SMALL MAMMALS AND FOREST MANAGEMENT IN NORTHERN CALIFORNIA
By
Steven Michael Gray

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Fisheries and Wildlife – Master of Science
2014

ABSTRACT
SMALL MAMMALS AND FOREST MANAGEMENT IN NORTHERN CALIFORNIA
By
Steven Michael Gray
Limited information exists on small mammals in industrial forests of northern California, USA.
My thesis focuses on patch-level and fine-scale habitat elements that influence small mammal
communities in industrial forests of northern California. I trapped 11 small mammal species
during the summers of 2011-2013 and collected count data on a subset of those species. In
Chapter 1, I analyzed small mammal populations in 4 forest types (recent clearcuts (3-5 years
old), 10-20 year-old plantations, rotation-aged stands (60-80 years old), and Watercourse and
Lake Protection Zones) commonly found in industrial forests. I used generalized linear mixed
models (GLMM) to assess patch-level (~6.35 ha) relationships between small mammal counts
and commonly found forest types, and downed wood volume. Land cover composition of areas
surrounding trapping webs was more influential on small mammal counts than was the forest
type that contained the trapping array. Downed wood volume was positively correlated to small
mammal abundance. In Chapter 2, I examined small mammal counts in relation to fine-scale (64
m2) habitat elements surrounding trap locations. I used GLMMs and found that shrub and
downed wood cover were positively correlated with the number of individual small mammals
captured; this relationship held across multiple taxon and trap types. This study is one of the first
to be conducted on the small mammal community in industrial forests of northern California.
Results of this research provide insight on small mammal populations in industrial forests and
can inform timber management practices.

ACKNOWLEDGEMENTS

Summer funding and field accommodations for this research was provided by Sierra
Pacific Industries (SPI). Thank you to SPI employees Tom Engstrom and Brian Dotters for their
mentorship and assistance during this project. Academic year funding was provided by Michigan
State University. I would like to thank my advisor, Gary Roloff, for his continued patience,
mentorship, and guidance. Thank you to committee members Rique Campa and Scott
Winterstein for sharing their expertise and lending their support throughout this process. I am
also thankful to those who assisted with data collection including M. Block, R. Caster, B. Benson,
S. Houston, C. Brockman, K. Raby, R. Feamster, and J. Kelley. An additional thanks to the
California Department of Fish and Wildlife for reviewing their animal handling protocol with the
field crews and for lending us trapping supplies. Thank you to the Steel Bridge Community for
welcoming me with open arms and treating me like family. Lastly, I am extremely grateful to my
family and friends. They instilled in me the motivation, work ethic, and confidence to complete
this stage in my career. Thank you to my father (Michael Gray), sister (Chelsie Gray),
grandmother (Lou Ann Hart), and mother (Judith Gray) for teaching me that anything is possible
if you work hard and remain humble.

iii

TABLE OF CONTENTS

LIST OF TABLES

vi

LIST OF FIGURES

vii

INTRODUCTION
LITERATURE CITED

1
4

CHAPTER 1
7
LOCALIZED FACTORS CORRELATED WITH SMALL MAMMAL ABUNDANCES IN
INDUSTRIAL FORESTS OF NORTHERN CALIFORNIA, USA
7
Abstract
7
1.1.Introduction
8
1.2.Methods
11
1.2.1. Study Area
11
1.2.2. Experimental Design
12
1.2.3. Vegetation Sampling
14
1.2.4. Proximate Forest Classes
14
1.2.5. Data Analysis
15
1.3.Results
16
1.3.1. Vegetation and Proximate Forest Classes
16
1.3.2. Small Mammals
17
1.4.Discussion
20
1.5.Acknowledgements
24
APPENDIX
26
LITERATURE CITED
45

CHAPTER 2
53
FINE-SCALE VEGETATIVE COVER AND LAND COVER INFLUENCES ON SMALL
MAMMAL USE IN INDUSTRIAL FORESTS OF NORTHERN CALIFORNIA, USA 53
Abstract
53
2.1.Introduction
54
2.2.Methods
56
2.2.1. Study Area
56
2.2.2. Experimental Design
57
2.2.3. Vegetation Sampling
59
2.2.4. Data Analysis
60
2.3.Results
61
2.3.1. Vegetation Measures and Land Cover Category at Trap Locations
61
2.3.2. Small Mammals
62
2.4.Discussion
64

iv

2.5.Acknowledgements
APPENDIX
LITERATURE CITED

68
69
84

CONCLUSIONS
LITERATURE CITED

90
92

v

LIST OF TABLES

Table 1.1.

Candidate generalized linear mixed models used to estimate the number of
individual Peromyscus spp., California ground squirrels, Neotoma spp., and
Allen’s chipmunks in industrial forests of northern California, USA, May-August
of 2011-2013.
27

Table 1.2.

Five top-ranking generalized linear mixed models used to estimate maximum
nightly captures for Peromyscus spp., California ground squirrel, Neotoma spp.,
and Allen’s chipmunk in industrial forests of northern California, USA, MayAugust of 2011-2013. K = the number of estimated model parameters, AICc =
Akaike Information Criteria adjusted for small sample sizes, ∆AICc = difference
in AIC from top-ranking model, and w = weight of evidence.
28

Table 2.1.

Average percent cover within 64 m2 plots at individual trap locations by
vegetation and land cover category in industrial forests of northern California,
USA, May-August 2011-13.
70

Table 2.2.

Candidate generalized linear mixed models used to estimate the number of small
mammal captures at individual trap locations in industrial forests of northern
California, USA, May-August 2011-13.
72

Table 2.3.

Five top-ranking generalized linear mixed models used to estimate the number of
individual small mammals (pooled across all species), Peromyscus spp., and
Allen’s chipmunks in industrial forests of northern California, USA, May-August
2011-13. K = the number of estimated model parameters, AICc = Akaike
Information Criteria adjusted for small sample sizes, ΔAICc = difference in AIC
from top-ranking model, and w = weight of evidence.
73

Table 2.4.

Five top-ranking generalized linear mixed models used to estimate the number of
individual small mammals and California ground squirrels caught in Tomahawk
traps in industrial forests of northern California, USA, May-August 2011-13. K =
the number of estimated model parameters, AICc = Akaike Information Criteria
adjusted for small sample sizes, ΔAICc = difference in AIC from top-ranking
model, and w = weight of evidence.
75

vi

LIST OF FIGURES

Figure 1.1.

Four common forest classes in industrial forests of northern California, USA. Top
left = recent clearcuts (3-5 years old), top right = 10-20 year-old plantations,
bottom left = rotation-aged stands, bottom right = Watercourse and Lake
Protections Zones (WLPZs).
30

Figure 1.2.

Small mammal trapping web design, northern California, USA, 2011-13. 31

Figure 1.3.

Average volume (m3) of downed wood per 0.75 ha by forest class and year in
industrial forests of northern California, USA. Average (filled circle), median
(solid horizontal bar), 75th data quartiles (shaded boxes), 95% confidence
intervals (dashed lines), and extreme values (open circles) are shown.
32

Figure 1.4.

Proportion of forest classes, by forest class containing the trapping webs and year,
within a 6.35 ha buffer around small mammal trapping webs in industrial forests
of northern California, USA. Average (filled circle), median (solid horizontal bar),
75th data quartiles (shaded boxes), 95% confidence intervals (dashed lines), and
extreme values (open circles) are shown.
33

Figure 1.5.

Maximum nightly captures in forest classes containing trapping webs by small
mammal species and year in industrial forests of northern California, USA.
35

Figure 1.6.

Relationship of Peromyscus spp. counts to a) average volume (m3) of downed
wood per 0.75 ha and b) proportional area of WLPZ within 6.35 ha surrounding
the trapping web in industrial forests of northern California, USA, 2011-2013.
37

Figure 1.7.

Relationship of California ground squirrel counts to a) proportional area of 3-5 yr
within 6.35 ha surrounding the trapping web and b) average volume (m3) of
downed wood per 0.75 ha in industrial forests of northern California, USA, 20112013.
39

Figure 1.8.

Relationship of Neotoma spp. counts to proportional area of WLPZ within 6.35 ha
surrounding the trapping web in industrial forests of northern California, USA,
2011-2013.
41

Figure 1.9.

Relationship of Allen’s chipmunk counts to a) proportional area of rotation age
forest class within 6.35 ha surrounding the trapping web, b) average volume (m3)
of downed wood per 0.75 ha and c) proportional area of WLPZ within 6.35 ha
surrounding the trapping web in industrial forests of northern California, USA,
2011-2013.
42

vii

Figure 2.1.

Four common forest classes in industrial forests of northern California, USA. Top
left = recent clearcuts (3-5 years old), top right = 10-20 year-old plantations,
bottom left = rotation-aged stands, bottom right = Watercourse and Lake
Protections Zones (WLPZs).
76

Figure 2.2.

Small mammal trapping web design, northern California, USA, 2011-13. 77

Figure 2.3.

Relationship of small mammal counts to proportion of shrub within the 64m2
surrounding Sherman traps in industrial forests of northern California, USA,
2011-2013. Shaded area represents the 95% confidence limits.
78

Figure 2.4.

Relationship of all small mammal counts to a) proportion of shrub and b)
proportion of downed wood within 64m2 surrounding Tomahawk traps in
industrial forests of northern California, USA, 2011-2013. Shaded area
represents the 95% confidence limits.
79

Figure 2.5.

Relationship of Peromyscus spp. counts to proportion of shrub within 64m2
surrounding Sherman traps in industrial forests of northern California, USA,
2011-2013. Shaded area represents the 95% confidence limits.
81

Figure 2.6.

Relationship of California ground squirrel counts to the proportion of forest litter
within 64m2 surrounding Sherman traps in industrial forests of northern California,
USA, 2011-2013. Shaded area represents the 95% confidence limits.
82

Figure 2.7.

Relationship of Allen’s chipmunk counts to the proportion of shrub within 64m2
surrounding Sherman traps in industrial forests of northern California, USA,
2011-2013. Shaded area represents the 95% confidence limits.
83

viii

INTRODUCTION

The Klamath Mountain region of southern Oregon and northern California is considered a
biodiversity hot spot (Whitaker 1960; Wagner 1997; DellaSala et al. 1999). Currently, a majority
of land cover change in this region is attributed to timber harvest (Parks et al. 2005); ~25% of
timberlands in California are owned by the timber industry (Laaksonen-Craig et al. 2003). Given
the substantial presence of industrial forest management in California and growing public
demand for ecologically sound forest management, conservation of wildlife has increasingly
influenced forest practices. Some members of the forest products industry have taken a proactive
approach in conducting research and adapting forest management to balance economic viability
with conservation goals. This is exceedingly important in California where the timber industry is
a polarizing entity, however, incorporating conservation goals and adapting forest management
can improve public standing and relationships with stakeholders.
Small mammals are commonly studied in the Pacific Northwest (PNW), however,
targeted habitat management for small mammals on industrial forests primarily occurs when a
small mammal species is legislatively protected, a predator is protected that preys on small
mammals, or to mitigate small mammal impacts on forest regeneration. Small mammals are
considered important components of forest ecosystems by serving as prey and thereby
influencing the distribution and habitat use of predatory species (Carey et al. 1992). In the
Klamath Mountains, several protected predators of small mammals occur on industrial forests,
including northern spotted owl (Strix occidentalis) and Pacific fisher (Martes pennant pacifica).
In addition, small mammals provide benefits to forest ecosystems. For instance, small mammals
can regulate invertebrate populations (Buckner 1966; Carey and Johnson 1995; Elkinton et al.

1

1996; Carey and Harrington 2001), disperse fungal spores (Maser et al. 1978), and serve as
indicators of habitat suitability in managed forests (Carey and Harrington 2001; Pearce and
Venier 2005). Although research on small mammals and forest management is abundant, small
mammal response to timber harvest often varies by species and geographic region. Currently,
small mammal research in the northern California portion of the Klamath Mountains is limited.
Given the importance of small mammals to forested ecosystems and the prevalence of
industrial forests in the PNW, understanding small mammal relationships in common forest
types and habitat features in industrial forests can aid management. Data on small mammal
response to timber harvest are variable and species-specific (Zwolak 2009) and often depend on
specific timber harvest techniques, geographic location, and climate. Some studies suggest that
small mammals respond positively to clearcutting (Kirkland 1990), while others propose that
clearcutting negatively impacts biodiversity (Peterken 1996; Lust et al. 1998; Lindenmayer and
Franklin 2002; Betts et al. 2005). In addition, research on small mammals has indicated the
importance of retained habitat features, such as retention patches, downed wood, and riparian
buffers (Cross 1985; Sullivan and Sullivan 2001; Lee 2012; Cockle and Richardson 2003; Smith
and Maguire 2004).
The topic of this thesis is how small mammal communities are influenced by timber
management practices in northern California. In Chapter 1, I explored patch-level (~6.35ha)
relationships between small mammals and common forest types found on industrial forestlands. I
also assessed stand-level responses of small mammals to downed wood volume. I used
generalized linear mixed models (GLMM) to determine species-specific associations with
surrounding forest types and downed wood volume. In Chapter 2, I used GLMMs to assess the
influence of localized (64m2) land cover designation and habitat features at trap locations on

2

small mammals. Results of this study can inform future forest management and can facilitate the
incorporation of forest practices that benefit small mammal communities.

3

LITERATURE CITED

4

LITERATURE CITED

BETTS, M. G., A. W. DIAMOND, G. J. FORBES, K. FREGO, J. A. LOO, B. MATSON, M. R. ROBERTS,
M. A. VILLARD, R. WISSINK, AND L. WUEST. 2005. Plantations and biodiversity: a
comment on the debate in New Brunswick. Forestry Chronicle 81(2): 265–26.
BUCKNER, C. H. 1966. Populations and ecological relationships of shrews in tamarack bogs of
southeastern Manitoba. Journal of Mammalogy 47(2): 181-194.
CAREY, A. B., S. P. HORTON, AND B. L. BISWELL. 1992. Northern spotted owls: influence of prey
base and landscape character. Ecological Monographs 62(2): 223-250.
CAREY, A. B., AND M. L. JOHNSON. 1995. Small mammals in managed, naturally young, and oldgrowth forests. Ecological applications 5(2): 336-352.
CAREY, A. B., AND C. A. HARRINGTON. 2001. Small mammals in young forests: implications for
management for sustainability. Forest Ecology and Management 154(1): 289-309.

COCKLE, K. L., AND J. S. RICHARDSON. 2003. Do riparian buffer strips mitigate the impacts of
clearcutting on small mammals? Biological Conservation 113(1): 133-140.
Conservation 7(2): 249–260.
CROSS, S. P. 1985. Responses of small mammals to forest riparian perturbations. Riparian
ecosystems and their management: reconciling conflicting uses. Rocky Mountain Forest
and Range Experiment Station, Fort Collins, Colorado, General Technical Report RM120.
DELLASALA, D. A., S. B. REID, T. J. FREST, J. R. STRITTHOLT, AND D. M. OLSON. 1999. A global
perspective on the biodiversity of the Klamath-Siskiyou ecoregion, Natural Areas Journal,
19(4) : 300-319.
ELKINTON, J. S., W. M. HEALY, J. P. BUONACCORSI, G. H. BOETTNER, A. M. HAZZARD, AND H. R.
SMITH. 1996. Interactions among gypsy moths, white-footed mice, and acorns. Ecology
77(8): 2332-2342.
KIRKLAND JR, G. L. 1990. Patterns of initial small mammal community change after clearcutting
of temperate North American forests. Oikos 313-320.
LAAKSONEN-CRAIG, S., G. E. GOLDMAN, AND W. MCKILLOP. 2003. Forestry, forest industry, and
forest products consumption in California. Oakland, CA: University of California,
Division of Agriculture and Natural Resources.

5

LEE, S. D. 2012. Association between coarse woody debris and small mammals and
insectivores in managed forests. Journal of Ecology and Environment, 35(3), 189-194.
LINDENMAYER, D. B., AND J. F. FRANKLIN. 2002. Conserving forest biodiversity: a
comprehensive multiscaled approach. Island Press.
LUST, N., B. MUYS, B., L. NACHTERGALE. 1998. Increase of biodiversity in homogeneous Scots
pine stands by an ecologically diversified management. Biodiversity and Conservation
7(2): 249-260.
MASER, C., J. M. TRAPPE, AND R. A. NUSSBAUM. 1978. Fungal-small mammal interrelationships
with emphasis on Oregon coniferous forests. Ecology 59(4): 799-809.
PARKS, C. G., S. R. RADOSEVICH, B. A. ENDRESS, B. J. NAYLOR, D. ANZINGER, L. J. REW, B. D.
MAXWELL, AND K. A. DWIRE. 2005. Natural and land-use history of the Northwest
mountain ecoregions (USA) in relation to patterns of plant invasions. Perspectives in
Plant Ecology, Evolution and Systematics 7(3): 137-158.
PEARCE, J., AND L. VENIER. 2005. Small mammals as bioindicators of sustainable boreal forest
management. Forest ecology and management 208(1): 153-175.
PETERKEN, G. F. 1996. Natural woodland: ecology and conservation in northern temperate
regions. Cambridge University Press.
SMITH, T. G., AND C. C. MAGUIRE. 2004. Small-mammal relationships with down wood and
antelope bitterbrush in ponderosa pine forests of central Oregon. Forest Science 50(5):
711-728.
SULLIVAN, T.P., D. S. SULLIVAN. 2001. Influence of variable retention harvests on forest
ecosystems. II. Diversity and population dynamics of small mammals. Journal of Applied
Ecology 38(6): 1234–1252.
WAGNER, D. H. 1997. Klamath-Siskiyou region, California and Oregon, USA, In: Davis, S. D.,
V. H. Heywood, O. Herrera-MacBryde, J. Villa-Lobos, and A. C. Hamilton (eds),
Centres of Plant Diversity, the Americas, Vol. 3, World Wildlife Fund for Nature and
IUCN (World Conservation Union), New York, New York, USA, pp. 74-76.
WHITTAKER, R. H. 1960. Vegetation of the Siskiyou mountains, Oregon and California.
Ecological monographs, 30(3), 279-338.
ZWOLAK, R. 2009. A meta-analysis of the effects of wildfire, clearcutting, and partial harvest on
the abundance of North American small mammals. Forest Ecology and Management
258(5): 539-545.

6

CHAPTER 1
LOCALIZED FACTORS CORRELATED WITH SMALL MAMMAL ABUNDANCES IN
INDUSTRIAL FORESTS OF NORTHERN CALIFORNIA, USA

Abstract
Limited information exists on small mammal communities in industrial forests of northern
California, USA. Small mammals are functionally important to ecosystems, so research on small
mammals is needed to inform timber management. I documented small mammals that were
susceptible to live-trapping in 4 forest classes commonly found throughout industrial forests of
northern California. I evaluated how forest class, downed wood volume, and proximate forest
classes influenced localized (~6.35 ha) abundances for the most commonly captured species. I
trapped from May to August of 2011-2013 in 69 stands that represented: 1) recent clearcuts (3-5
years post-harvest), 2) 10-20 year-old conifer plantations, 3) rotation-aged conifer stands, and 4)
Watercourse and Lake Protection Zones (WLPZs). I captured 11 small mammal species; 4 were
captured in sufficient numbers from 2011-13 (≥ 10 individuals) for regression modeling
(Peromyscus spp., Neotoma spp., California ground squirrel (Spermophilus beecheyi), and
Allen’s chipmunk (Tamias senex)). Average abundance estimates across all forest classes were
4.66 (SE = 0.42), 0.28 (SE = 0.11), 1.13 (SE = 0.33), and 0.24 (SE = 0.10) individuals per web
location (~0.75 ha) for Peromyscus spp., Neotoma spp., California ground squirrels, and Allen’s
chipmunks, respectively. The forest class containing the trap array was not an important variable
for describing small mammal abundance. Rather, downed wood volume and the composition of
proximate areas were more influential. My results indicate that retaining forest elements like
downed wood and providing a small-scale mosaic of diverse forest types and age classes are

7

factors positively influencing small mammal abundances in industrial forests of northern
California.
1.1. Introduction
In the Pacific Northwest of the United States (PNW) small mammals are known to influence the
distribution and habitat use of predatory species (Carey et al. 1992), regulate invertebrate
populations (Buckner 1966; Carey and Johnson 1995; Elkinton et al. 1996; Carey and Harrington
2001), disperse fungal spores (Maser et al. 1978), and serve as indicators of habitat suitability
(Carey and Harrington 2001; Pearce and Venier 2005). Industrial forests are common throughout
the PNW. For instance, corporate owners manage 14% of forestlands in California (Christensen
et al. 2008). Although industrial forests are common in the PNW, they are rarely managed for
small mammals unless the areas contain a protected small mammal species, protected predators
that depend on small mammals, or small mammals that damage forest regeneration. For example,
in the Klamath-Siskiyou Mountains of southern Oregon and northern California, several
protected predators of small mammals occupy industrial forests including northern spotted owl
(Strix occidentalis caurina), Pacific fisher (Martes pennanti pacifica), and Humboldt marten (M.
americana humboldtensis). Given that land uses in the Klamath-Siskiyou Mountain region
include timber harvest (Smith et al. 2004; Parks et al. 2005), management of industrial
timberlands often occurs in conjunction with protected species conservation. Understanding the
relationships between small mammal communities and vegetation characteristics provided by
industrial forests can aid managers in providing the habitat conditions needed to support small
mammals and their associated predators (Maser et al. 1978; Aubry et al. 1991; Carey and
Johnson 1995; Williams et al. 2014).

8

Small mammal habitat is generally described based on food, cover, nesting (or denning),
and microclimate requirements (Hallet et al. 2003). These vary among forest types, seral stages,
soils, and management regimes (Hallet et al. 2003). Although some researchers have
demonstrated that clearcutting (even-aged forest management) negatively impacts biodiversity
by reducing horizontal and vertical structural diversity (Peterken 1996; Lust et al. 1998;
Lindenmayer and Franklin 2002; Betts et al. 2005), Kirkland (1990) found a positive initial (≤ 6
years post clearcut) response by small mammals to clearcutting in temperate coniferous forests.
Furthermore, varying species-specific responses were observed among small mammals between
conventional clearcuts and unmanaged forests, with generalist species colonizing shortly after
clearcutting (Sullivan et al. 2012). Species richness was found to be higher in young pine (17
yrs) and seed-tree (17-18 yrs) age classes than in older growth (70-133 yrs; Sullivan et al. 2000).
As forests mature these differences may be lost. For example, in the Washington and Oregon
Cascades and Coast Ranges few differences in small mammal community structure and
composition were detected between young (35-79 yrs), mature (80-195 yrs), and old growth
forests (200-730 yrs; Aubry et al. 1991).
In industrial forests, managers can manipulate several fine-scale features known to
benefit small mammals. Downed wood is an important habitat component for several small
mammals because it is used for reproduction, foraging, resting, and thermal cover (Maser et al.
1978; Amaranthus et al. 1994; Carey and Johnson 1995; McComb 2003). Downed wood, also
called coarse woody debris, is defined as fallen trees or branches (Keddy and Drummond 1996).
In western Washington State, Lee (2004) found that sites with higher amounts of downed wood
resulted in significantly higher populations and greater population stability in deer mice
(Peromyscus maniculatus) than sites with lower amounts of downed wood. In the central Oregon

9

Coast Range, small mammal survival was positively linked to the downed wood volume at the
individual home range (Manning and Edge 2004). Differences in small mammal community
composition, structure, and abundances between young (44-67 yrs) and old-growth (300-400 yrs)
stands in the Olympic Peninsula of Washington were attributed to the reduced amount of
localized downed wood found in young, managed stands (Carey and Johnson 1995).
Management of downed wood can potentially mitigate the impacts of timber harvest on small
mammals.
Riparian zones also influence small mammal communities in managed forest landscapes.
Small mammal species richness and abundance are generally greater in riparian zones than in
upland areas (southwest Oregon, Cross 1985; Cascade Range of Oregon, Doyle 1990).
Alternatively, a study in the boreal mixed wood of Alberta, Canada found that small mammal
assemblages did not respond to timber harvest and riparian buffer width (Hannon et al. 2002).
The influence of riparian buffer zones on small mammal communities likely relates to the aridity
of the larger landscape and the habitat matrix, which potentially explains these conflicting results
among studies.
Although extensive research has been conducted on small mammal communities of the
PNW, limited information exists on small mammals within the northern California portion of the
Klamath Mountains. I used a combination of live trapping and modeling to explore relationships
between small mammal communities and forest conditions that result from intensive
management at the local-level (~6.35 ha). Specifically, I: 1) documented the small mammal
communities that were susceptible to live-trapping in 4 forest classes that commonly occur in
industrial forests, and 2) evaluated how downed wood and proximate forest classes influenced
localized abundances for the most commonly captured species. Results of this study provide

10

insight into the factors that influence small mammal occurrence and abundance in industrial
forests.
1.2. Methods
1.2.1. Study Area
This study was conducted in the Klamath Mountain ecoregion of northern California (Trinity
County, 8,309 km2), USA. This landscape features heterogeneous and intricate vegetation
patterns partially resulting from diverse climate, topography, and parent materials (Sawyer et al.
1977). Soil moisture regimes are xeric with soil temperatures varying from mesic to frigid and
some cryic at higher elevations (Miles and Goudey 1997). The climate is considered
Mediterranean, with hot and dry summers (Skinner et al. 2006). Average maximum daily
temperatures from May through August range from 25 to 34°C and average precipitation ranges
from 3.4 to 0.5 cm. The coolest and wettest month is May and the hottest (August) and driest
(July) months occur toward the end of summer (Weaverville Ranger Station, US Forest Service,
Trinity County).
Land use is predominately forestry, agriculture, tourism, and mining, with 83% of the land
within the ecoregion (47,791 km2) federally owned (Sleeter and Calzia 2008). Historically, fire
was the primary disturbance in this region that shaped current forest structure (Mohr et al. 2000).
Vegetation in this region is broadly classified as Douglas-fir (Pseudotsuga menziesii) –
Ponderosa pine (Pinus ponderosa; Miles and Goudey 1997), with the industrial forests managed
for Douglas-fir, incense cedar (Calocedrus decurrens), ponderosa pine, and secondarily
supporting diverse hardwoods including canyon live oak (Quercus chrysolepis), black oak (Q.
kelloggii), and madrone (Arbutus menziesii).
I conducted this project on timberlands owned and managed by Sierra Pacific Industries

11

(SPI). My replicates were stands, where a stand refers to a relatively homogeneous forest patch
harvested at approximately the same time. The dominant silviculture regime is small-scale (<8
ha) clearcutting followed by site preparation that includes various combinations of chemical,
mechanical, and fire treatments. Stands in this study were clearcut but contained a diversity of
retained structures including riparian buffers (which are called Watercourse and Lake Protection
Zones (WLPZ) in California regulatory parlance), retention patches, and occasional single,
isolated leave trees. Harvested stands were later replanted (within 1 year of harvest) and
monitored periodically for regeneration success. Stands used for trapping averaged
approximately 7-8 ha and were located north and south of Weaverville, CA on elevations
ranging from 679 to 1,467 m.
1.2.2. Experimental Design
I trapped from May to August of 2011-2013 in 69 stands that represented four common forest
classes (Figure 1.1.): 1) recent clearcuts (3-5 years old; 17 stands), 2) 10-20 year-old plantations
(16 stands), 3) rotation-aged stands (60-80 years old; 19 stands), and 4) Watercourse and Lake
Protection Zones (WLPZ; 17 stands). I used a web-based trapping design with a combination of
Sherman (Model LFA, 7.6 x 8.9 x 22.9 cm; H.B. Sherman Traps, Inc., Tallahassee, Florida) and
Tomahawk (Model 202, 48.3 x 15.2 x 15.2 cm; Tomahawk Live Trap Co., Tomahawk,
Wisconsin) live traps (Parmenter and McMahon 1989; Figure 1.2.). The web-based design was
first described by Anderson et al. (1983) and has become a favorite design among small-mammal
researchers (Bagne and Finch 2010) because it requires fewer assumptions and is more robust to
smaller sample sizes (Parmenter and McMahon 1989, Parmenter et al. 2003).
During sampling, I placed a single trapping array in a stand. I trapped each array for 3
(2011) to 5 (2012-2013) nights, which constituted a trapping period. After each trapping period I

12

moved the trapping arrays to the next set of replicate stands. When feasible, one stand of each
forest class was trapped during a sampling period to account for population fluctuations. Each
individual stand was trapped only once over the course of this study. A trapping array consisted
of 5 spokes containing 7 nodes with nodes separated by 7 m. I placed a Sherman live trap at each
node, resulting in 35 Sherman traps per web. At the web center and the 3rd and 7th nodes I also
placed a Tomahawk live trap, resulting in 11 Tomahawk traps per web. I baited traps with a
mixture of whole oats, raisins, creamy peanut butter, and molasses. Traps were set under or
beside ground cover such as logs or heavy foliage and those at risk of exposure to direct sunlight
were shaded. I also applied cotton batting to all traps. During the 2012-13 field season I also
placed two remote sensing cameras in control and WLPZ stands to document other small
mammal species potentially not susceptible to ground-based box or cage traps (e.g., northern
flying squirrels (Glaucomys sabrinus)). Cameras were aimed at a bait mixture that was placed on
tree stumps or downed logs within the limits of the array. I also attached several Tomahawk traps
to trees at breast height to improve the likelihood of capturing flying squirrels (Risch and Brady
1996).
For stands containing riparian zones or leave patches, I placed arrays so that one or more
spokes intersected the retention elements. Due to the limited size of many WLPZs, I centered the
webs on the stream channel yet some spokes extended beyond the WLPZ and into adjacent areas.
Generally, the vegetation characteristics found within a WLPZ extended beyond the regulatory
boundaries of the WLPZ area.
Traps were checked daily between daybreak and noon. I individually marked small
mammals to document movements within a trapping array and to ensure that individuals were
not captured in more than a single array. Captured animals were marked with a 9-mm passive

13

integrated transponder (PIT) tag injected via a 12-gauge needle subcutaneously in the flank. I
used PIT tags instead of ear tags so that individuals could be identified during subsequent
captures with minimal handling, to increase accuracy of individual identification, and to shorten
animal handling time (Schooley et al. 1993; Morley 2002). Schooley et al. (1993) found no
evidence that PIT tagging increased small mammal mortality.
During the 2013 field season I removed a small patch of hair from the back or flank of
PIT-tagged Peromyscus spp. to document the rate of PIT tag loss in my study. If an animal was
captured with a hair clip and without a PIT tag, I recorded the absence of the tag and re-marked
the individual. After marking, animals were released on site for potential recapture. Animals that
I seldom captured or those that were not conducive to tagging (e.g., shrews) were released
without administering a PIT tag. Capture and handling of animals followed American Society of
Mammalogists guidelines (Sikes et al. 2011), guidelines recommended by the California
Department of Fish and Wildlife under scientific collection permit SC-11913, and was
considered exempt via Michigan State University Institutional Animal Care and Use Committee.
1.2.3. Vegetation Sampling
In this study, I considered downed wood to be any piece of fallen wood that had a large end
diameter that was >11.4 cm. I conducted line intercept (Canfield 1941) sampling for downed
wood along the length of each web spoke. For each piece of wood (with a large-end diameter
≥11.4 cm) that intersected the line, I measured length, and large and small-end diameters. The
location of the debris along the line was also noted in meters. I calculated the volume of downed
wood per web area (~0.75 ha) based on the diameter and length measurements.
1.2.4. Proximate Forest Classes
Spatial data were analyzed using ArcGIS 10.1 (Environmental Systems Research Institute,

14

Redlands, CA). Spatial layers including land ownership and forest class were obtained from SPI.
Forest classes that occurred in areas surrounding trapping webs that were not part of SPI
ownership were acquired through the continuously updated Classification and Assessment with
Landsat of Visible Ecological Groupings (Calveg) layer (USDA Forest Service 1981). I used
ArcGIS to delineate a circular 142.2 m buffer (~6.35 ha) around the center of each trapping array.
I calculated the radius of the buffer based on the maximum straight-line distance moved (93.2 m)
by any individual small mammal I recaptured in a web. This distance was then added to the
length of a single web spoke (49 m) to represent the potential area used by small mammals
during trapping. These buffers were intended to encompass the maximum distance that an animal
could have traveled and still be captured within an array. In addition, the buffer area exceeded
the estimated home ranges for small mammal species I captured (i.e., yellow-pine chipmunk
(Tamias amoenus; a similar species to Allen’s chipmunk) ~1.6 ha (Broadbooks 1970); duskyfooted woodrat (Neotoma fuscipes) ~0.23 ha (Cranford 1977); California ground squirrel
(Spermophilus beecheyi) ~0.09 ha (Boellstorff and Owings 1995); and brush mouse (Peromyscus
boylii) ~0.12 ha (Gottesman et al. 2004)). Within each 6.35 ha buffer, I calculated the
proportional area of each forest class and used these as explanatory variables in our small
mammal abundance models.
1.2.5. Data Analysis
I calculated summary statistics for downed wood volume and the proportions of different forest
types within a 6.35 ha buffer of the trapping web by forest class. I used the maximum count of
small mammals captured on any trap night for the 4 most commonly captured species by forest
class to index abundance. I used generalized linear mixed models (GLMM) and a Poisson
distribution in program R 3.0.2 to estimate the effects of independent covariates on small

15

mammal abundance by species (R Development Core Team 2013). Independent covariates
included the forest class containing the trapping grid, downed wood volume, the size of the stand
that contained the trapping grid that was within the 6.35 ha buffer, and the proportions of forest
classes surrounding the trapping web in the 6.35 ha area. I first conducted a Kruskal-Wallis rank
sum test to determine if the forest class containing the trapping grid influenced small mammal
counts (by species); a non-significant finding would indicate that this factor could be excluded
from the GLMM. Using a Kendall tau rank correlation coefficient, I then generated a correlation
matrix and identified those variable combinations that were correlated (P < 0.05). I included
year as a random effect in species-specific abundance models to account for annual differences
in small mammal populations or catchability. I used AICc to rank candidate models and deemed
model parameters significant if the 95% confidence intervals did not overlap 0 (Burnham and
Anderson 2002).
1.3. Results
1.3.1. Vegetation and Proximate Forest Classes
Within a trapping web in 2012 and 2013, I found that average volume of downed wood was
highest in rotation-aged and WLPZ stands (Figure 1.3.). In 2011, the average volume of downed
wood was highest in 10-20 yr stands (Figure 1.3.). More recently harvested stands (i.e., 3-5 and
10-20 years old) consistently had average downed wood volumes ≤0.5m3/0.75 ha (Figure 1.3.).
Generally, downed wood volumes were most variable in the older stands (i.e., rotation-aged and
WLPZ) and in most instances, wood volumes were 3-15 times higher in the older compared to
younger stands (Figure 1.3.).
The non-forest class around trapping webs was rare and hence was not included in my
analyses (Figure 1.4.). Trapping webs located in 3-5 yr forest class were closer to more rotation-

16

aged forest (average >40% of the 6.35 ha buffer) and, to a lesser extent, WLPZs (~>10%)
compared to the other forest classes (Figure 1.4.a). The proportion of different forest classes
around the 10-20 yr trapping webs was highly variable, with all forest classes represented
(Figure 1.4.b). Rotation-aged trapping webs were generally surrounded by rotation-aged, and to a
lesser extent (<30%) the other forest classes (Figure 1.4.c). Forest classes surrounding our WLPZ
webs were highly variable, with all forest classes represented (Figure 1.4.d). Collectively these
results indicate that the younger forest classes tended to occur in a matrix of rotation-aged forests,
and that WLPZs were equally represented among my trapping webs.
1.3.2. Small Mammals
Over the 3 field seasons, 12,411 trap nights were accumulated (~86% of the maximum trap
nights that could have occurred). Bears (Ursus americanus) and gray foxes (Urocyon
cinereoargenteus) were most frequently responsible for disabling traps, as indicated by my
remote cameras. I caught 11 species: white-footed deer mouse, brush mouse, California ground
squirrel, Allen’s chipmunk, dusky-footed woodrat, bushy-tailed woodrat (N. cinerea),
Trowbridge’s shrew (Sorex trowbridgii), Douglas squirrel (Tamiasciurus douglasii), striped
skunk (Mephitis mephitis), western harvest mouse (Reithrodontomys megalotis), and California
vole (Microtus californicus). The Peromyscus spp. were pooled for modeling because field crews
could not reliably differentiate the species, particularly juveniles. I also pooled dusky-footed and
bushy-tailed woodrats into Neotoma spp. because they are found in similar habitat (i.e., areas
with abundant shrub cover; Carey 1991) and I only caught 5 bushy-tailed woodrats (~26% of
Neotoma captures) during this study. Of the 11 captured species, 415 unique individuals were
marked with a PIT tag, with Peromyscus spp. being the most frequently captured species (78%
of all captures). My data on PIT tag retention during the 2013 field season indicated that 5 out of

17

113 (4.4%) individual Peromyscus spp. lost their tag.
Average maximum captures of Peromyscus spp. per stand were highest in the WLPZ class
(x¯ = 5.82, SE = 0.75), followed by 3-5 yr (x¯ = 4.88, SE = 0.84), rotation-aged (x¯ = 4.16, SE =
0.67), and 10-20 yr (x¯ = 3.81, SE = 1.07), but none of these counts were significantly different
among forest classes (2 = 5.674, P = 0.129). The number of individual Peromyscus spp. among
forest classes ranged from 0 (10-20 yr class in 2012) to 17 (10-20 yr class in 2013; Figure 1.5.a).
Generally, most California ground squirrels were captured in younger forest classes,
although I also caught a low number in WLPZs (Figure 1.5.b). I marked 61 individual California
ground squirrels in 2012 and 2013 and found an average of 2.42 (SE = 1.01) and 1.85 (SE =
1.15) individuals in 3-5 and 10-20 yr forest classes, respectively (Figure 1.5.b). This species was
not marked in 2011. Counts did not differ among forest classes (2 = 7.616, P = 0.055).
I marked 19 individual Neotoma spp. during the 2012 and 2013 field seasons (Figure
1.5.c) but none during 2011. Neotoma spp. were only captured in rotation-aged and WLPZ
classes, with the exception of 1 individual that was caught in the 10-20 class (Figure 1.5.c).
Wood rats were generally rare; on average 0.88 (SE = 0.40) per WLPZ stand. Counts did not
differ among forest classes (2 = 7.749, P = 0.051).
Allen’s chipmunks were also rare with most caught in rotation-aged forests (Figure 1.5.d),
but counts did not differ among forest classes (2 = 2.594, P = 0.459). I caught 13 individual
Allen’s chipmunks during 2012 and 2013 (the only years I marked this species); this was the
least frequently captured species that we analyzed. The number of individual Allen’s chipmunks
per forest class ranged from 0 to 5 (WLPZ; Figure 1.5.d).
High variability of counts for all commonly captured species within a forest type likely
contributed to my finding that the forest type containing the trapping grid was not an important

18

determinant of small mammal counts (Figure 1.5.). This result suggests that small mammal
abundances were more likely influenced by within stand structures, the mosaic of forest classes
found in proximity to my trapping webs, or some unmeasured environmental factor(s).
I tested 21 candidate GLMMs for the 4 commonly captured species (Table 1.1.). The topranking model for Peromyscus spp. included average downed wood volume per 0.75 ha (ß1) and
proportional area of the WLPZ forest class (ß2; Table 1.2.). This model accounted for 57% of the
evidence weight (Table 1.2.). Both parameters in the top-ranking model were significant (ß1 =
0.20, 95% CI = 0.05, 0.34; ß2 = 0.68, 95% CI = 0.05, 1.30). Counts of Peromyscus spp. increased
nonlinearly as average downed wood volume and proportional WLPZ area increased (Figure
1.6.a,b).
I found a single, top-ranking model for California ground squirrel that accounted for 64%
of the evidence weight (Table 1.2.). The top-ranking model included the proportion of 3-5 yr
class within the 6.35 ha buffer (ß1) and average downed wood volume (ß2; Table 1.2.). Both
parameters were significant (ß1 = -2.60, 95% CI = -4.37, -1.15; ß2 = -0.54, 95% CI = -1.08, -0.11),
and indicated a slight decline in California ground squirrel counts as the proportion of 3-5 yr
class and volume of downed wood increased, but the effect size for the 3-5 yr class parameter
was negligible (Figures 1.7.a,b).
The top-ranking model for Neotoma spp. consisted of the proportion of WLPZ in the 6.35
ha area surrounding my trapping webs (Table 1.2.). The WLPZ parameter was significant (ß1 =
4.21, 95% CI = 1.89, 6.74) and indicated that Neotoma counts increase as the amount of WLPZ
increased (Figure 1.8.). I also identified a competing Neotoma spp. model (i.e., ΔAICc < 2.00)
that included the proportional area of rotation-aged (ß1) and WLPZ (ß2) forest classes (Table
1.2.). The rotation-aged class parameter was not significant (ß1 = 1.60, 95% CI = -0.55, 4.09) but

19

the WLPZ parameter was significant (ß2 = 4.91, 95% CI = 2.31, 7.95).
The top-ranking model for Allen’s chipmunk included the proportional area of rotationaged forest (ß1), average downed wood volume (ß2), and proportion of WLPZ (ß3; Table 1.2.).
All model parameters were significant (ß1 = -1.66, 95% CI = -3.60, -0.35; ß2 = 6.52, 95% CI =
2.79, 11.82; ß3 = 8.63, 95% CI = 4.43, 14.50). Significant parameters in a competing model also
included the proportion of rotation-aged forest class (ß1 = 7.06, 95% CI = 3.35, 11.83), average
downed wood volume (ß3 = -1.69, 95% CI = -3.56, -0.44), and the proportional WLPZ area (ß4 =
7.17, 95% CI = 2.94, 13.06). My data suggest that Allen’s chipmunk counts are maximized when
rotation-aged forests make up 50-75% of the 6.35 ha buffer surrounding a trap web (Figure 1.9.a),
when wood volume is low (but this effect size is negligible, Figure 1.9.b), and when the amount
of WLPZ in the 6.35 ha buffer increases (Figure 1.9.c).
1.4. Discussion
I captured 11 species of small mammals in industrial forests of northern California using
Sherman and Tomahawk live traps. Small mammal species richness in this study was relatively
low in comparison to other studies conducted in the PNW, although I am not aware of similar
published studies from the Klamath Mountains of northern California. For example, Carey and
Harrington (2001) found 18 species (using Sherman live traps) and Carey and Johnson (1995)
found 13 species (using pitfall and snap traps) in the Olympic Peninsula, WA. Carey and Wilson
(2001) documented 17 species in the Puget Trough, WA, and Wilk et al. (2010) documented 19
species in the Washington Coast Range using Sherman traps. Suzuki and Hayes (2003)
documented 18 species in the Oregon Coast Range using pitfall and snap traps. Although
comparison to other studies provides context for my results, I caution that species richness is a
complex expression of historic and current land use, vegetation structure and composition, site

20

productivity (Heaney 2001), climate, elevation (Rahbek 1995; but see Brown 2001), the regional
species pool, and trapping techniques (Stephens and Anderson 2014). For example, other small
mammal studies in the PNW have occurred in highly productive areas (e.g., Puget Trough, WA;
Olympic Peninsula, WA) relative to the arid Klamath Mountains of northern California.
I found that the composition of localized areas surrounding trapping webs was more
influential on small mammal counts than the forest type that contained the trapping array.
Peromyscus spp. and Neotoma spp. were more often captured in areas with higher proportions of
rotation-aged and WLPZ forests near the trapping webs. I captured Neotoma spp. primarily in
riparian areas, consistent with other studies, likely due to higher amounts of understory cover
(Sakai and Noon 1993; Innes et al. 2007; Hamm and Diller 2009). My findings for Peromyscus
spp. contradict other research from the PNW. In general, Peromyscus spp. are positively
associated with recently harvested forests (Tevis 1956; Gashwiler 1970; Sullivan 1979; Kirkland
1990; Fantz and Renken 2005; but see Anthony et al. (1987); Carey and Johnson (1995). I found
Peromyscus spp. to more closely associate with downed wood and proximity to WLPZs. Similar
to other studies conducted in the PNW, we most frequently captured Peromyscus spp. in our
trapping webs (Anthony et al. 1987; Coppeto et al. 2006; Manning and Edge 2008; Sullivan et al.
2000, 2009).
Consistent with other studies from the PNW (Carey and Johnson 1995; Carey and
Harrington 2001; Lee 2004), I found that downed wood volume was a significant habitat
component that positively influenced captures of Peromyscus spp. Downed wood benefits small
mammals by providing resting and thermal cover, and serves as a substrate for reproduction and
foraging (Maser et al. 1978; Amaranthus et al. 1994; Carey and Johnson 1995; McComb 2003).
Currently, California Forest Practice Rules (CAL FIRE 2014) in this region primarily focus on

21

the reduction of fuel loads and pests in preparation for reforestation; therefore, retention of
downed wood is not required. Peromyscus spp. in my study positively responded to downed
wood when it exceeded 2 m3 per 0.75 ha (or 2.7 m3/ha), therefore, I recommend the retention of
≥9 logs with a length of 4.9 m, and 30 cm in diameter (0.3 m3 of downed wood) per ha to be
randomly distributed post-harvest. Retaining multiple logs of these dimensions is likely a more
conducive downed wood treatment than the retention of a single large log or many smaller logs
equivalent to 2.7 m3. My results suggest that this volume of downed wood will result in more
Peromyscus spp. in managed forests. Although Peromyscus spp. is a minor prey item for
northern spotted owls in terms of biomass (Rosenberg et al. 2003; Forsman et al. 2004), it may
serve as an important supplemental food source for northern spotted owls during the breeding
season (Rosenberg et al. 2003). It is unknown how other protected predators like Pacific fisher
use Peromyscus spp. in this region.
In contrast to the relationship I observed between downed wood and Peromyscus spp.,
captures of California ground squirrels and Allen’s chipmunks slightly decreased as downed
wood volume increased, but I caution that the effect sizes were minimal (Figures 1.5.b, 1.7.b).
Ground squirrels tend to create burrows in open areas where there is minimal tree canopy and
ground cover (Owings and Borchert 1975; Ordeñana et al. 2012), presumably to allow improved
visibility for predator detection (Grinnell and Dixon 1918; Schooley et al. 1996). Hence, the
negative relationship I found between California ground squirrel abundance and downed wood is
consistent with their life history. In contrast, Tevis (1956) suggested that Townsend’s chipmunks
(Neotamias townsendii), a similar species to Allen’s chipmunk, respond positively to downed
logs and timber harvest, although specific data on this relationship are lacking. My findings on
the influence of downed wood on California ground squirrels and Allen’s chipmunks are based

22

on low captures and effect sizes and thus require further evaluation.
Relative to other variables I measured, my results indicate that small mammal captures are
not strongly influenced by the type of forest containing trapping webs in northern California.
Rather, small mammal captures in this study were more likely influenced by structures within
stands and the proximate forest classes. These results likely relate to the relatively small size of
clearcuts in northern California, the practices of retaining habitat elements like downed wood
and patches of live and dead trees within harvest units, and the protection of riparian zones
consistent with California Forest Practice Rules. Peromyscus spp., Neotoma spp., and Allen’s
chipmunks responded positively to higher amounts of WLPZ in the localized buffer surrounding
trapping webs. My results indicate that riparian corridors in industrial forest landscapes provide
important habitat elements that encourage the persistence of Peromyscus spp., Neotoma spp. and
Allen’s chipmunks. In northern California and other drier portions of the PNW, Neotoma spp.
and to a lesser extent Peromyscus spp. are recognized as prey for northern spotted owls (Ward et
al. 1998; Forsman et al. 2004). Hence, in addition to protecting water quality in managed forest
landscapes WLPZs also have a positive effect on prey for protected predator species. Other
studies have similarly shown that riparian zones increase small mammal diversity (Cross 1985;
Anthony et al. 1987).
Ground squirrels were frequently observed using burrows within 3-5 yr stands during my
study. Gashwiler (1970) also observed California ground squirrels moving into and establishing
a local population in a clearcut shortly after harvesting was complete. My modeling results
suggesting that California ground squirrel counts are negatively related to the amount of 3-5 yr
forest class in the surrounding area are surprising considering that the 3-5 yr forest class satisfied
several habitat criteria that are thought to positively influence California ground squirrels (e.g.,

23

open area, good visibility; Grinnell and Dixon 1918; Schooley et al. 1996). Although the effect
sizes were minimal, 3-5 yr stands generally had a sparse understory and hence may have
provided minimal food for California ground squirrels causing them to locate burrows closer to
older forest types. McGrann et al. (2013) found that California ground squirrel abundance was
highest in areas adjacent to fruit and nut crops, suggesting that lands adjacent to burrows
influenced space use. In addition, ground squirrels as a group generally benefit from human
disturbance (Grinnell and Dixon 1918), potentially making industrial forests suitable for
colonization.
Small mammals are essential components to forested ecosystems. Understanding how
small mammals influence forest function and biodiversity are significant ecological issues that
impact conservation (Hallet et al. 2003). For predators that prey on small mammals, conservation
of food sources is critical to the maintenance and recovery of threatened populations. Industrial
forests can support a diverse small mammal community if forest elements such as downed wood
and riparian zones are retained (Gomez and Anthony 1998; Carey and Harrington 2001; Cockle
and Richardson 2003; Manning and Edge 2004; Lee 2012). Small mammals are generally
adaptable to landscape perturbations at smaller scales (Middleton and Merriam 1983; VanDruff
and Rowse 1986), indicating that both habitat patches and the surrounding matrix are important
to the movement and stability of small mammal populations in a heterogeneous landscape
(Szacki and Liro 1991). It is likely that the diverse habitat mosaic commonly associated with
forest practices in northern California creates a variety of habitats and corridors conducive to the
small mammal species that I commonly captured.
1.5. Acknowledgments

24

Summer funding for this research was provided by Sierra Pacific Industries. Academic year
funding was provided by Michigan State University. I thank M. Block, R. Caster, B. Benson, S.
Houston, C. Brockman, K. Raby, R. Feamster, and J. Kelley for their assistance in the collection
of field data. Additional thanks to the California Department of Fish and Wildlife for reviewing
their animal handling protocol with the field crews and for lending us trapping supplies.

25

APPENDIX

26

Table 1. 1.
Candidate generalized linear mixed models used to estimate the number of individual
Peromyscus spp., California ground squirrels, Neotoma spp., and Allen’s chipmunks in industrial
forests of northern California, USA, May-August of 2011-2013.
Candidate Modelsa
1. Rotation + Stand Size + Volume +WLPZ

12. Volume + WLPZ

2. 10-20 + Stand Size + Volume

13. Rotation + Stand Size

3. Rotation + Stand Size + Volume

14. Rotation + WLPZ

4. Rotation + Stand Size + WLPZ

15. Rotation + Volume

5. Rotation + Volume + WLPZ

16. Stand Size

6. 3-5 + Volume + WLPZ

17. 3-5

7. 10-20 + Rotation

18. 10-20

8. Stand Size + Volume

19. Rotation

9. 10-20 + Volume

20. WLPZ

10. 3-5 + WLPZ
21. Volume
11. 3-5 + Volume
a

Proportions of forest class in 6.35 ha buffer around the trapping web where 3-5 = 3-5 yr class;

10-20 = 10-20 yr class; Rotation = rotation-aged class; and WLPZ= Watercourse and Lake
Protection Zones. Stand Size= stand area (ha); Volume = average volume (m3) of downed wood.

27

Table 1.2.
Five top-ranking generalized linear mixed models used to estimate maximum nightly captures
for Peromyscus spp., California ground squirrel, Neotoma spp., and Allen’s chipmunk in
industrial forests of northern California, USA, May-August of 2011-2013. Kb = the number of
estimated model parameters, AICc = Akaike Information Criteria adjusted for small sample sizes,
∆AICc = difference in AIC from top-ranking model, and w = weight of evidence.
K

AICc

∆AICc

w

Volume + WLPZ

4

384.59

0.00

0.57

Rotation + Volume + WLPZ

5

386.73

2.14

0.11

Volume

3

386.84

2.24

0.10

Rotation + Stand Size + Volume + WLPZ

6

386.85

2.26

0.10

3-5 + Volume + WLPZ

5

386.86

2.27

0.10

3-5 + Volume

4

236.18

0.00

0.64

3-5 + Volume + WLPZ

5

238.36

2.17

0.22

3-5

3

240.22

4.04

0.08

3-5 + WLPZ

4

241.41

5.22

0.05

10-20

3

247.45

11.26

0.00

WLPZ

3

93.28

0.00

0.29

Rotation + WLPZ

4

93.53

0.26

0.26

3-5 + WLPZ

4

95.32

2.04

0.11

Volume + WLPZ

4

95.56

2.28

0.09

Stand Size + Rotation + WLPZ

5

95.93

2.65

0.08

Modela

Species
Peromyscus spp.

California ground squirrel

Neotoma spp.

28

Table 1.2. (cont’d)
Species
Allen’s chipmunk

a

K

AICc

∆AICc

w

Rotation + Volume + WLPZ

5

57.99

0.00

0.47

Rotation + Stand Size + Volume+ WLPZ

6

58.86

0.87

0.31

3-5 + Volume + WLPZ

5

60.35

2.36

0.15

Rotation + WLPZ

4

62.84

4.85

0.04

Rotation + Stand Size + WLPZ

5

64.54

6.55

0.02

Modela

Proportions of forest class in 6.35 ha buffer around the trapping web where 3-5 = 3-5 yr class;

10-20 = 10-20 yr class; Rotation = rotation-aged class; and WLPZ= Watercourse and Lake
Protection Zones. Stand Size= stand area (ha); Volume= average volume (m3) of downed wood.
b

Intercept and random effect (year) included in all models.

29

Figure 1.1.
Four common forest classes in industrial forests of northern California, USA. Top left = recent
clearcuts (3-5 years old), top right = 10-20 year-old plantations, bottom left = rotation-aged
stands, bottom right = Watercourse and Lake Protections Zones (WLPZs).

30

Figure 1.2.
Small mammal trapping web design, northern California, USA, 2011-13.

7 m (23 ft)

Center Point
Sherman Trap Location
Tomahawk Trap Location

31

Figure 1.3.
Average volume (m3) of downed wood per 0.75 ha by forest class and year in industrial forests
of northern California, USA. Average (filled circle), median (solid horizontal bar), 75th data
quartiles (shaded boxes), 95% confidence intervals (dashed lines), and extreme values (open
circles) are shown.

32

Figure 1.4.
Proportion of forest classes, by forest class containing the trapping webs and year, within a 6.35
ha buffer around small mammal trapping webs in industrial forests of northern California, USA.
Average (filled circle), median (solid horizontal bar), 75th data quartiles (shaded boxes), 95%
confidence intervals (dashed lines), and extreme values (open circles) are shown.

33

Figure 1.4. (cont’d)

34

Figure 1.5.
Maximum nightly captures in forest classes containing trapping webs by small mammal species
and year in industrial forests of northern California, USA.

35

Figure 1.5. (cont’d)

36

Figure 1.6.
Relationship of Peromyscus spp. counts to a) average volume (m3) of downed wood per 0.75 ha
and b) proportional area of WLPZ within 6.35 ha surrounding the trapping web in industrial
forests of northern California, USA, 2011-2013. Shaded area represents the 95% confidence
limits.

37

Figure 1.6. (cont’d)

38

Figure 1.7.
Relationship of California ground squirrel counts to a) proportional area of 3-5 yr within 6.35 ha
surrounding the trapping web and b) average volume (m3) of downed wood per 0.75 ha in
industrial forests of northern California, USA, 2011-2013. Shaded area represents the 95%
confidence limits.

39

Figure 1.7. (cont’d)

40

Figure 1.8.
Relationship of Neotoma spp. counts to proportional area of WLPZ within 6.35 ha surrounding
the trapping web in industrial forests of northern California, USA, 2011-2013. Shaded area
represents the 95% confidence limits.

41

Figure 1.9.
Relationship of Allen’s chipmunk counts to a) proportional area of rotation age forest class
within 6.35 ha surrounding the trapping web, b) average volume (m3) of downed wood per 0.75
ha and c) proportional area of WLPZ within 6.35 ha surrounding the trapping web in industrial
forests of northern California, USA, 2011-2013. Shaded area represents the 95% confidence
limits.

42

Figure 1.9. (cont’d)

43

Figure 1.9. (cont’d)

44

LITERATURE CITED

45

LITERATURE CITED

AMARANTHUS, M., J. M. TRAPPE, L. BEDNAR, AND D. ARTHUR. 1994. Hypogeous fungal
production in mature Douglas-fir forest fragments and surrounding plantations and its
relation to coarse woody debris and animal mycophagy. Canadian Journal of Forest
Research 24: 2157-2165.
ANDERSON, D. R., K. P. BURNHAM, G. C. WHITE, AND D. L. OTIS. 1983. Density estimation of
small mammal populations using a trapping web and distance sampling methods.
Ecology 64: 674-680.
ANTHONY, R. G., E. D. FORSMAN, G. A. GREEN, G. WITMER, AND S. K. NELSON. 1987. Small
mammal populations in riparian zones of different-aged coniferous forests. The Murrelet
68(3): 94-102.
AUBRY, K. B., M. J. CRITES, AND S. D. WEST. 1991. Regional patterns in small mammal
abundance and community composition in Oregon and Washington. Wildlife and
Vegetation of Unmanaged Douglas-fir Forests (tech. coor. L. F. Ruggiero, K. B. Aubry,
A. B. Carey and M. H. Huff), pp. 285-294. U.S. Forest Service General Technical Report
PNW-285. Pacific Northwest Research Station, Portland, Oregon, USA.
BAGNE, K. E, AND D. M. FINCH. 2010. Response of small mammal populations to fuel
treatment and precipitation in a ponderosa pine forest, New Mexico. Restoration
Ecology 18: 409-417.
BETTS, M. G., A. W. DIAMOND, G. J. FORBES, K. FREGO, J. A. LOO, B. MATSON, M. R. ROBERTS,
M. A. VILLARD, R. WISSINK, AND L. WUEST. 2005. Plantations and biodiversity: a
comment on the debate in New Brunswick. Forestry Chronicle 81(2): 265–26.
BOELLSTORFF, D. E., AND D. H. OWINGS. 1995. Home range, population structure, and spatial
organization of California ground squirrels. Journal of Mammalogy 76(2): 551-561.
BROADBOOKS, H. E. 1970. Home ranges and territorial behavior of the yellow-pine chipmunk,
Eutamias amoenus. Journal of Mammalogy 51(2): 310-326.
BROWN, J. H. 2001. Mammals on mountainsides: elevational patterns of diversity. Global
Ecology & Biogeography 10: 101-109.
BUCKNER, C. H. 1966. Populations and ecological relationships of shrews in tamarack bogs of
southeastern Manitoba. Journal of Mammalogy 47(2): 181-194.
BURNHAM, K. P., AND D. R. ANDERSON. 2002. Model selection and multimodel inference: a
practical information-theoretic approach. Springer-Verlag, New York.

46

CAL FIRE (CALIFORNIA DEPARTMENT OF FORESTRY AND FIRE PROTECTION). 2014. California
forest practice rules. Title 14, California Code of Regulations Chapters 4, 4.5, and 10.
Sacramento, CA.
CANFIELD, R. H. 1941. Application of the line interception method in sampling range
vegetation. Journal of Forestry, 39(4), 388-394.
CAREY, A. B. 1991. The biology of arboreal rodents in Douglas-fir forests. United States Forest
Service General Technical Report PNW-276.
CAREY, A. B., AND C. A. HARRINGTON. 2001. Small mammals in young forests: implications for
management for sustainability. Forest Ecology and Management 154(1): 289-309.
CAREY, A. B., S. P. HORTON, AND B. L. BISWELL. 1992. Northern spotted owls: influence of prey
base and landscape character. Ecological Monographs 62(2): 223-250.
CAREY, A. B., AND M. L. JOHNSON. 1995. Small mammals in managed, naturally young, and oldgrowth forests. Ecological applications 5(2): 336-352.
CAREY, A. B., AND S. M. WILSON. 2001. Induced spatial heterogeneity in forest canopies:
responses of small mammals. The Journal of Wildlife Management 65(4): 1014-1027.
COCKLE, K. L., AND J. S. RICHARDSON. 2003. Do riparian buffer strips mitigate the impacts of
clearcutting on small mammals? Biological Conservation 113(1): 133-140.
COPPETO, S. A., D. A. KELT, D. H. V. VUREN, J. A. WILSON, AND S. BIGELOW. 2006. Habitat
associations of small mammals at two spatial scales in the northern Sierra Nevada.
Journal of Mammalogy 87(2): 402-413.
CHRISTENSEN, G. A., S. J. CAMPBELL, J. S. FRIED, tech. eds. 2008. California’s forest
resources, 2001–2005: five-year Forest Inventory and Analysis report. Gen. Tech. Rep.
PNW-GTR-763. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific
Northwest Research Station. 183 p. 125.
CRANFORD, J. A. 1977. Home range and habitat utilization by Neotoma fuscipes as determined
by radiotelemetry. Journal of Mammalogy 58(2): 165-172.
CROSS, S. P. 1985. Responses of small mammals to forest riparian perturbations. Riparian
ecosystems and their management: reconciling conflicting uses. Rocky Mountain Forest
and Range Experiment Station, Fort Collins, Colorado, General Technical Report RM120.
DOYLE, A. T. 1990. Use of riparian and upland habitats by small mammals. Journal of
Mammalogy 71(1): 14-23.

47

ELKINTON, J. S., W. M. HEALY, J. P. BUONACCORSI, G. H. BOETTNER, A. M. HAZZARD, AND H. R.
SMITH. 1996. Interactions among gypsy moths, white-footed mice, and acorns. Ecology:
77(8): 2332-2342.
FANTZ, D. K., AND R. B. RENKEN. 2005. Short-term landscape-scale effects of forest management
on Peromyscus spp. mice within Missouri Ozark forests. Wildlife Society Bulletin 33(1):
293-301.
FORSMAN, E. D., R. G. ANTHONY, E. C. MESLOW AND C. J. ZABEL. 2004. Diets and foraging
behavior of northern spotted owls in Oregon. The Journal of Raptor Research 38(3):
214-230.
GASHWILER, J. S. 1970. Plant and mammal changes on a clearcut in west-central Oregon.
Ecology 51(6): 1018-1026.
GOMEZ, D. M., AND R. G. ANTHONY. 1998. Small mammal abundance in riparian and upland
areas of five seral stages in western Oregon. Northwest Science 72: 293-302.
GOTTESMAN, A. B., P. R. KRAUSMAN, M. L. MORRISON, AND Y. PETRYSZYN. 2004. Movements
and home range of brush mice. The Southwestern Naturalist 49(2): 289-294.
GRINNELL, J., AND J. DIXON. 1918. Natural history of the ground squirrels of California.
California State Printing Office.
HALLET, J. G, M. A. O’CONNELL AND C. C. MAGUIRE. 2003. Ecological relationships of
terrestrial small mammals in western coniferous forests. Pp. 120-156 in Mammal
Community Dynamics: Management and Conservation in the Coniferous Forests of
Western North America (Zabel, C. J. and R. G. Anthony, eds.). Cambridge University
Press, New York, New York, USA.
HAMM, K. A., AND L. V. DILLER. 2009. Forest management effects on abundance of woodrats in
northern California. Northwestern Naturalist 90(2): 97-106.
HANNON, S. J., C. A. PASZKOWSKI, S. BOUTIN, J. DEGROOT, S. E. MACDONALD, M. WHEATLEY,
AND B. R. EATON. 2002. Abundance and species composition of amphibians, small
mammals, and songbirds in riparian forest buffer strips of varying widths in the boreal
mixedwood of Alberta. Canadian Journal of Forest Research 32(10): 1784-1800.
HEANEY, L. R. 2001. Small mammal diversity along elevational gradients in the Philippines: an
assessment of patterns and hypotheses. Global Ecology and Biogeography 10: 15-39.
INNES, R. J., D. H. V. VUREN, D. A. KELT, M. L. JOHNSON, J. A. WILSON, AND P. A. STINE. 2007.
Habitat associations of dusky-footed woodrats (Neotoma fuscipes) in mixed-conifer
forest of the Northern Sierra Nevada. Journal of Mammalogy 88(6): 1523-1531.

48

KEDDY, P. A., AND C. G. DRUMMOND. 1996. Ecological properties for the evaluation,
management, and restoration of temperate deciduous forest ecosystems. Ecological
Applications 6(3): 748-762.
KIRKLAND JR., G. L. 1990. Patterns of initial small mammal community change after clearcutting
of temperate North American forests. Oikos 59(3) 313-320.
KÜCHLER, A.W. 1964. Potential Natural Vegetation of the Conterminous United States. Digital
vector data in an Albers Equal Area Conic polygon network and derived raster data on a
5 km by 5 km Albers Equal Area 590x940 grid. In: Global Ecosystems Database Version
2.0. Boulder CO: NOAA National Geophysical Data Center.
LAAKSONEN-CRAIG, S., G. E. GOLDMAN, AND W. MCKILLOP. 2003. Forestry, forest industry, and
forest products consumption in California. Oakland, CA: University of California,
Division of Agriculture and Natural Resources.
LINDENMAYER, D. B., AND J. F. FRANKLIN. 2002. Conserving forest biodiversity: a
comprehensive multiscaled approach. Island Press, Washington.
LEE, S. D. 2004. Population dynamics and demography of deermice (Peromyscus maniculatus)
in heterogeneous habitat: role of coarse woody debris. Polish Journal of Ecology 52(1):
55-62.
LEE, S. D. 2012. Association between coarse woody debris and small mammals and
insectivores in managed forests. Journal of Ecology and Environment, 35(3), 189-194.
LUST, N., B. MUYS, AND L. NACHTERGALE. 1998. Increase of biodiversity in homogeneous Scots
pine stands by an ecologically diversified management. Biodiversity and
Conservation 7: 249–260.
MANNING, J. A., AND W. D. EDGE. 2004. Small mammal survival and downed wood at multiple
scales in managed forests. Journal of Mammalogy 85(1): 87-96.
MANNING, J. A., AND W. D. EDGE. 2008. Small mammal responses to fine woody debris and
forest fuel reduction in southwest Oregon. Journal of Wildlife Management 72(3): 625632.
MASER, C., J. M. TRAPPE, AND R. A. NUSSBAUM. 1978. Fungal-small mammal interrelationships
with emphasis on Oregon coniferous forests. Ecology 59(4): 799-809.
MCCOMB, W. C. 2003. Ecology of coarse woody debris and its role as habitat for mammals.
Mammal community dynamics: management and conservation in the coniferous forests
of western North America. Cambridge University Press, New York, New York, 374-404.

49

MCGRANN, M. C., D. H. V. VUREN, AND M. A. ORDEÑANA. 2013. Influence of adjacent crop type
on occurrence of California ground squirrels on levees in the Sacramento Valley,
California. Wildlife Society Bulletin 38(1): 111-115.
MCNAB, W. H., AND P. E. AVERS, eds. 1994. Ecological Subregions of the United States: Section
Descriptions. Washington, DC. U.S. Department of Agriculture, Forest Service.
Publication WO-WSA-5.
MIDDLETON, J. AND G. MERRIAM. 1983. Distribution of woodland species in farmland woods.
Journal of Applied Ecology 20(2): 625-644.
MILES, S. R. AND C. B. GOUDEY. 1997. Ecological subregions of California. USDA Forest
Service. Publication R5-EM-TP-005. Pp. 5-4
MOHR, J. A., C. WHITLOCK, AND C. N. SKINNER. 2000. Postglacial vegetation and fire history,
eastern Klamath Mountains, California, USA. The Holocene 10(4): 587-601.
MORLEY, C. G. 2002. Evaluating the performance of PIT tags and ear tags in a capture-recapture
experiment. New Zealand Journal of Zoology 29(2): 143-148.
ORDEÑANA, M. A., D. H. V. VUREN, AND J. P. DRAPER. 2012. Habitat associations of California
ground squirrels and Botta's pocket gophers on levees in California. The Journal of
Wildlife Management 76(8): 1712-1717.
OWINGS, D. H., AND M. BORCHERT. 1975. Correlates of burrow location in Beechey ground
squirrels. Western North American Naturalist 35(4): 402-404.
PARKS, C. G., S. R. RADOSEVICH, B. A. ENDRESS, B. J. NAYLOR, D. ANZINGER, L. J. REW, B. D.
MAXWELL, K. A. DWIRE. 2005. Natural and land-use history of the Northwest mountain
ecoregions (USA) in relation to patterns of plant invasions. Perspectives in Plant Ecology,
Evolution and Systematics 7(3): 137-158.
PARMENTER, R. P., AND J. A. MCMAHON. 1989. Animal density estimation using a trapping web
design: Field validation experiments. Ecology 70(1): 169-179.
PARMENTER, R. R., T. L. YATES, D. R. ANDERSON, K. P. BURNHAM, J. L. DUNNUM, A. B.
FRANKLIN, M. T. FRIGGENS, B. C. LUBOW, M. MILLER, G. S. OLSON, C. A. PARMENTER, J.
POLLARD, E. REXSTAD, T. M. SHENK, T. R. STANLEY, AND G. C. WHITE.. 2003. Smallmammal density estimation: a field comparison of grid-based vs. web-based density estimators.
Ecological Monographs 73(1): 1-26.
PEARCE, J., AND L. VENIER. 2005. Small mammals as bioindicators of sustainable boreal forest
management. Forest ecology and management, 208(1), 153-175.
PETERKEN, G. F. 1996. Natural woodland: ecology and conservation in northern temperate
regions. Cambridge University Press.

50

R DEVELOPMENT CORE TEAM. 2008. R: A language and environment for statistical computing. R
Foundation for Statistical Computing, Vienna, Austria.
RAHBEK, C. 1995. The elevational gradient of species richness: a uniform pattern? Ecography
18(2): 200-205.
RISCH, T. S., AND M. J. BRADY. 1996. Trap height and capture success of arboreal small
mammals: evidence from southern flying squirrels (Glaucomys volans). American
Midland Naturalist 136(2): 346-351.
ROSENBERG, D. K., K. A. SWINDLE, AND R. G. ANTHONY. 2003. Influence of prey abundance on
northern spotted owl reproductive success in western Oregon. Canadian Journal of
Zoology 81(10): 1715-1725.
SAKAI, H. F., AND B. R. NOON. 1993. Dusky-footed woodrat abundance in different-aged forests
in northwestern California. The Journal of Wildlife Management 57(2): 373-382.
SAWYER, J. O., D. A. THORNBURGH, AND J. R. GRIFFIN. 1977. Mixed evergreen forest. Pp. 359382 in M. G. Barbour and J. Major, eds. Terrestrial vegetation of California. John Wiley
and Sons, New York, 359-382.
SCHOOLEY, R. L., B. VAN HORNE, AND K. P. BURNHAM. 1993. Passive integrated transponders
for marking free-ranging townsend’s ground squirrels. Journal of Mammalogy 74(2):
480-484.
SCHOOLEY, R. L., P. B. SHARPE, AND B. V. HORNE. 1996. Can shrub cover increase predation risk
for a desert rodent? Canadian Journal of Zoology 74(1): 157-163.
SIKES, R. S., W. L. GANNON, AND THE ANIMAL CARE AND USE COMMITTEE OF THE AMERICAN
SOCIETY OF MAMMALOGISTS. 2011. Guidelines of the American Society of
Mammalogists for the use of wild mammals in research. Journal of Mammalogy 92: 235253.
SKINNER, C. N., A. H. TAYLOR, AND J. K. AGEE. 2006. Klamath Mountains bioregion. Pages 170194 in: N.G. Sugihara, J.W. van Wagtendonk, J. Fites-Kaufmann, K.E. Shaffer, and A.E.
Thode, eds. Fire in California’s ecosystems. University of California Press, Berkeley,
USA.
SLEETER, B. M., AND J. P. CALZIA. 2008. Contemporary land cover change in the Klamath
Mountains Ecoregion in Acevedo, W. eds., Status and Trends of Western United States
Land Cover, U.S. Geological Survey Professional Paper.
SMITH, W. B., P. D. MILES, J. S. VISSAGE, AND S. A. PUGH. 2004. Forest resources of the United
States, 2002. St. Paul, MN: US Department of Agriculture, Forest Service, North Central
Research Station.

51

STEPHENS, R. B., AND E. M. ANDERSON. 2014. Effects of trap type on small mammal richness,
diversity, and mortality. Wildlife Society Bulletin 1-9.
SULLIVAN, T. P. 1979. Demography of populations of deer mice in coastal forest and clear-cut
(logged) habitats. Canadian Journal of Zoology 57(8): 1636-1648.
SULLIVAN, T. P., D. S. SULLIVAN, AND P. M. LINDGREN. 2000. Small mammals and stand
structure in young pine, seed-tree, and old-growth forest, southwest Canada. Ecological
Applications 10(5): 1367-1383.
SULLIVAN, T. P., D. S. SULLIVAN, P. M. F. LINDGREN, AND D. B. RANSOME. 2009. Stand structure
and the abundance and diversity of plants and small mammals in natural and intensively
managed forests. Forest Ecology and Management 258: S127-S141.
SULLIVAN, T. P., D. S. SULLIVAN, P. M. LINDGREN, AND D. B. RANSOME. 2012. If we build
habitat, will they come? Woody debris structures and conservation of forest mammals.
Journal of Mammalogy 93(6): 1456-1468.
SUZUKI, N., AND J. P. HAYES. 2003. Effects of thinning on small mammals in Oregon coastal
forests. The Journal of Wildlife Management 352-371.
SZACKI, J., AND A. LIRO. 1991. Movements of small mammals in the heterogeneous landscape.
Landscape Ecology 5(4): 219-224.
TEVIS, L. 1956. Responses of small mammal populations to logging of Douglas-fir. Journal of
Mammalogy 37(2): 189-196.
USDA FOREST SERVICE. 1981. CALVEG: A Classification of California Vegetation. Pacific
Southwest Region, Regional Ecology Group, San Francisco CA. 168 pp.
VANDRUFF, L. W. AND ROWSE, R. N. 1986. Habitat association of mammals in Syracuse, New
York. Urban Ecology 9: 413-434.
WARD JR., J. P., R. J. GUTIÉRREZ, AND B. R. NOON. 1998. Habitat selection by northern spotted
owls: the consequences of prey selection and distribution. Condor 100: 79-92.
WILK, R. J., M. G. RAPHAEL, C. S. NATIONS, AND J. D. RICKLEFS. 2010. Initial response of
ground-dwelling mammals to forest alternative buffers along headwater streams in the
Washington Coast Range, USA. Forest Ecology and Management 260: 1567-1578.
WILLIAMS, P. J., S. A. WHITMORE, AND R. J. GUTIÉRREZ. 2014. Use of private lands for foraging
by California spotted owls in the central Sierra Nevada. Wildlife Society Bulletin DOI:
10.1002/wsb.445.

52

CHAPTER 2
FINE-SCALE VEGETATIVE COVER AND LAND COVER INFLUENCES ON SMALL
MAMMAL USE IN INDUSTRIAL FORESTS OF NORTHERN CALIFORNIA, USA

Abstract
Limited information exists on small mammal communities in industrial forests of northern
California, USA. Small mammal communities are important components of forest ecosystems
and a better understanding of small mammal relationships to fine-scale habitat features in
industrial forests can aid management. I developed overall and species-specific models to assess
the relationships between small mammals and fine-scale (64m2) habitat features (i.e., shrub, forb,
grass, rock, mineral soil, forest litter, downed wood, and tree). I also assessed fine-scale land
cover category (i.e., clearcut, retention, clearcut-riparian, control, or control-riparian zone). I
trapped small mammals from May to August of 2011-2013 in 65 stands using a web based
trapping design that consisted of both Sherman and Tomahawk live-traps. I captured 11 small
mammal species with the most frequently captured species being Peromyscus spp. and California
ground squirrels in Sherman and Tomahawk traps, respectively. Pooled small mammal captures
in Sherman traps were positively influenced by shrub cover at trapping locations. This
relationship was also observed in Peromyscus spp. and Allen’s chipmunk. In addition, I found
that I captured more Peromyscus spp and pooled small mammals when a trap was placed in
retention areas than in clearcuts. In Tomahawk traps, pooled small mammal captures were
positively influenced by both shrub cover and downed wood. I captured more California ground
squirrels in clearcuts opposed to controls and found forest litter to negatively influence ground
squirrel captures. My findings emphasize the importance of fine-scale habitat elements, primarily

53

downed wood, shrub cover, and retention patches on small mammal habitat use in industrial
forests of northern California.
2.1. Introduction
Small mammal activity and occurrence influences numerous organisms and ecological processes
in forest ecosystems. The distribution and habitat use of numerous predators can be directly
linked to small mammals (Carey et al. 1992). For example, home ranges of Northern Spotted
Owls (Strix occidentalis caurina) in southern Oregon were influenced by the abundance and
diversity of medium-sized prey (e.g., flying squirrels (Glaucomys sabrinus) and woodrats
(Neotoma spp.); Carey et al. 1992). Small mammals can also regulate invertebrate populations
(Buckner 1966; Carey and Johnson 1995; Elkinton et al. 1996; Carey and Harrington 2001).
Elkinton et al. (1996) found that white-footed mice (Peromyscus leucopus) effectively regulated
low populations of gypsy moth (Lymantria dispar). Small mammals are also known seed
dispersers. Maser et al. (1978) documented the importance of small mammals as dispersers of
hypogeous fungal spores in the Pacific Northwest. Monitoring small mammal populations can
reveal structural and functional changes within forest ecosystems (Carey and Harrington 2001;
Pearce and Venier 2005).
Interest in the relationships between small mammal populations and intensive forest
management has recently increased, and likely relates to the growing demand for comprehensive
forest management that includes considerations for wildlife, water quality, and aesthetics.
Studies on small mammals and forest management include the influence and utility of retention
patches (Carey and Wilson 2001; Sullivan and Sullivan 2001; Sullivan et al. 2001;Gitzen et al.
2007), riparian zones (Anthony et al. 1987), downed wood (Carey and Johnson 1995, McComb
2003, Lee 2004, Manning and Edge 2008, Sullivan et al. 2012), and structure of the managed

54

stand (Carey and Johnson 1995, Sullivan et al. 2000, Sullivan et al. 2009). The influence of finescale habitat elements like herbaceous or woody shrub cover, forest litter, small pieces of
downed wood, or the amount of exposed mineral soil on small mammals is less understood.
Forest managers can manipulate several fine-scale features known to benefit small
mammals. Occurrence of these fine scale habitat features are known to positively influence small
mammal survival in moist environments like the Oregon Coast Range (Manning and Edge 2004).
However these finer scale habitat features may be even more important to small mammals where
moisture is limiting during certain times of the year, like in the drier coniferous forests that occur
in some parts of the western United States. For example, understory cover was an important
covariate on small mammal occupancy in dry ponderosa pine (Pinus ponderosa) forests of
northern Arizona (Kalies et al. 2012). Similarly, shrub cover and downed wood were the most
important habitat characteristics affecting small mammal densities in Arizona (Converse et al.
2006).
Some forest landowners are required or have voluntarily adopted retention strategies in
timber harvest areas to supplement wildlife habitat. Retained green trees within timber harvest
areas impact small mammal populations, though study results are variable. For example, Sullivan
and Sullivan (2001) concluded that small mammal abundance and diversity in harvested conifer
forests of British Columbia, Canada, were similar across varying levels of retention due to postharvest colonization by generalists and early successional species. Gitzen et al. (2007) predicted
that small mammal species associated with closed canopy forests would decrease, early
successional species would increase, and habitat generalists would show little response to habitat
retention in coniferous forests of western Oregon and Washington. Some species did not follow
the expected response, leading Gitzen et al. (2007) to suggest that additional factors such as

55

small mammal community composition, latitude, and elevation influenced the response of small
mammals to green-tree retention. Green tree retention, particularly in patches, can correspond to
unique fine-scale habitat features that are different from surrounding timber harvest areas
(Linden and Roloff 2014).
The goal of my research was to explore how small mammals were influenced by finescale habitat features in dry industrial forests to better inform retention practices. My objective
was to correlate the number of captured individual small mammals to fine-scale (64m2) habitat
elements surrounding trap locations. I also evaluated if land cover category (e.g., retention,
riparian zone) at a trapping location influenced captures to determine if fine-scale habitat
features corresponded to existing retention practices. I used a combination of live trapping,
vegetation sampling, and generalized linear mixed models. My response variable for modeling
was the number of uniquely captured individuals at a trap location; this metric represented an
index to the number of animal home ranges overlapping a location. My findings provide insight
into small mammal habitat use in relation to fine-scale features that can be purposefully managed
in industrial forest landscapes of northern California.
2.2. Methods
2.2.1. Study Area
My study was conducted in the Klamath Mountain ecoregion of northern California (Trinity
County, 8,309 km2), USA. The landscape of this ecoregion features heterogeneous and intricate
vegetation patterns partially resulting from diverse climate, topography, and parent materials
(Sawyer et al. 1977). Soil moisture regimes are xeric with soil temperatures varying from mesic
to frigid and some cryic at higher elevations (Miles and Goudey 1997). The climate is considered
Mediterranean, with hot and dry summers (Skinner et al. 2006). Average maximum daily

56

temperatures from May through August range from 25 to 34°C and average precipitation ranges
from 3.4 to 0.5 cm. The coolest and wettest month is May, with the hottest (August) and driest
(July) months toward the end of summer (Weaverville Ranger Station, US Forest Service,
Trinity County).
Land use is predominately forestry, agriculture, tourism, and mining, with 83% of the land
within the ecoregion (47,791 km2) federally owned (Sleeter and Calzia 2008). Historically, fire
was the primary disturbance in this region that shaped forest structure (Mohr et al. 2000).
Current broad scale disturbances include occasional wild fires and industrial forest management.
Vegetation in this region is broadly classified as Douglas-fir (Pseudotsuga menziesii) –
Ponderosa pine (Miles and Goudey 1997), with the industrial forests managed for Douglas-fir,
incense-cedar (Calocedrus decurrens), and ponderosa pine, and secondarily supporting diverse
hardwoods including canyon live oak (Quercus chrysolepis), black oak (Q. kelloggii), and
madrone (Arbutus menziesii).
I conducted this project on timberlands owned and managed by Sierra Pacific Industries
(SPI). The dominant silviculture regime is small-scale (<8 ha) clearcutting followed by site
preparation that includes various combinations of chemical, mechanical, and fire treatments.
Stands in this study were clearcut but contained a diversity of retained structures including
riparian buffers (which are called Watercourse and Lake Protection Zones (WLPZ) in California
regulatory parlance), retention patches, and occasional single, isolated leave trees. Harvested
stands were later replanted (within 1 year of harvest) and monitored periodically for regeneration
success. Stands used for trapping averaged approximately 7-8 ha and were located north and
south of Weaverville, CA on elevations ranging from 679 to 1,467 m.
2.2.2. Experimental Design

57

I trapped from May to August of 2011-2013 in 65 stands that represented four broadly defined
forest classes (Figure 2.1.): 1) recent clearcuts (3-5 years old; 15 stands), 2) 10-20 year-old
plantations (16 stands), 3) rotation-aged stands (60-80 years old; 16 stands), and 4) Watercourse
and Lake Protection Zones (WLPZ; 18 stands). I used a web-based trapping design with a
combination of Sherman (Model LFA, 7.6 x 8.9 x 22.9 cm; H.B. Sherman Traps, Inc.,
Tallahassee, Florida) and Tomahawk (Model 202, 48.3 x 15.2 x 15.2 cm; Tomahawk Live Trap
Co., Tomahawk, Wisconsin) live traps (Parmenter and McMahon 1989; Figure 2.2.). The webbased design was first described by Anderson et al. (1983) and has become a favorite design
among small-mammal researchers because it requires fewer assumptions and is more robust to
smaller sample sizes (Parmenter and McMahon 1989, Parmenter et al. 2003, Bagne and Finch
2010).
During trapping, I placed a single array in a stand. I trapped each array for 3 (2011) to 5
(2012-2013) nights, which constituted a trapping period. After each trapping period I moved the
trapping arrays to the next set of replicate stands. When feasible, one stand of each forest class
was trapped during a sampling period to account for broad-scale small population fluctuations of
small mammals that impacted all stands collectively. Each individual stand was trapped once. A
trapping array consisted of 5 spokes containing 7 nodes with nodes separated by 7 m (Figure
2.2.). I placed a Sherman live trap at each node, resulting in 35 Sherman traps per web. At the
web center and the 3rd and 7th nodes I also placed a Tomahawk live trap, resulting in 11
Tomahawk traps per web. I baited traps with a mixture of whole oats, raisins, creamy peanut
butter, and molasses. Traps were set under or beside ground cover such as logs or heavy foliage
and those at risk of exposure to direct sunlight were shaded. I also applied cotton batting to all
traps. For stands containing riparian zones or leave patches, I placed arrays so that one or more

58

spokes intersected those retention elements. In the WLPZ forest class, webs were centered on the
stream channel yet some spokes extended beyond the WLPZ and into adjacent areas (because
some WLPZs were narrow).
Traps were checked daily between daybreak and noon. Captured animals were marked
with a 9-mm passive integrated transponder (PIT) tag injected via a 12-gauge needle
subcutaneously in the flank (Model HPT9, Biomark, Boise, ID). I used PIT tags instead of ear
tags so that individuals could be identified during subsequent captures with minimal handling, to
increase accuracy of individual identification, and to shorten animal handling time (Schooley et
al. 1993; Morley 2002). Schooley et al. (1993) found no evidence that PIT tagging increased
small mammal mortality.
After marking, animals were released on site for potential recapture. Animals that were
seldom captured or those that were not conducive to tagging (e.g., shrews) were released without
administering a PIT tag. Capture and handling of animals followed guidelines recommended by
the California Department of Fish and Wildlife under scientific collection permit SC-11913, and
was considered exempt by the Institutional Animal Care and Use Committee at Michigan State
University.
2.2.3. Vegetation Sampling
At each web array, a 9m-diameter plot was centered on each individual trap location. The northsouth and east-west diameters of the plot were used for point-line transect surveys of ground
cover. Points were spaced 1 m apart, starting at 1.5 m and ending at 4.5 m from the individual
trap location. I recorded if the point intersected shrub, forb, grass, rock, mineral soil, forest litter,
downed wood, or tree. Forest litter included leaves, needles, pine cones, ash and pulverized slash
from timber harvest. Downed wood was defined as downed logs, branches, and discernible

59

woody slash. I did not set a size limit for inclusion in the downed wood category; therefore, this
category could be considered an amalgam of coarse and fine downed wood. I also recorded
whether the trap locations were in a clearcut, retention, clearcut-riparian, control, or controlriparian zone. Here, control patches correspond to rotation-aged forests and riparian areas were
based on buffer requirements associated with the California Forest Practice Rules (CAL FIRE
2014).
2.2.4. Data Analysis
I calculated the proportion of each ground cover category within the 9m-diameter plot at all
individual trap locations. I generated a correlation matrix of the predictor variables using a
Kendall tau rank correlation coefficient and identified correlated variables (P < 0.05); correlated
variables were not included in the same candidate model. My response variable was the number
of unique individuals captured at a trap location over the course of one trapping period (i.e., 5
nights) for each species. I used generalized linear mixed models (GLMM) with a Poisson
distribution in program R 3.0.2 for estimating the impact of localized ground cover measures on
small mammal species abundance. I also investigated whether the year of sampling or land cover
category (i.e., clearcut, retention, clearcut-riparian, control, or control-riparian zone) of where the
trap was placed influenced small mammal counts for each species. A Kruskal-Wallis rank sum
test was used to determine the significance of these factors on individual small mammal captures
and if I found a significant effect I included the factors in the GLMMs. I included a trapping web
identifier as a random effect in models to account for differences in small mammal abundance
and catchability among trapping arrays that might be caused by broad-scale environmental
phenomenon (e.g., elevation). I used AICc to rank candidate models and deemed model
parameters significant if the 95% confidence intervals did not overlap 0 (Burnham and Anderson

60

2002).
2.3. Results
2.3.1. Vegetation Measures and Land Cover Category at Trap Locations
I sampled 65 stands and recorded vegetation and small mammal data at 2,913 trap locations
during the summers of 2011-2013. For the 64m2 surrounding each trap location, average cover of
forest litter was 31% (SE = 0.4; range = 0 – 100), followed by grass (16%; SE = 0.3; range = 0 –
94), downed wood (14%; SE = 0.3; range = 0 – 94), forb (11%; SE = 0.3; range = 0 – 88),
mineral soil (9%; SE = 0.3; range = 0 – 100), shrub (9%; SE = 0.3; range = 0 – 100), tree (8%;
SE = 0.2; range = 0 - 94), and rock (2%; SE = 0.2; range = 0 - 81). Traps were most commonly
placed in the clearcut land cover category (45%), followed by control (34%), control riparian
(13%), retention (5%), and clearcut-riparian (2%) areas.
Vegetation measures also varied by land cover classification (Table 2.1.). The most
common land cover category at Sherman trap locations was clearcut (n = 1,394) followed by
control (n = 1,176), control-riparian (n = 380), retention (n = 166), and clearcut-riparian (n = 88).
A Kruskal-Wallis rank sum test was used to compare small mammal counts to land cover
category. I found land cover category to significantly influence pooled small mammal counts in
Sherman (2 = 17.594, P = 0.001) and Tomahawk traps (2 = 29.423, P = <0.001), Peromyscus
spp. (2 = 17.875, P = 0.001), and California ground squirrels (2 = 57.272, P = <0.001). Land
cover category did not significantly influence Allen’s chipmunk counts (2 = 6.300, P = 0.178).
In addition, I tested the relationship between counts and year. I found that the year of sampling
significantly influenced pooled small mammals counts in Tomahawks (2 = 7.431, P = 0.024)
and California ground squirrels (2 = 7.294, P = 0.026). Year did not significantly influence
Peromyscus spp. (2 = 2.662, P = 0.264), Allen’s chipmunk (2 = 0.277, P = 0.871), or pooled

61

small mammal counts in Sherman traps (2 = 1.865, P = 0.394)
2.3.2. Small Mammals
I accumulated 12,261 trap nights (87% of the potential trap nights) and caught 11 small mammal
species: white-footed deer mouse (P. maniculatus), brush mouse (P. boylii), California ground
squirrel (Spermophilus beecheyi), Allen’s chipmunk (Tamias senex), dusky-footed woodrat (N.
fuscipes), bushy-tailed woodrat (N. cinerea), Trowbridge’s shrew (Sorex trowbridgii), Douglas
Squirrel (Tamiasciurus douglasii), striped skunk (Mephitis mephitis), western harvest mouse
(Reithrodontomys megalotis), and the California vole (Microtus californicus). I pooled whitefooted deer mice and brush mice into Peromyscus spp. because field differentiation was not
accurate. I marked 380 individuals with a PIT tag; 284 Peromyscus spp., 60 California ground
squirrels, 13 Allen’s chipmunks, 14 dusky-footed woodrats, 5 bushy-tailed woodrats, 3 Douglas
squirrels, and 1 California vole. Peromyscus spp. was the most frequently captured species in
Sherman traps (75% of all captures) whereas California ground squirrel was the most frequently
captured species in Tomahawk traps (16% of all captures).
I tested 18 candidate GLMMs for commonly captured species in Sherman and
Tomahawk traps (Table 2.2.); I also ran the models for pooled small mammal species by trap
type. The top-ranking model for combined small mammal captures in Sherman traps included the
proportion of shrub (ß1) and downed wood (ß2) per 64m2 and land cover category (ß3 = retention;
ß4 = clearcut-riparian; ß5 = old-growth; ß6 = old-growth riparian; Table 2.3.). This model
accounted for 54% of the evidence weight (Table 2.3.) with shrub and retention being significant
(ß1 = 1.43, 95% CI = 0.86, 1.75; ß3 = 0.44, 95% CI = 0.06, 0.83). My findings indicate that
counts of individual small mammals captured in Sherman traps increased as proportions of shrub
increased (Figure 2.3.a) and that I caught more small mammals when a trap was placed in the

62

retention land cover category.
In Tomahawk traps, a top-ranking model and two competing models were identified (i.e.,
ΔAICc < 2.0; Table 2.4.). The top-ranking model included the proportion of shrub (ß1) and
downed wood (ß2) within 64m2 plots, year (ß3 = 2012, ß4 =2013) and land cover category (ß5 =
retention, ß6 = clearcut-riparian, ß7 = old-growth, ß8 = old-growth-riparian). In this model only
downed wood was significant (ß2 = 1.55, 95% CI = 0.25, 2.86); as downed wood cover increased
at Tomahawk trap locations the number of individual small mammals increased (Figure 2.4.).
The top competing model consisted solely of the proportion of downed wood (ß1) and this
parameter was significant (ß1 = 1.43, 95% CI = 0.12, 2.73); more individual small mammals
were caught at Tomahawk trap locations as downed wood increased. The second competing
model from the Tomahawk traps included the proportion of forest litter (ß1), which was also
significant (ß1 = -1.18, 95% CI = -2.34, -0.02); more forest litter resulted in lower small mammal
captures in Tomahawk traps but I caution that this result is heavily influenced by captures of
California ground squirrels.
I identified two top-ranking models for the number of individual Peromyscus spp.
captured in Sherman traps that both accounted for 34% of the evidence weight (Table 2.3.). One
top-ranking model included the proportion of shrub (ß1) per 64m2 and land cover category (ß2 =
retention; ß3 = clearcut-riparian; ß4 = old-growth; ß5 = old-growth riparian; Table 2.3.). In this
model, both shrub and retention were significant (ß1 = 1.39, 95% CI = 0.79, 1.99; ß2 = 0.44, 95%
CI = 0.05, 0.83). The other top-ranking model included the proportion of shrub (ß1) and downed
wood (ß2) per 64m2, and land cover category (ß3 = retention; ß4 = clearcut-riparian; ß5 = oldgrowth; ß6 = old-growth riparian; Table 2.3.) with the proportion of shrub and the retention land
cover category significantly influencing counts (ß1 = 1.44, 95% CI = 0.84, 2.05 ; ß3 = 0.40, 95%

63

CI = 0.01, 0.80). Both of these models indicate that the number of individual Peromyscus spp. at
a trap increased as the proportion of shrub increased (Figure 2.5.) and I caught more individual
Peromyscus in traps placed in retention areas opposed to clearcuts.
The top-ranking model for Allen’s chipmunks captured in Sherman traps included shrub
cover (ß1) per 64m2. Shrub cover was significant (ß1 = 2.99, 95% CI = 5.63, 0.34) indicating that
more individual Allen’s chipmunks were captured as shrub cover increased at the trap locations
(Figure 2.7.). I also identified 4 competing models (Table 2.3.), but only shrub cover was
significant in any of these models.
California ground squirrels were the most frequently captured species in Tomahawk traps.
The top-ranking model for California ground squirrel included the proportion of forest litter (ß1)
in the 64m2 trap area. Forest litter was significant (ß1 = -1.71, 95% CI = -3.25, -0.16) indicating
that individual California ground squirrel counts increased as the amount of forest litter
decreased (Figure 2.6.). In a competing model, the proportion of downed wood (ß1 = 1.98, 95%
CI = 0.23, 3.73) and land cover category were significant; I captured more California ground
squirrels as downed wood increased and fewer individual California ground squirrels when traps
were in controls compared to clearcuts.
2.4. Discussion
During the 2011-13 fields seasons, I captured 11 small mammal species in Sherman and
Tomahawk live-traps on dry industrial managed forests in northern California. The most
frequently captured species were Peromyscus spp. and California ground squirrels in Sherman
and Tomahawk traps, respectively. Captures of small mammal species other than Peromyscus
spp. were low thereby limiting the number of species-specific models that would converge. I
found that shrub cover was positively correlated to the number of individual small mammals

64

captured; this relationship held across multiple taxon and trap types. In Tomahawk traps, downed
wood cover was also found to positively influence pooled small mammal counts. This result is
consistent with other studies from drier environments of the western United States and Canada
that collectively found that fine-scale retention of shrubs and downed wood positively affects
small mammal habitat use (Manning and Edge 2004; Smith and Maguire 2004; Converse et al.
2006; Coppeto et al. 2006; Kalies et al. 2012). I further found that the land cover class at the trap
location had impacted small mammal captures, with higher small mammal counts being recorded
in retention areas. California ground squirrels showed a different trend, with counts of this
species being higher in clearcuts opposed to controls. Collectively, my results indicate that small
mammal habitat use corresponds to fine-scale (64m2) habitat features as well as certain land
cover designations. This fine-scale finding somewhat contradicts patterns observed at larger
scales. For example, Gray (2014:Chapter 1) found that land cover designation was not related to
the likelihood of capturing small mammals in a 6.35ha area surrounding trapping webs.
My species-specific analyses found that Peromyscus spp. were positively associated with
the presence of shrub cover and the retention land cover category. Research results on
Peromyscus and its relationship with shrub and downed are variable. Smith and Maguire (2004)
observed little response by deer mice to shrub cover. In contrast, other studies have found a
positive response by deer mice to shrub cover (Carey and Johnson 1995; Kyle and Block 2000).
Research findings on deer mice in relation to retention practices are contradictory to the
relationship I observed. Several studies have found retention patches to have little influence on
deer mouse abundance. Sullivan and Sullivan (2001) found deer mice to be more abundant in
clearcuts than in retention areas while other studies did not observe significant differences in
deer mouse abundance between clearcuts and retention prescriptions (Klenner and Sullivan

65

2003; Sullivan and Sullivan 2008).
I found that Allen’s chipmunk captures in Sherman traps were positively influenced by
the localized amount of shrub cover. Smith and Maguire (2004) found higher abundances of
yellow-pine chipmunks (Tamias amoenus; a similar species to Allen’s chipmunk) in areas of
high shrub cover. It is likely that Allen’s chipmunks rely on shrub cover for forage and cover.
Chipmunks use shrubs as cover and have been observed placing burrows near the base of shrubs
(Smith and Maguire 2004). In addition, shrubs are used to minimize heat exposure (Chappell
1978) and may produce edible nuts and berries.
I caught more individual California ground squirrels in areas with sparse forest litter,
likely reflecting the relationship between established forests and litter accumulation. California
ground squirrels tend to occur in open areas, likely related to their apparent affinity for disturbed
areas and habitats where predators can visually be detected (Grinnell and Dixon 1918; Owings
and Borchert 1975; Ordeñana et al. 2012). In my study area, recently harvested stands apparently
provide the fine-scale features conducive to California ground squirrels.
My results emphasize the importance of downed wood, shrub cover, and forest litter to
small mammals, however some current forest practices likely reduce these habitat elements in
recent clearcuts. The application of herbicides to control competing vegetation lowers the
amount of living woody and herbaceous vegetation during site preparation, although the
herbicide effect typically lasts for <5 years (Morrison and Meslow 1984; Harrington et al. 1995).
Fire is also commonly used in some landscapes after clearcutting to release nutrients, however,
burning will also reduce vegetative cover and residual downed wood. The adoption of timber
management practices that retain habitat elements like downed wood, green-tree, and riparian
buffers likely help ameliorate these negative impacts on small mammal habitat. Furthermore, it

66

also appears that the retention land cover category is important to small mammals. I found
retention patches to positively influence counts of Peromyscus spp. and pooled small mammals.
In forest management, retention patches are used to provide wildlife refuge as well as aiding
seeding and regeneration after a site has been harvested. My findings are consistent with others
that have deemed retention areas an important component in sustaining small mammal species
(Moses and Boutin 2001; Rosenvald and Lohmus 2008; Lindenmayer et al. 2010).
I acknowledge that the fine-scale habitat associations I documented for the pooled small
mammal community were heavily influenced by the most frequently captured species,
Peromyscus spp., hence my results should be cautiously applied to other species. I also
acknowledge that the analytical model I used did not include spatial autocorrelation among trap
locations within a web, which potentially resulted in a negative bias in the variability of my data.
As a result, those relationships that are marginally significant (i.e., the 95% CI approaches 0)
may be spurious. I used a web-based random effect to account for unmeasured environmental
conditions (e.g., weather, elevation) that may have influenced the localized small mammal
community and thus did not have the ability to explicitly evaluate factors that are known to affect
small mammal capture probability like temperature and precipitation (Converse et al. 2006). In
several of my models I detected a year effect on small mammal counts that could be attributed to
weather or population differences among years.
My findings emphasize the importance of fine-scale retained elements, primarily downed
wood and shrub cover, on small mammal habitat use. I observed the downed wood effect at
multiple scales, including the patch (~6.35ha; Gray 2014:Chapter 1) and micro-site (64m2; this
study). Collectively these results indicate a close, multi-scale relationship between small
mammal abundance and downed wood in dry managed forests. Downed wood is important to

67

small mammals because it provides food, cover and nesting sites (Hallet et al. 2003). Shrub
cover also provides food and vertical cover for small mammal species. Retention of these
features in an industrial forest could potentially increase small mammal abundance and diversity
and contribute to management prescriptions for threatened and endangered predators. However,
it is also important to note that increasing habitat elements such as downed wood and shrubs in
dry forest ecosystems will increase forest floor fuel and could potentially amplify risk of
wildfire. My results for downed wood suggest that a moderate amount of wood may be optimal
for small mammals (i.e., I observed a weak quadratic relationship) and thus I caution against a
management philosophy that strives to leave downed wood in abundance. Finding optimal
amounts of retention elements without increasing wildfire risk or compromising the ability of
forest landowners to regenerate harvested sites for desirable tree species would be particularly
useful to forest managers. My study provides insight into fine-scale retention that can be used to
enhance small mammal habitat.
2.5. Acknowledgements
Summer funding for this research was provided by Sierra Pacific Industries. Academic year
funding was provided by Michigan State University. I would like to thank my advisor, G. Roloff,
and committee members R. Campa and S. Winterstein. I thank M. Block, R. Caster, B. Benson,
S. Houston, C. Brockman, K. Raby, R. Feamster, and J. Kelley for their assistance in the
collection of field data. Additional thanks to the California Department of Fish and Wildlife for
reviewing their animal handling protocol with the field crews and for lending us trapping
supplies.

68

APPENDIX

69

Table 2.1.
Average percent cover within 64 m2 plots at individual trap locations by vegetation and land
cover category in industrial forests of northern California, USA, May-August 2011-13.

70

Table 2.1. (cont’d)
Land Cover
Category
Clearcut

Retention

Clearcut-riparian

Control

Control-riparian

Vegetation
Category
Shrub
Forb
Grass
Rock
Mineral Soil
Forest Litter
Downed Wood
Tree
Shrub
Forb
Grass
Rock
Mineral Soil
Forest Litter
Downed Wood
Tree
Shrub
Forb
Grass
Rock
Mineral Soil
Forest Litter
Downed Wood
Tree
Shrub
Forb
Grass
Rock
Mineral Soil
Forest Litter
Downed Wood
Tree
Shrub
Forb
Grass
Rock
Mineral Soil
Forest Litter
Downed Wood
Tree

Average Percent

Standard Error

Range

7
10
26
3
15
19
14
6
7
4
15
1
11
38
17
7
12
14
15
2
8
37
9
4
7
9
6
1
4
43
12
9
17
19
5
4
2
30
13
9

0.003
0.004
0.006
0.002
0.005
0.005
0.004
0.002
0.012
0.006
0.014
0.014
0.010
0.020
0.013
0.008
0.020
0.019
0.020
0.004
0.019
0.032
0.014
0.009
0.004
0.004
0.003
0.001
0.002
0.008
0.004
0.006
0.010
0.010
0.005
0.005
0.004
0.011
0.007
0.006

0 – 100
0 – 78
0 – 94
0 – 63
0 – 100
0 – 89
0 – 75
0 – 63
0 – 100
0 – 33
0 – 69
0 – 25
0 – 50
0 – 100
0 – 81
0 – 50
0 – 78
0 – 89
0 – 75
0 – 19
0 – 100
0 – 100
0 – 56
0 – 31
0 – 94
0 – 81
0 – 81
0 – 56
0 – 56
0 – 100
0 – 94
0 – 94
0 – 88
0 – 88
0 – 63
0 – 81
0 – 100
0 – 89
0 – 88
0 – 56

71

Table 2.2.
Candidate generalized linear mixed models used to estimate the number of small mammal
captures at individual trap locations in industrial forests of northern California, USA, MayAugust 2011-13.
Candidate Modelsa
1. Forb + Rock + Shrub

10. Grass + Downed Wood

2. Forb + Rock + Tree

11. Forb

3. Grass + Rock

12. Forest Litter

4. Rock + Tree

13. Grass

5. Forb + Shrub

14. Mineral Soil

6. Forb + Rock

15. Rock

7. Forb + Tree

16. Shrub

8. Rock + Shrub

17. Tree

9. Shrub + Downed Wood

18. Downed Wood

a

Proportion forb, rock, tree, grass, shrub, downed wood, mineral soil, and forest litter around

individual trap locations. Year and land cover category were included in species models when
identified as significant via a separate analysis of variance.

72

Table 2.3.
Five top-ranking generalized linear mixed models used to estimate the number of individual
small mammals (pooled across all species), Peromyscus spp., and Allen’s chipmunks in
industrial forests of northern California, USA, May-August 2011-13. Kb = the number of
estimated model parameters, AICc = Akaike Information Criteria adjusted for small sample sizes,
ΔAICc = difference in AIC from top-ranking model, and w = weight of evidence.
K

AICc

ΔAICc

w

Downed Wood + Shrub

8

2635.23

0.00

0.54

Shrub

7

2636.80

1.57

0.24

Forb + Shrub

8

2638.78

3.54

0.09

Rock + Shrub

8

2638.78

3.55

0.09

Forb + Rock + Shrub

9

2640.75

5.52

0.03

Shrub

7

2483.13

0.00

0.34

Downed Wood + Shrub

8

2483.14

0.00

0.34

Rock + Shrub

8

2484.91

1.78

0.14

Forb + Shrub

8

2485.08

1.95

0.13

Forb + Rock + Shrub

9

2486.85

3.71

0.05

Shrub

3

155.95

0.00

0.26

Downed Wood

4

157.09

1.14

0.15

Forest Litter

3

157.18

1.23

0.14

Rock + Shrub

4

157.58

1.63

0.11

Forb + Shrub

4

157.93

1.98

0.10

Species
All small mammalsa

Peromyscus spp.

Allen’s chipmunk

Model

73

Table 2.3. (cont’d)
a

Captures of individual Peromyscus spp., dusky-footed woodrats, bushy-tailed woodrats,

California voles, California ground squirrels, Allen’s chipmunks, Douglas squirrels, and
Trowbridge’s shrews.
b

Models also included an intercept, random effect (Web ID), and year (2011, 2012, 2013) and

category (clearcut, retention, clearcut-riparian, control, or control-riparian zone) factor if
significant via an analysis of variance.

74

Table 2.4.
Five top-ranking generalized linear mixed models used to estimate the number of individual
small mammals and California ground squirrels caught in Tomahawk traps in industrial forests
of northern California, USA, May-August 2011-13. K = the number of estimated model
parameters, AICc = Akaike Information Criteria adjusted for small sample sizes, ΔAICc =
difference in AIC from top-ranking model, and w = weight of evidence.
K

AICc

ΔAICc

w

Shrub + Downed Wood

10

581.81

0.00

0.25

Downed Wood

9

582.25

0.44

0.20

Forest Litter

9

582.39

0.58

0.19

Grass + Downed Wood

10

583.87

2.06

0.09

Shrub

9

584.87

3.06

0.05

Species
All small mammalsa

California ground squirrel

a

Model

Forest Litter

9

410.04

0.00

0.28

Downed Wood

9

410.61

0.57

0.21

Mineral Soil

3

412.08

2.03

0.10

Shrub + Downed Wood

10

412.09

2.04

0.10

Grass + Downed Wood

10

412.59

2.55

0.08

Captures of individual Peromyscus spp., dusky-footed woodrats, bushy-tailed woodrats,

California ground squirrels, Allen’s chipmunks, and Douglas squirrels.

75

Figure 2.1.
Four common forest classes in industrial forests of northern California, USA. Top left = recent
clearcuts (3-5 years old), top right = 10-20 year-old plantations, bottom left = rotation-aged
stands, bottom right = Watercourse and Lake Protections Zones (WLPZs).

76

Figure 2.2.
Small mammal trapping web design, northern California, USA, 2011-13.

7 m (23 ft)

Center Point
Sherman Trap Location
Tomahawk Trap Location

77

Figure 2.3.
Relationship of small mammal counts to proportion of shrub within the 64m2 surrounding
Sherman traps in industrial forests of northern California, USA, 2011-2013. Shaded area
represents the 95% confidence limits.

78

Figure 2.4.
Relationship of all small mammal counts to a) proportion of shrub and b) proportion of downed
wood within 64m2 surrounding Tomahawk traps in industrial forests of northern California, USA,
2011-2013. Shaded area represents the 95% confidence limits.

79

Figure 2.4. (cont’d)

80

Figure 2.5.
Relationship of Peromyscus spp. counts to proportion of shrub within 64m2 surrounding
Sherman traps in industrial forests of northern California, USA, 2011-2013. Shaded area
represents the 95% confidence limits.

81

Figure 2.6.
Relationship of California ground squirrel counts to the proportion of forest litter within 64m2
surrounding Sherman traps in industrial forests of northern California, USA, 2011-2013. Shaded
area represents the 95% confidence limits.

82

Figure 2.7.
Relationship of Allen’s chipmunk counts to the proportion of shrub within 64m2 surrounding
Sherman traps in industrial forests of northern California, USA, 2011-2013. Shaded area
represents the 95% confidence limits.

83

LITERATURE CITED

84

LITERATURE CITED

AMARANTHUS, M., J. M. TRAPPE, L. BEDNAR, AND D. ARTHUR. 1994. Hypogeous fungal
production in mature Douglas-fir forest fragments and surrounding plantations and its
relation to coarse woody debris and animal mycophagy. Canadian Journal of Forest
Research 24: 2157-2165.
ANDERSON, D. R., K. P. BURNHAM, G. C. WHITE, AND D. L. OTIS. 1983. Density estimation of
small mammal populations using a trapping web and distance sampling methods.
Ecology 64: 674-680.
ANTHONY, R. G., E. D. FORSMAN, G. A. GREEN, G. WITMER, AND S. K. NELSON. 1987. Small
mammal populations in riparian zones of different-aged coniferous forests. The Murrelet
68(3): 94-102.
BAGNE, K. E, AND D. M. FINCH. 2010. Response of small mammal populations to fuel treatment
and precipitation in a ponderosa pine forest, New Mexico. Restoration
Ecology 18: 409-417.
BUCKNER, C. H. 1966. Populations and ecological relationships of shrews in tamarack bogs of
southeastern Manitoba. Journal of Mammalogy 47(2): 181-194.
BURNHAM, K. P., AND D. R. ANDERSON. 2002. Model selection and multimodel inference: a
practical information-theoretic approach. Springer-Verlag, New York.
CAL FIRE (CALIFORNIA DEPARTMENT OF FORESTRY AND FIRE PROTECTION). 2014. California
forest practice rules. Title 14, California Code of Regulations Chapters 4, 4.5, and 10.
Sacramento, CA.
CAREY, A. B., S. P. HORTON, AND B. L. BISWELL. 1992. Northern spotted owls: influence of prey
base and landscape character. Ecological Monographs 62(2): 223-250.
design: Field validation experiments. Ecology 70(1): 169-179.
CAREY, A. B., AND M. L. JOHNSON. 1995. Small mammals in managed, naturally young, and oldgrowth forests. Ecological applications 5(2): 336-352.
CAREY, A. B., AND C. A. HARRINGTON. 2001. Small mammals in young forests: implications for
management for sustainability. Forest Ecology and Management 154(1): 289-309.
CAREY, A. B., AND S. M. WILSON. 2001. Induced spatial heterogeneity in forest canopies:
responses of small mammals. The Journal of Wildlife Management 65(4): 1014-1027.
CONVERSE, S. J., W. M. BLOCK, AND G. C. WHITE. 2006. Small mammal population and habitat
response to forest thinning and prescribed fire. Forest Ecology and Management 228(1):
263-273.

85

COPPETO, S. A., D. A. KELT, D. H. V. VUREN, J. A. WILSON, AND S. BIGELOW. 2006. Habitat
associations of small mammals at two spatial scales in the northern Sierra Nevada.
Journal of Mammalogy 87(2): 402-413.
CRAIG, V. J., W. KLENNER, M. C. FELLER, AND T. P. SULLIVAN. 2006. Relationships between deer
mice and downed wood in managed forests of southern British Columbia. Canadian
Journal of Forest Research 36(9): 2189-2203.
CHAPPELL, M. A. 1978. Behavioral factors in the altitudinal zonation of chipmunks (Eutamias).
Ecology: 565-579.
ELKINTON, J. S., W. M. HEALY, J. P. BUONACCORSI, G. H. BOETTNER, A. M. HAZZARD, AND H. R.
SMITH. 1996. Interactions among gypsy moths, white-footed mice, and acorns. Ecology:
77(8): 2332-2342.
FANTZ, D. K., AND R. B. RENKEN. 2005. Short-term landscape-scale effects of forest management
on Peromyscus spp. mice within Missouri Ozark forests. Wildlife Society Bulletin 33(1):
293-301.
GASHWILER, J. S. 1970. Plant and mammal changes on a clearcut in west-central Oregon.
Ecology 51(6): 1018-1026.
GITZEN, R. A., S. D. WEST, C. C. MAGUIRE, T. MANNING, AND C. B. HALPERN. 2007. Response of
terrestrial small mammals to varying amounts and patterns of green-tree retention in
Pacific Northwest forests. Forest Ecology and Management 251(3): 142-155.
GRAY, S. M. 2014. Localized factors correlated with small mammal abundances in industrial
forests of northern California, USA. Thesis, Michigan State University, East Lansing.
GRINNELL, J., AND J. DIXON. 1918. Natural history of the ground squirrels of California.
California State Printing Office.
HALLET, J. G, M. A. O’CONNELL AND C. C. MAGUIRE. 2003. Ecological relationships of
terrestrial small mammals in western coniferous forests. Pp. 120-156 in Mammal
Community Dynamics: Management and Conservation in the Coniferous Forests of
Western North America (Zabel, C. J. and R. G. Anthony, eds.). Cambridge University
Press, New York, New York, USA.
HARRINGTON, T.B., R.G. WAGNER, S.R. RADOSEVICH, AND J.D. WALSTAD. 1995. Interspecific
competition and herbicide injury influence 10-year responses of coastal Douglas-fir and
associated vegetation to release treatments. Forest Ecology and Management 76: 55-67.
KALIES, E. L., B. G. DICKSON, C. L. CHAMBERS, AND W. W. COVINGTON. 2012. Community
occupancy responses of small mammals to restoration treatments in ponderosa pine
forests, northern Arizona, USA. Ecological Applications 22(1): 204-217.

86

KIRKLAND JR., G. L. 1990. Patterns of initial small mammal community change after clearcutting
of temperate North American forests. Oikos 59(3): 313-320.
KLENNER, W., AND T. P. SULLIVAN. 2003. Partial and clear-cut harvesting of high-elevation
spruce fir forests: implications for small mammal communities. Canadian Journal of
Forest Research 33(12): 2283-2296.
KYLE, S. C., AND W. M. BLOCK. 2000. Effects of wildfire severity on small mammals in northern
Arizona ponderosa pine forests. In: Moser, W.K., Moser, C.F. (Eds.), Fire and Forest
Ecology: Innovative Silviculture and Vegetation Management. Tall Timbers Fire Ecology
Conference Proceedings, vol. 21, pp. 163-168.
LEE, S. D. 2004. Population dynamics and demography of deermice (Peromyscus maniculatus)
in heterogeneous habitat: role of coarse woody debris. Polish Journal of Ecology 52(1):
55-62.
LEE, S. D. 2012. Association between coarse woody debris and small mammals and
insectivores in managed forests. Journal of Ecology and Environment, 35(3): 189-194.
LINDEN, D.W., AND G.J. ROLOFF. 2014. Retained structures and bird communities in clearcut
forests of the Pacific Northwest, USA. Forest Ecology and Management 310:1045-1056.
LINDENMAYER, D. B., E. KNIGHT, L. MCBURNEY, D. MICHAEL, AND S. C. BANKS. 2010. Small
mammals and retention islands: an experimental study of animal response to
alternative logging practices. Forest ecology and management 260(12): 2070-2078.
MANNING, J. A., AND W. D. EDGE. 2004. Small mammal survival and downed wood at multiple
scales in managed forests. Journal of Mammalogy 85(1): 87-96.
MANNING, J. A., AND W. D. EDGE. 2008. Small mammal responses to fine woody debris and
forest fuel reduction in southwest Oregon. Journal of Wildlife Management 72(3): 625632.
MASER, C., J. M. TRAPPE, AND R. A. NUSSBAUM. 1978. Fungal-small mammal interrelationships
with emphasis on Oregon coniferous forests. Ecology 59(4): 799-809.
MCCOMB, W. C. 2003. Ecology of coarse woody debris and its role as habitat for mammals.
Mammal community dynamics: management and conservation in the coniferous forests
of western North America. Cambridge University Press, New York, New York, 374-404.
MILES, S. R. AND C. B. GOUDEY. 1997. Ecological subregions of California. USDA Forest
Service. Publication R5-EM-TP-005. P. 5-4
MOHR, J. A., C. WHITLOCK, AND C. N. SKINNER. 2000. Postglacial vegetation and fire history,
eastern Klamath Mountains, California, USA. The Holocene 10(4): 587-601.

87

MORLEY, C. G. 2002. Evaluating the performance of PIT tags and ear tags in a capture-recapture
experiment. New Zealand Journal of Zoology 29(2): 143-148.
MORRISON, M.L., AND E.C. MESLOW. 1984. Effects of the herbicide glyphosate on bird
community structure, western Oregon. Forest Science 30: 95-106.
MOSES, R. A., AND S. BOUTIN. 2001. The influence of clear-cut logging and residual leave
material on small mammal populations in aspen-dominated boreal mixedwoods.
Canadian Journal of Forest Research 31(3): 483-495.
ORDEÑANA, M. A., D. H. V. VUREN, AND J. P. DRAPER. 2012. Habitat associations of California
ground squirrels and Botta's pocket gophers on levees in California. The Journal of
Wildlife Management 76(8): 1712-1717.
OWINGS, D. H., AND M. BORCHERT. 1975. Correlates of burrow location in Beechey ground
squirrels. Western North American Naturalist 35(4): 402-404.
PARMENTER, R. P., AND J. A. MCMAHON. 1989. Animal density estimation using a trapping web
design: Field validation experiments. Ecology 70(1): 169-179.
PARMENTER, R. R., T. L. YATES, D. R. ANDERSON, K. P. BURNHAM, J. L. DUNNUM, A. B.
FRANKLIN, M. T. FRIGGENS, B. C. LUBOW, M. MILLER, G. S. OLSON, C. A. PARMENTER, J.
POLLARD, E. REXSTAD, T. M. SHENK, T. R. STANLEY, AND G. C. WHITE. 2003. Smallmammal density estimation: a field comparison of grid-based vs. web-based density
estimators. Ecological Monographs 73(1): 1-26.
PEARCE, J., AND L. VENIER. 2005. Small mammals as bioindicators of sustainable boreal forest
management. Forest ecology and management 208(1): 153-175.
ROSENVALD, R., AND A. LOHMUS. 2008. For what, when, and where is green-tree retention
better than clear-cutting? A review of the biodiversity aspects. Forest Ecology and
Management 255(1): 1-15.
SAWYER, J. O., D. A. THORNBURGH, AND J. R. GRIFFIN. 1977. Mixed evergreen forest. Pp. 359382 in M. G. Barbour and J. Major, eds. Terrestrial vegetation of California. John Wiley
and Sons, New York, 359-382.
SCHOOLEY, R. L., B. VAN HORNE, AND K. P. BURNHAM. 1993. Passive integrated transponders
for marking free-ranging townsend’s ground squirrels. Journal of Mammalogy 74(2):
480-484.
SKINNER, C. N., A. H. TAYLOR, AND J. K. AGEE. 2006. Klamath Mountains bioregion. Pages 170194 in: N.G. Sugihara, J.W. van Wagtendonk, J. Fites-Kaufmann, K.E. Shaffer, and A.E.
Thode, eds. Fire in California’s ecosystems. University of California Press, Berkeley,
treatment and precipitation in a ponderosa pine forest, New Mexico. Restoration
USA.

88

SLEETER, B. M., AND J. P. CALZIA. 2008. Contemporary land cover change in the Klamath
Mountains Ecoregion in Acevedo, W. eds., Status and Trends of Western United States
Land Cover, U.S. Geological Survey Professional Paper.
SMITH, T. G., AND C. C. MAGUIRE. 2004. Small-mammal relationships with down wood and
antelope bitterbrush in ponderosa pine forests of central Oregon. Forest Science 50(5):
711-728.
SULLIVAN, T. P. 1979. Demography of populations of deer mice in coastal forest and clear-cut
(logged) habitats. Canadian Journal of Zoology 57(8): 1636-1648.
SULLIVAN, T. P., D. S. SULLIVAN, AND P. M. LINDGREN. 2000. Small mammals and stand
structure in young pine, seed-tree, and old-growth forest, southwest Canada. Ecological
Applications 10(5): 1367-1383.
SULLIVAN, T.P., D. S. SULLIVAN, AND P. M. F. LINDGREN. 2001. Influence of variable retention
harvests on forest ecosystems. I. Diversity and population dynamics of small mammals.
Journal of Applied Ecology 38(6): 1221–1233.
SULLIVAN, T.P., D. S. SULLIVAN. 2001. Influence of variable retention harvests on forest
ecosystems. II. Diversity and population dynamics of small mammals. Journal of Applied
Ecology 38(6): 1234–1252.
SULLIVAN, T. P., D. S. SULLIVAN, AND P. M. F. LINDGREN. 2008. Influence on variable retention
harvests on forest ecosystems: Plant and mammal responses up to 8 years post-harvest.
Forest Ecology and Management 254(2): 239-254.
SULLIVAN, T. P., D. S. SULLIVAN, P. M. F. LINDGREN, AND D. B. RANSOME. 2009. Stand structure
and the abundance and diversity of plants and small mammals in natural and intensively
managed forests. Forest Ecology and Management 258: S127-S141.
SULLIVAN, T. P., D. S. SULLIVAN, P. M. LINDGREN, AND D. B. RANSOME. 2012. If we build
habitat, will they come? Woody debris structures and conservation of forest mammals.
Journal of Mammalogy 93(6): 1456-1468.
TEVIS, L. 1956. Responses of small mammal populations to logging of Douglas-fir. Journal of
Mammalogy 37(2): 189-196.

89

CONCLUSIONS

My thesis focused on small mammal communities and how they relate to timber management in
industrial forests. Specifically, I examined overall and species-specific responses to forest type
and retention elements at two scale: 1) patch-level (~6.35ha), and 2) and fine scales (64m2). This
research informs forest managers and provides detail on habitat elements that are important to
small mammals in industrial forest landscapes. The strengths of this research are that: 1) the
analysis of populations were conducted at multiple scales (patch-level ~6.35 ha; fine-scale
~64m2), 2) the research was conducted in relation to current forest management practices, and 3)
the results provide a ranking and graphic portrayal of the species-specific relationships of small
mammals to varying habitat elements. The limitations of my study include: 1) low captures for
some small mammals that made inference difficult for those species, 2) inability to directly
account for weather impacts on small mammal numbers, and 3) lack of a spatial autocorrelation
term (Chapter 2) in my models potentially biasing my parameter estimates. I recommend that
future research focuses on downed wood and shrubs, recognizing that a balance must be reached
among forest operational needs (e.g., ability to regenerate trees, control wildfire risk) and the
provision of wildlife habitat. For example, the retention of slash piles and windrows has been a
topic of recent study (e.g., Sullivan et al. 2012) but additional research is needed.
In Chapter 1, I used generalized linear mixed models to evaluate how forest class,
downed wood volume, and proximate forest classes influenced localized (~6.35 ha) abundances
for commonly captured small mammal species. I found proximate forest class and downed wood
volume to be more influential than the forest class containing trapping grids on small mammal
abundance. Peromyscus spp. and Neotoma spp. displayed a positive relationship with proximate

90

WLPZ forest class. Peromyscus spp. captures also increased with increasing downed wood
volume, however, the opposite pattern was observed in California ground squirrels and Allen’s
chipmunks. My findings indicate that the diverse habitat mosaic commonly associated with
forest practices in northern California creates a variety of habitats and corridors conducive to the
small mammal species that I commonly captured.
In Chapter 2, I assessed the relationship between fine-scale (64m2) habitat features and
land cover category at trapping locations to small mammal counts. I developed overall and
species-specific GLMMs and found shrub and downed wood to be significant parameters
influencing small mammal captures in Sherman and Tomahawk live-traps. Shrub and downed
wood also positively influenced Peromyscus spp. captures. Allen’s chipmunk counts were
positively associated with shrub cover while California ground squirrel counts responded
negatively to forest litter. My findings emphasize the importance of fine-scale retained elements,
primarily downed wood and shrub cover, on small mammal habitat use in industrial forests of
northern California.
It appears that current practices that influence patch configuration and fine-scale habitat
elements on industrial timberlands encourage small mammal occupancy and abundance.
However, I note that responses to timber practices are often species-specific. In addition,
management recommendations and relationships observed in this study are relative to industrial
forests of northern California but may be applicable to forests in other arid regions. Continuous
research on retention practices is needed to inform discussions on Forest Practices Rules and
management so that landowners can adapt when necessary. This study, along with others in the
Pacific Northwest, indicate that retention practices on industrial forests influence small mammal
species and findings should be used to inform future forest management.

91

LITERATURE CITED

92

LITERATURE CITED

SULLIVAN, T. P., D. S. SULLIVAN, P. M. LINDGREN, AND D. B. RANSOME. 2012. If we build
habitat, will they come? Woody debris structures and conservation of forest mammals.
Journal of Mammalogy 93(6): 1456-1468.

93