubland—

Open low-medium nc - 12.6 12.0 -0.5 7.0 8.8 1.7* 95.8 94.6 -1.2

Closed low-medium nc nc 1.6 1.4 -0.2 2.8 2.6 -0.2 21.8 21.3 -0.5

Open tall nc nc 2.8 2.8 0.1 7.0 8.0 1.1 25.0 27.7 2.7

Closed tall - - 2.7 1.5 -1.2* 6.5 6.2 -0.2 28.5 15.1 -13.4*

Structural classes-herbland—

Open nc - 0.9 1.1 0.1 2.4 3.6 1.2* 25.6 16.7 -8.9

Closed + - 1.7 2.2 0.5* 4.8 6.5 1.6* 22.9 23.7 0.8

Structural classes-othere

—

Nonforest-nonrange + + 4.4 5.4 1.1* 12.8 15.8 3.0* 31.4 39.7 8.2
319

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Columbia Plateau ERU:

Physiognomic types—

Forest + nc 26.1 29.1 3.0* 5.6 4.9 -0.6 1116.2 930.0 -186.1

Woodland + + 6.7 12.2 5.5* 4.9 4.2 -0.7 69.9 220.6 150.8*

Shrubland - - 32.2 23.4 -8.8* 9.6 9.7 0.1 842.8 265.9 -576.9*

Herbland nc nc 12.7 14.0 1.4 17.1 18.7 1.6 205.1 155.4 -49.7

Othere nc nc 22.4 21.4 -1.0 11.3 9.8 -1.5 656.5 639.4 -17.1

Cover types-forest and woodland—

Grand fir-white fir nc nc 1.1 0.4 -0.7 0.6 0.7 0.1 20.3 7.1 -13.2

Engelmann spruce-subalpine fir nc nc 0.0 0.0 0.0 0.0 0.0 0.0 6.1 1.5 -4.7

Aspen-cottonwood-willow nc nc 0.3 0.3 0.0 1.3 1.3 -0.1 10.8 7.5 -3.3

Juniper + + 6.5 12.0 5.5* 4.7 3.9 -0.8 60.6 208.4 147.8*

Western larch - nc 1.0 0.1 -0.9* 0.3 0.4 0.1 40.6 3.3 -37.3

Lodgepole pine nc nc 1.3 0.9 -0.4 0.7 1.1 0.4 93.9 11.9 -82.0

Ponderosa pine + nc 19.2 21.4 2.3* 5.2 5.3 0.1 752.8 334.4 -418.4

Douglas-fir + + 3.0 3.9 0.9* 2.4 3.6 1.2* 37.7 39.7 2.0

Western hemlock-western redcedar + + 0.4 2.2 1.9* 0.3 0.9 0.6* 5.7 14.7 9.0

Mountain hemlock nc nc 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.2 0.2

Cover types-shrubland—

Colline low-medium - - 29.1 21.7 -7.4* 5.2 1405.2 1400.1* 838.4 14.1 -824.3*

Montane low-medium nc + 1.3 0.9 -0.3 1.8 0.7 -1.1* 10.4 20.1 9.7

Colline mahogany species nc nc 0.4 0.1 -0.2 0.5 0.2 -0.4 7.0 11.4 4.4

Montane mahogany species nc nc 0.0 0.0 0.0 0.4 0.1 -0.3 0.3 0.1 -0.2

Colline tall nc nc 0.3 0.1 -0.1 0.8 0.7 -0.1 3.2 2.9 -0.4

Montane tall nc - 0.9 0.4 -0.6 1.5 1.8 0.3 12.3 2.8 -9.5*

Colline wet-site - nc 0.2 0.1 -0.1* 0.7 0.6 -0.1 9.3 6.9 -2.4

Montane wet-site nc nc 0.1 0.1 0.0 0.3 0.3 -0.1 4.4 4.0 -0.4

Montane subshrub nc nc 0.0 0.0 0.0 0.1 0.2 0.0 0.5 0.3 -0.2

Cover types-herbland—

Dry meadow nc nc 0.1 0.0 -0.1 0.1 0.1 0.0 3.5 0.3 -3.2

Colline bunchgrass - nc 8.3 6.9 -1.4* 8.8 8.3 -0.5 258.2 416.6 158.4

Montane bunchgrass + nc 1.3 1.8 0.5* 4.5 4.1 -0.4 15.9 22.8 6.9

Colline exotic grasses-forbs + + 0.8 2.3 1.5* 2.4 4.2 1.8* 11.3 29.3 18.0*

Montane exotic grasses-forbs nc nc 0.1 0.3 0.2 0.4 0.7 0.3 6.9 7.3 0.5

Colline moist-site nc nc 0.1 0.2 0.1 0.7 0.6 -0.1 1.8 3.5 1.7

Montane moist-site nc nc 0.5 0.5 0.1 2.6 2.7 0.1 5.0 4.7 -0.2

Wet meadow nc nc 0.1 0.0 -0.1 0.4 0.0 -0.3 0.8 2.8 2.0

Postlogging-grasses-forbs nc - 0.0 0.0 0.0 0.2 2.4 2.2* 1.3 0.0 -1.3*

Cover types-agriculture-rural-urban—

Cropland nc + 18.1 17.9 -0.1 7.8 4.8 -3.0* 708.9 815.4 106.4

Pasture nc nc 1.1 1.4 0.3 0.9 1.5 0.6 27.1 36.9 9.8

Urban-rural nc - 0.6 0.8 0.2 1.2 2.7 1.4* 17.1 9.5 -7.6
320

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Cover types-other—

Rock nc + 0.4 0.5 0.1 2.8 2.4 -0.4 4.5 9.6 5.1*

Postlogging-bare ground-burned nc - 2.8 1.6 -1.2 0.4 2.2 1.8* 39.5 25.2 -14.3

Postloggingbare ground-slumps-erosion nc + 0.0 0.1 0.1 0.0 0.3 0.3* 0.2 1.2 1.1

Stream channelnonvegetated flood plain nc nc 0.3 0.0 -0.2 0.3 0.2 -0.1 12.9 1.6 -11.3

Water + + 0.3 0.4 0.1* 0.5 0.9 0.3* 13.0 16.4 3.4

Structural classes-forest—

Stand initiation nc nc 2.3 2.8 0.5 4.0 5.1 1.1 71.1 24.7 -46.4

Stem exclusion, open canopy nc nc 6.7 7.8 1.1 12.7 9.9 -2.9 35.4 103.9 68.5

Stem exclusion, closed canopy nc nc 3.8 3.6 -0.2 1.6 2.2 0.5 65.7 34.6 -31.1

Understory reinitiation nc nc 3.1 3.3 0.2 4.6 4.3 -0.3 35.2 42.7 7.5

Young, multistory + - 7.3 10.0 2.7* 8.6 7.7 -0.9 54.6 81.4 26.8*

Old, multistory nc + 2.3 1.3 -1.0 1.0 1.2 0.2 33.9 11.1 -22.8*

Old, single story nc nc 1.1 1.0 -0.1 2.1 2.4 0.3 10.0 9.9 0.0

Structural classes-woodland—

Stand initiation nc nc 0.1 0.3 0.2 0.3 0.4 0.2 2.7 5.5 2.8

Stem exclusion + + 5.9 10.9 5.0* 4.6 4.4 -0.2 63.8 152.7 88.9*

Understory reinitiation nc nc 0.6 1.0 0.3 0.9 1.3 0.4 16.9 10.2 -6.7

Old multistory nc nc 0.0 0.0 0.0 0.2 0.1 0.0 1.7 1.8 0.1

Old single story nc nc 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.5

Structural classes-shrubland—

Open low-medium - - 23.4 19.4 -4.1* 10.5 9.4 -1.1 435.1 172.9 -262.2*

Closed low-medium - - 6.9 3.3 -3.7* 5.2 2.9 -2.2* 61.4 54.2 -7.1

Open tall - nc 0.9 0.4 -0.6* 3.2 1.9 -1.4 13.4 9.1 -4.3

Closed tall nc - 0.9 0.4 -0.6 1.5 1.7 0.2 14.7 3.7 -11.0*

Structural classes-herbland—

Open + nc 7.4 9.0 1.5* 11.6 11.5 -0.1 176.0 430.8 254.8

Closed nc - 3.8 3.2 -0.5 8.0 9.1 1.1 41.5 23.1 -18.4*

Structural classes-othere

—

Nonforest-nonrange nc - 23.8 23.2 -0.6 11.8 9.3 -2.5* 782.4 708.6 -73.9

Lower Clark Fork ERU:

Physiognomic types—

Forest nc nc 91.7 94.5 2.8 3.4 2.4 -1.0 4549.5 5749.1 1199.5

Shrubland nc nc 1.9 0.6 -1.4 6.6 4.2 -2.4 9.0 7.8 -1.2

Herbland nc nc 5.4 3.2 -2.3 13.6 18.6 5.0 48.9 43.3 -5.6

Othere nc nc 0.9 1.8 0.8 6.4 15.6 9.2 20.6 8.4 -12.3

Cover types-forest and woodland—

Grand fir-white fir nc nc 40.4 42.5 2.1 20.8 23.8 3.0 210.4 206.6 -3.8
321

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No. /10 000 ha Hectares

Engelmann spruce-subalpine fir nc nc 2.5 2.2 -0.3 6.2 5.2 -1.0 32.7 34.5 1.8

Aspen-cottonwood-willow nc + 0.1 0.7 0.6 0.6 2.2 1.6* 3.0 14.2 11.2*

Western larch nc + 0.8 2.6 1.7 2.6 4.8 2.2* 18.6 39.7 21.1

Lodgepole pine nc - 2.1 1.8 -0.3 4.8 5.0 0.2 38.7 18.3 -20.4*

Limber pine nc nc 0.0 0.0 0.0 0.4 0.0 -0.4 2.3 0.0 -2.3

Sugar pine-western white pine nc nc 0.3 0.6 0.2 2.6 2.6 0.0 8.5 23.5 15.1

Ponderosa pine nc nc 3.0 5.1 2.1 5.2 4.4 -0.8 29.1 43.8 14.7

Douglas-fir - nc 26.4 21.1 -5.3 26.2 24.6 -1.6 125.1 90.9 -34.1

Western hemlock-western redcedar nc nc 14.7 17.3 2.6 19.0 20.0 1.0 63.0 66.5 3.5

Mountain hemlock - - 1.3 0.6 -0.7* 1.6 0.6 -1.0* 41.1 23.9 -17.2

Cover types-shrubland—

Subalpine-alpine low-medium nc nc 0.2 0.1 -0.1 0.8 0.6 -0.2 5.8 3.6 -2.1

Montane tall nc nc 1.6 0.3 -1.3 6.8 3.8 -3.0 5.9 4.3 -1.6

Colline wet-site nc nc 0.0 0.0 0.0 0.0 0.4 0.4 0.0 0.8 0.8

Montane wet-site nc - 1.4 1.5 0.1 4.2 8.8 4.6* 63.9 20.0 -43.9

Cover types-herbland—

Montane bunchgrass nc nc 0.1 0.2 0.1 0.8 0.6 -0.2 4.3 12.7 8.4

Montane exotic grasses-forbs nc nc 0.1 0.1 0.0 0.2 0.8 0.6 4.1 4.8 0.6

Montane moist-site nc nc 0.2 0.2 -0.1 1.2 0.8 -0.4 12.3 11.5 -0.8

Wet meadow nc nc 0.0 0.0 0.0 0.0 0.2 0.2 0.0 2.1 2.1

Postfire-grasses nc - 2.9 0.0 -2.9 8.8 0.0 -8.8* 13.3 0.0 -13.3*

Postlogging-grasses-forbs nc nc 0.4 0.9 0.5 2.0 20.4 18.4 6.3 0.2 -6.1

Cover types-agriculture-rural-urban—

Pasture nc nc 0.4 0.4 0.0 2.2 1.4 -0.8 7.4 17.9 10.5

Urban-rural nc nc 0.0 0.0 0.0 0.2 0.0 -0.2 0.9 0.0 -0.9

Cover types-other—

Rock nc nc 0.5 0.3 -0.2 5.6 3.8 -1.8 4.9 4.7 -0.2*

Postlogging-bare ground-burned nc + 0.0 1.1 1.1 0.6 10.2 9.6 0.8 6.3 5.4*

Stream channelnonvegetated flood plain nc nc 0.2 0.3 0.1 0.2 0.8 0.6 11.9 14.6 2.7

Water nc nc 0.2 0.1 -0.1 0.6 1.4 0.8 18.5 2.6 -15.9

Structural classes-forest—

Stand initiation - - 32.7 9.5 -23.3* 22.8 31.8 9.0 208.3 24.2 -184.2*

Stem exclusion, open canopy - - 15.7 9.2 -6.5* 28.0 23.0 -5.0* 52.4 25.9 -26.6*

Stem exclusion, closed canopy + + 10.3 17.6 7.3* 17.2 17.4 0.2 31.8 64.4 32.6*

Understory reinitiation + + 16.4 37.7 21.3* 24.0 33.8 9.8* 68.2 189.6 121.4

Young, multistory + nc 14.3 17.5 3.2 29.4 34.4 5.0 48.8 51.4 2.6

Old, multistory nc nc 0.2 0.5 0.3 0.4 1.6 1.2 11.8 6.8 -5.0

Old, single story nc - 2.2 2.5 0.4 2.8 8.2 5.4* 39.4 18.6 -20.8*

Structural classes-shrubland—

Open low-medium nc nc 0.2 0.1 -0.1 0.8 0.2 -0.6 5.8 6.7 0.9
322

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No. /10 000 ha Hectares

Closed low-medium nc nc 0.0 0.0 0.0 0.0 0.2 0.2 0.0 0.6 0.6

Open tall nc nc 2.1 1.2 -0.9 4.8 4.4 -0.4 59.1 14.9 -44.2

Closed tall nc nc 1.0 0.7 -0.3 5.4 7.8 2.4 10.0 6.3 -3.7

Structural classes-herbland—

Open nc nc 0.2 0.1 -0.1 1.8 1.0 -0.8 8.9 5.6 -3.3

Closed nc nc 0.2 0.3 0.2 0.4 0.8 0.4 10.3 21.9 11.6

Structural classes-othere

—

Nonforest-nonrange nc nc 4.7 3.2 -1.5 16.2 21.6 5.4 28.0 23.6 -4.4

Northern Cascades ERU:

Physiognomic types—

Forest nc nc 78.8 78.2 -0.6 3.8 3.6 -0.2 3769.5 3444.9 -324.6

Woodland + + 0.3 0.7 0.3* 1.1 1.8 0.7* 3.2 6.5 3.3*

Shrubland nc - 4.8 4.1 -0.7 7.2 8.7 1.5* 38.0 33.3 -4.7

Herbland nc - 6.7 6.5 -0.3 7.6 11.0 3.3* 78.5 55.0 -23.6*

Othere + + 9.4 10.6 1.2* 13.5 19.0 5.6* 79.4 86.6 7.3

Cover types-forest and woodland—

Pacific silver fir + - 6.0 8.3 2.3* 4.0 359.8 355.7* 61.5 3.6 -57.9*

Grand fir-white fir + + 1.0 2.2 1.3* 1.1 3.7 2.5* 25.7 33.6 7.9

Engelmann spruce-subalpine fir - - 16.8 13.6 -3.2* 10.0 11.2 1.3* 283.8 158.2 -125.6*

Oregon white oak + + 0.6 0.9 0.3* 2.1 2.8 0.7* 10.8 12.1 1.3 

Juniper nc nc 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 -0.2

Western larch nc - 1.0 1.0 0.0 1.2 1.7 0.5* 24.3 21.5 -2.8

Whitebark pine-subalpine larch + + 3.3 4.7 1.4* 4.0 4.9 0.9* 35.4 63.3 27.8*

Lodgepole pine nc nc 5.9 5.2 -0.6 3.6 3.9 0.3 101.9 93.4 -8.5

Sugar pine-western white pine nc + 0.1 0.3 0.1* 0.2 0.5 0.3* 2.4 6.5 4.1*

Ponderosa pine - - 16.5 13.2 -3.2* 7.3 8.2 1.0* 241.3 156.1 -85.2*

Douglas-fir + - 23.8 25.8 2.0* 10.9 13.3 2.4* 294.1 254.0 -40.1

Western hemlock-western redcedar - - 3.0 2.4 -0.6* 1.3 2.2 0.9* 62.9 40.2 -22.8*

Mountain hemlock nc - 1.3 1.2 -0.1 1.5 1.7 0.2 30.4 22.8 -7.7*

Cover types-shrubland—

Colline low-medium nc - 1.6 1.8 0.2 1.1 105.4 104.4* 12.7 1.1 -11.7*

Montane low-medium nc - 0.3 0.4 0.1 0.7 1.0 0.3 5.5 4.2 -1.3*

Colline mahogany species nc - 0.2 0.0 -0.1 0.0 0.2 0.2* 23.6 1.2 -22.4

Montane mahogany species nc + 0.0 0.0 0.0* 0.0 0.2 0.2* 0.4 1.1 0.7*

Colline tall nc nc 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0 -0.6

Montane tall nc - 0.0 0.0 0.0* 0.1 0.0 -0.1* 2.6 0.7 -1.9*

Colline wet-site nc nc 0.0 0.0 0.0 0.0 0.1 0.1 4.9 1.4 -3.5

Montane wet-site nc nc 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0

Montane subshrub nc nc 0.9 0.3 -0.5 1.5 1.4 -0.1 5.0 2.2 -2.9

Cover types-herbland—

Alpine nc nc 0.7 0.8 0.1 2.1 2.4 0.3 17.9 13.9 -4.1
323

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No. /10 000 ha Hectares

Dry meadow nc nc 1.7 1.5 -0.2 2.3 1.9 -0.4 47.1 36.6 -10.5

Colline bunchgrass nc - 1.0 1.2 0.2 0.7 1.9 1.2* 13.7 6.7 -7.0*

Montane bunchgrass - - 1.0 0.7 -0.3* 0.9 1.5 0.7* 9.3 5.5 -3.8

Colline exotic grasses-forbs - - 0.9 0.5 -0.4* 0.7 0.8 0.1 16.6 4.5 -12.1*

Montane exotic grasses-forbs + + 0.7 0.9 0.2* 0.9 0.7 -0.2* 8.2 12.8 4.6*

Colline moist-site nc nc 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1

Montane moist-site nc nc 0.0 0.0 0.0 0.0 0.0 0.0 1.1 0.3 -0.8

Wet meadow nc nc 0.2 0.1 -0.1 1.2 0.9 -0.3 6.3 7.4 1.0

Postlogging-grasses-forbs + - 0.1 0.4 0.4* 0.2 19.2 19.0* 1.6 0.2 -1.4*

Cover types-agriculture-rural-urban—

Cropland nc nc 1.7 1.6 -0.1 1.6 1.5 -0.1 29.7 25.0 -4.7

Pasture nc - 0.3 0.2 -0.2 0.3 0.4 0.2* 7.0 2.8 -4.2*

Urban-rural + + 0.1 0.3 0.2* 0.2 0.7 0.5* 4.6 9.0 4.5*

Cover types-other—

Rock nc + 4.8 5.1 0.3 7.9 8.3 0.4 62.4 84.2 21.9*

Postlogging-bare ground-burned + - 0.5 1.5 0.9* 0.8 5.7 4.9* 29.1 17.5 -11.6

Postloggingbare ground-slumps-erosion nc - 1.5 1.3 -0.2 2.9 3.5 0.6* 13.1 12.5 -0.6 

Water nc nc 0.8 0.8 0.0 2.6 2.4 -0.2 26.4 24.7 -1.7

Structural classes-forest—

Stand initiation nc - 9.2 10.4 1.3 11.8 18.8 7.0* 100.0 67.4 -32.5

Stem exclusion, open canopy nc - 13.2 13.2 0.0 16.3 20.7 4.4* 88.2 70.1 -18.1*

Stem exclusion, closed canopy nc - 7.6 7.9 0.3 7.4 11.2 3.8* 101.2 88.1 -13.2

Understory reinitiation + + 17.5 19.5 2.0 15.7 19.5 3.8* 153.0 195.9 42.9

Young, multistory nc - 21.2 22.0 0.8 21.5 25.0 3.5* 130.3 101.2 -29.1*

Old, multistory - - 5.8 2.7 -3.1* 4.5 4.9 0.4 145.0 37.5 -107.5*

Old, single story - - 4.3 2.4 -1.9* 4.3 4.5 0.3 81.9 38.9 -43.0*

Structural classes-woodland—

Stand initiation nc nc 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.3

Stem exclusion + + 0.3 0.6 0.3* 1.0 1.7 0.7* 2.3 6.3 4.0*

Understory reinitiation nc nc 0.0 0.0 0.0* 0.0 0.2 0.1 0.5 1.5 1.0

Old multistory nc nc 0.0 0.0 0.0 0.1 0.1 0.0 2.7 2.4 -0.2

Old single story nc nc 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.4 0.3

Structural classes-shrubland—

Open low-medium nc - 2.0 1.8 -0.2 2.8 3.3 0.5* 9.2 8.9 -0.2

Closed low-medium nc - 0.8 0.8 0.0 0.4 1.3 0.9* 11.7 7.2 -4.5

Open tall nc - 0.0 0.0 0.0* 0.1 0.0 0.0 3.5 0.6 -2.9*

Closed tall nc nc 0.0 0.1 0.0* 0.0 0.1 0.1* 2.9 2.8 -0.2

Structural classes-herbland—

Open nc - 2.3 2.4 0.1 1.4 2.0 0.5* 21.8 11.5 -10.3*

Closed nc - 1.5 1.0 -0.5 1.6 2.3 0.7* 14.3 6.5 -7.8*

Structural classes-othere

—

Nonforest-nonrange + - 14.3 15.2 0.9* 17.9 25.2 7.2* 117.0 104.3 -12.7*
324

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Northern Glaciated Mountains ERU:

Physiognomic types—

Forest nc nc 81.0 80.8 -0.2 4.8 5.1 0.2 3749.4 3919.1 169.8

Woodland nc nc 0.0 0.0 0.0 0.0 0.1 0.1 1.8 1.0 -0.8

Shrubland nc - 3.1 2.5 -0.5 5.0 9.5 4.5* 40.6 20.6 -20.0*

Herbland nc - 7.4 8.1 0.7 11.1 18.0 6.9* 93.8 65.9 -27.9

Othere nc - 8.5 8.5 0.0 12.4 17.9 5.5* 86.4 58.6 -27.8

Cover types-forest and woodland—

Grand fir-white fir + + 0.0 1.2 1.2* 0.1 2.3 2.2* 3.6 18.9 15.3*

Engelmann spruce-subalpine fir + - 11.5 13.2 1.7* 6.1 11.0 4.9* 177.6 138.9 -38.6*

Aspen-cottonwood-willow nc + 0.3 1.9 1.6 1.2 2.6 1.5* 8.0 40.8 32.8

Juniper nc nc 0.0 0.0 0.0 0.0 0.1 0.1 1.8 1.0 -0.8

Western larch - - 14.8 11.4 -3.4* 9.6 13.7 4.1* 134.4 61.1 -73.4*

Whitebark pine-subalpine larch nc nc 0.3 0.2 -0.1 0.6 0.4 -0.2 10.6 5.8 -4.8

Lodgepole pine nc - 8.0 8.3 0.3 9.7 13.3 3.6* 68.8 52.4 -16.4*

Sugar pine-western white pine - - 1.5 0.0 -1.4* 0.6 0.2 -0.4* 21.5 1.7 -19.8*

Ponderosa pine - - 13.4 11.4 -2.0* 7.7 10.3 2.6* 151.9 108.8 -43.1

Douglas-fir nc - 30.3 30.2 -0.1 16.1 23.0 6.8* 441.8 427.4 -14.4

Western hemlock-western redcedar + - 0.7 2.8 2.5* 1.1 4.4 3.3* 19.1 17.0 -2.1

Mountain hemlock nc nc 0.1 0.0 0.0 0.2 0.2 0.0 0.6 0.7 0.0

Cover types-shrubland—

Colline low-medium nc - 0.1 0.1 0.0 0.3 5.4 5.1* 1.8 0.1 -1.7*

Montane low-medium + + 0.0 0.1 0.1* 0.0 0.2 0.2* 0.0 2.2 2.2*

Subalpine-alpine low-medium nc - 1.1 0.8 -0.2 1.4 2.0 0.6* 8.4 5.1 -3.4

Colline mahogany species - - 0.4 0.0 -0.4* 0.4 0.0 -0.4* 7.2 0.0 -7.2*

Montane mahogany species - - 0.2 0.0 -0.2* 0.3 0.0 -0.3* 3.1 0.0 -3.1*

Colline tall nc nc 0.7 0.3 -0.4 0.8 0.6 -0.2 9.7 4.9 -4.8

Montane tall nc - 0.4 0.6 0.2 1.0 3.4 2.4* 12.1 9.2 -2.9

Colline wet-site - - 0.3 0.2 -0.1* 0.4 0.5 0.1 9.0 5.1 -3.9*

Montane wet-site + + 0.1 0.2 0.1* 0.3 0.6 0.3* 4.7 8.6 3.9*

Subalpine-alpine wet-site nc nc 0.0 0.0 0.0 0.1 0.0 -0.1 0.2 0.0 -0.2

Montane subshrub nc - 0.3 0.4 0.1 0.7 2.3 1.6 2.8 1.2 -1.6*

Subalpine-alpine subshrub + - 0.0 0.1 0.1* 0.0 10.0 10.0* 2.2 0.1 -2.1

Cover types-herbland—

Alpine nc nc 0.0 0.0 0.0 0.2 0.2 0.0 0.8 1.0 0.2

Dry meadow nc + 0.0 0.0 0.0* 0.1 0.4 0.3* 0.3 2.1 1.8*

Colline bunchgrass - - 1.6 0.8 -0.8* 0.7 1.5 0.8* 34.9 9.8 -25.0*

Montane bunchgrass nc nc 1.6 1.9 0.2 4.0 3.9 -0.1 22.0 41.4 19.4

Subalpine-alpine bunchgrass nc nc 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.6

Colline exotic grasses-forbs nc + 1.0 1.2 0.2 0.9 1.9 1.0* 11.8 14.0 2.2
325

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Montane exotic grasses-forbs nc nc 0.5 0.7 0.1 2.6 2.3 -0.3 5.5 14.5 9.0

Colline moist-site nc nc 0.0 0.0 0.0 0.1 0.2 0.1 2.6 2.6 0.0

Montane moist-site nc nc 0.2 0.2 0.0 0.8 1.0 0.2 7.7 5.4 -2.3

Subalpine-alpine moist-site nc nc 0.0 0.0 0.0 0.1 0.1 0.0 0.4 0.3 -0.1

Wet meadow nc + 0.0 0.1 0.1* 0.2 0.8 0.6* 2.0 4.1 2.1

Postlogging-grasses-forbs + - 0.1 0.8 0.7* 0.7 21.2 20.6* 4.1 0.2 -3.9*

Cover types-agricultural-rural-urban— 

Cropland nc - 3.4 4.3 0.9 4.1 3.2 -0.9* 49.0 47.3 -1.7

Pasture + + 1.4 1.7 0.3* 1.4 1.1 -0.3 11.2 49.1 38.0*

Urban-rural nc + 0.2 0.3 0.1 0.8 1.3 0.5* 4.1 8.1 4.0*

Cover types-other—

Bare ground nc nc 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 -0.2

Glacier nc nc 0.0 0.0 0.0 0.1 0.1 0.0 1.4 2.0 0.7

Rock + - 2.3 2.7 0.5* 4.9 9.2 4.3* 32.5 29.2 -3.4

Postlogging-bare ground-burned - - 2.2 0.4 -1.7* 1.3 3.1 1.8* 24.9 7.2 -17.7

Postloggingbare ground-slumps-erosion nc + 0.0 0.0 0.0 0.1 0.1 0.0 0.3 0.7 0.4*

Stream channelnonvegetated flood plain nc - 0.1 0.1 0.0* 0.0 0.0 0.0 11.8 10.8 -0.9*

Water nc nc 0.4 0.5 0.1 2.7 3.0 0.3 8.8 10.1 1.2

Structural classes-forest—

Stand initiation - - 16.9 9.4 -7.5* 18.3 26.5 8.2* 103.6 38.5 65.1*

Stem exclusion, open canopy nc - 11.8 11.6 -0.2 18.0 27.8 9.9* 75.3 49.1 -26.2*

Stem exclusion, closed canopy + + 7.2 12.8 5.6* 8.6 15.0 6.5* 61.2 71.4 10.2

Understory reinitiation + - 18.4 23.3 4.9* 12.9 22.1 9.2* 170.6 150.7 -19.9

Young, multistory - - 25.5 22.8 -2.7 22.2 32.4 10.2* 218.1 106.3 -111.9*

Old, multistory nc - 0.5 0.4 -0.1 0.5 1.2 0.8* 22.7 7.8 -14.8*

Old, single story nc nc 0.7 0.6 -0.1 0.9 1.4 0.5 9.2 10.1 0.9

Structural classes-woodland—

Stem exclusion nc nc 0.0 0.0 0.0 0.0 0.1 0.1 1.8 0.3 -1.5

Understory reinitiation nc nc 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.9 1.9

Structural classes-shrubland—

Open low-medium nc nc 1.2 1.1 -0.2 1.8 3.7 1.9 14.0 12.6 -1.3

Closed low-medium nc - 0.3 0.5 0.2 0.6 1.3 0.7* 5.6 4.5 -1.1

Open tall nc - 1.2 0.8 -0.4 1.7 3.2 1.5* 22.9 12.5 -10.4

Closed tall nc nc 0.3 0.4 0.2 0.8 1.9 1.1* 10.2 10.9 0.6

Structural classes-herbland—

Open nc nc 1.4 1.5 0.1 2.7 2.6 -0.1 21.8 20.9 -0.8

Closed nc - 4.2 3.4 -0.8 6.9 7.9 1.0* 38.3 27.7 -10.6

Structural classes-othere

—

Nonforest-nonrange + + 10.5 11.6 1.1* 14.7 25.1 10.5* 90.3 221.4 131.0
326

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Northern Great Basin ERU:

Physiognomic types—

Forest nc nc 7.2 7.3 0.0 19.5 19.5 0.0 32.9 37.6 4.7

Woodland + nc 15.3 22.2 6.9* 12.8 11.5 -1.3 178.4 205.9 27.5

Shrubland - - 72.8 57.6 -15.2* 11.8 21.0 9.3 934.1 337.1 -597.0*

Herbland + + 3.9 12.2 8.3* 15.0 21.5 6.5 24.4 68.6 44.2*

Othere nc nc 0.8 0.8 0.0 3.0 3.8 0.8 6.5 5.1 -1.4

Cover types-forest and woodland—

Aspen-cottonwood-willow nc nc 8.4 7.7 -0.8 20.0 19.0 -1.0 37.3 39.4 2.2

Juniper + nc 14.1 21.8 7.7* 12.3 12.3 0.0 139.9 180.4 40.5

Cover types-shrubland—

Colline low-medium nc - 20.0 18.1 -1.8 1.3 1411.3 1410.0* 788.7 14.1 -774.6*

Montane low-medium - nc 51.2 37.7 -13.5* 16.8 22.5 5.8 316.1 248.1 -68.0

Subalpine-alpine low-medium nc nc 0.6 2.0 1.4 0.8 1.3 0.5 21.3 113.0 91.8

Montane mahogany species nc nc 0.4 0.4 0.0 0.3 0.3 0.0 32.4 30.2 -2.2

Montane tall nc nc 0.1 0.1 0.0 1.3 1.3 0.0 2.1 2.1 0.0

Montane wet-site - - 1.0 0.9 -0.1* 5.3 4.0 -1.3* 8.7 5.5 -3.3

Cover types-herbland—

Colline bunchgrass nc nc 0.0 0.5 0.5 0.0 1.3 1.3 0.0 10.3 10.3

Montane bunchgrass + + 1.1 5.5 4.5* 3.0 5.3 2.3 11.2 92.6 81.4* 

Subalpine-alpine bunchgrass nc nc 1.5 0.8 -0.7 1.8 2.0 0.3 40.2 21.9 -18.3

Colline exotic grasses-forbs + + 0.0 2.5 2.5* 0.0 3.3 3.3* 0.0 38.5 38.5*

Montane exotic grasses-forbs nc nc 0.0 0.0 0.0 0.5 0.0 -0.5 2.0 0.0 -2.0

Montane moist-site nc + 0.6 1.2 0.6 4.8 6.0 1.3* 8.9 14.2 5.3

Subalpine-alpine moist-site nc nc 0.1 0.0 -0.1 0.8 0.5 -0.3 4.6 2.3 -2.3

Cover types-other—

Rock nc nc 0.8 0.7 -0.1 3.0 3.3 0.3 6.5 5.5 -1.0 

Water nc nc 0.0 0.0 0.0 0.0 0.3 0.3 0.0 0.9 0.9

Structural classes-forest—

Stem exclusion, open canopy nc nc 6.5 6.0 -0.5 19.8 18.8 -1.0 29.2 29.1 -0.1

Stem exclusion, closed canopy nc + 0.7 1.3 0.6 2.5 3.8 1.3* 22.5 31.7 9.2

Structural classes-woodland—

Stem exclusion + nc 15.3 22.2 6.9* 12.8 11.5 -1.3 178.4 205.9 27.5

Structural classes-shrubland—

Open low-medium - - 71.8 57.8 -13.9* 13.3 22.5 9.3 903.8 346.1 -557.8*

Open tall nc nc 1.2 1.2 0.0 3.3 3.5 0.3 14.0 13.3 -0.7

Closed tall nc nc 0.4 0.2 -0.1 3.5 2.0 -1.5 5.0 2.9 -2.1

Structural classes-herbland—

Open + + 3.4 10.1 6.7* 11.0 17.0 6.0 28.3 64.8 36.5*

Closed nc nc 0.0 0.5 0.5 0.0 1.3 1.3 0.0 11.1 11.1

Structural classes-othere

—

Nonforest-nonrange nc nc 0.8 0.8 0.0 3.0 3.8 0.8 6.5 5.1 -1.4
327

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Owyhee Uplands ERU:

Physiognomic types—

Forest nc nc 0.2 0.2 0.0 0.2 0.4 0.2 10.2 6.4 -3.8

Woodland + + 5.5 7.6 2.1* 9.0 4.4 -4.6* 15.9 64.4 48.5*

Shrubland - - 88.8 81.0 -7.8* 7.9 5.7 -2.2* 4695.3 3439.3 -1256.0*

Herbland + + 1.0 7.4 6.4* 3.0 4.5 1.5* 22.2 202.0 179.7

Othere nc + 4.5 3.8 -0.6 6.7 4.5 -2.2* 53.2 86.0 32.8*

Cover types-forest and woodland—

Aspen-cottonwood-willow nc nc 0.2 0.2 0.0 0.3 0.6 0.2 11.7 5.4 -6.3

Juniper + + 5.5 7.5 2.0* 9.0 4.4 -4.6* 15.8 64.3 48.5*

Douglas-fir nc nc 0.0 0.0 0.0 0.0 0.0 0.0 1.7 0.9 -0.8

Cover types-shrubland—

Colline low-medium - - 87.7 79.3 -8.5* 8.9 7007.0 6998.1* 4443.5 70.1 -4373.4*

Colline mahogany species nc nc 0.8 1.1 0.4 2.3 0.6 -1.8* 4.1 18.9 14.8

Colline tall nc nc 0.1 0.3 0.2 0.4 0.7 0.3 1.9 4.7 2.7

Colline wet-site nc nc 0.3 0.3 -0.1 1.0 1.1 0.2 14.1 10.4 -3.7

Russian olive nc nc 0.1 0.0 -0.1 0.6 0.0 -0.6 1.0 0.0 -1.0

Cover types-herbland—

Colline bunchgrass nc nc 0.2 0.2 0.0 1.3 1.2 0.0 3.4 4.1 0.6

Colline exotic grasses-forbs + + 0.2 6.2 6.1* 0.6 2.0 1.4* 5.8 195.8 190.0*

Colline moist-site + + 0.1 0.5 0.4* 0.1 0.6 0.5* 7.4 29.9 22.4*

Cover types-agricultural-rural-urban—

Cropland nc + 1.1 1.4 0.3 0.5 0.3 -0.2* 21.8 31.7 10.0*

Pasture nc nc 0.5 0.5 0.0 0.8 0.7 0.0 13.4 24.7 11.2

Cover types-other—

Bare ground nc nc 0.0 0.0 0.0 0.1 0.2 0.0 0.8 1.1 0.3

Bare ground-road nc nc 0.0 0.0 0.0 0.1 0.1 0.0 0.6 1.0 0.4

Rock nc - 2.8 1.9 -0.9 4.1 3.3 -0.8 34.3 23.5 -10.7*

Postlogging-bare ground-burned nc nc 0.1 0.1 0.0 0.0 0.1 0.0 4.7 3.1 -1.5

Stream channelnonvegetated flood plain nc + 0.4 0.3 -0.1 2.3 0.7 -1.5* 6.5 8.3 1.8

Water nc + 0.1 0.1 0.0* 0.5 0.5 0.0 2.9 4.2 1.3*

Structural classes-forest—

Stand initiation nc nc 0.0 0.0 0.0 0.0 0.1 0.1 0.0 1.7 1.7

Stem exclusion, open canopy nc nc 0.0 0.1 0.0 0.1 0.2 0.0 4.2 5.9 1.7

Stem exclusion, closed canopy nc nc 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.0 -0.3

Understory reinitiation nc nc 0.4 1.1 0.7 1.2 1.7 0.4 10.2 11.8 1.6

Young, multistory nc nc 0.1 0.1 0.0 0.0 0.2 0.1 20.1 1.8 -18.4

Structural classes-woodland—

Stand initiation nc nc 0.0 0.0 0.0 0.0 0.1 0.1 0.0 1.7 1.7

Stem exclusion + + 5.2 6.5 1.3* 8.8 5.3 -3.6* 15.4 42.2 26.8*

Understory reinitiation nc nc 0.3 1.1 0.8 1.2 1.5 0.3 4.8 10.0 5.2
328

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Structural classes-shrubland—

Open low-medium - - 85.1 77.2 -7.8* 10.0 6.5 -3.5* 4607.3 3232.1 -1375.2* 

Closed low-medium nc + 2.7 2.1 -0.6 4.7 1.6 -3.1* 24.3 103.8 79.5*

Open tall + nc 0.8 1.4 0.6* 2.8 2.3 -0.6 14.0 20.8 6.8

Closed tall nc nc 0.3 0.3 0.0 1.5 0.7 -0.8* 7.1 9.4 2.3

Structural classes-herbland—

Open + + 0.3 6.4 6.1* 1.9 3.5 1.6* 6.3 183.0 176.7*

Closed nc nc 0.1 0.5 0.4 0.1 0.3 0.2 3.4 8.6 5.2

Structural classes-othere

—

Nonforest-nonrange nc + 5.0 4.4 -0.6 6.6 4.9 -1.7* 63.2 96.0 32.8*

Snake Headwaters ERU:

Physiognomic types—

Forest nc nc 74.5 73.8 -0.7 18.1 19.9 1.8 982.4 1013.9 31.4

Woodland + nc 0.2 0.3 0.1* 0.8 0.6 -0.1 1.7 7.2 5.5

Shrubland - - 16.3 13.9 -2.4* 22.3 23.6 1.3 56.7 43.5 -13.3*

Herbland + + 6.1 8.7 2.6* 21.3 29.1 7.8* 30.4 36.7 6.3

Othere nc + 3.0 3.3 0.4 7.6 5.2 -2.4* 26.6 34.2 7.7*

Cover types-forest and woodland—

Engelmann spruce-subalpine fir + nc 24.3 31.4 7.1* 19.9 23.7 3.8 173.5 236.1 62.6

Aspen-cottonwood-willow - - 8.8 5.7 -3.1* 25.4 25.4 0.1 38.3 26.2 -12.1*

Juniper + nc 0.2 0.3 0.1* 0.7 0.6 -0.1 1.8 7.1 5.3

Whitebark pine-subalpine larch nc - 6.9 5.7 -1.3 6.0 4.1 -1.9* 57.0 37.8 -19.1

Lodgepole pine - + 15.6 11.3 -4.3* 19.1 15.4 -3.7* 93.8 125.1 31.3

Pinyon pine-juniper nc nc 0.0 0.0 0.0 0.0 0.1 0.1 0.0 4.8 4.8

Limber pine + + 0.7 1.1 0.4* 3.1 2.8 -0.3 2.3 9.9 7.7*

Ponderosa pine nc nc 0.0 0.0 0.0 0.1 0.0 -0.1 0.3 0.0 -0.3

Douglas-fir nc + 18.2 18.6 0.4 19.3 18.8 -0.4 96.3 139.3 43.0*

Cover types-shrubland—

Colline low-medium nc nc 0.1 0.0 -0.1 0.1 0.0 -0.1 6.5 0.0 -6.5

Montane low-medium - nc 13.0 10.7 -2.3* 22.7 22.4 -0.3 49.6 38.5 -11.1

Subalpine-alpine low-medium nc nc 0.1 0.3 0.2 0.3 0.2 -0.1 2.3 18.2 15.9

Montane mahogany species nc + 0.0 0.1 0.1 0.0 0.4 0.4* 0.0 2.4 2.4*

Colline tall nc nc 0.0 0.0 0.0 0.1 0.0 -0.1 0.9 0.0 -0.9

Montane tall nc nc 2.1 2.1 -0.1 7.3 9.4 2.1 10.9 10.6 -0.3

Montane wet-site nc - 2.8 2.8 0.0 5.3 4.9 -0.4 66.1 49.1 -17.0*

Cover types-herbland—

Colline bunchgrass nc nc 0.0 0.0 0.0 0.0 0.2 0.2 0.0 1.1 1.1

Montane bunchgrass + + 2.2 4.3 2.1* 12.8 19.7 6.9* 17.1 88.8 71.7

Subalpine-alpine bunchgrass nc nc 0.1 0.3 0.2 0.5 0.5 0.0 4.9 13.5 8.6

Montane exotic grasses-forbs + nc 0.2 0.7 0.5* 0.8 0.9 0.1 5.9 41.7 35.8
329

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Subalpine-alpine

exotic grasses-forbs nc nc 0.0 0.1 0.1 0.0 0.1 0.1 0.0 6.3 6.3

Montane moist-site - nc 1.5 1.1 -0.4* 6.6 6.4 -0.2 13.7 17.8 4.1

Subalpine-alpine moist-site nc nc 0.0 0.0 0.0 0.1 0.3 0.3 1.7 0.5 -1.2

Postlogging-grasses-forbs nc nc 0.0 0.1 0.1 0.0 3.1 3.1 0.0 0.0 0.0

Cover types-agricultural-rural-urban—

Cropland nc nc 0.3 0.1 -0.3 0.2 0.1 -0.1 17.3 12.1 -5.2

Cover types-other—

Bare ground-road nc + 0.0 0.1 0.0 0.4 0.8 0.3* 1.5 2.0 0.5

Glacier nc nc 0.1 0.0 -0.1 0.5 0.3 -0.3 1.0 0.6 -0.4

Rock nc nc 1.7 2.1 0.5 2.1 2.0 -0.1 13.2 18.0 4.8

Postlogging-bare ground-burned + + 0.0 0.0 0.0* 0.0 0.3 0.3* 0.0 1.1 1.1*

Postloggingbare ground-slumps-erosion nc nc 0.1 0.0 -0.1 0.3 0.2 -0.1 5.3 0.5 -4.8

Stream channelnonvegetated flood plain nc nc 0.1 0.1 0.1 0.2 0.1 -0.1 5.8 12.7 7.0

Water nc nc 0.9 0.9 0.1* 4.3 2.4 -1.9* 11.8 13.1 1.3

Structural classes-forest—

Stand initiation nc + 6.4 7.0 0.6 14.9 19.8 4.9 26.5 50.1 23.5*

Stem exclusion, open canopy - nc 19.1 15.3 -3.8* 35.7 39.2 3.5 55.8 43.8 -12.1

Stem exclusion, closed canopy - - 7.9 4.8 -3.1* 19.7 13.8 -5.9* 40.9 25.3 -15.6*

Understory reinitiation nc - 13.8 12.6 -1.2 18.4 19.9 1.6 96.7 61.5 -35.2*

Young, multistory + + 22.0 30.9 8.9* 23.9 34.8 10.9* 145.3 269.6 124.3*

Old, multistory - - 3.2 1.8 -1.4* 2.0 2.0 0.0 27.5 13.9 -13.6*

Old, single story - nc 2.0 1.3 -0.7* 3.1 2.1 -0.9 18.5 21.7 3.1

Structural classes-woodland—

Stand initiation nc nc 0.1 0.0 -0.1 0.4 0.1 -0.3 1.9 0.1 -1.9

Stem exclusion nc + 0.1 0.3 0.2 0.4 0.6 0.2* 1.2 7.3 6.1

Understory reinitiation nc nc 0.0 0.0 0.0 0.3 0.3 0.1 0.2 0.4 0.2

Structural classes-shrubland—

Open low-medium - nc 9.3 7.0 -2.3* 18.1 16.8 -1.4 39.8 38.6 -1.2

Closed low-medium nc nc 3.9 4.0 0.1 7.6 7.6 0.0 25.9 28.7 2.7

Open tall nc nc 2.9 2.6 -0.3 8.5 9.8 1.3 31.0 26.6 -4.4

Closed tall nc nc 2.1 2.3 0.2 4.8 5.6 0.8 36.4 27.9 -8.5

Structural classes-herbland—

Open + + 1.8 4.2 2.4* 10.0 17.6 7.6* 12.6 90.2 77.6*

Closed nc nc 2.3 2.3 0.1 10.6 10.6 0.0 17.1 15.0 -2.1

Structural classes-othere

—

Nonforest-nonrange nc + 3.1 3.5 0.3 7.7 5.4 -2.3* 25.1 37.9 12.9*
330

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Southern Cascades ERU:

Physiognomic types—

Forest + nc 80.5 88.3 7.8 3.1 2.0 -1.1 7716.4 7484.1 -232.4

Woodland + + 0.0 0.4 0.4 0.0 0.2 0.2* 0.1 21.1 21.0

Shrubland nc - 0.5 0.5 0.1 0.9 1.9 1.1* 49.6 11.8 -37.7

Herbland + - 0.6 2.7 2.1* 3.6 19.4 15.8* 14.9 15.8 1.0

Othere - - 18.4 8.1 -10.4* 11.8 22.3 10.5* 835.0 46.6 -788.5

Cover types-forest and woodland—

Grand fir-white fir nc nc 5.9 6.5 0.6 3.3 3.9 0.6 108.6 109.8 1.2

Engelmann spruce-subalpine fir + + 0.0 0.2 0.2* 0.0 0.4 0.4* 0.0 8.9 8.9*

Shasta red fir nc - 0.2 0.4 0.2 0.1 1.3 1.1* 14.4 4.1 -10.3*

Aspen-cottonwood-willow nc nc 0.0 0.0 0.0 0.0 0.0 0.0 1.7 0.9 -0.8

Juniper nc nc 0.0 0.4 0.4 0.0 0.1 0.1 0.0 20.8 20.8

Western larch nc nc 0.0 0.0 0.0 0.0 0.1 0.1 0.3 2.5 2.1

Whitebark pine-subalpine larch + + 0.0 0.8 0.8 0.0 0.3 0.3 0.0 20.5 20.5

Lodgepole pine nc + 19.4 20.6 1.2 5.2 7.3 2.1* 340.8 387.3 46.5

Sugar pine-western white pine nc - 0.3 0.3 0.0 0.6 1.1 0.5* 3.6 2.9 -0.7

Ponderosa pine + - 22.7 28.1 5.4 5.8 10.9 5.1* 1531.6 671.5 -860.1

Douglas-fir nc - 1.5 1.7 0.2 0.9 1.8 0.9* 35.7 24.5 -11.1

Mountain hemlock nc nc 30.5 29.7 -0.8 2.9 2.8 -0.2 970.5 995.6 25.1

Cover types-herbland—

Alpine nc nc 0.1 0.2 0.1 0.4 1.4 1.0* 3.3 3.2 0.0

Dry meadow + + 0.0 0.1 0.0* 0.4 0.8 0.4* 1.6 2.7 1.2

Montane moist-site nc nc 0.0 0.1 0.1 0.0 0.2 0.2 0.2 3.0 2.8

Wet meadow nc + 0.5 0.6 0.0 2.6 4.3 1.7* 18.5 25.6 7.1

Postlogging-grasses-forbs + - 0.0 1.6 1.6* 0.0 42.1 42.1* 3.3 0.4 -2.9

Cover types-agricultural-rural-urban—

Cropland nc nc 0.2 0.0 -0.1 0.2 0.0 -0.2 4.8 4.0 -0.8

Urban-rural + + 0.0 0.3 0.3* 0.1 0.4 0.4* 4.1 18.6 14.6*

Cover types-other—

Rock nc nc 5.2 4.1 -1.1 3.7 4.3 0.6 89.6 66.4 -23.1

Postlogging-bare ground-burned - - 10.1 1.8 -8.4* 2.8 10.6 7.9* 749.3 8.5 -740.8

Postloggingbare ground-slumps-erosion nc nc 0.4 0.2 -0.2 0.4 0.3 -0.1 13.9 5.0 -8.9

Stream channelnonvegetated flood plain nc nc 0.0 0.0 0.0 0.0 0.0 0.0 0.0 10.3 10.3

Water nc nc 1.5 1.6 0.1 5.1 6.2 1.1 39.6 80.1 40.5

Structural classes-forest—

Stand initiation nc - 9.1 9.9 0.8 6.8 24.3 17.6* 171.5 75.4 -96.2

Stem exclusion, open canopy nc - 12.3 14.3 2.1 8.6 19.2 10.6* 150.5 86.5 -64.0*

Stem exclusion, closed canopy + + 0.5 4.8 4.2* 0.9 4.8 3.9* 19.2 116.7 97.5*
331

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Understory reinitiation nc - 10.3 8.7 -1.7 5.6 9.2 3.6* 232.6 106.6 -126.1*

Young, multistory nc - 46.0 45.6 -0.4 7.6 17.3 9.8* 670.9 563.9 -106.9

Old, multistory nc nc 0.7 1.4 0.7 0.6 0.9 0.3 22.6 53.9 31.3 

Old, single story + + 1.6 3.7 2.1 1.1 2.9 1.8* 52.9 54.5 1.6

Structural classes-woodland—

Stem exclusion + + 0.0 0.4 0.4 0.0 0.2 0.2* 0.0 24.4 24.4

Old multistory nc nc 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.8 0.7

Structural classes-shrubland—

Open nc nc 0.0 0.1 0.1 0.1 0.2 0.1 0.2 3.0 2.8

Structural classes-othere

—

Nonforest-nonrange - - 19.5 11.2 -8.3* 14.4 40.5 26.1* 856.6 40.4 -816.2

Upper Clark Fork ERU:

Physiognomic types—

Forest nc nc 87.2 86.2 -1.0 4.7 4.6 -0.1 4140.6 4436.8 296.3

Shrubland nc - 2.5 2.1 -0.4 3.7 4.6 0.9* 60.5 31.4 -29.0

Herbland nc - 5.5 5.7 0.2 13.8 18.2 4.4* 33.6 28.7 -4.9

Othere nc + 4.8 6.0 1.2 8.0 10.5 2.6* 44.3 50.4 6.1

Cover types-forest and woodland—

Grand fir-white fir nc nc 0.0 0.1 0.1 0.0 0.0 0.0 0.7 14.3 13.6

Engelmann spruce-subalpine fir + - 14.2 17.3 3.1* 13.6 16.5 2.9* 126.7 120.1 -6.6

Aspen-cottonwood-willow nc nc 0.3 0.3 0.0 1.0 0.9 -0.1 9.8 11.2 1.3

Western larch nc - 2.5 3.0 0.6 3.8 6.6 2.8* 19.1 14.2 -4.8

Whitebark pine-subalpine larch - nc 4.3 3.5 -0.8* 6.6 5.3 -1.3 39.1 37.3 -1.9

Lodgepole pine nc nc 20.9 19.5 -1.3 17.8 16.4 -1.4 168.4 135.4 -33.0

Limber pine nc + 0.0 0.4 0.3 0.1 0.3 0.2* 3.4 7.7 4.3

Ponderosa pine - - 12.3 9.5 -2.9* 6.8 7.9 1.1 155.6 78.2 -77.3*

Douglas-fir nc - 32.7 32.5 -0.2 14.8 17.6 2.8* 417.1 262.9 -154.3*

Mountain hemlock nc + 0.0 0.1 0.1 0.0 0.1 0.1* 0.0 4.5 4.5*

Cover types-shrubland—

Colline low-medium nc - 0.8 0.7 -0.1 0.5 21.1 20.5* 9.7 0.2 -9.5*

Montane low-medium nc + 0.4 0.7 0.2 0.5 0.7 0.2* 6.3 19.8 13.6

Subalpine-alpine low-medium nc nc 0.2 0.2 -0.1 1.0 0.9 -0.1 6.7 3.7 -3.0

Montane mahogany species - - 0.1 0.0 -0.1* 0.3 0.0 -0.3* 1.9 0.6 -1.3*

Montane tall nc + 0.2 0.2 -0.1 0.5 0.9 0.4* 8.0 8.1 0.1

Colline wet-site nc nc 0.1 0.1 0.0 0.2 0.3 0.0 2.5 1.6 -1.0*

Montane wet-site nc nc 0.6 0.6 0.0 2.8 3.0 0.2 14.0 12.8 -1.2

Subalpine-alpine wet-site nc - 0.0 0.0 0.0* 0.1 0.0 -0.1* 0.8 0.0 -0.8*

Montane subshrub - - 0.3 0.0 -0.3* 0.8 0.1 -0.7* 3.6 3.1 -0.6

Subalpine-alpine subshrub nc nc 0.0 0.0 0.0 0.0 1.6 1.6 0.0 0.0 0.0
332

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Cover types-herbland—

Alpine nc nc 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.3 0.3

Colline bunchgrass nc nc 0.3 0.3 -0.1 0.5 0.6 0.1 3.1 1.7 -1.4

Montane bunchgrass - - 3.1 1.8 -1.4* 8.4 7.3 -1.2* 23.9 13.6 -10.2*

Subalpine-alpine bunchgrass nc nc 0.1 0.0 0.0* 0.4 0.2 -0.2* 1.3 1.2 -0.1

Colline exotic grasses-forbs nc nc 0.1 0.2 0.0 0.2 0.2 0.0 3.5 3.6 0.1

Montane exotic grasses-forbs + - 0.1 0.2 0.1* 0.4 1.2 0.8* 5.3 3.9 -1.4

Subalpine-alpine

exotic grasses-forbs nc nc 0.1 0.0 -0.1 0.2 0.1 -0.2 1.0 0.8 -0.2

Colline moist-site nc nc 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.6 0.6

Montane moist-site nc + 0.7 0.7 0.0 1.8 2.3 0.5* 9.6 11.1 1.5

Subalpine-alpine moist-site nc + 0.0 0.3 0.2 0.1 0.6 0.4* 2.6 7.1 4.5

Postfire-grasses nc nc 0.0 0.5 0.4 0.2 0.8 0.7 1.0 1.9 0.9

Postlogging-grasses-forbs + - 0.0 0.9 0.9* 0.3 40.5 40.2* 1.9 0.4 -1.5*

Cover types-agricultural-rural-urban—

Cropland nc nc 1.2 1.3 0.1 0.8 0.8 0.0 31.1 32.4 1.3

Pasture nc nc 0.4 0.4 0.0 0.7 0.8 0.1 12.3 7.8 -4.5

Urban-rural nc + 0.0 0.1 0.0 0.3 0.6 0.3* 1.2 2.0 0.8

Cover types-other—

Bare ground-road nc nc 0.0 0.0 0.0* 0.1 0.1 0.0 2.7 1.9 -0.8*

Rock nc nc 2.5 2.4 -0.1 5.0 5.3 0.3 20.0 13.9 -6.1*

Postlogging-bare ground-burned + + 0.1 1.5 1.4* 0.5 2.3 1.8* 3.1 15.9 12.8*

Postloggingbare ground-slumps-erosion nc nc 0.0 0.0 0.0 0.2 0.0 -0.2 0.6 0.0 -0.6

Stream channelnonvegetated flood plain nc nc 0.1 0.1 0.0 0.2 0.4 0.2 2.2 3.1 0.9

Water nc + 0.8 0.7 -0.1 1.5 1.8 0.3* 23.6 26.9 3.3

Structural classes-forest—

Stand initiation - - 15.9 11.1 -4.8* 21.1 23.5 2.5 69.8 50.8 -18.9*

Stem exclusion, open canopy nc - 18.5 18.2 -0.3 27.5 35.3 7.8* 78.2 56.3 -21.9*

Stem exclusion, closed canopy + + 16.7 21.1 4.4* 14.9 16.3 1.4 157.9 402.9 245.0*

Understory reinitiation nc - 15.6 14.0 -1.5 16.3 19.8 3.4* 97.6 68.6 -29.0*

Young, multistory nc nc 19.7 21.1 1.3 21.9 21.0 -0.9 90.5 100.6 10.1

Old, multistory nc nc 0.6 0.4 -0.2 0.6 1.2 0.5 3.1 7.3 4.2

Old, single story nc + 0.2 0.3 0.1 0.5 1.0 0.5 1.1 4.5 3.3*

Structural classes-shrubland—

Open low-medium nc nc 1.2 0.8 -0.4 1.7 1.4 -0.3 12.7 24.3 11.6

Closed low-medium nc nc 0.6 0.8 0.2 1.3 1.5 0.2 5.0 8.4 3.4

Open tall nc + 0.5 0.6 0.2 2.0 2.7 0.7* 13.1 17.0 3.9

Closed tall - nc 0.5 0.3 -0.3* 1.7 1.5 -0.2 14.9 8.7 -6.2
333

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Structural classes-herbland—

Open nc nc 1.1 1.3 0.2 3.7 4.8 1.1* 15.5 15.8 0.3

Closed - - 3.5 2.1 -1.5* 8.3 7.6 -0.8 25.9 15.3 -10.6*

Structural classes-othere

—

Nonforest-nonrange + + 5.3 7.9 2.6* 8.7 14.6 5.9* 53.6 57.3 3.7

Upper Klamath ERU:

Physiognomic types—

Forest - - 50.5 47.5 -3.1* 7.8 5.9 -1.9* 1840.7 1711.3 -129.4

Woodland + + 8.4 12.8 4.4* 10.6 9.0 -1.6* 58.0 189.2 131.2*

Shrubland nc nc 21.4 18.8 -2.6 20.5 18.1 -2.4 275.8 116.8 -159.0

Herbland nc nc 10.6 9.0 -1.6 7.4 8.4 0.9 297.3 202.9 -94.5

Othere + + 9.1 12.0 2.9* 3.9 6.9 3.0* 160.2 338.7 178.4*

Cover types-forest and woodland—

Grand fir-white fir nc nc 7.8 8.1 0.3 5.1 3.9 -1.2 152.1 261.3 109.1

Engelmann spruce-subalpine fir nc nc 0.1 0.1 0.0 0.1 0.2 0.1 4.2 4.1 -0.1

Shasta red fir nc nc 7.8 8.5 0.7 1.5 1.5 0.0 124.1 117.3 -6.9

Aspen-cottonwood-willow nc nc 0.0 0.1 0.0 0.1 0.0 -0.1 2.3 6.8 4.5

Juniper + + 8.4 12.8 4.4* 10.6 8.9 -1.7* 58.0 189.2 131.2*

Western larch nc nc 0.0 0.1 0.1 0.0 0.2 0.2 0.0 3.1 3.1

Whitebark pine-subalpine larch nc nc 0.0 0.0 0.0 0.1 0.1 0.0 1.8 1.4 -0.4

Lodgepole pine nc nc 1.4 1.7 0.3 2.7 2.4 -0.3 15.0 19.6 4.6

Sugar pine-western white pine nc nc 0.0 0.0 0.0 0.1 0.0 -0.1 0.5 0.0 -0.5

Ponderosa pine - nc 26.7 23.5 -3.2* 8.2 8.7 0.5 387.3 256.7 -130.6

Douglas-fir nc - 2.1 1.2 -0.8 2.3 2.6 0.4 31.9 10.3 -21.6*

Mountain hemlock nc - 4.7 4.2 -0.5 1.1 1.0 -0.1 308.0 242.9 -65.1*

Cover types-shrubland—

Colline low-medium nc - 1.8 2.9 1.1 4.7 139.0 134.3* 13.4 1.4 -12.0*

Montane low-medium - nc 18.5 14.9 -3.6* 15.0 13.6 -1.4 273.9 106.7 -167.2

Subalpine-alpine low-medium nc nc 0.1 0.1 0.0 0.2 0.1 -0.1 3.7 7.3 3.6

Colline mahogany species nc nc 0.0 0.1 0.1 0.2 0.2 0.0 2.6 5.0 2.4

Montane mahogany species nc nc 0.1 0.1 0.0 0.2 0.1 -0.1 18.0 9.3 -8.8

Colline tall nc nc 0.0 0.0 0.0 0.3 0.1 -0.1 2.1 1.5 -0.6

Montane tall nc nc 0.3 0.4 0.2 1.1 1.0 -0.1 8.9 7.0 -1.9

Colline wet-site nc nc 0.5 0.0 -0.5 0.6 0.0 -0.6 5.7 0.7 -5.0

Montane wet-site - - 0.6 0.4 -0.1* 1.5 0.8 -0.7* 35.8 29.5 -6.3

Cover types-herbland—

Dry meadow nc nc 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.5 0.5

Colline bunchgrass - nc 2.8 1.0 -1.8* 2.4 0.8 -1.6 32.1 24.1 -8.0

Montane bunchgrass - - 0.7 0.4 -0.3* 1.5 1.1 -0.4 26.3 9.1 -17.2*

Colline exotic grasses-forbs nc + 0.0 0.4 0.4 0.1 0.4 0.3* 1.5 18.8 17.3
334

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Montane exotic grasses-forbs nc nc 0.0 0.0 0.0 0.1 0.0 -0.1 1.2 0.0 -1.2*

Colline moist-site - - 1.1 0.1 -1.0* 0.4 0.2 -0.2 49.2 3.2 -46.0*

Montane moist-site nc - 0.8 0.7 -0.1 1.9 2.9 1.1* 14.7 12.2 -2.5

Postlogging-grasses-forbs + - 0.0 0.1 0.1* 0.1 7.4 7.2* 1.9 0.1 -1.9*

Cover types-agricultural-rural-urban—

Cropland + + 7.0 10.5 3.5* 2.4 2.4 0.0 187.0 384.8 197.7*

Pasture nc + 4.4 5.3 0.9 0.3 0.0 -0.3* 702.3 898.1 195.8

Urban-rural nc + 0.0 0.1 0.1 0.4 0.5 0.1 1.2 3.8 2.5*

Cover types-other—

Bare ground-road nc nc 0.0 0.0 0.0* 0.0 0.0 0.0 0.0 3.8 3.8*

Rock nc + 0.2 0.4 0.2 0.9 0.9 0.0 2.7 5.4 2.7*

Postlogging-bare ground-burned + + 0.0 0.4 0.4* 0.1 2.9 2.8* 4.2 5.7 1.5

Postloggingbare ground-slumps-erosion nc nc 0.0 0.0 0.0 0.0 0.2 0.2 0.0 1.1 1.1

Water nc nc 2.2 1.4 -0.8 1.1 1.3 0.2 256.9 77.2 -179.7

Structural classes-forest—

Stand initiation nc + 1.9 3.6 1.6 4.4 3.6 -0.7 31.2 62.1 30.9*

Stem exclusion, open canopy nc nc 11.3 10.9 -0.4 16.9 18.3 1.4 92.0 77.6 -14.4

Stem exclusion, closed canopy nc - 1.2 1.6 0.3 2.1 3.7 1.6* 23.7 22.1 -1.5

Understory reinitiation + + 5.6 8.1 2.5 6.9 10.5 3.6* 42.9 292.3 249.4

Young, multistory - nc 21.1 16.4 -4.7* 10.2 11.7 1.5 401.1 163.9 -237.2

Old, multistory nc - 4.3 5.5 1.2 3.5 6.6 3.1* 46.1 34.1 -11.9

Old, single story - - 7.4 4.8 -2.6* 3.9 7.1 3.3* 69.6 22.7 -47.0*

Structural classes-woodland—

Stand initiation + nc 0.4 1.1 0.7 1.2 0.9 -0.3 7.1 8.5 1.5

Stem exclusion + nc 5.9 7.6 1.6* 8.2 7.1 -1.1 55.8 131.6 75.7

Understory reinitiation + + 2.0 3.8 1.8* 2.8 3.4 0.6* 5.3 330.1 324.9

Old multistory nc nc 0.0 0.3 0.3 0.3 0.6 0.4 0.9 3.2 2.3

Structural classes-shrubland—

Open low-medium nc nc 18.5 15.9 -2.6 18.9 16.7 -2.2 269.6 99.3 -170.4

Closed low-medium nc + 1.9 2.0 0.1 3.6 1.4 -2.2* 24.8 73.1 48.3*

Open tall nc + 1.1 0.9 -0.2 3.2 1.9 -1.4* 32.5 48.3 15.8

Closed tall nc - 0.3 0.2 -0.1 1.3 0.6 -0.6* 9.2 4.3 -4.9*

Structural classes-herbland—

Open - - 3.8 1.4 -2.4* 3.3 2.2 -1.1 101.6 35.8 -65.8

Closed - nc 1.6 1.1 -0.4* 2.7 3.3 0.6 28.9 24.2 -4.7

Structural classes-othere

—

Nonforest-nonrange + + 13.9 18.2 4.3* 4.5 9.1 4.6* 340.8 630.1 289.2*
335

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Upper Snake ERU:

Physiognomic types—

Forest + + 2.4 3.2 0.9* 2.7 2.1 -0.6 26.6 42.5 15.9*

Woodland nc nc 3.0 2.9 0.0 6.7 6.6 -0.1 13.5 20.7 7.2

Shrubland - nc 73.8 68.5 -5.3 7.6 7.6 0.0 3784.1 4304.2 520.1

Herbland nc nc 10.6 9.9 -0.7 7.1 7.6 0.5 345.8 497.1 151.3

Othere + nc 10.3 15.4 5.1 5.5 5.5 0.0 427.4 428.3 0.9

Cover types-forest and woodland—

Engelmann spruce-subalpine fir nc nc 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.8 0.8

Aspen-cottonwood-willow nc + 0.9 1.0 0.1 2.3 2.5 0.2 5.5 7.0 1.5*

Juniper nc nc 2.6 2.5 -0.1 6.3 6.1 -0.2 12.4 19.2 6.9

Lodgepole pine nc nc 0.1 0.2 0.1 0.7 0.3 -0.4 1.3 13.3 12.0

Pinyon pine-juniper nc nc 0.4 0.5 0.1 0.7 0.7 0.0 8.3 10.2 1.9

Douglas-fir nc + 1.4 2.1 0.7 2.7 1.3 -1.4* 13.0 39.8 26.9

Cover types-shrubland—

Colline low-medium - - 71.0 62.3 -8.6* 7.3 5679.9 5672.5* 3639.5 56.8 -3582.7*

Montane low-medium nc nc 0.3 0.5 0.2 0.7 1.2 0.5 2.8 5.5 2.7

Colline mahogany species nc nc 0.4 0.0 -0.4 0.5 0.0 -0.5 6.1 0.0 -6.1

Montane mahogany species nc nc 0.1 0.1 0.0 0.7 0.5 -0.3 0.6 0.8 0.2

Colline tall nc + 3.4 5.1 1.6 5.8 3.6 -2.2* 29.9 50.9 20.9*

Montane tall nc nc 0.1 0.4 0.3 0.3 1.6 1.3 4.5 4.7 0.1*

Colline wet-site nc nc 0.1 0.1 0.0 1.0 0.7 -0.3 1.7 4.9 3.1

Montane wet-site nc nc 0.0 0.0 0.0 0.3 0.3 0.0 0.3 0.3 0.0

Cover types-herbland—

Alpine nc nc 0.0 0.0 0.0 0.1 0.0 -0.1 1.2 0.0 -1.2

Colline bunchgrass + nc 3.7 5.2 1.5* 1.1 1.9 0.8 344.4 488.2 143.8

Colline exotic grasses-forbs nc + 4.6 4.0 -0.6 5.3 5.4 0.1 29.3 75.4 46.2*

Colline moist-site nc nc 0.1 0.2 0.0 0.5 0.5 0.0 11.1 12.2 1.1

Wet meadow nc nc 0.0 0.0 0.0 0.0 0.2 0.2 0.0 0.9 0.9

Postfire-grasses-forbs nc nc 0.4 0.2 -0.2 0.5 0.2 -0.3 15.8 11.0 -4.7

Cover types-agricultural-rural-urban—

Cropland + + 2.7 12.1 9.4* 3.3 4.2 0.9 52.1 229.4 177.3*

Pasture nc nc 0.1 0.2 0.2 0.1 0.2 0.1 9.4 13.3 3.9

Urban-rural + + 0.0 0.2 0.2* 0.6 1.7 1.1* 1.1 3.8 2.7*

Cover types-other—

Bare ground-road nc nc 0.1 0.1 0.0 0.2 0.2 0.0 9.3 10.2 0.9

Rock - nc 6.8 2.6 -4.1* 0.5 0.7 0.2 1884.0 182.3 -1701.7

Sand nc nc 0.5 0.4 -0.1 0.6 0.5 -0.1 13.4 10.6 -2.8

Stream channelnonvegetated flood plain nc nc 0.1 0.0 -0.1 0.4 0.0 -0.4 2.1 0.6 -1.5

Water nc nc 0.1 0.1 0.0 0.4 0.2 -0.2 3.4 5.5 2.1
336

Table 32—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No. /10 000 ha Hectares

Structural classes-forest—

Stand initiation - + 0.8 0.3 -0.5* 4.9 1.7 -3.3* 3.7 6.4 2.7

Stem exclusion, open canopy + + 0.4 1.0 0.6* 3.0 3.3 0.3 6.9 11.9 5.1*

Stem exclusion,

closed canopy nc nc 0.1 0.1 0.0 0.9 0.5 -0.4 1.6 1.5 -0.1

Understory reinitiation nc nc 2.5 1.6 -1.0 5.7 3.5 -2.1 11.6 13.7 2.0

Young, multistory nc + 0.6 1.1 0.5 2.7 1.2 -1.5* 7.5 22.6 15.1

Old, multistory nc nc 0.0 0.0 0.0 0.1 0.1 0.0 1.7 2.0 0.3

Old, single story nc nc 0.1 0.0 -0.1 0.3 0.1 -0.1 2.9 1.3 -1.7

Structural classes-woodland—

Stand initiation nc nc 0.4 0.2 -0.3 2.8 0.9 -1.9 1.7 1.9 0.2

Stem exclusion + + 0.7 2.0 1.3* 4.0 6.2 2.2* 8.7 17.9 9.3*

Understory reinitiation - - 1.8 0.8 -1.1* 4.4 2.9 -1.5 7.9 4.4 -3.5*

Structural classes-shrubland—

Open low-medium - nc 63.1 57.8 -5.3 9.7 8.5 -1.2 2352.3 2323.8 -28.5

Closed low-medium - + 8.2 5.0 -3.2 11.1 2.9 -8.2* 73.9 217.3 143.4

Open tall + + 3.0 5.2 2.3* 5.3 4.3 -1.1 35.6 54.5 18.9*

Closed tall - - 0.7 0.4 -0.4* 4.0 2.1 -1.9* 13.3 2.5 -10.8

Structural classes-herbland—

Open nc nc 8.1 9.1 1.0 5.4 6.2 0.8 371.1 480.2 109.2

Closed nc nc 0.7 0.3 -0.4 2.0 1.1 -0.9 24.9 17.6 -7.3

Structural classes-othere—

Nonforest-nonrange + nc 10.8 16.0 5.1 5.9 5.8 -0.1 395.0 433.3 38.3

a Choices for either field are (+) increase; (-) decrease; (nc) no ecologically significant change.

b Con. = connectivity change among patches in a patch type. 

c H = historical ; C = current; MD = mean difference of pairwise comparisons of historical and current subwatersheds.

d * = statistically significant difference at P≤0.2; all values rounded to 1 decimal place.

e “Other” includes anthropogenic cover types and other nonforest and nonrangeland (nonshrubland, nonherbland, nonwoodland) types.
337

Appendix 3

Table 33—Historical and current percentage of area, patch density, and mean patch size for insect

and pathogen disturbance vulnerability classes of sampled subwatersheds of the ERUs of the midscale ecological assessment of the interior Columbia River basin

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No. /10 000 ha Hectares

Blue Mountains ERU:

Western spruce budworm—

Low nc - 47.2 46.3 -0.9 27.7 35.3 7.6* 475.0 465.9 -9.1

Moderate nc - 14.6 14.8 0.2 29.1 35.0 5.9* 60.8 53.6 -7.2

High nc - 38.2 38.9 0.7 12.4 14.7 2.2* 568.4 516.4 -52.0

Douglas-fir beetle

Low - - 75.0 69.8 -5.2* 16.2 19.5 3.3* 1332.0 1241.5 -90.5

Moderate nc + 19.8 22.4 2.6 17.7 22.8 5.0* 145.3 199.2 53.9

High + + 5.2 7.8 2.5* 4.5 8.9 4.4* 65.3 76.1 10.8

Western pine beetle (type 1)— 

Low nc + 78.8 81.0 2.3 12.4 13.2 0.8 2098.7 3572.1 1473.5*

Moderate - - 18.8 16.5 -2.3* 11.3 15.2 3.9* 304.5 128.5 -176.0

High nc nc 2.5 2.5 0.0 4.2 3.8 -0.4 31.3 23.0 -8.3

Western pine beetle (type 2)— 

Low nc nc 51.6 54.2 2.6 26.7 27.6 0.9 589.7 680.2 90.5

Moderate - - 30.6 26.0 -4.5* 20.6 26.7 6.0* 259.7 141.8 -118.0*

High nc + 17.8 19.7 1.9 10.5 13.7 3.1* 166.9 254.5 87.6*

Mountain pine beetle (type 1)—

Low nc - 49.1 49.4 0.3 29.9 34.3 4.4* 661.0 447.3 -213.7*

Moderate nc nc 44.3 45.5 1.3 13.6 14.6 1.1 445.1 508.1 63.1

High - nc 6.7 5.1 -1.5* 9.1 10.6 1.6 55.0 46.1 -8.9

Mountain pine beetle (type 2)—

Low nc nc 51.6 54.2 2.6 26.7 27.6 0.9 589.7 680.2 90.5

Moderate - - 30.6 26.0 -4.5* 20.6 26.7 6.0* 259.7 141.8 -118.0*

High nc + 17.8 19.7 1.9 10.5 13.7 3.1* 166.9 254.5 87.6*

Fir engraver—

Low + - 65.0 70.4 5.3* 20.4 21.6 1.2 1907.4 1409.0 -498.4*

Moderate + + 10.3 14.6 4.3* 18.4 22.6 4.2* 65.3 81.4 16.1*

High - - 24.6 15.0 -9.7* 9.0 12.4 3.4* 428.3 142.2 -286.1*

Spruce beetle—

Low + nc 63.3 66.0 2.7* 28.1 29.0 0.9 1466.6 1452.4 -14.2

Moderate nc nc 34.1 33.3 -0.8 16.7 15.2 -1.5 385.6 350.0 -35.6

High - nc 2.6 0.7 -2.0* 1.9 0.9 -1.0* 25.2 19.2 -6.0

Douglas-fir dwarf mistletoe—

Low - - 65.5 57.4 -8.0* 20.8 29.0 8.2* 1016.1 903.9 -112.1

Moderate nc - 24.4 26.0 1.6 17.6 23.1 5.5* 199.6 185.0 -14.6

High + + 10.1 16.5 6.4* 9.3 19.6 10.3* 87.5 125.7 38.3*
338

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No. /10 000 ha Hectares

Western dwarf mistletoe—

Low nc nc 70.9 71.1 0.2 13.7 14.0 0.4 1741.6 2037.2 295.6

Moderate nc + 18.7 20.9 2.1 16.4 22.9 6.5* 161.0 171.3 10.2

High - - 10.4 8.1 -2.3* 9.6 12.7 3.0* 83.8 59.8 -24.0

Western larch dwarf mistletoe—

Low + nc 95.9 96.5 0.6* 5.2 4.9 -0.3 3638.2 4384.5 746.4

Moderate nc nc 2.9 2.7 -0.2 4.4 6.9 2.6* 26.5 30.1 3.5

High nc - 1.3 0.8 -0.4 1.8 3.6 1.7* 16.0 9.8 -6.1*

Lodgepole pine dwarf mistletoe—

Low + + 93.9 95.1 1.2* 6.3 5.5 -0.8* 3203.1 4194.6 991.6*

Moderate - nc 4.5 3.3 -1.2* 6.1 7.4 1.2 42.3 43.3 1.0

High nc nc 1.5 1.6 0.0 2.9 4.0 1.0 21.5 21.8 0.3

Armillaria root disease—

Low nc - 39.6 39.1 -0.5 27.3 34.2 7.0* 414.9 393.6 -21.2

Moderate nc - 19.6 19.9 0.2 28.7 35.2 6.6* 97.6 81.2 -16.4

High nc nc 40.7 41.0 0.3 13.0 13.6 0.7 485.0 616.2 131.2

Laminated root rot—

Low nc nc 50.6 50.1 -0.6 27.3 34.0 6.7* 523.7 545.4 21.7

Moderate - nc 14.9 13.0 -1.9* 22.2 26.0 3.8* 84.5 90.5 6.0

High nc + 34.5 37.0 2.5 12.6 13.9 1.3 376.7 572.4 195.6*

S-group annosum root disease—

Low nc nc 65.5 68.3 2.8 20.6 23.8 3.2* 2140.7 2092.4 -48.3

Moderate + + 10.2 14.8 4.7* 17.8 21.7 3.8* 54.0 84.1 30.0*

High - - 24.3 16.9 -7.5* 11.0 15.0 4.0* 238.3 114.7 -123.6*

P-group annosum root disease—

Low nc nc 72.7 72.1 -0.6 13.4 13.2 -0.2 1759.3 1993.3 234.1

Moderate nc nc 15.7 17.5 1.8 17.2 26.3 9.1* 87.5 91.8 4.4

High nc - 11.6 10.4 -1.1 9.5 11.3 1.8 110.7 75.2 -35.5*

Tomentosus root and butt rot—

Low nc nc 93.3 94.1 0.8 7.3 6.3 -1.0* 3335.0 3812.5 477.6

Moderate + nc 2.3 3.4 1.1* 3.7 4.9 1.3 18.4 23.5 5.2

High - nc 4.4 2.5 -1.9* 2.6 3.0 0.4 33.4 37.2 3.7

Schweinitzii root and butt rot—

Low nc nc 38.1 37.3 -0.9 26.9 32.0 5.1* 376.6 389.0 12.4

Moderate - - 15.1 10.6 -4.5* 25.0 27.8 2.7* 63.3 41.5 -21.8*

High + + 46.7 52.1 5.4* 12.7 10.5 -2.2* 807.1 956.2 149.1

Rust-red stringy rot—

Low nc nc 71.8 72.7 0.9 21.4 21.7 0.3 1656.8 1728.1 71.3

Moderate nc nc 27.0 26.5 -0.5 15.2 14.3 -1.0 233.3 215.2 -18.1

High nc nc 1.1 0.8 -0.4 1.7 2.4 0.7* 21.4 13.1 -8.3
339

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No. /10 000 ha Hectares

Central Idaho Mountains ERU:

Western spruce budworm—

Low nc + 31.7 32.0 0.3 26.6 33.7 7.1* 461.0 474.4 13.3

Moderate - - 18.9 16.9 -2.0* 29.9 36.7 6.8* 73.9 51.9 -22.1*

High nc nc 49.4 51.1 1.7 13.4 14.0 0.7 869.7 911.9 42.2

Douglas-fir beetle—

Low nc - 74.0 72.9 -1.1 14.7 15.5 0.8 2322.0 1776.8 -545.2*

Moderate nc nc 21.6 22.1 0.6 15.7 17.4 1.7 164.1 141.1 -23.0

High nc nc 4.4 5.0 0.6 8.1 8.6 0.5 44.4 60.6 16.2

Western pine beetle (type 1)—

Low nc nc 94.7 95.2 0.4 7.2 8.4 1.2* 2679.7 2738.8 59.1

Moderate - - 4.3 3.5 -0.8* 3.7 4.3 0.6 34.3 20.1 -14.2*

High nc - 1.0 1.3 0.3 1.6 2.8 1.2* 9.3 8.7 -0.6

Western pine beetle (type 2)—

Low - - 57.1 54.6 -2.6* 23.0 30.7 7.7* 888.3 850.7 -37.6

Moderate + nc 39.6 42.1 2.5* 22.4 22.7 0.3 395.2 463.0 67.8

High nc nc 3.3 3.3 0.0 3.0 3.6 0.6 28.7 23.8 -4.8

Mountain pine beetle (type 1)—

Low - - 43.8 41.8 -2.0* 23.9 29.3 5.4* 1173.9 857.3 -316.6*

Moderate nc - 35.1 36.0 0.9 24.8 27.2 2.4 452.6 184.5 -268.1*

High nc nc 21.0 22.1 1.1 16.4 17.3 0.9 165.4 130.6 -34.8

Mountain pine beetle (type 2)—

Low - - 57.1 54.6 -2.6* 23.0 30.7 7.7* 888.3 850.7 -37.6

Moderate + nc 39.6 42.1 2.5* 22.4 22.7 0.3 395.2 463.0 67.8

High nc nc 3.3 3.3 0.0 3.0 3.6 0.6 28.7 23.8 -4.8

Fir engraver—

Low nc + 57.1 56.9 -0.2 20.5 26.9 6.4* 1079.7 1220.7 141.1

Moderate - - 21.6 16.9 -4.7* 30.3 32.3 2.1 97.2 55.9 -41.3*

High + + 21.3 26.2 4.9* 17.3 16.7 -0.6 156.7 254.6 97.9*

Spruce beetle—

Low - - 65.8 63.1 -2.8* 17.4 23.9 6.5* 1831.2 1491.0 -340.2*

Moderate + nc 31.1 33.4 2.3* 19.9 19.8 -0.1 225.7 241.5 15.9

High nc nc 3.1 3.6 0.4 4.6 6.3 1.7* 59.4 37.2 -22.2

Douglas-fir dwarf mistletoe—

Low + nc 67.4 69.6 2.2* 15.4 16.2 0.8 2343.7 1896.8 -446.9*

Moderate - nc 21.9 19.9 -2.0* 20.4 22.8 2.4 137.8 97.4 -40.4

High nc nc 10.7 10.5 -0.2 11.0 14.6 3.6* 95.4 75.0 -20.3

Western dwarf mistletoe—

Low nc nc 93.8 93.9 0.1 6.7 8.3 1.5* 3121.7 2991.7 -130.0

Moderate nc nc 3.9 4.4 0.4 5.1 5.3 0.1 24.1 23.5 -0.6

High - - 2.2 1.8 -0.5* 2.8 2.8 0.0 17.2 11.4 -5.7*
340

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Western larch dwarf mistletoe—

Low + + 97.4 98.7 1.3* 5.1 4.5 -0.7* 3389.1 4079.1 689.9*

Moderate - nc 2.1 1.1 -0.9* 3.7 3.0 -0.6 15.9 13.2 -2.7

High nc nc 0.5 0.1 -0.4 0.7 0.5 -0.1 5.5 3.1 -2.5

Lodgepole pine dwarf mistletoe—

Low + nc 70.1 71.7 1.7* 13.6 14.3 0.7 2035.5 2086.5 51.0

Moderate - - 16.3 13.1 -3.1* 22.0 21.9 -0.2 68.0 50.7 -17.3*

High nc nc 13.7 15.1 1.5 16.4 16.1 -0.3 71.1 76.2 5.0

Armillaria root disease—

Low nc - 31.6 30.7 -0.9 27.8 37.0 9.1* 541.7 425.5 -116.2

Moderate nc - 30.8 30.1 -0.7 31.8 33.9 2.1 166.8 128.2 -38.6*

High nc nc 37.6 39.2 1.6 17.5 18.6 1.0 361.6 418.2 56.6

Laminated root rot—

Low nc - 43.6 43.7 0.1 23.8 32.0 8.2* 737.0 545.4 -191.6*

Moderate nc nc 27.0 28.5 1.4 26.8 28.2 1.4 196.3 227.6 31.3

High nc - 29.3 27.8 -1.5 14.5 19.3 4.8* 321.5 253.2 -68.3*

S-group annosum root disease—

Low nc - 38.8 38.7 -0.2 28.7 36.3 7.5* 592.8 467.3 -125.6

Moderate - - 25.0 22.4 -2.5* 35.2 36.9 1.7 89.1 61.4 -27.7*

High + nc 36.2 38.9 2.7* 17.9 19.3 1.4 378.4 377.5 -0.9

P-group annosum root disease—

Low nc nc 94.4 94.3 0.0 6.6 8.0 1.5* 2993.0 3088.2 95.2

Moderate nc nc 3.5 3.9 0.4 4.6 5.3 0.7 21.6 20.9 -0.6

High - - 2.1 1.7 -0.4* 2.7 2.8 0.1 15.0 12.4 -2.7*

Tomentosus root and butt rot—

Low nc + 79.3 77.7 -1.6 11.1 11.8 0.7 2363.1 2375.5 12.4

Moderate nc - 11.4 11.3 -0.1 16.6 19.9 3.3* 55.4 43.1 -12.3*

High + + 9.3 11.0 1.7* 12.4 15.0 2.6* 61.5 69.9 8.4

Schweinitzii root and butt rot—

Low nc - 30.2 29.9 -0.3 22.4 30.4 8.0* 591.0 462.4 -128.6

Moderate nc + 12.7 13.9 1.2 25.3 28.5 3.2* 50.9 53.2 2.2

High nc nc 57.1 56.2 -0.9 10.2 11.0 0.9 1254.1 1527.6 273.5

White pine blister rust (type 1)—

Low nc nc 62.1 61.9 -0.1 8.9 10.0 1.2* 2912.8 2712.5 -200.3

Moderate nc nc 37.9 38.0 0.1 8.0 8.5 0.6 1154.9 1103.2 -51.7

High nc nc 0.0 0.1 0.0 0.2 0.4 0.2 1.4 0.5 -0.9

White pine blister rust (type 2)—

Low nc - 84.1 84.1 0.0 4.4 5.9 1.5* 4812.1 4353.2 -458.9*

Moderate nc nc 15.2 15.3 0.1 11.5 12.1 0.5 151.5 128.7 -22.8

High nc nc 0.7 0.6 0.0 2.2 2.2 0.0 6.7 7.7 1.0
341

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Rust-red stringy rot—

Low - - 80.4 77.6 -2.8* 7.9 12.3 4.4* 3042.7 2607.3 -435.4*

Moderate + nc 19.5 22.2 2.6* 18.9 19.5 0.6 125.7 178.6 52.9

High nc nc 0.1 0.3 0.2 0.2 0.5 0.3* 1.3 2.5 1.2

Columbia Plateau ERU:

Western spruce budworm—

Low - nc 83.7 82.3 -1.3* 9.9 12.4 2.4 3311.6 3089.5 -222.1

Moderate nc nc 7.0 5.7 -1.3 8.7 7.4 -1.3 66.4 43.3 -23.2

High + nc 9.3 12.0 2.7* 3.6 4.2 0.6 132.7 172.9 40.2

Douglas-fir beetle—

Low - nc 90.0 88.0 -2.0* 10.4 10.1 -0.3 2690.2 2432.6 -257.6

Moderate + nc 7.1 9.4 2.3* 5.3 6.2 0.9 58.7 81.6 22.9

High nc nc 2.9 2.6 -0.3 2.2 2.0 -0.2 31.5 36.8 5.4

Western pine beetle (type 1)—

Low nc nc 83.7 82.5 -1.2 11.9 10.6 -1.3 2651.5 2838.7 187.2

Moderate + + 11.8 14.6 2.9* 6.5 6.3 -0.2 105.2 171.5 66.3*

High nc - 4.6 2.9 -1.6 3.9 3.1 -0.8 50.8 26.6 -24.1*

Western pine beetle (type 2)—

Low - nc 75.3 71.1 -4.2* 10.6 12.7 2.1 4404.0 3719.9 -684.1

Moderate + nc 9.8 11.8 2.0* 10.3 9.2 -1.1 81.3 301.2 219.9

High + nc 14.9 17.1 2.2* 4.6 4.0 -0.6 199.1 245.8 46.7

Mountain pine beetle (type 1)—

Low - - 87.5 85.9 -1.7* 6.6 10.6 3.9* 4032.8 3505.1 -527.6

Moderate nc nc 10.7 11.7 1.1 6.5 6.3 -0.1 124.6 102.2 -22.4

High nc nc 1.8 2.4 0.6 1.4 2.6 1.1 32.2 36.2 4.1

Mountain pine beetle (type 2)—

Low - nc 75.3 71.1 -4.2* 10.6 12.7 2.1 4404.0 3719.9 -684.1

Moderate + nc 9.8 11.8 2.0* 10.3 9.2 -1.1 81.3 301.2 219.9

High + nc 14.9 17.1 2.2* 4.6 4.0 -0.6 199.1 245.8 46.7

Fir engraver—

Low nc + 92.9 94.8 1.9 6.1 7.1 1.0* 3089.7 3281.7 192.0

Moderate nc - 2.6 2.3 -0.3 3.9 4.4 0.5 27.9 20.2 -7.6*

High + nc 1.8 2.9 1.0* 1.6 2.7 1.1 47.2 26.8 -20.4

Douglas-fir dwarf mistletoe—

Low - nc 87.5 85.5 -2.0* 10.7 10.9 0.2 2491.6 2397.0 -94.7

Moderate + nc 5.6 8.1 2.5* 8.9 7.3 -1.6 38.7 41.8 3.1

High nc nc 6.9 6.4 -0.6 3.9 3.9 0.0 70.1 65.7 -4.4

Western dwarf mistletoe—

Low - nc 80.7 77.8 -2.9* 10.4 10.3 -0.1 3217.1 3203.4 -13.7

Moderate + + 8.5 14.3 5.9* 11.1 7.4 -3.7* 40.9 163.8 122.9*

High nc nc 10.8 7.8 -3.0 5.3 5.5 0.2 108.9 65.5 -43.4
342

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Western larch dwarf mistletoe—

Low + nc 98.7 99.4 0.8* 5.9 6.1 0.2 4148.8 3954.7 -194.1

Moderate - nc 1.3 0.5 -0.8* 0.7 1.0 0.3 23.2 4.8 -18.4

High nc nc 0.0 0.1 0.0 0.1 0.2 0.2 2.0 3.2 1.1

Lodgepole pine dwarf mistletoe—

Low nc + 98.3 98.1 -0.3 6.8 7.1 0.3 3689.6 4175.1 485.5*

Moderate nc nc 1.4 1.6 0.1 1.0 1.0 -0.1 89.6 31.2 -58.4

High nc + 0.2 0.4 0.1 0.4 0.3 -0.1 3.7 15.3 11.6*

Armillaria root disease—

Low nc nc 77.2 76.2 -1.0 11.1 12.8 1.7 2568.0 2725.7 157.7

Moderate nc - 13.7 13.3 -0.5 10.8 10.8 0.0 349.2 78.5 -270.8*

High nc nc 9.1 10.5 1.4 4.0 5.0 1.0 117.8 117.8 0.0

Laminated root rot—

Low - nc 84.7 82.1 -2.6* 10.7 11.3 0.6 3055.8 3239.5 183.7

Moderate + nc 4.9 8.3 3.4* 9.0 7.5 -1.5 37.3 55.4 18.1

High nc nc 10.4 9.7 -0.8 4.1 4.8 0.7 114.4 98.4 -16.0

S-group annosum root disease—

Low - + 94.4 92.3 -2.1* 6.4 9.2 2.8* 3504.4 3588.7 84.4

Moderate - - 4.8 2.3 -2.5* 2.8 3.6 0.7 72.1 20.7 -51.4*

High + + 0.8 5.4 4.6* 1.3 2.2 0.9* 15.6 132.1 116.5*

P-group annosum root disease—

Low nc nc 80.6 78.8 -1.8 11.4 10.2 -1.2 3116.6 3219.4 102.9

Moderate + nc 7.7 10.0 2.4* 10.6 9.1 -1.5* 53.2 61.7 8.5

High nc nc 11.8 11.2 -0.6 5.0 5.0 0.0 139.1 137.3 -1.8

Schweinitzii root and butt rot—

Low - nc 75.1 72.6 -2.5* 11.1 13.3 2.2 2891.4 2727.1 -164.2

Moderate + nc 7.8 12.0 4.3* 10.4 9.6 -0.9 106.3 82.4 -23.8

High nc nc 17.2 15.4 -1.8 5.7 6.7 0.9 209.8 184.5 -25.4

White pine blister rust (type 1)—

Low + nc 95.7 97.1 1.5* 4.1 4.7 0.6 8057.2 7847.6 -209.6

Moderate nc nc 2.9 2.8 -0.1 0.4 1.0 0.5 60.6 24.5 -36.1

High - nc 1.4 0.1 -1.4* 0.2 0.2 0.0 45.6 4.3 -41.3

Rust-red stringy rot—

Low - - 98.2 95.2 -2.9* 6.0 7.7 1.6* 4276.8 3221.8 -1055.0*

Moderate + nc 1.8 4.7 2.9* 1.7 3.2 1.5* 30.0 36.3 6.4

High nc + 0.0 0.1 0.0* 0.1 0.2 0.1* 0.8 3.5 2.7*

Lower Clark Fork ERU: 

Western spruce budworm—

Low nc - 20.2 15.7 -4.5 27.4 38.2 10.8 93.5 45.8 -47.7*

Moderate nc nc 23.0 19.3 -3.6 38.6 37.2 -1.4 59.6 54.9 -4.8

High nc nc 56.8 65.0 8.2 20.8 15.0 -5.8 511.6 563.2 51.6
343

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Douglas-fir beetle—

Low - - 91.6 65.3 -26.4* 2.4 12.4 10.0* 4905.7 1580.2 -3325.5*

Moderate + + 8.1 28.8 20.7* 13.0 18.8 5.8 56.4 173.9 117.5*

High nc nc 0.2 5.9 5.7 0.2 4.2 4.0 19.0 49.2 30.2

Western pine beetle (type 1)—

Low nc nc 99.9 96.5 -3.3 5.8 5.6 -0.2 3334.5 3339.5 5.0

Moderate nc nc 0.2 2.9 2.7 0.2 3.6 3.4 14.1 19.5 5.4

High nc nc 0.0 0.6 0.6 0.0 0.4 0.4 0.0 36.0 36.0

Western pine beetle (type 2)—

Low - - 28.7 15.3 -13.4* 30.8 47.4 16.6 155.7 37.6 -118.1*

Moderate + + 69.8 80.9 11.1* 17.0 5.0 -12.0* 652.6 2399.2 1746.7*

High nc nc 1.5 3.8 2.3 2.4 3.6 1.2 26.3 35.6 9.3

Mountain pine beetle (type 1)—

Low - - 30.0 17.3 -12.6* 28.8 49.4 20.6* 150.1 36.4 -113.7*

Moderate nc + 66.1 69.8 3.7 15.2 7.8 -7.4* 726.3 1898.4 1172.1

High + nc 4.0 12.9 8.9* 10.6 15.8 5.2 40.1 60.8 20.7

Mountain pine beetle (type 2)—

Low - - 28.7 15.3 -13.4* 30.8 47.4 16.6 155.7 37.6 -118.1*

Moderate + + 69.8 80.9 11.1* 17.0 5.0 -12.0* 652.6 2399.2 1746.7*

High nc nc 1.5 3.8 2.3 2.4 3.6 1.2 26.3 35.6 9.3

Fir engraver—

Low nc - 56.9 48.8 -8.1 16.2 28.6 12.4* 1435.3 198.3 -1237.0

Moderate nc nc 14.8 14.2 -0.6 27.2 33.6 6.4 54.0 49.3 -4.7

High nc nc 28.3 37.0 8.7 22.6 25.4 2.8 129.7 171.8 42.1

Spruce beetle—

Low nc nc 87.8 85.7 -2.1 4.6 3.4 -1.2 4346.8 4712.6 365.8

Moderate nc nc 12.1 13.8 1.7 17.6 23.0 5.4 81.2 61.6 -19.6

High nc nc 0.1 0.5 0.4 0.6 1.4 0.8 11.0 16.8 5.8

Douglas-fir dwarf mistletoe—

Low nc nc 56.5 58.0 1.5 12.2 14.6 2.4 642.1 624.4 -17.7

Moderate nc + 37.5 34.1 -3.4 32.4 22.8 -9.6* 127.9 208.2 80.3

High nc nc 6.0 7.9 1.9 13.0 15.4 2.4 44.7 52.0 7.3

Western dwarf mistletoe—

Low nc nc 97.8 94.9 -2.9 4.8 4.6 -0.2 3437.3 4609.8 1172.5

Moderate nc + 2.2 4.3 2.1 3.4 5.2 1.8* 27.1 37.2 10.1

High nc nc 0.0 0.9 0.9 0.0 0.4 0.4 0.0 53.7 53.7

Western larch dwarf mistletoe—

Low nc nc 95.7 94.9 -0.8 3.8 2.6 -1.2 3290.7 5281.9 1991.2

Moderate nc + 4.1 4.9 0.8 6.8 7.0 0.2 32.2 54.8 22.6*

High nc nc 0.2 0.2 0.0 0.6 0.8 0.2 6.7 11.6 4.9
344

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Lodgepole pine dwarf mistletoe—

Low nc - 95.5 90.0 -5.5 2.2 3.8 1.6* 6118.5 2691.1 -3427.4*

Moderate nc nc 4.3 7.5 3.2 8.8 13.2 4.4 39.5 42.1 2.6

High nc + 0.2 2.6 2.3 1.2 3.4 2.2 9.1 31.2 22.1*

Armillaria root disease—

Low nc nc 9.9 6.9 -3.0 21.2 34.8 13.6 61.7 25.7 -36.0

Moderate nc nc 35.1 28.0 -7.1 34.4 32.0 -2.4 124.0 88.8 -35.2

High nc nc 55.0 65.1 10.1 18.2 14.8 -3.4 684.7 548.2 -136.4

Laminated root rot—

Low nc nc 11.2 11.0 -0.2 23.6 38.2 14.6 79.4 35.5 -43.9

Moderate nc nc 29.4 27.0 -2.4 33.0 33.8 0.8 99.2 83.9 -15.2

High nc nc 59.4 62.0 2.6 17.0 16.2 -0.8 515.9 479.0 -36.9

S-group annosum root disease—

Low nc nc 11.0 10.0 -1.0 23.0 36.6 13.6 71.5 35.2 -36.3

Moderate nc nc 17.6 12.9 -4.7 32.0 23.0 -9.0* 62.7 65.6 2.9

High nc nc 71.4 77.0 5.7 12.0 8.0 -4.0 3051.7 2622.5 -429.2

P-group annosum root disease—

Low nc nc 98.1 96.7 -1.4 5.8 4.8 -1.0 1896.2 3420.4 1524.3

Moderate nc nc 1.9 3.0 1.1 2.6 3.8 1.2 15.0 22.3 7.3

High nc nc 0.0 0.2 0.2 0.0 0.8 0.8 0.0 9.8 9.8

Tomentosus root and butt rot—

Low nc nc 97.7 97.4 -0.3 3.8 2.0 -1.8 5265.8 6322.7 1056.9

Moderate nc nc 1.3 1.1 -0.2 4.6 4.6 0.0 17.5 21.5 4.1

High nc + 1.0 1.5 0.5 2.8 2.6 -0.2 28.3 42.6 14.3*

Schweinitzii root and butt rot—

Low nc nc 8.4 6.1 -2.3 21.0 33.2 12.2 56.5 25.3 -31.2

Moderate + + 35.4 41.6 6.2* 25.0 17.8 -7.2* 204.2 479.6 275.4

High nc nc 56.2 52.3 -4.0 17.8 17.0 -0.8 436.8 1437.1 1000.2

White pine blister rust (type 1)—

Low nc - 27.4 29.9 2.5 25.4 18.0 -7.4* 216.4 204.1 -12.3

Moderate nc nc 71.8 66.4 -5.4 7.2 8.8 1.6 1466.1 1814.6 348.5

High nc + 0.8 3.7 2.9 3.2 6.6 3.4* 29.8 54.1 24.2

Rust-red stringy rot—

Low nc nc 47.9 46.2 -1.7 22.0 34.4 12.4 644.3 1073.8 429.5

Moderate nc + 51.2 52.1 0.9 18.6 14.2 -4.4* 400.9 1053.3 652.3*

High nc nc 1.0 1.7 0.7 2.6 4.2 1.6 16.2 30.8 14.6

Northern Cascades ERU: 

Western spruce budworm—

Low nc + 30.7 31.8 1.1 21.1 29.0 7.9* 373.3 497.0 123.8

Moderate nc nc 17.8 17.8 0.0 20.3 27.0 6.7* 107.6 104.2 -3.4

High nc nc 51.5 50.4 -1.1 10.4 10.9 0.5 972.3 929.1 -43.2
345

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Douglas-fir beetle—

Low + + 65.1 68.4 3.3* 11.7 16.9 5.2* 1599.1 1614.2 15.1

Moderate nc - 26.2 24.2 -2.0 11.8 15.2 3.4* 376.5 274.8 -101.7*

High nc - 8.7 7.4 -1.3 6.2 8.2 2.0* 149.9 89.2 -60.8*

Western pine beetle (type 1)—

Low + nc 84.5 89.3 4.8* 7.3 6.9 -0.3 3112.8 3373.0 260.2

Moderate - - 11.8 8.9 -2.9* 7.2 7.5 0.3 153.9 89.4 -64.6*

High - - 3.7 1.8 -1.9* 2.8 2.4 -0.4 74.5 42.8 -31.7*

Western pine beetle (type 2)—

Low + + 46.6 49.9 3.3* 16.8 23.0 6.1* 765.4 801.8 36.4

Moderate nc - 43.6 41.9 -1.7 13.5 17.4 3.9* 631.7 369.6 -262.1*

High - - 9.8 8.2 -1.6* 4.8 5.2 0.4 227.4 96.8 -130.6*

Mountain pine beetle (type 1)—

Low nc + 48.5 48.8 0.3 16.9 23.1 6.1* 740.3 753.0 12.6

Moderate nc nc 46.2 44.4 -1.8 13.9 15.3 1.4 522.6 553.7 31.1

High nc + 5.3 6.8 1.5 4.8 6.6 1.7* 91.6 163.2 71.7

Mountain pine beetle (type 2)—

Low + + 46.6 49.9 3.3* 16.8 23.0 6.1* 765.4 801.8 36.4

Moderate nc - 43.6 41.9 -1.7 13.5 17.4 3.9* 631.7 369.6 -262.1*

High - - 9.8 8.2 -1.6* 4.8 5.2 0.4 227.4 96.8 -130.6*

Fir engraver—

Low nc - 57.0 57.8 0.8 16.1 21.0 5.0* 1569.1 1302.1 -267.0

Moderate - - 22.6 20.7 -1.9* 19.0 24.2 5.1* 149.3 126.7 -22.6

High nc nc 20.4 21.5 1.1 12.6 13.2 0.6 236.3 207.3 -29.0

Spruce beetle—

Low + + 56.8 60.7 3.8* 15.5 19.1 3.6* 1023.9 1037.4 13.5

Moderate - - 37.2 34.0 -3.2* 13.8 16.6 2.8* 375.5 330.3 -45.2

High nc nc 6.0 5.3 -0.7 3.8 4.1 0.3 105.3 93.3 -12.0

Douglas-fir dwarf mistletoe—

Low nc - 58.1 59.1 1.0 12.3 18.9 6.6* 1400.9 1250.2 -150.7

Moderate nc - 23.4 23.1 -0.3 14.1 18.1 4.0* 212.4 183.8 -28.6

High nc nc 18.6 17.9 -0.7 9.5 11.2 1.7* 222.1 196.2 -25.9

Western dwarf mistletoe—

Low + nc 81.5 85.3 3.9* 7.6 7.7 0.1 2992.8 2971.5 -21.3

Moderate - - 13.0 10.8 -2.2* 7.1 9.2 2.1* 156.3 90.4 -65.8*

High - - 5.6 3.9 -1.7* 4.1 4.1 0.0 87.0 42.5 -44.6*

Western larch dwarf mistletoe—

Low nc nc 98.5 98.4 0.0 3.7 4.1 0.5 5414.5 5393.3 -21.1

Moderate nc nc 1.0 1.1 0.1 1.8 2.2 0.4 29.5 23.9 -5.6

High nc nc 0.5 0.4 -0.1 0.6 0.5 -0.1 20.6 10.6 -10.0
346

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Lodgepole pine dwarf mistletoe—

Low nc nc 90.8 91.8 1.0 4.7 3.9 -0.8* 4662.7 5303.4 640.8

Moderate - nc 6.5 5.1 -1.4* 4.3 4.4 0.1 104.1 114.2 10.2

High nc nc 2.7 3.1 0.4 2.2 2.5 0.4* 65.3 68.0 2.7

Armillaria root disease—

Low nc nc 27.6 28.8 1.2 19.3 28.8 9.4* 353.2 330.6 -22.5

Moderate + nc 23.7 25.9 2.2* 20.4 26.2 5.7* 142.5 145.7 3.2

High - - 48.6 45.2 -3.4* 10.7 12.4 1.7* 681.2 563.9 -117.3*

Laminated root rot—

Low nc + 35.8 35.7 -0.1 19.3 28.4 9.0* 575.7 625.7 49.9

Moderate + + 22.5 25.0 2.6* 16.8 21.3 4.5* 203.6 344.0 140.4

High - - 41.7 39.2 -2.5* 8.5 10.4 1.9* 837.9 541.1 -296.8*

S-group annosum root disease—

Low nc - 47.6 46.4 -1.2 19.1 27.2 8.1* 1187.8 743.0 -444.8

Moderate nc nc 22.7 21.4 -1.4 17.7 19.1 1.4 144.0 147.0 3.0

High + + 29.6 32.2 2.6* 13.2 14.9 1.7* 335.3 360.5 25.3

P-group annosum root disease—

Low + nc 82.0 85.1 3.1* 7.6 7.5 -0.1 2928.6 3196.4 267.8

Moderate - - 10.6 9.0 -1.6* 7.5 9.9 2.4* 99.6 52.7 -46.9*

High - - 7.5 5.9 -1.5* 4.6 4.8 0.2 114.1 74.9 -39.2*

Tomentosus root and butt rot—

Low nc + 79.8 80.9 1.2 7.2 6.7 -0.6 2608.8 3563.5 954.6*

Moderate nc nc 8.9 9.2 0.3 11.3 11.6 0.3 74.1 72.3 -1.7

High - nc 11.4 9.9 -1.5* 8.4 9.5 1.1* 141.3 120.5 -20.8

Schweinitzii root and butt rot—

Low + nc 26.0 27.4 1.4* 18.0 26.9 8.9* 358.4 387.1 28.7

Moderate + nc 12.9 15.4 2.6* 17.9 22.5 4.6* 76.8 83.4 6.6

High - - 61.2 57.2 -4.0* 5.9 7.6 1.7* 1855.9 1266.6 -589.4*

White pine blister rust (type 1)—

Low nc nc 61.2 61.0 -0.2 8.4 9.0 0.7* 3103.1 3097.6 -5.5

Moderate nc nc 38.7 38.8 0.1 5.5 5.5 0.0 1053.2 1157.0 103.8

High + + 0.1 0.2 0.1* 0.3 0.4 0.1 2.2 6.7 4.5*

White pine blister rust (type 2)—

Low - nc 93.2 92.7 -0.5* 1.8 1.7 -0.1 7479.3 7874.9 395.6

Moderate nc - 6.4 6.4 0.0 7.4 8.6 1.2* 77.1 59.5 -17.6*

High + + 0.4 0.9 0.5* 0.8 1.1 0.3* 11.5 24.5 13.0*

Rust-red stringy rot—

Low nc - 64.5 64.8 0.3 14.7 19.0 4.2* 1504.8 1258.1 -246.8

Moderate nc - 34.9 34.1 -0.9 11.5 14.1 2.6* 399.7 364.1 -35.7

High + nc 0.6 1.1 0.6* 0.9 1.9 1.0* 21.0 25.1 4.1
347

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Northern Glaciated Mountains ERU: 

Western spruce budworm—

Low nc - 29.8 28.2 -1.7 24.2 41.3 17.1* 405.0 334.2 -70.8

Moderate nc - 25.7 23.9 -1.7 23.3 38.3 15.0* 144.5 74.7 -69.7*

High + - 44.5 47.9 3.4* 12.2 16.5 4.3* 806.8 742.4 -64.4

Douglas-fir beetle—

Low nc - 66.3 65.5 -0.7 15.7 26.0 10.3* 1363.3 834.5 -528.9*

Moderate nc - 30.2 29.5 -0.7 13.8 21.9 8.0* 359.2 281.3 -77.9*

High nc nc 3.6 5.0 1.4 4.9 9.3 4.4* 43.6 44.2 0.6

Western pine beetle (type 1)—

Low nc nc 91.6 91.3 -0.3 7.9 10.0 2.1 3684.8 3900.6 215.8

Moderate nc nc 7.2 7.8 0.6 7.1 7.1 0.0 70.7 83.5 12.8

High nc nc 1.2 0.9 -0.3 1.7 2.9 1.2 13.5 8.8 -4.7

Western pine beetle (type 2)—

Low nc - 45.6 45.9 0.3 25.1 39.4 14.3* 919.2 438.0 -481.2*

Moderate nc - 46.5 46.8 0.4 15.6 20.8 5.2* 704.3 578.3 -126.0

High nc nc 7.9 7.3 -0.6 6.0 7.0 1.0 81.1 110.5 29.4

Mountain pine beetle (type 1)—

Low nc - 39.6 38.3 -1.3 21.9 37.2 15.3* 733.5 570.7 -162.9

Moderate nc - 45.1 42.8 -2.3 13.5 22.0 8.5* 561.7 367.9 -193.9*

High + + 15.4 18.9 3.6* 9.3 15.8 6.4* 186.6 201.1 14.5

Mountain pine beetle (type 2)—

Low nc - 45.6 45.9 0.3 25.1 39.4 14.3* 919.2 438.0 -481.2*

Moderate nc - 46.5 46.8 0.4 15.6 20.8 5.2* 704.3 578.3 -126.0

High nc nc 7.9 7.3 -0.6 6.0 7.0 1.0 81.1 110.5 29.4

Fir engraver—

Low - - 76.0 70.5 -5.5* 10.6 18.4 7.9* 2305.4 1307.7 -997.7*

Moderate + - 17.2 21.1 3.9* 14.4 22.8 8.5* 151.3 117.4 -33.9*

High nc - 6.8 8.4 1.6 4.3 12.0 7.7* 135.2 90.6 -44.7

Spruce beetle—

Low nc - 60.7 60.2 -0.5 16.1 29.2 13.1* 1379.3 726.4 -653.0*

Moderate nc - 36.2 35.2 -1.0 13.3 19.3 6.0* 381.4 307.8 -73.6*

High + + 3.0 4.5 1.5* 2.6 4.7 2.1* 46.6 79.9 33.3*

Douglas-fir dwarf mistletoe—

Low nc - 57.3 56.4 -1.0 17.1 28.2 11.1* 921.0 710.4 -210.6*

Moderate nc - 29.6 29.3 -0.3 18.2 27.4 9.2* 293.1 197.3 -95.8*

High nc - 13.1 14.3 1.2 9.4 15.8 6.4* 219.5 129.9 -89.6

Western dwarf mistletoe—

Low nc nc 86.3 86.8 0.5 8.2 12.2 4.0* 3766.2 3466.3 -299.9

Moderate nc nc 9.9 10.7 0.8 9.2 10.5 1.3 96.3 123.6 27.4

High - - 3.8 2.5 -1.2* 4.1 5.3 1.2 57.1 16.0 -41.2*
348

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Western larch dwarf mistletoe—

Low + + 73.8 81.3 7.5* 11.4 13.0 1.6 1923.9 2306.4 382.5*

Moderate - - 19.4 14.6 -4.8* 11.3 16.0 4.7* 195.2 92.2 -103.0*

High - - 6.9 4.2 -2.7* 7.8 7.0 -0.7 57.6 38.5 -19.1*

Lodgepole pine dwarf mistletoe—

Low + nc 73.8 77.2 3.4* 9.8 13.2 3.5* 2245.8 2011.0 -234.8

Moderate - - 16.9 13.6 -3.3* 11.1 17.0 5.8* 156.0 91.0 -65.0*

High nc - 9.3 9.1 -0.1 6.1 9.9 3.8* 130.2 83.3 -46.9*

Armillaria root disease—

Low nc + 24.1 23.8 -0.3 26.2 41.2 15.0* 289.3 315.9 26.5

Moderate - - 38.6 35.5 -3.1* 20.7 31.2 10.5* 324.0 199.1 -124.9*

High + - 37.3 40.7 3.4* 14.1 20.8 6.6* 511.9 461.9 -50.1

Laminated root rot—

Low - - 40.2 35.9 -4.3* 23.9 40.8 16.9* 443.4 357.2 -86.2

Moderate nc - 32.0 33.1 1.1 19.0 26.6 7.6* 353.0 281.3 -71.7

High nc + 27.8 31.0 3.2 15.0 20.4 5.4* 364.3 537.3 172.9

S-group annosum root disease—

Low - - 54.1 47.1 -6.9* 18.4 32.2 13.8* 776.2 531.0 -245.2*

Moderate nc - 25.9 26.1 0.2 17.2 31.0 13.8* 254.8 109.6 -145.2*

High + + 20.0 26.8 6.8* 9.3 20.5 11.2* 317.8 312.8 -5.0

P-group annosum root disease—

Low nc nc 87.8 87.8 0.0 7.5 10.5 3.0* 4000.9 4282.0 281.1

Moderate nc nc 9.1 8.2 -0.9 8.5 11.1 2.6 105.9 103.7 -2.2

High nc nc 3.1 4.0 0.8 3.6 5.4 1.9 40.0 23.7 -16.4

Tomentosus root and butt rot—

Low nc nc 85.1 83.4 -1.7 7.0 8.1 1.0* 2409.5 2265.9 -143.5

Moderate nc nc 7.8 7.5 -0.2 7.5 14.5 7.0* 98.0 87.4 -10.6

High + + 7.1 9.0 1.9* 5.9 10.8 4.9* 89.6 84.7 -4.9

Schweinitzii root and butt rot—

Low nc + 20.0 20.1 0.1 20.1 34.0 14.0* 288.8 313.8 25.0

Moderate nc - 13.2 14.1 1.0 15.8 27.2 11.4* 93.7 70.6 -23.1*

High nc - 66.9 65.8 -1.1 5.9 8.0 2.2* 2614.0 1998.3 -615.7*

White pine blister rust (type 1)—

Low + + 62.9 63.7 0.9* 7.8 9.8 2.0* 2451.0 2208.7 -242.3

Moderate nc - 35.3 35.9 0.6 8.0 9.7 1.7* 1277.6 1055.8 -221.8

High - - 1.9 0.3 -1.5* 1.1 0.6 -0.5 26.3 4.2 -22.1*

White pine blister rust (type 2)—

Low nc + 87.7 87.5 -0.3 3.6 4.2 0.6* 4868.2 4894.0 25.8

Moderate nc - 12.3 12.5 0.2 6.4 9.0 2.6* 213.6 188.7 -24.9

High nc nc 0.0 0.0 0.0 0.0 0.0 0.0 0.3 2.0 1.7
349

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Rust-red stringy rot—

Low - - 87.3 81.7 -5.6* 5.7 11.1 5.4* 3925.2 2290.7 -1634.5*

Moderate + nc 12.7 18.1 5.4* 9.8 20.0 10.2* 142.9 122.5 -20.4

High + + 0.0 0.2 0.2* 0.0 0.6 0.6* 1.1 5.9 4.8*

Snake Headwaters ERU:

Western spruce budworm—

Low nc nc 30.4 29.6 -0.8 29.4 35.4 5.9* 126.3 102.8 -23.5

Moderate - - 24.7 18.6 -6.0* 35.5 42.1 6.6* 79.5 60.6 -18.9*

High + + 45.0 51.8 6.8* 24.3 24.8 0.6 333.1 455.5 122.4*

Douglas-fir beetle—

Low - - 82.0 78.3 -3.7* 12.6 15.3 2.7* 1751.3 1041.0 -710.3*

Moderate nc nc 15.9 17.9 2.0 16.5 22.0 5.5* 112.3 114.0 1.7

High + + 2.1 3.9 1.7* 5.1 7.1 2.0* 17.5 31.6 14.0*

Mountain pine beetle (type 1)—

Low nc nc 48.6 48.4 -0.2 20.1 26.4 6.3* 451.2 358.1 -93.0

Moderate + + 16.8 22.3 5.6* 37.8 39.8 2.0 51.5 88.6 37.1*

High - nc 34.6 29.2 -5.4* 19.0 18.0 -1.0 238.3 216.4 -21.9

Fir engraver—

Low nc nc 54.1 55.8 1.7 17.4 21.9 4.4 648.0 1392.0 744.0

Moderate nc nc 26.6 28.1 1.5 32.0 35.6 3.6 98.9 126.1 27.1

High nc - 19.3 16.1 -3.2 10.8 18.1 7.4* 211.3 131.9 -79.4*

Spruce beetle—

Low + nc 52.4 57.1 4.7* 17.4 21.1 3.6 1325.1 958.3 -366.8

Moderate - - 39.2 35.3 -4.0* 21.9 23.1 1.3 276.5 207.9 -68.6*

High - nc 8.3 7.6 -0.7* 7.7 6.9 -0.8 63.3 60.2 -3.1

Douglas-fir dwarf mistletoe—

Low - nc 79.3 71.8 -7.4* 13.6 13.7 0.1 835.8 1283.0 447.2

Moderate nc nc 16.6 21.8 5.1 20.6 20.4 -0.2 107.6 586.4 478.8

High + + 4.1 6.4 2.3* 9.0 10.6 1.6 19.2 49.6 30.4*

Lodgepole pine dwarf mistletoe—

Low + nc 62.3 67.7 5.4* 15.1 15.6 0.5 1571.7 1585.0 13.3

Moderate + + 7.0 11.5 4.5* 20.6 19.6 -0.9 37.6 74.1 36.5*

High - - 30.8 20.9 -9.9* 15.9 15.4 -0.5 274.3 186.6 -87.8*

Armillaria root disease—

Low nc nc 32.1 30.3 -1.8 28.1 33.8 5.6 145.1 116.4 -28.7

Moderate - - 47.4 38.1 -9.3* 30.2 36.1 5.9* 270.6 170.3 -100.3*

High + + 20.4 31.5 11.1* 24.7 26.4 1.8 106.6 205.4 98.8*

Laminated root rot—

Low nc - 56.3 53.7 -2.6 19.6 24.6 5.0* 407.9 328.3 -79.6

Moderate nc nc 32.8 33.4 0.6 27.4 30.1 2.7 272.4 211.6 -60.8

High + + 10.9 12.8 2.0* 17.2 18.2 1.0 71.4 100.8 29.5*
350

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

S-group annosum root disease—

Low - - 39.7 33.1 -6.6* 26.1 35.5 9.4* 220.3 118.7 -101.6*

Moderate nc nc 38.3 36.2 -2.1 31.9 34.9 3.0 190.6 149.8 -40.8

High + + 22.0 30.6 8.6* 23.3 26.6 3.3 141.1 204.0 62.9*

Tomentosus root and butt rot—

Low - - 72.4 64.6 -7.7* 9.4 15.0 5.6* 1678.3 1311.6 -366.7

Moderate + + 14.3 20.3 6.0* 16.3 23.5 7.2* 90.9 119.7 28.8

High nc nc 13.3 15.1 1.7 8.7 9.9 1.3 194.4 137.8 -56.6

Schweinitzii root and butt rot—

Low nc nc 37.9 35.8 -2.1 25.6 31.0 5.4 193.8 183.7 -10.1

Moderate nc + 12.2 15.6 3.3 34.9 37.8 2.9 45.3 65.9 20.6*

High nc nc 49.9 48.6 -1.3 22.4 22.4 0.0 442.2 351.7 -90.5

White pine blister rust (type 2)—

Low nc - 52.5 52.3 -0.2 10.0 12.1 2.1* 1521.8 968.8 -553.0*

Moderate + nc 43.5 45.7 2.2* 17.5 16.8 -0.7 695.7 601.8 -93.9

High nc nc 4.0 2.0 -2.0 1.4 1.3 -0.1 59.4 16.0 -43.4

Southern Cascades ERU:

Western spruce budworm—

Low nc - 79.9 77.6 -2.4 7.3 20.4 13.2* 3892.6 3845.0 -47.6

Moderate nc - 10.0 10.1 0.2 5.6 15.1 9.6* 133.3 54.4 -78.9*

High + - 10.1 12.3 2.2* 4.1 6.0 1.9* 252.1 204.3 -47.8

Douglas-fir beetle—

Low nc nc 96.2 96.9 0.7 4.8 5.9 1.1 7208.7 6289.7 -919.0

Moderate nc nc 2.1 3.0 1.0 1.4 2.1 0.6 56.9 75.9 19.0

High - nc 1.8 0.1 -1.7* 0.3 0.1 -0.1 186.8 9.1 -177.8

Western pine beetle (type 1)—

Low nc nc 83.0 78.7 -4.3 4.6 8.4 3.8* 4860.6 3697.3 -1163.3

Moderate nc nc 11.8 16.2 4.5 4.8 6.8 2.1 235.0 355.9 120.9

High nc nc 5.2 5.1 -0.2 1.9 1.8 -0.1 134.8 189.7 54.8

Western pine beetle (type 2)—

Low nc - 51.6 42.4 -9.1 12.3 30.8 18.6* 1581.7 219.0 -1362.7*

Moderate nc nc 27.9 33.2 5.3 10.1 14.2 4.1* 346.4 453.3 106.8

High nc nc 20.5 24.4 3.8 3.6 5.8 2.1* 1125.9 1294.7 168.9

Mountain pine beetle (type 1)—

Low nc - 36.1 35.6 -0.5 17.9 43.3 25.4* 2281.2 680.8 -1600.4*

Moderate + - 34.9 39.5 4.6* 10.3 17.7 7.4* 469.1 428.6 -40.5

High - nc 29.0 24.9 -4.1 4.2 5.9 1.8 765.6 634.6 -131.0

Mountain pine beetle (type 2)—

Low nc - 51.6 42.4 -9.1 12.3 30.8 18.6* 1581.7 219.0 -1362.7*

Moderate nc nc 27.9 33.2 5.3 10.1 14.2 4.1* 346.4 453.3 106.8

High nc nc 20.5 24.4 3.8 3.6 5.8 2.1* 1125.9 1294.7 168.9
351

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Fir engraver—

Low nc - 86.1 85.0 -1.1 5.2 13.2 8.0* 6081.3 3561.2 -2520.0*

Moderate nc - 5.0 4.8 -0.1 3.0 7.9 4.9* 114.4 39.0 -75.4*

High nc nc 9.0 10.2 1.2 3.3 4.8 1.4* 166.3 207.9 41.7

Spruce beetle—

Low + nc 91.6 93.1 1.5* 3.6 7.5 3.9* 6605.5 7422.3 816.8

Moderate - - 8.4 6.8 -1.6* 3.6 6.1 2.6* 152.7 68.4 -84.4*

High nc nc 0.1 0.1 0.1 0.4 0.3 -0.1 1.7 9.9 8.1

Douglas-fir dwarf mistletoe—

Low - - 95.4 93.1 -2.4* 4.0 8.1 4.1 6743.6 4501.3 -2242.3*

Moderate + + 2.3 6.4 4.1* 2.6 4.5 1.9* 31.9 74.0 42.1*

High - - 2.3 0.5 -1.7* 0.5 0.4 -0.1 95.1 24.1 -71.0*

Western dwarf mistletoe—

Low nc - 74.6 70.9 -3.8 3.9 8.3 4.3* 4673.0 2356.8 -2316.2*

Moderate nc nc 12.4 11.3 -1.2 6.4 11.9 5.5* 525.4 106.3 -419.1

High nc nc 12.9 17.9 5.0 2.9 5.1 2.1* 545.1 442.3 -102.9

Lodgepole pine dwarf mistletoe—

Low nc + 76.9 74.4 -2.6 8.5 17.6 9.1* 2440.9 2892.8 451.9

Moderate nc - 12.9 13.7 0.8 7.4 14.8 7.4* 186.0 105.9 -80.1*

High nc nc 10.2 11.9 1.7 4.2 6.5 2.3* 164.8 115.6 -49.2

Armillaria root disease—

Low nc - 32.8 34.5 1.6 18.9 49.6 30.7* 1231.4 523.4 -708.0

Moderate nc nc 56.3 52.7 -3.6 4.7 11.2 6.5* 1769.7 1114.4 -655.2

High + nc 10.9 12.8 1.9* 3.5 6.1 2.6* 230.0 171.4 -58.6

Laminated root rot—

Low nc - 52.6 51.7 -0.9 13.6 31.7 18.1* 3220.0 2721.4 -498.6

Moderate - - 16.3 12.8 -3.4* 12.9 18.6 5.8* 109.0 63.1 -45.9*

High + nc 31.1 35.4 4.3* 4.6 5.2 0.6 754.9 945.3 190.4

S-group annosum root disease—

Low nc - 56.3 56.4 0.1 13.3 26.0 12.8* 2713.4 2028.1 -685.4

Moderate nc - 6.6 5.3 -1.3 6.5 9.3 2.8* 83.9 40.6 -43.3*

High nc nc 37.1 38.3 1.2 4.7 5.9 1.3 1151.5 884.2 -267.3

P-group annosum root disease—

Low nc - 75.2 69.4 -5.8 3.8 8.9 5.1* 4690.1 2318.5 -2371.6*

Moderate nc - 11.0 7.2 -3.8 6.1 13.8 7.6* 494.1 66.6 -427.5*

High + + 13.8 23.4 9.6* 3.6 5.8 2.2* 541.6 816.2 274.6

Tomentosus root and butt rot—

Low nc nc 99.1 99.1 0.0 4.1 2.7 -1.4* 5427.1 6002.6 575.5

Moderate nc nc 0.1 0.1 0.1 0.3 0.7 0.4 3.5 4.8 1.2

High nc nc 0.8 0.8 0.0 1.6 2.4 0.8 27.1 18.2 -8.9
352

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Schweinitzii root and butt rot—

Low - - 27.8 20.8 -7.0* 16.5 48.2 31.7* 1111.6 63.0 -1048.5*

Moderate nc nc 46.6 49.9 3.3 8.3 19.1 10.9* 836.3 530.3 -306.1

High nc nc 25.6 29.4 3.8 6.1 7.9 1.8* 775.3 574.2 -201.1

White pine blister rust (type 1)—

Low - - 61.4 59.0 -2.3* 6.1 9.3 3.2* 5072.1 4551.8 -520.3

Moderate + + 38.5 40.7 2.2* 5.1 7.9 2.8* 1626.8 2098.8 472.0

High nc nc 0.2 0.3 0.1 0.3 0.8 0.5* 3.8 3.8 0.0

Rust-red stringy rot—

Low nc - 59.2 57.0 -2.2 14.6 27.8 13.3* 4149.6 1796.8 -2352.8*

Moderate nc nc 39.7 41.4 1.7 4.6 5.9 1.4* 1486.4 915.3 -571.1

High nc nc 1.1 1.7 0.5 0.6 2.5 1.9* 34.5 41.1 6.7

Upper Clark Fork ERU:

Western spruce budworm—

Low nc - 20.4 21.5 1.1 19.3 25.2 5.9* 149.5 102.1 -47.4*

Moderate nc - 20.5 22.6 2.1 28.9 34.8 5.8* 86.0 72.9 -13.1

High nc nc 59.1 55.9 -3.2 11.4 11.2 -0.2 1318.4 982.5 -335.9

Douglas-fir beetle— 

Low nc + 61.6 62.6 1.0 14.3 21.7 7.4* 1472.4 1552.4 80.1

Moderate nc nc 30.4 32.6 2.2 13.5 14.9 1.5 446.1 275.1 -170.9

High - - 8.0 4.8 -3.2* 5.4 10.0 4.5* 114.6 44.4 -70.1*

Western pine beetle (type 1)—

Low + - 90.6 93.4 2.8* 5.3 6.5 1.2* 4022.3 3727.7 -294.5

Moderate nc - 6.5 6.2 -0.4 6.4 6.5 0.1 85.8 54.7 -31.1*

High - nc 2.9 0.5 -2.4* 1.1 1.2 0.1 20.7 8.7 -12.1

Western pine beetle (type 2)—

Low nc - 39.1 39.0 -0.1 22.8 32.6 9.8* 341.9 334.5 -7.4

Moderate nc nc 51.0 52.9 1.9 16.8 15.3 -1.5 889.2 835.0 -54.2

High - nc 9.9 8.1 -1.7* 6.0 5.3 -0.6 102.5 91.9 -10.6

Mountain pine beetle (type 1)—

Low nc - 32.2 33.1 1.0 20.6 26.2 5.6* 338.7 195.0 -143.7

Moderate nc - 31.7 29.3 -2.4 26.3 32.3 6.0* 175.0 100.1 -74.9*

High nc nc 36.1 37.6 1.5 14.9 13.3 -1.7 549.1 551.1 2.1

Mountain pine beetle (type 2)—

Low nc - 39.1 39.0 -0.1 22.8 32.6 9.8* 341.9 334.5 -7.4

Moderate nc nc 51.0 52.9 1.9 16.8 15.3 -1.5 889.2 835.0 -54.2

High - nc 9.9 8.1 -1.7* 6.0 5.3 -0.6 102.5 91.9 -10.6

Fir engraver—

Low nc - 62.7 63.4 0.7 13.6 17.2 3.6* 1341.0 818.3 -522.8*

Moderate nc - 29.5 26.9 -2.6 23.0 28.3 5.3* 192.5 105.5 -87.0*

High + + 7.8 9.7 1.9* 6.4 8.7 2.3* 88.0 111.0 23.0
353

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Spruce beetle—

Low nc - 64.0 65.1 1.1 13.1 16.6 3.5* 1313.2 1001.4 -311.8*

Moderate nc nc 29.2 29.3 0.2 20.8 21.9 1.1 200.9 160.1 -40.8

High nc nc 6.9 5.6 -1.3 4.3 5.9 1.6* 80.5 60.8 -19.7

Douglas-fir dwarf mistletoe—

Low nc + 54.5 56.6 2.1 17.4 22.0 4.6* 747.1 1077.5 330.4*

Moderate nc nc 29.4 30.2 0.9 17.1 18.3 1.2 211.4 179.3 -32.1

High - - 16.2 13.2 -3.0* 12.3 15.4 3.1* 154.0 75.1 -78.9*

Western dwarf mistletoe—

Low + + 87.4 89.4 2.0* 6.3 6.6 0.3 3389.7 4244.5 854.8*

Moderate nc nc 7.6 8.3 0.7 7.9 6.9 -1.0 76.4 85.3 8.9

High - - 5.0 2.3 -2.7* 3.2 4.2 1.1 50.2 20.4 -29.8*

Western larch dwarf mistletoe—

Low + nc 87.0 89.1 2.1* 7.7 7.7 0.1 3067.0 2913.6 -153.3

Moderate nc - 10.2 9.7 -0.6 4.9 8.0 3.1* 83.3 70.7 -12.6

High - - 2.8 1.3 -1.6* 3.3 3.7 0.3 18.8 8.4 -10.4*

Lodgepole pine dwarf mistletoe—

Low + + 45.2 50.4 5.2* 17.8 20.9 3.1* 530.6 628.8 98.2

Moderate - - 32.1 27.0 -5.1* 18.6 21.9 3.3* 500.8 146.6 -354.2*

High nc nc 22.6 22.5 -0.1 17.2 15.5 -1.7 199.5 190.8 -8.7

Armillaria root disease—

Low nc - 19.3 20.6 1.3 20.4 28.3 7.9* 138.0 96.6 -41.4*

Moderate nc - 46.5 47.6 1.1 21.3 26.7 5.3* 589.4 391.8 -197.7*

High nc nc 34.2 31.8 -2.4 19.8 18.0 -1.8 337.1 234.1 -103.0

Laminated root rot—

Low + - 40.9 44.3 3.4* 20.7 25.1 4.4* 558.9 541.8 -17.0

Moderate nc - 37.5 34.9 -2.6 20.9 25.8 4.9* 321.1 166.0 -155.1*

High nc nc 21.6 20.8 -0.8 18.5 18.3 -0.2 196.5 108.4 -88.1

S-group annosum root disease—

Low + nc 30.0 33.8 3.8* 25.8 31.0 5.3* 161.4 161.8 0.4

Moderate - - 37.8 31.6 -6.2* 24.8 31.4 6.6* 365.0 197.7 -167.3*

High nc nc 32.2 34.6 2.3 18.9 17.3 -1.6 338.9 365.3 26.4

P-group annosum root disease—

Low + nc 88.6 90.3 1.7* 6.2 6.2 0.0 3660.5 4077.6 417.1

Moderate nc nc 5.9 5.6 -0.3 8.3 7.3 -1.0 53.2 53.8 0.7

High - - 5.4 4.0 -1.4* 3.3 4.5 1.2* 51.8 39.4 -12.4

Tomentosus root and butt rot—

Low nc nc 84.3 84.0 -0.3 7.0 7.8 0.9 3198.7 2900.6 -298.1

Moderate nc - 5.8 5.7 -0.1 10.4 12.6 2.2* 38.4 31.3 -7.1*

High nc nc 9.9 10.3 0.4 9.9 12.8 2.9* 89.1 73.1 -16.0
354

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Schweinitzii root and butt rot—

Low nc - 18.0 18.6 0.6 16.9 22.9 6.0* 142.2 114.0 -28.2*

Moderate nc nc 21.4 22.4 1.1 26.3 31.2 4.9* 87.3 83.5 -3.7 

High nc nc 60.6 59.0 -1.6 10.8 9.8 -1.0 1291.3 1249.4 -41.9

White pine blister rust (type 1)—

Low nc - 80.0 79.8 -0.2 6.1 5.6 -0.5 3460.9 2650.9 -810.0*

Moderate + nc 17.5 18.2 0.8* 14.1 15.1 1.1 146.2 142.6 -3.5

High nc nc 2.5 1.4 -1.1 0.1 1.0 0.9 72.4 5.9 -66.5

White pine blister rust (type 2)—

Low nc nc 63.0 62.6 -0.4 10.3 12.1 1.8 1147.9 1089.9 -58.0

Moderate nc - 34.1 34.6 0.5 15.3 18.0 2.8* 348.6 240.4 -108.2*

High nc nc 2.9 2.4 -0.6 3.0 2.6 -0.5 26.2 20.9 -5.4

Rust-red stringy rot—

Low - nc 94.5 91.0 -3.5* 4.3 5.3 1.0 4918.9 4863.7 -55.2

Moderate + + 4.3 6.7 2.4* 7.7 12.5 4.9* 41.3 51.5 10.2*

High nc nc 1.2 2.3 1.1 0.8 2.3 1.5* 5.8 7.0 1.2

Upper Klamath ERU: 

Western spruce budworm—

Low nc nc 78.7 78.2 -0.5 6.0 10.1 4.1* 3265.3 4022.6 757.3

Moderate nc nc 6.7 5.9 -0.8 8.1 11.9 3.7* 66.5 68.5 2.0

High nc nc 14.6 15.9 1.3 3.7 3.7 0.0 459.4 599.7 140.3

Douglas-fir beetle

Low nc nc 94.2 93.2 -1.0 5.6 8.4 2.8 4785.6 4839.6 54.0

Moderate nc nc 5.7 6.8 1.0 1.6 2.3 0.6 185.0 135.5 -49.5

High nc nc 0.0 0.0 0.0 0.3 0.1 -0.2 0.8 1.2 0.4

Western pine beetle (type 1)—

Low + + 72.1 75.9 3.9* 15.5 14.5 -1.0 3507.6 4916.7 1409.1*

Moderate nc - 22.3 19.6 -2.7 9.6 6.5 -3.1* 426.4 347.5 -78.8

High nc - 5.7 4.5 -1.2 3.5 4.9 1.4* 67.6 51.1 -16.5

Western pine beetle (type 2)—

Low nc nc 61.7 59.9 -1.8 20.9 20.8 -0.1 1745.6 1380.0 -365.6

Moderate nc + 19.0 18.8 -0.2 20.6 10.2 -10.4* 172.1 259.8 87.8*

High nc nc 19.3 21.3 2.0 6.3 5.8 -0.5 322.7 273.1 -49.6

Mountain pine beetle (type 1)—

Low nc nc 76.0 75.1 -0.8 10.1 11.9 1.7 5837.0 4452.9 -1384.1

Moderate nc nc 19.3 20.6 1.3 8.3 8.1 -0.1 242.7 305.7 62.9

High nc nc 4.7 4.3 -0.4 2.5 2.9 0.4 71.5 54.1 -17.4

Mountain pine beetle (type 2)—

Low nc nc 61.7 59.9 -1.8 20.9 20.8 -0.1 1745.6 1380.0 -365.6

Moderate nc + 19.0 18.8 -0.2 20.6 10.2 -10.4* 172.1 259.8 87.8*

High nc nc 19.3 21.3 2.0 6.3 5.8 -0.5 322.7 273.1 -49.6
355

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Fir engraver—

Low nc + 80.8 79.8 -1.1 6.1 9.9 3.9* 4330.2 4419.0 88.8

Moderate nc nc 2.1 2.2 0.1 5.2 5.9 0.6 25.9 48.7 22.8

High + + 17.1 18.0 1.0* 3.7 2.0 -1.7* 586.7 700.1 113.5

Douglas-fir dwarf mistletoe—

Low nc nc 94.1 93.3 -0.8 5.3 7.1 1.8* 4520.0 4504.8 -15.2

Moderate nc nc 5.1 6.5 1.4 2.8 2.4 -0.4* 149.2 102.4 -46.8

High nc nc 0.8 0.2 -0.6 0.4 0.5 0.1 65.2 8.2 -57.0

Western dwarf mistletoe—

Low + + 69.5 73.4 3.9* 17.4 14.4 -2.9* 2186.7 3866.1 1679.4*

Moderate nc - 12.7 11.1 -1.6 14.5 11.6 -2.9* 228.6 124.5 -104.1

High nc nc 17.8 15.5 -2.3 6.9 5.3 -1.6 196.7 215.1 18.4

Lodgepole pine dwarf mistletoe—

Low nc nc 95.2 96.4 1.2 5.9 5.2 -0.7 3982.3 4218.8 236.5

Moderate nc nc 4.4 3.3 -1.1 3.3 3.2 -0.1 59.3 29.3 -30.0*

High nc nc 0.4 0.3 -0.1 0.7 0.9 0.1 7.7 6.0 -1.6

Armillaria root disease—

Low + + 60.6 67.6 7.0* 15.9 13.9 -2.0 4661.8 5950.4 1288.6*

Moderate - - 26.2 18.9 -7.4* 11.1 14.9 3.7* 251.1 130.7 -120.4*

High nc nc 13.2 13.6 0.4 4.9 3.7 -1.2 474.5 355.1 -119.4

Laminated root rot—

Low nc nc 73.9 73.7 -0.2 6.7 10.3 3.6* 3041.5 4142.1 1100.6

Moderate nc nc 7.6 8.6 1.0 5.4 9.4 4.1* 83.1 95.0 11.9

High nc nc 18.5 17.7 -0.7 4.9 2.9 -2.1* 668.8 808.5 139.7

S-group annosum root disease—

Low nc nc 75.4 75.6 0.2 6.0 10.1 4.1* 4058.0 4518.7 460.7

Moderate nc nc 1.9 1.1 -0.7 5.2 2.9 -2.3* 20.9 30.5 9.6

High nc nc 22.8 23.3 0.5 4.1 2.4 -1.8* 1008.2 1243.0 234.9

P-group annosum root disease—

Low + + 69.6 73.3 3.7* 17.4 14.6 -2.7* 2526.0 3855.7 1329.7*

Moderate - - 11.4 7.0 -4.5* 14.7 11.6 -3.1* 221.7 91.5 -130.2

High nc nc 19.0 19.8 0.8 5.8 5.4 -0.4 263.3 214.9 -48.4

Schweinitzii root and butt rot—

Low nc + 52.4 54.1 1.7 17.4 19.2 1.9 1551.8 2746.9 1195.2*

Moderate + nc 21.2 28.0 6.9* 13.1 13.9 0.8 256.5 253.2 -3.3

High - nc 26.4 17.9 -8.6* 6.4 6.6 0.3 615.8 234.6 -381.2

White pine blister rust (type 1)—

Low nc nc 93.6 93.6 0.0 2.8 2.6 -0.2 9352.5 9385.8 33.3

Moderate nc nc 6.4 6.4 0.0 1.3 1.1 -0.2 297.2 343.8 46.6

High nc nc 0.0 0.0 0.0 0.1 0.0 -0.1 0.2 0.0 -0.2
356

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Rust-red stringy rot—

Low nc - 76.5 76.4 -0.1 7.8 11.2 3.4* 3923.1 3783.2 -139.8

Moderate nc + 18.7 19.5 0.8 6.0 4.0 -2.0* 301.6 334.6 33.0

High nc nc 4.8 4.1 -0.7 1.5 3.9 2.4* 66.6 26.8 -39.9*

Upper Snake ERU: 

Western spruce budworm—

Low - nc 97.8 97.6 -0.2* 3.0 3.3 0.3 8642.0 8582.3 -59.7

Moderate - - 0.5 0.3 -0.3* 3.1 2.3 -0.8 8.3 3.1 -5.2* 

High + + 1.6 2.1 0.5* 1.1 0.5 -0.6* 32.4 95.4 62.9*

Douglas-fir beetle—

Low - nc 98.3 97.8 -0.5* 3.9 4.0 0.1 8180.8 7893.6 -287.1

Moderate nc nc 1.2 1.2 0.0 1.8 1.5 -0.3 9.5 48.9 39.4

High nc nc 0.5 1.0 0.5 1.9 1.4 -0.5 3.6 8.6 5.0

Mountain pine beetle (type 1)—

Low nc nc 97.9 97.7 -0.2 3.8 3.3 -0.5 8536.7 10757.0 2220.3

Moderate nc nc 1.5 2.0 0.4 3.1 3.3 0.2 12.9 20.9 8.0

High nc nc 0.6 0.3 -0.2 1.2 0.5 -0.7 9.2 22.5 13.4

Douglas-fir dwarf mistletoe—

Low nc nc 98.2 97.8 -0.5 3.7 3.8 0.1 8282.1 7903.6 -378.5

Moderate nc + 1.2 0.7 -0.5 2.7 1.9 -0.9* 9.7 23.3 13.6

High nc + 0.6 1.5 0.9 1.8 1.1 -0.7* 5.3 18.8 13.5

Lodgepole pine dwarf mistletoe—

Low nc nc 99.6 99.6 0.1 3.8 3.8 0.0 10037.3 9835.6 -201.7

Moderate nc nc 0.1 0.0 -0.1 0.8 0.1 -0.7 1.7 4.3 2.6

High nc nc 0.3 0.3 0.0 0.6 0.3 -0.3 6.7 22.3 15.7

Armillaria root disease—

Low nc nc 98.2 97.7 -0.5 3.2 3.7 0.5 10132.5 9762.1 -370.4

Moderate nc + 0.9 0.7 -0.2 3.0 2.1 -0.9* 6.7 20.0 13.2

High nc + 1.0 1.6 0.6 2.1 1.1 -1.1* 9.2 20.9 11.7

Laminated root rot—

Low nc nc 98.2 97.7 -0.5 3.5 3.9 0.4 8290.6 7903.1 -387.6

Moderate nc + 0.9 0.7 -0.2 3.2 2.1 -1.1* 5.9 42.9 37.0

High nc nc 1.0 1.6 0.6 2.1 1.1 -1.0 9.2 21.0 11.8

S-group annosum root disease—

Low nc nc 98.2 97.7 -0.5 3.5 3.9 0.4 8290.6 7903.1 -387.6

Moderate nc nc 0.8 0.6 -0.2 2.8 2.1 -0.7 5.4 22.6 17.2

High nc + 1.0 1.7 0.6 2.3 0.9 -1.4* 10.2 31.7 21.4
357

Table 33—(continued)

Trenda Area Patch density Mean patch size 

Ecological reporting unit Area Con.b Hc C MDd H C MDd H C MDd

Percent No./10 000 ha Hectares

Schweinitzii root and butt rot—

Low nc nc 98.2 97.7 -0.5 3.2 3.7 0.5 10132.5 9762.1 -370.4

Moderate nc nc 0.3 0.2 -0.1 2.7 1.5 -1.2* 1.8 2.1 0.2

High + + 1.5 2.1 0.6* 1.4 0.7 -0.7* 20.4 57.8 37.4*

a Choices for either field are (+) increase; (-) decrease; (nc) no ecologically significant change.

b Con. = connectivity change among patches in a patch type

c H = historical; C = current; MD = mean difference of pairwise comparisons of historical and current subwatersheds.

d * = statistically significant difference at P≤0.2; all values rounded to 1 decimal place.