Habitat-Specific Fitness Benefits of Sociality in Octodon Degus

HABITAT-SPECIFIC FITNESS BENEFITS OF SOCIALITY IN OCTODON DEGUS

MADELINE KLEES STROM

Loren Hayes Hope Klug Associate Professor Associate Professor Biology, Geology, and Environmental Science Biology, Geology, and Environmental Science (Advisor) (Committee Member)

Mark Schorr Professor Biology, Geology, and Environmental Science (Committee Member)

HABITAT-SPECIFIC FITNESS BENEFITS OF SOCIALITY IN OCTODON DEGUS

MADELINE KLEES STROM

A Thesis Submitted to the Faculty of the University of Tennessee at Chattanooga in Partial Fulfillment of the Requirements of the Degree of Master of Science: Environmental Science

The University of Tennessee at Chattanooga Chattanooga, Tennessee

August 2017

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ABSTRACT

Recent debate has focused on how ecology shapes the evolution of group-living and cooperation in social vertebrates. Evidence suggests that group-living and cooperation enhance reproductive success under harsh local conditions in some species. Across two years, I studied two populations of Octodon degus, a plurally breeding rodent, to answer three questions: (1)

Does living in large groups and having strong social network strength improve access to resources in harsh environments? (2) Does increased access to resources improve the reproductive success of group-living females? (3) Does living in large groups and having strong social network strength improve reproductive success of females in harsh environments? I quantified group sizes and social network strength, ecological conditions at burrow systems, and per capita offspring weaned of social groups to answer these questions. I found site- and year-specific relationships in partial support of predictions, demonstrating habitat-specific costs and benefits of social group-living and cooperation.

DEDICATION

To Mary K. Harris, for always lifting me up when I doubted myself.

ACKNOWLEDGMENTS

I would like to thank my dedicated advisor, Dr. Loren Hayes, for his continued guidance, wisdom and support during my many years in the Hayes lab. I also thank my thesis committee members, Dr. Hope Klug and Dr. Mark Schorr, for their advice in statistical analyses and the writing process. I am extremely thankful for, and indebted to my collaborators in Chile. Firstly, I thank Dr. Luis Ebensperger and his lab members at Pontificia Universidad Católica de Chile, without whom this project would not exist. Secondly, I thank Dr. Rodrigo Vasquez and his lab members at Universidad de Chile for providing me with essential and hardworking field assistants. I thank the graduate students at UTC for always giving me emotional support

(especially fellow Hayes students who accompanied me to remote field stations in Chile), and my friends who encouraged me to pursue a graduate degree. Finally, I thank my loving family, for always cheering me on, teaching me to say yes to every inspiring opportunity that comes my way, and without whom none of my dreams would be possible.

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TABLE OF CONTENTS

ABSTRACT ...... v

DEDICATION ...... vi

ACKNOWLEDGEMENTS ...... vii

LIST OF TABLES ...... xi

LIST OF FIGURES ...... xii

LIST OF TERMS ...... xiv

LIST OF ABBREVIATIONS ...... xvi

CHAPTER

I. INTRODUCTION ...... 1

Hypotheses for the formation of social groups and cooperation ...... 3 Costs and benefits of group-living and cooperation ...... 7 Direct fitness consequences of social group-living ...... 13 Challenges ...... 14 Ecology and social variation ...... 15 Social structure and social network analysis ...... 16 Thesis objectives ...... 18 Study sites ...... 21

II. HABITAT-SPECIFIC FITNESS BENEFITS OF SOCIALITY IN OCTODON DEGUS ..... 25

Introduction ...... 25 Habitat-specific fitness consequences ...... 28 Social networks ...... 29 Study organism and objectives ...... 31 Methods ...... 34 Study populations ...... 34 Social group identification ...... 35 viii

Social network analysis ...... 37 Ecological sampling ...... 38 Fitness estimates ...... 39 Statistical analysis ...... 39 Hypothesis Tests About Means ...... 39 Hypothesis Tests about Regression Relationships ...... 40 Question 1 ...... 40 Question 2 ...... 41 Question 3 ...... 41 Results ...... 42 Descriptive statistics ...... 42 Question 1: Does living in large groups and having strong network strength improve access to resources in harsh environments? ...... 44 Rinconada ...... 44 Fray Jorge ...... 45 Per capita offspring weaned ...... 49 Question 2: Does increased access to resources improve the direct fitness of group-living females? ...... 50 Rinconada ...... 50 Fray Jorge ...... 52 Question 3: Does living in large groups and having strong network strength improve direct fitness of females in harsh environments? ...... 52 Rinconada ...... 52 Fray Jorge ...... 53 Discussion ...... 55 Question 1: Benefits of social group-living and cooperation ...... 57 Question 2: Access to resources and fitness benefits ...... 61 Question 3: Direct fitness benefits of social group-living and cooperation ...... 63 Why live in groups? ...... 64 Evolutionary history ...... 65 Stress physiology ...... 65

III. CONSERVATION IMPLICATIONS ...... 68

APPENDIX

A. SOCIAL GROUPS ...... 72

B. ECOLOGICAL DATA ...... 75

C. SOCPROG PROCEDURE ...... 80

D. SOCPROG OUTPUTS/NETWORK DATA ...... 84

REFERENCES ...... 87

VITA ...... 113

LIST OF TABLES

1.1 Definition of terms used to describe breeding strategy and cooperation ...... 3

2.1 Descriptive statistics for degu social groups and ecological variables at Rinconada and Fray Jorge in 2014 and 2015 ...... 42

2.2 Study questions and support ...... 55

LIST OF FIGURES

1.1 A theoretical social group. Ovals represent male (M) and female (F) group members (A-D), lines represent pairwise social associations between group members. Thicker lines represent stronger associations (i.e., high temporal and spatial overlap) ...... 19

1.2 Geographic location of Fray Jorge (top) and Rinconada (bottom) in north-central Chile ...... 22

1.3 Mean (±SE) burrow opening density at burrow systems used by social groups at Fray Jorge (n=9) and Rinconada (n=22) and mean (±SE) number of predators per scan at Fray Jorge (n=40) and Rinconada (n=40) in 2015. * P<0.05 ...... 23

1.4 Mean (± SE) edible ground vegetation (g/m2) at burrow systems used by social groups at Rinconada (2014: n=15, 2015: n=22) and Fray Jorge (2014: n=14, 2015: n=9). No edible ground vegetation was present at Fray Jorge in 2014 due to an unusually dry winter. Different letters represent significant differences P<0.05 ...... 24

2.1 Scatterplot showing the statistically significant relationship between mean social network strength and shrub leaf abundance at Fray Jorge in 2014. Data points represent social groups ...... 46

2.2a Scatterplot showing the statistically significant relationship between mean social network strength and edible ground vegetation at Fray Jorge in 2015 including an outlier data point. Data points represent social groups ...... 47

2.2b Scatterplot showing the relationship between mean social network strength and edible ground vegetation at Fray Jorge in 2015 excluding an outlier data point. Data points represent social groups ...... 48

2.3 Female group size and mean (±SE) shrub leaf abundance at Fray Jorge in 2015 ...... 49

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2.4 Scatterplot showing the statistically significant relationship between per capita number of offspring weaned by social groups and soil hardness at Rinconada in 2014. Data points represent social groups ...... 50

2.5 Scatterplot showing the statistically significant relationship between per capita number of offspring weaned and soil hardness at Rinconada in 2015. Data points represent social groups ...... 51

2.6a Scatterplot showing the positive relationship between per capita offspring weaned and mean social network strength at Fray Jorge in 2015 including an outlier data point. Data points represent social groups ...... 53

2.6b Scatterplot showing the relationship between per capita offspring weaned and mean social network strength at Fray Jorge in 2015 excluding an outlier data point. Data points represent social groups ...... 54

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LIST OF TERMS

Association – measure of the amount of spatial and temporal overlap between two individuals, calculated from trapping and telemetry overlap Benefits of philopatry hypothesis – the lifetime fitness benefits gained from remaining philopatric outweigh the benefits of dispersing and breeding independently Communal rearing – multiple females breed and provide care to offspring Cooperation – interactions of individuals acting together for a common or mutual benefit Direct fitness – an individual’s contribution to the gene pool of a succeeding generation based only on the reproductive success of the individual (number of own offspring) Ecological constraints hypothesis – individuals delay dispersal and remain in the natal ‘nest’ or area when conditions for independent reproduction are limited Fitness – the contribution of an individual to the gene pool of a succeeding generation Group size effects – the costs and benefits experienced as a result of living in close proximity with conspecifics Indirect fitness – benefit to the reproductive success of an individual’s relative due to help provided by the individual; a function of both the relatedness of the donor and recipient of cooperation, and the amount of cooperation Inclusive fitness – the sum of an individual’s direct and indirect fitness Kin structure – degree of genetic relatedness within a group or population Life history hypothesis – longevity, reproductive and dispersal rates explain cooperative breeding Natal philopatry – when offspring remain in the natal ‘nest’ or area beyond sexual maturity Plural breeder – breeding system in which multiple same-sexed individuals breed Reproductive skew – the degree of reproductive inequality Singular breeder – breeding system in which one or few individuals dominate breeding

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Spatio-temporal ecological variation – change in environmental conditions across years and within the landscape Social network analysis – the mathematical quantification of relationships between individuals within a given area during a given time Strength – social network parameter which quantifies the sum of an individual’s social associations, based on the total number and intensity of associations Social system – includes three inter-related components: social organization, social structure, and mating system Social organization – group size and composition Social structure – types and patterns of interactions between individuals of a social group Socioecological theory – uses ecological parameters to predict the variation in social systems Social groups – a form of sociality in which individuals live in relatively long-lasting, stable groups

LIST OF ABBREVIATIONS

PCOW, per capita offspring weaned

ANOVA, analysis of variance

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CHAPTER 1

INTRODUCTION

Animal social systems consist of three inter-related components: (1) social organization

(i.e., group size and composition), (2) social structure and (i.e., social interactions between individuals), and (3) the mating system (Kappeler and van Schaik 2002). Each component of the social system may be influenced by ecological conditions (e.g., food availability, predation risk, climate), socioecological processes (e.g., dispersal, natal philopatry, immigration, emigration), or life history (e.g., rate of growth and development, longevity). The distinctions between the components of the social system are not always understood discretely but rather remain interconnected, and each component alone cannot characterize the social system of a species

(Kappeler and van Schaik 2002). Consequently, understanding animal social systems requires an understanding of how groups form and the fitness benefits of social interactions among group members. To this end, behavioral ecologists have developed a socioecological theory that encompasses the ecological and life history conditions influencing group formation and cooperation, the costs and benefits, as well as reproductive consequences of group-living

(social organization) and cooperation (social structure) (Hamilton 1964; Trivers 1971; Emlen

1982, 1995; Cockburn 1998; Arnold and Owens 1999; Rubenstein 2011; Ebensperger et al.

2012a; Ebensperger et al. 2014). Herein, I discuss (i) hypotheses explaining the formation of social groups and cooperation, (ii) costs and benefits of group-living and cooperation, and (iii) 1 hypotheses for the reproductive consequences of group-living and cooperation, including kin selection theory.

Before discussing these components of theory, it is important to clarify terminology used to describe social species. In the literature, descriptions of social organization and social structure are often integrated into a single term (see: Whitehead 1997; Silk 2007). Here, I address social organization and social structure as two discrete components of the social system. Social organization describes variation in group-living, i.e., group sizes and composition.

Social structure describes the level of interaction, and thus the potential for cooperation, between individuals in the social group. Adding to the confusion, terms are often used interchangeably in describing the breeding strategy of social species. Some authorities refer to cooperative breeders as singular breeders. Species in which multiple same-sexed individuals in a group breed are often referred to as plural breeders, communal breeders, or cooperative breeders. Eusocial breeders are a type of singular breeder in which sterile helpers carry out specialized tasks to care for reproductive members and non-descendent offspring. Meanwhile helpers and non-breeders in singular breeding systems maintain the potential to breed (Wilson

1971; Lacey and Sherman 1997). Some perceive eusocial to plural breeding systems as a continuum (Sherman et al. 1995), although recent work suggests a more dichotomous structure of reproductive monopolization in eusocial insects and cooperatively breeding vertebrates

(Rubenstein et al. 2016). For clarity, I will use the following terms (Table 1.1).

Table 1.1 Definition of terms used to describe breeding strategy and cooperation

Term Operative definition Overlapping terms Cooperative Members of a social group assist with the rearing of non- Singular breeding breeding descendent offspring Singular breeding One pair with disproportionate amount of direct Cooperative reproduction within a social group; includes eusocial breeding animals such as hymenopteran insects, termites, naked and Damaraland mole-rats, as well as non-eusocial groups Eusocial breeding High reproductive skew, cooperative care of offspring, Cooperative overlapping generations, division of labor into breeding, singular reproductive and non-reproductive groups (insects: breeding Wilson 1971, naked mole-rats and Damaraland mole- rats: Jarvis et al. 1994) Plural breeding Direct reproduction shared more equally in the social Communal rearing, group; multiple females breed within the social group communal breeding, joint nesting, plural cooperative breeder Communal care Breeding females share parenting within a social group

Hypotheses for the formation of social groups and cooperation

Three non-mutually exclusive hypotheses can explain the formation of social groups (a form of sociality in which individuals live in relatively long-lasting, stable groups; Alexander

1974): ecological constraints, benefits of cooperation, and life history. To a lesser extent, predation pressure influences group formation in primates (Alexander 1974; Van Schaik 1983,

1989). Group-living in New World hystricognath rodents is associated with burrow-digging

(Ebensperger and Blumstein) burrow availability or the costs of burrow construction and maintenance (Branch 1993; Ebensperger and Bozinovic 2000b).

The ‘ecological constraints hypothesis’ posits that individuals delay dispersal and remain philopatric to natal nests when conditions for independent reproduction are limited.

The hypothesis predicts greater natal philopatry (i.e., when offspring remain in the natal ‘nest’ or area beyond sexual maturity) and the formation of larger groups when population density is high, high quality breeding habitat is not available, and the availability of mates is low (Selander

1964; Emlen 1982; Koenig et al. 1992; Komdeur 1992; Emlen 1995; Schradin and Pillay 2005;

Schradin et al. 2010). Delayed dispersal and natal philopatry results in the formation of extended family groups characterized by overlapping generations and high levels of relatedness between group members, conditions favoring cooperation by non-breeders (Hamilton 1964) and high reproductive skew (i.e., reproduction is shared unequally among group members)

(Emlen 1995).

Support for ecological constraints comes from observational studies demonstrating negative associations between habitat availability and natal philopatry or group size in birds

(Russell 2001; Carrete et al. 2006; Moreira 2006). Further support is demonstrated by positive associations between population density and philopatry mammals (Wolff 1994; Cochran and

Solomon 2000). Additionally, experimental studies have provided causal support for this hypothesis (Komdeur 1992; Walters et al. 1992; Lucia et al. 2008). For example, Seychelles warblers (Acrocephalus sechellensis) transferred to an unoccupied island remained philopatric only once all high quality territories became occupied (Komdeur 1992). Lucia et al. (2008) found 4 strong causal support for the positive relationship between population density and group formation in prairie voles (Microtus ochrogaster), where the proportion of philopatric offspring increased as population density was experimentally increased. Lastly, African striped mice

(Rhabdomys pumilio) living in experimentally manipulated low population density territories moved from social groups into vacant territories and became solitary more often than mice in control groups (Schoepf and Schradin 2012).

Natal philopatry is not universal for social species. In some species, groups form due to the movement of adults between groups (insects: Queller et al. 2000; Seppä et al. 2008; birds:

Silk et al. 2014; mammals: Kerth and Konig 1999; Connor et al. 2000; Ebensperger and Hayes

2008; Ebensperger et al. 2009). Thus, factors other than ecological constraints, including immigration and emigration, may drive the formation of groups in some species (Faulkes and

Bennett 2001; Ebensperger and Hayes 2008). As a result, kin structure will be low or absent in these populations, given that the genetic relatedness of individuals within groups will likely be similar to that of the background population (Quirici et al. 2011; Davis et al. 2016).

The ‘benefits of philopatry hypothesis’ posits that in cooperative species, the lifetime fitness benefits gained from remaining philopatric outweigh the benefits of immediate dispersal, while the opposite is true for non-cooperative species (Stacey and Ligon 1991). Non- breeders may stay as ‘helpers at the nest’ to the dominant breeding female(s) (Brown 1978) and benefit by increasing their inclusive fitness (the sum of indirect and direct fitness benefits)

(Hamilton 1964). Individuals’ direct fitness may benefit from opportunities for future reproduction (Woolfenden and Fitzpatrick 1978; Waser et al. 1994). In other words, individuals

5 will remain philopatric when the dispersal costs associated with (or during) independent breeding are greater than the costs of forgoing reproduction at the natal nest, even in the absence of habitat saturation (Stacey and Ligon 1987, 1991). For example, juvenile acorn woodpeckers (Melanerpes formicivorus) that remain in high quality natal territories, with greater access to food stores, and forgo early reproduction gain greater lifetime inclusive fitness than individuals that disperse from groups and attempt to breed in low quality territories (Stacey and Ligon 1987). Additional benefits of philopatry include future territorial inheritance (Woolfenden and Fitzpatrick 1978; Ragsdale 1999; Queller et al. 2000), improved survival in the natal territory (Emlen 1995; Kokko and Ekman 2002) or developing critical hunting skills (Bednarz and Ligon 1988). Conversely, philopatric individuals may ‘pay-to-stay’

(Kokko et al. 2002), where an individual remains and helps to avoid eviction from the group

(Bergmüller and Taborsky 2005). Dispersal occurs when the need for cooperation is reduced; in other words, when environmental conditions are more favorable for independent breeding. For example, Bergmüller et al. (2005) showed that in cooperatively breeding cichlids

(Neolamprologus pulcher), helpers dispersed and bred independently when breeding shelters were made available. After much debate (Heinsohn et al. 1990; Koenig et al. 1992; Walters et al. 1992), the ‘benefits of philopatry’ hypothesis is now accommodated under the ‘ecological constraints hypothesis’, with the distinction lying in the emphasis on the cost of leaving or the benefits of staying (Koenig et al. 1992; Mumme 1992; Emlen 1994, 1997).

The ‘life history hypothesis’ posits that longevity, reproductive and dispersal rates, rather than breeding ecology or ecological constraints, explain cooperative breeding in birds

(Arnold and Owens 1998, 1999; Hatchwell and Komdeur 2000). This hypothesis predicts that 6 cooperative breeding is associated with delayed maturity, high adult survival, and low reproductive output (Brown 1974; Rowley and Russell 1990; Poiani and Jermiin 1994; Arnold and Owens 1998). Arnold and Owens (1998) tested this hypothesis in a comparative analysis and found cooperative breeding was negatively associated with species characterized by high annual adult mortality. Furthermore, in a family-level analysis, Arnold and Owens (1998) confirmed that that cooperative breeding is more common in families with decreased annual mortality rates among breeders (i.e., high survivorship). Thus, lineages with a slow life history i.e., delayed maturity, high adult survival, and low reproductive output, may be predisposed to cooperative breeding. Contrary to this hypothesis, an analysis of life history traits in cooperative and non-cooperative bird species failed to confirm differences in reproductive output or longevity in the Australian Corvidae (Poiani and Jermiin 1994). Furthermore, Lukas and Clutton-

Brock (2012) did not find support for effects of longevity or other life-history parameters on cooperative breeding in mammals, but rather suggest that cooperative breeding is restricted to monogamous lineages where helpers can increase reproductive output of breeders.

Costs and benefits of group-living and cooperation

The costs and benefits of social group living can be thought of in terms of group size effects (i.e., the costs and benefits experienced from simply living among other individuals), or in terms of cooperation (i.e., interactions of individuals acting together for a common or mutual benefit) (Alexander 1974; Krause and Ruxton 2002). Social theory predicts that social group-living should persist if individuals living together gain greater net benefits compared to individuals living alone (Alexander 1974; Krause and Ruxton 2002). A positive benefit:cost ratio 7 should result in greater fitness, which is a function of survival and lifetime reproductive success

(e.g., number of offspring surviving in a lifetime). Thus, natural selection will favor living in groups and cooperation among group members when these social strategies confer greater lifetime fitness to those individuals than others engaged in different strategies.

Arguably, natural selection favors living with close relatives. Delayed or limited dispersal promotes cooperation when clusters of related individuals are formed (Hamilton 1964; Emlen

1995). Ultimately, individuals in groups of kin cooperate to enhance their inclusive fitness

(Hamilton 1964). Hamilton’s rule states that an individual will provide care when the relatedness of the helper to the recipient (coefficient of relatedness, r), multiplied by the benefit of the care to the recipient (B), is greater than the cost (C) to the helper (rB>C;

(Hamilton 1964). Hamilton (1964) predicted that selection will favor strategies to maximize inclusive fitness (kin selection: Hamilton 1964; Smith 1964) which allows for the formation and maintenance of kin groups. Support for Hamilton’s rule comes from studies of invertebrates

(Trivers 1971; Field et al. 2006), birds (Brown 2014; Green et al. 2016) and mammals (Sherman

1981; Solomon 2003; Kappeler 2008). In the last 15 years, the role of kin selection as the ultimate driver of cooperation in social groups has been questioned (Griffin and West 2002;

Wilson 2005; Nowak et al. 2010). Griffin and West (2002) argue that theoretical and empirical studies of Hamilton’s rule disregard competition between relatives, which will underestimate the trade-offs of cooperation. Furthermore, understanding the adaptive significance of cooperation in social groups becomes more complex when considering species that participate in cooperative behaviors (e.g., communal care, allonursing) yet exhibit low kin structure within social groups (e.g., mammals: Quirici et al. 2011; Davis et al. 2016; insects: Queller et al. 2000). 8

Even in the absence of high kin structure, social group-living confers numerous direct benefits from group size effects (Krause and Ruxton 2002). For example, individuals living in a group may experience decreased predation risk in three ways. First, there is a dilution of predation risk simply because any one individual is less likely to be attacked when they are among other individuals than when they are alone, and the probability of depredation relative to other individuals in the group decreases further in a larger group (Williams 1966; Roberts

1996).The dilution of predation risk hypothesis predicts negative relationships between per capita rate of attack and group size as well as the per capita rate of mortality and group size. A non-mutually exclusive hypothesis is that individuals in groups are more likely to detect predators in large groups due to increased vigilance (‘many eyes hypothesis’; Powell 1974; Lima

1995; Uetz et al. 2002). This hypothesis predicts that total vigilance increases and per capita attack rates or mortality decrease with increasing group size. Evidence to support this hypothesis comes mainly from studies of birds and herbivorous mammals (Lima 1995; Caro

2005). Third, as proposed by Hamilton (1971), the ‘selfish herd’ hypothesis posits that individuals form large aggregations to reduce their own predation risk, with individuals located centrally within a group or herd experiencing the least risk. In this case, competition for access to safe places within a group is intense. Evidence to support this hypothesis comes from observations of insects, fish and mammals (Couzin and Krause 2003). For example, King et al.

(2012) showed that sheep appear to consider the position of multiple neighbors in the flock to move themselves toward to an approximate center upon the approach of a predator.

Social group-living can enhance access to critical resources, such as food. When members share information with other individuals, the group benefits from the increased likelihood of locating quality resources (Ward and Zahavi 1973; Wrangham 1980; Rubenstein and Wrangham 1986). Additionally, larger groups may be more successful at defending territories for access to food resources than smaller groups (‘resource defense hypothesis’;

Wrangham 1980; Slobodchikoff 1984; Ostfeld 1985, 1990; Miller 1996; Wilkinson and

Boughman 1998; Dechmann et al. 2009). Female greater spear-nosed bats (Phyllostomus hastatus) exhibited higher rates of calling and increased group foraging during seasons when food resources are more concentrated and more limited, and thus inter-group competition is greater (Wilkinson and Boughman 1998). Wedge-capped capuchins (Cebus olivaceus) living in larger groups benefitted from a consistent daily level of food intake and smaller groups suffered from variation in food intake between the wet and dry seasons (Miller 1996). Predators such as spotted hyena (Crocuta crocuta) and lions (Panthera leo) experience similar benefits, capturing larger prey when hunting in a group versus solitarily (Kruuk 1972; Stander 1992).

Group members may also benefit from cooperative behaviors including communal rearing (Clutton-Brock et al. 2001) , alloparental care (Bădescu et al. 2016) , cooperative defense of offspring against infanticide (see Ebensperger 1998 for a review), allogrooming

(Henazi and Barrett 1999), social thermoregulation (Arnold 1993), and cooperative hunting

(Kruuk 1972; Macdonald 1983). These cooperative behaviors reduce the individual’s cost, in terms of time or physiology, allowing more energy to be allocated to reproduction, often resulting in fitness benefits. For example, social thermoregulation, or huddling, increases nest

10 or microhabitat temperature (Glaser and Lustick 1975), lowers metabolic rates (Andrews and

Belknap 1986), and reduces the amount of food cold-stressed individuals require to maintain a high body temperature (Andrews and Belknap 1986). Thus, huddling may allow for individuals to allocate more energy to reproduction, rather than to foraging or in temperature regulation.

Finally, in subterranean, semi-fossorial species or cavity-dwelling species, groups of individuals may cooperate to build and maintain underground burrows or cavities used as places to rear offspring or escape predators (Kinlaw 1999; Ebensperger and Bozinovic 2000b; Ebensperger and Bozinovic 2000a; Ebensperger and Blumstein 2006). Benefits of cooperation differ from group-size effects in that cooperating individuals share responsibilities and resources, and may be independent of social group size.

On the other hand, individuals will incur costs of group-living, including greater exposure to parasites and disease (Alexander 1974; Hoogland 1979; Møller et al. 1993; Côté and Poulinb

1995; Roulin and Heeb 1999), increased infanticide (Van Schaik and Janson 2000), increased conspicuousness to predators (Eiserer 1984; Reichard 1998) and intraspecific competition for resources and mates (Pride 2005). Although individuals living with close relatives may be at risk of inbreeding, mechanisms such as sex-biased dispersal and reproductive suppression that reduce this cost have evolved (Wolff 1992). The costs of group-living and cooperation are not always shared equally among group members. For example, group augmentation may be costly to current members, yet still provide benefits to new members (Sibly 1983). Thus, while optimal group sizes exist (i.e., the benefits exceed the costs; Krause and Ruxton 2002), groups will often increase beyond the optimal size and the costs will vary for group members.

Unequal costs and benefits can lead to reproductive skew, where reproduction is shared unequally among group members. An extensive review of reproductive skew theory is beyond the scope of my thesis and not the focus of my thesis research. Briefly, reproductive skew theory states that within social groups, reproduction is partitioned between dominant breeders and subordinates (Emlen 1982; Keller and Reeve 1994). Animal societies exhibiting high skew will have only one female that breeds, such as in wild dogs (Lycaon pictus; Creel and Creel

2002), meerkats (Suricata suricatta; Griffin et al. 2003; Hodge et al. 2008), naked mole rats

(Heterocephalus glaber; Faulkes and Abbott 1997), long-tailed tits (Aegithalos caudatus;

Hatchwell et al. 2001), and white-winged choughs (Corcorax melanorhamphos; Heinsohn 1992).

Societies exhibiting low reproductive skew have greater equality of reproduction among group members and include species such as in African lions (Panthera leo; Packer et al. 2001),

European rabbits (Oryctolagus cuniculus; Cowan 1987), and Mexican Jays (Aphelocoma wollweberi; Brown et al. 1997). In high skew societies, the dominant breeder may allow subordinates to breed to keep them in the group if staying will increase the dominant’s inclusive fitness (Emlen 1995). In this way, reproductive skew can shape social organization and social structure. High skew societies are expected to exhibit more dominance interactions (a component of social structure) compared to low skew societies (Keller and Reeve 1994).

Following the predictions of reproductive skew theory, in a study of two populations of pukeko

(Porphyrio porphyrio), Jamieson (1997) found that the population under stronger ecological constraints (e.g., habitat saturation), and characterized by greater genetic relatedness between co-breeders, exhibited higher skew.

Direct fitness consequences of social group-living

Single-population studies of mammals (König 1994; Manning et al. 1995; Packer et al.

2001; Gerlach and Bartmann 2002; McGuire et al. 2002), birds (Canestrari et al. 2008), fish

(Balshine et al. 2001) and insects (Wilson 1971) have demonstrated that the direct fitness consequences of social group-living vary considerably between taxa. Some species show greater reproductive benefits with increasing group size (Cant 2000; Packer et al. 2001;

Canestrari et al. 2008) while others show the opposite trend (Hoogland 1995; van Noordwijk and van Schaik 1999; Treves 2001; Hayes et al. 2009) or a neutral relationship (Van Vuren and

Armitage 1994; Mann et al. 2000; Randall et al. 2005; Robbins et al. 2007). Previous studies show between-population differences in group size and composition (Schradin and Pillay 2004;

Isvaran 2007; Ebensperger et al. 2012b; Schradin 2013; Marino and Baldi 2014), but without a measure of fitness benefits, these results cannot contribute to our understanding of the evolutionary significance of social group-living. Inter-population studies of social organization

(group size), social structure (including cooperation), and reproductive success are needed to understand the reproductive consequences of social group-living. Furthermore, given the inter- related nature of social systems, we need to determine the reproductive consequences of both social organization and social structure (Kappeler and van Schaik 2002; Wey et al. 2008). We can accomplish this by comparing the frequency, type, or intensity of social interactions, coupled with estimates of reproductive success of those interactions across groups or populations.

Challenges

Critically, the evolutionary relationships between social organization and social structure remain unclear. We still do not understand whether variation in group size and composition

(group-living) allows for specific social interactions to occur (cooperation), or if instead the social interactions shape the composition and size of social groups. In yellow-bellied marmots

(Marmota flaviventris), the number of associations decreases with increasing group size

(Maldonado-Chaparro et al. 2015), showing that there is a constraint on social structure in this species, and that it is related to social organization. Moreover, the two components have independent effects on reproductive success based on breeding strategy (Kappeler and van

Schaik 2002; Silk 2007; Ebensperger et al. 2012a). For example, the adaptive significance (i.e., enhancing individuals’ fitness; Tinbergen 1963) of social organization and social structure will differ for singular breeders (e.g., African wild dogs - Lycaon pictus, meerkats - Suricata suricatta), where one female monopolizes breeding (high reproductive skew) versus plural breeders (i.e., multiple females in the group breed, low reproductive skew) with (e.g, ground squirrels, macaques) and without (e.g., African lions - Panthera leo) communal care (Silk 2007).

Historically, the reproductive consequences of group-living and cooperation are well studied in singular breeders, especially in avian species (Stacey and Koenig 1990), but are less clear in plural breeders (Hodge et al. 2009). Singularly breeding birds exhibit positive, neutral and negative fitness benefits from increasing number of helpers at the nest (Cockburn 1998). A meta-analysis of 8 mammalian orders revealed singularly breeding mammals experience greater fitness benefits from group-living than plural breeders, although variation in fitness

14 effects are influenced by climate conditions (e.g., rainfall), and sociality-fitness relationships may be dependent on the fitness metrics used (Ebensperger et al. 2012a). Reproductive skew can also occur in plural breeders (Dugdale et al. 2008; Hayes and Ebensperger, unpublished data), but is often assumed to be low as seen in egalitarian reproduction (e.g., lions: Packer et al. 2001). Thus, it is essential to study the tradeoffs of group-living and cooperation in plurally breeding species, and particularly in previously understudied taxa (Ebensperger et al. 2012a).

Ecology and social variation

Socioecological models have implicated ecological variation as a key determinant in an individual’s decision to remain philopatric, a mechanism that promotes group-living (‘ecological constraints theory’; Emlen 1982). Spatio-temporal ecological variation in climate conditions, such as rainfall and temperature, influences the distribution of cooperatively breeding birds

(Rubenstein and Lovette 2007; Jetz and Rubenstein 2011) and mammals (Lukas and Clutton-

Brock 2017). Specifically, cooperative and communal breeding is most beneficial in unpredictable or harsh environments (Covas et al. 2008; Shen et al. 2012; Ebensperger et al.

2014a; Rubenstein 2016), though recent analyses suggest an alternative hypothesis that cooperative breeding evolved in stable environments and then allowed for colonization of harsh environments (Cornwallis et al. 2017). Long-term studies of single species have demonstrated cooperative or communal breeding is most advantageous under harsh conditions

(Magrath 2001; Covas et al. 2008; Shen et al. 2012; Ebensperger et al. 2014). In a 10+ year study of the superb starling (Lamprotornis superbus), Rubenstein (2011) found that variance in reproductive success decreases with increasing rainfall and increasing group size (used as a 15 proxy for the potential for cooperation). Rubenstein (2011) argued that cooperation reduces variance of reproductive success in years with high variation in rainfall and territory quality. This so-called form of bet hedging can explain why some individuals in communal breeders forgo direct reproduction under variable conditions. In some species, harshness based on mean ecological conditions seems to be more important. In plurally breeding Taiwan yuhinas (Yuhina brunneiceps; Shen et al. 2012) and degus (Octodon degus; Ebensperger et al. 2014), benefits of cooperation are greatest when mean environmental conditions during reproduction are most challenging. Studies of non-passerine birds (e.g., hornbills and woodpeckers) suggest the opposite trend, with cooperative breeding being the most beneficial when ecological conditions are more favorable, or less harsh (Koenig et al. 2011; Gonzalez et al. 2013).

Social structure and social network analysis

Research on animal social systems has largely focused on the quantification of group size and composition (i.e., social organization) to describe the population of a social species

(Lott 1991). However, a simple understanding of variation in social organization in a population does not account for variation in social structure, although they are inter-related (Whitehead

1997). Social structure is examined through the interactions between conspecifics, including the type, frequency or duration, and can point to dominance hierarchies, cooperation, or within- group conflict. How these interactions influence reproductive success within and between populations will reveal habitat-specific costs and benefits of social structure (i.e., cooperation).

Reproductive correlates of variation in social structure have been identified in insects

(Formica et al. 2012), lizards (Godfrey et al. 2013), birds (Ryder et al. 2008) and mammals (Wey 16 et al. 2013). Recently, long- term studies have examined how ecology influences the potential for cooperation, measured as group size (Rubenstein 2011; Ebensperger et al. 2014; Koenig and

Walters 2015; Rubenstein 2016). How temporal or spatial variation in ecology influences the reproductive consequences of varying social structure remains understudied. In order to form a relevant and applicable evaluation of a population or group’s social structure, social interactions among group members should be quantified and considered along with the traditional measurements of social group-living (e.g. group size; Ebensperger et al. 2012a;

Hayes et al. 2009). In species that are difficult to observe in the wild, including subterranean or semi-fossorial animals, other indices of social interactions are necessary.

A powerful method to index social structure this is social network analysis (Wasserman and Faust 1994; Wey et al. 2008; Scott 2012). A social network is a visual presentation of nodes

(individuals) and ties (pairs of associating individuals; Wasserman and Faust 1994; Figure 1.1).

Ties can be depicted as arrows to show direction of the interaction (e.g., grooming), or as lines when the interaction is non-directional. Ties will be weighted, shown by the width of a connecting line or arrow, to indicate the strength, or the sum of associations, between two nodes (Whitehead 2009). Social network analyses have broad applications, allowing us to understand modes of pathogen transmission, inequality of females, and reproductive success

(Croft et al. 2011 ; Klovdahl et al. 1994; Côté and Poulinb 1995; Lusseau 2003; Croft et al. 2004;

Archie et al. 2006). Critically, there is evidence that high affiliative interactions are associated with the decision to remain philopatric and cooperate in the social group (‘social cohesion hypothesis’: Bekoff 1977; Poirier et al. 1978). In other words, high social network strength can be considered a proxy for the potential for cooperation in social groups. For example, Blumstein 17

Daniel et al. (2009) suggests that yearling female yellow-bellied marmots (Marmota flaviventris) increased their social group cohesion through affiliative interactions to remain in the social group and increase their direct fitness. Using social network analysis metrics, we can explore the habitat-specific reproductive consequences of variation in social structure, and inform a more comprehensive theory of social group-living.

A (F) B (M)

C (F) D (F)

Figure 1.1 A theoretical social group. Ovals represent male (M) and female (F) group members (A-D), lines represent pairwise social associations between group members. Thicker lines represent stronger associations (i.e., high temporal and spatial overlap)

Thesis Objectives

The aim of this study was to examine how local environmental conditions influence the fitness benefits of variation in social organization (group size) and social structure (cooperation) in two populations of the common degu, Octodon degus. Degus are a social, caviomorph rodents endemic to central Chile. Degus live in social groups of 1-5 males and 1-8 females that share multiple burrow systems (a group of interconnected burrow openings; Fulk 1976) where

18 they communally rear young (Ebensperger et al. 2002; Ebensperger et al. 2004; Jesseau et al.

2009). In two populations, a high percentage of social groups consist of unrelated individuals and overall, groups lack strong kin structure (Quirici et al. 2011; Davis et al. 2016). Specifically, some groups consist of close relatives while others do not. In non-kin groups, the main component of their inclusive fitness comes from direct fitness benefits of cooperation or group size effects. In contrast, in kin groups, cooperative individuals may benefit from both direct and indirect benefits (Hamilton 1964).

In one population (Rinconada de Maipú, Chile; 33°23′S, 70°31′W, herein Rinconada), there is evidence for net costs of increasing group size in degus. The per capita number of offspring weaned (PCOW) (Hayes et al. 2009) and surviving to reproductive age (Ebensperger et al. 2011) decreases with increasing total group size and number of females, suggesting a direct fitness cost of social group-living. Subsequent analyses of long-term dataset showed that the relationship between social organization and direct fitness becomes less negative when mean annual food abundance is low (Ebensperger et al. 2014). Moreover, early studies showing negative trends did not account for the potential of habitat-specific fitness benefits of group- living and cooperation. Across their geographical range, degus live in varying environments with major differences in climate, elevation, vegetation cover, food abundance and predation risk.

There is evidence that such variation is linked to inter-population differences in social group size (Ebensperger et al. 2012b; Sobrero et al. 2016). To date, no one has determined if the group size-direct fitness relationships differ between populations. Finally, these studies relied on one metric of social organization (group size). However, we know that social network structure is variable between degu social groups (Wey et al. 2013; Davis et al. 2016) and differs 19 between populations (Davis et al. 2016). Wey et al. (2013) found that group-level social network strength was greater among females during lactation than mating in Rinconada, but found no support for their hypothesis that reproductive success increases with increasing social network strength female group members. We have yet to compare habitat-specific relationships between social structure and reproductive success.

The objective of this study was to answer three questions: (1) Does living in large groups and having strong social network strength improve access to resources in harsh environments? (2)

Does increased access to resources improve the direct fitness of group-living females? and (3)

Does living in large groups and having strong social network strength improve direct fitness of females in harsh environments? To this end, I quantified group size, social network strength, and

PCOW of social groups in two degu populations in Chile. I quantified the food abundance, burrow opening density, and soil hardness at burrow systems used by each group. My aim was to determine how (1) group size or social network strength influence access to resources (food abundance, burrow opening density) differently in each site, (2) site-specific ecological conditions

(food abundance, burrow opening density, soil hardness) influences PCOW in each site, and (3) how group size or social network strength influence PCOW in each site.

I hypothesize that degu social groups benefit from living and cooperating with others under harsh conditions, and thus predict that (1) access to resources (food abundance, burrow opening density) will increase with increasing group size and social network strength (2) PCOW will increase with increasing food and increasing burrow opening density and (3) PCOW will increase with increasing group size and social network strength. I tested these predictions across two

20 years, in two sites in north-central Chile that varied in ecology (food abundance, burrow opening density, and soil hardness).

Study sites

This study was conducted on two degu populations in geographically distinct sites in north- central Chile, Rinconada and Parque Nacional Bosque de Fray Jorge (herein, Fray Jorge: 71°40'W,

30° 38'S, altitude 200 m; see Figure 1.2). For degus, a primary predictor of spatial ecology and social behavior is predation risk (Lagos et al. 1995). In the time of our study, predator abundance was comparable between sites (Student’s two-sample t test: t(78)=-0.19, P=0.85; Figure 1.3), although burrow opening density, or the number of burrow openings per m2 at burrow systems and an index of refuge from predators, was greater at Rinconada (Student’s two-sample t test: t(29)=6.42, P<0.001; Figure 1.3). Likewise, the distribution and abundance of food differs between sites (Meserve 1981; Hayes et al. 2007; Two-way ANOVA: F1,56 = 95.51, P<0.001; Figure

1.4), possibly influencing the costs and benefits of grouping and social behavior. The abundance of grasses and green herbs (preferred foods; Meserve and Martin 1983; Meserve et al. 1984) is greater and more uniformly distributed at Rinconada, suggesting a less harsh environment than

Fray Jorge, in terms of food availability (Figure 1.4). Given these ecological differences between sites, there are likely differences in the net costs and benefits of group-living and cooperation for each population. The significance in this work also lies in the fact that this is the first study to describe ecological and social variation, as well as reproductive success, in the population at Fray

Jorge.

Figure 1.2 Geographic location of Fray Jorge (top) and Rinconada (bottom) in north-central Chile

0 . 4

R i n c o n a d a

F r a y J o r g e

0 . 3

a i

r * P < 0 . 0 5

a 0 . 2

c E 0 . 1

0 . 0 P r e d a t o r s p e r s c a n B u r r o w o p e n i n g d e n s i t y

Figure 1.3 Mean (±SE) burrow opening density at burrow systems used by social groups at Fray Jorge (n=9) and Rinconada (n=22) and mean (±SE) number of predators per scan at Fray Jorge (n=40) and Rinconada (n=40) in 2015. * P<0.05

2 0 0

2 0 1 4

) 2

2 0 1 5 m

/ b

g (

1 5 0 n

o b

e g

e 1 0 0

d n

u a

l 5 0

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0 F r a y J o r g e R i n c o n a d a

Figure 1.4 Mean (± SE) edible ground vegetation (g/m2) at burrow systems used by social groups at Rinconada (2014: n=15, 2015: n=22) and Fray Jorge (2014: n=14, 2015: n=9). No edible ground vegetation was present at Fray Jorge in 2014 due to an unusually dry winter. Different letters represent significant differences P<0.05

CHAPTER 2

HABITAT-SPECIFIC FITNESS BENEFITS OF SOCIALITY IN OCTODON DEGUS

Introduction

A central question in behavioral ecology is ‘why do animals live in groups and cooperate with conspecifics?’ (Alexander 1974; Krause and Ruxton 2002; Silk 2007; West et al. 2007; Ward and Webster 2016; Robinson and Barker 2017). Historically, researchers have quantified the costs and benefits of social group-living to answer this question. The costs and benefits of social group-living can result from group size effects (i.e., the costs and benefits experienced from simply living among other individuals), or cooperation (i.e., interactions of individuals acting together for a common or mutual benefit) (Alexander 1974; Krause and Ruxton 2002).

Beneficial group size effects include decreased predation risk by collective vigilance (‘many eyes hypothesis’; Powell 1974) or dilution (Roberts 1996) and increased access to resources

(Wrangham 1980; Ostfeld 1985, 1990). Cooperative interactions among group members, such as group-foraging (Brown 1988; Miller 1996; Wilkinson and Boughman 1998), communal care of offspring (Clutton-Brock et al. 2001; Bădescu et al. 2016), and allogrooming (Henazi and Barrett

1999) may contribute to increased survival and reproductive success (for recent reviews, see

Erb and Porter 2017; Smith et al. 2017). Individuals are expected to maintain interactions with a maximum number of group members until the costs outweigh the benefits (Sueur et al. 2011).

Costly group size effects include increased visibility to predators (Eiserer 1984; Reichard 1998) and exposure to pathogenic parasites (Hoogland, 1979; Møller et al. 1993).

If groups become too large, group-living can confer net costs to some individuals through increased within-group competition and reproductive suppression (Alexander 1974;

Krause and Ruxton 2002; Silk 2007). The extent to which group-living and cooperation is beneficial may depend on the composition of groups (Kappeler & van Schaik 2002). Whereas cooperation among non-kin can only influence direct fitness, cooperation directed to close relatives may increase both the indirect and direct components of inclusive fitness (Hamilton

1964; Emlen 1995; Balshine-Earn et al. 1998; Abbot et al. 2011). Even in kin groups, some individuals may experience fitness costs resulting from competition for resources or mates

(Pride 2005; Clutton-Brock and Huchard 2013) or infanticide (van Schaik and Janson 2000).

Recent debate has focused on how ecology shapes the evolution of group-living and cooperation (Cockburn and Russell 2011; Jetz and Rubenstein 2011; Gonzalez et al. 2013;

Ebensperger et al. 2014; Rubenstein 2016). One hypothesis is that cooperation evolved in environments characterized by ecological conditions that are unfavorable to reproduction

(Magrath 2001; Rubenstein and Lovette 2007; Covas et al. 2008; Jetz & Rubenstein 2011; Shen et al. 2012; Ebensperger et al. 2014; Rubenstein 2016; but see Gonzalez et al. 2013; Koenig et al. 2011; Cornwallis et al. 2017). Low mean or variable rainfall can reduce the availability of food or territories to rear offspring, resulting in unfavorable breeding conditions (Ebensperger et al. 2001; Magrath 2001; Ebensperger et al. 2014). Support for this hypothesis comes from comparative studies indicating that cooperative breeding, a social system in which members of a social group assist with the rearing of non-offspring, occurs in unpredictable environments 26 and most often in semi-arid habitats in passerine birds (Rubenstein & Lovette 2007; Jetz &

Rubenstein 2011) and mammals (Lukas & Clutton-Brock 2017). In contrast, a phylogenetic analysis of hornbills (Bucerotidae) revealed that cooperative breeding is positively associated with inter- and intra-annual climatic stability rather than variability (Gonzalez et al. 2013).

Empirical evidence from studies of cooperatively and communally breeding (i.e., multiple group members breed and share parenting of offspring) birds (Shen et al. 2012; Covas et al. 2008; Rubenstein 2011) and mammals (Ebensperger et al. 2014; Marshall et al. 2016a;

Marshall et al. 2016b) suggest cooperative and communal breeding is most beneficial to breeders in unpredictable or harsh environments. Rubenstein (2011, 2016) found that variation in mean monthly precipitation (an ecologically harsh condition) during the pre-breeding season influenced helping behavior in plurally breeding superb starlings (Lamprotornis superbus).

Variance in lifetime reproductive success of breeders decreased with increasing rainfall and group size (a proxy for cooperation and the number of helpers in the group), supporting the hypothesis that cooperative care is a bet hedging strategy that reduces environmentally induced variation of reproductive success. Similarly, Koenig and Walters (2015) found that in acorn woodpeckers (Melanerpes formicivorus), ‘helpers at the nest’ reduced environmentally induced variation of fecundity when food abundance (acorn crop) was low. In the cooperatively breeding sociable weaver (Philetairus socius), breeders benefit the most from help provided by non-breeders when total monthly rainfall is low (Covas et al. 2008). In banded mongooses

(Mungos mungo), males breed cooperatively, presumably due to limited breeding opportunities resulting from high female mortality under harsh conditions (Marshall et al. 2016b). The amount of care provided by male banded mongooses is positively associated with variability in 27 rainfall from the previous year (Marshall et al. 2016b), and males experiencing harsher (mean monthly rainfall) and more variable (standard deviation of monthly rainfall) ecological conditions during their first year of life have increased lifetime reproductive success (Marshall et al. 2016a).

Other studies have demonstrated that the net benefits of cooperative or communal breeding are the greatest when mean, not variability, in ecological conditions are most challenging to direct reproduction. Communally breeding Taiwan yuhinas (Yuhina brunneiceps) employ more cooperative strategies under harsh conditions (low mean rainfall), and reproductive success is higher as a result (Shen et al. 2012). In contrast, studies of non- passerine birds (Gonzalez et al. 2013; Koenig et al. 2011) and mammals (Harrington et al. 1983;

Solomon and Crist 2008) suggest the opposite trend, with group-living and cooperation yielding greater reproductive success when ecological conditions are more favorable, or less harsh.

Habitat-specific fitness consequences

To date, most studies have focused on how direct fitness is influenced by variation in group size within single populations. Not surprisingly, results vary with evidence that reproductive success increases (Packer et al. 2001; Canestrari et al. 2008b; Cant 2000) decreases (Hayes et al. 2009; Hoogland 1995; van Noordwijk and van Schaik 1999; Treves 2001;

Lacey 2004) or does not significantly covary (Hayes et al. 2009; Van Vuren and Armitage 1994;

Mann et al. 2000; Robbins et al. 2007; Randall et al. 2005) with increasing group size. These studies have demonstrated that the fitness costs and benefits of group-living and cooperation vary widely across social species. In mammals, breeding success of females increases with 28 increasing group size in singular or cooperative breeders but not plural breeders with and without communal care (Ebensperger et al. 2012a).

Most likely, there are population or habitat-specific fitness benefits and costs of social group-living and cooperation (Silk 2007). Determining how ecology shapes social evolution requires the determination of how both social organization and social structure covary with reproductive success within and between populations. There have been numerous studies on intraspecific differences in social organization and structure between populations of social vertebrates (Ebensperger et al. 2012b; Davis et al. 2016; Schradin and Pillay 2004; Schradin et al. 2013; Marino and Baldi 2014; Isvaran 2007; Sobrero et al. 2016). However, only a few studies (Treves 2001) have determined how both group size and cooperation influence reproductive success within and between populations, and they do not address the different environmental conditions that could potentially influence the relationship. We still need to examine the effect of local environmental conditions in social vertebrates to understand how group size and cooperation covary with reproductive success.

Social networks

Social organization (group size and composition) is the most common metric of social group-living. In most species, quantifying group size can be accomplished via behavioral observations, temporary trapping, and tracking of individuals to shared areas, nests, or burrows. In contrast, social structure (cooperative and competitive interactions) can be difficult to quantify when social interactions are cryptic, such as in species that rear offspring in cavities or underground burrows. Social network analyses can be used to model the extent of social 29 interactions between individuals in a group or population (Whitehead 2009; Wey et al. 2008;

Sih et al. 2009; Farine and Whitehead 2015). In semi-fossorial species (i.e., those that spend some amount of their lives underground), trapping history at burrow entrances can account for spatial and temporal overlap at shared burrow systems, providing information necessary for indices of associations among group members. With this information, we can use social network analyses to calculate association metrics that index the extent of social interaction and potential for cooperation among group members (Maldonado-Chaparro et al. 2015; Blumstein et al. 2009; Whitehead 2009). One such metric is strength, or how connected an individual is to others both spatially and temporally (Whitehead 2009). Strength can be more important indicator of sociality than the number of associations in a group (group size) (Silk et al. 2003;

Silk et al. 2009; Frère et al. 2010; Silk et al. 2010; Barocas et al. 2011; Stanton and Mann 2012) and can serve as a proxy for the potential for cooperation between group members (Blumstein et al. 2009).

Previous studies demonstrated that higher indices of group member strength (e.g, greater time spent grooming and in close proximity to adult group members) enhance adult female survival, reproductive success, and offspring survival in social mammals (Silk et al. 2003;

Silk et al. 2010; Silk et al. 2009; Cameron et al. 2009; Barocas et al. 2011; Frère et al. 2010). For example, in a long-term study of rock hyrax (Procavia capensis), a plurally breeding mammal with communal care, Barocas et al. (2011) found that adult longevity (age at death) was negatively associated with variance in group strength centrality (a metric of social interaction;

Wey et al. 2008). Individuals in more egalitarian social groups (i.e., a more homogenous distribution of centrality across the social network) lived longer, even after accounting for 30 group size in statistical analyses (Barocas et al. 2011). Offspring of female baboons (Papio cynocephalus spp.) with greater proportions of time spent grooming, being groomed, or in close proximity to other adults, had higher survival rates than offspring of females with fewer or weaker associations (Silk et al. 2003; Silk et al. 2009). Following previous work, my study incorporates social network strength with traditional measurements of group size in two populations to generate important insights into how social local ecological conditions influence the direct fitness consequences of variation in social organization and social structure.

Study organism and objectives

The common degu (Octodon degus) is a social, caviomorph rodent endemic to central

Chile. Degus live in social groups of 1-5 males and 1-8 females that share multiple burrow systems (a group of interconnected burrow openings; Fulk 1976; Hayes et al. 2009) in which adults communally rear young (Ebensperger et al. 2002; Ebensperger et al. 2004; Jesseau et al.

2009; Hayes et al. 2009). Across their geographical range, degus live in environments characterized by differences in climate (e.g., annual rainfall, temperature), elevation, vegetation cover, food abundance and predation risk (Ebensperger et al. 2012b; Davis et al.

2016). Previously, we have observed differences in social organization (Ebensperger et al.

2012b; Sobrero et al. 2016) and social network structure of groups (Davis et al. 2016) within different degu populations.

The aim of this study was to determine if the fitness benefits and costs of social group- living are determined by the harshness of the environment, requiring comparisons within and

31 between populations experiencing different ecological conditions. To this end, I determined if the per capita access to resources and offspring weaned of females depended on group size and social network strength of group members in two degu populations, Estación Experimental

Rinconada de Maipú (33°23′S, 70°31′W; hereafter Rinconada) and Parque Nacional Bosque Fray

Jorge (30° 38'S, 71°40'W; hereafter Fray Jorge). Preliminary observations suggest that several ecological conditions in Fray Jorge are harsher than Rinconada. Burrow systems at Fray Jorge have fewer burrow openings per m2 at burrow systems (places to rear young, escape predators;

Chapter 1, Fig. 1.3) and less edible vegetation nearby (Chapter 1, Fig. 1.4). Soils are softer at

Fray Jorge than Rinconada, conditions that may make it difficult to maintain burrow integrity

(Davis et al. 2016). I asked the following questions.

Question 1: Does living in large groups and having strong network strength improve access to resources in harsh environments?

I expected that females in larger groups and groups with higher network strength (potential for cooperation) have access to more food and more burrow openings per burrow system area

(burrow openings/m2; hereafter, burrow opening density) and that this relationship would be more positive in Fray Jorge than Rinconada. If living in groups and cooperating are most beneficial when conditions are most harsh then I expected (i) that independent of group size and social network strength, per capita offspring weaned (PCOW) is greater in Fray Jorge than

Rinconada and (ii) that there are larger groups and greater social network strength in Fray Jorge than Rinconada.

Question 2: Does increased access to resources improve the direct fitness of group-living females?

Independent of group size, I expected that PCOW is greater among females in groups living in burrow systems with more food and greater burrow opening density. Soil hardness may also influence reproductive success if digging burrow openings in hard soils or maintaining burrow systems in soft soils is costly. Thus, I also determined if there was a correlation between PCOW and soil hardness (not a resource gained by groups) at burrow systems.

Question 3: Does living in large groups and having strong network strength improve direct fitness of females in harsh environments?

I expected that living in large groups and having high social network strength predicts greater fitness benefits (PCOW) in the harshest environments. In Rinconada, PCOW increases with increasing group size when food abundance at burrow systems used by groups is low; the opposite trend occurs when food abundance at burrow systems used by groups is high

(Ebensperger et al. 2014). A recent analysis of a 9-year dataset on degus at Rinconada suggests a fitness cost (lower PCOW) to increasing social network strength, regardless of ecological conditions at burrow systems (Carroll et al. Submitted 2017). To date, we have not determined if social organization-direct fitness and social structure-direct fitness relationships observed in

Rinconada (Ebensperger et al. 2014; Wey et al. 2013; Carroll et al. Submitted 2017) are similar in other populations. If Rinconada is considered a less harsh environment, then I expected that the relationship between PCOW and group size and social network strength will be more negative in Rinconada than Fray Jorge (the harsher environment).

Methods

Study populations

This study was conducted concurrently at Fray Jorge and Rinconada in 2014 and 2015.

The sites are characterized by differences in annual rainfall, edible ground vegetation and shrub cover (Chapter 1, Fig. 1.4). Fray Jorge is a semi-arid site approximately 400 km northwest of

Santiago with a mean annual rainfall of 133 mm Gutierrez et al. 2010 and strong inter-annual variation in rainfall due to ENSO events (Jaksic et al. 1997; Meserve et al. 2003; Previtali et al.

2009; Armas et al. 2016). Fray Jorge is a predominately cactus and shrubland plant community interspersed with herbaceous ground cover and bare, sandy areas. Rinconada is a semi-arid site approximately 30 km west of Santiago with a mean annual rainfall of 236 mm Bauer et al.

2013). The landscape at Rinconada is a mix of open savanna with limited shrub cover and uniformly distributed herbs and forbs, a primary food source for degus (Meserve and Martin

1983; Quirici et al. 2010). During each field season, two teams conducted concurrent studies with coordinated methods at each site, accounting for the site-specific timing of degu breeding.

I led the field work at Fray Jorge, and collaborators under the supervision of Dr. Luis

Ebensperger (Pontificia Universidad Católica de Chile) led the field work at Rinconada.

Bioethics: The care and use of animals followed all applicable international, national and institutional guidelines, including those of American Society of Mammalogists (Sikes 2016). The study was approved by the UTC Institutional Animal Use and Care Committee (IACUC permit no.

0507LH-02 to Dr. Loren Hayes).

Social group identification

Social group membership was determined during the austral winter-spring (August-

November) 2014 and 2015, the time of year when degus are pregnant and lactating. Groups occupy multiple burrow systems (i.e., the area encompassing multiple burrow openings in which degus overlap during the night-time). Therefore, the main criterion used to assign degus to social groups was the sharing of burrow systems (Ebensperger et al. 2004; 2014; Hayes et al.

2009). Social group determination required a combination of live-trapping at burrow systems during the early morning hours and night-time or early morning radio-tracking of adults to burrow systems.

Between early September and early November, burrow systems were trapped for 59 days in 2014 and 68 days in 2015 at Rinconada, and for 58 days in 2014 and 62 days in 2015 at

Fray Jorge. Tomahawk live-traps (model 201, Tomahawk Live Trap Company, Tomahawk,

Wisconsin, USA) were set in the early morning before sunrise (06:00-07:00) to live-capture animals as they were leaving their burrow systems to forage. The traps were left open for 1.5 hours after which we recorded the location, identity, sex, body mass of all individuals, and the reproductive condition of females (perforated, pregnant, or lactating). Each degu was identified with unique ear tags (Monel 1005-1, National Band and Tag Co., Newport, KY) on each ear at first capture.

Night-time telemetry was used to track individuals to burrow systems shared with other group members. Adults weighing more than 110 g were fitted with 5 g radiocollars (BD-2C;

Holohil Systems Limited, Carp, Ontario, Canada) and individuals weighing more than 150g were 35 fitted with 7g radiocollars (PD-2C; Holohil Systems Limited, Carp, Ontario, Canada) with unique frequencies. During September and October at Rinconada, and October and November in Fray

Jorge, radio-collared degus were tracked to their burrow system once per night approximately

1 hour before sunrise or 1 hour after sunset using an FM-100 receiver (for transmitters tuned to

164.00-164.999 MHz frequency; Advanced Telemetry Systems, Isanti, MN, U.S.A.) and a hand- held three element Yagi antenna (AVM instrument Co., or Advanced Telemetry Systems).

Previous work confirmed that degus do not move between burrow systems during the night- time (Ebensperger et al. 2004). We tracked radiocollared degus for 22.4 ± 1.0 (mean ± SE) nights and 20.9 ± 0.6 nights at Rinconada in 2014 and 2015, respectively. We tracked degus for

18 ± 00 nights and 20.2 ± 1.5 nights at Fray Jorge in 2014 and 2015, respectively.

For both trapping and telemetry data, I calculated pairwise “simple ratio” association indices. The association (overlap) between any two individuals was quantified by dividing the number of days or evenings that these individuals were captured at or tracked to the same burrow system by the number of days or evenings that both individuals were trapped or tracked on the same day (Ebensperger et al. 2004). To calculate social group membership, I conducted a hierarchical cluster analysis of the burrow trapping and night telemetry association matrices in SOCPROG 2.5 software (Whitehead 2008). Only individuals trapped 4 or more days were included in the analysis. Only groups with an average association greater than 0.1 (i.e.

10% overlap of trapping/telemetry locations) in the SOCPROG cluster analysis were considered in assigning social groups. We confirmed the correlation between association and the level of clustering in the dendrogram output with the cophenetic correlation coefficient (Whitehead

2009). Under this analysis, values about 0.8 indicate effective data representation. We selected 36 the maximum modularity criteria Newman 2006 in SOCPROG to cut off the dendrogram and define social groups.

Social network analysis

Social structure can be described using metrics of social network analysis. I used

‘strength’, or the sum of associations (Whitehead 2008), indicating how connected an individual is to others in a social group. For this metric, aIJ is the association index between individuals I and J and includes both the number of associates and the intensity of associations (Whitehead

2008). Thus, high strength results from strong associations, many associations, or a combination of the two.

Using SOCPROG 2.5. software (Whitehead 2009), I calculated the mean ‘strength’ for all adults or adult females only within each group (i.e., within-group strength) from pairwise association matrices based on trapping data and including only individuals assigned to that group. Individuals captured fewer than 5 times were excluded from these analyses (Wey et al.

2013). Social network strength indicates temporal and spatial overlap of group members, and is an indicator of cooperation within groups (Wey et al. 2013; Blumstein et al. 2009). Groups with high strength will have many associations and/or strong associations between group members

(Wey et al. 2013). Social network strength is an important measurement of social structure 37

(potential for cooperation; Croft et al. 2004, 2006) because direct fitness is measured at the group level (per capita offspring weaned per group), where parental care is shared by group members (e.g., communal nursing), and maternity analyses are not conducted.

Ecological sampling

We quantified the abundance of preferred foods (ground vegetation: herbs, forbs;

Meserve et al. 1983) at burrow systems by placing a 250mm x 250mm quadrat on the ground at

3m and 9m from a burrow system in one of the cardinal directions, randomly selected for each distance at each burrow system. All green herbs in the quadrant were removed and immediately stored in 2-kg paper bags. We oven-dried each sample at 60°C for 72 hours to determine its dry biomass. We averaged the sampling points from 3m and 9m and standardized to gram per square meter. The majority of burrow systems at Fray Jorge are covered by a shrub, and I observed degus eating leaves in the shrubs at burrow systems in 2014. Given the lack of green ground vegetation at Fray Jorge in 2014, I counted the number of branches with green leaves at approximately mid-height of shrubs that covered each burrow system. Burrow opening density (openings per square meter) is an indicator of predation risk (i.e. refuges from predators) and places to rear offspring. We counted the number of burrow openings within a

9m radius from the center of a burrow system. Soil hardness was sampled at 3m and 9m from each burrow system at a randomly selected direction (Hayes et al. 2009; Ebensperger et al.

2012b; Davis et al. 2016). We used a hand-held soil compaction meter (Lang Penetrometer Inc.,

Gulf Shores, AL) and transformed the units to kPa for analyses. An individual’s ecological values

38 were weighted based on the number of captures at burrow systems. Mean values per group were calculated by averaging the weighted ecological values of all group members.

Fitness estimates

During both years of study, the number of offspring weaned by social groups (an indicator the number of weaned offspring from communal litters) was determined by quantifying the number of offspring captured for the first time at active burrow systems used by a social group between September and November (Hayes et al. 2009). Subsequently, PCOW was determined by dividing the number of offspring captured at burrow systems by the number of adult female group members known to live in the group that used these same burrow systems (Ebensperger et al. 2014). This index has been an accurate measure of direct fitness in previous studies on degus (Hayes et al. 2009; Ebensperger et al. 2011). Trapping ended when less than 5% of captured offspring were new individuals.

Statistical analysis

Statistical analyses were conducted using SPSS 24 (Chicago, IL, U.S.A). For all analyses, I set the alpha level to P= 0.05. Throughout my thesis, I report site- and year-specific means ±SE.

Hypothesis Tests About Means

Analysis of variance (ANOVA) and two-sample t tests were used to test hypotheses about the effects of fixed-effects factors (independent variable) on mean responses of social variables, ecological variables and reproductive success (dependent variable). Two-way 39

ANOVAs were used for two-factor analyses, one-way ANOVAs and Tukey’s multiple comparison tests for single-factor analyses with three or more factor levels, and Student’s two-sample t tests for single-factor analyses with two levels. I verified the assumptions of normal distribution and homogeneity of variance with the use of Shapiro-Wilks and Levene’s tests, respectively. When the assumption of normality was violated, variables were square-root transformed; this either corrected or improved conditions of skewed distributions and/or heteroscedasticity.

Hypothesis Tests About Regression Relationships

Simple linear regression was used to test hypotheses about relationships between two measurement variables (social, ecological, and reproductive success metrics). To test the assumption that the regression models were linear, I visually inspected a plot of standardized residuals. To test for homoscedasticity, I visually inspected the data point spread showing the regression standardized residual vs. the regression standardized predicted value.

Question 1

Most degu social groups break up year to year, thus, social groups determined at each site each year were entered as replicates (Ebensperger et al. 2009; Ebensperger et al. 2012b).

To determine if social organization and social network strength varied between years and sites,

I used separate two-way ANOVAs with year and study site as fixed factors and one of three social group metrics (total group size, number of females per group, number of males per group) and social network strength as response variables. I used the same approach to examine site and annual (year of study) variation in ecological conditions (food abundance, burrow 40 opening density, soil hardness). I used a Student’s two-sample t test to compare PCOW at

Rinconada and Fray Jorge in 2015. In 2014 this was comparison was not possible because females did not produce offspring in Fray Jorge in 2014.

To evaluate the relationship between group size and social network strength and access to resources within both populations, I conducted simple linear regressions between each sociality metric (total group size, female group size, social network strength) as the independent variable and each weighted (based on proportion of captures at burrow systems) ecological variable as the dependent variable (food abundance, burrow opening density). The replicate (social group) to predictor ratio in my study was very low (range 3-7.3) and not suitable for multiple regression (Miller and Kunce 1973), justifying separate simple linear regressions.

Question 2

I used the same approach to evaluate the relationship between access to resources and

PCOW within both populations; I conducted simple linear regressions between weighted ecological variables as the independent variable and PCOW as the dependent variable.

Question 3

To evaluate the relationship between group size and social network strength and PCOW within both populations, I conducted simple linear regressions with sociality measurements as the independent variable and PCOW as the dependent variable.

Results

Table 2.1 Descriptive statistics for degu social groups and ecological variables at Rinconada and Fray Jorge in 2014 and 2015 Variable Rinconada Rinconada Fray Jorge Fray Jorge 2014 2015 2014 2015

Number of social groups 15 22 14 9 Adult females per group 2.0±0.28 2.0±0.23 2.14±0.28 1.3±0.17 Adult males per group 0.9±0.18 1.0±0.20 1.0±0.28 0.6±0.18 Total adults per group 2.9±0.33 3.0±0.30 3.1±0.38 1.9±0.31 Social network strength 1.86±0.27 1.55±0.18 1.28±0.22 0.86±0.17 Per capita offspring weaned 5.2±3.12 4.1±2.34 - 6.6±2.54 Edible ground vegetation 140.35±10 115.66±9.86 - 53.49±12.78 (g/m2) .89 Leaf abundance (# branches - - 10.61±3.10 4.75±0.91 with green leaves/shrub) Burrow opening density 0.14±0.02 0.18±0.02 0.05±0.01 0.07±0.01 (#/m2) Soil hardness (kPa) 2894±20 2709± 51 2076±75 1309±73

Descriptive statistics

In 2014, we monitored 85 and 65 adult degus at Rinconada and Fray Jorge, respectively.

In 2015, we monitored 94 and 18 adults at Rinconada and Fray Jorge, respectively. We identified a total of 15 and 14 social groups in 2014 at Rinconada and Fray Jorge, respectively

(Table 2.1). We identified 22 and 9 social groups in 2015 at Rinconada and Fray Jorge, respectively. Total group sizes in Rinconada ranged from 1 to 5 (2.9± 0.33) and 1 to 5 (3.0±0.30)

42 adults in 2014 and 2015, respectively. Total group sizes in Fray Jorge ranged from 2 to 6

(3.1±0.4) and 1 to 3 (1.9±0.3) in 2014 and 2015, respectively.

The mean number of adults per group did not significantly differ between sites (two-

2 2 way ANOVA: F1,56 = 1.88, P=0.175,  =0.033) and years (F1,56 = 2.299, P=0.135,  =0.039). There

2 was a marginally significant site*year interaction (F1,56 = 3.811, P=0.056,  =0.064). The mean number of adult females per group did not differ significantly between sites (F1,56= 1.206,

2 2 P=0.28,  =0.021) and years (F1,56 = 1.649, P=0.20,  =0.029) and there was not a statistically

2 significant site*year interaction (F1,56= 2.588, P=0.113,  =0.044). The mean number of adult

2 males per group did not differ significantly between sites (F1,56 = 0.659, P= 0.42,  =0.012) and

2 years (F1,56= 0.659, P= 0.42,  =0.012) and there was not a statistically significant site*year

2 interaction (F1,56= 1.206, P=0.28,  =0.021).

The mean (SE) social network strength per group at Rinconada was 1.86±0.27 and 1.55±

0.18 in 2014 and 2015, respectively (Table 2.1). The mean (SE) social network strength per group at Fray Jorge was 1.28±0.22 and 0.864±0.17 in 2014 and 2015, respectively. Mean social network strength was statistically greater at Rinconada than Fray Jorge (two-way ANOVA: F1,42 =

6.139, P=0.017, 2=0.128; Table 2.1). Mean social network strength did not differ significantly

2 between years (F1,42= 2.074, P=0.157,  =0.047) and there was not a statistically significant

2 site*year interaction (F1,42 =0.027, P=0.836,  = 0.001).

Question 1: Does living in large groups and having strong network strength improve access to resources in harsh environments?

Rinconada

In 2014, there was not a statistically significant relationship between abundance of

2 edible ground vegetation and total group size (r =0.006, F1,13=0.08, P=0.78), female group size

2 2 (r =0.004, F1,13=0.05, P=0.83), or square root transformed social network strength (r =0.086,

F1,11=1.04, P=0.33). There was not a statistically significant relationship between soil hardness

2 2 and total group size (r =0.123, F1,13=1.83, P=0.20) or female group size (r =0.118, F1,13=1.75,

P=0.21). There was not a statistically significant relationship between square root transformed

2 burrow opening density and total group size (r =0.003, F1,13=0.04, P=0.85), female group size

2 2 (r <0.001, F1,13=0.003, P=0.956), or square root transformed social network strength (r =0.252,

F1,11=0.75, P=0.41).

In 2015, there was not a statistically significant relationship between abundance of

2 edible ground vegetation and total group size (r =0.016, F1,20=0.33, P=0.57), female group size

2 2 (r =0.008, F1,20=0.15, P=0.70), or square root transformed social network strength (r =0.001,

F1,13=0.33, P=0.91). There was no relationship between soil hardness and total group size

2 2 (r =0.65, F1,20=1.386, P=0.25), female group size (r =0.011, F1,20=0.23, P=0.64) or square root

2 transformed social network strength (r =0.067, F1,13=0.932, P=0.35). There was not a statistically significant relationship between square root transformed burrow opening density

2 2 and total group size (r =0.021, F1,20=0.44, P=0.52), female group size (r =0.081, F1,20=1.77,

2 P=0.19), or square root transformed social network strength (r =0.101, F1,13=1.46, P=0.25).

Fray Jorge

In 2014, there was a positive, statistically significant, cubic relationship between square

2 root transformed shrub leaf abundance and social network strength (r =0.67, F1,12=6.20, P=0.01,

Fig. 2.1). There was not a statistically significant relationship between square root transformed

2 shrub leaf abundance and total group size (r =0.197, F1,12=2.95, P=0.11). There was not a statistically significant relationship between square root transformed shrub leaf abundance and

2 female group size (r =0.047, F1,12=0.593, P=0.46). There was not a statistically significant

2 relationship between soil hardness and total group size (r =0.01, F1,12=0.13, P=0.72), female

2 2 group size (r =0.006, F1,12=0.08, P=0.78), or social network strength (r =0.012, F1,11=0.14,

P=0.72). There was not a statistically significant relationship between burrow opening density

2 2 and total group size (r =0.012, F1,12=0.15, P=0.71), female group size (r =0.023, F1,12=0.28,

2 P=0.61), or social network strength (r =0.012, F1,11=0.14, P=0.72).

)

e 4

d n

u 3

a e

l 2

u 2

r r = 0 . 6 7

h s

( 1 P = 0 . 0 1

o n = 1 3

e 0

r a

u 0 1 2 3 q

S S o c i a l n e t w o r k s t r e n g t h

Figure 2.1 Scatterplot showing the statistically significant relationship between mean social network strength and shrub leaf abundance at Fray Jorge in 2014. Data points represent social groups

In 2015, there was a statistically significant positive relationship between edible ground

2 vegetation and social network strength (r =0.791, F1,3=11.38 P=0.043, Fig. 2.2a). This

2 relationship became non-significant when an outlier was removed (r =0.117, F1,2=0.265,

P=0.658; Fig. 2.2b). Mean shrub leaf abundance was marginally greater in groups with one female (12.4±3.6) than groups with two females (2.7±2.7) (Student’s t test: t(7)=2.07, P=0.08,

Fig. 2.3). Edible ground vegetation did not differ between groups of one (42.9 ± 10.9), two (47.7

± 18.9) or three (71.5 ± 36.8) adults (F2,6=0.43, P=0.67), or between groups of one (45.1 ± 8.7), or two (67.7 ± 34.9) females (t(7)=-0.86, P=0.42). Soil hardness did not differ between groups with one (1361.9 ± 130.9), two (1392.2±65.9), or three (1183.1 ± 72.6) adults (F2,6=0.71, P=0.53) or between groups with one female (1372 ± 85) or two females (1183 ± 124) (Student’s t test: 46 t(7)=1.27, P=0.24). There was not a statistically significant relationship between soil hardness

2 and social network strength (r =0.002, F1,3=0.01, P=0.94). Burrow opening density did not differ between groups with one (0.08±0.01), two (0.08±0.03), or three (0.05 ± 0.01) adults (one-way

ANOVA, F2,6=0.72, P=0.52), or between groups of one (0.08±0.01) or two (0.05 ±0.01) females

(t(7)=1.34, P=0.22). There was not a statistically significant relationship between burrow

opening density and social network strength (r =.103, F1,3=0.35, P=0.60). )

2 1 5 0

m 2

/ r = 0 . 7 9

g (

P = 0 . 0 4

n o

i n = 5 t

a 1 0 0

d n

u 5 0

i d

E 0 0 . 0 0 . 5 1 . 0 1 . 5

S o c i a l n e t w o r k s t r e n g t h

Figure 2.2a Scatterplot showing the statistically significant relationship between mean social network strength and edible ground vegetation at Fray Jorge in 2015 including an outlier data point. Data points represent social groups

)

2 m

/ 8 0

g 2 (

r = 0 . 1 1 n

o P = 0 . 6 6 i

t 6 0

a n = 4

e g

e 4 0

n u

o 2 0

l b

i 0 d

E 0 . 5 0 . 6 0 . 7 0 . 8 0 . 9 1 . 0

S o c i a l n e t w o r k s t r e n g t h

Figure 2.2b Scatterplot showing the relationship between mean social network strength and edible ground vegetation at Fray Jorge in 2015 excluding an outlier data point. Data points represent social groups

2 5

P = 0 . 0 8 e

c 2 0

d n

u 1 5

a e

l 1 0

n = 6

u r

h 5 S

n = 3 0

1 2

F e m a l e g r o u p s i z e

Figure 2.3 Female group size and mean (±SE) shrub leaf abundance at Fray Jorge in 2015

Per capita offspring weaned

At Fray Jorge, adult females showed no signs of pregnancy and did not produce viable offspring in 2014. Independent of group size, social network strength, and ecological conditions, the mean per capita number of offspring weaned was greater at Fray Jorge

(mean=6.6±2.5) than Rinconada (mean=4.1±2.3) in 2015 (Student’s t test: t(29)=-2.56, P=0.02;

Table 2.1).

Question 2: Does increased access to resources improve the direct fitness of group-living females?

Rinconada

In 2014, there was a significant negative relationship between soil hardness and per

2 capita offspring weaned (r =0.363, F1,13=7.423, P=0.02, Fig. 2.4). There was not a statistically significant relationship between per capita offspring weaned and abundance of edible ground

2 vegetation (r <0.001, F1,13=0.0, P=0.99) or square root transformed burrow opening density

2 (r =0.082, F1,13=1.16, P=0.30).

d r = 0 . 3 6 e

n 1 0 P = 0 . 0 2 a

e n = 1 5

f f

o 5

e P

0 2 6 0 0 2 7 0 0 2 8 0 0 2 9 0 0 3 0 0 0 3 1 0 0

S o i l h a r d n e s s ( k P a )

Figure 2.4 Scatterplot showing the statistically significant relationship between per capita number of offspring weaned by social groups and soil hardness at Rinconada in 2014. Data points represent social groups

In 2015, there was a statistically significant relationship between soil hardness and per

2 capita offspring weaned (r =0.182, F1,20=4.45, P=0.05; Fig.2.5). There was not a statistically significant relationship between PCOW and abundance of edible ground vegetation (r2=0.019,

2 F1,20=0.39, P=0.54) or square root transformed burrow opening density (r <0.001, F1,20=0.001,

P=0.98).

d e

n 2

a r = 0 . 1 8 e

w 6 P = 0 . 0 5

g n = 2 2

r p

s 4

t i

p 2

e P 0 2 2 0 0 2 4 0 0 2 6 0 0 2 8 0 0 3 0 0 0 3 2 0 0

S o i l h a r d n e s s ( k P a )

Figure 2.5 Scatterplot showing the statistically significant relationship between per capita number of offspring weaned and soil hardness at Rinconada in 2015. Data points represent social groups

Fray Jorge

In 2015, there was not a statistical relationship between per capita offspring weaned

2 and abundance of edible ground vegetation (r =0.014, F1,7=0.09, P=0.77), burrow opening

2 2 density (r =0.078, F1,7=0.59, P=0.47) or soil hardness (r =0.13, F1,7=1.0, P=0.34).

Question 3: Does living in large groups and having strong network strength improve direct fitness of females in harsh environments?

Rinconada

In 2014, there was not a statistically significant relationship between per capita number

2 of offspring weaned and the total number of adults per group (r =0.006, F1,13=0.074, P=0.79)

2 2 number of adult females (r =0.025, F1,13=0.335, P=0.57), number of adult males (r =0.01,

2 F1,13=0.141, P=0.71), or square root transformed social network strength (r =0.09, F1,11=1.09,

P=0.32).

In 2015, there was not a statistically significant relationship between per capita number

2 of offspring and the total number of adults per group (r =0.009, F1,20=0.183, P=0.67), number of

2 2 adult females (r =0.008, F1,20=0.157, P=0.70), number of adult males (r =, 0.002, F1,20=0.031,

2 P=0.861, ) or square root transformed social network strength (r =0.057, F1,13=0.786, P=0.39).

Fray Jorge

No offspring were captured in 2014. In 2015, there was a positive, marginally significant relationship between per capita number of offspring weaned per social group and social

2 network strength (r =0.691, F1,3=6.7, P=0.08, Fig. 2.6a). This relationship became statistically

2 non-significant when an outlier was removed (r =0.037, F1,2=0.078, P=0.80; Fig. 2.2b). Per capita offspring weaned did not differ between groups consisting of one (n=4), two (n=2), or three (n=3) adults in 2015 (one-way ANOVA: F2,6=0.455, P=0.66). Per capita offspring weaned did not differ between groups consisting of one (n=6) or two (n=3) adult females (Student’s t test: t(7)=-0.087, P=0.93) or in groups with zero adult males (n=4) or one adult male (n=5) in

2015 (Student’s t test: t(7)=0.710, P=0.50).

d 1 0

a e

n i

r 6

f f

o 4 2

a r = 0 . 6 9

t i

p P = 0 . 0 8

2 a

c n = 5

e 0 P 0 . 5 1 . 0 1 . 5

S o c i a l n e t w o r k s t r e n g t h

Figure 2.6a Scatterplot showing the positive relationship between per capita offspring weaned and mean social network strength at Fray Jorge in 2015 including an outlier data point. Data points represent social groups

d 8

e w

r p

s 4

f o

a r = 0 . 0 4 t i 2

p P = 0 . 8 0 a

c n = 4

e 0 P 0 . 5 0 . 6 0 . 7 0 . 8 0 . 9 1 . 0

S o c i a l n e t w o r k s t r e n g t h

Figure 2.6b Scatterplot showing the relationship between per capita offspring weaned and mean social network strength at Fray Jorge in 2015 excluding an outlier data point. Data points represent social groups

Discussion

Table 2.2 Study questions and support Question Expected relationship Support? 1. Does living in large groups Positive relationship between Partial: and having strong network both group size and social strength improve access to network strength and Fray Jorge, only resources in harsh resources (food abundance, Cubic relationship between mean group strength and shrub leaf environments? burrow opening density) abundance in 2014

Edible ground vegetation increases with and increasing mean group strength in 2015 (relationship is non-significant with an outlier excluded)

Groups with 1 female have greater shrub leaf abundance than 2 females in 2015 2. Does increased access to Positive relationship between None resources improve the direct resources (food abundance, fitness of group-living burrow opening density) and Observation: females? PCOW Rinconada, only PCOW decreases with increasing soil hardness in 2014 and 2015 3. Does living in large groups Positive relationship between Partial: and having strong network social measurements and strength improve direct PCOW Fray Jorge, only fitness of females in harsh PCOW increases with mean group strength in 2015 (relationship is environments? non-significant with an outlier excluded)

Taken together, my results lend only partial support to my three predictions: (1) living in larger groups and having higher social network strength is associated with increased access to quality resources in degus (greater food abundance, greater burrow opening density), (2) increased access to resources is associated with increased the direct fitness in group-living females and (3) living in groups with high social network strength is associated with increased direct fitness of females.

My study revealed benefits (access to resources) of social group-living and social network strength (Question 1, Table 2.2) at Fray Jorge, only. There was a positive, statistically significant, cubic relationship between shrub leaf abundance and social network strength in

2014. Social groups with low and high social network strength associated with greater shrub leaf abundance than social groups with moderate social network strength. There was a positive, statistically significant relationship between edible ground vegetation and social network strength in 2015. However, shrub leaf abundance was greater for groups with 1 female than groups with 2 females in 2015, suggesting that the benefits of social group-living and social network strength is context-dependent, likely affected by year and/or the type of food resource. I did not observe a positive relationship between PCOW and access to resources

(Question 2) at either site in 2014 or 2015. However, there was a negative relationship between

PCOW and soil hardness at Rinconada during both years, suggesting that living in hard soils is costly in that population. I found direct fitness benefits associated with living in groups with higher social network strength (Question 3) at Fray Jorge in 2015, only. PCOW increased with increasing social network strength, although the number of social groups was very small (n=5), 56 and the relationship was not significant. Based on previous evidence, I expected that the slope of the relationship between PCOW and group size or social network strength that would differ between sites and across years, as this relationship can be modulated by yearly mean ecological conditions (Ebensperger et al. 2014). Fray Jorge is considered the harsher environment in terms of food abundance and burrow opening density (Chapter 1, Figure 1.3-1.4). Thus, it follows my prediction that a positive relationship between PCOW and social network strength would be detected there. However, this result lends only partial support to my prediction, given the relationship was found only at one site, in one year. We could not measure this relationship at Fray Jorge in 2014 due to reproductive failure of females.

Question 1: Benefits of social group-living and cooperation

One benefit-based hypothesis is that social group-living enhances access to resources such as food and shelter (e.g., burrow openings). Increased access to resources can occur when individuals share information about location and quality of resources with other group members (Ward and Zahavi 1973; McCracken and Bradbury 1981; Wilkinson 1992; Brown 1988;

Wilkinson and Boughman 1998; Safi and Perth 2007). Additionally, larger groups may be more successful at defending territories for access to food resources than smaller groups (‘resource defense hypothesis’; Ostfeld 1985, 1990; Wrangham 1980; Slobodchikoff 1984; Wilkinson and

Boughman 1998; Miller 1996; Dechmann et al. 2009). At Fray Jorge, my observations that (i) in

2014 social groups with low and high social network strength were positively associated with greater access to shrub leaf abundance than social groups with moderate social network strength and (ii) higher social network strength associated with increased access to edible 57 ground vegetation in 2015 suggest that increased cooperation (i.e., groups with high social network strength) confers greater benefits in the form of access to food resources, but only in the habitat with harsher food conditions (Fray Jorge). However, the curvilinear relationship in

2014 also suggests that the costs of cooperating (i.e., intra-group conflict) in groups with moderate social network strength exceed the benefits in terms of accessing food resources.

Groups with lower social network strength, and presumably decreased social conflict, received greater food benefits than groups of moderate social network strength.

My observation that living in social groups with greater cooperation enhanced access to food resources is consistent with studies of cooperative foraging in birds (Brown 1988) and mammals (Wilkinson and Boughman 1998; Miller 1996). For example, cliff swallows (Hirundo pyrrhonota) foraging in large colonies returned with food more often and with more food per trip than birds in small colonies (Brown 1988). Female greater spear-nosed bats (Phyllostomus hastatus) used social calls to coordinate group foraging and recruit roost mates into foraging groups, suggesting group defense of feeding sites (Wilkinson and Boughman 1998). Female bats exhibited higher rates of calling and increased group foraging during seasons when food resources are more concentrated and more limited, and thus inter-group competition is greater

(Wilkinson and Boughman 1998). The cubic relationship between social network strength and shrub leaf abundance in 2014 suggests that social groups with low or high social network strength receive greater food benefits than groups of moderate social network strength.

Support for this observation comes from a study of socially foraging Pallas’s mastiff bat

(Molossus molossus), where selection pressure seems to favor groups with fewer cooperating

58 individuals, presumably because information sharing becomes costly, or the network of signalers and receivers becomes too complex (Gager et al. 2016). This may be the case in degu social groups, as we see access to food decreasing with increasing social network strength. At a certain threshold, the benefits of maintaining strong or many relationships (cooperation) exceeded the costs, and degu social groups with high social network strength experienced greater access to food compared to groups with moderate social network strength. In socially foraging birds (Goldberg et al. 2001; Johnson et al. 2004), mammals (Monaghan and Metcalfe

1985), and fish (Grant et al. 2002), individuals become less aggressive with group members, indicating reduced intra-group conflict, when food patches are large. Degus may be able to maintain more or stronger relationships when food resources (i.e., shrub leaf abundance) are high at burrow systems. Thus, even though social network strength is high, social conflict between individuals may be low due to greater access to food (i.e., greater shrub leaf abundance at burrow systems). In other words, the benefits of cooperating exceed the costs of potential intra-group conflict when food resources are abundant. For example, when food was clumped and predictable, the rate of aggression in Zenaida doves (Zenaida aurita) was smallest at low competitor density and high competitor density (Goldberg et al. 2001). Degu social groups may experience similar interactions under levels of low, or high social network strength

(cooperation). The benefits of cooperating under these conditions may exceed the costs, resulting in a positive association with access to food under both low and high social network strength.

In 2015, solitary females at Fray Jorge accessed burrow systems with higher shrub leaf abundance compared to groups with 2 females. This trend could be due to small sample size of social groups (n=9 social groups) with little variation in group size. The relationship between food abundance and group size and social network strength was not observed at Rinconada, likely because food resources are more uniformly distributed and thus inter-group competition for food likely is low. My observation at Rinconada aligns with the ‘resource defense hypothesis’ (Wrangham 1980; Slobodchikoff 1984). This hypothesis posits that group defense of resources occurs when high quality food is relatively scare, or ‘patchy’, and where patches are large enough to support multiple group members but small enough to be defended by groups.

Green grasses and herbs, are the primary food source for degus at Rinconada (Quirici et al.

2010), and group defense of food is less likely because grasses are a less depletable food resource (Ostfeld 1986), and more abundant and uniformly distributed at Rinconada (Chapter

1, Figure 1.4).

Contrary to expectations, burrow opening density was not associated with group size and social network strength in either site. Past studies at Rinconada have noted that burrow availability is not a limited resource at Rinconada (Ebensperger et al. 2011), although larger groups used more burrow systems than smaller groups (Hayes et al. 2009). Burrow opening density may not be an important resource in these populations, but rather distance to the nearest burrow may be more important in reducing predation risk than burrow opening density. Socially foraging degus retreated to burrows (refuges) at a shorter distance after detecting a predator in more abundant food patches that were closer to burrow openings,

60 compared to patches that were farther from a burrow opening (Lagos et al. 2009). Finally, previous studies found that degus in larger foraging groups improved collective vigilance and ability to detect predators (Ebensperger and Wallem 2002; Ebensperger et al. 2006).

Specifically, time allocated to individual vigilance decreased with increasing group size, and time allocated to individual foraging increased with increasing group size (Ebensperger et al.

2006). Thus, social foraging group size may be a more relevant to enhance access to resources in degus than social group size.

Question 2: Access to resources and fitness benefits

At Rinconada in 2014 and 2015, there was a negative relationship between soil hardness and PCOW, suggesting degus living in harder soils experience a direct fitness cost. It has been suggested that burrow-digging in semi-fossorial species, like degus, is particularly costly compared to fossorial species that have evolved structural specializations (e.g., claw, forelimb and pectoral girdle structural development) for digging (Hildebrand 1988; White et al. 2006). A previous study of degus revealed that the energetic cost of digging in hard soil is greater than digging in soft soil and degus digging in groups remove more soil per capita than solitary degus

(Branch 1993; Ebensperger and Bozinovic 2000b; Ebensperger and Bozinovic 2000a). Thus, group-living and cooperation may be beneficial for burrow construction and maintenance in degus, yet these benefits do not result in direct fitness benefits.

Although living in larger groups and having greater social network strength enhanced access to food at Fray Jorge in 2014, no females produced viable offspring that year. Conditions 61 were sufficiently harsh (Chapter 1, Fig. 1.4) that female suffered fitness costs regardless of group size and social network strength. This observation suggests critically harsh conditions may constrain the extent to which group-living and the potential for cooperation enhance reproductive success in harsh environments. In 2015, higher social network strength increased access to edible ground vegetation, but I did not find a significant relationship between PCOW and increased access to edible ground vegetation. In degus, food abundance at burrow systems could be more important predictor of female body condition and survival rather than reproductive output (Schoech 1996; Murray 2002).

Previous studies found that degus in larger foraging groups improved collective vigilance and ability to detect predators (Ebensperger and Wallem 2002; Ebensperger et al. 2006), and studies suggest distance to the nearest burrow is a predictor of foraging behavior in degus

(Lagos et al. 2009). Burrow opening density is thought to indicate refuge from predators (Hayes et al. 2009; Ebensperger et al. 2012b). Thus, I predicted that increased burrow opening density would confer fitness benefits. My results suggest that burrow opening density is not an important predictor of PCOW in degus. PCOW may be more influenced by the quality and quantity of parental care that offspring receive in the burrow system (König 1997; Cockburn

1998; Taborsky et al. 2007), which we are unable to measure in wild populations. However, under laboratory conditions, the number of pups and the mass of pups of female degus breeding communally did not differ from pups of females breeding singularly or solitarily

Ebensperger et al. 2007). Future studies should examine quality of pups weaned (e.g., size, weight gain) or post-weaning survival of pups in free-living degu populations to understand

62 how living in larger groups or groups with high social network strength influences reproductive success.

Question 3: Direct fitness benefits of social group-living and cooperation

In contrast to previous studies (Ebensperger et al. 2014), I found little support for the prediction that living in larger groups or having higher social network strength is associated with increased reproductive success. At Fray Jorge in 2015 there was a positive, marginally significant relationship between PCOW and social network strength. This is in disagreement with a recent analysis of degus at Rinconada suggesting PCOW decreases with increasing social network strength (Carroll et al. Submitted 2017), and past studies revealing negative or neutral fitness consequences associated with group-living (Hayes et al. 2009, Ebensperger et al. 2011). In my study, direct fitness benefits of group size and social network structure were not detected in

Rinconada in either year, or Fray Jorge 2014, suggesting that selection pressures affecting the relationship between direct fitness and social organization and social structure are habitat- specific. For example, survival and reproductive success in these sites might be linked to foraging group size aboveground instead of social group-living belowground (Ebensperger and Wallem

2002; Lagos et al. 2009), or inter-annual variation in predator abundance. Furthermore, the short duration of my study does not capture the effects of group-living or cooperation on reproductive success, given small samples sizes at Fray Jorge in 2015 (n=9) and reproductive failure of the Fray

Jorge population in 2014. In order to advance theory, it is important to utilize long-term studies

63 of relationships between reproductive success and social organization and social structure within and between populations.

Why live in groups?

The question remains: why do degus live in groups and cooperate? To answer this question, we need to examine ecological drivers of group-living in taxonomically similar species, notably the caviomorph (Caviomorpha) rodents. Predation risk has been noted as a driver of social group foraging in degus, as foraging closely with group members confers a benefit of reduced predation risk (Ebensperger & Wallem 2002; Ebensperger et al. 2006) and species- specific traits, such as susceptibility to predation and habitat requirements, are implicated as drivers of social evolution in some caviomorphs (Lacher 1981; Rowe and Honeycutt 2002;

Trillmich et al. 2004; Ebensperger and Blumstein 2006; Maher and Burger 2011). Different populations may exhibit different life histories, which in turn can explain habitat-specific costs and benefits. For example, at Rinconada, more than 80% of breeding adult males and females do not survive beyond one year of life (Ebensperger et al. 2009, 2013), and therefore most adults at Rinconada will breed only once in a lifetime. At Fray Jorge degus are observed living beyond 3 years (Meserve et al. 1995), and produce more than one litter per year (Meserve et al. 1984). A long-term study in Fray Jorge found that degu life history parameters are affected by El Niño events (Previtali et al. 2010). Specifically, survival and fecundity decreased during La

Niña year events, when precipitation and food availability is low (Previtali et al. 2010). Thus, life history alone does not explain group-living in degus, and the effects of environmental variation on survival and fecundity needs to be examined across populations. 64

Evolutionary history

Comparative studies on social group-living in mammals indicate the cooperative breeding occurs in unpredictable environments, and most often in semi-arid habitats (Lukas and Clutton-Brock 2017). Phylogenetic reconstructions indicate that singular breeding in mammals is restricted to monogamous lineages (Lukas and Clutton-Brock 2012). Phylogenetic analyses suggest 12 transitions to communal breeding from a plurally breeding ancestor (Lukas and Clutton-Brock 2012). More recent phylogenetic analyses suggest that social group-living was present early during the evolution of octodontid rodents (Rivera et al. 2014). An emerging hypothesis is that species may be phylogenetically constrained to social group-living (Rivera et al. 2014; Sobrero et al. 2016). This alternative hypothesis is supported by comparative analyses showing a non-significant association between habitat conditions and sociality in the rodent superfamily Cavioidea (Rowe and Honeycutt 2002). Thus, rather than using an ecological constraints approach to support the evolution of social group-living, phylogenetic effects may be more important in the maintenance of social group-living in current populations of caviomorph rodents (Rowe and Honeycutt 2002). As we generate more information on the social systems of caviomorphs (Hayes et al. 2011), it will be possible to test evolutionary hypotheses using comparative approaches.

Stress physiology

Finally, we can use studies of proximate mechanisms connecting social behavior and stress physiology to understand why degus live in groups and cooperate. Inter-population 65 studies of Rinconada and Fray Jorge revealed habitat differences in the endocrine stress response of degus (Bauer et al. 2013). Baseline cortisol levels can be used as an index of an animal’s health (Bonier et al. 2009), and were lower in Fray Jorge than Rinconada (Bauer et al.

2013). Increased levels of stress hormones could reduce immune function and increase the risk of parasitism (Alexander 1974), influencing reproductive success and body condition of females

(Burger et al. 2012). At Rinconada, female degus exhibited highest stress-induced cortisol levels during late gestation and lactation when food is most abundant (Bauer et al. 2014), suggesting that stress-induced cortisol patterns may be influenced by proximate causes like food availability. Ebensperger et al. (2015) found that lactating females with higher glucocorticoid levels experienced an increase in the immune response (circulating lymphocytes and monocytes relative to other measures of immunocompetence), which could compromise reproduction.

Future studies should determine stress responses, including the ability to turn off HPA responses after a stressor, across populations of degus. Additionally, stress hormones can be affected by the social environment (e.g., animal density, social instability; Bartolomucci 2007).

Stress responses of pups can also be impacted by maternal stress physiology. Bauer et al.

(2015) showed that pups in the presence of both unstressed and manipulatively stressed mothers in the communal breeding group are buffered from the negative impacts experienced by pups in the presence of only stressed mothers. Thus, the measures of female’s stress response (baseline, stress induced cortisol) may be better predictors of PCOW than group size or composition. However, at Rinconada, Ebensperger et al (2011) found circulating cortisol

66 levels in lactating females increased with PCOW, but group size was not associated with cortisol levels. This suggests that variation in cortisol is not a response to variation in group size, although relationships between the endocrine stress response, group size and PCOW still need to be examined in other populations of degus, and other plural breeders.

CHAPTER 3

CONSERVATION IMPLICATIONS

Recent debate has focused on how ecology shapes the evolution of group-living and cooperation in social vertebrates (Cockburn and Russell 2011; Gonzalez et al. 2013). Evidence suggests that group-living and cooperation enhance reproductive success under harsh local conditions in some species. Spatio-temporal ecological variation in climate conditions, such as rainfall and temperature, influences the distribution of cooperatively breeding birds

(Rubenstein and Lovette 2007; Jetz and Rubenstein 2011) and mammals (Lukas and Clutton-

Brock 2017). Cooperative and communal breeding is most beneficial in unpredictable or harsh environments (Covas et al. 2008; Shen et al. 2012; Ebensperger et al. 2014), though recent analyses suggest an alternative hypothesis that cooperative breeding evolved in stable environments and then allowed for colonization of harsh environments (Cornwallis et al. 2017).

Degus inhabit ranges along the Pacific coast of South America, a region that is particularly sensitive to El Niño-Southern Oscillation (ENSO) events (Meserve et al. 1995). ENSO is a global phenomenon that explains irregular but recurring periods of climate variability, and consists of an El Niño, La Niña and neutral phase. Although the timing of La Niña and El Niño phases is irregular, the climate patterns within the phases are predictable (Philander 1990).

Marine and terrestrial ecosystems on the western coast of North America, South America and

Antarctic are influenced by ENSO, mainly by quick and dramatic changes in abundance, distribution and phenology of organisms (Poloczanska et al. 2013; Pörtner et al. 2014; O'Connor 68 et al. 2015). Degu populations at Fray Jorge are impacted by El Nino-Southern Oscillation

(ENSO) events every 5-7 years, and long term research (>25 years) has revealed that these periodic fluctuations in rainfall influence community structure at this site (Gutiérrez et al. 1997;

Gutiérrez and Meserve 2000; Gutiérrez et al. 2010; Meserve et al. 2011). For solitary species, distribution of resources such as food, territory, and mates have the largest impact on survival and reproduction (Clutton-Brock 1988). However, social species and their social systems are complex, with many social and ecological factors influencing survival and reproduction (Clutton-

Brock 1988; Charmantier et al. 2007; Hatchwell 2009; Kerhoas et al. 2014). For example, at Fray

Jorge degu population dynamics are driven by density-dependence and rainfall (Previtali et al.

2009).

As global climate change continues to influence these recurring periods of climate variability (Timmermann et al. 1999; Cai and Whetton 2000; Collins 2005), it is important to recognize habitat-specific responses, especially in social species for which group-level dynamics must be considered in addition to population-level dynamics. For instance, some social species are obligate cooperative breeders, relying on helpers to successfully reproduce (Heinsohn 1992;

Cant 1999; Courchamp and Macdonald 2001). African wild dogs (Lycaon pictus) require group sizes of at least five individuals to successfully reproduce (Courchamp and Macdonald 2001).

Smaller than average groups accept unrelated adults and pups (McNutt 1996), suggesting that wildlife managers should consider not only the number of social groups but also group sizes when planning wild dog translocations (Courchamp and Macdonald 2001). Clutton-Brock et al.

(1999) found that during a year of low rainfall, all social groups of meerkats (Suricata suricatta) with less than 9 individuals went extinct. It is crucial for conservation biologists to monitor 69 social group dynamics in populations like this in order to prevent devastating local extinctions within imperiled populations. Long-term studies examining the modulating effect of ecological conditions on sociality-fitness relationships will become increasingly more important with increasing variability in ecological conditions due to global climate change, habitat degradation, and periodic events such as the El Niño Southern Oscillation, which is particularly influential to the degu’s habitat in South America.

One of the challenges that we face is that long-term datasets (usually 10 or more years or 3 or more generations; Clutton-Brock and Sheldon 2010; Schradin and Hayes 2017) are needed to understand how changes in environmental conditions influence populations. Long- term studies of rodents (Avilés and Tufiño 1998; Ceballos et al. 2010; Horváth and Herczeg

2013), primates (Sauther and Cuozzo 2009), and carnivores (Kolowski and Holekamp 2009; Van

Meter et al. 2009) reveal conservation concerns resulting from human impacts (e.g., habitat fragmentation and modification) and effects of global climate change (e.g., food quality;

Rothman et al. 2015 ). Long-term research can yield unexpected results that are restricted in short term studies. For example, European badger (Meles meles) populations are benefitting from greater survival and reproductive success under warming climates (Macdonald and

Newman 2001). For long-lived, socially complex species, like primates, typical studies ranging between 1-3 years are not sufficient for revealing insights into social behavior. Given that nearly 50% of simian species are at risk of extinction (Mittermeier et al. 2009; Estrada 2013), it is crucial to evaluate population dynamics with extensive studies monitoring social group behavior, survival and fecundity, and ecological conditions, especially under the effects of global climate change. 70

In conclusion, the effectiveness of conservation programs will depend on our ability to gather long-term datasets about the social behavior, population dynamics, and reproductive success across sites with different environmental conditions, especially in the face of global climate change. By focusing on two populations, my study answers questions about the habitat- specific costs and benefits of social organization and social structure in degus. More importantly, my work is in the context of a long-term study of degu social systems in one population (Rinconada), and has the potential for long-term research in another population

(Fray Jorge). Given the differences in ecology between these two sites, and the inter-annual variation in ecology that exists within sites, long-term studies at both Rinconada and Fray Jorge will continue to yield important insights into the evolution of group-living in degus.

APPENDIX A

SOCIAL GROUPS

Individual ID numbers, individuals in the same column represent social groups

Rinconada 2014:

Group 1 Group 2 Group 4 Group 5 Group 6 Group 7 Group 8 Group 9 3261 (M) 3220 (F) 3260 (M) 1987 (F) 3109 (F) 3258 (F) 1915 (F) 3267 (F) 1847 (F) 3192 (F) 3206 (F) 1925 (F) 1972 (F) 1951 (M) 3273 (F) 1913 (M) 3134 (M) 3045 (F) 3264 (F) 1956 (M) 3070 (F) 3263 (F) 3044 (F) 1931 (M)

Group 10 Group 12 Group 13 Group 14 Group 15 Group 16 Group 17 3252 (M) 3274 (F) 1983 (F) 3184 (F) 0023 (F) 3243 (F) 1892 (M) 3148 (F) 3163 (M) 3110 (F) 3253 (F) 3191 (M) 1879 (F) 3159 (F) 3078 (M) 1924 (M) 3182 (M) 3129 (F) 1789 (F) 1812 (F)

Rinconada 2015:

Group 1 Group 2 Group 3 Group 4 Group 5 Group 6 Group 7 Group 8 3632 (F) 3529 (M) 3516 (F) 3498 (F) 1779 (F) 1780 (F) 3029 (M) 3044 (F) 3647 (M) 3551 (M) 1753 (F) 3544 (M) 3343 (F) 3581 (F) 3574 (F) 3045 (F) 3618 (F) 3426 (F) 3469 (M) 3564 (F) 3575 (F) 3413 (F) 3415 (F) 3349 (M) 3565 (F) 3696 (F) 3396 (F) 3558 (F) 3029 (F) 3552 (M) Group 12 Group 15 Group 17 Group 18 Group Group Group 20 Group 21 19a 19b 3195 (F) 3140 (F) 3537 (F) 3348 (F) 3159 (F) 3436 (F) 3308 (F) 1972 (F) 3201 (F) 3576 (M) 3452 (F) 3534 (M) 3567 (M) 3109 (F) 3577 (M) 3264 (F) 3352 (F) 3548 (M)

Group 22 Group 23 Group 24 Group 27 Group 28 Group 29 3557 (F) 3220 (F) 3486 (F) 3052 (F) 3056 (F) 3504 (F) 3539 (M) 3523 (M) 3561 (M) 3375 (F) 3554 (M) 3659 (F) 3438 (F) 3524 (M) 3485 (F) 3541 (M) 3168 (M) 3208 (M) 3674 (F) 3392 (M)

Fray Jorge 2014:

Group 2 Group 3 Group 4 Group 5 Group 6 Group 7 Group 8a Group 8b 2 (M) 54 (F) 9 (F) 17 (F) 70 (F) 25 (F) 8 (M) 63 (F) 7 (F) 21 (M) 24 (F) 19 (M) 60 (F) 41 ( M) 23 (F) 65 (F) 40 (F) 15 (M) 43 (F) 1 (F)

Group 11 Group 12 Group Group Group 14 Group 15 13a 13b 30 (M) 33 (F) 66 (M) 78 (F) 29 (M) 12 (M) 35 (M) 64 (F) 37 (F) 72 (F) 32 (F) 20 (F) 42 (F) 53 (M) 47 (F) 44 (F) 11 (F) 51 (F) 68 (F) 34 (F) 46 (M) 56 (F) 38 (M) 67 (F)

Fray Jorge 2015:

Group 1 Group 2 Group 3 Group 4 Group 5 Group 6 Group 7 Group 8 56 (M) 88 (M) 67 (F) 6704 (M) 69 (M) 60 (F) 71 (F) 57 (F) 55 (F) 70 (F) 52 (F) 61 (F) 68 (F) 923 (F) 54 (F)

Group 9 63 (F)

APPENDIX B

ECOLOGICAL DATA

Group means of all ecological variables- all group members

Rinconada 2014:

Group ID Food abundance Burrow opening density Soil hardness (g/m2) (#/m2) (kPa) 1 190.7 0.13 2865.9 2 168.7 0.16 2787.9 4 104.3 0.05 3007.6 5 143.4 0.12 2758.7 6 117.8 0.26 2957.4 7 148.0 0.10 2889.5 8 42.6 0.26 2910.3 9 129.7 0.11 2957.4 10 102.0 0.11 2996.6 12 147.8 0.09 2938.5 13 204.3 0.25 2921.8 14 162.4 0.16 2813.7 15 197.7 0.13 2938.5 16 121.7 0.09 2894.2 17 124.1 0.11 2774.6

Rinconada 2015:

Group ID Food abundance Burrow opening density Soil hardness (g/m2) (#/m2) (kPa) 1 98.4 0.31 2824.1 2 142.5 0.19 2850.9 3 156.6 0.19 2849.1 4 96.9 0.15 2917.8 5 72.1 0.13 2666.6 6 143.0 0.27 3004.4 7 166.3 0.26 2289.2 8 143.3 0.08 2731.8 12 132.9 0.19 2533.1 15 72.2 0.12 2731.5 17 175.7 0.18 2900.9 18 22.2 0.14 2966.8 19a 86.9 0.13 2656.8 19b 83.8 0.13 2659.8 76

20 129.4 0.11 2232.8 21 145.5 0.37 2415.7 22 128.7 0.18 2568.0 23 219.3 0.23 2668.8 24 129.8 0.27 2289.2 27 63.4 0.14 2920.6 28 72.9 0.13 2949.2 29 62.7 0.18 2968.8

Fray Jorge 2014:

Group Food abundance Shrub leaf Burrow opening Soil hardness ID (g/m2) abundance density (#/m2) (kPa) 2 0 8.67 0.04 1966.0 3 0 5.30 0.03 2568.2 4 0 4.00 0.09 1404.7 5 0 5.01 0.06 2059.7 6 0 1.71 0.07 1919.7 7 0 2.35 0.10 2230.2 8a 0 6.96 0.02 2206.8 8b 0 0.93 0.01 1942.0 11 0 7.74 0.02 2060.3 12 0 13.00 0.07 1743.5 13a 0 13.32 0.04 2358.6 13b 0 4.45 0.06 2209.6 14 0 5.27 0.03 2182.2 15 0 0.45 0.02 2214.8

Fray Jorge 2015:

Group Food abundance Shrub leaf Burrow opening Soil hardness ID (g/m2) abundance density (#/m2) (kPa) 1 28.8 7.89 0.05 1458.0 2 139.4 1.17 0.03 1354.0 3 17.1 16.67 0.08 1668.2 4 62.1 7.98 0.06 1254.4 5 12.9 0.00 0.06 940.8 6 38.3 15.75 0.07 1367.1 7 46.4 25.00 0.11 1028.3 8 69.9 0.00 0.04 1384.2 9 66.6 20.56 0.11 1326.3 77

Group means of all ecological variables-female group members only

Rinconada 2014:

Group ID Food abundance Burrow opening density Soil hardness (g/m2) (#/m2) (kPa) 1 170.7 0.15 2885.7 2 168.7 0.16 2787.9 4 102.4 0.05 3007.1 5 143.4 0.12 2704.8 6 117.8 0.26 2957.4 7 141.8 0.12 2862.3 8 42.6 0.26 2910.3 9 129.7 0.11 2957.4 10 102.0 0.11 2995.2 12 147.8 0.09 2938.5 13 206.9 0.25 2930.3 14 162.0 0.16 2816.9 15 197.7 0.13 2938.5 16 119.3 0.09 2893.4 17 120.7 0.11 2826.1

Rinconada 2015:

Group ID Food abundance Burrow opening density Soil hardness (g/m2) (#/m2) (kPa) 1 100.6 0.30 2817.3 2 141.5 0.19 2838.6 3 156.6 0.19 2849.1 4 98.9 0.15 2910.3 5 77.9 0.13 2642.1 6 143.0 0.27 3004.4 7 166.3 0.26 2289.2 8 144.2 0.08 2733.1 12 132.9 0.19 2533.1 15 72.2 0.12 2731.5 17 175.7 0.18 2900.9 18 22.2 0.14 2966.8 19a 86.9 0.13 2656.8 19b 83.7 0.12 2631.9 78

20 129.3 0.11 2232.2 21 146.6 0.39 2415.6 22 136.5 0.18 2513.6 23 226.6 0.23 2513.2 24 129.8 0.27 2289.2 27 63.7 0.14 2921.0 28 72.1 0.13 2945.5 29 65.8 0.17 2966.8

Fray Jorge 2014:

Group Food abundance Shrub leaf Burrow opening Soil hardness ID (g/m2) abundance density (#/m2) (kPa) 2 0 8.56 0.04 1954.5 3 0 4.93 0.03 2548.7 4 0 4.00 0.09 1404.7 5 0 5.24 0.06 2050.7 6 0 1.71 0.07 1919.7 7 0 3.13 0.10 2179.2 8a 0 7.47 0.04 2260.4 8b 0 0.93 0.01 1942.0 11 0 6.56 0.02 1922.4 12 0 13.0 0.07 1743.5 13a 0 12.19 0.04 2331.0 13b 0 4.45 0.06 2209.6 14 0 5.00 0.03 2187.9 15 0 0.34 0.02 2207.9

Fray Jorge 2015:

Group Food abundance Shrub leaf Burrow opening Soil hardness ID (g/m2) abundance density (#/m2) (kPa) 1 29.9 8.21 0.05 1461.2 2 129.6 0.00 0.03 1298.5 3 17.1 16.67 0.08 1668.2 4 64.3 8.07 0.06 1185.2 5 8.7 0.00 0.07 846.9 6 38.3 15.75 0.07 1367.1 7 46.4 25.00 0.11 1028.3 8 68.9 0.00 0.04 1384.2 9 69.2 20.13 0.11 1323.2 79

APPENDIX C

SOCPROG PROCEDURE

Select “Input data”

Under data input select “Excel association matrix”

After selecting the tab that contains the matrix hit ‘OK’ and leave the long title the same.

Select ‘Analyze single association measure

Select ‘Network analysis statistics’ and then make sure both boxes are checked on the box ‘Statistics of

Weighted Network: Options’

Then hit ‘Run’

Name and save txt file.

Copy and paste data from txt file into excel.

APPENDIX D

SOCPROG OUTPUTS/NETWORK DATA

Rinconada 2014:

Group ID Social network Social network strength- strength- all members females only 1 1.33 N/A 2 2.00 1.00 4 3.62 2.90 5 0.94 0.94 6 3.60 3.00 7 1.0 N/A 8 N/A N/A 9 2.00 1.00 10 2.42 1.89 12 N/A N/A 13 2.49 0.57 14 1.88 0.95 15 1.0 1.00 16 1.17 N/A 17 0.75 N/A

Rinconada 2015:

Group ID Social network Social network strength- strength- all members females only

1 N/A N/A 2 1.50 N/A 3 1.00 1.00 4 0.75 N/A 5 1.11 1.00 6 2.80 2.80 7 N/A N/A 8 2.51 2.76 12 N/A N/A 15 N/A N/A 17 N/A N/A 18 N/A N/A 19a 1.00 1.0 19b 0.60 N/A 20 1.0 N/A 21 2.21 1.53 22 1.89 0.45 85

23 1.00 N/A 24 N/A N/A 27 2.00 1.00 28 1.79 0.63 29 2.06 0.00

Fray Jorge 2014:

Group ID Social network Social network strength- strength- all members females only 2 0.33 N/A 3 0.63 N/A 4 1.33 1.33 5 1.25 0.28 6 N/A N/A 7 0.59 0.25 8a 0.32 N/A 8b 1.00 1.00 11 2.73 0.83 12 2 1.00 13a 2.73 2.05 13b 1.00 1.00 14 1.47 1.12 15 1.31 0.73

Fray Jorge 2015:

Group ID Social network Social network strength- strength- all members females only 1 0.6 N/A 2 1.5 0.82 3 N/A N/A 4 0.8 0.50 5 0.85 0.88 6 N/A N/A 7 N/A N/A 8 N/A N/A 9 0.89 N/A

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VITA

Madeline Strom was born in Phoenix, Arizona to parents Gerald Strom and Grace Klees.

She has a twin brother, Andy Strom, and a younger brother, Timmy Strom. She attended

Chaparral High School in Scottsdale, Arizona. In 2012, she completed two degrees at the

University of Arizona: a Bachelor of Science in Organismal Biology and a Bachelor of Arts in

Spanish. Bear Down, Wildcats! Madeline worked for over a year at the Phoenix Zoo’s Native

Species Conservation Center as a Conservation Technician before accepting a graduate teaching assistantship at the University of Tennessee at Chattanooga in the Environmental Sciences program. Madeline will graduate with a Master’s of Science in Environmental Science in August

2017. In the fall she will begin a Ph.D. program at New Mexico State University studying the behavioral ecology of small mammals.

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