Small Mammal Communities in the Oregon

Coast Range

Paul Stephen Corn and R. Bruce Bury

Authors

PAUL STEPHEN CORN and R. BRUCE BURY are zoologists, U.S. Department of the Interior, Fish and Wildlife

Service, National Ecology Research Center, Fort Collins,

Colorado 80525-3400.

Abstract

We used pitfall trapping to sample small mammals in clearcut, young, mature, and old-growth forests in the Coast

Ranges of Oregon in 1984 and 1985. Our objectives were to

identify species or groups of species associated with oldgrowth forests and to identify structural components of the

habitat associated with mammal abundance. Trowbridge’s

shrews, red-backed voles, and Pacific shrews were the most

abundant species in forested stands; vagrant shrews, deer

mice, and creeping voles were most abundant in clearcuts.

Significantly more red tree voles were captured in old-growth

stands than in mature and young stands, and Pacific shrews

were significantly more abundant in mature stands than in

either young or old-growth stands. No significant differences

were found in the abundance of any species across a moisture

gradient in old-growth stands. No strong correlations were

found between habitat variables and the abundance of any

mammals. Abundance and diversity of small mammals were

greater in mature stands than in young stands, but abundance

and diversity in old-growth stands broadly overlapped both

mature and young stands. Diversity of small mammals did

not display a U-shaped curve relative to stand age (high

diversity in young and old-growth stands and low diversity

in mature stands).

Introduction

The Pacific Northwest harbors one of the richest communities of small mammals in North America. Several species are

endemic to the region, with their distributions restricted to

forests west of the Cascade Range in California, Oregon,

Washington, and British Columbia (Hagmeier and Stults

1964, Simpson 1964). These species include the Trowbridge’s

shrew, Pacific shrew, marsh shrew, shrew-mole, western

red-backed vole, creeping vole, red tree vole, and whitefooted vole (Ingles 1965, Maser and others 1981, van Zyll de

Jong 1983). Because a majority of the forests west of the

Cascade Range were old growth before logging began

(Harris 1984, Spies and Franklin 1988), a logical hypothesis

is that many of the unique small mammals of the region

would reach their greatest abundance in old-growth forests.

Early lists of vertebrates associated with old-growth forests

included several small mammals (Franklin and others 1981,

Meslow and others 1981), but data on habitat use were

scarce for most of them.

Several habitat features of Douglas-fir forests when plotted

against stand age have a U-shaped curve (high values in

young forests, low values in mature forests, and the highest

values in old-growth forests). These features include amount

241
of coarse woody debris, heterogeneity of the understory, and

plant species diversity (Spies and Franklin 1988). Because

these features (particularly coarse woody debris) may be significant biological components of the habitat of forest mammals, Spies and Franklin (1988) hypothesized that species

diversity of mammals follows the same U-shaped distribution

with forest age. Raphael (1988c) did not find this distribution

of mammals in northern California (diversity of mammals

was highest in mature and old-growth forests), but few data

existed relating species diversity to age of Douglas-fir forests

in Oregon and Washington.

The Old-Growth Program was chartered, in part, to address

the lack of information on the abundance of vertebrates and

their habitat associations (Ruggiero and Carey 1984). Pilot

studies were conducted in the Cascade Range in 1983 (Corn

and others 1988), and, in 1984, vertebrate community studies

were extended to the Coast Ranges in Oregon. The need for

studies of old growth is most acute in the Coast Ranges.

Because of fire and logging, little old growth remains (Spies

and Franklin 1988), and it is distributed in small, scattered

fragments (Harris 1984, Monthey 1984).

In this paper, we report the results of pitfall trapping of small

mammals over a large area of the Coast Ranges in 1984 and

1985. Our objectives were to:

l Determine the relative abundance and diversity of small

mammals in young, mature, and old-growth forests and

across a moisture gradient in old growth;

l Compare the abundance of small mammals to physiographic features and vegetative characteristics important for

maintaining diversity of small mammals; and

l Contrast differences in the abundance of small mammals

between old-growth forests and clearcuts as a first step in

comparing managed and natural forests.

Met hods

Study Areas

We studied 45 closed-canopy forest stands and 3 recently

clearcut stands in the Coast Ranges of Oregon (see frontispiece). Three stands were near the coast in the vicinity of

Cape Perpetua, but most stands were in the interior or on the

eastern flank (valley margin) of the Coast Ranges. Most of

the stands were south of Eugene on land managed by the

Bureau of Land Management (BLM). One stand near Drain

was on land owned by International Paper Company. Stands

north of Eugene were on BLM land, the Siuslaw National

Forest (including Cape Perpetua and Lost Creek Wilderness

Areas), or land managed by the city of Corvallis (Marys

Peak).

Stand Selection and Classification

Stands were selected initially to conform to a chronosequence

of four categories beginning with 3 clearcut stands (less than

10 years old), 8 closed-canopy young stands (40-75 years),

10 mature stands (80-120 years), and 27 old-growth stands

(150-525 years). Except for one young stand, the last three

categories were all composed of naturally regenerated forests.

Ages of stands were estimated a posteriori by increment

coring of at least five dominant Douglas-fir trees per stand

(young and mature stands), Ages of old-growth stands were

estimated from increment cores and by examining stumps in

adjacent clearcuts and roadsides (Spies and others 1988).

A moisture gradient (wet, moderate, and dry) was examined

for old-growth stands. The initial position on the moisture

gradient was determined largely by topographic position, for

example, south- or west-facing ridges were generally dry,

whereas stands on north-facing slopes were usually moist to

wet. Later, a moisture classification was made based on a

multivariate ordination of understory vegetation (Spies and

Franklin, this volume). In the Coast Ranges, this resulted in

five stands originally considered wet being reclassified as

moderate, and one stand originally considered moderate

being reclassified as dry. We used the revised classifications

in this paper.

Pitfall Trapping

We installed 36 pitfall traps, 15 m apart in a square grid, in

each stand in summer 1984. Each trap was constructed from

two number-10 cans (3.2 1 volume), stacked and joined

with duct tape (Bury and Corn 1987). A short plastic funnel

(0.45kg margarine tub with the bottom cut out) nested in the

top of the trap. Traps were buried flush with the ground and

covered with a cedar shingle that was suspended 3 to 4 cm

above the opening with twigs or small rocks. Between the

time traps were installed and trapping began and at the end

of each trapping season, traps were closed with a tight-fitting

plastic lid.

Logistics of trapping 48 stands concurrently dictated placement of pitfall grids to some extent. The near comer of each

grid was placed about 100 m from the edge of the stand.

This distance was a compromise between the need to avoid

edge effects and the need for a field crew to be able to check

the grids in five to seven stands in one day.

We opened traps during the first week in October and

trapped continuously for 50 days in 1984 and for 30 days in

1985. No water was put in traps because this has a deleterious effect on the preservation of amphibians, which were

242
also sampled with pitfall traps (Corn and Bury, this volume

b). In practice, most traps accumulated some water and most

mammals drowned. Drowning is the method recommended

by the American Society of Mammalogists (1987) when pitfall traps are used as kill traps. We checked traps about once

a week; trapped animals were removed and any water that

had accumulated was bailed out.

We determined sex and age and made standard measurements (total, tail, foot, and ear lengths, and mass) of mammals, which were then preserved whole in lo-percent formalin, or as skulls, skeletons, or skins and skulls. Specimens

were deposited in the National Museum of Natural History,

Washington, DC, where all species identifications were

verified.

Vegetation Sampling

We sampled vegetation at nine points within the pitfall grid,

with the center of each sampling plot equidistant from four

pitfall traps. We measured or estimated physiographic, coarse

woody debris, live tree, and ground-cover variables (appendix, table 6) in two nested circles. Percentage cover was

estimated visually; all other variables were direct counts or

were measured. Variables in the interior circle (5.6-m radius,

100 m2) included slope, cover by down wood, numbers of

small snags and small trees, and most ground-cover variables.

Variables in the outer circle (15-m radius, 707 m2) included

the presence or absence of water, rock outcrops, or talus; the

number of medium and large snags and trees, and cover by

midstory and canopy trees. Count variables were converted

to density (number per hectare). Because no single vegetation

measurement was directly related to a single pitfall trap, we

averaged the nine values for each variable to produce a single

value for each pitfall grid.

Statistical Analyses

All statistical analyses were done on a microcomputer using

SYSTAT. Analysis of the chronosequence was originally

intended to exclude wet and dry old-growth stands, so comparisons among young, mature, and old-growth stands would

not be influenced by the greater range of moisture conditions

in old-growth stands (Carey and Spies, this volume). Mature

and young stands had much greater variation on the moisture

gradient than expected (Spies and Franklin, this volume),

however, so only those old-growth stands that were outliers

on the moisture gradient were excluded. In the Coast Ranges,

all but two old-growth stands were’ retained in the chronosequence analyses. Analysis of the moisture gradient was

restricted to old-growth stands.

To facilitate comparisons between years and to reduce the

effect of migration onto the trap grid, we used only animals

captured during the first 32 to 34 days (the closest we could

come to 30 days, because traps were not checked daily) in

1984 (but see below). We measured abundance as the

number captured per 100 trap-nights. Analysis of the abundance of individual species depended on numbers captured.

“Common” species were captured in more than 50 percent of

the stands and with more than 50 total captures. “Rare”

species occurred in less than 50 percent of stands with less

than 50 but more than 10 captures. For some species-for

example, flying squirrels-abundance data may reflect bias

from the trapping technique rather than the actual density of

the species. Differences on the age and moisture gradients

for common species were analyzed by analysis of variance

(ANOVA) of log-transformed data (loge of abundance + 1).

We used Tukey’s honestly significant difference for unplanned multiple comparisons (Sokal and Rohlf 1981). Because of the low sample sizes, we used all captures of rare

species in both years. Differences in numbers captured among

age- and moisture-classes were tested using the G-test (log

likelihood ratio) for goodness of fit (Sokal and Rohlf 1981).

Physiographic and vegetative variables--Variables measuring percentage cover were arcsin-transformed (Sokal and

Rohlf 1981) before analysis. Count variables had large variances which were log-transformed. We computed Pearson

product-moment correlation coefficients between the abundance of common species and each physiographic and vegetation variable. For these six species, we performed multiple

regression on subsets of physiographic and vegetative variables. We first eliminated highly intercorrelated variables,

then chose variables for each regression model using a stepwise procedure with a significance level of 0.10 to add or

remove variables. For rare species, we compared mean

values of physiographic and vegetation variables between

stands where each species was present or absent. We also

performed a principal components analysis with a subset of

eight vegetation variables (table 1): LOGS (the sum of

DLOGSA, DLOGSB, and DLOGSC), LSNAG, DECSNAG,

CTREEL, MCTREE, CCTREE, FERN, AND ESHRUB.

These variables represent characteristics used in ecological

definitions of old-growth Douglas-fir forests (Franklin and

Spies 1984, Morrison 1988, Spies and Franklin 1988). The

variables were transformed but not standardized because the

scales were generally equivalent after transformation. We

used factors produced by the principal components analysis

with eigenvalues greater than 1 to examine whether the vegetation variables we measured were reflecting differences

among habitat types.

Mammal community structure-We examined the relations

among stands in small mammal fauna by using nonmetric

multidimensional scaling. By using a matrix of similarities

among stands, multidimensional scaling analysis computes

the coordinates of a set of stands in a few dimensions (usually 2 to 3), so that the distances between pairs of stands

fit as closely as possible to their measured similarities

(Wilkinson 1988). We measured similarity as the Euclidean

243
distance between pairs of stands using the abundance (number

per 100 trap-nights) of Trowbridge’s shrews, Pacific shrews,

vagrant shrews, marsh shrews, shrew-moles, and red-backed

voles. We chose these six species as most likely to have been

sampled in an unbiased manner by pitfall traps. Abundance

was not standardized, because we were interested in the

relative contributions of each species. To interpret the axes

produced by multidimensional scaling analysis, we correlated

them with the abundance of each species, total abundance

(the sum of the six species), species diversity (Berger-Parker

index, Magurran 1988), and physiographic and vegetative

variables.

We used the abundances of the six species above and the

K-MEANS procedure of SYSTAT to generate a specified

number of non-overlapping pools (clusters, see Pielou 1984)

of stands. We generated five pools because of the a priori

classification of stands into five habitat types. The stands

belonging to each pool were then plotted against the axes

generated by the multidimensional scaling analysis to see if

any patterns could be identified in the mammal community.

Results

Abundance of Small Mammals

We captured 3047 individuals of 20 species of small mammals in both years (table 1). Total numbers captured in each

year were very similar: 1514 in 1984 and 1533 in 1985. Precipitation may affect capture rates of small mammals (Bury

and Corn 1987), so we examined data from eight weather

stations in the Coast Ranges (U.S. Department of Commerce,

Climatological Data). Mean precipitation was slightly higher

in 1984 (19.9 cm) than in 1985 (16.6 cm), but patterns of

rainfall were similar in both years. The first region-wide rain

was recorded 4 October in 1984 and 7 October in 1985, and

rain was recorded almost daily in the second half of October

in both years.

Deer mice were captured more frequently in 1985 than 1984

(P < O.OOl), but no significant differences were found

between years for any other species. All further analyses

used the combined abundance (1984 + 1985) of each species.

Six common species (Trowbridge’s shrew, Pacific shrew,

shrew-mole, coast mole, western red-backed vole, and deer

mouse) had 55 to 1690 total captures (62-64 trap days). Four

other rare species (marsh shrew, vagrant shrew, red tree vole,

and flying squirrel) had 17 to 31 total captures (80 trap

days). Ten other species had fewer than 10 captures, which

was too few for meaningful analysis of differences in habitat

types. These included species not well-sampled by pitfall

traps (Townsend’s chipmunk, Douglas’ squirrel, and ermine),

species from adjacent grassland habitats (Townsend’s mole

and California vole), and species most common in riparian

habitats (white-footed vole and western jumping mouse).

Table l-Total numbers of small mammals captured by

pitfall grids in 45 forest stands in the Oregon Coast Ranges

in 1984 and 1985

Species 1984a 1985 Total

Insectivores:

Trowbridge’s shrewb

Pacific shrewb

Vagrant shrewc

Marsh shrewc

Shrew-moleb

Coast rnoleb

Townsend’s moled

Rodents:

Western red-backed voleb

Red tree volec

White-footed voled

Creeping voled

California voled

Long-tailed voled

Townsend’s voled

Deer mouseb

Western jumping moused

Northern flying squirrelc

Townsend’s chipmunkd

Douglas’ squirreld

Carnivores:

Ermined

Total (all mammals)

Number of species

896 794 1690

187 153 340

12 14 26

7 10 17

45 41 8 6

27 28 55

2 1 3

282

5

0

2

2

0

0

29

1

11

0

0

359

8

2

7

0

1

90e

4

14

4

2

641

13

9

2

1

119

5

25

4

2

6 0 6

1514 1533 3047

14 19 20

a

, Only captures from the first 32 to 34 trap days are listed.

Common species were captured in more than 50 percent of the

stands and with more than 50 total captures.

c

 Rare species occurred in less than 50 percent of stands with less

than 50 but more than 10 captures. Analyses of abundance used all

captures (50 trap days in 1984).

Abundance of species not analyzed.

e

 Trap rate was higher in 1985 than 1984 (P < 0.001).

Sixty-two percent of the Trowbridge’s shrews, 61 percent of

the Pacific shrews, and 64 percent of the western red-backed

voles captured were male. Because the home ranges of small

mammal males are usually larger than those of females

(Hawes 1977, Van Home 1981), males may have a higher

probability of encountering traps. Habitat use by small

mammals may not be constant among sex and age groups

(Van Home 1981), but our data showed little variation in the

proportions of adult male, adult female, and juvenile Trowbridge’s shrews, Pacific shrews, and western red-backed

voles among young, mature, and old-growth stands (fig. 1).

All further analyses did not differentiate among sex and age

groups.

244
Trowbridge’s shrew 

100 

% Pacific shrew 

tl IL Western red-backed vole 

100 

Young Mature Old-growth 

Habitat 

Variation with stand age-We calculated the mean abundance, relative abundance (percentage of total captures within 

a stand), and the frequency of cccorrence of the six most 

abundant species in each age-class (table 2). Only Pacific 

shrews varied significantly among stand types in abundance 

(F = 4.86, P = 0.013). This species was more abundant in 

mature stands than either old-growth (P = 0.024) or young 

(P = 0.052) stands. The two most abundant species, Trowbridge’s shrew and the western red-backed vole, were also 

more abundant in mature stands, but the differences were not 

statistically significant Frequency of occurrence was high 

for all six species in all stand tps, ranging from coast moles 

and deer mice detected in 60 percent of mature stands, to 

Trowbridge’s shrews and western red-backed voles detected 

Table 2-Mean abundyce, mean relative abundance; and 

occurrence of common small mammals In different forest types 

in the Oregon Coast Ranges 

1.660 

57.0 

100 

,256 

8.4 

96.0 

.w9 

3.3 

68.0 

.wJ 

2.1 

64.0 

2563 

21.7 

loo 

.I38 

4.6 

96.0 

(10) 

1.907 

54.2 

100 

,596 

15.3 

ml 

,079 

2.3 

70.0 

.040 

1.4 

60.0 

,741 

21.7 

10 

,053 

1.5 

60.0 

100 

.251 

10.1 

100 

,049 

1.9 

62.5 

.044 

1.9 

37.5 

,449 

17.7 

100 

,132 

5.2 

75.0 

in all stands. Relative abundance of these six species was 

similar in old-growth and young stands; species ranks in 

order of abundance were: Trowbridge’s shrew > western redbacked vole > Pacific shrew > deer moose > shrew-mole > 

coast mole. In mature stands, the. order was the same, except 

that shrew-moles were more abundant than deer mice. This 

minor variation is probably not significant, because pitfall 

traps do not sample deer mice well (Bury and Corn 1987). 

Two rare species were not distributed evenly on the chronosequence (fig. 2). All but one red tree vole were captured in 

old growth (old growth verses mature plus young: G = 9.58, 

P < 0.01). and significantly more vagrant shrews were captured in mature stands than in old-growth and young stands 

(G = 29.8, P < 0.001). Captures of flying squirrels and marsh 

shrews were evenly dishibuted among age-classes. Of nine 

creeping voles captured in forested stands, five were in 
Young + mature Old-growth 

Young MatINe Old-growth 

Age-class 

old-growth stands and four were in mature stands. Three 

white-footed voles were captured in forested stands, and one 

each in old-growth, mature, and young stands. 

Variation on the moisture gradient-Neither abundance of 

the common species (table 3) nor number of caphxes of the 

rare species (fig. 3) varied significantly across the moisture 

gradient (only seven vagrant shrews were captured in old 

growth, too few for analysis on the moisture gradient). The 

relative abundances suggest some dilferentiation of the mammal community in wet stands, however. Pacific shrews and 

shrew-moles contributed a greater percentage of captures and 

red-backed voles a lower percentage of captures in wet stands 

than in moderate or dry stands. 

Clearcuts versus old growth-We captured nine species in 

three clearcuts (F = 5.7 per stand) and 10 species in three 

adjacent old-growth stands (?= 6.0 per stand). Total abundance was also not significantly diCferent (?= 2.26 per 100 

trap-nights in old growth; X= 1.95 per 100 trap-nights in 

clearcuts), but the species composition of the small mammal 

Table Z--Mean abund$nce, mean relative abundance,” and 

occurrence of common small mammals on the moisture 

gradient in old-growth forests in the Oregon Coast Ranges 

,692 .67R 

23.8 *a* 

1”” 100 

Deermause ,117 .I67 

3.9 5.2 

92.9 100 

” iklative abundance = the percentage of captures contnhurcd h? each 

pecks in each stand. 

fauna was considerably different between clearcuts and oldgrowth stands. The four small mammals with tbe greatest 

mean relative abundance in clearcuts were vagrant shrews, 

Trowbridge’s shrews, deer mice, and creeping voles, but, in 

the three old-growth stands, the four most abundant species 

were Trowbridge’s shrews, red-backed voles, Pacific shrews, 

and shrewmoles (fig. 4). Red tree voles, marsh shrews, and 

ermines were captured in at least one old-growth stand and 

not in any clearcuts. Creeping voles, pocket gophers, and 

white-footed voles were captured in at least one clearcut and 

not in any of the three old-growth stands. White-footed voles 

and creeping voles were captured in other old-growth stands, 

however. 

Habitat Associations 

Physiographic featuresNone of the physiographic varables we measured varied among the forested stands (table 4): 

We compared the abundance of common species or the occurrence of rare species to these variables plus latitude, 

longitude, and stand age, but we observed only six weak 

associations. Abundance of Trowbridge’s shrews was weakly 

correlated with latitude (r = 0.37, P < 0.05). Abundance of 

246 
Northern flying squirrel 

100 10 i 10 

Mean relative abundance (log scale) 

Pacific shrews was weakly correlated with longitude 

(r = 0.32, P < 0.05) and negatively correlated with aspect 

(r = -0.32, P < 0.05; abundance was lower on southwestfacing slopes). Mean age of 13 stands where red tree voles 

were present was 294 years; 32 stands without red tree voles 

averaged 188 years old (F = 6.75, P = 0.013). Abundance of 

red-backed voles was 0.67 per 100 hap-nights in 39 stands 

without surface water and 0.36 per 100 trap-nights in 6 

stands with surface water (F = 4.19, P = 0.047). 

Vegetative characteristics-Only a few of the vegetation 

variables varied significantly (P < 0.05) among age-classes 

of forest stands (table 4). Small and medium-sized snags 

were most nume~oos in young stands. Densities of small and 

large coniferous trees were highest in old-growth stands, but 

medium-sized conifers were densest in young stands. Cover 

by broadleaf trees in the midstory was highest in young 

stands, but cover by conifers in the midstory was highest in 

old growth. Old-growth stands had the lowest canopy cover 

by coniferous trees. 

Abundances of common species were correlated with few of 

the vegetation variables. Trowbridge’s shrews were negatively correlated with percentage cover of class 3 and 4 down 

wood (DLOGSB: r = -0.35, P < 0.05) and cover by conifers 

in the midstory (MCI’REE; r = -0.30, P < 0.05): they were 

positively associated with cover by ferns (FEERN, r = 0.32, 

P < 0.05). Pacific shrews were correlated with the density of 

medium-sized snags (MSNAG; r = 0.30, P < 0.05) and cover 

by berry shrubs (BSHRUB; r = 0.40, P < 0.01). Coast moles 

were negatively correlated with canopy cover by broadleaf 

evergreens (CBTREE I = -0.31, P < 0.05). Western redbacked voles were negatively correlated with cow by moss 

(MOSS: r = 4.32, P < 0.05) and positively correlated with 

cover by berry shrubs 0. = 0.33, P < 0.05). Abundances of 

two species, shrew-moles and deer mice. were not significantly correlated with any vegetative variables. 

Similarly, only a few vegetative variables varied between 

stands with rare species present or absent. In the 18 stands 

where marsh shrews were captured, mean canopy cover by 

conifers (CCTRJZE) was lower (41.3 percent versus 50.4 

percent, P = O.CKl9) than in the 27 stands where they were 

not captured. Mean density of all deciduous trees and 

broadleaf evergreen trees (BTREES+BTREEM+BTREEL) 

was lower (45 per ha versus 145 per ha, P = 0.002) in 13 

stands where vagrant shrews were collected versus 32 stands 

without vagrant shrews. In 13 stands where we captured red 

tree voles, there were more large coniferous trees (CTREEL: 

34 per ha versus 17.4 per ha; P = 0.014) than in 32 stands 

where we did not capture this species. In 15 stands where 

flying squirrels were caught, mean density of large snags 

(LSNAG) was greater (9.2 per ha versus 4.9 pa ha, P = 

0.032). mean cover by fine litter (FLITTBR) was greater 

(71.6 percent versus 58.6 percent, P = O.oOS), but mean cover 

by moss (MOSS) was lower (19.2 percent versus 33.2 percent, P = 0.005) than in 30 stands without flying squirrels. 

247 
Table 4-Mean values of physiographic and vegetative variables (standard deviations in parentheses) 

measured at pitfall grids in the Oregon Coast Ranges” 

Stand type (N) 

Variable Units Old-growth (27) Mature (10) yaw (8) P 

1.03 t.62) 1.25 (.40) 1.20 (.70) 

Physiographic: 

TRASPECT 

SLOPE 

WATER 

OUTCROP 

TALUS 

Come woody debris: 

DLOGSA 

DLOGSB 

DLOGSC 

STUMP 

SSNAG 

MSNAG 

LSNAG 

DECSNAG 

Live tree: 

CTREES 

CTREEM 

CTREEL 

BTREES 

BTREEM 

BTREEL 

MDTREE 

MBTREE 

MCTREE 

CDTREE 

CBTREE 

CCTREE 

Ground cover: 

LlTDEPTH 

son. 

ROCK 

FLllTER 

MOSS 

FORB 

GRASS 

FERN 

ESHRUB 

DSHRUB 

BSHRUB 

MSHRUB 

Percent 

Percent ,esent 

Percent present 

Percentage CoVeI 1.9 (1.55) 2.3 (2.23) 1.8 (1.19) 

Percentage CoVeI 4.7 (2.65) 4.0 (3.38) 3.5 (2.10) 

Percentage CoVeI 1.5 (1.48) 1.6 (1.77) 1.4 (1.42) 

NUlllber/ha 20.6 (22.6) 61.1 (57.4) 62.5 (100.2) 

NUdXr/ha 62.1 (79.5) 68.9 (74.4) 154 (91.3) 

Numberlba 37.0 (38.0) T31 (1ZY) 146(6h3) 

Number/ha 7.2 (5.44) 6.7 (6.2) 2.9 (1.13) 

Number/ha 8.4 (16.8) 22.6 (22.7) 14.1 (19.5) 

NlUXlber/ha 531 (644) 260 (344) 81.9 (106) 

NWllkiha 271 (138) 321 (156) 501 (198) 

NUlIlberlha 32.8 (13.1) 8.0 (6.73) 4.3 (9.31) 

NLUl&XIiha 30.0 (39.3) 109 (187) 86.1 (86.0) 

Number/ha 58.9 (50.8) 30.0 (39.0) 94.0 (71.1) 

Number/ha 

Percentage ccl”.% 

Percentage CoVeI 

Percentage cover 

Percentage CoVeI 

Percentage CoVeI 

Pemntage CoVeI 

.l (.30) .3 C.99) .2 C.56) 

a.2 i9sj 4.3 (6.9b) 4.7 &Sk, 

.8 (1.61) .a (2.20) 3.9 (5.32) 

22.3 (11.1) 10.5 (13.3) 5.1 (2.54) 

.6 (1.08) .6 (1.90) 1.4 (3.27) 

.1 C.30) .1 C.231 .3 C.65) 

~~~ I ~~~I ~ ~~I 

41.4 (8.38) 52.4 (13.5) 57.9 (6.98) 

all 

Percentage co”.% 

Percentage CcYeI 

Percentage cove* 

Percentage coyer 

Percentage CoYa 

Percentage coyer 

Percentage cover 

Percentrlge ccwer 

Percentage cover 

Percentage Kwer 

Percentage Ulver 

3x.4 (i9.2j 46.1 (i2.4j 32.1 (23.0) 

22.2 0 0 

14.8 20.0 25.0 

48.2 50.0 50.0 

3.6 (2.98) 6.0 (7.74) 3.1 (1.22) 

2.2 (2.12) 3.1 (6.48) 2.1 (1.92) 

.4 (.46) 1.5 (3.98) .3 (.42) 

65.9 (11.8) 56.3 (22.91 61.2 (10.5) 

26.5 i13.4j 31.6 (24.9j 31.8 (12.4j 

4.3 (4.41) 6.4 (7.1) 3.8 (7.86) 

.4 (.62) 1.0 (1.33) .2 (.12) 

28.1 (25.5) 18.1 (27.1) 5.8 (3.74) 

23.8 (19.8j 22.2 i3i.4j 36.6 i20.4j 

7.5 (8.5) 5.5 (5.93) 7.8 (6.93) 

1.9 (3.02) 4.6 (5.19) 5.1 (9.31) 

16.4 (15.6) 9.2 (8.82) 12.1 (8.9) 

0.047 

,001 

,012 

,007 

<.cal 

,048 

<.cQl 

<.col 

Multiple regression models of abundance of common species models was low (table 5). Shrew-moles and deer mice, which 

on vegetative variables usually included the same variables did not have any significant simple correlations, both had 

that were significant in the simple correlations plus one or multiple-regression models that contained four variables, but 

two additional variables, but the predictive power of the each model accounted for only about a third of the variance 

248 
Table 5-Stepwise multiple regression of the abundance of commona

 species on vegetative variables

Species and variable Coefficient SE

Multiple SE of the

t r

2

estimate F P

Trowbridge’s shrew

constant

DLOGSB

FERN

SLOPE

LITDEPTH

MDTREE

1.124 0.126 8.902

-1.639 .408 -4.015

.272 .082 3.310

-.308 .112 -2.753

.129 .053 2.444

.313 .154 2.024

0.428 0.163 5.845

Pacific shrew

constant

DECSNAG

FERN

SHRUBb

BSHRUB

-.142 .105 -1.361

.049 .020 2.404

.203 .088 2.289

.157 .088 1.783

.480 .273 1.756

.331 .170 4.951

Shrew-mole

constant

HERB

DECSNAG

MOSS

MDTREE

Western red-backed vole

constant

BSHRUB

MOSS

TRASPECT

CTREEL

.232 .057 4.093

.355 .111 3.192

-.030 .010 -2.942

-.173 .068 -2.544

-.149 .077 -1.939

.479 .117 4.080

.909 .275 3.311

-.444 .148 -3.012

-.059 .027 -2.165

.038 .022 1.728

.324 .076 4.802

.395 .177 6.531

Deer mouse .366 .084

Constant .381 .068 5.638

DLOGSC -.949 .255 -3.722

SLOPE -.186 .060 -3.123

BSHRUB -.297 .125 -2.371

TRASPECT -.024 .013 -1.858

a

 Common species were captured in more than 50 percent of the stands and with more than 50 total captures.

5.767

<O.OOl

.002

.003

<.00l

.OOl

b

 ESHRUB+BSHRUB.

in abundance. Most of the variables that were included in the

regression models reflected ground cover at or below the

shrub layer (less than 2 m above the ground). Abundance of

Trowbridge’s and Pacific shrews appeared to be associated

with denser growth of shrubs and ferns, but the abundance of

shrew-moles was associated with herbaceous vegetation,

which indicates a more open shrub layer.

Multivariate analyses-A principal components analysis of

eight vegetation variables with no rotation of factors produced three factors with eigenvalues greater than 1.0; these

accounted for 67.6 percent of the variance. We interpret factor 1 (33.1 percent of the variance) as describing the structure of live trees; it was positively correlated with cover by

conifers in the midstory, numbers of large conifers and large

snags, and negatively correlated with cover by conifers in the

canopy. Factors 2 (19.3 percent) and 3 (15.2 percent) together accounted for only about one-third of the variance. Factor

2 appears to represent coarse woody debris. It was positively

correlated with numbers of well-decayed snags and cover by

down wood. Factor 3 was associated with the shrub layer. It

was positively correlated with cover by evergreen shrubs and

negatively correlated with cover by ferns.

Young stands differed from old-growth stands mainly on

factor 1 (fig. 5), which would be expected, because young

stands lacked large Douglas-fir trees and a well-developed

midstory layer. Most young stands had Factor 1 scores less

than zero, and most old-growth stands had scores greater

249
than zero. Factor 1 scores for mature stands, however, 

overlapped young and old-growth stands, so the three 

age-classes did not form discrete groups. 

Mammal Community Structure 

Multidimensional scaling of the similariry of 45 stands and 

K-MEANS clustering based on the abundance of six species 

of small mammals revealed differences among stands that do 

not fall in a simple gradient from young forests to old growth 

(fig. 6). The first multidimensional scaling axis (dimension 1) 

was strongly correlated with the abundance of Trowbridge’s 

shrews (r = 0.96). Pacific shrews (r = 0.60), and with the sum 

of the abundance of all six species (r = 0.93, fig. 7). The second multidimensional scaling axis (dimension 2) was strongly 

correlated with the abundance of red-backed voles (r = 0.80) 

and the Berger-Parker index of species diversity (r = 0.86, 

fig. 8). This index measures dominance (Magurran 1988), so 

in stands with a low value, Trowbridge’s shrews were a high 

proportion of captures. Stands with higher diversity indices 

had relatively fewer captures of Trowbridge’s shrews and 

greater contributions from other species. Dimensions 1 and 2 -2 -1 0 1 2 3 4 

define a gradient in the complexity of the mammal commun. 

ity. Stands with low abundance and species diversity (less 

complex) had low scores on both dimensions, and &ds 

with high abundance and species diversity (more complex) 

had high scores on both dimensions. 

Dimension 1 (abundance) 

3 

2 

1 6 

-1 

Trowbridge’s shrew 

Pacific shrew 

250 
Nonhierarchical clustering generated pool 1 containing 23 others 1984), and they were listed as a species potentially 

stands, pool 2 containing 14 stands, pool 3 containing 5 dependent on old-growth forests (Meslow and others 1981). 

stands, and two outlying pools with ‘2 and 1 stands (fig. 6). Anecdotal reports have long indicated an affinity for large 

Pools 1 and 2 orient on the gradient from lower to higher Douglas-fir trees (Bailey 1936, Howell 1926, Maser and 

complexity. Membership in pools 1 and 2 was not random others 1981), and we found greater density of large conifers 

with respect to age-class (C = 7.93, 2 df, P = 0.02). Old- in stands where we caught red tree voles. Recent searches for 

growth stands were evenly distributed between pool 1 and nests of red nee voles support the notion that old-growth 

pool 2, but seven of eight young stands were in pool 1 and trees are preferred as nest sites (Gill&erg and Carey, this 

five of six mature stands were in pool 2. The remaining four volume); Meiselman and Doyle, in press), although nests 

mature stands were in pools with either high diversity or have also been observed occasionally in young second-growth 

high abundance. trees (Carey 1989, Maser 1966). 

No strong correlations were found between dimensions 1 and 

2 and any of the physiographic or vegetation variables. Dimension 1 was weakly correlated with latitude (r = 0.32, 

P < 0.05). and dimension 2 was weakly correlated with longitude (r = 0.38, P < 0.05). 

Discussion 

Species Associated With Old-Growth Forests 

One species, the red tree vole, was significantly more abundant in old-growth forests than in young or mature forests in 

the Oregon Coast Ranges. This small, arboreal rodent was 

seldom captured on the ground until we began using large 

numbers of pitfall traps (Corn and Buy 1986). Red tree 

voles are an important prey of spotted owls (Forsman and 

The 17 red tree voles we trapped in the Coast Ranges constitute a small sample, but since 1983.46 red tree voles have 

been trapped in the Coast and Cascade Ranges of Oregon by 

old-growth researchers (this study; Corn and Bury 1986; 

Gilbert and Allwine, this volume a). Most (39) were captured 

in old-growth stands (fig. 9). and, because the trapping effort 

was about evenly split between old-growth stands and younger stands, a significant excess of captures was in old growth 

(G = 24.0,2 df, P < OKll). Raphael (1988~) captured an 

additional 19 red tree voles in pitfall traps in Douglas-fir 

forests in northwestern California. Although the difference in 

relative abundance among stand age-classes was not significant, most red tree voles were captured in stands older than 

100 years. Meiselman and Doyle (in press) located several 

nests of red nee voles in northwestern California. and a 

Young plus Mature 

clearcuts (0.23) 

(0.26) 

Oldgrowth 

(0.51) 

251 
statistically significant majority were in old-growth forests.

These results indicate that red tree voles are strongly

associated with old-growth Douglas-fir forests.

Aside from red tree voles and Pacific shrews (most abundant

in mature stands), no statistically significant relations were

found between stand age and the abundance of small mammals. Our results agree with other old-growth research from

Oregon and Washington that found few species of terrestrial

small mammals associated with older forests (Anthony and

others 1987; Corn and others 1988; Gilbert and Allwine, this

volume a; West, this volume).

The lack of strong correlations between habitat features and

mammal abundance was somewhat surprising, considering

that studies of insectivores (Hawes 1977, Terry 1981). earlier

studies from the old-growth program (Corn and others 1988),

and studies in California (Raphael 1988c, Raphael and

Barrett 1984) found several significant habitat associations.

One possibility is that by trapping only in the fall, we were

sampling populations composed of high proportions of

subadult animals (Sullivan 1979, Van Home 1981), which

might be transients in habitat of lower quality. Abundance

data, then, would give a misleading indication of habitat

quality (Sullivan 1979, Van Home 1983). Our data did not

reveal any marked differences in the proportions of subadult

Trowbridge’s and Pacific shrews and red-backed voles

among young, mature, and old-growth forests. Hawes (1977)

found that home ranges of subadult vagrant and montane

shrews in British Columbia were smaller subsets of the areas

they occupied when breeding the next spring. This finding

suggests that subadult shrews have the narrowest habitat

requirements and that trapping in the fall would reveal

important habitat associations.

A more likely explanation for finding few habitat associations is that threshold values for critical habitat features to

small mammals are exceeded in naturally regenerated forests

after the canopy is reestablished (West, this volume). Understory plant communities in Douglas-fir forests are resilient

and rapidly return to the composition found in old growth

after disturbance (Halpern 1988). In the Coast Ranges, structural features likely to be associated with terrestrial mammals

did not differ among different ages of stands. For example,

no difference was found in the Coast Ranges in the percentage cover by down wood among young, mature, and oldgrowth stands (Spies and others 1988). Different age-classes

of naturally regenerated forest represent a single habitat type

for most small mammal species. This conclusion is supported

by the observation that neither abundance nor diversity of

small mammals displayed the predicted U-shaped pattern

(Spies and Franklin 1988) when compared to stand age. No

decline occurred in abundance or diversity in mature stands

in the Cascade Range (Gilbert and Allwine, this volume a;

West, this volume). In the Coast Ranges, the trend was

opposite of the prediction; abundance and diversity of six

species of mammals were greater in mature stands. These

studies provide little support for a U-shaped pattern of diversity of small mammals.

Managed Forests

Many studies have examined the effects of logging on small

mammals in the Pacific Northwest, and they have documented major changes in the composition of the mammal community. In general, populations of deer mice, creeping voles,

vagrant shrews, and Townsend’s chipmunks increase after

logging, while red-backed voles and Trowbridge’s shrews

decline (Anthony and Morrison 1985; Corn and others 1988;

Gashwiler 1959, 1970b; Hooven and Black 1976; Raphael

1988c; Sullivan and Krebs 1980; Tevis 1956; West, this

volume). Some of these changes represent increased abundance by species adapted to open habitats, but for other

species, clearcuts may act as dispersal sinks and the increased

abundance is transitory (Sullivan 1979).

Species composition of mammal communities in clearcuts is

less predictable than that of old-growth forests. Considering

both this study and the earlier study in the Oregon Cascades

(Corn and others 1988), Trowbridge’s shrews (76 percent of

captures in forested stands) and vagrant shrews (71 percent

of captures in clearcuts) had similar relative abundances in

forests and clearcuts, respectively. But while Trowbridge’s

shrews were always the most abundant insectivore in forested stands, vagrant shrews were the most abundant insectivore in only three of six clearcuts. Abundance of creeping

voles and deer mice also varied widely among clearcuts. The

low predictability of mammal populations in clearcuts may

be related to the rapid succession occurring in the plant communities (Halpern 1988, Schoonmaker and McKee 1988),

which may generate greater variability in food resources and

microclimates than is found in closed-canopy forests.

The apparent low habitat quality and unpredictibility of

clearcuts for many mammal species means that, as naturally

regenerated forests are converted into managed forests, the

long-term survival of many species will depend on whether

managed forests provide essential habitat features. For example, modem logging practices greatly reduce both the

amount of coarse woody debris carried over into a stand after

harvest and the amount accumulated before the next harvest

(Spies and Franklin 1988, Spies and others 1988). The results

of our studies, however, provide little insight into this question. We did not investigate managed stands after closure of

the canopy, and the range of variation of habitat variables in

naturally regenerated stands is probably insufficient to make

predictions about habitats and small mammal communities in

intensively managed forests.

252
Recommendations

The studies of old-growth forests reported in this volume

have provided baseline data on the occurrence of vertebrate

species in natural Douglas-fir forests in the Pacific Northwest.

In general, however, more questions have been created than

answers supplied. We offer the following suggestions for

high-priority research in the Coast Ranges of Oregon:

Determine the abundance of red tree voles in old-growth,

mature, young, and managed forests. The data collected so

far suggest that this species may depend on old growth, but

the sample size is small. The red tree vole is probably the

most difficult small mammal in the Pacific Northwest to

study, but recently developed techniques (Gillesberg and

Carey, this volume; Meiselman and Doyle, in press) show

promise.

Compare small mammal populations in naturally regenerated

and intensively managed forests. The changes in forest structure predicted between managed and natural forests are of a

much greater magnitude than we measured in a natural sere.

Although we found few differences among different-aged

forests, the same prediction cannot be made for a comparison

of managed and natural forests. Some work along this line

has begun; more is needed.

Determine the effects of forest fragmentation on small mammal populations. We did not deal with fragmentation in this

paper, and, currently, little evidence indicates that smallmammal populations are strongly influenced by stand size

or degree of fragmentation (Raphael 1984, Rosenburg and

Raphael 1986). Few data have been collected so far on the

effects of fragmentation in western forests, however, and any

effects are likely to be severe in the Coast Ranges, where

most old growth exists as small, isolated patches (Harris

1984, Monthey 1984, Spies and Franklin 1988).

The lack of a unique community of small mammals in oldgrowth forests does not reduce the value of these habitats.

Old growth is a nonrenewable resource (Schoen and others

1981) with numerous other intrinsic assets. In the Coast

Ranges, our results suggest that the biological integrity of

isolated blocks of old growth may be enhanced if tracts of

younger, naturally regenerated forest are contiguous.

Acknowledgments

Funding was supplied by the U.S. Department of the Interior,

Bureau of Land Management, and the U.S. Department of

Agriculture, Forest Service, through cooperative agreements

between the Forest Service and the Fish and Wildlife Service.

We thank L. Benson, J. Corn, B. Fiero, A. Gillesberg,

L. Jones, R. Kuntz, P. Morrison, R. Newton, L. Rottman,

D. Smith, W. Stolzenburg, and P. Sullivan for assistance in

the field under occasionally trying conditions. We acknowledge the valuable contributions of BLM Roseburg and Salem

Districts, Siuslaw National Forest, and the Pacific Northwest

Research Station for logistical support. R. Anthony, A. Carey,

W. McComb, S. West, and an anonymous reviewer provided

valuable comments on the manuscript.

This paper is contribution 122 of the Wildlife Habitat Relationships in Western Washington and Oregon Research

Project, Pacific Northwest Research Station, USDA Forest

Service. 

253
Appendix

Table 6-Vegetative variables measured at 9 points within pitfall grids

Variable Description

Physiographic:

TRASPECT

SLOPE

WATER

TALUS

Transformed aspect (cosine transformation [NE=O, SW=2])

Percent slope

Presence or absence of open water (seeps, ponds, permanent or intermittent streams) on grid

Presence or absence of exposed talus on grid

Coarse woody debris:

DLOGSA

DLOGSB

DLOGSC

STUMP

SSNAG

MSNAG

LSNAG

DECSNAG

Percentage cover by decay class 1 and 2 down wood

Percentage cover by decay class 3 and 4 down wood

Percentage cover by decay class 5 down wood

Number of stumps per hectare

Number of small snags (<10 cm d.b.h.) per hectare

Number of medium snags (l0-50 cm d.b.h.) per hectare

Number of large snags (>50 cm d.b.h.) per hectare

Number of well-decayed (class 4 and 5) medium and large snags per hectare

Live tree:

CTREES, CTREEM, CTREEL Number of small (<l0 cm d.b.h.), medium (> 10 cm and <l m d.b.h.), and large (>1 m d.b.h.)

coniferous trees per ha

BTREES, BTREEM, BTREEL Number of broadleaf trees (same size-classes) per ha

MDTREE Percentage cover by deciduous midstory trees

MBTREE Percentage cover by broadleaf evergreen midstory trees

MCTREE Percentage cover by coniferous midstory trees

CDTREE Percentage canopy cover by deciduous trees

CBTREE Percentage canopy cover by broadleaf evergreen trees

CCTREE Percentage canopy cover by coniferous trees

Ground cover:

LITDEPTH

SOIL

ROCK

FLITTER

MOSS

HERB

GRASS

FERN

ESHRUB

DSHRUB

BSHRUB

MSHRUB

Depth (cm) of organic litter layer

Percentage cover by bare soil

Percentage cover by exposed rock

Percentage cover by fine organic litter

Percentage cover by moss

Percentage cover by forbs

Percentage cover by grasses

Percentage cover by ferns

Percentage cover by evergreen shrubs

Percentage cover by deciduous shrubs

Percentage cover by berry shrubs (Rubus spp. and Vaccinium spp.)

Percentage cover by midstory shrubs (>2 m high)

254