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-454

November 1999

Modeling Change in Potential

Landscape Vulnerability to Forest

Insect and Pathogen Disturbances:

Methods for Forested Subwatersheds

Sampled in the Midscale Interior

Columbia River Basin Assessment

Paul F. Hessburg, Bradley G. Smith, Craig A. Miller,

Scott D. Kreiter, and R. Brion Salter
Authors

PAUL F. HESSBURG is a research plant pathologist and area forest pathologist, Pacific Northwest Research

Station and Pacific Northwest Region, 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; and CRAIG A. MILLER is a geographer and SCOTT

D. KREITER and R. BRION SALTER are geographical information system analysts, Pacific Northwest

Research Station, Forestry Sciences Laboratory, 1133 N. Western Avenue, Wenatchee, WA 98801.
Modeling Change in Potential Landscape Vulnerability

to Forest Insect and Pathogen Disturbances: Methods

for Forested Subwatersheds Sampled in the Midscale

Interior Columbia River Basin Assessment

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

and R. Brion Salter

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-454

November 1999
Abstract

Hessburg, Paul F.; Smith, Bradley G.; Miller, Craig A.; Kreiter, Scott D.; Salter, R. Brion. 1999. Modeling change

in potential landscape vulnerability to forest insect and pathogen disturbances: methods for forested subwatersheds

sampled in the midscale interior Columbia River basin assessment. Gen. Tech. Rep. PNW-GTR-454. Portland, OR:

U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 56 p. (Quigley, Thomas M.,

ed.; Interior Columbia Basin Ecosystem Management Project: scientific assessment).

In the interior Columbia River basin midscale ecological assessment, including portions of the Klamath and Great

Basins, we mapped and characterized historical and current vegetation composition and structure of 337 randomly

sampled subwatersheds (9500 ha average size) in 43 subbasins (404 000 ha average size). We compared landscape

patterns, vegetation structure and composition, and landscape vulnerability to 21 major forest insect and pathogen

disturbances of historical and current forest vegetation coverages. Forest vegetation composition, structure, and

patterns were derived from attributes interpreted and mapped from 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 to a minimum size of 4 ha. Results of change analyses were reported for province-scale

ecological reporting units (ERUs). In this paper, we report on methods used to characterize historical and current

patch and subwatershed vulnerability to each of 21 insect and pathogen disturbance agents.

We assessed landscape vulnerability to defoliator, bark beetle, dwarf mistletoe, root disease, blister rust, and stem

decay disturbances. We used patch composition, structure, logging disturbance, and physical environment attributes

to compare vegetation vulnerability of historical subwatersheds with that of their current condition. Patch vulnerability factors included items such as site quality, host abundance, canopy layers, host age or host size, patch vigor,

patch (stand) density, connectivity of host patches, topographic setting, and presence of visible logging disturbance.

Methods reported here can be used in landscape or watershed analysis to evaluate or monitor change in the magnitude

and spatial pattern of vegetation vulnerability to insect and pathogen disturbances, and in planning to compare potential disturbance futures associated with alternative vegetation management scenarios.

Keywords: Ecological assessment, interior Columbia River basin, ecosystem health, insect disturbance, pathogen

disturbance, vegetation vulnerability, ecosystem processes, succession processes.
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 landscape assessment was conducted to validate the results of the

broad-scale landscape assessment at a scale appropriate to observing the vegetation pattern-disturbance process

interactions. This paper is one in a series of four papers developed to document the results of that midscale

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 ecologyWendel Hann, Paul Hessburg, and Mark Jensen; aquaticJim Sedell, Kris Lee,

Danny Lee, Jack Williams, and Lynn Decker; economicRichard Haynes, Amy Horne, and Nick Reyna; social

scienceJim Burchfield, Steve McCool, and Jon Bumstead; terrestrialBruce Marcot, Kurt Nelson, John Lehmkuhl,

Richard Holthausen, and Randy Hickenbottom; and broad-scale spatial analysisBecky Gravenmier, John Steffenson,

and Andy Wilson.

Thomas M. Quigley, Editor

Forest Service

United States

Department of

Agriculture

Interior Columbia

Basin Ecosystem

Management Project

United States

Department of

the Interior

Bureau of Land

Management
Contents

1 Introduction

11 Insects Modeled

11 Defoliators

15 Bark Beetles

27 Pathogens Modeled

27 Dwarf Mistletoes

27 Root Diseases

31 Butt Rots

39 Rusts

39 Stem Decays

43 Acknowledgments

43 English Conversions

44 Literature Cited

47 Appendix 1

50 Appendix 2

53 Appendix 3
1

Introduction

In this paper, we describe methods used in the midscale (1:24,000) ecological assessment of the interior

Columbia River basin (the basin) to assess recent change

in vulnerability of forest vegetation to disturbances

caused by the major forest pathogens and insects of

the basin (see Hessburg and others 1999). Change in

potential vulnerability to forest insect and pathogen

disturbances was characterized for continuously mapped

recent historical (1932 to 1966) and current (1981 to

1993) vegetation coverages of 337 subwatersheds

sampled in 43 subbasins (table 1, fig. 1). Subwatershed

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. Methods

reported here are a substantial revision of those reported

in Lehmkuhl and others (1994). Figure 1 and table 2

display sampled subbasins by geographic area, province

from Bailey (1995) and ecoregion from Omernik (1987).

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 replacement 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 budworm1

 (table 3) 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, western pine, mountain

pine, fir-engraver, and spruce beetles. 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, 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,

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, and S- and P-group annosum root diseases.

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, 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.

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 items

such as (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.

Text continues on page 9.

1 Scientific and common names and abbreviations for all species

mentioned in the text are provided in table 3.
2

Table 1—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

Subbasin

Subbasin percentage percentage

Span, Span,

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 Henrys 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 Sanpoil 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

Source: Hessburg and others 1999.
3

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

midscale ecological assessment of the interior Columbia River basina b

4th code

Subbasin HUC no. Samples State Bailey province Omernik ecoregion

(1)c Pend Oreille 17010216 8 WA M333-Northern Northern Rockies

Rocky Mountain

(2) Kettle 17020002 5 WA M333-Northern Northern Rockies

Rocky Mountain

(3) Sanpoil 17020004 6 WA M333-Northern Northern Rockies

Rocky 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 Eastern 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

Figure 1Sampled subbasins of the midscale assessment of the interior Columbia River basin (see 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. Numbers in subbasins correspond with

subbasins listed in table 2.
4

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

midscale ecological assessment of the interior Columbia River basina b (continued)

4th code

Subbasin HUC no. Samples State Bailey province Omernik ecoregion

(10) Lower Grande Ronde 17060106 9 OR M332-Middle Blue Mountains

Rocky Mountain

(11) Upper Grande Ronde 17060104 9 OR M332-Middle Blue Mountains

Rocky Mountain

(12) Wallowa 17060105 7 OR M332-Middle Blue Mountains

Rocky Mountain

(13) Burnt 17050202 6 OR M332-Middle Blue Mountains and

Rocky Mountain 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 Blue Mountains

342-Intermountain

Semidesert

(16) Lower Crooked 17070305 6 OR M332-Middle Rocky Blue Mountains and

Mountain and Snake River Basin

M242-Cascade and High Desert and

Eastern Cascades

Slopes and Foothills

(17) Upper Deschutes 17070301 10 OR M242-Cascade Eastern Cascades

Slopes and Foothills

(18) Little Deschutes 17070302 6 OR M242-Cascade Eastern Cascades

Slopes and Foothills

(19) Silvies 17120002 4 OR M332-Middle Rocky Blue Mountains and

Mountain Snake River Basin and

High Desert

(20) Donner und Blitzen 17120003 4 OR 342-Intermountain Snake River Basin and

Semidesert High Desert

(21) Crooked Rattlesnake 17050109 7 OR 342-Intermountain Snake River Basin and

Semidesert High Desert

(22) Lost 18010204 5 OR M261-Sierran Eastern Cascades

Slopes and Foothills

and Snake River

Basin and High Desert

(22) Lost 18010204 4 CA M261-Sierran Eastern Cascades

Slopes and Foothills

and Snake River

Basin and High Desert

(23) Upper Klamath Lake 18010203 4 OR M261-Sierran and Eastern Cascades

M242-Cascade Slopes and Foothills

(24) Big Wood 17040219 6 ID 342-Intermountain Northern Rockies and

Semidesert and Snake River Basin and

M332-Middle High Desert

Rocky Mountain
5

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

midscale ecological assessment of the interior Columbia River basina b (continued)

4th code

Subbasin HUC no. Samples State Bailey province Omernik ecoregion

(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 Montana Valley and

M333-Northern Foothill Prairies

Rocky Mountain

(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 Northern Rockies

Rocky Mountain and

M332-Middle Rocky

Mountain

(32) Lower Flathead 17010212 14 MT M333-Northern Northern Rockies and

Rocky Mountain Montana Valley and

Foothill Prairies

(33) Lower Henrys 17040203 3 ID M331-Southern Middle Rockies and

Rocky Mountain and Snake River Basin and

342-Intermountain High Desert

Semidesert

(33) Lower Henrys 17040203 1 WY M331-Southern Middle Rockies and

Rocky Mountain Snake River Basin and

High Desert

(34) Medicine Lodge 17040215 5 ID 342-Intermountain Northern Rockies and

Semidesert and Snake River Basin and

M332-Middle High Desert

Rocky Mountain

(35) Palisades 17040104 5 ID M331-Southern Middle Rockies

Rocky Mountain

(35) Palisades 17040104 1 WY M331-Southern Middle Rockies

Rocky Mountain

(36) Snake Headwaters 17040101 8 WY M331-Southern Middle Rockies

Rocky Mountain

(37) South Fork Clearwater 17060305 6 ID M332-Middle Northern Rockies and

Rocky Mountain Columbia Basin
6

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

midscale ecological assessment of the interior Columbia River basina b (continued)

4th code

Subbasin HUC no. Samples State Bailey province Omernik ecoregion

(38) South Fork Salmon 17060208 7 ID M332-Middle Northern Rockies

Rocky Mountain

(39) Swan 17010211 4 MT M333-Northern Northern Rockies

Rocky Mountain

(40) Upper Owyhee 17050104 12 ID 342-Intermountain Snake River Basin and

Semidesert High Desert and no.

Great Basin and Range

(41) Upper Coeur

d Alene 17010301 5 ID M333-Northern Northern Rockies

Rocky Mountain

(42) Upper Middle

Fork Salmon 17060205 9 ID M332-Middle Northern Rockies

RockyMountain

(43) Yaak 17010103 4 MT M333-Northern Northern Rockies

 Rocky Mountain

a

 A total of 337 subwatersheds were sampled in 43 subbasins.

b

 See also figure 1.

c Numbers in parentheses identify subbasins shown in figure 1.

Table 3—Common and scientific names, and abbreviations of species discussed in the text

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 Nuttex Engelm.

P-group annosum root disease HEANp Heterobasidion annosum (Fr.) Bref

Rust-red stringy rot

(Indian paint fungus) RRSR Echinodontium tinctorium (Ell. & Ev.) Ell. & Ev.

Schweinitzii root and butt rot SRBR Phaeolus schweinitzii (Fr.) Pat.

S-group annosum root disease HEANs Heterobasidion annosum

H. annosum (Fr.) Bref

Tomentosus root and butt rot TRBR Inonotus tomentosus (Fr.) Gilbertson

Western dwarf mistletoe PPDM Arceuthobium campylopodum Engelm.

Western larch dwarf mistletoe WLDM A. laricis (piper) St. John

White pine blister rust WPBR Cronartium ribicola Fisher ex. Rabh.

Insects:

Douglas-fir beetle DFB Dendroctonus pseudotsugae Hopkins

Douglas-fir tussock moth DFTM Orgyia pseudotsugata McDunnough

Fir engraver beetle FE Scolytus ventralis Leconte

Mountain pine beetle MPB Dendroctonus ponderosae Hopkins

Spruce beetle SB D. rufipennis Kirby

Western pine beetle WPB D. brevicomis Leconte

Western spruce budworm WSB Choristoneura occidentalis Freeman
7

Table 3—Common and scientific names, and abbreviations of species discussed in the text

(continued)

Common name Abbreviation Scientific name

Trees:

Bigleaf maple Acer macrophyllum Pursh

Bigtooth maple A. grandidentatum Nutt.

Black cottonwood Populus trichocarpa Torr. & Gary

Blue spruce PIPU Picea pungens Engelm.

Bog birch Betula glandulosa Sary.

Douglas-fir PSME Pseudotsuga menziesii (Mirb.) Franco

Douglas maple Acer glabrum var. douglasii Pursh

Engelmann spruce PIEN Picea engelmannii Parry ex Engelm.

Grand fir ABGR Abies grandis (Dougl. ex D. Don) Lindl.

Hemlocks Tsuga spp. Carr.

Incense-cedar Calocedrus decurrens (Torr.) Florin

Limber pine PIFL Pinus flexilis James

Lodgepole pine PICO P. contorta var. latifolia Dougl. ex Loud.

Mountain hemlock TSME Tsuga mertensiana (Bong.) Carr.

Narrow-leaved cottonwood P. angustifolia James

Noble fir ABPR Abies procera Rehd.

Pacific silver fir ABAM A. amabilis Dougl. ex Forbes

Paper birch Betvia papyrifera Marsh.

Pinyon pine Pinus monophylla Dougl. ex D. Don

Ponderosa pine PIPO P. ponderosa Dougl. ex Laws.

Quaking aspen Aspen Populus tremuloides Michx.

Rocky Mountain juniper Junipers scopulorum Sarg.

Rocky Mountain maple Acer glabrum var. glabrum Torr.

Russian-olive 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. Mill

Utah juniper Juniperus osteosperma (Torr.) Little

Vine maple Acer circinatum Pursh

Water birch Betvia occidentalis Hook.

Western hemlock TSHE Tsuga heterophylla (Raf.) Sarg.

Western juniper Juniperus occidentalis Hook.

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 (Cord. of Glend.)

Lindl. ex Hildebr:

White spruce PIGL Picea glauca (Moench) Voss

Shrubs:

Alder Alder Alnus spp. Hill

Basin big sagebrush Artemisia tridentata var. tridentata Nutt.

Bitterbrush Purshia tridentata (Pursh) DC.

Bittercherry Prunus emarginata (Dougl.) Walp.

Bog birch Betula glandulosa Michx.
8

Table 3—Common and scientific names, and abbreviations of species discussed in the text

(continued)

Common name Abbreviation Scientific name

Shrubs: (continued)

Common chokecherry Chokecherry Prunus virginiana L.

Currant Ribes spp. L.

Curlleaf mahogany Cercocarpus ledifolius Nutt.

Dogwood Cornus spp. L.

Greasewood Sarcobatus vermiculatus (Hook.) Torr.

Low sagebrush Artemisia arbuscula Nutt.

Mountain big sagebrush A. tridentata var. vaseyana Nutt.

Mountain heather Heather Phyllodoce spp. Salisb.

Mountain mahogany Cercocarpus montanus Raf.

Rabbitbrush Chrysothamnus spp. Nutt.

Rocky Mountain maple Mountain maple Acer glabrum var. glabrum Torr.

Rose Rosa spp. L.

Russet buffaloberry Buffaloberry Sheperdia canadensis (L.) Nutt.

Scoulers willow Salix scouleriana Barratt

Serviceberry Amelanchier spp. Medic.

Silver sagebrush Artemisia cana Pursh

Snowberry Snowberry Symphoricarpus spp. Duhamel

Spiny hopsage Grayia spinosa (Hook.) Collotz

Spiny saltbush, shadscale Atriplex confertifolia (Torr. & Frem.) Wats.

Willow Willow Salix spp. L.

Winterfat Eurotia lanata (Pursh) Mog.

Wyoming big sagebrush Artemisia tridentata wyomingensis Nutt.

Grasses and forbs:

Alkaligrass Pucinellia spp. Parl.

Bluebunch wheatgrass Agropyron spicatum (Pursh) Scribn. & Smith

Bottlebrush squirreltail Sitanion hystrix (Nutt.) Smith, L.

Cheatgrass Bromus tectorum L.

Crested wheatgrass Agropyron cristatum (L.) Gaertn.

Idaho fescue Festuca idahoensis Elmer.

Leafy spurge Euphorbia esula L.

Medusahead Taeniatherum caput-medusae L.

Rushes Rushes Juncus spp. L.

Sedges Sedges Carex spp. L.

Spotted knapweed Centaurea maculosa Lam.

Wildrye Wildrye Elymus spp. L.

Yellowstar thistle Centaurea solstitialis L.
9

Site quality was modeled by using plant series-level

potential vegetation types as described in Hessburg and

others (1999), and Smith and others (in press). Site

quality was used as a vulnerability factor because hosts

on poorer sites are often 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 by using the photo-interpreted 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 by using the photo-interpreted attributes:

canopy layers, overstory species, and understory species.

Host size was used to indicate both sizes of hosts, and in

some cases, to approximate host age, because host age

could not be directly estimated by 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 vulnerable

to change as a consequence of disturbance when hosts

are large than when hosts are small. Host size was

estimated by using the photo-interpreted 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 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).

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 patchthis 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 %LANDthe percentage of area within a patch

type; MPSthe mean size in hectares of patches within

a patch type; and PDthe estimated patch density,

or number of patches per 10 000-ha area (see also

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 ecological

reporting unit (ERU). As described in Hessburg and

others (1999), change from historical to current

conditions was estimated as the difference between

historical and current conditions, not as the percentage

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 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 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 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.
10

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 to 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 significance of differences

among 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 were most often highly skewed and only

in rare instances were normally distributed. 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 unique

contexts or environments, or rare and often extreme

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 changes that were unique or

abnormal.

We acknowledge shortcomings of modeling vegetation

vulnerability to different pathogen and insect disturbances as intermediate ecological conditions or

indicators. Intermediate indicators such as patch

or subwatershed vulnerability to an insect, require

additional interpretation of modeled landscape

outcomes. Interpreters rely on their experience,

applicable scientific literature, and judgment.

Interpretations should be calibrated, validated, and

refined, and users of the interpretations must rely

on the experience, knowledge, and judgment of those

providing them. By comparison, estimating landscape

vulnerability by using endpoint conditions or indicators,

however crudely quantified, are more readily calibrated

and validated.

We might have projected landscape vulnerability and

potential ecosystem outcomes with endpoint indicators

via stand or landscape growth and yield projection

systems, inventory plot data, and insect and pathogen

disturbance submodels as are available with the

PROGNOSIS (FVS-forest vegetation simulator)

modeling system (Stage 1973). Time and monetary

constraints of the Interior Columbia Basin Ecosystem

Management Project (ICBEMP) project, and questionable or uneven quality of existing inventory data made

this route infeasible. As an alternative to either of these

courses of action, we considered the option of not

characterizing landscape vulnerability to pathogen and

insect disturbances. Knowing the policy and resource

planning analyses that lay ahead and the decisions that

would be made subsequent to the landscape assessment analyses, we thought no action an unacceptable

course, and opted to assess changes in vulnerability and

the spatial configuration of vulnerability, in the manner

described. Although a formidable task, it is preferable

to project changes in landscape vulnerability to disturbance with inventoried distributions of pathogens and

insects (where practicable), patch-scale tree attribute

data, measured density, structure, and composition, and

modeled disturbance effects to ecosystems. Important

endpoint indicators to model in future efforts would

include relations among changing landscape structural

attributes, site potentials, insect and pathogen disturbances, coarse wood accumulations, snag abundances,

stand densities, disease center areas, shrub structures

and densities, floral and faunal habitat abundances, and

others.
11

In addition to modeling changes in the measure and

spatial pattern of landscape vulnerability to insect and

pathogen disturbances, we describe for the first time,

living and dead vegetation structures commonly

associated with the insect and pathogen disturbances

modeled (appendices 2 and 3). These are provided for

persons interested in interpreting potential abundance

and spatial distribution of microhabitat structures of

importance to wildlife. Most living and dead vegetation

structure at the patch scale occurs as a direct result of

disturbance. Where effective fire prevention and

suppression strategies have been in place for a halfcentury or more, microhabitat structure most often will

be the result of insect and pathogen disturbances, and

unavoidable fires. The inference is that microhabitat

structures essential to wildlife will occur with high

likelihood where vegetation is most vulnerable to

insect, pathogen, and fire disturbances. Microhabitat

structure shown in appendices 2 and 3 can be related

to midscale historical or current subwatershed and

subbasin vegetation conditions to estimate the potential

area and spatial patterning of such structures for each

period in time. Change analysis comparing conditions

of the two periods would provide valuable insight

into likely differences in the potential availability of

microhabitat structures.

Insects Modeled

Defoliators

Principal lepidopteran defoliators of basin conifer

forests are the western spruce budworm (WSB) and

the Douglas-fir tussock moth (DFTM). Basin forests

are comprised of areas of low (0-11 years of visible

defoliation per 100 years), moderate (7-48 years of

visible defoliation per 100 years), and high (60 or

more years of visible defoliation per 100 years)

budworm defoliation frequency areas (Kemp 1985a,

1985b). Areas of high defoliation frequency are

characterized by low annual precipitation, droughty

growing season conditions, cold winters, and cool

spring and fall temperature regimes. Low defoliation

frequency areas are characterized by higher annual

precipitation, mild winter temperatures, and warmer

spring and fall temperature regimes. Figure 2 shows

defoliation frequency areas in Oregon, Washington,

Idaho, and western Montana according to Kemp

(1985b).

Figure 2Classes of budworm defoliation frequency (1947-78) developed for forested areas of Idaho, Montana, Oregon,

and Washington. High defoliation frequency = 1 ( > 60 years of visible defoliation in 100 years); medium defoliation frequency =

2 (7-48 years of visible defoliation in 100 years); low defoliation frequency = 3 (0-11 years of visible defoliation in 100 years); no

defoliation frequency = 0 (nonhost type) (source: Kemp 1985b).
12

There appears to have been no obvious change in

outbreak frequency in the basin since the region was

first settled, but vegetation structural attributes (both

composition and configuration) that strongly influence

outbreak extent, duration, and severity, have changed

(Gast and other 1991, Hessburg and others 1994,

Lehmkuhl and others 1994, OLaughlin and others

1993). Western spruce budworm outbreak extent,

duration, and severity depend on (1) the amount,

structure, quality, and spatial distribution of available

host patches; (2) conducive environmental conditions

for budworm life stages; and (3) dispersal opportunities

to suitable host patches. Large areas that are successionally advanced and have multiple canopy layers

within the Douglas-fir, grand fir, white fir, and subalpine fir zones (Franklin and Dyrness 1973), are

vulnerable to defoliation by budworm. Warm, dry

sites are more vulnerable to defoliator outbreaks than

are cool mesic sites. During an outbreak, warm mesic

sites may incur the greatest reduction in growth of

host species (see Brookes and others [1985, 1987] and

Sanders and others [1985] for further WSB references).

Defoliation extent increases with area and connectivity

of budworm host patches. Duration varies with forage

quality, vertical stratification of hosts, environmental

conditions for each life stage, fecundity, survivorship,

sex ratio, and dispersal efficiency. Severity varies with

the duration and amount of defoliation, and host vigor

before, during, and after defoliation episodes.

Douglas-fir tussock moth outbreak extent and severity

depend on many of the same variables as the WSB,

though there are several important differences. The

WSB feeds primarily on new foliage and buds, and

feeds earlier in spring; the DFTM feeds on both new

and old foliage and readily defoliates entire trees in a

single growing season. Vertical stratification of hosts

can enhance both WSB and DFTM survival and

defoliation severity. The DFTM is somewhat more

sensitive to droughty sites than is the WSB; DFTM

outbreaks typically begin in some of the driest Douglasfir plant communities where the exclusion of fire has

allowed an increased presence of Douglas-fir. Douglasfir tussock moth outbreak duration is naturally regulated

by parasites and predators, and nucleopolyhedrosis

virus (NPV) epizootics. The interval between individual

DFTM population increases is about 9 years, and the

pattern of population fluctuation appears to be cyclic.

Factors governing whether a population increase results

in a DFTM outbreak are not well understood. When

populations begin to increase but do not build to

outbreak levels, parasites and predators are principal

regulators. When populations build to outbreak levels,

collapse is often the result of an NPV epizootic (see

Brookes and others 1978 for additional DFTM

references).

Mapping vulnerability to western spruce budworm

and Douglas-fir tussock mothVulnerability characterizations for WSB and DFTM were collapsed into

one, but vulnerability factors used here were most appropriate to the budworm. Vulnerability to WSB and

DFTM was attributed to all forested vegetation patches;

those containing no host species in the understory and

overstory were given the lowest score for each of seven

factors. The WSB vulnerability factors were (1) site

qualityusing climax conifer series group; (2) host

abundanceusing host crown cover percentage;

(3) canopy structureusing number of canopy layers

in host species; (4) patch (stand) densityusing total

crown cover percentage as a relative measure of stand

density; (5) host ageestimated from overstory and

understory size classes; (6) patch vigorusing estimated

degree of overstory crown differentiation; and (7) connectivity of WSB host patchesestimating connectivity

of patches of host types within a specified radius. Table

4 displays the seven WSB vulnerability factors and

criteria for rating vegetation polygons for each factor.

When all patches in a historical or current vegetation

coverage of a subwatershed were rated for each vulnerability factor, factor ratings were summed for

individual patches. This sum was the patch WSB

vulnerability rating. Patch vulnerability ratings were

collapsed into three vulnerability classes as follows:

low for patches with a composite rating of 7 to 10;

moderate for patches rated 11 to 14; and high for

patches rated 15 and above. Vulnerability classes were

used to characterize change in area and connectivity of

area vulnerable to WSB disturbance between historical

and current vegetation conditions of subwatersheds of

a pooling stratum. Figure 3A illustrates increased area

vulnerable to WSB disturbance in a subwatershed of the

Palisades subbasin.

Carlson and others (1985) used host age and an index

of vigor to rate patch vulnerability to budworm. We

interpreted and attributed the effect of existing stand

density on overall patch vigor by using degree of overstory crown differentiation, and we estimated host age

from size class. We could not reliably interpret age or

density via photointerpretation. The degree of canopy

layering also provided some indication of relative differences in site occupancy, density, and vigor. In the

basin, patch age and vigor appear to influence the

severity and extent of disturbance associated with

budworm outbreaks, but relations are still poorly

understood.
13

Table 4—Criteria for rating forest vegetation patch vulnerability to western spruce budworm

(WSB) disturbance in the midscale assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site qualitya 3 Warm-dry PSME/ABGR(ABCO) or warm-dry ABLA2/PIEN sites

2 Cool-moist PSME/ABGR(ABCO) or cool-moist ABLA2/PIEN sites

1 Other sites

Host abundanceb 3 > 50 percent crown cover of host species

2 30 to 50 percent crown cover of host species

1 < 30 percent crown cover of host species, or other

Canopy structurec 3 2 layers of WSB host species, or 2 mixed-species layers with WSB host species

2 1 layer of WSB host species

1 1 mixed-species layer with WSB host species, or other

Patch (stand) densityd 3 > 70 percent total crown cover (all species)

2 40 to 70 percent total crown cover (all species)

1 < 40 percent total crown cover (all species)

Host agee 3 Estimated as > 120 years old, overstory or understory PSME, ABGR(ABCO), ABAM, ABMA,

ABPR or PIEN large trees (> 63.5 cm d.b.h.), or ABLA2 medium trees (40.6 to 63.5 cm d.b.h.)

2 Estimated as 80 to 120 years old, overstory or understory PSME, ABGR(ABCO), ABAM,

ABMA, ABPR, or PIEN medium trees (40.6 to 63.5 cm d.b.h.), or ABLA2 small trees

(22.9 to 40.5 cm d.b.h.)

1 Estimated as < 80 years old, overstory or understory PSME, ABGR(ABCO), ABAM, ABMA,

ABPR, or PIEN seedling, sapling, pole, or small trees (D 40.5 cm d.b.h.), or ABLA2 seedlings,

saplings, or poles (< 22.9 cm d.b.h.)

Patch vigor f 3 Degree of differentiation among overstory crowns < 30 percent

2 Degree of differentiation among overstory crowns 30 to 100 percent

1 Degree of differentiation among overstory crowns >100 percent

Host patch connectivity g 3 > 40 percent of the area within a 1135-m radius of host patch boundaries is host type

2 20 to 40 percent of the area within a 1135-m radius of host patch boundaries is host type

1 < 20 percent of the area within a 1135-m radius of host patch boundaries is host type

a Site quality was estimated by using a modeled climax conifer series or series group patch attribute. Series group was a midscale estimate of potential

natural vegetation. Series group options here and following were PIPO, PSME/ABGR (ABCO), TSHE/THPL, ABAM, TSME, ABLA2/PIEN,

PIAL/LALY, PICO, and ABMA (see table 3 for a complete listing of tree species abbreviations). Series group was modeled by using the overstory and

understory species attributes of both the recent historical and current vegetation coverages, coupled with elevation and aspect setting attributes derived

from a 90-m digital elevation model (see Hessburg and others 1999 and Smith and others (in press) for complete descriptions of modeling methods and

subbasin rule sets). A patch rating of 3 in site quality here and following indicated that temperature and moisture conditions during the growing season

contributed maximally to host vulnerability to disturbance.

b Budworm hosts were PSME, ABGR(ABCO), ABLA2, ABAM, ABMA, ABPR, and PIEN. Here and following, ABGR was treated as being

synonymous with ABCO; this was indicated by the notation, ABGR(ABCO). LAOC, although vulnerable, was omitted from this host list because even

older larch are considerably less vulnerable than the shade-tolerant conifers included in this list (Wulf and Carlson 1985). Host abundance, here and

following, was calculated by using the photo-interpreted attributes total crown cover, overstory crown cover, understory crown cover, overstory species, and

understory species. Overstory crown cover was subtracted from total crown cover to obtain apparent understory crown cover. Note that forested crown

cover was estimated by photo-interpretation in 10-percent cover increments (e.g., 10 percent = 5-14 percent; 20 percent = 15-24 percent). Maximum crown

cover was 100 percent. In reality, overstory and understory crown cover of some patches would sum to a value greater than 100 p ercent. Photo-interpreted

patch overstory and understory species attributes allowed for pure and mixed compositions. When a patch overstory or understory was attributed as

having more than one species, each species represented at least 20 percent of the crown cover of the layer. Mixes of two and three species were commonly

attributed. Host abundance was obtained by computing overstory and understory crown cover in each defoliator host species. When budworm hosts

were PSME or ABGR(ABCO) or ABLA2, or PIEN, the host abundance weighting factor was 1.5; i.e., the host abundance rating was multiplied by

1.5. When hosts were ABAM or ABMA or ABPR, the host abundance weighting factor was 1.0. When hosts were other than these, the host abundance

weighting factor was 0.5.

c

 Canopy structure here and following was derived from photo-interpreted attributes: overstory species, understory species, and canopy layers. d

 Density here and following was estimated by using total crown cover of all species.

e

 Host age here and following was approximated by using photo-interpreted attributesoverstory species, overstory size class, understory species, and

understory size class. When hosts occurred in the overstory and understory, the size class of the overstory was used to estimate host age.

f

 Patch vigor here and following was estimated by using the patch overstory crown differentiation attribute. See appendix 1 for complete descriptions

of photo-interpreted attributes.

g Here and following, connectivity of host patches was rated by computing the percentage of the area within a specified dispersal radius (buffer) comprised

of host patches, at a scale of 30 m with raster coverages. Patches were classified as host or nonhost in a geographical informa tion system based on the

presence or absence of a host species (see factor 2 above) in the overstory and understory. A 1135-m radius around host patch boundaries represents an

area of about 400 ha used by Wulf and Carlson (1985) to estimate connectivity of host patches for WSB. Using this radius, we assume that budworm

larvae and adults will locate host patches with high probability when hosts are within the identified search radius. Beyond this radius, we assume that

dispersal losses of larvae or adults are significant.
14

Figure 3Historical and current vegetation vulnerability to (A) western spruce budworm disturbance in subwatershed 1102 in the Palisades subbasin of

the Snake Headwaters Ecological Reporting Unit, (B) Douglas-fir beetle disturbance in subwatershed 40c in the Silvies subbasin of the Blue Mountains

Ecological Reporting Unit.
15

elsewhere in the upper Columbia basin. This mortality is

an excellent indicator of forest aging as a result of fire

exclusion, synchronous landscapes, high-density growing

conditions, drought vulnerability, vigor depression of

forests and stands, and spatial connectivity of vulnerable

conditions. Ground fuel inputs associated with pine bark

beetle mortality over the same timeframe also have been

significant (Huff and others 1995; Ottmar and others, in

press).

Douglas-fir beetleDouglas-fir beetle (DFB) outbreaks are primarily associated with large-scale wind,

fire, or drought events, or defoliator (WSB or DFTM)

outbreaks. Areas with severe dwarf mistletoe and root

disease in Douglas-fir also tend to support elevated

DFB populations. At least 40 percent of the Douglasfir in eastern Oregon and Washington are infected with

Douglas-fir dwarf mistletoe (Bolsinger 1978); infection

rates are comparable in the upper Columbia basin.3

An additional 5 to 10 percent are root-diseased (Byler

1988).

Mapping vulnerability to the Douglas-fir beetle

The primary host of the DFB is Douglas-fir (PSME),

although western larch (LAOC) windthrow is occasionally infested. Vulnerability to DFB disturbance

was attributed to all forested vegetation patches; those

containing no hosts in either the understory or overstory

were given the lowest score for each factor where host

was identified. Douglas-fir beetle vulnerability factors

were (1) site quality, (2) host abundance, (3) canopy

structure, (4) patch (stand) density, (5) host age, and

(6) connectivity of DFB host patches. Table 5 displays

the six DFB vulnerability factors and criteria for rating

vegetation polygons for each factor.

When all patches in a historical or current vegetation

coverage of a subwatershed were rated for each vulnerability factor, factor ratings were summed for individual

patches. This sum was the patch DFB vulnerability

rating. Patch vulnerability ratings were collapsed into

three vulnerability classes as follows: low for patches

with a composite rating of 6 to 9; moderate for patches

rated 10 to 13; and high for patches rated 14 and above.

Vulnerability classes were used to characterize change

in area and connectivity of area vulnerable to DFB

disturbance between historical and current vegetation

conditions of subwatersheds of a pooling stratum.

Figure 3b illustrates increased area vulnerable to DFB

disturbance in a subwatershed of the Silvies subbasin.

Bark Beetles

Vulnerability of forest vegetation to the Douglas-fir

beetle, western pine beetle, mountain pine beetle,

fir engraver, and spruce beetle was characterized. In

endemic populations, each bark beetle species attacks

low vigor, diseased, weakened or injured trees, and

recent wind-thrown or collapsed trees. In outbreaks,

vigorous hosts are mass attacked and killed, occasionally across large areas. In pine-dominated patches,

stressed trees are commonly associated with highdensity growing conditions, droughty growing seasons,

or protracted droughts. In successionally advanced

patches comprised of shade-tolerant species, root

pathogens, dwarf mistletoes, drought, and overstocking

maintain an abundance of beetle-vulnerable stressed

trees.

In endemic populations, mountain pine and western

pine beetles typically attack stressed or declining pines.

Lacking regular underburning fires or tree density

management, vigor-depressed pockets or patches

of ponderosa or lodgepole pine often develop. Under

the right environmental conditions, when host stems are

sufficiently large, and when phloem thickness (mountain

pine beetle) is adequate to support beetle brood development, beetles attack and kill trees in the manner of an

indiscriminant thinning or a thinning from above. Under

these outbreak conditions, pockets or patches of trees,

whole stands, and even large forests of similar type are

destroyed, often yielding new cover types, structural

conditions, and significantly increased fuels. In outbreak

conditions, vigorous host-dominated patches and

landscapes also are affected. During extended drought

periods, the western pine beetle may replace or join

the mountain pine beetle in attacking small-diameter

ponderosa pine.

Between 1987 and 1994, widespread pine bark beetle

mortality in ponderosa, lodgepole, and western white

pines was recorded throughout the basin within the

grand fir, white fir, Douglas-fir, and ponderosa pine

zones2

 (see also Gast and others 1991, Hessburg and

others 1994, OLaughlin and others 1993 and references

therein). Over the last several decades, lodgepole pine

mortality associated with large-scale mountain pine

beetle outbreaks also has been recorded throughout

the cover type in eastern Oregon and Washington

(Gast and others 1991, Hessburg and others 1994), and

2

 Refer to the annual aerial detection survey maps and insect and disease

conditions reports of the USDA Forest Service, Pacific Northwest,

Northern, and Intermountain Regions, Forest Pest Management Group,

for the period 1987-94.

3

 Hoffman, James. 1994. Insect, disease, animal, and abiotic damages

associated with central Idaho habitat types. 2 p. Unpublished data. On

file with: Pacific Northwest Research Station, Forestry Sciences Laboratory,

1133 N. Western Avenue, Wenatchee, WA 98801-1713.
16

Table 5—Criteria for rating forest vegetation patch vulnerability to Douglas-fir beetle (DFB)

disturbance in the midscale assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Vulnerability factor

Site quality 3 Warm-dry PSME/ABGR(ABCO) sites

2 Cool-moist PSME/ABGR(ABCO); warm-dry ABLA2/PIEN sites

1 Other sites

Host abundancea 3 > 50 percent crown cover in PSME 22.9 cm d.b.h. and larger

2 30 to 50 percent crown cover in PSME 22.9 cm d.b.h. and larger

1 < 30 percent crown cover in PSME 22.9 cm d.b.h. and larger, or other

Canopy structure 3 2 or more PSME layers with PSME 22.9 cm d.b.h. or larger, or 2

or more mixed-species layers with PSME 22.9 cm d.b.h. or larger

2 1 PSME layer 22.9 cm d.b.h. or larger

1 1 mixed-species layer with PSME 22.9 cm d.b.h. or larger

Patch (stand) density 3 > 70 percent total crown cover (all species)

2 40 to 70 percent total crown cover (all species)

1 < 40 percent total crown cover (all species)

Host ageb 3 Estimated as > 120 years old, PSME overstory large trees

(> 63.5 cm d.b.h.)

2 Estimated as 81 to 120 years old, PSME overstory or understory

medium trees (40.6 to 63.5 cm d.b.h.)

1 Estimated as 40 to 80 years old, PSME overstory or understory

small trees (22.9 to 40.5 cm d.b.h.)

Host patch connectivityc 3 > 40 percent of the area within a 1-km radius of host patch

boundaries is host type

2 20 to 40 percent of the area within a 1-km radius of host patch

boundaries is host type

1 < 20 percent of the area within a 1-km radius of host patch

boundaries is host type

a Host abundance was obtained by computing overstory and understory crown cover in PSME 22.9 cm d.b.h. and larger, because PSME smaller than

22.9 cm are infrequently attacked by the DFB.

b

 Here and following, when the host species, in this case PSME, occurred in both the overstory and understory, the size class of the overstory was used

to attribute host age.

c

 Connectivity was computed for patches with PSME 22.9 cm d.b.h. and larger. Using a 1-km radius, we assumed that DFB adults would locate host

patches with high probability when hosts were within the identified search radius. Beyond this radius, we assumed that adult dispersal losses were

significant.
17

Table 6—Criteria for rating forest vegetation patch vulnerability to type 1 western pine beetle

(WPB) disturbance of mature and old ponderosa pine (PIPO) in the midscale assessment of

the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site quality 3 PIPO sites

2 Warm-dry PSME/ABGR(ABCO) sites

1 Cool-moist PSME/ABGR(ABCO), other sites

Host abundance 3 > 50 percent crown cover in PIPO 22.9 cm d.b.h. and larger

2 30 to 50 percent crown cover in PIPO 22.9 cm d.b.h. and larger

1 < 30 percent crown cover in PIPO 22.9 cm d.b.h. and larger, or other

Patch (stand) density 3 > 60 percent total crown cover (all species)

2 40 to 60 percent total crown cover (all species)

1 < 40 percent total crown cover (all species)

Host age 3 Estimated as > 120 years old, PIPO overstory

large trees (> 63.5 cm d.b.h.)

2 Estimated as 80 to 120 years old, PIPO overstory or understory

medium trees (40.6 to 63.5 cm d.b.h.)

1 Estimated as < 80 years old, PIPO overstory or understory small trees

(22.9 to 40.5 cm d.b.h.)

Host patch connectivitya 3 > 40 percent of the area within a 1-km radius of host patch

boundaries is host type

2 20 to 40 percent of the area within a 1-km radius of host patch

boundaries is host type

1 < 20 percent of the area within a 1-km radius of host patch

boundaries is host type

a

 Connectivity was computed for patches with PIPO 22.9 cm d.b.h. and larger. Using a 1-km radius, we assumed that WPB adults would locate host

patches with high probability when hosts were within the identified search radius. Beyond this radius, we assumed that adult dispersal losses were

significant.

Western pine beetleThe western pine beetle (WPB)

primarily affects ponderosa pine (PIPO) in the basin.

Large, mature, and old ponderosa pine are vulnerable

as are immature pole, small, and medium-sized pine

growing in high-density conditions. The WPB is often

responsible for the demise of ponderosa pine infected

with the western dwarf mistletoe, P-group annosum

root disease, Armillaria root disease, and those stressed

by persistent drought or winter dessication injury.

Mapping vulnerability to the western pine beetle

Vulnerability to WPB disturbance was attributed to

all forested vegetation patches; those containing no

hosts in either the understory or overstory were given

the lowest score for each factor where host was

identified. Two types of WPB vulnerability evaluated

were type 1 vulnerability of mature and old PIPO

patches; and type 2 vulnerability of immature, highdensity PIPO patches. Western pine beetle vulnerability

factors (types 1 and 2) were (1) site quality, (2) host

abundance, (3) patch (stand) density, (4) host age,

(5) patch vigor, and (6) connectivity of WPB host

patches. Table 6 displays type 1 WPB vulnerability

factors and criteria for rating vegetation polygons for

each factor; table 7 displays type 2 WPB vulnerability

factors and criteria for rating vegetation polygons for

each factor.
18

Table 7—Criteria for rating forest vegetation patch vulnerability to type 2 western pine beetle

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

pine (PIPO) in the midscale assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site quality 3 PIPO sites

2 Warm-dry PSME/ABGR(ABCO) sites

1 Cool-moist PSME/ABGR(ABCO), or other sites

Host abundance 3 > 50 percent crown cover in 12.7 to 40.5 cm d.b.h. PIPO

2 30 to 50 percent crown cover in 12.7 to 40.5 cm d.b.h. PIPO

1 < 30 percent crown cover in 12.7 to 40.5 cm d.b.h. PIPO, or other

Patch (stand) density 3 > 60 percent total crown cover (all species)

2 40 to 60 percent total crown cover (all species)

1 < 40 percent total crown cover (all species)

Host age 3 Estimated as 41 to 80 years old, PIPO overstory or understory small

trees ( 22.7 to 40.5 cm d.b.h.)

2 Estimated as 21 to 40 years old, PIPO overstory or understory poles

(12.7 to 22.6 cm d.b.h.)

1 Estimated as 20 years old, PIPO overstory or understory seedlings

and saplings (< 12.7 cm d.b.h.)

Patch vigor 3 Degree of differentiation among overstory crowns < 30 percent

2 Degree of differentiation among overstory crowns 30 to 100 percent

1 Degree of differentiation among overstory crowns > 100 percent

Host patch connectivitya 3 > 40 percent of the area within a 1-km radius of host patch

boundaries is host type

2 20 to 40 percent of the area within a 1-km radius of host patch

boundaries is host type

1 < 20 percent of the area within a 1-km radius of host patch

boundaries is host type

a

 Connectivity was computed for patches with PIPO 12.7 to 40.5 cm d.b.h. Using a 1-km radius, we assumed that WPB adults would locate host patches

with high probability when hosts were within the identified search radius. Beyond this radius, we assumed that dispersal losses were significant.

As described above, factor ratings were summed for

individual patches. Type 1 WPB patch vulnerability

ratings were collapsed into vulnerability classes as

follows: low for patches with a composite rating of

5 to 7; moderate for patches rated 8 to 10; and high

for patches rated 11 and above. Type 2 WPB patch

vulnerability ratings were collapsed into vulnerability

classes as follows: low for patches with a composite

rating of 6 to 8; moderate for patches rated 9 to 11;

and high for patches rated 12 and above. Vulnerability

classes were used to characterize change in area and

connectivity of area vulnerable to type 1 and type 2

WPB disturbance between historical and current

vegetation conditions of subwatersheds of a pooling

stratum. Figure 4a illustrates reduced area vulnerable to

WPB type 1 disturbance in a subwatershed of the Lower

John Day subbasin. Figure 4b illustrates increased area

vulnerable to WPB type 2 disturbance in a subwatershed

of the Lower John Day subbasin.
19

Figure 4Historical and current vegetation vulnerability to (A) western pine beetle type 1 disturbance in subwatershed 1303 in the Lower John Day

subbasin of the Columbia Plateau Ecological Reporting Unit, (B) western pine beetle type 2 disturbance in subwatershed 1903 in the Lower John Day

subbasin of the Columbia Plateau Ecological Reporting Unit.
20

Table 8—Criteria for rating forest vegetation patch vulnerability to type 1 mountain pine beetle

(MPB) disturbance of immature, high-density lodgepole pine (PICO) in the midscale assessment

of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site quality 3 Edaphic PICO; warm-dry ABLA2/PIEN; cool-moist PSM ABGR

(ABCO) sites

2 ABMA; cool-moist ABLA2/PIEN; TSME sites

1 Other sites

Host abundance 3 > 50 percent crown cover in PICO 12.7 cm d.b.h. and larger

2 30 to 50 percent crown cover in PICO 12.7 cm d.b.h. and larger

1 < 30 percent crown cover in PICO 12.7 cm d.b.h. and larger, or other

Patch (stand) density 3 > 70 percent total crown cover (all species)

2 50 to 70 percent total crown cover (all species)

1 < 50 percent total crown cover (all species)

Host size 3 PICO overstory or understory small, medium, and large trees

(> 22.7 cm d.b.h.)

2 PICO overstory or understory poles (12.7 to 22.6 cm d.b.h.)

1 PICO overstory or understory seedling and saplings (< 12.7 cm d.b.h.)

Patch vigor 3 Degree of differentiation among overstory crowns < 30 percent

2 Degree of differentiation among overstory crowns 30 to 100 percent

1 Degree of differentiation among overstory crowns > 100 percent

Host patch connectivitya 3 > 40 percent of the area within a 1-km radius of host patch boundaries

is host type

2 20 to 40 percent of the area within a 1-km radius of host patch

boundaries is host type

1 < 20 percent of the area within a 1-km radius of host patch boundaries

is host type

a

 Connectivity was computed for patches with PICO 12.7 cm d.b.h. and larger. Using a 1-km radius, we assumed that MPB adults would locate host

patches with high probability when hosts were within the identified search radius. Beyond this radius, we assumed that dispersal losses were significant.

Mountain pine beetleThe mountain pine beetle

(MPB) primarily attacks lodgepole (PICO) and

ponderosa pines; poles and small trees growing in

overcrowded conditions are vulnerable. Western white

pine (PIMO) 35.6 cm d.b.h. and larger, having more

than 13 m2 of associated basal area, and older than

140 years often are killed by the MPB, as are those with

severe white pine blister rust bole cankers. In addition,

the mountain pine beetle kills stressed, injured, or old

sugar pine, whitebark pine, and limber pine, and those

with blister rust bole infections. Large, old lodgepole

pine, and those injured or stressed also are attacked.

Mapping vulnerability to the mountain pine beetle

Vulnerability to MPB disturbance was attributed to all

forested vegetation patches; those containing no hosts in

either the understory or overstory were given the lowest

score for each factor where host was identified. Two

types of MPB vulnerability were evaluated: type 1 vulnerability of high-density PICO; and type 2 vulnerability

of immature, high-density PIPO. Type 1 MPB vulnerability factors were (1) site quality, (2) host abundance,

(3) patch (stand) density, (4) host size, (5) patch vigor,

and (6) connectivity of WPB host patches. Type 2 MPB

vulnerability factors were identical to those used to

assess type 2 WPB vulnerability. Table 8 displays type 1

MPB vulnerability factors and criteria for rating vegetation polygons for each factor; table 7 displays type 2

WPB (and type 2 MPB) vulnerability factors and criteria

for rating vegetation polygons for each factor.
21

Type 1 and type 2 MPB patch vulnerability ratings were

collapsed into vulnerability classes as follows: low for

patches with a composite rating of 6 to 8; moderate for

patches rated 9 to 11; and high for patches rated 12 and

above. Vulnerability classes were used to characterize

change in area and connectivity of area vulnerable to

type 1 and type 2 MPB disturbance between historical

and current vegetation conditions of subwatersheds

of a pooling stratum. Figure 5A illustrates reduced

area vulnerable to type 1 MPB disturbance in a

subwatershed of the Wallowa subbasin. Figure 5B

illustrates expanded area vulnerable to type 2 MPB

disturbance in a subwatershed of the Palouse subbasin.

Fir engraverAll true firs (Abies spp.) are host to the

fir engraver beetle (FE)B. Fir engraver beetles often are

described as secondary bark beetlesbeetles lacking

a means of overcoming robust trees, that instead attack

and overcome trees stressed by drought, other insects,

or pathogens. Grand fir, white fir, and subalpine fir are

primarily affected by FEB. Each seems to be droughtsensitive and vulnerable to three root pathogens:

Phellinus weirii, which causes laminated root rot,

Heterobasidion annosum, which causes S-type annosum

root disease, and Armillaria ostoyae, which causes

Armillaria root disease. During drought-free periods,

FEB mortality reliably indicates root disease distribution

and severity within the grand and white fir zones (Lane

and Goheen 1979).

Mapping vulnerability to the fir engraver beetle

Vulnerability to FEB disturbance was attributed to all

forested vegetation patches; those containing no hosts

in either the understory or overstory, were given the

lowest score for each factor where host was identified.

Fir engraver vulnerability factors were (1) site quality,

(2) host abundance, (3) canopy structure, (4) patch

(stand) density, (5) host size, and (6) connectivity of FEB

host patches. Table 9 displays the six FEB vulnerability

factors and criteria for rating vegetation polygons for

each factor.

Factor ratings were summed for individual patches. Fir

engraver patch vulnerability ratings were collapsed into

vulnerability classes as follows: low for patches with a

composite rating of 6 to 9; moderate for patches rated

10 to 12; and high for patches rated 13 and above. Vulnerability classes were used to characterize change in

area and connectivity of area vulnerable to FE disturbance between historical and current vegetation

conditions of subwatersheds of a pooling stratum.

Figure 6A illustrates expanded area vulnerable to FE

disturbance in a subwatershed of the South Fork

Clearwater subbasin. Figure 6B illustrates reduced

area vulnerable to FE disturbance in a subwatershed

of the lower Grande Ronde subbasin.

Spruce beetleIn the basin, Engelmann spruce

(PIEN) is host to the spruce beetle (SB). Spruce beetles

attack injured trees and those stressed by drought,

pathogens, or other insects. Like the Douglas-fir beetle,

spruce beetle outbreaks often are associated with large

wind, fire, drought, or defoliation events. Engelmann

spruce appear to be sensitive to extended drought and

often succumb to any of four root diseases: S-type

annosum root disease, Armillaria root disease, tomentosus root and butt rot, and Schweinitzii root and butt

rot. In the latter two cases, Engelmann spruce with

significant tomentosus root and butt rot or Schweinitzii

root and butt rot eventually collapse and are typically

colonized by the spruce beetle.

Mapping vulnerability to the spruce beetleVulnerability to SB disturbance was attributed to all forested

vegetation patches; those containing no hosts in either

the understory or overstory were given the lowest score

for each factor where host was identified. Spruce beetle

vulnerability factors were (1) site quality, (2) host abundance, (3) topographic setting, (4) host size, (5) patch

(stand) density, and (6) connectivity of SB host patches.

Table 10 displays the six SB vulnerability factors and

criteria for rating vegetation polygons for each factor.

Factor ratings were summed for individual patches.

Spruce beetle vulnerability ratings were collapsed into

vulnerability classes as follows: low for patches with a

composite rating of 6 to 8; moderate for patches rated

9 to 11; and high for patches rated 12 and above. Vulnerability classes were used to characterize change in

area and connectivity of area vulnerable to SB disturbance between historical and current vegetation

conditions of subwatersheds of a pooling stratum.

Figure 7A illustrates reduced area vulnerable to SB

disturbance in a subwatershed of the Upper Grande

Ronde subbasin.

Text continues on page 27.
22

Figure 5Historical and current vegetation vulnerability to (A) mountain pine beetle type 1 disturbance in subwatershed 40 in the Wallowa subbasin of

the Blue Mountains Ecological Reporting Unit (B) mountain pine beetle type 2 disturbance in subwatershed 2002 in the Palouse subbasin of the

Columbia Plateau Ecological Reporting Unit.
23

Table 9—Criteria for rating forest vegetation patch vulnerability to fir engraver (FE) disturbance

in the midscale assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site quality 3 Warm-dry PSME/ABGR(ABCO); warm-dry ABLA2/PIEN

2 Cool-moist PSME/ABGR(ABCO); ABMA; cool-moist ABLA2/PIEN

1 Other sites

Host abundancea 3 > 50 percent crown cover in FE host species 12.7 cm d.b.h. and

larger

2 30 to 50 percent crown cover in FE host species 12.7 cm d.b.h. and

larger

1 < 30 percent crown cover in FE host species 12.7 cm d.b.h. and

larger, or other

Patch (stand) density 3 > 70 percent total crown cover (all species)

2 50 to 70 percent total crown cover (all species)

1 < 50 percent total crown cover (all species)

Host size 3 Overstory or understory medium or large trees, FE host species

(> 40.6 cm d.b.h.)

2 Overstory or understory small trees, FE host species

(22.9 to 40.5 cm d.b.h.)

1 Overstory or understory seedlings, saplings or poles, FE host species

(< 22.9 cm d.b.h.)

Canopy structure 3 2 or more layers FE host species 12.7 cm d.b.h. and larger, or 2 or

more mixed-species layers with FE host species 12.7 cm d.b.h.

and larger

2 1 layer FE host species 12.7 cm d.b.h. and larger

1 1 mixed-species layer with FE host species 12.7 cm d.b.h. and larger

Host patch connectivityb 3 > 40 percent of the area within a 1-km radius of host patch

boundaries is host type

2 20 to 40 percent of the area within a 1-km radius of host patch

boundaries is host type

1 < 20 percent of the area within a 1-km radius of host patch

boundaries is host type

a

 FE hosts were ABGR(ABCO), ABLA2, ABAM, ABPR, and ABMA. When hosts were ABGR(ABCO), the host abundance weighting factor was

1.5. When hosts were ABLA2, ABAM, ABMA, or ABPR, the host abundance weighting factor was 1.0. When hosts were other than these, the host

abundance weighting factor was 0.5.

b

 Connectivity was computed for patches with ABGR(ABCO), ABLA2, ABMA, ABAM, ABPR 12.7 cm d.b.h. and larger. Using a 1-km radius, we

assumed that FE adults would locate host patches with high probability when hosts were within the identified search radius. Beyond this radius, we

assumed that dispersal losses were significant.
24

Figure 6Historical and current vegetation vulnerability to (A) fir engraver disturbance in subwatershed 0703 in the South Fork Clearwater subbasin of the

Central Idaho Mountains Ecological Reporting Unit, (B) fir engraver disturbance in subwatershed 12 in the Lower Grande Ronde subbasin of the Blue

Mountains Ecological Reporting Unit.
25

Table 10—Criteria for rating forest vegetation patch vulnerability to spruce beetle (SB)

disturbance in the midscale assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site quality 3 Cool-moist PSME/ABGR(ABCO); warm-dry ABLA2/PIEN sites

2 Cool-moist ABLA2/PIEN sites, TSHE/THPL, ABAM, ABMA sites

1 Other sites

Host abundance 3 > 50 percent crown cover in PIEN 22.9 cm d.b.h. or larger

2 30 to 50 percent crown cover in PIEN 22.9 cm d.b.h. or larger

1 < 30 percent crown cover in PIEN 22.9 cm d.b.h. or larger, or other

Patch (stand) density 3 > 70 percent total crown cover (all species)

2 50 to 70 percent total crown cover (all species)

1 < 50 percent total crown cover (all species)

Host size 3 Large PIEN overstory trees (> 63.5 cm d.b.h.)

2 Medium PIEN overstory or understory trees (40.6 to 63.5 cm d.b.h.)

1 Small PIEN overstory or understory trees (22.9 to 40.5 cm d.b.h.)

Topographic setting 3 Valley bottom settings (toe-slope to valley bottom) with

PIEN > 22.7 cm d.b.h.

1 Other settings

Host patch connectivitya 3 > 40 percent of the area within a 1-km radius of host patch boundaries

is host type

2 20 to 40 percent of the area within a 1-km radius of host patch

boundaries is host type

1 < 20 percent of the area within a 1-km radius of host patch

boundaries is host type

a

 Connectivity was computed for patches with PIEN 22.9 cm d.b.h. and larger. Using a 1-km radius, we assumed that SB adults would locate host patches

with high probability when hosts were within the identified search radius. Beyond this radius, we assumed that dispersal losses were significant.
26

Figure 7Historical and current vegetation vulnerability to (A) Douglas-fir dwarf mistletoe disturbance in subwatershed 29 in the Wallowa subbasin of

the Blue Mountains Ecological Reporting Unit, (B) spruce beetle disturbance in subwatershed 28 in the Upper Grande Ronde subbasin of the Blue

Mountains Ecological Reporting Unit.
27

Pathogens Modeled

Dwarf Mistletoes

Ponderosa pine, western larch, Douglas-fir, and lodgepole pine are dominant early-seral species in the basin;

a host-specialized dwarf mistletoe is associated with

each tree species. It is likely that under pre-European

settlement fire regimes, dwarf mistletoe presence in

these cover types favored compositions dominated

by early-seral tree species, in the manner of a positive

feedback. Fires associated with nonlethal and mixedseverity fire regimes favored the establishment and

perpetuation of early seral tree species, maintaining

spatial and temporal continuity of hosts, and local

persistence of host-specialized mistletoes. Locally

severe mistletoe infestations favored the torching of the

most infested trees or tree groups. By this mechanism,

dwarf mistletoes of early-seral species were potentially

well distributed under presettlement conditions, but

perhaps at lower infestation levels within host populations than is observed today. Dwarf mistletoes of

shade-tolerant species occurring in mid- and latesuccessional communities were likely destabilizing

to those communities, favoring tree group torching,

crowning fires, and regeneration of early-seral species,

in the manner of a negative feedback.

Mapping vulnerability to dwarf mistletoesAt

least 40 percent of the Douglas-fir east of the crest of

the Cascade Range in Oregon and Washington are

infected with dwarf mistletoe (Bolsinger 1978). An

equivalent proportion are infected in the upper

Columbia basin (see footnote 2). About one-quarter of

the ponderosa pine, one-half of the western larch, and

40 percent of the lodgepole pine in eastern Oregon and

Washington are infected with a host-specialized dwarf

mistletoe (Bolsinger 1978). It is estimated that an even

greater proportion of the lodgepole pine in the upper

Columbia basin are infected (see footnote 2). Landscape

vulnerability to dwarf mistletoe disturbance is correlated with host abundance, pathogen distribution,4

patch structure, host size and age, site quality, and host

connectivity. Vulnerability to Douglas-fir (DFDM),

ponderosa pine (PPDM), western larch (WLDM), and

lodgepole pine (LPDM) dwarf mistletoe disturbances

was attributed to all forested vegetation patches; those

containing no host species in either the overstory or

understory were given the lowest score for each factor

where host was identified. Vulnerability factors for

each host-specific dwarf mistletoe disturbance were

(1) site quality, (2) host abundance, (3) canopy structure, (4) host age, and (5) connectivity of host patches.

Tables 11-14 display vulnerability factors for DFDM,

PPDM, WLDM, and LPDM, respectively, and criteria

for rating vegetation polygons for each factor.

Patch vulnerability ratings for each of the four dwarf

mistletoe disturbances were collapsed into vulnerability

classes as follows: low for patches with a composite

rating of 5 to 7; moderate for patches rated 8 to 10;

and high for patches rated 11 and above. Vulnerability

classes were used to characterize change in area and

connectivity of area vulnerable to each dwarf mistletoe

disturbance between historical and current vegetation

conditions of subwatersheds of a pooling stratum.

Figure 7B illustrates expanded area vulnerable to

DFDM disturbance in a subwatershed of the Wallowa

subbasin. Figure 8A illustrates reduced area vulnerable

to WLDM disturbance in a subwatershed of the Swan

subbasin.

Root Diseases

Landscape vulnerability to four root diseases was

evaluated. Root pathogens of interest were Phellinus

weirii, which causes laminated root rot, Armillaria ostoyae,

which causes Armillaria root disease, and Heterobasidion

annosum, which causes both the S (spruce)- and P (pine)-

group annosum root diseases. Collectively, these root

pathogens cause extensive mortality to Douglas-fir,

grand fir, white fir, subalpine fir, and ponderosa pine,

and cause butt rot and tree failure of most other

conifers. Throughout the Douglas-fir, grand fir, and

white fir zones (Franklin and Dyrness 1973), three root

diseases have increased dramatically in distribution and

severity in this centurylaminated root rot, Armillaria

root disease, and the S-group annosum root disease

(Gast and other 1991, Hessburg and others 1994,

Schmitt and others 1991). The noted increase is

attributable to marked increases in the abundance

of vulnerable shade-tolerant, fire-sensitive hosts as a

result of fire exclusion and selective harvest activities

(Agee 1993, 1994; Hessburg and others 1994, 1999;

Lehmkuhl and others 1994; Oliver and others 1994;

Schmitt and others 1991).

4

 Note here and following, actual inventory data on the distribution of

dwarf mistletoes are needed for most accurate vulnerability characterization. Such inventories are needed Columbia basin-wide on a sampling

basis. Lacking these data, vulnerability characterizations are based on the

distribution and arrangement of vulnerable host patches, and presence

of each host-specific mistletoe is assumed.
28

Table 11—Criteria for rating forest vegetation patch vulnerability to Douglas-fir dwarf mistletoe

(DFDM) disturbance in the midscale assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site quality 3 Warm-dry PSME/ABGR(ABCO) sites

2 Cool-moist PSME/ABGR(ABCO) sites

1 Other sites

Host abundance 3 > 50 percent crown cover in PSME

2 30 to 50 percent crown cover in PSME

1 < 30 percent crown cover in PSME, or other

Canopy structure 3 2 or more PSME layers

2 2 or more mixed-species layers with PSME

1 1 PSME layer, or 1 mixed-species layer with PSME

Host age 3 Estimated > 120 years old, overstory large tree PSME (> 63.5 cm d.b.h.)

2 Estimated 80 to 120 years old, overstory or under story medium tree PSME (40.6 to 63.5 cm d.b.h.)

1 Estimated < 80 years old, overstory or understory seedling, sapling, pole, or small tree PSME

(< 40.5 cm d.b.h.)

Host patch connectivitya 3 > 50 percent of the area within a 1-hm radius of host patch boundaries is host type

2 30 to 50 percent of the area within a 1-hm radius of host patch boundaries is host type

1 < 30 percent of the area within a 1-hm radius of host patch boundaries is host type

a

 Connectivity was computed for patches with PSME. Using a 1-hm radius (1 hm = 100 m), we assumed that DFDM seeds would spread disease to

adjacent patches with high probability when hosts were within the 1-hm radius. Beyond this radius, we assumed that dispersal opportunities including

occasional seed dispersal by birds were insignificant.

Table 12—Criteria for rating forest vegetation patch vulnerability to western dwarf mistletoe

(PPDM) disturbance in the midscale assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site quality 3 PIPO sites

2 Warm-dry PSME/ABGR(ABCO) sites

1 Cool-moist PSME/ABGR(ABCO) sites, and other sites

Host abundance 3 > 50 percent crown cover in PIPO

2 30 to 50 percent crown cover in PIPO

1 < 30 percent crown cover in PIPO, or other

Canopy structure 3 2 or more layers of PIPO

2 2 or more mixed-species layers with PIPO

1 1 PIPO layer, or 1 mixed-species layer with PIPO

Host age 3 Estimated > 120 years old, overstory large tree PIPO (> 63.5 cm d.b.h.)

2 Estimated 80 to 120 years old, overstory or understory medium tree PIPO (40.6 to 63.5 cm d.b.h.)

1 Estimated < 80 years old, overstory or understory seedling, sapling, pole, or small tree PIPO

(< 40.6cm d.b.h.)

Host patch connectivitya 3 > 50 percent of the area within a 1-hm radius of host patch boundaries is host type

2 30 to 50 percent of the area within a 1-hm radius of host patch boundaries is host type

1 < 30 percent of the area within a 1-hm radius of host patch boundaries is host type

a

 Connectivity was computed for patches with PIPO. Using a 1-hm radius (1 hm = 100 m), we assumed that PPDM seeds would spread disease to

adjacent patches with high probability when hosts were within the 1-hm radius. Beyond this radius, we assumed that dispersal opportunities including

occasional seed dispersal by birds were insignificant.
29

Table 13—Criteria for rating forest vegetation patch vulnerability to western larch dwarf mistletoe

(WLDM) disturbance in the midscale assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site quality 3 Cool-moist PSME/ABGR(ABCO) sites

2 ABLA2/PIEN sites

1 Other sites

Host abundance 3 > 50 percent crown cover in LAOC

2 30 to 50 percent crown cover in LAOC

1 < 30 percent crown cover in LAOC, or other

Canopy structure 3 2 or more layers with LAOC

2 2 or more mixed-species layers with LAOC

1 1 LAOC layer, or 1 mixed-species layer with LAOC

Host age 3 Estimated > 120 years old, large tree LAOC (> 63.5 cm d.b.h.) overstory

2 Estimated 80 to 120 years old, medium tree LAOC ( 40.6 to 63.5 cm d.b.h.) overstory or understory

1 Estimated < 80 years old, overstory or understory seedling, sapling, pole, or small tree LAOC

(< 40.6 cm d.b.h.)

Host patch connectivitya 3 > 50 percent of the area within a 1-hm radius of host patch boundaries is host type

2 30 to 50 percent of the area within a 1-hm radius of host patch boundaries is host type

1 < 30 percent of the area within a 1-hm radius of host patch boundaries is host type

a

 Connectivity was computed for patches with LAOC. Using a 1-hm radius (1 hm = 100 m), we assumed that WLDM seeds would spread disease to

adjacent patches with high probability when hosts were within the 1-hm radius. Beyond this radius, we assumed that dispersal opportunities including

occasional seed dispersal by birds were insignificant.

Table 14—Criteria for rating forest vegetation patch vulnerability to lodgepole pine dwarf

mistletoe (LPDM) disturbance in the midscale assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site quality 3 Edaphic PICO sites, ABLA2/PIEN sites

2 PSME/ABGR(ABCO) or ABMA sites

1 Other sites

Host abundance 3 > 50 percent crown cover in PICO

2 30 to 50 percent crown cover in PICO

1 < 30 percent crown cover in PICO, or other

Canopy structure 3 2 or more layers of PICO

2 2 or more mixed-species layers with PICO

1 1 PICO layer, or 1 mixed-species layer with PICO

Host age 3 Estimated as > 120 years old, PICO overstory or understory medium and large trees

(> 40.6 cm d.b.h.)

2 Estimated as 80 to 120 years old, PICO overstory or understory small trees (22.9 to 40.5 cm d.b.h.)

1 Estimated as < 80 years old, PICO overstory or understory seedling/saplings, poles (< 22.9 cm d.b.h.)

Host patch connectivitya 3 > 50 percent of the area within a 1-hm radius of host patch boundaries is host type

2 30 to 50 percent of the area within a 1-hm radius of host patch boundaries is host type

1 < 30 percent of the area within a 1-hm radius of host patch boundaries is host type

a

 Connectivity was computed for host patches with PICO. Using a 1-hm radius (1 hm = 100 m), we assumed that LPDM seeds would have the ability

to spread disease to adjacent patches with high probability when hosts were within the 1-hm radius. Beyond this radius, we assumed that dispersal

opportunities including occasional seed dispersal by birds were insignificant.
30

Figure 8Historical and current vegetation vulnerability to (A) western larch dwarf mistletoe disturbance in subwatershed

0202 in the Swan subbasin of the Northern Glaciated Mountains Ecological Reporting Unit, (B) Armillaria root disease

disturbance in subwatershed 20 in the Kettle subbasin of the Northern Glaciated Mountains Ecological Reporting Unit.
31

Native true firs other than grand and white fir, Engelmann spruce, and western hemlock often develop

severe butt rot associated with either S-group annosum

root disease or laminated root rot, especially when they

are infected as large trees. Mountain hemlock is also

highly vulnerable to butt rot and mortality effects of

laminated root rot. Increased S- and P-group annosum

root disease incidence and severity is correlated with

increased selective harvest activity (Schmitt and others

1991). New centers of disease are initiated when freshly

cut stump surfaces are infected by spores of either

host-specialized variant. P-group annosum root disease mortality is most prevalent on hot, dry climax

ponderosa pine sites (Goheen and Goheen 1989).

Ponderosa pine is commonly infected on more

productive ponderosa pine sites within the Douglasfir and grand fir zones, but mortality is infrequent

except in drought years or during prolonged droughts

when tree vigor is depressed. In general, root disease

mortality produces abundant gaps in host forest canopies, and mosaics of dead, dying, and symptomless

trees and tree groups. In the Douglas-fir, grand fir, and

white fir zones, this gradual and continuous thinning

favors release and regeneration of additional vulnerable

shade-tolerant trees.

Mapping vulnerability to root diseasesLandscape

vulnerability to root disease disturbance is correlated

with site quality, host abundance, pathogen distribution,

host size and age, patch (stand) density and structure,

logging disturbance history, host vigor, and connectivity

of host patches. Vulnerability to Armillaria root disease

(AROS), laminated root rot (PHWE), and S- and Pgroup annosum root disease (HEANs

 and HEANp)

disturbances was attributed to all forested vegetation

patches; those containing no host species in either the

overstory or understory were given the lowest score

for each factor where host was identified. Vulnerability

factors for the four root disease disturbances were

(1) site quality, (2) host abundance, (3) canopy structure,

(4) host age, (5) disturbance history by using visible

logging entry, and (6) connectivity of host patches.

Tables 15-18 display vulnerability factors for AROS,

PHWE, HEANs

, and HEANp disturbances, respectively, and criteria for rating vegetation polygons for

each factor.

Patch vulnerability ratings for AROS and PHWE root

disease disturbances were collapsed into vulnerability

classes as follows: low for patches with a composite

rating of 5 to 8; moderate for patches rated 9 to 11;

and high for patches rated 12 and above. Patch

vulnerability ratings for HEANs and HEANp root

disease disturbances were collapsed into slightly

different vulnerability classes: low for patches with a

composite rating of 6 to 9; moderate for patches rated

10 to 12; and high for patches rated 13 and above.

Vulnerability classes were used to characterize change

in area and connectivity of area vulnerable to each root

disease disturbance between historical and current

vegetation conditions of subwatersheds of a pooling

stratum. Figure 8B illustrates expanded area vulnerable

to AROS disturbance in a subwatershed of the Kettle

subbasin. Figure 9A illustrates expanded area vulnerable

to PHWE disturbance in a subwatershed of the Upper

Deschutes subbasin. Figure 9B illustrates expanded area

vulnerable to HEANs disturbance in a subwatershed of

the Snake Headwaters subbasin.

Butt Rots

Tomentosus root and butt rotThe fungus Inonotus

tomentosus causes a root and butt rot common on

spruces and is occasionally reported on most western

coniferous species. Local intertree spread is via mycelial

extension between diseased and healthy roots, and by

ectotrophic or surface growth on roots. Long-distance

spread occurs via spores. The fungus acts as a nibbler

on root systems of most conifers, causing both localized

and extensive root and butt decay. But, on spruces, root

and butt decay can be quite spectacular. Severely

affected trees are predisposed to windthrow

or collapse especially on moist sites. Wind-thrown or

collapsed spruce are almost immediately colonized

by the spruce beetle. In moist to wet soils, Engelmann

spruce tends to exhibit a shallow pancake rooting

habit. Significant windthrow in mature spruce patches

often is predicated on initial windthrow of trees with

root disease.

Text continues on page 37.
32

Table 15—Criteria for rating forest vegetation patch vulnerability to Armillaria root disease

(AROS) disturbance in the midscale assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site qualitya 3 Cool-moist PSME/ABGR(ABCO); cool-moist ABLA2/PIEN; cool-moist

TSHE/THPL sites

2 Warm-dry PSME/ABGR(ABCO); warm-dry ABLA2/PIEN; warm-dry

TSHE/THPL sites

1 Other sites

Host abundanceb 3 > 50 percent crown cover in host species

2 30 to 50 percent crown cover in host species

1 < 30 percent crown cover in host species, or other

Canopy structure 3 2 or more layers PSME or ABGR(ABCO) or ABLA2/PIEN; or 2 or more

mixed-species layers with PSME or ABGR(ABCO) or ABLA2/PIEN in both layers

2 1 layer PSME or ABGR(ABCO) or ABLA2/PIEN

1 1 mixed-species layer with PSME or ABGR(ABCO) or ABLA2/PIEN

Host agec 3 Estimated as > 120 years old, overstory or under story PSME, ABGR(ABCO),

ABAM, ABMA, ABPR, PIEN, PIPO, PIMO, PILA, TSHE/THPL, CADE or

LAOC large trees (> 63.5 cm d.b.h.), or overstory or understory ABLA2, PICO,

or TSME medium and large trees (> 40.6 cm d.b.h.)

2 Estimated as 80 to 120 years old, overstory or understory PSME, ABGR(ABCO),

ABAM, ABMA, ABPR, PIEN, PIPO, PIMO, PILA, TSHE/THPL, CADE or

LAOC medium trees (40.6 to 63.5 cm d.b.h.), or overstory or understory ABLA2,

PICO, or TSME small trees (22.9 to 40.5 cm d.b.h.)

1 Estimated as < 80 years old overstory or understory PSME, ABGR(ABCO), ABAM,

ABMA, ABPR, PIEN, PIPO, PIMO, PILA, TSHE/THPL, CADE or LAOC

seedling/sapling, pole, or small trees (< 40.6 cm d.b.h.), or overstory or understory

ABLA2, PICO, or TSME seedling/sapling, or pole trees (< 22.9 cm d.b.h.)

Host patch connectivityd 3 > 50 percent of the area within a 1-hm radius of host patch boundaries is host type

2 30 to 50 percent of the area within a 1-hm radius of host patch boundaries is

host type

1 < 30 percent of the area within a 1-hm radius of host patch boundaries is host type

a

 McDonald (1990, 1991) reports that in Idaho and Montana, mortality effects associated with Armillaria root disease (NABS I) were more likely expressed

on sites of intermediate productivity (mesic sites), and rarely expressed on dry or wet sites.

b

 All conifers are host to Armillaria ostoyae, but some are more susceptible than others. Differences in susceptibility to infection were captured by weighting

host abundance. When hosts were PSME, ABGR(ABCO), or ABLA2/PIEN, the host abundance weighting factor was 1.5. When hosts were PIPO,

PICO, PIMO, PILA, ABAM, ABPR, ABMA, and TSHE/THPL, TSME the host abundance weighting factor was 1.0. When hosts were other than these,

the host abundance weighting factor was 0.5.

c

 Host age was primarily used as a vulnerability factor for AROS because patch structural and compositional attributes are more vulnerable to change as a

consequence of root disease disturbance when hosts are large than when hosts are small. Host age differences also were estimated to incorporate a measure

of patch vulnerability as a function of inoculum potential. Large infected host trees, whether living or dead, will persist as viable infectious inoculum

longer than smaller trees, thereby potentially bridging the disease to subsequent generations of vulnerable trees. Older trees of some species, not including

PSME or ABGR(ABCO), are also more vulnerable to damage by AROS than younger trees.

d

 Connectivity was computed for patches with PSME, ABGR(ABCO), PIPO, PICO, PIMO, PILA, ABAM, ABPR, ABMA, TSHE/THPL, ABLA2/PIEN,

TSME, LAOC, or CADE. Using a 1-hm radius (1 hm = 100 m), we assumed that vegetative spread of AROS to adjacent patches would occur with high

probability when areas of hosts were within the 1-hm radius. Beyond this radius, we assumed that dispersal opportunities by vegetative spread or spore

infection were insignificant.
33

Table 16—Criteria for rating forest vegetation patch vulnerability to laminated root rot (PHWE)

disturbance in the midscale assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site quality 3 Cool-moist PSME/ABGR(ABCO); cool-moist ABLA2/PIEN; TSME; cool-moist

TSHE/THPL sites

2 Warm-dry PSME/ABGR(ABCO); warm-dry ABLA2/PIEN; warm-dry

TSHE/THPL; ABAM sites

1 Other sites

Host abundancea 3 > 50 percent crown cover in host species

2 30 to 50 percent crown cover in host species

1 < 30 percent crown cover in host species, or other

Canopy structure 3 2 or more layers of PSME or ABGR(ABCO) or TSME; or 2 or more mixed-species

layers with PSME or ABGR(ABCO) or TSME

2 1 layer PSME or ABGR(ABCO) or TSME

1 1 mixed-species layer with PSME or ABGR(ABCO) or TSME

Host ageb 3 Estimated as > 120 years old, overstory or understory PSME or ABGR(ABCO) or

ABAM or ABMA or ABPR or PIEN or PIPO or PIMO or PILA or TSHE/THPL

or CADE or LAOC large trees (> 63.5 cm d.b.h.), or ABLA2 or PICO or TSME

medium and large trees (> 40.6 cm d.b.h.)

2 Estimated as 80 to 120 years old, overstory or understory PSME or ABGR(ABCO)

or ABAM or ABMA or ABPR or PIEN or PIPO or PIMO or PILA or

TSHE/THPL or CADE or LAOC medium trees (40.6 to 63.5 cm d.b.h.), or

ABLA2 or PICO or TSME small trees (22.9 to 40.5 cm d.b.h.)

1 Estimated as < 80 years old, overstory or understory PSME or ABGR(ABCO) or

ABAM or ABMA or ABPR or PIEN or PIPO or PIMO or PILA or TSHE/THPL

or CADE or LAOC seedling, sapling, pole, or small trees (< 40.5 cm d.b.h.), or

ABLA2 or PICO or TSME seedlings, saplings, or poles (< 22.9 cm d.b.h.)

Host patch connectivityc 3 > 50 percent of the area within a 1-hm radius of host patch boundaries is host type

2 30 to 50 percent of the area within a 1-hm radius of host patch boundaries is

host type

1 < 30 percent of the area within a 1-hm radius of host patch boundaries is host type

a

 All conifers are host to Phellinus weirii, but differences in susceptibility to infection and mortality effects are well documented (Filip and Schmitt 1979,

Hadfield and others 1986, Hadfield and Johnson 1977). When hosts were PSME, ABGR(ABCO), or TSME, the host abundance weighting factor was 1.5.

When hosts were ABAM, ABPR, ABMA, TSHE/THPL, ABLA2/PIEN, or LAOC, the host abundance weighting factor was 1.0. When hosts were other

than these, host abundance weighting was 0.5.

b

 Host age was used as a vulnerability factor for PHWE because patch structural attributes are more vulnerable to change as a consequence of root disease

disturbance when hosts are large than when hosts are small. Host age differences also were estimated to incorporate a measure of patch vulnerability as a

function of inoculum potential. Large infected host trees, whether living or dead, will persist as viable infectious inoculum longer than smaller trees,

thereby potentially bridging the disease to subsequent generations of vulnerable trees.

c

 Connectivity was computed for patches with PSME, ABGR(ABCO), ABAM, ABPR, ABMA, TSHE/THPL, ABLA2/PIEN, or TSME. Using a 1-hm

radius (1 hm = 100 m), we assumed that vegetative spread of PHWE to adjacent patches would occur with high probability when hosts were within the

1-hm radius. Beyond this radius, we assumed that dispersal opportunities by vegetative spread or spore infection were insignificant.
34

Table 17—Criteria for rating forest vegetation patch vulnerability to S-group annosum (HEANs)

root disease disturbance in the midscale assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site quality 3 Cool-moist PSME/ABGR(ABCO); cool-moist ABLA2/PIEN; cool-moist

TSHE/THPL; TSME; ABAM; ABMA sites

2 Warm-dry PSME/ABGR(ABCO); warm-dry TSHE/THPL; warm-dry

ABLA2/PIEN sites

1 Other sites

Host abundancea 3 > 50 percent crown cover in host species

2 30 to 50 percent crown cover in host species

1 < 30 percent crown cover in host species, or other

Canopy structureb 3 2 or more layers host species; or 2 or more mixed-species layers with host species

2 1 layer with host species

1 1 mixed-species layer with host species

Host agec 3 Estimated as > 120 years old, overstory or understory ABGR(ABCO), PSME

(Idaho and Montana subbasins only), ABAM, ABMA, ABPR, PIEN or

TSHE/THPL large trees (> 63.5 cm d.b.h.), or overstory or understory ABLA2

or TSME medium and large trees (> 40.6 cm d.b.h.)

2 Estimated as 80 to 120 years old, overstory or understory ABGR(ABCO), PSME

(Idaho and Montana subbasins only), ABAM, ABMA, ABPR, PIEN or

TSHE/THPL medium trees (40.6 to 63.5 cm d.b.h.), or overstory or understory

ABLA2 or TSME small trees (22.9 to 40.5 cm d.b.h.)

1 Estimated as < 80 years old, overstory or understory ABGR(ABCO), PSME

(Idaho and Montana subbasins only), ABAM, ABMA, ABPR, PIEN, TSHE/THPL

seedling/saplings, poles, small trees (< 40.5 cm d.b.h.), or overstory or understory

ABLA2 or TSME seedling/saplings, poles (< 22.9 cm d.b.h.)

Logging disturbance 3 Selective harvest visible with hosts present history

2 Regeneration harvest (including patch clearcutting) or commercial thinning visible

with hosts present

1 No visible logging entry, or other

Host patch connectivityd 3 > 50 percent of the area within a 1-hm radius of host patch boundaries is host type

2 30 to 50 percent of the area within a 1-hm radius of host patch boundaries is

host type

1 < 30 percent of the area within a 1-hm radius of host patch boundaries is host type

a

 True firs, hemlocks, Douglas-fir (Idaho and Montana subbasins only), and spruces are host to S-group Heterobasidion annosum. When hosts were

ABGR(ABCO), PSME (Idaho and Montana subbasins only), ABLA2/PIEN, ABAM, or TSME, the host abundance weighting factor was 1.5. When

hosts were ABPR, ABMA, and TSHE/THPL, the host abundance weighting factor was 1.0. When hosts were other than these, the host abundance

weighting factor was 0.5.

b

 Hosts were ABGR (ABCO), PSME (Idaho and Montana subbasins only), ABLA2/PIEN, ABAM, ABPR, ABMA, TSME, and TSHE/THPL.

c

 Host age was used as a vulnerability factor for HEANs because patch structural attributes are more vulnerable to change as a consequence of root disease

disturbance when hosts are large than when hosts are small. Host age differences also were estimated to incorporate a measure of patch vulnerability as a

function of inoculum potential. Large vulnerable trees, whether living or dead, will persist as viable infectious inoculum longer than smaller trees, thereby

potentially bridging the disease to subsequent generations of vulnerable trees.

d

 Connectivity was computed for host patches with ABGR(ABCO), PSME (Idaho and Montana subbasins only), ABAM, ABPR, ABMA, TSHE/THPL,

ABLA2/PIEN, or TSME. Using a 1-hm radius (1 hm = 100 m), we assumed that vegetative spread of HEANs

 to adjacent patches would occur with high

probability when hosts were within the 1-hm radius. Beyond this radius, we assumed that dispersal opportunities by vegetative spread or spore infection

were insignificant. Because spore infection of freshly cut stumps and injured trees is a common occurrence, this estimate of connectivity may be highly

conservative. Patch-specific data on harvest history and borax treatment of stumps for all sampled subwatersheds, were unavailable. Logging disturbance

was photo-interpreted, but we assumed occurrence was underestimated.
35

Table 18—Criteria for rating forest vegetation patch vulnerability to P-group annosum (HEANp)

root disease disturbance in the midscale assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site quality 3 PIPO sites

2 Warm-dry PSME/ABGR(ABCO) sites

1 Other sites

Host abundance 3 > 50 percent crown cover in PIPO

2 30 to 50 percent crown cover in PIPO

1 < 30 percent crown cover in PIPO, or other

Canopy structure 3 2 or more layers of PIPO, or 2 or more mixed-species layers with PIPO

2 1 layer PIPO

1 1 mixed-species layer with PIPO

Host agea 3 Estimated as > 120 years old, PIPO large trees (> 63.5 cm d.b.h.)

2 Estimated as 80 to 120 years old, PIPO medium trees (40.6 to 63.5 cm d.b.h.)

1 Estimated as < 80 years old, PIPO seedling, sapling, pole, or small trees

(< 40.5 cm d.b.h.)

Logging disturbance 3 Selective harvest visible with hosts present history

2 Regeneration harvest (including patch clearcutting) or commercial thinning visible

with hosts present

1 No visible logging entry, or other

Host patch connectivityb 3 > 50 percent of the area within a 1-hm radius of host patch boundaries is host type

2 30 to 50 percent of the area within a 1-hm radius of host patch boundaries is

host type

1 < 30 percent of the area within a 1-hm radius of host patch boundaries is host type

a

 Host age was used as a vulnerability factor for HEANp because patch structural attributes are more vulnerable to change as a consequence of root disease

disturbance when hosts are large than when hosts are small. Host age differences also were estimated to incorporate a measure of patch vulnerability as a

function of inoculum potential. Large vulnerable trees, whether living or dead, will persist as viable infectious inoculum longer than smaller trees, thereby

potentially bridging the disease to subsequent generations of vulnerable trees.

b

 Connectivity was computed for patches with PIPO. Using a 1-hm radius (1 hm = 100 m), we assumed that vegetative spread of HEANp to adjacent

patches would occur with high probability when hosts were within the 1-hm radius. Beyond this radius, we assumed that dispersal opportunities by

vegetative spread or spore infection were insignificant. Because spore infection of freshly cut stumps and injured trees commonly occurs, this estimate

of connectivity may be highly conservative. Patch-specific data on harvest history and borax treatment of stumps for all sampled subwatersheds, were

unavailable. Logging disturbance was photo-interpreted, but we assumed occurrence was underestimated.
36

Figure 9Historical and current vegetation vulnerability to (A) laminated root rot disturbance in subwatershed 30 in the Upper Deschutes subbasin of the

Southern Cascades Ecological Reporting Unit, (B) S-group annosum root disease disturbance in subwatershed 0305 in the Snake Headwaters subbasin of

the Snake Headwaters Ecological Reporting Unit.
37

Table 19—Criteria for rating forest vegetation patch vulnerability to tomentosus root and butt rot

(TRBR) root disease disturbance in the midscale assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Host abundance 3 > 50 percent crown cover in PIEN

2 30 to 50 percent crown cover in PIEN

1 Other spp. or < 30 percent crown cover in PIEN

Host age 3 Estimated as > 120 years old, PIEN large trees (> 63.5 cm d.b.h.)

overstory or understory

2 Estimated as 80 to 120 years old, PIEN medium trees (40.6 to

63.5 cm d.b.h.) overstory or understory

1 Estimated as < 80 years old, PIEN small trees (22.9 to

40.5 cm d.b.h.) overstory or understory

Topographic setting 3 Valley bottom settings (toe-slopes to valley bottoms) with hosts present

1 Other settings

Host patch connectivitya 3 > 50 percent of the area within a 1-hm radius of host patch boundaries

is host type

2 30 to 50 percent of the area within a 1-hm radius of host patch

boundaries is host type

1 < 30 percent of the area within a 1-hm radius of host patch

boundaries is host type

a

 Connectivity was computed for host patches with PIEN. Using a 1-hm radius (1 hm = 100 m), we assumed that vegetative spread of TRBR to adjacent

patches would occur with high probability when hosts were within the 1-hm radius. Beyond this radius, we assumed that dispersal opportunities were

insignificant.

Mapping vulnerability to tomentosus root and butt

rotLandscape vulnerability to tomentosus root and

butt rot (TRBR) disturbance is correlated with host

abundance, pathogen distribution, topographic setting,

host size and age, and connectivity of host patches. Site

quality is not included because most patches of older

spruce, regardless of site quality, appear to be affected

by this disease. Vulnerability to TRBR disturbance

was attributed to all forested vegetation patches; those

containing no spruce in either the overstory or understory were given the lowest score for each factor where

host was identified. The TRBR host in this analysis was

PIEN. Vulnerability factors for TRBR disturbance were

(1) host abundance, (2) host age, (3) topographic setting

by using the riparian status attribute, and (4) connectivity of host patches. Table 19 displays vulnerability

factors for TRBR disturbance and criteria for rating

vegetation polygons for each factor.

Patch vulnerability ratings for TRBR disturbance were

collapsed into vulnerability classes as follows: low for

patches with a composite rating of 4 to 6; moderate for

patches rated 7 to 8; and high for patches rated 9 and

above. Vulnerability classes were used to characterize

change in area and connectivity of area vulnerable to

TRBR disturbance between historical and current

vegetation conditions of subwatersheds of a pooling

stratum.
38

Table 20—Criteria for rating forest vegetation patch vulnerability to Schweinitzii root and butt rot

(SRBR) root disease disturbance in the midscale assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site quality 3 Cool-moist PSME/ABGR(ABCO); cool-moist TSHE/THPL; ABAM; ABMA;

cool-moist ABLA2/PIEN; TSME sites

2 Warm-dry ABLA2/PIEN; warm-dry PSME/ABGR(ABCO); warm-dry

TSHE/THPL sites

1 Other sites

Host abundancea 3 > 50 percent crown cover in host species

2 30 to 50 percent crown cover in host species

1 < 30 percent crown cover in host species, or other

Host age 3 Estimated as > 120 years old, overstory or understory PSME, LAOC, PIPO,

or PIEN large trees (> 63.5 cm d.b.h.), or PICO medium and large trees

(> 40.6 cm d.b.h.)

2 Estimated as 80 to 120 years old, overstory or understory PSME, LAOC, PIPO,

or PIEN medium trees ( 40.6 to 63.5 cm d.b.h.), or PICO small trees

(22.9 to 40.5 cm d.b.h.)

1 Estimated as < 80 years old, overstory or understory PSME, LAOC, PIPO, or

PIEN seedling, sapling, pole, or small trees (< 40.6 cm d.b.h.), or PICO seedling,

sapling, or pole trees (<22.9 cm d.b.h.)

Host patch connectivityb 3 > 50 percent of the area within a 1-hm radius of host patch boundaries is host type

2 30 to 50 percent of the area within a 1-hm radius of host patch boundaries is

host type

1 < 30 percent of the area within a 1-hm radius of host patch boundaries is host type

a

 All conifers are host to Phaeolus schweinitzii, but some species are more susceptible to infection and tree collapse than others. When hosts were PSME or

LAOC, the host abundance weighting factor was 1.5. When hosts were PIPO, PIEN, and PICO, the host abundance weighting factor was 1.0. When hosts

were other than these, the host abundance weighting factor was 0.5.

b

 Connectivity was computed for patches with PSME, LAOC, ABGR(ABCO), PIPO, PICO, PIMO, PILA, ABAM, ABPR, ABMA, TSHE/THPL,

ABLA2/PIEN, or TSME. Using a 1-hm radius (1 hm = 100 m), we assumed that SRBR would spread to adjacent patches with high probability when

hosts were within the 1-hm radius. Beyond this radius, we assumed that dispersal opportunities were insignificant.

Schweinitzii root and butt rotThe fungus Phaeolus

schweinitzii causes an important root and butt rot

(Schweinitzii root and butt rotalso called brown

cubical butt rot) of western larch, Douglas-fir,

ponderosa pine, Engelmann spruce, lodgepole pine,

and occasionally most other western conifers. Over

several centuries, ongoing tree collapse associated with

this pathogen has been responsible for significant

structural and compositional change of patches and

landscapes dominated by hosts. Local intertree spread

is slow, occurring via mycelial extension through duff

between diseased and healthy roots. Long-distance

spread occurs via spore infections of recent scars,

especially fire scars. In its primary hosts, the fungus

causes an extensive decay of the roots and butt. Butt

decay may extend 6 to 9 m or more up the bole.

Severely affected trees are predisposed to collapse,

breaking off in a characteristic barber-chair fashion.

Wind-thrown or collapsed trees often are colonized by

bark beetles native to each host. In the case of western

larch, which lacks primary bark beetle associates, the

Douglas-fir beetle occasionally colonizes recent windthrown or collapsed larch.

Mapping vulnerability Schweinitzii root and butt rot

Landscape vulnerability to Schweinitzii root and butt rot

(SRBR) disturbance is correlated with site quality, host

abundance, pathogen distribution, host size and age,

and connectivity of host patches. Vulnerability to SRBR

disturbance was attributed to all forested vegetation

patches; those containing no host species in either the

overstory or understory were given the lowest score for

each factor where host was identified. Schweinitzii root

and butt rot hosts in this analysis were LAOC, PSME,

PIPO, PIEN, and PICO. Vulnerability factors for SRBR

disturbance were (1) site quality, (2) host abundance, (3)

host age, and (4) connectivity of host patches. Table 20

displays vulnerability factors for SRBR disturbance, and

criteria for rating vegetation polygons for each factor.
39

Patch vulnerability ratings for SRBR disturbance were

collapsed into vulnerability classes as follows: low for

patches with a composite rating of 4 to 6, moderate for

patches rated 7 to 8, and high for patches rated 9 and

above. Vulnerability classes were used to characterize

change in area and connectivity of area vulnerable to

SRBR disturbance between historical and current

vegetation conditions of subwatersheds of a pooling

stratum. Figure 10A illustrates expanded area vulnerable to SRBR disturbance in a subwatershed of

the Burnt subbasin.

Rusts

White pine blister rustSince its introduction into

North America in the early part of this century (1909-

10), the fungus that causes white pine blister rust

(Cronartium ribicola) has devastated native five-needle

pines throughout their ranges. Throughout the basin,

western white pine, sugar pine and whitebark pine

have been significantly impacted. The blister rust is

macrocyclic (has a long life cycle including five separate

spore stages) and heteroecious, completing its life cycle

on two different types of hostsfive-needle pines and

native currants (Ribes spp.). Effects of the rust on native

five-needle pines are primarily mortality and topkilling,

although some genotypes of native five-needle pines

exhibit resistance. Bark beetles are frequently involved

in the demise of trees with bole infections. Monnig

and Byler (1992) estimated that in the West (Idaho and

Montana5

), about 90 percent of the western white pine

have been killed by the fungus to date. Efforts to reintroduce western white and sugar pines are ongoing

via the deployment of genetically resistant stock.

Whitebark pine is also severely damaged throughout

its range, but efforts to select and deploy genetically

resistant whitebark pine stock have been minimal to

date. This is perhaps because of a combination of

factors: a lack of public awareness of the current plight

of whitebark pine; little commercial value of the species, and limited access to whitebark pine forests (Keane

and Arno 1993)whitebark pine is a subalpine species

occurring primarily in high-elevation wilderness settings.

Mapping vulnerability to white pine blister rust

Vulnerability to white pine blister rust (WPBR)

disturbance was attributed to all forested vegetation

patches; those containing no hosts in either the understory or overstory were given the lowest score for each

factor where host was identified. Hosts of WPBR are

western white pine (PIMO), sugar pine (PILA), and

whitebark pine (PIAL). Two types of WPBR vulnerability were evaluated: type 1 vulnerability of PIMO

and PILA, and type 2 vulnerability of PIAL. Three

vulnerability factors were used to attribute patch

vulnerability to types 1 and 2 WPBR disturbance:

(1) site quality, (2) host abundance, and (3) host size.

Tables 21 and 22 display type 1 and 2 WPBR vulnerability factors and criteria for rating vegetation polygons for each factor, respectively.

Type 1 and type 2 WPBR patch vulnerability ratings

were collapsed into vulnerability classes as follows:

low for patches with a composite rating of 3 to 4,

moderate for patches rated 5 to 6, and high for patches

rated 7 and above. Vulnerability classes were used to

characterize change in area and connectivity of area

vulnerable to type 1 and type 2 WPBR disturbance

between historical and current vegetation conditions

of subwatersheds of a pooling stratum. Figure 10B

illustrates reduced area vulnerable to type 1 WPBR

disturbance in a subwatershed of the Pend Oreille

subbasin.

Stem Decays

Rust-red stringy rotThe Indian paint fungus

(Echinodontium tinctorium) causes an important heartrot

of true firs and hemlocks (Tsuga spp.). Severe stem

decay reduces most of the heartwood to a rust-red

stringy rot. Live and dead trees with rotted heartwood

are important to cavity-excavating birds, and other

birds and small mammals for their soft, rotted interiors,

and for the arthropod prey species they house. Severely

decayed live trees collapse in high winds and under the

burden of heavy snow and ice accumulation. True firs

and hemlocks suppressed 40 years or more are most

vulnerable to infection. Windborne spores infect lateral

branchlet vascular traces of suppressed hosts. Infections

lie dormant until trees are injured. Common injuries

that initiate heartwood decay include logging injuries,

basal frost cracks, basal fire scalding, and bark beetle

strip attacks. In recent years, significant increase of this

defect in the grand fir, white fir, and subalpine fir zones

has been associated with effective fire exclusion and

selective harvest practices (Gast and others 1991,

Hessburg and others 1994), both of which encourage

regeneration and release of shade-tolerant true firs. 5

 Personal communication. 1996. Jim Byler, Group Leader. USDA Forest Service, Idaho Panhandle National Forests, 1201 Ironwood Drive,

Coeur dAlene, ID 83814.
40

Figure 10Historical and current vegetation vulnerability to (A) Schweinitzii root and butt rot disturbance in subwatershed 0901 in the Burnt subbasin

of the Blue Mountains Ecological Reporting Unit, (B) white pine blister rust type 1 disturbance in subwatershed 09 in the Pend Oreille subbasin of the

Northern Glaciated Mountains Ecological Reporting Unit.
41

Table 21—Criteria for rating forest vegetation patch vulnerability to type 1 white pine blister

rust (WPBR) disturbance of western white pine (PIMO) and sugar pine (PILA) in the midscale

assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site quality 3 ABAM; TSME; cool-moist TSHE/THPL; cool-moist ABLA2/PIEN sites

2 Warm-dry TSHE/THPL; ABMA; cool-moist PSME/ABGR(ABCO); warm-dry

ABLA2/PIEN sites

1 Other sites

Host abundance 3 > 50 percent crown cover in PIMO or PILA

2 30 to 50 percent crown cover in PIMO or PILA

1 Other spp. or < 30 percent crown cover in PIMO or PILA

Host sizea 3 Overstory or understory PIMO or PILA medium or large trees (> 40.6 cm d.b.h.)

2 Overstory or understory PIMO or PILA poles or small trees (12.7 to 40.5 cm d.b.h.)

1 Overstory or understory PIMO or PILA seedling/saplings, (< 12.7 cm d.b.h.)

a

 Host size was used as a vulnerability factor for WPBR because patch structural attributes are more vulnerable to change as a consequence of rust

disturbance when hosts are large than when hosts are small.

Table 22—Criteria for rating forest vegetation patch vulnerability to type 2 white pine blister

rust (WPBR) disturbance of whitebark pine (PIAL) in the midscale assessment of the interior

Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site quality 3 Warm-dry ABLA2/PIEN; cold-dry-harsh ABLA2/PIEN sites

2 TSME; ABMA; cool-moist ABLA2/PIEN sites

1 Other sites

Host abundance 3 > 50 percent crown cover in PIAL

2 30 to 50 percent crown cover in PIAL

1 <30 percent crown cover in PIAL, or other

Host sizea 3 Overstory or understory PIAL medium or large trees (> 40.6 cm d.b.h.)

2 Overstory or understory PIAL poles or small trees (12.7 to 40.5 cm d.b.h.)

1 Overstory or understory PIAL seedling-saplings, (< 12.7 cm d.b.h.)

a

 Host size was used as a vulnerability factor for WPBR because patch structural attributes are more vulnerable to change as a consequence of rust

disturbance when hosts are large than when hosts are small.
42

Mapping vulnerability to rust-red stringy rot

Vulnerability to RRSR disturbance was attributed

to all forested vegetation patches; those containing

no hosts in either the overstory or understory were

given the lowest score for each factor where host was

identified. Vulnerability factors for RRSR disturbance

were (1) site quality, (2) host abundance, (3) canopy

structure, (4) host age and (5) disturbance history by

using visible logging entry. Table 23 displays vulnerability factors for RRSR disturbance, and criteria for

rating vegetation polygons for each factor.

Table 23—Criteria for rating forest vegetation patch vulnerability to rust-red stringy rot (RRSR)

disturbance in the midscale assessment of the interior Columbia River basin

Patch

Vulnerability factor rating Rating criteria

Site quality 3 Cool-moist PSME/ABGR(ABCO); cool-moist TSHE/THPL; ABMA; TSME;

ABAM sites

2 Warm-dry PSME/ABGR(ABCO); cool-moist ABLA2/PIEN; warm-dry

TSHE/THPL sites

1 Other sites

Host abundancea 3 > 50 percent overstory and understory crown cover in host species

2 30 to 50 percent overstory and understory crown cover in host species

1 < 30 percent overstory and understory crown cover in host species, or other

Canopy structure 3 > 2 canopy layers

2 2 canopy layers

1 1 canopy layer

Host age 3 Estimated as > 120 years old, overstory or understory ABGR(ABCO), ABAM,

ABMA, ABPR, or TSHE/THPL large trees (> 63.5 cm d.b.h.), or ABLA2 or

TSME medium trees ( 40.6 to 63.5 cm d.b.h.)

2 Estimated as 80 to 120 years old, overstory or understory ABGR(ABCO), ABAM,

ABMA, ABPR or TSHE/THPL medium trees (40.6 to 63.5 cm d.b.h.), or ABLA2

or TSME small trees (22.9 to 40.5 cm d.b.h.)

1 Estimated as < 80 years old, overstory or understory ABGR(ABCO), ABAM,

ABMA, ABPR, or TSHE/THPL (22.9 to 40.5 cm d.b.h.) or ABLA2 or TSME

seedling, sapling, or pole trees (< 22.9 cm d.b.h.)

Logging disturbance 3 Selective harvest visible with hosts present history

2 Regeneration harvest (incl. patch clearcutting) or thinning (commercial or

recommercial) visible with hosts present

1 No visible logging entry

a

 RRSR hosts were ABGR(ABCO), ABLA2, ABAM, ABMA, ABPR, TSHE, and TSME.

Patch vulnerability ratings for RRSR disturbance were

collapsed into vulnerability classes as follows: low for

patches with a composite rating of 5 to 8, moderate for

patches rated 9 to 12, and high for patches rated 13 and

above. Vulnerability classes were used to characterize

change in area and connectivity of area vulnerable to

RRSR disturbance between historical and current

vegetation conditions of subwatersheds of a pooling

stratum.
43

Acknowledgments

We thank Jim Byler, Paul Flanagan, Don Goheen,

Ellen Michaels Goheen, Jim Hadfield, Al Harvey,

Jim Hoffman, and Julie Weatherby for critical reviews

of an earlier draft of this paper. Their comments and

suggestions improved the modeling logic and its

presentation in this paper.

English Conversions

When you know: Multiply by: To find:

Centimeters (cm) 0.39370 Inches

Hectares (ha) 2.47105 Acres

Hectometers (hm) 328.08398 Feet

Kilometers (km) 3280.83989 Feet

Kilometers (km) 0.62137 Mile

Meters (m) 0.04971 Chain

Meters (m) 3.28084 Feet

Square meters (m2

) 10.76391 Square feet
44

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Appendix 1

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 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
48

Crown differentiation Degree of differentiation among overstory tree crowns. Estimated as low (< 30-percent

difference), moderate (30- to 100-percent difference), and high (> 100-percent difference). Visual templates are

provided below.

Low Moderate High

Canopy layers Estimated as 1, 2, or > 2 layers visible.

Riparian or wetland Indicated whether a patch resided within a riparian or wetland setting. Used with overstory

vegetation to estimate forest and nonforest riparian and wetland area.

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 (year-round saturated soils), alpine meadow, dry

meadow (seasonally saturated soils), 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 2 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, 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; Douglas-fir; grand fir

and/or white fir; Pacific silver fir; subalpine fir and/or Engelmann spruce; western hemlock and/or western redcedar;

mountain hemlock; whitebark pine and/or subalpine larch; 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; Douglas-fir 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
49

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 and/

or grand fir and/or white fir and/or Pacific silver fir; western hemlock and/or western redcedar; mountain hemlock;

subalpine fir and/or Engelmann spruce; 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 and/or subalpine larch; 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.

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, and/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 (exampleswildrye, bluebunch wheatgrass, Idaho fescue, alkali grass, bottlebrush squirreltail); annual grasses (examplescheatgrass, medusahead); seeded wheatgrasses (examplescrested

wheatgrass, other seeded dryland grasses); exotic forbs (examplesspotted knapweed, yellowstar thistle, leafy spurge);

native moist site herbs (examplessedges, rushes); low sagebrush (exampleslow sagebrush, salt desert shrub); low

alpine shrubs (examplesmeadow heathers); sagebrush and bitterbrush (examplesbasin big sagebrush, Wyoming

sagebrush, mountain big sagebrush, silver sagebrush, bitterbrush, rabbitbrush); mahoganies (examplesmountain and

curlleaf mahoganies); mountain shrubs (examplesserviceberry, rose, snowberry, Rocky Mountain maple, Scoulers

willow, buffaloberry, chokeberry, bittercherry); wet site shrubs (exampleswillow, alder, bog birch, dogwood);

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 similar in all attributes, 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 more than 66 percent cover.

Tree cover of herbland and shrubland types Tree cover was identified, where present, in herbland and shrubland

patches.

Source: Hessburg and others 1999.
50Appendix 2

Table 24—Living and dead vegetation structure commonly associated with major insect disturbances of forest vegetation in the interior Columbia River basin

Tree Estimated snag Shrub

sizes residence time (yr)c Bark Channelizing understory

Insect Primary factors affected Down Hard Soft Structure in beetle invertebrates development

spp.a influencing vulnerability Hostsa Effects (d.b.h.)b wood <20 20-50 >50d snagsc snagsc living or dead treese assoc. associatesf encouraged

Centimeters

WSB and Hosts occurring over PSMEg Tree < 12.7 Minorh + —— + —i — ++ +

DFTM large (> 404.7 ha) ABGR mortality 12.7-22.6 + + — — + + — + + +

contiguous areas; ABCO 22.7-40.5 + + — — + + — + + +multilayered host ABLA2 40.6-63.5 + + +j —+ + — + + +

canopies; outbreaks ABAM > 63.5 + + + +j ++ — + + +

are typically initiated ABPR Topkilling < 12.7 Minor n/ak n/a n/a n/a n/a New top(s), spike top,l In dead In dead tops —

on warm, dry to PIEN 12.7-22.6 Minorh n/a n/a n/a n/a n/a stem crookm (potential tops —

mesic PSME, ABGR, 22.7-40.5 Minorh + — — + + nest platforms) —

or ABCO climax sites 40.6-63.5 + + +n — + + New top(s), toprot,o major In dead tops and

> 63.5 + + + +n + + stem crook, or snag top toprotted area +

(potential nest platforms)

DFB Warm, dry to mesic PSME Tree 22.7-40.5 + + — — + + — + + +

PSME, ABGR, and mortality 40.6-63.5 + + + — + + — + + +ABCO climax sites; > 63.5 + + + + + + — + + +abundant mediumand large fire-killed, Topkilling 40.6-63.5 + + + — + + New top(s), toprot, major In dead In dead tops +wind-thrown, stem crook, or snag top tops and toprotted areastressed, injured, or > 63.5 + + + + + + (potential nest platforms) +diseased hosts Bole strip 22.7-40.5 Minor + — — + + Mainstem saprot,p In strip- In strip-attacked —

are needed to initiate attackq 40.6-63.5 Minor + + — + + heartrot,r and dead attacked and heartrotted —

an outbreak branches associated area area —

> 63.5 Minor + + + + + with strip-attacked length

of bole

WPB Warm to hot dry PIPO Tree 22.7-40.5 + + — — + + — + + —

type 1 sites; abundant mortality 40.6-63.5 + + + — + + — + + —

medium to largePIPO; stressed, > 63.5 + + + + + + — + + —injured, or severely Topkilling 40.6-63.5 + + + + + + New top(s), toprot, major In dead In dead tops and —

diseased hosts are stem crook, or snag top tops toprotted areaneeded to initiate > 63.5 + + + + + + (potential nest platforms)an outbreak Bole strip 22.7-40.5 Minor + — — + + Mainstem saprot, heartrot In strip- In strip-attacked —

attack 40.6-63.5 Minor + + — + + and dead branches attack and heartrotted —

> 63.5 Minor + + + + + associated with strip- area area

attacked length of bole —
51

WPB Warm, dry sites; PIPO Tree 12.7-22.6 + + — — + + — + + +

type 2 abundant pole and mortalityand small PIPO growing 22.7-40.5 + + — — + + — + + +MPB in dense thickets or Topkilling 22.7-40.5 + + — — + + New top(s), toprot, stem In dead Indead tops and —

type2 stands; stressed or crook (potential nest tops toprotted area

injured hosts are platforms, roosts)needed to initiatean outbreak Bole strip 12.7-22.6 Minor + — — + + Mainstem saprot, heartrot In strip- In strip-attacked —

attack and dead branches attacked and heartrotted

22.7-40.5 Minor + — — + + associated with strip- area area —

attacked length of bole

MPB Mesic and cool PICO Tree 12.7-22.6 + + — — + —i — ++ +

type1 sites; abundant mortality 22.7-40.5 + + — — + —i — ++ +

pole, small, and 40.6-63.5 + + + — + + — + + +medium PICO;stressed or injured > 63.5 + + + — + + — + + +hosts needed to (rare)initiate an outbreak Topkilling 22.7-40.5 Minor + + — + —i New top(s), spike top, In dead In dead tops —

stem crook potential tops nest platforms)

40.6-63.5 + + + — + + New top(s), toprot, major In dead tops and —> 63.5 + + + — + + stem crook, or snag top toprotted area(rare) (potential nest platforms) —

Bole strip 12.7-22.6 Minor + — — + — Mainstem saprot, heartrot In strip In strip attacked

attack 22.7-40.5 Minor + + — + + and dead branches attacked and heartrotted

40.6-63.5 Minor + + — + + associated with strip- area area

> 63.5 + + + — + + attacked length of bole(rare) —

FE Mesic and cool- ABGR Tree 12.7-22.6 + + — — + + — + + —

moist sites; ABCO mortality 22.7-40.5 + + — — + + — + + —abundant pole and ABLA2 40.6-63.5 + + + — + + — + + +larger true fir often ABAM > 63.5 + + + —s ++ — + + +

growing in dense ABPR Topkilling 22.7-40.5 Minor + — — + + New top(s), spike top, stem In dead In dead tops —

layered stands; ABMA crook (potential nest topsstressed, injured, or platforms)diseased hosts 40.6-63.5 + + + — + + New top(s), toprot, major In dead tops and —needed to initiate stem crook or snag top toprotted areaan outbreak > 63.5 + + + + + + (potential nest platforms) —

Bole strip 12.7-22.6 Minor + — — + — — In strip- In strip-attacked —

attack 22.7-40.5 Minor + + — + + Mainstem saprot, heart- attacked and heartrotted —

40.6-63.5 Minor + + + + + rot and dead branches area area

associated with strip- —

> 63.5 Minor + + + + + attacked length of bole —
52

Table 24—Living and dead vegetation structure commonly associated with major insect disturbances of forest vegetation in the interior Columbia River basin (continued)

Tree Estimated snag Shrub

sizes residence time (yr)c Bark Channelizing understory

Insect Primary factors affected Down Hard Soft Structure in beetle invertebrates developmentspp.a influencing vulnerability Hostsa Effects (d.b.h.)b wood <20 20-50 >50d snagsc snagsc living or dead treese assoc. associatesf encouraged

Centimeters

SB Cool-moist to wet PIEN Tree 22.7-40.5 + + — — + + — + + +

sites; abundant mortality 40.6-63.5 + + — — + + — + + +PIEN > 22.7 cm > 63.5 + + + — + + — + + +

d.b.h., fire-killed, Topkilling 22.7-40.5 Minor + — — + + New top(s), spike top, In dead In dead tops —

windthrown, stem crook topsstressed, diseasedor injured PIEN 40.6-63.5 + + + — + + New top(s), toprot, major In dead tops and —needed to initiate > 63.5 + + + + + + stem crook or sang top toprotted areaan outbreak Bole strip 22.7-40.5 Minor + + — + + Mainstem saprot, heartrot + In strip-attacked —

attack 40.6-63.5 Minor + + + + + and dead branches + land heartrotted —

associated with strip- area

> 63.5 Minor + + + + + attacked length of bole + —

a See table 3 for common and scientific names.b Size classes are seedlings and saplings < 12.7 cm d.b.h.; poles 12.7 to 22.6 cm d.b.h.; small trees 22.7 to 40.5 cm d.b.h.; medium trees 40.6 to 63.5 cm d.b.h.; large trees > 63.5 cm d.b.h.c Snags are defined as dead trees or partially dead trees with diameters 10.2 cm at d.b.h., and heights 1.8 m tall (sensu Thomas and others 1979); live trees with dead tops or exposed heartrot of the bole also function as snags and are included

here.

d Note that for each estimated residence time we assume continuous fall down of individuals within each size range, only a portion of the original population within a size range will persist; ABGR, ABCO, ABLA2, and ABAM decay and

fall down rapidly; these will be lost first; large PSME, THPL, LAOC, and PIPO will tend to have the highest residence times.

e Structures include forked or multiple tops, toprot associated with injuries to tree tops and subsequent infection by wound parasites, mainstem heartrot cavities, and dwarf mistletoe brooms.fChannelizing invertebrates noted here are primarily Cerambycid and Buprestid woodboring beetles (Coleoptera) and carpenter ants (Camponotus spp. /Hymenoptera).g Hosts in italics are primary hosts of the DFTM.h May be significant under extreme outbreak conditions.i Saprot occurs, but thin-barked, small-caliper stems and tops dry out quickly and typically do not function as soft snags.j Some snags will reside, especially when hosts are Douglas-fir.k Not applicable; snag tops will seldom meet the minimum size requirements.l A spike top is a small-diameter (< 12.2 cm) remnant of a former tree top that is retained when a lateral branch turns upward and becomes a new top. Spike tops are often embedded in stemwood of the new top and may be retained for

decades. Presence of a spike top usually indicates that a topkilling event occurred high in the crown. Larger diameter dead tops typically break out once decayed. Birds and small mammals often build nests between a spike top and the mainstem once a new top has developed.

m Stem crook describes the residual structure occurring after a new top develops adjacent to topkilling or breakage of a large-diameter ( 12.2 cm) top. Vertical displacement of the new top increases with increasing diameter of broken or killed

tops. When crooked stems display a significant horizontal component in the crook, and when crooks are associated with a spike top, birds or small mammals often use these as elevated platforms for nests.

n Some snag tops that meet the minimum size requirements will reside, especially when hosts are Douglas-fir.o Toprot often occurs in living trees that have been damaged by top breakage or a prior topkilling disturbance. Opportunistic wood decay fungi such as Fomitopsis pinicola and wound parasites such as F. officinalis and F. cajenderi invade the top

portion of the remaining live tree, decaying the heartwood. When a new top has developed, the heartwood of the new top and that occurring below the new top often is decayed, thereby making the toprotted area above and below thenew top vulnerable to re-injury by top breakage. Severely toprotted trees typically loose their top. Raptor stick nests are common on broken topped trees.

p Saprot describes fungal decay confined to the sapwood. Saprotting can begin once the vascular cambium associated with sapwood has been killed by insects, fungi, or injury. Some saprotting fungi are directly introduced by attacking bark

beetles (e.g., Cryptoporus volvatus). Others invade the sapwood once young adult beetles have emerged. In most cases, sapwood of recently killed trees, or of dead portions of living trees, is decayed within 3 or 4 years of cambial mortality.

q Bole strip attack is one of several consequences of bark beetle mass attack. Strip attack occurs when beetles systematically attack a vertical section or strip of the bole. Brood development is similarly confined to that vertical strip. Following

the strip attack, the strip-attacked section of the bole provides access to sapwood and heartwood decay fungi. Large-diameter trees with evidence of a prior strip attack event often will have significant heartrot associated with the stripattacked area. When the strip-attacked area is wide, or when the attacked tree is old and declining in vigor, the area of strip attack may never be enclosed by new sapwood and bark.

r Heartrot describes fungal decay of the heartwood. Many heartrotting fungal species are uniquely associated with heartwood substrates of living trees.s Some ABPR and ABMA snags will reside > 50 years.
53

Table 25—Living and dead vegetation structure commonly associated with major pathogen disturbances of forest vegetation in the interior Columbia River basin

Tree Estimated snag Shrub

Primary factors sizes residence time (yr)c Bark Channelizing understory

Insect influencing affected Down Hard Soft Structure-in beetle invertebrates developmentspp.a vulnerability Hostsa Effects (d.b.h.)b wood <20 20-50 >50d snagsd snagsd living or dead treese assoc. associatesf encouraged

Centimeters

DFDM Warm, dry sites; PSME Tree < 12.7 Minor + — — + — g Dead upright fine-structured +h + —

layered PSME mortality 12.7-22.6 + + — — + + mistletoe brooms +h + —stand 22.7-40.5 + + — — + + +h + —

40.6-63.5 + + + — + + Dead coarse-structured and +h + —

often massive mistletoe

> 63.5 + + + + + + brooms +h + —

Topkilling 22.7-40.5 Minor + + — + + Toprot,i large live mistletoe In dead In dead tops —

40.6-63.5 + + + + + + brooms, snag top topsh —

> 63.5 + + + + + + —

Growths < 12.7 — n/aj n/a n/a n/a n/a Live mistletoe brooms, — — —

loss 12.7-22.6 — n/a n/a n/a n/a n/a dense shrublike or tree — — —

22.7-40.5 Minork n/a n/a n/a n/a n/a — — —

40.6-63.5 Minor n/a n/a n/a n/a n/a Large upright or pendulous — — —> 63.5 Minor n/a n/a n/a n/a n/a mistletoe brooms — — —

WLDM Cool, moist sites; LAOC Tree 40.6-63.5 + + + + + + Lead upright fine-structured — — —

layered LAOC mortality > 63.5 + + + + + + mistletoe brooms — + —stands Topkilling 40.6-63.5 + + + + + + Toprot, fine-structured live — + —

> 63.5 + + + + + + mistletoe brooms, snag top — —

Growth < 12.7 — n/a n/a n/a n/a n/a Fine-structured live — In dead tops — loss 12.7-22.6 — n/a n/a n/a n/a n/a mistletoe brooms, tree — — —

22.7-40.5 — n/a n/a n/a n/a n/a growth form — — —40.6-63.5 — n/a n/a n/a n/a n/a — — —> 63.5 — n/a n/a n/a n/a n/a — — —

PPDM Warm, dry sites; PIPO Tree < 12.7 Minor + — — + —g Dead upright mistletoe +h + —

layered PIPO mortality 12.7-22.6 + + — — + + brooms +h + —stands 22.7-40.5 + + — — + + +h + —

40.6-63.5 + + + — + + Dead coarse-structured +h + —> 63.5 + + + + + + often massive uprignt

mistletoe brooms +h + —

Topkilling 22.7-40.5 Minor + + — + + Toprot, large live mistletoe Indead Indead tops —

40.6-63.5 + + + + + + brooms snag top topsh —

> 63.5 + + + + + + —

Growth < 12.7 — n/aj n/a n/a n/a n/a Live mistletoe brooms, — — —

 loss 12.7-22.6 — n/a n/a n/a n/a n/a dense shrublike or tree — — —

22.7-40.5 Minork n/a n/a n/a n/a n/a growth form — — —

40.6-63.5 Minor n/a n/a n/a n/a n/a Large upright and often — — —>63.5 Minor n/a n/a n/a n/a n/a massive mistletoe brooms — — —

Appendix 3
54

Table 25—Living and dead vegetation structure commonly associated with major pathogen disturbances of forest vegetation in the interior Columbia River basin (continued)

Tree Estimated snag Shrub

Primary factors sizes residence time (yr)c Bark Channelizing understory

Insect influencing affected Down Hard Soft Structure-in beetle invertebrates developmentspp.a vulnerability Hostsa Effects (d.b.h.)b wood <20 20-50 >50d snagsd snagsd living or dead treese assoc. associatesf encouraged

Centimeters

LPDM Cool, moist sites; PICO Tree 12.7-22.6 + + — — + —g Dead upright mistletoe +h +

layered PICO mortality broomsstands 22.7-40.5 + + — — + + Dead coarse-structured and +h + —

40.6-63.5 + + + — + + occasionally massive +h + —> 63.5 + + + — + + upright mistletoe brooms +h + —

Topkilling 22.7-40.5 Minor + + — + + Toprot, mistletoe brooms, +h In dead tops —

40.6-63.5 + + + — + + snag top +h —> 63.5 + + + — + + +h —

Growth < 12.7 — n/a n/a n/a n/a n/a Live upright, occasionally — — —

12.7-22.6 — n/a n/a n/a n/a n/a massive mistletoe brooms, — — —22.7-40.5 — n/a n/a n/a n/a n/a tree growth form — — —40.6-63.5 — n/a n/a n/a n/a n/a — — —> 63.5 — n/a n/a n/a n/a n/a — — —

AROS Hosts; layered PSME Tree < 12.7 Minor + — — + —g — ++ +

stands; viable ABGR mortality 12.7-22.6 + + — — + —g — ++ +inoculum ABCO 22.7-40.5 + + — — + + — + + +

present 40.6-63.5 + + + — + + — + + +

> 63.5 + + + — + + — + + +

Stressed hosts; PIEN Tree < 12.7 Minor + — — + —g — ++ +

viable inoculum ABLA2 mortalitypresent PICO 12.7-22.6 + + — — + + — + + +

TSHETSMEABAM 22.7-40.5 + + — — + + — + + +PILAPIPO 40.6-63.5 + + + — + + — + + +LAOCABPRPIMO > 63.5 + + + — + + — + + +ABMAPHWE

Hosts; viable PSME Tree < 12.7 Minor + — — + —g — ++ +

inoculum present ABGR mortality 12.7-22.6 + + — — + + — + + +present; ABCO 22.7-40.5 + + — — + + — + + +

TSME 40.6-63.5 + + + — + + — + + +

> 63.5 + + + — + + — + + +

Hosts, viable PSME Butt rot 40.6-63.5 + + + + + — <10.5 m of decayed With tree Often with With tree

inoculum ABGR and tree heartwood in the butt collapse carpenter ants colapse

present; mature ABCO collapse section of the bole in the decayedand older trees TSME (potential cavity butt

TSHE excavation sites)ABLA2
55

PIEN > 63.5 + + + + + — With treeABAM collapseABMAABPRLAOCPinus supp.

HEANS Mesic to cool, PSMEl Tree < 12.7 Minor + — — + —g — ++ +

moist sites; ABGR mortality 12.7-22.6 + + — — + —g — ++ +hosts; layered ABCOstands; viable ABLA2 22.7-40.5 + + — — + + — + + +inoculum 40.6-63.5 + + + — + + — + + +present; loggingentry > 63.5 + + + — + + — + + +

Hosts; viable PIEN Butt rot 40.6-63.5 + + + + + — < 4.9 m of decayed With tree Often with With tree

inoculum TSHE and tree heartwood in the butt collapse carpenter ants collapsepresent TSME section of the bole in the decayed

ABAM (potential cavity buttABMA > 63.5 + + + + + — excavation sites With treeABPR collapse

HEANP Warm to hot, dry PIPO Tree < 12.7 Minor + — — + —g — ++ +

sites; hosts; mortality 12.7-22.6 + + — — + + — + + +viable inoculum 22.7-40.5 + + — — + + — + + +present 40.6-63.5 + + + — + + — + + +

> 63.5 + + + + + + — + + +

TRBR Cool moist to wet PIEN Butt rot 40.6-63.5 + + + + + — < 4.9 m of decayed With tree Often with With tree

sites; hosts and and tree heartwood in the butt collapse carpenter ants in collapseviable inoculum collapse section of the bole the decayed buttpresent > 63.5 + + + + + — (potential cavity With tree

excavation sites) collapse

SRBR Mesic to cool PSME Butt rot 40.6-63.5 + + + + + — < 9.8 m of decayed With tree Often with With tree

moist to wet LAOC and tree heartwood in the butt collapse carpenter ants in collapsesites; hosts; PIPO collapse section of the bole the decayed buttviable inoculum PIEN (potential cavity With treepresent PICOm > 63.5 + + + + + — excavation sites) collapse

RRSR Mesic to cool ABGR Main stem 40.6-63.5 + + + + + — < 9.8 m of decayed With tree Often with With tree

moist sites; ABCO heartrot heartwood in the butt collapse carpenter ants in collapse

hosts present ABLA2 and mid- section of the bole the decayed buttand supressed ABAM or lower- (potential cavitymore than 40 ABPR stem excavation sites) With treeyears prior to TSHE collapse > 63.5 + + + + + — collapse

release; hosts TSMEinjured oncereleased
56

Table 25—Living and dead vegetation structure commonly associated with major pathogen disturbances of forest vegetation in the interior Columbia River basin (continued)

Tree Estimated snag Shrub

Primary factors sizes residence time (yr)c Bark Channelizing understory

Insect influencing affected Down Hard Soft Structure-in beetle invertebrates development

spp.a vulnerability Hostsa Effects (d.b.h.)b wood <20 20-50 >50d snagsd snagsd living or dead treese assoc. associatesf encouraged

Centimeters

WPBR Cool, moist sites; PIMO Tree < 12.7 Minor + — — + —g — ++ +

type 1 hosts present PILA mortality 12.7-22.6 + + — — + + — + + +

22.7-40.5 + + — — + + — + + +40.6-63.5 + + + — + + — + + +> 63.5 + + + — + + — + + +

Topkilling < 12.7 Minor — — — — — — + + —

12.7-22.6 Minor + — — + —g Short-term, small-diameter + + +22.7-40.5 + + — — + + snag top + + —40.6-63.5 + + + — + + Large-diameter snag top + + —

(potential cavity excavation

> 63.5 + + + — + + sites) + + —

WPBR Cool, moist to PIAL Tree < 12.7 Minor + — — + —g — ++ —

 type2 cold, harsh high mortality 12.7-22.6 + + — — + —g — ++ —

elevation sites; 22.7-40.5 + + + — + + — + + —hosts present 40.6-63.5 + + + + + + — + + —

> 63.5 + + + + + + — + + —

Topkilling < 12.7 Minor — — — — — — + + —

12.7-22.6 Minor + — — + —g Short-term, small-diameter + + —

22.7-40.5 + + + — + + snag top + + —40.6-63.5 + + + + + + Large-diameter snag top + + —> 63.5 + + + + + + (potential cavity excavation + + —

sites)

a See table 3 for common and scientific names.b Size classes are seedlings and saplings < 12.7 cm d.b.h.; poles 12.7 to 22.6 cm d.b.h.; small trees 22.7 to 40.5 cm d.b.h.; medium trees 40.6 to 63.5 cm d.b.h.; large trees > 63.5 cm d.b.h.c Note that for each estimated residence time we assume continuous fall down of individuals within each size range; only a portion of the original population within a size range will persist; ABGR, ABCO, ABLA2, and ABAM decay and fall

down rapidly; these will be lost first; large PSME, THPL, LAOC, and PIPO will tend to have the highest residence times.

d Snags are defined as dead trees or partially dead trees (e.g., dead tops or partially dead stems) with diameters 10.2 cm at d.b.h. and heights 1.8 m tall (sensu Thomas and others 1979); live trees with dead tops or exposed heartrot of the bole

also function as snags, and are included here.

e Structures include forked or multiple tops, toprot associated with injuries to tree tops and subsequent infection by wound parasites, mainstem heartrot cavities, brooms.f Channelizing invertebrates noted here are primarily Cerambycid and Buprestid woodboring beetles (Coleoptera) and carpenter ants (Camponotus spp. /Hymenoptera).g Saprot occurs, but thin-barked, small-caliper stems and tops dry out quickly and typically do not function as soft snags.h Conventional wisdom suggests that bark beetles are typically associated with dwarf mistletoe-induced tree mortality and topkilling. Our observations suggest that bark beetles are often not associated.i Toprot often occurs in living trees that have been damaged by top breakage or a prior topkilling disturbance. Opportunistic wood decay fungi such as Fomitopsis pinicola and wound parasites such as F. officinalis and F. cajenderi invade the top

portion of the remaining live tree, decaying the heartwood. When a new top has developed, the heartwood of the new top and that occurring below the new top often are decayed making the toprotted area above and below the new topvulnerable to reinjury by top breakage. Severely toprotted trees typically lose their top. Raptor stick nests are common on broken topped trees.

j Not applicable.k Fuel accumulations are minor in the form of fallen dwarf mistletoe brooms and branch litter.l PSME is an important host in Idaho and Montana in the Clearwater, Lolo, and Nez Perce National Forests.m All conifers are host to Phaeolus schweinitzii ; those listed are primary hosts that contribute most significantly to standing and down structure.
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