United States 

Department of 

Agriculture

Forest Service

Pacific Northwest 

Research Station

Research Paper

PNW-RP-577

January 2009

Dry Forests of the 

Northeastern Cascades 

Fire and Fire Surrogate 

Project Site, Mission Creek, 

Okanogan-Wenatchee 

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Compilers 

James K. Agee is an emeritus professor, College of Forest Resources, Box 

32100, University of Washington, Seattle, WA 98195; and John F. Lehmkuhl 

is a research wildlife biologist, U.S. Forest Service, Pacific Northwest Research 

Station, 1133 N Western Ave., Wenatchee, WA 98801. 
Dry Forests of the Northeastern Cascades 

Fire and Fire Surrogate Project Site, 

Mission Creek, Okanogan-Wenatchee 

National Forest

James K. Agee and John F. Lehmkuhl, Compilers

U.S. Department of Agriculture, Forest Service

Pacific Northest Research Station

Portland, Oregon

Research Paper PNW-RP-577

January 2009
Abstract

Agee, James K.; Lehmkuhl, John F. (comps.) 2009. Dry forests of the 

Northeastern Cascades Fire and Fire Surrogate Project site, Mission Creek, 

Okanogan-Wenatchee National Forest. Res. Pap. PNW-RP-577. Portland, OR: 

U.S. Department of Agriculture, Forest Service, Pacific Northwest Research 

Station. 158 p.

The Fire and Fire Surrogate (FFS) project is a large long-term metastudy established to assess the effectiveness and ecological impacts of burning and fire 

“surrogates” such as cuttings and mechanical fuel treatments that are used instead 

of fire, or in combination with fire, to restore dry forests. One of the 13 national 

FFS sites is the Northeastern Cascades site at Mission Creek on the OkanoganWenatchee National Forest. The study area includes 12 forested stands that 

encompass a representative range of dry forest conditions in the northeastern Cascade Range. We describe site histories and environmental settings, experimental 

design, field methods, and quantify the pretreatment composition and structure of 

vegetation, fuels, soils and soil biota, entomology and pathology, birds, and small 

mammals that occurred during the 2000 and 2001 field seasons. We also describe 

the implementation of thinning treatments completed during 2003 and spring 

burning treatments done during 2004 and 2006. 

Keywords: Dry forest, Washington, Cascade Range, vegetation, fuels, soils, 

soil biota, entomology, pathology, wildlife. 
Summary

The Mission Creek Fire and Fire Surrogate (FFS) project was initiated in 2000. 

Since that time, pretreatment measurements have been completed and analyzed 

and are summarized in this report. Treatments have also been applied, although 

they were completed in two phases: thinning and four of the prescribed burns were 

completed in 2002–2004, and the final two prescribed burns were completed in 

2006. This research paper summarizes the implications of the pretreatment results 

and the implementation of treatments and posttreatment progress.

The forests of the Mission Creek study site are representative of larger dry 

forest landscapes of the West. Mission Creek is within Ecological Subregion 11 

(ESR 11) of the interior Columbia River basin, and the primary scope of inference 

for the study results. The subregion extends along the lower elevation forested 

lands of the eastern Cascades of Washington and Oregon, and on an easterly 

arc to the Kettle Range in northeastern Washington. The Mission Creek results 

combined with those from the Lubrecht FFS site in the northern Rocky Mountains 

of northeastern Montana and the Hungry Bob FFS site in the Blue Mountains of 

northeastern Oregon expand the FFS scope of inference to much of the dry forest 

in the interior Columbia River basin. 

This dry forest is codominated by Douglas-fir (Pseudotsuga menziesii (Mirb.) 

Franco) and ponderosa pine (Pinus ponderosa Dougl. ex Laws). About 10 percent 

of the forest composition consists of grand fir (Abies grandis (Dougl. ex D. Don) 

Lindl.) and western larch (Larix occidentalis Nutt.). Among FFS sites, it is less 

ponderosa pine-dominated than dry forests of the Southwest, has less lodgepole 

pine (Pinus contorta Dougl. ex Loud.) than dry forests of the northern Rocky 

Mountains, and has lower tree species richness than sites in the Sierra Nevada. 

Among FFS sites, Mission Creek is closest in tree composition to the Hungry Bob 

site in northeastern Oregon, but our experimental units appear to have had fewer 

logging entries and higher basal area. Compared to historical stands in ESR 11, 

current units have higher tree density and basal area, more small trees, and more 

tree layers. All of these features are likely to be affected by treatments of thinning 

or prescribed fire.

There are few significant vegetation differences among Mission Creek units. 

However, there is substantial within-unit variation. Overstory vegetation is 

generally similar across all pretreatment units in terms of tree density, snag density, 

basal area, stand density index, sapling density, species composition, canopy cover, 

bulk density, and base height. The site is fairly species rich with 124 understory 

species, most with low cover and frequency, but graminoids and shrubs dominate 

the understory. Serviceberry (Amelanchier alnifolia (Nutt.) Nutt. ex M. Roem.), 

The forests of the 

Mission Creek study 

site are representative 

of larger dry forest 

landscapes of the West.
snowberry (Symphoricarpos albus (L.) S.F. Blake), and rose (Rosa spp.) are the 

dominant shrubs, and pinegrass (Calamagrostis rubescens Buckley) and elk 

sedge (Carex geyeri Boott) are the dominant graminoids. Understory community 

structure differs among treatment units, and understory vegetation is correlated 

with physical and biological elements, such as elevation and overstory tree density. 

Dry forests of Montana have shrub-forb understory dominance, and the Oregon 

and Southwest sites are forb-graminoid dominated.

Current fuel conditions at Mission Creek show moderate variability among 

units, but few significant differences. The ranges of biomass for 1-hr, 10-hr, and 

100-hr fuels are within the ranges of other dry forests, but the larger fuels (1,000-

hr+ [>7.62 cm diameter]) are 25 to 65 percent of levels in other dry forests. Fire 

behavior is affected primarily by the smaller dead fuels plus herbs and shrubs, 

so the low levels of coarse woody debris have few fire behavior implications. 

Projections of fire behavior show a majority of units would be affected by severe 

fire behavior (torching and crowning) under worst-case weather using either the 

Northern Forest Fire Laboratory models or custom models where shrub depth 

was used to define fuelbed depth. Less severe fire behavior is predicted if fuelbed 

depth is defined by dead fuel particle height.

Soils of Mission Creek are largely mollisols, with some alfisols, inceptisols, and 

entisols, derived primarily from sandstone. The A horizons, on average, are deep 

for a forest soil (up to 88 cm), but quite variable across units; Bw and Bt horizons 

are also quite variable. Soils are well-structured with moderate bulk densities, usually loamy to sandy loamy at the surface, grading to increasingly sandy or clayey 

texture at depth. Hydrophobicity is common at the surface owing to exudates from 

leaf litter coating surface soil particles. Carbon and nitrogen are high in these soils, 

with a high base saturation as well. Nutrients appear less limiting for plant growth 

than moisture, and it appears that by June, soil moisture levels are significantly 

drawn down by evapotranspiration.

Soil enzymes and microarthropods are variable across and within units. Both 

can affect site productivity by influencing organic matter input and decomposition. 

Sampling on a landscape gradient of ridgetop, sideslope, open bare area, and valley 

bottom showed some differences by landscape position, probably associated with 

moisture availability. Soil enzyme activity was relatively low in the surface soil 

samples, generally higher with increasing Douglas-fir dominance, and not significantly different by landscape position. The soil microarthropod fauna density was 

dominated by oribatid mites (84 percent) and Collembola (springtails, 7 percent). 

The total populations of these two microarthropods did not differ by landscape 

position, but some of the less abundant microarthropods were more often found 

Projections of fire 

behavior show a 

majority of units would 

be affected by severe 

fire behavior under 

worst-case weather.
in valleys than on ridges. There were some positive correlations with available 

moisture and negative relationships with increasing bulk density for both soil 

enzymes and soil microarthropods.

Root pathogens were almost absent at Mission Creek with only one sample 

(on an asymptomatic tree) showing the presence of a root rot. This reflects the dry 

conditions at the study site, and would not generally apply to moist forests, even in 

the same ecoregion. Analysis of fungal endophytes showed that they exist in large 

woody roots of live conifers. Almost half of asymptomatic Douglas-fir and ponderosa pine sampled contained fungal endophytes, generating an interesting question 

of how they might influence the dynamics of pathenogenic fungi in the rhizosphere 

of forest tree roots. Bark beetle activity was largely due to western pine beetle 

(Dendroctonus brevicomis) and mountain pine beetle (D. ponderosae) attacking 

ponderosa pine. Although some large centers of activity were found, the percentage of trees affected by bark beetle attack was relatively low in the pretreatment 

sampling. Dwarf mistletoe was found on all but two units, and was present on both 

Douglas-fir and ponderosa pine. Every overstory class was affected, but the density 

of trees affected was relatively low. Infection rates ranged from 0 to 8.8 percent of 

unit basal area. Woodpecker foraging was observed on less than 1 percent to more 

than 8 percent of snags or trees larger than 20 cm diameter.

The most common birds detected at Mission Creek were the chipping sparrow 

(Spizella passerina), dark-eyed junco (Junco hyemalis), mountain chickadee 

(Poecile gambeli), Nashville warbler (Vermivora ruficapilla), pine siskin (Carduelis 

pinus), red-breasted nuthatch (Sitta canadensis), Townsend’s warbler (Dendroica 

townsendi), western tanager (Piranga ludoviciana), and yellow-rumped warbler 

(D. coronata). Species assemblages did not differ across units. Nesting success 

was highest for cavity nesters, intermediate for ground nesters, and lowest for 

foliage nesters, representing decreasing ability to provide safe sites for young birds. 

Bark gleaners (predominantly red-breasted nuthatch), brown creeper (Certhia 

americana), and hairy woodpecker (Picoides villosus) exhibited preference for 

larger trees, with the first two showing no preference for whether the tree was live 

or dead, and the woodpecker preferentially selecting larger snags. Responses of 

focal species to potential treatment were projected as being positive for the chipping 

sparrow, white-headed woodpecker (Picoides albolarvatus), western bluebird 

(Sialia mexicana), and Cassin’s finch (Carpodacus cassinii), and negative for the 

hermit thrush (Catharus guttatus), western tanager, and brown creeper.

About two-thirds of the 21 expected species of small mammals were captured 

at the Mission Creek study site. The deer mouse (Peromyscus maniculatus) was 

the dominant small rodent (51 percent of captures), the yellow-pine chipmunk 
(Neotamias amoenus) was the dominant arboreal or semiarboreal rodent (21 percent 

of captures), and the Trowbridge’s shrew (Sorex trowbridgii) was the most common 

insectivore. The deer mouse and yellow-pine chipmunk were codominant if the 

larger size of the chipmunk was factored in. Other species individually accounted 

for <5 percent of the catch and occurred in <50 percent of the stands. Other than 

chipmunks, few arboreal or semiarboreal species were captured, probably because 

of a lack of cover (low numbers of snags, logs, and mistletoe) and food (particularly 

truffles and lichens for northern flying squirrels [Glaucomys sabrinus]). Mammal 

assemblages were similar among the assigned treatment groups of stands, but 

assemblages did differ among units. Half the units were relatively mesic habitats 

and supported a richer assemblage of small mammals that included all the captured 

species, compared to the other relatively species-poor dry units. Management 

practices that open and dry stands, reduce large down wood, and shift understory 

dominance to grass likely will shift mammal species assemblages to favor species 

associated with the dry end of the gradient. 

Planning for the fire and surrogate (thinning) treatments began in 2000. The 

thin treatment was designed as a low thinning to reduce basal area so the residual 

stand would have a clumped distribution of roughly 15 m2/ha, similar to that found 

in historical stands. Owing to access limitations and soils concerns, all thinning 

treatments were yarded by helicopter. Thinning treatments were completed by 

spring 2003. Burn treatments were partially accomplished during spring 2004. 

Because of unusual weather, only four of the six units scheduled for burning were 

ignited, and they burned lightly or patchily. One of the burn-only units and one of 

the thin-burn units did not receive their burn treatment. The resulting unbalanced 

design with four control (Crow 3, Pendleton, Sand 19, Sand 2), four thin (Crow 1, 

Crow 6, Ruby, Slawson), two burn (Poison, Spromberg), and two thin-burn (Camas, 

Tripp) units was used in the first posttreatment sampling during 2004–2005. Data 

on the economics of harvesting dry eastern Cascade forests, using a variety of yarding techniques, were also gathered as part of the FFS project, and will be reported 

separately. 

In 2006, the design was balanced by the addition of two more burns that 

occurred in spring 2006. The resulting balanced design has three control units 

(Crow 3, Sand 19, Sand 2), three thin units (Crow 1, Ruby, Slawson), three burn 

units (Pendleton, Poison, Spromberg), and three thin-burn units (Camas, Crow 6, 

Tripp). Immediate remeasurement of these units was not possible owing to lack of 

funding. It is anticipated that this design will remain stable and serve as the template for future remeasurement of the Mission Creek FFS site.

The resulting balanced 

design has three 

control units, three thin 

units, and three thinburn units. This design 

is anticipated to remain 

stable and serve as 

the template for future 

remeasurement of the 

Mission Creek FFS site.
Contents

1 Chapter 1: Introduction

 James K. Agee and John F. Lehmkuhl

1 Background

3 Study Site

6 General Methods

8 Implementation of Treatments

9 References

13 Chapter 2: Pretreatment Variation in Overstory and 

 Understory Vegetation

 Richy J. Harrod, Erich K. Dodson, Nicholas A. Povak, and 

 David W. Peterson

13 Introduction

14 Methods

14 Sampling Design

14 Overstory Sampling and Analysis

15 Understory Sampling and Analysis

17 Results and Discussion

17 Overstory Structure and Composition

22 Understory Structure and Composition

29 Conclusions

29 Literature Cited

35 Chapter 3: Fuels and Fire Behavior

 James K. Agee and M. Reese Lolley 

35 Introduction

35 Methods

39 Results and Discussion

44 Literature Cited

47 Chapter 4: Soils

 Darlene Zabowski, Jeffrey Hatten, Elizabeth Dolan, and 

 George Scherer

47 Introduction

47 Methods

47 Soil Sampling

48 Soil Analysis

49 Results and Discussion

49 Soil Properties

53 Soil Classification

54 Conclusions

54 Literature Cited
57 Chapter 5: Soil Enzyme Activity 

 Nicholas J. Brazee, Robert L. Edmonds, and James L. Marra 

57 Introduction

58 Methods

58 Sampling Design

58 Field Sampling

58 Lab Analyses

58 Statistical Analyses

59 Results

59 Soil Moisture, Bulk Density, and pH

61 Soil Enzyme Activities

60 Relationships Among Soil Enzyme Activities and Soil and Stand Conditions

62 Discussion

62 Soil Moisture, Bulk Density, and pH

62 Soil Enzyme Activities

65 Relationships Between Soil Enzyme Activities and Soil and Stand Conditions

66 Acknowledgments

66 Literature Cited

69 Chapter 6: Soil Microarthropods 

 Amy C. Ramsey, James L. Marra, and Robert L. Edmonds 

69 Introduction

70 Materials and Methods

70 Sampling Design

70 Soil Sampling

71 Lab Analyses

71 Statistical Analyses

71 Results

71 Soil Moisture, Bulk Density, and pH

72 Microarthropod Taxa and Influence of Landscape Position

74 Relationships Between Oribatid Mite and Collembola Taxa Richness and

Density and Soil Moisture, Bulk Density, and pH

74 Discussion

76 Acknowledgments

76 Literature Cited

81 Chapter 7: Pretreatment Variability in Bark Beetle, Root Disease, and 

 Dwarf Mistletoe Incidence and Severity

 Paul F. Hessburg, R. Brion Salter, and Anne C. Conway 

81 Introduction

81 Methods

84 Identifying Tree-Killing Root Pathogens

85 Identifying Tree-Killing Bark Beetles
86 Recording Woodpecker Foraging

87 Recognizing Dwarf Mistletoe Incidence and Severity

88 Analysis

101 Results and Discussion

101 Root Pathogens

101 Fungal Endophytes

103 Bark Beetles

105 Mistletoe

107 Woodpecker Foraging

108 Literature Cited

109 Chapter 8: Avian Community Composition, Nesting Ecology, and

 Cavity-Nester Foraging Ecology

 William L. Gaines, Andrea L. Lyons, John F. Lehmkuhl, 

 Maryellen Haggard, James S. Begley, and Marlene Farrell

109 Introduction

110 Methods

110 Avian Community Composition

111 Nest Productivity and Substrate

111 Cavity-Nester Foraging Behavior and Habitat

112 Statistical Analysis

114 Results

114 Avian Community Composition

118 Nest Productivity and Substrate

120 Cavity-Nester Foraging Behavior and Habitat

125 Discussion

125 Avian Community Composition

129 Nest Productivity and Substrate

129 Cavity-Nester Foraging Behavior and Habitat

132 Management Implications

132 Acknowledgments

133 Literature Cited

143 Chapter 9: Small Mammals

 John F. Lehmkuhl

143 Introduction

144 Methods

146 Results

150 Discussion

154 Acknowledgments

154 Literature Cited

158 Acknowledgments

158 English Equivalents

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

James K. Agee and John F. Lehmkuhl 1

Background

Concerns about declining forest health in the dry forests of the Western United 

States have generated multiple efforts to restore fire-resilient forest structures 

across the dry forests of the West. Programs to deal with the problem of larger and 

more severe fires in the West have been initiated at the state level (e.g., Western 

Governor’s Association 2003: Policy Resolution 03-18, September 15, 2003, at 

Big Sky, Montana) and the federal level (e.g., Healthy Forests Restoration Act of 

2003). Focus has been both on values (the wildland-urban interface) and hazards 

(fuel reduction), including timing (Allen et al. 2002) and treatment type (Agee and 

Skinner 2005, Brown et al. 2004). A national research program, known as the Joint 

Fire Science Program, has also been enacted to provide information necessary to 

assist fuel reduction while protecting and restoring ecological values.

The largest project funded by the Joint Fire Science Program in its early years 

was the Fire and Fire Surrogate (FFS) project (http://frames.nbii.gov/ffs). The FFS 

is a long-term study to assess the effectiveness and ecological impacts of burning 

and fire “surrogates” such as cuttings and mechanical fuel treatments that are used 

instead of fire, or in combination with fire. For many of the sites, the long-term goal 

of these treatments is to restore historical ecosystem structure and function, but the 

consequences for nutrient cycling, seed scarification, plant diversity, disease and 

insect abundance, and wildlife are mostly unknown. Similarly, although combining 

managed fire with silvicultural treatments adds the critical effects of combustion, 

we know little about ecological effects, economics, and fire hazard reduction of 

these methods. There are 12 FFS sites with the full complement of fire and fire 

surrogate treatments, plus an additional satellite site with fire treatments only (table 

1-1). Each of these sites had a historically short-interval, low- to moderate-severity 

fire regime. Eight of the western sites share ponderosa pine (Pinus ponderosa

Dougl. ex Laws) as an important tree component. One of the 12 complete sites 

is the Northeastern Cascades site at Mission Creek on the Okanogan-Wenatchee 

National Forest (fig. 1-1). For this report, we refer to this site as “Mission Creek.”

Chapter 1: Introduction

1 James K. Agee is Emeritus Professor at the College of Forest Resources, Box 32100, University of Washington, Seattle, WA 98195 jagee@u.washington.edu; John F. Lehmkuhl

is a research wildlife biologist, U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station, 1133 N Western Ave., Wenatchee, WA 98801.

The FFS is a longterm study to assess 

the effectiveness and 

ecological impacts 

of burning and fire 

“surrogates” such as 

cuttings and mechanical 

fuel treatments. This 

report summarizes the 

pretreatment conditions 

of the Mission Creek 

site.
2

RESEARCH PAPER PNW-RP-577

Table 1-1—The Fire and Fire Surrogate study national network

Site Location

Northeastern Cascades Mission Creek, north-central Washington

Blue Mountains Wallowa-Whitman National Forest, Oregon

Northern Rocky Mountains Lubrecht Experimental Forest, western Montana

Southern Cascades Klamath National Forest, northeastern California

Central Sierra Nevada Blodgett Forest, northern California

Southern Sierra Nevadaa Sequoia and Kings Canyon National Parks, California

Southwestern Plateau Coconino and Kaibab National Forests, northern Arizona

Southern Rocky Mountains Santa Fe National Forest, northern New Mexico

Central Appalachian Plateau Ohio Division of Forestry and Mead Corporation, Ohio

Southeastern Piedmont Clemson Experimental Forest, northwestern South Carolina

Florida Coastal Plain Myakka River State Park, southwest Florida

Gulf Coastal Plain Solon Dixon, southern Alabama

Southern Appalachian Mountains Green River, western North Carolina

a No thinning treatments applied here.

Figure 1-1—Location of Mission Creek study site in the northeastern Cascades of Washington.
Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Our goal with this paper is to document the physical and biological elements 

of dry forest found at the Mission Creek site. The study area includes 12 forested 

stands that encompass a representative range of dry forest conditions in the northeastern Cascade Range. In this paper, we describe site histories and environmental 

settings, experimental design, and field methods, and quantify the pretreatment 

composition and structure of vegetation, fuels, soils and soil biota, entomology 

and pathology, birds, and small mammals. 

Study Site

The forests of the Mission Creek study site are representative of larger dry forest 

landscapes of the West. However, even within the dry forests, there is considerable 

ecological variability in terms of physical environment and biota. Mission Creek is 

within Ecological Subregion 11 (ESR 11) (fig. 1-2) of the interior Columbia River 

basin (Hessburg et al. 2000a), the primary scope of inference for the study results. 

The subregion extends along the lower elevation forested lands of the eastern 

Cascades of Washington and Oregon, and on an easterly arc to the Kettle Range 

Figure 1-2—The primary scope of inference of the Mission Creek Fire and Fire Surrogate study 

(star) is best defined by dry forest Ecological Subregion 11 (dark grey) of the interior Columbia River 

basin (Hessburg et al. 2000a). Ecological Subregion 11 characterizes the lower montane forests of 

northeastern Washington and the east slope of the northern Cascade Range in Washington and parts 

of Oregon.

The forests of the 

Mission Creek study 

site are representative 

of larger dry forest 

landscapes of the 

West.
RESEARCH PAPER PNW-RP-577

in northeastern Washington. The Mission Creek results combined with those from 

the Lubrecht FFS site in the northern Rocky Mountains of northeastern Montana 

and the Hungry Bob FFS site in the Blue Mountains of northeastern Oregon expand 

the FFS scope of inference to much of the dry forest in the interior Columbia River 

basin. 

The northeastern Cascades of Washington have the most maritime climate 

within the interior Columbia River basin because of the proximity to Pacific Coast 

air masses (Hessburg et al. 2000a). Climatic data from Wenatchee (station 459074, 

1931–2005) and Leavenworth 3S (station 454572, 1948–2005) east and west of 

Mission Creek for the last 60 years show average annual precipitation of 22.5 to 64.9 

cm, most of which falls as snow between November and April, average maximum air 

temperatures of 16.3 to 16.9 °C, and average minimum air temperatures of 4.9 to 1.4 

°C (Western Regional Climate Center online historical summaries: http://www.wrcc.

dri.edu). Regional winds are generally westerly, and precipitation declines to the 

east and at lower elevation. Soil parent material is primarily nonglaciated sandstone 

intermixed with some shale and conglomerate (Tabor et al. 1982). Typical soil types 

(soil taxonomy great groups) found in the area include Haploxerepts, Haploxerolls, 

Argixerolls, and Haploxeralfs (USDA FS 1995).

The historical vegetation of these dry forests was dominated by ponderosa 

pine and Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) (Agee 1993, 1994). 

In the lower Teanaway Valley, 25 km to the south, reconstructions of historical 

tree populations (ca. 1870–1890) from General Land Office records indicated that 

tree density and basal area were relatively low (Wright and Agee 2004) (table 

1-2). Ponderosa pine was the dominant species in both the dry Douglas-fir and dry 

grand fir plant associations (sensu Daubenmire 1968). Other species, such as grand 

fir (Abies grandis (Dougl. ex D. Don) Lindl.), western larch (Larix occidentalis

Nutt.), lodgepole pine (Pinus contorta Dougl. ex Loud.), western redcedar (Thuja 

plicata Donn ex. D. Don), and various hardwood species were minor components 

of the vegetation. Common understory species included pinegrass (Calamagrostis 

rubescens Buckl.), elk sedge (Carex geyeri Boott), bitterbrush (Purshia tridentata

Table 1-2—Historical vegetation of the lower Teanaway Valley, 25 km south of the Mission Creek units

Relative density Relative basal area

Plant association group Density Basal area PIPO PSME ABGR LAOC PIPO PSME ABGR LAOC

Trees/ha m

2

/ha - - - - - - - - - - - - - - - - - - - - - - Percent - - - - - - - - - - - - - - - - - - - - 

Dry Douglas-fir 73.3 15.3 76.5 22.1 1.4 — 72.9 26.4 0.7 —

Dry grand fir 49.3 13.4 61.4 35.4 — 2.5 70.5 28.2 — 1.2

PIPO = Pinus ponderosa, PSME = Pseudotsuga menziesii, ABGR = Abies grandis, LAOC = Larix occidentalis, — = not present.

Source: Wright and Agee 2004.
Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

(Pursh) DC.), snowberry (Symphoricarpos albus (L.) Blake), spirea (Spiraea 

betulifolia Pall. var. lucida (Douglas ex Greene) C.L. Hitchc.), wood rose (Rosa 

gymnocarpa Nutt.), and ocean spray (Holodiscus discolor (Pursh) Maxim.). As 

on the Teanaway, Harrod et al. (1999) found a similar pre-1850 tree density (50 

trees/ha) and basal area (16 m2/ha) in Mission Creek with a higher relative density 

of ponderosa pine (90 percent).

Reconstructions of forest structure suggest that early successional stages 

covered a small proportion of the historical dry forest landscape. Hessburg et al. 

(2000b) estimated for a large study area north of Mission Creek that 11.3 percent 

of the landscape was in “stand initiation” structure, and for another large study 

area that encompassed Mission Creek, Agee (2003) estimated a range of 6.3 to 

15 percent in seedling and sapling stages. Older forest totaled 41.2 percent in the 

Hessburg et al. (2000b) study and 38.4 to 63.5 percent for medium tree and larger 

structural stages in the Agee (2003) study. These proportions of larger, older structures would likely be higher if just the dry forest portions of those larger landscapes 

were considered. 

Many studies in dry forests of the West have suggested that tree distributions 

tend to be clustered or aggregated rather than randomly or uniformly distributed 

(Cooper 1961, Thomas and Agee 1986). Locally this appears to be true, as Harrod 

et al. (1999) evaluated historical ponderosa pine forests in Mission Creek and found 

aggregated distribution of historical trees in patch sizes up to 15 m.

Low-severity fires had a major influence on the species composition and structure of historical dry forests across the West (Agee 1993). In the eastern Cascades 

near Mission Creek, Everett et al. (2000) found a mean fire-free interval of 6.6 to 7 

years on two similar sites within 60 km of Mission Creek. These were composite 

fire intervals over roughly 582- to 644-ha sites. Fire-return intervals in the Swauk 

Valley, 25 km to the southwest of Mission Creek, averaged 6.2 years within polygons averaging 1096 ha (Schellhaas et al. 2007). In the lower Teanaway Valley, 40 

km to the southwest of Mission Creek, Wright and Agee (2004) found an 18.8- to 

20.6-year mean fire-free interval for dry Douglas-fir and dry grand fir plant associations, using a much smaller polygon size (0.5 to 2.5 ha). Most fires were late-season 

fires, some were above 10,000 ha, and larger fires were associated with drought 

years. Because of the high proportion of surviving trees with fire scars, most of 

these fires are assumed to have been of low severity (Hessburg et al. 2005).

Modern-era dry forests have been affected by many changes from the pre-EuroAmerican era (Hessburg and Agee 2003). Change agents acted to exclude fires, 

directly advance secondary succession, directly suppress fires, or some combination 

of these effects (Hessburg et al. 2005). Domestic livestock grazing beginning in the 

Low-severity fires 

had a major influence 

on the species 

composition and 

structure of historical 

dry forests across 

the West.
RESEARCH PAPER PNW-RP-577

1870s acted to reduce flashy fuels that could carry fire across the landscape (Belsky 

and Blumenthal 1997). In Mission Creek, intensive sheep grazing was present by 

the 1890s and continued through the 1920s (USDA 1938). This watershed was a 

sheep driveway in spring and fall, and an estimated 30,000 sheep passed through 

the drainage twice a year. By the 1950s, the number of grazing animals had been 

reduced considerably (Holstine 1992). Currently, there is no active grazing by 

livestock on public lands in the watershed. Selective timber harvest began in 

Mission Creek in the late 1800s for railroad construction, mining, homesteading, 

and to supply boxes for an expanding fruit industry (Lolley 2005). From 1928 to 

1938, the mill at Cashmere at the base of Mission Creek processed over 200 million 

board feet (472,000 cubic meters) a year (USDA SCS 1938). Selective harvest of 

the largest and best-form (clear bole) ponderosa pine occurred through the most 

accessible portions of the landscape. Active fire suppression during this period 

dramatically increased fire-free intervals (Everett et al. 2000, Wright and Agee 

2004).

The resulting changes in forest structure are summarized by Hessburg et al. 

(2000b) and Hessburg and Agee (2003). More shade-tolerant species that once 

would have been removed by frequent, low-intensity fires filled in natural canopy 

gaps and gaps created by selective removal of large pines, average tree size 

declined, and multilayered canopies became common. In these dry forests, mixedto high-severity fire regimes replaced the historical low-severity fire regime. The 

Rat Creek Fire (1994) and Fischer Fire (2004), directly adjacent to Mission Creek, 

are examples of this regime change.

General Methods

The experimental design of the FFS project is a balanced, two-way design with 

three replications of each main factor (fig. 1-3A). The first main factor is prescribed 

fire. The second is a surrogate for fire, which in our case was a low thinning. A 

total of 12 units out of a possible 30 were randomly chosen in the watersheds of 

Mission and Peshastin Creeks (fig. 1-4). The 30 units were selected with the criteria 

that the majority of the unit was in the Pseudotsuga menziesii series (Lillybridge 

et al. 1995), at least 90 percent of the unit was forested, none of the plant or animal 

species of concern were present (except Survey and Manage species under the 

Northwest Forest Plan), average slope was less than 50 percent, and the unit consisted of a relatively square or rectangular area of 10 ha or more. Treatments were 

randomly assigned, except that one unit initially designated a burn-only unit (Sand 

19) was switched with a designated control unit (Spromberg) because of fire control 

concerns by ranger district fire personnel, who were responsible for conducting 

The experimental 

design of the FFS 

project is a balanced, 

two-way design with 

three replications 

of each main factor: 

prescribed fire and 

low thinning.
Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

3 units

3 units

3 units

3 units

4 units

4 units

2 units

2 units

No burn Burn No burn Burn

No thin Thin

No thin Thin

A B

Figure 1-3—Experimental design of the Fire and Fire Surrogate project. Each experimental 

treatment (prescribed fire or no prescribed fire, thinning or no thinning) was replicated three 

times in the initial (A) design. An unbalanced design (B) resulted when two burn units did not 

receive the prescribed fire treatment. This was resolved in 2006. 

Figure 1-4—Location of the 12 experimental units at the Mission Creek study site.
RESEARCH PAPER PNW-RP-577

the prescribed fires. Because of unanticipated events, two of the scheduled burns 

did not occur before the first posttreatment measurement, resulting initially in an 

unbalanced experimental design (fig. 1-3B). Burns were completed during 2006, 

rebalancing the design.

Each discipline developed unique methods to assess pretreatment conditions 

and the effect of treatment (Youngblood et al. 2005). A 40- by 40-m grid was 

established over each experimental unit. The fuels, soils, and bird sampling used 

different grid intersections across the entire matrix as plot centers to avoid concentrated disturbance at selected locations. The small mammal sampling was done on 

a 6- by 6-point interior portion of the grid, and the vegetation group used six 20- by 

50-m rectangular “Daubenmire” plots to do the vegetation sampling in completely 

forested locations, augmented by four 20- by 20-m plots placed in nonforested 

locations. The entomology and pathology group used a 100-percent survey of trees 

across a 10-ha area of each unit.

This report summarizes the pretreatment conditions of the Mission Creek site. 

Although some units described herein are designated as control, thin, burn, or 

thin-burn units, all measurements reported were taken and analyzed before treatments were applied. Any “treatment” comparisons are for units aggregated by the 

final 2006 balanced design (fig. 1-3). Control units are Crow 3, Sand 19, and Sand 2. 

Thin units are Crow 1, Ruby, and Slawson. Burn units are Pendleton, Poison, and 

Spromberg. Thin-burn units are Camas, Crow 6, and Tripp.

Implementation of Treatments

Planning for the fire and surrogate (thinning) treatments began in 2000. The thin 

treatment was designed as a low thinning to reduce basal area so the residual 

stand would have a clumped distribution of roughly 15 m2/ha, similar to that found 

in historical stands (Harrod et al. 1999). Because of access limitations and soils 

concerns, all thinning treatments were yarded by helicopter. Thin treatments were 

completed by spring 2003. Burn treatments were scheduled for autumn 2003, but 

an unusual, intense early rain so dampened the fuels that burning was delayed, 

and normal autumn rains then came shortly thereafter, postponing any burning 

until spring 2004. Unusual weather again prevailed. A late dry winter allowed 

substantial herbaceous growth (“greenup”), and when the spring prescribed fire 

season occurred, only four of the six units scheduled for burning were ignited and 

they burned lightly or patchily. One of the burn-only units (Sand 2) and one of the 

thin-burn units (Ruby) did not receive the planned burn treatment. 
9

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

The resulting unbalanced design (fig. 1-3B) with four control (Crow 3, Pendleton, Sand 19, Sand 2), four thin (Crow 1, Crow 6, Ruby, Slawson), two burn 

(Poison, Spromberg), and two thin-burn (Camas, Tripp) units was used in the first 

posttreatment sampling during 2004-2005. Published results to date include effects 

of the first cycle of treatment on vegetation (Harrod et al. 2007) and fuels (Agee and 

Lolley 2006), and other disciplinary results are in preparation. Data on the economics of harvesting dry eastern Cascade forests, using a variety of yarding techniques, 

were also gathered as part of the FFS project, and will be reported separately.

The design was balanced by the addition of two more burns in spring 2006. A 

few changes in treatment allocations among stands were necessary to accommodate 

endangered species (northern spotted owl [Strix occidentalis caurina]) and 

prescribed fire control issues. The Pendleton unit was switched from a control unit 

to a burn-only unit, and Sand 2 from burn-only to control because of fire control 

and logistical issues in Sand 2. Crow 6 was randomly selected from the thin-only 

units to switch from a thin unit to a thin-burn unit, and the Ruby treatment was 

changed from thin-burn to thin-only because of spotted owl regulatory issues 

near Ruby. The resulting balanced design has three control units (Crow 3, Sand 

19, Sand 2), three thin units (Crow 1, Ruby, Slawson), three burn units (Pendleton, 

Poison, Spromberg), and three thin-burn units (Camas, Crow 6, Tripp). Immediate 

remeasurement of these units was not possible owing to lack of funding. It is 

anticipated that this design will remain stable and serve as the template for future 

remeasurement of the Mission Creek FFS site.

References

Agee, J.K. 1993. Fire ecology of Pacific Northwest forests. Washington, DC: 

Island Press. 491 p.

Agee, J.K. 1994. Fire and weather disturbances in terrestrial ecosystems of 

the eastern Cascades. Gen. Tech. Rep. PNW-GTR-320. Portland, OR: U.S. 

Department of Agriculture, Forest Service, Pacific Northwest Research Station. 

52 p.

Agee, J.K. 2003. Historical range of variability in eastern Cascade forests, 

Washington, USA. Landscape Ecology. 18: 725–740.

Agee, J.K.; Lolley, M.R. 2006. Thinning and prescribed fire effects on fuels and 

potential fire behavior in an eastern Cascades forest, Washington. Fire Ecology. 

2(2): 142–158.

Agee, J.K.; Skinner, C.N. 2005. Basic principles of forest fuel reduction 

treatments. Forest Ecology and Management. 211: 83–96.

The resulting balanced 

design has three 

control units, three thin 

units, and three thinburn units. This design 

is anticipated to remain 

stable and serve as 

the template for future 

remeasurement of the 

Mission Creek FFS site.
10

RESEARCH PAPER PNW-RP-577

Allen, C.D.; Savage, M.; Falk, D.A.; Suckling, K.F.; Swetnam, T.W.; Schulke, 

T.; Stacey, P.B.; Morgan, P.; Hoffman, M.; Klingel, J.T. 2002. Ecological 

restoration of southwestern ponderosa pine ecosystems: a broad perspective. 

Ecological Applications. 12: 1418–1433.

Belsky, J.A.; Blumenthal, D.M. 1997. Effects of livestock grazing on stand 

dynamics and soils in upland forests of the interior West. Conservation Biology. 

11: 315–327.

Brown, R.T.; Agee, J.K.; Franklin, J.F. 2004. Forest restoration and fire: 

principles in the context of place. Conservation Biology. 18: 903–912.

Cooper, C.F. 1961. Pattern in ponderosa pine forests. Ecology. 42: 493–499.

Daubenmire, R. 1968. Plant communities. New York: Harper and Row. 300 p. 

Everett, R.L.; Schellhaas, R.; Keenum, D.; Spurbeck, D.; Ohlson, P. 2000. 

Fire history in the ponderosa pine/Douglas-fir forests on the east slope of the 

Washington Cascades. Forest Ecology and Management. 129: 207–225.

Harrod, R.J.; McRae, B.H.; Hartl, W.E. 1999. Historical stand reconstruction in 

ponderosa pine forests to guide silvicultural prescriptions. Forest Ecology and 

Management. 114: 433–446.

Harrod, R.J.; Povak, N.A.; Peterson, D.W. 2007. Comparing the effectiveness 

of thinning and prescribed fire for modifying structure in dry coniferous 

forests. In: Butler, B.W.; Cook, W., comps. The fire environment—innovations, 

management, and policy. Proceedings RMRS-P-46CD. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain Research Station: 

329–346. [CD-ROM].

Hessburg, P.F.; Agee, J.K. 2003. An environmental narrative of inland Northwest 

US forests, 1800-2000. Forest Ecology and Management. 178: 23–59.

Hessburg, P.F.; Agee, J.K.; Franklin, J.F. 2005. Dry forests and wildland fires 

of the inland Northwest USA: contrasting the landscape ecology of the presettlement and modern eras. Forest Ecology and Management. 211(1-2): 117–139.

Hessburg, P.F.; Salter, R.B.; Richmond, M.B.; Smith, B.G. 2000a. Ecological 

subregions of the interior Columbia basin, USA. Applied Vegetation Science. 

3: 163–180.
11

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Hessburg, P.F.; Smith, B.G.; Salter, R.B.; Ottmar, R.D.; Alvarado, E. 2000b. 

Recent changes (1930s-1990s) in spatial patterns of interior Northwest forests. 

Forest Ecology and Management. 136: 53–83.

Holstine, C. 1992. An historical overview of the Wenatchee National Forest. 

Archeological historical series. [Microform] Rep 100.80. On file with: 

Brooks Library, Eastern Washington University, Cheney, WA.

Lillybridge, T.R.; Kovalchik, B.L.; Williams, C.K.; Smith, B.G. 1995. Field 

guide for forested plant associations of the Wenatchee National Forest. Gen. 

Tech. Rep. PNW-GTR-359. Portland, OR: U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station. 335 p.

Lolley, M.R. 2005. Wildland fuel conditions and effects of modeled fuel 

treatments on wildland fire behavior and severity in dry forests of the Wenatchee 

Mountains. Seattle, WA: University of Washington. M.S. thesis.

Schellhaas, R.; Ohlson, P.; Spurbeck, D.; Keenum, D. 2007. Report to the 

Okanogan and Wenatchee National Forests on the results of the Swauk Area fire 

history research. 114 p. Unpublished report. On file with: Wenatchee Forestry 

Sciences Laboratory, 1133 N Western Ave, Wenatchee, WA 98801. 

Tabor, R.W.; Waitt, R.B., Jr.; Frizzell, V.A., Jr.; Swanson, D.A.; Byerly, G.R.; 

Bentley, R.D. 1982. Geologic map of the Wenatchee National Forest. 1:100,000 

Quadrangle, Central Washington. Misc. Invest. Ser., MI 1-311, [Reston, VA]: 

U.S. Geological Survey. 

Thomas, T.B.; Agee, J.K. 1986. Prescribed fire effects on mixed conifer 

forest structure at Crater Lake, Oregon. Canadian Journal of Forest Research. 

16: 1082–1087.

U.S. Department of Agriculture, Forest Service [USDA FS]. 1995. Cashmere 

Mountain soil survey: Leavenworth Ranger District soil handbook: nonwilderness. Preliminary report. Wenatchee, WA: Okanogan and Wenatchee 

National Forests, Soil Survey Staff. 25 p. 

U.S. Department of Agriculture, Soil Conservation Service [USDA SCS]. 1938.

Conclusion report: Mission Creek watershed. Spokane, WA: Pacific Northwest 

Region 11. 31 p.

Wright, C.S.; Agee, J.K. 2004. Fire and vegetation history in the eastern Cascade 

Mountains, Washington. Ecological Applications. 14: 443–459.
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Youngblood, A.; Metlen, K.L.; Knapp. E.E; Outcalt, K.W.; Stephens, S.L.; 

Waldrop, T.A.; Yaussy, D. 2005. Implementation of the Fire and Fire Surrogate 

study, a national research effort to evaluate the consequences of fuel reduction 

treatments. In: Peterson, C.E.; Maguire, D.A., eds. Balancing ecosystem values: 

innovative experiments for sustainable forestry: proceedings of a conference. 

Gen. Tech. Rep. PNW-GTR-635. Portland, OR: U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station: 315–321.
13

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Richy J. Harrod, Erich K. Dodson, Nicholas A. Povak, and David W. Peterson1

Introduction 

Changes in forest vegetation as a result of fire exclusion, sheep and cattle grazing, 

and large-tree logging have been well documented for western forests (Agee 

1998; Arno et al. 1997; Covington and Moore 1994; Everett et al. 2000; Harrod 

et al. 1999; Hessburg and Agee 2003; Hessburg et al. 2000, 2005). These changes 

in forest structure and composition have increased the hazard of large, highseverity wildfires (Agee 1994, Peterson et al. 2005, Scott and Reinhardt 2001, 

Weatherspoon and Skinner 1996), which lead to degraded water quality and costly 

losses of wildlife habitat, wood products, and residential buildings (Armstrong 

and Cumming 2003). In addition, current forests have increased vulnerability to 

many insects and diseases (Hessburg et al. 2005); have altered understory diversity, 

composition, and abundance (Covington et al. 1997, Hall 1977, Smith and Arno 

1999); and generally have an overall deterioration in forest ecosystem integrity 

(Everett et al. 1996). A reduction in the current risks of uncharacteristically severe 

wildfires and insect outbreaks is desirable for local communities and many land 

managers. Before restoration activities are planned, it is important to understand 

the current variability in vegetation so that treatment effects can be appropriately 

interpreted.

Current dry forest landscapes have become homogeneous in their composition 

and structure (Hessburg et al. 2005), but variable vegetation patterns at small scales 

still exist. Restoration treatments are designed to incorporate natural or historical 

fire regimes, which promote heterogeneous landscapes, reduce stand density, raise 

height to live crown, and lead to tree clumping at fine scales (Agee 1993, Harrod 

et al. 1999). However, restoration treatments are often implemented with minimal 

information of how current, local vegetation patterns and composition will respond 

to treatment. Thus, better information is needed about the pretreatment structural 

and compositional elements of dry forests, so that treatment effects can better be 

distinguished from vegetation variability. The national Fire and Fire Surrogates 

(FFS) study was designed to be a long-term research project to evaluate treatment 

alternatives, but it also provides an opportunity to quantify pretreatment structure 

and composition of forest vegetation. 

Chapter 2: Pretreatment Variation in 

Overstory and Understory Vegetation

1 Richy J. Harrod is a fire ecologist, Okanogan-Wenatchee National Forest, 215 Melody 

Lane, Wenatchee, WA 98801 rharrod@fs.fed.us; Erich K. Dodson and Nicholas A. Povak

are ecologists, and David W. Peterson is a research forester, Pacific Northwest Research 

Station, Wenatchee, WA 98801.

Before restoration 

activities are planned, 

it is important to 

understand the 

current variability in 

vegetation so that 

treatment effects 

can be appropriately 

interpreted.
14

RESEARCH PAPER PNW-RP-577

In this paper, we describe the pretreatment overstory and understory vegetation 

at the Mission Creek site, with the specific purpose of determining potential differences in vegetation variables among units that are assigned to specific treatments. 

The specific objectives for the pretreatment overstory measurements were to:

1. Quantify the pretreatment forest structure within treatment groups and 

the variability among treatment units.

2. Determine how biophysical factors affected initial forest characteristics. 

3. Determine potential effects of pretreatment structural variability on 

subsequent analyses. 

The specific objectives for the pretreatment understory measurements were to:

1. Describe the understory plant community, including variability among and 

within units, and test for significant pretreatment differences among units 

assigned to specific treatments.

2. Identify environmental variables that are associated with the understory 

community.

3. Examine the relationship between overstory trees and understory 

vegetation.

4. Compare pretreatment species cover and richness between sampling 

years (2000 or 2001).

Methods

Sampling Design

Sampling of overstory and understory vegetation was conducted on a series of 

fixed-area plots that were permanently established within each treatment unit. 

Based on a preliminary analysis of an adjacent site, it was determined that six, 

20- by 50-m plots would adequately capture the within-unit variability and provide 

an accurate estimate of vegetation characteristics. In summer 2000, the sample 

plots were nonrandomly located in areas of continuous forest vegetation and were 

stratified to include the most dominant plant associations within each unit. Sampling of understory and overstory vegetation occurred in 2000 and 2001.

Overstory Sampling and Analysis

Within each sample plot, all live and standing dead trees >7.62 cm diameter at 

breast height (d.b.h.) were identified; permanently numbered; and measured for 

diameter, total height, height to crown base (height from tree base to the intersection of the lowest live limb at the tree bole), bole scarring, and crown condition (e.g. 

Hawksworth 1977, Keen 1943). Diameters were measured using a diameter tape, 

and heights were estimated using a clinometer. Saplings (height >1.37 m, diameter 

Sampling of overstory 

and understory 

vegetation was 

conducted on a series 

of fixed-area plots 

that were permanently 

established within 

each treatment unit. 
15

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

<7.62 cm) were tallied by species at the plot level. Canopy closure was estimated at 

the four cardinal directions from the center of the plot using a Lemmon Spherical 

Densiometer, Model-A. Canopy cover was then calculated by averaging the four 

measurements, multiplying its inverse by 1.04 and subtracting it from 100 (Lemmon 1956). Slope was measured at each plot using a clinometer, and aspect was 

measured using a compass. 

Data were averaged up from the plot level to the experimental-unit level for all 

analyses unless otherwise noted (Hurlbert 1984). Live trees, snags, and saplings 

were analyzed separately. Folded aspects were calculated for each following plot, 

where aspect values range from 0 (NE slopes) to π (SW slopes). Heat load index 

(HLI) was calculated for each plot using equation 3 of McCune and Keon (2002), 

where slope, aspect, and latitude are used to estimate incident radiation. Values 

for HLI range from 0 to 1 with 0 representing cool NE-facing, shallow slopes and 

larger numbers representing warmer, SW-facing steep slopes. Canopy bulk density, 

canopy base height, and canopy fuel loading were calculated using the Crown Mass 

model included in the Fire Management Analyst (FMA) software package. Data 

were entered into the program at the plot level for these analyses. 

A two-factorial analysis of variance was used to identify initial differences in 

forest structural components among treatments prior to the experiment. Unlike the 

understory analysis (see below), the experimental design was a balanced completely 

randomized design. Factors were burn (two levels: burn or no burn) and thin (two 

levels: thin or no thin). Least square means were used to compare significance 

between treatments, and the experiment-wise error rate was controlled using the 

Tukey-Kramer adjustment for multiple comparisons. Two plots were removed from 

all overstory analyses because they were outside of the fire line and were mistreated 

during the prescribed burn in 2004. For purposes of future integration of these data 

with subsequent analyses, these two plots were removed from the current analyses. 

A significance level of P < 0.10 was set prior to analyses.

Correlation analysis was conducted to determine significant relationships 

between overstory structural characteristics and environmental factors. Data were 

averaged to the plot level (n = 70), and Pearson’s correlation coefficients were 

computed for each combination of variables. Significant correlations were based 

on P < 0.10.

Understory Sampling and Analysis

The 72 permanent 20- by 50-m plots used to sample trees were also used for 

sampling understory vegetation. Ten nested 5- by 10-m subplots placed in a continuous 10- by 50-m strip in the center of each plot were used to collect shrub cover. 
16

RESEARCH PAPER PNW-RP-577

Cover was ocularly estimated to the nearest percentage point. Also, twenty 1- by 

1-m quadrats were nested in each plot in a stratified random fashion for sampling 

herbaceous vegetation. In each quadrat, all herbaceous species were inventoried 

and their cover ocularly estimated to the nearest percentage point.

Cover for each shrub and herbaceous species (forbs and graminoids) were 

averaged to the plot level for each species (n = 72). Average cover and richness 

(number of species on each plot) were then calculated for each site. Species were 

grouped into shrubs, forbs, and graminoids (Collins et al. 2007, Metlen and Fielder 

2006). Understory variability in cover and richness was partitioned into withinand among-site components using a Hierarchical Linear Model in the SAS (Littell 

et al. 1996) Proc Mixed procedure (Singer 1998). The simplest Unconditional 

Means Model was fit with the overall mean as the fixed effect and two variance 

components—one within units and one among units (Raudenbush and Bryk 2002, 

Singer 1998). Variability in understory plant cover and richness was partitioned into 

within- and among-site components for each life form (shrub, forb, and graminoid) 

as well as overall cover and richness.

Pretreatment differences in units assigned to treatments were evaluated using 

a general linear model in SPSS (2001). Prior to analysis, all data were averaged 

to the site level where the treatments were to be applied later (n = 12 units). Thinning (yes or no) and burning (yes or no) were treated as fixed factors in the model 

applied in factorial combination. As posttreatment understory data were collected 

in 2005 and two units were not burned until 2006, the analysis was unbalanced in 

regard to burning (eight units unburned, four units burned), but balanced in regard 

to thinning. Separate tests were performed for richness and cover of each life form 

and overall richness and cover of all understory species. Marginal means were used 

to estimate the mean value and standard error for each of the four treatments with 

each variable for interpretation of the statistical tests.

The influence of environmental variables on community composition was 

assessed using nonmetric multidimensional scaling (NMS) (McCune and Grace 

2002). We used the slow and thorough autopilot mode in PC-ORD (McCune and 

Mefford 1999) with a stepdown from six dimensions, with a random starting 

configuration and Sorenson distance measure. A Monte Carlo test with 250 

randomizations was performed to determine the likelihood of obtaining as good 

a solution by chance. All species (including those that were uncommon) were 

included in the analysis. The final NMS solution had three axes, and correlations 

with environmental variables were calculated for each axis. Those with an r

2

greater than 0.2 were plotted on the graphs with site scores.
17

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Relationships between overstory and understory variables were assessed 

using Pearson correlations in SPSS (2001). All data were averaged to the plot level 

(n = 72) for these analyses. Four measures of overstory trees, basal area, trees per 

hectare, canopy cover, and percentage of trees per hectare that are ponderosa pine 

(Pinus ponderosa Dougl. ex Laws) were correlated with understory richness and 

cover for each life form and overall.

Total understory cover and richness were averaged to the site level for each year 

of pretreatment sampling (2000 or 2001) to determine if obvious trends between 

years were evident. Means and standard errors for cover and richness were calculated for each site in each year to look for systematic year biases. One site (Sand 

19) had three plots sampled in each year. Therefore, the three plots sampled in each 

year were considered separately. 

Results and Discussion

Overstory Structure and Composition

Forest density and stocking were similar among the study units prior to the 

experiment (table 2-1). Live tree density averaged 589 (standard error [SE] = 52) 

trees/ha, and basal area averaged 33.2 (SE = 1.5) m2/ha over all treatment units. 

Diameter distributions for each unit were generally bell-shaped indicating an evensized structure; however, the distribution of tree diameters on higher elevations 

Table 2-1—Pretreatment structural characteristics for each treatment combination at the Mission Creek 

study site

Control Burn Thin Thin-Burn

Structural characteristic Mean SE Mean SE Mean SE Mean SE

Live tree density (trees/ha) 593 104 478 79 627 125 659 135

Basal area (m2/ha) 33.5 0.5 31.9 5.9 34.5 2.9 33.1 2.1

Stand density index 616 16 572 97 643 42 626 43

Quadratic mean diameter (cm) 28.8 1.5 29.9 0.1 27.7 2.5 26.2 1.7

Overstory ponderosa pine (% of trees) 22.2 15.2 56.5 20.0 43.8 26.4 40.7 28.2

Canopy cover (%) 87.6 1.8 79.1 4.4 82.4 7.9 87.7 6.3

Canopy height (m) 18.7 0.7 18.9 0.5 19.1 0.1 17.8 0.1

Canopy base height (m) 3.9 0.6 3.8 0.7 4.6 0.6 4.2 0.7

Canopy bulk density (kg/m3) 0.077 0.002 0.067 0.008 0.080 0.007 0.078 0.006

Snag Density (snags/ha) 58.3 11.1 49.2 13.8 51.1 17.5 30.6 11.3

Snag basal area (m2/ha)* 1.4ab 0.4 1.8ab 0.3 2.5b 0.3 0.8a 0.4

SE = standard error, n = 3.

* No significant differences were found between treatments for forest structural components, with the exception of snag basal area. For 

this variable, cells with different letters are significantly different (p < 0.1), with analyses based on post hoc pairwise comparisons. 

Diameter distributions 

for each unit were 

generally bell-shaped 

indicating an evensized structure.
18

RESEARCH PAPER PNW-RP-577

units tended to be slightly irregular (i.e., Ruby and Camas). Units dominated 

by Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) had higher densities of 

understory or subcanopy trees, particularly in the 10- to 20-cm d.b.h. class (fig. 2-1). 

Density, basal area, and stand density index (SDI) were somewhat lower on burn-only 

units as compared to the other treatments, but the differences were not significant. 

Tree density was higher on cooler, NE-facing units and on steeper slopes (tables 2-2 

and 2-3). These sites are generally less water-limited, and dense understory tree layers 

often form under these conditions. Basal area was not correlated with either aspect or 

Figure 2-1—Diameter distributions for live trees located on treatment units within the Mission Creek study site. Units are arranged 

by treatment based on a balanced design with three replications per treatment combination. PIPO = Pinus ponderosa; PSME = 

Pseudotsuga menziesii.
19

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Table 2-2—Treatment unit descriptions, including treatment applied (planned treatment in parentheses), 

topographic attributes, and forest structural characteristics for the Mission Creek study sites

Treatment Treatment Mean Mean Folded Heat load Tree Tree

unit description elevation slope aspect index density basal area

Meters Percent Trees/ha (m2/ha)

Crow 3 Control 747 38 2.17 0.87 470 (48) 32.5 (1.9)

Sand 19 Control 780 43 2.46 0.93 510 (93) 34.0 (3.1)

Sand 2 Control 683 58 1.40 0.70 800 (129) 34.1 (1.6)

Pendleton Control (burn only) 841 16 2.59 0.91 342 (70) 22.7 (2.3)

Poison Burn only 768 40 2.50 0.90 476 (77) 30.2 (2.8)

Spromberg Burn only 848 57 2.36 0.90 616 (48) 42.7 (3.5)

Crow 1 Thin 738 21 2.18 0.90 487 (54) 29.0 (2.3)

Ruby Thin 975 43 2.60 0.94 518 (104) 38.7 (4.9)

Slawson Thin 838 35 1.39 0.81 875 (132) 44.6 (3.4)

Crow 6 Thin (thin-burn) 718 26 2.04 0.84 568 (98) 34.1 (4.9)

Camas Thin-burn 1097 43 1.30 0.73 485 (38) 29.0 (2.4)

Tripp Thin-burn 765 67 0.79 0.57 925 (116) 36.1 (2.6)

Note: Numbers in parentheses for tree density and basal area are standard errors. 

Table 2-3—Pearson’s correlation coefficients (r) for basic overstory structural and compositional components 

and biophysical environment

 Heat Tree Pine Basal Mean Canopy Sapling Snag

Slope Folded load density percentage area diameter cover density density

Variable (percent) aspect index (trees/ha) of trees (m2

/ha) (cm) (percent) (trees/ha) (snags/ha)

Slope (percent) 1.00 -0.31 -0.46 0.28 -0.64 0.21 -0.15 0.26 -0.14 0.08

Folded aspect -0.31 1.00 0.92 -0.47 0.37 0.00 0.55 -0.33 -0.32 -0.19

Heat load index -0.46 0.92 1.00 -0.39 0.38 0.07 0.50 -0.29 -0.23 -0.11

Tree density (trees/ha) 0.28 -0.47 -0.39 1.00 -0.44 0.50 -0.76 0.39 0.46 0.44

Overstory ponderosa pine -0.64 0.37 0.38 -0.44 1.00 -0.44 0.10 -0.59 -0.18 -0.18

 (percentage of trees)

Basal area (m2/ha) 0.21 0.00 0.07 0.50 -0.44 1.00 0.09 0.44 0.07 0.36

Mean diameter (cm) -0.15 0.55 0.50 -0.76 0.10 0.09 1.00 -0.10 -0.39 -0.29

Canopy cover (percent) 0.26 -0.33 -0.29 0.39 -0.59 0.44 -0.10 1.00 0.09 0.24

Sapling density (trees/ha) -0.14 -0.32 -0.23 0.46 -0.18 0.07 -0.39 0.09 1.00 0.05

Snag density (snags/ha) 0.08 -0.19 -0.11 0.44 -0.18 0.36 -0.29 0.24 0.05 1.00

Note: Correlation analyses were conducted at the plot level. Bold-faced type indicates statistically significant correlations (p < 0.05).

HLI, most likely because the large number of small-diameter trees on the cooler sites 

does not contribute appreciably to basal area. Quadratic mean diameter was similar 

among treatments and averaged 28.1 (SE = 0.8) cm. Average diameters were larger on 

drier units where densities of small understory trees were lower. 

Douglas-fir represented over half of the trees on experimental units and ponderosa pine made up >40 percent (fig. 2-1). Ponderosa pine dominance was somewhat 

lower on control units and higher on thin-only units, but there were no significant 

differences between treatments. Although there was much variability in species 

Douglas-fir represented 

over half of the trees 

on experimental units 

and ponderosa pine 

made up >40 percent.
20

RESEARCH PAPER PNW-RP-577

composition, there were no significant differences between treatment combinations 

(table 2-1). The lack of significance is most likely due to the large standard errors 

associated with ponderosa pine dominance, which represents high within-treatment 

variability (table 2-1). In general, each treatment combination included one unit 

dominated by ponderosa pine, one by Douglas-fir, and one by mixed conifers (fig. 

2-1). Douglas-fir dominance was higher on cooler, NE-facing units and on steeper 

slopes, and ponderosa pine dominance increased on warmer, SW-facing slopes. 

Other species observed in the experiment include grand fir (Abies grandis (Dougl. 

ex D. Don) Lindl.) and western larch (Larix occidentalis Nutt.), which generally 

occurred at higher elevations (>900 m). 

The overstory composition at the Mission Creek site is somewhat different than 

other dry forest sites in the FFS network. The Southwest Plateau site in northern 

Arizona is more dominated by ponderosa pine than Mission Creek, largely owing 

to warmer and drier conditions (Fulé et al. 2001b). The Blodgett site in the southern 

Sierra Nevada is more overstory-species rich with higher tree densities than 

Mission Creek (Stephens and Moghaddas 2005) and the Lubrecht site in western 

Montana has a lodgepole pine (Pinus contorta Dougl. ex Loud.) component (Metlen 

and Fiedler 2006), which is missing from Mission Creek. The overstory at our site 

is probably most similar to Hungry Bob in eastern Oregon, although our climate 

is slightly more maritime as opposed to continental conditions in eastern Oregon 

(Youngblood et al. 2006). These differences in overstory structure make 

the Mission Creek site important to the overall understanding of treatment 

responses in a range of dry forest types. 

Canopy cover averaged >80 percent across all treatment units, and there 

were no significant differences between treatments. Canopy cover was higher on 

Douglas-fir-dominated units and increased with higher tree densities. Canopy 

bulk density (CBD) averaged 0.071 (0.005) kg/m3 and was statistically similar 

among treatments. Canopy base height (CBH), a measure of the vertical distance 

from the forest floor to the lowest point in the canopy where CBD is equal to 0.011 

kg/m3 (Reinhardt and Crookston 2003), averaged ~4 m on all treatment units and 

was not significantly different among treatments. These values are comparable to 

those reported by Stephens and Moghaddas (2005) for mixed-conifer forests of the 

Sierra Nevada, which were found to be highly susceptible to crown fires modeled 

under 90th- and 97th-percentile weather conditions. Similar results were found in 

ponderosa pine forests of northern Arizona prior to restoration treatments (Fulé et 

al. 2001a). Further, recent large-scale high-severity fires have burned in the forests 

surrounding Mission Creek, which suggests that our study area is susceptible to 

such a disturbance.

Canopy cover averaged 

>80 percent across all 

treatment units.
21

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Sapling densities were also similar across all treatments prior to the experiment and averaged 235 per ha (range 32 to 405 per ha). There were no significant 

differences in sapling densities between treatments; however, sapling densities 

were highly variable within treatment with densities increasing on cooler, moister 

units. On average, about two-thirds of the saplings were Douglas-fir (range 9 to 97 

percent). Grand fir saplings were present on higher elevation units, particularly at 

the highest elevation site where more than 300 grand fir saplings were tallied per 

hectare. The sapling layer at Mission Creek was most likely not present historically 

as it was suppressed by frequent, low-intensity surface fires (Harrod et al. 1999). 

This layer adds structural complexity to the forest by increasing canopy layering 

and lowering CBH; both of which increase crown fire susceptibility (Peterson et al. 

2005). 

Snag density (snags per hectare), but not snag basal area, was statistically 

similar across units prior to treatments (table 2-1, fig. 2-2). Snag density was higher 

in denser stands, and most snags were <20 cm d.b.h. The majority of snags were 

ponderosa pine on most units, with the exception of the higher elevation units and 

units heavily dominated by Douglas-fir (fig. 2-2). Snag basal area was significantly 

higher on thin-only units compared to thin-burn units, which had one-third the 

snag basal area of thin-only units. 

Figure 2-2—Basal area of snags on treatment units within the Mission Creek study site. 

PIPO = Pinus ponderosa; PSME = Pseudotsuga menziesii.

Snag density (snags 

per hectare), but not 

snag basal area, was 

statistically similar 

across units prior to 

treatments.
22

RESEARCH PAPER PNW-RP-577

Understory Structure and Composition

The majority of species found at our study site had low cover and frequency prior to 

any treatment application, which is similar to other forest ecosystems (Dodson et al. 

2007, Peterson and Reich 2008, Stohlgren et al. 2005). A total of 124 species were 

identified at our 12 units, but the majority of these species were not abundant. The 

five most frequent species were all graminoids and shrubs; Amelanchier alnifolia

(Nutt.) Nutt. ex M. Roem., Carex geyeri Boott, Calamagrostis rubescens Buckley, 

Rosa spp., and Symphoricarpos albus (L.) S.F. Blake. The most frequent forb was 

Osmorhiza berteroi DC., which was the sixth most frequent species overall, and 

the forb with the highest cover was Arnica cordifolia Hook., which had the ninth 

highest cover among all species. Only 10 species had more than 1 percent cover 

each and made up over 78 percent of total understory cover. Eighty-three species 

had less than 0.1 percent cover each, making up just over 3 percent total understory 

cover. A similar pattern was also apparent with frequency. There were only 15 

species that occurred on more than half the plots, and 67 species occurred on less 

than one-tenth of the 72 plots. 

Shrubs and graminoids made up the majority of understory cover across all 

units, whereas forbs made up the majority of understory richness (fig. 2-3). There 

was considerable variability among units in total cover and cover for each life form 

(fig. 2-3a). Average vascular plant cover for the 12 units ranged from 23.7 to 78.7 

Figure 2-3—Mean cover (a) and richness (b) for each life form on the 12 Mission Creek treatment units.

A total of 124 species 

were identified at 

our 12 units, but the 

majority of these 

species were not 

abundant.
23

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

percent. Each life form also differed among units, ranging from 2.4 to 38.7 percent 

cover for graminoids, from 3 to 16.3 percent cover for forbs, and from 8.8 to 43.5 

percent shrub cover. Richness also showed considerable variability among units, 

although the variability was considerably less than for cover (fig. 2-3b). Among the 

12 units, total richness per plot ranged from 17.3 to 29.8, graminoid richness from 

1.7 to 4.8, forb richness from 8.6 to 18.5, and shrub richness from 4.3 to 11.

Despite the considerable variability among units in cover and richness for each 

life form, much of the variability was still within units. Partitioning the variance in 

cover into within- and among-site components revealed that most of the variability 

in cover for shrubs and forbs was within units (fig. 2-4). Only graminoid cover 

varied more among units than within units. Richness was about roughly equally 

divided into within and among unit components for each of the three life forms 

(fig. 2-4). 

Figure 2-4—Diversity partitioning into within- and among-unit components for (a) cover and (b) richness of the Mission Creek site.

Total Shrub Forb Graminoid

100

80

60

40

20

0

Plant cover

Percentage of total variance

Within units

Among units

Total Shrub Forb Graminoid

100

80

60

40

20

0

Percentage of total variance

Within units

Among units

Plant species richness

a b

The understory vegetation at the Mission Creek units has notable similarities 

with and differences from the understory in other dry forests of the Western United 

States. Understory cover at our study site was dominated by shrubs and graminoids, 

whereas forbs and shrubs made up the majority of cover in a dry Montana mixedconifer forest (Metlen and Fiedler 2006). Graminoids and forbs are more dominant 

in ponderosa pine forests in the Blue Mountains of eastern Oregon (Metlen et al. 

2004, Youngblood et al. 2006) and in northern Arizona (Bailey and Covington 
24

RESEARCH PAPER PNW-RP-577

2002). As on our site, high forb richness is a common pattern throughout dry 

forests of the Western United States (Metlen and Fiedler 2006, Wayman and 

North 2007).

Comparisons among assigned treatments—

There were numerous significant pretreatment differences in understory vegetation 

among treatment units (table 2-4). Total understory cover averaged 56.5 percent in 

the unthinned units (burn-only and control) and was significantly greater than the 

38.0 percent total cover in the thinned units (thin-burn and thin-only) (P = 0.0562). 

There was also a significant difference in species richness between the thinned and 

unthinned units (P = 0.0879), with the unthinned units averaging almost five more 

species per plot than thinned units (table 2-4). 

Table 2-4—Means (and standard errors) of understory vegetation conditions within and among treatment 

groups prior to treatment

Mean treatment value	 Pretreatment effect significance

Variable Control Burn-only Thin-only Thin-burn Thin Burn Thin × Burn

Total understory cover (%) 51.44 (5.52) 61.62 (17.09) 47.38 (6.23) 28.69 (5.00) 0.056 NS NS

Total understory richness 25.37 (1.78) 27.00 (2.83) 21.13 (1.15) 22.17 (4.83) 0.088 NS NS

Shrub cover (%) 14.50 (3.93) 33.34 (10.13) 21.32 (2.9) 18.88 (3.68) NS NS 0.063

Shrub richness 5.79 (0.81) 9.42 (1.58) 6.38 (0.69) 8.67 (2.00) NS 0.029 NS

Forb cover (%) 10.89 (2.93) 12.39 (2.61) 8.41 (1.44) 6.14 (2.09) NS NS NS

Forb richness 15.42 (1.53) 13.33 (1.17) 10.75 (0.55) 10.92 (2.25) 0.040 NS NS

Graminoid cover (%) 25.59 (3.66) 15.18 (4.94) 17.5 (7.33) 3.42 (1.00) NS 0.089 NS

Graminoid richness 3.21 (0.30) 3.08 (0.08) 3.21 (0.55) 2.08 (0.42) NS NS NS

Pretreatment conditions analysis of variance (using unbalanced design produced by actual, not planned, treatments).

Note: NS = No statistically significant differences among treatment groups (P > 0.1)

There were also pretreatment differences among assigned treatment units for 

each life form (table 2-4). The interaction of thinning and burning treatment assignments was significant for shrub cover (P = 0.0630), suggesting that units assigned to 

each treatment had different values for shrub cover (table 2-4). Shrub richness was 

significantly higher at the units that were slated to receive burn treatments than the 

units not designated for a burning treatment (P = 0.0291). Forb cover did not differ 

significantly among units assigned to treatments, but forb richness was significantly 

lower on thinned units than on unthinned units (P = 0.040). Similarly, graminoid 

cover was significantly lower in the burned units than in the unburned units (P = 

0.089; table 2-4) reflecting especially high graminoid cover in control units and low 

graminoid cover in thin-burn units.

There were numerous 

significant pretreatment 

differences in understory vegetation among 

treatment units.
25

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

High variability among sites has also been observed in southwestern dry 

conifer forests (Abella and Covington 2006, Fulé et al. 2005, Gildar et al. 2004). 

The ubiquity of pretreatment differences in understory vegetation suggests that site 

characteristics, including the biophysical environment and the disturbance history 

of the site, may significantly influence vegetation composition. This highlights the 

need for pretreatment data to draw reasonable conclusions in these highly variable forests. Partitioning the variance into within- and among-unit components 

also revealed that much of the variability in these forests occurs at smaller spatial 

scales (i.e., much of the variabilities in cover and richness were within the 10-ha 

units). This high pretreatment variability among and within units contributes to the 

biodiversity of the Mission Creek dry forest ecosystem.

Environmental influences on understory—

Units differed considerably prior to treatment application in their understory 

communities as evidenced by the separation in ordination space (fig. 2-5). The 

nonmetric multidimensional scaling (NMS) ordination resulted in three axes that 

explained 83 percent of the variation in the original data set. The final solution 

with three dimensions was much better than expected by chance (P = 0.004). The 

third axis explained by far the most variation in the understory community (52 

percent), and was positively correlated with trees per hectare and elevation while 

negatively correlated with the percentage of trees that were ponderosa pine and 

graminoid cover. The first axis explained 16 percent of the variation in the original 

data set, and was positively correlated with shrub cover (fig. 2-5a). The second axis 

explained 15 percent of the variation and was not significantly correlated with any 

measured environmental variables. Pretreatment canopy cover and basal area were 

not strongly correlated (r

2

 < 0.2) with any of the axes in this study.

Understory vegetation showed significant correlations with overstory variables 

(table 2-5). In general, trees per hectare, basal area, and/or canopy cover were 

negatively correlated with understory cover and richness. However, tree density had 

a much stronger negative effect on understory vegetation than basal area or canopy 

cover (table 2-5). Graminoids had more significant correlation with overstory structure variables than forbs and shrubs. Despite being negatively correlated with tree 

density, basal area, and canopy cover, graminoid cover and richness were positively 

correlated with a ponderosa pine overstory. Shrubs were not significantly correlated 

with a ponderosa pine overstory, but forb richness was reduced with an increased 

presence of ponderosa pine in the overstory (table 2-5).

The understory vegetation in this study was influenced by environmental conditions and overstory trees. Elevation played an important role in dictating understory 

Site characteristics, 

including the biophysical environment 

and the disturbance 

history of the site, may 

significantly influence 

vegetation composition.
26

RESEARCH PAPER PNW-RP-577

Figure 2-5—Nonmetric multidimensional scaling (NMS) ordination of Mission Creek understory 

species data prior to treatment with environmental variables with >0.2 correlation with axes 1 and 3 

(a) and 2 and 3 (b).
27

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

composition (fig. 2-5), which has also been documented in dry coniferous forests 

of the Southwestern United States (Fischer and Fulé 2004). In general, overstory 

trees had negative effects on understory species (table 2-5), a pattern that has been 

well documented for dry coniferous forests (Riegel et al. 1992, 1995). Interestingly, 

graminoid cover and richness were positively associated with stands that had higher 

proportions of ponderosa pine. Tree density had much stronger negative effects on 

the understory community than basal area or canopy cover. In dry forests, trees 

may reduce understory growth more by competing for belowground nutrients than 

by shading (Riegel et al. 1992). Units with higher tree densities were the result 

of many trees in smaller size classes (fig. 2-1), which may have a larger effect on 

understory species than basal area or canopy cover. This suggests that treatments 

should focus more on reducing stand density (trees per hectare) than on basal area 

to benefit understory species.

Effects of sample year—

There was a large amount of unit-to-unit variability in understory cover within 

both pretreatment sample years. On average, units sampled in 2000 had 9.1 percent 

more cover than units sampled in 2001 (fig. 2-6). Much of the difference between 

years may be due to one unit with very high cover sampled in 2000 (Poison). The 

understory cover in Poison was more than 13 percent higher than the second highest 

unit in either pretreatment sampling year. Also, Sand 2, which had plots sampled 

in both years, actually had higher average cover on the plots that were sampled in 

2001, contradicting the overall trend. Overall, there appears to be no obvious trend 

between the 2 years of pretreatment sampling for understory cover. 

Table 2-5—Relationships between overstory stand structure and understory vegetation characteristics 

prior to treatment, as indicated by Pearson correlation coefficients (r) and associated significance levels (P) 

in parentheses

Tree basal area Tree density Tree canopy cover Ponderosa pine

(m2/ha) (trees/ha) (percent) (percent)

Understory vegetation characteristic r (P) r (P) r (P) r (P)

Understory cover (percent) -0.24 (0.04) -0.45(< 0.001) -0.10 (0.44) 0.20 (0.09)

Understory richness -0.09 (0.46) -0.38 (0.001) -0.22 (0.09) -0.13 (0.26)

Shrub cover (percent) -0.02 (0.86) -0.24 (0.04) -0.02 (0.89) -0.05 (0.66)

Shrub richness 0.20 (0.09) -0.14 (0.24) -0.08 (0.54) -0.13 (0.29)

Forb cover (percent) -0.15 (0.22) -0.17 (0.16) 0.01 (0.97) -0.07 (0.56)

Forb richness -0.14 (0.23) -0.26 (0.03) -0.06 (0.63) -0.26 (0.03)

Graminoid cover (percent) -0.27 (0.02) -0.30 (0.01) -0.13 (0.31) 0.41 (< 0.001)

Graminoid richness -0.32 (0.01) -0.37 (0.002) -0.50(< 0.001) 0.52 (< 0.001)

Note: Ponderosa pine (percent) is the percentage of overstory trees that are ponderosa pine (tree density basis). Bold-faced type 

indicates statistically significant correlations (P < 0.10).

Treatments should 

focus more on 

reducing stand 

density than on 

basal area to benefit 

understory species.
28

RESEARCH PAPER PNW-RP-577

Figure 2-6—Site means for (a) cover and (b) richness (+ standard error) for the two pretreatment 

sample years at the Mission Creek site.
29

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

There was high variability among units, even within a given year, for understory richness. Richness was higher in 2001 than in 2000 by an average of about 

four species per plot, which was opposite the pattern for cover (fig. 2-6). Sand 2 had 

very little difference in species richness between plots sampled in 2000 and those 

sampled in 2001. Overall, there was little evidence of a strong year effect that may 

bias later results.

Conclusions

Overstory vegetation at the Mission Creek site was generally similar across all 

pretreatment units, but understory vegetation was highly variable. Tree density, 

snag density, live tree basal area, stand density index, sapling density, species 

composition, canopy cover, canopy bulk density, and canopy base height were 

statistically similar among the four assigned treatments. Only snag basal area was 

significantly higher on thin-only units compared to thin-burn units. Overstory 

vegetation at Mission Creek is relatively unique compared to most other sites in 

the FFS network.

Understory vegetation was variable among treatment units, but much more 

variable within units. The Mission Creek site is fairly species rich with 124 species, mostly dominated by graminoids and shrubs, but most species had low cover 

and frequency prior to treatment application. Species richness and cover was 

significantly different among assigned treatments, highlighting the importance of 

pretreatment measurements rather than the use of just control units. Understory 

community structure also differed among treatment units, and understory vegetation was correlated with physical and biological elements, such as elevation and 

overstory tree density. These correlations suggest that restoration treatments may be 

targeted to have positive effects on understory vegetation. Finally, there was a large 

amount of unit-to-unit variability in understory cover and richness between sample 

years, but there was little evidence of a strong year effect that may bias later results.

Literature Cited

Abella, S.R.; Covington, W.W. 2006. Forest ecosystems of an Arizona Pinus 

ponderosa landscape: multifactor classification and implications for ecological 

restoration. Journal of Biogeography. 33: 1368–1383.

Agee, J.K. 1993. Fire ecology of Pacific Northwest forests. Washington, DC: 

Island Press. 491 p.
30

RESEARCH PAPER PNW-RP-577

Agee, J.K. 1994. Fire and weather disturbances in terrestrial ecosystems of 

the eastern Cascades. Gen. Tech. Rep. PNW-GTR-320. Portland, OR: U.S. 

Department of Agriculture, Forest Service, Pacific Northwest Research Station. 

52 p.

Agee, J.K. 1998. The landscape ecology of western forest fire regimes. Northwest 

Science. 72(special issue): 24–34.

Armstrong, G.W.; Cumming, S.G. 2003. Estimating the cost of land base 

changes due to wildfire using shadow prices. Forest Science. 49(5): 719–730.

Arno, S.F.; Smith, H.Y.; Krebs, M.A. 1997. Old growth ponderosa pine and 

western larch stand structures: influences of pre-1900 fires and fire exclusion. 

Res. Pap. INT-RP-495. Ogden, UT: U.S. Department of Agriculture, Forest 

Service, Intermountain Research Station. 20 p.

Bailey, J.D.; Covington, W.W. 2002. Evaluating ponderosa pine regeneration 

rates following ecological restoration treatments in northern Arizona, USA. 

Forest Ecology and Management. 155: 271–278.

Collins, B.M.; Moghaddas, J.J.; Stephens, S.L. 2007. Initial changes in forest 

structure and understory plant communities following fuel reduction activities 

in a Sierra Nevada mixed conifer forest. Forest Ecology and Management. 

239: 102–111.

Covington, W.W.; Fulé, P.Z.; Moore, M.M.; Hart, S.C.; Kolb, T.E.; Mast, J.N.; 

Sackett, S.S.; Wagner, M.R. 1997. Restoring ecosystem health in ponderosa 

pine forests. Journal of Sustainable Forestry. 2: 153–181.

Covington, W.W.; Moore, M.M. 1994. Southwestern ponderosa pine forest 

structure: changes since Euro-American settlement. Journal of Forestry. 

92: 39–47.

Dodson, E.; Metlen, K.; Fiedler, C. 2007. Common and uncommon understory 

species differentially respond to restoration treatments in ponderosa pine/

Douglas-fir forests, Montana. Restoration Ecology. 15: 696–708.

Everett, R.L.; Schellhaas, R.; Anderson, T.A.; Lehmkuhl, J.F.; Camp, A.E. 

1996. Restoration of ecosystem integrity and land use allocation objectives in 

altered watersheds. In: McDonnel, J.J.; Stribling, J.B.; Neville, L.R.; Leopold, 

D.J. eds. American Water Resources Association on watershed restoration 

management. Herndon, VA: American Water Resources Association: 271–280.
31

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Everett, R.L.; Schellhaas, R.; Keenum, D.; Spurbeck, D.; Ohlson, P. 2000. 

Fire history in the ponderosa pine/Douglas-fir forests on the east slope of the 

Washington Cascades. Forest Ecology and Management. 129: 207–225.

Fischer, M.A.; Fulé, P.Z. 2004. Changes in forest vegetation and arbuscular 

mycorrhizae along a steep elevation gradient in Arizona. Forest Ecology and 

Management. 200: 293–311.

Fulé, P.Z.; Laughlin, D.C.; Covington, W.W. 2005. Pine-oak forest dynamics 

five years after ecological restoration treatments, Arizona, USA. Forest Ecology 

and Management. 218: 129–145.

Fulé, P.Z.; McHugh, C.M.; Heinlein, T.A.; Covington, W.W. 2001a. Potential 

fire behavior is reduced following forest restoration treatments. In: Vance, R.K.; 

Covington, W.W.; Edminster, C.B.; Blake, J., eds. Ponderosa pine ecosystems 

restoration and conservation: steps toward stewardship. Proc. RMRS-P-22. 

Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain 

Research Station: 28–35.

Fulé, P.Z.; Waltz, A.E.M.; Covington, W.W.; Heinlein, T.A. 2001b. Measuring 

forest restoration effectiveness in reducing hazardous fuels. Journal of Forestry. 

98: 24–29.

Gildar, C.N.; Fulé; P.Z.; Covington, W.W. 2004. Plant community variability 

in ponderosa pine forest has implications for reference conitions. Natural Areas 

Journal. 24: 101–111. 

Hall, F.C. 1977. Ecology of natural underburning in the Blue Mountains of Oregon. 

Report PNW R6-ECOL-79-001. Portland, OR: U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Region. 11 p.

Harrod, R.J.; McRae, B.H.; Hartl, W.E. 1999. Historical stand reconstruction in 

ponderosa pine forests to guide silvicultural prescriptions. Forest Ecology and 

Management. 114: 433–446.

Hawksworth, F.G. 1977. The 6-class dwarf mistletoe rating system. Gen. Tech. 

Rep. RM-48. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Forest and Range Experiment Station. 7 p.

Hessburg, P.F.; Agee, J.K. 2003. An environmental narrative of inland Northwest 

US forests, 1800–2000. Forest Ecology and Management. 178: 23–59.

Hessburg, P.F.; Agee, J.K.; Franklin, J.F. 2005. Dry forests and wildland fires 

of the inland Northwest USA: contrasting the landscape ecology of the presettlement and modern eras. Forest Ecology and Management. 211(1–2): 117–139.
32

RESEARCH PAPER PNW-RP-577

Hessburg, P.F.; Smith, B.G.; Salter, R.B.; Ottmar, R.D.; Alvarado, E. 2000.

Recent changes (1930s-1990s) in spatial patterns of interior Northwest forests. 

Forest Ecology and Management. 136: 53–83.

Hurlbert, S.H. 1984. Pseudoreplication and the design of ecological field 

experiments. Ecological Monographs. 54: 187–211.

Keen, F.P. 1943. Ponderosa pine tree classes redefined. Journal of Forestry. 

41: 249–253.

Lemmon, R.E. 1956. A spherical densiometer for estimating forest overstory 

density. Forest Science. 2: 314–320.

Littell, R.C.; Milliken, G.A.; Stroup, W.W.; Wolfinger, R.D. 1996. SAS system 

for mixed models. Cary, NC: SAS Institute, Inc.

McCune, B.; Grace, J.B. 2002. Analysis of Ecological Communities. Gleneden 

Beach, OR: MjM Software Design.

McCune, B.; Keon, D. 2002. Equations for potential annual direct incident 

radiation and heat load. Journal of Vegetation Science. 13: 603–606.

McCune, B.; Mefford, M.J. 1999. PC-Ord. Multivariate analysis of ecological 

data. Version 4. Gleneden Beach, OR: MjM Software Design.

Metlen, K.L.; Fiedler, C.E. 2006. Restoration treatment effects on the understory 

of ponderosa pine/Douglas-fir forests in western Montana, USA. Forest Ecology 

and Management. 222: 355–369.

Metlen, K.L.; Fieldler, C.E.; Youngblood, A. 2004. Understory response to fuel 

reduction treatments in the Blue Mountains of northeastern Oregon. Northwest 

Science. 78: 175–185.

Peterson, D.L.; Johnson, M.C.; Agee, J.K.; Jain, T.B.; McKenzie, D.; 

Reinhardt, E.D. 2005. Forest structure and fire hazard in dry forests of the 

Western United States. Gen. Tech. Rep. PNW-GTR-628. Portland, OR: U.S. 

Department of Agriculture, Forest Service, Pacific Northwest Research Station. 

30 p.

Peterson, D.W.; Reich, P.B. 2008. Fire frequency and tree canopy structure 

influence plant species diversity in a forest-grassland ecotone. Plant Ecology. 

194: 5–16.

Raudenbush, S.W.; Bryk, A.S. 2002. Hierarchical linear models: applications and 

data analysis methods. Thousand Oaks, CA: Sage Publications.
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Reinhardt, E.D.; Crookston, N.L. 2003. The fire and fuels extension to the forest 

vegetation simulator. Gen. Tech. Rep. RMRS-GTR-116. Fort Collins, CO: U.S. 

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

209 p.

Riegel, G.M.; Miller, R.F.; Krueger, W.C. 1992. Competition for resources 

between understory vegetation and overstory ponderosa pine. Ecological 

Applications. 2: 71–85.

Riegel, G.M.; Miller, R.F.; Krueger, W.C. 1995. The effects of aboveground 

and belowground competition on understory species composition in a Pinus 

ponderosa forest. Forest Science. 41: 864–889.

Scott, J.H.; Reinhardt, E.D. 2001. Assessing crown fire potential by linking 

models of surface and crown fire behavior. Res. Pap. RMRS-RP-29. Fort 

Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain 

Experiment Station. 59 p.

Singer, J.D. 1998. Using SAS PROC MIXED to fit multilevel models, hierarchical 

models, and individual growth models. Journal of Educational and Behavioral 

Sciences. 24(4): 323–355.

Smith, H.Y.; Arno, S.F., eds. 1999. Eighty-eight years of change in a managed 

ponderosa pine forest. Gen. Tech. Rep. RMRS-GTR-23. Ogden, UT: U.S. 

Department of Agriculture, Forest Service, Intermountain Research Station. 

55 p.

SPSS, Inc. 2001. SPSS Base Version 10.1.3 for Windows. Chicago, IL: SPSS Inc. 

217 p. 

Stephens, S.L.; Moghaddas, J.J. 2005. Experimental fuel treatment impacts 

on forest structure, potential fire behavior, and predicted tree mortality in a 

California mixed conifer forest. Forest Ecology and Management. 215: 21–36.

Stohlgren, T.J.; Guenther, D.A.; Evangelista, P.H.; Alley, N. 2005. Patterns of 

plant species richness, rarity, endemism, and uniqueness in an arid landscape. 

Ecological Applications. 15: 715–725.

Wayman, R.B.; North, M. 2007. Initial response of mixed-conifer understory 

plant community to burning and thinning restoration treatments. Forest Ecology 

and Management. 239: 32–44.
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Weatherspoon, C.P.; Skinner, C.N. 1996. Landscape-level strategies for forest 

fuel management. In: Sierra Nevada Ecosystems Project: Final report to 

Congress, Vol II: Assessments, scientific basis for management options. Davis, 

CA: University of California, Centers for Water and Wildland Resources: 

1471–1492. Chapter 56. 

Youngblood, A.; Metlen, K.L.; Coe, K. 2006. Changes in stand structure 

and composition after restoration treatments in low elevation dry forests of 

northeastern Oregon. Forest Ecology and Management. 234: 143–163.
35

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

James K. Agee and M. Reese Lolley1

Introduction

One of the major goals of silvicultural treatment of dry forest stands is to reduce the 

behavior of potential wildfires by reducing fuels. Thinning and burning treatments 

have the potential to either increase or decrease dead fuel loading, so it is important 

to measure fuels and fire behavior effects of such treatments.

Methods

Dead and down fuels, herb and shrub biomass, and canopy fuel parameters were 

estimated at 30 to 35 sample points in each of the 12 experimental units (see chapter 

1). This allowed 1200 to 1400 m of line intersect transect per unit, sufficient to 

estimate average biomass of coarse woody debris within 20 percent of the mean 90 

percent of the time in similar mixed-conifer forests (Bate et al. 2004). Beginning 

at the upslope row of gridpoints, each separated by 40 m in columns and rows, 

alternate gridpoints were sampled (with an 80-m separation), with the samples in 

the next row offset one column from the previous ones. Both line intersect and 

plot samples were used for fuels. Where the soils grid and sampling were already 

established, the fuels grid used alternate gridpoints to avoid excessive impact by 

either group.

Dead and down woody load was measured using Brown’s (1974) fuel transect 

method. Two 20-m transects were deployed at random azimuths from sampled grid 

points. The second transect had to be separated by at least 90° from the first. Each 

transect began 5 m away from the gridpoint to avoid excessive ground disturbance 

to the sampled area. Fuels of different timelag classes (Rothermel 1983) were measured in different ways. One-hr timelag fuels (0 to 0.62 cm diameter) were tallied 

along the first 2 m of the transect; 10-hr timelag fuels (0.62 to 2.54 cm diameter) 

were tallied along the first 3 m; and 100-hr timelag fuels (2.55 to 7.62 cm diameter) 

were tallied along the first 5 m of the transect. Dead and down fuels larger than 

7.62 cm diameter (1,000-hr+ timelag) were individually measured along the entire 

20-m length of the transect in one of five decay classes (Brown 1974), with specific 

gravities ranging from 0.48 to 0.30. Forest floor depth was measured at three locations (10, 15, and 20 m), and separate depths were recorded for litter (recognizable 

Chapter 3: Fuels and Fire Behavior

1 James K. Agee is Emeritus Professor, College of Forest Resources, Box 32100, 

University of WA, Seattle, WA 98195 jagee@u.washington.edu; M. Reese Lolley was a 

graduate student, College of Forest Resources, University of Washington, and currently is 

an ecologist, The Nature Conservancy, Yakima, WA 98902.

Using 1200 to 1400 m of 

line intersect transect 

per unit is sufficient 

to estimate average 

biomass of coarse 

woody debris within 

20 percent of the mean 

90 percent of the time.
36

RESEARCH PAPER PNW-RP-577

organic material, Oi), and duff (intermediate to highly decomposed organic material, Oe). Fuelbed depth was measured as the height of the tallest dead woody fuel 

particle along three 1-m-long, closely spaced segments of the transect (9 to 10, 10 to 

11, and 11 to 12 m segments).

A regression to develop a depth-mass relationship for the forest floor was determined locally on the Ruby, Camas, and Pendleton experimental units, representing 

the geographical range of the units. Litter (n = 108) and duff (n = 21) samples were 

collected on 100-cm2 plots using a square board and cutting through litter and duff 

along its edges. Samples were removed down to mineral soil, obvious mineral fraction was discarded, and the remainder was bagged for laboratory analysis. Depth 

of both layers was recorded along four edges of each sample and averaged. In the 

lab, each sample was dried at 70 °C until a constant mass was obtained, and then 

a 3-cm3 subsample was ashed to determine mineral content. The mineral content 

in excess of 4 percent (Agee et al. 2002) was subtracted from the total forest floor 

biomass in calculating forest floor biomass for each sample, as it was assumed to be 

soil contamination. The mineral fraction determined from samples was 14.6 percent 

for litter and 21.6 percent for duff. Simple linear regression was used to develop 

general models for litter and duff mass from depth measurements obtained from the 

transect sampling.

Herbaceous and shrub fuel loading was estimated on a 400-m2 plot centered 

on each sampled gridpoint by an ocular estimation of cover, height, density, and 

dominant type based on procedures of Burgan and Rothermel (1984). Herbaceous 

fuels were placed in one of two classes: type 1, a fine herb like cheatgrass (Bromus 

tectorum L.), or type 2, a coarser herb such as pinegrass (Calamagrostis rubescens 

Buckl.) or elk sedge (Carex geyeri Boott). One of three average density classes 

(1 [low], 3, or 5 [high]) was assigned from the Burgan and Rothermel photo key, 

as were cover classes: 1 (10 to 40 percent cover), 3 (40 to 70 percent cover, and 

5 (70 to 100 percent cover). Depth was recorded as 70 percent of the maximum 

leaf or stalk height (Burgan and Rothermel 1984). Three shrub types were locally 

identified based on stem diameter and leaf thickness: type 1 (thin stems and leaves, 

such as shinyleaf spirea [Spiraea betulifolia Pall.] or dwarf rose [Rosa gymnocarpa

Nutt.]); type 2 (thick stems but thin leaves, such as antelope bitterbrush [Purshia 

tridentata (Pursh) DC.] or ocean spray [Holodiscus discolor (Pursh) Maxim.]); and 

type 3, (thick stems and thick leaves, such as snowbrush ceanothus [Ceanothus 

velutinus Dougl.]). Density, cover, and depth were also recorded for the shrub layer. 

Using these data, biomass of shrubs and herbs were calculated using the program 

FUELCALC (Reinhardt et al. 2006).
37

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Canopy fuel profiles were created by establishing square plots at each grid point 

where surface fuel transects were sampled. Plots were of variable size to include at 

least 10 trees per plot. Usually this was achieved with 400 m2 plots, but occasionally plots were as small as 25 m2

 or as large as 3600 m2. Data for all trees 1.4 m and 

taller included species, diameter at breast height, height to dead crown, height to 

live crown, and total height. Canopy closure was measured with a spherical densiometer at four directions from plot center, beginning in the upslope direction, and 

separated by 90°. Data were entered into the Forest Vegetation Simulator-Fire and 

Fuels Extension (FVS-FFE) (Reinhardt and Crookston 2003) to calculate canopy 

base height (CBH) and canopy bulk density (CBD), variables useful to predict 

crown fire hazard for each stand surrounding a sampled gridpoint.

Two types of analyses were applied to the fuels data. A canonical correspondence analysis (CCA) was used to evaluate the similarity of the entire fuels profile 

among units, and a nonparametric analysis of variance (ANOVA) was used to 

evaluate differences between individual fuel categories between units. Fuels and 

selected canopy parameters on experimental units (all variables in tables 3-1 and 

3-2) were described by CCA using PC-ORD v. 4.0 (McCune and Mefford 1999). 

Environmental variables chosen for comparison in the ordination included unit 

elevation, average slope, percentage of unit in southerly aspect, percentage ponderosa pine (Pinus ponderosa Dougl.), and past logging history (represented by 

dummy variables: 0 = no logging; 1 = logging up to 1930s only; 2 = logging since 

1970). Fuel differences between experimental units were tested using a nonparametric ANOVA by ranks (Kruskal-Wallis H test) using SPSS (2002), as sampled 

fuel populations rarely were normally distributed or had equal variances (Zar 1999). 

Table 3-1–Biomass (and standard errors) of dead and down surface fuels by experimental unit 

1-hr	 10-hr	 100-hr	 1,000-hr+ 	 1,000-hr+	 Forest floor

Unit fuel load fuel load fuel load sound fuel load rotten fuel load load

Mg/ha

Camas 1.9 (0.4) 2.3 (0.3) 6.4 (1.0) 11.6 (2.4) 4.5 (1.3) 23.0 (2.3)

Crow 1 0.3 (0.0) 1.5 (0.3) 5.7 (0.7) 11.9 (1.7) 7.8 (1.6) 45.6 (2.8)

Crow 3 0.7 (0.1) 1.6 (0.2) 2.8 (0.6) 6.7 (2.4) 2.3 (1.0) 39.5 (2.9)

Crow 6 0.3 (0.0) 1.3 (0.2) 4.4 (0.6) 8.8 (1.9) 3.2 (0.8) 43.1 (3.3)

Pendleton 0.3 (0.1) 2.4 (0.3) 5.2 (0.9) 16.5 (3.2) 2.1 (1.0) 53.3 (3.0)

Poison 1.5 (0.3) 1.7 (0.2) 3.0 (0.7) 5.1 (1.2) 9.7 (4.3) 37.0 (3.1)

Ruby 1.5 (0.3) 1.3 (0.2) 6.6 (1.5) 17.1 (4.1) 16.4 (4.6) 40.7 (4.3)

Sand 19 1.6 (0.2) 1.5 (0.2) 2.0 (0.5) 3.0 (1.8) 3.0 (1.7) 34.4 (2.9)

Sand 2 1.7 (0.3) 2.6 (0.4) 4.0 (0.8) 6.8 (1.5) 4.9 (1.4) 32.8 (2.3)

Slawson 1.3 (0.1) 0.8 (0.1) 4.2 (0.8) 8.1 (3.3) 10.2 (2.3) 25.1 (2.0)

Spromberg 1.4 (0.2) 2.3 (0.4) 6.9 (1.2) 12.3 (3.4) 9.6 (2.3) 38.7 (3.9)

Tripp 1.7 (0.4) 2.3 (0.4) 5.0 (1.2) 17.7 (5.0) 8.8 (3.0) 32.6 (2.3)
38

RESEARCH PAPER PNW-RP-577

Differences between groups (P < 0.05) were analyzed with the Dunn test, a nonparametric multiple comparison with unequal sample sizes statistic that takes into 

account the number of comparisons made by using a Bonferroni adjustment. This 

adjustment uses a smaller alpha value in pairwise comparisons to keep the actual 

probability of family-wide type I error at or below the desired level (the significance 

level here was set at alpha = 0.05).

Surface fuel models were assigned using the Northern Forest Fire Laboratory 

(NFFL) models available in 2000 (Albini 1976, Anderson 1982). On a 400-m2 plot 

centered on a sampled gridpoint, the proportion of the area in any of the 13 NFFL 

fuel models (minimum 10 percent cover) was recorded. Custom fuel models for 

each pretreatment unit were developed from the fuel transect data, with 0.5 cm of 

forest floor added to the 1-hr timelag fuel load. Worst-case fire weather was taken 

from Agee and Lolley (2006): 1-hr, 10-hr, and 100-hr fuel moisture were set at 3, 4, 

and 6 percent; open windspeed was set at 36 kph, and slope was held constant at 45 

percent, the average slope for all units at the site. Fuelbed depth was defined in two 

ways: (1) by the average height of the tallest dead fuel particle on each experimental 

unit, and (2) by average shrub height on each unit (based on 70 percent of measured 

shrub height) to account for shrub contribution to the fuelbed depth. Fire behavior 

simulations were run in NEXUS (Scott 1999) with the most common NFFL models 

(2, 5, 8, 9, and 10) and for each custom unit model using the two fuelbed depths. 

Results were expressed by the type of fire predicted by NEXUS: surface, a fire 

restricted to the surface fuel profile; passive, a fire that will transition from a surface fire to torching fire behavior and return to a surface fire; active, a fire that will 

Table 3-2—Vegetation characteristics (and standard errors) useful in fuel and fire modeling 

on experimental units

Canopy Canopy Canopy Herb Shrub Fuelbed

Unit closure base heighta bulk densitya biomass biomass depth

Percent Meters Kg/m3 Mg/ha Mg/ha Centimeters

Camas 63 (5) 1.2 0.056 0.1 (0.0) 2.5 (0.8) 11.2 (2.4)

Crow 1 65 (3) 4.6 0.043 1.2 (0.1) 6.3 (1.3) 9.2 (1.7)

Crow 3 65 (5) 2.7 0.056 0.4 (0.1) 6.3 (2.4) 7.7 (1.4)

Crow 6 55 (4) 4.3 0.044 1.1 (0.1) 3.3 (0.7) 10.1 (2.5)

Pendleton 71 (4) 3.0 0.052 0.5 (0.1) 2.0 (0.8) 11.8 (2.1)

Poison 64 (5) 2.4 0.052 0.3 (0.1) 8.8 (2.3) 10.0 (1.4)

Ruby 75 (3) 1.5 0.051 0.3 (0.1) 3.8 (1.0) 15.8 (3.6)

Sand 19 67 (5) 3.0 0.062 0.5 (0.1) 2.3 (1.4) 8.3 (1.6)

Sand 2 76 (5) 2.4 0.072 0.6 (0.1) 5.7 (1.6) 13.2 (2.7)

Slawson 80 (3) 1.2 0.116 0.5 (0.1) 4.3 (1.8) 6.3 (0.8)

Spromberg 75 (5) 1.2 0.060 0.1 (0.0) 5.8 (1.1) 9.9 (2.0)

Tripp 73 (4) 1.5 0.082 0.3 (0.1) 5.8 (2.0) 18.2 (3.6)

a Forest Vegetation Simulator—Fire and Fuels Extension (FVS-FFE) does not calculate standard errors.
39

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

torch and maintain itself as an active, running crown fire; and conditional, a rare 

situation where the canopy bulk density is high enough to maintain active crown 

fire, given the predicted rate of spread, but one that is not supported by surface fire 

flame lengths or torching.

Results and Discussion

Dead and down fuel, herb and shrub, and canopy variables showed moderate 

variability across experimental units (tables 3-1, 3-2). The CCA analysis (fig. 3-1) 

indicated that the total variance (“inertia”) was a very low 0.0566, suggesting 

considerable homogeneity among sites for fuels variables. The cumulative variance 

explained by the first three axes totaled 55 percent (axis 1, 34.2 percent; axis 2, 14.1 

percent; axis 3, 6.8 percent), and the correlation with the environmental variables 

and sample scores was 0.934 for axis 1 and 0.767 for axis 2. The environmental 

variables in figure 3-1 are shown as lines, with the direction indicating the 

correlation to axis and the line length indicating the strength of the relationship. 

The ordination separates the fuel characters of the units into three geographic 

groups: the first is at the left side of axis 1 and consists of the southerly group 

of units (Crow 1, Crow 3, Crow 6, and Pendleton). The second consists of the 

Figure 3-1—Canonical correspondence analysis of fuels data. Axis 1 was associated with increasing 

slope steepness (+) and percentage of forest in pine and percentage on south aspects (-). Axis 2 was 

less significantly associated with evidence of past logging (-) and elevation (+).

The CCA analysis suggested considerable 

homogeneity among 

sites for fuel variables.
40

RESEARCH PAPER PNW-RP-577

northeasterly units (Poison, Sand 19, Sand 2, and Slawson), and the third contains 

the westerly units (Camas, Ruby, Spromberg) plus Tripp (an anomalous primarily 

north aspect unit). The first group consists of units with a high proportion of 

southerly aspect, large basal area in ponderosa pine, and gentle slopes. The third 

group is at higher elevation, with more Douglas-fir (Pseudotsuga menziesii [Mirbel] 

Franco) basal area and steeper slopes, and the second group is intermediate to the 

first and third groups. These environmental variables are strongly related to axis 

1. Of the environmental variables included, past logging history was most highly 

correlated to axis 2, followed by elevation and basal area in ponderosa pine. 

Regression equations predicting forest floor mass from depth had coefficients 

of determination ranging from 0.75 to 0.86. Separate regressions for ponderosa 

pine-dominated litter, mixed Douglas-fir litter, a combined litter general model, 

and a duff general model are shown in figure 3-2.

The number of significant pairwise comparisons (of a possible total of 66 for 

each variable) between units was highest for the forest floor (23 for litter, 36 for 

duff), 1-hr timelag fuels (25), and herbaceous load (23) (Lolley 2005). The largest 

number of significant differences for all variables was between two groups of units: 

Crow 1-Crow 6-Pendleton versus Camas-Ruby-Slawson-Spromberg, and is fairly 

consistent with what the ordination showed. The dead and down fuel loads are 

either in the range of or lower than other mixed-conifer forests. The 1-hr and 10-hr 

fuel loads are in the range of southern Cascade and Sierra Nevada forests (Stephens 

and Finney 2002, Stephens and Moghaddas 2005, Thomas and Agee 1986), but 

100-hr and 1,000-hr+ (both sound and rotten) fuel mass is 25 to 65 percent of the 

load in these other regions. Mission Creek loads of larger coarse woody debris 

are more comparable to those of northern Arizona (Fulé et al. 2002). Forest floor 

loads are well below the reported loads in these other areas, ranging from 20 to 50 

percent of those loads. At Mission Creek, the duff (Oe) layer is generally poorly 

developed, and that is often where the bulk of the forest floor mass is found.

The canopy profiles appear fairly consistent with other mixed-conifer forests 

that have been protected from surface fires for many decades. Canopy closure 

values are high, averaging 69 percent, but typically canopy closure, as measured 

with densiometers, is about 20 percent higher than canopy cover as measured with 

densitometers (Ganey and Block 1994). Average canopy base heights (2.4 m) are 

low, representing the in-filling of shade-tolerant trees (Hessburg et al. 2005). Our 

canopy base heights are lower than those found by Harrod et al. (this volume) on 

selected 20- by 50-m plots in the same experimental units because we included 

trees 1 m and taller in our inventory (their smallest tree included was 7.62 cm). 

Average canopy bulk density (0.062 kg/m3) is lower than estimated for other 

The dead and down 

fuel loads are either in 

the range of or lower 

than other mixedconifer forests. 
41

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Figure 3-2—Depth/mass regressions for ponderosa pine, Douglas-fir, and mixed litter and for duff.
42

RESEARCH PAPER PNW-RP-577

Cascade and Sierra Nevada mixed-conifer forests (Stephens and Moghaddas 2005) 

but comparable to ponderosa pine forests of northern Arizona (Fulé et al. 2002) and 

what Harrod et al. (this volume) found on forested portions of the same experimental units.

Surface fire behavior models (fig. 3-3) assigned to experimental units were 

weighted toward NFFL 2 (a grass-dominated fuel type) and NFFL 5 (a shrub-dominated fuel type). Fuel types dominated by timber litter (NFFL 8, 9, and 10) did not 

cover a majority of the area of any unit. The average fuel load across all experimental units does not have a reasonable fit to any of the new set of standard surface fuel 

models (Scott and Burgan 2005). 

Fire behavior simulations using closest-fit NFFL models and worst-case (97 

percentile) weather (fig. 3-4, left) showed active crown fire to be associated with 

most units, which were dominated by NFFL models 2 and 5 (Albini 1976). For this 

analysis, the output used in the pie chart was weighted to 75 percent models 2 and 

5, and 25 percent allocated evenly between NFFL models 8, 9, and 10. Custom fuel 

models designed from the fuels data on each unit, and using the dead fuel particle 

height measured on the fuel transects, predicted more benign fire behavior with the 

same weather data (fig. 3-4, middle). Each unit represents one-twelfth of the total 

shown in the pie chart. Surface fire behavior dominated across the units, with only 

single units expressing passive (Camas) or active (Tripp) crown fire behavior. When 

fuelbed depth was defined by 70 percent of shrub depth on each unit, representative 

of the shrub component in the understory that was incorporated as part of the fuel 

load of the custom models, and maintaining the same fuel loads, the simulations 

produced results much more similar to the NFFL runs (fig. 3-4, right). The fire 

behavior in five units was predicted to be passive crown fire behavior (Crow 1, 

Crow 6, Pendleton, Poison, and Ruby), and the remaining seven units were predicted to have active crown fire behavior. Using the dead fuel particle height to 

represent fuelbed depth compresses the fuelbed to the extent that the packing ratio 

is too compact, so that the combustion properties of the fuelbed are not optimum. 

The increase in depth produces a more optimum packing ratio and makes fire 

behavior more intense. These results suggest that pretreatment conditions are 

conducive to severe fire behavior, and this has been borne out by empirical evidence 

on many recent wildfires in the area (Entiat 1970, Dinkelman 1988, Tyee 1994, 

Rat 1994, and Fischer 2004). The variability in predicted fire behavior between 

these fuel models argues for field calibration under average as well as worst-case 

fire behavior before they are used in fire management operations.

Results suggest 

that pretreatment 

conditions are 

conducive to severe 

fire behavior, and this 

has been borne out by 

empirical evidence.
43

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Figure 3-3—Closest-fit Northern Forest Fire Laboratory (NFFL) surface fuel models for the 12 experimental units. The NFFL models 

2 (timber and grass) and 5 (low shrub) were the most common models assigned. The NFFL models 8 (compact timber litter), 9 (loose 

timber litter), and 10 (litter plus understory) were also present on most units.

CamasCrow 1Crow 3Crow 6

Pendleton

Poison

Ruby

Sand 19

San 2

Slawson

Spromberg

Tripp

Experimental unit

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0

Fuel model presence (proportion)

Bare

NFFL 10

NFFL 9

NFFL 8

NFFL 7

NFFL 5

NFFL 2

Figure 3-4—Proportion of active, conditional, passive, and surface crown fire at Mission Creek experimental units. Left: classification 

according to best-fit Northern Forest Fire Laboratory (NFFL) models; middle, classification using fuelbed depth defined by dead particle 

fuel height; right, classification using a fuelbed depth better representing the shrub component of the fuelbeds.

Closest-fit

NFFL models

Fuelbed depth 

defined as dead fuel 

particle height

Fuelbed depth 

defined as 70 percent 

of shrub depth

Active

Conditional

Passive

Surface
44

RESEARCH PAPER PNW-RP-577

The fuels ordination and statistical comparisons suggest that the similarity of 

these experimental units is high, so that a randomized design for assigning treatments (control, thin, burn, and thin-burn) is justified. When units were grouped by 

proposed treatment (the balanced design of 2006), no main factor variables showed 

significant differences among treatment for the 12 variables analyzed (see tables 3-1 

and 3-2 for listing of variables). There was a single significant interaction for 1,000-

hr rotten fuels, indicating biomass in that category was higher on units proposed for 

thinning and lower on units proposed for burning treatment.

Literature Cited

Agee, J.K.; Lolley, M.R. 2006. Thinning and prescribed fire effects on fuels and 

potential fire behavior in an eastern Cascades forest, Washington. Fire Ecology. 

2(2): 142–158.

Agee, J.K.; Wright, C.S.; Williamson, N.; Huff, M.H. 2002. Foliar moisture 

content of Pacific Northwest vegetation and its relation to wildland fire behavior. 

Forest Ecology and Management. 167: 57–66.

Albini, F.A. 1976. Estimating wildfire behavior and effects. Gen. Tech. Rep. INT30. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain 

Research Station. 92 p.

Anderson, H.A. 1982. Aids to determining fuel models for estimating fire 

behavior. Gen. Tech. Rep. INT-122. Ogden, UT: U.S. Department of Agriculture, 

Forest Service, Intermountain Research Station. 22 p.

Bate, L.J.; Torgersen, T.R.; Wisdom, M.J.; Garton, E.O. 2004. Performance of 

sampling methods to estimate log characteristics for wildlife. Forest Ecology and 

Management. 199: 83–102.

Brown, J.K. 1974. Handbook for inventorying downed woody material. Gen. 

Tech. Rep. INT-16. Ogden, UT: U.S. Department of Agriculture, Forest Service, 

Intermountain Research Station. 24 p.

Burgan, R.E.; Rothermel, R.C. 1984. BEHAVE: fire behavior prediction and fuel 

modeling system–FUEL subsystem. Gen. Tech. Rep. INT-167. Ogden, UT: U.S. 

Department of Agriculture, Forest Service, Intermountain Research Station. 

126 p.

Fuels ordination and 

statistical comparisons 

suggest that these 

units are very similar 

and a randomized 

treatment design is 

justified.
45

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Fulé, P.Z.; Covington, W.W.; Smith, H.B.; Springer, J.D.; Heinlein, T.A.; 

Huisinga, K.D.; Moore, M.M. 2002. Comparing ecological restoration 

alternatives, Grand Canyon, Arizona. Forest Ecology and Management. 

170: 19–41.

Ganey, J.L.; Block, W.M. 1994. A comparison of two techniques for measuring 

canopy closure. Western Journal of Applied Forestry. 9: 21–23.

Hessburg, P.F.; Agee, J.K.; Franklin, J.F. 2005. Dry forests and wildland fires 

of the inland Northwest USA: contrasting the landscape ecology of the presettlement and modern eras. Forest Ecology and Management. 211(1–2): 117–139.

Lolley, M.R. 2005. Wildland fuel conditions and effects of modeled fuel 

treatments on wildland fire behavior and severity in dry forests of the Wenatchee 

Mountains. Seattle, WA: University of Washington. 145 p. M.S. thesis.

McCune, B.; Mefford, M.J. 1999. PC-Ord. Multivariate analysis of ecological 

data. Version 4. Gleneden Beach, OR: MjM Software Design.

Reinhardt, E.D.; Crookston, N.L. 2003. The fire and fuels extension to the forest 

vegetation simulator. Gen. Tech. Rep. RMRS-GTR-116. Fort Collins, CO: U.S. 

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

209 p. 

Reinhardt, E.D.; Lutes, D.; Scott, J. 2006. FuelCalc: a method for estimating fuel 

characteristics. In: Andrews, P.L.; Butler, B.W., comps. Fuels management—

how to measure success. Proceedings RMRS-P-41. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain Research Station: 

273–282.

Rothermel, R.C. 1983. How to predict the spread and intensity of wildfires. 

Gen. Tech. Rep. INT-193. Ogden, UT: U.S. Department of Agriculture, Forest 

Service, Intermountain Research Station. 161 p. 

Scott, J.H. 1999. NEXUS: a system for assessing crown fire hazard. Fire 

Management Notes. 59(2): 20–24.

Scott, J.H.; Burgan, R.E. 2005. Standard fire behavior fuel models: a 

comprehensive set for use with Rothermel’s surface fire spread model. Gen. 

Tech. Rep. RMRS-GTR-153. Fort Collins, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Experiment Station. 72 p.

SPSS. 2002. SPSS for Windows Version 11.5.0. Chicago, IL: SPSS, Inc.
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Stephens, S.L.; Finney, M.A. 2002. Prescribed fire mortality of Sierra Nevada 

mixed conifer tree species: effects of crown damage and forest floor combustion. 

Forest Ecology and Management. 162: 261–271.

Stephens, S.L.; Moghaddas, J.J. 2005. Experimental fuel treatment impacts 

on forest structure, potential fire behavior, and predicted tree mortality in a 

California mixed conifer forest. Forest Ecology and Management. 215: 21–36.

Thomas, T.B.; Agee, J.K. 1986. Prescribed fire effects on mixed conifer 

forest structure at Crater Lake, Oregon. Canadian Journal of Forest Research. 

16: 1082–1087.

Zar, J.S. 1999. Biostatistical analysis. 3rd ed. Upper Saddle River, NJ: Prentice 

Hall. 662 p.
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Chapter 4: Soils

Darlene Zabowski, Jeffrey Hatten, Elizabeth Dolan, and George Scherer1

Introduction

Soils in the Mission Creek study area occur on widely ranging slopes, aspects, 

elevations, parent materials, and topographic positions. Although the vegetation 

encompasses assemblages typical of ponderosa pine/Douglas-fir forests, it is also 

quite variable with some areas covered by thickets of young trees with sparse 

understory, whereas other areas have widely scattered trees with extensive grasses 

and shrubs. This variability could result in widely divergent soil types; therefore, 

a comprehensive study was made of soils in the area to insure that effects of 

prescribed burning could be determined despite soil variability. This report briefly 

summarizes the soils and soil properties found at the Mission Creek study site.

Methods

Soil Sampling

Soils were measured and sampled for physical and chemical properties during the 

summers of 2000 and 2001 using a grid with an 80-m spacing resulting in 15 to 21 

sampling sites for each study plot (plots were irregularly shaped and not equally 

sized). Major genetic horizons were identified and horizon thickness measured. 

Soil samples were collected for laboratory analyses from O, A, and B horizons 

(either Bw or Bt) as present, to a mineral soil depth of 30 cm. Hydrophobicity of 

each O, A, and B horizon was measured in the field by dropping 1 ml of water and 

measuring the amount of time needed for the droplet to completely infiltrate the 

soil. Bulk density samples of O horizons were sampled by cutting out and removing 

a 150-cm2 area of forest floor and measuring the depth at four locations along the 

edges to determine a volume; coarse woody debris >2 cm was not included in the 

O horizon samples. The O horizon material was taken to the lab and dried at 70 °C 

and weighed. The bulk density of each mineral soil horizon was determined on a 

representative soil core using a hammer corer with a 137 cm3 core; samples were 

taken to the lab and dried at 105 °C to obtain dry weight and calculate bulk density. 

Soil available N was measured once per year in spring (April-May) of 2000, 

2001, and 2002. The buried bag method was used to determine net mineralizable 

nitrogen (N). Half (vertically divided) of a 137-cm3 core (5.4 cm diameter by 6 cm 

depth) of O and A horizon were incubated at their respective depths in the field for 

1 Darlene Zabowski is Professor, College of Forest Resources, Box 32100, University of 

Washington, Seattle, WA 98195 zabow@u.washington.edu; Jeffrey Hatten, Elizabeth 

Dolan, and George Scherer were graduate students, College of Forest Resources, University of Washington, Seattle, WA 98195.
48

RESEARCH PAPER PNW-RP-577

4 weeks (Raison et al. 1987). The other half of the core was immediately returned 

to the lab and extracted using 2 M potassium chloride (KCl) for initial ammonium 

(NH4) and nitrate (NO3). Incubated samples were subsequently retrieved and also 

extracted using 2 M KCl for NH4 and NO3. Solution analysis was done using an 

autoanalyzer (Keeney and Nelson 1982). Net mineralization was the difference 

between final and initial extractable N. 

In addition to sampling soil at each grid point, four soil pits were dug within 

each experimental unit to either a maximum of 1.5-m depth or to weathered bedrock for soil profile descriptions and additional sampling. Pit locations were stratified within each plot, with one pit located on a ridge, one in a valley, and one on a 

sideslope; the fourth pit was randomly located in an area bare of vegetation within 

each unit. Complete profile descriptions were done at each pit, and samples were 

collected from each horizon to determine soil classification. 

Because the sideslope pit of each plot was considered to be the most representative of each plot (83 percent of the gridpoints were on sideslope or toeslope topographic positions), these pits were used to monitor soil moisture and temperature. 

Five fiberglass soil moisture/temperature blocks were installed in major genetic 

horizons (at the interface of the O and A horizons, and within the A, AB or Bw1, 

within the Bw2 or Bt, and within the Bt2 or BC horizons) of each treatment plot. 

Soil moisture and temperature were measured during the day (mid-morning to 

late afternoon) at monthly intervals over a 3-year period (2000 to 2003) using an 

electrical resistance meter with standard moisture calibration curves (Soil Moisture 

Corp.2) for fiberglass blocks. Measurements of air temperature were made using a 

shaded hand-held thermometer at 1 m above the soil surface each time soil temperature was measured. Snowpack depths were also measured with each site visit using 

a marked snow rod. Owing to the difficulty of accessing the sites in winter, only one 

reading was made in January 2001, which was during the first year of sampling.

Soil Analysis

Mineral soil samples were air-dried and sieved to 2 mm for chemical analyses. 

Subsamples from each mineral horizon and representative O horizon material were 

analyzed for pH using the saturated paste method (Van Miegroet et al. 1994). Six 

grid-point sampling sites were randomly selected for further chemical analysis 

of each horizon within each experimental unit. Subsamples of each horizon were 

finely ground and analyzed for total carbon (C) and nitrogen (N) using a PerkinElmer 2400 CHN analyzer. Available phosphorous (P) was extracted by shaking 10 

2 The use of trade or firm names in this publication is for reader information and does not 

imply endorsement by the U.S. Department of Agriculture of any product or service.
49

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

g of soil with a 0.01M solution of calcium chloride (CaCl2) for 30 minutes, filtering 

with a Whatman no. 42 filter paper, and analyzed using the molybdenum blue 

method of Olsen and Sommers (1982). Cation exchange capacity (CEC) was determined with a 12-hour extraction using unbuffered 2M ammonium chloride (NH4Cl) 

and a mechanical extractor with a subsequent 2M KCl extraction (Skinner et al. 

2001). Base cation saturation was determined on the NH4Cl extracts using a Jarrel 

Ash Atomcomp ICP. 

Results and Discussion

Soil Properties

The top 20 cm of the soil found in the Mission Creek area typically has horizons 

of O, A, and either a Bw or Bt horizon (table 4-1, fig. 4-1). The O horizons were 

predominantly Oi with some Oe, and almost no Oa; sometimes a very thin layer of 

charcoal separated the O horizon from the surface mineral horizon. The A-horizon 

depths were extremely variable, ranging from nonexistent in high-erosion areas, to 

an average thickness of 35 cm; in one valley location the A horizon reached 88 cm 

deep. In some cases, an AB horizon was also present. Although A horizons were 

variable, overall they were deep for a forest soil. Both Bw and Bt horizons were 

also quite variable, being absent in extremely steep eroded areas and greater than 

75 cm in aggrading sites. BC or C horizons commonly occurred at depth, although 

in some cases, Crt horizons of weathered sandstone with inclusions of clay were 

present. Of the profiles shown in figure 4-1, three were found rarely, occurring only 

once (profile with O, A1, A2, C, 2BCb; and profile with O, A, Bw, C, CB, 2Bwb) or 

twice (profile with thin O over A, Cr) within the entire study area. The remaining 

five soil profile types dominated the soil landscape, but no one soil type consistently 

occurred at a particular topographic position.

The soil is generally well structured with a moderate bulk density in the upper 

horizons but higher bulk densities in the lower profile (table 4-1). The moderate to 

high bulk densities are partially explained by the texture, which is typically loamy 

or sandy loam in the upper profile, but is increasingly sandy or clayey at depth. This 

increase in sand or clay can increase bulk density despite good structure. In some 

cases, the BC or C horizon became massive resulting in even higher bulk densities 

(as high as 1.9 g/cm in a Crt horizon). Hydrophobicity was high in the O horizons, 

undoubtedly because of a high concentration of hydrophobic waxes and the extreme 

dryness of the O when hydrophobicity was measured during summer. There was a 

slightly slower water penetration rate in the A horizons than the B horizons, but no 

strong hydrophobic layer was evident. 
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RESEARCH PAPER PNW-RP-577

Figure 4-1—Typical soil profiles found within the Mission Creek study area showing relative horizon types and depths. 

Table 4-1—Common soil horizons and typical physical properties of soil within the Mission Creek study area 

Average Hydro- Bulk density

Horizon thickness Color Texture Structure phobicity (standard error)

Centimeters Seconds Mg/m3

O 7 — Mostly Oi — 40 0.08(0.01)

A or A1 25 10YR3/1 Loam, sandy loam Weak, fine, granular to 7 1.1 (.10)

or 3/2 moderate medium

 subangular blocky

AB or A2 25 10YR3/2 Loam, sandy clay loam Weak to moderate medium ND 1.1 (.05)

subangular blocky

Bw 60 10YR4/3 Sandy loam, loamy sand Weak to moderate, medium 3 1.2 (.05)

subangular blocky

Bt 80 10YR4/4 Sandy clay loam, clay loam Moderate, medium to, ND 1.4 (.05)

to 5/6 coarse angular blocky

BC, CB, C, Crt 0 to 73 10YR5/6 Loamy sand, sandy Weak, fine granular to ND 1.4 (.10)

to 5/8 clay loam massive

ND = not determined.
51

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Soil temperature ranged from 0 to 15 °C in the O horizon with peak temperatures occurring in August (fig. 4-2). July, August, and September are the hottest 

months. The maximum recorded temperature in the A horizon was 14 °C. Average 

soil temperature at 50 cm depth was between 5 and 10 °C. The soil temperature 

regime is frigid. A snowpack generally began in December and left in March and 

was at least 18 cm thick, but a small snowpack was present in one November and 

April, and some snowpack persisted into May of one year. Typically, melting was 

complete in either late March or early April. When snow is present, soils are insulated and therefore little soil freezing occurs. 

Soil moisture measurements indicate a xeric moisture regime, with the three 

drier months occurring in July, August, and September, the same months of maximum soil temperatures (fig. 4-2). Rewetting occurs in fall and winter through both 

rain and snowfall. Once the snowpack melts in March–April, the soil begins to 

rapidly dry in April, and soil moisture has already dropped to approximately half by 

June. Gravimetric water content ranged from 25 to 12 percent in the upper mineral 

horizons, and from 15 to 8 percent in the lower mineral horizons. This consistently 

lower moisture content in the deeper soil profile suggests that deeper soil horizons 

never completely wet; however, the drawdown in moisture during the summer does 

indicate that moisture in these horizons is used by vegetation. 

Soil chemical properties of the Mission Creek area generally indicated fertile 

soils (table 4-2), with moderately high pH and organic carbon. Two notable properties were found. First, the total quantity of C and N in these soils is high. The concentration of N in the A and B horizons is moderately high for a forest soil, but these 

horizons are typically deep; therefore the total site N was high, averaging a total of 

3.5 Mg/ha within the O, A, and B horizons, with a total soil profile N capital of 4.7 

Mg/ha. Over 50 percent of this N is found in the A horizon. Similarly, total carbon 

was high with 82 Mg/ha within the combined O, A, and B horizons and 105 Mg/ha 

in the total soil profile. Total C and N in the grid sampling areas (table 4-2) were 

similar to that of the soil profiles but slightly less N (2.7 versus 3.5 Mg N/ha). The 

favorable N concentrations resulted in relatively low C/N ratios for all soil samples. 

The total net N mineralized was moderately high (averaging 0.84 kg N/ha per 

month in spring) when compared to that of a more nutrient-poor ponderosa pine 

stand in eastern Oregon (2.0 to 6.4 kg N/ha per year) (Monleon et al. 1997). Overall, 

N availability does not appear to be the most limiting factor in growth of these 

forests. A fertilizer study in a ponderosa pine forest north of the Mission Creek 

area found no growth response by trees to N fertilization when total soil N was 

somewhat lower in the O horizon, but slightly higher in the mineral soil (Zabowski 

and Henry 1994). 

Overall, N availability 

does not appear to be 

the most limiting factor 

in growth of these 

forests. 
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RESEARCH PAPER PNW-RP-577

Figure 4-2—Average soil temperature and gravimetric soil water content by horizon for soils within 

the Mission Creek study area. Values are averages of 12 replicates from midslope soils taken over a 

3-year period.
53

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Table 4-2—Average and standard error of soil chemical properties of O, A, and B horizon grid 

samples in the Mission Creek study area of Wenatchee National Forest

Available Cation exchange Base

Horizon pH phosphorus capacity saturation Carbon Nitrogen

mg/kg cmolc /kg - - - - - - - - - - - - Percent - - - - - - - - - - - -

O 5.5 ± 0.1 ND ND ND 40 ± 2 1.50 ± 0.10

A 6.3 ± .2 1.11 ± 0.26 17 ± 2 90 ± 1 2.6 ± 0.6 .11 ± .05

B 6.2 ± .1 .61 ± .20 14 ± 2 90 ± 2 1.2 ± .2 .05 ± .01

 Extractable Extractable Net mineralizable Total Total

C/N ammonium nitrate nitrogen carbon nitrogen

- - - - - - - - - - - - - - - mg/kg - - - - - - - - - - - - - - - Mg/ha kg/ha

O 29 6.70 ± 2.40 3.30 ± 3.90 1.20 ± 0.29 16 ± 1 550 ± 120

A 27 2.30 ± .56 .58 ± .19 .54 ± .16 47 ± 34 1300 ± 120

B 27 ND ND ND 21 ± 2 830 ± 80

ND = not determined, cmolc = centimoles of charge.

Note: Values are averages of 8 to 18 samples collected within 12 plots (n = 12). Mineralizable N is that available within a 

4-week period in spring determined by using buried bags.

The second notable soil chemical property found was the high base saturation. 

Base saturation averaged 90 percent, and was never less than 40 percent in the A 

horizon. Although CEC values are not exceptionally high, these base saturation 

values are high for a forest soil. Overall, nutrients do not appear to be limiting at 

the site when water is available for uptake. Water availability is probably the most 

limiting growth factor at this site. Zabowski and Henry (1994) also concluded that 

seasonal water limitations were probably more limiting to growth than nitrogen.

Several areas within the study site had been burned by low-intensity wildfire 

within the last 27 years before sampling. The soils in the burned areas showed 

little effect from these contemporary fires compared to adjacent areas that had not 

burned since fire suppression began (Hatten et al. 2005). Soil variability appears 

to be dominated more by topographic factors, erosion, and vegetation (see Dolan 

2002) than recent fire. 

Soil Classification

A preliminary soil survey done in this area found Haploxerolls, Argixerolls, and 

Haploxeralfs throughout the area (McColley 1995). Soils data from the Mission 

Creek study site found that Haploxerolls predominate, with some Argixerolls, 

Haploxeralfs, Haploxerepts, and Entisols (a few Xeropsamments or Xerorthents on 

steep, eroded slopes) also present. The common deep A horizons with good physical properties and high base saturation have resulted in Mollisols being common 

despite the presence of a mixed coniferous forest. Several soil-forming factors 

probably contribute to this. First, although the bedrock is nonglaciated sandstone 

Water availability is 

probably the most 

limiting growth factor 

at this site.
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RESEARCH PAPER PNW-RP-577

intermixed with limited amounts of shale and conglomerate from the Chumstick 

Formation (Tabor et al. 1982), loess and volcanic ash deposits are common in the 

area providing young, fine-textured parent materials in the upper profile. The total 

precipitation is about 60 cm per year (NRCS 2005), which does not strongly leach 

cations, but is adequate for grasses to be a common understory species contributing 

fine-root organic matter to keep well-developed A horizons prevalent. The low precipitation also favors frequent low-severity fires, which can replenish base cations 

without removing mineral soil organic matter. This effect has persisted despite 

fire exclusion in the last 100 years. Despite prevalent steep slopes, the understory 

vegetation and O horizon depth appear adequate to limit erosion to the steepest 

sites with the coarsest soil textures and the poorest soil structure (mostly the areas 

with shale and conglomerate). 

Conclusions

Soils within the Mission Creek Study area were found to be largely Mollisols with 

some Alfisols, Inceptisols, and Entisols. Although soil variability is extensive 

within the plots, almost all of the soils present were found to have physical and 

chemical properties favorable for forest growth. Overall, the soils appear to be 

fertile containing high amounts of C, N, and base cations. Nitrogen availability 

does not appear to be the primary limitation to tree growth. The most limiting 

growth factor is undoubtedly availability of soil water, which declines beginning 

in June.

Literature Cited

Dolan, E. 2002. Soil and site variability in the northeast Wenatchee Mountains, 

Washington. Seattle, WA: University of Washington. 103 p. M.S. thesis

Hatten, J.; Zabowski, D.; Scherer, G.; Dolan, E. 2005. A comparison of soil 

properties after contemporary wildfire and fire suppression. Forest Ecology and 

Management. 220: 227–241.

Keeney, D.R.; Nelson, D.W. 1982. Nitrogen—inorganic forms. In: Page, A.L., ed. 

Methods of soil analysis. Part II. Agronomy Monograph 9. 2nd ed. Madison, WI: 

American Society of Agronomy; Soil Science Society of America: 643–698.

McColley, P. 1995. Cashmere Mountain soil survey: Leavenworth Ranger District 

soil handbook: non-wilderness. Preliminary report. Wenatchee, WA: U.S. 

Department of Agriculture, Forest Service, Okanogan and Wenatchee 

National Forests. 375 p.

Although soil variability 

is extensive within 

the plots, almost all of 

the soils present were 

found to have physical 

and chemical properties 

favorable for forest 

growth.
55

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Monleon, V.J.; Cromack, K.; Landsberg, J.D. 1997. Short- and long-term effects 

of prescribed underburning on nitrogen availability in ponderosa pine stands in 

central Oregon. Canadian Journal of Forest Research. 27: 369–378.

Natural Resource Conservation Service [NRCS]. 2005. National water and 

climate center: Washington monthly precipitation averages, 1961–1990. 

ftp://ftp.wcc.nrcs.usda.gov/data/snow/ads/wa/wa6190pr.html. (17 January 2005).

Olsen, S.; Sommers, L. 1982. Phosphorus. In: Page, A.L., ed. Methods of soil 

analysis. Part II. Agronomy Monograph 9. 2nd ed. Madison, WI: American 

Society of Agronomy; Soil Science Society of America: 403–430.

Raison, R.; Connell, M.; Khanna, P. 1987. Methodology for studying fluxes of 

soil mineral N in situ. Soil Biology and Biochemistry. 19: 521–530.

Skinner, M.F.; Zabowski, D.; Harrison, R.; Lowe, A.; Xue, D. 2001. Measuring 

the cation exchange capacity of forest soils. Communications in Soil Science and 

Plant Analysis. 32: 1751–1764.

SPSS. 2001. SPSS Base Version 10.1.3 for Windows. Chicago, IL: SPSS Inc. 

Tabor, R.W.; Waitt, R.B., Jr.; Frizzell, V.A., Jr.; Swanson, D.A.; Byerly, G.R.; 

Bentley, R.D. 1982. Geologic map of the Wenatchee National Forest. Misc. 

Invest. Ser., MI 1-311. 1:100,000 Quadrangle, Central Washington. Reston, VA: 

U.S. Geological Survey. 25 p.

Van Miegroet, H.; Zabowski, D.; Smith, T.; Lundkvist, H. 1994. Review of 

measurement techniques in site productivity studies. In: Dyck, W.C.; Cole, 

D.W; Comerford, N.B., eds. Impacts of forest harvesting on long-term site 

productivity. London: Chapman and Hall: 287–362.

Zabowski, D.; Henry, C.L. 1994. Soil and foliar nitrogen after fertilizer treatment 

of ponderosa pine. New Zealand Journal of Forest Science. 24: 333–343.
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57

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Nicholas J. Brazee, Robert L. Edmonds, and James L. Marra1

Introduction

Fire suppression and selective logging over the past 100 years in eastern Washington have changed the vegetation from primarily low-density forests dominated by 

ponderosa pine (Pinus ponderosa Laws) to high-density forests of mixed ponderosa 

pine, Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) and other species (Agee 

1993). There is now considerable interest in returning fire to these ecosystems as a 

management tool and making these ecosystems less likely to burn catastrophically. 

As the use of fire grows as a restoration tool, so has the need for a robust, quantitative metric of fire effects reflecting soil health and functioning. Enzymes produced 

by soil microbes are sensitive indicators of stress on ecosystems and can provide 

robust measures of the ecosystem health and sustainability (Boerner and Brinkman 

2003, Boerner et al. 2005, Dick 1994). However, there are few data on soil enzyme 

activities available from the dry forests of eastern Washington. 

We selected four extracellular soil enzymes to study: β-glucosidase, acid 

phosphatase, N-acetyl-glucosaminidase (chitinase), and polyphenoloxidase. 

β-glucosidase aids in accelerating litter decomposition by breaking down labile 

cellulose and other carbohydrate polymers (Burns 1978). Acid phosphatase is 

responsible for the mineralization of organic phosphorus (P) to inorganic P (Burns 

1978, Ho 1979). High levels of both acid phosphatase and β-glucosidase indicate 

high organic matter quality, rapid mineralization, and high nutrient availability 

(Sinsabaugh and Moorhead 1997). Chitinase degrades chitin, and releases low 

molecular weight carbon (C)- and nitrogen (N)-rich compounds (Skujiņš 1978). 

Polyphenoloxidase is one of several enzymes involved in the degradation of lignin 

in plant litters and is in higher abundance where litter quality is low (Skujiņš 

1978). Organisms most effective at lignin degradation are adapted to low-nutrient 

conditions (Killham 1994).

The objectives of this study were to determine (1) soil conditions (i.e., bulk 

density, moisture content, and mineral soil pH ) in forests at the Mission Creek 

site on the east slopes of the Cascade mountains of Washington, (2) mineral 

soil enzyme activities across the landscape in different experimental units and 

Chapter 5: Soil Enzyme Activity

1 Nicholas J. Brazee was a graduate student, College of Forest Resources, Box 32100, 

University of Washington, Seattle, WA 98195, and is currently a Ph.D. student, Department 

of Plant, Soil, and Insect Sciences, University of Massachusetts, Amherst; Robert L. 

Edmonds is Professor and Associate Dean, College of Forest Resources, Box 32100, 

University of Washington, Seattle, WA 98195 bobe@u.washington.edu; and James L. 

Marra was a research associate, College of Forest Resources, University of Washington, 

Seattle, WA 98195, and is currently a managing entomologist, Washington State 

Department of Agriculture, Olympia, WA 98504.

Enzymes produced 

by soil microbes 

can provide robust 

measures of 

ecosystem health 

and sustainability.
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RESEARCH PAPER PNW-RP-577

landscape positions (ridge, slope, bare areas, and valley), and (3) whether 

enzyme activities are related to soil and stand conditions. We hypothesized that 

(1) soil enzyme activity would be highest in valleys and lowest in bare areas, 

(2) soil enzyme activity would be positively correlated with soil moisture, and 

(3) soil enzyme activity would be related to stem density and forest floor depth 

(indicators of organic matter inputs and decomposition rates).

Methods

Sampling Design

Four landscape positions were delineated on each of the 12 experimental units for 

soil enzyme analysis: (1) ridge—highest elevation area within plot, closed canopy, 

(2) slope—midslope, closed canopy, (3) bare—midslope in an overstory canopy 

gap, and (4) valley—lowest elevation area, closed canopy. 

Field Sampling

Mineral soil samples were taken in August 2001. Soil was sampled with a 2.5-cmdiameter bulk density corer at 48 sampling locations (at each of the four landscape 

positions—ridge, slope, bare areas, and valley—on the 12 experimental units). 

Each soil core was taken to a depth of 8 cm below the forest floor, and the corer was 

sterilized with 95-percent ethanol between each use to reduce cross contamination. 

Soil cores were brought on ice to the laboratory at the College of Forest Resources, 

University of Washington, where soil was placed in a refrigerator at 3 °C. 

Lab Analyses

 Moisture content and bulk density were determined for each soil core. Soil was 

dried at a temperature of 105 °C for 24 hours. Soil pH was determined using a 

Radiometer pH meter (pHM-92), a pHC2051-8 combined pH electrode, and a 1:1 

(volume:volume) soil to water paste.

For enzyme analyses, 3 g (wet weight) of soil from each sample core (< 2 mm 

fraction) were sent overnight on ice to Dr. Robert Sinsabaugh at the University of 

New Mexico, Albuquerque. Activities of β-glucosidase, acid phosphatase, chitinase, 

and polyphenol oxidase were determined. Enzyme assays were conducted using 

methods adopted from Saiya-Cork et al. (2002). Briefly, assays were conducted 

using 0.5 g of soil in sodium acetate buffer (50 mmol/L, pH 5.0) with either methylumbelliferyl enzyme substrates for β-glucosidase, acid phosphatase, and chitinase, 

or L-3, 4-dihydroxyphenylalanine (L-DOPA, 10 mmol/L, [Sigma-Aldrich, St. 

Louis, Missouri, USA]) as the substrate for polyphenoloxidase. Four analytical 

replicates per sample were used, and assays were conducted at 20 °C for 1 to 2 
59

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

hours, using both substrate and sample controls. Enzyme activity was expressed as 

mmol • kg-1• h-1 of dry weight mineral soil for each sample. 

Statistical Analyses

Two-way Analysis of Variance (ANOVA) was used to determine if there were differences in soil enzyme activity relative to site and landscape feature (bare, ridge, 

slope, valley) using SPSS (2004). Two-way ANOVA was also used to determine 

if soil moisture content, soil bulk density, and soil pH were different by site and 

landscape position. Data were checked with respect to variance and normality. Soil 

enzyme data were natural-log transformed, and soil moisture data were squareroot transformed. Tukey’s Honestly Significant Difference (HSD) test was used to 

determine differences among means. Linear regression (SPSS 2004) was used to 

determine if enzyme activity was related to soil and stand variables. Significance 

levels were interpreted at α = 0.05. 

Results

Soil Moisture, Bulk Density, and pH

Soil characteristics (bulk density, moisture content, and pH) were not significantly 

different among the 12 experimental units (p > 0.05) (table 5-1). Bulk density 

ranged from 0.87 to 1.18 Mg/m3 (average 1.05 Mg/m3). Soil moisture ranged from 

4.0 to 10.8 percent (average 7.6 percent) and pH ranged from 5.97 to 6.64 (average 

6.16). There were also no significant differences in soil characteristics by landscape 

Table 5-1—Soil moisture in August 2001, bulk density, and pH in the 0- to 

8-cm mineral soil layer, by experimental unit at Mission Creek

Experimental unit Gravimetric moisture Bulk density pHwater

Percent Mg/m3

Camas 8.9 (3.6) 0.99 (0.10) 5.98 (0.35)

Crow 1 8.5 (4.0) 1.08 (0.31) 6.14 (0.28)

Crow 3 7.1 (1.6) 1.11 (0.26) 6.04 (0.26)

Crow 6 6.9 (1.3) 1.17 (0.06) 6.15 (0.49)

Pendleton 6.3 (2.1) 1.18 (0.11) 5.97 (0.34)

Poison 7.3 (2.6) 1.01 (0.10) 6.18 (0.33)

Ruby 6.1 (2.3) 1.19 (0.11) 5.97 (0.23)

Sand 2 4.0 (1.7) 1.01 (0.04) 6.47 (0.45)

Sand 19 6.5 (1.8) 1.18 (0.20) 6.64 (0.78)

Slawson 8.5 (2.9) 0.87 (0.13) 6.26 (0.13)

Spromberg 10.8 (5.3) 0.89 (0.21) 6.04 (0.86)

Tripp 9.5 (2.7) 0.88 (0.07) 6.11 (0.22)

 Average 7.6 (3.0) 1.05 (0.19) 6.16 (0.44)

Note: No significant differences in moisture, bulk density, and pH among experimental units 

(p < 0.05). Standard deviations are in parentheses (n = 4).

Soil characteristics 

were not significantly 

different among the 12 

experimental units.
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Table 5-2—Mineral soil moisture in August 2001, bulk density, and pH in the 

top 8 cm by landscape position

Landscape position Gravimetric moisture Bulk density pHwater

Percent Mg/m3

Bare 6.0 (1.9)a 1.10 (0.15)a 6.43 (0.56)a

Ridge 8.1 (3.8)ab 1.10 (0.23)a 6.06 (0.34)a

Slope 7.2 (1.8)ab 1.01 (0.18)a 6.15 (0.42)a

Valley 9.2 (3.3)b 0.97 (0.15)a 6.00 (0.32)a

 Average (all) 7.6 (3.0) 1.05 (0.19) 6.16 (0.44)

Note: Values with different letters are significantly different among landscape positions 

(p < 0.05). Standard deviations are in parentheses (n = 12).

position except that soil moisture was significantly higher in the valleys than in bare 

canopy gaps (p > 0.05) (table 5-2). The lack of differences in bulk density and pH 

probably reflects the high variability in the data and low sample numbers. There 

was a tendency for lower bulk density and pH in valleys and higher bulk density 

and pH in bare canopy gaps (table 5-2). 

Soil Enzyme Activities

β-glucosidase and chitinase activities were significantly different among 

the 12 experimental units (table 5-3). β-glucosidase ranged from 172 to 

823 mmol • kg-1 • h-1, and chitinase ranged from 41 to 362 mmol • kg-1 • h-1. 

The Camas site had the highest activities of both β-glucosidase and chitinase, 

and Crow 3 had the lowest activity. Acid phosphatase followed a trend similar to 

both β-glucosidase and chitinase, but activities were not significantly different 

among units and ranged from 85 to 328 mmol • kg-1 • h-1. Polyphenoloxidase 

activity ranged from 0 to 317 mmol • kg-1 • h-1 (table 5-3); it was not detected in 

8 of the 12 experimental units (table 5-3). Enzyme activity was not significantly 

different by landscape position for any of the four enzymes (table 5-4). There 

was a tendency for β-glucosidase, acid phosphatase, and chitinase to be highest 

in valleys, but not polyphenoloxidase.

Relationships Among Soil Enzyme Activities and Soil and 

Stand Conditions

Enzyme activities were related to soil bulk density and moisture content (table 

5-5), but not pH (data not shown in table 5-5). Activity levels of β-glucosidase, acid 

phosphatase, and chitinase were negatively correlated with bulk density (table 5-5), 

which explained < 30 percent of the variance in enzyme activity. β-glucosidase, 

acid phosphatase, and chitinase activities were positively correlated with moisture 

Activity levels of 

β-glucosidase, 

acid phosphatase, 

and chitinase were 

negatively correlated 

with bulk density 

and were positively 

correlated with 

moisture content.
61

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Table 5-3—Enzyme activity in August 2001 by experimental unit at Mission Creek

Experimental Acid N-acetyl-glucosaminidase Polyphenol

unit	 β-glucosidase 	 phosphatase	 (chitinase)	 oxidase

mmol • kg-1 • h-1

Camas 823 (326)a 245 (182)a 362 (205)a 0a

Crow 1 230 (68)bc 122 (96)a 53 (25)bc 0a

Crow 3 172 (61)c 85 (36)a 41 (30)c 0a

Crow 6 230 (57)bc 123 (28)a 88 (45)abc 0a

Pendleton 354 (195)abc 159 (73)a 78 (41)abc 0a

Poison 394 (340)abc 169 (81)a 91 (103)abc 0a

Ruby 422 (159)abc 158 (25)a 115 (96)abc 317 (634)a

Sand 2 409 (336)abc 118 (62)a 142 (118)abc 102 (205)a

Sand 19 419 (81)abc 259 (18)a 188 (107)abc 0a

Slawson 627 (108)abc 275 (165)a 187 (91)abc 141 (282)a

Spromberg 619 (200)abc 328 (298)a 240 (135)ab 0a

Tripp 702 (212)ab 242 (61)a 221 (92)ab 2 (3)a

 Average 450 (203) 190 (77) 151 (93) 47 (97)

Note: Values with different letters in columns are significantly different (p < 0.05). Standard deviations are in 

parentheses (n=4).

Table 5-4—Enzyme activity in August 2001 by landscape position

Landscape Acid N-acetyl-glucosaminidase Polyphenol

position	 β-glucosidase 	 phosphatase	 (chitinase)	 oxidase

mmol • kg-1 • h-1

Bare 472 (270) 150 (80) 117 (99) 106 (366)

Ridge 408 (245) 217 (183) 147 (141) 47 (163)

Slope 467 (307) 158 (79) 153 (134) 1 (2) 

Valley 472 (272) 235 (144) 185 (140) 34 (118)

 Average (all) 455 (267) 190 (130) 151 (128) 47 (205)

Note: No significant differences in any enzyme activity measured among Landscape Positions at p < 0.05.

Standard deviations are in parentheses (n = 12).

Table 5-5—Pearson correlation coefficients for relationships among soil enzyme activities and 

soil bulk density, soil moisture, stem density, and forest floor depth in experimental units at 

Mission Creek

Bulk densityb Gravimetric moistureb Stem densityc	 Forest floor depthc

Enzymea r	 p	 r	 p	 r	 p	 r	 p

β-glucosidase -0.525 <0.001 +0.347 0.016 +0.751 0.005 -0.742 0.006

Acid phosphatase -0.548 <0.001 +0.699 <0.001 +0.530 0.077 -0.540 0.077

Chitinase -0.458 0.001 +0.439 0.002 +0.521 0.082 -0.761 0.004

a Phenol oxidase activity was not related to any variable measured. b n = 48.

c n = 12.
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RESEARCH PAPER PNW-RP-577

content (table 5-5). Polyphenoloxidase activity was not related to any soil variable, 

but only four of the units had polyphenoloxidase activity.

Linear regression was also used to determine whether enzyme activity was 

related to slope, aspect, elevation, forest floor depth, canopy cover, tree basal area, 

and stem density. Enzyme activity was only related to stem density and forest floor 

depth (table 5-5). β-glucosidase activity was positively related to stem density and 

negatively related to forest floor depth (table 5-5). There were similar trends for 

acid phosphatase and chitinase activities, but the relationship was only significant 

for chitinase and forest floor depth (table 5-5). Polyphenoloxidase activity was 

not related to any stand variable. More of the variance in β-glucosidase activity 

was explained by stand variables than by soil variables, e.g., 56.4 percent for stem 

density and 55.1 percent for forest floor depth. Also 57.9 percent of chitinase activity was explained by forest floor depth. However, no single variable explained more 

than 60 percent of the variance in enzyme activity. 

Discussion

Soil Moisture, Bulk Density, and pH

There was little variation in mineral soil bulk density, moisture content, and pH 

among the 12 experimental units, despite differences in soil types across the study 

area (Dolan 2002). Variations in slope, elevation, and aspect did not strongly influence the soil environmental factors. There were no significant differences relative 

to landscape position except for soil moisture, which was significantly higher in the 

valleys than in bare areas on slopes in canopy gaps. The time of year of sampling 

(summer) may have reduced differences in soil moisture content among study 

units. Soil moisture contents in this study were similar to those in a mixed-conifer 

dry forest at the Teakettle site in the Sierra National Forest, California, in summer 

(Marra and Edmonds 2005). Bulk densities at Teakettle, however, had a slightly 

greater range (0.27 g/cm3 under canopies to 1.03 g/cm3 in canopy gaps) than those 

at Mission Creek (0.97 g/cm3 in valleys to 1.10 g/cm3 in canopy gaps and ridges). 

Parent material at the Mission Creek site is largely sedimentary compared to granite 

at Teakettle. Soil pH values were similar to those in unburned forest plots in the 

Entiat Experimental Forest located just north of our study area (Grier 1975). 

However, they were lower than those in dry western juniper and ponderosa pine 

forests in eastern Oregon (Ho 1979). 
63

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Soil Enzyme Activities

Soil enzyme activities were based on soil mass rather than organic matter mass, 

so as to provide a robust ecosystem-level measure of soil health and productivity 

(Boerner et al. 2005). We found that β-glucosidase had the highest average activity 

in the top 8 cm of mineral soil (455 ± 267 [standard deviation] mmol • kg-1 • h-1) 

followed by acid phosphatase (190 ± 130 mmol • kg-1 • h-1), chitinase (151 ± 128 

mmol • kg-1 • h-1) and polyphenoloxidase (47 ± 205 mmol • kg-1 • h-1). There are few 

studies of soil enzyme activity in the dry interior forest ecosystems of the Pacific 

Northwest with which to compare our data. Ho (1979) investigated acid phosphatase 

activity in Juniperus occidentalis (Hook.) and Pinus ponderosa forests in eastern 

Oregon and found activity levels of 114 and 119 mmol • kg-1 • h-1, respectively, 

slightly less than the average of 190 mmol • kg-1 • h-1 we found. More recently, 

slightly lower β-glucosidase, and similar chitinase activities, were reported from 

soils in ponderosa pine forests in northern Arizona (Boyle et al. 2005). 

Overall, activity levels of all enzymes in our study were lower than those 

found in moister temperate deciduous and coniferous forests in Australia, Spain, 

Canada, Missouri, Ohio, and Michigan (Boerner and Brinkman 2003, Eivazi and 

Bayan 1996, Grierson and Adams 2000, Hassett and Zak 2005, Saa et al. 1993, 

Staddon et al. 1998, Waldrop et al. 2004). Low summer soil moisture in the Pacific 

Northwest greatly reduces enzyme activities. In comparison, Boerner et al. (2005) 

found higher activities in August for some enzymes in a moist oak forest soil in 

Ohio: acid phosphatase (1000 mmol • kg-1 • h-1 versus 190 at Mission Creek) and 

polyphenoloxidase (1500 mmol • kg-1 • h-1 versus 47 at Mission Creek). On the other 

hand, chitinase activity was similar in the oak forest (100 mmol • kg-1 • h-1) to that 

at Mission Creek (151 mmol • kg-1 • h-1). Grierson and Adams (2000) reported much 

higher acid phosphatase activities in a eucalyptus forest in southwestern Western 

Australia (9250 mmol • kg-1 • h-1 in the 0- to 10-cm layer), but also noted that 

activity varied with depth, being twice as high in the 0- to 5-cm layer than the 

5- to 10-cm layer. 

Tropical forests also have high enzyme activity. Olander and Vitousek (2000) 

found phosphatase levels of 7820 to 9686 mmol • kg-1 • h-1 and chitinase levels of 

380 to 2760 mmol • kg-1 • h-1 in Hawaii along a soil chronosequence. Phosphatase 

was high at all their sites, but chitinase decreased as N availability increased. This 

difference in response of chitinase and phosphatase suggested that the N supply 

in older soils is high enough to trigger feedback and inhibit enzyme production, 

whereas the P supply was never high enough to trigger inhibition of phosphatase.

We were particularly interested in the variability in mineral soil enzyme 

activities across the 12 experimental units. Although we found few differences 

Activity levels of all 

enzymes in our study 

were lower than those 

found in moister 

temperate deciduous 

and coniferous forests.
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RESEARCH PAPER PNW-RP-577

in soil environmental conditions among units, there were differences in some 

soil enzyme activities. There were significant differences in β-glucosidase and 

chitinase activity among the 12 experimental units, but not in acid phosphatase or 

polyphenoloxidase activity. This might have been expected considering the range 

in elevation, aspect, forest characteristics, and soil types at Mission Creek. The 

lack of significant differences in polyphenoloxidase and phosphatase activities 

among experimental units was probably due to the high variability in activities. For 

example, only four of the units had detectable activity levels of polyphenoloxidase. 

Tree species composition may also influence enzyme activity (Grierson and 

Adams 2000). We found that units dominated by ponderosa pine (e.g., Crow 1, 

3, and 6) tended to have lower activities of β-glucosidase, acid phosphatase, and 

chitinase compared to sites with high proportions of Douglas-fir (e.g., Camas) (table 

5-3). This suggests that Douglas-fir-dominated units had higher decomposition and 

mineralization rates compared to ponderosa pine. β-glucosidase activity levels were 

positively related to chitinase activity. This was unexpected, as the two are typically negatively correlated with one another (Sinsabaugh et al. 1999). High levels 

of β-glucosidase activity are indicative of high organic matter quality, high nutrient 

availability, and increased mineralization (Burns 1978, Killham 1994). In contrast, 

high levels of chitinase activity are indicative of low N availability and poor organic 

matter quality. High chitinase in soils suggests the site supports large soil microbial communities of fungi, actinomycetes, and arthropods that would immobilize 

available nutrients, making them unavailable to plants until they die and decompose 

(Decker et al. 1999, Killham 1994). The Douglas-fir-dominated sites had higher 

activities of both enzymes, suggesting they had higher organic matter quality and 

a larger fungal population than the ponderosa pine-dominated site (Burns 1978). 

Even polyphenoloxidase activities tended to be higher in the Douglas-fir sites, and 

this enzyme was not detected in sites dominated by ponderosa pine. High polyphenoloxidase activity suggests that sites have low-quality litter and slow nutrient 

mineralization rates, where lignin makes up a larger portion of decomposable 

materials (Decker et al. 1999), but this seems to be the opposite of what we found.

In contrast to individual experimental units, there were no significant 

differences in enzyme activities relative to landscape position. This is contrary to 

our hypothesis that enzyme activity would be highest in valley areas and lowest in 

bare areas. There was considerable variation in the data, and we only examined soil 

enzyme activities in the summer when soils were dry. Differences may have been 

detected in other seasons. Other investigators have studied seasonal variability in 

soil enzymes. Boerner et al. (2005) found little seasonal effect on acid phosphatase 

and polyphenoloxidase activities in oak-dominated forests in Ohio in a humid 

Our findings suggest 

that Douglas-firdominated units had 

higher decomposition 

and mineralization 

rates compared to 

ponderosa pine.
65

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

climate. On the other hand, Grierson and Adams (2000) found seasonal differences 

in acid phosphatase in soil in a eucalyptus forest in Australia, and Boerner et al. 

(2005) noted high chitinase activity in spring in Ohio oak forest soils. Seasonal 

differences in enzyme activities at Mission Creek should be examined in the future. 

Relationships Between Soil Enzyme Activities and 

Soil and Stand Conditions

We hypothesized that soil moisture would be a major factor contributing to variation 

in soil enzyme activity. Ross et al. (1984) found that temporal fluctuations in soil 

enzyme activity were mostly the result of soil moisture and were independent of 

soil organic C and N. β-glucosidase, acid phosphatase, and chitinase activities were 

positively correlated with moisture content; soil moisture explained 48.9 percent 

of the variance in acid phosphatase. Grierson and Adams (2000) and Boerner et al. 

(2005) also showed that soil moisture has a strong influence on activity of some soil 

enzymes, particularly chitinase. Similarly, Boyle et al. (2005) found that soil moisture was correlated with β-glucosidase and chitinase activities in a Southwestern U.S. 

ponderosa pine forest during the summer monsoon period.

Soil enzyme activity was negatively related to bulk density, which explained 

< 30 percent of the variation in enzyme activity. Dick et al. (1988) also found soil 

enzyme activity to be negatively correlated with soil bulk density on compacted 

soils in a 4-year-old clearcut in western Oregon. Many of our experimental units 

have been subjected to management activities in the past, which may have affected 

bulk density. Low bulk density favors soil microbes and invertebrates and is usually 

associated with a relatively structured soil profile with developed systems of pore 

channels and spaces and a soil organic matter content higher than that of soils with 

high bulk densities (Marra and Edmonds 2005). There was no relationship between 

soil enzyme activity and soil pH probably because of the narrow range of soil pH at 

Mission Creek (6.00 to 6.43).

We examined potential relationships among soil enzyme activities and stand 

variables, including slope, aspect, elevation, forest floor depth, canopy cover, tree 

basal area, and stem density. The experimental units differed considerably in slope, 

aspect, and elevation. However, enzyme activities were only significantly related to 

stem density and forest floor depth. We hypothesized that units with high stem densities (No. trees/ha) would have increased enzyme activities. Higher tree density would 

provide more litterfall, therefore stimulating soil microbes and overall enzymatic 

activity. β-glucosidase activity was positively related to stem density, supporting our 

hypothesis. There were similar trends for acid phosphatase and chitinase activities. 

Polyphenoloxidase activity, however, was not related to any stand variable. 
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RESEARCH PAPER PNW-RP-577

Deeper forest floors indicate slower litter decomposition, greater litter input, 

or both. We hypothesized that soil enzyme activity would be negatively related 

to forest floor depth. β-glucosidase and chitinase activities were significantly 

negatively related to forest floor depth, and there was a trend for a similar 

relationship with acid phosphatase, supporting our hypothesis. These data support 

the concept that β-glucosidase, chitinase, and acid phosphatase aid in accelerating 

litter decomposition and releasing N and P in soils (Burns 1978, Ho 1979, 

Sinsabaugh and Moorhead 1997, Skujiņš 1978). Overall, more of the variation 

in enzyme activity was explained by stand variables than by soil variables. 

In conclusion, we found a wide range of variability in the activity of the 

four enzymes in the top 8 cm of mineral soil at Mission Creek. Activity levels 

were generally low compared to those in other temperate forest ecosystems. 

β-glucosidase had the highest activity across experimental units averaging 

450 mmol • kg-1 • h-1. Acid phosphatase was next highest (190 mmol • kg-1 • h-1), 

followed by chitinase (151 mmol • kg-1 • h-1), and polyphenoloxidase 

(47 mmol • kg-1 • h-1). Chitinase and β-glucosidase activities were significantly 

different among the 12 units, but acid phosphatase and polyphenoloxidase were 

not. Units with a higher proportion of Douglas-fir tended to have higher enzyme 

activity than those dominated by ponderosa pine. Enzyme activity was not 

significantly different by landscape position. Soil characteristics (bulk density, 

soil moisture, and pH) were not significantly different among units or by landscape 

position, except that soil moisture was significantly higher in the valleys than in 

bare areas in canopy gaps. β-glucosidase, acid phosphatase, and chitinase activities 

were negatively correlated with soil bulk density and positively correlated with soil 

moisture. β-glucosidase activity was also positively correlated with stem density 

and negatively correlated with forest floor depth. Polyphenoloxidase activity was 

not correlated with any measured variable. No single variable explained more than 

60 perecent of the variance in a given enzyme activity. 

Acknowledgments

We appreciated the field assistance provided by Amy Ramsey and George Scherer. 

We thank Dr. Robert Sinsabaugh, University of New Mexico, for providing enzyme 

analyses. 

Literature Cited

Agee, J.K. 1993. Fire ecology of Pacific Northwest forests. Washington, DC: 

Island Press. 491 p.
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Boerner, R.E.J.; Brinkman, J.A. 2003. Fire frequency and soil enzyme activity in 

southern Ohio oak-hickory forests. Applied Soil Ecology. 23: 137–146.

Boerner, R.E.J.; Brinkman, J.A.; Smith, A. 2005. Seasonal variations in enzyme 

activity and organic carbon in soil of a burned and unburned hardwood forest. 

Soil Biology and Biochemistry. 37: 1419–1426.

Boyle, S.I.; Hart, S.C.; Kaye, J.P.; Waldrop, M.P. 2005. Restoration and canopy 

type influence soil microflora in a ponderosa pine forest. Soil Science Society of 

America Journal. 69: 1627–1638. 

Burns, R.G. 1978. Soil enzymes. New York: Academic Press, Inc. 380 p.

Decker, K.L.M.; Boerner, R.E.J.; Morris, S.J. 1999. Scale-dependent patterns 

of soil enzyme activity in a forested landscape. Canadian Journal of Forest 

Research. 29: 232–241.

Dick, R.P. 1994. Soil enzyme activities as indicators of soil quality. In: Soil 

enzymes. Madison, WI: Soil Science Society of America: 107–124.

Dick, R.P.; Myrold, D.D.; Kerle, E.A. 1988. Microbial biomass and soil enzyme 

activities in compacted and rehabilitated skid trail soils. Soil Science Society of 

America Journal. 52: 512–516.

Dolan, E. 2002. Soil and site variability in the northeast Wenatchee mountains, 

Washington. Seattle, WA: University of Washington. 103 p. M.S. thesis.

Eivazi, F.; Bayan, M.R. 1996. Effects of long-term prescribed burning on the 

activity of select soil enzymes in an oak-hickory forest. Canadian Journal of 

Forest Research. 26: 1799–1804.

Grier, C.C. 1975. Wildfire effects on nutrient distribution and leaching in a 

coniferous ecosystem. Canadian Journal of Forest Research. 5: 599–608.

Grierson, P.F.; Adams, M.A. 2000. Plant species affect acid phosphatase, 

ergosterol and microbial P in a jarrah (Eucalyptus marginata Donn ex Sm.) 

forest in south-western Australia. Soil Biology and Biochemistry. 32: 1817–1827.

Hassett, J.E.; Zak, D.R. 2005. Aspen harvest intensity decreases microbial 

biomass, extracellular enzyme activity, and soil nitrogen cycling. Soil Science 

Society of America Journal. 69: 227–235.

Ho, I. 1979. Acid phosphatase activity in forest soil. Forest Science. 25(4): 567–568. 

Killham, K. 1994. Soil ecology. Cambridge, United Kingdom: Press Syndicate of 

the University of Cambridge. 242 p.
68

RESEARCH PAPER PNW-RP-577

Marra, J.L.;, Edmonds, R.L. 2005. Soil arthropod responses to different 

patch types in a mixed-conifer forest of the Sierra Nevada. Forest Science. 

51(3): 255–265.

Olander, L.P.; Vitousek, P.M. 2000. Regulation of soil phosphatase and chitinase 

by N and P availability. Biogeochemistry. 49: 175–190.

Ross, D.J.; Spier, T.W.; Cowling, J.C.; Whale, K.N. 1984. Temporal fluctuations 

in biochemical properties of soil under pasture. II. Nitrogen mineralization and 

enzyme activities. Australian Journal of Soil Research. 22: 319–330.

Saa, A.; Trasar-Cepeda, M.C.; Gil-Sotres, F.; Carballas, T. 1993. Changes in 

soil phosphorous and acid phosphatase activity immediately following forest 

fires. Soil Biology and Biochemistry. 25: 1223–1230.

Saiya-Cork, K.R.; Sinsabaugh, R.L.; Zak, D.R. 2002. Effects of long term 

nitrogen deposition on extracellular enzyme activity in an Acer saccharum forest 

soil. Soil Biology and Biochemistry. 34: 1309–1315.

Sinsabaugh, R.L.; Klug, M.J.; Collins, H.P.; Yeager, P.E.; Petersen, S.O. 1999. 

Characterizing soil microbial communities. In: Standard soil methods for longterm ecological research. New York: Oxford University Press: 318–348.

Sinsabaugh, R.L.; Moorhead, D.L. 1997. Synthesis of litter quality and enzymic 

approaches to decomposition modeling. In: Cadisch, G.; Giller, K.E., eds. Driven 

by nature: plant litter quality and decomposition. Cambridge, United Kingdom: 

CAB International: 363–375.

Skujiņš, J. 1978. History of abiotic soil enzyme research. In: Soil enzymes. New 

York: Academic Press, Inc.: 1–33.

SPSS. 2004. Version 13.0. Chicago, IL: SPSS, Inc.

Staddon, W.J.; Duchesne, L.C.; Trevors, J.T. 1998. Acid phosphatase, alkaline 

phosphatase and arylsulfatase activities in soils from a jack pine (Pinus 

banksiana Lamb.) ecosystem after clear-cutting, prescribed burning, and 

scarification. Biology and Fertility of Soils. 27: 1–4.

Waldrop, M.P.; Zak, D.R.; Sinsabaugh, R.L.; Gallo, M.; Lauber, C. 2004. 

Nitrogen deposition modifies soil carbon storage through changes in microbial 

enzymatic activity. Ecological Applications. 14(4): 1172–1177.
69

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Amy C. Ramsey, James L. Marra, and Robert L. Edmonds1

Introduction

Selective logging and fire suppression over the past century have changed the tree 

species in the eastern Washington Cascade Mountains as well as increasing tree 

density and fuel loading. Fires that occur now tend to burn more catastrophically 

than historical, low-intensity, pre-European-settlement fires. There is currently 

much interest in using fire and thinning in these forests as management tools to 

reduce the incidence of high-intensity fires. 

The influence of fire and thinning treatments on soil organisms, such as soil 

microarthropods, is not well understood. Soil microarthropods are sensitive bioindicators of environmental change because of the fine grain at which they occupy 

the soil and their rapid reproductive rates (Moldenke and Lattin 1990). They are 

important contributors to soil functioning (Seastedt 1984, Seastedt and Crossley 

1987). Through their interactions with soil microbes, they regulate decomposition 

and nutrient mineralization processes and increase soil structure and porosity 

(Asquith et al. 1990, Killham 1994, Stork and Eggleton 1992). In particular, soil 

microarthropods mobilize nutrients, provide food for soil micro-organisms through 

their feces, and transport bacteria and fungi (Behan-Pelletier 1999, Moldenke 1990, 

Moldenke et al. 2000, Norton and Behan-Pelletier 1991). 

Mites and Collembola dominate in conifer ecosystems (Marra and Edmonds 

1998, 2005). Landscape position can strongly influence them, particularly in mountainous terrain where vegetation may be patchy. For example, Marra and Edmonds 

(2005), working in the Sierra Nevada Mountains of California, found differences 

in mite and Collembola taxa and densities under closed-canopied forests compared 

to those in canopy gaps. In the eastern Washington Cascades, there is considerable 

topographic variation in the landscape. Steep slopes, sandy soils, rock outcroppings, 

and low precipitation create patchy vegetation cover (Dolan 2002, Lillybridge et al. 

1995). Little information is available on soil microarthropods in the dry forests of 

eastern Washington, especially in relation to landscape position. 

Chapter 6: Soil Microarthropods

1 Amy C. Ramsey was a graduate student, College of Forest Resources, Box 32100, 

University of Washington, Seattle, WA 98195, and is currently a forest pathologist, 

Washington Department of Agriculture, Olympia, WA 98504; James L. Marra was a 

research associate, College of Forest Resources, University of Washington, Seattle, WA, 

and is currently a managing entomologist, Washington State Deptartment of Agriculture, 

Olympia, WA; and Robert L. Edmonds is Professor and Associate Dean, College of Forest 

Resources, University of Washington, Seattle, WA 98195 bobe@u.washington.edu.

Soil microarthropods 

mobilize nutrients, 

provide food for soil 

micro-organisms, 

and transport bacteria 

and fungi.
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Data on forest soil arthropod taxonomic richness in different landscape positions and habitats can provide understanding of how ecosystems respond to forest 

management practices and ecological change (Moldenke et al. 2000). The study 

described here provides data on soil microarthropods at the Mission Creek site of 

the National Fire and Fire Surrogate Study, which was implemented to examine 

the ecological consequences of fire and thinning treatments.

The specific objectives of our study were to determine (1) pretreatment soil 

environmental conditions (i.e., soil moisture, bulk density, and pH), (2) pretreatment 

soil microarthropod density and taxonomic richness, (3) the effect of soil environmental conditions on soil microarthropod density and taxonomic richness, (4) the 

influence of landscape position (ridge, slope, open canopy gap, and valley) on soil 

microarthropod density and taxonomic richness, and (5) the influence of soil depth 

(0 to 4 and 5 to 9 cm) on soil microarthropod density and taxonomic richness. 

Materials and Methods

Sampling Design

In May 2001, the 12 Mission Creek experimental units were sampled, but only 9 

of the units were processed for invertebrates (Camas, Crow 1, Crow 3, Crow 6, 

Pendleton, Poison, Sand 2, Sand 19, and Spromberg). These units ranged in area 

from 9.5 to 20 ha and ranged in elevation from 640 to 1219 m. Each unit had four 

landscape positions: (1) ridge, (2) slope, (3) open canopy gap, and (4) valley. Slope 

positions were located between the ridges and valleys on the side of a mountain, 

and canopy gaps were defined by the absence of overstory vegetation in an area of 

at least 0.25 ha. Two samples were collected at each landscape position at each of 

the nine experimental units adjacent to the unit soil pit, for a total of 72 samples. 

One sample from each landscape position in each experimental unit was used to 

determine soil moisture, bulk density, and pH (36 samples), and the other sample at 

each landscape position was used for microarthropod extraction (36 samples). All 

sampling locations were mapped to follow ecosystem responses through time. 

Soil Sampling

Soil was collected with a soil corer (5.4-cm diameter) at each of the 72 sampling 

locations. Each soil core was taken from the top of the forest floor to a depth of 

10 cm in the mineral soil and divided into two samples, 0 to 4 cm and 5 to 9 cm 

depths. The 4-5 and 9-10-cm soil was not used. The volume of each soil sample was 

91.6 cm3. Soil cores were brought on ice to the laboratory in the College of Forest 

Resources, University of Washington, Seattle, Washington, and stored at 3 °C. 
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Lab Analyses

Microarthropods were extracted using a modified high-gradient Berlese method 

(Moldenke 1994). Soil samples were left in the arthropod extractors for 14 

days. Arthropods fell into antifreeze (polyethylene glycol) and were stored until 

identified. Soil samples were processed for soil moisture, bulk density, pH, and 

arthropods within 4 days of field sampling. Oribatid mites were identified to 

genus, if possible, and then to morphospecies (Oliver and Beatie 1996). All other 

arthropods and annelids were identified to class, order, or family, depending on 

local identification expertise. Bulk specimens were sorted and identified using a 

dissection scope boosted to a magnification of up to 120×. A reference collection 

was established for each species. Some morphospecies identified with a dissection 

scope were found to contain more than one genus or species when viewed with 

the higher magnification compound scope. Since it was not possible to mount and 

identify all specimens with a compound scope, some species groups listed contain 

more than one genus or species. For data analysis, taxa were composited across the 

9 experimental units by depth and landscape position. 

Moisture content and bulk density samples were dried at 105 oC and both were 

expressed as Mg/m3 on a dry mass basis. Soil pH was determined using a Radiometer pH meter (pHM-92), a pHC2051-8 combined pH electrode, and a 1:1 (volume:

volume) soil to water paste.

Statistical Analyses

One-way analyses of variance (ANOVA) were used to compare differences among 

number of taxa and density (number/m3) of oribatid mites and Collembola for different soil depths and landscape positions using SPSS (2004). One-way ANOVAs 

were also used to compare differences in soil moisture content, bulk density, and 

pH among landscape positions. Tukey’s Honestly Significant Difference (HSD) 

test was used to determine differences among means. Linear regression was 

used to determine relationships among oribatid mite and Collembola density and 

taxonomic richness and soil moisture, bulk density, and pH using SPPS (2004). 

Pearson’s correlation coefficients were calculated. Significance was determined 

at α ≤ 0.05.

Results

Soil Moisture, Bulk Density, and pH

Soil moisture content was not significantly different among landscape positions 

(table 6-1). Bulk density of the soil was significantly higher in the open canopy 

gaps (0.88 Mg/m3) than in valleys (0.55 Mg/m3) (p ≤ 0.05), while slope and ridge 
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bulk densities were intermediate. Bulk densities were low because forest floor material was included. Soil pH ranged from 5.98 to 6.40 and did not differ significantly 

among landscape positions. 

Microarthropod Taxa and Influence of Landscape Position

Mites (Acarida), including Mesostigmata, Oribatida, and Prostigmata were the 

dominant microarthropods present along with Collembola. Oribatid mites had the 

highest number of adult taxa (69). Taxa of oribatid mites and Collembola sampled 

in May 2001 are shown in table 6-2. Insects sampled were Coleoptera (beetles), 

Diptera (flies), Hemiptera (true bugs), Hymenoptera (ants, bees, and wasps), Lepidotpera (moths and butterflies), Psocoptera (barklice), Thysanoptera (thrips), and 

Thysanura (silverfish). Other invertebrates present were Diplura (two-pronged 

bristletails), Araneae (spiders), Chilopoda (centipedes), Diplopoda (millipedes), 

Annelida (segmented worms), and Pauropoda (pauropods). Mites were the most 

numerically dominant group, making up 84 percent of the total soil arthropods 

extracted. Collembola made up 7 percent of the total, and all other invertebrates 

made up 9 percent. 

Taxonomic richness of the oribatid mites was not significantly different among 

soil depth and landscape positions (table 6-3). The average number of taxa per 

sample ranged from 5.0 in the open canopy gaps at the 5- to 9-cm depth to 11.8 in 

the valleys at the 0- to 4-cm depth. Average oribatid mite densities ranged from 

327,511/m3 in ridges at the 5- to 9-cm depth to 1,146,288/m3 in the open canopy 

gaps at the 0- to 4-cm depth (table 6-3) and were not significantly different 

among landscape positions. However, densities were significantly higher in the 

0- to 4-cm depth than the 5- to 9-cm depth (p ≤ 0.05). 

Collembola were only identified to family. Taxonomic richness of Collembola 

was not significantly different between soil depths and among landscape positions 

(table 6-4). The average number of taxa per sample ranged from 0.7 in the ridges 

at the 0- to 4- and 5- to 9-cm depths and in the open canopy gaps at the 5- to 9-cm 

Table 6-1—Mean soil moisture, bulk density, and pH for different 

landscape positions, May 2001

Landscape position Soil moisture Bulk density pHwater

Mg/m3 Mg/m3

Ridge 0.10 (0.03)a 0.65 (0.18)ab 6.40 (0.61)a

Slope 0.10 (0.04)a 0.65 (0.14)ab 6.02 (0.38)a

Open canopy gap 0.10 (0.04)a 0.88 (0.23)a 6.22 (0.46)a

Valley 0.13 (0.05)a 0.55 (0.22)b 5.98 (0.32)a

Note: Values with different letters in the same column are significantly different 

(p ≤ 0.05). Standard deviations are in parentheses (n = 9).

Taxonomic richness 

of oribatid mites and 

Collembola was not 

significantly different 

among soil depth and 

landscape positions
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Table 6-2—Taxa of oribatid mites (genera and superfamilies) and Collembola (families) found at the Mission 

Creek site

Taxonomic level Genera or family name Taxonomic level Genera or family name

Oribatid genera Achiptera (1 species) Oribatid genera Maerkelotritia (3 species)

Achiptera immature Phauloppia 

Anachipteria (3 species) Quadroppia 

Camisia Scheloribates (4 species)

Carabodes (2 species) Sphaerochthonius 

Caenobelba Suctobelbella

Ceratoppia Tectocepheus 

Ceratozetes Unknown genera (20 species)

Cosmochthonius

Cultroribula Oribatid superfamily Crotonioidea 

Ctenacarus Damaeoidea (3 taxa) 

Eniochthonius Damaeoidea immature (2 taxa)

Eporibatula Gustavioidea immature (2 taxa)

Eremaeus (4 species) Phenopelopoidea immature

Eremaeus immature (1 species) Plateremaeoidea (2 taxa)

Hermaniella

Liacarus (4 species) Collembola family Entomobryidae

Neoribates Hypogastrura

Odontodamaeus (2 species) Isotomidae

Oppia Onychiuridae

Oppiella Sminthuridae

Oribatella (2 species)

Table 6-3—Mean oribatid mite richness and density relative to soil depth and landscape position

Ridge Slope Open canopy gap Valley

Metric 0–4 cm 5–9 cm 0–4 cm 5–9 cm 0–4 cm 5–9 cm 0–4 cm 5–9 cm

Richness (number of taxa) 7.9 5.2 9.3 6.9 8.0 5.0 11.8 7.3 

(standard deviation) (6.6) (4.8) (6.3) (5.3) (5.9) (4.9) (5.8) (5.3)

Density (number/m3) 906,114 327,511 1,048,035 698,690 1,146,288 425,764 1,102,620 665,939

(standard deviation) (873,362) (393,013) (917,031) (807,860) (1,189,956) (502,183) (545,852) (753,275)

Note: Average number of taxa per sample unit was not significantly different among landscape positions and depths (p ≤ 0.05). 

Individual sample unit = 91.6 cm3 (n = 9).

Average density was not significantly different among landscape positions, but was significantly higher in 0–4-cm depth than 

5–9-cm depth (p ≤ 0.05).

Table 6-4—Collembola richness and density relative to soil depth and landscape position 

Ridge Slope Open canopy gap Valley

Metric 0–4 cm 5–9 cm 0–4 cm 5–9 cm 0–4 cm 5–9 cm 0–4 cm 5–9 cm

Richness (number of taxa) 0.7 0.7 1.1 0.9 0.8 0.7 1.9 1.6

(standard deviation) (0.9) (0.9) (1.3) (0.8) (1.4) (0.9) (1.6) (1.0)

Density (number/m3) 120,087 65,502 32,751 87,336 21,834 10,917 98,253 98,253

(standard deviation) (316,594) (152,838) (43,668) (163,755) (54,585) (21,834) (87,336) (120,087)

Average number of taxa per sample unit and density were not significantly different among landscape position and depths (p ≤ 0.05). 

Individual sample unit = 91.6 cm3 (n = 9).
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depth to 1.9 in the valleys at the 0- to 4-cm depth. Average Collembola densities 

ranged from 10,917/m3 in gaps at the 5- to 9-cm depth to 120,087/m3 on ridges at 

the 0- to 4-cm depth (table 6-4), but were not significantly different by depth and 

landscape position because of the large variance. 

Relationships Between Oribatid Mite and Collembola Taxa 

Richness and Density and Soil Moisture, Bulk Density and pH

There were no significant relationships between oribatid mite taxa richness or 

density in the 5- to 9-cm layer and soil environmental variables except that mite 

density and pH were correlated (r = -0.97, p = 0.03, n = 4) as were Collembola 

density and soil bulk density (r = -0.97, p = 0.03, n = 4). 

Discussion

Oribatid mites and Collembola were the most numerous soil microarthropods at 

Mission Creek. This is similar to reports for the dry soils of the Teakettle Experimental Forest in the southern Sierra Nevada Mountains of California (Marra and 

Edmonds 2005) and for the moist soils on the Olympic Peninsula, Washington 

(Marra and Edmonds 1998). There were more mites (84 percent of invertebrates) 

than Collembola (7 percent) at Mission Creek. Similarly, Marra and Edmonds 

(2005) found that mites made up 78 percent of invertebrates sampled in spring in 

the top 8 cm of soil at Teakettle, whereas Collembola made up 13 percent. Studies 

in other conifer (mediterranean pine, mixed-conifer) and hardwood (birch, red oak, 

red maple) forest types also found greater numbers of mites than Collembola in the 

soil (Ojala and Huhta 2001, Peck and Niwa 2005, Reynolds et al. 2003, Tsiafouli et 

al. 2005). 

Mites tend to dominate undisturbed habitats and forest soils, whereas Collembola are more dominant in managed grasslands and arable lands (Filser 2002). 

The high incidence of mites in forest soils across the landscape could be due to 

the lack of mite predators such as thrips and predatory mites, but there are few 

studies examining forest soil predator-prey relationships (Anderson 1978, Halliday 

2005, Naher et al. 2005). The thick cuticles and leg protection mechanisms of adult 

oribatid mites probably decrease the probability of predation (Norton 1994). 

Sixty-nine total taxa of mature oribatid mites occurred at Mission Creek, only 

slightly fewer than the number of taxa found in the moist soils of the Olympic 

Mountains of Washington, which involved a similar sampling method (Marra and 

Edmonds 1998). The higher number of taxa at the Olympic Peninsula site may be 

due to the milder climate on the Olympic Peninsula compared to that at the Mission 

Mites tend to dominate 

undisturbed habitats 

and forest soils, 

whereas Collembola 

are more dominant in 

managed grasslands 

and arable lands.
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Creek site, which is drier and has more extreme temperature fluctuations. It could 

also be because the taxa at Mission Creek are adapted to unique habitat niches, 

represented by the different landscape positions we sampled. 

Similar or lower total oribatid mite taxa have been reported from other forest 

soils in North America and Europe. For instance, 22 oribatid mite taxa were found 

in an oak forest in Greece (Stamou and Sgardelis 1989), 51 in a mixed-conifer forest 

in California (Marra and Edmonds 2005), 61 in a hardwood forest in New York 

(Minor and Cianciolo 2007), 71 in the organic layer of spruce stands in Germany 

(Zaitsev et al. 2002), and 73 in a hardwood forest in North Carolina (Johnston and 

Crossley 1993). 

Landscape position at Mission Creek did not significantly influence the taxonomic richness of mites. However, there was a tendency toward lower richness of 

oribatid mites on ridges and in open canopy gaps, suggesting that conditions in 

these environments were less favorable for mites than those in slopes and valleys. 

Landscape position also did not significantly influence Collembola taxonomic richness, but the largest average numbers were in the valley position. Collembola have 

close associations with roots and plant communities (Hiol et al. 1994). Thus Collembola richness patterns could be related to higher root production and biological 

activity occurring within rhizospheres and rhizoplanes in valley positions (Curl et 

al. 1988, Hiol et al. 1994, Maire et al. 1999). Collembola can feed on a wide variety 

of organisms, ranging from algae to invertebrates to living plant matter (Rusek 

1998, Thimm and Larink 1995). Many species of Collembola are generalists, but 

some have been shown to be highly selective on fungi in soils (Jorgensen et al. 

2005, Marshall 1978, Scheu and Falca 2000, Thimm and Larink 1995). 

Because Collembola are sensitive to drought, their taxonomic richness has been 

related to vegetation type in areas with dry soils (Ehrnsberger et al. 1997; Hagvar 

1982; Materna 2004; Rusek 1993, 1994). Soil moisture may influence Collembola 

because some species lack true tracheal systems and are prone to desiccation 

(Joosse 1981, Tsiafouli et al. 2005). However, we found that Collembola taxa and 

soil moisture were not strongly related, and soil moisture was not significantly 

different by landscape position. 

Bulk density also influences oribatid mites and Collembola. Low bulk density 

tends to be favorable to many soil arthropods because soils with low bulk density 

usually have more pore spaces and higher soil organic matter content than soils 

with high bulk densities (Marra and Edmonds 2005). Pore size is positively correlated with microarthropod abundance (Vreeken-Buijs et al. 1998). Many Collembolan species feed on fungi, and soil with greater pore sizes allows for greater 

fungal growth and sporulation. Furthermore, the presence of small invertebrate 
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species may serve as food sources for larger invertebrates (Anderson et al. 1984, 

Visser 1985, Vreeken-Buijs et al. 1998). Marra and Edmonds (2005) found that bulk 

density explained a high amount of the variance in invertebrate populations in the 

California Sierra Nevada Mountains. We also found a significant negative relationship between Collembola density and soil bulk density at the Mission Creek site. 

There was little variation in soil pH across our experimental units (5.98 to 6.40), 

and pH did not strongly influence Collembola communities. However, we did find 

a significant relationship between oribatid mite density and soil pH, with higher 

densities in the more acidic environments.

In conclusion, we found soil microinvertebrates in all landscape positions 

(ridges, slopes, open canopy gaps, and valleys), with oribatid mites and Collembola 

being the most abundant. Oribatid mites had a higher number of taxa and higher 

densities than Collembola. There were no significant differences among landscape 

positions with respect to mite or Collembola taxonomic richness or density, except 

that oribatid mite density was significantly higher in the 0- to 4-cm layer than the 

5- to 9-cm layer. Collembola density was negatively correlated with bulk density. 

No soil environmental variables were significantly correlated with oribatid mite 

taxa richness and density except pH, which was negatively correlated with mite 

density. 

Acknowledgments

We thank George Scherer and Nick Brazee for help with fieldwork and Jeff Hatten 

for providing soils data. 

Literature Cited

Anderson, J.M. 1978. Competition of two unrelated species of soil Cryptostigmata 

(Acari) in experimental microcosms. Journal of Animal Ecology. 47: 787–803.

Anderson, R.V.; Ingham, R.E.; Trofymow, J.A.; Coleman, D.C. 1984. Soil 

mesofaunal distribution in relation to habitat types in a shortgrass prairie. 

Pedobiologia. 26: 257–261.

Asquith, A.; Lattin, J.D.; Moldenke, A.R. 1990. Arthropods: the invisible 

diversity. Northwest Environmental Journal. 6: 2404–2405.

Behan-Pelletier, V.M. 1999. Oribatid mite biodiversity in agroecosystems: role for 

bioindication. Agriculture, Ecosystems and Environment. 74: 411–423.

Collembola density 

was negatively 

correlated with bulk 

density and pH was 

negatively correlated 

with mite density.
77

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Curl, E.A.; Lartey, R.; Peterson, C.M. 1988. Interactions between root 

pathogens and soil microarthropods. Agriculture, Ecosystems and 

Environment. 24: 249–261. 

Dolan, E. 2002. Soil and site variability in the northeast Wenatchee Mountains, 

Washington. Seattle, WA: University of Washington. 103 p. M.S. thesis.

Ehrnsberger, R.; Sterzynska, M.; Szeptycki, A. 1997. Apterygota of a North 

Sea salt marsh-community structure and vertical distribution. Pedobiologia. 

41: 123–130. 

Filser, J. 2002. The role of Collembola in carbon and nitrogen cycling in soil. 

Pedobiologia. 46: 234–245. 

Hagvar, S. 1982. Collembola in Norwegian coniferous forest soils. I. Relations to 

plant communities and soil fertility. Pedobiologia. 24: 255–296. 

Halliday, R.B. 2005. Predatory mites from crops and pastures in South Africa: 

potential natural enemies of redlegged earth mite Halotydeus destructor

(Acari: Penthaleidae). Zootaxa. 1079: 11–64.

Hiol, F.H.; Dixon, R.K.; Curl, E.A. 1994. The feeding preference of mycophagous 

collembolan varies with the ectomycorrhizal symbiont. Mycorrhiza. 5: 99–103.

Johnston, J.M.; Crossley, D.A., Jr. 1993. The significance of coarse woody 

debris for the diversity of soil mites. Gen. Tech. Rep. SE-94. Athens, GA: U.S. 

Department of Agriculture, Forest Service, Southern Research Station: 82–87.

Joosse, E.N.G. 1981. Ecological strategies and population regulation of collembola 

in heterogeneous environments. Pedobiologia. 21: 346–356. 

Jorgensen, H.B.; Johansson, T.; Canback, B.; Hedlund, K.; Tunlid, A. 2005. 

Selective foraging of fungi by collembolans in soil. Biology Letters. 1: 243–246. 

Killham, K. 1994. Soil ecology. Cambridge, United Kingdom: Press Syndicate of 

the University of Cambridge. 242 p.

Lillybridge, T.R.; Kovalchik, B.L.; Williams, C.K.; Smith, B.G. 1995. Field 

guide for forested plant associations of the Wenatchee National Forest. Gen. 

Tech. Rep. PNW-GTR-359. Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station. 337 p.

Maire, N.; Borcad, D.; Laczko, E.; Matthey, W. 1999. Organic matter cycling in 

grassland soils of the Swiss Jura Mountains: biodiversity and strategies of living 

communities. Soil Biology and Biochemistry. 31: 1281–1293. 
78

RESEARCH PAPER PNW-RP-577

Marra, J.L.; Edmonds, R.L. 1998. The effects of coarse woody debris and 

soil depth on the density and diversity of soil invertebrates on clearcut 

and forested sites on the Olympic Peninsula Washington. Environmental 

Entomology. 27: 1111–1124.

Marra, J.L.; Edmonds, R.L. 2005. Soil arthropod responses to different 

patch types in a mixed-conifer forest of the Sierra Nevada. Forest Science. 

51(3): 255–265.

Marshall, V.G. 1978. Gut content analysis of the Collembolan Bourletiella 

hortensis (Fitch) from a forest nursery. Revue d’Ecologie et de Biologie 

du Sol. 15: 243–250.

Materna, J. 2004. Does forest type and vegetation patchiness influence horizontal 

distribution of soil collembola in two neighboring forest sites? Pedobiologia. 

48: 339–347.

Minor, M.A.; Cianciolo, J.M. 2007. Diversity of soil mites (Acari: Oribatida, 

Mesostigmata) along a gradient of land use types in New York. Applied Soil 

Ecology. 35: 140–153.

Moldenke, A.R. 1990. One-hundred twenty-thousand little legs. Wings. 15: 11–14.

Moldenke, A.R. 1994. Arthropods. In: Weaver, R.W., ed. Methods of soil analysis: 

Part 2 Microbiological and biochemical properties. Madison, WI: Soil Science 

Society of America: 517-542.

Moldenke, A.R.; Lattin, J.D. 1990. Density and diversity of arthropods as 

“biological probes” of complex soil phenomena. Northwest Environmental 

Journal. 6: 409–410.

Moldenke, A.R.; Pajutee, M.; Ingham, E. 2000. The functional roles of forest 

soil arthropods: the soil is a living place. In: Powers, R.F.; Hauxwell, D.L.; 

Nakamura, G.M., eds. Proceedings, California Forest Soils Council conference 

on forest soils biology and forest management. Gen. Tech. Rep. PSW-GTR-186. 

Berkeley, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest 

Research Station: 7–22.

Naher, N.; Islam, W.; Haque, M.M. 2005. Predation of three predators on twospotted spider mite, Tetranychus urticae Koch. (Acari: Tetranychidae). Journal 

of Life Earth Science. 1: 1–4.
79

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Norton, R.A. 1994. Evolutionary aspects of oribatid mites life histories and 

consequences for the origin of the Astigmata. In: Houck, M.A., ed. Mites: 

ecological and evolutionary analyses of life-history patterns. New York: 

Chapman and Hall: 99–135. 

Norton, R.A.; Behan-Pelletier, V.M. 1991. Calcium carbonate and calcium oxalate 

as cuticular hardening agents in oribatid mites (Acari: Oribatida). Canadian 

Journal of Zoology. 69: 1504–1511.

Ojala, R.; Huhta, V. 2001. Dispersal of microarthropods in forest soil. 

Pedobiologia. 45: 443–450.

Oliver I.; Beattie, A.J. 1996. Designing a cost-effective invertebrate survey: a 

test of methods for rapid assessment of biodiversity. Ecological Applications. 

6: 594–607.

Peck, R.W.; Niwa, C.G. 2005. Longer-term effects of selective thinning 

on microarthropod communities in a late-successional coniferous forest. 

Environmental Entomology. 34: 646–655.

Reynolds, B.C.; Crossley, D.A., Jr.; Hunter, M.D. 2003. Response of soil 

invertebrates to forest canopy inputs along a productivity gradient. 

Pedobiologia. 47: 127–139.

Rusek, J. 1993. Air-pollution-mediated changes in alpine ecosystems and ecotones. 

Ecological Applications. 3: 409–416. 

Rusek, J. 1994. Succession of Collembola and some ecosystem components on a 

pingo in the Mackenzie River Delta, N.W.T., Canada. Acta Zoologica Fennica. 

195: 119–123.

Rusek, J. 1998. Biodiversity of collembola and their functional role in the 

ecosystem. Biodiversity and Conservation. 7: 1207–1219.

Scheu, S.; Falca, M. 2000. The soil food web of two beech forests (Fagus 

sylvatica) of contrasting humus type: stable isotope analysis of a macroand mesofauna-dominated community. Oecologia. 123: 285–296.

Seastedt, T.R. 1984. The role of microarthropods in decomposition and 

mineralization processes. Annual Review of Entomology. 29: 25–46.

Seastedt, T.R.; Crossley, D.A., Jr. 1987. Soil arthropods and their role in 

decomposition and mineralization processes. In: Swank, W.T.; Crossley, D.A., Jr., 

eds. Forest hydrology and ecology at Coweeta. New York: Springer: 233–243.
80

RESEARCH PAPER PNW-RP-577

SPSS. 2004. Version 13.0. Chicago, IL.: SPSS, Inc. 

Stamou, G.P.; Sgardelis, S.P. 1989. Seasonal distribution patterns of oribatid mites 

(Acari: Cryptostigmata) in a forest ecosystem. The Journal of Animal Ecology. 

58: 893–904.

Stork, N.E.; Eggleton, P. 1992. Invertebrates as determinants and indicators of soil 

quality. American Journal of Alternative Agriculture. 7: 38–47.

Thimm, T.; Larink, O. 1995. Grazing preferences of some collembola for 

endomycorrhizal fungi. Biology and Fertility of Soils. 19: 266–268.

Tsiafouli, M.A.; Kallimanis, A.S.; Katana, E.; Stamou, G.P.; Sgardelis, 

S.P. 2005. Responses of soil microarthropods to experimental short-term 

manipulations of soil moisture. Applied Soil Ecology. 29: 17–26.

Visser, S. 1985. Role of soil invertebrates in determining the composition of 

soil microbial communities. In: Fitter, A.H., ed. Ecological interaction in soil. 

Oxford, United Kingdom: Blackwell: 297–317.

Vreeken-Buijs, M.J.; Hassink, J.; Brussaard, L. 1998. Relationships of soil 

microarthropod biomass with organic matter and pore size distribution in soils 

under different land use. Soil Biology and Biochemistry. 30: 97–106.

Zaitsev, A.S., Chauvat, M., Pflug, A., Wolters, V. 2002. Oribatid mite diversity 

and community dynamics in a spruce chronosequence. Soil Biology and 

Biochemistry. 34: 1919–1927.
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Paul F. Hessburg, R. Brion Salter, and Anne C. Conway 1

Introduction

A primary objective of dry forest stand silvicultural treatments is to reduce the 

overstory and understory tree density while favoring large-diameter trees and 

fire-tolerant species. Thinning and burning treatments have the potential to either 

increase or decrease root disease and bark beetle mortality and dwarf mistletoe 

incidence. For example, after treatments, residual trees with larger diameters may 

occur in clumps where basal area per hectare may be higher, which may be attractive to bark beetles. 

Similarly, dwarf mistletoe infections in dry mixed-conifer stands may show 

considerable latency when stands are relatively dense, not fully expressing the presence of all infections via visible mistletoe plants or significant witches brooms until 

stands have been released by thinning or burning. In such cases, the residual trees 

and the infections both tend to respond significantly to release. Thus, it is important 

to measure and compare pre- and posttreatment incidence and severity to determine 

whether treatments are producing favorable effects on native pathogen and insect 

disturbances.

Methods

In this segment of the study, 10 contiguous hectares of each experimental unit were 

systematically surveyed; all trees showing signs, symptoms, or evidence of tree 

decline or mortality were evaluated for evidence of attack by native root pathogens 

or bark beetles. A 10-ha survey area was chosen because the smallest experimental 

units (Camas, Crow 3, and Slawson) were approximately 10 ha (fig. 7-1). All dead 

and symptomatic trees of each experimental unit were recorded on 1:900-scale 

orthophotograph field maps. 

Chapter 7: Pretreatment Variability in 

Bark Beetle, Root Disease, and Dwarf 

Mistletoe Incidence and Severity

1 Paul F. Hessburg is a research ecologist (phessburg@fs.fed.us), R. Brion Salter is a 

geographer, and Anne C. Conway was a biological technician, Pacific Northwest Research 

Station, 1133 N Western Ave, Wenatchee, WA 98801.

Thinning and burning 

treatments have the 

potential to either 

increase or decrease 

root disease and 

bark beetle mortality 

and dwarf mistletoe 

incidence.
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RESEARCH PAPER PNW-RP-577

Figure 7-1—Vicinity map of the Mission Creek Fire and Fire Surrogate Study Area showing experimental unit boundaries and 

sampled areas.

Field maps were generated in a geographic information system (GIS) by 

overlaying a high-resolution (0.2-m ground resolution) color digital orthophotograph with a 40-m sampling grid and 40-ft (12-m) elevation contours. The sampling 

grid spatial layer was created with the ArcInfo (Environmental Systems Research 

Institute 2006) GENERATE command and was anchored on universal transverse 

mercator (UTM) coordinates that were evenly divisible by 40 m to ease navigation 

intervals in the field. 
83

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

2 The use of trade or firm names in this publication is for reader information and does not 

imply endorsement by the U.S. Department of Agriculture of any product or service.

We generated the color digital orthophotos by georeferencing high-resolution 

(15 μm) digitally scanned images of standard resource aerial photograph negatives, 

which we then digitally flipped to photo-positives. The aerial photo scans were 

acquired from the USDA Farm Services Agency (FSA) Aerial Photography Field 

Office (APFO) and had an original photo scale of 1:15,840. Orthorectification was 

conducted with ERDAS Imagine2 (Leica Geosystems 2006) software, and the highresolution orthophotos were horizontally georeferenced to the 1998 USDA Forest 

Service, 1-m digital orthoquadrangles, and vertically to USGS 7.5-minute digital 

elevation models (10-m DEM). The field-mapped trees were then digitized onscreen with ArcView software (Environmental Systems Research Institute 2006) 

over the same digital orthophoto and 40-m grid as the field maps. This constituted 

the initial spatial data layer of tree locations; the orthophotos functioned as highresolution aerial photographs and georeferenced maps of tree locations such that 

little time was needed in the field to georeference tree data. We simply needed to 

circle the relevant trees on the photos when we recorded data on them.

The dead and symptomatic trees ≥ 12.7 cm (5.0 in) diameter at breast height 

(d.b.h.) were identified in each experimental unit and mapped directly on the 

orthophotos in the field, and site and tree attribute data were recorded. Site and 

tree data included: 

1. Plant association 

2. Elevation 

3. Aspect 

4. Experimental unit number 

5. UTM grid cell alphanumeric code (letters-rows, numbers-columns) 

6. Tree number (restarted numbering each UTM grid cell) 

7. Tree height (m) 

8. Tree d.b.h (cm) 

9. Tree species

10. Tree status (dead, symptomatic, nonsymptomatic)

11. Damaging agent(s)

12. Tree live crown ratio (LCR) 

13. Tree radial growth (last 10 yr growth measured in 20ths of an inch, 

e.g., 13 = 13/20 in)

14. Bark beetle species present

15. Extent of bark beetle activity
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RESEARCH PAPER PNW-RP-577

16. Presence/absence of woodborers 

17. Extent of any woodpecker foraging activity 

18. Type of woodpecker foraging (hits—deep round holes, 

scaling—flaked-away outer bark) 

19. Identity of any sap-rotting fungi present 

20. Extent of sapwood decay

Attribute data were entered into a database, and this database was joined with 

the spatial data of tree locations based on a unique identifier, which included site, 

grid cell, and grid-cell-specific tree number codes (e.g., 11-C8-1).

Identifying Tree-Killing Root Pathogens

The primary purpose of the national pathology protocols for all installations was 

to survey for root disease and treatment effects on root diseases. For the pathology 

pre- and posttreatment surveys, we implemented a 100-percent field survey of 10 

ha of each experimental unit because we anticipated that we would find little to no 

root disease on these dry plant associations. We surveyed and mapped all existing root-disease-affected trees. Root-disease-affected trees and mortality centers 

were georeferenced in the field to high-resolution orthorectified 1:900 resource 

aerial photographs by means the 40-m UTM grid and a Mylar® overlay. Individual 

diseased and symptomatic or killed trees were mapped to the full extent of the drip 

line of each affected tree. 

During the pre- and posttreatment surveys, we identified and mapped all 

trees showing new symptoms or mortality associated with any native root disease 

pathogen. Root pathogens of interest were Phellinus weirii (PHWE), the cause of 

laminated root rot, Heterobasidion annosum (HEAN) (both S- and P-groups), the 

cause of annosum root disease, Armillaria ostoyae (AROS), the cause of Armillaria 

root disease, and Leptographium wageneri (LEWA), the cause of black stain root 

disease. 

Minimally invasive root collar excavations were used to locate and identify 

possible root pathogens in symptomatic trees. We exposed a major lateral root 

to a distance of 1 m from the root collar and looked for signs of infection such 

as presence of rhizomorphs on or around the root collar or root, laminated decay 

with pitting on one or both sides, setal hyphae, mycelial fans beneath the bark, 

resin-soaked straw-colored decay with characteristic flecking, basal resinosus, or 

resin-soaked bark, and evidence of mushrooms or other more conk-like basidiomes 

in stumps, under or on roots, or at the root collar. 

For pathology surveys, 

we implemented a 

100-percent field 

survey of 10 ha of 

each experimental 

unit.
85

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Specimens were collected from the root of symptomatic trees by cutting 

a wedge, with bark intact, using a hand pruning saw. The specimen was then 

wrapped in tree flagging to secure the bark and placed in a sealable plastic 

sandwich bag. The root was then recovered with soil. Putative rhizomorphs were 

collected and placed in plastic drinking straws, the straw ends were crimped and 

flame-sealed. All specimens were marked with date, species code, and unique 

identifier showing the site number, the grid cell number, and the tree number of 

that grid cell. Specimens were placed in cold storage until weekly shipments in 

coolers on dry ice were made to the Moscow, Idaho, Forestry Sciences Laboratory 

for identification. 

Isolations from infected root samples and rhizomorphs were conducted using 

standard protocols and cultural media (Hoff 2002, Hoff et al. 2004a). Any putative 

Armillaria spp. isolates were identified to genet and North American Biological 

Species by our cooperator Dr. Ned Klopfenstein or his students using established 

tester cultures and amplified restriction fragment length polymorphism molecular 

assays (Hoff 2002; Hoff et al. 2004a, 2004b). We also isolated and identified any 

fungal endophytes that were present in roots (Hoff 2002; Hoff et al. 2004a, 2004b). 

In addition to collecting samples from visibly symptomatic trees, trees without 

visible symptoms of root disease or other damaging agents were surveyed in a 

systematic random sample for HEAN and Armillaria spp. because these diseases 

could be present at low levels or as yet unexpressed. Nonsymptomatic trees were 

selected in every other grid cell, forming a checkerboard pattern. The first apparently healthy tree encountered north of the SW corner of each sampled grid cell was 

used as a nonsymptomatic sample tree. We then recorded the site and tree data, as 

described above, examined one major lateral root to a distance of 1 m from the root 

collar, and removed and placed a root core in a soda straw; the straw was sealed and 

labeled with a unique identifier, cold stored, and shipped as previously described for 

later identification.

Identifying Tree-Killing Bark Beetles

For the entomology pre- and posttreatment surveys, we implemented a 100-percent 

field survey of a 10-ha area of each experimental unit. We surveyed and mapped all 

existing bark-beetle affected-trees. Bark-beetle-affected trees and mortality centers 

were likewise georeferenced in the field to high-resolution orthorectified 1:900 

resource aerial photographs by means of the 40-m UTM grid and a Mylar® photo 

overlay. Individual bark-beetle-infested or killed trees were mapped as the full 

extent of the drip line of each affected tree. 
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RESEARCH PAPER PNW-RP-577

Bark beetles of primary interest in Douglas-fir (Pseudotsuga menziesii (Mirb.) 

Franco) were Dendroctonus pseudotsugae (DEPS), the Douglas-fir beetle, and 

Scolytus unispinosus (SCUN), the Douglas-fir engraver. In ponderosa pine (Pinus 

ponderosa Dougl. ex Laws), the bark beetles of interest were D. ponderosae

(DEPO), the mountain pine beetle; D. brevicomis (DEBR), the western pine beetle; 

D. valens (DEVA), the red turpentine beetle; and Ips spp. In addition, we surveyed 

for Scolytus ventralis (SCVE), the fir engraver, on grand fir (Abies grandis (Dougl. 

ex D. Don) Lindl.), which occurred in only four units (Camas, Crow 3, Ruby, and 

Poison). Bark beetles were identified by the host species attacked, the characteristic 

egg and larval gallery patterns, the presence and color of boring frass, and by the 

presence and number of gallery ventilation holes. 

Survey crews were trained in the field to identify dry forest pathogen and insect 

damages by their signs and symptoms. They were also given line drawings, photos, 

and keys depicting these diagnostic criteria. Diagnostic aids were used to link the 

field training with the field identification procedure, and to establish positive identifications. Galleries were examined in the field by removing a section of bark with a 

Pulaski or cruiser’s axe in the vicinity of pitch tubes, pitch streaming, woodpecker 

activity, and/or boring frass. 

Recording Woodpecker Foraging 

We recorded the vertical extent of the bole with visible signs of woodpecker foraging by identifying the section(s) that displayed evidence of woodpecker foraging. 

There were two types of foraging recognized: subsurface scaling or flaking of the 

bark, and hits, a narrow horizontal cone of bark removal to the cambium that was 

required to remove deeply buried woodborer or bark beetle larvae. 

Scaling only occurred on ponderosa pine that had been mass attacked by the 

western pine beetle, where woodpeckers would find late instar larvae migrating 

outward in the outer bark. Teneral (callow) adults ultimately emerge from a region 

just beneath the outer bark surface. Hits were associated with woodpecker foraging 

for bark beetles and woodborers that complete their development in the cambial 

region between the inner bark and secondary xylem. 

Woodpeckers were found hit foraging on most Scolytid (Ips spp., Dendroctonus

spp., Scolytus spp.) bark beetles (excluding the western pine beetle, Dendroctonus 

brevicomis) and most woodborers (Coleoptera/Cerambycidae, long-horned borers; 

Coleoptera/Buprestidae, metallic woodborers). Furthermore, woodpeckers tended 

to produce a large hit-foraging excavation hole to remove woodborer larvae, which 

Scaling only occurred 

on ponderosa pine 

that had been mass 

attacked by the 

western pine beetle.
87

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

tend to be much larger at maturity than bark beetle larvae. Each bole segment 

displaying woodpecker hit or scaling foraging behavior was recorded by entering the starting and ending vertical heights of the bole segments displaying such 

foraging. The lengths of bole segment(s) were ocularly estimated to the nearest 1.5 

m. To calibrate the observer’s eye, ocular estimates were checked each day against 

clinometer measurements of the same. 

We also recorded the presence and extent of saprot basidiomes (fruiting 

bodies) such as that associated with Cryptoporus volvatus, the pouch fungus, 

and Hirschioporus abietinum, the purple conk. The presence of the pouch fungus 

is highly indicative of prior bark beetle mass or strip attack episodes.

Recognizing Dwarf Mistletoe Incidence and Severity

Because the characterization of pretreatment dwarf mistletoe conditions is not 

addressed in the national protocols, collection of the pre- and posttreatment dwarf 

mistletoe data was optional in our study plan. We collected dwarf mistletoe data 

because field experience taught us that there would be no appreciable root disease 

identified in dry forest stands such as these. Preliminary surveys showed that dwarf 

mistletoe (Arceuthobium spp.) infection centers were relatively well distributed in 

many experimental units; thus, we deemed it impractical to conduct a complete 

census of the infected trees. We adopted a variable-plot sampling method to capture 

the overstory tree mistletoe data. This involved placing a single variable-prism or 

Relaskop plot (BAF 20) in the center of every other 40-m UTM grid cell (random 

start), as indicated on the rectified aerial photo, until 32 plots had been measured. 

The grid cells sampled were overlaid on the same area (64 grid cells covered 10 ha) 

sampled for bark beetles. 

For each tree that fell within the variable radius prism plot, we collected: 

1. Tree d.b.h. 

2. Tree species 

3. Live crown ratio 

4. Crown class 

5. Dwarf mistletoe rating (Hawksworth 6-class system) 

Tree height, age, and radial growth were recorded for the first tree of each 

species and size class in each prism plot. We tallied all seedlings and saplings 

below breast height in a 1/100-acre microplot using the same plot center. 
88

RESEARCH PAPER PNW-RP-577

Each tree was inspected for signs and symptoms of dwarf mistletoe infection. 

If mistletoe was present, the damage and severity were listed with the individual 

tree information. Dwarf mistletoe infections were identified by the presence of 

mistletoe-induced witches’ brooms in the host, the presence of basal cups or branch 

swelling, and by the presence of the male (staminate—pollen producing) and female 

(pistillate—seed producing) plants of the parasite. Infection severity was recorded 

by estimating a Hawksworth dwarf mistletoe rating (DMR) for that tree (Hawksworth 1977). For reference, the individual tree DMRs were obtained by dividing 

the stacked live crown vertically into equal thirds, and to each third assigning a 

rating of 0, 1, or 2 as follows:

0 = no visible branch infections (mistletoe plants) or witches’ brooms located 

anywhere in the third. 

1 = ≤ 1⁄2 of the branches in the third are infected or with brooms. 

2 = > 1⁄2 of the branches in the third are infected or with brooms.

In ponderosa pine, a single large witches’ broom (i.e., the broom is the dominant feature) in any crown third is sufficient to give that crown third a rating of 

2. In Douglas-fir, mistletoe plants were often too small to see from the ground, 

and individual tree DMR ratings were based almost entirely on visible brooms in 

infected branches. The maximum DMR score was 6 for any tree; the minimum 

score was 0. 

Analysis

Dwarf mistletoe and root disease incidence and severity, bark beetle mortality, and 

woodpecker foraging evidence were recorded in all experimental units. Root disease infection and mortality and bark beetle mortality were surveyed in a complete 

census owing to our recent advances with developing high-resolution orthophoto 

field maps. Such georeferencing saved about 80 percent of the time ordinarily 

needed in the field to georeference data, thereby allowing a complete census rather 

than sampling, and it freed up resources to conduct the dwarf mistletoe survey. 

Owing to the large number of infected trees, dwarf mistletoe incidence and 

severity were sampled by using variable and fixed plots. Data were averaged up 

from the plot level to the experimental unit level for all analyses, or they were 

summed in the case of the total census. 
89

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Bark beetle impact on the site conditions was summarized by experimental 

unit and reported by diameter class for trees per hectare (fig. 7-2) and basal area per 

hectare (m2/ha, fig. 7-3) killed by each bark beetle species. Likewise, dwarf mistletoe impact to the baseline conditions was summarized by experimental unit and 

reported by diameter distributions of mistletoe-infected trees per hectare (fig. 7-4) 

and infected basal area per hectare (m2/ha, fig. 7-5) by host species. 

In addition to showing tree stocking and basal area effects, we summarized 

average dwarf mistletoe infection severity (average DMR) for ponderosa pine and 

Douglas-fir host diameter classes (fig. 7-6). 

Finally, we summarized baseline conditions with respect to snags and available 

woodpecker foraging habitat. To complete this analysis, we computed the percentage of the total trees greater than 20 cm d.b.h. that were snags with evidence of any 

woodpecker foraging. These results are shown in figure 7-7.
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RESEARCH PAPER PNW-RP-577

Crow 3 Sand 19 Sand 2

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

<10

10–20

20–30

30–40

40–50

50–60

>60

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

<10

10–20

20–30

30–40

40–50

50–60

>60

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

<10

10–20

20–30

30–40

40–50

50–60

>60

Bark

beetle

m

ortality (trees/ha)

0 0 0

Control

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

<10

10–20

20–30

30–40

40–50

50–60

>60

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

<10

10–20

20–30

30–40

40–50

50–60

>60

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

<10

10–20

20–30

30–40

40–50

50–60

>60

Burn

Bark

beetle

m

ortality (trees/ha)

0 0 0

Pendleton Poison Spromberg

Tree diameter (cm)

DEBR DEPO DEPS Other

Figure 7-2—Diameter distributions of trees killed by bark beetles in experimental units within the Mission Creek Fire and Fire Surrogate Study. Units are arranged by treatment based on a balanced design with three replicates per treatment or treatment combination. 

Abbreviations are: DEBR—Dendroctonus brevicomis, the western pine beetle; DEPO—Dendroctonus ponderosae, the mountain pine 

beetle; DEPS—Dendroctonus pseudotsugae, the Douglas-fir beetle; Other—Scolytus ventralis, the fir-engraver beetle, Pseudohylesinus 

nebulosus, the Douglas-fir engraver beetle, Dendroctonus valens, the red turpentine beetle, and Ips spp., pine engraver beetles.
91

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Figure 7-2—Diameter distributions of trees killed by bark beetles in experimental units within the Mission Creek Fire and Fire 

Surrogate Study (continued). Bark beetle mortality (trees/ha) Bark beetle mortality (trees/ha)

Camas Crow 6 Tripp

<10

10–20

20–30

30–40

40–50

50–60

<10

>60

10–20

20–30

30–40

40–50

50–60

>60

<10

10–20

20–30

30–40

40–50

50–60

>60

Thin

<10

10–20

20–30

30–40

40–50

50–60

>60

<10

10–20

20–30

30–40

40–50

50–60

>60

<10

10–20

20–30

30–40

40–50

50–60

>60

Thin-Burn

Crow 1 Ruby Slawson

Tree diameter (cm)

DEBR DEPO DEPS Other

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

0
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RESEARCH PAPER PNW-RP-577

Figure 7-3—Diameter distributions of basal area killed by bark beetles in experimental units within the Mission Creek Fire and 

Fire Surrogate Study. Units are arranged by treatment based on a balanced design with three replicates per treatment or treatment 

combination. Abbreviations are: DEBR—Dendroctonus brevicomis, the western pine beetle; DEPO—Dendroctonus ponderosae, 

the mountain pine beetle; DEPS—Dendroctonus pseudotsugae, the Douglas-fir beetle; Other—Scolytus ventralis, the fir-engraver 

beetle, Pseudohylesinus nebulosus, the Douglas-fir engraver beetle, Dendroctonus valens, the red turpentine beetle, and Ips spp., 

pine engraver beetles.

Pendleton Poison Spromberg

Crow 3 Sand 19 Sand 2

Tree diameter (cm)

DEBR DEPO DEPS Other

<10

0 0

<10

0

<10

0 0

<10

0

Control

Burn

Bark beetle mortality (m2/ha) Bark beetle mortality (m2/ha)

10–20

20–30

30–40

40–50

50–60

>60

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

<10

10–20

20–30

30–40

40–50

50–60

>60

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

10–20

20–30

30–40

40–50

50–60

>60

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

10–20

20–30

30–40

40–50

50–60

>60

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

<10

10–20

20–30

30–40

40–50

50–60

>60

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

10–20

20–30

30–40

40–50

50–60

>60

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0
93

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Figure 7-3—Diameter distributions of basal area killed by bark beetles in experimental units within the Mission Creek Fire and Fire 

Surrogate Study (continued).

Thin

Bark beetle mortality (m2/ha) Bark beetle mortality (m2/ha)

10–20

20–30

30–40

40–50

50–60

>60

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

<10

10–20

20–30

30–40

40–50

50–60

>60

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

10–20

20–30

30–40

40–50

50–60

>60

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

10–20

20–30

30–40

40–50

50–60

>60

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

<10<10<10

<10<10

10–20

20–30

30–40

40–50

50–60

>60

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

10–20

20–30

30–40

40–50

50–60

>60

0.5

0 0 0

0 0 0

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Camas Crow 6 Tripp

Thin-Burn

Crow 1 Ruby Slawson

Tree diameter (cm)

DEBR DEPO DEPS Other
94

RESEARCH PAPER PNW-RP-577

Figure 7-4—Diameter distributions of trees infected by dwarf mistletoes in experimental units within the Mission Creek Fire and Fire 

Surrogate Study. Units are arranged by treatment based on a balanced design with three replicates per treatment or treatment combination. Abbreviations are: PSME—Pseudotsuga menziesii, which is infected by the host specialized mistletoe—Arceuthobium douglasii, 

and PIPO—Pinus ponderosa, which is infected by the host-specialized mistletoe—Arceuthobium campylopodum.

D

warf mistletoe infested (trees/ha)

Pendleton Poison Spromberg

Crow 3 Sand 19 Sand 2

Tree diameter (cm)

PSME PIPO

<10<10

<10<10

Control

Burn

10–20

20–30

30–40

40–50

50–60

<10

>60

10–20

20–30

30–40

40–50

50–60

>60

10–20

20–30

30–40

40–50

50–60

>60

10–20

20–30

30–40

40–50

50–60

<10

>60

10–20

20–30

30–40

40–50

50–60

>60

10–20

20–30

30–40

40–50

50–60

>60

1,600

1,400

1,200

1,000

800

600

400

200

0

D

warf mistletoe infested (trees/ha) 1,600

1,400

1,200

1,000

800

600

400

200

0

1,600

1,400

1,200

1,000

800

600

400

200

0

1,600

1,400

1,200

1,000

800

600

400

200

0

1,600

1,400

1,200

1,000

800

600

400

200

0

1,600

1,400

1,200

1,000

800

600

400

200

0
95

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Figure 7-4—Diameter distributions of trees infected by dwarf mistletoes in experimental units within the Mission Creek Fire and 

Fire Surrogate Study (continued).

D

warf mistletoe infested (trees/ha)

Camas Crow 6 Tripp

Crow 1 Ruby Slawson

Tree diameter (cm)

PSME PIPO

<10<10

<10<10

Thin

Thin-Burn

10–20

20–30

30–40

40–50

50–60

<10

>60

10–20

20–30

30–40

40–50

50–60

>60

10–20

20–30

30–40

40–50

50–60

>60

10–20

20–30

30–40

40–50

50–60

<10

>60

10–20

20–30

30–40

40–50

50–60

>60

10–20

20–30

30–40

40–50

50–60

>60

1,600

1,400

1,200

1,000

800

600

400

200

0

D

warf mistletoe infested (trees/ha) 1,600

1,400

1,200

1,000

800

600

400

200

0

1,600

1,400

1,200

1,000

800

600

400

200

0

1,600

1,400

1,200

1,000

800

600

400

200

0

1,600

1,400

1,200

1,000

800

600

400

200

0

1,600

1,400

1,200

1,000

800

600

400

200

0
96

RESEARCH PAPER PNW-RP-577

Figure 7-5—Diameter distributions of basal area infected by dwarf mistletoes in experimental units within the Mission Creek Fire 

and Fire Surrogate Study. Units are arranged by treatment based on a balanced design with three replicates per treatment or treatment 

combination. Abbreviations are: PSME—Pseudotsuga menziesii, which is infected by the host specialized mistletoe—Arceuthobium 

douglasii, and PIPO—Pinus ponderosa, which is infected by the host-specialized mistletoe—Arceuthobium campylopodum.

D

warf mistletoe infested (m2/ha)

Pendleton Poison Spromberg

Crow 3 Sand 19 Sand 2

Tree diameter (cm)

PSME PIPO

<10<10

<10<10

Control

Burn

10–20

20–30

30–40

40–50

50–60

<10

>60

10–20

20–30

30–40

40–50

50–60

>60

10–20

20–30

30–40

40–50

50–60

>60

10–20

20–30

30–40

40–50

50–60

<10

>60

10–20

20–30

30–40

40–50

50–60

>60

10–20

20–30

30–40

40–50

50–60

>60

5.0

4.0

3.0

2.0

1.0

0

D

warf mistletoe infested (m2/ha)

5.0

4.0

3.0

2.0

1.0

0

5.0

4.0

3.0

2.0

1.0

0

5.0

4.0

3.0

2.0

1.0

0

5.0

4.0

3.0

2.0

1.0

0

5.0

4.0

3.0

2.0

1.0

0
97

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Figure 7-5—Diameter distributions of basal area infected by dwarf mistletoes in experimental units within the Mission Creek 

Fire and Fire Surrogate Study (continued).

D

warf mistletoe infested (m2/ha)

Camas Crow 6 Tripp

Crow 1 Ruby Slawson

Tree diameter (cm)

PSME PIPO

<10<10

<10<10

Thin

Thin-Burn

10–20

20–30

30–40

40–50

50–60

<10

>60

10–20

20–30

30–40

40–50

50–60

>60

10–20

20–30

30–40

40–50

50–60

>60

10–20

20–30

30–40

40–50

50–60

<10

>60

10–20

20–30

30–40

40–50

50–60

>60

10–20

20–30

30–40

40–50

50–60

>60

5.0

4.0

3.0

2.0

1.0

0

D

warf mistletoe infested (m2/ha)

5.0

4.0

3.0

2.0

1.0

0

5.0

4.0

3.0

2.0

1.0

0

5.0

4.0

3.0

2.0

1.0

0

5.0

4.0

3.0

2.0

1.0

0

5.0

4.0

3.0

2.0

1.0

0
98

RESEARCH PAPER PNW-RP-577

Figure 7-6—Diameter distributions and average dwarf mistletoe rating of trees infected by dwarf mistletoes in experimental units within 

the Mission Creek Fire and Fire Surrogate Study. Units are arranged by treatment based on a balanced design with three replicates 

per treatment or treatment combination. Abbreviations are: PSME—Pseudotsuga menziesii, which is infected by the host specialized 

mistletoe—Arceuthobium douglasii, and PIPO—Pinus ponderosa, which is infected by the host-specialized mistletoe—Arceuthobium 

campylopodum. Average dwarf 

mistletoe rating Average dwarf 

mistletoe rating

Pendleton Poison Spromberg

Crow 3 Sand 19 Sand 2

Tree diameter (cm)

PSME PIPO

<10

Burn

Control

10–20

20–30

30–40

40–50

50–60

>60

6.0

5.0

4.0

3.0

2.0

1.0

0

<10

10–20

20–30

30–40

40–50

50–60

>60

6.0

5.0

4.0

3.0

2.0

1.0

0

<10

10–20

20–30

30–40

40–50

50–60

>60

6.0

5.0

4.0

3.0

2.0

1.0

0

<10

10–20

20–30

30–40

40–50

50–60

>60

6.0

5.0

4.0

3.0

2.0

1.0

0

<10

10–20

20–30

30–40

40–50

50–60

>60

6.0

5.0

4.0

3.0

2.0

1.0

0

<10

10–20

20–30

30–40

40–50

50–60

>60

6.0

5.0

4.0

3.0

2.0

1.0

0
99

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Figure 7-6—Diameter distributions and average dwarf mistletoe rating of trees infected by dwarf mistletoes in experimental units 

within the Mission Creek Fire and Fire Surrogate Study (continued). Average dwarf 

mistletoe rating Average dwarf 

mistletoe rating

Tree diameter (cm)

PSME PIPO

<10

10–20

20–30

30–40

40–50

50–60

>60

6.0

5.0

4.0

3.0

2.0

1.0

0

<10

10–20

20–30

30–40

40–50

50–60

>60

6.0

5.0

4.0

3.0

2.0

1.0

0

<10

10–20

20–30

30–40

40–50

50–60

>60

6.0

5.0

4.0

3.0

2.0

1.0

0

<10

10–20

20–30

30–40

40–50

50–60

>60

6.0

5.0

4.0

3.0

2.0

1.0

0

<10

10–20

20–30

30–40

40–50

50–60

>60

6.0

5.0

4.0

3.0

2.0

1.0

0

<10

10–20

20–30

30–40

40–50

50–60

>60

6.0

5.0

4.0

3.0

2.0

1.0

0

Camas Crow 6 Tripp

Crow 1 Ruby Slawson

Thin

Thin-Burn
100

RESEARCH PAPER PNW-RP-577

Figure 7-7—Percentages of trees greater than 20 cm diameter at breast height (d.b.h.) that were snags with evidence of 

woodpecker foraging. Units are arranged by treatment based on a balanced design with three replicates per treatment 

or treatment combination. Evidence of woodpecker foraging was found in trees attacked by all bark beetles species 

surveyed, and in those attacked by woodborers (Coleoptera/Cerambycidae and Buprestidae). 

0

1

2

3

4

5

6

7

8

9

Crow 3

Sand 19

Sand 2

Average

Percentage of trees > 20 cm

d.b.h.

with w

o

o

d

pecker foraging

0

1

2

3

4

5

6

7

8

9

0

1

2

3

4

5

6

7

8

9

0

1

2

3

4

5

6

7

8

9

Control

Pendleton

Poison

Spromberg

Average

Crow 1

Ruby

Swanson

Average

Percentage of trees > 20 cm

d.b.h.

with w

o

o

d

pecker foraging

Camas

Crow 6

Tripp

Average

Burn

Thin Thin-Burn
101

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Results and Discussion

In all, 1,170 trees were mapped and processed for evidence of root pathogens and 

bark beetle attacks or mortality. Of this total, 398 were nonsymptomatic trees, 

595 were attacked by bark beetles, and 177 were either symptomatic or dead from 

causes other than root pathogens or known bark beetles. In these latter instances, 

the bark beetle gallery signatures in the inner bark had long since decomposed, 

and egg gallery engravings had sap-rotted such that a positive identification of 

the attacking bark beetle species was impossible. However, blue staining of the 

sapwood was in evidence so that a positive identification of an unknown bark beetle 

attack was possible. Other causes of symptomatic or dead trees included droughtrelated mortality, dwarf mistletoe infection, mechanical injury, or top killing from 

historical insect defoliation (western spruce budworm [Choristoneura occidentalis

Freeman]) or comandra rust (Cronartium comandrae) infections. 

Root Pathogens

There was only one confirmed case of a root pathogen (HEAN), which occurred in 

the Pendleton experimental unit. Interestingly, this root pathogen was cultured from 

an apparently clean root sample taken from an asymptomatic tree. There were no 

confirmed cases of root disease mortality caused by any of the surveyed pathogens. 

No further studies beyond those reported here are anticipated for root pathogens.

Fungal Endophytes

The fungal community inhabiting large woody roots of healthy conifers has not 

been well documented. To provide more information about such communities, 

we conducted an exploratory survey of the fungal endophyte community of 

dry forests using the same increment cores extracted from the woody roots of 

the asymptomatic Douglas-fir and ponderosa pine that were sampled for latent 

root disease. Fungal isolates were cultured on standard media, and then were 

identified using a combination of molecular and morphological methods (Hoff et 

al. 2004b). Fungal genera and species identified in this study provide baseline data 

for future surveys of fungal endophytes. A complete write-up and explanation of 

the ecological roles of endophytes, methods for isolation, and a discussion of their 

importance may be found in Hoff 2002, and Hoff et al. 2004b.

A total of 289 root cores were evaluated for the presence of endophytes, and 

fungi were isolated from woody roots of 138 (47.8 percent) asymptomatic ponderosa 

pine and Douglas-fir (table 7-1). Averaged across all experimental plots, fungal 

isolates were obtained from 50 percent of the ponderosa pine roots and 45 percent 

of the Douglas-fir roots. Twenty-seven cores (9.3 percent) yielded multiple fungal 

Of 1,170 trees, 

examined, 398 were 

nonsymptomatic, 595 

were attacked by bark 

beetles, and 177 were 

symptomatic or dead 

from other causes. 

There was only one 

confirmed case of a 

root pathogen.
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RESEARCH PAPER PNW-RP-577

Table 7-1—Summary of fungal species isolated from roots of asymptomatic ponderosa pine and Douglas-fir 

hosts growing in dry forest environments of the Mission Creek study area 

Ponderosa pine host	 Douglas-fir host

PIPO plant PSME plant PIPO plant PSME plant

association association association association Total

Number (percent)

Total number of trees 48 112 1 128 289

Trees with isolated fungal endophyte 22 (45.8) 58 (51.8) 0 (0) 58 (45.3) 138 (47.8)

Trees with no isolated fungal endophytes 26 (54.2) 54 (48.2) 1(100) 70 (54.7) 151 (52.2)

Trees with multiple fungal endophytes 6 (12.5) 8 (7.1) 0 (0) 13 (10.2) 27 (9.3)

Byssochlamys sp. 5 (10.4) 22 (19.6) 0 32 (25.0) 59 (20.4)

Umbelopsis spp. 4 (8.3) 16 (14.3) 0 10 (7.8) 30 (10.4)

Mucor sp. 1 (2.1) 8 (7.1) 0 9 (7.0) 18 (6.2)

Penicillium sp. 1 (2.1) 3 (2.7) 0 6 (4.7) 10 (3.5)

Verticillium sp. 2 (4.2) 0 (0) 0 2 (1.6) 4 (1.4)

Cladosporium sp. 1 (2.1) 1 (0.9) 0 1 (0.8) 3 (1.0)

Tremella sp. 1 (2.1) 1 (0.9) 0 0 (0) 2 (0.7)

Epicoccum sp. 1 (2.1) 0 (0) 0 0 (0) 1 (0.3)

Phialophora sp. 1 (2.1) 0 (0) 0 0 (0) 1 (0.3)

Alternaria sp. 0 (0) 1 (0.9) 0 0 (0) 1 (0.3)

Ulocladium sp. 1 (2.1) 0 (0) 0 0 (0) 1 (0.3)

Rhinocladiella sp. 0 (0) 1 (0.9) 0 0 (0) 1 (0.3)

Heterobasidion sp. 0 (0) 1 (0.9) 0 0 (0) 1 (0.3)

Eupenicillium sp. 1 (2.1) 0 (0) 0 0 (0) 1 (0.3)

Merimbla sp. 0 (0) 0 (0) 0 1 (0.8) 1 (0.3)

Hormonema sp. 0 (0) 0 (0) 0 1 (0.8) 1 (0.3)

Pesotum sp. 0 (0) 0 (0) 0 1 (0.8) 1 (0.3)

Unidentified 7 (14.6) 11 (9.8) 0 9 (7.0) 27 (9.3)

Note: For this study, PIPO typically included PIPO/PUTR, PIPO/CARU, and PIPO/AGSP plant associations; PSME included 

PSME/SPBEL, PSME/PUTR, PSME/CARU, PSME/SYAL, and PSME/AGSP plant associations (see text; Lillybridge et al. 

1995, Williams and Smith 1991). AGSP, Agropyron spicatum Pursh.; CARU, Calamagrostis rubescens Buckler; PIPO, Pinus 

ponderosa C. Lawson; PSME, Pseudotsuga menziesii (Mirb.) Franco; PUTR, Purshia tridentata (Pursh) DC.; SPBEL, Spiraea 

betulifolia var. lucida Pall.; SYAL, Symphoricarpos albus (L.) S.F. Blake. Table excerpted from Hoff et al. 2004a.

genera, 111 (38.4 percent) yielded growth of one fungal genus, and 151 (52.2 percent) yielded no fungi (table 7-1). A wide diversity of fungi was recovered from root 

cores, comprising 3 phyla, 11 orders, 13 families, and 17 genera. Fourteen genera 

were isolated from ponderosa pine, and nine genera were isolated from Douglas-fir. 

Although a medium selective for basidiomycetous fungi was used, the only basidiomycetes isolated were Tremella spp. (two isolates) and Heterobasidion spp. (one 

isolate). Most of the fungi isolated were ascomycetes and zygomycetes (table 7-2). 

Byssochlamys nivea Westling, Umbelopsis spp., and Mucor spp. were the fungi 

most frequently recovered from ponderosa pine (16.9, 12.5, and 5.6 percent of cores, 

respectively) and Douglas-fir (24.8, 7.8, and 7.0 percent of cores, respectively). 
103

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Results revealed that a relatively small number of cores from woody roots of 

Douglas-fir and ponderosa pine were colonized by various other fungal genera (e.g., 

Mucor spp., Penicillium spp., Verticillium spp., Cladosporium spp., and Tremella

spp.). Many of the taxa isolated infrequently in this study have been isolated in 

studies of root-colonizing fungi of other conifers (Fisher et al. 1991, Holdenrieder 

and Sieber 1992). Fisher et al. (1991) speculated that the presence of common soil 

and organic-debris-colonizing fungi, such as Cladosporium, Penicillium, Mucor, 

and Umbelopsis (as Mortierella), in woody roots may indicate that many different 

saprotrophic fungi have some limited ability to live in living root tissue. 

The diversity of fungi obtained from healthy, large, woody roots of two conifer 

species growing in a relatively narrow range of dry-forest settings suggests that 

an even broader flora of fungal endophytes might be found across diverse forest 

environments. This may be fertile ground for future research. It will be of further 

interest to study how fungi occupying this recently discovered niche might also 

influence the dynamics of fungi, perhaps most especially pathogenic fungi, in the 

rhizosphere of forest tree roots.

Bark Beetles

Across all 12 experimental units, the majority of bark-beetle-killed trees were 

killed by the western (378) and mountain pine beetles (144). We found very few 

instances of Douglas-fir beetle (41), Douglas-fir engraver (6), fir engraver (22), red 

turpentine beetle (4) and Ips spp. (6), considering that all dead and declining trees 

were censused across 12 overstocked, 10-ha experimental units. Table 7-2 shows 

the number of trees killed by pooled bark beetle species, experimental unit, and 

overstory tree size class. In each unit, the overstory is dominated by small (22.7- to 

37.9-cm d.b.h.) and medium sized (38.0- to 75.9-cm d.b.h.) trees, and most beetle 

mortality occurred in these same size classes. Three units, Crow 1, Crow 6, and 

Table 7-2—Pooled bark beetle mortality by overstory tree size class

Control Burn Thin Thin-burn

Overstory tree size class (cm)Crow 3Sand 19Sand 2PendletonPoisonSprombergCrow 1RubySlawsonCamasCrow 6Tripp

12.7–22.6 cm (poles) 2 0 0 23 0 4 14 9 0 4 14 1

22.7–37.9 cm (small trees) 19 1 3 70 2 8 73 19 6 16 63 1

38.0–75.9 cm (medium trees) 7 5 10 38 4 2 43 6 16 9 34 8

≥ 76.0 cm (large trees) 0 10 2 1 1 0 0 1 2 0 0 6

Note: Units are arranged by treatment based on a balanced design with three replicates per treatment or treatment combination.

The majority of barkbeetle-killed trees 

were killed by the 

western and mountain 

pine beetles.
104

RESEARCH PAPER PNW-RP-577

Pendleton, had large bark beetle mortality centers (fig. 7-8, and table 7-2), but when 

compared to the number of available host trees, the percentage of affected trees was 

relatively low (see fig. 7-2, and chapter 2, fig. 2-1). In each of these three experimental units, the cover type was clearly dominated by ponderosa pine, where pine cover 

exceeded 90 or 95 percent in each instance. Crow 1, the thinning experimental unit 

with the highest percentage of bark-beetle-killed trees, had a pine infestation rate of 

about 3.6 percent when averaged across trees of all size classes. All of the experimental units displayed a Douglas-fir beetle mortality rate of less than 1 percent of 

the total trees. 

The basal area of bark-beetle-infested trees told a similar story. Mortality 

expressed in terms of basal area per hectare (m2/ha) was relatively low in all units, 

highest in thinning experimental unit Crow 1, and much lower elsewhere (fig. 7-3). 

Figure 7-8—Western and mountain pine beetle mortality spatial distributions in experimental units Crow 1, Crow 6, and Pendleton. 

DEBR—Dendroctonus brevicomis, the western pine beetle; DEPO—Dendroctonus ponderosae, the mountain pine beetle.
105

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Figure 7-8—Western and mountain pine beetle mortality spatial distributions in experimental units Crow 1, Crow 6, and Pendleton. 

DEBR—Dendroctonus brevicomis, the western pine beetle; DEPO—Dendroctonus ponderosae, the mountain pine beetle.

Mistletoe

Dwarf mistletoe was found on all but two control units (Crow 3 and Sand 19), and 

incidence in Crow 6 was exceedingly low in ponderosa pine. In the Slawson thinning unit (fig. 7-4), mistletoe effects on stocking were greatest in Douglas-fir, but 

the greatest effects on basal area were to ponderosa pine. Douglas-fir and ponderosa 

pine were both infected in every overstory size class, although infection levels 

expressed in trees per hectare were low. These overstory infections had, over time, 

produced relatively high levels of infection in understory Douglas-fir seedlings 

and saplings (fig. 7-4) throughout the stand. Mistletoe effects on basal area per 

hectare were also greatest in Slawson, but most of the infected basal area occurred 

in the largest diameter trees, which were ponderosa pine (fig. 7-5). The story was 

Dwarf mistletoe was 

found on all but two 

units, but infection 

levels were low.
106

RESEARCH PAPER PNW-RP-577

Figure 7-8—Western and mountain pine beetle mortality spatial distributions in experimental units Crow 1, Crow 6, and Pendleton. 

DEBR—Dendroctonus brevicomis, the western pine beetle; DEPO—Dendroctonus ponderosae, the mountain pine beetle.

quite similar in the thin and burn experimental unit Tripp, although the number of 

Douglas-fir seedlings and saplings infected was much lower. 

Overall, dwarf mistletoe infection levels were low, affecting as little as 0 

percent (Crow 3, Sand 19) and as much as 7.9 (Tripp) to 8.8 percent (Slawson) of 

the total basal area per hectare (fig. 7-5). In Sand 2, Spromberg, Tripp, and Camas, 

overstory Douglas-fir made up the primary affected basal area. In Pendleton, 

Poison, Ruby, and Slawson, the primary infection was in ponderosa pine (fig. 7-5). 

Mistletoe effects on trees per hectare were trivial in all units but Slawson (fig. 7-4).

The distribution of mistletoe by severity rating (DMR) told a somewhat different story (fig. 7-6). In Slawson, dwarf mistletoe severity in Douglas-fir was nearly 

twice that in ponderosa pine, and the largest overstory size classes generally supported the worst mistletoe infections. The average DMR in the 50- to 60-cm size 
107

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

class was 6, denoting infection top to bottom. Ponderosa pine infection levels were 

much lower, and we suspect that thinning and combined thin-burn treatments could 

drastically reduce average infection levels. Tripp was quite similar to Slawson, but 

the highest average DMRs were in 20- to 30-cm ponderosa pine, which carried an 

average DMR severity level of 6. Above this size class, infection severity in overstory Douglas-fir and ponderosa pine was generally evenly distributed, and DMR 

severity ranged between 2.5 and 3.5.

Dwarf mistletoe infection severity was evenly distributed among most size 

classes of ponderosa pine in the Pendleton unit, but generally increased with 

increasing size class in the Poison unit. Infection severity was lowest in ponderosa 

pine in the Crow 1 and Crow 6 units, which had relatively low incidence to begin 

with. It is likely that with carefully designed silvicultural prescriptions, dwarf 

mistletoe may be maintained at low levels indefinitely in these two units.

In naturally occurring stands, dwarf mistletoe infection severity tends to be 

highest in the oldest and largest trees and lowest in the smaller and younger trees, 

even though effects on stocking may be highest in the smaller size classes. The 

distribution of infection severity in the Ruby and Sand 2 units suggests that prior 

thinning, partial removal, or selection cutting entries targeted the most severely 

infected ponderosa pine and Douglas-fir. In Ruby, these occurred in the intermediate size classes. In Sand 2, these occurred in the upper size classes (fig. 7-6).

Woodpecker Foraging

At the treatment level, there was little difference in the percentage of trees > 20 cm 

with woodpecker foraging. On average, approximately 2 to 3 percent of the trees 

> 20 cm were snags with evidence of woodpecker foraging. However, in the burn 

(Pendleton), thin (Crow 1), and thin-burn (Crow 6) treatments, higher than average 

snag abundance and evidence of woodpecker foraging was evident in at least one 

unit, but no difference was significant (p ≤ 0.05) owing to small sample size.

We opted to display the amount of foraging in trees greater than 20 cm (7.9 in) 

because many tree-killing bark beetles ordinarily have difficulty successfully rearing broods in small trees owing to their extremely thin secondary phloem (living 

inner bark), and the most prevalent bark beetles in these units (namely: Dendroctonus brevicomis, the western pine beetle; D. ponderosae, the mountain pine beetle; 

D. pseudotsugae, the Douglas-fir beetle; and Scolytus ventralis, the fir engraver) 

generally attack larger trees.

On average, approximately 2 to 3 percent of 

the trees > 20 cm were 

snags with evidence of 

woodpecker foraging. 
108

RESEARCH PAPER PNW-RP-577

Literature Cited

Environmental Systems Research Institute, Inc. 2006. ArcGISTM, Version 9.1. 

Redlands, CA.

Fisher, P.J.; Petrini, O.; Petrini, L.E. 1991. Endophytic ascomycetes and 

deuteromycetes in roots of Pinus sylvestris. Nova Hedwigia. 52: 11–15.

Hawksworth, F.G. 1977. The 6-class dwarf mistletoe rating system. Gen. Tech. 

Rep. RM-48. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Forest and Range Experiment Station. 7 p.

Hoff, J.A. 2002: Fungal diversity in woody roots of east-slope Cascade ponderosa 

pine (Pinus ponderosa) and Douglas-fir (Pseudotsuga menziesii). Pullman, WA: 

Washington State University. 77 p. M.S. thesis.

Hoff, J.A.; Klopfenstein, N.B.; McDonald, G.I.; Tonn, J.R.; Zambino, P.J.; 

Hessburg, P.F.; Rogers, J.D.; Peever, T.L.; Carris, L.M. 2004a. Fungal 

endophytes in woody roots of Douglas-fir (Pseudotsuga menziesii) and 

ponderosa pine (Pinus ponderosa). Journal of Forest Pathology. 34(4): 255–271. 

Hoff, J.A.; Klopfenstein, N.B.; Tonn, J.R.; McDonald, G.I.; Zambino, P.J.; 

Rogers, J.D.; Peever, T.L.; Carris, L.M. 2004b. Roles of woody rootassociated fungi in forest ecosystem processes: recent advances in fungal 

identification. Res. Pap. RMRS-RP-47. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station. 6 p.

Holdenrieder, O.; Sieber, T.N. 1992. Fungal associations of serially washed 

healthy non-mycorrhizal roots of Picea abies. Mycological Research. 

96: 151–156.

Leica Geosystems Geospatial Imaging, LLC. 2006. ERDAS Imagine®, Version 

8.7. Norcross, GA.

Lillybridge, T.R.; Kovalchik, B.L.; Williams, C.K.; Smith, B.G. 1995. Field 

guide for forested plant associations of the Wenatchee National Forest. Gen. 

Tech. Rep. PNW-GTR-359. Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station. 335 p.

Williams, C.K.; Smith, B.G. 1991. Forested plant associations of the Wenatchee 

National Forest. Unpublished report. On file with: Wenatchee National Forest, 

215 Melody Lane, Wenatchee, WA 98022-9240.
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

William L. Gaines, Andrea L. Lyons, John F. Lehmkuhl, Maryellen Haggard, 

James S. Begley, and Marlene Farrell 1

Introduction

The effects of fire exclusion on forests of the interior Western United States include 

changes to forest structure and composition at both the stand and landscape scales 

(Agee 2003, Camp et al. 1997, Everett et al. 2000, Harrod et al. 1999, Hessburg et 

al. 2000, 2007). It is expected that these changes result in corresponding changes to 

wildlife communities, with species generally associated with closed-canopy forests 

being favored over species associated with open-canopy forests (Lyon et al. 2000). 

Fire exclusion has been identified as one factor contributing to habitat loss for 

some key avian focal species (Germaine and Germaine 2002, Wisdom et al. 2000). 

However, limited information is available concerning the structure and composition 

of avian communities in dry interior western forests that have changed dramatically 

as a result of fire-exclusion policies. In this paper, we present the results of 2 years 

of monitoring avian species in forest stands that have experienced several decades 

of fire exclusion. In addition, we hypothesize about the effects that fire and fire surrogate restoration treatments may have on avian communities and some key focal 

species.

A growing number of studies have investigated the effects of restorative 

treatments in dry forests on avian species and communities (Gaines et al. 2007, 

Germaine and Germaine 2002, Greenberg et al. 2007, Wightman and Germaine 

2006, Zebehazy et al. 2004). Generally, these treatments have little effect on overall 

species abundance, richness, or evenness (Gaines et al. 2007, Greenberg et al. 2007, 

Zebehazy et al. 2004). However, the response of individual avian species varies. 

For example, the western bluebird (Sialia mexicana) and white-headed woodpecker 

may respond favorably to these treatments (Gaines et al. 2007, Wightman and 

Chapter 8: Avian Community 

Composition, Nesting Ecology, and 

Cavity-Nester Foraging Ecology

1 William L. Gaines (wgaines@fs.fed.us) and Andrea L. Lyons are wildlife biologists, 

Okanogan-Wenatchee National Forest, 215 Melody Lane, Wenatchee, WA 98801; John F. 

Lehmkuhl is a research wildlife biologist, and Marlene Farrell was a wildlife technician, 

U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 1133 

N Western Ave., Wenatchee, WA 98801; Maryellen Haggard was a wildlife biologist, 

U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 

Wenatchee, WA, now a planning biologist, Washington State Parks, Wenatchee, WA; 

James S. Begley was a wildlife biologist, U.S. Department of Agriculture, Forest Service, 

Pacific Northwest Research Station, Wenatchee, WA, now a research assistant, Western 

Transportation Institute, Ellensburg, WA 98926.

Fire exclusion has been 

identified as one factor 

contributing to habitat 

loss for some key avian 

focal species.
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Germaine 2006), whereas the red-breasted nuthatch may occur at lower densities in 

treated stands (Gaines et al. 2007). (See table 8-1 for scientific names of birds.) As 

Germaine and Germaine (2002) pointed out, the effects of these kinds of restoration 

treatments on wildlife need to be understood because it is imperative that forest 

restoration not focus solely on forest structural attributes without consideration of 

impacts to native wildlife. 

We monitored birds because (1) they are the most easily and inexpensively 

detected and identified vertebrate animals, (2) a single survey method can cover 

many species, and (3) accounting for and maintaining many species with different 

requirements promotes conservation strategies at the landscape scale (Hutto 1998, 

Hutto and Young 2002). In this paper we present results of pretreatment monitoring for the avian portion of the Fire and Fire Surrogate Study. We anticipate these 

results will be useful when interpreting the posttreatment monitoring results. In 

addition, they provide valuable insights into the ecology of avian species in dry forest stands that have experienced several decades of fire exclusion, a condition that is 

predominant across dry forest landscapes (Agee 1993, Harrod et al. 1999, Hessburg 

et al. 2005). Our study objectives were to determine (1) the composition of the avian 

community, (2) the foraging behavior and habitat of cavity-nesting birds, and (3) the 

nesting success and nesting substrate of as many species within the bird community 

as possible.

Methods

Avian Community Composition

Point counts are a relatively standardized method for estimating the relative 

abundance and diversity of avian species (Ralph et al. 1993). Point counts were 

conducted at 4 to 6 points per stand for four visits to each of the 12 study stands 

during May and June. Point count centers were located 200 m apart and 100 m from 

the stand edge. Each point count began within 1⁄2-hr of the official sunrise and was 

completed no later than 10 a.m. PST. Once at the point, the observer waited at least 

2 min., then identified and counted birds for 10 min. Birds were identified by song, 

call, or visual observations. Detections of birds were recorded at 10-m increments 

out to 80 m using horizontal distance. Flyovers were documented but not used in 

the analyses. Standard four-letter codes for each bird species were recorded.

A survey of all stands was completed before the next survey was initiated. 

Logistical constraints prevented a random sequencing of sampling. Some stands 

were grouped together (Crow 1, Crow 3, Crow 6) and sampled on a single day to 

improve sampling efficiency. All points used for counts were georeferenced using 

global positioning system.

Our study objectives 

were to determine (1) 

the composition of 

the avian community, 

(2) the foraging 

behavior and habitat 

of cavity-nesting birds, 

and (3) the nesting 

success and nesting 

substrate of as many 

species within the 

bird community as 

possible.
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Nest Productivity and Substrate

Standardized methods have been developed to assess avian productivity (Martin 

and Geupel 1993, Ralph et al. 1993). Nest searches provide the most direct measurement of nest success in specific habitats. They also allow identification of important 

habitat features associated with successful nests and insight into important habitat 

requirements and species coexistence. We conducted nest searching and monitoring 

from early May until mid July.

Nest searches were conducted in two replicates of each treatment (including 

controls), and nests were monitored until the fate (fledging young or failure) was 

determined. Stands were thoroughly searched for nests following routes that traversed all parts of the stands. Once a nest was found, flagging was used (10 to 15 m 

away) to indicate the species and nest number. Detailed instructions with a drawing 

were made so that the nest could be relocated for subsequent monitoring. 

Nests were monitored from a distance and all efforts were made to minimize 

disturbance. Nests were checked every 2 to 4 days, keeping careful track of the 

stage of each nest. Species-specific literature on clutch sizes, incubation, and nestling periods was used to estimate when incubation, hatching, or fledging was likely 

to occur, and more frequent visits were made during these times. Dead-end paths 

were avoided when checking nests by entering along one path and exiting along 

another so that predators had difficulty determining the exact nest location. Active 

nests were not visited if predators were observed nearby.

Once the nesting season was over in 2001 (the nest substrate protocol was not 

available in 2000), nesting habitat data were collected for the most common species (>9 nests). At each nest we recorded the height of the nesting substrate (m), 

nest substrate diameter at breast height (d.b.h.) (cm) (if applicable), nest height (m), 

percentage cover at the nest, and the orientation of the nest (N, S, E,W).

Cavity-Nester Foraging Behavior and Habitat

We used focal animal sampling (Martin and Bateson 1986) to quantify foraging 

activities of cavity-nesting bird species such as nuthatches and chickadees. Birds 

were located within each stand by walking a random transect for a 2-hr observation 

session, for a total of 24 hr of observation per stand per year. Upon visual detection 

of a cavity-nesting species, we observed and recorded the first foraging behavior 

demonstrated by the bird (Hejl et al. 1990) after a 10-sec delay to eliminate conspicuous behavior. To avoid collecting multiple observations of the same individual 

and to insure independence between observations, we collected data on individuals 

of the same species only if they were detected >120 m apart during a sampling 

session (Bell et al. 1990, Hurlbert 1984, Weikel and Hayes 1999). We then recorded 
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habitat information for the substrate upon which they were feeding at the observed 

moment. Habitat variables were tree species, tree height (m), d.b.h. (cm), status 

(alive or snag), beetle presence, fire effects (evidence of past fire), percentage of 

bark present, snag condition (based on Parks et al. 1997), and vertical and horizontal strata of foraging location on the tree. 

Data for assessing “available” habitats were collected for all trees greater than 

1.3 m tall in three 20- by 50-m Whitaker plots per study stand (see Harrod et al. 

this volume). Habitat variables recorded were tree species, tree height (m), tree 

d.b.h. (cm), and status (alive or snag). Canopy cover for each study stand was also 

calculated using a spherical densiometer. The available habitat data set consisted of 

5,338 trees, from which 360 trees were randomly selected to describe habitat “available” to cavity-nesting birds. We used a subset of the 5,338 trees to provide a ratio 

of used:available habitat appropriate for our habitat selection modeling approach 

(Max, T. 2003. Personal communication, statistician, Pacific Northwest Research 

Station, Portland, OR 97208).

Statistical Analyses

We examined the compositional similarity of the avian communities among the 

treatments using a nonparametric multivariate analysis in PC-ORD4 software 

(McCune and Mefford 1999). We chose this method over univariate measures 

because it summarizes all the information on the bird community simultaneously, 

allowing for an assessment of the community-level response to the treatments 

(Hanowski et al. 2003). For the community-level analyses, we used data out to 50 m 

from point centers combining pretreatment (2000, 2001) years to calculate an index 

of relative abundance for species with >1 detection. Examination of the detection 

probabilities for several species using program DISTANCE (Buckland et al. 2001) 

indicated that they were nearly equal out to 60 to 70 m; therefore, we chose 50 m 

to be conservative. We used multiresponse permutation procedures (MRPP) to test 

the hypothesis of no difference in avian species composition between the treatments 

in pretreatment avian communities (Biondini et al. 1988, Zimmerman et al. 1985). 

This produced an A statistic that measured the grouping “effect size,” or distinctiveness of groups, on a scale of 0 to 1. Values of A >0.3 are considered fairly 

high. Monte Carlo permutations calculated probabilities for differences between 

the treatments. To address the issue of multiplicity, we compared those probabilities 

with Bonferroni-adjusted P-values obtained by dividing the experiment-wise 

P ≤ 0.05 by three comparisons.
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

We used indicator species analysis (ISA), in PC-ORD4, to identify characteristic species found mostly in a single type (treatment) and present in the majority 

of the sites (replicate stands) belonging to that type (Dufrene and Legendre 1997). 

The ISA combined information on both species relative abundance and constancy 

to estimate indicator values for each species in each group. The maximum indicator 

value for a species within the treatment types was tested for statistical significance 

against random expectation calculated by Monte Carlo permutation. 

We used program DISTANCE to estimate bird density and assess detection 

probabilities of several species (Buckland et al. 2001). Again, data were pooled 

across the pretreatment (2000, 2001) sample years to increase sample sizes and the 

number of species for which we could calculate density estimates. We calculated 

mean density and 95-percent confidence intervals (CI) using data from the replicates of each treatment. We used the density estimates to compare stands among 

the assigned treatments. Abundance indices and ISA were used to corroborate the 

density estimate results. We did not use the abundance indices or the ISA alone to 

evaluate differences among assigned treatments because of difficulties in accounting for differing detection probabilities (Buckland et al. 2001).

We calculated daily survival rates, Mayfield estimates (Mayfield 1961, 1975), 

and standard error (SE) for species, or for a nesting guild (ground nester, foliage 

nester, cavity nester), with >20 nests (Hensler and Nichols 1981).

We analyzed selection of foraging habitat for cavity-nesting birds by comparing characteristics of foraged trees to randomly available trees within the study 

stands. We examined variables that would explain the variability inherent in habitat 

selection and attempted to create models that would be useful to habitat managers 

in predicting foraging habitat selection of cavity-nesting birds. A detection rate for 

cavity-nesting species was also calculated as the number of observations per 24-hr 

period. Additionally, we described bird foraging behavior and characteristics of 

selected substrates to supplement modeling results.

We designated five, a priori, binary linear logistic regression models of foraging tree selection that included data collected for both used and available trees. 

These model variables were chosen because (1) previous research indicated they are 

influential in habitat selection, (2) they are quantifiable components that can affect 

foraging habitat selection, and (3) they may be altered through forest management. 

We used SPSS Base Version 10.1 (SPSS, Inc. 2001) to model habitat selection. 

We evaluated each of the models separately using the “Enter” method, where 

all variables are entered in a single step. Our evaluation continued by applying 
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Akaike’s Information Criteria (AIC) (Anderson et al. 2001, Burnham and Anderson 

2002), adjusted for small sample sizes (AICc), to determine which of the models, or 

combination of models, best approximated the structure of our data set. The relative 

importance of each model variable was also calculated as described by Burnham 

and Anderson (2002: 168). This method provides a sum of the Akaike weights (wi) 

for each model where the variable of interest is present. The most “important” 

variables therefore have the largest total Akaike weights.

Results

Avian Community Composition

We recorded a total of 5,999 detections representing 84 avian species in our surveys. We calculated abundance indices for 49 species (table 8-1) and had sufficient 

data to calculate density estimates for 9 species (table 8-2). The most commonly 

detected species included the chipping sparrow, dark-eyed junco, mountain chickadee, Nashville warbler, pine siskin, red-breasted nuthatch, Townsend’s warbler, 

western tanager, and yellow-rumped warbler. The foraging guilds that composed 

the avian community included low understory/ground insectivores (36.2 percent), 

tree foliage insectivores (33.0 percent), bark insectivores (11.1 percent), tree 

seedeaters (10.5 percent), aerial insectivores (8.1 percent), omnivore/scavengers 

(0.8 percent), and nectivores (0.5 percent). Of the species for which we calculated 

abundance indices, 48 percent were neotropical migrants, making up 49.5 percent 

of the total detections.

None of the avian species assemblages differed among assigned treatments 

based on the pretreatment data (MRPP A = 0.065, P = 0.901). However, there were 

some differences in individual species densities and detections among the assigned 

treatments (table 8-2). The chipping sparrow occurred at a higher density in the 

assigned thin-only stands compared to the assigned thin-burn stands (table 8-2). 

The Nashville warbler occurred at higher densities in the assigned burn-only, and 

thin-burn stands compared to the control (table 8-2). Red-breasted nuthatch was 

found in higher densities in the assigned thin-only and thin-burn stands compared 

to the control (table 8-2). Finally, the yellow-rumped warbler had higher densities in 

the assigned burn-only stands compared to the control stands (table 8-2). In addition 

to these differences, Wilson’s warbler and white-throated swift were only detected 

in the assigned burn-only stands (tables 8-1, 8-3).

None of the avian 

species assemblages 

differed among 

assigned treatments, 

but there were 

some differences in 

individual species 

densities and 

detections.
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Table 8-1—Mean avian abundance and 95-percent confidence interval (95% CI) by treatment for species with 

>1 detection for the pretreatment sampling years 2000–2001, Northeastern Cascades Fire and Fire Surrogate 

Study site

Thin Thin-burn Burn Control

±95% ±95% ±95% ±95%

Scientific name	 Common name	 Mean	 CI 	 Mean	 CI	 Mean	 CI	 Mean	 CI

Detections per point per visit

Low understory ground insectivores:

Carpodacus purpureus Purple finch 0.25 0.12 0.18 0.07 0.28 0.17 0.26 0.24

Catharus guttatus Hermit thrusha b 0.05 0.06 0.16 0.18 0.06 0.02 0.05 0.08

Catharus ustulatus Swainson thrushb 0 0.04 0.04 0.03 0.06 0.03 0.04

Junco hyemalis Dark-eyed junco 0.99 0.36 1.12 0.18 0.89 0.22 1.07 0.30

Molothrus ater Brown-headed cowbirdb 0.06 0.06 0.11 0.16 0.16 0.09 0.07 0.04

Myadestes townsendi Townsend’s solitaire 0.30 0.14 0.31 0.07 0.48 0.09 0.36 0.19

Oporornis tolmiei MacGillivray’s warblerb c 0.24 0.17 0.20 0.16 0.35 0.25 0.22 0.20

Pheucticus melanocephalus Black-headed grosbeakb 0.02 0.02 0.15 0.26 0.08 0.14 0.05 0.04

Pipilo maculatus Spotted towhee 0.17 0.09 0.42 0.35 0.31 0.26 0.48 0.14

Spizella passerina Chipping sparrowa b 0.33 0.27 0.37 0.35 0.44 0.19 0.40 0.43

Troglodytes aedon House wrenb 0 0.05 0.10 0.01 0.02 0

Troglodytes troglodytes Winter wren 0.02 0.02 0.01 0.02 0 0.01 0.02

Turdus migratorius American robin 0.09 0.07 0.24 0.29 0.15 0.10 0.22 0.16

Vermivora ruficapilla Nashville warblerb 0.54 0.50 0.78 0.92 0.77 0.67 0.44 0.20

Tree foliage insectivores:

Catharus fuscescens Veeryb 0 0.05 0.10 0 0.02 0.03

Dendroica coronata Yellow-rumped warblerb 0.74 0.19 0.71 0.26 0.80 0.28 0.57 0.49

Dendroica petechia Yellow warblerb 0.02 0.04 0.05 0.08 0.03 0.05 0

Dendroica townsendi Townsend’s warblerb 0.81 0.80 1.05 1.19 0.64 0.36 0.39 0.48

Passerina amoena Lazuli buntingb 0 0 0.03 0.01 0.04 0.04

Piranga ludoviciana Western tanagerb d 0.94 0.45 0.73 0.36 0.92 0.27 0.92 0.41

Poecile gambeli Mountain chickadee 0.51 0.25 0.71 0.31 0.75 0.07 0.55 0.09

Poecile rufescens Chestnut-backed chickadee 0.01 0.02 0.06 0.11 0 0.02 0.03

Regulus satrapa Golden-crowned kinglet 0.08 0.05 0.19 0.24 0.07 0.12 0.01 0.01

Wilsonia pusilla Wilson’s warblerb 0 0 0 0.02 0.01

Vireo cassinii Cassin’s vireob 0.22 0.18 0.15 0.04 0.33 0.13 0.29 0.22

Vireo gilvus Warbling vireob 0.01 0.01 0.03 0.05 0.06 0.12 0.01 0.03

Zenaida macroura Mourning dove 0 0.01 0.01 0 0.01 0.01

Bark insectivores:

Certhia americana Brown creepera 0.05 0.04 0.03 0.03 0.09 0.09 0.07 0.06

Colaptes auratus Northern flicker 0.06 0.07 0.06 0.06 0.05 0.04 0.07 0.07

Picoides albolarvatus White-headed woodpeckerc 0.02 0.02 0.01 0.01 0.01 0.02 0.03 0.03

Picoides villosus Hairy woodpecker 0.08 0.06 0.09 0.13 0.15 0.22 0

Sitta canadensis Red-breasted nuthatchd 0.92 0.20 0.97 0.09 0.78 0.10 0.81 0.28

Sitta carolinensis White-breasted nuthatch 0.04 0.05 0.06 0.09 0.07 0.14 0.02 0.03

Sitta pygmaea Pygmy nuthatcha 0.01 0.02 0.01 0.02 0 0

Aerial insectivores:

Aeronautes saxatalis White-throated swiftb 0 0 0 0.01 0.03

Empindonax difficilis Pacific-slope flycatcherb 0.01 0.01 0 0.03 0.03 0.08 0.13

Empindonax oberholseri/ Dusky/Hammond’s flycatcherb 0.63 0.68 0.61 0.54 1.35 0.62 0.58 0.58

 hammondii

Tachycineta thalassina Violet-green swallowb 0 0.01 0.01 0 0.01 0.03
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Table 8-1—Mean avian abundance and 95-percent confidence interval (95% CI) by treatment for species with 

>1 detection for the pretreatment sampling years 2000–2001, Northeastern Cascades Fire and Fire Surrogate 

Study site (continued)

Thin Thin-burn Burn Control

±95% ±95% ±95% ±95%

Scientific name	 Common name	 Mean	 CI 	 Mean	 CI	 Mean	 CI	 Mean	 CI

Detections per point per visit

Tree seedeaters:

Carduelis pinus Pine siskin 0.56 0.40 0.66 0.20 0.59 0.30 0.54 0.23

Carpodacus cassinii Cassin’s finchc 0.28 0.17 0.27 0.23 0.21 0.17 0.35 0.30

Coccothraustes vespertinus Evening grosbeak 0.01 0.01 0.02 0.04 0.03 0.04 0.01 0.02

Loxia curvirostra Red crossbill 0.20 0.06 0.18 0.05 0.10 0.04 0.14 0.11

Nucifraga columbiana Clark’s nutcracker 0.02 0.02 0.06 0.04 0.05 0.05 0.03 0.01

Omnivore-scavengers:

Corvus corax Common raven 0.02 0.02 0.05 0.07 0.01 0.01 0.02 0.04

Cyanocitta stelleri Steller’s jay 0.03 0.05 0.03 0.06 0.07 0.13 0.02 0.04

Perisoreus canadensis Gray jay 0 0 0.05 0.07 0.01 0.02 0.01 0.03

Nectivores:

Selasphorus rufus Rufous hummingbirdb 0.01 0.01 0.01 0.01 0.01 0.01 0

Stellula calliope Calliope hummingbirdb 0.04 0.04 0.06 0.07 0.03 0.04 0

Unknown hummingbird 0 0.01 0.01 0.01 0.01 0.01 0.02

a Focal species in Altman 2000

b Neotropical migratory species 

c Pacific Northwest Region Focal species (USDA FS 2006)

d Indicator species in Gaines et al. 2007

Table 8-2—Density (and confidence interval [CI]) estimates of avian species during the pretreatment sampling 

years of 2000 and 2001, Northeastern Cascades Fire and Fire Surrogate study site

Control Burn Thin Thin-burn

Species Density 95% CI Density 95% CI Density 95% CI Density 95% CI

Number per hectare

Chipping sparrowa 0.84 0.41–1.74 0.68 0.41–1.15 1.83 0.94–3.57 0.30 0.13–0.70

Dark-eyed junco 2.62 1.77–3.89 3.54 2.28–5.52 5.51 3.55–8.56 4.08 2.64–6.29

Mountain chickadee 0.53 0.37–0.75 0.69 0.48–0.99 0.87 0.47–1.60 0.69 0.32–1.50

Nashville warbler 0.36 0.17–0.78 4.10 0.97–17.42 1.47 0.34–6.39 3.20 0.94–10.96

Pine siskin 0.75 0.39–1.47 0.34 0.16–.074 0.31 0.18–0.53 0.93 0.37–2.34

Red-breasted nuthatchb 0.50 0.37–0.69 0.76 0.54–1.09 1.02 0.78–1.34 1.37 1.00–1.87

Townsend’s warbler 0.21 0.08–0.54 0.84 0.40–1.79 0.58 0.22–1.56 1.25 0.45–3.48

Western tanagerb 0.56 0.39–0.80 0.90 0.56–1.46 0.56 0.35–0.89 0.60 0.33–1.07

Yellow-rumped warbler 0.49 0.25–0.96 2.27 1.00–5.15 0.54 0.43–0.67 0.53 0.28–1.01

a Focal species in Altman 2000

b Indicator species in Gaines et al. 2007
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Table 8-3—Avian indicator species values by treatment for the pretreatment sampling 

years of 2000 and 2001, Northeastern Cascades Fire and Fire Surrogate study site

Indicator species values

Species Control Thin Thin-Burn Burn P-value

Low understory ground insectivores:

Chipping sparrow 21 24 29 26 0.946

Dark-eyed junco 24 27 22 26 0.701

Townsend’s solitaire 21 21 33 25 0.090

American robin 13 35 21 31 0.827

Brown-headed cowbird 14 27 41 18 0.243

House wren 0 83 17 0 1

Nashville warbler 21 31 30 17 0.907

Black-headed grosbeak 7 50 27 17 0.843

Spotted towhee 13 31 23 34 0.462

Hermit thrush 17 48 18 18 0.407

MacGillivray’s warbler 24 20 35 22 0.536

Purple finch 26 19 29 27 0.935

Swainson thrush 0 39 32 29 0.673

Winter wren 50 25 0 25 0.614

Tree foliage insectivores:

Yellow-rumped warbler 26 25 28 20 0.766

Western tanager 27 21 26 26 0.960

Mountain chickadee 20 28 30 22 0.464

Townsend’s warbler 28 36 22 14 0.679

Cassin’s vireo 22 15 33 30 0.581

Chestnut-backed chickadee 12 68 0 20 1

Golden-crowned kinglet 22 55 20 3 0.291

Veery 0 75 0 25 1

Wilson’s warbler 0 0 0 100 0.022

Lazuli bunting 0 0 36 64 0.266

Warbling vireo 6 24 58 12 1

Mourning dove 0 33 0 67 0.496

Yellow warbler 19 47 31 3 0.526

Bark insectivores:

Red-breasted nuthatch 26 28 22 23 0.408

Hairy woodpecker 25 28 45 1 0.441

White-breasted nuthatch 22 33 36 9 0.952

Pygmy nuthatch 50 50 0 0 1

White-headed woodpecker 33 10 14 43 0.730

Brown creeper 18 11 41 30 0.869

Northern flicker 26 26 20 29 0.896

Aerial insectivores:

Pacific-slope flycatcher 6 0 24 71 0.489

Dusky/Hammond’s flycatcher 20 19 43 18 0.148

Violet-green swallow 0 33 0 67 1

White-throated swift 0 0 0 100 1
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RESEARCH PAPER PNW-RP-577

Table 8-3—Avian indicator species values by treatment for the pretreatment sampling 

years of 2000 and 2001, Northeastern Cascades Fire and Fire Surrogate study site 

(continued)

Indicator species values

Species Control Thin Thin-Burn Burn P-value

Tree seedeaters:

Cassin’s finch 25 24 19 31 0.754

Pine siskin 24 28 25 23 0.841

Red crossbill 32 29 16 23 0.472

Evening grosbeak 11 32 42 16 0.884

Clark’s nutcracker 13 38 29 21 0.381

Omnivore/scavengers:

Gray jay 4 67 13 17 0.486

Steller’s jay 18 20 45 16 1

Common raven 22 48 7 22 0.791

Nectivores:

Calliope hummingbird 30 44 23 2 0.719

Rufous hummingbird 43 29 29 0 0.728

Unknown hummingbird 0 29 29 43 1

Nest Productivity and Substrate

We located and monitored a total of 198 nests representing 25 avian species (table 

8-4). The most common species that we found nests for included the dark-eyed 

junco (n = 53), a ground-nester, and red-breasted nuthatch (n = 27), a cavity-nester. 

Overall nest success was highest for cavity-nesters (70 percent, n = 39), followed by 

ground-nesters (48 percent, n = 75), and then foliage-nesters (43 percent, n = 67). 

We did not detect any differences in daily survival rates (DSR) for ground-nesting 

and cavity-nesting species among the assigned treatments (table 8-5). However, 

DSRs were higher in the assigned control stands compared to the assigned burnonly and thin-only stands for foliage-nesters. We observed three incidents of 

cowbird nest parasitism, one each on MacGillivray’s warbler, Nashville warbler, 

and dusky flycatcher. We were able to calculate Mayfield estimates (not by treatment) for two species. Mayfield survival estimate for the dark-eyed junco was 27 

percent (n = 53, 16.2 to 45.8, 95-percent CI) and for the red-breasted nuthatch was 

59 percent (n = 27, 41.2 to 83.9, 95-percent CI). 

We initiated the nest substrate measurement protocol in 2001 and gathered data 

on a total of 65 nests from four species; two cavity-nesters (n = 28), one foliagenester (n = 9), and one ground-nester (n = 28). The average tree height used by 

cavity-nesters was 3.1 m for the mountain chickadee and 13.6 m for the red-breasted 

nuthatch, shorter than average height of trees available within the study stands, 

Overall nest success 

was highest for cavitynesters, followed by 

ground-nesters, and 

then foliage-nesters.
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

which was 16.9 m. The average tree height used by foliage-nesters was 18.6 m for 

the chipping sparrow, which was similar to available trees (18.6 m). Tree d.b.h. for 

cavity-nesters averaged 46.9 cm for mountain chickadees and 40.4 cm for redbreasted nuthatches. The foliage-nesting chipping sparrow used trees that averaged 

47.1 cm. All three avian species used trees much larger for nesting than available in 

the study stands (mean d.b.h. = 22.5 cm). The amount of cover at the nest averaged 

52.5 percent for the chipping sparrow, a foliage-nester, and 74.1 percent for the 

dark-eyed junco, a ground-nester. 

Table 8-4—Number of nests/treatment and nest success (percentage) for the pretreatment sampling years of 

2000 and 2001, Northeastern Cascades Fire and Fire Surrogate study site

Burn Control Thin Thin-burn

Species Total Successful Total Successful Total Successful Total Successful

Ground-nesting species:

Common nighthawk 1 0 0 — 3 1 0 —

Dark-eyed junco 12 4 17 9 13 7 11 6 

Nashville warbler 3 2 1 1 0 — 0 —

Spotted towhee 2 1 0 — 2 2 1 0 

Townsend’s solitaire 2 1 0 — 5 2 2 0 

 Total 20 8 (40%) 18 10 (55%) 23 12 (52%) 14 6 (43%)

Foliage-nesting species:

Cassin’s vireo 0 — 1 0 1 1 1 1 

Chipping sparrow 3 3 3 2 7 4 1 1 

Dusky/Hammond’s flycatcher 10 2 2 2 7 2 4 0 

Hermit thrush 0 — 0 — 0 — 1 0

MacGillivray’s warbler 1 0 2 1 0 — 0 —

American robin 0 — 0 — 4 3 0 —

Cassin’s finch 1 0 0 — 0 — 0 —

Calliope hummingbird 0 — 0 — 1 0 1 1 

Townsend’s warbler 0 — 0 — 0 — 1 1 

Western tanager 2 0 4 3 4 0 2 1 

Yellow-rumped warbler 1 1 0 — 1 — 1 0 

 Total 18 6 (33%) 12 8 (67%) 25 10 (40%) 12 5 (42%)

Cavity-nesting species:

American kestrel 0 — 1 1 0 — 0 —

Chestnut-backed chickadee 1 1 0 — 0 — 1 0 

Hairy woodpecker 0 — 0 — 3 2 0 —

House wren 0 — 0 — 3 2 0 —

Mountain chickadee 6 6 5 3 3 2 1 1 

Northern flicker 0 — 0 — 2 2 0 —

Pygmy nuthatch 0 — 0 — 1 0 1 0 

Red-breasted nuthatch 8 6 5 3 10 6 4 3 

White-breasted nuthatch 0 — 0 — 1 1 0 —

 Total 15 13 (87%) 11 7 (64%) 23 15 (65%) 7 4 (57%)

All species 53 27 (51%) 41 25 (61%) 71 37 (52%) 33 15 (45%)
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RESEARCH PAPER PNW-RP-577

Cavity-Nester Foraging Behavior and Habitat

The available habitat data set consisted of 360 trees to describe habitat available to 

cavity-nesting birds. Approximately 50 percent of the trees available were ponderosa pine (Pinus ponderosa Dougl. ex Laws.) and 48 percent were Douglas-fir 

(Pseudotsuga menziesii (Mirb.) Franco). Canopy cover in the plots ranged from 66 

to 95 percent (mean = 79 percent) closed canopy. Mean d.b.h. was 22.5 cm ± 0.7, 

and mean tree height was 16.9 m ± 0.4 (table 8-6).

Table 8-5—Daily nest survival rates (DSR) and standard error (SE) 

by nesting guild during pretreatment breeding seasons, 2000–2001, 

Northeastern Cascades Fire and Fire Surrogate study site

Number Number of

Functional group of nests observation days DSR ± SE

Ground-nesting species:

Control 18 193.5 0.964 + 0.013

Burn 20 228.5 0.952 + 0.014

Thin 23 294 0.963 + 0.011

Thin-burn 14 162.5 0.957 + 0.016

Foliage-nesting species:

Control 12 112 0.982 + 0.013

Burn 18 221 0.950 + 0.015

Thin 25 252.5 0.945 + 0.014

Thin-burn 12 171.5 0.965 + 0.014

Cavity-nesting species:

Control 11 239 0.983 + 0.008

Burn 15 327.5 0.994 + 0.004

Thin 23 427 0.984 + 0.006

Thin-burn 7 126.5 0.976 + 0.014

Table 8-6—Mean (± standard error) diameter at breast height 

and height of trees used for foraging by cavity-nesting birds, 

and trees available within the pretreatment study stands, 

Northeastern Cascades Fire and Fire Surrogate study site

Bird species and habitat availability Diameter Height

Centimeters Meters

Hairy woodpecker 40.9 ± 2.51 17.5 ± 1.15

Mountain chickadee 38.6 ± 1.65 15.9 ± 0.62

Red-breasted nuthatch 43.4 ± 1.97 18.5 ± 0.63

Available habitat 22.5 ± 0.65 16.9 ± 0.37
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

In all, 253 foraging bouts were detected for all woodpeckers and cavity-nesting species. Observed species were black-capped chickadee (Poecile atricapillus), 

chestnut-backed chickadee, hairy woodpecker, mountain chickadee, northern 

flicker, pygmy nuthatch, red-breasted nuthatch, white-breasted nuthatch, and 

white-headed woodpecker. We conducted subsequent habitat selection analyses 

on the three species detected most frequently (88 percent of detections): hairy 

woodpecker (n = 32), mountain chickadee (n = 91), and red-breasted nuthatch 

(n = 99). In general, these species foraged on trees with diameters that were much 

greater than the average available trees within the study stands (table 8-6).

Logistic regression results suggested these three species exhibited selection 

with regard to foraging substrate (tables 8-7, 8-8). Although all five models were 

analyzed for all three bird species, we only retained those models with good support 

from the data, i.e., models with ∆AICc (∆i table 8-8) < 2. (Burnham and Anderson 

2002). This resulted in two models for each species that most likely approximated 

the “true” model. Evidence ratios for the models not presented here were generally 

exponentially greater than the chosen models. 

The global model was the most parsimonious model (i.e., lowest AICc value) 

for both hairy woodpecker and mountain chickadee (table 8-8). The second best 

mountain chickadee model, model 4, also had substantial empirical support. Model 

4 was the most parsimonious model for the red-breasted nuthatch (table 8-8). The 

probability of the top-ranked models being “true,” was much greater relative to 

the other models for the hairy woodpecker and red-breasted nuthatch. All models 

included the variables of tree species, diameter, height, and the diameter × height 

interaction term. The global model also included status.

All variables in each of the top-ranked models were relatively important 

(∑wi ≈ 1) with the exception of status. Status was moderately important in the 

hairy woodpecker model (∑wi = 0.68) and the mountain chickadee model (∑wi = 

0.51). Status was not as important in the red-breasted nuthatch model (∑wi = 0.31).

Table 8-7—Description of the models and variables tested to describe foraging selection of cavity-nesting 

birds in pretreatment sampling, Northeastern Cascades Fire and Fire Surrogate study site

Model	 Model variations	 Variable	 Label	 Definition

1 = tree spp. x1 tree spp. Tree species (PIPO, PSME, ABGR)

2 = tree spp. + dbh x2 dbh Tree diameter at breast height (cm)

3 = tree spp. + dbh + ht x3 ht Tree height (m)

4 = tree spp. + dbh + ht + dbh × ht x4 dbh × ht Interaction term, diameter × height

5 = tree spp. + dbh + ht + dbh × ht + status x5 status Tree status, live or snag

Note: PIPO = Pinus ponderosa, PSME = Pseudotsuga menziesii, ABGR = Abies grandis, 

dbh = diameter at breast height.

Hairy woodpeckers, 

mountain chickadees, 

and red-breasted 

nuthatches foraged on 

species with diameters 

much greater than the 

average available trees.
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Tree size appeared to influence selection for all three bird species (table 8-9). 

Both diameter and height were useful in explaining habitat use variation. Tree 

diameter was influential in each of the “best” models and Bdbh was always positive 

and significant in models that included diameter (table 8-9). All three bird species 

selected for trees with a diameter at least 1.7 times as large as the average available 

diameter. The average size of the foraging trees used by hairy woodpecker was 40.9 

cm (±2.51 cm SE), for the mountain chickadee it was 38.6 cm (±1.65 cm SE), and 

for the red-breasted nuthatch 43.4 cm (±1.97 cm SE). Most foraging observations 

occurred on 31- to 40 cm-diameter trees (fig. 8-1). Height was also influential, but 

Table 8-8—The best models for describing foraging habitat selection in cavity-nesting birds in pretreatment 

stands, Northeastern Cascades Fire and Fire Surrogate study site 

 Model Weight

Species number Model variables n (used) -2log(L) K AICc	 ∆AIC	 L(Mi/x) (wi)

Hairy woodpecker 5 Tree spp. + dbh + ht 31 114.84 7 133.71 0 1.0 0.68 + dbh × ht + status

4 Tree spp. + dbh + ht 31 120.26 6 135.76 2.05 0.36 0.24

 + dbh × ht

Mountain chickadee 5 Tree spp. + dbh + ht 91 230.04 7 245.39 0 1.0 0.51

 + dbh × ht + status

 4 Tree spp. + dbh + ht 91 232.50 6 245.50 0.11 0.95 0.49

 + dbh × ht

Red-breasted nuthatch 4 Tree spp. + dbh 99 275.71 6 288.62 0 1.0 0.69

 + ht + dbh × ht

5 Tree spp. + dbh + ht 99 274.99 7 290.22 1.60 0.45 0.31

+ dbh × ht + status

Note: K = number of parameters; AICc = Akaike’s Information Criterion adjusted for small sample sizes; ∆AIC = difference in AICc

between models; L(Mi/x) = evidence ratio; wi = Akaike weights.

Table 8-9—Values of β, standard error (SE) and confidence intervals for 

influential foraging selection variables in the top-ranked model for each 

cavity-nesting bird species within the Mission Creek study stands

	 95% confidence

Bird species	 Covariate	 β ± SE	 interval for β

Hairy woodpecker diameter 0.369 ± 0.092 1.208, 1.731

height 0.050 ± 0.142a 0.796, 1.388

dbh × height -0.009 ± 0.004 0.983, 0.999

status 1.559 ± 0.662 1.299, 17.386

Mountain chickadee diameter 0.356 ± 0.043 1.313, 1.553

height -0.218 ± 0.058 0.718, 0.900

dbh × height -0.006 ± 0.697 0.991, 0.996

status 1.055 ± 0.001a 0.733, 11.247

Red-breasted nuthatch diameter 0.317 ± 0.047 1.253, 1.505

height -0.078 ± 0.071a 0.805, 1.062

dbh × height -0.006 ± 0.002 0.990, 0.997

a Covariate was not significant at P < 0.05.
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

the relationship, in terms of correlation and significance, differed among species. 

Values of βht and βdbh× ht were negative for all species with the exception of βht 

for hairy woodpeckers. The interaction term was significant for all three species, 

whereas height was only significant for mountain chickadees. Most foraging 

observations occurred on trees 11 to 15 m tall (fig. 8-2). 

>80

71–80

61–70

51–60

41–50

31–40

21–30

10–20

<10

Tree diameter (cm)

Number of observations

0 10 20 30 40 50 60 70

Hairy woodpecker

Mountain chickadee

Red-breasted nuthatch

Figure 8-1—Diameter class of trees used as foraging substrate by cavity-nesting birds in the 

pretreatment stands, Northeastern Cascades Fire and Fire Surrogate study site.

>30

26–30

21–25

16–20

11–15

5–10

<5

Tree height (cm)

Number of observations

0 10 20 30 40 50 60 70 80

Hairy woodpecker

Mountain chickadee

Red-breasted nuthatch

Figure 8-2—Height class of trees used as foraging substrate by cavity-nesting birds in the 

pretreatment stands, Northeastern Cascades Fire and Fire Surrogate study site.
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Tree species did not influence selection. Birds were observed foraging more 

frequently on ponderosa pine (fig. 8-3); however, the relationship was not statistically significant relative to availability.

Tree status indicated whether the tree upon which the bird foraged was alive 

or dead (snag). Status did not significantly influence selection with the exception 

of hairy woodpeckers, suggesting woodpeckers selected for snags. Woodpeckers 

accounted for 40 percent of overall snag use. Only approximately 8 to 9 percent of 

the trees available were snags.

We also examined foraging activity on different substrates (table 8-10). The 

majority of observations were located on living portions of live trees. With the 

exception of hairy woodpeckers, birds were seldom observed using snags or dead 

portions of trees as a foraging substrate. Mountain chickadees and red-breasted 

nuthatches predominantly foraged on distal or medial portions of branches. Hairy 

woodpeckers were usually observed foraging on proximal portions of branches or 

on the bole of the tree. The vertical locations of observations were similar for all 

three species. Although birds demonstrated a slight tendency to forage higher up on 

the tree, observations were distributed fairly evenly between low and high locations 

on the tree. This does not give an indication of actual tree height, but rather relative 

location on the tree. Woodpeckers were generally observed pecking at or excavating 

the substrate, whereas chickadees and nuthatches were observed gleaning insects 

from the bark surface or foliage.

Figure 8-3—Tree species used as foraging substrate by cavity-nesting birds in the pretreatment 

stands, Northeastern Cascades Fire and Fire Surrogate study site.

140

120

100

80

60

40

20

0

Number of observations

Ponderosa pine Douglas-fir Grand fir

Tree species

Hairy woodpecker

Mountain chickadee

Red-breasted nuthatch
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Table 8-10—Percentage of bird detections relative to tree status and location 

on the tree for cavity-nesting birds observed foraging in pretreatment stands, 

Northeastern Cascades Fire and Fire Surrogate study site 

Status (of

tree or branch)

Horizontal location

Vertical location Proximal Distal or

Species Dead Alive or bole medial High Low

Percent

Hairy woodpecker 26 74 90 10 52 48

Mountain chickadee 6 94 18 82 58 42

Red-breasted nuthatch 11 89 36 64 60 40

Bole = main trunk of tree or snag.

High = upper half of tree/snag; low = lower half of tree/snag.

Proximal = proximal end of branch; medial = midway point on branch; distal = distal end of branch.

Detection rates differed among bird species. Detection rates for mountain 

chickadees and red-breasted nuthatches were at least three times that of hairy 

woodpecker rates. Hairy woodpeckers were observed approximately 1.3 times per 

hour. Mountain chickadees and red-breasted nuthatches were observed approximately 3.8 and 4.1 times per hour, respectively. Detection rates for all other species 

were less than 0.4 per hour.

Discussion

Avian Community Composition

Dense dry forest stands provide habitat for a bird community different than found 

in presettlement forests, and represent a forest condition that is currently dominant 

on the dry forest landscape (Agee 1993, Harrod et al. 1999, Hessburg et al. 2005). 

We found no differences in the overall avian community composition among 

stands, and this may be explained in part by the similarity in stand structure among 

the stands. Harrod et al. (this volume) found no significant differences in tree density and stocking, basal area, species composition, and canopy closure among the 

study stands. Gaines et al. (2007) found differences in avian species assemblages 

among dry forest stands that were dense due to fire exclusion, compared to stands 

that had been treated with restorative treatments.

The dominant foraging guilds (tree foliage insectivore, low understory/ground 

insectivore) within our study stands are similar to those reported by Piper (1996) 

for Douglas-fir forests within the same subbasin. Neotropical birds made up 49.5 

percent of the avian community in our study area. This compares to 33 percent 

in mature Douglas-fir forests and 45 percent in young Douglas-fir forests of the 

southern Washington Cascade Range (Manuwal 1991), and 70 percent in the oak 

Detection rates for 

mountain chickadees 

and red-breasted 

nuthatches were at 

least three times that 

of hairy woodpecker 

rates.

Neotropical birds made 

up 49.5 percent of the 

avian community in our 

study area.
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RESEARCH PAPER PNW-RP-577

woodlands of south-central Washington (Manuwal 2003). Forest stands in our study 

provide important habitat for a number of Neotropical bird species.

We limited our discussion about individual species to those either identified as 

a USFS Pacific Northwest Region (Region 6) focal species (USDA FS 2006) or a 

focal species in the east-slope Cascade Mountains conservation strategy (Altman 

2000). The chipping sparrow was identified as a focal species for ponderosa pine 

forests in the east-slope Cascade Mountains conservation strategy (Altman 2000). 

Their populations have been reported as declining in the Cascade Mountains 

physiographic province (Sauer et al. 1999). They nest in open woodlands with a 

relatively open overstory (10 to 30 percent canopy closure) (Altman 2000, Baicich 

and Harrison 1997). The densities of chipping sparrow in our pretreatment stands 

ranged from 0.3 to 1.83 birds/ha, which are similar to those reported for the control 

stands and much lower than densities in the treated stands described in Gaines et al. 

(2007). The control stands in Gaines et al. (2007) were similar in stand structure to 

the pretreatment stands in this study. Based on the findings of Gaines et al. (2007), 

we suspect that restorative treatments will result in a positive numerical response 

for chipping sparrow.

Hermit thrush is a focal species in the east-slope Cascade Mountains conservation strategy for multilayered, structurally diverse mixed-conifer forests (Altman 

2000). We did not detect the hermit thrush in sufficient numbers to estimate 

pretreatment densities. Putnam (1983) found significantly fewer hermit thrush in 

precommercially thinned stands compared to unthinned stands of ponderosa pine. 

Their abundance was positively correlated with foliage volume of shrubs and small 

trees indicating a preference for areas with a dense understory (Putnam 1983). 

Gaines et al. (2007) did not detect any hermit thrush in stands that were the most 

heavily thinned. These results indicate that the hermit thrush is likely to respond 

negatively to the Fire and Fire Surrogate treatments being implemented in this 

study. 

The MacGillivray’s warbler was selected as a Region 6 focal species for riparian forests (USDA FS 2006). Monitoring of this species on the Wenatchee National 

Forest has shown a significant decline over a period of 10 years, 1992-2001 (Nott 

et al. 2005). We did not detect the MacGillivray’s warbler in sufficient numbers 

to estimate pretreatment densities. The abundance of MacGillivray’s warbler was 

lower in stands treated with thinning and prescribed fire described in Gaines et 

al. (2007). Lehmkuhl et al. (2007) found MacGillivray’s warbler to be four times 

as abundant in dry forest riparian habitats compared to dry forest upland habitats. 

Thus, although dry forest restoration treatments may reduce the abundance of 
127

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

MacGillivray’s warbler in dry forest upland habitats, riparian protections provided 

by the Northwest Forest Plan are likely important to the viability of this species. 

Other studies have reported either a positive numerical response or no response 

for western tanager to prescribed fire and light overstory removal silvicultural treatments (Anderson and Crompton 2002, Bock and Bock 1983, Finch et al. 1997, Hejl 

et al. 1995). However, Gaines et al. (2007) found lower densities in stands that were 

treated with thinning and prescribed fire. In northeastern Oregon (Sallabanks et al. 

2002) and west-central Idaho (Medin 1985), western tanager was associated with 

high canopy closures, perhaps explaining their response to the treatments described 

in Gaines et al. (2007). The densities that we found in pretreatment stands in this 

study ranged from 0.56 to 0.9 birds/ha, similar to those reported for control stands 

in Gaines et al. (2007) but higher than densities found in treated stands (0.31 to 0.32 

birds/ha). We anticipate a negative posttreatment response for western tanager.

Reported responses of red-breasted nuthatches to prescribed fire (Finch et al. 

1997, Horton and Mannan 1988) and light overstory-removal silvicultural treatments (Anderson and Crompton 2002, Finch et al. 1997) have been mixed. Gaines 

et al. (2007) reported reduced densities for the red-breasted nuthatch in stands 

treated with restorative treatments. We found densities in our pretreatment stands 

that ranged from 0.5 to 1.37 birds/ha, somewhat higher that those reported for 

control stands (0.67 birds/ha), and much higher than densities in treated stands 

(0.19 to 0.32 birds/ha) in Gaines et al. (2007). The red-breasted nuthatch has been 

associated with high canopy closure in northeast Oregon (Mannan and Meslow 

1984, Sallabanks et al. 2002) and in west-central Idaho (Medin 1985). We predict a 

negative numerical response to the treatments in our study.

Pygmy nuthatch was selected as a focal species in the land-bird conservation 

strategy for the east slope of the Cascade Mountains owing to their association with 

large ponderosa pine (Pinus ponderosa Dougl. ex Laws.) trees (Altman 2000). We 

could not estimate densities for this species because of low pretreatment sample 

sizes. A decline in source habitat for the pygmy nuthatch was reported by Wisdom 

et al. (2000). We detected pygmy nuthatches in low numbers, similar to those 

reported in Gaines et al. (2007). It is unknown if we’ll be able to evaluate any posttreatment effects because of small samples sizes.

The white-headed woodpecker is a focal species for ponderosa pine forests in 

the east-slope Cascade Mountains conservation strategy (Altman 2000) and for 

Region 6 (USDA FS 2006). Broad-scale habitat declines have been reported for this 

species, especially in the North Cascades (Wisdom et al. 2000). Several researchers 

have suggested that active management, such as Fire and Fire Surrogate treatments, 

be used to restore habitat for this species (Gaines 2000, Marshall 1997, Wisdom et 
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RESEARCH PAPER PNW-RP-577

al. 2000). Although we did detect white-headed woodpeckers in our pretreatment 

study stands, they were low in abundance (0.01 to 0.03)—much lower than the 

abundance (0.09) reported in Gaines et al. (2007) for the low-retention thinning/

prescribed fire restoration treatment. We anticipate a favorable response by whiteheaded woodpeckers to our restorative treatments.

The brown creeper is a focal species for large trees in mixed-conifer forests 

in the east Cascade Mountains land-bird conservation strategy (Altman 2000). 

Declines in both numbers (Sauer et al. 1999) and available habitat (Wisdom et al. 

2000) have been reported for the brown creeper. Brown creeper is associated with 

old forests having high structural complexity (Anthony et al. 1996, Carey et al. 

1991, Lundquist and Mariani 1991). Heavy thinning has been documented to reduce 

the abundance of brown creepers (Weikel 1997). We only detected the brown 

creeper in relatively low abundance, making it uncertain if we can measure any 

treatment response for this species.

The western bluebird is a Region 6 focal species for open dry forests (USDA 

FS 2006). Recent declines have been noted for the western bluebird in many parts 

of its range (Ehrlich et al. 1988), and Wisdom et al. (2000) reported strong declines 

in source habitat in the North Cascades. Fire exclusion leading to a decrease in 

open forest habitat has been cited as one reason for this decline (Guinan et al. 2000, 

Wisdom et al. 2000). Germaine and Germaine (2002) studied the effects of ponderosa pine forest restoration treatments on the nesting success of western bluebirds 

in Arizona and found a higher probability of successfully fledging young, but a 

greater risk of parasitic infections that reduced postfledgling success. Wightman 

and Germaine (2006) reported habitat variables associated with higher nest success 

included increased herbaceous and bare ground cover, and reduced ponderosa pine 

densities. Gaines et al. (2007) reported a positive numerical response in the abundance of western bluebirds to restorative treatments, as western bluebirds were only 

detected in stands that were treated with thinning and prescribed fire. We predict a 

similar response in our study, as no western bluebirds were detected during pretreatment sampling.

The Cassin’s finch was identified as a focal species in Region 6 of the Forest 

Service (USDA FS 2006). Sallabanks et al. (2002) reported that Cassin’s finch was 

a generalist and showed no strong associations with any forest structural class in 

the Blue Mountains of Oregon. Mannan and Meslow (1984) suggested that managed forest may provide more openings that can be used for foraging and nesting by 

Cassin’s finch. Gaines et al. (2007) found higher densities of Cassin’s finch in stands 

treated by thinning/prescribed fire. We expect similar responses to our Fire and Fire 

Surrogate treatments.
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Nest Productivity and Substrate

We consistently found that cavity-nesters were more successful in completing nesting attempts compared to ground- or foliage-nesters. This result was also reported 

by Zebehazy et al. (2004) at another Fire and Fire Surrogate study site in South 

Carolina. In addition, survival estimates for dark-eyed junco, a ground-nester, were 

much lower than the survival estimates of the red-breasted nuthatch. This information exemplifies the advantages of a cavity in providing extra protection for young 

birds resulting in increased survival.

Based on the low pretreatment sample sizes for nesting birds, it is unlikely that 

we will be able to analyze for treatment effects on nest survival of any individual 

species. Such analyses could be done at a broader spatial scale using information 

from the FFS network. For example, Farris et al. (in press) used data from nine 

network sites to analyze for treatment effects of nest survival. They found that 

ground-nesters experienced an increase in daily nest survival in FFS treatments, 

shrub-nesters had lower nest survival in treatments, and snag and tree-nesters 

showed no response to treatments. The results were highly variable among study 

sites (Farris et al., in press). Other studies of the effects of silvicultural treatments 

on nest survival have shown that although the treatments may enhance habitat, they 

can also predispose nests to higher levels of nest predation (Martin 1992, 1993) or 

increase the risk of parasitic infections (Germaine and Germaine 2002). However, 

our study is not designed to specifically determine the causes of nest failure.

Many studies have reported the importance of large-diameter trees as nesting habitat for cavity nesters (Adams and Morrison 1993, Bevis and Martin 2002, 

Bunnell et al. 2002a, Dickson et al. 2004, Lundquist 1988, Lundquist and Manuwal 

1990, Thomas et al. 1979, Weikel and Hayes 1999). Our findings concur, as cavitynesters used trees that were much larger than available. In addition, we found the 

same importance of large trees as nesting substrate for foliage nesters.

Cavity-Nester Foraging Behavior and Habitat

Hairy woodpeckers, mountain chickadees, and red-breasted nuthatches foraged on 

large trees and snags in dry conifer forests within the Mission Creek Watershed. 

In our study, most of the trees available for foraging were alive, and use of snags 

differed among bird species. Although they foraged primarily on live trees, hairy 

woodpeckers selected for snags relative to snag availability. Hessburg et al. (this 

volume) found similar levels of woodpecker foraging activity among study stands. 

Bent (1939) found hairy woodpeckers prefer to forage on snags, where they excavate and probe bark to obtain insects. This behavior was also observed in woodpeckers in the Blue Mountains (Thomas et al. 1979), the coastal range of Oregon 

Cavity-nesters used 

trees that were much 

larger than available. In 

addition, we found the 

same importance of 

large trees as nesting 

substrate for foliage 

nesters.

Hairy woodpeckers, 

mountain chickadees, 

and red-breasted 

nuthatches foraged on 

large trees and snags 

in dry conifer forests 

within the Mission 

Creek Watershed. 
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RESEARCH PAPER PNW-RP-577

(Weikel and Hayes 1999), and southern Washington (Lundquist 1988, Lundquist 

and Manuwal 1990). However, hairy woodpeckers in our study area and other 

regions (Conner 1980, Imbeau and Desrochers 2002) do not strictly limit foraging 

to snags and often foraged on live trees. The density of snag habitat did not differ 

among study stands; however, basal area was higher in the thin-only stands compared to the thin-burn (Harrod et al. this volume)

Snags were not a preferred foraging substrate for chickadees and nuthatches. 

In general, tree status was not an important variable in these models. The diet 

of nuthatches and chickadees consists of both seeds and insects that they forage 

from foliage and the bark surface (Ghalambor and Martin 1999, Lundquist 1988, 

McCallum et al. 1999). We observed these behaviors primarily on live trees. 

Similarly, Lundquist and Manuwal (1990) found chickadees preferred live trees 

and nuthatches did not exhibit selection. Mannan and Meslow (1984) found 

nuthatches foraging on snags infrequently in Oregon. Woodpeckers, nuthatches, 

and chickadees all forage primarily on arthropods (Ghalambor and Martin 1999, 

Jackson et al. 2002, McCallum et al. 1999), and were most likely keying into the 

distribution and abundance of their prey, not necessarily the substrate. Analysis of 

the bark condition of foraged trees indicated most trees and snags had a great deal 

of intact bark such as found on condition class 1 and 2 snags (Parks et al. 1997). 

Generally, more than 90 percent of the bark was intact on live trees, and most 

snags had more than 75 percent intact bark. Hessburg et al. (this volume) found 

that about 15 percent of the trees sampled in the study stands had evidence of bark 

beetles. The primary species were western (Dendroctonus valens) and mountain 

(D. brevicomis) pine beetles. This information may also help explain why hairy 

woodpeckers frequently foraged on live trees. Imbeau and Desrochers (2002) found 

three-toed woodpeckers (Picoides tridactylus) foraging on large snags that were 

less deteriorated than the average available and on large live trees that were more 

deteriorated than available. In Arizona (Dickson et al. 2004), hairy woodpeckers 

and other bark-gleaning species were observed on more vigorous trees. Farris et al. 

(2002) found that woodpeckers concentrate their foraging on younger snags. 

Tree size, particularly diameter, appeared to be an influential aspect of habitat 

selection. All three bird species selected for larger diameter trees. The importance 

of diameter in habitat selection of cavity-nesting birds is well documented (Adams 

and Morrison 1993, Bevis and Martin 2002, Bunnell et al. 2002a, Dickson et 

al. 2004, Lundquist 1988, Lundquist and Manuwal 1990, Thomas et al. 1979, 

Weikel and Hayes 1999). Cavity-nesting birds, especially woodpeckers, need 

large-diameter trees for nesting, to have cavities capable of housing large birds 

(Thomas et al. 1979). Foraging tree diameters are not directly dependent on bird 
131

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

size, but again appear to be related to prey. In the spring, cavity-nesters are busily 

foraging for themselves and their young. To maximize foraging efficiency, birds 

will forage where they are most likely to find large quantities of prey (Krebs 1994). 

Nuthatches and chickadees are considered “major predators of forest insect pests 

in the Pacific Northwest” (Torgersen et al. 1990: 19). In spring, a large prey base is 

readily available (Adams and Morrison 1993, Lundquist and Manuwal 1990), and 

arthropod abundance and distribution is influenced by bark characteristics (Adams 

and Morrison 1993). Older trees usually have a greater diameter, which provides for 

greater surface area, deeper furrows in the bark, and greater likelihood of decay, 

all of which increase the likelihood of being inhabited by insects and exploited by 

birds (Adams and Morrison 1993, Bull et al. 1997).

The relative importance of diameter and height as predictor variables was 

calculated as the sum of wi in all models where the variables were present (Burnham and Anderson 2002). The sum of wi

 for models containing dbh and ht was at 

least 0.98 for all model sets, indicating these were very important covariates when 

predicting foraging selection of cavity-nesting birds. However, tree height was not 

a consistent factor. Although inclusion of the diameter × height interaction term 

improved the model, there was likely greater variability in tree height than can be 

explained by these models. Several studies found tree height was not a consistent 

factor in habitat selection (Bunnell et al. 2002b, Conner 1980, Jackson et al. 2002). 

Bevis and Martin (2002), however, did find that birds selected for taller snags. A 

great amount of literature exists to describe the importance of tree diameter in 

predicting foraging selection (Dickson et al. 2004, Weikel and Hayes 1999), nesting 

selection (Bull et al. 1997, Thomas et al. 1979, Welsh and Capen 1992) and bird 

abundance (Morrison et al. 1987), whereas height does not appear to have as great 

an influence and can differ greatly (Conner 1980, Jackson et al. 2002). With regard 

to foraging, this may be because tree diameter has a greater effect than height on 

the immediate foraging surface area, thereby increasing foraging efficiency. More 

than half of the foraging observations were detected in the upper parts of the tree, 

where the diameter is actually smaller and the bark is smoother. The discrepancy 

increased for mountain chickadees and red-breasted nuthatches. Woodpeckers, nuthatches, and chickadees use different strategies for catching their prey (i.e., excavating vs. gleaning) (Ghalambor and Martin 1999, Jackson et al. 2002, McCallum et 

al. 1999) so foraging here might be explained by two possibilities. First, nuthatches 

and chickadees may have been foraging on insects or seeds in the foliage (Weikel 

and Hayes 1999). Or secondly, these two species are not as well equipped as woodpeckers to forage in deep bark furrows (Ghalambor and Martin 1999, Jackson et al. 

Older trees usually 

have a greater diameter, 

which provides for 

greater surface area, 

deeper furrows in 

the bark, and greater 

likelihood of decay, 

all of which increase 

the likelihood of being 

inhabited by insects 

and exploited by birds.
132

RESEARCH PAPER PNW-RP-577

2002, McCallum et al. 1999), so they may have been trying to forage in the more 

accessible bark, higher up on the tree bole and on branches.

Management for cavity-nesting birds is usually based on managing for 

nesting habitat through protection of snags. Although focusing on snags may be 

beneficial to some species, our information suggested that large live trees also 

provide important foraging habitat in dry forest types for cavity-nesting birds 

such as woodpeckers, chickadees, and nuthatches. Several studies concur that 

nesting cavities are not a limiting factor when adequate numbers of snags are 

available (Waters et al. 1990, Welsh and Capen 1992). However, in managed stands, 

snag abundance is often below optimal nesting levels (Ohmann et al. 1994, Thomas 

et al. 1979). Additionally, birds need far more foraging sites than nesting sites 

(Bunnell et al. 2002b); thus management should include adequate foraging habitat 

as well as nesting habitat.

Management Implications

There are three findings from our pretreatment analyses that are worthy of discussion in terms of management implications. First, we found that large trees were 

important for both nesting and foraging habitats. For nesting, this included both 

cavity-nesters and foliage-nesters. Second, management of nesting habitat for 

cavity-nesters is typically focused on providing adequate snag habitat. Our analyses 

show that although snags are important nesting habitat component, so are large 

live trees, and both components need to be considered in silvicultural treatments. 

Finally, the study design posed limitations for gaining sufficient sample sizes for 

some avian species that allow for the assessment of treatment effects. Examples 

include the relatively few species in which adequate pretreatment samples allowed 

for estimates of density (only 18 percent of those in which abundance indices were 

calculated). Another example includes the inability to calculate survival estimates 

for any species at the stand or treatment level. These limitations may restrict the 

inferences that managers will be able to draw on the effects of dry forest restorative 

treatments on birds, especially on their survival. 

Acknowledgments

We are very grateful to the field personnel who worked in extremely rugged 

terrain, diverse weather conditions, and long hours to gather these data. These 

people included Dorsey Berger, Emily Drew, Keith Kistler, John Merriwether, 

Janet Millard, Danielle Munzing, Susan Piper, Sarah Smith, Robert Strand, Gail 

Roberts, and John Wagenknecht. We thank J. Hallett and T. Max for their reviews 

of the manuscript.

Although snags may 

be beneficial to some 

species, large live 

trees provide important 

foraging habitat, and 

birds need far more 

foraging sites than 

nesting sites.
133

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Literature Cited

Adams, E.M.; Morrison, M.L. 1993. Effects of forest stand structure and 

composition on red-breasted nuthatches and brown creepers. Journal of 

Wildlife Management. 57(3): 616–629.

Agee, J.K. 1993. Fire ecology of Pacific Northwest forests. Washington, DC: 

Island Press. 491 p.

Agee, J.K. 2003. Historical range of variability in eastern Cascade forests, 

Washington, USA. Landscape Ecology. 18: 725–740.

Altman, B. 2000. Conservation strategy for landbirds of the east-slope of the 

Cascade Mountains in Oregon and Washington. Corvallis, OR: American Bird 

Conservancy. 121 p.

Anderson, D.R.; Link, W.A.; Johnson, D.H.; Burnham, K.P. 2001. Suggestions 

for presenting the results of data analyses. Journal of Wildlife Management. 

65(3): 373-378.

Anderson, S.H.; Crompton, B.J. 2002. The effects of shelterwood logging on 

bird community composition in the Black Hills, Wyoming. Forest Science. 

48(2): 365–372.

Anthony, R.L.; Green, G.A.; Forsman, E.D.; Nelson, S.K. 1996. Avian 

abundance in riparian zones of three forest types in the Cascade Mountains, 

Oregon. Wilson Bulletin. 108(2): 280–291.

Baicich, P.J.; Harrison, C.J.O. 1997. A guide to the nests, eggs, and nestlings of 

North American birds. San Diego, CA: Academic Press. 347 p.

Bell, G.W.; Hejl, S.J.; Verner, J. 1990. Proportional use of substrates by foraging 

birds: model considerations on first sightings and subsequent observations. 

Studies in Avian Biology. 13: 161–165.

Bent, A.C. 1939. Life histories of North American woodpeckers. Bulletin 174. 

Washington, DC: U.S. National Museum. 334 p. 

Bevis, K.R.; Martin, S.K. 2002. Habitat preferences of primary cavity excavators 

in Washington’s East Cascades. In: Laudenslayer, W.F., Jr.; Shea, P.J.; Valentine, 

B.E.; Weatherspoon, C.P.; Lisle, T.E., tech. coords. Proceedings of the 

symposium on the ecology and management of dead wood in western forests. 

Gen. Tech. Rep. PSW-GTR-181. Albany, CA: U.S. Department of Agriculture, 

Forest Service, Pacific Southwest Research Station: 207–220.
134

RESEARCH PAPER PNW-RP-577

Biondini, M.E.; Mielke, P.W., Jr.; Berry, K.J. 1988. Data-dependent permutation 

techniques for the analysis of ecological data. Vegetatio. 75: 161–168.

Bock, C.E.; Bock, J.H. 1983. Responses of birds and deer mice to prescribed 

burning in ponderosa pine. Journal of Wildlife Management. 47: 836–840.

Buckland, S.T.; Anderson, D.R.; Burnham, K.P.; Lakke, J.L.; Borchers, D.L.; 

Thomas, L. 2001. Introduction to distance sampling. Estimating abundance of 

biological populations. Oxford, United Kingdom: Oxford University Press. 432 p.

Bull, E.L.; Parks, C.G.; Torgersen, T.R. 1997. Trees and logs important to 

wildlife in the interior Columbia River basin. Gen. Tech. Rep. PNW-GTR-391. 

Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest 

Research Station. 55 p.

Bunnell, F.L.; Houde, I.; Johnston, B.; Wind, E. 2002a. How dead trees 

sustain live organisms in western forests. In: Laudenslayer, W.F., Jr.; Shea, P.J.; 

Valentine, B.E.; Weatherspoon, C.P.; Lisle, T.E., tech. coords. Proceedings of the 

symposium on the ecology and management of dead wood in western forests. 

Gen. Tech. Rep. PSW-GTR-181. Albany, CA: U.S. Department of Agriculture, 

Forest Service, Pacific Southwest Research Station: 291–318. 

Bunnell, F.L.; Wind, E.; Boyland, M.; Houde, I. 2002b. Diameters and heights 

of trees with cavities: their implications to management. In: Laudenslayer, W.F., 

Jr., Shea, P.J.; Valentine, B.E.; Weatherspoon, C.P.; Lisle, T.E., tech. coords. 

Proceedings of the symposium on the ecology and management of dead wood in 

western forests. Gen. Tech. Rep. PSW-GTR-181. Albany, CA: U.S. Department 

of Agriculture, Forest Service, Pacific Southwest Research Station: 717–737.

Burnham, K.P.; Anderson, D.R. 2002. Model selection and multimodel inference: 

a practical information-theoretic approach. 2nd edition. New York: Springer 

Verlag. 488 p.

Camp, A.E.; Hessburg, P.F.; Everett, R.L.; Oliver, C.D. 1997. Predicting latesuccessional fire refugia pre-dating European settlement in the Wenatchee 

Mountains. Forest Ecology and Management. 95: 63–77.

Carey, A.B.; Hardt, M.; Horton, S.P.; Biswell, B.L. 1991. Spring bird 

communities in the Oregon Coast Range. In: Ruggiero, L.F.; Aubry, K.B.; Carey, 

A.B.; Huff, M.H., tech. coords. Wildlife and vegetation of unmanaged Douglasfir forests. Gen. Tech. Rep. GTR-PNW-285. Portland, OR: U.S. Department of 

Agriculture, Forest Service, Pacific Northwest Research Station: 123–137. 
135

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Conner, R.N. 1980. Foraging habitats of woodpeckers in southwestern Virginia. 

Journal of Field Ornithology. 51: 119–127.

Dickson, B.G.; Block, W.M.; Sisk, T.D. 2004. Conceptual framework for studying 

the effects of fuels treatments on avian communities in ponderosa pine forests of 

northern Arizona. 6th Biennial Conference of Research on the Colorado Plateau, 

Flagstaff, AZ. Tucson, AZ: University of Arizona Press. Chapter 17.

Dufrene, M.; Legendre, P. 1997. Species assemblages and indicator species: the 

need for a flexible asymmetrical approach. Ecological Monographs. 67: 345-366.

Ehrlich, P.R.; Dobkin, D.S.; Wheye, D. 1988. The birder’s handbook. New York: 

Simon and Schuster. 785 p.

Everett, R.L.; Schellhaas, R.; Keenum, D.; Spurbeck, D.; Ohlson, P. 2000. 

Fire history in the ponderosa pine/Douglas-fir forests on the east slope of the 

Washington Cascades. Forest Ecology and Management. 129: 207–225.

Farris, K.L.; Converse, S.J.; Zack, S.; Amacher, A.; Contreras, T.; Gaines, W.; 

Greenberg, K.; Lanham, D.; Miles, D.; Robinson, D.; Sieving, K.; Woolf, J. 

[In press]. The effects of fire and fire surrogate treatment on avian nest survival: 

a national perspective. Forest Ecology and Management. (Special Issue).

Farris, K.L.; Garton, E.O.; Heglund, P.J.; Zack, S.; Shea, P.J. 2002. 

Woodpecker foraging and the successional decay of ponderosa pine. In: 

Laudenslayer, W.F., Jr.; Shea, P.J.; Valentine, B.E.; Weatherspoon, C.P.; 

Lisle, T.E., tech. coords. Proceedings of the symposium on the ecology and 

management of dead wood in western forests. Gen. Tech. Rep. PSW-GTR-181. 

Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest 

Research Station: 237–246. 

Finch, D.M.; Ganey, J.L.; Yong, W.; Kimball, R.T.; Sallabanks, R. 1997. Effects 

and interactions of fire, logging and grazing. In: Block, W.M.; Finch, D.M., 

tech. eds. Songbird ecology in southwestern ponderosa pine forests: a literature 

review. Gen. Tech. Rep. RM-GTR-292. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment 

Station: 103–136. 

Gaines, W.L. 2000. Disturbance ecology, land allocations, and wildlife 

management. In: Proceedings of the management of fire maintained ecosystems 

workshop. Vancouver, BC: British Columbia Forest Service: 29–34.
136

RESEARCH PAPER PNW-RP-577

Gaines, W.L.; Haggard, M.; Lehmkuhl, J.L.; Lyons, A.; Harrod, R.J. 2007. 

Short-term response of land birds to ponderosa pine restoration. Restoration 

Ecology. 15: 670–678.

Germaine, H.L.; Germaine, S.S. 2002. Forest restoration treatment effects on 

the nesting success of western bluebirds (Sialia mexicana). Restoration Ecology. 

10(2): 362–367.

Ghalambor, C.K; Martin, T.E. 1999. Red-breasted nuthatch. In: Poole, A.; Gill, 

F., eds. The Birds of North America. No. 459. Philadelphia, PA: The Academy of 

Natural Sciences; Washington, DC: The American Ornithologists’ Union. 28 p.

Greenberg, C.H.; Tomcho A.L.; Lanham J.D.; Waldrop, T.A.; Tomcho, 

J.; Phillips, R.J.; Simon, D. 2007. Short-term effects of fire and other fuel 

reduction treatments on breeding birds in southern Appalachian upland 

hardwood forest. Journal of Wildlife Management. 71: 1906–1916. 

Guinan, J.A.; Gowaty, P.A.; Eltzroth, E.K. 2000. Western bluebird. In: Poole, 

A.; Gill, F., eds. The Birds of North America. No. 510. Philadelphia, PA: The 

Academy of Natural Sciences; Washington, DC: The American Ornithologists’ 

Union. 32 p.

Hanowski, J.; Danz, N.; Lind, J.; Neimi, G. 2003. Breeding bird response to 

riparian forest harvest and harvest equipment. Forest Ecology and Management. 

174: 315–328.

Harrod, R.J.; McRae, B.H.; Hartl, W.E. 1999. Historical stand reconstruction in 

ponderosa pine forests to guide silvicultural prescriptions. Forest Ecology and 

Management. 114: 433–446.

Hejl, S.J.; Hutto, R.L.; Preston, C.R.; Finch, D.M. 1995. Effects of silvicultural 

treatments in the Rocky Mountains. In: Martin, T.E.; Finch, D.M., eds. Ecology 

and management of Neotropical migratory birds. Oxford, United Kingdom: 

Oxford University Press: 220–244.

Hejl, S.J.; Verner, J.; Bell, G.W. 1990. Sequential versus initial observations in 

studies of avian foraging. Studies in Avian Biology. 13: 166–173.

Hensler, G.L.; Nichols, J.D. 1981. The Mayfield method of estimating nesting 

success: a model, estimators and simulation results. Wilson Bulletin. 93: 42–53.

Hessburg, P.F.; Agee, J.K.; Franklin, J.F. 2005. Dry forests and wildland fires 

of the inland Northwest USA: contrasting the landscape ecology of the presettlement and modern eras. Forest Ecology and Management. 211(1–2): 117–139.
137

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Hessburg, P.F.; Salter, R.B.; Jones, K.M. 2007. Re-examining fire severity 

relations in pre-management era mixed conifer forests: inferences from 

landscape patterns of forest structure. Landscape Ecology. 22(1): 5–24.

Hessburg, P.F.; Smith, B.G.; Salter, R.B.; Ottmar, R.D.; Alvarado, E. 2000.

Recent changes (1930s–1990s) in spatial patterns of interior Northwest forests. 

Forest Ecology and Management. 136: 53–83.

Horton, S.P.; Mannan, R.W. 1988. Effects of prescribed fire on snags and 

cavity-nesting birds in southeastern Arizona pine forests. Wildlife Society 

Bulletin. 16: 37–44.

Hurlbert, S.H. 1984. Pseudoreplication and the design of ecological field 

experiments. Ecological Monographs. 54: 187–211.

Hutto, R.L. 1998. Using landbirds as an indicator species group. In: Marzluff, 

J.M.; Sallabanks, R., eds. Avian conservation: research and management. 

Washington, DC: Island Press: 75–92.

Hutto, R.L.; Young, J.S. 2002. Regional landbird monitoring: perspectives from 

the northern Rocky Mountains. Wildlife Society Bulletin. 30(3): 738–750.

Imbeau, L.; Desrochers, A. 2002. Foraging ecology and use of drumming trees 

by three-toed woodpeckers. Journal of Wildlife Management. 66(1): 222–231.

Jackson, J.A.; Ouellet, H.R.; Jackson, B.J.S. 2002. Hairy Woodpecker. In: Poole, 

A.; Gill, F., eds. The Birds of North America. No. 702. Philadelphia, PA: The 

Academy of Natural Sciences; Washington, DC: The American Ornithologists’ 

Union. 32 p. 

Krebs, C.J. 1994. Ecology: The experimental analysis of distribution and 

abundance. 4th ed. Philadelphia, MA: Addison-Wesley Pub. Co. 801 p. 

Lehmkuhl, J.F.; Burger, E.D.; Drew, E.K.; Lindsey, J.P.; Haggard, M.; 

Woodruff, K.Z. 2007. Riparian and upland birds on the east-slope of the 

Cascade Range. Journal of Wildlife Management. 71: 2632–2643.

Lundquist, R.W. 1988. Habitat use by cavity-nesting birds in the southern 

Washington Cascades. Seattle, WA: University of Washington. M.S. thesis.

Lundquist, R.W.; Manuwal, D.A. 1990. Seasonal differences in foraging habitat 

of cavity-nesting birds in the southern Washington Cascades. Studies in Avian 

Biology. 13: 218–225.
138

RESEARCH PAPER PNW-RP-577

Lundquist, R.W.; Mariani, J.M. 1991. Nesting habitat and abundance of snagdependent birds in the southern Washington Cascade Range. In: Ruggiero, L.F.; 

Aubry, K.B.; Carey, A.B.; Huff, M.H., tech. coords. Wildlife and vegetation of 

unmanaged Douglas-fir forests. Gen. Tech. Rep. PNW-GTR-285. Portland, OR: 

U.S. Department of Agriculture, Forest Service, Pacific Northwest Research 

Station: 221–240.

Lyon, L.J.; Huff, M.H.; Smith, J.K. 2000. Fire effects on fauna at landscape 

scales. In: Smith, J.K., ed. Wildland fire in ecosystems: effects of fire on 

fauna. Gen. Tech. Rep. RMRS-GTR-42-vol. 1. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station: 43-50.

Mannan, R.W.; Meslow, E.C. 1984. Bird populations and vegetation 

characteristics in managed and old-growth forests, northeastern Oregon. Journal 

of Wildlife Management. 48(4): 1219–1238.

Manuwal, D.A. 1991. Spring bird communities in the southern Washington 

Cascade Range. In: Ruggiero, L.F.; Aubry, K.B.; Carey, A.B.; Huff, M.H., tech. 

coords. Wildlife and vegetation of unmanaged Douglas-fir forests. Gen. Tech. 

Rep. PNW-GTR-285. Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station: 160–174.

Manuwal, D.A. 2003. Bird communities in oak woodlands of southcentral 

Washington. Northwest Science. 77: 194–201.

Marshall, D.B. 1997. Status of the white-headed woodpecker in Oregon and 

Washington. Portland, OR: Audubon Society. 30 p.

Martin, P.R.; Bateson, P. 1986. Measuring behavior: an introductory guide. 

Cambridge, England: Cambridge University Press. 160 p.

Martin, T.E. 1992. Breeding productivity considerations: What are the appropriate 

habitat features for management? In: Johnston, D.W., ed. Ecology and 

conservation of Neotropical migrants. Washington, DC: Smithsonian Institution 

Press: 455–473.

Martin, T.E. 1993. Nest predation among vegetation layers and habitat types: 

revising the dogmas. American Naturalist. 141: 897–913.

Martin, T.E.; Geupel, G.R. 1993. Nest-monitoring plots: methods for locating 

nests and monitoring success. Journal of Field Ornithology. 64(4): 507–519.

Mayfield, H.F. 1961. Nesting success calculated from exposure. Wilson Bulletin. 

73: 255–261.
139

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Mayfield, H.F. 1975. Suggestions for calculating nesting success. Wilson Bulletin. 

87: 456–466.

McCallum, D.A.; Grundel, R.; Dahlsten, D.L. 1999. Mountain chickadee. In: 

Poole, A.; Gill, F., eds. The Birds of North America. No. 453. Philadelphia, 

PA: The Academy of Natural Sciences; Washington, DC: The American 

Ornithologists’ Union. 28 p.

McCune, B.; Mefford, M.J. 1999. PC-Ord. Multivariate analysis of ecological 

data. Version 4. Gleneden Beach, OR: MjM Software Design. 300 p.

Medin, D.E. 1985. Breeding bird responses to diameter-cut logging in westcentral Idaho. Gen. Tech. Rep. INT-GTR-355. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Intermountain Research Station. 12 p.

Morrison, M.L.; Timossi, I.C.; With, K.A. 1987. Development and testing of 

linear regression models predicting bird-habitat relationships. Journal of Wildlife 

Management. 51(1): 247–253.

Nott, P.M.; DeSante, D.F.; Pyle, P.; Michel, N. 2005. Managing landbird 

populations in forests of the Pacific Northwest: formulating population 

management guidelines from landscape-scale ecological analyses of MAPS data 

from avian communities on seven national forests in the Pacific Northwest. Point 

Reyes Station, CA: The Institute for Bird Populations. 163 p.

Ohmann, J.L.; McComb, W.C.; Zumrawi, A.A. 1994. Snag abundance 

for primary cavity-nesting birds on nonfederal forest lands in Oregon and 

Washington. Wildlife Society Bulletin. 22: 607–620.

Parks, C.G.; Bull, E.L.; Torgersen, T.L. 1997. Field guide for the identification 

of snags and logs in the interior Columbia River basin. Gen. Tech. Rep. PNWGTR-390. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station. 40 p.

Piper, S.D. 1996. Terrestrial amphibian and passerine bird abundance in riparian 

habitats of eastern Washington Cascade forests. Pullman, WA: Washington State 

University. 131 p. M.S. thesis. 

Putnam, B.J. 1983. Songbird populations of precommercially thinned and 

unthinned stands of ponderosa pine in east-central Washington. Corvallis, OR: 

Oregon State University. M.S. thesis.
140

RESEARCH PAPER PNW-RP-577

Ralph, C.J.; Geupel, G.; Pyle, P.; Martin, T.E.; DeSante, D.F. 1993. Handbook 

of field methods for monitoring landbirds. Gen. Tech. Rep. PSW-GTR-144. 

Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest 

Research Station. 41 p.

Sallabanks, R.; Riggs, R.A.; Cobb, L.E. 2002. Bird use of forest structural 

classes in grand fir forests of the Blue Mountains, Oregon. Forest Science. 

48(2): 311–321.

Sauer, J.R.; Hines, J.E.; Thomas, I.; Fallon, J.; Gough, G. 1999. The North 

American breeding bird survey: results and analysis. Version 98.1. Laurel, MD: 

Patuxent Wildlife Research Center.

SPSS, Inc. 2001. SPSS Base Version 10.1.3 for Windows. Chicago, IL.

Thomas, J.W.; Anderson, R.G.; Maser, C.; Bull, E.L. 1979. Snags. In: Thomas, 

J.W., tech. ed. Wildlife habitats in managed forests: the Blue Mountains of 

Oregon and Washington. Agric. Handb. No. 553. Washington, DC: U.S. 

Department of Agriculture, Forest Service: 60–77.

Torgersen, T.R.; Mason, R.R.; Campbell, R.W. 1990. Predation by birds and 

ants on two forest insect pests in the Pacific Northwest. Studies in Avian Biology. 

13: 14–19.

U.S. Department of Agriculture Forest Service [USDA FS]. 2006. Terrestrial 

species assessments: R6 forest plan revisions. Portland, OR: Pacific Northwest 

Region.

Waters, J.R.; Noon, B.R.; Verner, J. 1990. Lack of nest site limitation in a cavitynesting bird community. Journal of Wildlife Management. 54(2): 239–245.

Weikel, J. 1997. Habitat use by cavity-nesting birds in young thinned and 

unthinned Douglas-fir forests of western Oregon. Corvallis, OR: Oregon State 

University. M.S. thesis.

Weikel, J.M.; Hayes, J.P. 1999. The foraging ecology of cavity-nesting birds in 

young forests of the northern coast range of Oregon. The Condor. 101: 58–66.

Welsh, C.J.E.; Capen, D.E. 1992. Availability of nesting sites as a limit to 

woodpecker populations. Forest Ecology and Management. 48: 31–41.

Wightman, C.S.; Germaine, S.S. 2006. Forest stand characteristics altered 

by restoration affect western bluebird habitat quality. Restoration Ecology. 

14: 653–661.
141

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Wisdom, M.J.; Holthausen, R.S.; Wales, B.C.; Hargis, C.D.; Saab, V.A.; Lee, 

D.C.; Hann, W.J.; Rich, T.D.; Rowland, M.M.; Murphy, W.J.; Eames, M.R. 

2000. Source habitats for terrestrial vertebrates of focus in the interior Columbia 

Basin: broad-scale trends and management implications. Gen. Tech. Rep. PNWGTR-485. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station. 156 p.

Zebehazy, L.A.; Lanham, J.D.; Waldrop, T.A. 2004. Seasonal avifauna 

responses to fuel reduction treatments in the upper Piedmont of South Carolina: 

results from phase 1 of the national Fire and Fire Surrogate study. In: Kristina, 

F., ed. Proceedings of the 12th biennial southern silvicultural research conference. 

Gen. Tech. Rep. SRS-71. Asheville, NC: U.S. Department of Agriculture, Forest 

Service, Southern Research Station: 82–86.

Zimmerman, G.; Goetz, H.; Mielke, P. 1985. Use of an improved statistical 

method for group comparisons to study effects of prairie fire. Ecology. 

66: 606–611.
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143

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

John F. Lehmkuhl1

Introduction

The ecology of small mammals in the eastern Cascade Range is interesting and 

important for several reasons. The area is a biogeographic ecotone for species 

typical of wet forests of western Washington, for species of the dry shrub-steppe 

of eastern Washington, and for species with primary distributions in forests of the 

Rocky Mountain region (Johnson and Cassidy 1997) (table 9-1). As such, species 

occurrences and abundances in the eastern Cascade Range vary along temperaturemoisture environmental gradients that affect vegetation pattern in a regional eastwest direction and locally by topography. For example, presence and abundance of 

species typical of wet western Washington forests decline in an easterly direction 

from the Cascade crest as the environment becomes increasingly dryer, but species 

may occur locally at low elevations on cool-moist northerly aspects. The distribution of shrub-steppe species follows an opposite pattern for warm-dry conditions. 

The complexity of the environment and the fact that most species occur at the 

edge of their range, where they may be less adapted than at the core of their ranges 

(Brown and Lomolino 1998), makes predicting species occurrence, abundance, and 

response to management actions difficult. 

Small mammals may be good indicators of ecosystem integrity, or the integrity 

of “biodiversity pathways” of forest development in response to natural or human 

disturbance (Carey and Harrington 2001, Carey and Johnson 1995). Small mammals are a vital prey base for a host of mammalian and avian carnivores. The varied 

life histories of small mammals encompass a wide range of habitat requirements 

for live and dead herbaceous and woody vegetation. Feeding behavior ranges 

from insectivory to granivory to mycophagy, which involves small mammals in 

many ecological webs. Their short lifespan and high productivity suggest they will 

respond quickly to management that impacts the environment of the forest floor. 

In this chapter, I describe patterns of pretreatment occurrence and abundance 

of small mammals in dry ponderosa pine (Pinus ponderosa Dougl. ex Laws) and 

Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) forests at the Mission Creek, 

Washington, site of the Fire and Fire Surrogate (FFS) study (Weatherspoon and 

McIver 2000). Insectivores, mice, voles, chipmunks, and squirrels are the primary 

focus of the small-mammal study. I also compare those results to other studies of 

small mammals in the local area. 

Chapter 9: Small Mammals

1 John F. Lehmkuhl is a research wildlife biologist, U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station, 1133 N Western Ave., Wenatchee, WA 

98801, jlehmkuhl@fs.fed.us.

Small mammals may 

be good indicators of 

ecosystem integrity, 

or the integrity 

of “biodiversity 

pathways” of forest 

development in 

response to natural or 

human disturbance.
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Methods

I used three trapping methods to target small mammals of varied size, natural 

history, and behavior in an efficient and humane (ASM 2007) manner. I strived to 

safely sample relatively large (8+ ha) and remote (up to 1.5 hours walk from a road) 

treatment units, and to replicate sampling designs of other regional small mammal 

studies (Aubry et al. 1991, 1997; Hallett and O’Connell 1997). I sampled terrestrial 

small mammals with pitfall kill traps and snap traps during a 5-week spring period 

to effectively capture different species (McComb et al. 1991) and to minimize the 

exposure of crews to aerosol transmission of endemic hantavirus while handling 

animals. Snap traps also more efficiently captured target rodent species in this area 

than Sherman live traps.2 Kill trapping is controversial (Sullivan et al. 2003), but 

Table 9-1—Small mammal insectivores and rodents expected to occur in upland dry forests 

studied by the Fire and Fire Surrogates study in the northeastern Cascade Range, Washington 

Habitat Distributiona

Speciesb Forest Shrub-steppe West East

Trowbridge’s shrew (Sorex trowbridgii) x x

Coast mole (Scapanus orarius) x x

American shrew-mole (Neurotrichus gibbsii) x x

Douglas’s squirrel (Tamiasciurus douglasii) x x

Keen’s mouse (Peromyscus keeni) x x

Creeping vole (Microtus oregoni) x x

Townsend’s chipmunk (Neotamias townsendii) x x

Cascade ground squirrel (Spermophilus saturatus) x x

Yellow-pine chipmunk (Neotamias amoenus) x x

Western gray squirrel (Sciurus griseus) x x

Masked shrew (Sorex cinereus) x x x

Montane shrew (Sorex monticolus) x x x

Northern flying squirrel (Glaucomys sabrinus) x x x

Southern red-backed vole (Clerthrionomys gapperi) x x x

Long-tailed vole (Microtus longicaudus) x x x

Northern pocket gopher (Thomomys talpoides) x x

Great Basin pocket mouse (Perognathus parvus) x x

Montane vole (Microtus montanus) x x

Vagrant shrew (Sorex vagrans) x x x x

Deer mouse (Peromyscus maniculatus) x x x x

Bushy-tailed woodrat (Neotoma cinerea) x x x x

Note: Species are sorted by habitat, distribution, and taxonomic order. a Primary species distribution in Washington state relative to the crest of the Cascade Range. West indicates a range 

primarily in western Washington; east indicates a range primarily in eastern Washington.

b Taxonomy according to Baker et al. (2003).

Source: Johnson and Cassidy 1997.

2 West, S.D. 2000. Personal communication. Professor wildlife science, College of Forest 

Resources, Box 352100, University of Washington, Seattle WA 98195.
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

our methods were humane (ASM 2007), effective, and efficient. Moreover, more 

reliable data are collected by kill trapping than live trapping. Necropsy of collected 

animals allowed species that are difficult to identify in the field (e.g., shrews, voles, 

two potential species of deer mice) to be positively identified, and reproductive 

condition and age to be determined with greater certainty than with live trapping. I 

sampled squirrels and chipmunks with Tomahawk live traps using guidelines recommended by Carey et al. (1991) and used in other regional (Carey 1995, Lehmkuhl 

et al. 1999) and local (Lehmkuhl et al. 2006b) studies of arboreal rodents. 

I sampled on a single 6 by 6 grid with 40-m spacing within each experimental 

unit, per the national FFS small mammal protocol (Weatherspoon and McIver 

2000). I built pitfall traps from two large (No. 2) coffee cans taped together with 

duct tape, buried traps to the lip of the can, and inserted a plastic margarine container with the bottom cut out to prevent animals from getting out. Each trap was 

filled with about 10 cm of water to operate them as humane kill (drowning) traps. 

When possible, I placed pitfall traps alongside logs or other natural runways of 

small mammals or at the base of a tree as close to the grid point as possible, but 

not more than 5 m away. I placed two Tomahawk live traps at each of the 36 grid 

points. One trap was placed on the ground and the other on a tree bole 1.5 m above 

the ground. In addition to the FFS protocol, I placed Museum Special snap traps on 

a 6 by 11 grid (20-m spacing on rows and 40-m spacing on columns) inset into the 

basic 6 by 6, 40-m grid. 

I sampled units over a 5-week period from mid-May through June 2000 in 

two groups of six experimental units. I operated Tomahawk and snap traps for 8 

days over a 12-day period, which conformed to a recommended trapping period 

for arboreal rodents (Carey et al. 1991, 1995; Lehmkuhl et al. 2006b). Traps were 

set on Monday, checked and closed on Friday, then reopened Monday for another 

four trap-nights. I concurrently operated pitfall traps in each stand for 11 continuous days. Analysis of data from another local study (Gaines and Lehmkuhl 2007) 

indicated that the combined pitfall and snap trap effort over 11 days likely would be 

adequate to sample most species known to occur in the area. 

Abundance for each species is reported as individuals captured per 100 trapnights, after adjusting trap-nights for sprung, stuck, or missing snap or Tomahawk 

traps (Nelson and Clark 1973). I assumed that capture probabilities for species 

were similar among stands owing to similar overstory, understory, and forest floor 

conditions (Harrod et al., this volume), and proximity of stands (15 km maximum); 

thus, I assumed heterogeneity in capture probabilities for individual species would 

be small to negligible. Weather during the relatively short 6-week spring period 

was consistently favorable, so time effects would be negligible. These assumptions 

Sampling was on a 

6 by 6 grid with 40-m 

spacing within each 

unit.
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RESEARCH PAPER PNW-RP-577

were necessary because removal estimates of abundance that could correct for 

potential differences in capture probability were not feasible to estimate. Many 

species were absent or captured in small numbers in individual stands: only deer 

mice (Peromyscus maniculatus) and yellow-pine chipmunk (Neotamias amoenus) 

were captured in all sites and in numbers that might allow removal estimates of 

abundance. Nomenclature follows Baker et al. (2003). 

I characterized mammal assemblages within and among units in three ways 

using algorithms in PCORD software (McCune and Mefford 1999). I used a 

frequency-abundance curve to show dominance relationships among species 

(McCune and Grace 2002). I used TWINSPAN cluster analysis (Gauch 1982) to 

examine how stands differ in mammal assemblages and to characterize those 

assemblages. The use of TWINSPAN was justified by a hypothetical single 

environmental gradient (temperature-moisture) represented by the sample stands 

(McCune and Grace 2002). Pseudospecies cut levels (recoding of a single species’ 

data into several separate “pseudospecies” abundance categories for analysis) for 

TWINSPAN were: 1 = 0 < × ≤2 captures/100 trap-nights; 2 = 2 < × ≤ 5 captures; 

and, 3 = 5 < × ≤10 captures. I did not consider grouping continuous capture data 

for TWINSPAN a disadvantage, vs. using original data with other clustering 

techniques (McCune and Grace 2002), because of the inherent variability in a 

sample of 12 experimental units and relatively few captures of many uncommon 

species. Finally, I used multiresponse permutation procedures (MRPP) to test 

the hypothesis of no difference in small mammal assemblages among assigned 

treatment groups of stands (Biondini et al. 1988, Zimmerman et al. 1985). The 

MRPP method estimates an A statistic that measures the distinctiveness of groups 

on a scale of ~0 to 1. Values of A >0.3 are considered fairly high for ecological 

studies. Monte Carlo permutations calculated the probability of observed vs. 

expected differences among assigned treatment groups. Assigned treatment groups 

were control (Crow 3, Sand 19, Sand 2), thin-only (Crow 1, Ruby, Slawson), burnonly (Pendleton, Poison Spromberg,), and thin-burn (Crow 6, Camas, Tripp).

Results 

I collected 413 animals of 12 species (table 9-2) in pitfall and snap traps over 10,800 

trap-nights, with an average of 3.8 animals captured per 100 trap-nights. Deer mice 

and yellow-pine chipmunks were commonly found in all units. Deer mice, however, 

dominated the small mammal community (fig. 9-1) accounting for 52 percent of the 

catch and more than twice the captures of yellow-pine chipmunks (21 percent of 

catch). These two species were co-dominant, however, if dominance was assessed 

in terms of species’ biomasses (deer mice = 797 g/100 trap-nights; yellow-pine 

Sampling captured 413 

animals of 12 species—

an average 3.8 animals 

per 100 trap-nights. 

Deer mice and yellowpine chipmunks were 

commonly found in 

all units.
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Table 9-2—Captures per 100 trap-nights of small mammals in pitfall and snap traps during June 2000 on the 

Mission Creek sites of the Fire and Fire Surrogates study, Washington

Unita SOMOb SOTR SOVA NEGI NEAM NETO THTA PEPA PEMA CLGA MILO MIOR Total

Camas 0.3 0.3 1.3 0.2 0.3 7.1 0.2 0.3 9.7

Crow 1 0.2 0.6 0.3 1.3 2.3

Crow 3 2.4 0.6 1.4 0.3 1.7 6.3

Crow 6 3.2 0.6 1.3 5.0

Pendleton 4.2 1.2 5.3

Poison 0.8 1.9 0.3 2.7 0.2 4.3

Ruby 0.4 3.7 1.9 0.2 0.2 6.9 0.2 12.6

Sand 19 0.3 3.5 0.8 4.6 9.8

Sand 2 0.4 0.3 0.8 1.4

Slawson 0.6 1.1 0.8 0.6 1.7 0.6 5.8 0.3 1.8 12.8

Spromberg 2.9 0.3 0.8 9.4 0.2 13.6

Tripp 0.4 0.2 0.4 0.3 0.7 3.7 0.5 6.1

 Total 1.2 11.4 2.0 1.8 18.6 0.4 1.5 2.5 45.8 0.2 0.3 3.9 88.7

 Total (%) 1.3 12.9 2.2 2.0 21.0 0.5 1.7 2.8 51.6 0.2 0.3 4.4

 Units (%) 25 58 42 25 100 17 42 42 100 8 8 50

a Survey mean 900 trap nights per stand.

b SOMO, Montane shrew (Sorex monticolus); SOTR, Trowbridge’s shrew (S. trowbridgii); SOVA, vagrant shrew (S. vagrans); NEGI, 

American shrew-mole (Neurotrichus gibbsii); NEAM, yellow-pine chipmunk (Neotamias amoenus); NETO, Townsend’s chipmunk (N. 

townsendii); THTA, Northern pocket gopher (Thomomys talpoides); PEPA, Great Basin pocket mouse (Perognathus parvus); PEMA, 

deer mouse (Peromyscus maniculatus); CLGA, southern red-backed vole (Clethrionomys gapperi); MILO, long-tailed vole (Microtus 

longicaudus); MIOR, creeping vole (M. oregoni).

Figure 9-1—Dominance curve of small mammals captured during June 2000 with pitfall and snap 

traps in 12 units of the Mission Creek study site of the Fire and Fire Surrogate study. See Table 9-2 

for explanation of species labels. 
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RESEARCH PAPER PNW-RP-577

chipmunk = 807 g/100 trap-nights). Trowbridge’s shrew (Sorex trowbridgii) was the 

third most abundant (13 percent of catch) and frequently caught (58 percent of units) 

species. The other nine species were a collection of rodents and insectivores that 

individually accounted for <5 percent of the total catch, and were captured in ≤50 

percent of the units. Captures of northern pocket gophers (Thomomys talpoides) 

should be considered incidental because pitfall and snap traps poorly sample this 

fossorial species. 

Pitfall and snap traps differed in effectiveness of capturing some species. 

Both trap types were equally efficient in capturing the dominant deer mice, which 

accounted for about 50 percent of the catch with both trap types (table 9-3). Relatively more insectivores were caught in pitfall traps. Captures of Trowbridge’s 

shrew, in particular, were four times as many with pitfall as with snap traps. In 

contrast, the percentage of yellow-pine chipmunk captures with snap traps was 

six times that of captures with pitfall traps. 

Table 9-3—A comparison of total captures/100 trap nights and 

percentage total catch of small mammals in pitfall and snap traps on the 

12 Mission Creek sites of the Fire and Fire Surrogates study, Washington

Pitfall traps Snap traps

Species Captures Percent Captures Percent

Montane shrew 0.8 2.3 0.4 0.7

Trowbridge’s shrew 7.8 24.2 3.6 6.4

Vagrant shrew 1.8 5.5 0.2 0.4

American shrew-mole 0 0 1.8 3.2

Yellow-pine chipmunk 1.5 4.7 17.1 30.3

Townsend’s chipmunk 0 0 0.4 0.7

Northern pocket gopher 1.5 4.7 0 0

Great Basin pocket mouse 2.3 7.0 0.2 0.4

Deer mouse 14.9 46.1 30.9 54.8

Southern red-backed vole 0 0 0.2 0.4

Long-tailed vole 0.3 0.8 0 0

Creeping vole 1.5 4.7 1.6 2.8

 Total 32.3 100.0 56.3 100.0
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Table 9-4—Captures per 100 trap-nights of small mammals in Tomahawk live 

traps during June 2000 on the Mission Creek sites of the Fire and Fire Surrogates 

study, Washington

Speciesa LEAMb SPSA GLSA NEAM NETO NECI Total

Camas 0.2 0.4 0.5 1.2 5.5

Crow 1 0.2 0.4 3.2

Crow 3 0.4 0.7 3.2

Crow 6 0.9 2.6

Pendleton 2.5 8.0

Poison 0.2 0.5 4.1

Ruby 0.7 0.5 0.2 6.0

Sand 19 0.4 2.5 6.9

Sand 2 0.2 2.5

Slawson 0.7 3.3

Spromberg 0.2 0.5 0.7 0.2 5.3

Tripp 0.2 0.7

 Total 1.2 0.5 1.9 10.8 0.2 0.2 51.2

a Survey mean 568 trap-nights per stand. 

b LEAM, snowshoe hare (Lepus americana); SPSA, Cascade golden-mantled ground squirrel 

(Spermophilus saturatus); GLSA, northern flying squirrel (Glacomys sabrinus); NEAM, yellow-pine 

chipmunk (Neotamias amoenus); NETO, Townsend’s chipmunk (N. townsendii); NECI, bushy-tailed 

woodrat (Neotoma cinerea).

Yellow-pine chipmunks dominated the catch from Tomahawk live traps (10.8 

captures/100 trap-nights) (table 9-4). There were few captures of five other species, 

including northern flying squirrels (Glaucomys sabrinus) and bushy-tailed woodrats (Neotoma cinerea), which were of particular interest. Snowshoe hares (Lepus 

americana) captured were juveniles, and should be considered incidental because 

the Tomahawk traps were too small to properly sample adults.

Mammal assemblages differed among units, but two primary assemblages were 

apparent (table 9-5). Half the units, which were relatively mesic habitats, supported 

a richer assemblage of small mammals that included all the captured species in at 

least one unit of the group, compared to the other relatively species-poor dry units. 

Voles and insectivores, except for vagrant shrews (Sorex vagrans) were found 

mostly in the mesic units. Deer mice were found in all units, but were most abundant and dominated the catch in mesic units. In contrast, yellow-pine chipmunks 

likewise were caught in all units, but were more abundant in the dry units. The 

Great Basin pocket mouse (Perognathus parvus) was a third species associated 

with open patches in dry units. Mammal assemblages were similar among the 

assigned treatment groups of stands (MRPP A = -0.111, P = 0.899). 

Units in relatively 

mesic habitats 

supported a richer 

assemblage of small 

mammals compared 

to dry units.
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RESEARCH PAPER PNW-RP-577

Discussion

Most (15 of 21) of the expected suite of species (table 9-1) were trapped in the FFS 

experimental units. Most of the expected species that were not collected in the 

FFS units, however, were trapped in low numbers by other nearby studies (table 

9-6). The western gray squirrel (Sciurus griseus) has a very localized distribution 

north of the study area (Johnson and Cassidy 1997) and has not been detected in 

any dry forest studies near the FFS site. Small mammal assemblages caught in pitfall traps in the FFS study units were mostly similar in composition and richness 

to those captured in nearby dry forest areas, but the dominance of deer mice and 

Trowbridge’s shrew differed among studies (table 9-6). Species similarly captured 

by autumn pitfall trapping for 28 days on 6 by 6 grids with 40-m spacing in the 

Peavine Canyon area just south of the FFS sites were similar to the FFS units, but 

deer mice dominated the Peavine catch with 72 percent of the captures (Gaines 

and Lehmkuhl 2007) vs. 46 percent in FFS units. 

Table 9-5—TWINSPAN clustering of stands and species based on captures/100 trap-nights in pitfall 

and snap traps in the Mission Creek site of the Fire and Fire Surrogates Study, Washington

Mesic standsa Dry stands

SpeciesCamasRubySprombergSlawsonPoisonTrippCrow 1Crow 3Crow 6PendletonSand 19Sand 2

Species group

Southern red-backed vole 1

b 000c

Long-tailed vole 1 000

Montane shrew 1 1 1 001

Townsend’s chipmunk 1 1 001

Creeping vole 1 1 1 1 1 1 001

American shrew-mole 1 1 1 001

Deer mouse 3 3 3 3 2 2 1 1 1 1 2 1 01

Trowbridge’s shrew 1 2 2 1 1 1 2 01

Northern pocket gopher 1 1 1 1 1 01

Great Basin pocket mouse 1 1 1 1 1 1

Vagrant shrew 1 1 1 1 1 1

Yellow-pine chipmunk 1 1 1 1 1 1 1 1 2 2 2 1 1

First-level stand groupsd 0 0 0 0 0 0 1 1 1 1 1 1

Second-level stand groupsd 0 0 0 0 1 1 0 0 1 1 1 1

a Stand type corresponds to first-level grouping at bottom of table.

b

 Captures/100 trap-nights recoded as pseudospecies with analysis categories (cut levels) of 1 = 0 < × ≤2 captures; 

2 = 2 < × ≤ 5; 3 = 5 < × ≤10.

c Sequence of 0 and 1 (in rightmost column) indicates membership in one of four species groups (indicated by a unique 

0,1 sequence) typically found in similar environmental (stand) conditions.

d The sequence of 0,1 (in bottom rows) indicates membership in a stand group with similar species composition.
151

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Table 9-6—Percentage composition of small mammals captured only with pitfall traps at the Mission Creek 

site of the Fire and Fire Surrogates (FFS) study compared to pitfall captures in nearby dry-forest areas from 

other studies

FFS Mission Creek Other studies

Dry stands Mesic stands Peavinea	 Devil’s Gulchb	 Teanawayb

Species n = 6 n = 6 Total n = 12 n = 8 n = 8

Masked shrew 3 1

Montane shrew 3 2 3 3 7

Trowbridge’s shrew 21 26 24 3 78 58

Vagrant shrew 8 4 5 5 2 2

American shrew-mole 3

Yellow-pine chipmunk 5 4 5 6

Northern pocket gopher 3 6 5 2 1

Great Basin pocket mouse 18 2 7 1

Keen’s mouse 13

Deer mouse 45 47 46 72 13 2

Southern red-backed vole 1 12

Long-tailed vole 1 1 5 2

Montane vole 2

Creeping vole 7 5 3 2

 Total 100 100 100 100 100 100

a Gaines and Lehmkuhl 2007. Peavine Canyon is in the Mission Creek drainage, and stands were similar to and immediately south 

of the FFS stands. 

b Peffer 2001. Devil’s Gulch sites were in the Mission Creek drainage and similar to FFS sites. Teanaway River sites were about 25 km 

east of Mission Creek and somewhat more mesic than Mission Creek sites. Data are from captures at distances >60 m from streams.

Peffer (2001) captured similar upland species in late spring on the two upland 

hillside (>60 m from a stream) rows of eight 5 by 6 pitfall grids (15-m spacing) 

sampled over 2 weeks in the nearby Devil’s Gulch Fork of Mission Creek. In 

contrast to the FFS and Peavine sites, Trowbridge’s shrew strongly dominated 

Peffer’s catch with 78 percent of the captures, and deer mice were only 13 percent 

of captures. Slightly more mesic dry forest stands sampled by Peffer in the 

Teanaway River drainage, about 25 km west of Mission Creek, also were dominated 

by Trowbridge’s shrew (58 percent of captures), but less so than the dryer sites 

in Devil’s Gulch. The southern red-backed vole (Clethrionomys gapperi), Keen’s 

mouse (Peromyscus keeni), and montane shrew (Sorex monticolus) were more 

abundant in the Teanaway than in the dryer FFS, Devil’s Gulch, or Peavine stands 

(tables 9-5, 9-6). 

As at the FFS site, uncommon species individually represented ≤5 percent 

of the captures at both the Peavine and Devil’s Gulch sites. Some other species 

captured in those sites, but not in the FFS site, add to the list of dry forest 

small mammals. Masked shrews (Sorex cinereus) and montane voles (Microtus 

montanus) were captured in small numbers at the Peavine or Teanaway sites. 
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RESEARCH PAPER PNW-RP-577

Peffer (2001) caught a few species in riparian areas that were not caught in the FFS 

or Peavine upland forest stands: water shrews (Sorex palustris) (2.7 percent of 

catch), Keen’s mouse (2.3 percent), and western jumping mice (Zapus princeps) (0.9 

percent). Peffer also had incidental captures of marsh shrews (Sorex bendirii) 

and coast moles (Scapanus orarius) in riparian or upland areas. 

The dominance differences among Trowbridge’s shrew and deer mice among 

studies is puzzling. The FFS, Peavine, and Peffer studies sampled in different 

years and seasons (spring 2000, fall 1996, spring 1997–98, respectively), so annual 

or seasonal differences in weather could have influenced the relative numbers of 

species. The strong dominance of Trowbridge’s shrew in Peffer’s study possibly 

could have been an artifact of differences in sampling design. Peffer’s pitfall grid 

had 15-m spacing, whereas pitfall traps were spaced at 40-m intervals in the FFS 

and Peavine studies. 

Trap type also influenced conclusions about terrestrial small mammal assemblages. Pitfall traps poorly sampled yellow-pine chipmunks, which both snap traps 

and Tomahawk live traps showed to be a dominant species in dry forest stands. 

Other than yellow-pine chipmunks, unexpectedly few arboreal or semiarboreal 

rodents were captured. Lehmkuhl et al. (2006b) captured an average of 2.6 northern flying squirrels/100 trap-nights (range 1.9 to 3.0 across open- to closed-forest 

gradient) in similar dry forest in the Swauk Creek drainage 16 km southeast of the 

FFS sites, whereas, an average 0.32 squirrels/100 trap-nights were caught in FFS 

units. Lehmkuhl et al. (2006a) also captured bushy-tailed woodrats in all Swauk 

Creek study stands at an average rate of 0.5 woodrats/100 trap-nights (range 0.2 to 

0.8 across years). In the FFS stands, woodrats were captured in only one unit at a 

capture rate of 0.2 woodrats/100 trap-nights. 

The low numbers of arboreal rodents captured in FFS units compared to 

Swauk Creek could have resulted from differences in methods, season of capture, 

or inherent differences in stands. The 6 by 6 grid that barely fit in the relatively 

small FFS units was smaller than the 8 by 8 grid used in the Swauk study, which 

was the minimum size recommended by Carey (1991). An abundance of truffle and 

herbaceous food during the spring FFS trapping season compared to the autumn 

Swauk trapping season could have contributed to fewer captures.3 The FFS stands 

may have been trapped during a low in populations, but winter weather prior to 

trapping was close to average, or at least not severe enough to reduce rodent numbers as observed by Lehmkuhl et al. (2006b). Finally, differences in the amount of 

3 Carey, A.B. 1996. Personal communication. Chief research wildlife biologist (retired). 

U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 3625 

93rd Ave. SW, Olympia WA 98512.
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Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

cover habitat (snags, logs, mistletoe for both species) and food (truffles and lichens 

for flying squirrels) associated with both species (Lehmkuhl et al. 2006b) may have 

been lacking. 

A final issue about comparing results among studies is the use of potentially 

biased capture indices instead of true abundance estimated by mark-recapture or 

removal modeling of capture probabilities. The use of captures/100 trap-nights as 

an index of abundance to compare stands or sites assumes that capture probabilities 

are equal across time and space within studies and across studies, which is considered an unlikely assumption (Williams et al. 2002). Nevertheless, there is some 

evidence that capture indices may be biased high or low, but can be highly correlated with mark-recapture abundance and useful for comparison of sites (Hopkins 

and Kennedy 2004, Lehmkuhl et al. 2006b, Ramsey et al. 2005, Ruscoe et al. 2001)

Despite the uncertainty of relative dominance among species from available 

studies, it is clear that Trowbridge’s shrew dominates the insectivore group, deer 

mice dominate the small rodents, and yellow-pine chipmunks dominate among 

arboreal and semi-arboreal rodents. That general pattern and the contribution of 

other species to the small mammal community will depend on the geographical 

and landscape location of the stand. 

The known distribution of species along the regional west-east temperaturemoisture gradient (Johnson and Cassidy 1997) also was observed at smaller 

landscape scales. Species typical of mesic closed forests west of the Cascade crest 

(e.g., Trowbridge’s shrew, creeping vole [Microtus oregoni]), or forest species with 

a wide distribution across Washington (e.g., southern red-backed vole) were more 

abundant closer to the crest (e.g., Keen’s mouse in the Teanaway drainage). Those 

species also were locally more abundant in mesic than dry stands in the same 

landscape (this study, Peavine). Eastern forest species (e.g., yellow-pine chipmunk), 

shrub-steppe species (e.g., Great Basin pocket mouse [Perognathus parvus], 

northern pocket gopher [Thomomys talpoides]), or open forest generalists (e.g., 

deer mouse) were found in stands at the dry end of the gradient because of easterly 

longitude or topographic location. 

Microhabitat patterns of understory vegetation, down wood, and climate in 

FFS units are the likely proximate basis for the observed mesic and dry forest small 

mammal assemblages (table 9-5). Dry units identified as having similar mammal 

assemblages are about 100 m lower in elevation, on warmer aspects, and have 

slightly lower tree density than mesic units (Harrod et al., this volume). Understory 

conditions in the FFS stands are most strongly differentiated by grass cover 

(Harrod et al., this volume), which in dry stands is three times that in mesic stands. 

Shrub cover in mesic units is 60 percent greater than in dry units, and is a primary 

Trowbridge’s shrew 

dominates the 

insectivore group, 

deer mice dominate 

the small rodents, and 

yellow-pine chipmunks 

dominate among 

arboreal and semiarboreal rodents. 
154

RESEARCH PAPER PNW-RP-577

driver of differences in understory among mesic stands. Mesic units also have 

larger amounts of small and large down wood than dry stands (Agee and Lolley, 

this volume), which adds to the structural complexity of small mammal cover and 

food resources. Biomass of fine woody debris (<0.62-cm diameter, 1-hour fuels) 

and large (>7.6-cm diameter, 1,000+ hour fuels) rotten down wood, which is cover 

and a potential source of invertebrate food, in mesic stands is 2 to 2.5 times that in 

dry units. Management practices that affect the temperature-moisture conditions 

by opening and drying a stand, reducing large down wood, and shifting understory 

dominance to grass will shift mammal species assemblages to favor species 

associated with the dry end of the gradient. 

Acknowledgments

Trapping and handling of animals was done under permit from the Washington 

Department of Fish and Wildlife. A. Conway and A. Lyons were critical crew 

members who organized and conducted field or laboratory work. R. Harrod and 

W. Gaines, Okanogan-Wenatchee National Forest, played pivotal roles in establishing and implementing the study, as well as conducting their own research within 

the study. 

Literature Cited

American Society of Mammalogists [ASM]. 2007. Guidelines for the 

capture, handling, and care of animals as approved by the American 

Society of Mammalogists. American Society of Mammalogists. http://www.

mammalsociety.org/committees/commanimalcareuse/98acucguidelines.pdf. 

(1 February 2007).

Aubry, K.B.; Crites, M.J.; West, S.D. 1991. Regional patterns of small mammal 

abundance and community composition in Oregon and Washington. In: 

Ruggierro, L.F.; Aubry, K.B.; Carey, A.B.; Huff, M.H., tech. cords. Wildlife and 

vegetation of unmanaged Douglas-fir forests. Gen. Tech. Rep. PNW-GTR-285. 

Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest 

Research Station: 285–294. 

Aubry, K.B.; West, S.D.; Manuwal, D.A.; Stringer, A.; Erickson, J.L.; 

Pearson, S. 1997. Wildlife use of managed forests: a landscape perspective. 

Volume 2, West-side studies research results. Publication TFW-WL4-98-002. 

Olympia, WA: Washington Department of Natural Resources, http://www.stage.

dnr.wa.gov/forestpractices/adaptivemanagement/cmer/publications/TFW_WL4_

98_002.pdf. (3 February 2007).

Management practices 

that affect the 

temperature-moisture 

conditions by opening 

and drying a stand, 

reducing large down 

wood, and shifting 

understory dominance 

to grass will shift 

mammal species 

assemblages to favor 

species associated 

with the dry end of 

the gradient. 
155

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Baker, R.; Bradley, L.; Bradley, R.; Dragoo, J.; Engstrom, M.; Hoffmann, 

R.; Jones, C.; Reid, F.; Rice, D.; Jones, C. 2003. Revised checklist of North 

American mammals north of Mexico, 2003. Occasional Paper No. 229. Lubbock, 

TX: Museum of Texas Tech University. 23 p.

Biondini, M.E.; Mielke, P.W., Jr.; Berry, K.J. 1988. Data-dependent permutation 

techniques for the analysis of ecological data. Vegetation. 75: 161–168.

Brown, J.; Lomolino, M. 1998. Biogeography. Sunderland, MA: Sinauer 

Associates. 691 p.

Carey, A.B. 1991. The biology of arboreal rodents in Douglas-fir forests. Gen. 

Tech. Rep. PNW-276. Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station. 46 p.

Carey, A.B. 1995. Sciurids in Pacific Northwest managed and old-growth forests. 

Ecological Applications. 5: 648–661.

Carey, A.B.; Biswell, B.L.; Witt, J.W. 1991. Methods for measuring populations 

of arboreal rodents. Gen. Tech. Rep. PNW-273. Portland, OR: U.S. Department 

of Agriculture, Forest Service, Pacific Northwest Research Station. 24 p.

Carey, A.B.; Harrington, C.A. 2001. Small mammals in young forests: 

implications for management for sustainability. Forest Ecology and 

Management. 154: 289–309.

Carey, A.B.; Johnson, M.L. 1995. Small mammals in managed, naturally young, 

and old-growth forests. Ecological Applications. 5: 336–352.

Gaines, W.L.; Lehmkuhl, J.F. 2007. Unpublished data from the Pendleton Canyon 

fuel reduction study. On file with: USDA Forest Service, Pacific Northwest 

Research Station, 1133 N Western Ave., Wenatchee, WA 98801.

Gauch, H., Jr. 1982. Multivariate analysis in community ecology. Cambridge, 

United Kingdom: Cambridge University Press. 298 p.

Hallett, J.; O’Connell, M. 1997. Wildlife use of managed forests: a landscape 

perspective. Volume 3, East-side studies research results. Publication TFW-WL4-

98-003. Olympia, WA: Washington Department of Natural Resources. http://

www.stage.dnr.wa.gov/forestpractices/adaptivemanagement/cmer/publications/

TFW_WL4_98_003.pdf. (4 February 2007).

Hopkins, H.L.; Kennedy, M.L. 2004. An assessment of indices of relative and 

absolute abundance for monitoring populations of small mammals. Wildlife 

Society Bulletin. 32: 1289–1296.
156

RESEARCH PAPER PNW-RP-577

Johnson, R.; Cassidy, K. 1997. Terrestrial mammals of Washington state: 

location data and predicted distributions. In: Cassidy, K.; Grue, C.; Smith, M.; 

Dvornich,K., eds. Washington State Gap Analysis final report, volume 3. Seattle, 

WA: Cooperative Fish and Wildlife Research Unit, University of Washington. 

304 p.

Lehmkuhl, J.F.; Kistler, K.D.; Begley, J.S. 2006a. Bushy-tailed woodrat 

abundance in dry forests of eastern Washington. Journal of Mammalogy. 

87: 371–379.

Lehmkuhl, J.F.; Kistler, K.D.; Begley, J.S.; Boulanger, J. 2006b. Demography 

of northern flying squirrels informs ecosystem management of western interior 

forests. Ecological Applications. 16: 584–600.

Lehmkuhl, J.F.; West, S.D.; Chambers, C.L.; McComb, W.C.; Manuwal, D.A.; 

Aubry, K.B.; Erickson, J.L.; Gitzen, R.A.; Leu, M. 1999. An experiment 

for assessing vertebrate response to varying levels and patterns of green-tree 

retention. Northwest Science. 73: 45–63.

McComb, W.C.; Anthony, R.G.; McGarigal, K. 1991. Differential vulnerability 

of small mammals and amphibians to two trap types and two trap baits in Pacific 

Northwest USA forests. Northwest Science. 65: 109–115.

McCune, B.; Grace, J.B. 2002. Analysis of ecological communities. Gleneden 

Beach, OR: MjM Software Design. 300 p.

McCune, B.; Mefford, M.J. 1999. PC-Ord. Multivariate analysis of ecological 

data. Version 4. Gleneden Beach, OR: MjM Software Design.

Nelson, L., Jr.; Clark, F. 1973. Correction for sprung traps in catch/effort 

calculations of trapping results. Journal of Mammalogy. 54: 295–298.

Peffer, R.D. 2001. Small mammal habitat selection in east slope Cascade Mountain 

riparian and upland habitats. Cheney, WA: Eastern Washington University. 42 p.

M.S. thesis. 

Ramsey, D.; Efford, M.; Ball, S.; Nugent, G. 2005. The evaluation of indices 

of animal abundance using spatial simulation of animal trapping. Wildlife 

Research. 32: 229–237.

Ruscoe, W.A.; Goldsmith, R.; Choquenot, D. 2001. A comparison of population 

estimates and abundance indices for house mice inhabiting beech forests in New 

Zealand. Wildlife Research. 28: 173–178.
157

Dry Forests of the Northeastern Cascades Fire and Fire Surrogate Project Site, Mission Creek, Okanogan-Wenatchee NF

Sullivan, T.P.; Sullivan, D.S.; Ransome, D.B.; Lindgren, P.M.F. 2003. Impact 

of removal-trapping on abundance and diversity attributes in small-mammal 

communities. Wildlife Society Bulletin. 31: 464–474.

Weatherspoon, P.; McIver, J. 2000. A national study of the consequences of fire 

and fire surrogate treatments. http://frames.nbii.gov/ffs. (3 March 2007).

Williams, B.; Nichols, J.; Conroy, M. 2002. Analysis and management of animal 

populations. San Diego, CA: Academic Press. 817 p.

Zimmerman, G.; Goetz, H.; Mielke, P. 1985. Use of an improved statistical 

method for group comparisons to study effects of prairie fire. Ecology. 

66: 606–611.
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Acknowledgments

This is Contribution Number 149 of the National Fire and Fire Surrogate Project 

(FFS), funded by the U.S. Joint Fire Science Program. Additional funding came 

from the PNW Research Station’s National Fire Plan research project on “Fuel 

reduction and forest restoration strategies that also sustain key habitats, species, and 

ecological processes in fire-prone ecosystems in the interior Northwest” (01.PNW.

C.2). Okanogan-Wenatchee National Forest Supervisors Sonny O’Neal and James 

Boynton fostered the science and management collaboration that made this project 

possible. Leavenworth District Rangers Becki Heath and Glen Hoffmann likewise 

made the project possible by encouraging their staff to learn by adaptive management and by providing the administrative and technical support to do the burning 

and thinning treatments. 

English Equivalents

When you know:	 Multiply by:	 To find:

Microns (μ) 0.000394 Inches

Millimeters 0.0394 Inches

Centimeters (cm) 0.394 Inches

Meters (m) 1.094 Yards

Kilometers (km) 0.621 Miles

Hectares (ha) 2.47 Acres

Square centimeters (cm2) 0.155 Square inches 

Square meters (m2) 10.76 Square feet

Square kilometers (km2) 0.386 Square miles

Cubic centimeters (cm3) 0.061 Cubic inches

Liter (l) 1.057 Quart

Grams (g) 0.036 Ounces

Grams 0.0022 Pounds

Kilograms (kg) 2.205 Pounds

Grams per cubic centimeter (g/cm3) 0.036 Pounds per cubic inch

Kilogram per cubic meter (kg/m3) 1.686 Pounds per cubic yard

Megagrams per cubic centimeter (Mg/cm3) 180.6 Tons per cubic inch

Kilograms per hectare (kg/ha) 0.893 Pounds per acre

Megagrams per hectare (Mg/ha) 0.446 Tons per acre

Square meters per hectare (m2/ha) 4.37 Square feet per acre

Trees per hectare 0.405 Trees per acre

Board feet (bf) 7 Cubic meters (m3

)

Degrees Celsius (C) 1.8 °C + 32 Degrees Fahrenheit
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