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PERSONALITY IN MICHIGAN’S PEROMYSCUS
By

Lauri L. Torgerson

A THESIS

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

MASTER OF SCIENCE
Zoology

2010

ABSTRACT
PERSONALITY IN MICHIGAN’S PEROMYSCUS
By
Lauri Lynn Torgerson
An emerging area of research investigates the ecological implications of
repeatable individual differences in behavior. A personality is any behavior that is
repeatable over time and across contexts. I examined inter- and intraspeciﬁc variation in
personality in Peromyscus leucopus noveboracencis, the white-footed mouse, and P.
maniculatus gracilis, the woodland deer mouse, as a mediator of coexistence and
dispersal. I used open-ﬁeld trials and principal component analysis to extract axes that
describe activity, sociality, aggression, and location. I then used linear, generalized
linear, and mixed effect models to reveal that P. maniculatus was more active and social
than P. leucopus. In dyadic trials, sociality and aggression of the focal mouse were
independent of the species of the opponent mouse. Analyses with raw variables
indicated that both species approached heterospeciﬁcs more than conspeciﬁcs, and
retreated from P. maniculatus more than ﬁom P. leucopus. Because extreme over-
winter mortality leﬁ my study area almost vacant, I used behavioral axes to examine
arrival date in dispersers. Early dispersers were more active, social, and submissive than
late-season dispersers. Activity and sociality were also plastic over time, with the trend
among all mice being to reduce activity and sociality as the season progressed. These
studies illustrate that personality may be an axis of niche differentiation and is
important in describing dispersal phenotypes in Peromyscus, thus illustrating the value

of including personality in ecological studies.

ACKNOWLEDGMENTS

My research advisers, Dr. Andrew McAdam and Dr. Barb Lundrigan, have
been valuable mentors to me throughout this process. Without their help in teaching
me how to form (and challenge) my own ideas, I would not have gotten to this point or
enjoyed the process as much as I have. Without their help on earlier versions of these
papers, I would not have learned the value of real scientiﬁc rigor and persistence in
making my work the best it can be. They have guided, motivated, and inspired me to
be the best scientist I can be. I would also like to thank my committee member Dr.
Kay Holekamp for offering help whenever it has been needed.

I would like to thank Phil Myers and Susan Hoffman for advising on trapping
site selection and the Michigan DNR for allowing us to work in the Pigeon River State
Forest; Faye d’Eon—Eggerston and Stephanie Zimmer for invaluable assistance in the
ﬁeld; the Michigan State University Museum, Brian Maurer, and Phil Myers for traps;
Susan Hoffman and Rosa Moscarella for ﬁeld supplies; Tom L’Ecuyer for lending
laboratory equipment; and the McAdam Lab members for comments on a previous
draft of these manuscripts. This research was funded by Michigan State University,
the University of Guelph, and the American Society of Mammalogists.

Finally, I’d like to thank my friends and family for supporting me through this

journey. Without them, I could not have made it through this last year.

iii

TABLE OF CONTENTS

LIST OF TABLES ........................................................................................................ vi

LIST OF FIGURES ...................................................................................................... vii
CHAPTER I

Introduction to Peromyscus, personality, coexistence, and dispersal ............................. 1

Coexistence in Peromyscus leucopus and P. maniculatus gracilis ........ 2

Dispersal ................................................................................................. 4

Sample sizes in study .............................................................................. 4

Hypotheses and Predictions .................................................................... 5

Literature Cited ................................................................................................... 6
CHAPTER 2

Inter- and intraspeciﬁc variation in the personality of sympatric Peromyscus ............. 9

Introduction ........................................................................................................ 9

Materials and Methods ..................................................................................... 13

Study site and population ..................................................................... 13

Open ﬁeld behavioral trials .................................................................. 14

Data extraction ...................................................................................... 16

Statistical analyses ................................................................................ 17

Results .............................................................................................................. l9

Interspeciﬁc differences in behavior .................................................... 19

Intraspeciﬁc variation and individual repeatability .............................. 23

Correlation of behavioral axes across contexts to form personalities .. 24
No difference in dyadic behavior between interspeciﬁc and intraspeciﬁc

dyads ..................................................................................................... 24
Discussion ......................................................................................................... 25
Activity ................................................................................................. 26
Contact with opponent mouse .............................................................. 28
Arboreality ............................................................................................ 28
Dyadic trials... ...................................................................................... 29
Differences in activity level could allow coexistence in a changing
environment .......................................................................................... 30
Literature Cited ................................................................................................. 37
CHAPTER 3
Personality is associated with dispersal in Peromyscus ............................................... 43
Introduction ...................................................................................................... 43
Materials and Methods ..................................................................................... 46
Study site and population ..................................................................... 46
Extraction of behavioral axes ............................................................... 46
Statistical analyses ................................................................................ 48
Results .............................................................................................................. 50

iv

Model selection .................................................................................... 50
Do early dispersers differ in personality because of individual variation,

plasticity, or habituation? .................................................................... 50

Discussion ......................................................................................................... 5 1

Activity ................................................................................................. 53

Sociality ................................................................................................ 53

Aggression ............................................................................................ 54

Conclusion ............................................................................................ 55

Literature Cited ................................................................................................. 61
CHAPTER 4

General conclusion: Personality in Peromyscus ........................................................... 64

Literature Cited ................................................................................................. 68

Table 2.1

Table 2.2

Table 3.1

Table 3.2

Table 3.3

LIST OF TABLES

Ecological and morphological differences between Peromyscus
leucopus and Peromyscus maniculatus. In cases where the subspecies
and/or location are not noted, it is assumed that this information was
not available and that the characteristics are representative of each
species as a whole. ................................................................................ 32

Loadings from the principal component analysis using the correlation
matrix of behavioral variables from basic, scent, and dyadic trials for
both Peromyscus maniculatus and Peromyscus leucopus. Zeros are
used for variables with very small loadings (close to zero). Behaviors
refer to the proportion of time spent doing each behavior or in each area
of the arena, unless noted otherwise. Behaviors that were measured as
count data are indicated by a # sign ...................................................... 34

Behavioral axes in Peromyscus leucopus and Peromyscus maniculatus
uncovered during open-ﬁeld trials ........................................................ 57

Candidate models to describe arrival date in Peromyscus leucopus and
Peromyscus maniculatus. Slopes (b), standard errors (SE), t-values and
p-values are presented for each predictor variable, while F-statistics,
degrees of freedom, and p-values are presented for each model .......... 58

Candidate models to describe arrival date in Peromyscus Ieucopus and

Peromyscus maniculatus, and Akaike’s Information Criteria (AICC)
results for effects of basic and personality variables on arrival date.

Number of parameters (model complexity) is represented by Ki. Models
were evaluated based on differences among AICC scores (Ai) and AICC
weights (wi). Model rank is based on differences among AICC scores.59

vi

Figure 2.1

Figure 2.2

Figure 3.]

LIST OF FIGURES

Principal component scores from the basic trial and the scent trial PCA
on Peromyscus maniculatus and Peromyscus Ieucopus (displaying ﬁrst

trial scores only). PCIbasic and PC 1 seem are both interpreted as activity
axes. Boxplot lines represent the minimum, maximum, quartiles, and
median, from the outside in. An asterisk indicates a signiﬁcant
difference between species. The diagonal line represents the regression

line ofPClbasic on Pc1scent (F = 23.4, d.f. = 1, 55, P < 0.0001) ....... 35

Principal component scores from the dyadic trial PCA on Peromyscus
maniculatus and Peromyscus Ieucopus (displaying ﬁrst trial scores

only). PCIdyadic is interpreted as a sociality axis, while Pczdyadic is
interpreted as an aggression axis. Boxplot lines represent the minimum,

maximum, quartiles, and median, from the outside in. An asterisk
indicates a signiﬁcant difference between species ............................... 36

Partial residual plots created using the best model from AICC selection
describing activity, sociality, and aggression of dispersing Peromyscus
Ieucopus and Peromyscus maniculatus in relation to their arrival date
on the grid ............................................................................................. 60

vii

CHAPTER ONE
Introduction to Peromyscus, personality, coexistence and dispersal

Psychologists have long studied consistent individual differences in human
behavior, or personalities (Allport 1937; Cattell 1946), and their impacts on an
individual’s place in society (Anderson et al. 2001; Goldberg 1972; Zhang and Arvey
2009). Until recently, ecologists and evolutionary biologists have regarded individual
differences in animal behavior as noise. However, recent research has begun to examine
the ecological and evolutionary implications of repeatable individual differences in
behavior. These are termed temperaments (Réale et al. 2007), behavioral syndromes
(Sih et al. 2004), or personalities (Dingemanse et al. 2003). For the purpose of this
thesis, I will use the term personality to refer to any behavior that is repeatable over
time and across contexts. Personalities can strongly inﬂuence community ecology,
population dynamics, and landscape ecology (Réale et al. 2007), possibly lending
insight into studies of coexistence and dispersal. This thesis seeks to examine the role of
animal personality in species coexistence and dispersal in deer mice of the genus
Peromyscus.

The white-footed mouse, Peromyscus Ieucopus noveboracensis, and the
woodland deer mouse, P. maniculatus gracilis, live both allopatrically and
sympatrically in the Great Lakes region and have experienced climate-induced
geographic range changes and shifts in relative abundance in recent years (Myers et al.
2009). Since 1980, populations of P. Ieucopus, the more southern congener, have
expanded northward and eastward from Wisconsin into the Upper Peninsula of

Michigan and become sympatric with Michigan P. maniculatus populations. Coincident

declines in P. maniculatus gracilis, the northern congener, have been observed in the
northern Lower Peninsula of Michigan (Myers et al. 2005; Myers et al. 2009).

In 2008, I live-trapped P. Ieucopus and P. maniculatus gracilis in the Pigeon
River State Forest, MI with the goal of uncovering inter- and intraspeciﬁc variation in
personality that might mediate species coexistence and explain recent geographic range
shifts and shifts in relative abundance. My study area supported one resident mouse in
early May, leaving a large area to be re-colonized. In the fall, the grid supported 40
residents. The extremely low spring abundance allowed me to examine how personality
mediated dispersal over the course of the season.

Coexistence in Peromyscus Ieucopus and P. maniculatus gracilis

To coexist stably, sympatric species need to differentiate niche space in
attributes such as their ecology or morphology (Gause 1934; Hardin 1960; MacArthur
and Levins 1967). Among some sympatric species, differential use of microhabitat has
been cited as enabling coexistence (Price and Kramer 1984). When microhabitat is not
partitioned spatially, small mammals might still partition the microhabitat temporally
(Hairn and Rozenfeld 1993; Kotler et al. 1993). In mice of the genus Peromyscus that
occupy the same microhabitat at the same time, coexistence is sometimes accomplished
through food partitioning (Smartt 1978; Wolff et al. 1985). While time, space, or food
partitioning are often sufﬁcient to explain coexistence in small mammals, in cases
where these axes are inadequate, we are unable to predict how the relative abundance of
competing species will respond to the changing environment in which they live

(Munkemuller et al. 2009).

 

Much research has examined the similarities and differences between
Peromyscus Ieucopus noveboracensis and either P. maniculatus gracilis (the subspecies
I studied) or a similar subspecies, P. m. nubiterrae, the cloudland deer mouse.
Peromyscus Ieucopus and P. maniculatus nubiterrae have similar population ecologies
and feeding habits (Wolff 1985a; Wolff et al. 1985), but some research has suggested
that the two species exhibit differences in microhabitat use, nest use, and winter
survivorship. One study showed that Peromyscus Ieucopus was active earlier in the
night and when the weather was comparably warmer, more humid, and more overcast
when compared with P. m. gracilis (Drickamer and Capone 1977). Another study
suggested that Peromyscus maniculatus gracilis used larger nests, increased food
hoarding behavior, and a greater use of torpor in winter (Pierce and Vogt 1993). Both
mice prefer arboreal nests when in allopatry, but P. Ieucopus seemed to move to ground
nests when sympatric with P. m. nubiterrjae (Dooley and Dueser 1996). Coexistence of
these two species has been partially attributed to interspeciﬁc differences in winter
acclimatization paired with ﬂuctuating environmental conditions, which allow P.
Ieucopus to increase in relative abundance during summers and warm years and P.
maniculatus to increase in relative abundance during winters and cold years (P. m.
gracilis—Long 1996; P. m. nubitterae—Wolff 1996). Despite a great deal of research
on these species, niche axes that allow their coexistence remain largely unknown. This
could be because morphology and ecology are not the primary niche axes in which
these two coexisting species differentiate themselves and should thus lead us to examine

personality as a potential axis of niche differentiation.

Dispersal

Much is already known about dispersal in P. Ieucopus and P. maniculatus. Two
types of dispersers have been identiﬁed, colonists and non-colonists. Colonists are adult
mice that disperse into habitat that has experienced extreme winter mortality early in the
spring, while non-colonizing late-season dispersers disperse into an already populated
area (Krohne et al. 1984). Among all dispersers, males disperse more often and farther
than females (Jacquot and Vessey 1995; Krohne et al. 1984). On the contrary, if one
considers only colonist dispersers, females disperse slightly more often than males, and
are adults (J acquot and Vessey 1995; Krohne et al. 1984). While much is known about
what ages and sexes are most likely to disperse, less is known about what actually
drives certain individuals to disperse. I propose that personality may be a motivating
force behind dispersal.

The decision to disperse is affected by external factors like inbreeding risk and
competition, and internal phenotypic factors like physiology, morphology, life history,
and behavior (Clobert et a1. 2009). Inter-individual variation in personality axes,
including sociality, aggression, exploration, and boldness, has been linked to dispersal
in several vertebrate species and may lend insight into the question of what personality
phenotypes are most likely to colonize de-populated habitats (Cote and Clobert 2007;
Cote et al. 2010; Dingemanse et al. 2003; Duckworth and Badyaev 2007).

Sample sizes in study

In 2008, I live-trapped Peromyscus Ieucopus noveboracensis and P. maniculatus

gracilis in the Pigeon River State Forest. I trapped 142 mice a total of 622 times.

Twenty-eight of these mice were P. Ieucopus and 44 were P. maniculatus. Because they

were not used in open-ﬁeld behavioral trials, I did not identify the species of the
remaining 70 mice. To investigate the following hypotheses, I performed open-ﬁeld
behavioral trials designed to extract behavioral axes on 40 P. maniculatus individuals
and 18 P. Ieucopus individuals. I also performed dyadic trials on 17 P. maniculatus
individuals and 12 P. Ieucopus individuals.

Hypotheses and Predictions

In Chapter 2, I used behavioral variables extracted from videos of open-ﬁeld
trials to examine inter- and intraspeciﬁc variation in Peromyscus Ieucopus
noveboracensis and P. maniculatus gracilis. I tested the prediction that P. maniculatus
would be more active than P. Ieucopus and that activity level would be correlated across
contexts to form a personality.

In Chapter 3, I used three of the four behavioral axes (activity, sociality, and
aggression) that were uncovered in Chapter 2 to create linear models and mixed effects
linear models that described the behavioral phenotypes of mice that dispersed onto my
grid throughout the season. To determine if plasticity had any effect on the relationship
between personality and arrival date, I also examined the effects of plasticity and

habituation on these personality axes.

 

LITERATURE CITED

Allport, G. W. 1937. Personality: a psychological interpretation. H. Holt and company,
New York.

Anderson, C., O. P. John, D. Keltner, and A. M. Kring. 2001. Who attains social status?
Effects of personality and physical attractiveness in social groups. Journal of
Personality and Social Psychology 81:116-132.

Cattell, R. B. 1946. Description and measurement of personality. World book company,
Yonkers-on-Hudson, N.Y.

Clobert, J ., J. F. Le Galliard, J. Cote, S. Meylan, and M. Massot. 2009. Informed
dispersal, heterogeneity in animal dispersal syndromes and the dynamics of
spatially structured populations. Ecology Letters 12:197-209.

Cote, J ., and J. Clobert. 2007. Social personalities inﬂuence natal dispersal in a lizard.
Proceedings of the Royal Society BeBiological Sciences 274:383-390.

Cote, J ., S. F ogart, K. Weinersmith, T. Brodin, and A. Sih. 2010. Personality traits and
dispersal tendency in the invasive mosquitoﬁsh (Gambusia aﬂinis). Proceedings

of the Royal Society. B, Biological sciences, published online before print
January 13, 2010, doi:10.1098/rspb.2009.2128.

Dingemanse, N. J ., C. Both, A. J. van Noordwijk, A. L. Rutten, and P. J. Drent. 2003.
Natal dispersal and personalities in great tits (Paras major). Proceedings of the
Royal Society of London Series B-Biological Sciences 270:741-747.

Dooley, J. L., and R. D. Dueser. 1996. Experimental tests of nest site competition in
two Peromyscus species. Oecologia 105:81-86.

Drickarner, L. C., and M. R. Capone. 1977. Weather parameters, trappability and niche
separation in 2 sympatric species of Peromyscus. American Midland Naturalist
98:376-381.

Duckworth, R. A., and A. V. Badyaev. 2007. Coupling of dispersal and aggression
facilitates the rapid range expansion of a passerine bird. Proceedings of the
National Academy of Sciences of the United States of America 104:15017-
15022.

Gause, G. F. 1934. The struggle for existence. The Williams & Wilkins company,
Baltimore.

Goldberg, L. R. 1972. Student personality characteristics and optimal college learning
conditions - Extensive search for trait by treatment interaction effects.
Instructional Science 1 : 1 53-210.

Haim, A., and F. M. Rozenfeld. 1993. Temporal segregation in coexisting Acomys
species - The role of odor. Physiology & Behavior 54:1159-1161.

Hardin, G. 1960. Competitive exclusion principle. Science 131:1292-1297.

Jacquot, J. J., and S. H. Vessey. 1995. Inﬂuence of the natal environment on dispersal
of white-footed mice. Behavioral Ecology and Sociobiology 37:407-412.

Kotler, B. P., J. S. Brown, and A. Subach. 1993. Mechanisms of species coexistence of
optimal foragers - Temporal partitioning by two species of sand dune gerbils.
Oikos 67:548-556.

Krohne, D. T., B. A. Dubbs, and R. Baccus. 1984. An analysis of dispersal in an
unmanipulated population of Peromyscus Ieucopus. American Midland
Naturalist l 12: 146-156.

Long, C. A. 1996. Ecological replacement of the Deer Mouse, Peromyscus maniculatus,
by the White-footed Mouse, P. Ieucopus, in the Great Lakes region. Canadian
F ield-Naturalist 110:271-277.

MacArthur, R., and R. Levins. 1967. Limiting similarity convergence and divergence of
coexisting species. American Naturalist 101 :377-3 80.

Munkemuller, T., B. Reineking, J. Travis, H. Bugrnann, and K. Johst. 2009.
Disappearing refuges in time and space: how environmental change threatens
species coexistence. Theoretical Ecology 2:217-227.

Myers, P., B. Lundrigan, and R. Vande Kopple. 2005. Climate Change and the
Distribution of Peromyscus in Michigan: Is Global Warming Already Having an
Impact? University of California Publications in Zoology.

Myers, P., B. L. Lundrigan, S. M. G. Hoffman, A. P. Haraminac, and S. H. Seto. 2009.
Climate-induced changes in the small mammal communities of the Northern
Great Lakes Region. Global Change Biology 15:1434-1454.

Pierce, S. S., and F. D. Vogt. 1993. Winter acclimatization in Peromyscus maniculatus
gracilis, P. Ieucopus noveboracensis, and P. I. Ieucopus. Journal of Mammalogy

74:665-677.

Price, M. V., and K. A. Kramer. 1984. On measuring microhabitat afﬁnities with
special reference to small mammals. Oikos 42:349-354.

Re'ale, D., S. M. Reader, D. Sol, P. T. McDougall, and N. J. Dingemanse. 2007.
Integrating animal temperament within ecology and evolution. Biological
Reviews 82:291-318.

Sih, A., A. Bell, and J. C. Johnson. 2004a. Behavioral syndromes: an ecological and
evolutionary overview. Trends in Ecology & Evolution 19:372-3 78.

Smartt, R. A. 1978. Comparison of ecological and morphological overlap in a
Peromyscus community. Ecology 59:216-220.

Wolff, J. O. 1985a. Comparative population ecology of Peromyscus Ieucopus and
Peromyscus maniculatus. Canadian Journal of Zoology 63: 1548-1 555.

Wolff, J. O., R. D. Dueser, and K. S. Berry. 1985. Food-habits of sympatric Peromyscus
Ieucopus and Peromyscus maniculatus. Journal of Mammalogy 66:795-79.

wolff, J. O. 1996. Coexistence of white footed mice and deer mice may be mediated by
ﬂuctuating environmental conditions. Oecologia 108:529-533.

Zhang, Z., and R. D. Arvey. 2009. Effects of Personality on Individual Earnings:
Leadership Role Occupancy as a Mediator. Journal of Business and Psychology
24:271-280.

CHAPTER TWO

Inter- and intraspeciﬁc variation in the personality of sympatric Peromyscus

INTRODUCTION

Ecologists have long been fascinated by how two or more similar species are
able to persist in sympatry. To coexist stably, sympatric species need to differentiate
niche space in attributes such as their ecology or morphology (Gause 1934; Hardin
1960; MacArthur and Levins 1967). Among some sympatric species in California, such
as deer mice (Peromyscus maniculatus), cactus mice (P. eremicus), agile kangaroo rats
(Dipodomys agilis), and desert woodrats (Neotoma lepida), differential use of
microhabitat has been cited as enabling coexistence (Price and Kramer 1984). When
microhabitat is not partitioned spatially, small mammals such as spiny mice (genus
Acomys) and sand dune gerbils (genus Gerbillus) partition the microhabitat temporally
(Haim and Rozenfeld 1993; Kotler et al. 1993). In mice of the genus Peromyscus that
occupy the same microhabitat at the same time, coexistence is sometimes accomplished
through food partitioning (Smartt 1978; Wolff et al. 1985). While time, space, or food
partitioning are often sufﬁcient to explain coexistence in small mammals, in cases
where these axes are inadequate, we are unable to predict how species will respond to
the changing environment in which they live (Munkemuller et al. 2009).

Deer mice of the genus Peromyscus are widespread across North America and
are being affected by the shifting environment produced by climate change (Moritz et
al. 2008; Myers et al. 2009). Many of these species are recently diverged (Weber and

Hoekstra 2009), are ecologically and morphologically similar, and live sympatrically

(Barry et al. 1990; Drickamer 1990; Wolff 1996). The white-footed mouse, Peromyscus
Ieucopus noveboracensis, and the woodland deer mouse, P. maniculatus gracilis, live
both allopatrically and sympatrically in the Great Lakes region and have experienced
climate-induced changes in recent years (Myers et al. 2009). Since 1980, populations of
P. Ieucopus, the more southern congener, have expanded northward and eastward from
Wisconsin and become sympatric with previously allopatric P. maniculatus populations
in Michigan’s Upper Peninsula. Coincident declines in P. maniculatus gracilis, the
northern congener, have been observed in southern parts of its range (Myers et al. 2005;
Myers et al. 2009).

An abundance of research has examined the similarities and differences between
Peromyscus Ieucopus noveboracensis and either P. maniculatus gracilis (the subspecies
1 studied) or a similar subspecies, P. m. nubiterrae, the cloudland deer mouse (Table
2.1), beginning with an investigation of the ecological differentiation of the species ﬁfty
years ago (Klein 1960). Although these taxa are very similar, there is no evidence of
interbreeding in the laboratory or in nature (Dice 1933). The population ecologies and
feeding habits of the two species are extremely similar (Wolff 1985a; Wolff et al.
1985), but some research has suggested that the two species exhibit differences in
microhabitat use, nest use, and winter survivorship. One study showed that Peromyscus
Ieucopus is active earlier in the night and when the weather is comparably warmer,
more humid, and more overcast (Drickamer and Capone 1977). Another study
suggested that Peromyscus maniculatus exhibits more pronounced behavioral and
physiological changes in response to winter, including larger nests, increased food

hoarding behavior, and a greater use of torpor (Pierce and Vogt 1993). Both species

10

prefer arboreal nests when in allopatry, but P. Ieucopus seemed to move to ground nests
when sympatric with P. maniculatus (Dooley and Dueser 1996). Finally, coexistence of
these two species has been partially attributed to interspeciﬁc differences in winter
acclimatization paired with ﬂuctuating environmental conditions, which allow P.
Ieucopus to increase in relative abundance during summers and warm years and P.
maniculatus to increase in relative abundance during winters and cold years (Long
1996; Wolff 1996). Despite a great deal of research on the ecology and morphology of
these species, mechanisms behind their coexistence remain largely unknown. This could
be because morphology and ecology are not the primary niche axes along which these
two coexisting species differentiate themselves, and should thus lead us to examine
other niche axes.

The ecological and evolutionary implications of repeatable individual
differences in behavior are being increasingly examined. These are termed
temperaments (Réale et al. 2007), behavioral syndromes (Sih et al. 2004a), or
personalities (Dingemanse et al. 2003). For the purpose of this chapter, I will use the
term personality to refer to any behavior that is repeatable over time and across
contexts. Personalities can strongly inﬂuence community ecology, population dynamics
(e.g., dispersal), and landscape ecology (Réale et al. 2007). Given a community with a
wide variety of personality types, individuals of each personality type may be adapted
to different environmental conditions (Minderrnan et a1. 2009). If certain personalities
achieve higher ﬁtness in particular environments, then ﬂuctuations in environmental
conditions might cause balancing selection (Boon et al. 2007) within a species, which

can allow different personality types within a population to persist, or these ﬂuctuations

11

might mediate competition between species that differ in personality. If P. Ieucopus and
P. maniculatus differ in mean personality, with one species being better at certain tasks
in certain environments, this could facilitate their coexistence, and in changing
environments, could lead to the range changes and shifts in species abundance (Sih et
al. 2004b) that have already been documented in the Great Lakes region (Myers et al.
2005; Myers et al. 2009).

The purpose of this study was to examine intraspeciﬁc and interspeciﬁc
variation in behavior and personality in Peromyscus Ieucopus noveboracensis and
Peromyscus maniculatus gracilis in the northern lower peninsula of Michigan where the
two species have historically coexisted in sympatry (Myers et al. 2009). The ﬁeld site
where these data were collected has historically supported high population densities of
both P. maniculatus and P. Ieucopus and has experienced climatic warming over the
last 30-40 years (Assel and Robertson 1995; Austin and Colman 2007; Field et al. 2007;
Magnuson et al. 2000; Myers et al. 2005; Myers et al. 2009). Peromyscus maniculatus
has a more northerly range and prefers colder temperatures than P. Ieucopus (Drickamer
and Capone 1977; Myers et al. 2009). Recent research revealing a link between energy
metabolism and animal personality uncovered that, in colder environments, deer mice
that are more active and have the capacity to raise their maximal metabolic rates are
expected to have higher ﬁtness (Sears et al. 2009). Careau et al. (2009) also found that
mice beneﬁt from high activity (termed exploration in his study), in unproductive
environments. These ﬁndings contrast with the competing hypothesis that deer mice
reduce energetic costs in colder temperatures by limiting activity (Stebbins 1971).

Because basal metabolic rates are correlated with maximal metabolic rates (Rezende et

12

al. 2004), and because P. maniculatus has a higher basal metabolic rate than P. Ieucopus
(Deavers and Hudson 1981; Sieg et al. 2009; White and Seymour 2003), I predict that
P. maniculatus will be have higher mean activity levels than P. Ieucopus and that
activity level will be correlated across contexts within an individual to form a
personality. Examination of the differences in personality between P. Ieucopus and P.
maniculatus could provide further insight into both their stable coexistence in
historically sympatric areas and the recent shifts in abundance where the species have
become newly sympatric.
MATERIALS AND METHODS
Study site and population

This study was conducted on a 14.4 hectare grid in the Pigeon River State Forest
in the northern lower peninsula of Michigan (45.3°N, 84.4°W). Individual mice were
monitored by livetrapping from May to August 2008 (11,603 trap nights). Sherman live
traps (7.62 x 8.89 x 22.86 cm and 5.08 x 12.70 x 16.51 cm) were placed at 20-m
intervals throughout the grid and baited with rolled oats. Traps were set at dusk and
checked between 0000 h and 0300 h, 4 to 6 nights per week. At ﬁrst capture, I ear-
tagged each mouse and recorded sex and several additional variables. Weight was
measured with a Pesola scale to the nearest 0.5 g. Age was recorded based on pelage
where juveniles were grey, subadults were grey and brown, and adults were brown
(Schug et al. 1991 ). For males, reproductive status was recorded as testes abdominal or
testes scrotal. For females, reproductive status was recorded as nipples small, nipples
enlarged but not lactating, lactating, or pregnant. Finally, I recorded putative species

based on ear size and general appearance and behavior. P. Ieucopus were generally

13

more excitable when handled and had smaller ears and a “roman” nose. Saliva samples
were collected from each mouse upon ﬁrst capture for later species typing by salivary
amylase electrophoresis (Aquadro and Patton 1980). During subsequent captures, I
recorded ear tag numbers, weight, sex, reproductive status, and putative species.
Open field behavioral trials

Open ﬁeld behavioral trials were performed in a portable arena that was placed
0.5 km from the trapping grid to control for home range effects on aggression (Oyegbile
and Marler 2006). The portable arena was a 70 cm x 50 cm x 40 cm painted wooden
box with a plexiglass lid and two holding areas made from 7.62 cm PVC pipes placed
on opposite sides of the arena. 1 performed three different types of trials on the mice:
basic, scent, and dyadic aggression trials (hereafter referred to as dyadic trials). Basic
and scent trials were conducted on 40 P. maniculatus individuals and 18 P. Ieucopus
individuals, with between one and three repetitions per mouse. This ratio of P.
maniculatus to P. Ieucopus was representative of their relative frequency in the area at
the time of the study. I also performed dyadic trials on 17 P. maniculatus individuals
and 12 P. Ieucopus individuals, with between one and three repetitions per mouse. On a
given night, an individual mouse was either subjected to all three trial types, to only the
basic and scent trials, or to only the dyadic trial, with at least ﬁve minutes between
trials. The order of trials for an individual mouse on a given night was always basic,
scent, then dyadic. Individuals were subjected to each trial type between one and three
times with at least two weeks between repetitions of a particular type of trial to avoid

habituation. All trials were recorded on a Sony DCR-SR45 Hard-Drive Handicam under

14

red light. All methods were approved by the Michigan State University All University
Committee on Animal Use and Care (AUF# 03/08-034-00).

For the basic trial, a toilet paper roll was taped in each corner of the bottom of
the arena to provide a hiding place for the mouse. A single mouse was then placed in
one of the holding areas for ﬁve minutes to acclimatize. At the end of ﬁve minutes, the
door between the holding area and the rest of the arena was opened, giving the mouse
the option to leave the holding area and enter the arena. The mouse was allotted three
minutes to enter the arena. If at the end of three minutes, the mouse still had not left the
holding area, it was placed into the center of the arena. Once in the arena, the mouse
was recorded continuously for ﬁve minutes.

For the scent trial, a paper plate (Walgreens 6” Paper Plates) containing bedding
(ﬁlling from a mattress) sprayed with three sprays of bobcat urine (Bobcat Peem) was
placed in one comer of the arena. The opposite comer of the arena contained a plate
with “forest” scented bedding (three sprays of Scent Killer® Autumn Formula®). Toilet
paper rolls were taped to the corners of the other two quadrants to provide hiding
places. The mouse was placed into the center of the arena following a ﬁve minute
acclimation period in the holding area and was then recorded continuously for ﬁve
minutes.

The dyadic trials were conducted between mice of the same sex, age, and
reproductive status, but differed with respect to whether mice were paired inter- or
intraspeciﬁcally. Mice were tagged but were not conspicuously marked for these trials.
For this reason, the toilet paper rolls were removed from the arena so that the mice

could not move out of sight. To avoid sibling dyads, mice were paired with individuals

15

that were trapped farthest from their trap location. Each mouse was initially placed in a
separate holding area for ﬁve minutes of acclimation. The mice were then placed
simultaneously into the arena directly in ﬁont of each holding area and given 10
minutes to interact. I never needed to separate the mice because there was never an
instance where aggression threatened to harm a mouse. The mice were recorded
continuously for 10 minutes.
Data extraction

Behavioral variables were extracted from the video ﬁles using J Watcher +
Video 1.0 (Blumstein et al. 2006). All videos were watched and recorded continuously
in their entirety. The basic trial was watched a total of three times to extract all
variables. During the ﬁrst viewing of the basic trial, I extracted the latency to leave the
holding area in seconds, the number of times the mouse looked out of the holding area,
the number of rears, the number of j umps, and the proportions of time climbing on the
walls, in contact with a toilet paper roll, in the holding area after the initial exit, running,
sitting, and sniffing. These behaviors were all mutually exclusive. During the second
viewing, I extracted the number of quadrant changes per minute, as a proxy for speed.
During the third viewing, I extracted the proportion of time the mouse spent in the
center of the arena and along the edge of the arena, which were mutually exclusive.

Each scent trial was watched twice. During the ﬁrst viewing, I extracted the
proportions of time in the quadrant containing the bobcat urine but not actively sniffing
the bobcat urine or on the bobcat plate, visibly snifﬁng the bobcat urine, on the bobcat
plate but not visibly snifﬁng, in the empty quadrants, in the quadrant containing the

forest scent but not actively snifﬁng the forest scent or on the plate, visibly snifﬁng the

16

forest scent, on the forest plate but not visibly snifﬁng, and in contact with a toilet paper
roll. All behaviors were mutually exclusive. During the second viewing, I extracted the
proportions of time running, sitting, and climbing on the walls. These three behaviors
were mutually exclusive.

For each dyadic trial, I watched each video twice and extracted the following
variables for each mouse separately: the proportions of time cuddling, ignoring the
opponent, on its back under the opponent, on top of the opponent, wrestling, and the
number of anogenital sniffs, the number of chases, the number of jumps away from the
opponent, the number of approaches toward the opponent, the number of retreats from
the opponent, and the number of rears in response to the opponent. All behaviors were
mutually exclusive.

Statistical analyses

I used generalized linear models with either a quasibinomial link (to account for
non-integer weights in proportion data) or a Poisson link (for count data) to determine
the effect of species on each behavior for all three trial types, and of opponent species
on each behavior for P. maniculatus and P. Ieucopus separately in dyadic trials.
Variables from the basic trial, the scent trial, and the dyadic trial were then loaded into
three separate principal component analyses using correlation matrices to reduce
dimensionality of the data and uncover behavioral axes. Before loading, I attempted to
normalize the variables by log transformation, arc-sin transformation, cube-root or 1/ 8
root transformations. While normality was not always achieved, all variables became

near-normal. Principal component scores (referred to as PC# with the trial type in

subscript; e. g., PCIbasic) for each of the three trial types were standardized by

17

subtracting the mean and dividing by the standard deviation and then analyzed using
linear models and linear mixed effects models (nlme package in R). Principal
component axes that were interpreted as activity and arboreality axes (see results) were
tested using Pearson’s correlations to determine whether mouse behavior was consistent
across contexts (i. e. , types of open ﬁeld trials), thus appropriately termed ‘personalities’
(Dingemanse et al. 2003). The signiﬁcance of individual identity was assessed for each
PC score by comparing the mixed effect model (nlme package in R) that included
individual identity as a random effect and the best combination of ﬁxed effects (e.g.,
species, sex, age, trial number) to the linear model with the same ﬁxed effects, but
without the individual identity random effect using a likelihood ratio test (Bolker et al.
2009; Pinheiro and Bates 2000). All statistical analyses were performed in R version
2.9.2 (R Development Core Team 2009). Values are presented as means i one standard
error unless otherwise noted. Parameters from linear models are reported as bx for

factors, where the subscripted term (x) indicates the factor level associated with the

parameter. For example bleucopus is the parameter representing the effect of the mouse

being a P. Ieucopus as compared to a P. maniculatus. Z-scores are presented for
generalized linear models with a Poisson link, while t-scores are presented for
generalized linear models with a quasibinomial link. The magnitudes of effect sizes are
based on raw behavioral data with statistics from linear models in parentheses.

One mouse (a P. Ieucopus) was unusually inactive in both the basic trial and the
scent trial. It remained perfectly still before, during, and after the trials, but otherwise
seemed healthy and then ran away when released. Based on my observations of many

open ﬁeld trials, this behavior was not within the range of typical Peromyscus

18

responses. As a result, data from the basic and scent trials for this single mouse were
excluded from subsequent analyses. My general conclusions were not affected by the
inclusion or exclusion of these two observations.

RESULTS

Druing the basic trials, on average, mice of both species left the holding area
after 60.6 i 9.7 s and spent the largest proportions of time running and snifﬁng (30.7 i
1.1% and 27.8 :t 1.1% respectively) on the edge (60.2 :t 1.9%) of the arena, sitting only
14.9 i 1.9 % of the time, and climbing only 11.1 i1.6% of the time. In contrast, during
the scent trials, mice spent the most time in the empty quadrants and sitting (47.5 d:
3.3% and 67.2 i 3.0% respectively), while they spent relatively little time running,
climbing, or exploring the scents.

During the ten minutes that the dyadic trials lasted, on average, both species
retreated from the opponent 4.0 :l: 0.9 times and approached the opponent 4.6 i 0.9
times. Both species spent most of their time ignoring the opponent (72.2 :t 5.4%) and
very little time in contact with the other mouse, but P. maniculatus jumped away from

the opponent only 0.41 i 0.23 times, while P. Ieucopus jumped away from the

opponent 4.8 i: 2.1 times (bmaniculalus i SE = -2.4 :f: 0.40, t = -6.1, p < 0.001).

Interspeciﬁc differences in behavior
For the basic trial, the ﬁrst two principal components (PCs) had eigenvalues
greater than one and explained 47.0 % of the variance (Table 2.2). The number of

quadrant changes, proportion of time running, and number of rears loaded heavily and

negatively into PCIbasica while the proportion of time sitting loaded heavily and

19

positively. PCIbasic was interpreted as an activity axis in which mice with lower scores

were more active. Linear models using only the ﬁrst trial for each mouse revealed that

P. maniculatus had signiﬁcantly lower PCIbasic scores than P. Ieucopus (F = 6.0, d.f. =

1, 55, P = 0.02, Fig. 2.1). In other words, P. maniculatus was more active as reﬂected
by more quadrant changes, running more, and rearing more, while P. Ieucopus sat more.
The statistics reported for the following species differences come from generalized
linear models while the effect sizes are based on actual differences in raw data. Raw

behavioral variables supported this ﬁnding by revealing that P. Ieucopus left the holding

area to explore the arena 38% later than P. maniculatus (bmaniculatus i SE = -0.33 i
0.001, 2 = -296.4, d.f. = 56, P < 0.0001). Peromyscus maniculatus also spent 23% more
time running during the basic trial (bmam'culatus :t SE = 0.29 i 0.11, t= 2.55, d.f. = 56, P
= 0.01), 60% more time running during the scent trial (bmaniculatus i SE = 0.56 :t 0.23,

t= 2.43, d.f. = 56, P = 0.02), and reared 1.3 times as much during the basic trial

(bmaniculam, i SE = 0.27 is 0.06, z = 4.78, d.f. = 56, P < 0.0001) when compared to P.

Ieucopus.

Proportion of time climbing and on the edge of the arena loaded heavily and

negatively into PCZbasiCa while proportion of time in the center of the arena and in the

holding area loaded heavily and positively (Table 2.2). PCZbasic was interpreted as a

location of activity axis in which mice with lower scores climbed more and spent more

time on the edge, while those with higher scores stayed either in the center of the arena

20

or in the holding area. There were no signiﬁcant differences between species in this
principal component axis (F = 0.1, d.f. = l, 55, P = 0.7).
For the scent trial, the ﬁrst two components had eigenvalues greater than one

and explained 46.6 % of the total variance (Table 2.2). Proportion of time running

loaded heavily and negatively into PClscem, while proportion of time in the empty

quadrants and proportion of time sitting loaded heavily and positively. PC 1 scent was
interpreted as an activity axis in which mice with higher scores were less active. The
proportion of time climbing loaded heavily and positively into PC2scem, while

proportion of time sniffmg the forest scent and the bobcat scent, proportion of time

sitting, and proportions of time on the forest plate and bobcat plate loaded heavily and
negatively. PC2536,“ was interpreted as a location of activity axis in which mice with
higher scores climbed up the walls and those with lower scores stayed on the ground.

There were no signiﬁcant differences between species in either PC 1 scent (F = 0.9, d.f. =

1, 55, P = 0.3, Fig. 2.1) or PCZScem (F1: 0.1, d.f. = 1, 55, P = 0.7).

For the dyadic trial, the ﬁrst two principal components had eigenvalues greater
than one and explained 45.5 % of the total variance (Table 2.2). The number of jumps
away from the opponent, the proportion of time ignoring the opponent, the number of

retreats, and the number of rears in response to the opponent loaded heavily and

negatively into PCIdyadic, while the proportion of time cuddling loaded heavily and

positively. PCIdyadic was interpreted as a sociality axis in which mice with higher PC
scores had contact with the opponent more often and mice with lower scores avoided

21

the opponent. During the dyadic trial, P. maniculatus had signiﬁcantly higher PCIdyadic

scores than P. Ieucopus (F = 8.9, d.f. = 1, 27, P = 0.006, Fig. 2.2). In other words, P.
maniculatus cuddled with the opponent more, while P. Ieucopus jumped away from the
opponent, ignored the opponent, retreated from the opponent, and reared in response to
the opponent. The statistics reported for the folloWing species differences come from

generalized linear models while the effect sizes are based on actual differences in raw

data. P. maniculatus wrestled 5.5 times as often (bmam‘culatus = 1.82 i 0.74, t= 2.5, d.f.

= 28, P = 0.02), sniffed the opponent’s anogenital region 3.9 times as often (bmaniculatus

= 1.35 :l: 0.35, z = 3.95, d.f. = 28, P < 0.0001), and chased the opponent 3.8 times as
often as P. Ieucopus (bmanicularus = 1.31 i 0.55, z= 2.40, d.f. = 28, P = 0.02).
Peromyscus Ieucopus jumped away from the opponent 11.6 times as often as P.
maniculatus (bmanicularus = -2.44 i 0.40, t= -6.11, d.f. = 28, P < 0.0001).

The number of rears in response to the opponent, the proportion of time

cuddling, the number of retreats, the proportion of time wrestling, and the proportion of

time on the back under the opponent loaded heavily and negatively into PCZdyadica

while the proportion of time ignoring the opponent loaded heavily and positively and

the number of approaches and pr0portion of time on top of the mouse loaded

moderately and positively (Table 2.2). Pczdyadic was interpreted as an aggression axis,

with mice with lower scores being more submissive and mice with higher scores being

more aggressive. There were no signiﬁcant differences between species in Pczdyadic (F
= 0.5, d.f. = 1, 27, P = 0.5. Fig. 2.2).

22

Intraspecific variation and individual repeatability

When assessing the signiﬁcance of individual identity in a model describing

PCIbasic (i. e. , the activity axis), the addition of mouse identity as a random effect

signiﬁcantly improved the ﬁt of the model to the data (x2 = 14.3, d.f. = 1, P < 0.001).

Mouse identity accounted for 52% of the variance in the PC 1 basic data not accounted

for by species, sex, the interaction of species and sex, age, and trial number. Noting that

in this case, more negative activity scores represented higher activity levels, this model

indicated that P. maniculatus was more active than P. Ieucopus (bmam'culatus = -1.47 i

0.42, t = -3.5, d.f. = 53, P = 0.001), males were more active than females (bmale = -1.03

:l: 0.45, t = -2.3, d.f. = 53, P = 0.025), P. Ieucopus males were more active than

conspeciﬁc females, but there was little difference between P. maniculatus males and

females (bmaniculatus*male = 1.49 i 0.51, t = 2.9, d.f. = 53, P = 0.005), juveniles and
sub-adults were not signiﬁcantly different from adults (bl-wen“e = -0.38 :l: 0.31, t = -1.2,

d.f. = 53, P = 0.23, bsubadult = -039 e 0.23, t = -1.8, d.f. = 53, P = 0.09), and mice

became less active with increasing trial repetitions (b = 0.66 :t 0.11, t = 5.9, d.f. = 53, P
< 0.001).

The addition of mouse identity as a random effect did not improve the ﬁt of the

best models to describe PCZbasic (x2 = 0.8, d.f. = 1, P = 0.4), PClscem (x2 = 2.3, d.f. = 1,
P = 0.13), Pc2scent (x2 = 0.3, d.f. = 1, P = 0.6), Pcrdyadic (x2 = 0.1, d.f. = 1, P = 0.7) or

Pczdyadic (x2 < 0.001, d.f. = 1, P = 0.9).

23

All linear models using principal component scores and all further analyses were
done using only the ﬁrst trials (i. e., the ﬁrst basic, scent, and dyadic trials) performed on
each mouse to avoid confounding habituation.

Correlation of behavioral axes across contexts to form personalities

By deﬁnition, a personality refers to individual behavioral differences that are

._ repeatable across time and situations (Réale et al. 2007). PCIbasic and PC 1 scent were
both interpreted as activity axes and were positively correlated (Pearson’s r = 0.55, P <
0.0001, Fig. 2.1). PCZbasic and PC2scem were both interpreted as location axes, but
several behavioral variables loaded in opposite directions on these two axes (e.g.,

proportion of time climbing loaded negatively into PC2baSic and positively into

PCZScem, see Table 2.2). PCZbasic and PCZScem were found to be negatively correlated

with marginal signiﬁcance (Pearson’s r = -0.24, P = 0.07), meaning that mice that
climbed more in the basic trial also climbed more in the scent trial.
No difference in dyadic behavior between interspecific and intraspecific dyads

Using linear models to test for the effects of intraspeciﬁc versus interspeciﬁc

dyads on PC] dyadic and PCZdyadiCa I found no difference in behavior for P. maniculatus

or P. Ieucopus; the focal mouse behaved the same towards heterospeciﬁcs as toward

conspeciﬁcs. For P. maniculatus, there was no effect of the opponent species on

PCIdyadic (F = 0.2, d.f. = 1, 8, P = 0.7) or PCZdyadic (F = 2.0, d.f. = 1, 8, P = 0.2). There
was also no effect of opponent species for P. Ieucopus on PCIdyadic (F = 0.09, d.f. = 1,
5, P = 0.8) or PCZdyadic (F= 0.8, d.f. = 1, 5, P = 0.4).

24

Despite the similarities I found when examining principal component scores,
when looking at the raw behavioral data extracted from the dyadic trials for each
species separately using generalized linear models, I found that both species approached
heterospeciﬁc opponents more often than they approached conspeciﬁcs and both
retreated from P. maniculatus opponents more often than from P. Ieucopus opponents.
As was noted previously, effect sizes are based on raw means while statistics from
supporting generalized linear models are given in parentheses for each behavior.
Speciﬁcally, Peromyscus maniculatus approached heterospeciﬁcs 1.8 times as often as
conspeciﬁcs (bwnspeciﬁcs = -0.6 i 0.20, z = -3.0, d.f = 18, P = 0.003) and retreated from
conspeciﬁcs 12.5 times as often as from heterospeciﬁcs (nonspeciﬁc; 2.53 :h 1.01, z =
2.5, d.f = 18, P = 0.01). Peromyscus Ieucopus approached heterospeciﬁcs 3.3 times as
often as conspeciﬁcs (bhcterospcciﬁcs = 1.20 i 0.61, z= 2.0, d.f = 6, P = 0.05) and retreated
from heterospeciﬁcs 13.6 times as often as from conspeciﬁcs (bhemospecmc, = 2.61 :l: 1.01 ,
z = 2.5, d.f = 6, P = 0.01). Peromyscus maniculatus was also on top of heterospeciﬁcs
16.7 times as often as on top of conspeciﬁcs (beonspcciflcs = -2.85 i 0.99, 2: -2.9, d.f = 18,
P = 0.01). The other eight behaviors showed no effect of opponent species.
DISCUSSION

For two species to coexist, they must be sufﬁciently different to allow niche
differentiation (Gause 1934; Hardin 1960; MacArthur and Levins 1967). Most studies
that examine coexistence look to morphology or ecology for evidence of niche
differentiation. In particular, there is a great deal of research revealing that Peromyscus
maniculatus and P. Ieucopus are extremely similar ecologically and morphologically

(Table 2.1). My results, indicating mean differences in personality between these two

25

species, complement this existing body of literature (Table 2.1) to provide a more
comprehensive understanding of the potential mechanism behind their coexistence.
Activity

My ﬁndings from both the principal component axes and analysis of raw
behavioral data revealed that P. maniculatus is more active than P. Ieucopus.
Peromyscus maniculatus and P. Ieucopus occupy different geographic ranges, with P.
maniculatus extending farther north, into colder temperatures, than P. Ieucopus. This
preference for more northern habitats has also been observed in microhabitat studies,
where P. maniculatus was found to prefer colder microhabitats than P. Ieucopus
(Drickamer and Capone 1977). In a recent study of deer mice, individuals spent less
time active as temperatures decreased, with the duration of each activity bout
decreasing, but the number of bouts staying the same (Sears et a1. 2009). Furthermore,
mice with higher maximal metabolic rates were better able to support activity in colder
temperatures (Sears et al. 2009). It is possible that the higher activity levels exhibited
by P. maniculatus allow it to generate more heat by exercise therrnogenesis, thus
making this species better able to avoid excessive heat loss (Makinen et al. 1996) and to
thrive in colder temperatures than P. Ieucopus.

My ﬁndings are in contrast to those from a recent study, which found a negative
correlation between basal metabolic rate and exploration in muroid rodent species
(Careau et al. 2009). The authors used percent time spent in locomotion as a proxy for
activity level, and equated activity level in the open ﬁeld with exploration. In their
meta-analysis, P. maniculatus was in locomotion 46.5 % of the time and had an average

BMR of 36.9 mL 02 per hour. On this basis, they described P. maniculatus as a

26

superﬁcial explorer with a low BMR. Peromyscus Ieucopus was in locomotion 54.6 %
of the time and had an average BMR of 33.2 mL 02 per hour and was described as a
thorough explorer with a low BMR. These ﬁndings are in contrast to my ﬁndings that

P. maniculatus is more active (43.2% of time in motion) than P. Ieucopus (38.4% of
time in motion). A possible explanation for this discrepancy is that the data for P.
maniculatus in the Careau et al. (2009) study were averaged between the two subspecies
P. m. bairdii (prairie deer mouse) and P. m. blandus (Chihuahua deer mouse), both of
which differ in morphology, behavior, and habitat preference from P. m. gracilis, the
mouse 1 studied (Baker 1983; Barry 1976; King 1968).

Furthermore, my estimates of personality for P. Ieucopus might not be
representative of the species (or subspecies) as a whole. In particular, most of my study
mice were likely recent dispersers. I began trapping on 7 May 2008, but did not trap any
P. Ieucopus until 5 June 2008. Trappability (sum of all individuals’ number of captures
minus the ﬁrst and last divided by the sum of all individuals’ number of potential
captures minus the ﬁrst and last—Lusk and Millar 1989) on my study site was 81.8%,
so it is unlikely that these animals were resident on the grid but remained undetected
during this time period. Dispersing individuals in other species have been previously
shown to differ in personality from philopatric individuals, being bolder, more
aggressive, faster explorers that are less social (Clobert et al. 2009; Cote and Clobert
2007 ; Dingemanse et al. 2003; Duckworth and Badyaev 2007; Duckworth and Kruuk
2009). As a result, some of the differences between these two species that I have
documented might be due to the increased proportion of dispersing individuals in my P.

Ieucopus sample.

27

Contact with opponent mouse

Peromyscus maniculatus had more contact with opponents than P. Ieucopus and
was thus more sociable (Cote et al. 2010). This is consistent with the reported
superiority of the former with respect to adaptation to cold temperatures, as small
mammals often use communal nesting as a way to conserve energy in the winter
(Merritt and Zegers 2002; West and Dublin 1984). In the wild, P. maniculatus and P.
Ieucopus have both been found to engage in communal nesting (Millar and Derrickson
1992; Wolff 1994), often doing so as population densities increase (Wolff 1994). To
understand the greater amount of contact P. maniculatus had with opponents when
compared to P. Ieucopus, I might look to their native ranges and note that P.
maniculatus gracilis has a range that extends farther north than P. Ieucopus, while the
range of P. Ieucopus noveboracensis extends much farther south into warmer climates,
possibly making the need for communal nesting as an energy conservation strategy less
important.

Arboreality

The second principal component axes from the basic and scent trials
represented location of activity axes and indicated that animals that climbed more in the
basic trial also climbed more in the scent trial. These results should be examined with
caution, however, due to the lack of individual repeatability. Differences among mice in
the amount of climbing behavior could reﬂect differences in arboreality or differences
in escape behavior. Inter- and intraspeciﬁc variation in climbing behavior has been

previously demonstrated in the genus Peromyscus (Lemen 1980), thus emphasizing the

28

need for future behavioral trials that examine climbing behavior so as to differentiate
between these two possibilities.
Dyadic trials

When looking at PC scores from the dyadic trials for each species separately, 1
found no differences in any of the PC scores based on whether the opponent was a
conspeciﬁc or a heterospeciﬁc. These ﬁndings are in agreement with past research that
found no difference in inter- versus intraspeciﬁc aggression for home ranges (Wolff
1985b). Wolff (1985b) determined that home range size is density dependent, and is
based on the population density of both species rather than just one.

When looking at the raw behavioral data extracted from the dyadic trials,
however, I found that both species approached heterospeciﬁc opponents more often
than they approached conspeciﬁcs, possibly suggesting aggression towards
heterospeciﬁcs. However, both species retreated from P. maniculatus opponents more
often than from P. Ieucopus opponents, suggesting that P. maniculatus wins these
encounters more often than P. Ieucopus. These results suggest that there might be
differences in aggression between the two species that I failed to uncover through my
principal component analyses. This could be due to the fact that some of the behaviors
that loaded heavily into the principle component axes did not differ between
heterospeciﬁcs and conspeciﬁcs, whereas the behaviors that I found to differ between
conspeciﬁcs and heterospeciﬁcs were less important to overall variation in dyadic
behavior. Future research should further examine dyadic behavior to better understand
the complexities of intraspeciﬁc and interspeciﬁc interactions between these two similar

species.

29

Differences in activity level might permit coexistence in a changing environment

The ﬁeld site where these data were collected has historically supported high
population densities of both P. maniculatus and P. Ieucopus, and has experienced
climatic warming over the last 30-40 years (Assel and Robertson 1995; Austin and
Colman 2007; Field et a1. 2007; Magnuson et al. 2000; Myers et al. 2005; Myers et al.
2009). It is possible that differences in activity level in these species may mediate their
coexistence in this location. If each species is better adapted to either colder or warmer
temperatures by being more or less active, population abundances should shift as the
environment changes from warmer to colder and vice versa. During warmer years, P.
Ieucopus might increase in relative abundance, while P. maniculatus, which is more
active and thus will experience higher ﬁtness in cooler temperatures (Sears et al. 2009),
might thrive in cooler years. These predictions are consistent with recent changes in
relative abundances associated with climate change (Myers et al. 2005; Myers et al.
2009)

In the northern lower peninsula of Michigan, where this study was conducted,
the percentage of P. Ieucopus among small forest mammal captures has increased ﬁ'om
38.3% (1883 to 1980) to 77.7% (1981 to 2006—Myers et a1. 2009). Over the same time
frame, representation of P. maniculatus has decreased from 28% of small mammal
captures (1883 to 1980) to only 5.9% (1981 to 2006—Myers et al. 2009). These shifts
in abundance are part of a large-scale range shift that involves several other small
mammals in the Great Lakes region (Myers et al. 2009). Previously documented

associations between higher activity level, colder temperatures and ﬁtness (Sears et al.

30

2009), suggest that the more active P. maniculatus is not as able as the less active P.
Ieucopus to exploit the warming temperatures produced by climate change in this area.
Using the relationships extrapolated from this research, I can begin to predict
how individual populations of Peromyscus will respond to climate change. For P.
maniculatus, populations of mice in which individuals are especially active, and thus
are well adapted to cold temperatures (Sears et al. 2009), may be the most vulnerable to
climatic warming. Less active populations of P. Ieucopus, which are thus less adapted to
cold temperatures, should do well at expanding their ranges as temperatures increase

and may out-compete more active P. maniculatus populations.

31

 

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34

Figure 2.1: Principal component scores from the basic trial and the scent trial PCA on
Peromyscus maniculatus and Peromyscus Ieucopus (displaying ﬁrst trial scores only).

PCIbasic and PClscem are both interpreted as activity axes. Boxplot lines represent the
minimum, maximum, quartiles, and median, from the outside in. An asterisk indicates a
signiﬁcant difference between species. The diagonal line represents the regression line

OfPCIbasic 0n PCIScent (F: 23.4, d.f. = 1, 55, P < 0.0001).

   
 

 

 

 

 

 

 

 

 

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35

Figure 2.2: Principal component scores from the dyadic trial PCA on Peromyscus
maniculatus and Peromyscus Ieucopus (displaying ﬁrst trial scores only). PCIdyadic is

interpreted as a sociality axis while Pczdyadic is interpreted as an aggression axis.
Boxplot lines represent the minimum, maximum, quartiles, and median, from the
outside in. An asterisk indicates a signiﬁcant difference between species.

 

 

 

 

 

 

 

 

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36

LITERATURE CITED

Aquadro, C. F ., and J. C. Patton. 1980. Salivary amylase variation in Peromyscus- Use
in species identiﬁcation. Journal of Mammalogy 61 :703-707.

Assel, R. A., and D. M. Robertson. 1995. Changes in winter air temperatures near Lake
Michigan, 1851-1993, as determined from regional lake ice records. Limnology
and Oceanography 40:165-176.

Austin, J. A., and S. M. Colman. 2007. Lake Superior summer water temperatures are
increasing more rapidly than regional air temperatures: A positive ice-albedo
feedback. Geophysical Research Letters 34.

Baker, R. H. 1983. Michigan Mammals. Wayne State University, Detroit, Michigan.

Barry, W. J. 1976. Environmental effects of food hoarding in deermice (Peromyscus).
Journal of Mammalogy 57:731-746.

Barry, R. E., A. A. Heﬁ, and T. E. Baummer. 1990. Spatial relationships of syntopic
white-footed mice, Peromyscus Ieucopus, deer mice, P. maniculatus, and red-
backed voles, Clethrionomys gapperi. Canadian Field-Naturalist 104:387-393.

Blumstein, D. T., J. C. Daniel, and C. S. Evans. 2006. JWatcher 1.0., Los Angeles,
California.

Bolker, B. M., et al. 2009. Generalized linear mixed models: a practical guide for
ecology and evolution. Trends in Ecology & Evolution 24:29.

Boon, A. K., D. Réale, and S. Boutin. 2007. F luctuating selection on personality
according to year and life history stage in North American red squirrels.
Master’s thesis. University of Alberta, Edmonton, Alberta, Canada.

Bruseo, J. A., and R. E. Barry. 1995. Temporal activity of syntopic Peromyscus in the
central Appalachians. Journal of Mammalogy 76:78-82.

Careau, V., O. R. P. Bininda-Emonds, D. W. Thomas, D. Réale, and M. M. Humphries.
2009. Exploration strategies map along fast-slow metabolic and life-history
continua in muroid rodents. Functional Ecology 23:150-156.

Careau, V., D. Thomas, M. M. Humphries, and D. Réale. 2008. Energy metabolism and
animal personality. Oikos 117:641-653.

Clobert, J ., J. F. Le Galliard, J. Cote, S. Meylan, and M. Massot. 2009. Informed

dispersal, heterogeneity in animal dispersal syndromes and the dynamics of
spatially structured populations. Ecology Letters 12:197-209.

37

Cogshall, A. S. 1928. Food Habits of Deer Mice of the Genus Peromyscus in Captivity,
Journal of Mammalogy 9:5.

Cote, J ., AND J. Clobert. 2007. Social personalities inﬂuence natal dispersal in a lizard.
Proceedings of the Royal Society B-Biological Sciences 274:383-390.

Cote, J ., S. Fogart, K. Iinersmith, T. Brodin, and A. Sih. 2010. Personality traits and
dispersal tendency in the invasive mosquitoﬁsh (Gambusia afﬁnis). Proceedings

of the Royal Society. B, Biological sciences, published online before print
January 13, 2010, doi:10.1098/rspb.2009.2128.

Deavers, D. R., and J. W. Hudson. 1981. Temperature regulation in two rodents
(Clethrionomys gapperi and Peromyscus Ieucopus) and a shrew (Blarina
brevicauda) inhabiting the same environment. Physiological Zoology 54:94-
1 08.

Dice, L. 1933. Fertility relationships between some of the species and subspecies of
mice in the genus Peromyscus. Journal of Mammalogy 14:298-305.

Dingemanse, N. J ., C. Both, A. J. van Noordwijk, A. L. Rutten, and P. J. Drent. 2003.
Natal dispersal and personalities in great tits (Parus major). Proceedings of the
Royal Society of London Series B-Biological Sciences 270:741-747.

Dooley, J. L., AND R. D. Dueser. 1996. Experimental tests of nest site competition in
two Peromyscus species. Oecologia 105:81-86.

Drickamer, L. C. 1987. Inﬂuence of time of day on captures of 2 species of Peromyscus
in a New-England deciduous forest. Journal of Mammalogy 68:702-703.

Drickamer, L. C. 1990. Microhabitat preferences of two species of deer mice
Peromyscus in a northeastern United States deciduous hardwood forest. Acta
Theriologica 35:241-252.

Drickamer, L. C., and M. R. Capone. 1977. Weather parameters, trappability and niche

separation in 2 sympatric species of Peromyscus. American Midland Naturalist
98 :3 76-3 8 1 .

Duckworth, R. A., and A. V. Badyaev. 2007. Coupling of dispersal and aggression
facilitates the rapid range expansion of a passerine bird. Proceedings of the
National Academy of Sciences of the United States of America 104: 15017-
15022.

Duckworth, R. A., and L. E. B. Kruuk. 2009. Evolution of genetic integration between
dispersal and colonization ability in a bird. Evolution 63:968-977.

38

Duncan, R. P., D. M. F orsyth, and J. Hone. 2007. Testing the metabolic theory of
ecology: Allometric scaling exponents in mammals, Ecology 88:324-333.

Field, C.B. et al. 2007. North America. In: Climate Change 2007: Impacts, Adaptation
and Vulnerability. Contribution of Working Group II to the Fourth Assessment
Report of the Intergovernmental Panel on Climate Change. Pp. 617-652 (C. O.
Parry ML, Palutikof JP, van der Linden PJ, Hanson CE, ed.). Cambridge
University Press, Cambridge, UK.

Gause, G. F. 1934. The struggle for existence. The Williams & Wilkins company,
Baltimore.

Graves, S., J. Maldonado, and J. O. Wolff. 1988. Use of ground and arboreal
microhabitats by Peromyscus-Ieucopus and Peromyscus-maniculatus. Canadian
Journal of Zoology-Revue Canadienne De Zoologie 66:277-278.

Haim, A., and F. M. Rozenfeld. 1993. Temporal segregation in coexisting Acomys
species - The role of odor. Physiology & Behavior 54:1159-1161.

Hardin, G. 1960. Competitive exclusion principle. Science 131:1292-1297.

King, J. A. 1968. Biology of Peromyscus (Rodentia). First Edition. The American
Society of Mammalogists, Stillwater, Oklahoma.

Klein, H. G. 1960. Ecological relationships of Peromyscus Ieucopus noveboracensis
and P. maniculatus gracilis in central New York. Ecological Monographs
30:388-407.

Kotler, B. P., J. S. Brown, and A. Subach. 1993. Mechanisms of species coexistence of
Optimal foragers - Temporal partitioning by two species of sand dune gerbils.
Oikos 67:548-556.

Lemen, C. 1980. Relationship between relative brain size and climbing ability in
Peromyscus. Journal of Mammalogy 61 :360-364.

Lindquist, E. S., C. F. Aquadro, D. Mcclearn, and K. J. Mcgowan. 2003. Field
identiﬁcation of the mice Peromyscus Ieucopus noveboracensis and P-
maniculatus gracilis in central New York, Canadian Field-Naturalist 117: l 84-
1 89.

Long, C. A. 1996. Ecological replacement of the Deer Mouse, Peromyscus maniculatus,
by the White-footed Mouse, P. Ieucopus, in the Great Lakes region. Canadian
Field-Naturalist 1 10:271-277.

Lusk, S. J. G., and J. S. Millar. 1989. Reproductive inhibition in a short season
population of Peromyscus maniculatus. Journal of Animal Ecology 58:329-341.

39

MacArthur, R., and R. Levins. 1967. Limiting similarity convergence and divergence of
coexisting species. American Naturalist 101 :377-3 80.

Magnuson, J. J ., ET AL. 2000. Historical trends in lake and river ice cover in the
Northern Hemisphere. Science 289: 1 743—1 746.

Makinen, T., H. Rintamaki, E. Hohtola, and R. Hissa. 1996. Energy cost and
thermoregulation of unrestrained rats during exercise in the cold. Comparative
Biochemistry and Physiology a-Physiology 114:57-63.

Merritt, J. F., and D. A. Zegers. 2002. Maximizing survivorship in cold: thermogenic
proﬁles of non-hibemating mammals. Acta Theriologica 47:221-234.

Millar, J. S., and E. M. Derrickson. 1992. Group nesting in Peromyscus maniculatus.
Journal of Mammalogy 73:403-407.

Minderrnan, J ., J. M. Reid, P. G. H. Evans, and M. J. Whittingham. 2009. Personality
traits in wild starlings: exploration behavior and environmental sensitivity.
Behavioral Ecology 20:830-837.

Moritz, C., J. L. Patton, C. J. Conroy, J. L. Parra, G. C. White, and S. R. Beissinger.
2008. Impact of a Century of Climate Change on Small-Mammal Communities
in Yosemite National Park, USA. Science 322:4.

Munkemuller, T., B. Reineking, J. Travis, H. Bugmann, and K. Johst. 2009.
Disappearing refuges in time and space: how environmental change threatens
species coexistence. Theoretical Ecology 2:217-227.

Myers, P., B. Lundrigan, And R. Vande Kopple. 2005. Climate Change and the
Distribution of Peromyscus in Michigan: Is Global Warming Already Having an
Impact? University of California Publications in Zoology.

Myers, P., B. L. Lundrigan, S. M. G. Hoffman, A. P. Haraminac, and S. H. Seto. 2009.
Climate-induced changes in the small mammal communities of the Northern
Great Lakes Region. Global Change Biology 15:1434-1454.

Oyegbile, T. 0., and C. A. Marler. 2006. Weak winner effect in a less aggressive
mammal: Correlations with corticosterone but not testosterone. Physiology &
Behavior 89: 171-179.

Pierce, S. S., and F. D. Vogt. 1993. Winter acclimatization in Peromyscus maniculatus

gracilis, P. Ieucopus noveboracensis, and P. I. Ieucopus. Journal of Mammalogy
74:665-677.

40

Pinheiro, J ., and D. Bates. 2000. Mixed-Effects Models in S and S-PLUS. Springer New
York, New York.

Price, M. V., and K. A. Kramer. 1984. On measuring microhabitat afﬁnities with
special reference to small mammals. Oikos 42:349-354.

R Development Core Team. 2009. R: A language and environment for statistical
computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-
900051-07-0, URL http://wwwR-proiectorg,

Réale, D., S. M. Reader, D. Sol, P. T. McDougall, and N. J. Dingemanse. 2007.
Integrating animal temperament within ecology and evolution. Biological
Reviews 82:291-318.

Rezende, E. L., F. Bozinovic, and T. Garland. 2004. Climatic adaptation and the
evolution of basal and maximum rates of metabolism in rodents, Evolution
58:1361-1374.

Schug, M. D., S. H. Vessey, and A. I. Korytko. 1991. Longevity and survival in a
population of white-footed mice (Peromyscus Ieucopus). Journal of Mammalogy
72:360-366.

Sears, M. W., J. P. Hayes, M. R. Banta, and D. McCormick. 2009. Out in the cold: '
physiological capacity inﬂuences behaviour in deer mice. Functional Ecology
23:774-783.

Sieg, A. E., M. P. O'Connor, J. N. McNair, B. W. Grant, S. J. Agosta, and A. E.
Dunham. 2009. Mammalian Metabolic Allometry: Do Intraspeciﬁc Variation,
Phylogeny, and Regression Models Matter? American Naturalist 174:720-733.

Sih, A., A. Bell, and J. C. Johnson. 2004a. Behavioral syndromes: an ecological and
evolutionary overview. Trends in Ecology & Evolution 19:372-3 78.

Sih, A., A. M. Bell, J. C. Johnson, and R. E. Ziemba. 2004b. Behavioral syndromes: An
integrative overview. Quarterly Review of Biology 79:241-277.

Smartt, R. A. 1978. Comparison of ecological and morphological overlap in a
Peromyscus community. Ecology 59:216-220.

Stebbins, L. L. 1971. Seasonal variations in circadian rhythms of deer mice, in
northwestern Canada. Arctic 24: 1 24-1 3 1.

Weber, J. N., and H. E. Hoekstra. 2009. The evolution of burrowing behaviour in deer
mice (genus Peromyscus). Animal Behaviour 77:603-609.

41

West, S. D., and H. T. Dublin. 1984. Behavioral strategies of small mammals under
winter conditions: solitary or social? Pp. 293-299 in Winter Ecology of Small
Mammals (J. F. Merritt, ed.). Special Publication, Carnegie Museum of Natural
History.

White, C. R., and R. S. Seymour. 2003. Mammalian basal metabolic rate is proportional

to body mass (2/3). Proceedings of the National Academy of Sciences of the
United States of America 100:4046—4049.

Wolff, J. O. 1985a. Comparative population ecology of Peromyscus Ieucopus and
Peromyscus maniculatus. Canadian Journal of Zoology 63:1548-1555.

Wolff, J. O. 1985b. The effects of density, food, and interspeciﬁc interference on home
range size in Peromyscus Ieucopus and Peromyscus maniculatus. Canadian
Journal of Zoology 63:2657-2662.

Wolff, J. O., R. D. Dueser, and K. S. Berry. 1985. Food-habits of sympatric Peromyscus
Ieucopus and Peromyscus maniculatus. Journal of Mammalogy 66:795-79.

Wolff, J. O. 1994. Reproductive success of solitarily and communally nesting white-
footed mice and deer mice. Behavioral Ecology 5:206-209.

Wolff, J. O. 1996. Coexistence of white footed mice and deer mice may be mediated by
ﬂuctuating environmental conditions. Oecologia 108:529—533.

42

CHAPTER THREE

Personality is associated with dispersal in Peromyscus

INTRODUCTION

In order for an animal to colonize a new habitat prior to the onset of spring
breeding, it must have successfully over-wintered and must be a suitable candidate for
dispersal. In general, the decision to disperse is affected by multiple factors, including
external factors like inbreeding risk and competition, and internal phenotypic factors
like physiology, morphology, life history, and behavior (Clobert et al. 2009). With
respect to behavior, a new area of research has developed that focuses on repeatable
individual differences in behavior, referred to as temperaments (Réale et al. 2007),
behavioral syndromes (Sih et al. 2004), and/or personalities (Dingemanse et al. 2003).

Individual variation in personality has been linked to dispersal in several
vertebrate species and may lend insight into the question of what personality
phenotypes are most likely to colonize de-populated habitats. For instance, among
mosquitoﬁsh (Gambusia aﬂinis), asocial individuals were more likely to disperse than
social individuals (Cote et al. 2010). In the common lizard (Lacerta vivipara), the
interaction of sociality and population density at the natal site predicted dispersal
behavior (Cote and Clobert 2007). Among great tits (Parus major), immigrant birds
were faster explorers than those that were born on the study site (Dingemanse et al.
2003). In bluebirds, biased dispersal of highly aggressive western bluebirds (Sialia
mexicana) facilitated their range expansion and the displacement of less aggressive

mountain bluebirds (Sialia currucoide —Duckworth and Badyaev 2007). Finally, in

43

Trinidad killiﬁsh (Rivulus hartii), bold individuals dispersed farther than shy
individuals (Fraser et al. 2001). I chose to examine this link between personality and
dispersal in deer mice of the genus Peromyscus.

The abundances of white-footed mice, Peromyscus Ieucopus, and deer mice, P.
maniculatus, ﬂuctuate and are driven by weather and food resources, with peaks in the
late summer and crashes in the winter followed by population grth from early spring
through late summer (Falls et al. 2007; Kalcounis-Rueppell et al. 2002; Lewellen and
Vessey 1998; Merritt et al. 2001). Overwinter mortality can result in depopulated
habitat fragments that are then re-colonized in the spring (Krohne et al. 1984). For a
mouse to re-colonize a depopulated habitat early in the spring, before spring breeding, it
must have successfully over-wintered and then be able to disperse from its current
habitat to the new habitat.

Much is already known about dispersal in the ecologically and morphologically
similar species, P. Ieucopus and P. maniculatus (Cogshall 1928; Drickamer 1987;
Drickamer and Capone 1977; Lindquist et al. 2003; Pierce and Vogt 1993; Wolff 1985;
Wolff et al. 1985). Two types of dispersers have been identiﬁed, colonists and non-
colonists. Colonists are adult mice that disperse into habitat that has experienced
extreme winter mortality early in the spring, while non-colonizing dispersers disperse
into an already populated area (Krohne et al. 1984). Mice that do not disperse are
termed residents. Previous studies of Peromyscus have shown that mice disperse more
often during times of increasing population density and most often in the spring and fall
rather than in winter (Fairbaim 1978; Krohne et al. 1984; Nadeau et al. 1981). Among

dispersers, males disperse more often and farther than females (J acquot and Vessey

44

1995; Krohne et al. 1984). On the contrary, if one considers only colonist dispersers,
adult females disperse slightly more often than adult males (J acquot and Vessey 1995;
Krohne et al. 1984). While juveniles cannot be early colonists (sensu Krohne et al.
1984), they do disperse, potentially as a means to avoid inbreeding and/or to reduce
reproductive or resource competition with parents and same-sexed offspring (Wolff
1992)

Recent research on interspeciﬁc and intraspeciﬁc variation in animal personality
in P. Ieucopus noveboracensis and P. maniculatus gracilis in Michigan has revealed
behavioral axes representative of activity level, sociality, and aggression (Chapter 2). In
2008, I live-trapped P. Ieucopus and P. maniculatus gracilis in the Pigeon River State
Forest, Michigan. My 14.4-hectare grid supported one resident mouse in early May
2008, leaving a large area to be re-colonized. In the fall of 2008, the grid supported 40
residents. The purpose of this study was to use basic descriptive data (i. e. age, sex, and
species) and behavioral axes to understand how the behavioral phenotypes of dispersers
change as the season progresses. The extremely low spring abundance allowed me to
examine which personality types were best able to colonize suitable habitat early in the

season compared with those that arrived in the area later in the breeding season. I used
small sample corrected Akaike’s Information Criteria (AICC) to determine which of

three a priori linear models best described arrival date on the grid: 1) a basic model
containing descriptor variables like age and sex 2) a model containing three behavioral

axes, or 3) a model combining basic and behavioral variables.

45

MATERIALS AND METHODS
Study site and population
This study was conducted on a 14.4-hectare grid in the Pigeon River State Forest
in the northern lower peninsula of Michigan (45.3°N, 84.4°W). Individual mice were
monitored by livetrapping from May to August 2008 (11,603 trap nights). Sherman live
traps (7.62 x 8.89 x 22.86 cm and 5.08 x 12.70 x 16.51 cm) were placed at 20-m
intervals throughout the grid and baited with rolled oats. Traps were set at dusk and
checked between 0000 h and 0300 h, 4 to 6 nights per week. Details on trapping data
collection can be found in Chapter 2. Brieﬂy, at ﬁrst capture, I ear-tagged each mouse
and recorded weight (measured with a Pesola scale to the nearest 0.5 g), sex, age (based
on pelage: grey = juvenile, grey and brown = subadult, brown = adult —-Schug et al.
1991), reproductive status (males: testes abdominal or testes scrotal; females: nipples
small, nipples enlarged but not lactating, lactating, or pregnant), and putative species
(based on ear size and general appearance and behavior). Saliva samples were collected
from each mouse upon ﬁrst capture for later species typing by salivary amylase
electrophoresis (Aquadro and Patton 1980). During subsequent captures, I recorded ear
tag numbers, weight, sex, reproductive status, and putative species.
Extraction of behavioral axes
Details on the open-ﬁeld trials can be found in Chapter 2. Brieﬂy, open-ﬁeld
behavioral trials were performed in a portable arena that was placed 0.5 km from the
trapping grid to control for home range effects on aggression (Oyegbile and Marler
2006). I performed three different types of trials on the mice: basic, scent, and dyadic

trials. During the basic trial, each mouse was video-recorded for ﬁve minutes in the

46

arena containing a toilet paper roll taped to each comer of the bottom of the arena.
During the scent trial, each mouse was recorded for ﬁve minutes in the arena containing
two toilet paper rolls, a paper plate with Bobcat PeeTM scented bedding, and a paper
plate with “forest” scented bedding (Scent Killer® Autumn F ormula®). For the dyadic
trial, two mice of the same sex, age, and reproductive status, but the same or different
species, were recorded together in an empty arena for 10 minutes. All methods were
approved by the Michigan State University All University Committee on Animal Use
and Care (AUF# 03/08-034-00).

Behavioral variables were extracted from the video ﬁles using J Watcher +
Video 1.0 (Blumstein et al. 2006) and analyzed using principal component analysis to
uncover the behavioral axes that captured most of the variation in these behaviors
(activity, sociality, aggression, Table 3.1). By deﬁnition, a personality refers to
individual behavioral differences that are repeatable across time and situations (Réale et
al. 2007). The activity axes in the basic and scent trials were positively correlated, thus
forming a personality (Chapter 2). Sociality and aggression were extracted only from
the dyadic trial, and were thus only measured in a single context, with most mice being
tested only once, thus making it difﬁcult to assess the repeatability of these traits across
time and context and making it impossible to determine if these are actual personalities.

From the mice that had scores for all three trial types, I subset out mice that
dispersed onto my grid (those that were ﬁrst trapped as adults or as subadults greater
than 15 grams, n=13). All analyses on dispersers used only these mice. Analyses on all
mice included dispersers as well as any mice for which I could not determine dispersal

status (mice that were ﬁrst trapped as juveniles or subadults less than 15 grams, n=16).

47

I calculated trappability for all mice as the sum of all individuals’ number of
captures (minus the ﬁrst and last) divided by the sum of all individuals’ number of
potential captures (minus the ﬁrst and last) (Lusk and Millar 1989). Trappability was
calculated at 81.8% in 2008, indicating that the ﬁrst time I trapped each mouse was
likely close to its arrival date on the grid.

Statistical analyses

To uncover factors affecting the timing of arrival on my grid, I used linear

models to assess the signiﬁcance of species, sex, age, activity, sociality, and aggression

on arrival date of dispersers. The effects of these variables as predictors of arrival date
were assessed by comparing three a priori models using AICC: 1) a basic model that

included species, sex and age, 2) a behavioral model that included activity, sociality,
and aggression, and 3) a full model that included all of the basic and behavioral
variables. Behavioral metrics (e.g., activity, sociality, aggression) were based on
appropriate PC scores from the ﬁrst open-ﬁeld trial for each mouse only (see Chapter 2
for details). Principal component scores for activity were multiplied by -1 so that higher
scores represented higher activity levels.

After ﬁnding that all three variables in the behavioral model had signiﬁcant
effects on arrival date, I tested whether habituation and plasticity had any effect on
activity, sociality, and aggression. Habituation refers to a directional change in behavior
as mice become accustomed to the behavioral trials. To examine the effect of
habituation on activity, I included trial number as a ﬁxed effect in statistical models of
mouse behavior. If trial number showed a signiﬁcant effect, it would indicate that the

mice became habituated to the open-ﬁeld trials. For the purpose of this paper, I deﬁne

48

plasticity as a directional change in behavior over the course of the season. To examine
the role of plasticity in changes in activity, sociality, and aggression in dispersers, I
included trial date as a ﬁxed effect in the statistical models described below. If trial date
showed a signiﬁcant effect on any of three behavioral axes, it would indicate that the
mice showed directional plasticity in that behavior over the course of the season. I used
Pearson’s correlations to determine if arrival date was correlated with trial date, and if
trial date was correlated with trial number. All dates used were based on the Julian
calendar.

For activity, I created a mixed effects linear model (nlme package in R) with
activity as the response variable and arrival date, trial number, and trial date as ﬁxed
effects. I used mouse ID as a random effect to test for individual repeatability. Because
arrival date is only relevant for dispersers, and is thus equivalent to emergence date for
mice born on the grid, I then created a mixed effect linear model using only trial
number and trial date as ﬁxed effects and mouse identity as a random effect. The
activity models examined 57 mice and a total of 93 trials.

For sociality and aggression, only 7 mice out of 29 had more than one trial (and
only 1 mouse had 3 trials). For this reason, I used only the ﬁrst trial for each mouse and
created linear models with the behavioral axis (sociality or aggression) as the response
variable and arrival date and trial date as ﬁxed effects. Again, because arrival date is
only relevant for dispersers, I then created linear models using only trial date as a ﬁxed
effect. The sociality and aggression models examined 29 mice. All statistical analyses

were performed in R version 2.9.2 (R Development Core Team 2009).

49

RESULTS
Model selection
The basic a priori model revealed that age and sex were signiﬁcant predictors of
arrival date, while species showed no effect, with adults arriving 24.6 :t 8.9 days before
subadults and males arriving 21.1 i 9.2 days before females (Table 3.2). The full model

revealed that activity, sociality, aggression, and species were signiﬁcant predictors of

arrival date, with age and sex not being signiﬁcant (Table 3.2). Model selection of these
three models using AICC revealed that the behavioral model was overwhelmingly the

best at predicting arrival date and will be referred to as the best model (Table 3.3). The

best model revealed that activity, sociality, and aggression were all signiﬁcant

predictors of arrival date. Speciﬁcally, mice that arrived on the grid earlier in the

season were more active, more social, and less aggressive than mice that arrived later in

the season (Table 3.2 and see Table 3.1, Figure 3.1).

Do early dispersers differ in personality because of individual variation, plasticity,
or habituation?

Arrival date was signiﬁcantly correlated with the date on which the behavioral
trials were performed (Pearson’s r = 0.79, P < 0.0001). As expected, the date on which
the trial was performed was also correlated with the trial number (Pearson’s r = 0.28, P
= 0.007). Mixed effect linear models designed to estimate the effect of plasticity and
habituation on these three behavioral axes showed different results for each behavioral
axis (activity, sociality, and aggression). For the activity axis, repeatability in activity
within an individual was demonstrated by mouse ID accounting for 55.8% of the

variation not accounted for by arrival date, trial date, or trial number. The addition of

50

this random effect signiﬁcantly improved the ﬁt of the model to the data ()8 = 15.9, d.f.
= l, P < 0.001). Only trial date had a marginally signiﬁcant effect on activity level (trial
date: b = -0.04 i 0.02, d.f. = 34, t = -1.8, P = 0.08, arrival date: b = 0.02 i 0.02, d.f. =
55, t = 1.1, P = 0.28, trial number: b = -0.09 i 0.34, d.f. = 34, t = -0.28, P = 0.78),
revealing that mice became less active as the season progressed. When arrival date was
removed from this model, trial date (b = -0.02 i 0.006, d.f. = 34, t = -2.5, P = 0.02) and
trial number became signiﬁcant (b = -0.44, SE = 0.12, d.f. = 34, t = -3.5, P = 0.002)
predictors of activity level.

For the sociality axis, neither arrival date nor trial date had a signiﬁcant effect
on sociality (arrival: b = 0.0005 i 0.02, t = 0.28, P = 0.98, Julian: b = -0.03 i 0.02, t = -
1.1, P = 0.28 model statistics: F = 2.0, d.f. = 2, 26, P = 0.15). When arrival date was
removed, trial date became a signiﬁcant predictor of sociality (F = 4.2, d.f. = 1, 27, P =
0.05), demonstrating that mice became less social as the season progressed.

For the aggression axis, neither arrival date nor trial date had a signiﬁcant effect
on aggression (arrival: b = -0.000 i 0.02, t = -0.001, P = 1.0, Julian: b = 0.01 i 0.02, t =
0.47, P = 0.6, model statistics: F = 0.4, d.f. = 2, 26, P = 0.7). When arrival date was
removed, trial date still had no effect (F = 0.8, d.f. = 1, 27, P = 0.4), demonstrating that
mice show no trend in aggression over the season.

DISCUSSION

Most studies that examine dispersal examine either basic descriptor variables
like age and sex (Jacquot and Vessey 1995; Krohne et al. 1984) or personality variables
(Cote et al. 2010; Duckworth and Badyaev 2007) as predictors of dispersal. My study

examined both basic descriptor variables and personality variables, and revealed that

51

personality describes disperser phenotypes better than basic descriptor variables. Early
dispersers on my trapping grid were active, social, and submissive mice, while later-
season dispersers were less active, less social, and more aggressive. While the basic
model was marginally signiﬁcant and indicated that early dispersers were likely adult
males, the full model containing basic descriptor and personality variables revealed that
the personality variables were the best predictors of arrival date (Table 3.2). Prior
studies of dispersal in Peromyscus focused solely on basic descriptor variables (J acquot
and Vessey 1995; Krohne et al. 1984), ﬁnding that males dispersed farther and more
often than females but early dispersers into an empty habitat were more likely adult
females. However, they did not examine the mechanism behind these dispersal
phenotypes. My study illustrates that personality may be mediating the relationship
between basic variables like age and sex and dispersal behavior.

While species was not a signiﬁcant predictor of arrival date in the basic model,
when behavioral axes were added to the model, it became signiﬁcant, revealing that P.
maniculatus arrived 12.4 days later than P. Ieucopus (Table 3.2). This shiﬁ from being
non-signiﬁcant in the basic model to becoming signiﬁcant in the full model suggests
that the species effect was counteracted by an opposite effect of some personality metric
that differed between the two species. Speciﬁcally, more active mice arrived earlier
than less active mice and P. maniculatus were more active than P. Ieucopus. However,
after controlling for the effects of activity on anival date, P. maniculatus were found to

arrive on the grid later than P. Ieucopus.

52

Activity

Previous work on muroid rodents suggests that in unproductive environments,
like northern Michigan in late winter and early spring, animals with high exploration, or
activity level, are better able to ﬁnd scarce resources (Careau et al. 2009). The trends I
uncovered in the activity personality axis among dispersers, which is repeatable across
time and across contexts, may be explained by the relationship between activity level
and the ability to ﬁnd resources. Thus, early in the spring, when the forest is less
productive than later in the summer, mice should be more active and thus more likely to
disperse in order to ﬁnd food (and hence more exploratory, according to the deﬁnition
in Careau et al. 2009). As the season progresses and forest productivity increases, mice
should reduce their activity levels because the abundance of resources makes them
easier to ﬁnd. How then is activity level linked to later-season dispersal?

After discovering ﬁom my best model that early dispersers were more active
than later dispersers, I proceeded to test whether plasticity had any effect on personality
in all of the mice I tested. My models revealed that activity was indeed a plastic
behavioral axis, with all mice showing a trend to become less active as the season
progressed and as trial number increased. This is expected, as activity is beneﬁcial in
the unproductive environment of early spring but not as beneﬁcial when the forest is at
high productivity (Careau et al. 2009).

Sociality

Previous studies have demonstrated that asocial animals are more likely to

disperse, thus moving away from conspeciﬁcs (Cote et al. 2010). However, my results

revealed that early dispersers were more social than late dispersers. This trend could be

53

due to a link between personality and over-winter survival, rather than dispersal.
Because cuddling is used in cold tolerance (Andrews and Belknap 1993a, 1993b;
Merritt and Zegers 2002), early in the spring when temperatures are colder, over-
wintered mice should be more social than later in the summer when temperatures are
warmer. Sociality played an important role in my best model, with the largest effect on
arrival date, and was thus likely an important trait in early dispersers. This suggests that
early dispersers may have over-wintered successfully as a result of using cuddling as a
method of cold tolerance.

As with activity, it is straightforward to link sociality to early dispersal because
mice that disperse early must have over-wintered successfully, and would thus have
beneﬁtted ﬁ'om communal nesting (Andrews and Belknap 1993a, 1993b; Merritt and
Zegers 2002). The link between late-season dispersal and low sociality is less clear, as
late-season dispersers are dispersing into higher population densities. Thus, I conclude
that the sociality trends may be due to plasticity among all mice. Sociality was found to
be a plastic behavioral axis, with mice becoming less social as the season progressed,
most likely in response to rising temperatures and a lower need for communal nesting as
a method of cold tolerance.

Aggression

Because mice are less aggressive at low population densities (Wolff 1985), most
likely as a way to conserve energy when aggression is not necessary, early dispersers
dispersing into almost empty habitat can be submissive individuals, while late-season
dispersers should be aggressive individuals. However, aggression was not plastic,

showing no distinct trends among all mice as the season progressed. This is likely

54

because the greatest population density on my trapping grid was 1.52 mice per hectare,
never reaching the density necessary to affect aggression (greater than 25 mice per
hectare—Wolff 1985). This ﬁnding suggests that aggression plays a key role in
differentiating early dispersers from late-season dispersers. Hence, while the general
trend among mice was to reduce activity level and sociality as the season progressed,
mice that were active, social, and submissive were likely to be early dispersers while
mice that were less active, less social, and aggressive were likely to be later dispersers.
Early dispersers are more likely to be less aggressive than late-season dispersers
because early dispersers disperse into lower population densities than late-season
dispersers, and thus do not need to devote energy to aggression (Wolff 1985b).
Conclusion

This study illustrates the utility of personality as a predictor of dispersal and
overwintering and emphasizes the need to examine more than one personality axis. If I
had studied only activity or sociality, my results would have been hard to tease apart
and might have suggested that, because all mice exhibit plasticity in these traits, neither
behavioral axis is sufficient to describe disperser phenotypes. However, when I used the
three behavioral axes together, I discovered that early dispersers are the most active,
most social, and least aggressive dispersers, with later-season dispersers becoming less
active, less social, and more aggressive. I know that these differences are distinct from
the plasticity seen in activity and sociality because of the different temporal trends in
aggression in dispersers versus the general population. Future studies of personality
should examine more than one behavioral axis, with multiple measures of each axis per

individual, for both the population under study (e. g. dispersers) and all animals in the

55

population to ensure that what appears as individual variation in personality is not only

due to plasticity.

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60

LITERATURE CITED

Andrews, R. V., and R. W. Belknap. 1993a. Season affects tolerance of cohabitation
by deer mice. Physiology & Behavior 53:617—620.

Andrews, R. V., and R. W. Belknap. 1993b. Seasonal acclimation of prairie deer mice.
International Journal of Biometeorology 37: 190-193.

Aquadro, C. F ., and J. C. Patton. 1980. Salivary amylase variation in Peromyscus— Use
in species identiﬁcation. Journal of Mammalogy 61 :703-707.

Blumstein, D. T., J. C. Daniel, and C. S. Evans. 2006. JWatcher 1.0., Los Angeles,
California.

Careau, V., O. R. P. Bininda-Emonds, D. W. Thomas, D. Réale, and M. M.
Humphries. 2009. Exploration strategies map along fast-slow metabolic and life-
history continua in muroid rodents. Functional Ecology 23:150-156.

Clobert, J ., J. F. Le Galliard, J. Cote, S. Meylan, and M. Massot. 2009. Informed
dispersal, heterogeneity in animal dispersal syndromes and the dynamics of
spatially structured populations. Ecology Letters 12:197-209.

Cote, J ., and J. Clobert. 2007. Social personalities inﬂuence natal dispersal in a lizard.
Proceedings of the Royal Society B-Biological Sciences 274:383-390.

Cote, J ., S. Fogart, K. Iinersmith, T. Brodin, and A. Sih. 2010. Personality traits and
dispersal tendency in the invasive mosquitoﬁsh (Gambusia aﬂinis). Proceedings
of the Royal Society. B, Biological sciences, published online before print
January 13, 2010, doi:10.1098/rspb.2009.2128.

Dingemanse, N. J ., C. Both, A. J. van Noordwijk, A. L. Rutten, and P. J. Drent. 2003.
Natal dispersal and personalities in great tits (Parus major). Proceedings of the
Royal Society of London Series B-Biological Sciences 270:741-747.

Drickamer, L. C. 1987. Inﬂuence of time of day on captures of 2 species of Peromyscus
in a New England deciduous forest. Journal of Mammalogy 68:702-703.

Drickamer, L. C., And M. R. Capone. 1977. Weather parameters, trappability and niche
separation in 2 sympatric species of Peromyscus. American Midland Naturalist
98:376-381.

Duckworth, R. A., and A. V. Badyaev. 2007. Coupling of dispersal and aggression
facilitates the rapid range expansion of a passerine bird. Proceedings of the
National Academy of Sciences of the United States of America 104:15017-
15022.

61

Fairbaim, D. J. 1978. Dispersal of deer mice, Peromyscus maniculatus- Proximal causes
and effects on ﬁtness. Oecologia 32: 171-193.

Falls, J. B., E. A. Falls, J. M. Fryxell, and Um. 2007. Fluctuations of deer mice in
Ontario in relation to seed crops. Ecological Monographs 77:19-32.

Fraser, D. F ., J. F. Gilliam, M. J. Daley, A. N. Le, and G. T. Skalski. 2001. Explaining
leptokurtic movement distributions: Intrapopulation variation in boldness and
exploration. American Naturalist 158: 124-1 35.

Jacquot, J. J ., and S. H. Vessey. 1995. Inﬂuence of the natal environment on dispersal
of white-footed mice. Behavioral Ecology and Sociobiology 37:407-412.

Kalcounis-Rueppell, M. C., J. S. Millar, and E. J. Herdman. 2002. Beating the odds:
effects of Weather on a short-season population of deer mice. Canadian Journal
of Zoology-Revue Canadienne De Zoologie 80:1594-1601.

Krohne, D. T., B. A. Dubbs, and R. Baccus. 1984. An analysis of dispersal in an
unmanipulated population of Peromyscus Ieucopus. American Midland
Naturalist 112:146-156.

Lewellen, R. H., and S. H. Vessey. 1998. The effect of density dependence and
Weather on population size of a polyvoltine species. Ecological Monographs
68:571-594.

Lindquist, E. S., C. F. Aquadro, D. McClearn, and K. J. McGowan. 2003. Field
identiﬁcation of the mice Peromyscus Ieucopus noveboracensis and P.
maniculatus gracilis in central New York. Canadian Field-Naturalist 117:184-
189.

Lusk, S. J. G., and J. S. Millar. 1989. Reproductive inhibition in a short-season
population of Peromyscus maniculatus. Journal of Animal Ecology 58:329-341.

Merritt, J. F., M. Lima, and F. Bozinovic. 2001. Seasonal regulation in ﬂuctuating
small mammal populations: feedback structure and climate. Oikos 94:505-514.

Merritt, J. F., and D. A. Zegers. 2002. Maximizing survivorship in cold: thermogenic
proﬁles of non-hibemating mammals. Acta Theriologica 47:221-234.

Nadeau, J. H., R. T. Lombardi, and R. H. Tarnarin. 1981. Population structure and
dispersal of Peromyscus Ieucopus on Muskeget Island. Canadian Journal of
Zoology-Revue Canadienne De Zoologie 59:793-799.

Oyegbile, T. O., and C. A. Marler. 2006. Weak winner effect in a less aggressive

mammal: Correlations with corticosterone but not testosterone. Physiology &
Behavior 89:171-179.

62

Pierce, S. S., and F. D. Vogt. 1993. Winter acclimatization in Peromyscus- maniculatus-

gracilis, P. Ieucopus-noveboracensis, and P. I. Ieucopus. Journal of
Mammalogy 74:665-677.

R Development Core Team. 2009. R: A language and environment for statistical
computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-
900051-07-0, URL http://wwwR-proiectrgg,

Réale, D., S. M. Reader, D. Sol, P. T. McDougall, and N. J. Dingemanse. 2007.
Integrating animal temperament within ecology and evolution. Biological
Reviews 82:291-318.

Schug, M. D., S. H. Vessey, and A. I. Korytko. 1991. Longevity and survival in a

population of white-footed mice (Peromyscus Ieucopus). Journal of Mammalogy
72:360-366.

Sih, A., A. Bell, and J. C. Johnson. 2004. Behavioral syndromes: an ecological and
evolutionary overview. Trends in Ecology & Evolution 19:372-3 78.

Wolff, J. O. 1985. Comparative population ecology of Peromyscus-Ieucopus and
Peromyscus-maniculatus. Canadian Journal of Zoology-Revue Canadienne De
Zoologie 63:1548-1555.

Wolff, J. O. 1985b. The effects of density, food, and interspeciﬁc interference on home

range size in Peromyscus Ieucopus and Peromyscus maniculatus. Canadian
Journal of Zoology 63:2657-2662.

Wolff, J. O. 1992. Parents suppress reproduction and stimulate dispersal in opposite sex
juvenile white-footed mice. Nature 359:409-410.

Wolff, J. O., R. D. Dueser, and K. S. Berry. 1985. Food-habits of sympatric

Peromyscus-Ieucopus and Peromyscus-maniculatus. Journal of Mammalogy
66:795-798

63

CHAPTER FOUR
General conclusion: Personality in Peromyscus

The goal of many ecological studies it to achieve a better understanding of the
mechanisms mediating classic ecological phenomena such as the coexistence of similar
species and the drivers of dispersal. Deer mice of the genus Peromyscus are widespread
across North America (King 1968), are relatively easy to live-trap, and thus are a prime
model system in which to address these questions. Although ecological research has
traditionally regarded individual variation as statistical noise, a new area of research
utilizes these individual differences to make inferences about ecological processes by
examining the implications of repeatable individual differences in behavior (Réale et al.
2007; Sih et al. 2004). These are termed temperaments (Réale et al. 2007), behavioral
syndromes (Sih et al. 2004), or personalities (Dingemanse et al. 2003). Because
Peromyscus have been so well studied, much is already known about their ecology and
morphology. For this reason, I chose to examine personality in two species of sympatric
Peromyscus in an attempt to uncover behavioral axes that might serve as axes of niche
differentiation and better describe dispersal phenotypes in these mice.

In Chapter 2, I examined inter- and intraspeciﬁc variation in personality using
open ﬁeld behavioral trials in two species of deer mice in the northern Lower Peninsula
of Michigan, Peromyscus Ieucopus noveboracensis, the white-footed mouse, and P.
maniculatus gracilis, the woodland deer mouse. I uncovered four behavioral axes that
describe activity, sociality, location, and aggression in these species. I found that P.
maniculatus was more active than P. Ieucopus. As activity is related to cold tolerance

(Sears et al. 2009), this ﬁnding is consistent with the difference in geographical range

64

between the two species, with P. maniculatus extending farther north, into colder
temperatures, than P. Ieucopus. It is possible that the higher activity levels exhibited by
P. maniculatus allow it to generate more heat by exercise therrnogenesis, thus making
this species better able to avoid excessive heat loss (Makinen et al. 1996) and to thrive
in colder temperatures than P. Ieucopus.

Peromyscus maniculatus also had more contact with the opponent in dyadic
trials than P. Ieucopus and was thus more sociable (Cote et al. 2010). This is consistent
with the reported superiority of the former with respect to adaptation to cold
temperatures, as small mammals often use communal nesting as a way to conserve
energy in the winter (Merritt and Zegers 2002; West and Dublin 1984).

When looking at sociality and aggression for each species separately, I found no
differences based on whether the opponent was a conspeciﬁc or a heterospeciﬁc. These
ﬁndings are in agreement with past research that found no difference in inter- versus
intraspeciﬁc aggression for home ranges (Wolff 1985). Wolff (1985) determined that
home range size is density dependent, and is based on the population density of both
species rather than just one. However, raw behavioral variables did reveal differences in
approach and retreat behaviors that should be further examined.

In Chapter 3, I used three of these personality axes to examine the personalities
of mice that dispersed onto my trapping grid early in the season compared to those that
dispersed onto my trapping grid later in the season. I found that early dispersers on my
trapping grid were active, social, and submissive mice, with later-season dispersers
becoming less active, less social, and more aggressive. I also found that activity and

sociality showed a plastic trend in response to trial date among all mice while

65

aggression showed no such trend, thus highlighting the importance of aggression in
describing dispersal phenotypes in Peromyscus.

In conclusion, Peromyscus Ieucopus noveboracensis and P. maniculatus gracilis
may coexist along behavioral axes of activity level and sociality. As winters ﬂuctuate
from year to year, the relative abundances of these two species should also ﬂuctuate.
Peromyscus maniculatus, which is more active and more social, should increase in
abundance in colder years, when higher activity levels will allow procurement of
resources in an unproductive environment (Careau et al. 2009) and cuddling will be
used as a means of cold tolerance (Andrews and Belknap 1993a, 1993b; Merritt and
Zegers 2002). In colder years, P. Ieucopus should decrease in abundance because it is
less active and less social, and is thus less able to procure resources and stay warm in
cold years. Then in warmer years, P. Ieucopus should increase in abundance while P.
maniculatus should either stay the same or decrease in abundance. Furthermore, the
behavioral axes I uncovered are useful to describe individual variation in disperser
phenotypes, with early season dispersers being more active, more social, and less
aggressive than late-season dispersers. While individual behavioral variation plays a
large role in describing disperser phenotypes, two of these axes were also shown to be
plastic, with all mice in general becoming less active and less social as the season
progressed.

This thesis highlights the value of including personality variables in ecological
ﬁeld studies. I have made a contribution to the already vast body of literature that
examines coexistence in Peromyscus Ieucopus and P. maniculatus and have used the

personality axes that I uncovered in the ﬁrst study to better understand which

66

individuals are likely to disperse. Because of the wide variance in personality
phenotypes, studies that include personality will give a detailed understanding of many

phenomena central to the study of ecology.

67

LITERATURE CITED

Andrews, R. V., and R. W. Belknap. 1993a. Season affects tolerance of cohabitation
by deer mice. Physiology & Behavior 53:617-620.

Andrews, R. V., and R. W. Belknap. 1993b. Seasonal acclimation of prairie deer mice.
International Journal of Biometeorology 37:190-193.

Careau, V., O. R. P. Bininda-Emonds, D. W. Thomas, D. Réale, and M. M. Humphries.
2009. Exploration strategies map along fast-slow metabolic and life-history
continua in muroid rodents. Functional Ecology 23:150-156.

Cote, J., S. F ogart, K. Iinersmith, T. Brodin, and A. Sih. 2010. Personality traits and
dispersal tendency in the invasive mosquitoﬁsh (Gambusia afﬁnis). Proceedings

of the Royal Society. B, Biological sciences, published online before print
January 13, 2010, doi:10.1098/rspb.2009.2128.

Dingemanse, N. J ., C. Both, A. J. van Noordwijk, A. L. Rutten, and P. J. Drent. 2003.
Natal dispersal and personalities in great tits (Parus major). Proceedings of the
Royal Society of London Series B-Biological Sciences 270:741-747.

King, J. A. 1968. Biology of Peromyscus (Rodentia). First Edition. The American
Society of Mammalogists, Stillwater, Oklahoma.

Makinen, T., H. Rintamaki, E. Hohtola, and R. Hissa. 1996. Energy cost and
thermoregulation of unrestrained rats during exercise in the cold. Comparative
Biochemistry and Physiology a-Physiology 114:57-63.

Merritt, J. F., and D. A. Zegers. 2002. Maximizing survivorship in cold: thermogenic
proﬁles of non-hibemating mammals. Acta Theriologica 47:221-234. .

Réale, D., S. M. Reader, D. Sol, P. T. McDougall, and N. J. Dingemanse. 2007.
Integrating animal temperament within ecology and evolution. Biological
Reviews 82:291-318.

Sears, M. W., J. P. Hayes, M. R. Banta, and D. McCormick. 2009. Out in the cold:
physiological capacity inﬂuences behaviour in deer mice. Functional Ecology
23:774-783.

Sih, A., A. Bell, and J. C. Johnson. 2004. Behavioral syndromes: an ecological and
evolutionary overview. Trends in Ecology & Evolution 19:372-378.

West, S. D., and H. T. Dublin. 1984. Behavioral strategies of small mammals under
winter conditions: solitary or social? Pp. 293-299 in Winter Ecology of Small
Mammals (J. F. Merritt, ed.). Special Publication, Carnegie Museum of Natural
History.

68

Wolff, J. O. 1985. The effects of density, food, and interspeciﬁc interference on home
range size in Peromyscus-Ieucopus and Peromyscus-maniculatus. Canadian
Journal of Zoology-Revue Canadienne De Zoologie 63:2657-2662.

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