United States Department of Agriculture

DEPAR TMENT OF AGRICULT URE

Forest 

Service

Pacific Northwest 

Research Station

General Technical Report

PNW-GTR-948

October

2016

Tree Voles: an Evaluation of 

Their Distribution and Habitat 

Relationships Based on Recent 

and Historical Studies, Habitat 

Models, and Vegetation Change 

Eric D. Forsman, James K. Swingle, Raymond J. Davis, Brian L. Biswell, 

and Lawrence S. Andrews
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Authors

Eric D. Forsman is a research wildlife biologist (emeritus) and James K. Swingle 

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

Northwest Research Station, 3200 SW Jefferson Way, Corvallis, OR 97331; Raymond J. Davis is the monitoring leader for old forests and northern spotted owls 

for the Northwest Forest Plan Interagency Monitoring Program, U.S. Department 

of Agriculture, Forest Service, Pacific Northwest Region, 3200 SW Jefferson Way, 

Corvallis, OR 97331; Brian L. Biswell is a wildlife biologist (retired), U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 3695 

93rd Ave SW, Olympia, WA 98512; Lawrence S. Andrews is a wildlife biologist, 

Department of Fisheries and Wildlife, Oregon State University, Corvallis, OR 97331.

Cover photos: (Upper left) A red tree vole nest under construction. The nest, 

constructed of resin ducts, debarked twigs, and Douglas-fir cuttings, was built at 

the junction of three tops in a 35-year-old Douglas-fir tree. Photo by Jim Swingle. 

(Lower left) An adult captive red tree vole mechanically removing one of two 

unpalatable resin ducts in a Douglas-fir needle before eating the rest of the needle. 

Photo by Michael Durham. (Right) Eric Forsman examining a red tree vole nest in a 

dwarf mistletoe broom in the top of a western hemlock tree. Photo by Jim Swingle.
Abstract

Forsman, Eric D.; Swingle, James K.; Davis, Raymond J.; Biswell, Brian L.; 

Andrews, Lawrence S. 2016. Tree voles: an evaluation of their distribution and 

habitat relationships based on recent and historical studies, habitat models, and 

vegetation change. Gen. Tech. Rep. PNW-GTR-948. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 119 p.

We describe the historical and current distribution of tree voles (Arborimus longicaudus; A. pomo) and compare the minimum density of trees with tree vole nests in 

different forest age-classes based on museum records, field notes of previous collectors, tree vole nest surveys conducted by federal agencies, and our field studies 

in Oregon and California. We conclude that tree voles are still fairly common in old 

forests within much of their historical range, but have become uncommon or rare 

in some areas as a result of fire and logging. Our analysis of food stored at red tree 

vole (A. longicaudus) nests in Oregon indicated that the vast majority of tree voles 

feed almost exclusively on needles of Douglas-fir (Pseudotsuga menziesii). However, tree voles in the Sitka spruce zone of northwestern Oregon feed primarily on 

western hemlock (Tsuga heterophylla) and Sitka spruce (Picea sitchensis). Historical field notes from the California coastal region also documented occasional voles 

that feed on grand fir (Abies grandis), Monterey pine (Pinus radiata), or Bishop 

pine (P. muricata). We used the program MaxEnt to develop predictive models 

of tree vole presence based on an a priori set of habitat, structure, and climate 

variables. Based on a comparison of potential vole habitat in historical and recent 

vegetation maps, we estimated that the geographic distribution of red tree voles in 

Oregon contracted by 23 percent in the period 1914–2013.

Keywords: Arboreal mammals, Arborimus longicaudus, A. pomo, Arvicolinae, 

California, forest management, Oregon, Northwest Forest Plan, red tree vole, 

Sonoma tree vole. 
Contents

1 Chapter 1: Distribution and Habitat of Tree Voles 

Based on Historical and Recent Studies

1 Introduction

2 Study Area

4 Methods

5 Data From Owl Pellets

6 Museum Specimens and Archived Field Notes

6 Pre-Project and Strategic Surveys

8 Random Plot Study

9 Retrospective and Targeted Surveys

10 California Department of Fish and Game Database

11 Elevation and Tree Voles

11 Results 

11 Oregon Pellet Data

13 California Pellet Data

15 Museum Specimens

21 Pre-Project Surveys and Strategic Surveys

25 Random Plot Study

28 Retrospective and Targeted Surveys

34 California Department of Fish and Game Database 

36 Elevation Limits

36 Discussion

36 Historical and Current Distribution

42 Habitat Relationships

45 Elevation Limits 

46 Sex Ratios

46 Population Density and Regulation

47 Management Implications

49 Chapter 2: Diet 

49 Introduction

49 Methods

49 Results

50 Discussion

53 Management Implications
iii

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

55 Chapter 3: Current Status of Potential Red Tree Vole Habitat 

Based on Species Distribution Models

55 Introduction

55 Methods

55 Vegetation Data

58 Abiotic Data

59 Data on Presence of Red Tree Voles

61 Habitat Modeling Regions

62 Habitat Modeling and Model Evaluation

64 Habitat Map Development 

66 Using Owl Pellet Data to Evaluate Habitat Maps

66 Results

72 Discussion

74 Management Implications

77 Chapter 4: Long-Term Trends in Habitat and Geographic Distribution of 

Tree Voles in Oregon, 1914−2006

77 Introduction

77 Methods

80 Results

80 Change in Potential Habitat

82 Estimated Effect on the Geographic Distribution of Tree Voles

84 Discussion

85 Management Implications

86 Summary

88 Acknowledgments

90 Tree Species Mentioned in This Report

91 English Equivalents

91 References

105 Appendix 1

106 Appendix 2

107 Appendix 3

108 Appendix 4
iv

GENERAL TECHNICAL REPORT PNW-GTR-948
1

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

Chapter 1: Distribution and Habitat of Tree Voles 

Based on Historical and Recent Studies

Introduction

Because they are the only truly arboreal Arvicoline mammals in the world and 

are among the few mammals that feed primarily on needles and twigs of conifers, 

red tree voles (Arborimus longicaudus) and Sonoma tree voles (A. pomo) have long 

intrigued collectors and naturalists (Clifton 1960, Maser et al. 1981, Taylor 1915, 

Todd 1891, Walker 1928). The two species of tree voles are ecologically similar but 

geographically isolated (Murray 1995, Smith et al. 2003). Red tree voles occur in 

western Oregon and northwestern California, north of the Klamath River. Sonoma 

tree voles occur in coastal California from the Klamath River south to southern 

Sonoma County (Bellinger et al. 2005, Blois and Arbogast 2006, Murray 1995). 

Tree voles are a challenge to study because they spend most of their time in the 

forest canopy and are difficult to capture using conventional methods (Forsman et 

al. 2009b, Swingle 2005, Swingle et al. 2004). Until fairly recently, tree voles were 

somewhat of an enigma; they were studied by a few mammalogists but otherwise 

were largely ignored by forest managers and land management agencies (Todd 1891, 

True 1890, Verts and Carraway 1998). This began to change after the adoption of 

the Northwest Forest Plan in 1994 because, for the first time, federal land management agencies were required to search for and manage red tree voles and many 

other little-known species that were native to old forests in Washington, Oregon, 

and northwestern California (USDA and USDI 1994). The reason for this change 

was simple—forest managers, scientists, and the lay public were becoming more 

aware of the many unique inhabitants of the old forests of the Pacific Northwest, 

and were increasingly concerned that some of those species could be harmed if 

measures were not taken to protect them from habitat loss resulting from timber 

harvest, wildfire, and changes in land use. This increased awareness, coupled with 

a series of court cases that compelled federal management agencies to respond to 

concerns about unique native species, led the USDA Forest Service (Forest Service) 

and USDI Bureau of Land Management (BLM) to adopt new monitoring and 

research programs in the 1990s to better understand the distribution and abundance 

of little-known species that were thought to be dependent on old forests. The result 

was an explosion of information regarding many species, including tree voles. Some 

of this information has been published (e.g., Bellinger et al. 2005; Dunk and Hawley 

2009; Forsman et al. 2004, 2009a, 2009b; Kelsey et al. 2009; Swingle and Forsman 

2009; Swingle et al. 2010), but most of the new empirical information on distribution and habitat of tree voles remains unpublished. 

Until fairly recently, 

tree voles were 

somewhat of an 

enigma; they were 

studied by a few 

mammalogists but 

otherwise were largely 

ignored by forest 

managers and land 

management agencies.
2

GENERAL TECHNICAL REPORT PNW-GTR-948

Our goal in this report is to summarize the historical and recent information 

on distribution and habitat of tree voles, and to provide managers with a new 

tool for assessing potential tree vole habitat. In chapter 1, we use historical and 

recent data to describe the current geographic distribution of tree voles. We also 

describe regional variation in habitat of tree voles, and compare the minimum 

density of trees with vole nests in different forest age-classes. In chapter 2, we 

describe regional variation in diets of red tree voles. In chapter 3, we describe an 

analysis based on maximum-entropy methods in which we used data on climate, 

forest structure, and forest tree species composition to predict the current distribution of potential red tree vole habitat in Oregon and northwestern California. In 

chapter 4, we examine changes that have occurred in the amount and distribution 

of potential tree vole habitat in western Oregon based on a comparison of forest 

cover maps generated in 1914 and 1936, and our modeled estimates of potential 

vole habitat in 2006. We believe this information will provide forest managers 

and policy makers with a better background and understanding of the distribution 

of tree voles and the kinds of habitat in which they occur, and will allow managers to better predict the consequences of various kinds of management on tree 

vole populations.

Study Area

Our study area included western Oregon and coastal northwestern California, 

from the Columbia River south to San Francisco Bay (fig. 1-1). With the exception 

of the Willamette Valley in Oregon and a few other interior valleys, this region 

is characterized by mountainous terrain and vegetation dominated by coniferous 

forests. Climate within the study area is characterized by warm, dry summers and 

cool, wet winters. Precipitation is highly variable depending on latitude and proximity to the ocean, ranging from very wet areas along the coast, to comparatively 

dry areas in the interior valleys of southwest Oregon. In areas below 800 m, most 

precipitation occurs as rain during the fall, winter, and early spring (October to 

April). At higher elevations in the Cascade Mountains, precipitation includes a mix 

of rain and snow, and the ground is often covered by snow for much of the winter 

(November to March). 

In Oregon, species composition of forests differs among regions, with Douglasfir1

 and western hemlock predominating in northwestern Oregon and mixed conifer 

or mixed evergreen forests predominating in southwestern Oregon (Franklin and 

1 See “Tree Species Mentioned in This Report” on page 90 for scientific names and authorities.
3

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

#*

#*

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YAMHILL

MARIN

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Point Reyes

Cape Arago

Cascade Head

Cape Lookout

Cape Meares

Cape Falcon

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Southwest

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WASHINGTON

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ett e malli W

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Figure 1-1—Geographic subregions and major geographic features used in analyses of the distribution and relative abundance of red tree 

voles and Sonoma tree voles in western Oregon and northwestern California. Study area is indicated by gray boxes in insert.
4

GENERAL TECHNICAL REPORT PNW-GTR-948

Dyrness 1973). A narrow belt of Sitka spruce and western hemlock is present along 

the coast. Mixed conifer and mixed evergreen forests typically include a diverse 

mix of species, including Douglas-fir, grand fir, western white pine, incense-cedar, 

Pacific madrone, California laurel, and tanoak. In California, forests are dominated 

by Douglas-fir or mixed-species stands of Douglas-fir, coast redwood and tanoak 

in the northern coastal region and by mixed-species stands of Douglas-fir, bishop 

pine, and grand fir in the coastal region between Fort Bragg and Bodega. Lumber 

production is a major industry throughout the study area, and landscapes typically 

include heterogeneous mixtures of forest age-classes that are the result of timber 

harvesting and fire. Private and state lands typically are dominated by young forests 

growing on harvested areas, whereas federal lands typically include a mixture of 

young forests growing on harvested areas and old forests growing on areas that 

have never been harvested. 

Methods

Data sources used to document the range and habitat of tree voles included 

specimens collected from 1886 to 2013, tree vole specimens identified in 

pellets of northern spotted owls (Strix occidentalis caurina) and barred owls 

(S. varia), and field surveys of tree voles and their nests that we and many 

others conducted on federal, state, and private lands in Oregon and California 

from 1990 to 2013. We also examined field notes of previous researchers and 

resurveyed many historical collection locations to try to determine if tree 

voles were still present at or near those locations (app. 1). In California, we 

used a database compiled by Gordon Gould at the California Department of 

Fish and Game that included records of tree voles or tree vole nests located in 

California from 1984 to 2000 (Gould 2005). Data from these different sources 

differed in quality, but always consisted of unequivocal evidence of the presence of tree voles, whether in the form of museum specimens, skulls, or nests 

documented by tree climbers. We considered either specimens or nests as 

evidence of presence, because nests of tree voles rarely persist for more than 

a few years after they are last occupied and are easily identified based on the 

presence of tree vole fecal pellets, debarked twigs, and resin ducts from conifer needles (Maser 1966, Thompson and Diller 2002). Tree voles are the only 

animals that remove resin ducts from conifer needles, so any nest containing 

resin ducts can safely be classified as a tree vole nest. Methods associated with 

each of the above sources of data are described below. All means are reported 

as  ̄x ± 1 standard error (SE).

We considered either 

specimens or nests as 

evidence of presence, 

because nests of tree 

voles rarely persist 

for more than a few 

years after they are last 

occupied and are easily 

identified based on the 

presence of tree vole 

fecal pellets, debarked 

twigs, and resin ducts 

from conifer needles.

Tree voles are the only 

animals that remove 

resin ducts from conifer 

needles, so any nest 

containing resin ducts 

can safely be classified 

as a tree vole nest.
5

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

Data From Owl Pellets

Based on the percentage of occurrence of tree voles in the diets of northern spotted 

owls, Forsman et al. (2004) estimated the distribution of red tree voles in western 

Oregon and compared the relative abundance of red tree voles in owl diets in different subregions of the state. We reanalyzed the same data examined by Forsman et 

al. (2004), with the addition of 13,571 prey items and 268 owl territories that were 

not available when Forsman et al. (2004) conducted their analysis. The number 

of spotted owl territories in our sample was 1,386, and the number of prey items 

examined was 38,068, of which 3,991 were tree voles. Methods for this part of our 

study were as described in Forsman et al. (2004), but in short, were as follows: 

• Regurgitated pellets were collected below northern spotted owl roosts and 

dissected in the laboratory. 

• Individual prey items in pellets were identified to the lowest possible phylogenetic group, including 78 percent to species, 14 percent to genus, 4 percent to family, and 4 percent to order or class. 

• Composition of the diet at each owl territory was calculated based on the percentage of numbers of each prey species in the total sample from the territory. 

We used the percentage of red tree voles in the diet at each territory as an index 

of red tree vole abundance in different geographic subregions (fig. 1-1) of Oregon. 

Obviously, owls do not sample prey in an unbiased way, and false negatives (no 

detections when the species is actually present) are possible with small samples of 

prey items. However, we reasoned that with the large number of owl territories in 

our sample, patterns in abundance of red tree voles in different geographic subregions should become apparent in spite of potential biases due to prey selection or 

small sample size.

We also obtained data on prey remains in pellets of spotted owls or barred owls 

from four areas in California, including samples from:

• 245 spotted owl territories on lands owned by the Green Diamond Resource 

Company in Del Norte, Humboldt, and Trinity Counties (Diller 2013).

• 79 spotted owl territories from the Northwestern California Study Area in 

Siskiyou, Trinity, Humboldt, and Mendocino Counties (Franklin 2015).

• 9 spotted owl and 2 barred owl territories in Redwood National and State 

Parks in Del Norte and Humboldt Counties (Schmidt 2013).

• 13 spotted owl territories in Point Reyes National Seashore in Marin 

County (Fehring 2013), and a sample from one spotted owl territory on private land near Bodega in Sonoma County (Moore 2013).

Of 38,068 prey items 

identified in pellets 

of spotted owls in 

Oregon, 3,991 were 

red tree voles.
6

GENERAL TECHNICAL REPORT PNW-GTR-948

Museum Specimens and Archived Field Notes

From 2004 to 2011, we searched museum catalogs and archived field notes and 

found 1,658 records of tree voles in museums, including 1,453 specimens and 

205 visual observations of tree voles or their nests that were documented in field 

notes but not supported by specimens (apps. 2 and 3). Based on these sources, we 

compiled a database of all historical records of tree voles collected or observed in 

Oregon and California, including some specimens that had been lost or destroyed 

(app. 3). We visited 25 of the 35 museums that had tree voles in their collections 

and physically examined 1,426 (98 percent) of specimens in museums (app. 2). We 

also read and transcribed the archived field notes of Murray Johnson, Chris Maser, 

William Hamilton III, Don Roberts, and Seth Benson, who collected a large proportion (51 percent) of the tree voles in museums and who also raised many tree voles 

in captivity (Hamilton 1962, Johnson 1973, Johnson and George 1991) (app. 1). To 

evaluate potential biases inherent in different methods of capturing tree voles, we 

used χ2 tests to compare sex ratios of museum specimens captured with different 

methods. We also assessed habitat associations by comparing the number of voles 

captured in four different forest age-classes, including early seral (0 to 15 years), 

young (16 to 79 years), mature (80 to 200 years), and old-growth (>200 years) 

forests. Museum specimens that were the result of captive breeding (n = 114) were 

included in some tables, but were not used to assess distribution.

Pre-Project and Strategic Surveys

After adopting the Northwest Forest Plan in 1994, the Forest Service and Bureau of 

Land Management initiated extensive surveys of red tree voles in western Oregon 

and northwestern California. For the most part, these surveys fell into three categories, which we will hereafter refer to as (1) pre-project surveys, (2) strategic surveys, and (3) the random plot study. Pre-project and strategic surveys were designed 

to determine if tree vole nests were present in areas proposed for management or in 

areas where there were few or no historical surveys. Pre-project surveyors followed 

an established protocol in which they visually searched for potential tree vole nests 

while walking transects in proposed project areas (Biswell et al. 2000, 2002; Huff 

et al. 2012). The survey protocol called for a minimum of 222 m of survey transect 

per hectare, with parallel transects spaced 40 to 46 m apart. Most (76 percent) trees 

containing potential nest structures detected from the ground were climbed to 

determine if the structures were built by red tree voles. 

Strategic surveys were conducted using a variety of protocols, including the 

same protocol used in pre-project surveys (Biswell et al. 2002) as well as less formal protocols in which contract climbers searched for nests in non-random samples 

We found 1,658 

records of tree voles 

in museums, including 

1,453 specimins and 

205 additional visual 

records documented in 

archived field notes.
7

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

of large trees in old forest that had broken tops, dwarf mistletoe (Arceuthobium

spp.) brooms, or large, epicormic branches. Size of pre-project and strategic survey 

polygons ranged from the immediate area around a single tree to 448 ha. 

Tree vole nests detected in pre-project and strategic surveys were classified as 

“active” or “inactive” depending on physical evidence (Biswell et al. 2000, 2002; 

Huff et al. 2012). Nests with resin ducts, fecal pellets, or cuttings that were still 

green were classified as active, whereas nests with resin ducts or cuttings that 

were tan or brown were described as inactive. Cases in which resin ducts were 

found on the ground below nests that were not climbed were classified as “neststatus undetermined.” 

Survey results and plot locations from pre-project and strategic surveys were 

maintained in an ArcGIS® (Esri, Inc., Redlands, California)2 geodatabase (geographic biotic observation or “GeoBOB”) that we obtained from the BLM in February 2011. The GeoBOB database included polygon feature classes for each survey 

location, as well as information on forest size-class, land ownership, and number of 

trees with tree vole nests detected in each polygon. 

We used data from pre-project surveys to estimate the minimum density of 

trees containing red tree vole nests per hectare as a function of forest size-class and 

elevation. The five forest size-classes were based on tree diameter-at-breast-height 

(dbh): (1) 2 to 13 cm dbh, (2) >13 to 23 cm dbh, (3) >23 to 53 cm dbh, (4) >53 to 81 

cm dbh, and (5) >81 cm dbh. If a tree contained multiple nests, the status of the tree 

was based on the most recently used nest, which was determined based on evidence 

at each nest (Biswell et al. 2002). Lack of consistency in terms of tree climbing and 

mapping of polygons in some pre-project surveys caused considerable uncertainty 

regarding estimates of minimum nest tree density. To reduce this uncertainty, we 

restricted our assessment of distribution to 5,285 survey polygons that included data 

that were linked to mapped polygons. For comparisons of minimum density of nest 

trees among areas, we further restricted the analysis to 3,234 polygons that were 

≥0.6 ha and in which ≥50 percent of potential nests were climbed to determine if 

they were tree vole nests. For comparisons of minimum nest tree density in different forest size-classes, we further restricted the analysis to 2,661 polygons for which 

field data sheets included information on the size of overstory trees. We excluded 

polygons that were <0.6 ha from our estimates of minimum density because many 

small polygons were surveyed after someone reported a possible nest and surveyors 

made a return visit to search the nest tree and a few adjacent trees. As a result, 

2The 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.
8

GENERAL TECHNICAL REPORT PNW-GTR-948

estimates of minimum nest tree density based on polygons <0.6 ha were often 

based on one or two trees and were not representative of average conditions. Plots 

that fell outside the known range of tree voles were used to define the limits of the 

range, but estimates of minimum nest tree density were based only on plots that fell 

within the range of the species, as defined in this report. Because survey protocols 

in strategic surveys were not consistent, we used the strategic survey data to assess 

presence or absence but not density. 

Random Plot Study

The random plot study was designed to assess the minimum density of red tree 

vole nests in different forest age-classes and land-use allocations on federal 

forest lands in Oregon and northwestern California in 2001–2004 (Dunk and 

Hawley 2009, Rittenhouse et al. 2002). The original sample for the random plot 

study was a stratified random sample of 400 1-ha plots selected from the grid of 

Current Vegetation Survey plots (CVS) and Forest Inventory and Analysis plots 

(FIA) in western Oregon and northwestern California (Bechtold and Patterson 

2005; Max et al. 1996; Rittenhouse et al. 2002; USDA FS 2001, 2008). Stratification of the sample was based on forest age and management designations, with 

70 percent of sampling plots classified as old forest and 80 percent of plots in 

reserved land use allocations under the Northwest Forest Plan (Rittenhouse et 

al. 2002, USDA and USDI 1994). Subsequent to implementation of surveys, a 

decision was made to double the plot size by adding a second 1-ha plot on the 

north side of each plot in the original sample of 400 plots. The decision to double 

the plot size at each location was controversial because vegetation in the north 

plot was not always the same as in the south plot and there was concern that 

the addition of a second plot would violate the assumption of independence of 

plots (Dunk and Hawley 2009). Because we did not want to discard data, we 

conducted one analysis with the original 1-ha plots and another analysis with the 

2-ha plots. This allowed us to compare the results using both the original random 

sample and the entire sample.

Surveys of random plots were conducted by walking along linear transects and 

visually searching for potential vole nests in each plot (Dunk and Hawley 2009, Rittenhouse et al. 2002). Transects were spaced 25 m apart, with four 100-m transects 

in each 1-ha plot. All potential nests seen from the ground were examined by tree 

climbers to determine if they were vole nests. Vole nests were classified as inactive 

or active, using the same criteria as in pre-project and strategic surveys (Biswell 

et al. 2000, 2002). In 185 plots with complex tree canopies or in which few or no 

potential vole nests were detected on the terrestrial transects in old forest, surveyors 

The random plot 

study was designed to 

assess the minimum 

density of red tree 

vole nests in different 

forest age-classes 

and land-use 

allocations on federal 

forest lands.
9

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

climbed a stratified random sample of 1 to 6 large trees and searched for nests in the 

tree canopies (Dunk and Hawley 2009, Rittenhouse et al. 2002). The random plot 

survey data were partially summarized by Dunk and Hawley (2009), who limited 

their analysis to an assessment of minimum density of tree vole nests in different 

forest age-classes in the original sample of 1-ha plots. We used the entire sample 

to evaluate tree vole distribution, but we used only plots that fell within the range 

of the species, as defined in this report, to estimate minimum nest tree densities in 

different forest types and subregions. 

After excluding plots that were not accessible because they were on nonfederal 

lands, had incomplete data, or had burned in recent wildfires, there were 350 1-ha 

plots in the original sample, 319 of which fell within the range of the red tree vole, 

and there were 317 2-ha plots, 302 of which fell within the range of the red tree 

vole. These were the samples we used in our analyses. However, the number of 

2-ha plots used in the analysis of minimum nest tree density was further reduced 

to 207 because there were 95 cases in which forest age-classes in the north and 

south plots were different. 

Retrospective and Targeted Surveys

During 1990–2013, we conducted a variety of field and laboratory studies on tree 

voles, including studies of home range and survival (Swingle and Forsman 2009, 

Swingle et al. 2010), distribution (Forsman et al. 2004, 2009a; Price et al. 2015), 

behavior (Forsman et al. 2009b), water consumption (Forsman and Price 2011), 

sampling methods (Swingle et al. 2004), and genetic relationships (Bellinger et al. 

2005, Miller et al. 2006). During these studies we searched for tree voles at many 

locations in Oregon and California, including 44 surveys in which we attempted to 

determine if tree voles were still present in areas where they were found by earlier 

researchers (retrospective surveys). The primary survey method we used to locate 

voles in these studies was to walk or drive through forest areas, visually searching for arboreal nests and climbing trees to determine if nests were built by tree 

voles. In six areas in which we located no tree vole nests during ground surveys, 

we conducted follow-up surveys by climbing large trees and searching for nests in 

the canopy (Forsman et al. 2008). When trying to determine if tree voles were still 

present in areas where they had been found by earlier researchers, we began our 

searches as close as possible to the original locations, and then expanded the search 

outward from there, looking for nests in a 1- to 20-km radius around the historical 

location. The radius of the area searched depended on multiple factors, including 

the time available, distribution of potential habitat, and restrictions on access to 

private lands. We examined 96 percent of 2,229 potential vole nest structures by 
10

GENERAL TECHNICAL REPORT PNW-GTR-948

climbing trees and probing nests with our fingers or a piece of stiff wire to chase 

voles out of their nests (Swingle et al. 2004). We categorized the occupancy status 

of each nest as follows:

• Occupied—tree vole(s) captured or observed (n = 230).

• Likely occupied—nest not probed or dissected, but intact, with fresh green 

cuttings present, usually accompanied by green resin ducts, greenish fecal 

pellets, and debarked twigs (n = 206). 

• Recent nest but not occupied—intact or predated nest, usually with some 

moderately old green cuttings present and variable amounts of faded green 

resin ducts. No tree vole detected when nest probed or dissected (n = 112).

• Old, unoccupied nest—no recent cuttings present. Debarked twigs usually 

present, along with old tan or brown resin ducts and decomposed fecal pellets (n = 491). 

• Non-tree vole—nest or structure with no evidence of use by tree voles 

(n = 1,093).

We used 1984 as the cutoff for retrospective surveys because 1984 was the first 

year in which the Forest Service and BLM initiated numerous pitfall sampling studies of small mammals in the Pacific Northwest and northwestern California (Aubry 

et al. 1991; Corn and Bury 1986, 1991; Gilbert and Allwine 1991; Ralph et al. 1991; 

Raphael 1988). Many of our surveys were concentrated on private or state lands in 

the North Coast, Central Coast, and North Cascades Subregions of Oregon, where 

there had been few or no prior surveys of red tree voles. However, we also searched 

for tree voles in many other areas in Oregon and California where there were prior 

records of tree voles, including some areas on Forest Service or BLM lands where 

pre-project surveys had already been conducted. 

Because the retrospective and targeted surveys included a mixture of different 

methods that were not appropriate for minimum density estimates, we summarized the data from these surveys based on the number of nests located per unit of 

survey effort (person-hours). For each area surveyed, we classified vegetation as 

old-growth forest (>200 years old), mature forest (80 to 200 years old), young forest 

(<80 years old), or rural-agricultural developments. Rural-agricultural developments consisted mainly of highly modified forest habitats intermixed with Christmas tree farms, pastures, vineyards, and residential developments.

California Department of Fish and Game Database

The California Department of Fish and Game tree vole database contained 448 

records of tree vole specimens or nests located during surveys in 1973–2000 

(Gould 2005). Because multiple tree voles or vole nests located in the same 
11

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

general area were lumped together as individual records in the database, we 

examined the original data and constructed a new database that included 1,323 

records of individual nests or voles, including 49 records of red tree voles and 

1,274 records of Sonoma tree voles. The majority of locations were on private 

(88.9 percent) or state (7.0 percent) lands, with the remainder on federal (3.7 

percent), county (0.1 percent), or tribal lands (0.3 percent). Most locations (1,132) 

were documented during surveys in which private contractors or employees of 

private timber companies searched for vole nests while walking through proposed harvest areas on non-federal lands (Humboldt Redwood Company 2009, 

Thompson and Diller 2002, Wooster and Towne 2002). A small subset of the 

locations (n = 107) were documented by graduate students who studied tree voles 

(Meiselman and Doyle 1996, Murray 1995, Zentner 1977). The data consisted 

mainly of nest observations but also contained 39 records of tree voles captured 

in pitfall traps, 15 voles captured by climbers, and 10 voles observed by a private 

contractor who probed nests with a long pole.

Elevation and Tree Voles

We used logistic regression (Procedure GLIMMIX in SAS®; Cary, N.C.) to model 

relationships between presence of tree voles and elevation. For this analysis, we 

used the data from owl pellets, pre-project surveys, and random plot surveys. In the 

analysis of pellet data, the nominal variable was presence or absence of tree voles 

in the sample from each owl territory. In the analysis of pre-project and random 

plot surveys the nominal variable was presence or absence of tree vole nests in 

each polygon or plot that was surveyed. We also plotted the raw data from each 

data source to see if there were any obvious relationships between elevation and 

the proportion of tree voles in owl diets or minimum density of vole nest trees in 

survey plots. 

Results 

Oregon Pellet Data

Red tree voles occurred in the diet at 647 (47 percent) of 1,386 spotted owl territories examined in 1970–2012 (fig. 1-2). The average percentage of red tree voles 

in the diet was 7.1 ± 2.6 percent, based on the grand mean from the six subregions 

in which red tree voles were detected (table 1-1). Red tree voles were most common 

in owl diets in the Central Coast, South Coast, and Central Cascades Subregions, 

and were uncommon or absent in diets of most spotted owls in the North Coast, 

North Cascades, and East Cascades Subregions (fig. 1-2; table 1-1). In the Interior 

Southwest Subregion, tree voles were relatively common in owl diets in Josephine 

Red tree voles were 

most common in owl 

diets in the Central 

Coast, South Coast, 

and Central Cascades 

Subregions, and were 

uncommon or absent 

in diets of most spotted 

owls in the North 

Coast, North Cascades, 

and East Cascades 

Subregions.
12

GENERAL TECHNICAL REPORT PNW-GTR-948

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Percentage of tree voles

in diet of spotted owls

0

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>10 to 20

>20

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Kilometers

Oregon

California

North

Coast

South

Coast

Interior

Southwest

East Cascades

North

Cascades

Central

Cascades

Central

Coast

COOS DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY

JOSEPHINE JACKSON

CLATSOP

COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

MULTNOMAH

HOOD

RIVER

CLACKAMAS

MARION

LINN

COOS DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY

JOSEPHINE JACKSON

CLATSOP

COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

MULTNOMAH

HOOD

RIVER

CLACKAMAS

MARION

LINN

COOS DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY

JOSEPHINE JACKSON

CLATSOP

COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

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HOOD

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CLACKAMAS

MARION

LINN

COOS DOUGLAS

YAMHILL

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JOSEPHINE JACKSON

CLATSOP

COLUMBIA

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TILLAMOOK

BENTON

POLK

MULTNOMAH

HOOD

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LINN

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Valley

Figure 1-2—Percentage of red tree voles (percentage of prey numbers) in diets of northern spotted owls in Oregon. Size and 

color of circles indicates percentage of tree voles in the diet at each of 1,386 owl territories sampled in 1970–2009.
13

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

County, but were absent in owl diets in most of Jackson County except for the area 

north of the Rogue River and Middle Fork Rogue River (fig. 1-2). Although diets 

of spotted owls in the North Coast Subregion contained few tree voles, our sample 

from that area was small because there were few spotted owls in the young forests 

that covered much of that subregion (fig. 1-2) (Forsman 1988). For that reason, we 

did not feel that the pellet data adequately reflected tree vole distribution or relative 

abundance in the North Coast Subregion. In those subregions where they occurred, 

the percentage of red tree voles in the diet was highly variable among owl territories, suggesting high local variation in abundance of voles, or variation in prey 

selection among owls (table 1-1). 

California Pellet Data

Of 245 spotted owl territories sampled in the Green Diamond Study Area in 

1989–2004, 123 (50.2 percent) had tree voles in the diet (fig. 1-3) (Green Diamond 

Resource Company 2006). Of 3,056 prey items in the total sample, 497 (16.3 

percent) were tree voles. The sample included owl territories both north and 

south of the Klamath River, the putative dividing line between the ranges of the 

red tree vole and Sonoma tree vole (fig. 1-3; Blois and Arbogast 2006, Murray 

1995). The majority of owl territories in this sample were in relatively young 

forests regenerating on lands that had been clearcut during the previous century 

(Thome et al. 1999).

Table 1-1—Abundance of red tree voles in diets of northern spotted owls at 1,386 owl 

territories in Oregon, subdivided by geographic subregions, 1970–2009

Geographic subregion

Percentage of territories 

with tree voles in dieta

Percentage of tree voles in diet

x ̄ ± SE Median Range

North Coast 19 2.1 ± 1.1 0 0–18

Central Coast 66 12.3 ± 1.0 11.1 0–100

South Coast 73 16.6 ± 0.8 16.7 0–100

North Cascades 4 1.3 ± 1.3 0 0–33

Central Cascades 46 8.8 ± 0.7 0 0–100

East Cascades 0 0 0 0

Interior Southwest 13 2.1 ± 0.5 0 0–67

Grand mean ± SEb 37 ± 15 7.1 ± 2.6

a

 The number of spotted owl territories sampled in each subregion was: North Coast (n = 21), Central Coast (n = 208), South Coast 

(n = 387), North Cascades (n = 25), Central Cascades (n = 409), East Cascades (n = 80), Interior Southwest (n = 256) . The mean 

percentage of prey numbers that were tree voles is indicated by x

 ̄ ± SE. b

 Grand mean was estimated based on data from the six subregions in which tree voles occurred in the diet.
14

GENERAL TECHNICAL REPORT PNW-GTR-948

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Klamath River

TRINITY

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Figure 1-3—Distribution of tree voles in northwestern California based on occurrence in diets of northern 

spotted owls or barred owls, 1990−2010. Data courtesy of Lowell Diller at Green Diamond Resource Company; 

Alan Franklin at the National Wildlife Research Center, USDA Animal and Plant Inspection Service; Kristin 

Schmidt at Redwood National and State Parks; Katie Fehring at Point Reyes National Seashore; and Stan Moore 

at Bodega, California. 
15

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

Pellets collected in the Northwestern California Study Area in 1987–2003 

included 1,051 prey items, 70 (6.7 percent) of which were Sonoma tree voles. Tree 

voles were detected in the diet at 34 (43 percent) of the 79 spotted owl territories 

sampled (fig. 1-3). The average percentage of tree voles in the diet was 5.9 ± 1.0 

percent. This sample extended the known range of the Sonoma tree vole 14 km east 

into central Trinity County (fig.1-3). 

The pellet sample from Redwood National and State Parks was collected in 

1997–2009 and included 37 prey items from three owl territories in Del Norte 

County and 77 prey items from eight owl territories in Humboldt County. Of 114 

prey items in the combined sample, 16 (14.0 percent) were tree voles. Tree voles 

were detected in one (33.3 percent) of the territories in Del Norte County and 

five (62.5 percent) of the territories in Humboldt County (fig. 1-3). The average 

percentage of tree voles in the diet was 4.2 ± 4.2 percent in Del Norte County, 

and 17.1 ± 7.0 percent in Humboldt County. Ten of the 11 owl pairs surveyed 

inhabited mixed-species forests of mature or old-growth Douglas-fir, coast 

redwood, and western hemlock, and one pair inhabited a mixed-species forest of 

oak and Douglas-fir.

The pellet collection from southern Sonoma County included 29 prey items 

collected in 2010 from one spotted owl territory at Fay Creek, 2.6 km west and 1.6 

km north of Bodega. Of 29 prey in the latter sample, two (7 percent) were Sonoma 

tree voles. This location was the southernmost record of a Sonoma tree vole in 

any of the data sources that we examined. The sample of pellets from spotted 

owls at Point Reyes National Seashore in Marin County included 357 prey items 

collected from 13 spotted owl territories in 2005. This area was approximately 30 

km south of the known range of the Sonoma tree vole. As expected, the sample 

included no tree voles.

Museum Specimens

Of 1,653 tree vole specimen records from museums or field notes of early collectors, most (68 percent) were collected or observed by biologists who climbed 

trees to chase voles from their nests (table 1-2; app. 3). The remainder were 

collected using a variety of methods, including capture by loggers (8 percent), 

capture in pitfall traps, live traps, or snap traps (11 percent), born in captivity 

to mothers that were pregnant at capture (3 percent), born to parents that were 

bred in captivity (7 percent), and unknown or miscellaneous methods (3 percent; 

table 1-2). The geographic distribution of museum specimens was non-uniform 

for both the red tree vole (fig. 1-4) and Sonoma tree vole (fig. 1-5). To some 

extent, this distribution reflected biased sampling efforts by collectors, who 

Of 1,653 tree vole 

specimen records from 

museums or field notes 

of early collectors, 

most (68 percent) were 

collected or observed 

by biologists who 

climbed trees to chase 

voles from their nests.

The southermost 

record of a tree vole in 

California was from an 

owl pellet at Fay Creek 

near Bodega.
16

GENERAL TECHNICAL REPORT PNW-GTR-948

returned to places where they or earlier collectors found voles. This was especially the case regarding the large numbers of voles collected in Oregon near 

Tillamook, Molalla, Newburg, Corvallis, and Monroe. These locations were all 

favorite collection sites where Alex Walker (1928, 1930), Doug Bake (Forsman 

and Swingle 2010), Harry Schoenborn (Maser 1966, Olterman 1972), Stanley 

Jewett (1920, 1930), Percy Clifton (1960), Chris Maser (1966), and Murray 

Johnson (Johnson and George 1991, Johnson 1957–1985) focused their collection efforts. In California, the Harry Wilder Ranch near Carlotta in Humboldt 

County was a favorite collection site that was visited by many early collectors in 

1913–1930, including Brazier Howell (1926), Joseph Mailliard (1923), and Seth 

Benson and Audry Borell (1931). Other popular collection sites in California 

Table 1-2—Number of tree vole specimens documented from museum 

specimens, field notes of collectors, or our captures

Age and collection method Females Males Unknown sex

Adults and subadults

Tree climbinga 545 248 55

Captured by loggersb 52 57 0

Pitfall traps 32 94 0

Other c 51 26 3

Juveniles

Tree climbingd 149 165 79

Captured by loggers 6 3 1 

Pitfall traps 1 6 1

Wildbred (born in captivity)e 21 24 14

Bred in captivity 49 57 8

Unknown capture method 4 1 0

Age unknown

Tree climbing 9 10 21

Captured by loggers 3 1 0

Pitfall traps 2 7 20

Other f 0 0 10

Totals 924 699 212

a Included 595 specimens (424 female, 171 male) in museums, 63 specimens described in collector’s field notes, 

and 190 specimens that we captured (85 female, 63 male) or observed but did not capture (n = 42) in 1990–2011.

b

 Collected from freshly felled trees except for two specimens that were killed when a hollow tree was blasted 

apart with dynamite.

c

 Included live traps (n = 2), roadkill (n = 4), visual sightings (n = 1), nests poked apart from the ground (n = 42), 

and unknown (n = 31).

d Included 370 specimens in museums or described in collector’s notes (146 female, 163 male, 61 unknown sex) 

and 23 specimens that we captured or observed in nests (3 female, 2 male, 18 unknown sex) in 1990–2011.

e

 Born in captivity to mothers that were pregnant when captured.

f

 Included live traps (n = 2), owl pellets (n = 1), visual sightings (n = 3), and unknown (n = 4).
17

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

North

Coast

South

Coast

Interior

Southwest

North

Central Cascades

Coast

Central

Cascades

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0 70 140

Kilometers

East Cascades

Oregon

California

COOS DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY

JOSEPHINE JACKSON

CLATSOP

COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

MULTNOMAH HOOD

RIVER

CLACKAMAS

MARION

LINN

COOS DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY

JOSEPHINE JACKSON

CLATSOP

COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

MULTNOMAH HOOD

RIVER

CLACKAMAS

MARION

LINN

COOS DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY

JOSEPHINE JACKSON

CLATSOP

COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

MULTNOMAH HOOD

RIVER

CLACKAMAS

MARION

LINN

COOS DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY

JOSEPHINE JACKSON

CLATSOP

COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

MULTNOMAH HOOD

RIVER

CLACKAMAS

MARION

LINN

Willamette

Valley

DEL NORTE

SISKIYOU

DEL NORTE

SISKIYOU

Figure 1-4—Distribution of red tree voles collected or observed in the wild. The sample included 686 museum specimens, 61 specimens 

described in collector’s field notes, and 230 specimens that we captured or observed during studies conducted in Oregon in 1990–2013. 

Some locations had multiple voles collected at the same location.
18

GENERAL TECHNICAL REPORT PNW-GTR-948

California

Klamath

o

California

Coast

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DEL NORTE

SISKIYOU

TRINITY

LAKE

HUMBOLDT

MENDOCINO

MARIN

SONOMA

TRINITY

LAKE

HUMBOLDT

MENDOCINO

0 75 150

Kilometers

Klamath River

Russian River

Figure 1-5—Distribution of Sonoma tree voles collected or observed in the wild. The sample included 

738 museum specimens, 62 specimens described in collector’s field notes, and 3 specimens that we 

captured and released during studies conducted in California in 2005–2007. Some locations had multiple 

voles collected at the same location.
19

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

were Arcata, Bridgeville, the lower Russian River, and the coastal headlands 

between Jenner and Fort Bragg. These areas were visited at different times by 

many early collectors, including Seth Benson, Audry Borell, Brazier Howell, 

Joseph Mailliard, Walter Dalquest, Don Roberts, William Hamilton III, Percy 

Clifton, and Murray Johnson. The most prolific and persistent collector at many 

of the California collection sites was Murray Johnson, who made annual collecting trips in 1969–1985 to collect Sonoma tree voles on the lower Russian River 

and many other areas in Sonoma and Mendocino Counties. Murray collected at 

least 150 tree voles on these trips (Johnson 1957–1985).

Some large areas in western Oregon and northwestern California had no 

museum records of tree voles, particularly in the North Coast Subregion of Oregon, where most locations were concentrated in southern Tillamook County and 

one small area in the Chehalem Mountains north of Newberg along the border of 

Washington and Yamhill Counties (fig. 1-4). We found only one historical record 

of a tree vole in Clatsop County, and no records in Columbia County, western 

Multnomah County, and most of Washington, Yamhill, and Polk Counties (fig. 

1-4). It is unclear if the absence of historical records of tree voles in these areas 

was because tree voles were not present before the arrival of European settlers or 

because tree voles were eliminated from these areas before anyone was paying 

attention; we suspect the latter. Forests in Clatsop, Columbia, Washington and 

western Multnomah Counties were mostly harvested or burned in the late 1800s or 

early 1900s, long before any serious effort was made to document the mammalian 

fauna of the region (fig. 1-6).

Table 1-3—Percentage of tree vole museum specimens captured in different 

forest age-classes, subdivided by capture methoda

Tree climbingc Loggingd Pitfall trap Othere

Forest age-classb (n = 402) (n = 115) (n = 37) (n = 3)

Clearcut or early seral 0 0 3 0

Young forest 84 1 5 33

Mature forest 6 2 43 33

Old-growth forest 10 97 49 33

a

 Estimates do not include records in which forest age-class was unknown or specimens were captured as 

juveniles or born in captivity.

b Approximate forest age-classes in years were clearcut or early seral (0 to 15 years), young forest (>15 to 80 

years), mature forest (>80 to 200 years), and old-growth forest (>200 years).

c Included 393 individuals captured by hand and 9 individuals captured when snap traps were placed on top of 

nests.

d Included 113 individuals captured by hand and 2 individuals captured when a hollow tree was blasted apart with 

dynamite.

e Included 2 voles captured in live traps on the ground, and 1 vole captured by hand inside a cabin.
20

GENERAL TECHNICAL REPORT PNW-GTR-948

California

0 50 100

Kilometers

Burned

Logged

COOS

DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY

JOSEPHINE JACKSON

CLATSOP COLUMBIA

WASHINGTON

POLK

MULTNOMAH

HOOD

RIVER

CLACKAMAS

MARION

LINN

North

Coast

South

Coast

Interior

Southwest

North

Cascades

Central

Coast

Central

Cascades

Oregon

o

CLACKAMAS

COOS

DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY

JOSEPHINE JACKSON

CLATSOP COLUMBIA

WASHINGTON

POLK

MULTNOMAH

HOOD

RIVER

MARION

LINN

Willamette

Valley

Tillamook Burn

TILLAMOOK

Silverton Fire

Columbia FireEast Cascades

BENTON

Figure 1-6—Areas logged or burned during the late 1800s to mid-1900s in western Oregon.
21

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

The relative number of non-juvenile males and females in museum samples 

varied with method of capture (χ2 = 96.4, df = 3, P < 0.001). Adult females predominated in collections from tree climbers, young males predominated in collections 

from pitfall traps, and sex ratios were nearly equal in samples collected by loggers 

(table 1-2). In contrast, relative numbers of juvenile males and females captured in 

nests or born to females that were pregnant at capture, did not differ, regardless of 

the method of capture (χ2 = 4.6, df = 3, P = 0.220, table 1-2). Another noticeable 

difference in samples collected using different methods was that the majority of 

specimens collected by climbers were in young forests whereas specimens from 

loggers and pitfall traps were mostly collected in mature and old-growth forests (χ2

= 432, df = 9, P < 0.001, table 1-3). 

Pre-Project Surveys and Strategic Surveys

Red tree vole nests were found in 28 percent of 4,415 pre-project survey polygons 

(fig. 1-7) and 36 percent of 423 strategic survey polygons (fig. 1-8). When we 

excluded surveys in areas outside the range of the tree vole, the percentage of 

polygons in which surveyors detected ≥1 tree vole nest increased to 37 percent in 

3,234 pre-project surveys and 43 percent in 348 strategic surveys. The distribution 

and minimum density of nest trees located in these surveys indicated that red tree 

voles were most common in the South Coast, Central Cascades, Central Coast, 

Interior Southwest, and South Coast Subregions, and were uncommon or rare in the 

North Coast, North Cascades, and California Klamath Subregions (fig. 1-7; table 

1-4). All estimates of mean minimum nest tree density from pre-project surveys 

(table 1-5) were much lower than estimates from random plot surveys. In the 

Interior Southwest, the distribution of pre-project surveys in which vole nests were 

detected followed the same pattern as in the analyses of owl pellets and random 

plots, with the eastern and southern edge of the range roughly following the Applegate River north to the Rogue River, and then east along the north side of the Rogue 

River and Middle Fork of the Rogue River in northeastern Jackson County (figs. 

1-7, 1-8). In the North Coast Subregion, no red tree vole nests were detected in any 

of the 87 pre-project surveys, suggesting that voles were absent from most areas. 

However, red tree voles were detected in 37 percent of 35 strategic-survey polygons 

that targeted old forests on BLM lands in the Nestucca River drainage, indicating 

that there were still local populations present in some areas in southern Tillamook 

County (fig. 1-8).

In the California Klamath Subregion, red tree vole nests were detected in only 

14 (8 percent) of 167 pre-project surveys and 9 (19 percent) of 48 strategic surveys. 

The distribution of survey plots in which nests were detected indicated that the 

The distribution and 

minimum density of 

nest trees located 

in pre-project and 

strategic surveys 

indicated that red 

tree voles were 

most common in the 

Central Cascades, 

Central Coast, Interior 

Southwest, and South 

Coast Subregions, and 

were uncommon or 

rare in the North Coast, 

North Cascades, and 

California Klamath 

Subregions.
22

GENERAL TECHNICAL REPORT PNW-GTR-948

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Kilometers

COOS

DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY JOSEPHINE

JACKSON

CLATSOP

COLUMBIA

TILLAMOOK WASHINGTON

BENTON

POLK

MULTNOMAH

HOOD

RIVER

CLACKAMAS

MARION

LINN

COOS

DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY JOSEPHINE

JACKSON

CLATSOP

COLUMBIA

TILLAMOOK WASHINGTON

BENTON

POLK

MULTNOMAH

HOOD

RIVER

CLACKAMAS

MARION

LINN

COOS

DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY JOSEPHINE

JACKSON

CLATSOP

COLUMBIA

TILLAMOOK WASHINGTON

BENTON

POLK

MULTNOMAH

HOOD

RIVER

CLACKAMAS

MARION

LINN

COOS

DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY JOSEPHINE

JACKSON

CLATSOP

COLUMBIA

TILLAMOOK WASHINGTON

BENTON

POLK

MULTNOMAH

HOOD

RIVER

CLACKAMAS

MARION

LINN

North

Coast

South

Coast

Interior

Southwest

North

Cascades

Central

Cascades

Central

Coast

California

Klamath

!

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Minimum density 

per hectare of red 

tree vole nest trees

0

>0–0.6

>0.6–1.0

>1.0

Oregon

California

DEL 

NORTE

SISKIYOU

TRINITY

HUMBOLDT

Willamette

Valley

East Cascades

Klamath River

Rogue River

Siuslaw River

Nestucca River

Nestucca River

Willamette River

Applegate R.

Figure 1-7—Distribution and relative abundance of red tree vole nest trees detected in 4,415 pre-project surveys in 

1995−2010. Size and shade of symbols indicates the estimated minimum number of tree vole nest trees per hectare in 

each survey polygon. Estimates were based on all tree vole nest trees detected, regardless of nest occupancy status.
23

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

California

Applegate R.

0 50 100

o

Kilometers

Oregon

North

Coast

South

Coast

Interior

Southwest

North

Cascades

Central

Cascades

Central

Coast

COOS DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY

JOSEPHINE

JACKSON

CLATSOP

COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

MULTNOMAH

HOOD

RIVER

CLACKAMAS

MARION

LINN

DEL NORTE

SISKIYOU

COOS DOUGLAS

YAMHILL

LINCOLN

CURRY

JOSEPHINE

JACKSON

CLATSOP

COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

MULTNOMAH

HOOD

RIVER

CLACKAMAS

MARION

LINN

DEL NORTE

SISKIYOU California

Klamath

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Applegate R.Applegate R.

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Rogue River Middle Fork

Willamette RiverWillamette River

Nestucca RiverNestucca River

Siuslaw River

Rogue River ogue River

Klamath River

Figure 1-8—Locations of 423 red tree vole strategic survey sites in western Oregon and northwestern California, 1997−2006. Orange dots indicate sites with tree vole detections and black dots indicate sites without tree 

vole detections.
24

GENERAL TECHNICAL REPORT PNW-GTR-948

Table 1-4—Estimated mean minimum density of trees per hectare (ha) containing 

nests of red tree voles based on pre-project surveys in different geographic 

subregions of Oregon and California, 1995–2010a

Trees per ha with tree vole nests (x ̄ ± SE)a

Geographic subregion nb Recent nestsc Old nests All nests

North Coast 86 0 0 0

Central Coast 64 0.11 ± 0.03 0.05 ± 0.01 0.17 ± 0.04

South Coast 430 0.13 ± 0.02 0.12 ± 0.02 0.28 ± 0.03

North Cascades 349 0.02 ± 0.01 0.01 ± 0.03 0.02 ± 0.01

Central Cascades 1,119 0.09 ± 0.01 0.10 ± 0.01 0.19 ± 0.02

Interior Southwest 1,135 0.07 ± 0.01 0.07 ± 0.01 0.17 ± 0.01

California Klamath 51 0.03 ± 0.01 0.02 ± 0.01 0.08 ± 0.02

Total 3,234 0.08 ± 0.01 0.08 ± 0.01 0.17 ± 0.01

a

 Estimates excluded surveys in which the survey polygon was <0.6 ha, or in which ≥50% of the potential nests 

were not climbed to confirm occupancy. If there were multiple nests in the same tree the count was based on the 

status of the most recently occupied nest.

bThe number of pre-project surveys conducted in each subregion is indicted by n.

c

 Recent nests included occupied nests as well as nests that had been recently occupied, as evidenced by the 

presence of green cuttings or green resin ducts.

Table 1-5—Estimated mean minimum density of trees per hectare (ha) containing 

nests of red tree voles in different forest size-classes based on 2,661 pre-project 

surveys in western Oregon and northwestern California, 1995–2010

Forest size-class 

(dbh in cm)

Trees per ha with tree vole nests (x ̄ ± SE)a

nb Recent nestsc Old nests All nests

2–13 5 0 0 0

>13–23 17 0.11 ± 0.04 0.10 ± 0.06 0.21 ± 0.08

>23–53 711 0.05 ± 0.01 0.07 ± 0.01 0.12 ± 0.01

>53–81 1,239 0.07 ± 0.01 0.08 ± 0.01 0.17 ± 0.02

>81 689 0.15 ± 0.01 0.12 ± 0.01 0.29 ± 0.02

a

 If there were multiple vole nests in the same tree, count was based on the status of the most recently occupied 

nest.

b

 The number of plots sampled in each forest age-class is indicated by n. We excluded plots if they fell outside the 

range of the species or if surveyors did not report the forest size-class.

c

 Recent nests included occupied nests as well as nests that had been recently occupied, as evidenced by the 

presence of green cuttings or green resin ducts.
25

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

range of the red tree vole in this subregion included Del Norte and Humboldt 

Counties north of the Klamath River, and the western edge of Siskiyou County (fig. 

1-8). When we restricted the sample to the latter area (58 pre-project polygons and 

11 strategic polygons), the percentage of plots with ≥1 nest detected was 34 percent 

in pre-project surveys and 60 percent in strategic surveys. The high estimate from 

strategic surveys was inflated because 9 of the strategic survey locations were 

selected because they were in old forests where tree voles had previously been 

located by researchers from Humboldt State University (Biswell et al. 2004). 

Random Plot Study

Of the random plots within the range of the red tree vole, 29 percent of 1-ha plots 

and 43 percent of 2-ha plots had ≥1 tree vole nest detected (fig. 1-9). The percentage of 1-ha plots and 2-ha plots with ≥1 nest tree detected was highest in the 

South Coast, Central Coast, and Central Cascades Subregions, and lowest in the 

California Klamath, North Coast, North Cascades, and Interior Southwest Subregions (table 1-6). In Oregon, the mean minimum density of trees containing tree 

vole nests was lowest in the North Cascades, Interior Southwest, and North Coast 

Subregions, and highest in the South Coast, Central Coast, and Central Cascades 

Subregions (table 1-7). Estimates of mean minimum nest tree density were similar 

regardless of whether we used 1-or 2-ha plots (table 1-7). Of 442 trees in which 

vole nests were detected in the combined sample of 1- and 2-ha plots, the majority 

(62 percent) contained old, apparently unoccupied nests, and the rest (38 percent) 

contained nests that were either occupied or recently occupied. The mean minimum 

density of trees containing red tree vole nests in the California Klamath Subregion 

was similar to the estimate from the adjacent Interior Southwest Subregion in 

Oregon (table 1-7).

There was a consistent pattern of increasing mean minimum nest tree density 

with increasing forest size-class, regardless of whether we used 1-ha or 2-ha plots 

(table 1-8). The mean minimum density of nest trees in old forests was typically 5 

to 7 times higher than in young forests (table 1-8).

There was a consistent 

pattern of increasing 

mean minimum nest 

tree density with 

increasing forest sizeclass, regardless of 

whether we used 1-or 

2-ha plots. The mean 

minimum density 

of nest trees in old 

forests was typically 5 

to 7 times higher than 

in young forests.
26

GENERAL TECHNICAL REPORT PNW-GTR-948

0 50 100

o

Kilometers

Oregon

North

Coast

South

Coast

Interior

Southwest

North

Cascades

Central

Cascades

Central

Coast

COOS DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY

JOSEPHINE

JACKSON

CLATSOP

COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

MULTNOMAH HOOD

RIVER

CLACKAMAS

MARION

LINN

DEL NORTE

SISKIYOU

COOS DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY

JOSEPHINE

JACKSON

CLATSOP

COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

MULTNOMAH HOOD

RIVER

CLACKAMAS

MARION

LINN

DEL NORTE

SISKIYOU

California

California

Klamath

Willamette

Valley

East Cascades

Plots with tree vole nests

Plots without tree vole nests

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Figure 1-9—Distribution of red tree vole nests located in 354 random plot surveys in western Oregon and northwestern 

California, 2001–2004. Orange and black circles indicate plots with and without detections of tree vole nests, respectively.
27

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

Table 1-6—Number and percentage of 1-ha and 2-ha random survey plots in 

which red tree vole nests were detected in Oregon and northwestern California, 

2001–2004

Geographic Subregion

1-ha plots 2-ha plots

Number Percentage Number Percentage

North Coast 13 15 13 23

Central Coast 38 34 38 55

South Coast 61 49 61 57

North Cascades 41 17 41 24

Central Cascades 105 31 104 48

Interior Southwest 32 13 31 23

California Klamath 29 17 29 31

Grand mean ± SE 7 25 ± 5 7 37 ± 6

Table 1-7—Estimated mean minimum density of trees per ha containing nests of 

red tree voles in different subregions based on the random plot study in western 

Oregon and northwestern California, 2001–2004a

Plot size and geographic 

subregion

Trees per ha with tree vole nests (x ̄ ± SE)b

nc Recent nests Old nests All nests

1-ha plots (n = 319):

North Coast 13 0 0.62 ± 0.54 0.62 ± 0.54

Central Coast 38 0.32 ± 0.12 0.61 ± 0.19 0.92 ± 0.25

South Coast 61 0.54 ± 0.15 0.89 ± 0.23 1.43 ± 0.31

North Cascades 41 0.07 ± 0.05 0.32 ± 0.13 0.39 ± 0.16

Central Cascades 105 0.33 ± 0.08 0.36 ± 0.09 0.70 ± 0.15

Interior Southwest 32 0.09 ± 0.05 0.25 ± 0.13 0.34 ± 0.18

California Klamath 29 0.17 ± 0.11 0.17 ± 0.11 0.34 ± 0.21

Grand mean 7 0.22 ± 0.07 0.46 ± 0.10 0.68 ± 0.15

2-ha plots (n = 207):

North Coast 9 0 0.17 ± 0.17 0.17 ± 0.17

Central Coast 26 0.23 ± 0.07 0.73 ± 0.20 0.96 ± 0.22

South Coast 34 0.53 ± 0.17 0.76 ± 0.24 1.29 ± 0.34

North Cascades 29 0.07 ± 0.05 0.28 ± 0.11 0.34 ± 0.13

Central Cascades 71 0.35 ± 0.10 0.51 ± 0.12 0.85 ± 0.20

Interior Southwest 21 0.05 ± 0.05 0.19 ± 0.14 0.24 ± 0.19

California Klamath 17 0.09 ± 0.05 0.06 ± 0.06 0.15 ± 0.07

Grand mean 7 0.19 ± 0.07 0.39 ± 0.11 0.57 ± 0.17

a Estimates were based on plots that fell within the geographic range of the species and were subdivided based on 

nest status and on 1-ha versus 2-ha plots.

b If there were multiple nests in the same tree the count was based on the status of the most recently occupied 

nest. Recent nests included occupied nests as well as nests that had been recently occupied, as evidenced by the 

presence of green cuttings or green resin ducts.

c

 The number of plots surveyed is indicted by n. 
28

GENERAL TECHNICAL REPORT PNW-GTR-948

Retrospective and Targeted Surveys

During 1990–2013, we spent 4,913 hours searching for tree voles at 261 different locations in Oregon and California, including 44 historical locations and 217 

targeted locations where there were no historical records of tree voles (table 1-9). 

The mean number of hours spent searching for and climbing to potential nests in 

the retrospective and targeted areas was 18.8 ± 2.0 hours (range = 1 to 397 hours). 

In our retrospective surveys of historical sites, we found evidence of tree voles at or 

near 66 percent of sites surveyed in the range of the red tree vole (fig. 1-10) and 44 

percent of the sites surveyed within the range of the Sonoma tree vole (fig. 1-11). At 

targeted sites we found evidence of tree voles at 44 percent of 210 sites surveyed in 

Oregon and 43 percent of 7 sites surveyed in California (table 1-9). In general, the 

number of nests located per hour of effort during retrospective and targeted surveys 

was lowest in the North Cascades and North Coast Subregions (table 1-9).

In the North Coast Subregion, most tree vole nests (56 percent) were in remnant 

patches of old forest or mixed-age stands of young and old forest (38 percent), and 

most nests were in state parks (31 percent), or on other state or federal lands (63 

percent). In this subregion we found vole nests at only one of five sites examined on 

Table 1-8—Estimated mean minimum density of trees per ha containing nests of 

red tree voles in different forest size-classes based on the random plot study in 

western Oregon and northwestern California, 2001–2004a

Plot size and forest size class 

(dbh in centimeters)

Trees per ha with tree vole nests (x ̄ ± SE)b

nc Recent nests Old nests All nests

1-ha plots (n = 319):

2–13 12 0 0 0

>13–23 23 0 0.17 ± 0.17 0.17 ± 0.17

>23–53 70 0.16 ± 0.05 0.14 ± 0.08 0.30 ± 0.12

>53–81 110 0.29 ± 0.08 0.56 ± 0.14 0.85 ± 0.19

>81 104 0.46 ± 0.10 0.70 ± 0.12 1.16 ± 0.17

2-ha plots (n = 207):

2–13 5 0 0 0

>13–23 10 0 0 0

>23–53 47 0.10 ± 0.03 0.06 ± 0.03 0.16 ± 0.05

>53–81 80 0.28 ± 0.08 0.59 ± 0.14 0.87 ± 0.20

>81 65 0.41 ± 0.12 0.69 ± 0.11 1.10 ± 0.18

a Estimates were based on plots that fell within the geographic range of the species and were subdivided based on 

nest status and on 1-ha versus 2-ha plots.

b

 If there were multiple vole nests in the same tree, count was based on the status of the most recently occupied 

nest. Recent nests included occupied nests as well as nests that had been recently occupied, as evidenced by the 

presence of green cuttings or green resin ducts.

c The number of plots surveyed is indicted by n.

In the North Coast 

Subregion, most tree 

vole nests (56 percent) 

were in remnant 

patches of old forest 

or mixed-age stands of 

young and old forest 

(38 percent), and most 

nests were in state 

parks (31 percent), or 

on other state or federal 

lands (63 percent).
29

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change Table 1-9—Mean number of red tree vole nests located per hour of survey effort during retrospective and targeted surveys of tree voles in western Oregon and California, 1990–2013a Geographic subregion Retrospective surveys Targeted surveys n x ̄ ± SE Median Effort Percent with vole nests n x ̄ ± SE Median Effort Percent with vole nests North Coast 8 0.09 ± 0.04 0.03 528 50 102 0.03 ± 0.01 0 1,206 12 North Cascades 2 0.15 ± 0.15 0.15 95 50 16 0.14 ± 0.06 0.02 276 50 East Cascades 1 0.29 0.29 21 100 12 0.11 ± 0.03 0.11 200 58 Central Coast 12 0.18 ± 0.07 0.09 422 75 34 0.31 ± 0.06 0.17 707 71 Central Cascades 5 0.22 ± 0.20 0 42 40 30 0.50 ± 0.07 0.42 424 93 South Coast 6 0.64 ± 0.17 0.75 18 83 7 0.43 ± 0.12 0.29 496 100 Interior Southwest 1 0.33 0.33 6 100 9 0.18 ± 0.11 0.09 340 67 California 9 0.21 ± 0.09 0 66 44 7 0.34 ± 0.18 0 66 43 Totals 44 0.25 ± 0.05 0.10 1,198 61 217 0.20 ± 0.02 0 3,715 44 a Data are subdivided by geographic subregion in Oregon. Retrospective surveys were conducted at approximate locations where tree voles were observed or collected prior to 1986. Targeted surveys were conducted at non-random locations that we selected to determine if tree voles were present in specific areas. Sample size (n) indicates number of areas surveyed and “Effort” indicates number of person hours spent conducting surveys and climbing trees to examine nests.
30

GENERAL TECHNICAL REPORT PNW-GTR-948

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YAMHILL

LINCOLN

LANE

CURRY JOSEPHINE

JACKSON

CLATSOP COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

MULTNOMAH

CLACKAMAS

MARION

LINN

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YAMHILL

LINCOLN

LANE

CURRY JOSEPHINE

JACKSON

CLATSOP COLUMBIA

WASHINGTON

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BENTON

POLK

MULTNOMAH

CLACKAMAS

MARION

LINN

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YAMHILL

LANE

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JACKSON

CLATSOP COLUMBIA

WASHINGTON

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BENTON

POLK

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CLACKAMAS

MARION

LINN

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RIVER

o California

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Kilometers

Oregon

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Coast

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Coast

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Cascades

Central

Cascades

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Coast

COOS DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY JOSEPHINE

JACKSON

CLATSOP COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

MULTNOMAH

CLACKAMAS

MARION

LINN

Willamette

Valley

Sites with tree vole nests

Sites without tree vole nests

HOOD

RIVER

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Figure 1-10—Results of retrospective and targeted surveys of red tree voles in Oregon, 2000−2013. Orange and black dots 

indicate sites with and without vole nest detections, respectively.
31

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

!

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California

Klamath

DEL NORTE

SISKIYOU

TRINITY

LAKE

HUMBOLDT

MENDOCINO

MARIN

SONOMA

TRINITY

LAKE

HUMBOLDT

MENDOCINO

0 50 100

Kilometers

o

Oregon

California

Klamath River

Russian River

Applegate R.

CURRY

JOSEPHINE JACKSON

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Coast

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Figure 1-11—Retrospective and targeted surveys of red tree voles and Sonoma tree voles in California, 

2005−2010. Locations with and without detections of tree voles or their nests are indicated by orange and black 

dots, respectively.
32

GENERAL TECHNICAL REPORT PNW-GTR-948

private lands, and the 94 locations where we found no evidence of voles included 

nine locations in old forest and 85 locations in young forest or recently harvested 

areas (fig. 1-10). 

In the Northern Cascades Subregion, we found tree vole nests in most of the 

drainages in the Columbia River Gorge between Portland and Hood River, and in 

the headwaters of Lake Branch, a tributary of the West Fork of Hood River (Forsman et al. 2009a) (fig. 1-10). Although the Lake Branch location technically fell on 

the east slope of the Cascades, vegetation in the upper Lake Branch drainage was 

predominantly western hemlock and Douglas-fir forest, typical of red tree vole habitat on the west slope of the Cascades. At other locations surveyed in the North Cascades, we found evidence of red tree voles at only 50 percent of the areas surveyed, 

and the number of nests located per hour of survey effort was considerably lower 

than in most other subregions except for the North Coast and East Cascades (fig. 

1-10; table 1-9). At the only location in the North Cascades where large numbers of 

red tree voles were collected prior to 1984 (Schoenborn Ranch south of Molalla), we 

found no evidence of tree voles (fig. 1-10). Most of the Schoenborn Ranch area had 

been harvested and converted to young forest and rural residential property after 

tree voles were collected there in 1954–1965 (Maser 1966, Olterman 1972).

In the Central Coast Subregion, we found tree vole nests at 75 percent of 

the historical sites and 71 percent of the targeted sites surveyed (fig. 1-10; table 

1-9). Most of the retrospective and targeted surveys with evidence of red tree 

voles in the Central Coast Subregion were in tracts of old forest (62 percent) or in 

young forests adjacent to older forest (38 percent). Occupancy of some locations 

in young forest appeared to be highly ephemeral. For example, we found four 

occupied nests in a 35-year-old plantation of Douglas-fir in Benton County in 

2004, but we found no occupied nests when we resurveyed the same area on four 

different occasions in 2007–2011.

One of the more interesting retrospective surveys in the Central Coast Subregion 

was a resurvey of the study area where Chris Maser (1966) conducted a population 

density study of red tree voles. The original Maser study plot was a 12.4-ha forest of 

14- to 49-year-old Douglas-fir and Oregon white oak adjacent to a pasture on Nichols 

Creek, 7.2 km southwest of Monroe in Benton County. The forest on Maser’s study 

plot was the result of natural reseeding of an area that had been cleared for pasture 

in 1918. Maser (1966) estimated the minimum number of tree voles present (12 

adults, 28 juveniles) by visually searching all trees in the plot, climbing every tree 

in which a nest was detected, and dissecting each nest to capture any voles that were 

present. We visited the same area in 2006 and found that the plot sampled by Maser 

had been clearcut in about 1988 and was covered by an even-aged stand of 15-year-
33

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

old Douglas-fir. In addition, the pasture adjacent to Maser’s old study plot had been 

planted with Douglas-fir in 1969 and was covered by a stand of 36-year-old trees that 

had been commercially thinned in 2005, a year before our resurvey. We found no 

vole nests in the 15-year-old trees on the old study plot, but we did find one occupied 

nest and several unoccupied nests in the recently thinned stand that was growing on 

the old pasture site. When we resurveyed this area in 2011 and 2013, we found no 

evidence of tree voles, and the stand was clearcut in 2016.

Another area where Maser (1966) and others (Brown 1964, Johnson and George 

1991, Wight 1925) found concentrations of red tree voles in the Central Coast 

Subregion was the McDonald-Dunn Research Forest 7.6 km northwest of Corvallis 

in Benton County. We conducted numerous surveys on this area in 1990–2012 and 

found tree voles or their nests at 16 of 20 locations surveyed, including 13 locations 

in old forest and four locations in young forests. Vole nests on McDonald-Dunn 

Forest were concentrated in a few widely spaced locations, suggesting that distribution of voles on the 4550-ha forest was not uniform. 

In the South Coast Subregion of Oregon we found evidence of red tree voles at 

five of six historical sites and all seven of the targeted sites surveyed (fig. 1-10; table 

1-9). The 12 sites where we found voles were in mixed-age stands of old and young 

forest. The only location where we found no evidence of voles was in a 30-year-old 

Douglas-fir stand growing on a site where the original homesteader had reported 

seeing tree voles when he cleared the land for pasture in 1973. 

The largest targeted survey conducted in the South Coast Subregion was a 

survey that we conducted on the Weyerhaeuser Millicoma Tree Farm 25 km east of 

Coos Bay in 2010. This tree farm was an intensively managed area dominated by 

a mosaic of recent clearcuts and young Douglas-fir forests that were 15–49 years 

old. In this study we surveyed 176 km of transect by visually searching for nests as 

we drove or walked along logging roads. We found 23 tree vole nests, including 20 

unoccupied nests and three occupied nests. The three occupied nests were in 32- to 

38-year-old stands of Douglas-fir. The number of nests found per person hour in this 

survey (0.07) was near the lowest value observed in all areas surveyed in Oregon 

except for the North Coast Subregion (table 1-9).

In the Interior Southwest Subregion we found tree vole nests at six of nine 

targeted sites and at the one retrospective site surveyed (Oregon Caves National 

Monument) (fig. 1-10; table 1-9). Tree vole presence at Oregon Caves was not surprising given that old forest in the monument had changed little since Roest (1951) 

collected a tree vole there in 1949. All nine targeted sites surveyed were in mixedage forests on federal lands. Of the seven sites where we found voles or vole nests in 

this subregion, all were in stands dominated by Douglas-fir. 
34

GENERAL TECHNICAL REPORT PNW-GTR-948

In the Central Cascades Subregion we found evidence of tree voles at 40 percent 

of historical sites and 93 percent of targeted sites (fig. 1-10; table 1-9). All of the 

historical sites surveyed were in foothills near the Willamette Valley and had been 

heavily affected by timber harvesting since the original collections. The high percentage of locations with vole nests in targeted surveys in the Central Cascades was 

expected because most of our surveys in that region were conducted during a genetic 

study in which we targeted areas where tree vole nests had already been documented 

during pre-project surveys in 2001–2006 (Bellinger et al. 2005, Miller et al. 2006). 

In California we found Sonoma tree vole nests at 44 percent of historical sites 

and 43 percent of targeted sites surveyed south of the Klamath River, and no red 

tree vole nests at one targeted site on the Applegate River just south of the Oregon 

border in Siskiyou County (fig. 1-11; table 1-9). At the five historical sites where we 

found no evidence of Sonoma tree voles we conducted fairly extensive surveys at 

two areas (Elk Creek south of Happy Camp, Wilder Ranch east of Carlotta), and 

very limited surveys at three areas (Forest Glen, Albion, Russian Gulch northwest 

of Jenner). Absence of detections at the Elk Creek location was particularly interesting because that historical location was over 25 km east of the known range of 

the species, and was based on a single report by Zentner (1977), who claimed that 

he found tree vole nests about 10 km south of Happy Camp in Siskiyou County. 

Zentner (1977) did not say how he confirmed that the nests he observed were tree 

vole nests, and all subsequent surveys in the Happy Camp area have been negative 

(figs. 1-7 through 1-9).

California Department of Fish and Game Database 

The California Department of Fish and Game tree vole database included 1,274 

records of Sonoma tree voles (1,222 nest locations, 52 specimen locations) and 49 

records of red tree voles (38 nest locations, 11 specimen locations). Most (68 percent) of the specimen records were voles collected during pitfall sampling studies in 

1993–1995. Of the 1,323 records in the database, 89 percent were on private lands, 4 

percent were on federal lands, and 7 percent were on state or county lands (fig. 1-12). 

The 49 red tree vole locations were mostly in western Del Norte County, and were 

mostly on private lands (73 percent). The distribution of Sonoma tree vole locations indicated that they were found in forested areas throughout most of Humboldt 

County and in locations scattered throughout the western portions of Mendocino 

and Sonoma Counties, at least as far south as Bodega and Freestone in Sonoma 

County (fig. 1-12). The data also included several records of tree vole nests in 

Siskiyou and Trinity Counties, all but one of which were reported by Zentner (1977) 

and were outside the known range of either the red tree vole or Sonoma tree vole. 

The distribution of 

Sonoma tree vole 

locations indicated 

that they were found 

in forested areas 

throughout most of 

Humboldt County and 

in locations scattered 

throughout the western 

portions of Mendocino 

and Sonoma Counties, 

at least as far south as 

Bodega and Freestone 

in Sonoma County.
35

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

0 50 100

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Oregon

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Russian River

California 

Coast

Figure 1-12—Distribution of 1,274 locations where tree voles or their nests were reported in the California 

Department of Fish and Game database, 1984−2000. Locations reported by Zentner (1977) were excluded 

because many of his unconfirmed locations were outside the confirmed range of either species of tree vole.
36

GENERAL TECHNICAL REPORT PNW-GTR-948

Elevation Limits

Our logistic regression analyses indicated that the odds of tree vole presence in 

owl pellet samples, pre-project survey polygons, and random plots declined with 

increasing elevation (table 1-10; figs. 1-13, 1-14a, and 1-14b). Results from all three 

analyses were similar, indicating that the odds of tree vole presence decreased by 

factors of 0.775 to 0.867 for every 100-m increase in elevation. In general, tree 

voles were uncommon in samples above 1200 m, and rare in samples above 1400 

m. The highest elevations at which tree voles were detected in pellet samples were 

1390 m in the Central Cascades and 1435 m in the Interior Southwest Subregion. In 

pre-project and random plot surveys, the highest elevations at which vole nests were 

detected were 1585 m in the Interior Southwest Subregion, 1432 m in the Central 

Cascades Subregion, and 1159 m in the North Cascades Subregion. Upper elevation 

limits where we found tree vole nests during targeted surveys in the Coast Ranges 

were 778 m on Marys Peak and 975 m on Prairie Peak. The lowest elevations where 

we found nests were on coastal lowlands and headlands only a few meters above 

sea level. Elevations of 2,232 Sonoma tree vole nests in the California Department 

of Fish and Game database and other sources (museum records, our surveys) ranged 

from 6 to 1555 m.

Discussion

Historical and Current Distribution

Based on the data from all sources examined, we concluded that tree voles in 

Oregon are most abundant and most evenly distributed in the central and southwestern portion of western Oregon and are uncommon or rare in the northern Coast 

Ranges and northern Cascades, where they are mostly restricted to isolated populations in remnant stands of old forest on federal and state lands (Forsman et al. 2008, 

2009; Price et al. 2015). The fact that tree voles still occur in some local areas in 

the northern Coast Ranges and northern Cascades suggests that the species probably occurred in old forests throughout this region prior to the arrival of European 

Table 1-10—Results of logistic regression analyses of elevation and red tree vole presence in 

northern spotted owl pellets, random plot surveys, and pre-project surveys in Oregon

Intercept Elevation (m)

Model Estimate SE P Estimate SE P

Owl pellets 1.5006 0.1192 < 0.0001 -0.0026 0.0002 < 0.0001

Random plot surveys 0.1106 0.2710 = 0.6835 -0.0014 0.0003 < 0.0001

Pre-project surveys 0.7206 0.0978 < 0.0001 -0.0021 0.0001 < 0.0001

We concluded that tree 

voles in Oregon are 

most abundant and 

most evenly distributed 

in the central and 

southwestern portion of 

western Oregon and are 

uncommon or rare in the 

northern Coast Ranges 

and northern Cascades.
37

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

settlers in the early 1800s. However, few people were paying any attention to tree 

voles in the 1800s or early 1900s, so the exact limits of tree vole distribution prior 

to European settlement are unknown. 

Elimination of red tree voles from many lowland forest areas in northwestern 

Oregon was suggested by the fact that we found few or no tree voles in many 

areas they once inhabited, including the Chehalem Mountains near Newberg 

(Clifton 1960; Hubbard 1940, 1941), Schoenborn Ranch near Molalla (Maser 

1966, Olterman 1972), Cape Meares near Tillamook (Forsman and Swingle 2010), 

most of the area surrounding Saddle Mountain in Clatsop County, and several 

historical sites adjacent to the southern Willamette Valley (Maser 1966). Since the 

original observations were made, virtually all of these areas had been harvested, 

burned, or both, and then converted to nonforest use or intensively managed 

young forest. Our retrospective survey of the Maser (1966) population study area 

near Monroe was probably typical of the recent history of many private forest 

Figure 1-13—Proportion of red tree voles in diets (of total prey numbers) of northern spotted owls in Oregon, plotted relative to elevation 

at the owl territory center. Sample included 1,386 owl territories sampled in 1970–2009. The curved line indicates the modeled relationship based on logistic regression analysis of presence or absence of tree voles in the diet.
38

GENERAL TECHNICAL REPORT PNW-GTR-948

Figure 1-14—Estimated minimum density of red tree vole nest trees at different elevations in 354 random plots (A) and 4,415 pre-project 

survey polygons (B) in western Oregon and northern California. Estimates were based on all tree vole nest trees detected, regardless of 

occupancy status. Curved lines indicate modeled relationships based on logistic regression analyses of presence or absence.
39

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

lands in western Oregon. In 1965, Maser found fairly high densities of tree voles 

(approximately one adult per hectare) in a young stand of Douglas-fir and Oregon 

white oak that had regenerated on an area that had been clearcut and converted 

to pasture in the early 1900s. When we resurveyed the site in 2006, we found 

that the study plot had been clearcut again, and we found no tree vole nests in 

the young trees regenerating on the study plot. This scenario of repeated heavy 

disturbance does not bode well for red tree voles on private lands in western 

Oregon. Tree voles may be able to reinvade harvested areas from adjacent refugia 

for the first few rotations, but the comparative rarity of tree voles in young stands 

does not instill much hope that they will be able to persist in areas where trees are 

managed on short rotations with frequent thinning.

Although our surveys indicate that tree voles have been largely eliminated 

from the Tillamook and Clatsop State Forests in the Northern Coast Subregion 

(Price et al. 2015), data from the strategic surveys and targeted surveys clearly 

revealed that some tree voles were still present in the old forests at the western 

edge of Tillamook State Forest, and on Forest Service and BLM lands adjacent to 

Tillamook State Forest in southern Tillamook County (figs. 1-7 through 1-10). It 

seems possible, therefore, that tree voles could eventually recolonize the Tillamook 

State Forest if the Oregon Department of Forestry actively managed forests to 

produce habitat for tree voles. To date, efforts to manage for old forests on state 

forest lands have met strong resistance from some stakeholders who have argued 

that the primary goal on state forests should be to produce revenue for schools and 

counties, as described by Wells (1999).

Other areas in western Oregon where there were few historical or recent records 

of red tree voles included much of the western half of Coos County and the central 

portion of Lincoln County. These areas were mostly in private ownership where 

virtually all old forests had been harvested or burned and replaced by young forests. 

Our limited data from these areas indicated that tree voles were still present but 

were comparatively rare. These results need to be better documented by additional 

surveys on other nonfederal lands in Lincoln, Lane, Douglas, and Coos Counties, 

which will require the cooperation of private landowners.

The combined data from all sources indicated that in most of western Oregon, 

the eastern edge of the range of the red tree vole in the Cascades Mountains corresponds with the transition zone between forests of Douglas-fir and high-elevation 

forests of mountain hemlock, Pacific silver fir (Abies amabilis (Douglas ex Loudon) 

Douglas ex Forbes), and noble fir. However, in southwestern Oregon, the eastern 

edge of the range follows the Applegate River north from California to the Rogue 

River, and then east on the north side of the Rogue River and Middle Fork of the 

Tree voles may be able 

to reinvade harvested 

areas from adjacent 

refugia for the first 

few rotations, but the 

comparative rarity of 

tree voles in young 

stands does not instill 

much hope that they 

will be able to persist 

in areas where trees 

are managed on 

short rotations with 

frequent thinning.
40

GENERAL TECHNICAL REPORT PNW-GTR-948

Rogue River (figs. 1-2, 1-4, and 1-7 through 1-10). In this area, summers are much 

hotter and dryer than in the rest of the range of the red tree vole in Oregon, and 

range limits appear to be determined by climate and the gradual transition to 

landscapes dominated by pine and oak woodlands. 

All sources of data examined in our analysis indicate that red tree voles do not 

occur east of the crest of the Cascades except in the eastern Columbia River Gorge 

and in a small area at the northern end of the Cascades in Hood River County, 

where forests of Douglas-fir and western hemlock extend east over the crest of the 

Cascades along the Columbia River Gorge and into the headwaters of the Lake 

Branch tributary of the Hood River (figs. 1-4, 1-9, and 1-10) (Forsman et al. 2009a). 

More surveys are needed in the latter area to determine if tree voles occur in the 

area south of Lake Branch, where other tributaries of the Hood River also include 

forests of Douglas-fir and western hemlock. 

Data from California indicate that the current range of the red tree vole includes 

Del Norte County, the western edge of Siskiyou County, and all of Humboldt 

County north of the Klamath River (figs. 1-3, 1-4, 1-7, 1-8, 1-9, 1-11, and 1-12). 

The range of the Sonoma tree vole includes the coastal forest extending from the 

Klamath River in Humboldt and Mendocino Counties and the western edge of Trinity County south to Freestone and Bodega in southern Sonoma County (figs. 1-3, 

1-5, 1-11, and 1-12). The large expanse of open grasslands, bays, and marshes south 

of Freestone and Bodega apparently represents an impassable barrier to Sonoma 

tree voles, as indicated by the absence of historical and recent records of tree voles 

farther south.

In contrast to the red tree vole, the range of the Sonoma tree vole is primarily on private lands. Our retrospective and targeted surveys, and surveys 

reported in the California Department of Fish and Game database (Gould 

2005), indicate that tree voles are still present on many of these lands, but we 

found relatively few occupied nests compared to some of the earlier collectors 

who easily collected large numbers of Sonoma tree voles. In some cases, the 

numbers of voles acquired by early collectors seem almost unbelievable today. 

For example, Harry Wilder and Irvin Clay claimed to have captured more than 

50 Sonoma tree voles in two mornings of collecting on the Wilder Ranch near 

Carlotta in 1913 (Howell 1926: 43). When we visited the same area in 2008, we 

found that the forested hillsides had all been harvested and converted to young 

saplings with no evidence of tree voles. Our overall impression, therefore, is that 

Sonoma tree voles are still present in much of their historical range in California, but that numbers have declined appreciably from levels encountered by 

earlier collectors.
41

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

Zentner (1977) claimed to have found tree vole nests outside the known range of 

the red tree vole and Sonoma tree vole at several locations in California, including 

locations in eastern Trinity County and western Siskiyou County east of the Klamath River. In subsequent surveys in those areas, we found no evidence of tree voles, 

but did document large numbers of nests built by squirrels (Glaucomys sabrinus, 

Tamiasciurus douglasii, Sciurus griseus) and woodrats (Neotoma spp.; fig. 1-11). 

In addition, no tree vole nests were found during numerous pre-project surveys, 

random plot surveys, and strategic surveys in areas around the historical Zentner 

locations east of the Klamath River in Siskiyou County (figs. 1-7 through 1-9), and 

no tree voles were found in owl pellets collected in this area (fig. 1-3). We think it 

is unlikely that tree voles were present but undetected during all of these surveys. 

We suspect, therefore, that Zentner (1977) may have incorrectly labeled nests of 

squirrels or woodrats as tree vole nests. We are especially suspicious of his data 

because he reported that the central mass of the nests he identified as tree vole nests 

consisted mainly of stripped bark as opposed to resin ducts (Zentner 1977: 35). We 

consider this issue unresolved until more surveys are conducted in the areas where 

Zentner claimed to have found tree voles, but until then, we think his data should be 

considered skeptically.

Although our targeted surveys, retrospective surveys, and owl pellet analyses 

indicate that tree voles are absent in some portions of their historical range, there 

are some important qualifications on these results. First, as already mentioned, 

detection rates of tree vole nests are never 100 percent, so it is certain that many 

nests were not detected during ground-based surveys (Swingle 2005, Swingle and 

Forsman 2009). Second, a retrospective survey is likely to find a population decline 

because the number of historical sites that are still occupied cannot exceed 100 

percent. However, the retrospective surveys that we conducted were not limited to 

the historical nest groves in which voles were collected. Instead, we searched large 

areas around each historical collection site, and if we found tree voles or their nests 

anywhere in the survey area we considered the site as still occupied, regardless of 

the distance from the historical nest location and regardless of whether nests were 

occupied. If anything, therefore, we think that our retrospective surveys overestimated the proportion of historical sites still occupied by tree voles.

The occurrence of tree voles in a large sample of owl diets was a useful indicator of tree vole presence in different geographic areas, but several factors limited 

the inferences that could be drawn from the data. Most importantly, the sample size 

of prey remains from many owl territories was small and this undoubtedly resulted 

in many false negatives (no detections of tree voles when the species was actually 

present). We could have reduced the odds of false negatives by limiting the analysis 
42

GENERAL TECHNICAL REPORT PNW-GTR-948

to owl territories with large samples of prey items, but this would have excluded a 

large number of owl territories in which tree voles were detected. We decided that 

retention of all of the distributional data was more important than trying to reduce 

the proportion of false negatives by setting artificial limits on sample size. 

Other concerns with data from owl pellets were that: (1) regional variation in 

prey diversity could cause diets to vary in ways that were unrelated to the density of 

tree voles, or (2) the results would not apply to areas where spotted owls had been 

eliminated by the removal of old forests. These are valid concerns, but the fact that 

the owl pellet data were in close agreement with regional patterns in tree vole abundance based on pre-project surveys, strategic surveys, targeted surveys, and random 

plot surveys led us to conclude that the owl pellet data provided a good indication of 

regional patterns of tree vole abundance and distribution. In regard to the concern 

that owl pellet data could not be used to assess vole distribution in areas where owls 

did not occur, we emphasized this in the results, and fig. 1-2 makes it obvious where 

those areas were. 

Although most sources of data that we examined were not selected randomly, 

we feel that our results are generally representative of the distribution and relative abundance of tree voles on federal and state lands in Oregon and California. 

Many thousands of forest stands and over a thousand different owl territories were 

sampled. The scope of the effort was so extensive that we felt that concerns about 

the lack of random sampling were overwhelmed by the sheer amount of data from 

throughout the range of the red tree vole. That being said, there were definitely 

some areas that were not covered by our surveys where more data are needed, 

especially within the range of the Sonoma tree vole, where the majority of the 

population is on private lands.

Habitat Relationships

Based on all sources of data in our analysis, we concluded that red tree voles were 

most abundant in old forests, and were often rare or absent in areas that had been 

harvested or burned and converted to young, intensively managed forests. Although 

similar conclusions have been reached by others (e.g., Aubry et al. 1991, Corn and 

Bury 1986, Dunk and Hawley 2009), imperfect detection of tree voles and their 

nests makes all comparisons among forest age-classes suspect. If anything, density 

of tree voles in old forests is disproportionately underestimated based on ground 

transects because many nests are located high above ground or inside cavities 

where they cannot be detected from the ground (Swingle 2005, Walker 1928). As a 

result, the high numbers of tree vole nests found in old forests probably underestimates the differences between old and young forests.

Density of tree voles 

in old forests is 

disproportionately 

underestimated based 

on ground transects 

because many nests 

are located high above 

ground or inside 

cavities where they 

cannot be detected 

from the ground.
43

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

Even in young forests, many tree vole nests are difficult to detect from the 

ground. For example, Swingle and Forsman (2009) estimated that only 48 percent of 

nests used by radio-marked tree voles in predominantly young forests were detectable from the ground. The only way to evaluate and correct for this source of bias 

would be to conduct studies in which large numbers of trees were inspected from 

the ground and then climbed to determine the number of nests actually present and 

to determine if those nests were actually occupied by tree voles. Any estimates that 

do not include correction for imperfect detection should be considered estimates 

of minimum density. We recommend that future population studies of tree voles 

include assessments of detection probabilities. This will not be easy or inexpensive, 

but is badly needed.

Although nest detectability is imperfect, our experience leads us to conclude 

that the odds that no tree vole nests will be detected in an area where tree voles 

actually occur (false negatives) are low, especially when survey plots are large. 

Even when survey plots are relatively small, as in the random plot study, the evidence suggests that false negatives are uncommon. For example, Dunk and Hawley 

(2009) estimated that the rate of false negatives in the random plot survey was only 

6 percent based on a comparison of nest detections from ground transects and nest 

detections in trees surveyed by climbers. 

The fact that tree vole nests were detected in only 27 percent of 1-ha random 

plot surveys and 28 percent of pre-project survey plots indicated that red tree voles 

were uncommon or absent in many areas, particularly in the northern Coast Ranges 

and northern Cascades. This result is even more significant given that most (80 

percent) of the random plot surveys were in old forest, where tree voles are most 

abundant (Corn and Bury 1986, 1991; Dunk and Hawley 2009; Forsman et al. 

2009a). 

Particularly noticeable was the absence of red tree vole detections in the 

northern Coast Ranges (Price et al. 2015) in the extensive areas that burned during 

the Tillamook Burn fires of 1933–1951 (Holbrook 1943, Kemp 1967, Lucia 1983, 

Wells 1999), and the 1902 Columbia and 1865 Silverton fires in the north Cascades 

(fig. 1-6). Apparently, red tree voles were almost completely eradicated during 

these huge fires and the extensive salvage logging that followed. Tree voles have 

been unable to recolonize the burned areas, either because the regenerating young 

forests are too far from a population source or because management of the burned 

areas has maintained conditions unsuitable for tree voles, or both. Subsequent to 

the Tillamook Burn fires, much of the region was salvage-logged and replanted 

with Douglas-fir, which has subsequently been intensively managed to the present 

day (ODF 2010, Wells 1999). At the time of our surveys, forests in the burned area 

Although nest 

detectability is 

imperfect, our 

experience leads us to 

conclude that the odds 

that no tree vole nests 

will be detected in an 

area where tree voles 

actually occur (false 

negatives) are low, 

especially when survey 

plots are large.
44

GENERAL TECHNICAL REPORT PNW-GTR-948

were predominantly young stands that were being managed on short rotations with 

periodic thinning to reduce crown density (ODF 2010). The thinned stands typically 

had low crown closure and were largely lacking in the kinds of canopy structures 

that provide sturdy foundations for tree vole nests, including broken tops, forked 

trunks, cavities, epicormic branching, dwarf mistletoe brooms, and heavy accumulations of moss and lichens (Forsman et al. 2008, Maser 1966, Swingle 2005). 

Without management to produce or retain such structures, there is little likelihood 

that tree voles will re-establish a presence in the areas burned during the Tillamook 

Burn. Though the red tree vole is listed as an Oregon Sensitive Species (ODFW 

2008), the most recent management plan for state forests in western Oregon (ODF 

2010) did not address the habitat needs of tree voles. Forests in the areas that burned 

in the 1902 Columbia and 1865 Silverton fires in the northern Cascades were 

considerably older than the forests in the Tillamook Burn, but the absence of tree 

voles even in those mature forests suggests that it may take centuries for tree voles 

to reinvade areas that burn during very large, hot fires.

Although the data from random plot surveys, pre-project surveys, and pitfall 

trapping studies indicated that tree voles were most abundant in old forests, the 

vast majority of tree voles captured by tree climbers were captured in young 

forests. This apparent contradiction was almost certainly due to sampling bias. 

Most specimen collectors tended to search for tree voles in young forests where 

nests were easy to see from the ground and trees were easy to climb. Few of the 

early collectors had the technical ability to climb old-growth trees (Bailey 1915, 

Jobanek 1988), so old-growth forests went largely unsurveyed, except by mammalogists who used pitfall traps, and a few loggers who captured voles in recently 

felled trees (Bailey 1915, Forsman and Swingle 2010, Walker 1928). Many mammalogists who used pitfall traps to sample tree voles (Corn and Bury 1986, 1991; 

Gilbert and Allwine 1991; Gomez and Anthony 1998; Gomez et al. 1997; Manning 

and Maguire 1999; Martin and McComb 2002; Ralph et al. 1991; Raphael 1988) 

sampled a cross-section of forest age-classes, so the results from pitfall traps in 

table 1-3 probably provide a more accurate picture of the relative abundance of tree 

voles in different forest age-classes than do results from tree climbing. However, 

even pitfall data may be biased if differences in tree spacing and canopy interconnectivity cause tree voles to travel on the ground more frequently in some forest 

age-classes than in others. 

Although the results from the random plot study, pre-project surveys, and 

strategic surveys indicated that tree vole nests were most abundant in old forests, all 

of these different sources also indicated that tree voles occurred at lower densities 

in young forests. This indicated that tree voles began to colonize young stands at 
45

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

a fairly early age (15 to 25 years). However, the fact that few or no tree vole nests 

were found in most young stands suggested that such stands were mostly not suitable for tree voles or were located too far from the nearest source population to be 

rapidly recolonized. 

When we did find tree voles in young forests, they were often in regenerating 

stands adjacent to mature or old-growth forest. Recolonization of these young 

stands was likely dependent on the presence of source populations in adjacent old 

forests. It is important, therefore, that forest managers be cognizant of the fact that 

remnant patches of old forest may be important as refugia for tree voles and that 

young forests may facilitate dispersal and gene flow between these remnant patches. 

Even very small patches of old forest may be important as refugia where they occur 

in landscapes that are otherwise dominated by young forests. 

Elevation Limits 

Based on data from all sources, the range of the red tree vole in Oregon extends 

from a few meters above sea level up to and including the lower edge of the 

transition zone where forests of Douglas-fir intergrade with forests of true fir and 

mountain hemlock. Although our surveys indicate that tree voles are now absent 

or uncommon in many of the young forests regenerating on harvested areas at low 

elevations along the coast, we also found that tree voles still occurred at sites near 

sea level in some locations, including Tillamook Head, Cape Falcon, Cape Meares, 

Cape Lookout, Cascade Head, Cape Arago, and Bandon. 

In the Coast Ranges and Cascades of western Oregon, red tree voles were 

uncommon above 1000 m elevation, although they were occasionally found up to 

1059 m in the north Cascades, 1475 m in the central Cascades, 1437 m in the southern Cascades, and 1585 m at Sturgis Creek in the Klamath Mountains just north of 

the Oregon-California border. Although Manning and Maguire (1999) reported a 

tree vole captured at 1600 m in the central Cascades, Manning (2012) subsequently 

informed us that they had plotted the location incorrectly, and that the elevation at 

the capture site was actually 1475 m. 

Hamilton (1962) suggested that tree voles may not occur at high elevations 

because their small, exposed nests do not provide adequate insulation during 

winter. Another possibility is that it may be difficult for tree voles to forage at high 

elevations during winter because limbs of trees are often covered by layers of snow 

and ice for long periods of time. We suspect that both of the above hypotheses 

may be true, albeit difficult to test. Another obvious hypothesis is that, in most 

areas, the upper limits of tree vole distribution could be determined by the upper 

elevation limits of Douglas-fir, the primary food source of tree voles in most areas. 

When we did find tree 

voles in young forests, 

they were often in 

regenerating stands 

adjacent to mature 

or old-growth forest. 

Recolonization of these 

young stands was 

likely dependent on 

the presence of source 

populations in adjacent 

old forests. 

Based on data from 

all sources, the range 

of the red tree vole in 

Oregon extends from 

a few meters above 

sea level up to and 

including the lower 

edge of the transition 

zone where forests of 

Douglas-fir intergrade 

with forests of true fir 

and mountain hemlock. 
46

GENERAL TECHNICAL REPORT PNW-GTR-948

This seems unlikely given that tree voles have learned to feed on other species 

of conifers such as Sitka spruce, western hemlock, grand fir, Monterey pine, and 

bishop pine in many low-elevation areas (Benson and Borell 1931, Clifton 1960, 

Jewett 1920, Kelsey et al. 2009, Taylor 1915, Vrieze 1980, Wooster and Town 

2002, this study). However, there are no records of tree voles feeding on mountain 

hemlock, Pacific silver fir, or noble fir, and we cannot rule out the possibility that 

these high-elevation species are unacceptable as a substitute for Douglas-fir as a 

food source.

Sex Ratios

We found that the sex ratio of tree voles captured by loggers was nearly 50:50. This 

result was probably most reflective of the actual sex ratio of tree voles, as there is 

good reason to believe that sex ratios from other sampling methods (pitfall traps, 

tree climbing) are biased. The predominance of females in samples collected by 

tree climbers probably results from the higher detectability of large female brood 

nests (Swingle 2005), whereas the predominance of males in samples from pitfall 

traps likely reflects higher levels of terrestrial movement by males searching 

their home ranges for potential mates (Swingle and Forsman 2009). We found no 

evidence that disproportionate sex ratios in samples collected by tree climbing 

and pitfall trapping were a result of ground nesting by males. In addition, Swingle 

and Forsman (2009) found that radio-collared male tree voles nested exclusively 

in trees, but regularly descended to the ground to move between trees. Thus, we 

think that ground nesting by tree voles (Bailey 1936, Howell 1926, Maser 1966, 

Thompson and Diller 2002) is a rare occurrence and that opinions to the contrary 

(Anthony 1928, Howell 1926, Maser 1966, Nowak and Paradiso 1983, Phillips and 

Chrostowski 1981) are incorrect. 

Population Density and Regulation

Although tree voles occur in coniferous forests throughout much of western Oregon 

and northwestern California, there was no evidence from our surveys or any of 

the historical data that they ever occurred at the high densities sometimes reported 

for other voles (e.g., Cornely and Verts 1988, Smolen and Keller 1987, Verts and 

Carraway 1987). Instead, they typically occurred at low densities, with clusters of 

nests distributed in a very patchy pattern at the landscape scale. Tree voles defend 

their nests in the wild and adults infrequently occupy the same nests at the same 

time except for brief periods when males visit female nests to breed (Forsman et al. 

2009b, Swingle 2005). Although there have been a few cases where two occupied 

nests were found in the same tree at the same time (Benson and Borell 1931, Taylor 

1915, Johnson 1957–1985, this study), this appears to be the exception rather than 
47

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

the rule, especially in young forests (Swingle and Forsman 2009). Based on the 

multiple sources of data described in this report, and observations of adult behavior 

in other studies (Forsman et al. 2009b, Swingle and Forsman 2009), we believe that 

tree vole populations are naturally maintained at low densities because of adult 

territoriality, a low reproductive rate (Clifton 1960, Forsman et al. 2009b, Hamilton 1962), high rate of predation (Swingle et al. 2010), and the comparatively low 

density of trees with good structures for nest support (i.e., habitat). 

Management Implications

Our analyses suggest that tree voles are still present throughout much of their 

historical range, but have become rare or absent in some areas that have been 

converted to young, intensively managed forests. In western Oregon and northwestern California, red tree voles will likely continue to thrive in the extensive areas of 

old forest on federal lands that are currently protected by the Northwest Forest Plan 

(USDA and USDI 1994). Where federal lands are lacking, however, there is a high 

likelihood that tree voles will gradually disappear unless managers actively manage 

for at least some old forests. This is especially true in the North Coast Subregion 

of Oregon where there is little federal forest land. In California, Sonoma tree 

voles occur primarily on private and state lands, where landowners are required 

to follow state forestry regulations, but are not specifically required to protect tree 

voles or their habitat (http://calfire.ca.gov/resource_mgt/downloads/2013_FP_Rulebook_with_Tech_RuleNo1.pdf). Thus, the persistence of Sonoma tree voles in many 

areas is in doubt. However, the continued persistence of Sonoma tree voles in small 

tracts of forest as far south as Freestone and Bodega does suggest that Sonoma tree 

voles may persist in highly fragmented forest landscapes, as long as some areas of 

tree vole habitat are retained. Ultimately, persistence of both species of tree voles 

will depend on the willingness of humans to protect mature and old-growth forests, 

which provide stable, high-quality habitat for tree voles and serve as refugia for 

recolonization of adjacent areas that have been harvested or burned. 

Where federal lands are 

lacking, however, there 

is a high likelihood that 

tree voles will gradually 

disappear unless 

managers actively 

manage for at least 

some old forests.

Persistence of both 

species of tree voles 

will depend on the 

willingness of humans 

to protect mature and 

old-growth forests, 

which provide stable, 

high-quality habitat 

for tree voles and 

serve as refugia for 

recolonization of 

adjacent areas.
48

GENERAL TECHNICAL REPORT PNW-GTR-948
49

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

Chapter 2: Diet 

Introduction

Although they may feed on other items in captivity (Benson and Borell 1931, 

Clifton 1960), tree voles (Arborimus pomo, A. longicaudus) in the wild feed primarily on needles and twigs of conifers (Forsman et al. 2009b, Maser 1966). To obtain 

food they harvest conifer branch tips (hereafter cuttings) at night and store them on 

or inside their nests. Cuttings harvested by tree voles are easily identified based on 

their small size (typically 8 to 25 cm) and the chisel-shaped bite marks on the base 

of each twig (Forsman et al. 2009b). In addition, cuttings harvested by tree voles 

are almost always found in association with tree vole fecal pellets, debarked twigs, 

and discarded resin ducts, which the voles remove from the edges of each needle 

(Kelsey et al. 2009, Maser 1966). In this chapter, we describe and compare diets 

of tree voles in different parts of their range based on the composition of cuttings 

found in tree vole nests that we examined in western Oregon and northwestern 

California in 2000–2013. 

Methods

We estimated diets based on the ratio of cuttings from different tree species that 

were stored in the nests of 421 red tree voles (A. longicaudus) nests and 10 Sonoma 

tree voles (A. pomo). In most cases (63 percent), we actually counted cuttings, but at 

a few nests with large numbers of cuttings we estimated the species ratio of cuttings based on what was visible on top of the nest because we did not want to tear 

the nests apart. The sample of nests examined was not selected randomly, and no 

attempt was made to sample equal numbers of nests in different regions. Instead 

we used all cases in which we climbed to nests and recorded the composition of 

cuttings in the nest.

Results

Of 421 nests examined within the range of the red tree vole, 362 (86 percent) 

contained exclusively Douglas-fir1 cuttings (table 2-1). At the other 59 nests, 

cuttings were grand fir (0.5 percent), western hemlock (7.6 percent), Sitka spruce 

(3.1 percent), or mixtures of western hemlock and Sitka spruce (2.1 percent), or 

western hemlock and Douglas-fir (0.7 percent) (table 2-1). The only area where 

red tree voles did not feed primarily on Douglas-fir was in the narrow zone 

of Sitka spruce and western hemlock along the coast of northwestern Oregon. 

In the Sitka spruce zone, where 88 percent of the tree vole nests examined 

had exclusively western hemlock or Sitka spruce cuttings, voles rarely used 

Douglas-fir, even when it was present (fig. 2-1). There was an apparent latitudinal difference in food preference in the Sitka spruce zone with 53 of 54 nests 

Of 421 nests examined 

within the range of 

the red tree vole, 

362 (86 percent) 

contained exclusively 

Douglas-fir cuttings.
50

GENERAL TECHNICAL REPORT PNW-GTR-948

(98 percent) in the North Coast Subregion containing western hemlock or Sitka 

spruce cuttings, but only 6 of 13 nests (46 percent) in the Sitka spruce zone in 

the Central and South Coast Subregions containing western hemlock or Sitka 

spruce cuttings (fig. 2-1).

Of 27 Sonoma tree vole nests examined in California, 23 (85 percent) contained 

Douglas-fir cuttings or resin ducts, and 4 (15 percent) contained cuttings or resin 

ducts from Monterey pine. The latter nests were in Monterey pine trees that were 

planted near the Green Diamond Resource Company office in Korbel, 10 km east of 

Arcata in Humboldt County. Many of the resin ducts from Monterey pine needles 

were over 9 cm long, much longer than Douglas-fir (3 cm), and all were from the 

outer edges of the needles. Monterey pine does not normally occur within the range 

of the Sonoma tree vole except where it is planted as an ornamental (McDonald and 

Laacke 1990).

Discussion

In most of their range, red tree voles were limited primarily to forests of Douglasfir, which was their primary food source. The main exception was the Sitka spruce 

zone (Franklin and Dyrness 1973) of coastal northwestern Oregon, where red tree 

voles lived primarily in forests of western hemlock or Sitka spruce, and largely 

avoided Douglas-fir, even when it was present. A good example of this behavior 

was an occupied nest that we found on Cape Meares in Tillamook County. The nest 

was in a Douglas-fir, but the cuttings and resin ducts in the nest were entirely western hemlock, which the vole had harvested from adjacent western hemlocks that 

had branches that were in contact with the nest tree. Tree voles that fed on western 

hemlock and Sitka spruce had to handle needles differently than voles that fed on 

Douglas-fir (Kelsey et al. 2009). When feeding on Douglas-fir, tree voles remove 

the resin ducts from the outer edges of each needle and eat the middle portion of 

Table 2-1—Number of occupied and recently occupied nests 

of red tree voles in Oregon, subdivided by the species of 

conifer cuttings that were being used for food

Species of cuttings in nest Number of nests

Douglas-fir 362

Grand fir 2

Western hemlock 32

Western hemlock and Douglas-fir 3

Western hemlock and Sitka spruce 9

Sitka spruce 13
51

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

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Figure 2-1—Species of cuttings documented in red tree vole nests in Oregon.
52

GENERAL TECHNICAL REPORT PNW-GTR-948

the needle (Benson and Borell 1931, Kelsey et al. 2009, Maser 1966, this study). In 

contrast, western hemlock has a single resin duct that runs down the center of the 

needle, and tree voles that feed on western hemlock eat the edges of the needle and 

discard the center of the needle (fig. 2-2) (Kelsey et al. 2009, this study).

In nests of red tree voles that were feeding on Sitka spruce, we did not find 

any resin ducts, but we did find some spruce needles that had the apical half eaten, 

apparently whole. Resin ducts in Sitka spruce needles may be difficult to remove 

because they are located midway between the edge of the needle and the midrib 

(fig. 2-2). In addition, the location of resin ducts in needles of Sitka spruce is 

unpredictable because they are discontinuous, varying in length and location within 

the needle (Kelsey et al. 2009, Weng and Jackson 2000). Some Sitka spruce needles 

have no ducts, whereas some have ducts on only one side of the needle and others 

have ducts concentrated in the basal half of the needle (fig. 2-2). Thus, it appears 

that tree voles that feed on spruce may avoid the resin ducts by only eating a portion 

of each needle. This calls for further investigation with captive voles, as our sample 

of vole nests in spruce trees was small. 

Some researchers (Clifton 1960, Johnson 1957–1985, Walker 1930) found that 

when red tree voles that were used to feeding on Sitka spruce or western hemlock 

were switched to a diet of Douglas-fir, they lost weight and died within a few days. 

Apparently these voles were unable to switch from one type of food to another, possibly because of the different techniques required to remove resin ducts of different 

species. We suspect that food-handling procedures are learned from the mother, and 

are not easily changed without considerable time to experiment with a novel food. 

An alternative hypothesis that could explain why tree voles cannot easily switch 

between alternative food types is that the intestinal flora needed to digest or neutralize leaf toxins is specific to certain plant species and is passed maternally when 

juveniles consume their mother’s fecal pellets (Clifton 1960, Hamilton 1962).

Tree voles also feed on other species of conifers, including grand fir (Benson 

and Borell 1931, Johnson 1957–1985, Taylor 1915, Vrieze 1980, this study), bishop 

pine (Wooster and Town 2002), and Monterey pine (this study). Feeding on these 

alternative species occurs primarily in California, but we did document a few cases 

of voles feeding on grand fir in Oregon. Grand fir and pine trees have resin ducts 

that are located near the edges of the needle, much like Douglas-fir. It is possible, 

therefore, that tree voles that are used to feeding on Douglas-fir may find it easier 

to switch to grand fir or pine than to western hemlock or Sitka spruce. Again, this 

hypothesis is in need of experimental testing with captive voles.
53

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

Observations of nests where Sonoma tree voles were feeding on Monterey pine 

or bishop pine (Wooster and Town 2002, this study) suggest that future researchers need to conduct surveys for Sonoma tree voles in bishop pine forests as well 

as forests of Douglas-fir. This may prove difficult because branches of bishop 

pine are commonly covered by dense mats of fallen needles that are difficult to 

distinguish from tree vole nests when viewed from the ground (Wooster and Town 

2002). Thus, unless resin ducts are found on the ground, the only way to effectively 

document tree vole nests in forests of bishop pine is to climb the trees to examine 

the mats of needles. 

In California and coastal southern Oregon, tree voles often occurred in mixed 

species stands of coast redwoods and other conifers. In these stands tree voles 

appeared to ignore the redwoods and feed on Douglas-fir, grand fir, western 

hemlock, or bishop pine. Apparently, the structure or chemical composition of 

redwood needles made them unpalatable. The same was true of western redcedar 

and incense-cedar, both of which were common conifers in our study areas but were 

never eaten.

Most tree vole nests that we examined contained the remains of conifer twigs 

that had the bark removed (fig. 2-3). These twigs looked like tiny toothpicks and 

were easy to miss without close inspection. Maser (1966) suggested that debarked 

twigs in tree vole nests were the result of voles removing the bark to feed on the 

cambium layer and the woody pith inside twigs. It remains unclear if the voles also 

eat the bark as well as the underlying cambium. This needs further investigation. 

Management Implications

In most of their range, tree voles depend on Douglas-fir as their primary food 

source, and are likely to benefit from management that retains mature or old forests 

of Douglas-fir. The exception is the Sitka spruce zone, where tree voles feed primarily on western hemlock and Sitka spruce and are likely to benefit from management that retains mature forests of hemlock and spruce. In all forest types, old trees 

with deep crowns likely provide a more stable food supply than do small trees with 

shallow crowns. Thinning that disrupts arboreal connections between tree limbs is 

likely to be particularly disruptive in young stands, where tree voles need to move 

between multiple trees to obtain food (Swingle 2005). 

Thinning that disrupts 

arboreal connections 

between tree limbs is 

likely to be particularly 

disruptive in young 

stands, where tree 

voles need to move 

between multiple trees 

to obtain food.
54

GENERAL TECHNICAL REPORT PNW-GTR-948

Figure 2-2—Location of resin ducts in three different species of conifers used as food by tree voles. 

Douglas-fir has two resin ducts located near the 

lateral edges of the needle. Western hemlock has a 

single resin duct located in the center of the needle. 

Sitka spruce has two resin ducts located halfway 

between the center and the edge of the needle, but 

the ducts are often incomplete or missing entirely.

Figure 2-3—Debarked twigs from a tree vole nest. These twigs look like tiny 

toothpicks. Also note the angled bite marks on the ends of the twigs.
55

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

Chapter 3: Current Status of Potential Red Tree Vole 

Habitat Based on Species Distribution Models

Introduction

An integral part of the Northwest Forest Plan (NWFP) is the monitoring of status 

and trends of habitat for species associated with late-successional and old-growth 

forests (Lint et al. 1999, Madsen et al. 1999). To meet NWFP monitoring requirements, the USDA Forest Service (Forest Service) and USDI Bureau of Land Management (BLM) developed satellite-based maps of forest composition and structure 

for assessing the distribution of different forest types and age-classes within the 

region covered by the NWFP (Moeur et al. 2005, 2011). The primary reason for 

development of these maps was to allow managers and researchers to monitor 

trends in forest vegetation over time and to assess the amount of late-successional 

and old-growth forest available to species that inhabit old forests, such as the northern spotted owl (Strix occidentalis caurina), marbled murrelet (Brachyramphus 

marmoratus), and red tree vole (Arborimus longicaudus). 

There have been several recent studies that used NWFP satellite maps and 

sophisticated models to predict distributions of habitat for northern spotted owls 

and marbled murrelets based on biotic and abiotic conditions (Davis et al. 2011, 

Huff et al. 2006, Lint 2005, Raphael et al. 2011). In this chapter, we use the NWFP 

satellite maps to predict the amount and distribution of potential habitat of the red 

tree vole in western Oregon and northwestern California (fig. 3-1). Our objective is 

to provide forest managers, wildlife biologists, and the public with a better understanding of the areas where red tree voles may be expected to occur in western 

Oregon and northwestern California. 

Methods

Vegetation Data

We obtained vegetation data (app. 4) from satellite maps produced by the NWFP 

late-successional and old-growth monitoring program (Moeur et al. 2011). These 

landscape-scale data were produced with “gradient nearest neighbor” (GNN) models 

developed by the Landscape Ecology, Modeling, Mapping and Analysis (LEMMA) 

group at Oregon State University (http://lemma.forestry.oregonstate.edu/) using a 

method that combined direct gradient analysis (Gauch 1982, ter Braak 1986) and 

nearest-neighbor imputation (Moeur and Stage 1995). These methods were described 

in detail by Ohmann and Gregory (2002). In general, the method used to develop 

GNN layers was to assign detailed forest vegetation data from forest inventory plots 

to every pixel in a geographic information system (GIS) raster map based on modeled relationships between plot data and a combination of spatial predictor variables 
56

GENERAL TECHNICAL REPORT PNW-GTR-948

1

3

2

4

Oregon

On April 25, 2004, this rare

cloud-free image of the forests 

of western Oregon and northwestern California was taken by 

a NASA satellite orbiting more 

than 400 miles above the Earth 

using a moderate-resolution 

imaging spectroradiometer 

(MODIS).

The burned footprint of the 

Biscuit Fire (2002) is clearly 

visible in the Klamath Mountains

modeling region (2).

Snow-covered mountain peaks 

clearly mark the high-elevation 

edges of the red tree vole's

range.

Oregon

Oregon

California

Modeling regions

1. Cascade Mountains

2. Klamath Mountains

3. Northern Coast

4. Southern Coast

0 50 100

Kilometers

Washington

o

Figure 3-1—Modeling regions used in the development of habitat suitability models for red tree voles in western Oregon and 

northwestern California.
57

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

derived from Landsat satellite imagery, climate variables, topographic variables, and 

soil parent materials. The assumption behind the GNN methods was that two locations with similar combined spatial signatures should also have similar forest structure and composition. Plot data were from the Forest Inventory and Analysis program 

(FIA) (USDA FS 2003) and Forest Service Current Vegetation Survey program 

(CVS) (Max et al. 1996). The GNN data used in our analysis included the entire range 

of the red tree vole. Satellite imagery from which GNN layers were created covered 

the time period through 2006 in Oregon and 2007 in California. On-the-ground plot 

data used to create the vegetation layers were collected during 2001–2007. 

Accuracy assessments for GNN continuous variables were based on the correlation of observed plot values against predicted (modeled) values. Ohmann and 

Gregory (2002) used a modified leave-one-out cross-validation approach that 

yielded results similar to those of a true cross-validation approach, but probably 

slightly underestimated true accuracy. Accuracy assessments were based on pooled 

plots for each modeling region.

Our selection of GNN variables was based on: (1) information on habitat 

relationships from literature and expert knowledge, (2) on-the-ground plot accuracies of vegetation variables, and (3) correlations between modeling covariates. We 

chose not to use any vegetation data measured on a continuous scale that had plot 

accuracies with Pearson correlation (r) < 0.5, which equates to moderate agreement 

between the GNN map prediction and the plot. The accuracy assessment for GNN 

species composition variables was based on Cohen’s Kappa coefficient, which is a 

measure of agreement between predicted and actual conditions (in this case, dominant tree species), taking into consideration agreement occurring by chance (Cohen 

1960). For species composition, we chose not to include any variables that had 

Cohen’s Kappa values < 0.2 (poor agreement) for individual species or < 0.3 (fair 

agreement) for estimates that were averaged for several species in a group category 

(e.g., “subalpine conifers”). In cases in which variables were highly correlated (r > 

0.7), we dropped the variable with the lowest plot accuracy. 

We dropped mean diameter-at-breast-height (dbh) of conifers, mean stand 

height, mean stand age, and basal area of conifers from our initial list of GNN 

variables because they were highly correlated with other GNN variables and 

had the lowest plot accuracies. We selected a consistent set of four variables for 

forest-stand structure that we included in all of our modeling regions. From least 

to most accurate (plot accuracy ± SD) these variables were density per hectare of 

large conifers (≥75 cm dbh; 0.63 ± 0.06), percentage of hardwood cover (0.63 ± 

0.05), diameter diversity index (0.71 ± 0.05), and percentage of conifer cover (0.74 

± 0.07). We also developed six variables of forest-species composition based on 
58

GENERAL TECHNICAL REPORT PNW-GTR-948

the percentage of total basal area in a stand composed of six focal tree species or 

groups of tree species. The latter variables were included as appropriate for each 

modeling region where tree voles occurred. The average Cohen’s Kappas for the 

tree-species groups or forest-type variables listed in order from lowest to highest 

accuracy were coast redwoods, (0.31); pines (0.37 ± 0.10); food-source trees (0.37 

± 0.09); subalpine forest (0.40 ± 0.10); and white fir or grand fir (0.43 ± 0.02). The 

food-source tree group variable consisted of the four tree species that red tree voles 

used for food, including Douglas-fir, western hemlock, Sitka spruce, and grand 

fir. Species composition of the four food-source tree species varied among regions 

with Douglas-fir and western hemlock predominate in the western Cascades and 

Coast Ranges, Sitka spruce and western hemlock predominate along the coast, and 

Douglas-fir and grand fir predominate in southwest Oregon. 

Abiotic Data

To a considerable extent, patterns of forest vegetation expressed in the GNN maps, 

especially tree species, reflected the underlying patterns of climate and topography. 

Therefore, we limited our inclusion of abiotic environmental variables (app. 4) to 

those that had potentially important influences on tree vole distribution, outside of 

vegetative patterns. 

Because Johnson (1973) suggested that red tree voles are adapted to a regime 

of moderate temperatures and high rainfall, we used temperature and precipitation 

variables in our models. We chose these abiotic features because tree voles obtain 

water from needles they consume (Forsman and Price 2011), and captive voles 

have been observed licking water from needles (Benson and Borell 1931, Clifton 

1960, Maser 1966). Hamilton (1962: 503) stated that “The humid coastal belt, 

bathed regularly by summer fogs, is effective both in maintaining fresh foliage 

and providing water to be licked from the needles. The habitat which in less humid 

zones annually becomes a virtual desert provides a full measure of moisture 

except in the driest months of early fall.” Thus, it seemed reasonable to assess 

whether precipitation, temperature, and the amount of water contained in needles 

are important factors influencing the distribution of tree voles, particularly in late 

summer (July to September).

To model the possible influence of temperature and precipitation on the distribution of red tree voles, we initially considered average annual precipitation, 

average maximum temperature in August, and summer-moisture stress (the ratio 

of summer temperature and precipitation) for inclusion in our models. However, 

the latter two variables were highly correlated (r > 0.7), so we dropped moisture 

stress and replaced it with an index of summer fog that was not highly correlated 
59

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

with summer temperature (r = -0.55–0.17). We developed the summer fog index 

from parameter-elevation regression on independent slope models (PRISM; http://

www.prism.oregonstate.edu/) following a multi-step procedure in which we used 

dew point (DEWPT) and minimum temperature (MINT) grids for the months of 

July and August. Using ArcGIS (Esri, Inc., Redlands, Calif.), we combined July and 

August estimates into summer average DEWPT and MINT. The original PRISM 

maps were produced in 4-km2 resolution, which was too coarse to capture the variation of DEWPT and MINT at the spatial scale of our habitat modeling, so we downscaled our DEWPT and MINT maps to 100-m2

 resolution and then used statistical 

software (SAS Institute, Inc., Cary, N.C.) to regress dependent variables against a 

100-m2 resolution digital elevation model (DEM) (Zimmermann and Roberts 2001). 

The predicted values of the regression were then used to generate smoothed 100-m2

grids of summer average DEWPT and MINT. We then used ArcGIS to calculate 

the difference between DEWPT and MINT. As ambient air temperature approaches 

the dew point temperature, the air becomes saturated and fog or moisture condensation on vegetation can occur. Thus, our summer fog layer (fig. 3-2) represents the 

average difference between MINT and DEWPT; the lower the value, the higher the 

potential that fog or condensation will occur during the summer period. 

They are thought to be poorly adapted to high-elevation areas characterized by 

low winter temperatures (Hamilton 1962). Thus another abiotic variable considered 

was winter minimum temperature, but this was dropped because it was highly correlated (r = 0.863) with the summer fog variable in the Cascade Mountains Region. 

We also included a variable for solar radiation. Southerly aspects in the northern 

hemisphere receive more annual solar radiation and are relatively warmer and drier 

than northerly aspects. We used this variable to evaluate whether tree voles tend to 

place their nests where they will be exposed to higher solar radiation (Meiselman 

and Doyle 1996, Swingle 2005). We used the potential relative radiation (PRR) index 

(Pierce et al. 2005) as a more realistic measure for solar radiation than simple aspect. 

Data on Presence of Red Tree Voles

Red tree vole presence data used to train and test our habitat models came from nest 

tree locations found during the random plot study, strategic surveys, and pre-project 

surveys described in chapter 1. From the random plot study data, plots with red tree 

vole nests were denoted using a single point in the center of the 1-ha plot, or a single 

point in the center of the mid-line separating paired plots. To reduce spatial autocorrelation and other modeling issues arising from biased strategic and pre-project survey 

data (Fourcade et al. 2014), we generated a 2.4 × 2.4-km sampling grid across the range 

of the red tree vole and randomly selected one nest tree location from each grid cell.
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GENERAL TECHNICAL REPORT PNW-GTR-948

Less fog

More fog

MODIS Terra Imagery

(Aug. 29, 2009)

Summer Fog Model

0 50 100

Kilometers

o

Figure 3-2—2009 National Aeronautics and Space Administration (NASA) moderate resolution imaging spectoradiometer (MODIS) 

image of summer fog in western Oregon and northwestern California (left) compared to the summer fog index model used in our 

analysis of habitat suitability for red tree voles (right).
61

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

Habitat Modeling Regions

Because of variation in habitat relationships of tree voles in different parts of their 

range, we split the range into four modeling regions (fig. 3-1). These divisions 

were based on large-scale geographic provincial boundaries that conformed to 

the existing GNN modeling regions (http://lemma.forestry.oregonstate.edu/data/

structure-maps), and allowed us to maintain a consistent set of variables for each 

modeling region based on geographic breaks that we thought were warranted, while 

also obtaining an adequate number of red tree vole locations within each region to 

conduct model training and testing. 

The largest modeling region was the Cascade Mountains Modeling Region (fig. 

3-1). This region encompassed about 3.3 million ha, contained about 2.6 million ha of 

forested land, and included 212 (44 percent) of the 484 red tree vole nest tree locations 

used in development of our habitat models. Forests in this region primarily consisted 

of Douglas-fir and western hemlock at lower elevations and Pacific silver fir, mountain 

hemlock, and subalpine fir at higher elevations. In the southern portion of this region, 

forests of Douglas-fir and western hemlock were gradually replaced by forests of 

white fir, Shasta red fir, sugar pine, western white pine, and ponderosa pine. About 68 

percent of the forest land in this modeling region was managed by federal agencies.

The second largest modeling region (2.2 million ha) was the North Coast Modeling Region, which included the area west of the Willamette River and north of the 

line separating Lane and Douglas Counties (fig. 3-1). This region included about 

1.6 million ha of forested land and 20 percent (n = 96) of the red tree vole locations 

used in model development. Forests in this region were dominated by Douglas-fir, 

western hemlock, and western redcedar. Other important forest types in this region 

included a narrow zone of Sitka spruce and western hemlock along the coast and 

mixed stands of Douglas-fir, grand fir, bigleaf maple, and Oregon white oak in the 

foothills adjacent to the Willamette Valley. Forest lands in this modeling region were 

managed by private owners (61 percent), federal agencies (24 percent), and the Oregon 

Department of Forestry (15 percent).

The Klamath Mountains Modeling Region (1.8 million ha) contained approximately 

1.6 million ha of forest land and 24 percent (n = 118) of the tree vole locations used to 

develop our models (fig. 3-1). It conformed to the GNN Oregon and California Klamath 

Mountains Modeling Region, which included portions of the Klamath physiographic 

provinces of Oregon and California. Forest vegetation was dominated by a diverse array 

of mixed conifer and mixed conifer/hardwood forests, including Douglas-fir mixed 

with a variety of other species, including white fir, grand fir, ponderosa pine, sugar pine, 

western white pine, tanoak, Pacific madrone, canyon live oak, and California laurel. 

About 73 percent of the forest land in this region was managed by federal agencies.
62

GENERAL TECHNICAL REPORT PNW-GTR-948

The South Coast Modeling Region (1.1 million ha) included the southern half of 

the GNN Oregon Coast Modeling Region (fig. 3-1). It contained about 1.0 million ha 

of forested land and 12 percent (n = 58) of the red tree vole locations that we used in 

model development. Forests in this region were mostly dominated by Douglas-fir, 

with a narrow belt of Sitka spruce and western hemlock along the coast (McCain 

and Diaz 2002). Forests at the southern edge of this region gradually transitioned 

into tanoak and coast redwood forests near the Oregon-California border. Most 

forests in the South Coast Modeling Region were managed by private landowners 

(65 percent). The other 35 percent were managed by federal agencies (31 percent), or 

the Oregon Department of Forestry (4 percent). 

The division of the North and South Coast Range Modeling Regions was based 

on a distinct north/south genetic discontinuity of red tree voles (Miller et al. 2006) and 

ecological differences that indicated a distinct population segment of red tree voles in 

the northern Coast Ranges of Oregon, north of the Siuslaw River (USFWS 2011).

Habitat Modeling and Model Evaluation

We used the software application MaxEnt (http://www.cs.princeton.

edu/~schapire/maxent/) to produce habitat models and maps for red tree vole 

distribution. MaxEnt uses a machine-learning process and a suite of potential 

response functions to estimate the most uniform maximum entropy probability 

distribution of the “average” environmental conditions at known species locations 

compared to what is available across the modeled area (Phillips and Dudík 2008, 

Phillips et al. 2006). It produces a prediction for each pixel in a grid map that 

represents the relative habitat suitability of each pixel for species presence based 

on the relationship of the pixel’s environmental conditions to those pixels with 

species presence, and its difference from the surrounding background environmental conditions within the modeling region (Phillips and Dudík 2008).

The modeling process fits model-training data (red tree vole nest tree locations) 

to environmental covariates using various combinations of linear, quadratic, product, hinge, and threshold response functions (features). The use of all feature types 

may lead to model overfitting depending on the sample size of the training data 

(Phillips et al. 2006). However, the “auto feature” setting in MaxEnt restricts the 

model to simpler linear, quadratic, and hinge features for small sample sizes (Elith 

et al. 2011). Modeling with just the hinge feature produces models with simpler or 

smoother functions and is generally a useful simplification that can reduce overfitting (Phillips 2013). Our selection of features included a combination of linear, 

product, and hinge features because our hypothesized variable responses fit these 

choices. We used the “auto feature” option, further limiting the subset of response 
63

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

features selected, and the model retained only those features with some effect. We 

also used the “regularization multiplier” (RM) in program MaxEnt to avoid overfitting the data. The RM feature performs a function similar to Akaike’s information 

criterion (Akaike 1974) by penalizing the complexity of the model. 

We produced 10 bootstrapped random replicates for each modeling region using 

25 percent of the red tree vole location data held out to test the model. We evaluated 

the contribution that each variable made to the overall model by reviewing the jackknife graphs produced by MaxEnt for mean test gain and area under the receiving 

curve (AUC) from the bootstrap replicates (Phillips et al. 2006). Based on these 

graphs, we dropped variables that decreased mean test gain and AUC.

Once the final list of modeling variables was selected, we evaluated and calibrated each habitat model. Model evaluation consisted of three steps. First, we used 

model test gain to evaluate predictions from our habitat models (Phillips et al. 2006). 

Test gain scores indicated how different the testing data were from the background 

data, and were similar to “deviance” in generalized linear modeling. Higher gains 

indicate larger differences between environmental conditions at locations with tree 

vole presences and average background environmental conditions. The exponent of 

gain produces the mean probability value of predicted species presences compared 

to a random location selected from the background. In addition, differences between 

model test gain and regularized training gain can be useful for controlling model 

overfitting, as a large difference is an indication of model overfitting (Phillips 2013). 

Second, we used the AUC statistic to evaluate model accuracy and fit to the 

testing data (Fielding and Bell 1997). The AUC statistic is a measure of the model’s 

predictive accuracy, and produces an index ranging from 0.5 to 1.0, with values 

close to 0.5 indicating no discrimination and a value of 1.0 indicating perfect 

predictions. We interpreted the AUC statistic as follows: 

• >0.9–1.0 = excellent model.

• >0.8–0.9 = good model,

• >0.7–0.8 = fair model.

• >0.6–0.7 = poor model.

• 0.5–0.6 = model that did not predict much better than a random guess. 

Examples of this interpretation in the field of niche-based species-distribution 

models can be found in Araújo et al. (2005) and Randin et al. (2006). In our analysis, we used 10,000 randomly selected background locations (map pixels) instead of 

true absence data, so it was not possible to achieve an AUC statistic of 1.0 (Wiley 

et al. 2003). Specific to our case, AUC statistics represented the percentage of times 

a location with red tree vole presence would have a higher habitat suitability value 

than a randomly selected background location without tree vole presence.
64

GENERAL TECHNICAL REPORT PNW-GTR-948

Third, we measured model performance based on the continuous Boyce index 

(CBI), which was designed specifically for testing habitat models produced from 

presence only data (Boyce et al. 2002, Hirzel et al. 2006). The CBI is based on the 

Spearman rank correlation coefficient (rs), which compares the ranks of modeled 

species presence with the area available to “binned” modeled prediction ranks. A 

good model predicts an increasing ratio of the percentage of species presence based 

on testing data to the percentage of the modeled landscape in each model bin as the 

bin values increase (Hirzel et al. 2006).

Our evaluation process was iterative. We ran the first habitat model using 

the default RM setting of 1.0 to determine which model variables to use, 

as described in the previous section. Once variables were selected, we then 

increased the RM setting by increments of 0.25 or 0.50 while observing changes 

in test gain and AUC, the difference between test gain and regularized training 

gain, and CBI, including the shape of the predicted/expected (P/E) curve. Our 

final calibrated model was the one that had the highest test gain, AUC, and CBI, 

when means and confidence intervals of the test and regularized training gain 

were similar and overlapped. 

Habitat Map Development 

In addition to being useful for model evaluation, the P/E curve also provides 

information that can be used to reclassify outputs of continuous habitat models 

into discrete habitat classes (Hirzel et al. 2006). The point along the model-prediction axis (x-axis) where the curve crosses P/E= 1 along the y-axis (fig. 3-3) is 

the threshold where species presence predicted by the model is higher than would 

be expected if habitat use was random. This threshold is often used to classify 

habitat models into binary maps, where logistic probability values greater than 

the P/E = 1 threshold represent “suitable” habitat (Hirzel et al. 2006). We further 

divided the continuous scale of probability of occurrence from our habitat models 

into four habitat classes that ranged from the least to the most suitable habitat 

conditions, as follows: 

• Unsuitable—MaxEnt logistic output from zero to the value where the 

95-percent confidence interval is below the P/E = 1 threshold. This habitat 

class represents the lowest suitability class and the model predicts that the 

species does not occur.

• Marginal—MaxEnt logistic output where the 95-percent confidence 

interval fluctuates along and encompasses the P/E = 1 threshold. This 

habitat class represents a condition near the low end of where the species 

may be present.
65

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

• Suitable—MaxEnt logistic output in which the 95-percent confidence 

interval departs from the P/E = 1 threshold to the logistic output of 0.5. A 

MaxEnt logistic output value of 0.5 represents the “average” environmental condition associated with the training data. This habitat class represents 

habitat conditions where the model predicts that the probability of red tree 

vole presence is higher than expected by random chance, up to average conditions associated with tree vole presence.

• Highly Suitable—MaxEnt logistic output ranging from >0.5 to the highest 

output from the habitat model. This habitat class represents the most suitable, 

or “above average,” conditions and the model predicts red tree vole presence.

We combined the suitable and highly suitable habitat classes into one map class 

that we termed “potential habitat,” which represented areas in which tree voles were 

likely to occur. Potential habitat maps were based on the average habitat model from 

10 bootstrap replicates. We used the standard deviation grids to calculate a 95-percent 

confidence interval for each grid cell and produced maps based on upper and lower 

confidence intervals. Summary maps were then used to generate histograms of modelarea predictions for each model region and for the entire range-wide modeling area. 

Figure 3-3—Curve illustrating the predicted versus expected ratio (P/E) used to classify continuous outputs from Program MaxEnt 

habitat models into discrete classes of habitat suitability for red tree voles in western Oregon and northwestern California (modified from 

fig. 6 in Hirzel et al. 2006: 150). Shaded area bracketing the line indicates 95-percent confidence intervals.

We combined the 

suitable and highly 

suitable habitat classes 

into one map class that 

we termed “potential 

habitat,” which 

represented areas in 

which tree voles were 

likely to occur.
66

GENERAL TECHNICAL REPORT PNW-GTR-948

Using Owl Pellet Data to Evaluate Habitat Maps

In addition to the map evaluations discussed above, we conducted independent 

tests of maps with the spotted owl diet data described in chapter 1. For this test, 

we defined each spotted owl location as the area within a 1900-m radius around 

the center of activity of the owls (usually a nest site). To reduce the likelihood of 

concluding that tree voles were absent when they were actually present (false negatives), we limited the analysis to spotted owl locations where ≥10 individual prey 

items were identified in pellets. To better represent the timeframe of our map, we 

also limited data to pellets collected in 2000–2008. We used Mann-Whitney U-tests 

(Mann and Whitney 1947) to assess whether mean habitat suitability values from 

the models and the mean percentages of potential habitat within owl territories were 

higher in territories with tree voles in the diet than in territories without tree voles 

in the diet. Our hypothesis was that average habitat suitability would be higher in 

spotted owl territories where tree voles were found in owl pellets than in spotted 

owl territories where tree voles were not found in pellets. Likewise, we expected 

higher amounts of potential habitat within territories where tree voles were found 

in pellets than in territories without tree voles in pellets. We also examined correlations between the percentage of tree voles in each pellet collection, and mean 

habitat suitability, and amounts of potential habitat within each owl territory. We 

expected positive Pearson correlation coefficients between habitat suitability and 

amounts of potential habitat with increasing percentage of tree voles in the diet.

Results

Stand-structure variables were the most informative explanatory variables in our 

analysis, contributing 42 to 81 percent of the information on which the final model 

was based (table 3-1). Tree species composition and abiotic variables contributed 

9 to 31 percent (table 3-2) and 11 to 27 percent (table 3-3), respectively. In terms 

of stand structure, density of large conifers (≥75 cm dbh) was the strongest variable, with habitat suitability increasing logarithmically as density of large conifers 

increased (app. 4, fig. A4-1). On average, the next most informative variable was 

diameter-diversity index, which was a measure of stand structural diversity. Habitat 

suitability increased sigmoidally as diameter-diversity index increased (app. 4, fig. 

A4-2). The third most important variable was percentage of conifer cover, which 

also had a positive sigmoidal relationship with habitat suitability (app. 4, fig. 4A-3). 

However, habitat suitability decreased as conifer cover approached 100 percent, 

indicating that some canopy opening was desirable. On average, hardwood cover 

contributed about 4 percent of the information that produced the habitat models, 

and in general had a negative relationship with habitat suitability (app. 4, fig. 4A-4). 

Suitability increased 

logarithmically as 

density of large 

conifers increased.
67

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

In terms of forest tree-species composition, the strongest variable was the percentage of total stand basal area composed of food-source trees, which was primarily 

Douglas-fir, but also included grand fir, and western hemlock and Sitka spruce in the 

North Coast Modeling Region (table 3-2). The relationship between food-source tree 

species and habitat suitability was mostly linear, where habitat suitability increased as 

percentage of basal area of food-source trees increased (app. 4, fig. 4A-5). The rest of the 

tree-species variables showed negative exponential or linear relationships with habitat 

Table 3-1—Percentage of contribution of stand structure variables to the final models in 

the analysis of habitat suitability for red tree voles in Oregon

Modeling region

Density of 

large conifersa

Diameter 

diversity indexb

Conifer 

cover

Hardwood 

cover

Cascade Mountains 21.0 8.5 8.3 4.3

Klamath Mountains 24.7 14.2 18.3 1.4

North Coast 48.2 12.3 16.5 3.5

South Coast 24.6 33.5 2.9 6.2

a

 Density of large conifers lowered gain the most when removed from models in the North Coast Modeling Region.

b

 Diameter diversity index had the highest gain by itself for each modeling region and lowered gain the most when 

removed for only the South Coast Modeling Region.

Table 3-2—Percentage of contribution of forest species composition variables to the final 

models in the analysis of habitat suitability for red tree voles in Oregon

Modeling regions Fooda Subalpineb White fir Redwood Pine

Cascade Mountains 11.5 12.2 3.5 4.0

Klamath Mountains 11.2 0.7 1.9 1.6

North Coast 8.1 1.4

South Coast 5.9 2.0 0.8

a

 The “Food” variable included the group of tree species used as food by tree voles: Douglas-fir, Sitka spruce, western hemlock, 

and grand fir.

b

 High-elevation conifers such as Pacific silver fir, noble fir, subalpine fir, and mountain hemlock.

Table 3-3—Percentage of contribution of abiotic environmental variables to the final models 

in the analysis of habitat suitability for red tree voles in Oregon

Modeling region

Summer 

foga

Average maximum 

summer 

temperature

Average annual 

precipitationb

Solar 

radiation

Cascade Mountains 9.7 10.0 4.4 2.5

Klamath Mountains 3.8 3.4 13.1 5.8

North Coast 5.9 1.4 2.0 1.7

South Coast 13.8 8.0 1.7 0.8

a Summer fog lowered gain the most when removed for the Cascade Mountains Modeling Region.

b

 Average annual precipitation lowered gain the most when removed from models in the Klamath Mountains Modeling Region.
68

GENERAL TECHNICAL REPORT PNW-GTR-948

suitability (apps. 4, fig. 4A-6 through 4A-9). Habitat suitability decreased rapidly as percentage of basal area of subalpine conifers (app. 4, fig. 4A-6), white fir (app. 4, fig. 4A-7), 

coast redwood (app. 4, fig. 4A-8), and pine (app. 4, fig. 4A-9) increased, suggesting that 

red tree voles were less likely to be present at higher elevations and in forests dominated 

by coastal redwoods and pines. On average, summer fog (app. 4, fig. 4A-10) was the 

most important abiotic variable, followed by summer maximum temperature (app. 4, fig. 

4A-11), average annual precipitation (app. 4, fig. 4A-12), and solar radiation (table 3-3). 

Our final models had mean test AUCs that ranged from 0.82 to 0.85 and CBIs that 

ranged from 0.996 to 0.999 (P < 0.001). These test statistics indicate that our models 

produced moderate to good predictions of red tree vole presence. The independent 

evaluation of the modeled habitat map based on owl pellet data produced similar results. 

At the rangewide scale, amounts of potential habitat (U = 6251.0, P < 0.001) and mean 

habitat suitability (fig. 3-4; U = 6368.5, P < 0.001) within owl territories where tree voles 

were found in owl pellets (n = 81) were higher than in owl territories where tree voles 

were not found in pellets (n = 92). There was fair to moderate correlation between the 

percentage of tree voles in owl pellets and mean habitat suitability (r = 0.546, P < 0.001) 

and amount of potential habitat (r = 0.506, P < 0.001) within owl territories (fig. 3-5). 

0

5

10

15

20

25

30

35

40

45

50

Potential habitat Habitat suitability

Percent 

Tree vole

No tree vole

Figure 3-4—Mean amount of potential habitat and mean habitat suitability for red tree voles in 

northern spotted owl territories in which tree voles were found in owl pellets (tree vole) versus 

spotted owl territories in which tree voles were not found in pellets (no tree vole). Error bars indicate 

95-percent confidence intervals.

Summer fog was the 

most important abiotic 

variable, followed by 

summer maximum 

temperature, average 

annual precipitation, 

and solar radiation.
69

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

y = 0.4425x - 2.3366

R2 = 0.2974

0

10

20

30

40

50

60

0 10 20 30 40 50 60

Mean habitat suitability

A

y = 0.2378x + 0.6675

R2 = 0.255

0

20

40

60

80

100

0 20 40 60 80 100

Red tree voles in diet (percent) Red tree voles in diet (percent)

Suitable habitat (percent)

B

Figure 3-5—Linear correlations between percentage of red tree voles in diets of northern spotted 

owls (percentage of prey numbers) and mean habitat suitability within the owl territories in which 

pellets were collected (A), and the percentage of potential habitat within owl territories (B). Owl 

territories were defined as the area within 1900 m of the owl nest site or center of activity.
70

GENERAL TECHNICAL REPORT PNW-GTR-948

Based on the summary statistic maps produced during bootstrapping, we 

estimated that there was a total of 1.6 million ha of red tree vole habitat within the 

range of the red tree vole as of 2006–2007 (fig. 3-6). Of this, about 1.1 million ha 

occurred on federal lands (Forest Service, BLM, and National Park Service), and 

0.5 million ha was on nonfederal lands (state, county, or private). Of the 1.1 million 

ha of habitat on federal lands, at least 59 percent was in reserve land-use allocations 

designated in the NWFP (USDA and USDI 1994). We could not estimate the total 

amount of tree vole habitat in NWFP reserves because Riparian Reserve allocations 

designated in the NWFP were never mapped. Aside from a few state parks, none of 

the 0.5 million ha of red tree vole habitat on nonfederal lands had any restrictions 

on harvest to protect tree voles.

The majority of potential tree vole habitat was located in the Cascade Mountains 

Modeling Region (fig. 3-6). In this modeling region, potential habitat was concentrated 

on federal lands in the central Cascades in eastern Lane and Douglas Counties. In the 

Cascade Mountains north of Lane County potential habitat was concentrated along the 

major river valleys of the Santiam, Clackamas, and Bull Run Rivers and their tributaries in Marion and Linn Counties. These concentrations of potential habitat appeared 

to be somewhat isolated from each other except where the headwaters converged 

between river drainages (fig. 3-6). South of the Rogue River in Jackson County, our 

models predicted little potential habitat in the Cascades Monitoring Region (fig. 3-6).

In the Klamath Mountains Modeling Region, potential tree vole habitat 

appeared to be fairly well distributed from north to south, but occurred in smaller 

blocks and patches than in the Cascade Mountains Modeling Region (fig. 3-6). This 

was expected because of the checkerboard pattern of land ownership, where squaremile sections of private land alternated with square-mile sections managed by the 

Bureau of Land Management. The largest, most contiguous area of potential habitat 

in the Klamath Modeling Region occurred in the forests separating the Umpqua and 

Rogue Valleys in Douglas and Josephine Counties (fig. 3-6). The small amount of 

potential habitat in Jackson County was mainly located north of the Rogue River 

and west of the Applegate River (fig. 3-6). Although the model predicted a large area 

of potential habitat in western Siskiyou County in California (fig. 3-6), no tree voles 

have been documented in that area, despite numerous surveys (Dunk and Hawley 

2009, chapter 1). Thus, that area appears to be outside the range of the red tree vole. 

Potential habitat within the two coastal modeling regions mostly occurred on 

BLM and Forest Service lands (fig. 3-7). Although our models predicted large areas 

of potential habitat on the Tillamook and Clatsop State Forests in the four northernmost counties in the Oregon Coast Ranges (fig. 3-6), recent surveys indicate that 

tree voles were absent from most of those areas (Price et al. 2015, chapter 1).

Although our models 

predicted large areas 

of potential habitat 

on the Tillamook 

and Clatsop State 

Forests in the four 

northernmost counties 

in the Oregon Coast 

Ranges, recent surveys 

indicate that tree voles 

were absent from most 

of those areas.
71

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

Red Tree Vole

Potential Habitat

Class Map

Habitat modeling

region boundaries

Unsuitable

Marginal

Suitable

Highly suitable

Modeling regions

1. Cascade Mountains

2. Klamath Mountains

3. Northern Coast

4. Southern Coast

Habitat classes

0 50 100

o

Kilometers

Oregon

California

Oregon

Washington

1

3

2

4

Figure 3-6—Predicted map of habitat suitability for red tree voles based on forest conditions in 2006 (Oregon) and 

2007 (California). 
72

GENERAL TECHNICAL REPORT PNW-GTR-948

Discussion

Our habitat modeling and mapping results provide a spatial representation of potential red tree vole habitat. Although obviously related, this should not be confused 

with maps of current red tree vole distribution developed from actual vole locations 

in chapter 1. Habitat models work well for producing maps that reflect the fundamental niche of the animal, but it is the realized niche that matters most for species 

occurrence. Although our map shows where forest structure, tree-species composition, and climate-based environmental gradients combine to produce conditions 

likely to be suitable for red tree voles, the analysis did not account for other factors, 

such as the history of natural- and human-caused forest disturbances, that can have 

long-lasting effects on the distribution of an arboreal species like the red tree vole. 

For example, the absence of tree voles from most of the apparently suitable habitat 

within the Tillamook and Clatsop State Forests (Price et al. 2015) is probably the 

result of the entire area being almost completely logged or burned or both between 

1880 and 1960, leaving few refugia for tree voles, and thus few sources of nearby 

colonizers. Subsequent management of the area with a focus on thinning of young 

stands and short rotations (Wells 1999) has probably made recolonization by tree 

voles even less likely. For an arboreal species that normally disperses only tens or 

hundreds of meters from its natal site (Swingle 2005), rapid and sustained reductions in habitat quality over tens or hundreds of thousands of hectares will likely 

have very long-term consequences on distribution. 

Similarly, although our habitat models classified some of the forests of western 

Siskiyou County in northern California as potential habitat for tree voles, few vole 

nests were found in that area. Whether this was due to abiotic factors or a physical 

barrier created by high-elevation forests of true fir in the Siskiyou Mountains to the 

north and west was unclear. 

As with all models, there is considerable uncertainty regarding our map of 

potential habitat (fig. 3-7). This uncertainty comes from a variety of sources, including accuracy of the GNN data and uncertainty in the climate models that we used to 

produce maps of precipitation and temperature. Nevertheless, we think our models 

are useful for estimating the approximate distribution of red tree vole habitat within 

the millions of hectares that compose the geographic range of the red tree vole. In 

addition, our models allowed us to investigate relationships between the presence of 

tree voles and various environmental conditions. 

The absence of tree 

voles from most of the 

apparently suitable 

habitat within the 

Tillamook and Clatsop 

State Forests is 

probably the result of 

the entire area being 

almost completely 

logged or burned or 

both between 1880 

and 1960.
73

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Federal

nonreserved

Federal

reserved

All 

federal

Nonfederal Total

Hectares (thousands)

Rangewide

1000

800

600

400

200

0

Federal

nonreserved

Federal

reserved

All federal

Nonfederal

Total

Hectares (thousands)

North Coast

1000

800

600

400

200

0

Federal

nonreserved

Federal

reserved

All federal

Nonfederal

Total

Hectares (thousands)

Cascades

Hectares (thousands)

North Coast

1000

800

600

400

200

0

Federal

nonreserved

Federal

reserved

All federal

Nonfederal

Total

Hectares (thousands)

South Coast

1000

800

600

400

200

0

Federal

nonreserved

Federal

reserved

All federal

Nonfederal

Total

Hectares (thousands)

Klamath

Figure 3-7—Area estimates (means and 95-percent confidence intervals) of potential red tree vole habitat (suitable and highly suitable 

habitat classes) for the range and by modeling region.
74

GENERAL TECHNICAL REPORT PNW-GTR-948

Overall, stand structure appeared to have the greatest influence on our models, 

especially in the coastal zones. To help land managers interpret what our habitat 

classes represent on the ground, we provided mean stand attributes summarized by 

habitat classes (table 3-4). The marginal class of habitat included young forests with 

an average age of 75 years. The highest suitability classes included the oldest and 

most structurally complex forests (table 3-4). These results were not unexpected, 

given the results in chapter 1, and the fact that other researchers have found that the 

probability of red tree vole nest occurrence was positively associated with latesuccessional and old-growth forest conditions (Dunk and Hawley 2009). 

Finally, the map variables that went into producing the tree vole habitat model 

were all designed for use at large spatial scales (Ohmann and Gregory 2002). Thus, 

it is unreasonable to expect that the habitat map would perfectly match every patch 

of red tree vole habitat across the range of the species. However, as light detection 

and ranging data (LiDAR) (Dubayah and Drake 2000) become increasingly available in the future, we expect that it will be possible to develop increasingly accurate 

maps of tree vole habitat.

Management Implications

Maps produced in our analysis provide context for analyzing the status and trends 

of red tree vole habitat. The habitat modeling and mapping process can be easily 

repeated using future Landsat imagery, allowing managers to continue to monitor 

habitat as it changes. Secondly, and perhaps more importantly, our habitat maps 

can be used to inform future management decisions on how to design projects to 

avoid or minimize impacts and where to focus conservation efforts for restoration and maintenance of future habitat. However, our habitat maps are meant to 

be used at the landscape scale (watershed scale or larger), and are not designed 

to identify any particular stand of habitat on the ground. They are well-suited 

Table 3-4—Mean (x ̄ ± SE) and median (in parentheses) forest stand characteristics 

for modeled red tree vole habitat classes based on forest inventory plot data

Habitat class

Density of large 

conifers per haa

Diameter 

diversity index

Percentage of 

conifer cover Stand age 

Years

Unsuitable 6.8 ± 0.4 (0) 3.7 ± 0.1 (3.2) 51.9 ± 0.9 (58) 58.6 ± 1.9 (46)

Marginal 13.3 ± 1.1 (3) 4.9± 0.1 (5.2) 66.8 ± 1.1 72) 75.3 ± 4.6 (56)

Suitable 24.3 ± 1.5 (19) 6.0 ± 0.1 (6.0) 71.5 ± 1.0 (76) 91.8 ± 6.5 (66)

Highly suitable 34.2 ± 1.6 (30) 6.6 ± 0.1 (6.5) 69.8 ± 1.0 (73) 95.4 ± 5.7 (82)

a

 Conifers ≥75 cm diameter-at-breast-height (dbh).

The highest suitability 

classes included 

the oldest and most 

structurally complex 

forests. These results 

were not unexpected 

and the fact that other 

researchers have found 

that the probability 

of red tree vole nest 

occurrence was 

positively associated 

with late-successional 

and old-growth forest 

conditions.
75

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

for illustrating current concentrations of potential habitat on the landscape, and 

connectivity among these areas. These maps are similar in quality and accuracy 

to maps developed for monitoring habitat for northern spotted owls (Davis et al. 

2011, Lint 2005) and marbled murrelets (Huff et al.2006, Raphael et al. 2011). 

When the NWFP Effectiveness Monitoring Program was developed, it included a 

potential module for “survey and manage species” that included the red tree vole 

(Mulder et al. 1999). Based on our models, we can now begin to monitor habitat 

for this arboreal species, providing land managers and regulatory agencies with 

useful maps and stand structure information for improving forest management and 

conservation of the species.

Models like ours will help managers address other species of concern, especially in cases where habitat suitability maps can be used to estimate species 

population dynamics and interactions. For example, the NWFP Effectiveness 

Monitoring Program has sponsored a series of rangewide demographic metaanalyses to monitor population trends of northern spotted owls (Anthony et al. 

2006, Dugger et al. 2016, Forsman et al. 2011). A nascent feature of the spotted 

owl meta-analyses has been to incorporate covariates to model habitat and climate 

factors that may influence demography. Climate has been considered a surrogate 

for modeling population dynamics of some species of spotted owl prey, but links 

between diets of spotted owls and prey population dynamics are not well documented. Habitat suitability models for northern spotted owl prey such as red tree 

voles, northern flying squirrels (Glaucomys sabrinus), and wood rats (Neotoma 

fuscipes, N. cinerea), could be incorporated into predictive models for spotted owl 

diets which in turn may have utility in developing covariates for analyses of the 

demographic performance of spotted owls. These methods would provide natural 

resource managers with a powerful tool to better address the needs of species of 

concern and address broader issues of ecosystem management. 
76

GENERAL TECHNICAL REPORT PNW-GTR-948
77

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

Chapter 4: Long-Term Trends in Habitat and 

Geographic Distribution of Tree Voles in Oregon, 

1914−2006

Introduction

In previous chapters, we used field data, specimen records, and habitat models to 

describe the distribution and habitat of red tree voles (Arborimus longicaudus) 

and Sonoma tree voles (A. pomo). In this chapter, we use maps from 1914, 1936, 

and 2006 to describe how the distribution and extent of potential red tree vole 

habitat has changed in western Oregon during the last century. Our objective was 

to develop a better understanding of the history of habitat change and its potential 

effect on the distribution of tree voles and to help managers and policy makers 

understand why the red tree vole was listed as a species of special management 

concern in the Northwest Forest Plan (USDA and USDI 1994) and why the U.S. 

Fish and Wildlife Service concluded that the red tree vole warranted listing under 

the Endangered Species Act (USFWS 2011). This retrospective analysis is an 

important first step in understanding the extent of changes that have transformed 

the landscape of the Pacific Northwest during the last century.

Methods

The oldest forest map that we used to assess potential vole habitat was compiled 

in 1911−1913 and published by the Oregon State Board of Forestry (1914). This 

map was prepared under the direction of Francis Elliott, the State Forester of 

Oregon, and showed the location of lands covered with merchantable timber, 

young forests, harvested areas, areas covered with brush, recently burned areas, 

and land used primarily for agriculture and grazing. The 1914 map was based on 

examination of county records, followed by field reconnaissance and mapping 

surveys conducted by township. The minimum mapping unit was not specified in 

the instructions to surveyors; however, the minimum mapping unit polygon size 

in the digitized version of this map was 15 ha (http://www.oregon.gov/DAS/CIO/

GEO/pages/alphalist.aspx#f).

We used a subset of the “merchantable timber” classification from the 1914 map 

to represent potential tree vole habitat in 1914. The instructions given to surveyors 

for mapping merchantable timber stated that, “Land bearing merchantable timber 

will, in the main, consist of areas covered with virgin timber” (fig. 4-1), which 

included both old- and “second-growth” forests (Elliott 1912: 65–66). Areas in 

which less than a third of the merchantable timber had been removed by fire or 

partial harvest were also classified as merchantable timber. The mapping instructions further stated that, “In determining whether or not a stand is merchantable, 

The oldest forest 

map that we used to 

assess potential vole 

habitat was compiled 

in 1911−1913 and 

published by the 

Oregon State Board of 

Forestry.
78

GENERAL TECHNICAL REPORT PNW-GTR-948

the size of the timber should be the only 

criterion. Even though the timber on a 

tract will be inaccessible for years to 

come, it should be considered merchantable if it has attained sawlog or piling 

size.” At that time, Douglas-fir piling 

dimensions had butt-end diameters of 33 

to 43 cm, stripped clean of bark (Cline 

and Knapp 1912). The minimum diameter 

for merchantable logs was 41 cm beneath 

the bark (Cline and Knapp 1912). We 

further restricted the merchantable timber 

class in the 1914 map to exclude forest 

types not used by tree voles, including 

ponderosa pine, lodgepole pine, mixed 

pine, coast redwoods, and high-elevation 

subalpine forests of Pacific silver fir, 

mountain hemlock, subalpine fir, and 

Figure 4-1—A “virgin” forest of old-growth Douglas-fir in western Oregon, circa 1910 Photograph 

from Elliot (1912: 10). 

Figure 4-2—Old-growth Douglasfir near the Columbia River, circa 

1930. Photograph from Andrews 

and Cowlin (1940: 3).
79

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

Englemann spruce. These forest cover types were not specifically identified in the 

1914 map, but were excluded by masking areas that were identified as those forest 

types in a mapping exercise conducted in 1930s (Andrews and Cowlin 1940). 

Our second map of potential habitat was based on a forest map compiled by 

the U.S. Forest Service Pacific Northwest Forest and Range Experiment Station in 

1936 (Andrews and Cowlin 1940). This map was based on aerial photos, county 

records, and field reconnaissance, and had slightly better spatial resolution than 

the 1914 map. Surveyors were told to map forest patches ≥16 ha, but were given 

liberty to map patches as small as 8 ha, if it did not slow progress (Andrews and 

Cowlin 1940). The digitized geographic information systems (GIS) version of this 

map (Harrington 2003) had a few polygons that were smaller than 8 ha, but for our 

purposes, we only used polygons that were ≥15 ha to approximate the minimum 

mapping unit of the 1914 map. From the 1936 map, we identified potential tree vole 

habitat as areas mapped as old-growth (fig. 4-2) or large second-growth Douglas-fir, 

Sitka spruce, or western hemlock (table 4-1; Andrews and Cowlin 1934). 

Our third habitat map was the 2006 map of potential tree vole habitat described 

in chapter 3. This map, which had a spatial resolution of 1 ha, included forested 

stands that averaged >80 years of age and primarily consisted of Douglas-fir trees 

that were >51 cm diameter-at-breast-height (dbh). To make this map comparable to 

the hand-drawn maps from 1914 and 1936, we used GIS filtering and smoothing 

techniques to remove small isolated pixels of habitat and produce a habitat map 

with a minimum mapping unit of 15 ha.

Table 4-1—Forest classifications used to map potential red tree vole habitat 

based on the digitized version of the 1936 forest habitat map of western Oregon 

(Andrews and Cowlin 1936)

Forest type Definition

Old-growth Douglas-fir Forest with 60 percent by volume of Douglas-fir where the 

major part of the volume was in trees >102 cm diameter-atbreast-height (dbh). Also included what was termed “small 

old growth” where the major part of the volume was in 

slower growing trees 51−102 cm dbh, mainly occurring in 

the Cascade Mountains.

Large “second-growth” 

Douglas-fir

Forest with 60 percent by volume of Douglas-fir where the 

majority of the volume was in trees 51−102 cm dbh. Mostly 

stands that were between 90–160 years old.

Large Sitka spruce or 

western hemlock

Forest with 50 percent by volume of Sitka spruce or western 

hemlock in which most of the volume was in Sitka spruce 

>61 cm dbh or western hemlock >51 cm dbh. Rarely in 

pure stands; usually in mixture with Douglas-fir, western 

redcedar, or true fir.
80

GENERAL TECHNICAL REPORT PNW-GTR-948

We used the 1914, 1936, and 2006 forest cover maps to manually delineate in 

GIS the potential geographic distribution of red tree voles in Oregon at each time 

step. We summarized changes in potential habitat and red tree vole distribution for 

the entire range in Oregon and also by the geographic subregions defined in chapter 

1 (fig. 1-1). Means are reported along with  ̄ x ± 95 percent confidence intervals.

Results

Change in Potential Habitat

We estimated that the total amount of potential tree vole habitat present in Oregon 

in 1914 was 3.3 million ha or 62 percent of the 5.3 million ha of forested area 

capable of developing into potential tree vole habitat (fig. 4-3). At that time, much of 

the potential habitat was distributed in a relatively contiguous “mosaic” that covered most of the western Cascades and much of the Klamath Mountains (fig. 4-3). 

The mean size of potential tree vole habitat patches in 1914 was 12 900 ± 9800 ha. 

By 1936, the estimated amount of potential tree vole habitat had declined to 2.8 

million ha, or 53 percent of the forested area capable of developing into potential 

tree vole habitat (fig. 4-3). The decline was due primarily to harvest and to the 

1933 Tillamook Burn, which incinerated slightly over 99 000 ha (10 percent) of 

forest land in the North Coast Subregion (Morris 1934, 1936). As a result of habitat 

fragmentation from timber harvest and fire, the mean size of potential habitat 

patches declined to 4900 ± 3800 ha, a reduction of more than 62 percent in a span 

of 22 years. Despite the considerable reduction in mean patch size of potential 

vole habitat, however, there were still many areas where habitat occurred as large 

contiguous mosaics. 

By 2006, we estimated that 22 percent (1.2 million ha) of the area capable of 

developing into potential tree vole habitat in western Oregon was still covered 

by potential habitat (fig. 4-3). This amounted to a 65-percent overall reduction in 

the area of potential tree vole habitat between 1914 and 2006 (fig. 4-4). The 1.2 

million ha of potential vole habitat that was present in 2006 included 819 000 ha 

that was classified as potential habitat in 1914 plus 342 000 ha that had developed 

into potential habitat since 1914. The latter areas mostly consisted of mature 

forests that had regenerated on areas burned in large wildfires between 1840 and 

1940. The loss of potential vole habitat was accompanied by a 98 percent reduction in the average size of the remaining patches of potential habitat, from 12 900 

± 9800 ha in 1914 to 240 ± 50 ha in 2006. In other words, the areas of potential 

vole habitat changed from the dominant forest type on the landscape in 1914 to a 

highly fragmented network of smaller patches within a mosaic of predominantly 

young forests by 2006 (fig. 4-3).

We used the 1914, 1936, 

and 2006 forest cover 

maps to manually 

delineate in GIS the 

potential geographic 

distribution of red tree 

voles in Oregon at each 

time step.
81

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

0 100 200

Kilometers

Potential habitat (thousand hectares)

Potential habitat (thousand hectares)

Potential habitat (thousand hectares)

4,000

3,000

2,000

400

300

200

100

0

1914 1936

Patch size classes (in hectares)

1 >1 to 5 >5 to 25 >25 to 50 >50

2006

o

NC

NC

4,000

3,000

2,000

400

300

200

100

0

4,000

3,000

2,000

400

300

200

100

0

CC

SC

IS

ECM

CCM

NCM

Figure 4-3—Estimated distribution of potential red tree vole habitat in Oregon in 1914, 1936, and 2006. Subregions were North Coast 

(NC), Central Coast (CC), South Coast (SC), Interior Southwest (IS), Central Cascades (CCM), North Cascades (NCM), and East 

Cascades (ECM).
82

GENERAL TECHNICAL REPORT PNW-GTR-948

Estimated Effect on the Geographic Distribution of Tree Voles

Based on the distribution of potential habitat and historical records of red tree 

voles, we estimated that the rangewide geographic distribution of red tree voles 

in 1914 included 5.3 million ha in Oregon, mostly west of the crest of the Cascade Mountains, but with a small extension east of the crest in the Hood River 

basin (fig. 4-3). The Applegate River and the upper reaches of the Rogue River 

largely defined the edge of the range in southern Oregon. We estimated that the 

geographic distribution of the vole covered 4.1 million ha by 2006, a 23-percent 

reduction since 1914 (fig. 4-5). We attributed this reduction to habitat loss and 

probable extirpation of tree voles in portions of the historical geographic range. 

The largest estimated range contractions were 80 percent in the North Coast 

Subregion and 73 percent in the North Cascades Subregion, which experienced 

large decreases in habitat. (fig. 4-5).

0

10

20

30

40

50

60

70

80

Forest with habitat (percent)

1914

1936

2006

North Coast

Central Coast

South Coast

North Cascades

Central Cascades

East Cascades

Oregon

Interior Southwest

Figure 4-4—Estimated percentage of habitat capable lands in western Oregon covered by potential habitat for red tree 

voles in 1914, 1936, and 2006. “Habitat capable lands” refers to lands capable of producing habitat for red tree voles. 
83

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

COOS

DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY

JACKSON

CLATSOP

COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

MULTNOMAH

CLACKAMAS

MARION

LINN

COOS

DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY

JACKSON

CLATSOP

COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

MULTNOMAH

CLACKAMAS

MARION

LINN

COOS

DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY

JACKSON

CLATSOP

COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

MULTNOMAH

CLACKAMAS

MARION

LINN

COOS

DOUGLAS

YAMHILL

LINCOLN

LANE

CURRY JACKSON

CLATSOP

COLUMBIA

WASHINGTON

TILLAMOOK

BENTON

POLK

MULTNOMAH

CLACKAMAS

MARION

LINN

Historical distribution

Current distribution

HOOD

RIVER

0 50 100

Kilometers

o

Oregon

California

Rogue River Rogue River Middle Fork

Applegate River

JOSEPHINE

Rogue River

Siuslaw R.

Willamette River

Nestucca R.Nestucca R.

Cascade Head

Cape Meares

Cape Falcon

Tillamook Head

Cape Lookout

Figure 4-5—Historical (1914) and current (2006) estimates of red tree vole distribution based on species locations and modeled 

habitat maps.
84

GENERAL TECHNICAL REPORT PNW-GTR-948

Discussion

Based on our estimates of the amount of potential red tree vole habitat, as modeled 

in chapter 3, and the amount of potential habitat estimated from the 1914 and 1936 

geographic distribution maps, we concluded that red tree voles probably had a much 

larger range in the early 19th century than in 2006 (fig. 4-5). Despite a series of very 

large wildfires that occurred between 1840 and 1902, much of the Coast Ranges and 

western Cascades were still covered by extensive areas of contiguous old forest in 

1914 (fig. 4-3). At that time, industrial timber harvesting was in its early stages in 

western Oregon but the rate of harvesting was steadily increasing and there were 

already large areas adjacent to the Columbia River that had been clearcut (fig. 1-6). 

Evidence of forest decline in Oregon was observed as early as 1909, when Kellogg (1909) estimated that old forests had already declined by 12 percent and were 

being cut at a rate that was three times faster than the rate of replacement. A little 

over a decade later, Greeley (1925) reported that forests in western Oregon were 

considerably more diminished and fragmented than in the previous century. Shortly 

thereafter, Peavy (1929: 17) predicted that old forests on private lands in Oregon 

would be “...approaching exhaustion in twenty-five years, and considerable inroads 

will have been made in national forest stumpage.” For the time of Peavy’s prediction, 

we estimated that 48 percent of potential tree vole habitat in Oregon was on private 

lands. Despite the obvious economic implications of these trends, potential impacts 

on wildlife were not mentioned until Merriam (1938: 104) noted that forest depletion 

could lead to “...destruction of, or injury to, scenic features and wild life habitats.” 

By 1936, the amount of old forest cover had declined by about 14 percent and 

larger patches were shrinking and being subdivided by wildfires and a steadily 

increasing footprint of clearcut harvest. However, there were still, extensive stands 

of old-growth Douglas fir covering the foothills and lower slopes of the Cascades for 

almost the entire length of the state of Oregon (Andrews and Cowlin 1940). In most 

of the Coast Ranges of Oregon, large areas of old Douglas-fir forests were still intermixed with extensive areas of young forest, but much of the old forest in the North 

Coast Subregion had been removed by timber harvest or by the 1933 Tillamook 

Burn (fig. 1-6) (Andrews and Cowlin 1940). Harvest rates of Douglas-fir forests 

continued to exceed growth rates. In their summary findings Andrews and Cowlin 

(1940: 1) wrote, “The major forest problem in the Douglas-fir region is the necessity 

for instituting a system of managing old-growth forests for continuous production. 

This means that clearcutting over vast areas, which has resulted in large areas of 

nonstocked harvested land, must be halted.” They advised a shift to single tree or a 

small group-selection forest management (Andrews and Cowlin 1940). Around that 

same time there was a brief shift from clearcuts to selective cutting on federal lands 

By 1936, the amount 

of old forest cover 

had declined by 

about 14 percent 

and larger patches 

were shrinking and 

being subdivided by 

wildfires and a steadily 

increasing footprint of 

clearcut harvest.
85

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

(Kirkland and Brandstrom 1936), but this shift was largely abandoned by 1950 in 

favor of the old paradigm of harvesting with clearcuts (Curtis 1998, Munger 1950). 

By 1952, timber harvesting had peaked on private lands in western Oregon 

(Wall 1972) and old forests on private timberlands were becoming increasingly 

rare. Meanwhile, the rate of harvest of old forests on public forests was beginning 

to increase markedly (Wall 1972), and fragmentation of the remaining areas of old 

forest was becoming a matter of concern (Huff et al. 1992, USDA and USDI 2000). 

Peavy’s predictions in 1929 proved to be remarkably prescient. 

Management Implications

Although the amount of potential tree vole habitat has been greatly reduced during the 

last century, tree voles in Oregon currently receive considerable protection because of 

restrictions on harvest of old forests on reserved federal forest lands (USDA and USDI 

1994). As long as those restrictions remain in effect, it is likely that red tree voles will 

continue to occupy extensive areas of old forest on federal lands in western Oregon. 

The situation on nonfederal lands is far less certain because most tree vole habitat 

on private and state lands has already been harvested or burned at least once, and there 

is no mandate to retain or produce extensive areas of old forest on nonfederal lands. 

Where there is little federal land, the persistence of the species will depend primarily 

on forest practices on private and state lands. The Oregon Forest Practices Act does 

not require state or private landowners to protect red tree voles or their nests, even if it 

is known that tree voles are present (http://www.oregon.gov/ODF/privateforests/pages/

fpaguidance.aspx). There is also no requirement that state or private landowners survey 

areas prior to harvest to determine if red tree voles are present. Given this situation, it is 

reasonable to assume that red tree voles in Oregon will eventually become rare or absent 

on most state and private forest lands, which has already occurred in the northern Coast 

Ranges. However, there are a few examples that make us hopeful that at least some landowners will try to reverse this trend. For example, the Oregon State University School 

of Forestry has continued to protect some areas of mature forest on the McDonald-Dunn 

Research Forest near Corvallis, Oregon, and tree voles continue to occupy some of 

those old forests and some adjacent young forests (see chapter 1). There are also other 

examples in which municipal watersheds owned by the cities of Corvallis and Portland 

are being managed on longer rotations and are still inhabited by red tree voles. These 

examples demonstrate that it is possible to retain tree voles in managed landscapes, 

albeit not without some cost in terms of reduced timber production. In addition, managers should not lose sight of the fact that management that is designed to provide habitat 

for tree voles will likely provide habitat for many other species as well, especially 

species that thrive in forests with high canopy closure, large trees, and trees with cavities 

and other structural features that provide support for arboreal nests or den sites.

Although the amount 

of potential tree vole 

habitat has been greatly 

reduced during the 

last century, tree voles 

in Oregon currently 

receive considerable 

protection because 

of restrictions on 

harvest of old forests 

on reserved federal 

forest lands. As long 

as those restrictions 

remain in effect, it is 

likely that red tree voles 

will continue to occupy 

extensive areas of old 

forest on federal lands 

in western Oregon. 

It is reasonable to 

assume that red tree 

voles in Oregon will 

eventually become 

rare or absent on 

most state and private 

forest lands, which has 

already occurred in the 

northern Coast Ranges.

It is possible to retain 

tree voles in managed 

landscapes, albeit not 

without some cost 

in terms of reduced 

timber production. 
86

GENERAL TECHNICAL REPORT PNW-GTR-948

Summary

Tree voles (Arborimus longicaudus; A. pomo) are unique arboreal arvicoline 

rodents that inhabit coniferous forests in western Oregon and northwestern California. In 1995–2013, field surveys conducted by the U.S. Forest Service and U.S. 

Bureau of Land Management produced a large amount of data on the distribution 

and relative abundance of tree voles and their nests. We used those data, plus data 

from museum specimens, owl pellets, and our own surveys to describe the current 

and historical range of tree voles in Oregon and California. We also compared the 

minimum density of tree vole nests in different forest age-classes. Our results indicate that tree voles still occur in much of their historical range, but have become 

uncommon or rare in some parts of their range where timber harvesting, large 

wildfires, or both have resulted in the almost complete conversion of old forests to 

young forests (<80 years old). In Oregon, red tree voles (A. longicaudus) primarily inhabited areas below 1000 m elevation, with occasional detections of voles or 

their nests up to 1159 m in the northern Cascades, 1475 m in the central Cascades, 

and 1585 m in the Klamath Mountains. We hypothesized that tree voles are 

restricted to lower elevations because their arboreal nests do not provide adequate 

protection from cold winter temperatures and because foraging at high elevations 

in winter may be hindered by snow- and ice-covered limbs. It is also possible that 

high-elevation conifer species do not provide adequate food for tree voles. All of 

these hypotheses are untested. Although most sources of data that we used were 

not selected randomly, we argue that the many thousands of forest stands and owl 

territories sampled were representative of conditions within the range of the red 

tree vole and accurately portrayed regional differences in the distribution and 

relative abundance of red tree voles. We were less confident that our results were 

representative of conditions within the range of the Sonoma tree vole because so 

much of the range was on private lands that had never been surveyed for tree voles.

Throughout most of their range in western Oregon and northwestern California, 

red tree voles fed primarily on the needles and twig bark of Douglas-fir (86 percent 

of 421 nests examined) and rarely grand fir (<1 percent). The main exception was in 

the comparatively narrow zone of Sitka spruce and western hemlock along the coast 

of northwestern Oregon, where red tree voles fed primarily on western hemlock, 

Sitka spruce, or both (98 percent of 54 nests examined). Sonoma tree voles fed 

primarily on Douglas-fir, but some individuals also fed on grand fir, and we found 

several nests in which Sonoma tree voles fed on introduced Monterey pine. Although 

tree voles occasionally built nests in coast redwood and western redcedar, they did 

not feed on redwood or redcedar, both of which were apparently unpalatable. 

We used climate data, red tree vole nest locations, and Landsat maps of forest 
87

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

structure and tree species composition to produce distribution models and habitat 

maps for the range of the red tree vole. Our models indicated that the most important 

biotic variables explaining the distribution of red tree voles were density of large 

conifers, diameter-diversity index, percentage of conifer cover, and combined basal 

area of conifer forage species (all positive relations). The abiotic variables that ranked 

highest were potential summer fog, maximum summer temperature, and average 

annual precipitation. Based on habitat maps produced from our models, we estimated 

that in 2007 there were approximately 1.6 million ha of red tree vole habitat, of which 

70 percent was located on federally managed lands.

Comparison of a generalized version of our 2006 habitat map from Oregon 

with historical forest maps from 1914 and 1936 indicated that the amount of tree 

vole habitat in Oregon declined by 65 percent between 1914 and 2006. This decline 

was most dramatic (80 percent) in the northern Coast Ranges where most lands 

were owned by private timber companies or the state of Oregon. Commensurate 

with this decline was a dramatic reduction in the average patch size of potential tree 

vole habitat, from 12 900 ha in 1914 to 240 ha in 2006. The majority of habitat loss 

was due to clear-cut harvesting of old forests and conversion to intensively managed young stands. However, large wildfires also removed large amounts of habitat, 

especially in the northern Coast Ranges and northern Cascade Range. Subsequent 

salvage and conversion of the burned areas to intensively managed young forests 

has maintained much of that area in unsuitable habitat conditions for tree voles. 

Based on maps of known tree vole locations, modeled habitat, and historical forest cover maps we estimated that the geographic distribution of the red tree vole in 

Oregon declined from approximately 5.3 million ha in 1914 to 4.1 million ha in 2006, 

a 23 percent reduction. We attributed this decline to habitat loss. The largest estimated range contractions were in the northern Coast Ranges and northern Cascade 

Range where most old forests on state and private lands had been converted to young 

forests. We suggest that isolation from extant tree vole populations may preclude 

eventual re-colonization of harvested or burned areas in northwestern Oregon.

Our analysis of the combined data from all sources suggests that tree voles are still 

present throughout much of their historical range, but have become rare or absent in 

some areas that have been converted to young, intensively managed forests. In western 

Oregon and northwestern California, red tree voles will likely continue to thrive in the 

extensive areas of old forest on federal lands that are currently protected by the Northwest Forest Plan (USDA and USDI 1994). Where federal lands are lacking, however, 

there is a high likelihood that tree voles will gradually disappear unless landowners 

actively manage for at least some old forests. This is especially true in the northern 

Coast Ranges of Oregon where there is little federal forest land. In California, Sonoma 

Although tree voles 

occasionally built nests 

in coast redwood and 

western redcedar, 

they did not feed on 

redwood or redcedar, 

both of which were 

apparently unpalatable.

The most important 

biotic variables 

explaining the 

distribution of red tree 

voles were density 

of large conifers, 

diameter-diversity 

index, percentage 

of conifer cover, and 

combined basal area 

of conifer forage 

species (all positive 

relations). The abiotic 

variables that ranked 

highest were potential 

summer fog, maximum 

summer temperature, 

and average annual 

precipitation.
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GENERAL TECHNICAL REPORT PNW-GTR-948

tree voles occur primarily on private and state lands, where landowners are required to 

follow state forestry regulations, but are not specifically required to protect tree voles 

or their habitat. Thus, the persistence of Sonoma tree voles in many areas is uncertain. 

However, the continued persistence of Sonoma tree voles in small tracts of forest as far 

south as Freestone and Bodega in Sonoma County, California, suggests that Sonoma 

tree voles may persist in highly fragmented forest landscapes, as long as some areas 

of tree vole habitat are retained. One mitigation measure that might reduce declines on 

private lands would be to encourage landowners to manage forests to retain some of 

the structural attributes that provide good nest structures for tree voles.

Ultimately, the persistence of both species of tree voles will depend on the 

willingness of humans to protect old forests, which provide stable, high-quality 

habitat for tree voles, and support source populations for recolonization of adjacent 

areas that have been harvested or burned. 

Acknowledgments

For giving us access to their collections, archived field notes, and correspondence we 

thank the American Museum of Natural History, California Academy of Sciences, California State University–Long Beach, Carnegie Museum of Natural History, Harvard 

University Museum of Comparative Zoology, Humboldt State University Vertebrate 

Museum, Corvallis Forestry Sciences Laboratory, Natural History Museum of Los 

Angeles County, Oregon State University Fisheries and Wildlife Mammal Collection, 

Royal Ontario Museum, San Diego Natural History Museum, Smithsonian National 

Museum of Natural History, The Field Museum of Natural History, University of 

Alaska Museum of the North, University of California–Berkeley Museum of Vertebrate 

Zoology, University of California–Davis Museum of Wildlife and Fisheries, University 

of California–Los Angeles Donald R. Dickey Museum, University of Kansas Museum 

of Natural History, University of Michigan Museum of Zoology, University of Montana 

Philip Wright Zoological Museum, University of Oregon Museum of Natural and Cultural History, University of Puget Sound James R. Slater Museum of Natural History, 

University of Washington Burke Museum of Natural History, University of Wisconsin 

Zoological Museum, and Washington State University Charles R. Connor Museum.

For allowing us to conduct surveys on their lands we thank the Georgia-Pacific 

Company, Green Diamond Resource Company, Hyla Tree Farm, Oregon Department of Forestry, Oregon Parks and Recreation Department, Shilo Timber Company, Stimson Lumber Company, Swanson-Superior Forest Products, The Nature 

Conservancy, Weyerhaeuser Company, and the cities of Corvallis, Eugene, Forest 

Grove, and Portland, Oregon. For providing us with data from their surveys we 
89

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

thank the USDA Forest Service, Bureau of Land Management, Oregon Department 

of Forestry, Oregon Department of Transportation, Northwest Ecosystem Survey 

Team, California Department of Fish and Game, Ascending the Giants, and Benton 

Forest Coalition. For collecting northern spotted owl pellets in Oregon and cleaning 

and identifying prey remains in pellets we thank Steve Ackers, Doug Barrett, Mark 

Brown, Matt Broyles, Rita Claremont, Ray Forson, Amy Ellingson, Larry Gangle, 

Scott Graham, Pete Loschl, Chad Marks-Fife, Chris McCafferty, Gary Miller, Ruth 

Miller, Gerry Mires, Jason Mowdy, Chet Ogan, Frank Oliver, Bill Otani, Ivy Otto, 

John Perkins, Amy Price, Janice Reid, Tom Snetsinger, Jim Thrailkill, Dave Wiens, 

and Joe Zisa. Lowell Diller, Katie Fehring, Stan Moore, Alan Franklin, and Kirsten 

Schmidt graciously allowed us to use their owl pellet data from California. For help 

with tree climbing and capturing voles we thank Jenny Allen, Lowell Diller, Scott 

Graham, Tim Grubert, Nick Hatch, Keith Hamm, Mark Linnell, Rich Lowell, Chad 

Marks-Fife, Katie Moriarty, Mike McDonald, Jerry Mires, Jason Mowdy, Matt 

Nixon, Amy Price, Bill Price, Josh Scharer, Stan Sovern, Megann Aitkin-Voth, Reed 

Wilson, Heather Wise, and Pat Wright. We also thank all the private contractors 

who conducted the random plot study, including Molly Alles, Wendell Bedell, Nolan 

Bowman, Matt Dunlap, Karl Gillick, Kelly Gleason, Brad Haeger, Dennis Hall, Paul 

Humphrey, Clint Jones, Daniel Juday, M. Kaye, Kalia Leen, Nancy Lozano, Dana 

Moberg, Giacomo Renzullo, Kopavi Reubens, Amy Sayre, Jim Campbell-Spickler, 

Jennifer Renzullo, Joesph Tremblay, Russell Ward, Adam Wanden, and Kyla Zaret. 

Rob Huff, Carol Hughes, and Kelli Van Norman in the USFS/BLM Interagency 

Special Status Sensitive Species Program were instrumental in helping us gain 

access to the databases in which Forest Service and BLM data on tree voles were 

stored. In addition, much of the funding for the random plot study and strategic 

surveys was provided by the USFS/BLM Interagency Special Status Sensitive Species Program. Funding and in-kind support for our work was provided by the U.S. 

Forest Service Ecological Processes and Function Program in the Pacific Northwest 

Research Station and by Oregon State University.

Pat Cunningham at the Pacific Northwest Research Station helped with statistical analyses, and we are greatly indebted to Eric Hellgen, Robert Steidl, and an 

anonymous reviewer for their detailed comments on an early draft of the manuscript. For the most part we followed their advice, but any errors are definitely our 

own. And finally, we thank Doug Bake, Percy Clifton, William Hamilton III, Chris 

Maser, Don Roberts, and Ken Walker for talking to us about the early years of tree 

vole research, and, in some cases, for letting us use their personal field notes and lab 

notes. They were truly an inspiration.
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GENERAL TECHNICAL REPORT PNW-GTR-948

Tree Species Mentioned in This Report

Common name Scientific name and authorities

Bigleaf maple Acer macrophyllum Pursh

Bishop pine Pinus muricata D. Don

California laurel Umbellularia californica (Hook. & Arn.) Nutt.

Canyon live oak Quercus chrysolepis Liebm.

Coast redwood Sequoia sempervirens (Lamb. ex D. Don) Endl.

Douglas-fir Pseudotsuga menziesii (Mirb.) Franco

Englemann spruce Picea engelmannii Parry ex Engelm.

Grand fir Abies grandis (Douglas ex D. Don) Lindl.

Incense-cedar Calocedrus decurrens Torr.) Florin

Jeffrey pine Pinus jeffreyi Balf.

Lodgepole pine Pinus. contorta Douglas ex Loudon

Monterey pine Pinus radiata D. Don

Mountain hemlock Tsuga mertensiana (Bong.) Carrière

Noble fir Abies procera Rehder

Oak Quercus spp.

Oregon white oak Quercus garryana Douglas ex Hook.

Pacific madrone Arbutus menziesii Pursh

Pacific silver fir Abies amabilis (Douglas ex Loudon) Douglas ex Forbes

Ponderosa pine Pinus ponderosa Lawson & C. Lawson

Shasta red fir Abies magnifica A. Murray bis var. shastensis Lemmon

Sitka spruce Picea sitchensis (Bong.) Carrière

Subalpine fir Abies lasiocarpa (Hook.) Nutt.

Sugar pine Pinus lambertiana Douglas

Tanoak Notholithocarpus densiflorus (Hook. & Arn.) P.S. Manos, C.H. Cannon, & S.H. Oh

True fir Abies spp.

Western hemlock Tsuga heterophylla (Raf.) Sarg.

Western redcedar Thuja plicata Donn ex D. Don

Western white pine Pinus monticola Douglas ex D. Don

White fir Abies concolor (Gord. & Glend.) Lindl. ex Hildebr.

Whitbark pine Pinus albicaulis Engelm

Yellow-cedar Cupressis nootkatensis D. Don
91

Tree Voles: Distribution and Habitat Relationships Based on Recent and Historical Studies, Habitat Models, and Vegetation Change 

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Appendix 1

Field notes used to document the historical and current distribution of red tree voles and Sonoma tree voles.

Author Year Location of notes

McLellan, J. Ellis 1894 Smithsonian Institution Manuscript Collection (USNM)

Camp, Charles L. 1913 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Shelton, Alfred C. 1913 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Stone, George 1913 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Taylor, Walter P. 1913 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Bailey, Vernon O. 1914 Smithsonian Institution Manuscript Collection (USNM)

Shelton, Alfred C. 1914 University of Oregon Natural and Cultural History Museum (UOMNH)

Mailliard, Joseph 1921–1926 California Academy of Sciences (CAS)

Benson, Seth B. 1930–1956 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Lamb, Charles T. 1932 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Watson, H. C. 1932 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Behle, William H. 1933 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Hooper, Emmett T. 1936 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Johnson, David H. 1936 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Davis, William B. 1936–1937 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Fisher, Harvey I. 1942 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Miller, Alden H. 1942 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Russell, Ward C. 1942 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Storer, Robert W. 1944 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Jollie, Malcom 1945 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Koford, Mary 1949 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Pearson, Oliver P. 1949 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Brock, Elbert M. 1954–1956 University of California–Berkeley Museum of Vertebrate Zoology (MVZ)

Johnson, Murray L. 1957–1985 University of Washington Burke Museum of Natural History(UWBM)

Hamilton, William J., III 1956−1959 University of Puget Sound Slater Museum of Natural History (PSM)

Roberts, Don 1956−1959 University of Puget Sound Slater Museum of Natural History (PSM)

Maser, Chris 1967–1974 University of Washington Burke Museum of Natural History (UWBM

Vrieze, John M. 1979 Humboldt State University Vertebrate Museum (HSU)

Gannon, William T. 1981 Humboldt State University Vertebrate Museum (HSU)

Webb, Mike G. 1981 Humboldt State University Vertebrate Museum (HSU)

Murray, Michael A. 1993 Humboldt State University Vertebrate Museum (HSU)

Hayes, John P. 1995 Forestry Sciences Laboratory, Corvallis, Oregon
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Appendix 2

Number of specimens of red tree voles (ARLO) and Sonoma tree voles (ARPO) in archived collections as 

of 2012. Of the 35 museums with tree voles, we visited 25 (indicated by asterisks) to examine specimens.

Institution ARLO ARPO

Academy of Natural Sciences of Drexel University (ANSP) 0 1

American Museum of Natural History (AMNH)* 21 12

Brigham Young University Bean Life Science Museum (BYU) 2 0

California Academy of Sciences (CAS)* 0 31a

California State University Long Beach (CSULB)* 0 2

Carnegie Museum of Natural History (CM)* 0 11

Cornell University Museum of Vertebrates (CUMV) 0 1

Corvallis Forestry Sciences Laboratory, Oregon (CFSL)* 38 0

Harvard University Museum of Comparative Zoology (MCZ)* 0 7

Humboldt State University Vertebrate Museum (HSU)* 12 76

Indiana State University Department of Life Sciences (ISUVC) 1 0

Kansas University Natural History Museum (KU)* 26 8

Michigan State University Science and Culture Museum (MSUM) 1 1

Museum of Texas Tech University (TTU) 3 0

Natural History Museum of Los Angeles County (LACM)* 3 14

Oregon State University Fisheries and Wildlife Collection (OSUFW)* 99a 1

Redwood Forestry Sciences Laboratory, California (RWSL) 1 1

Royal Ontario Museum (ROM)* 6 2

San Diego Natural History Museum (SDNHM)* 23 4

Smithsonian National Museum of Natural History (USNM)* 44 22

Texas A & M Biodiversity Research and Teaching Collections (BRTC) 0 4

The Field Museum of Natural History (FMNH)* 3 0

University of Alaska Museum of the North (UAM)* 38 0

University of California–Davis Museum of Wildlife and Fisheries (UCDAVIS)* 0 6

University of California–Los Angeles Dickey Collection (UCLA)* 1 35a

University of California–Berkeley Museum of Vertebrate Zoology (MVZ)* 5 140a

University of Florida Museum of Natural History (UF) 0 3

University of Michigan Museum of Zoology (UMMZ)* 9 5

University of Montana Zoological Museum (UMZM)* 0 2

University of New Mexico Museum of Southwestern Biology (MSB) 4 4

University of Oregon Museum of Natural and Cultural History (UOMNH)* 2a 0

University of Puget Sound Slater Museum of Natural History (PSM)* 309 324a

University of Washington Burke Museum of Natural History (UWBM)* 43 35a

University of Wisconsin Zoological Museum (UWZM)* 9 1

Washington State University Charles R. Conner Museum (CRCM)* 15 2

Totals 718 755

a

 In addition to the specimens found in museums, we confirmed 17 specimens that were lost or discarded as follows: CAS (7 ARPO), MVZ (1 

ARPO), PSM (1 ARPO), OSUFW (5 ARLO), UCLA (1 ARPO), UOMNH (1 ARLO), and UWBM (1 ARPO).
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Appendix 3

Number of red tree voles and Sonoma tree voles documented during field or 

laboratory studies, but not represented by specimens in museums. These 

records were based on field notes and data forms of collectors as well as our own 

observations and included voles that escaped during capture attempts, voles that 

escaped from captivity and voles that were captured and discarded or released.

Type of observationa Red tree vole Sonoma tree vole

Vole seen at nest but not captured 45 14

Escaped from captivity 3 4

Specimen discarded 4 42

Captured but not located in any museums 55 57

Live-trapped on the ground and released 2 0

Live-trapped at nest and released* 3 0

Captured at nest and released* 101 2

Captured at nest and radio-collared* 40 0

Total 253 119

a Observation categories indicated by asterisks were exclusively from our studies. Other categories were mostly 

documented from field notes of other observers.
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Appendix 4

The following figures show model response curves for predictor variables used in 

development of the rangewide habitat map for the red tree vole. The mean response 

of the 10 replicates is shown in red and  ̄ x ± 1 SD in blue.

Figure A4-1—Density per ha of large (≥75 cm dbh) conifers.
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Figure A4-2—Diameter diversity index.
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Figure A4-3—Percentage of conifer cover. 
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Figure A4-4—Percentage of hardwood cover. 
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Figure A4-5—Percentage of total basal area of red tree vole food-source trees (Douglas-fir, grand fir, western hemlock, and Sitka spruce). 
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Figure A4-6—Percentage of total basal area of subalpine forest tree species (Pacific silver fir, subalpine fir, noble fir, Shasta red fir, 

Yellow-cedar, Engelmann spruce, whitebark pine, and mountain hemlock). 
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Figure A4-7—Percentage of total basal area in white fir.
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Figure A4-8—Percentage of total basal area in coast redwood.
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Figure A4-9—Percentage of total basal area in pine forest tree species (lodgepole pine, Jeffrey pine, and ponderosa pine). 
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Figure A4-10—Summer fog was modeled as the difference between average summer dew point and average summer minimum temperature in the months of July and August, 2000–2005 (http://www.prism.oregonstate.edu/).
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Figure A4-11—Mean maximum temperature in the month of August, 1971–2000 (http://www.prism.oregonstate.edu/).
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Figure A4-12—Mean annual precipitation (logarithmic scale) in 1971–2000 (http://www.prism.oregonstate.edu/).

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