The fitness consequences of sociability in eastern grey kangaroos (Macropus giganteus)
Paloma Alexandra Corvalan Bachelor of Science (Honours)
A thesis submitted for the degree of Doctor of Philosophy at The University of Queensland in 2019 School of Biological Sciences
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Abstract
The level of individuals’ sociability, their propensity to associate and form close relationships with others, has fitness costs and benefits, but these have mostly been observed in females and in more socially complex species. My objective was to examine the social patterns of eastern grey kangaroos (Macropus giganteus) and investigate how these may relate to aspects of individuals’ fitness. The eastern grey kangaroo is a highly social macropod that exhibits high fission-fusion dynamics. I studied a population of wild kangaroos in Sundown National Park, Queensland, Australia, where research on females’ social patterns has been conducted since 2010. I collected data on both females’ and males’ grouping associations from January 2014 to February 2016. Adult kangaroos do not engage in allogrooming as a form of social exchange or allomothering, and there is no evidence of any other forms of cooperative behaviour.
In Chapter 2, I studied how the social and space-use patterns of adult males differed among size classes to examine potential age and dominance related changes in males’ reproductive strategies. Large males were the most dominant, and they roamed further and had more adult female associates; however, their strength of association with their top ten female associates (i.e. “top 10 score”) was weaker than that of small males. Older, more dominant males likely adopt a strategy of maximising the number of females they are exposed to, as they have priority access to receptive females. Small males had a smaller space-use area, as they may have been investing more time into foraging for growth. Their higher top 10 score with adult females may have been due to their smaller range, but could also be indicative of a reproductive tactic that increases their chances of mating with a close associate when she first becomes receptive.
I explored the link between males’ sociability and their reproductive success in Chapter 3. I examined the paternity of 136 young-at-foot from 96 known mothers for 58 adult males, and performed further analyses on 25 males. I found that more dominant males sired more young-at- foot, but their gregariousness and top 10 score were not related to their overall reproductive success in our site. The stronger the association between a male and female, the higher their probability of sharing an offspring. This may be because males that spend more time with a particular female are more likely to be present when she is in oestrous, but may also be due to females’ preference for more familiar males.
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In Chapter 4, I examined the testosterone (T) and glucocorticoid (GC) metabolite levels of 476 faecal samples collected from 31 adult males. I assessed whether the patterns of males’ hormone levels were consistent with the challenge hypothesis, social buffering theory, and an extended version of the steroid/peptide theory (a hypothesis that stipulates low T levels are related to greater nurturance behaviour). I found that males’ T levels were higher during months with more courtship and male-male competition, which is consistent with the challenge hypothesis, but it is not known whether heightened T was in response to competition or for increased spermatogenesis. There was no correlation between males’ GC levels and their sociability, thus I did not find any evidence for social buffering effects in male kangaroos. There was no evidence of testosterone being lower in more sociable males, but I found that the more frequently males were present in our site, the lower their T levels; if males that were infrequently present in our site were active roamers, this may have been indicative of T-mediated roaming behaviour.
In Chapter 5, I explored whether females’ survival was related to their body condition, gregariousness, top 10 score, boldness, rainfall, and temperature. Of 138 females observed in 2010- 2011, only 60 were present in the final year of study. I did not find evidence of survival benefits of having close social relationships, as top 10 score was not a significant predictor of survival. I found that survival between periods was higher when there was more rainfall in the previous month and females in better body condition had higher survival. Females with larger group sizes had a higher probability of survival showing that there is a direct fitness benefit of being gregarious. As predation is unlikely to be a cause of mortality in these females, I suggest that gregarious females are gaining foraging benefits from reduced vigilance when in larger groups.
My thesis contributes to our understanding of the costs and benefits of sociability by examining a species with high fission-fusion dynamics, in which adults do not engage in complex cooperative behaviours or groom one another as a form of social exchange. Research comparing the social patterns of different species of mammals and the fitness consequences of their social relationships could help us understand what aspects of species’ social relationships are linked to particular fitness consequences.
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Declaration by author
This thesis is composed of my original work, and contains no material previously published or written by another person except where due reference has been made in the text. I have clearly stated the contribution by others to jointly-authored works that I have included in my thesis.
I have clearly stated the contribution of others to my thesis as a whole, including statistical assistance, survey design, data analysis, significant technical procedures, professional editorial advice, financial support and any other original research work used or reported in my thesis. The content of my thesis is the result of work I have carried out since the commencement of my higher degree by research candidature and does not include a substantial part of work that has been submitted to qualify for the award of any other degree or diploma in any university or other tertiary institution. I have clearly stated which parts of my thesis, if any, have been submitted to qualify for another award.
I acknowledge that an electronic copy of my thesis must be lodged with the University Library and, subject to the policy and procedures of The University of Queensland, the thesis be made available for research and study in accordance with the Copyright Act 1968 unless a period of embargo has been approved by the Dean of the Graduate School.
I acknowledge that copyright of all material contained in my thesis resides with the copyright holder(s) of that material. Where appropriate I have obtained copyright permission from the copyright holder to reproduce material in this thesis and have sought permission from co-authors for any jointly authored works included in the thesis.
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Publications included in this thesis
No publications included.
Submitted manuscripts included in this thesis
While no manuscripts have been submitted, Chapters 2 to 5 have been written with the intention of submitting to peer-reviewed journals. I have therefore outlined the contributions of all co-authors to the manuscripts below.
Chapter 2: Corvalan, P. A.; Goldizen, A. W. How do male eastern grey kangaroos’ (Macropus giganteus) movement and social patterns change with size?
Contributor Statement of contribution Corvalan, P. C. (candidate) Fieldwork (100%), designed study (80%), statistical analysis (100%), wrote manuscript (100%) Goldizen, A. W. Project support, designed study (20%), edited manuscript (100%)
Chapter 3: Corvalan, P. A.; Seddon, J. M.; Goldizen, A. W. The social correlates of reproductive success in male eastern grey kangaroos (Macropus giganteus)
Contributor Statement of contribution Corvalan, P. C. (candidate) Fieldwork (100%), designed study (80%), statistical analysis (100%), genetic analysis (100%), wrote manuscript (100%) Seddon, J. M Training in genetic analysis, edited manuscript (30%) Goldizen, A. W. Project support, designed study (20%), edited manuscript (70%)
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Chapter 4: Corvalan, P. A., Gilmour, M., Hobbs, R. J., Goldizen, A. W. The social correlates of males’ testosterone and glucocorticoid levels in eastern grey kangaroos (Macropus giganteus)
Contributor Statement of contribution Corvalan, P. C. (candidate) Fieldwork (75%), designed study (80%), statistical analysis (90%), faecal hormone extraction (80%), wrote manuscript (100%) Gilmour, M Fieldwork (25%), statistical analysis (10%), faecal hormone extraction (20%), edited manuscript (5%) Hobbs, R. J. Faecal hormone analysis (100%), edited manuscript (30%) Goldizen, A. W. Project support, designed study (20%), edited manuscript (65%)
Chapter 5: Corvalan, P. A.; Blomberg, S. P.; Menz, C. S.; Best E. C.; Freeman, N. J.; Goldizen, A. W. Social correlates of survival in female eastern grey kangaroos (Macropus giganteus)
Contributor Statement of contribution Corvalan, P. C. (candidate) Fieldwork (25%), designed study (60%), statistical analysis (50%), wrote manuscript (100%) Blomberg, S. P. designed study (20%), statistical analysis (50%), edited manuscript (30%) Menz, C. S Fieldwork (25%) Best E. C. Fieldwork (25%) Freeman, N. J. Fieldwork (25%) Goldizen, A. W. Project support, designed study (20%), edited manuscript (70%)
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Other publications during candidature
Conference Abstracts
Corvalan, P. A. (2016). Testosterone, stress, and social interactions in male eastern greys. Paper presented at the Annual Conference of the Australasian Society for the Study of Animal Behaviour, Katoomba, Australia, Speed talk format.
Corvalan, P. A., Blomberg, S. P., Goldizen, A. W. (2016). Is sociability a predictor of survival in female kangaroos?. Poster presented at the 2016 Conference of the International Society for Behavioral Ecology, Exeter, UK.
Corvalan, P. A., Seddon, J. M., Goldizen, A. W. (2017). Patterns of paternity in eastern grey kangaroos. Paper presented at the Annual Conference of the Australasian Society for the Study of Animal Behaviour, Mooroolbark, Australia.
Corvalan, P. A., Blomberg, S. P., Goldizen, A. W. (2017). The hormonal correlates of male social relationships in a large marsupial. Poster presented at the Behaviour 2017 Conference, a joint meeting of the 35th International Ethological Conference and the 2017 Summer Meeting of the Association for the Study of Animal Behaviour, Estoril, Portugal.
Public presentations
Corvalan, P. C. (2016). Spatial data in R - a tool to examine animals' social patterns. Presentation at RezBaz Brisbane 2016, Brisbane, Australia.
Contributions by others to the thesis
The kangaroo project was originally conceived and designed by Anne Goldizen and Emily Best, and Anne contributed to conceiving my particular project. Since parts of my thesis use the long- term dataset collected by previous researchers in the site, there are significant field work and genetic analysis contributions by Emily Best, Clementine Menz, and Natalie Freeman. Emily, Clementine, and Natalie collected field data (social grouping surveys and body condition data), tested kangaroos’ flight initiation distances, and collected and analysed scat samples for genetic vi
analysis. Molly Gilmour and Aliesha Dodson were honours students who helped collect scat samples for genetic and hormone analysis. Tamara Keeley provided training on faecal hormone extraction and analysis and provided invaluable advice for my hormone study. Molly Gilmour assisted in extracting hormones from scat samples, and Rebecca Hobbs analysed the hormone contents of the scat samples. Sean Corley assisted in genotyping all the DNA samples. Numerous volunteers aided in field work by collecting scat samples for hormone and genetic analysis. Ross Dwyer helped in the revision of the spatial analysis R code. Tony Battistel helped format my thesis. Simone Blomberg reviewed the data analysis in R, assisted in the interpretation of the results, and wrote a large portion of the code for the survival analysis in Chapter 5.
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Statement of parts of the thesis submitted to qualify for the award of another degree
No works submitted towards another degree have been included in this thesis.
Research Involving Human or Animal Subjects
Permit Permit Number Date valid Scientific Purposes Permit WISP11362712 1 July 2012 – 30 June 2015 Scientific Purposes Permit WISP16018615 1 July 2015 – 30 June 2018 Permit to Take, Use, Keep or WITK11362312 1 July 2012 – 30 June 2015 Interfere with Cultural or Natural Resources Permit to Take, Use, Keep or WITK16019015 1 July 2015 – 30 June 2018 Interfere with Cultural or Natural Resources Animal Ethics Approval SIB/142/12/ARC 8 July 2012 – 8 July 2015 Certificate Animal Ethics Approval SBS/160/15/ARC 1 June 2015 – 1 June 2018 Certificate
Permits and ethics approval certificates can be found in the appendices.
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Acknowledgements
I would like to acknowledge all the people who have touched my life. From my weak associations with colleagues that helped me form new ideas, to my close social bonds that helped reduce my stress levels and overcome the challenges of completing a PhD, all have contributed to my success. To my family and friends, I appreciate your support, encouragement, and kindness. Tony, you have been incredible throughout my PhD. Thank you for sharing your unconditional love and supporting me when I was feeling overwhelmed. To my sisters, Carolina and Soumina, thank you for cheering me on, pushing me forward, and showing me how discipline and hard work pay off in the long run. To my cherished mother, thank you for giving me the comfort of a safety net, allowing me to take risks and follow my dreams fearlessly. To my patient father, thank you for nurturing my love of science and helping me believe I could achieve anything I put my mind to. To my extended family and good friends, your love and care has given me the strength to persevere and has made this journey more enjoyable. It was easy for me to write about the benefits of social bonds in my thesis, as, thanks to my family and friends, I have been experiencing these first-hand. Thank you! My wellbeing, idea generation, and (likely) longevity have all been improved by you!
To my supervisor, Anne Goldizen, thank you for trusting me when I forged new paths and for helping me figure out new directions when I hit a wall. I am grateful to have had such a supportive supervisor and mentor who saw their students as people first. The impact you have had on all of us goes beyond what we have produced during our research degrees. We have seen how compassion makes for the best of leaders and will be holding ourselves and others up to that standard.
To my co-supervisor, Simone Blomberg, I owe a huge debt of gratitude for patiently guiding me in my learning of R and statistics. I now use R in my everyday life and have taught others to use it too, and this journey started with your R course in my first year at UQ. All of us at the School of Biological Sciences are incredibly lucky to be able to discuss our data collection and analysis plans with you, and I am grateful to have worked closely with you throughout my PhD.
To my co-supervisor, Jenny Seddon, thank you for taking the time to teach me the genetic laboratory techniques and helping me understand my results. Your positivity and easy going nature helped me feel confident during the steep learning curve of the first year of my PhD. Tamara Keeley, thank you for opening up your lab space for our use and taking time out of your day to teach us about hormone extraction. Your passion for your research is inspiring and I am grateful for ix
your generosity. Rebecca Hobbs, thank you for showing us the hormone analysis protocol in your lab and analysing all our samples. After learning how complicated and time-consuming hormone analysis can be, I am grateful that my samples could be processed by a professional in a lab space specifically designed for it. Sean Corley, thank you for your assistance in the genetic analysis of our kangaroos since the inception of the study. Ross Dwyer, I appreciate the time you took to guide me in my learning of spatial analysis in R.
To my lab mates, Natalie Freeman, Clementine Menz, Joanne Towsey, Molly Gilmour, Aliesha Dodson, and Rebecca Dannock, thank you for the fun times in the office and creating a welcoming work environment. Natalie and Clemmie, thank you for all your hard work on the kangaroo project and teaching me all the skills and knowledge I needed to thrive in the field and the lab. Thank you for you dedication to the project and management of our historical data, which made all of this possible for me. Natalie, Molly, and Aliesha, I appreciate the good times we shared in the field - the yummy food we made together, the silly shows we watched at night, and the smelly workouts we did despite sometimes not always having access to showers; you all helped make our field house feel welcoming and eased the home-sickness. Molly, I do not know how I would have fared without you during our long months processing samples in the Gatton lab. You were the ray of sunshine in our windowless room and I treasure the memories from this time, despite those taxing days being some of the hardest we had to endure.
I am fortunate to have had fantastic volunteers visit my field site and remain enthusiastic after spending hours collecting kangaroo scat. Conor O’Brien, Katie Cook, Bart Peeters, Adrienne McGill, Rémi Bigonneau, Louis Latham, Katherine Jeffrey, William Arnold, Cassy Corvalan (my mum!), Hera Sengers, and Tony Battistel, you were amazing and I thank you for contributing to my project.
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Financial support
This research was supported by an Australian Government Research Training Program Scholarship.
Fieldwork, hormone analyses, and genetic analyses were supported by three Holsworth Wildlife Research Endowment grants (2014-2017), Anne Goldizen’s ARC Discovery Grant (Year: 2012- 2014; Title: Evolutionary roots of social bonds in female mammals; ResearchMaster Number: 2011002969), and Anne Goldizen’s research funds from the University of Queensland. I am grateful for the support of these funding organizations and university.
Keywords
Kangaroo, sociability, reproductive strategies, reproductive success, survival, hormones, stress, testosterone
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Australian and New Zealand Standard Research Classifications (ANZSRC)
ANZSRC code: 060201, Behavioural Ecology, 60% ANZSRC code: 060801, Animal Behaviour, 40%
Fields of Research (FoR) Classification
FoR code: 0602, Ecology, 60% FoR code: 0608, Zoology, 40%
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Table of Contents
ABSTRACT ...... I DECLARATION BY AUTHOR ...... III PUBLICATIONS INCLUDED IN THIS THESIS ...... IV SUBMITTED MANUSCRIPTS INCLUDED IN THIS THESIS ...... IV OTHER PUBLICATIONS DURING CANDIDATURE ...... VI CONTRIBUTIONS BY OTHERS TO THE THESIS ...... VI STATEMENT OF PARTS OF THE THESIS SUBMITTED TO QUALIFY FOR THE AWARD OF ANOTHER DEGREE...... VIII RESEARCH INVOLVING HUMAN OR ANIMAL SUBJECTS ...... VIII ACKNOWLEDGEMENTS ...... IX FINANCIAL SUPPORT ...... XI KEYWORDS ...... XI AUSTRALIAN AND NEW ZEALAND STANDARD RESEARCH CLASSIFICATIONS (ANZSRC)...... XII FIELDS OF RESEARCH (FOR) CLASSIFICATION ...... XII LIST OF FIGURES ...... XV LIST OF TABLES ...... XV LIST OF SUPPLEMENTARY TABLES ...... XVI LIST OF ABBREVIATIONS ...... XVI
CHAPTER 1 – GENERAL INTRODUCTION ...... 1
THE SOCIAL LIVES OF MAMMALS ...... 1 FITNESS CONSEQUENCES OF SOCIAL BONDS ...... 3 EVIDENCE THAT SOCIABILITY CAN REDUCE STRESS LEVELS ...... 5 THE ROLES OF TESTOSTERONE IN SOCIAL RELATIONSHIPS ...... 8 STUDYING SOCIAL RELATIONSHIPS IN MAMMALS ...... 9 MALE REPRODUCTIVE STRATEGIES IN SPECIES WITH HIGH FISSION-FUSION DYNAMICS ...... 10 STUDY SPECIES: EASTERN GREY KANGAROOS ...... 11 STUDY SITE AND POPULATION ...... 13 THESIS OUTLINE, OBJECTIVES, AND SIGNIFICANCE...... 14 REFERENCES ...... 15
CHAPTER 2 – HOW DO MALE EASTERN GREY KANGAROOS’ (MACROPUS GIGANTEUS) SOCIAL AND SPACE USE PATTERNS CHANGE WITH SIZE? ...... 33
ABSTRACT ...... 33 INTRODUCTION ...... 33 METHODS ...... 36 RESULTS ...... 41 DISCUSSION ...... 48 REFERENCES ...... 52
CHAPTER 3 THE SOCIAL CORRELATES OF REPRODUCTIVE SUCCESS IN MALE EASTERN GREY KANGAROOS (MACROPUS GIGANTEUS) ...... 56 xiii
ABSTRACT ...... 56 INTRODUCTION ...... 56 METHODS ...... 60 RESULTS ...... 66 DISCUSSION ...... 70 REFERENCES ...... 74
CHAPTER 4 – THE SOCIAL CORRELATES OF MALES’ TESTOSTERONE AND GLUCOCORTICOID LEVELS IN EASTERN GREY KANGAROOS (MACROPUS GIGANTEUS) ...... 82
ABSTRACT ...... 82 INTRODUCTION ...... 82 METHODS ...... 86 RESULTS ...... 92 DISCUSSION ...... 96 REFERENCES ...... 100 SUPPLEMENTARY MATERIAL CHAPTER 4 ...... 124
CHAPTER 5 – SOCIAL CORRELATES OF SURVIVAL IN FEMALE EASTERN GREY KANGAROOS (MACROPUS GIGANTEUS) ...... 125
ABSTRACT ...... 125 INTRODUCTION ...... 125 METHODS ...... 129 RESULTS ...... 133 DISCUSSION ...... 136 REFERENCES ...... 140 SUPPLEMENTARY MATERIAL CHAPTER 5 ...... 147
GENERAL DISCUSSION ...... 148
OVERVIEW ...... 148 IMPLICATIONS FOR THE STUDY OF MALES’ REPRODUCTIVE STRATEGIES IN SPECIES WITH HIGH FISSION-FUSION DYNAMICS AND INDETERMINATE GROWTH ...... 149 IMPLICATIONS FOR THE STUDY OF THE SOCIAL BONDS IN MAMMALS ...... 151 COOPERATION AND AFFECTIONATE TOUCH AS DRIVING FORCES OF THE BENEFITS OF SOCIAL BONDING ...... 152 LIMITATIONS AND FUTURE RESEARCH ...... 155 REFERENCES ...... 159
APPENDICES ...... 166
A1. SCIENTIFIC PURPOSES PERMIT 2012-2015 ...... 166 A2. SCIENTIFIC PURPOSES PERMIT 2015-2018 ...... 169 A3. PERMIT TO TAKE, USE, KEEP OR INTERFERE WITH CULTURAL OR NATURAL RESOURCES 2012-2015 ...... 172 A4. PERMIT TO TAKE, USE, KEEP OR INTERFERE WITH CULTURAL OR NATURAL RESOURCES 2015-2018 ...... 175 A5. ANIMAL ETHICS 2012-2015 ...... 178 xiv
A6. ANIMAL ETHICS 2015-2018 ...... 179
List of figures Figure 2.1. The relative dominance scores (measured using David’s scores) of male kangaroos of different size classes ...... 42 Figure 2.2. The proportions of their dominance interactions that small, medium and large males engaged in with small males (red), medium-sized males (green) and large males (blue) ...... 43 Figure 3.1. The relationship between males’ dominance rank, 1 being the highest rank, and their reproductive success ...... 69 Figure 3.2. Predictors of the likelihood of sharing an offspring ...... 70 Figure 4.1. Variation in the logged values of faecal testosterone metabolite levels against monthly intensity of competition and courtship ...... 94 Figure 4.2. The relationship between males’ dominance ranks and faecal testosterone metabolite levels ...... 94 Figure 4.3. Faecal testosterone metabolite levels as a function of the frequency that male eastern grey kangaroos were observed ...... 95 Figure 4.4. The relationship between male eastern grey kangaroos’ faecal GC and testosterone metabolite levels ...... 95 Figure 4.5. Male EGK’s faecal glucocorticoid metabolite levels across the seventeen months of our study ...... 96 Figure 5.1. Female kangaroos’ survival probability ...... 136
List of tables Table 2.1. Estimates and standard errors in the linear model used to test for differences in male eastern grey kangaroos’ average group size...... 43 Table 2.2. Estimates and standard errors in the generalized linear model used to test for differences in male eastern grey kangaroos’ nearest neighbour distance (metres)...... 44 Table 2.3. Estimates and standard errors in the linear model used to test for differences in male eastern grey kangaroos’ numbers of female associates...... 45 Table 2.4. Estimates and standard errors in the generalized linear model used to test for differences in male eastern grey kangaroos’ number of preferred female associates...... 45 Table 2.5. Estimates and standard errors in the linear model used to test for differences in male eastern grey kangaroos’ top 10 score...... 45
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Table 3.1. Microsatellite characteristics of eastern grey kangaroos found in our site of Sundown National Park, QLD, in 2010-2016...... 67 Table 3.2. Possible correlates of reproductive success of male EGKs. Data are for males that were adults in 2014 and included in statistical analyses (n = 25)...... 68 Table 3.3. Estimates and standard errors in the three generalized linear models used to explain male eastern grey kangaroos’ reproductive success in our site over two years...... 69 Table 3.4. Estimates and standard errors in the generalized linear mixed model used to explain the probability of male-female dyads sharing an offspring...... 70 Table 4.1. Estimates and standard errors in the linear mixed model used to explain male eastern grey kangaroos’ faecal testosterone metabolite levels...... 93 Table 4.2. Estimates and standard errors in the linear mixed model used to explain male eastern grey kangaroos’ faecal glucocorticoid metabolite levels...... 96 Table 5.1. Correlations among predictors that varied among individuals ...... 134 Table 5.2. Correlations among predictors that varied with time ...... 134 Table 5.3. Estimates and standard errors in the mark-recapture model used to explain the survival probability of female eastern grey kangaroos ...... 135
List of supplementary tables Table S4.1. Principal component analysis of males’ competition and courtship behaviours……. 124 Table S4.2. Estimates and standard errors in the linear mixed model used to explain male eastern grey kangaroos’ fT levels, with top 10 score as a predictor……………………………………… 124 Table S5.1. Estimates and standard errors in the mark-recapture model used to explain the sighting probability of female eastern grey kangaroos……………………………………………………. 147
List of abbreviations AIC: Akaike information criterion ANOVA: Analysis of variance E: East EGK: Eastern Grey Kangaroo FID: Flight initiation distance fGC: Faecal glucocorticoid fT: Faecal testosterone GC: Glucocorticoid GLM: Generalized linear model xvi
GLMM: Generalized linear mixed model GPS: Geographical positioning system Ha: Hectares HWI: Half weight index ID: Identity kUD: Kernel utilisation distribution LMM: Linear mixed model NP: National park QLD: Queensland S: South SE: Standard error T: Testosterone YAF: Young-at-foot
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Chapter 1
Chapter 1 – General Introduction
The social lives of mammals As outlined in Hinde’s (1976) framework of animal societies, the pattern, content and quality of interactions form the relationships between individuals, and these relationships make up the social structure of a species. Mammals exhibit a wide range of social systems (Clutton-Brock 2016). Individuals may live a solitary lifestyle; for example, male rhinoceroses (Rhinocerotidae) tend to be solitary, with interactions between adults of the Asian species limited to mating (Hutchins and Kreger 2006). Other species, such as meerkats (Suricata suricatta), live in groups with stable group compositions over time, with only rare occurrences of individuals leaving or joining groups (Drewe et al. 2009). Species’ grouping dynamics can be characterised partly by their fission-fusion dynamics - the extent to which groups or individuals separate (fission) or join together (fusion) - with species varying from having highly cohesive to highly flexible group membership (Aureli et al. 2008).
Mammals show varying degrees of fission-fusion dynamics, likely affected by individual choice and driven at least partly by genetic relatedness (e.g., African savannah elephants, Loxodonta africana) (Archie et al. 2006), dominance rank (e.g., spotted hyena, Crocuta crocuta) (Smith et al. 2007), social preferences (e.g., wild giraffes, Giraffa camelopardalis) (Carter et al. 2013b), and/or space-use (e.g., eastern grey kangaroo, Macropus giganteus) (Best et al. 2014). In some species, individuals live in large stable communities or small family units that are relatively stable over time, while still showing daily group composition changes. For example, chimpanzees (Pan troglodytes) and bonobos (Pan paniscus) live in communities of up to 150 and 75 individuals respectively, but forage and move in subgroups with continuously changing membership (reviewed in Grueter et al. 2012). African elephants live in stable core groups with an average of 6 to 10 members; individuals from this core group may separate for short periods or the core group can temporarily fuse with two or more other ‘families’ to form large social groups (Buss 1961, Archie et al. 2006). Other species do not live in stable groups, but still exhibit structed association patterns. Individual bottlenose dolphins (Tursiops truncatus) associate in temporary groups, with some males having strong and long-term (up to seven years) social bonds driven in part by kinship, and research also finding that females show social preferences that are stable over several weeks (Smolker et al. 1992, Parsons et al. 2003, Frère et al. 2010, Smith et al. 2016). Eastern grey kangaroos (EGKs)
1 Chapter 1 associate in temporary feeding groups, with females showing preferences for particular females that are only partly driven by genetic relatedness (Best et al. 2014).
Grouping is a social strategy that has fitness benefits and costs, with the patterns of species’ and populations’ grouping structure dependent upon these trade-offs. Group-living species tend to have a reduction in their predation risk, with individuals able to allocate less time to vigilance behaviour and more to foraging when in larger groups (Treisman 1975, Brown and Brown 1987, Jakob 1991, Molvar and Bowyer 1994, Mappes et al. 1995, Blumstein and Daniel 2003, Kuukasjarvi et al. 2004). Group-living animals may engage in cooperative behaviours, which can provide direct or kin-related fitness benefits to individuals, yet the evolution of cooperation is not yet fully understood (Packer and Ruttan 1988, Creel and Creel 2015, Dillard and Westneat 2016, Taborsky et al. 2016). Individuals’ short-term survival can be strongly dependent on others, such as in vampire bats (Desmodus rotundus) that rely on reciprocal altruism, through sharing blood-meals, to avoid starvation (Denault and Mcfarlane 1995, Carter and Wilkinson 2015, Carter et al. 2017). Furthermore, when living in groups, individuals can learn from others (i.e. social learning) through observation and imitation (reviewed in Heyes 1994, Galef and Laland 2005). Group living also incurs fitness costs. In addition to information, harmful pathogens or parasites may also be spread between individuals (Altizer et al. 2003, Bull et al. 2012, VanderWaal et al. 2014, Kappeler et al. 2015). A meta-analytic review of the social transmission of parasites found that individuals in larger groups had greater parasite intensity and prevalence, suggesting that being in larger groups can incur greater costs (Patterson and Ruckstuhl 2013), yet these costs vary among species and the effect of group size on parasite infection only appears to be a strong predictor in species that live in large aggregations (Rifkin et al. 2012). Despite increasing the risk of pathogen transfer, recent research has found that exposure to low doses of pathogens and commensal microbes from group living can increase individuals’ resistance and tolerance to pathogens (Ezenwa et al. 2016). When living in groups, individuals may be exposed to greater competition for resources, harm from aggressive interactions with conspecifics, and experience social stress that can make them more disease-prone (Beauchamp 1998, Creel 2001, Proudfoot and Habing 2015, Dantzer et al. 2017, Hintz and Lonzarich 2018). However, these costs may be offset by the benefits of having strong social relationships, which I discuss further later in this chapter. The trade-offs between the costs and benefits of sociality varies among species and populations, leading to the great diversity in mammalian social systems we see today.
2 Chapter 1 Sociability, a broad term that describes aspects of individuals’ propensity to seek or avoid the presence of conspecifics, and the kinds of relationships that they form, is considered a dimension of animals’ personality traits (Réale et al. 2007). Studies measure sociability in different ways depending on the questions of interest and the social structure of the species. These aspects of sociability can be broadly separated into two dimensions: the gregariousness of individuals and their propensity to form strong relationships with conspecifics. The extent of individuals’ tolerance of conspecifics is considered a measure of their sociability (van Schaik and Pradhan 2003). A study on the common lizard (Lacerta vivipara) estimated individuals’ social tolerance/ sociability by measuring their attraction towards the scent of conspecifics (Cote et al. 2008). Individuals’ sociability has also been measured as their average group size and distance to nearest neighbour (Sibbald et al. 2005, Cote et al. 2012, Menz et al. 2017). Integration in the social network, estimated through various social network metrics of centrality, is a dimension of sociability that has been linked to individuals’ fitness (Barocas et al. 2011, Gilby et al. 2013). The strength of relationships among individuals, measured from rates of affiliative interactions or associations, has also been used as a measure of sociability, with studies examining how the strength of relationships between dyads relates to other aspects of their relationships, or how individuals’ top social bonds are linked to their fitness (Schulke et al. 2010, Silk 2010, Carter et al. 2013a).
Fitness consequences of social bonds Despite a great understanding of the consequences of group living, research on the fitness consequences of investing in strong social relationships is still an emerging field. In humans, individuals who have a strong social support network live longer, and friendship has even been dubbed ‘the medicine of life’ (Alberts 2010, Uchino et al. 2018). An experimental study by Cohen et al. (1997) linked sociality with infection rates; participants were exposed to cold viruses, and those who had a high diversity of social ties had a lower risk of infection and less cold symptoms than individuals with a less diverse social network. Both quantity and quality of social relationships matter when considering their health benefits (Umberson and Montez 2010). A seminal meta- analytic review of 148 long-term studies on humans showed that social relationships and social integration are strongly correlated with survival, with a 50% and 91% increased likelihood of survival as a function of social relationships and social integration, respectively (Holt-Lunstad et al. 2010). Social isolation increases the risk of incident coronary heart disease and stroke, and increases the risk of mortality in humans by around 30% (Holt-Lunstad et al. 2015, Valtorta et al. 2016). The patterns linking social relationships to health are especially important for men, as studies have found that social isolation is a stronger predictor of mortality for men than for women
3 Chapter 1 (Shye et al. 1995), however no differences between the sexes were found in the meta-analytic review of the link between social isolation and coronary heart disease and stroke (Valtorta et al. 2016). Even having weak social ties can benefit people, as a study found that people tend to be more physically active when they engage with others, and engaging with a diversity of social ties (i.e. both weak and strong social relationships) is linked to better mood (Fingerman et al. 2019).
The health and fitness benefits of social relationships have also been demonstrated in other mammals. Female chacma baboons (Papio hamadryas ursinus) with stronger and more stable friendships were found to have increased longevity compared to females with weaker and less stable social bonds (Silk 2010). Long-term studies on this species also showed that strong female social relationships were associated with higher offspring survival (Silk et al. 2003, Silk et al. 2009). In a study of captive western lowland gorillas (Gorilla gorilla gorilla), extraversion was a strong predictor of individuals’ survival (Weiss et al. 2013). Social integration was a significant predictor of both birth rates and offspring survival rates in unrelated female feral horses (Equus caballus), and a study in which horse groups were disrupted found that more social juvenile horses had a higher probability of survival, providing clear evidence that individuals’ social relationships and social characteristics can have fitness benefits in this species (Cameron et al. 2009, Nuñez et al. 2015). However, a study on male bottlenose dolphin calves found that more sociable calves had lower survival, and a study on yellow-bellied marmots (Marmota flaviventer) found that more social individuals had greater mortality, suggesting that the link between social relationships and survival may differ depending on species’ social systems (Stanton and Mann 2012, Yang et al. 2017, Blumstein et al. 2018).
Male-male social bonds are rarer than female-female bonds, likely because males are not only in competition for food and other resources, but often also for mates (Van Hooff and Van Schaik 1994). Male-male affiliative relationships have been examined most thoroughly in species that exhibit male alliances and coalitionary aggression, with evidence of reproductive benefits from these associations. Male chimpanzees display coalitionary alliances, whereby two or more males jointly direct aggression at an opponent (Gilby et al. 2013). Using social network metrics derived from observations of male coalitions, Gilby et al. (2013) found that male chimpanzees that were centralized in the coalition social network sired a greater number of offspring and had a higher future dominance rank. In alliances between Camargue horses, the dominant individual in a pair achieved most of the matings, while the subordinate male engaged in aggressive behaviour twice as often to protect the harem. Despite the subordinate male being more at risk for less reward
4 Chapter 1 compared to the dominant male, alliances were beneficial to both parties, as dominants received help with fights and subordinates sired more offspring than males that adopted a sneak-mating strategy (Feh 1999). Formation of alliances between male bottlenose dolphins is a mating strategy believed to benefit males’ reproductive success, due to improved mate guarding abilities and female preference for coordinated behaviours (Krutzen et al. 2004). The reproductive success of male Indo- Pacific bottlenose dolphins (Tursiops aduncus) is correlated with alliance size, providing insight into the benefits of these close male-male social bonds (Wiszniewski 2011). Similar patterns are also found outside of mammals. Although the top three ranked males in a given lek of wire-tailed manakins (Pipra filicauda) sired over 80% of offspring, males that were more socially connected with other males (mostly during coordinated displays to attract females) sired a relatively larger number of offspring than less connected males (Ryder et al. 2009).
Intersexual social bonds can also provide health and fitness benefits, even in non-monogamous species living in multi-male multi-female groups. Female primates can benefit from having strong social bonds with males by receiving protection from predators, harassment, or infanticidal males (Smuts 1985, Palombit 1999, Nguyen et al. 2009, Haunhorst et al. 2017). Assamese macaques (Macaca assamensis) form strong and enduring intersex bonds, with females benefitting from these strong relationships with males; females receive agonistic support, experience reduced harassment, and have greater feeding efficiency when with their close male partner (Haunhorst et al. 2016, Haunhorst et al. 2017). The fitness benefits to males of having strong social bonds with females have not been as clear, with studies on primates either finding no clear evidence of benefits to males (Hill 1990, Manson 1994, Nguyen et al. 2009), or slight evidence that males may benefit from increased reproductive success through caring for the offspring that they have most likely sired (Moscovice et al. 2010, Baniel et al. 2016) or increased probability of mating with their close female partner (Ménard et al. 2001, Kulik et al. 2012, Ostner et al. 2013). Nguyen et al. (2009) suggest that males may be receiving other benefits from their relationships with females, such as grooming or an unidentified service, or perhaps that other females may find males that protect infants more attractive and thus increase that male’s mating success with other females.
Evidence that sociability can reduce stress levels A stressful event activates the hypothalamic-pituitary-adrenal axis, whereby adrenaline is released into the circulatory system, increasing heart rate, blood pressure, and breathing rate (Sands and Creel 2004). Adrenaline stimulates the adrenal cortex to release glucocorticoids (GCs), which divert energy from basic physiological processes for immediate use. Although acute stress responses can
5 Chapter 1 promote survival, the stress response is maladaptive when chronically stimulated, with deleterious long-term effects. Heightened GC levels from stress may suppress the immune system, cause tissue damage, compromise growth and reproduction, and in humans, are linked to increased blood pressure and vascular hypertrophy, among other health issues (Munck et al. 1984, Moore and Zoeller 1985, Dobson and Smith 2000, Schreck et al. 2001, Troxel et al. 2003, Schneiderman et al. 2005, Cohen et al. 2007, McEwen 2008). In birds, findings on the link between GC levels and fitness have been mixed. A study where black-legged kittiwakes (Rissa tridactyla) were treated with subcutaneous corticosterone (the main GC in birds) implants found that treated birds had lower survival than control birds, suggesting that the treated birds may have experienced negative health consequences from heightened GC levels (Goutte et al. 2010). The opposite trend was found in juvenile Swainson’s thrush (Catharus ustulatus), with higher blood corticosterone levels measured at the nestling stage predictive of greater survival at the post-fledgling stage; the main cause of mortality in juveniles is predation, and it is believed that individuals with higher GC levels were more active and thus better able to avoid predation (Rivers et al. 2012). Female European starlings (Sturnus vulgaris) exposed to experimentally induced stressors had lower reproductive success, but these females also had lower baseline corticosterone levels, showing a complex link between stress and GCs in animals (Cyr and Romero 2007). In primates, heightened GCs have been linked to higher parasitic infection, and lower reproduction and survival, but research testing the direct link between GCs and fitness is lacking (reviewed in Beehner and Bergman 2017).
The social buffering hypothesis suggests that social connections act as buffers to minimize the physiological and psychological reactions to stressful events (Cohen 2004). Social relationships may help mediate individuals’ stress levels by inhibiting or limiting individuals’ adrenal responses to stressful stimuli, thereby preventing or minimizing the negative impacts of chronically elevated stress hormone levels (Hennessy et al. 2006). This social buffering of the stress response has been shown in rodents, non-human primates, and humans (Kikusui et al. 2006, Hennessy et al. 2009), with research in the last decade finding evidence for buffering effects of social relationships in farm animals (Rault 2012, Kanitz et al. 2014, Gutmann et al. 2015, Costa et al. 2016). Social support and strong social bonds are negatively correlated with perceived stress in humans and stress hormone levels in other primates (Cohen and Wills 1985, Cohen et al. 1992, Boey 1999, Engh et al. 2006, Shutt et al. 2007, Wittig et al. 2008, Young et al. 2014, Wittig et al. 2016), and being socially isolated induces heightened stress responses in a diversity of gregarious species (Cockram et al. 1994, Hennessy et al. 2000, Weiss et al. 2004, Toth et al. 2011). In female chacma baboons, GC levels increased after the loss of a relative from predation, and females compensated for this loss by
6 Chapter 1 increasing both their numbers of grooming partners and their grooming rates (Engh et al. 2006). A subsequent study on this population examined females’ stress levels before, during and after a period of male dominance hierarchy instability, with females showing increased GC levels at the beginning of the period, and higher than normal levels until three weeks after the alpha position was resolved (Wittig et al. 2008). Females decreased their number of grooming partners during the period of instability but focused more on preferred partners, which was correlated with a subsequent decrease in GC levels; moreover, females with few but strong grooming partners before the period of instability had a lower initial increase in GC levels than those with a higher grooming partner diversity, suggesting that close bonds may reduce females’ stress responses to stressful events (Wittig et al. 2008). A direct benefit to the individual being groomed is the removal of ectoparasites; however, Aureli and Yates (2010) demonstrated that the groomer also benefits, as shown by the reduction in anxiety and aggressive tendencies of groomers in crested black macaques (Macaca nigra) post-grooming. Social buffering has also been found in male-male relationships in a species where males can compete fiercely for females; male Barbary macaques (Macaca sylvanus) with strong social bonds with their top three male partners were found to have lower GC levels in response to social and environmental stressors (Young et al. 2014). The stress-mediating effects of social partners have also been examined in experimental trials using guinea pigs, showing that periadolescent guinea pigs exposed to novel environments had lower plasma cortisol levels when with their mother or an unfamiliar female than when isolated (Hennessy et al. 2000).
In vertebrates, stress levels can be estimated by measuring blood GC or faecal GC metabolites. Estimating individuals’ stress hormone levels by measuring faecal GC has the advantage of being non-invasive, thereby avoiding research-induced stress on animals due to manipulations required in the collection of blood samples (Dehnhard et al. 2001). Faecal GCs are indicative of stress levels over a longer time period than blood metabolites, thus dampening the evidence of responses to short-term stressful events (Millspaugh and Washburn 2004). Moreover, large amounts of data can easily be collected using faecal samples, since potentially time-consuming and costly capture and blood sampling are not required. Roe deer (Capreolus capreolus) exposed to stressors, including capture, manipulation and transportation, showed a large and significant increase in faecal metabolites (Dehnhard et al. 2001). Spotted hyenas showed an increase in faecal GC levels following translocation and agonistic social interactions (Goymann et al. 1999). Shutt et al. (2007), studying the link between sociability and stress, examined faecal GC levels and found a strong negative correlation between stress levels and amount of grooming given in Barbary macaques.
7 Chapter 1 Glucocorticoids are metabolized in the liver and either re-absorbed into the blood or excreted via urine and/or faeces (Dehnhard et al. 2001). The time lag between a stress response and the resulting increase in faecal GC depends on digesta passage rates (ie. the rate at which materials move in the gut), which is often estimated by mean retention time, the duration that materials remains in the gut (Palme et al. 1996). Species differ in the amount and content of blood GCs, the metabolism of GCs in the liver, their gut microbes, and their digesta passage rate, thus preventing the direct comparison of faecal GCs between species (Palme et al. 1996, Millspaugh and Washburn 2004). Due to these interspecific differences, the use of faecal GCs to examine stress responses need to be validated for each species.
The roles of testosterone in social relationships Testosterone is considered to be a social hormone, as it both affects and is affected by individuals’ social behaviours, including their competitive and reproductive behaviours (Eisenegger et al. 2011, Adkins-Regan 2013). Testosterone is strongly linked to dominance rank, with more dominant individuals having higher testosterone levels and individuals with higher testosterone levels having increased dominance rank (Rose et al. 1971, Beehner et al. 2006, Booth et al. 2006, Arlet et al. 2011, Kalbitzer et al. 2015). Testosterone increases in response to winning a fight, which is believed to be the underlying mechanism driving the winner’s effect (Oliveira et al. 2009). An experimental study on Mozambique tilapia (Oreochromis mossambicus) treated winners with an anti-androgen and losers with testosterone, finding that the winner’s effect was no longer present in treated winners, but the treatment on losers had no effect on their chance of winning their subsequent fight (Oliveira et al. 2009). Males’ testosterone levels increase during the breeding season, a trend which, in some species, can be partly explained by the challenge hypothesis – a hypothesis that suggests males’ testosterone levels increase in response to challenges from other males that threaten their reproductive success (Wingfield et al. 1990). This review provided examples from birds, fish, and reptiles, but there is evidence for the challenge hypothesis in mammals too (Woodroffe et al. 1997, Cavigelli and Pereira 2000, Ostner et al. 2002, Goymann et al. 2003, Muller and Wrangham 2004, Bales et al. 2006, Cristobal-Azkarate et al. 2006). Resident mantled howler monkey males had higher T levels when more solitary males were present, as these males posed a reproductive threat to resident males (Cristobal-Azkarate et al. 2006). In spotted hyenas, T levels were higher in males that were defending females than in males that were not doing so, but T levels were not related to their social ranks (Goymann et al. 2003). A study on the faecal testosterone levels of male ring-tailed lemurs (Lemur catta) found that prior to females’ oestrous, there was no link between males’ testosterone and aggression, whereas during females’
8 Chapter 1 oestrous when competition would directly affect males mating success, testosterone and aggression were strongly correlated, supporting the challenge hypothesis (Cavigelli and Pereira 2000). Heightened testosterone is beneficial in a reproductive and competitive context, but has trade-offs in terms of males’ health (Muehlenbein and Bribiescas 2005, Mills et al. 2009) and their parental investment.
Low testosterone is linked to pair-bonding and greater paternal investment, and thus males’ testosterone levels may be the result of the trade-off between their competitive and nurturance behaviours (Hegner and Wingfield 1987, Ketterson and Nolan 1999, van Anders et al. 2011). It is believed that low testosterone can help build and maintain pair-bonds (Farrelly et al. 2015, Dibble et al. 2017), with monogamous males tending to have smaller testes and lower testosterone levels than polygynous males (Dixson 1997, Klein and Nelson 1998). A meta-analytic study on humans, which included an analysis of men’s commitment to their partner and involvement in the activities of their children, found both large effect sizes and significant relationships that supported the link between low testosterone and pair-bonding and paternal care in (Grebe et al. 2019). Male superb fairywrens (Malurus cyaneus) treated with testosterone decreased their nestling feeding rate, showing that high testosterone can negatively impact parental care. However, other factors interplay in this relationship, as measures of natural levels of testosterone in this species did not differ between dominant individuals and helpers, despite dominant males decreasing their nestling care with increasing number of helpers (Peters et al. 2002). The behavioural effects of testosterone are complex, with some bird species showing insensitivity to testosterone treatment, and environmental factors also influencing the link between hormones and behaviour (reviewed in Lynn 2008). We do not know whether testosterone is linked to males’ extended (outside of the pair bond and infant care setting) social relationships. A hypothesis, termed the steroid/peptide theory, extends the competition/ nurturance trade-off to include males’ social relationships with other individuals (van Anders et al. 2011). Studies on the link between males’ testosterone and social relationships in species that do engage in monogamy or paternal care are needed to determine whether low testosterone promotes nurturance in other contexts.
Studying social relationships in mammals Recent technical advances in social network analyses allow a great depth of information to be extracted from relatively simple social association and interaction data (Wey et al. 2008, Whitehead 2008). The strengths of relationships between dyads, measured from associations or rates of interactions, can be the foundation for analysing network parameters and provide insight into
9 Chapter 1 individuals’ social integration (Cameron et al. 2009, Gilby et al. 2013, Poirier and Festa-Bianchet 2018), the community structuring of the network (Fortuna et al. 2009, Best et al. 2013b, Zanardo et al. 2018), and overall network connectivity for disease propagation/ information flow (Fenner et al. 2011, Rimbach et al. 2015, Webber et al. 2016, Sah et al. 2018), among others (Whitehead 2008).
Interactions are the fundamental element of social structure, but are not always possible to observe, as species may be cryptic or visible interactions rare. Social interactions, such as touching, grooming, and coalitionary aggression have been measured to assess the frequency of interactions between individuals and thus the strength of the dyad’s relationship. In studies of primates, a composite score combining multiple interaction types is often used to obtain a holistic view of a pair’s relationship (Silk et al. 2009). Instead of observing interactions, when that is difficult or they are rare, associations between identified individuals may be used as a proxy to examine social relationships, as individuals that associate strongly have more opportunities to interact (Whitehead and Dufault 1999). Methods of determining associations are species specific, with individuals’ shared group membership or spatial distance the most common methods of estimating the strength of associations between dyads in species that frequently change group membership (Whitehead 2008). These grouping methods can be validated by showing that behavioural synchrony occurs among group members (Croft et al. 2008), but with large enough data sets, slightly conservative or liberal estimates of group size and membership will have little to no effect on subsequent analyses of network parameters (Whitehead 2008). There are different association indices that can be used to determine the strength of association between pairs of individuals, but they all measure the proportion of time that dyads spend together versus apart (Cairns and Schwager 1987).
Male reproductive strategies in species with high fission-fusion dynamics Although dominance tends to be strongly linked to reproductive success in species with male dominance hierarchies, the most dominant male may not be able to monopolise matings, as females can be spread out in space and have synchronised oestrous cycles, and other traits than dominance can influence males’ mating success (Wroblewski et al. 2009, Dubuc et al. 2011, Rioux-Paquette et al. 2015). Even though male white-tailed deer (Odocoileus virginianus) establish a dominance hierarchy pre-rut, spatial memory and mobility are important in males’ ability to locate females in oestrous and thus be reproductively successful (Foley et al. 2015). As discussed earlier, males’ propensity to form social relationships can also impact their reproductive success. Male chimpanzees’ reproductive success is strongly linked to their dominance rank, but as their centrality in the coalitionary aggression network is linked to their reproductive success, males’ ability to
10 Chapter 1 strategically choose coalitionary partners would also provide reproductive advantages (Wroblewski et al. 2009, Gilby et al. 2013).
Especially in species with high fission-fusion dynamics, we would expect that the frequent movement of individuals between groups would prevent dominant males from monopolising groups of females (i.e. female defence polygyny). Instead, males can defend areas where females are likely to visit (resource defence polygyny) or engage in scramble competition polygyny (Ostfeld 1987, Sundaresan et al. 2007, Foley et al. 2018). An example of resource defence polygyny can be found in Grevy’s zebra (Equus grevyi); females form unstable social groups and males defend areas with resources (e.g. water and high quality forage) to increase their chances of mating with females that frequent their territories (Sundaresan et al. 2007). White-tailed deers’ mating strategy is categorised as scramble competition, with young and post-prime males siring offspring, and dominance only being important when multiple males locate a female in oestrous (Foley et al. 2015, Foley et al. 2018). Reproductive strategies are not mutually exclusive, as males can exhibit multiple strategies. For example, some male proboscis bats (Rhynchonycteris naso) are territorial during nights and defend areas that females can frequent, a system that resembles resource defence polygyny, but during the day, the bats form cohesive multi-male multi-female groups with the males engaging in female defence polygyny (Günther et al. 2016). Particular strategies that males adopt can also change with age, with males’ relative dominance and thus ability to compete for females increasing when males approach their prime (Rasmussen et al. 2007).
Study species: eastern grey kangaroos My study species, the eastern grey kangaroo (EGK), is a macropod that is among the largest of the marsupial species. The distribution of the species ranges between the inland plains and the eastern coast of Australia from Cooktown in the north to eastern Tasmania in its southernmost range (Poole 1982). This kangaroo lives in scrubland, woodlands, and forests, and can also inhabit open pastures near human developments, including farmlands. EGKs actively forage in areas with open undergrowth, feeding preferentially on high-protein, green, soft grass leaves (Taylor 1980, Taylor 1984). EGKs are relatively drought tolerant, as their foregut fermentation is water efficient and they can highly concentrate their urine; however, they are not as adapted to arid landscapes as red kangaroos (Macropus rufus) and must drink water to meet their thermoregulatory requirements (Caughley 1964b, Dawson et al. 2000).
11 Chapter 1 Studies of EGKs in captivity inform us that females attain sexual maturity at 18 months, while males attain sexual maturity at approximately 3.5 years, with maximum spermatozoa activity reached at around 4 years (Poole and Catling 1974). Females can breed year-round, with a peak in matings in the summer between September and March (Poole and Pilton 1964, Poole and Catling 1974, Jarman and Southwell 1986). After mating and successful egg fertilisation, females can undergo embryonic diapause, effectively delaying the development of the blastocyst (Poole and Catling 1974). The gestation period of kangaroos varies by geographic location, with EGKs in Queensland having an average gestation of 36.7 days (Kirkpatrick 1965). Young remain in their mother’s pouch for approximately 10.5 months (319 +/-18 days); from permanent pouch emergence until weaning, young-at-foot remain close to their mothers (Poole 1975, Poole et al. 1982). Kangaroos show strong site-fidelity, only dispersing short distances, with males more likely to disperse than females (Zenger et al. 2003, Coghlan et al. 2017). Males appear to be more prone to road mortality due to their greater dispersal rate, as a study found that most kangaroo road kill (14 of 19 identified EGKs) were male (Coulson 1997a).
EGKs are highly gregarious, often aggregating in feeding groups of 2 to over 20 individuals (Jarman 1987). EGKs have high fission-fusion dynamics, with frequent changes in group composition each day (Carter et al. 2009a). It was previously believed that kangaroos associated at random (Caughley 1964a, Grant 1973), but structured social organization was observed once detailed studies examining the grouping patterns of known individuals were undertaken (Jaremovic and Croft 1991). Female EGKs have non-random associations and exhibit social preferences and avoidances that are only partially explained by genetic relatedness (Jarman 1994, Carter et al. 2009a, Best et al. 2013b, Best et al. 2014). EGKs do not exhibit complex social behaviours, such as allogrooming as a social exchange of favours, caring for others’ young, or cooperative hunting, as seen in other social species (Jarvis 1981, Boesch 1994, Aureli and Yates 2010).
EGKs are polygynous and have marked sexual dimorphism, with males having indeterminate growth (Jarman 1983), and the largest males twice the size of adult females (Poole et al. 1982, Jaremovic and Croft 1991, Miller et al. 2010). The behaviours most commonly observed in EGKs are feeding, vigilance, and lying down (Jarman 1987), with adults also engaging in reproductive behaviours and males involved in aggressive encounters (Coulson 1997b). Only sexually mature males engage in acts related to sexual contexts (Coulson 1997b), although younger males may also exhibit interest in females. Males check females’ oestrous status by sniffing their cloaca and urine (Coulson 1997b), and may remain with females for prolonged periods before and after copulation
12 Chapter 1 (i.e. mate guarding) (Jarman and Southwell 1986). According to Coulson (1997), only adult males exhibit behaviours associated with male-male aggression; however, juveniles play fight and exhibit similar behavioural patterns (Croft and Snaith 1990). The outcomes of aggressive encounters are indicative of males’ dominance rank, and more dominant males can supplant subordinates from females (Jarman and Southwell 1986), thus ensuring they have priority access to females in oestrous. More dominant males have been found to have greater reproductive success, yet reproductive skew is lower than expected given the strength of males’ dominance hierarchy and the long breeding season (Miller et al. 2010, Rioux-Paquette et al. 2015). Most male EGKs move more and have larger home ranges than females, likely to increase exposure to numerous females; however, males differ widely in their ranging patterns (Clarke et al. 1989, Jaremovic and Croft 1991).
Study site and population My study examined the fitness consequences of sociability in wild EGKs. My field research was conducted in a 37.4 ha study site within Sundown National Park (NP), Queensland, Australia (28°55’03’’S, 151°34’46’’E). The study area was a mosaic of open grassy areas and mixed dry forests, consisting of mostly silver-leaved ironbarks (Eucalyptus melanophloia) and cypress pines (Callitris intratropica). Most observations were recorded in the open grassy areas, where the EGKs grazed during the early morning and late afternoon, with some recorded in the margins of the forested areas. The site was in a valley, where the Severn River flowed through the south side. The kangaroos were not restricted in their movement within and outside of my study site. EGKs in Sundown NP had few predators, since dingoes (Canis familiaris), their natural predator, have been mostly exterminated in the area. There were regular sightings of foxes (Vulpes vulpes), and wedge- tailed eagles (Aquila audax), which are predators of young EGKs (Jarman and Coulson 1989).
There were approximately 300 identified EGKs found permanently or occasionally in my study site. Since these wild kangaroos moved freely within and outside of my study site, there was extensive variation in the observation rates of individuals. The kangaroos were quite habituated to humans, as researchers had been present in the site since September 2009, and the kangaroos could be approached to within 2-5 metres. Previous research in the site included studies on kangaroos’ feeding and vigilance behaviour, personalities, genetic relationships, and social relationships (Favreau et al. 2010, Best et al. 2013a, Best et al. 2013b, Dannock et al. 2013, Edwards et al. 2013, Best et al. 2014, Best et al. 2015, Favreau et al. 2015, Coghlan et al. 2017, Menz et al. 2017). Kangaroos were identified using unique features (e.g. scars, ear rips, coat markings) or an
13 Chapter 1 amalgamation of characteristics (e.g. coat colour, shape of ears) that provide information on the identity of individuals (Jarman et al. 1989, Carter et al. 2009b, Best et al. 2014). Genetic testing confirmed that researchers were able to successfully recognise individual kangaroos (Menz 2015).
Thesis outline, objectives, and significance The overall objective of this study was to explore the fitness consequences of sociability in EGKs. Specifically, I examined the relationships between sociability, stress, testosterone, dominance rank, and reproductive success in males and survival and sociability in female kangaroos. I personally collected data for this project from October 2013 to February 2017, and also used long-term data collected by previous researchers in the site (Emily Best, Clementine Menz, Natalie Freeman). There are six chapters in this thesis, including this general introduction, four data chapters written as manuscripts for publication, and a general discussion, with overlap among them unavoidable due to the thesis being written as a set of manuscripts. The four manuscripts are intended for publication but have not yet been formatted for specific journals.
In Chapter 2, I explore EGK males' social patterns to determine whether there could be different social strategies that males adopt to maximise their mating success. Specifically, I assess whether there were age-related changes in males’ roaming, gregariousness, and social association patterns. In this chapter, I also explore whether males’ social association patterns differed non-randomly and explore males’ agonistic interactions and dominance ranking.
Chapter 3 explores the correlates of males’ reproductive success. I assess whether males’ overall sociability predicted their paternity success, and whether the strengths of male-female social associations were linked to their probability of having an offspring together.
I examine the correlations between the social relationships and testosterone and stress hormone levels of male EGKs in Chapter 4. In this chapter, I assess whether the stress-buffering hypothesis and challenge hypothesis were supported in male EGKs.
In Chapter 5, I examine the correlates of female kangaroos’ survival. Using six years of data collected on female kangaroos from the beginning of 2010 to the end of 2015 (Best et al. 2013b, Best et al. 2014, Menz et al. 2017), I created a mark-recapture model to examine both individuals’ traits (gregariousness, strength of social relationships, boldness, body condition) and environmental conditions (rainfall, temperature) as possible predictors of females’ probability of survival.
14 Chapter 1
In the general discussion, Chapter 6, I integrate the findings of my study and propose suggestions of future studies. I focus on two possible reasons that kangaroos do not exhibit a strong positive link between their strength of social relationships and their fitness. I suggest that, in other species, cooperative behaviours and affectionate touch in adults are the main drivers of the fitness benefits of investing in strong social relationships with particular individuals.
This study will shed light into the fitness consequences of having strong social relationships in a species with high fission-fusion dynamics. Aureli et al. (2008) highlight the importance of examining species’ spatiotemporal variation in cohesion, group size and group membership to investigate whether species’ degrees of fission-fusion dynamics relate to their socio-ecological conditions or cognitive abilities. Most studies exploring the links between sociability and stress have been limited to laboratory studies with rodents, and research on the complex social systems of primates. Therefore, studies on the relationship between sociability and stress levels in a diversity of taxa will be invaluable in gaining insight into the underlying mechanisms driving these correlations, and will increase our understanding of the social buffering effect and the benefits of close bonds in social species. Furthermore, studies exploring the consequences of social bonds in males are limited and have mostly focused on species with complex social organisation and behaviours. EGKs do not exhibit complex forms of social interactions such as allogrooming as a social exchange, alloparental care, alliances, or cooperative aggression, and thus the examination of the fitness consequences of sociability in EGKs is not confounded by complex interactions among individuals. To understand the evolution of complex social behaviours, we must understand and cross-compare the fitness benefits of social bonds in a wide range of species (Ryder et al. 2009), and this study, along with other research on the costs and benefits of male’s social patterns, may help in understanding the evolution of cooperative behaviours, enduring social bonds, and cognition in mammals. Studying the interindividual variation in sociability within species can help us understand the fitness consequences of individuals’ sociability, helping us understand the impact of being gregarious versus more solitary, having weak versus strong social bonds, and having many versus few preferred associates. Understanding relationships among conspecifics can contribute to the effective implementation of conservation (Sutherland 1998, Somers et al. 2008, Snijders et al. 2017), and farming practices (Keeling 2001), and help us gain a deeper understanding of the social lives of animals.
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32 Chapter 2
Chapter 2 – How do male eastern grey kangaroos’ (Macropus giganteus) social and space use patterns change with size?
Abstract In mammals with male dominance hierarchies, large and dominant males tend to have higher reproductive success. However, smaller and more subordinate males are often still able to mate with females by adopting different reproductive tactics. One of the factors linked to males’ reproductive success can be their social behaviours, which may change with age to maximise males’ mating opportunities. Our study examined potential factors that could be linked to male eastern grey kangaroos’ (Macropus giganteus) reproductive success by determining how males’ social patterns and space use differed among size classes. We studied a wild population of kangaroos at Sundown National Park in Queensland, Australia. We collected daily group association data for 12 days each month for 26 months. Our analyses of space use focused on a subset of 15 adult males for whom we had extensive data to analyse their space use within our site and preferred associates (i.e. females that males associated with more frequently than expected from their shared space use). We found that male kangaroos’ space use and social association patterns differed among size classes. Large males utilised a larger area within our site and were exposed to more females overall, a strategy that is likely more energetically costly than those used by small males. Small males had stronger relationships with some females than did larger males, shown by their higher association scores with their top 10 female associates. Small males’ strong associations with particular females, even if due to their more limited movements and home ranges, may help increase their mating opportunities. A strong association with a female could increase the chance of a small male being present when one of their female associates is in oestrus without there being a more dominant male present to supplant him. The patterns we found may reflect differences in males’ reproductive strategies with age and relative dominance.
Introduction In mammals, males usually compete for access to reproductive females (Clutton-Brock 2017). In polygynous species, traits that increase males’ competitive ability in male-male interactions are selected for, with males’ shape, size, colouring, and other morphological features influenced by both female choice and male-male competition (Emlen and Oring 1977, Andersson 1994). Sexual size dimorphism is common in mammals, with males being larger than females, and the largest males achieving the greatest number of copulations (Trivers 1972, Jarman 1983). When females are
33 Chapter 2 clumped in space, males’ dominance rank usually plays an important role in determining access to reproductive females, yet there is extensive variation in males’ reproductive strategies among and within mammalian species (Altmann 1962, Oliveira et al. 2008, Alberts 2012).
Even when females prefer large males and dominant males have priority of access to reproductive females, smaller and more subordinate males may still achieve matings by adopting different reproductive tactics to copulate with females. In northern elephant seals (Mirounga angustirostris), older and larger males hold harems of females, yet alpha males’ percentages of copulations have been found to range from 14% to 100%, with subordinates adopting a sneak mating strategy to achieve copulations (le Boeuf 1974). In Camargue horses (Equus caballus), subordinates can also adopt a sneak-mating strategy or can form an alliance with an alpha male to help protect a harem of females, with evidence that subordinates in alliances have higher reproductive success than those adopting a sneak-mating strategy (Feh 1999). In male chimpanzees (Pan troglodytes schweinfurthii), males’ relative dominance increases with age, and more dominant males have greater reproductive success (Wroblewski et al. 2009). However, there is ample variation in reproductive skew in primate species that cannot be explained by dominance rank alone (Dubuc et al. 2011). In mammal species with indeterminate growth, adult males that are not fully developed may benefit from delaying heavy investment in breeding and using alternative reproductive tactics to achieve matings (Whitehead 1994). This begs the question, what other traits than dominance may influence males’ reproductive success?
Males’ social behaviours can be linked to their reproductive fitness, and these behaviours may change with age to maximise mating opportunities. Females have been shown to benefit from having close social bonds with males (Haunhorst et al. 2017), but the benefits to males of having strong relationships with females are still unclear, with evidence for reproductive benefits in some primate species. In wild Assamese macaques (Macaca assamensis), a species that forms multimale- multifemale groups similar to the grouping of baboons, male-female bonds are stable for 2-3 years, thus spanning multiple mating periods (Ostner et al. 2013). Ostner et al. (2013)’s study found that male-female associations during the mating season, measured from proximity data, predicted mating success and thus show that males benefit from associating with particular females. In rhesus macaques (Macaca mulatta), the sociality score of male-female dyads, a composite measure of a pair’s interaction rates, was a positive predictor of the male’s paternity of the female’s offspring (Kulik et al. 2012). These primate species live in groups and males may receive other benefits, such as grooming, from having strong bonds with females. The benefits to the males are not always
34 Chapter 2 evident, though. In chacma baboons (Papio hamadryas ursinus), 78% of males formed strong social bonds with lactating females with whom they had had the highest consort success, presumably helping to protect the infant that they had a high probability of having sired (Moscovice et al. 2010). The patterns of male-female friendship in this species support the mate-then-care hypothesis, as these male-female bonds tend to last during pregnancy and lactation, but do not predict future mating (Baniel et al. 2016). There were no clear benefits to male friends that were not the father of the offspring they helped protect, as reported in a study on wild baboons (Papio cynocephalus) (Nguyen et al. 2009). This may be because benefits to males are only evident over longer time scales, for example from increased future dominance ranking by being socially integrated with powerful females (Young et al. 2017).
Our study investigated how males’ social and space use patterns change with size in a species where individuals continue to grow with age and there is no evidence of cooperative behaviours among adults. The eastern grey kangaroo (EGK; Macropus giganteus) is a species that has high fission-fusion dynamics (Aureli et al. 2008), with individuals frequently moving between groups. Males have indeterminate growth, a strong dominance hierarchy, and do not engage in paternal care or allogrooming (Jarman 1983). Our study aimed to examine the differences among small, medium, and large male EGKs’ (1) agonistic interactions, (2) gregariousness, (3) social relationships with adult females, and (4) space use. We discuss how the changes in males’ social and space use patterns with age may reflect different age-related strategies to maximise fitness. Preferred associations and differences in males’ association patterns among size classes would also show that male kangaroos have non-random social association patterns.
Male kangaroos can violently compete amongst each other for access to females and to determine dominance (Coulson 1997b). A study on a semi-free-ranging captive population of EGKs found that more dominant males had greater reproductive success (Miller et al. 2010), but another study found reproductive skew to be weaker than expected for this species (Rioux-Paquette et al. 2015). Gaining high relative rank and finding females in oestrous are the two key elements of male EGK’s reproductive strategies (Jarman and Southwell 1986). Adult males should therefore generally be working towards increasing their relative rank, but can also increase their current mating opportunities by finding oestrous females when other more dominant males are not present (Foley et al. 2015). Male EGKs have similar but slightly larger home ranges than females (Jarman and Taylor 1983, Jaremovic and Croft 1987), likely traveling greater distances to overlap with more females’ home ranges. Alpha males tend to roam the furthest; they forage less than other males and
35 Chapter 2 are often alone, with their tenure only lasting around one year due to the high energetic cost of their behaviour (Jarman 1983, Jarman and Southwell 1986). We would expect that males’ roaming and social patterns would vary with their relative size, indicating that males employ age-specific reproductive strategies. Males might either focus on a smaller subset of females and reduce energy expenditure by decreasing movement and increased foraging, or maximise the number of females that they are exposed to by roaming further.
This is the first study to examine the male-female social relationships of male kangaroos in a wild population and to assess whether male kangaroos exhibit non-random social association patterns with females. Furthermore, as most studies of the mating strategies of male mammals have been focused on primates and mammal species that live in fixed-membership groups, this study contributes to our understanding of males’ social relationships and reproductive strategies in species with high fission-fusion dynamics. Studying males’ social patterns can help us understand the fitness trade-offs of sociability and how males may modify their social patterns with age to maximize their reproductive success.
Methods Study organism and field site The eastern grey kangaroos is a highly social macropod (Jarman and Coulson 1989). These kangaroos forage in groups of 1 to over 20 individuals with frequently changing group membership (Jarman 1987, Coulson 2009). Females of this species have been found to have non-random social organisation, with females showing recurring associations with particular females significantly more frequently than expected by their space use overlap and only partially explained by genetic relatedness (Best et al. 2014). EGKs show strong sexual size dimorphism and have indeterminate growth with males up to twice the size of adult females (Jarman 1983). There is a skewed sex ratio, with fewer adult males than females, due in part to higher mortality of males (Jarman and Southwell 1986, Coulson 1997a). Females exhibit mild oestrous synchronicity with a peak in matings during a relatively long breeding season, however females can undergo oestrous at any time of the year (Poole and Catling 1974, Jarman and Southwell 1986). Males frequently check females’ oestrous status by sniffing their cloaca and urine (Coulson 1997b).
We studied a population of wild eastern grey kangaroos at a 37.4 hectare site in Sundown National Park, Queensland, Australia (28°55’03’’S, 151°34’46’’E). The study area was composed of open grassland, where the kangaroos did most of their foraging, surrounded by mixed sclerophyll forests
36 Chapter 2 (for additional information see Best et al. 2013b). We visited the site for twelve days each month from January 2014 to February 2016 and conducted field surveys once or twice daily while the kangaroos were foraging. This kangaroo species is crepuscular, and kangaroos were thus observed in the first two-three hours after sunrise and before sunset. We recognised individuals by their unique morphological features, a method described in Jarman et al. (1989) and validated at our site by genetic testing (Best et al. 2013b). Researchers had been visiting the site since 2009 to observe the kangaroos and recording females’ social grouping patterns since 2010. We previously found that females in our site were arranged into five distinct communities – groups of individuals that associated more strongly with each other than with others – yet kangaroos did associate with individuals from other communities and had high overlap in their space use with females in different communities (Best et al. 2013b). Approximately 300 kangaroos, including over 62 adult males and 162 adult females, frequented the study site over the course of our 26 month study. Individuals differed in the amount of time they spent in our site, with some individuals observed almost every field session, and others only rarely seen.
Size categories We categorised the adult males in our site into three sizes: small, medium, and large. Small males were those that were approximately the same size as an adult female, medium males were approximately 1.5 times the size of adult females, and large males were approximately twice the size of adult females. Small males tended to have small chests and undeveloped biceps musculature. Medium males had developed biceps musculature but undeveloped chest musculature, whereas large males had large chests and bicep muscles. Males’ sizes were assessed each month for all males that were present in our site. Males’ size classes were recorded by one observer, the field researcher (P. Corvalan). As our study was conducted over two years, some males changed size class during the course of the study, and for our analyses we categorised them as the size class in which they were recorded for the longest time period.
Agonistic behaviours We recorded all observed agonistic interactions between males following Coulson (1997b) descriptions of males’ behaviours. As both males in an agonistic interaction may display dominant behaviours, in which case the interaction may escalate into fighting, we only used the common submissive behaviour of “coughing” to define the dominance relationship between pairs of males (Coulson 1997b). A male that coughed at another male was considered subordinate to that male, and these interactions were the basis for examining pairwise dominance relationships.
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Pairwise dominance relationships were used to construct a dominance hierarchy. We used David’s scores, which measure a male’s relative dominance from his proportions of wins and losses in interactions with all other males. We used normalised David’s scores, which correct for chance and account for differences in numbers of dominance interactions observed between different pairs. This method has been found in some studies to provide accurate and reliable estimates of individuals’ relative dominance with missing dyadic data (Gammell et al. 2003, de Vries et al. 2006). Normalised David’s scores and the linearity of the hierarchy were calculated in the R package steeptest (de Vries et al. 2006).
As EGKs have high fission-fusion dynamics and males utilised different areas within our site, not all pairs of males were observed in agonistic interactions. We calculated the percentage of all possible pairs that were observed in dominance interactions to examine the extent of our missing data. To determine whether males in particular size classes tended to interact more with males of some size categories than others, we examined the proportions of their interactions that males engaged in with each size class. This was performed to assess how David’s scores may have been biased due to differences in interaction rates among size classes.
Grouping patterns During the field surveys, individuals were identified and their group membership and nearest neighbour distance recorded. Groups were defined using a 15-metre chain rule, with individuals within 15 metres from at least one other group member considered part of the same foraging group. We assumed that individuals in the same groups were associating and had the potential to interact, termed the “gambit of the group” method for quantifying associations (Franks et al. 2009). All group members were identified and recorded, including young kangaroos that were independent from their mother, but not dependent (lactating) young. Males’ gregariousness was estimated from their average group size and nearest neighbour distance from all the groups they were observed in during our study. Group size was measured as the number of independent individuals in a group including the focal individual. The nearest neighbour distance was an estimate of the distance between the focal individual and the closest independent group member. A nearest neighbour distance was not assigned to individuals that were observed foraging alone.
38 Chapter 2 Social association patterns We examined males’ social relationships by measuring their pairwise associations. We calculated the strength of association between pairs using the half-weight index (HWI) (Whitehead 2008), using the R package asnipe (Farine 2013). The formula is:
푋 퐻푊퐼 = 1 푋 + 푌푎푏 + 2 (푌푎 + 푌푏) where 푋 is the number of times that individuals a and b were sighted in the same group in the same session (thus considered “associates”), 푌푎푏 is the number of times a and b were sighted in different groups in the same session, and 푌푎 and 푌푏 are the number of times that individuals a or b were sighted in a group and the other individual was not sighted in that session. HWI values range from 0-1 and are a measure of how often two individuals are observed together, with close associates having high HWI values (Whitehead 2008). HWIs are the least biased of the social association indices when not all associates are identified when examining group composition (Cairns and Schwager 1987). Only individuals with a minimum of 50 sightings were included in our analyses, to examine the social relationships among individuals that commonly frequented our study area.
We examined the total number of adult female associates that each adult male had and the sum of the HWIs for their relationships with their top 10 adult female associates (top 10 score). The number of female associates was an indicator of how many females a male had been exposed to overall, whereas the top 10 score was a measure of how strongly a male associated with particular females.
Preferred associates We determined which pairs of kangaroos were preferred associates, defined here as individuals that were found in groups together more frequently than predicted by their space use overlap. We performed 1000 simulations of individuals’ grouping patterns for each survey day, which consisted of randomly placing individuals within the study area according to their space use (see below) and probability of observation, a method implemented in the package digiroo2 (Dwyer et al. 2013, Best et al. 2014). Dyads’ HWIs were calculated for each simulation, and we compared these to our observed pairwise associations. Pairs of individuals that had an observed HWI in the top 2.5% of the simulated HWIs were considered to be preferred associates. We calculated the number of adult
39 Chapter 2 female preferred associates of each of our study males. Only males sighted a minimum of 50 times were included in these analyses (see below).
Space use of males Kangaroos’ locations were recorded using a handheld Garmin eTrex GPS (Garmin International Inc., Olathe, KS, U.S.A) accurate to 3 metres. Using this spatial data, we measured the area within the boundaries of the field site that individual kangaroos occupied in our site while foraging (called here their “space use area”). We measured individuals’ 95% kernel utilisation distributions (kUD) from a minimum of 50 spatial location points using the package adehabitatHR (Calenge 2006) in R (R Core Team 2016). This method provides a more accurate representation of where individuals spent most of their time by removing infrequently used areas. A previous study in our site (Best et al. 2014) found that the increase in space use area of an individual with sample size plateaued at approximately 50 location points, so we used this cut-off.
Statistical analyses Analyses were conducted in the R environment, version 1.0.136 (R Core Team 2016). To test for differences in dominance among size classes to address aim 1, we used an ANOVA to compare males’ normalised David’s scores among size categories and performed post hoc comparisons using the Tukey HSD test to examine which pairs of size classes differed significantly in this measure. We performed chi-square tests to determine if there were differences in the proportions of their agonistic interactions that small, medium, and large males engaged in with males of different size classes. Our expected proportions were based on the number of males in each size class, for example, the expected proportion of the interactions with small males was the number of small males divided by the total number of adult males. To address aim 2, we performed a linear model with males’ average group size and another with males’ average nearest neighbour distance as the response variables, with size class and frequency seen as predictor variables. We included males with a minimum of 10 sightings in this analysis. For aim 3, we examined how males’ social relationships differed among size classes through linear models with males’ number of adult female associates, number of adult preferred female associates, and top 10 score as the response variables. First, we tested whether there were differences in how often males were seen (i.e. frequency seen) among size class by performing a Kruskal-Wallis test, as we expected that differences in frequency seen would affect our results because males’ top 10 score and space use increase with frequency seen.
40 Chapter 2 For the models of the numbers of adult female associates and top 10 scores, we accounted for differences in observation rates of males by performing network randomisations using the R package asnipe (Farine 2013). This randomization technique involved creating 1000 permutations of the group association data, which randomised individuals’ grouping patterns by switching individuals between groups, while keeping the size of groups and number of groups the same as in the original data (Bejder et al. 1998). The p-values of our model estimates were obtained by comparing the model estimates using the social metrics (number of adult female associates and top 10 scores) from our permuted datasets to the estimates using the social metrics from our original data. Our method of determining preferred associates accounts for individuals’ probability of observation, but we were not able to perform randomisations with this social metric due to insufficient sample sizes. We thus first examined whether there was a relationship between the number of preferred associates and frequency seen using Pearson’s correlation, and then included frequency seen in the preferred associates model as the two variables were strongly correlated. Finally, for aim 4, testing for differences in space use among size classes, we first examined whether males’ space use was correlated with their frequency seen by performing a Pearson’s correlation. We examined frequency seen to account for differences in males’ rates of observation. We scaled frequency seen by subtracting the mean and dividing by the standard deviation. As frequency seen and space use were not correlated, we performed an ANOVA with males’ 95% kUD within our site as the response and size class as the predictor.
Results Males’ sizes and dominance interactions We had sufficient data on agonistic interactions for 41 adult males, which included 8 small, 18 medium, and 15 large males. We found that there were differences in dominance with size (ANOVA, F=28.61, p<0.001). Large males had significantly higher David’s scores than small and medium males, but there was not a significant difference between the mean David’s scores of small and medium males (Figure 2.1). We did not observe interactions between all pairs of males, with only 57% of all possible dyads (300 observed dyads interacting out of a possible 528) observed in at least one dominance interaction. Six dyads reversed their dominance relationships during the course of our study.
The expected percentages of interactions with each size class given random interaction patterns were 20% with small males, 43% with medium males, and 37% with large males. Small males’ agonistic interaction rates with each size class were significantly different than expected
41 Chapter 2 (χ2=24.667, p<0.001), with more frequent interactions with other small-sized males (40%), and infrequent interactions with large males (15%) (Figure 2.2). Medium-sized males interacted most frequently with large males, with over half of their dominance interactions (54%) being with large males (χ2=29.075, p<0.001). There were only two interactions in which a male from a smaller group size was recorded as dominant over a male from a larger size class. The two cases involved males that were similar in size and were at the upper and lower limits of their respective size classes (i.e. two males in the upper end of the medium size category were dominant over males in the lower end of the large size category).
Figure 2.1. The relative dominance scores (measured using David’s scores) of male kangaroos of different size classes. The boxed blue area shows the interquartile range, the horizontal line inside box is the median, the vertical line shows the range of values, the dots show the outliers, and the bars above show the significance among groups. N =41 males, *** = p<0.001, NS= not significant
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Figure 2.2. The proportions of their dominance interactions that small, medium and large males engaged in with small males (red), medium-sized males (green) and large males (blue). The expected bar shows the expected proportion of dominance interactions given the number of males in each size class and equal probability of interactions among size classes. The values above the bars show the number of males in each size class.
Males’ sizes and gregariousness Using a cut-off of ten sightings per male, we had sufficient data for 39 males. There were no significant differences in average group sizes or nearest neighbour distances among males of different size classes (Table 2.1; Table 2.2). Frequency seen was a significant predictor, with males that were more frequently seen having higher average group sizes and nearest neighbour distances.
Table 2.1. Estimates and standard errors in the linear model used to test for differences in male eastern grey kangaroos’ average group size.
Predictor variable Estimate Standard error t value P value
Intercept 6.491 0.286 22.729 <0.001 Size Medium -0.191 0.349 -0.549 0.587 Large 0.314 0.356 -0.881 0.384 Frequency seen 0.334 0.132 2.528 0.016 A LM was used to examine males’ average group size (Average group size ~ Size + Frequency seen scaled). Bolded variables indicate a significant effect using a threshold of 0.05. N=39 males
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Table 2.2. Estimates and standard errors in the generalized linear model used to test for differences in male eastern grey kangaroos’ nearest neighbour distance (metres).
Predictor variable Estimate Standard error t value P value
Intercept 4.587 0.222 20.579 <0.001 Size Medium -0.390 0.272 -1.436 0.160 Large -0.481 0.278 -1.731 0.092 Frequency seen 0.303 0.103 2.944 0.006 A LM was used to examine males’ nearest neighbour distance (Nearest neighbour distance ~ Size + Frequency seen scaled). Bolded variables indicate a significant effect using a threshold of 0.05. N=39 males
Males’ sizes and social association patterns There were 15 adult males sighted 50 or more times, which included three small males, six medium males, and six large males. Individual males were observed in 55 to 187 of our surveys (mean ± SE, 101.5 ± 9.0). There was not a significant difference in frequency seen among size classes (Kruskal- Wallis test, χ2 = 0.503, p = 0.778).
Large males had an average of 22 more adult female associates than did small males (Table 2.3; Figure 2.3A). There were no significant differences in the numbers of female associates between medium and small males or large and medium males. Males’ number of preferred associates and frequency seen were strongly correlated (Pearson’s correlation = 0.866, t value = 6.257, p < 0.001), thus we included frequency seen in the linear model for number of preferred associates. Small males had significantly fewer preferred female associates than medium or large males, but there was not a significant difference in the average number of preferred female associates among medium and large males (Table 2.4; Figure 2.3B). Top 10 score decreased significantly with increasing size, with large males having the lowest top 10 scores and small males the highest top 10 scores (Table 2.5, Figure 2.3C).
44 Chapter 2 Table 2.3. Estimates and standard errors in the linear model used to test for differences in male eastern grey kangaroos’ numbers of female associates.
Predictor variable Estimate Standard error t value P value
Intercept 57.333 9.087 6.309 <0.001 Size Medium 16.667 11.129 1.498 0.156 Large 21.667 11.129 1.947 <0.001 A LM was used to examine males’ number of female associates (Number of female associates ~ Size). Bolded variables indicate a significant effect using a threshold of 0.05. P values were obtained through network randomisation. N=15 males
Table 2.4. Estimates and standard errors in the generalized linear model used to test for differences in male eastern grey kangaroos’ number of preferred female associates.
Predictor variable Estimate Standard error t value P value
Intercept 35.477 3.238 10.958 <0.001 Size Medium 9.061 3.974 2.280 0.044 Large 11.747 3.988 2.945 0.0133 Frequency seen 11.961 1.534 7.796 <0.001 A LM was used to examine males’ number of preferred female associates (Number of preferred female associates ~ Size + Frequency seen scaled). Bolded variables indicate a significant effect using a threshold of 0.05. N=15 males
Table 2.5. Estimates and standard errors in the linear model used to test for differences in male eastern grey kangaroos’ top 10 score.
Predictor variable Estimate Standard error t value P value
Intercept 1.112 0.085 13.121 <0.001 Size Medium -0.322 0.104 -3.097 0.014 Large -0.453 0.104 -4.364 0.017 A LM was used to examine males’ top 10 score (i.e. sum strength of association with top 10 female associates; Top 10 score ~ Size). Bolded variables indicate a significant effect using a threshold of 0.05. P values were obtained through network randomisation. N=15 males
45 Chapter 2 A)
B)
46 Chapter 2 C)
Figure 2.3. Differences in males’ social association patterns among size classes, specifically the differences in A) males’ number of female associates, B) number of preferred female associates (i.e. females that males spent more time with than expected from their spatial overlap), and C) top 10 score (i.e. sum of strength of association with top 10 female associates). The boxed blue area shows the interquartile range, the horizontal line inside box is the median, the vertical line shows the range of values, the dots show the outliers, and the bars above show the significance among groups. N =15 males, * = p <0.05, ** = p <0.01, NS= not significant
Males’ sizes and space use patterns There was a significant difference in space use among size classes (ANOVA, F = 5.938, p = 0.016; Figure 2.4). Large males had significantly greater space use areas than small males, with large males’ 95% kUD within the field site approximately 15 hectares greater than those of small males, on average (Tukey’s test, difference = 15.266, p = 0.014). There were no significant differences in the space use of small and medium males (Tukey’s test, difference = 8.264, p = 0.199) or of large and medium males (Tukey’s test, difference = 7.002, p = 0.178). Frequency seen was not significantly correlated with males’ space use area (Pearson’s correlation = 0.190, t value = 0.697, p = 0.498).
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Figure 2.4. The differences among size classes in males’ 95% kernel utilisation distributions within the study area. The boxed blue area shows the interquartile range, the horizontal line inside box is the median, the vertical line shows the range of values, the dots show the outliers, and the bars above show the significance among groups. N =15 males, * = p <0.05, NS= not significant
Discussion We found that male kangaroos’ spatial use and social association patterns differed among size classes. This may reflect differences in males’ reproductive strategies with age and relative dominance. Larger, older, more dominant males roamed within a larger area in our site and had more female associates, presumably adopting a strategy of maximising the number of females they were exposed to. This is likely to be an energetically costly strategy, and thus smaller, younger males may allocate more energy towards growth by limiting their travel time and increasing their foraging time. However, smaller males were found to have stronger associations with their top 10 female associates, showing that they spent more time with particular females than did larger males. This strong association with particular females, even if it is a result of their more limited movements and home ranges, may help small males increase their mating opportunities, as they are more likely to be present when one of their female associates first becomes sexually receptive without there being another more dominant male around. In white-tailed deer (Odocoileus virginianus), which have a similar fission-fusion social system to EGKs, males increased their mating effort during the breeding season, but young males’ movement rates were found to be lower than older males (Foley et al. 2015). Similarly, young adult Himalayan tahr (Hemitragus jemlahicus) rely on opportunistic mating with smaller groups of females during the breeding
48 Chapter 2 season, while older males travel further in search of copulations with females; the strategy that older males adopt is energetically demanding, shown by their reduced kidney fat levels, and compromises their survival (Forsyth et al. 2005). A previous study on a high-density population of EGKs found that reproductive skew was relatively low in male EGKs despite their long breeding season and strong dominance hierarchy (Rioux-Paquette et al. 2015), and our study suggests that smaller males’ close social ties with females could play a role in increasing subordinate males’ mating success.
In our study population, large males were dominant over small and medium-sized adult males, but there were no differences in average David’s scores between small and medium males. Although there might not be a difference in relative dominance between small and medium males, we believe that it is more likely that David’s scores do not reflect the true relative dominance of the males in our study, as suggested by the differences in rates of agonistic interactions among males of different size classes. Medium-sized males mostly interacted with other medium-sized males and large-sized males, with the lowest proportion of their interactions being with small males. Not all males were observed interacting, and we believe that medium-sized males’ dominance scores were lower than they should have been. Medium males were frequently observed losing to large males and less frequently observed winning against small males, due to the difference in interaction rates among size classes. There were no instances where a small-sized male was dominant in an agonistic interaction with a medium-sized male. David’s scores may be most effective for estimating dominance ranking in group-living species or in laboratory experiments where all individuals are observed interacting at similar rates. For example, David’s scores have been used in group-living primates (Heesen et al. 2015, McFarland et al. 2017) and canids (van der Borg et al. 2015), where all pairs of individuals have a good chance of interacting. For species with high fission-fusion dynamics, such as the eastern grey kangaroo, where individuals have different home ranges, roam freely, and can choose to interact with or avoid particular individuals, David’s scores may partially reflect the overall pattern but not provide a highly accurate estimate of individuals’ relative dominance. A study of African elephants (Loxodonta africana) in a fenced reserve found that the second oldest male had the highest normalised David’s score despite having lost some interactions, whereas the oldest male was never observed losing (Doughty et al. 2014). This apparent anomaly was linked to the higher number of wins attributed to the second oldest male due to the greater number of interactions that he engaged in. For species that do not live in fixed groups, we suggest that dominance measures combine David’s scores with other parameters, such as age or size, to create a more accurate estimate of individuals’ dominance.
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A further finding from our study is that males had non-random association patterns, as males had preferred associates that they associated with more frequently than expected from their space use overlap. Furthermore, there were differences among size classes in males’ numbers of preferred female associates, with small males having fewer preferred associates than medium and large males. Our method of determining preferred associations accounted for differences in males’ roaming behaviours, as the sizes of males’ space use areas were embedded within the model (Dwyer et al. 2013, Best et al. 2014). Thus, unlike the number of female associates, differences in the numbers of preferred associates among size-classes were not affected by space use. Despite the method of determining preferred associates also accounting for frequency seen, as the Digiroo model embeds the probability of males’ observation (Dwyer et al. 2013), we found that males more frequently seen had more preferred associates. We included both size and frequency seen as predictors in the linear model for number of preferred associates, however we only had a sample size of 15. The results for this analysis must therefore be taken with caution. As males’ numbers of preferred female associates scaled up similarly with their total numbers of female associates, it appears that males of different ages had similar ratios of preferred female associates to total associates. Although kangaroos may associate with any individual within their home range, females form distinct communities (Best et al. 2013b), and males may follow similar trends in their association patterns.
We did not find differences in gregariousness among size classes, but we found that more frequently seen males had higher average group sizes and higher nearest neighbour distances. Males that were more frequently observed in our site were likely to be more familiar with all the individuals that frequented the area and therefore perhaps more at ease when aggregating in larger groups. In contrast, males that were infrequently in our site may not have been as familiar with other individuals who frequented the area and were perhaps thus less prone to aggregate in large groups of individuals. When males that were infrequently present in the area were in a group, perhaps they were more likely to be checking the oestrous cycle of a female and thus would have had a lower nearest neighbour distance. We do not have information on males’ social behaviours outside of our study area, but infrequently seen males could have been unsociable roamers that travelled long distances and mostly joined groups to check females’ oestrous cycle, similar to the reproductive tactics of the male striped mice (Rhabdomys pumilio) solitary roamers (Schradin et al. 2009).
50 Chapter 2 Although we accounted for differences in the number of times that males were recorded within our site, our study was still limited by the extent of our observations. For our analyses of males’ social relationships and space use, we focused on the fifteen males that were most frequently observed, yet even these males were only sighted in 30% of our surveys on average. As the EGKs we studied were wild, they could roam to areas outside of our study area, and we do not have information on where they went or who they associated with in those areas. The study site was surrounded by woodland, with other areas of open pasture where kangaroos could aggregate too distant to include in our 2-3 hour sessions when the kangaroos were foraging. The social metrics we measured were therefore only representative of their social lives within our study area. We did not have information of the sizes of males’ overall home ranges, and thus cannot be certain that a larger space use within our site was indicative of males having a larger home range. A further limitation is that our data consisted of daily point samples for individuals that were observed, and we did not collect information of males’ daily movement patterns. We assumed that males with a higher space use within our site had to travel further each day, which would have been a more energetically demanding behaviour, but we cannot be sure that there were differences among size classes in males’ daily movement patterns. Despite these limitations, we believe that the differences we found among different size classes of males are likely to reflect males’ overall patterns.
To conclude, we found that males’ space use and social association patterns differed among size groups. As males aged, their relative dominance increased, and they appeared to adopt a strategy of maximising the number of females they came in contact with by roaming widely. Although younger adult males may roam less to conserve energy and spend more time foraging, they had stronger associations with particular females than did larger males, which may help them achieve more copulations than expected for their dominance rank. Studies assessing the fitness consequences of male kangaroos’ social patterns may further elucidate the costs and benefits of having strong versus numerous social relationships. Specifically, we need to examine whether male EGKs’ reproductive success is linked to their strengths of associations with females to determine whether having strong associations with females may benefit males. As alternative reproductive tactics have been linked to differences in hormonal levels, such as testosterone in males (Bass 1996, Schradin et al. 2009), studies linking males’ social patterns with their hormonal levels could also shed further light on whether the changes in males’ sociability with age could reflect different reproductive strategies. Few studies have examined the social relationships of non-primate males, and even within studies of primates, few have linked males’ sociability with their reproductive tactics. Males’ social relationships are more complex than previously thought and warrant further research.
51 Chapter 2
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52 Chapter 2 Coulson, G. 2009. Behavioural ecology of red and grey kangaroos: Caughley’s insight into individuals, associations and dispersion. Wildlife Research 36:57-69. de Vries, H., J. M. G. Stevens, and H. Vervaecke. 2006. Measuring and testing the steepness of dominance hierarchies. Animal Behaviour 71:585-592. Doughty, L. S., K. Slater, H. Zitzer, T. Avent, and S. Thompson. 2014. The impact of male contraception on dominance hierarchy and herd association patterns of African elephants (Loxodonta africana) in a fenced game reserve. Global Ecology and Conservation 2:88-96. Dubuc, C., L. Muniz, M. Heistermann, A. Engelhardt, and A. Widdig. 2011. Testing the priority-of- access model in a seasonally breeding primate species. Behavioral ecology and sociobiology 65:1615-1627. Dwyer, R. G., E. C. Best, and A. W. Goldizen. 2013. Digiroo2: An application program- ming interface for generating null models of social contact based on individuals’ space use. R package version 0.5. Emlen, S. T., and L. W. Oring. 1977. Ecology, sexual selection, and the evolution of mating systems. Science 197:215-223. Farine, D. R. 2013. Animal social network inference and permutations for ecologists in R using asnipe. Methods in Ecology and Evolution 4:1187-1194. Feh, C. 1999. Alliances and reproductive success in Camargue stallions. Animal Behaviour 57:705- 713. Foley, A. M., R. W. DeYoung, D. G. Hewitt, M. W. Hellickson, K. L. Gee, D. B. Wester, M. A. Lockwood, and K. V. Miller. 2015. Purposeful wanderings: mate search strategies of male white-tailed deer. Journal of Mammalogy 96:279-286. Forsyth, D. M., R. P. Duncan, K. G. Tustin, and J.-M. Gaillard. 2005. A substantial energetic cost to male reproduction in a sexually dimorphic ungulate. Ecology 86:2154-2163. Franks, D. W., G. D. Ruxton, and R. James. 2009. Sampling animal association networks with the gambit of the group. Behavioral Ecology and Sociobiology 64:495-503. Gammell, M. P., H. de Vries, D. J. Jennings, C. o. M. Carlin, and T. J. Hayden. 2003. David's score: a more appropriate dominance ranking method than Clutton-Brock et al.'s index. Animal Behaviour 66:601-605. Haunhorst, C. B., M. Heesen, J. Ostner, and O. Schülke. 2017. Social bonds with males lower the costs of competition for wild female Assamese macaques. Animal Behaviour 125:51-60. Heesen, M., S. Macdonald, J. Ostner, and O. Schulke. 2015. Ecological and social determinants of group cohesiveness and within-group sspatial position in wild Assamese macaques. Ethology 121:270-283.
53 Chapter 2 Jaremovic, R. V., and D. B. Croft. 1987. Comparison of techniques to determine eastern grey kangaroo home range. The Journal of Wildlife Management 51:921-930. Jarman, P. 1983. Mating system and sexual dimorphism in large, terrestrial, mammalian herbivores. Biological Reviews of the Cambridge Philosophical Society 58:485-520. Jarman, P., and G. Coulson. 1989. Dynamics and adaptiveness of grouping in macropods. Kangaroos, wallabies and rat-kangaroos 2:527-547. Jarman, P., and C. J. Southwell. 1986. Grouping, associations, and reproductive strategies in eastern grey kangaroos. Page 399 in D. I. Rubenstein and R. W. Wrangham, editors. Ecological Aspects of Social Evolution: Birds and Mammals. Princeton, New Jersey: Princeton University Press, Princeton, New Jersey, USA. Jarman, P., and R. Taylor. 1983. Ranging of eastern grey kangaroos and wallaroos on a New England pastoral property. Wildlife Research 10:33-38. Jarman, P. J. 1987. Group-size and activity in eastern gray kangaroos. Animal Behaviour 35:1044- 1050. Jarman, P. J., M. E. Jones, C. N. Johnson, C. J. Southwell, R. I. Stuart-Dick, K. B. Higginbottom, and J. L. Clarke. 1989. Macropod studies at Wallaby Creek. VIII. Individual recognition of kangaroos and wallabies. Australian Wildlife Research 16:179-185. Kulik, L., L. Muniz, R. Mundry, and A. Widdig. 2012. Patterns of interventions and the effect of coalitions and sociality on male fitness. Molecular Ecology 21:699-714. le Boeuf, B. J. 1974. Male-male competition and reproductive success in elephant seals. American Zoologist 14:163-176. McFarland, R., D. Murphy, D. Lusseau, S. P. Henzi, J. L. Parker, T. V. Pollet, and L. Barrett. 2017. The 'strength of weak ties' among female baboons: fitness-related benefits of social bonds. Animal Behaviour 126:101-106. Miller, E. J., M. D. B. Eldridge, D. W. Cooper, and C. A. Herbert. 2010. Dominance, body size and internal relatedness influence male reproductive success in eastern grey kangaroos (Macropus giganteus). Reproduction Fertility and Development 22:539-549. Moscovice, L. R., A. Di Fiore, C. Crockford, D. M. Kitchen, R. Wittig, R. M. Seyfarth, and D. L. Cheney. 2010. Hedging their bets? Male and female chacma baboons form friendships based on likelihood of paternity. Animal Behaviour 79:1007-1015. Nguyen, N., R. C. Van Horn, S. C. Alberts, and J. Altmann. 2009. "Friendships" between new mothers and adult males: adaptive benefits and determinants in wild baboons (Papio cynocephalus). Behavioral Ecology and Sociobiology 63:1331-1344.
54 Chapter 2 Oliveira, R. F., M. Taborsky, and H. J. Brockmann. 2008. Alternative reproductive tactics: an integrative approach. Cambridge University Press. Ostner, J., L. Vigilant, J. Bhagavatula, M. Franz, and O. Schülke. 2013. Stable heterosexual associations in a promiscuous primate. Animal Behaviour 86:623-631. Poole, W., and P. Catling. 1974. Reproduction in the two species of grey kangaroo, Macropus giganteus-Shaw and M. fuliginosus (Desmarest) I. Sexual maturity and oestrus. Australian Journal of Zoology 22:277-302. R Core Team. 2016. R: A language and environment for statistical computing. Rioux-Paquette, E., D. Garant, A. M. Martin, G. Coulson, and M. Festa-Bianchet. 2015. Paternity in eastern grey kangaroos: moderate skew despite strong sexual dimorphism. Behavioral Ecology 26:1147-1155. Schradin, C., M. Scantlebury, N. Pillay, and B. Konig. 2009. Testosterone levels in dominant sociable males are lower than in solitary roamers: physiological differences between three male reproductive tactics in a sociably flexible mammal. American Naturalist 173:376-388. Trivers, R. 1972. Parental investment and sexual selection. Biological Laboratories, Harvard University Cambridge. van der Borg, J. A. M., M. B. H. Schilder, C. M. Vinke, and H. de Vries. 2015. Dominance in domestic dogs: A quantitative analysis of its behavioural measures. PLoS ONE 10:e0133978. Whitehead, H. 1994. Delayed competitive breeding in roving males. Journal of Theoretical Biology 166:127-133. Whitehead, H. 2008. Analyzing animal societies: quantitative methods for vertebrate social analysis. University of Chicago Press. Wroblewski, E. E., C. M. Murray, C. F. Keele, J. C. Schumacher-Stankey, B. H. Hahn, and A. E. Pusey. 2009. Male dominance rank and reproductive success in chimpanzees, Pan troglodytes schweinfurthii. Animal behaviour 77:873-885. Young, C., R. McFarland, L. Barrett, and S. P. Henzi. 2017. Formidable females and the power trajectories of socially integrated male vervet monkeys. Animal Behaviour 125:61-67.
55 Chapter 3
Chapter 3 The social correlates of reproductive success in male eastern grey kangaroos (Macropus giganteus)
Abstract In polygamous species, males’ mating success may be determined by their physical and social attributes. However, the synchronous receptivity of females provides the opportunity for multiple males to mate during peak breeding. Our aim was to explore the correlates of males’ reproductive success in a wild population of kangaroos. We examined the paternity of 136 offspring from 96 mothers with 58 candidate father, and had complete social data for 25 of these adult males. Although more dominant males were found to sire more of the sampled young-at-foot, all but one of the 25 adult males sired at least one offspring. Males may adopt alternative reproductive strategies or females may be choosy based on other criteria in addition to dominance. We did not find a relationship between the number of offspring males sired in our site with their top 10 score, a measure of males strength of association with their closest ten female associates. However, male- female dyads’ strength of association predicted their likelihood of sharing an offspring, even when accounting for spatial overlap and genetic relatedness. Our study shows that male kangaroos can benefit from their close association with females, but further research is needed to determine whether close associates are simply more likely to be around when females are in oestrous or whether females could have a preference for familiar males.
Introduction In group living animals, individuals can benefit from being sociable. Strong social bonds, support, and social network positions have been linked to greater survival (Silk 2010), reproductive success (Silk et al. 2003, Cameron et al. 2009, Silk et al. 2009), and lower stress levels (Cohen and Wills 1985, Seeman 1996, Hennessy et al. 2006, Kikusui et al. 2006, Hennessy et al. 2009). However, most of these mammalian studies have focused on females’ social relationships, whereas the fitness trade-offs of having strong social bonds in males have not been studied in as much depth (but see Feh 1999, Schulke et al. 2010, Wiszniewski 2011, Young et al. 2014).
More than 90% of mammalian species are polygynous, with males usually competing for mating opportunities with females (Kleiman 1977, Clutton-Brock 1989, Clutton-Brock 2017). We can measure males’ reproductive success by counting the number of offspring they sire, which is determined by their fertility, success in mating, and in promiscuous or polyandrous species, their
56 Chapter 3 success in sperm competition. Males’ reproductive success is influenced by a suite of factors. In species that engage in scramble competition polygyny, males’ competition for females is characterized by a race to locate and mate with females (Foley et al. 2018). On the other end of the spectrum, males fight for access to females, and in mammals with social hierarchies, more dominant individuals often have greater reproductive success (Ellis 1995, Girman et al. 1997, Wroblewski et al. 2009, Muniz et al. 2010, Georgiev et al. 2015). In cooperatively breeding mammals, such as African wild dogs (Lycaon pictus) and dwarf mongooses (Helogale parvula), the reproduction of subordinate males can be suppressed, preventing them from breeding or successfully siring offspring (Creel et al. 1992, Creel et al. 1997). Dominant males may guard a harem of females, securing mates and preventing other males from mating with the females, such as in elephant seals (Mirounga angustirostris), where males with harems have greater reproductive success (le Boeuf 1974). However, even though reproduction may be highly skewed towards the most dominant male, the alpha male may not be able to completely monopolize access to females and subordinates can use other strategies to mate with females. In chimpanzees (Pan troglodytes schweinfurthii), higher ranking males sire more offspring, however lower ranking males have a greater reproductive success than expected, which is likely due to females’ mate choice and males’ alternative reproductive tactics (Wroblewski et al. 2009).
Being more social may be a strategy that males can adopt to increase their reproductive success. In species with complex social relationships and cooperative behaviours, females’ social relationships have been linked to their reproductive success. Cooperative behaviours such as allomothering contribute to reduced inter-birth time in female vervet monkeys (Cercopithecus aethiops sabaeus) (Fairbanks 1990), and having strong social bonds increases offspring survival in chacma baboons (Papio cynocephalus ursinus) (Silk et al. 2009) and is linked to both offspring survival and increased birth rate in feral horses (Equus caballus) (Cameron et al. 2009). It was previously thought that males would only cooperate with closely related kin, as there were no benefits to be gained otherwise (Van Hooff and Van Schaik 1994). However, more recent studies (Feh 1999, Schulke et al. 2010, Gilby et al. 2013) have shown that males’ social relationships with non-kin can be beneficial, with the quality of males’ social relationships and their positions in social networks being predictive of their reproductive output.
Male-male social affiliations, such as the formation of alliances or breeding groups, have been linked to greater male reproductive success in equids, cetaceans, and primates. Male Camargue horses (Equus ferus caballus) can form alliances to jointly hold a harem of females, with the
57 Chapter 3 subordinate male benefiting from greater reproduction than non-harem holders (Feh 1999). In bottlenose dolphins (Tursiops sp.), males form alliances to herd females during courtship (Connor et al. 1992), and the greater the stability of individuals’ alliances, the greater their rate of consortship with females (Connor et al. 2001). Males may form long-term alliances that can last a lifetime, and these bonds are predictive of their overall reproductive output (Krutzen et al. 2004, Wiszniewski 2011). Male chimpanzees (Pan troglodytes schweinfurthii) engage in coalitionary aggression, where two individuals jointly display aggression to another male. Males with a larger coalitionary network have higher future dominance rank and greater reproductive success (Gilby et al. 2013). Finally, a study by Schulke et al. (2010) on male Assamese macaques (Macaca assamensis) found that the strength of males’ top three social bonds with other males is predictive of their future dominance rank. This study also confirmed that dominance rank was positively linked to reproductive success (Schulke et al. 2010). Few studies, however, have looked at the benefits to males of male-female social bonds.
Males and females can form strong social bonds, which clearly benefit females and their offspring (Haunhorst et al. 2017), but the benefits that males gain from investing in these relationships is less clear. Male primates may be increasing the survival of their likely offspring (Huchard et al. 2010, Murray et al. 2016), or be increasing their chances of mating through having a higher probability of mating with females with whom they have a strong social relationship (Smuts 1985) and with those whose offspring they have previously nurtured (Ménard et al. 2001), but this is not evident in all species (Hill 1990, Manson 1994). A study of Assamese macaques (Macaca assamensis) found that males and females had enduring bonds that spanned several mating seasons, and male-female associations during the mating seasons predicted their mating success (Ostner et al. 2013). Similarly, the sociality score of male-female pairs in rhesus macaques (Macaca mulatta) was positively correlated with the males’ paternity of the female’s offspring (Kulik et al. 2012). However, in chacma baboons (Papio hamadryas ursinus), males appeared to form stable bonds with lactating females they had the highest consort success with, but these bonds did not predict future mating success, suggesting that the advantage to males is protecting the infant that they are most likely to have sired (Moscovice et al. 2010, Baniel et al. 2016). In a study of male-female friendships in yellow baboons (Papio cynocephalus), Nguyen et al. (2009) identified the closest male friend of new mothers. Being a female’s close social partner did not increase the male’s chance of mating with her in the future, and it was unlikely that males were protecting the infant that they had likely sired, as most non-fathers were not observed to have previously mated with the mother. The authors suggest that males might be gaining other benefits, such as grooming received
58 Chapter 3 by their female friend, increased attractiveness (if females find infant care attractive) and thus matings with other females, or other unidentified services (Nguyen et al. 2009). Males’ investment in social relationships with females is time costly, so we would expect there to be fitness advantages to such relationships, but these are not always clear. To further elucidate the benefits of male- female social relationships for males and to examine the evolutionary origins of such bonds, we must examine a variety of species with different life histories and social structures.
Our study is the first to examine the link between social bonds and reproductive success in male eastern grey kangaroos (EGKs; Macropus giganteus). In mammals with strong sexual dimorphism, mating polygyny, and competition for females, we expect high reproductive skew favouring the largest and most dominant males (Andersson 1994, Ellis 1995, Vanpé et al. 2008). EGKs are sexually dimorphic and males have strong dominance relationships (Jarman and Southwell 1986, Miller et al. 2010). A study on male EGKs found that the alpha male in a population sired over half of the offspring in that area (Miller et al. 2010); however, this study was conducted in enclosed areas, and involved only 21 males and 39 offspring from three populations. A six-year study of paternity of EGKs in a wild population found a much weaker reproductive skew than expected from the large size differences among breeding males, the long breeding season, and the clear dominance hierarchy among males (Rioux-Paquette et al. 2015). Rioux-Paquette et al. (2015) found that even small males, similar in size to adult females, sired offspring. This recent study of paternity in EGKs by Rioux-Paquette et al. (2015) did not examine how the social relationships of kangaroos may influence their reproductive success, and we strived to unravel these relationships in our study.
The overall objective of our study was to examine the social correlates of paternity in EGKs. Our first aim was to examine the correlates of reproductive success in males, including males’ dominance rank, gregariousness, and social relationships with females. Our second aim was to examine whether the strength of association between males and females was a strong predictor of whether they parented an offspring together, controlling for the spatial overlap between individuals and their genetic relatedness. To address these aims, we examined the social associations of males and females over 16 months, and the paternity of offspring that were conceived during that time. We expected that males’ reproductive success would be positively correlated with their strengths of associations with females, gregariousness, and dominance rank. For our second aim, we expected that males and females that associated more strongly, when accounting for spatial overlap, would have a greater probability of having an offspring together. A positive relationship between strength of association and probability of sharing an offspring would be indicative of a benefit to male
59 Chapter 3 kangaroos of associating with females, and thus provide support for potential alternative reproductive strategies that males may adopt to increase their reproductive fitness. This study, along with the suite of research on a diversity of species, will contribute to our understanding of mammals’ social relationships by providing insight into the mechanistic and functional explanations of males’ social bonds.
Methods Study species EGKs are a highly social macropod that exhibits high fission-fusion dynamics (Aureli et al. 2008), foraging in groups of 1 to over 20 individuals of constantly changing composition (Jarman 1987, Jarman and Coulson 1989, Coulson 2009). Group membership changes multiple times a day, yet there are trends in the individuals with which particular kangaroos choose to associate. Females have preferred social associates with whom they are more often observed in feeding groups than predicted by their spatial overlap (Best et al. 2013b, Best et al. 2014).
Adult male EGKs have similar, but slightly larger, home ranges than females (Kaufmann 1974, Jaremovic and Croft 1987, Croft 1989). They actively roam around, especially in the summer (Clarke et al. 1989), visiting different groups of individuals and frequently approaching females to check if they are in oestrous (Jarman and Southwell 1986). Male EGKs have a strong dominance hierarchy (Miller et al. 2010), maintained through fights and displays (Coulson 1997b). Males’ forelimb musculature, the size of which is likely linked to fighting ability, is under sexual selection (Warburton et al. 2013), and could act as a signal to rivals and mates. Males serially defend females, which entails guarding one female at a time before and/or after mating, with a more dominant individual able to supplant subordinate males (Jarman and Southwell 1986). Male kangaroos have indeterminate growth (Jarman 1983), with the largest males likely to also be the oldest. The differences in size among adults can be quite large, as males reach full adulthood at age four with the onset of spermatogenesis when they are approximately the size of an adult female, and the largest adult males can reach nearly four times that weight (Poole and Catling 1974, Jarman and Southwell 1986, Rioux-Paquette et al. 2015).
Study area The study area was in the south-west corner of Sundown National Park, Queensland, Australia (28°55’03’’S, 151°34’46’’E). The 37.4 ha area consisted of pastures intermixed with and surrounded by forests of silver-leaves ironbark (Eucalyptus melanophloia) and cypress pine
60 Chapter 3 (Callitris intratropica). The average monthly rainfall in 2014 and 2015 was 50.1 ml (6.4 – 197.2 ml), with the driest months occurring around August-October (Australian Bureau of Meteorology station number: 041100; 28°51’00” S, 151°10’12” E). Our study species, the eastern grey kangaroo, mostly forages in the open pastures, and we only observed them while they were foraging within our study site. The kangaroos at our site were habituated to people, as there was a small campground nearby and researchers had been studying the kangaroos since 2009 (Favreau et al. 2010).
Approximately 300 individuals frequented our site during 2014-2015, including over 62 adult males, and 162 adult females. Individuals that frequented our site were photographed, named, and recognised by their unique morphological features, a method described in Jarman et al. (1989) and validated in our site (Best et al. 2013b). As these are wild animals, individuals were free to move anywhere within and outside of our study area. There were therefore large differences in the frequency at which we observed different individuals, as some were present at the site regularly, while others likely roamed widely outside of our study area.
Social measures We visited the field site for twelve days each month from January 2014 to February 2016 and surveyed the social grouping patterns of kangaroos once or twice daily in the early mornings and late afternoons, as EGKs are a crepuscular species. These surveys consisted of recording the identities and group memberships of all the kangaroos observed in our study area while they were foraging. Social groups were defined by a 15-metre chain rule: by this definition any individual within at least 15 metres of another group member was considered part of that group. We used the gambit of the group method (reviewed in Franks et al. 2009), which assumes that individuals in the same group were associating and could interact.
We estimated the gregariousness of males from their average group sizes. The group size was the number of individuals in a group, including all individuals that were independent from their mothers, which was a measure of the grouping tendency of males. We obtained the average group size of males from all the groups in which they were observed during our surveys, including when they were observed alone.
The strength of association between dyads was measured using the half-weight index (HWI) (Whitehead 2008):
61 Chapter 3 푋 퐻푊퐼 = 1 푋 + 푌 + (푌 + 푌 ) 푎푏 2 푎 푏 where 푋 is the number of times that individuals a and b were sighted in the same group in the same session, 푌푎푏 is the number of times a and b were sighted in different groups in the same session, and
푌푎 and 푌푏 are the number of times that individuals a or b were sighted and the other individual was not sighted in that session. A dyad’s HWI is a measure of the time that these two individuals are observed together versus apart, and corrects for bias due to missed sightings (Whitehead 2008). Only individuals sighted a minimum of ten times were included in the HWI calculation. The strength of individuals’ top ten associations with females (top 10 score) was measured as the sum of their ten highest HWIs with females. We use this top 10 score measure instead of overall strength to assess sociability, as we wanted to determine how males’ close social relationships with females are linked to their reproductive success. Dyads’ HWIs were calculated using the R package asnipe (Farine 2013).
Genetic analyses Faecal samples from identified individuals were collected immediately after defecation and frozen at -20°C until DNA extraction. We attempted to collect faecal samples from all individuals that we observed frequenting our site, including adult males, and mothers and their young-at-foot (YAF; kangaroo that has permanently emerged from the pouch but is not yet weaned). We also sampled young that were in the large pouch young stage (a kangaroo that leaves the pouch but has not permanently emerged from the pouch), but these were rare and tended to be soon before permanent emergence, and henceforth we categorise all the sampled young as YAF. Gestation lasts 36 days (36.41 ± 1.63) in EGKs (Poole 1975), and permanent pouch emergence occurs approximately 10.5 months (319 ± 18 days) after birth (Poole et al. 1982). Only young that survived to permanent pouch emergence were included in paternity analyses, as it was not possible to collect faecal samples prior to this stage. The YAF included in the paternity analyses were those that reached permanent emergence between October 2014 and February 2017, ensuring the timing of our social data collection corresponded with time of conception of the YAF (with a 10-12 months delay to account for gestation and time in pouch). It was not possible to accurately predict mating time from the timing of permanent pouch emergence, as female EGKs can undergo gestational diapause (Kirkpatrick 1965, Poole 1975), but we believe this is the best approximation given our limited knowledge of the timing and occurrence of diapause.
62 Chapter 3 DNA extraction was conducted using a commercial kit (QIAamp® DNA stool mini kit, Qiagen). PCR amplifications of twelve microsatellite markers with 5' fluorescently labeled forward primers were carried out in three multiplexes and a singleplex. PCR conditions are reported in Best et al. (2013b). PCR products were separated by capillary electrophoresis with the Applied Biosystems 3730 Cappillary DNA Analyser. We examined 12 polymorphic microsatellite loci: G12.6, G15.4, G16.1, G16.2, G26.4, G31.1, G31.3 (Zenger and Cooper 2001b), B151, B123, B90, Ym148 (Sigg et al. 2005), and T17.2 (Zenger and Cooper 2001a). Alleles were assigned using GeneMapper version 3.7 (Applied Biosystems Inc., Foster City, CA, U.S.A.); two replicates were required to confirm a heterozygous locus, while three replicates were used to confirm homozygous loci. Individuals with genotypes at fewer than seven loci were discarded from further analysis.
We calculated observed and expected heterozygosity in the program Cervus 3.0 (Marshall et al. 1998). To estimate allele frequencies in our population, we used all the individuals that we had genotyped in our site since 2010 (Best et al. 2014, Menz 2015), most of which were adult females that were still present in 2014. Given the frequency of males’ presence in the site, we estimated that we had sampled 80% of the potential fathers. Although females may encounter males outside of our study area, most of the mothers were individuals that we regularly observed in our site (mean percentage of surveys that females were recorded in ± SE, 45.9 ± 2.1%) , and therefore, we assume that they mostly mated with males that we observed within our site. Paternity was estimated using likelihood-based paternity inference in Cervus 3.0. We included all the genotyped adult males observed between January 2014 and February 2016 as candidate fathers for all offspring, and included additional genotyped males that were observed prior to January 2014. Although some males were only considered to have reached adulthood later in the study, we included them as candidate fathers for all offspring, as there was still the potential that they could have mated with females when they were slightly smaller than the size of the average female. Some males disappeared and likely died during the study; however, we included these males as candidate fathers for all offspring because we were uncertain of their fate (we did not observe any carcasses of large males around our site), and because the females could have undergone diapause with their fertilized embryo. Males only sighted prior to January 2014 (earliest sightings in late 2012) were also included as potential fathers, as they could have a) been present in our site when we were not recording surveys, b) mated with our sampled mothers outside of our study area, or c) mated with mothers that delayed blastocyst development; the collection of adult male scat samples for genetic analysis started in 2012. The most-likely candidate father with a positive and significant LOD score was considered the father of a given offspring. The number of allocated paternities of a male was
63 Chapter 3 used as an estimate of the male’s reproductive success within our study area. Males’ siring success with females outside of our study area was not monitored, and thus we did not examine males’ overall reproductive success. We used the program GenAIEx (Peakall and Smouse 2006, 2012) to estimate pairwise relatedness coefficients (Queller and Goodnight 1989).
Dominance ranking Agonistic interactions between males were recorded ad libitum and used to assess the dominance relationships between interacting dyads. We focused specifically on the “coughing” behaviour of submissive males (Coulson 1997), with data from January 2014 to February 2016 used in analyses. A win-loss sociomatrix was constructed for all males that were observed engaging in agonistic interactions. The R package steeptest was used to obtain an estimate of individuals' relative dominance using normalised David's Scores (de Vries et al. 2006). This method can provide accurate and reliable estimates of individuals’ relative dominance, even with missing dyadic data and repeated interactions between individuals (Gammell et al. 2003, de Vries et al. 2006). Although the hierarchy was likely dynamic over time, we used all the data in one analysis. Miller et al. (2010) found that males exhibited a strongly linear dominance hierarchy in their captive kangaroos, however, dominance hierarchies are likely to be less evident in our wild population, since not all pairs of males interact, males have different ranging areas and different males are present at different times.
Male kangaroos have indeterminate growth (Jarman 1983), and we differentiated adult males by categorising them into three size categories (large, medium, and small adult males). Size categories were assessed each month for all males present in the site by one observer, the field research (P. Corvalan). Small males were those that were approximately the same size as an adult female, medium males were approximately 1.5 times the size of adult females, and large males were approximately twice the size of adult females. Small males tended to have small chests and undeveloped biceps musculature, whereas large males had large chests and bicep muscles. It was assumed that larger males would be dominant over smaller males. As not all pairs of males were observed in dominance interactions, we believe that males’ David’s scores could be biased due to the tendency of males to interact more with males within their own size category. To address this issue, we estimated males’ dominance ranks by combining their David’s scores and sizes, ranking males according to their size category first, and then their ranking within their size category according to their David’s score. The large male with the highest David’s score was given a rank of 1, with the second most dominant male given a rank of 2, and so forth.
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Spatial analyses Although kangaroos could freely roam around the study area and beyond it, most individuals did not use the entire study area. Associations between dyads may therefore be driven by space use, with individuals associating more strongly simply due to shared space rather than social preference. To account for this covariate, we examined the space use by adult males and females within our study area. Individuals’ locations were recorded during the field sessions using a handheld Garmin eTrex GPS (Garmin International Inc., Olathe, KS, U.S.A), which is accurate to 3 metres. Only individuals with a minimum of ten location data points were used in analyses. We calculated the centroids of each individual’s 95% kernel utilisation distribution (kUD) using the package adehabitatHR (Calenge 2006), and measured the distance between males’ and females’ centroids as a proxy for spatial overlap. A previous study in our site (Best et al. 2014) found that the cumulative increase in space use area of an individual with sample size plateaued at approximately 50 GPS points, however we wanted to include males that we had observed fewer than 50 times. Therefore, we used centroid distance instead of kUD overlap, as kUD increased with sample size, whereas centroid location appeared relatively stable with sample size.
Statistical analyses All analyses were conducted in R (R Core Team 2016). For Aim 1, which was to determine the correlates of males’ reproductive success, we fit three generalised linear models (GLM). The response variable was the number of offspring that a male sired (i.e. reproductive success in our study area), which followed a Poisson distribution. The predictors were the male’s dominance rank, and either average group size, the sum of males’ top 10 HWIs with females (“top 10 score”), or the frequency at which a male was observed (# of sightings during surveys). We fit separate models due to our low sample size and the high correlation between males’ top 10 scores and numbers of times they were observed (Pearson correlation: r = 0.72, p < 0.001). The predicted relationship between dominance rank and reproductive success was obtained using the frequency seen model. To address Aim 2, which was to examine whether the strengths of relationships between male-female dyads predicted their likelihood of sharing an offspring, we fit a generalised linear mixed model (GLMM) using lme4 (Bates et al. 2015). We examined the spatial distance between centroids, relatedness, and HWIs between pairs of males and females to ascertain whether male-female strength of association (HWI) predicted their probability of sharing an offspring, controlling for spatial overlap and relatedness. The binomial response variable was whether the male and female shared an offspring, and male identity (ID) was included as a random effect. It was not necessary to include
65 Chapter 3 female ID as a random effect, as there was little variation in the number of offspring that mothers had in our study. Only males that were adults at the beginning of this study in January 2014 were included in analyses. Males with missing data were removed from analyses. All predictors were scaled by subtracting the mean and dividing by the standard deviation.
The significance of the network measures (top 10 scores and dyads’ HWIs) in our models was determined using randomisation tests. Using the R package asnipe, we conducted 1000 permutations of the group association dataset to create randomised networks. These permutations randomised individuals’ grouping patterns, while keeping the group sizes and numbers of groups per session the same as in our original survey (Bejder et al. 1998). Furthermore, the number of sightings of individuals in these permutations remained the same as in our survey, therefore controlling for any effects of numbers of sightings in our models. These randomisations allowed us to account for the non-independence of network measures. For both models, p values for the social network measures were calculated by comparing the model parameters of the observed and randomised data.
Results Individual observations We conducted a total of 337 surveys between January 2014 and February 2016, with 249 individuals, including 153 adult females, recorded in our surveys ten or more times during this period. We examined the paternity of 58 adult males, which included seven adult males that were sighted only prior to the start of our study. We had complete social and dominance data for thirty- two males, of which 25 were adults at the start of our study in January 2014. The 25 adult males differed in size, dominance, and which parts of our study area they utilized. Only males of the medium and large size categories were represented, as males categorised as small-sized were not adults at the beginning of our study. Males also differed in their frequency of presence in our site, with males recorded in our surveys between 14 and 133 times (mean = 51.28 ± 7.38). These 25 adult males were included in analyses of reproductive success and shared offspring to address aims 1 and 2.
Microsatellite analyses and paternity assignment There was a mean of 15.5 (± 1.8) alleles per locus, ranging from 6 to 26, with 14% missing data. All loci were at Hardy-Weinberg equilibrium and there was no evidence of null alleles (Table 3.1). All twelve loci were used for our paternity analyses.
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Table 3.1. Microsatellite characteristics of eastern grey kangaroos found in our site of Sundown National Park, QLD, in 2010-2016.
Locus N° individuals N° alleles Hobs Hexp B123 488 6 0.713 0.762 B151 492 24 0.927 0.928 B90 503 11 0.821 0.791 G12.6 466 15 0.865 0.845 G15.4 407 17 0.912 0.870 G16.1 478 16 0.862 0.862 G16.2 460 9 0.772 0.707 G26.4 424 26 0.908 0.902 G31.1 397 14 0.814 0.776 G31.3 339 19 0.864 0.844 T17.2 437 20 0.719 0.699 Ym148 354 9 0.740 0.703 mean 0.807 0.785 Hobs and Hexp are the observed and expected heterozygosity.
Of 167 offspring from 115 mothers that permanently emerged from the pouch during our study period, we genotyped 136 YAF offspring from 96 known and genotyped mothers. We were unable to genotype all the offspring that reached the young-at-foot stage, as some offspring disappeared, and were presumed dead, before scat samples were collected, or we were unable to genotype the collected samples at 7 loci. We assigned a candidate father to 125 of the 136 offspring using a strict confidence level of 95%.
Reproductive success The 25 adult males included in our analyses were assigned a total of 106 offspring (mean = 4.24 ± 0.71), with one male not achieving paternity of any of the analysed young, and two males each assigned more than 10 offspring (Table 3.2). Dumpster was only observed to be submissive to Chad, the highest ranking male in our study, and was dominant over Gareth, the third highest ranking male, yet was ranked #6 in our hierarchy.
67 Chapter 3 Table 3.2. Possible correlates of reproductive success of male EGKs. Data are for males that were adults in 2014 and included in statistical analyses (n = 25). N° David’s Dominance Group Top10 N° % ID Size offspring score rank size score sightings sightings Chad 8 21.59 Large 1 6.25 0.53 90 26.71 Trevor 8 20.91 Large 2 7.03 0.80 91 27.00 Gareth 14 20.90 Large 3 6.62 0.73 93 27.60 Rusty 3 20.84 Large 4 5.43 0.65 48 14.24 Jimmy 6 20.81 Large 5 5.60 0.74 28 8.31 Dumpster 12 20.79 Large 6 7.07 0.53 23 6.82 Shamien 5 20.73 Large 7 4.80 0.43 15 4.45 Horatio 6 20.73 Large 8 6.11 0.59 88 26.11 Tim 8 20.53 Large 9 6.99 0.84 133 39.47 Johnny 1 20.40 Large 10 5.47 0.60 21 6.23 Damien 2 20.37 Large 11 6.43 0.50 19 5.64 Wilbur 3 20.30 Large 12 6.32 0.74 44 13.06 Chopper 5 20.13 Large 13 4.64 0.32 21 6.23 Peto 5 19.89 Large 14 6.41 0.62 63 18.69 Lachlan 2 20.18 Medium 15 8.00 0.36 14 4.15 Chips 3 20.03 Medium 16 6.91 0.94 135 40.06 Wired 3 20.02 Medium 17 6.29 0.44 17 5.04 Mason 1 19.90 Medium 18 7.53 0.56 43 12.76 Xavier 1 19.81 Medium 19 4.43 0.33 14 4.15 Kyle 2 19.81 Medium 20 6.09 0.76 32 9.50 Ross 1 19.76 Medium 21 5.19 0.56 47 13.95 Rudolph 2 19.74 Medium 22 6.45 0.78 91 27.00 Castro 3 19.59 Medium 23 6.22 0.77 55 16.32 Basil 2 19.57 Medium 24 4.97 0.44 30 8.90 Tyrone 0 19.54 Medium 25 5.29 0.37 27 8.01 mean 4.24 20.28 6.10 0.60 51.28 15.22 (SE) (0.71) (0.11) (0.18) (0.03) (7.38) (2.19) David’s score is a measure of dominance, with high values denoting greater dominance. Data are sorted by dominance rank, estimated from males’ David’s scores and sizes. Group size is the average foraging group size that males were observed in. Top 10 score is the sum of males’ top 10 HWIs with adult females. The number of sightings is the number of surveys that the male was recorded in, and the percentage sightings is calculated from the number of sightings divided by the number of surveys (337) conducted.
We found a significant positive relationship between males’ dominance scores and the numbers of offspring they sired (Table 3.3; Figure 3.1). However, the most dominant males did not monopolise reproductive success, with only one of the 25 males not siring any offspring. The ‘frequency seen’ model that included dominance rank and number of sightings had the lowest AIC score, however number of sightings was not a significant predictor of offspring sired. There were no significant relationships between males’ average group sizes or their top 10 scores and the number of offspring they sired in our site.
68 Chapter 3 Table 3.3. Estimates and standard errors in the three generalized linear models used to explain male eastern grey kangaroos’ reproductive success in our site over two years. Model Predictor variable Estimate ± se z value P value AIC
a) Frequency seen Intercept 1.303 ± 0.118 11.056 <0.001 104.2 Dominance rank -0.602 ± 0.112 -5.386 <0.001 Number of 0.217 ± 0.125 1.729 0.084 sightings b) Social relationship Intercept 1.244 ± 0.117 10.640 <0.001 106.1 Dominance rank -0.627 ± 0.113 -5.551 <0.001 Top 10 score 0.114 ± 0.112 1.020 0.482 c) Gregariousness Intercept 1.231 ± 0.118 10.389 <0.001 104.4 Dominance rank -0.632 ± 0.112 -5.660 <0.001 Average group size 0.182 ± 0.110 1.650 0.099 Three GLMs were used to examine males’ reproductive success (Reproductive success ~ Dominance rank + changing variable). The changing variables were a) Number of sightings (i.e. the number of times that males were observed in our study area), b) top 10 score (i.e. the sum of males’ top ten HWIs), and c) average group size. All predictor variables were scaled by subtracting the mean and dividing by the standard deviation. Bolded variables indicate a significant effect using a threshold of 0.05. The p value for top 10 score was obtained from randomisation tests.
Figure 3.1. The relationship between males’ dominance rank, 1 being the highest rank, and their reproductive success in our site, measured as the number of offspring they sired over 2 years. Dots are the observed values and the grey shaded area shows the 95% confidence interval.
Probability of male-female dyads sharing an offspring The probability of a male-female pair having an offspring decreased significantly as the distance between their centroids increased (Table 3.4; Figure 3.2A). When the distance between their centroids was almost zero, male-female pairs had a 13% probability of sharing an offspring. However, this percentage dropped to below 1% when the distance in male-female centroids was over 350 metres. Only four out of 2200 male-female pairs had a genetic relatedness coefficient greater than 0.25, with a genetic relatedness of 0.33 for the most genetically related pair. The genetic relatedness of male-female pairs was negatively correlated with the probability of male-
69 Chapter 3 female dyads sharing an offspring, but this effect was not significant. The probability of male- female dyads having an offspring together increased significantly with dyads’ half weight index, with the strongest associates having almost a 7% probability of sharing an offspring (Figure 3.2B).
Table 3.4. Estimates and standard errors in the generalized linear mixed model used to explain the probability of male-female dyads sharing an offspring.
Variable Estimate Standard error z value P value
Intercept -3.908 0.233 -16.759 <0.001 Spatial distance -1.273 0.201 -6.350 <0.001 Genetic relatedness -0.160 0.115 -1.395 0.163 Half weight index 0.281 0.112 2.502 <0.001 A binomial GLMM was used to examine male-female dyads shared offspring (Shared offspring ~ Spatial distance + Genetic relatedness + Half weight index + (1|ID)). Bolded variables indicate a significant effect using a threshold of 0.05. The p value for the half weight index was obtained from randomisation tests.
A) B)
Figure 3.2. Predictors of the likelihood of sharing an offspring. The probability of male-female dyads sharing an offspring against their A) spatial distance, measured as the distance in metres between males and females’ centroids, and B) half weight index, a measure of the strength of association. The grey shaded area shows the 95% confidence interval.
Discussion Our study is the first to examine the fitness consequences of social bonds in male kangaroos. We found that the strength of males’ social relationships, measured from the sum of their HWIs with their top ten female associates, was not linked to their reproductive success in our site. There was also no link between males’ grouping tendency and their reproductive success, and even though there was high variation in the number of times that males were sighted in our site, we did not find a link between how often males were seen and their reproductive success (i.e. number of young-at-
70 Chapter 3 foot offspring sired) in our site. Our findings suggests that male kangaroos do not gain reproductive benefits from being sociable. However, males’ strength of association with particular females predicted the likelihood of siring that female’s offspring, even when accounting for the distance between the centroids of the male’s and female’s 95% kernel utilisation distributions. As expected from previous studies, males’ dominance rank was a strong predictor of reproductive success, yet all but one male sired at least one offspring, suggesting that the most dominant males do not monopolize access to females in oestrous.
We found a positive relationship between males’ dominance rank and reproductive success, as was expected from previous studies in kangaroos and other mammals, but the relationship was weaker than expected. In group-living mammals, more dominant individuals tend to have a higher reproductive success (Ellis 1995, Georgiev et al. 2015). In EGKs, dominant males can supplant subordinates from females (Jarman and Southwell 1986), thus ensuring they have priority access to females in oestrous. Dumpster ranked #6 in our hierarchy, but the only other male he was submissive to was the highest ranking male. We believe that he should have been closer to second place in the hierarchy, but due to his infrequent presence in our site, we did not observe many other males being submissive to him. Our study supports the findings of Miller et al. (2010)’s study of EGKs in enclosed areas, thus corroborating the relationship between dominance and reproductive success in wild EGKs. Although there was a strong positive relationship between dominance and reproductive success in our study, the most dominant males did not monopolise reproduction, as all but one of the 25 adult males that were the focus of our study achieved paternity of at least one offspring and the top six most dominant males sired less than half the offspring. There is weak evidence that males may face a trade-off between size and sperm competition, as western grey kangaroo males with greater forelimb musculature had slower sperm, however, the same trade-off was not found for other traits of sperm competition (Martin et al. 2018). A six-year study of over 200 males from two populations of EGKs found a weaker mating skew than expected for this species (Rioux-Paquette et al. 2015). A stronger mating skew was expected, as kangaroos are sexually dimorphic, females tend to go into oestrous over a long breeding season, and males’ dominance hierarchy is strong (Rioux-Paquette et al. 2015). The weaker than expected mating skew could be explained by females showing preferences for male characteristics other than dominance, but there is no evidence for this yet.
We did not find a significant relationship between males’ top 10 HWIs with females and their reproductive success. Although the benefits to male primates of having strong social bonds with
71 Chapter 3 females are still unclear, there is evidence that strong and enduring social bonds with females may boost males’ reproductive success through increased mating success and protection of infants that the male likely sired (Smuts 1985, Moscovice et al. 2010, Kulik et al. 2012, Ostner et al. 2013, Baniel et al. 2016). There is no evidence of male kangaroos aiding in offspring rearing or protection, and thus it is unlikely that male kangaroos would associate with females that they have previously mated with in order to increase the survival of their potential offspring. Males could increase their chances of mating with a female that they are closely associated with by being more likely to be present when she first enters oestrous. It is also possible that males could track when the females would become most receptive, as males sniff females’ cloaca to determine when they are in oestrous, and a study on red-necked wallabies found that males were keen to sniff females in pre- oestrous and oestrous, and were even able to relocate them from their scent (Jarman and Southwell 1986, Johnson 1989). We did not test how other aspects of males’ social relationships, such as their relationships with other males or their network positions, are linked to their reproductive success, as this was not the focus of our study.
The strength of association between male-female dyads was a significant predictor of the probability of them sharing an offspring, even when accounting for dyads’ spatial overlap, which was, not surprisingly, also positively correlated with the probability of the pair sharing an offspring. Kulik et al. (2012)’s study of rhesus macaques found that a high composite sociality score (measured from grooming, sharing resources, and friendly approaches) between male-female dyads was linked to a higher probability of paternity. Similarly, in a study of the social associations, spatial roaming patterns, and reproductive success of wild chimpanzees, Langergraber et al. (2013) found that the strength of male-female dyads’ socio-spatial index (measured from their overall spatial proximity and group associations) was as strong a predictor of males’ reproductive success as their dominance rank. The authors suggest that this pattern could be due to females’ preferences or males’ knowledge of females’ oestrous cycles, but further research into the quality of the relationships is needed to ascertain the underlying mechanisms (Langergraber et al. 2013). In our study, male-female dyads with a higher HWI spent more time together, which would have increased the male’s probability of being present when the female became sexually receptive, and could have improved the male’s ability to track the female’s oestrous cycle. Female kangaroos could also prefer to mate with familiar males. Preference for familiar males is unlikely to be motivated by reducing the chance of infanticide, as there have not been any reports of males harming young in the decades of research on EGKs, female EGKs that lose their YAF may not go into oestrous immediately because they could already have a young in the pouch or a delayed blastocyst (Poole
72 Chapter 3 and Catling 1974), and dominant male EGKs do not monopolise groups of females as in other species that exhibit infanticide (Palombit 2015, Harano and Kutsukake 2018). Further research into female choice in kangaroos is needed to determine what aspects other than dominance might affect males’ mating success.
In Japanese macaques (Macaca fuscata) and rhesus macaques (Macaca mulatta), female friends can be valuable allies, helping males establish or maintain their ranking position (Takahata 1982, Smuts 1985). Associating with many females and engaging in sustained grooming with well-connected females appears to improve male vervet monkeys’ (Chlorocebus pygerythrus) power trajectory, measured as the shift in competitive ability over time (Young et al. 2017). In a study of male-male affiliative relationships in Assamese macaques, the strength of males’ top three social bonds with other males predicted their future dominance rank, which was a strong predictor of reproductive success (Schulke et al. 2010). We were unable to examine how male kangaroos’ social bonds could predict future dominance rank and reproductive output, due to time and data limitations. We had sufficient data on dominance relationships to create one hierarchy for the two years, and from observation, rankings were relatively stable over time, with the most dominant male appearing to have retained the alpha male status for the duration of our study. It is unlikely that male kangaroos’ social relationships would greatly affect their dominance ranking, as kangaroos have indeterminate growth and dominance appears to be driven primarily by size (Jarman 1983, Jarman and Southwell 1986, Rioux-Paquette et al. 2015), whereas adult male macaques are more similar in size and other factors influence their dominance hierarchies. We suggest that studies on species with more dynamic social hierarchies and those that tracked the same individuals over multiple years could elucidate how individuals’ social relationships may influence their future fitness.
We did not find a significant relationship between males’ gregariousness or frequency of presence in our site and their reproductive success. Males that were in our site more frequently would have had greater exposure to the females and be more likely to be present when they were in oestrous, however, the positive trend we found was not significant. We had expected that more gregarious males would be exposed to more females on a regular basis, thus increasing their mating opportunities, but, although male EGKs’ reproductive success appeared to increase with their average group size, this trend was not significant. The average group sizes of males in our study only ranged from 4.4 to 7.5 individuals, and this small difference in gregariousness of males may have limited the importance or the power to detect any importance of this possible predictor of reproductive success. Furthermore, high gregariousness may negatively impact males’ reproductive
73 Chapter 3 success; males that are in larger groups may be faced with more competition for mates, as there is a greater chance that a more dominant male would also be present.
There is slight evidence of inbreeding avoidance in kangaroos, as there was a negative relationship between relatedness and probability of sharing an offspring in our study, however, this was not significant. Male kangaroos tend to disperse from their natal area, and thus likely avoid inbreeding through dispersal (Coghlan et al. 2017). Only four pairs had a relatedness score above 0.25 and most pairs of individuals would not be considered to be related, and there may not have been a high enough variation in relatedness to find significant evidence of inbreeding avoidance.
The scope of our study is limited, as we do not have a complete overview of the males’ reproductive success and it was not possible to document individuals’ full home ranges. Only offspring of females that frequented our study area were sampled, and given that the males’ full home ranges were not known, they may have sired further offspring outside of our site. Our open grassy study area was surrounded by forest, but there were other open areas where kangaroos could aggregate further away. Males included in our study were sighted in only 4% to 40% (mean ± SE, 15.22 ± 2.19%) of the surveys conducted, and we do not have information on their ranging behaviour outside of our study area. This was not logistically feasible, for a variety of reasons, and would not have allowed the intensive study of the animals within our focal study area.
Despite more dominant male EGKs having higher reproductive success, even low ranking males sired offspring, suggesting that other traits than dominance predict reproductive success in kangaroos. Males’ overall sociability, as measured by our top 10 score variable, did not influence their reproductive success, but proximity and familiarity appeared to be linked to their fathering young with particular females, and further research on females’ preferences is needed to understand the mechanisms underlying this trend (Cheetham et al. 2008). Further research on the long-term social relationships of kangaroos could increase our understanding of cognition in kangaroos and the fitness consequences of having social bonds.
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79 Chapter 3 Peakall, R., and P. E. Smouse. 2006. GenAlEx 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6:288-295. Peakall, R., and P. E. Smouse. 2012. GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update. Bioinformatics 28:2537-2539. Poole, W., and P. Catling. 1974. Reproduction in the two species of grey kangaroo, Macropus giganteus-Shaw and M. fuliginosus (Desmarest) I. Sexual maturity and oestrus. Australian Journal of Zoology 22:277-302. Poole, W. E. 1975. Reproduction in the two species of grey kangaroos, Macropus giganteus Shaw and M. fuliginosus (Desmarest). II. Gestation, parturition and pouch life. Australian Journal of Zoology 23:333-353. Poole, W. E., S. M. Carpenter, and J. T. Wood. 1982. Growth of grey kangaroos and the reliability of age determination from body measurements. I. The eastern grey kangaroo, Macropus giganteus. Australian Wildlife Research 9:9-20. Queller, D. C., and K. F. Goodnight. 1989. Estimating relatedness using genetic markers. Evolution 43:258-275. R Core Team. 2016. R: A language and environment for statistical computing. Rioux-Paquette, E., D. Garant, A. M. Martin, G. Coulson, and M. Festa-Bianchet. 2015. Paternity in eastern grey kangaroos: moderate skew despite strong sexual dimorphism. Behavioral Ecology 26:1147-1155. Schulke, O., J. Bhagavatula, L. Vigilant, and J. Ostner. 2010. Social bonds enhance reproductive success in male macaques. Current Biology 20:2207-2210. Seeman, T. E. 1996. Social ties and health: the benefits of social integration. Annals of Epidemiology 6:442-451. Sigg, D. P., A. W. Goldizen, and A. R. Pople. 2005. The importance of mating system in translocation programs: reproductive success of released male bridled nailtail wallabies. Biological Conservation 123:289-300. Silk, J. B., S. C. Alberts, and J. Altmann. 2003. Social bonds of female baboons enhance infant survival. Science 302. Silk, J. B., J. C. Beehner, T. J. Bergman, C. Crockford, A. L. Engh, L. R. Moscovice, R. M. Wittig, R. M. Seyfarth, and D. L. Cheney. 2009. The benefits of social capital: close social bonds among female baboons enhance offspring survival. Proceedings of the Royal Society B 276:3099-3104.
80 Chapter 3 Silk, J. B., Beehner, J.C., Bergman, T.J., Crockford, C., Engh, A.L., Moscovice, L.R., Wittig, R.M., Seyfarth, R.M., Cheney, D.L. 2010. Strong and consistent social bonds enhance the longevity of female baboons. Current Biology 20:1359-1361. Smuts, B. B. 1985. Sex and friendship in baboons. Transaction Publishers, New York. Takahata, Y. 1982. Social relations between adult males and females of Japanese monkeys in the arashiyama B troop. Primates 23:1-23. Van Hooff, J. A. R. A. M., and C. P. Van Schaik. 1994. Male bonds: affiliative relationships among nonhuman primate males. Behaviour 130:309-337. Vanpé, C., P. Kjellander, M. Galan, J.-F. Cosson, S. Aulagnier, O. Liberg, and A. J. M. Hewison. 2008. Mating system, sexual dimorphism, and the opportunity for sexual selection in a territorial ungulate. Behavioral Ecology 19:309-316. Warburton, N. M., P. W. Bateman, and P. A. Fleming. 2013. Sexual selection on forelimb muscles of western grey kangaroos (Skippy was clearly a female). Biological Journal of the Linnean Society 109:923-931. Whitehead, H. 2008. Analyzing animal societies: quantitative methods for vertebrate social analysis. University of Chicago Press. Wiszniewski, J., Corrigan, S., Beheregaray, L.B., Moller, L.M. 2011. Male reproductive success increases with alliance size in Indo-Pacific bottlenose dolphins (Tursiops aduncus). Journal of Animal Ecology 81:423-431. Wroblewski, E. E., C. M. Murray, C. F. Keele, J. C. Schumacher-Stankey, B. H. Hahn, and A. E. Pusey. 2009. Male dominance rank and reproductive success in chimpanzees, Pan troglodytes schweinfurthii. Animal behaviour 77:873-885. Young, C., B. Majolo, M. Heistermann, O. Schulke, and J. Ostner. 2014. Responses to social and environmental stress are attenuated by strong male bonds in wild macaques. Proceedings of the National Academy of Sciences of the United States of America 111:18195-18200. Young, C., R. McFarland, L. Barrett, and S. P. Henzi. 2017. Formidable females and the power trajectories of socially integrated male vervet monkeys. Animal Behaviour 125:61-67. Zenger, K. R., and D. W. Cooper. 2001a. Characterization of 14 macropod microsatellite genetic markers. Animal Genetics 32:166-167. Zenger, K. R., and D. W. Cooper. 2001b. A set of highly polymorphic microsatellite markers developed for the eastern grey kangaroo (Macropus giganteus). Molecular Ecology Notes 1:98-100.
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Chapter 4 – The social correlates of males’ testosterone and glucocorticoid levels in eastern grey kangaroos (Macropus giganteus)
Abstract In group-living mammals, males' testosterone levels may reflect a trade-off between greater dominance versus more amicable behaviour for social living. Numerous studies of mammals and birds have shown that stress inhibits the production of testosterone in males, but some species show an initial increase in testosterone after exposure to acute stress. We examined the associations between sociability and males’ hormone levels by untangling the relationships among male eastern grey kangaroos’ faecal testosterone (fT) and glucocorticoid (stress; fGC) levels, social relationships, gregariousness, frequency of presence in our site, exposure to competition and mating opportunities, and dominance. Hormones were measured from repeated sampling of faecal samples collected over 17 months from thirty-one adult males in Sundown National Park, Queensland. Testosterone was strongly positively related to dominance rank, and was higher in months with higher intensity of male-male competition and female courtship, consistent with the challenge hypothesis or linked to increased testosterone for reproduction. Counter to the many studies finding a negative relationship between stress and testosterone, we found a weak significant positive relationship between fT and fGC levels. Despite the strong association between stress and rank in many socially hierarchical mammals, dominance was not a significant predictor of males' fGC levels. Our measure of males' strength of social relationships was not related to levels of either of the hormones, but males that were more frequently present in our site had lower fT levels, which could indicate different reproductive strategies involving T-mediated roaming behaviour.
Introduction The field of behavioural endocrinology is now 70 years old, founded by Beach (1948) with the publishing of the book Hormones and Behavior. Since then, behavioural endocrinologists have been examining the links between hormones and behaviour in a multitude of species, with a focus on their reproductive, parental, and social behaviours. Testosterone (T) and glucocorticoids (GC; stress hormones) are considered social hormones, as they are influenced by and affect individuals’ social behaviours (Eisenegger et al. 2011, Adkins-Regan 2013). With the recent introduction of social network analysis in the field of behavioural endocrinology, we can now ascertain the links between individuals’ social network patterns and hormonal profile, increasing our understanding of the intricate relationships between individuals’ hormones and social relationships.
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Testosterone is linked to reproductive and territorial behaviour, aggression, competition, and dominance (Eisenegger et al. 2011). In humans, T has been linked to social status (Booth et al. 2006) and dominance (Mazur and Booth 1998). In species with strong male dominance hierarchies, T is linked to both individuals’ current and future dominance ranks (Beehner et al. 2006), with more dominant males having higher T levels (Rose et al. 1971, Arlet et al. 2011, Kalbitzer et al. 2015). Males’ T levels are usually higher during breeding periods, linked in part to males’ reproductive physiology, but also to levels of male aggression in a reproductive context. Variation in T levels can be explained in part by the “challenge hypothesis”, which posits that T levels in males increase over the short-term in response to a challenge by a conspecific male that threatens their reproductive success, for example from competition, territorial breaches, or attempted courtship with mates (Wingfield et al. 1990). First suggested for birds, the challenge hypothesis has also been supported in mammals (Woodroffe et al. 1997, Ostner et al. 2002, Bales et al. 2006, Cristobal-Azkarate et al. 2006). For example, while males mate with both types of females at equal rates, male chimpanzees (Pan troglodytes schweinfurthii) show increased T levels when they are with high-quality (parous) females in oestrous, with no change in their T levels when with low-quality (nulliparous) females, as the latter do not elicit competition among males (Muller and Wrangham 2004).
Glucocorticoids, including cortisol and corticosterone, are stress-response hormones, and have a major role in the hypothalamic-pituitary-adrenal axis. Released in response to stressful events, GCs divert energy from basic physiological processes for immediate use. The relationship between dominance rank and GC levels in male mammals has been investigated in a number of species, with very different findings. In some species, subordinates can be exposed to higher levels of aggression and thus have the highest stress levels, while in other species, high ranking individuals experience higher stress levels due to the constant challenge of their position (Creel et al. 2013). Differences in the rank-stress pattern may be linked to the energetic requirement of different ranking positions and the species’ social system (reviewed in Creel 2001, Goymann and Wingfield 2004, Sapolsky 2005, Creel et al. 2013). In a recent review of rank-related GC patterns in primates, Cavigelli and Caruso (2015) show that in some species, rank-related differences in the patterns of individuals’ GC levels may not be evident in the baseline levels, but only when short-term temporal patterns are examined. The rank-stress pattern can also differ among age groups; subordinate adult male rhesus macaques (Macaca mulatta) receive high levels of aggression and have higher stress levels, as measured from hair cortisol concentration, than dominant males, whereas this trend is not found within adolescent rhesus macaques (Feng et al. 2016).
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Having heightened T and GC levels can be deleterious for an animal’s health. The stress response is maladaptive in chronically stressed individuals, linked to negative health effects and fitness outcomes in many species (reviewed in McEwen 2008). Heightened GC levels in the long-term may suppress or compromise the immune system, cause tissue damage, and compromise growth and reproduction (Munck et al. 1984, Moore and Zoeller 1985, Dobson and Smith 2000, Schreck et al. 2001, Kiecolt-Glaser et al. 2003). However, further research in non-human animals is needed to fully understand the link between individuals’ GC patterns and their fitness outcomes (Beehner and Bergman 2017). Similarly to heightened GC levels, elevated T may increase males’ mortality risk, as T increases males’ metabolism, and because T acts as an immunosuppressant it can make males with high T more prone to disease (Alexander and Stimson 1988, Wingfield et al. 1997, Muehlenbein and Bribiescas 2005, Mills et al. 2009).
Studies have shown that the negative fitness consequences of chronically-elevated stress levels may be reduced by having strong social bonds and support. Strong social bonds between individuals have been linked to positive mental and physical health effects in humans (Holt-Lunstad et al. 2010, Umberson and Montez 2010), increased longevity and offspring survival in female chacma baboons (Papio hamadryas ursinus) (Silk et al. 2003, Silk et al. 2009, Silk 2010), and greater offspring survival in feral horses (Cameron et al. 2009). The fitness benefits of social relationships and social integration may be explained, in part, by the stress-buffering hypothesis, which stipulates that the presence of positive interactions with social partners acts as a buffer against stressors, decreasing the severity or duration of individuals' stress responses, thereby helping to mediate the negative health effects of chronic stress (Cohen and Wills 1985, Hennessy et al. 2009). Social support is negatively correlated with perceived stress in humans, and strong social bonds and interactions with bond partners are linked to lower stress hormone levels in non-human primates (Cohen 2004, Young et al. 2014, Wittig et al. 2016), while social isolation induces heightened stress responses in a variety of gregarious species (Cockram et al. 1994, Weiss et al. 2004, Toth et al. 2011). Many studies have shown the buffering effect of social relationships on stress, whereas the association can be in the other direction, with stress affecting social relationships. In an experimental study of housed meadow voles, females exposed to a stressor spent less time huddling with new partners compared to control females, suggesting that short-term increases in stress levels can impair these females’ ability to form new social preferences (Anacker et al. 2016).
84 Chapter 4 There is little evidence of direct relationships between T and social affiliation, however T in males has been negatively linked to pair-bonding and parenting behaviour in many species. Interspecific variation in testis size and circulating blood T levels has been linked to species’ mating systems, with males of monogamous species usually having smaller testes, lower ejaculation rates, and lower T levels than males of species in which females have multiple mates (Dixson 1997, Klein and Nelson 1998). Pair-bonding is vital in socially monogamous species and having lower T levels may help build this bond (Dibble et al. 2017). Research on the length of human males’ relationships with their partner found that the T levels of males in new relationships (less than 12 months) was the same as single males, but the testosterone levels of males that were in longer term relationships was lower (Farrelly et al. 2015), suggesting that lower testosterone may be more conducive to maintaining rather than building pair bonds. There is also strong evidence that T is linked to parenting effort in males. For example, male house sparrows (Passer domesticus) treated with T fed their nestlings less than did control males (Hegner and Wingfield 1987). However, the optimal T level might be higher than that required for maximising parenting effort, as there is a trade-off between parenting behaviour and male-male competition.
The steroid/peptide theory (S/P theory) by van Anders et al. (2011) extends the understanding of the competition/nurturance trade-off of T in pair-bonding and parenting to include social bonds with other individuals. The S/P theory suggests that there is a trade-off between competitive and nurturing behaviours mediated by T. Low T promotes infant-feeding behaviour and pair-bonding, however, the authors suggest that for social animals, low T may also promote other nurturing behaviours towards conspecifics, such as grooming and huddling (van Anders et al. 2011). In humans, high T levels are associated with antisocial behaviour (Rowe et al. 2004), and low T and GC levels may be linked to social bonding (Ketay et al. 2017). Ketay et al. (2017) found that individuals that had lower baseline T and cortisol levels reported feeling closer to others; this study also showed that doing a task that promotes greater closeness causes decreases in T, suggesting that the relationship between social-bonding and low T may be reinforcing. Research in this area is quite recent and only primates have been studied so far, so there is, to date, no evidence relating to T’s role in affiliative behaviours outside of parenting and pair-bonding in other mammals. The S/P theory stipulates that low T promotes nurturing behaviour, which includes grooming and huddling, however, it is not known whether this would also be the case for less socially complex animals where males do not exhibit parenting behaviours and adults do not groom one another.
85 Chapter 4 In this study, we examined the links between male eastern grey kangaroos’ (EGKs; Macropus giganteus) hormone levels and their social patterns. Ours is the first study to examine the hormonal correlates of males’ social relationships in a marsupial. Studying the social correlates of hormones in EGKs provides the opportunity to test whether the trends found in primates are evident in a social species in which males do not groom others, cooperate, or provide paternal care. Our objective was to examine how faecal T (fT) and faecal GC (fGC) metabolite levels related to wild male EGKs’ dominance ranking and sociability (with sociability described by patterns of individuals’ gregariousness and social relationships), accounting for other potentially related factors, including a proxy for the amount of grass available each month and a variable that reflected the relative intensity of male-male competition and the availability of oestrous females each month. Our aims were to test whether hormone levels patterns were consistent with 1) the stress buffering hypothesis, 2) an extended version of the S/P theory, and 3) the challenge hypothesis in males. The S/P theory was posited for species that exhibit nurturance behaviours; in our extended version we examine whether there is a link between T and strength of social relationships in species that do not groom or huddle.
Exploring the relationships between individuals' measures of sociability, social environments, and baseline hormone levels can provide insights into potential trade-offs of individuals’ social patterns. Furthermore, given the intricate relationships and feedbacks among different hormones, individuals’ behaviours, and dynamic physical and social environments, it has been difficult to unravel the links between hormones and behaviour. To further our understanding of the underlying mechanisms of these relationships, we must study a diversity of species with different evolutionary pasts and life histories. Our study strives to increase our knowledge on the relationships between T, GC, and individuals’ social connections in a species that has a lower social complexity than most other species studied in this field.
Methods Study site and study species Research on a population of wild EGKs was undertaken at Sundown National Park, QLD, Australia (28°55’03’’S, 151°34’46’’E), where kangaroos have been studied since 2009 (Favreau et al. 2010, Best et al. 2014). Individual kangaroos were recognised by unique features or the amalgamation of their morphological characteristics, shown to be a reliable method of recognising EGKs (Jarman et al. 1989, Best et al. 2013b). The 37.4 ha study area consisted of open pastures surrounded by mixed open woodland containing silver-leaved ironbark (Eucalyptus melanophloia) and cypress pine
86 Chapter 4 (Callitris intratropica). When kangaroos were not in our site, we assumed they were either in the surrounding forests or had travelled further to aggregate with individuals in other open areas, the closest of which was 1.5 km from the edge of our study area. We did not collect data for individuals when they were outside of our study area and thus our findings are limited to their behaviours within our site.
The EGK is a highly social macropod that forages in groups of 1 to over 20 individuals (Jarman 1987, Coulson 2009). EGKs have high fission-fusion dynamics (Aureli et al. 2008), foraging and resting in groups that frequently change in size and individual composition (Carter et al. 2009a). Kangaroos in larger groups likely benefit from shared predatory vigilance (Favreau et al. 2010, Pays et al. 2013). There are foxes (Vulpes vulpes) and wedge-tailed eagles (Aquila audax), which are predators of young EGKs (Jarman and Coulson 1989), at Sundown National Park. Although dingoes (Canis lupus dingo) have not been observed in our site, wild dogs have been spotted in other areas of the national park (Park Ranger Ian Elms, pers. comm.).
Males have a dominance hierarchy maintained through fights and displays (Jarman and Southwell 1986, Croft and Snaith 1990), but although males can supplant subordinates from a female, they do not defend a territory and multiple males can forage harmoniously in the same group. There is no paternal care, no evidence for any cooperative behaviour, and adults do not groom each other. However, despite their apparent lack of social complexity, females have been found to preferentially associate with particular females; these pairs of females spend more time foraging in groups together than predicted from their spatial overlap (Best et al. 2014).
As these were wild animals that could roam freely within and outside of our study area, and members of a kangaroo population differ in their home ranges, the adult males that we studied differed in the parts of our site they used and how often they were present in the site. Previous research in our site focused only on adult females and their young, and the ages of only two of the small adult males were known, as the other males were either born before our research group started studying this population or immigrated from outside our study area.
Sociability measurement and analyses Fieldwork for this project was conducted for twelve days each month between January 2014 and February 2016. Data on individuals' social associations and grouping patterns were gathered each day for all individuals found within the study site; either in the early morning, or late afternoon
87 Chapter 4 when the kangaroos were most active and when most individuals were foraging. On rare occasions, we missed a sampling session due to extreme weather conditions. Groups were determined using a fifteen-metre chain rule, whereby individuals found within fifteen metres of at least one other individual were recorded as belonging to the same group (Jarman 1987, Carter et al. 2009a, Favreau et al. 2010, Best et al. 2013b). All individuals in a group were identified. For each individual, we recorded group size, nearest neighbour identity and distance, and their location using a handheld Garmin eTrex GPS (Garmin International Inc., Olathe, KS, U.S.A), which is accurate to 3 metres. We used the 'gambit of the group' method, which assumes that all individuals within a group are associating with each other (Whitehead and Dufault 1999, Franks et al. 2009). Monthly mean group sizes were calculated for all males.
Daily group compositions were analysed using the R (R Core Team 2016) package sna (Butts 2016). We calculated the proportion of time that individuals were in groups together using half- weight indices (HWI) between dyads (Whitehead 2008):
푋 퐻푊퐼 = 1 푋 + 푌 + (푌 + 푌 ) 푎푏 2 푎 푏 where 푋 is the number of times that individuals a and b were sighted in the same group in the same session, 푌푎푏 is the number of times a and b were sighted in different groups in the same session, and
푌푎 and 푌푏 are the number of times that individuals a or b were sighted in a group and the other individual was not sighted in that session. We then calculated the strength (sum of HWIs) of males’ strongest ten associations with females (“top 10 score”) (Whitehead 2008, 2009). Overall strength of associations, the sum of individuals' HWIs, is a measure of gregariousness (Barthélemy et al. 2005), whereas the strength of individuals’ strongest associations shows how close they are to particular individuals. Individuals with a high top 10 score spend a greater amount of time with specific individuals, perhaps showing stronger social bonding or preference of association for particular individuals. We focused on males’ relationships with females, as some male-male relationships may lead to heightened stress levels in males thus biasing results because male kangaroos can aggressively fight for dominance.
Dominance ranking Agonistic interactions between males were recorded ad libitum. These included submissive behaviours, threat displays, and fighting (reviewed in Ganslosser 1989); when any of these interactions were observed, this was considered an agonistic event. Agonistic events in which a
88 Chapter 4 male coughed - a submissive behaviour (Coulson 1997b) - at another male, were used in dominance analyses. The R package steeptest was used to obtain an estimate of individuals' relative dominance using normalised David's scores (de Vries et al. 2006). We used David's scores, as this ranking system has been found to provide accurate and reliable estimates of individuals’ relative dominance, even with missing dyadic data and repeated interactions between individuals (Gammell et al. 2003, de Vries et al. 2006).
Male kangaroos have indeterminate growth (Poole et al. 1982), so we grouped adult males into size categories by visual assessment, with males characterised as either small, medium, or large-sized. Visual assessments of size categories was recorded by one observer, the field researcher (P. Corvalan), every month for all males that were present in the site. Small males were approximately the same size as an adult female, medium males 1.5 times the size of adult females, and large males twice the size of adult females. Small males had small chests and undeveloped biceps musculature, while large males had large chests and bicep muscles. It was assumed that larger males would be dominant over smaller males. As not all pairs of males were observed in dominance interactions, we believe that males’ David’s scores could be biased due to males tending to interact more with males within their own size category (see chapter 2). To address this issue, we estimated males’ dominance ranks by combining their David’s scores and sizes, ranking males according to their size category first, and then their ranking within their size category according to their David’s score. The large male with the highest David’s score was given a rank of 1, with the second most dominant male given a rank of 2, and so forth.
Competition and courtship For each of the 17 months, we calculated (1) the total number of agonistic interactions observed among males, (2) the number of courtship events (defined by a male engaging in behaviours performed in a sexual context (described in Coulson 1997b) in a given morning or afternoon sampling session) recorded, and (3) the number of different males recorded in our surveys that month. We divided these metrics by the number of surveys we conducted each month, as our monthly sampling intensity differed slightly due to weather conditions. As these three variables were all correlated, we conducted a principal components analysis with the first component explaining over 80% of the variation in our data (supplementary material). This first component was equally positively loaded for all three variables, with high values denoting months when there were more males present, more agonistic encounters, and more courtship events. We used this first
89 Chapter 4 component as a measure of the relative amount of male-male competition and courtship (i.e. competition and courtship intensity score) that occurred in the study area each month. Rainfall We obtained the total rainfall and maximum temperature each month from the Australian Bureau of Meteorology website for the Texas Post Office station (station number: 041100; 28°51’00” S, 151°10’12” E), which was approximately 40 km from our study site. The rainfall was highly variable in our site, ranging from 6.4 ml to 197.2 ml with an average monthly rainfall of 50.1ml in 2014-2015. The previous month’s total rainfall was considered a proxy for kangaroos’ food availability, as total monthly rainfall in our site has been shown to be strongly correlated to green grass abundance in the following month (Menz et al. 2017).
Hormone analysis Faecal samples were collected from thirty-three adult males between October 2014 and February 2016. Numerous studies have been successful at quantifying individuals’ hormone levels from faeces, and this methodology has the advantage of being non-invasive, thereby avoiding both research-induced stress on animals through manipulations required in the collection of blood samples, and the measured hormone levels being affected by capture (Goymann et al. 1999, Dehnhard et al. 2001, Shutt et al. 2007). Collecting faecal samples instead of blood also allowed for more samples to be collected over time with little disruption to the social grouping patterns of the kangaroos. Although faecal samples reflect an average of the kangaroos’ hormone levels from the previous days (Fanson et al. 2017), samples were only collected in the morning during the first three hours after sunrise to minimise effects of time of day on circulating hormone concentrations (Touma et al. 2003). We waited at least two days before resampling a given male.
Faecal samples were made up of multiple pellets, and samples were homogenized prior to extraction. Faecal hormones were extracted by mixing 0.49-0.51 grams of wet faeces in 5 mL of 80% methanol using the overnight rack shaker method (for more detail see Sherwen et al. 2015). Individuals' GC and T levels were estimated by measuring faecal GC (fGC) and T (fT) metabolites by enzyme immunoassay. The 37e assay, developed for wild mice (Musculus musculus) (Touma et al. 2003) and validated for EGKs (Fanson et al. 2017) measures GC metabolites with a 5α-3β, 11β- diol structure. Standards, antibodies and labels were obtained from the Institute of Biochemistry, University of Veterinary Medicine, Austria. The polyclonal anti-testosterone antibody R156/7 and testosterone-3CMO- HRP conjugate, supplied by Coralie Munro from the University of California Davis, were used to measure T metabolites. The T antiserum was raised in rabbits against 6-
90 Chapter 4 carboxymethyloxime-testosterone-BSA, and had immuno-cross reactivities of 100% with T, 29% with 5alpha-dthydrotestosterone, 0.5% with androstenedione, and < 0.1% with 6 other steroids, including estradiol, progesterone and cortisol. The T assay has been validated in EGKs (Hilton 2019). The optical density of samples was analysed using a Dynex Technologies MRX II and results were examined using the Dynex Revelation 4.25 program. All samples were run in duplicate. Samples were run across multiple plates and were randomly assigned to plates, so that samples from different males and months were run on the same plate. Inter-assay CV was below 10% and intra-assay CV below 15% for both assays.
As the water content in grass varies seasonally and kangaroos are geophagous (Best et al. 2013a), we accounted for differences in pellets’ moisture and inorganic content, providing a more accurate estimate of the samples’ hormone levels. The organic matter content and dry weights of samples were calculated by drying and burning each sample. The samples were first dried overnight (17 hours) in a 60C° oven to determine the percentage of water in the sample. Organic matter and ash content were then determined by combustion in a 550C° muffle furnace (Modutemp Pty. Ltd.; Perth, WA, Australia) for 8 hours (AOAC 1990). The fGC and fT measures of each sample were corrected for their water and inorganic contents, to determine the amount of hormone in the dry organic part of the sample. Only males for which we had collected a minimum of four faecal samples were included in analyses.
Statistical methods All analyses were performed in the statistical environment R (R Core Team 2016). We used the package lmerTest to fit two linear mixed models (LMM), one with males’ fGC levels and the other with males’ fT levels as the response variable. We log transformed males’ fGC and T levels to normalize these variables. Our fixed predictors were the males’ dominance rank, top 10 score, average group size, the monthly competition and courtship intensity score and lagged rainfall, and our random factors were male ID, month, and the assay that the hormones were measured in as random factors. We included the other hormone as a predictor, as previous studies have shown that they can be correlated. We fit two more linear models to examine how males’ hormone levels varied by the number of times they were observed in our site, including this variable in identical models as the ones above except without top 10 score, as these two variables were highly correlated (Pearson correlation, r = 0.77, p < 0.001).
91 Chapter 4 We tested for 1) the social buffering hypothesis and 2) an extended S/P theory by examining whether there were relationships between males’ fGC and fT levels with their top 10 score. We also tested whether our findings were consistent with the 3) challenge hypothesis, by examining whether males’ fT levels were higher in months with more intense competition and courtship. The response variables were logged to normalise them and all predictors were scaled by subtracting the mean and dividing by the standard deviation. R-squared values were examined using the package MuMin (Bartoń 2016), which provides a marginal R-squared value showing the proportion of the variation explained by the fixed effects, and a conditional R-squared value showing the proportion of the variation explained by both the fixed and random effects. Samples with missing data were removed. Variance inflation factors were below 2. We used standard errors around the mean.
The significance of the social network variable in our models (top 10 score) was determined using randomisation tests. We conducted 1000 permutations of the group association dataset to create randomised networks using the R package asnipe (Farine 2013). These permutations randomised individuals’ grouping patterns, while keeping the group sizes and numbers of groups per session the same as in our original surveys (Bejder et al. 1998). The numbers of sightings of individuals in these permutations also remained the same as in our surveys, controlling for any effects of numbers of sightings in our models. These randomisations allowed us to account for the non-independence of social network measures, with p-values for the social network measure calculated by comparing the model parameters of the observed and randomised data.
Results Faecal samples and observations Although there were approximately 300 individuals that frequented our site in 2014-2015, we only observed a mean of 70 individuals (73.2 +/- 1.4) and a maximum of 186 individuals during our 2-3 hour data collection periods. Over 60 adult males were observed in our site during our study. We had sufficient social data and faecal samples for further analyses on thirty-one adult males. These 31 males were sighted in surveys from 15 to 217 times per individual. We analysed a total of 476 faecal samples collected from these 31 males, with an average of 15.4 (± 1.9) samples per male. There was an average of 68.4% (± 0.3%; range: 37.6 – 81.0%) water in the fresh faecal samples and 22.1% (± 0.3%; range: 10.6 – 64.9%) inorganic content in the dried faecal samples. A total of 433 agonistic interactions were recorded during the course of our 17 month study.
92 Chapter 4 Factors relating to males’ fT metabolite levels Testosterone was not correlated to males’ top 10 score (linear mixed model, estimate = -0.087 ± 0.037, p = 0.134; supplementary material). However, T was significantly correlated with our intensity of competition and courtship score with males’ fT levels higher in months when there were more males present, more courtship events, and more male-male agonistic encounters (Table 4.1; Figure 4.1). Males’ fT levels were also significantly correlated with their dominance rank, with more dominant males having higher fT levels (Figure 4.2). Males that were seen more frequently in our site had significantly lower fT levels (Figure 4.3). There was no correlation between the number of times males were observed in our site and their dominance rank (Spearman correlation, r = 0.22, p = 0.23). There was a significant but slight positive relationship between males’ fT and fGC levels (Figure 4.4). Males’ fT levels differed significantly among individuals, months, and assay plates, with ID accounting for 13.8%, month 8.0% , and assay plate 38.1%, of the variation in the faecal samples’ T levels. The marginal R-squared value was 0.345 and the conditional R-squared value was 0.736.
Table 4.1. Estimates and standard errors in the linear mixed model used to explain male eastern grey kangaroos’ faecal testosterone metabolite levels.
Variable Estimate Standard error t value P value
Intercept 5.259 0.068 76.986 <0.001 Competition and courtship intensity score 0.087 0.033 2.627 0.029 Dominance rank -0.223 0.031 -7.126 <0.001 Rainfall -0.027 0.031 -0.885 0.403 log GC 0.036 0.013 2.682 0.008 Average group size 0.038 0.037 1.032 0.300 Frequency seen -0.116 0.041 -2.801 0.009 A LMM was used to examine males’ testosterone levels (log fT ~ Competition and courtship intensity score + David’s score + Rainfall + log GC + Average group size + Frequency seen + (1|ID) + (1|Month) + (1|Assay)). Bolded variables indicate a significant effect using a threshold of 0.05.
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Figure 4.1. Variation in the logged values of faecal testosterone metabolite levels against monthly intensity of competition and courtship in the study area, taken from a principal components analysis of the numbers of males present, agonistic events recorded, and courtship events recorded each month. Dots are the observed values and the grey shaded area shows the 95% confidence interval. The x-axis is the competition and courtship intensity score, with higher values reflecting months with more intense levels of competition and courtship.
Figure 4.2. The relationship between males’ dominance ranks and faecal testosterone metabolite levels. The highest ranking male had a dominance rank of 1. Dots are the observed values and the grey shaded area shows the 95% confidence interval.
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Figure 4.3. Faecal testosterone metabolite levels as a function of the frequency that male eastern grey kangaroos were observed in our site. Dots are the observed values and the grey shaded area shows the 95% confidence interval.
Figure 4.4. The relationship between male eastern grey kangaroos’ faecal GC and testosterone metabolite levels. Dots are the observed values and the grey shaded area shows the 95% confidence interval.
Factors relating to males’ fGC metabolite levels Male EGKs’ fGC levels ranged from 101 to 4810 ng/g and differed significantly among months (Figure 4.5) and assay plates, but not among individuals. There were no significant trends with any of our other predictor variables (Table 4.2), including no relationship with the frequency that males were observed (linear mixed model, estimate = -0.027 ± 0.039, p = 0.505). Month accounted for 5.9% and assay plate 14.5% of the variation in levels of fGC metabolites. The marginal R-squared value was 0.040 and the conditional R-squared value was 0.295.
95 Chapter 4 Table 4.2. Estimates and standard errors in the linear mixed model used to explain male eastern grey kangaroos’ faecal glucocorticoid metabolite levels.
Variable Estimate Standard error t value P value
Intercept 6.305 0.050 126.016 <0.001 Competition and courtship -0.031 0.034 -0.909 0.377 intensity score Dominance rank -0.036 0.031 -1.144 0.268 Rainfall 0.035 0.032 1.110 0.287 log T 0.046 0.025 1.807 0.072 Average group size -0.032 0.033 -0.977 0.341 Top 10 score -0.010 0.035 -0.289 0.548 A LMM was used to examine males’ fGC levels (log fGC ~ Competition and reproduction + David’s score + Rainfall + log fT + Average group size + Top 10 score + (1|ID) + (1|Month) + (1|Assay)). Bolded variables indicate a significant effect using a threshold of 0.05. The p value for top 10 score was obtained from randomisation tests.
Figure 4.5. Male EGK’s faecal glucocorticoid metabolite levels across the seventeen months of our study. The thick line is the median value for each month, with interquartile range shown by the box and the range of values by the vertical line. The dots are the outliers for each month.
Discussion Males’ faecal testosterone metabolite levels varied temporally and with males’ dominance ranks and social environments. We found that more dominant males had higher T levels, which is consistent with the trend found in many other species with dominance hierarchies (Rose et al. 1971, Clarke and Faulkes 1998, Eisenegger et al. 2011). In months when there were high levels of competition and courtship behaviour, males had elevated T levels, a trend consistent with the challenge hypothesis. However, a more detailed examination of males’ behaviours and subsequent T levels would be needed to untangle the two possible explanations for increasing T during peaks in breeding, namely baseline T increases for reproduction, and shorter-term increases due to bouts of
96 Chapter 4 competition. Males that were more frequently seen had lower T levels, which could indicate different reproductive strategies involving T-mediated roaming behaviour that may be adopted by male EGKs. The stress levels of male eastern grey kangaroos did not differ significantly among individuals and were not related to the strength of males’ social relationships or their dominance ranking, and thus we did not find evidence for stress-buffering in male EGKs. Water content and inorganic matter of kangaroos’ faecal samples varied a lot, and we recommend that future studies account for these, especially for wild or geophagous species, or animals exposed to variable diets and/or water availability.
We did not find a relationship between males’ strengths of social relationships and their T levels. Thus, we did not find evidence for a trade-off between male kangaroos’ sociability and their competitiveness mediated by T, as has been found in more socially complex species (van Anders et al. 2011). Kangaroos do not huddle, groom, or pair bond, nor do males care for infants and the steroid peptide theory may not extend to social species that do not exhibit the “nurturing” behaviours described in van Anders et al. (2011)’s review. We did, however, find that males that were more frequently present in our site had lower T levels. Males that visited our site infrequently likely had larger home ranges and spent time in other unmonitored open pastures with groups of kangaroos and travelling between these areas. Alternatively, it is possible that males that were infrequently in our site were more solitary and spent more time in the surrounding forests grazing alone or in small groups.
Testosterone has been linked to activity, roaming behaviour, and boldness (Chandler et al. 1994, Sinervo et al. 2000, Raynaud and Schradin 2014). Male side-blotched lizards (Uta stansburiana) have different reproductive strategies, and the roamers with bright orange throats were found to have larger home ranges, and higher endurance, activity and T levels than the blue- and yellow- throated males (Sinervo et al. 2000). The causal effect of T was shown by administering T implants to the blue- and yellow-throated males; similar trends resulted to the natural variation between morphs, with the treated males showing increased home ranges, endurance, and activity level (Sinervo et al. 2000). Male kangaroos that have a smaller home range could have stronger social relationships with the females they forage with and be more likely to sire their offspring. Males with large home ranges would be exposed to more females and may therefore have a higher overall reproductive success as they have a higher chance of encountering females in oestrous. However, these roamers might have a higher mortality rate, similarly to the lower survival of orange-throated lizards (Sinervo et al. 2000), and because dispersing kangaroos face greater mortality risks (Coulson
97 Chapter 4 1982, Coulson 1997a). We did not find a significant relationship between dominance rank and the number of surveys in which males were seen within our study site, a measure which likely reflects their roaming behaviour. Thus, the positive relationship between EGK’s frequency of presence in our site and T levels may be evidence of different reproductive strategies used by males, with males’ roaming behaviours mediated by T.
Our data show that T levels vary seasonally, with higher T in months with greater intensity of competition and courtship, consistent with the challenge hypothesis (Wingfield et al. 1990). Although female EGKs can go into oestrous at any time of the year, there are approximately two- three months in the summer (December-January) each year when most females are in oestrous (Rioux-Paquette et al. 2015). In our site, these were also the months when more males were present, and there were more male-male agonistic interactions and courtship behaviour. We found that males’ fT levels were higher in these months, likely because they were in competition with other males for access to females and needed a greater sperm production for multiple matings and greater success in sperm competition. We cannot determine if T levels were higher in the peak breeding season due to the need for increased spermatogenesis, or whether it was in response to the greater levels of male-male competition.
There was a statistically significant but weak positive relationship between males’ T and GC levels in the testosterone model. These hormones usually have a negative relationship, as acute stress responses lead to a decrease in energy allocated to reproduction, with GC having a direct negative effect on T levels, by suppressing its production (Cumming et al. 1983, Orr and Mann 1992). There can be uneven distribution of hormones in faecal pellets (Hadinger et al. 2015), and some of our faecal samples may have had higher overall levels of hormones than others, thereby creating a positive relationship between GC and T. This is unlikely, however, as multiple faecal pellets were homogenised for each sample. Faecal GC levels in EGKs peak 0.8 days (0.4 – 1.4 days) after application of a stressor, suggesting that the faecal samples show an average of the hormone levels over the previous day (Fanson et al. 2017). We would expect males’ GC levels to be highest during months when there were more agonistic interactions and greater reproductive efforts (Fichtel et al. 2007), however, these were also the months when we expected and found males to have higher T levels (Wingfield et al. 1990). Therefore, the seasonal trends that may be affecting males’ GC levels may be the same ones that affect their T levels, resulting in a positive relationship between males’ fGC and fT levels, as was found in this study. Furthermore, males’ GC levels may not have been
98 Chapter 4 elevated from their normal, healthy ranges, and thus were not negatively affecting their testosterone production.
Males’ fGC levels differed among months, but were not explained by the previous month’s rainfall, a proxy for food abundance (Menz et al. 2017) or the intensity of competition and courtship each month. We did not find a relationship between stress and the strength of males’ social relationships with females, and thus do not have any evidence that male kangaroos receive stress-buffering benefits from being socially close to particular adult females. Similar to our study, no relationship was found between social metrics and baseline stress levels in yellow-bellied marmots (Marmota flaviventris) (Wey and Blumstein 2012). The lack of a social buffering effect may be more common in males than females. In a laboratory experiment where mice were exposed to a stressful event and then housed alone or with a partner, researchers found that females housed with a partner had a lower stress response than when housed alone, while males’ stress responses did not differ when alone or with a partner (Sterley et al. 2018). Human males have higher mortality effects of social isolation than females, which may be due in part to their higher inflammation responses to stressors (Yang et al. 2013). Further research on females’ stress levels is needed to determine whether there are sex differences in kangaroos’ stress responses. Furthermore, our study focused on adult males’ social relationships with adult females, whereas males may experience social buffering from their relationships with other males, especially for younger males that appear to form stronger associations with other young males. We were not able to examine the interaction between age and male-male social relationships on males’ stress levels, as we did not have data on the age of males and did not collect data from sub-adult males. As males age, their relationship with other males changes, and we suggest that studies assess the effect of age on the relationship between males’ sociability and aspects of their fitness.
Studying the relationships between stress, sociability and fitness is complicated by intraspecific differences in physiological homeostatic ranges, stress reactivity, and individuals’ perceptions of the social environment. Although affiliative social relationships and interactions can reduce individuals’ stress responses, their social environments, hierarchical positions, and exposure to agonistic interactions can also increase their stress levels (Creel 2001, Crockford et al. 2008, Nuñez et al. 2014). It has also been suggested that wild animals do not experience chronic stress, as it is maladaptive, and that chronic stress may only be evident in humans and other social primates, captive animals, and some wild species in environments affected by human activity (reviewed in Beehner and Bergman 2017). A longer-term study on the fitness correlates of kangaroos’ GC levels
99 Chapter 4 is needed to determine whether high baseline GC levels affect individuals’ survival and reproductive success.
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123 Chapter 4 Supplementary Material Chapter 4
Table S4.1. Principal component analysis of males’ competition and courtship behaviours Principal Principal Principal Component 1 Component 2 Component 3 Nº agonistic interactions 0.574 -0.664 0.479 Nº courtship events 0.571 0.744 0.348 Nº adult males present 0.587 -0.074 -0.806
Standard deviation 1.627 0.469 0.363 Proportion of variance 0.883 0.073 0.044 Cumulative Proportion 0.883 0.956 1.000
Table S4.2. Estimates and standard errors in the linear mixed model used to explain male eastern grey kangaroos’ fT levels, with top 10 score as a predictor
Variable Estimate Standard error t value P value Intercept 5.280 0.068 78.028 <0.001 Competition and courtship 0.091 0.031 2.909 0.019 intensity score Dominance rank -0.225 0.034 -6.761 <0.001 Rainfall -0.031 0.029 -1.057 0.323 log fGC 0.034 0.013 2.714 0.007 Average group size 0.0003 0.013 0.020 0.984 Top 10 score -0.069 0.029 -2.323 0.537 A LMM was used to examine males’ GC levels (log fT ~ Competition and courtship + David’s score + Rainfall + log fGC + Average group size + Top ten HWI + (1|ID) + (1|Month) + (1|Plate)). Bolded variables indicate a significant effect using a threshold of 0.05. The p value for top ten HWI was obtained from randomisation tests.
124 Chapter 5
Chapter 5 – Social correlates of survival in female eastern grey kangaroos (Macropus giganteus)
Abstract Animals’ grouping patterns and social bonding can affect their survival. In gregarious species, being in larger groups tends to provide anti-predatory and foraging benefits, with individuals in larger groups having a lower mortality risk. The survival benefits of social relationships have only been examined in more recent years, with a few studies in mammals showing that individuals with strong social bonds have higher survival, in part linked to the stress-buffering effects of having close relationships. However, another study has linked social relationships to higher mortality, and we do not fully understand the fitness trade-offs of social bonds that different species may face. Our study examined the social correlates of survival in female eastern grey kangaroos (EGKs; Macropus giganteus) in a wild population at Sundown National Park in Queensland, Australia, also testing the effects on survival of females’ boldness and body condition, and the temperature and rainfall that females were exposed to. We used a mark-recapture model to estimate females’ survival over three- month periods from January 2010 to December 2015. Of 138 adult females observed in our site in 2010, 78 were no longer present in the last year of our study. Females’ probability of survival significantly increased with their average group size, body condition, and lagged rainfall. There was a trend showing a decrease in survival with temperature, but this was not significant. As it is unlikely that kangaroos died from predation in our site, the relationship between survival and group size may be driven by foraging benefits. Previous research has shown that kangaroos in larger groups spend a smaller proportion of time being vigilant, thus allowing for more foraging time, but it is not known whether this would have a noticeable impact on individuals’ survival. Further research is needed to understand the underlying mechanisms driving the relationship between group size and survival in female EGKs.
Introduction Associating and interacting with conspecifics can have fitness trade-offs. For example, cooperative hunters rely on each other for access to food and cooperative breeders could not raise as many young without the help of subordinates. These benefits may occur at the detriment to some individuals’ direct fitness, but could increase individuals’ inclusive fitness in animals living with close kin (Packer and Ruttan 1988, Creel and Creel 1995, 2015). Direct fitness consequences of being sociable (i.e. gregariousness and strength of social relationships) have also been found in
125 Chapter 5 mammals that form social bonds with genetically unrelated individuals. Females with strong social relationships have been found to have greater reproductive success in some species (Cameron et al. 2009, Silk et al. 2009, Vander Wal et al. 2015), yet higher sociability has also been linked to lower reproductive success in another species (Wey and Blumstein 2012). For iteroparous organisms, an individual’s reproductive output is not just a function of their birth rate, as their longevity also affects their overall fitness.
Individuals’ risk of mortality can be affected by their gregariousness (reviewed in Hofmann et al. 2014). The benefits of group living linked to anti-predatory and foraging benefits. When in larger groups, individuals have a lower predation risk, explained by the many-eyes hypothesis and the dilution and confusion effects, and can allocate less time to predatory vigilance and more time to foraging, increasing their probability of survival (Vine 1973, Treisman 1975, Landeau and Terborgh 1986, Brown and Brown 1987, Delm 1990, Jakob 1991, Molvar and Bowyer 1994, Blumstein and Daniel 2003). Grouping also provides the opportunity for social learning, providing individuals with critical knowledge or skills (Heyes 1994). However, individuals in groups can be harmed by conspecifics, and face greater competition for resources (Beauchamp 1998, Hintz and Lonzarich 2018). Individuals have a greater exposure to parasites and pathogens when in large groups (Altizer et al. 2003, Kappeler et al. 2015), but recent research suggests that group-living can also expose animals to low doses of pathogens and commensal microbes that can help build individuals’ resistance and tolerance to pathogens (Ezenwa et al. 2016).
Individuals’ social relationships have been positively linked to survival in some primate species, explained in part by the stress buffering hypothesis, which suggests that having social support and strong social bonds can buffer the impact of stressful events (Cohen and Wills 1985). Being socially isolated is one of the strongest predictors of mortality in humans (Holt-Lunstad et al. 2010). In female chacma baboons (Papio hamadryas ursinus), females’ top social partners were tracked throughout their lifetime, and those with stronger social relationships and more consistent top social partners were found to live longer than females with weaker and shorter lasting relationships (Silk 2010). The size of an individual’s familial network can also be a predictor of survival; more socially integrated female rhesus macaques (Macaca mulatta), measured from the number of close female relatives, had greater survival than females with fewer relatives (Brent et al. 2017).
Similar trends have been found in non-primate mammals. After the removal of 40% of individuals in a population of feral horses (Equus caballus), more sociable juvenile horses (those with a larger
126 Chapter 5 number of social relationships) had a higher probability of survival, especially for those juveniles that lost their parents and were not in their natal groups (Nuñez et al. 2015). Individuals’ early social network metrics have also been linked to their survival, with juvenile male bottlenose dolphins that were more centralised in their networks having a higher probability of survival (Stanton and Mann 2012). Male killer whales (Orcinus orca) that were more centralised in their social network were found to have a lower risk of mortality, likely linked to social information transfer and food-sharing during times of low food availability reducing their risk of starvation (Ellis et al. 2017). In rock hyraxes (Procavia capensis), individuals living in groups with lower variance in individual centrality - groups where social relationships were more equal - were found to have lower mortality (Barocas et al. 2011).
However, social relationships can also hinder individuals’ survival, as being social can be time costly or can lead to social stress, mostly in species with social hierarchies (Tamashiro et al. 2005). More sociable yellow-bellied marmots (Marmota flaviventer), measured from the strength of individuals’ affiliative relationships, were more likely to die during hibernation (Yang et al. 2017), and Blumstein et al. (2018) found that the less social the marmots the greater their longevity. Marmots, unlike primates and social ungulates, are facultatively social and do not display any cooperative behaviours. The authors argue that being more socially connected is costly in facultatively social species and may not confer any benefits to resident adults (Blumstein et al. 2018). The consistency of strong social relationships can also be important, as was found in blue monkeys (Cercopithecus mitis stuhlmanni); females that had strong social bonds that were inconsistent (i.e. different top partners) between years had a higher mortality risk than females with weak social bonds (Thompson and Cords 2018). These findings challenge the social buffering hypothesis that simply having strong social relationships helps to buffer against the deleterious effects of stress and show the need to test whether sociability and longevity are positively or negatively correlated in other social species.
Individuals’ personality can also be linked to their survival. In a study on the association between personality and survival, Weiss et al. (2013) found that more extraverted gorillas (Gorilla gorilla gorilla) had greater longevity. The personality traits of these captive gorillas were determined from surveys of their keepers, with extraverted individuals considered to be sociable, playful, active, popular, and curious, and not solitary or slow (Weiss et al. 2013). Individuals’ boldness can also impact their survival. A meta-analysis of animals’ personality found that although bold individuals tend to have higher reproductive success, they also tend to experience higher risk of mortality
127 Chapter 5 (Smith and Blumstein 2008). However, studies have reported both negative and positive links between boldness and survival, such as in reintroduction programs where bold captive-bred swift foxes (Vulpes velox) were more likely to die after release (Bremner-Harrison et al. 2004), compared to the higher survival of bold Tasmanian devils after translocation (Sarcophilus harrisii) (Sinn et al. 2014).
In this study, we sought to examine the relationships between sociability and survival in a species with high fission-fusion dynamics (i.e. with frequent changes in group membership) (Aureli et al. 2008) that does not exhibit cooperative behaviours. We studied adult female eastern grey kangaroos (EGKs; Macropus giganteus) over a period of six years. We examined the links between survival and females’ gregariousness, strength of social relationships, body condition, and boldness. We also examined the variation in survival with rainfall and temperature to determine whether female kangaroos’ survival may be linked to environmental factors. As we did not have data for the full lifespan of individuals and deaths could not be confirmed, we used a mark-recapture model to estimate apparent annual survival of adult females (White and Burnham 1999). Studies on EGKs found that females in larger groups spent less time being vigilant, allowing for more foraging time (Dannock et al. 2013), and thus we hypothesised that more gregarious females would have a higher probability of survival. We also hypothesised that females with stronger social relationships would have greater survival, consistent with the stress buffering hypothesis. However, it is not known whether female kangaroos experience stress buffering when they have stronger social relationships, and an alternative hypothesis is that having stronger social relationships can negatively impact individuals and that kangaroos would show a negative correlation between the strength of their social relationships and survival. As females in poor condition would be more likely to die, we hypothesized that survival would show a positive relationship with females’ body conditions. We hypothesised that bolder females would have higher survival, as it was believed that bolder females would spend less time being vigilant and more time foraging. Periods of drought are linked to mortality in kangaroos (Caughley et al. 1985), and we predicted that the lower the rainfall the lower females’ survival. We hypothesized that higher temperatures would be linked to greater mortality of kangaroos, and that there would be a negative relationship between survival and temperature.
We do not fully understand what aspects of species’ social lives and environmental contexts lead to the drastic differences in the link between sociability and fitness, partly because there have been relatively few studies on sociability and longevity in mammals, as many large sociable species are long-lived animals. Using mark-recapture techniques, research groups that have observed animals
128 Chapter 5 over a significant span of their lifetime can study direct fitness consequences beyond reproductive success (Kanive et al. 2015, Martin et al. 2017). We discuss how mark-recapture analyses could be a valuable tool in examining the fitness consequences of sociability in a diversity of species.
Methods Study area and study species We observed kangaroos within a 37.4 hectare area in the south-western part of Sundown National Park, Queensland, Australia (28°55’03’’S, 151°34’46’’E), where eastern grey kangaroos have been studied since 2009. This area contained open grassland where the kangaroos foraged during the day, and mixed woodland to which the kangaroos often retreated on hot days or cold nights. There are two main seasons in this part of Australia, although their timing differs slightly among years. The dry season around May-November is characterised by low rainfall and lower temperatures, and the wet season around December-April by high rainfall and higher temperatures.
The females used in our analyses were those that were adults in 2010-2011 and observed a minimum of ten times in those two years. Our minimum sighting threshold was to ensure we only included females that were more regularly observed in our site, thereby reducing the chances of including females who may have stopped using the site due to slight home range shifts. We focused on females rather than males, as dispersal is male-biased in eastern grey kangaroos (Zenger et al. 2003, Coghlan et al. 2017).
Data collection We visited the field site 10-14 days each month from January 2010 to December 2013, and 12 days each month from January 2014 to February 2016. As EGKs are crepuscular, we observed them during the 2-3 hours after sunrise and before sunset. We collected group composition data, which consisted of walking around our study site and recording the identities of all individuals observed and which individuals were in groups together. Groups were defined using a fifteen-metre chain rule with all individuals within 15 metres of at least one other group member considered to be part of that group. This criterion for grouping was validated at our study site based on patterns of vigilance behaviour (Favreau et al. 2010). Kangaroos were recognised from unique morphological features (Jarman et al. 1989, Best et al. 2013).
129 Chapter 5 Social attributes We only examined the relationships of females with other females. Adult males can disrupt females when they are foraging (Poole and Catling 1974), with a study in our site showing that females’ social vigilance was affected by males’ presence/ absence (Dannock et al. 2013). We thus focused solely on females in our site. We measured a female’s average group size as the average number of independent (i.e. weaned) females in the foraging groups that she was observed in. This measure was considered to reflect the gregariousness of individuals and their group size preferences, with those having a low average group size considered to be less gregarious. We measured the strength of females’ social associations by examining how often they were in the same group with particular other females. We used the half-weight index, a social association metric that measures the number of times two individuals were observed in a group together, divided by the total number of times they were each observed. To examine the strength of females’ top associations, we summed females’ highest ten half-weight indices with adult females (i.e. “top 10 score”). Females with higher top 10 scores spent more time associating with particular individuals and were thought to have stronger social associations, and females with low top 10 scores were considered to have weak social associations. These social measures were estimated from data gathered on females’ social grouping patterns in 2010-2011.
Boldness Female EGKs’ boldness was estimated from flight initiation distance (FID) tests (Stankowich and Blumstein 2005). Female kangaroos with high FID scores (i.e. shyer individuals) have been found to be significantly more vigilant (Edwards et al. 2013), have a lower mean group size, and have fewer preferred associates (Best et al. 2015). The FID data used in this study were obtained from Best et al. (2015)’s research on kangaroos in our site between 2010-2011, and unpublished data from 2012-2013 (Menz 2015). In brief, when the kangaroo was feeding, a person not known by the kangaroo walked head on towards the kangaroo at a constant pace until the kangaroo hopped away. This person started at approximately 10 metres from the kangaroo and the distance between them and the kangaroo when it hopped away was measured. Females were sampled multiple times in each period, with 51 females sampled in 2010-2011 and 56 in 2012-2013. There was a high consistency in FID scores of individuals between years (Menz 2015) and we used the average FID score for all years as our measure of boldness.
130 Chapter 5 Body condition Each month, individuals were photographed while feeding to examine the amount of fat on the females’ hips and ribs. The body condition of individuals was visually estimated from these photographs, using Menz et al. (2017)’s modified version of the body condition index from Best et al. (2015). We used three categories of body condition (1=low, 3=high). Females with low body condition were considered in poor physical state with low fat levels and ribs and hips that stuck out, whereas females with high body condition were considered well fed and to have high amounts of fat stored.
Environmental data We obtained the total rainfall and maximum temperature each month from the Australian Bureau of Meteorology website for the Texas Post Office station (station number: 041100; 28°51’00” S, 151°10’12” E), approximately 40 km from our study site. Monthly rainfall varied from 1.4 mm to 212.6 mm (mean = 60.2 mm), and maximum monthly temperature from 17.5 °C to 35.7 °C (mean = 26.9 °C). The previous month’s rainfall was significantly related to green grass abundance in our site (Menz et al. 2017), so we used the previous three month’s total rainfall as a proxy for kangaroos’ food availability (since we considered survival over 3-month periods). We used lagged maximum temperature (the average maximum temperature of the previous three months) in our analyses to test the prediction that females’ survival was lower during periods of extreme high temperatures.
Imputation of missing data We had missing data for monthly body condition, as not all kangaroos were observed each month and not all kangaroos that were present were photographed. Furthermore, the boldness experiments were only performed on a subset of females, therefore we were missing flight initiation data for some adult females. It is common to delete entries with missing values, but this can increase estimation bias, while imputing missing data has been shown to provide accurate parameter estimates (Nakagawa and Freckleton 2008, 2011). We used the package mice (van Buuren and Groothuis-Oudshoorn 2011) in R (R Core Team 2016) to impute the missing data, creating six imputed datasets. One imputed dataset was used to determine the best model, and the five other datasets to obtain averaged parameter estimates and 95% confidence intervals. We used our social variables (top 10 score, group size) to predict the missing body condition and FID data. We also used the previous six and following six months’ body condition to predict individuals’ missing monthly body conditions, as individuals’ body condition does not tend to change drastically
131 Chapter 5 between months. Fewer previous months were used for the first six months of our study and fewer following months for the final six months of our study, as we did not have body condition data prior to January 2010 nor after February 2016. For the imputation, body condition was coded as an ordered category, and we used the proportional odds logistic regression model to impute missing values. Flight initiation distance was normally distributed, and missing data were imputed using a Bayesian linear regression model.
Survival Analyses All statistical analyses were performed in the R environment (R Core Team 2016). To examine the apparent annual survival (ф) and detection (p) of females, we used a Cormack-Jolly-Seber model, fit with the RMark package (White and Burnham 1999, Laake 2013). We used a three-month interval as our sampling period, recording the presence or absence of each individual for each sampling period. We removed data from January and February 2016, as these last two months of our study did not fit into a three-month period. We obtained the best model to describe our data by assessing the variables that explained the most variation in probability of survival (Phi) and probability of sighting (p) of kangaroos. We included the lagged total rainfall and lagged average maximum daily temperature for each sampling period. We included females’ top 10 score, average group size, and FID score to examine whether these variables were linked to females’ survival. Each female’s average body condition for each sampling period was included as a time-varying individual covariate.
We calculated the Pearson’s correlations among our predictors to examine their relationship. As body condition varied by individual and three-month period, we took each individual’s average body condition when looking at the correlations between body condition and other variables. When examining the correlation between body condition and other variables that varied among individuals, we examined the average body condition of the individual for 2010-2011. When examining the correlations between body condition and rainfall and temperature, we obtained the average body condition for each 3-month period. It was not possible to test the correlations between environmental variables and individuals’ social variables, as we did not examine the change in social variables over time and instead focused on individuals’ average sociability measures for 2010-2011. We assessed whether there were likely issues of multicollinearity by examining the VIFs of our predictors using the variance-covariance matrix of the MARK model.
132 Chapter 5 We fit all possible additive models with our predictors. Model averaging has not been implemented in MARK for models that include covariates, therefore we obtained a single best model using the fullest model within two AIC (Akaike information criteria) from the model with the lowest AIC score. As previously stated, we used the first imputed dataset to obtain the best model, and then used the last five imputed datasets to obtain averaged parameter estimates and 95% confidence intervals. Parameter estimates were obtained by combining among-analysis variances with the within-analysis variances using Rubin's rules (Barnard and Rubin 1999). This allowed the construction of correct standard errors for parameter estimates, taking into account that some of the data were missing. Goodness-of-fit tests for models that contain individual covariates has not been implemented in MARK, and therefore we were unable to test for this in this study.
Results Sightings and missing data In 2010-2011, there were 138 adult females that were observed a minimum of 10 times. The number of sightings ranged from 10 to 239, with females sighted an average of 96 times (mean ± SE, 96.06 ± 5.70) over the two years. Of the 138 adult females from 2010-2011, 78 (56.52%) were not sighted in the final year of study (March 2015-February 2016). The probability of survival of females between each three-month period was high, ranging from 91.6% to 99.2% probability of survival between periods.
Overall, 62.78% of monthly body condition values were missing, ranging from 33.33% to 82.60% depending on the month. Missing data could be attributed to an individual kangaroo not being observed that month, being observed that month and not recorded for body condition, or having emigrated or died and no longer being observed in our site. We were missing data for flight initiation distance for 62.32% of females.
Correlations among predictors Females’ average group size was positively correlated with females’ top 10 score and average body condition in 2010-2011 (Table 5.1). Rainfall and temperature were positively correlated (Table 5.2). However, the variance inflation factors were all below 2 and therefore all variables were included in the models.
133 Chapter 5 Table 5.1. Correlations among predictors that varied among individuals. Pearson’s correlation coefficient is shown with the p value in brackets below. Bolded entries show significant correlations.
Top 10 Average Flight Initiation Average Body Score Group Size Distance Condition Top 10 Score - - - - Average Group Size 0.630 - - - (<0.001) Flight Initiation Distance 0.201 0.230 - - (0.153) (0.101) Body Condition 0.111 0.321 0.151 - (0.217) (<0.001) (0.284)
Table 5.2. Correlations among predictors that varied with time. Pearson’s correlation coefficient is shown with the p value in brackets below. Bolded entries show significant correlations.
Rainfall Temperature Average Body Condition Rainfall - - - Temperature 0.540 - - (0.006) Average Body 0.296 -0.245 - Condition (0.160) (0.248)
Survival probability The best model included top 10 score, average group size, body condition, lagged rainfall, and lagged maximum temperature as predictors of probability of survival (Table 5.3; Figure 5.1). Flight initiation distance was not included as a predictor of survival in the best model. Females’ survival was higher in periods when the previous three months’ rainfall was higher. Females had higher survival if they had stronger relationships with their top associations and when the previous three months’ maximum temperature was lower, but these trends were not significant. The predictors included in the best model to predict the probability of sightings were top 10 score, average group size, flight initiation distance, body condition, and lagged rainfall, and all except flight initiation distance were significantly correlated with females’ probability of sighting (supplementary material).
134 Chapter 5 Table 5.3. Estimates and standard errors in the mark-recapture model used to explain the survival probability of female eastern grey kangaroos. All predictors were scaled by subtracting the mean and dividing by the standard deviation. A logit link function was used in the model. Variable Estimate Standard error t value P value
Intercept 3.634 0.159 22.870 <0.001 Top 10 Score 0.261 0.177 1.474 0.143 Average Group Size 0.387 0.172 2.247 0.026 Body Condition 0.479 0.174 2.751 0.009 Lagged Rainfall 0.628 0.187 3.357 0.001 Lagged Maximum Temperature -0.264 0.147 -1.799 0.074
A) B)
C) D
135 Chapter 5 E)
Figure 5.1. Female kangaroos’ survival probability as a function of females’ A) top 10 score (the sum strength of association with their top 10 female associations), B) average group size, C) body condition (lower values denote poor body condition), D) lagged rainfall (mm) (total rainfall for the 3 month period lagged by one month), and E) lagged maximum temperature (°C) (average monthly maximum temperature for the 3 month period lagged by one month). Predictions are limited to the range of observed values. The rug plot shows the x-axis values; no values are shown for body condition, as we had measures for each individual for each 3-month period. Grey error bars are the 95% confidence intervals, red lines show trends that are significant at an alpha level of 0.05, blue lines show trends that are significant at an alpha level of 0.1, and black lines show non-significant trends.
Discussion One aspect of females’ sociability, their gregariousness, was linked to survival. Females with a higher average group size had a higher probability of survival, showing that individuals’ grouping tendency is linked to their fitness. One possible explanation for this is that more gregarious females may experience antipredator benefits from being in larger groups. Despite not observing any wild dogs in our site, wild dogs have been recorded in other areas of the national park (Ian Elms, personal communication). However, although the kangaroos were free to roam in areas outside our study area where they might have been wild dogs, predation was likely not a cause of death for many of our females. Instead, females may have been gaining foraging benefits from being in larger groups. Mammals and birds tend to show reduced vigilance when in larger groups due to shared antipredator vigilance behaviour (Elgar 1989), and this trend has also been found in EGKs (Jarman 1987, Carter et al. 2009b, Dannock et al. 2013). The more gregarious females may have benefitted from increased foraging time due to reduced vigilance when in larger groups, increasing their probability of survival. Previous studies show that females foraging alone spent up to 40% of their time being vigilant, whereas the most vigilant females in larger groups only spent around 20% of their time being vigilant (Carter et al. 2009b, Dannock et al. 2013). Dannock et al. (2013)’s study was carried out at our field site. We found that females’ body condition and group size were positively correlated, but it is not known whether females in better condition seek out larger groups, or whether being in larger groups helps females forage more efficiently and thus be in better
136 Chapter 5 condition. It is also not yet known whether females experience feeding competition when in larger groups, which might reduce their intake. Further research on the trade-off between vigilance and food intake and how this may affect individuals’ health and survival is needed to understand the underlying drivers of the relationship between group size and survival in female kangaroos.
There was not a significant relationship between the strength of female kangaroos’ top associations and their survival, however, this variable was included in the best model and thus was still an important contributor to the variation in females’ survival. There was a trend that females with higher top 10 scores had a higher probability of survival, which is consistent with the study on female chacma baboons that showed females with stronger and more stable social bonds had greater longevity (Silk 2010). Female kangaroos who had strong associates (i.e. particular females that they frequently associated with) may have benefited through decreased predatory vigilance when in groups with trusted partners, thus allowing for more time allocated to foraging. Furthermore, females may experience social buffering effects from having strong social partners, and may have had a reduction in the harmful effects of chronic stress compared to less sociable females (Cohen and Wills 1985, Hennessy et al. 2009). Despite top 10 score contributing to the variation in females’ survival, the relationship between these two variables may not have been significant at an alpha level of 0.05 due to a variety of reasons. The probability of survival between periods was very high, and just over half of the females disappeared within our six-year study. There may not have been sufficiently high mortality between periods to assess the true relationship between survival and females’ strength of social relationships. The lack of a significant relationship between females’ association strengths and their survival could also have occurred because the benefits of having social relationships are likely weak for kangaroos compared to other social species with complex relationships (Silk 2010, Stanton and Mann 2012). Kangaroos may also experience costs to having social relationships, similar to the facultatively social yellow-bellied marmots from Blumstein et al. (2018)’s study, and these costs may cancel out any benefits. A study on EGKs found that females that were feeding in a group with a female that they spent more time with spent less time being socially vigilant, allowing for more grazing time (Carter et al. 2009a). However, more socially selective individuals may spend more time looking for individuals they prefer, thus spending more time searching and less time foraging. In addition, if an individual’s close associate is more active or reacts excessively to stimuli, then spending time following that individual around or being more vigilant may be energetically taxing and allow for less foraging time.
137 Chapter 5 There was no link between females’ boldness and their probability of survival. Female EGKs’ boldness has been linked to their vigilance, gregariousness, and social relationship preferences (Edwards et al. 2013, Best et al. 2015), and gregariousness and the strength of females’ top associations were included in our analysis and were stronger predictors than FID score. Although being bold has been linked to lower survival, this has been found to be most pronounced in fish and juveniles (reviewed in Smith and Blumstein 2008), whereas our study was on adult female mammals. A study on a large female mammal, bighorn sheep ewes (Ovis canadensis), found that bold females had higher survival during a period of higher predation by cougars, suggesting that ewes’ boldness may help reduce their risk of predation (Réale and Festa-Bianchet 2003). The lack of predators at our study site may help explain the lack of relationship between boldness and survival found for our female kangaroos.
Females in better physical condition, determined from the amount of fat on their hips, had a higher probability of survival. This pattern followed our expectation, as deaths are likely to be linked to disease and starvation, and thus mortality would be more likely after a female was observed in poor condition. When food availability is low, such as during a drought, kangaroos die from starvation (Caughley et al. 1985), and would be recorded as having low body condition in the months prior to their death. Despite some months having up to 80% of data missing and thus there being a large margin of error in our imputed data, body condition was still found to be a significant predictor of survival. This shows the effectiveness of using imputations for mark-recapture analyses, and we suggest that future studies include time-varying individual covariates into mark-recapture models by imputing missing values.
One of our environmental predictors, lagged rainfall, was a strong predictor of survival in female eastern grey kangaroos, with periods of higher rainfall linked to greater survival. A previous study in our site found that rainfall is linked to green grass abundance, and thus kangaroos may have limited food availability after periods of low rainfall. Periods of prolonged drought are challenging for kangaroos and our finding is consistent with studies that have shown higher levels of mortality during periods of drought and low rainfall (Bayliss 1985, Caughley et al. 1985, Coulson 1989). In months with higher temperatures, female EGKs’ probability of survival was lower. Temperature was, however, a weak predictor of survival, likely due to kangaroos’ thermoregulatory abilities. Kangaroos are crepuscular and tend to rest in the shade during the hottest part of the day and forage in the early morning and late evening when the temperature is lower. Furthermore, kangaroos are effective at regulating their internal temperature by evaporative heat loss from panting and licking
138 Chapter 5 their forearms (Robinson and Morrison 1957). The highest maximum temperatures recorded near our site did not exceed 38°C, whereas a study on EGKs found that they were efficient at maintaining a stable core temperature when outside temperatures were up to 45°C (Dawson et al. 2000). Temperature may be a stronger predictor of mortality in female EGK in arid areas where the maximum temperature exceeds 45°C than in mesic areas with that do not reach those high temperatures, such as our site.
Tests of goodness-of-fit and variance inflation factors have not been implemented in MARK for models that contain individual covariates. We calculated VIFs using the variance-covariance matrix of the MARK model, but there may be issues with this method given the format of MARK models. Females’ average group sizes and top 10 scores and their average group sizes and body condition were significantly positively correlated. Typically, a cut-off correlation of 0.8 is used when assessing multicollinearity, even though weaker correlations can still bias results (Vatcheva et al. 2016), while our highest correlation coefficient was 0.63. Our parameter estimates and confidence intervals could have been inflated due to this issue (Yoo et al. 2014), and thus our findings must be taken with caution. VIFs above 10 are considered to showcase severe multicollinearity (Quinn and Keough 2002), whereas the VIFs we calculated were all below 2, suggesting that multicollinearity was likely not an issue in our MARK models. Furthermore, the relationships we found were as expected, such as survival being higher for individuals with high body condition and lower after periods of low rainfall.
Our study only accounted for two dimensions of females’ sociability and did not account for changes in females’ sociability over time and how this might affect their survival. Social traits are considered a dimension of individuals’ personality, and some aspects of female EGKs’ sociability (average group size, total number of different associates, and total number of different nearest neighbours) have been found to be consistent over time (Réale et al. 2007, Menz et al. 2017). Our study examined females’ average group size and the strength of relationships with their top partners, as our focus was on the potential effect of gregariousness and strong social bonds on survival. Further studies could examine the link between other dimensions of sociability (e.g. propensity to approach or follow others) and females’ survival. Furthermore, future studies could examine both social relationships with same-sex and opposite-sex partners, as relationships with males was also found to predict females’ survival in baboons (Papio sp.) (Archie et al. 2014). Individuals’ social behaviours can also change with age, but we did not account for this in our study. For example, a study on the social interactions of yellow-bellied marmots found that younger
139 Chapter 5 marmots initiated more affiliative interactions with others, while older individuals initiated more agonistic interactions (Wey and Blumstein 2010). We did not account for changes in sociability over time, as females died during the course of our study and we did not have social data for them past their disappearance date. Furthermore, females’ sociability could be change between years due to external factors, and we wanted to ensure that our measure reflected females’ sociability at a time when they were all present and experienced similar conditions. To reduce this bias, we focused on the survival of females that were adults at the beginning of our study and examined how their social trends in the first two years of our study affected their future survival. Future studies could incorporate age of individuals and determine how changes in individuals’ social metrics over time may affect their fitness.
Examining the longevity of wild animals that have high fission-fusion dynamics and roam widely has its set of limitations. Death can only be confirmed by the discovery of dead individuals, and individuals that are never seen again may have died, evaded resighting or emigrated from the site. Furthermore, for long-lived animals, studies need to track individuals over a long period of time, which is a resource intensive endeavour that tends to be limited to studies on primates and more socially complex animals. Using mark-recapture analysis accounts for the sighting probability of individuals, allowing researchers to examine individuals’ characteristics and environmental factors that may affect survival. Thus, studies on survival need not be limited to animals that have been studied for their whole lifespan, or for which all deaths are known. Female EGKs can live up to 15 years of age, whereas our research on this population ended after 6 years of intensive study, and we did not observe the deaths of individuals. Despite these limitations, we have found factors that are linked to kangaroos’ probability of survival. To further understand the relationships between sociability and survival and ascertain the fitness costs and benefits of sociability in different species, research is needed on species that have different types of social relationships and degrees of social complexity. We suggest that even shorter-term studies on wild mammals that were tracked over time could use mark-recapture analyses to expand our knowledge and understanding of these links.
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144 Chapter 5 Réale, D., and M. Festa-Bianchet. 2003. Predator-induced natural selection on temperament in bighorn ewes. Animal Behaviour 65:463-470. Réale, D., S. M. Reader, D. Sol, P. T. McDougall, and N. J. Dingemanse. 2007. Integrating animal temperament within ecology and evolution. Biological Reviews 82:291-318. Robinson, K. W., and P. R. Morrison. 1957. The reaction to hot atmospheres of various species of Australian marsupial and placental animals. Journal of Cellular and Comparative Physiology 49:455-478. Silk, J. B., J. C. Beehner, T. J. Bergman, C. Crockford, A. L. Engh, L. R. Moscovice, R. M. Wittig, R. M. Seyfarth, and D. L. Cheney. 2009. The benefits of social capital: close social bonds among female baboons enhance offspring survival. Proceedings of the Royal Society B 276:3099-3104. Silk, J. B., Beehner, J.C., Bergman, T.J., Crockford, C., Engh, A.L., Moscovice, L.R., Wittig, R.M., Seyfarth, R.M., Cheney, D.L. 2010. Strong and consistent social bonds enhance the longevity of female baboons. Current Biology 20:1359-1361. Sinn, D. L., L. Cawthen, S. M. Jones, C. Pukk, and M. E. Jones. 2014. Boldness towards novelty and translocation success in captive-raised, orphaned Tasmanian devils. Zoo Biology 33:36- 48. Smith, B. R., and D. T. Blumstein. 2008. Fitness consequences of personality: a meta-analysis. Behavioral Ecology 19:448-455. Stankowich, T., and D. T. Blumstein. 2005. Fear in animals: a meta-analysis and review of risk assessment. Proceedings. Biological sciences 272:2627-2634. Stanton, M. A., and J. Mann. 2012. Early social networks predict survival in wild bottlenose dolphins. Plos One 7. Tamashiro, K. L. K., M. M. N. Nguyen, and R. R. Sakai. 2005. Social stress: From rodents to primates. Frontiers in Neuroendocrinology 26:27-40. Thompson, N. A., and M. Cords. 2018. Stronger social bonds do not always predict greater longevity in a gregarious primate. Ecology and Evolution 8:1604-1614. Treisman, M. 1975. Predation and the evolution of gregariousness. I. Models for concealment and evasion. Animal Behaviour 23, Part 4:779-800. van Buuren, S., and K. Groothuis-Oudshoorn. 2011. mice: Multivariate imputation by chained equations in R. 2011 45:67. Vander Wal, E., M. Festa-Bianchet, D. Réale, D. W. Coltman, and F. Pelletier. 2015. Sex-based differences in the adaptive value of social behavior contrasted against morphology and environment. Ecology 96:631-641.
145 Chapter 5 Vatcheva, K. P., M. Lee, J. B. McCormick, and M. H. Rahbar. 2016. Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies. Epidemiology (Sunnyvale, Calif.) 6:227. Vine, I. 1973. Detection of prey flocks by predators. Journal of Theoretical Biology 40:207-210. Weiss, A., M. C. Gartner, K. C. Gold, and T. S. Stoinski. 2013. Extraversion predicts longer survival in gorillas: an 18-year longitudinal study. Proceedings of the Royal Society B: Biological Sciences 280. Wey, T. W., and D. T. Blumstein. 2010. Social cohesion in yellow-bellied marmots is established through age and kin structuring. Animal Behaviour 79:1343-1352. Wey, T. W., and D. T. Blumstein. 2012. Social attributes and associated performance measures in marmots: bigger male bullies and weakly affiliating females have higher annual reproductive success. Behavioral Ecology and Sociobiology 66:1075-1085. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46:S120-S139. Yang, W. J., A. A. Maldonado-Chaparro, and D. T. Blumstein. 2017. A cost of being amicable in a hibernating mammal. Behavioral Ecology 28:11-19. Yoo, W., R. Mayberry, S. Bae, K. Singh, Q. Peter He, and J. W. Lillard, Jr. 2014. A study of effects of multicollinearity in the multivariable analysis. International journal of applied science and technology 4:9-19. Zenger, K. R., M. D. B. Eldridge, and D. W. Cooper. 2003. Intraspecific variation, sex-biased dispersal and phylogeography of the eastern grey kangaroo (Macropus giganteus). Heredity 91:153-162.
146 Chapter 5 Supplementary Material Chapter 5
The best model contained Top 10 score, average group size, flight initiation distance, body condition, and lagged rainfall as predictors of probability of sighting (Table S5.1). Lagged maximum temperature was not included in the best model. Females with higher top 10 scores, larger average group sizes, and better body conditions had a significantly higher sighting probability. There was a higher probability of sighting female kangaroos in periods with higher rainfall in the previous three months.
Table S5.1. Estimates and standard errors in the mark-recapture model used to explain the sighting probability of female eastern grey kangaroos. All predictors were scaled by subtracting the mean and dividing by the standard deviation. A logit link function was used in the model. Bolded entries show parameters that were significant at an alpha level of 0.05.
Variable Estimate Standard error t value P value
Intercept 2.509 0.093 26.998 <0.001 Top 10 score 1.006 0.123 8.186 <0.001 Average Group Size 0.261 0.122 2.140 0.043 Flight Initiation Distance -0.196 0.153 -1.282 0.240 Body Condition 0.196 0.093 2.113 0.041 Lagged Rainfall 0.231 0.089 2.606 0.010
147 Chapter 6
General Discussion
Overview The overall objective of my study was to examine the fitness consequences of individuals’ social patterns in a species in which adults do not groom one another or exhibit cooperative behaviours, using the eastern grey kangaroo as a model organism. I found that some aspects of male eastern grey kangaroos’ social patterns were linked to some aspects of their fitness, but these relationships were relatively weak and others were not significant. To understand the social relationships of males, I first examined how their social and space use patterns differed among size classes. I found that larger males used a larger area in my site and had more but weaker associations with females, perhaps reflecting changes in reproductive strategies with age (Chapter 2). Because of the efforts that alpha males focus on reproduction, it has been suggested that these males deteriorate rapidly due to the high energetic cost of their behaviour. I found that males’ social association strengths with particular adult females predicted the likelihood of their fathering offspring with those females, showing that there are reproductive benefits of having close associations with females (Chapter 3). However, males’ sociability, as measured from their top 10 associations with females, did not predict their overall reproductive success. Male kangaroos become more dominant as they age, and as growth is indeterminate, the older the males live, the more dominant they will be. As I found in Chapter 3, the more dominant the male, the higher their reproductive success. It has been suggested that dominant males may have higher stress levels, and this can lower their fertility, or conversely that dominant males may suppress the reproduction of subordinate individuals through mechanisms related to stress levels. There was no relationship between males’ stress hormone levels and their dominance ranks, therefore there does not appear to be support for reproductive suppression of subordinates mediated by stress hormones in male kangaroos (Chapter 4). I also did not find evidence for the stress buffering hypothesis in male kangaroos, as the strength of males’ social associations was not related to their stress levels. I did not find evidence of survival benefits of having strong social associations in female kangaroos, but did find that more gregarious females had higher survival (Chapter 5). Below, I discuss the findings of my research in the broader context of our understanding of animals’ social relationships and propose that two attributes that kangaroos lack might be key in driving the fitness benefits of social relationships in other species. I outline the limitations of my study and propose further research that could be conducted to increase our understanding of mammals’ social relationships and the factors that influence the fitness trade-offs of investing in affiliative social bonds.
148 Chapter 6
Implications for the study of males’ reproductive strategies in species with high fission-fusion dynamics and indeterminate growth Studies on male reproductive strategies have most commonly focused on species that display discontinuous differences in morphological and physiological traits rather than continuous differences along a spectrum, as discontinuous distributions in traits is evidence of alternative reproductive tactics (Taborsky et al. 2008). Males can show discrete differences in reproductive strategies, such as those involving distinct morphological differences in colour (i.e. colour polymorphism), size (i.e. size dimorphism), and behaviour (Gross 1991, Thompson et al. 1993, Sinervo and Zamudio 2001). However, males’ reproductive strategies can also differ incrementally along different spectra (e.g. age, body size, dominance, social status, size of weaponry, roaming behaviour, hormonal profile). Behavioural changes along these spectra are harder to quantify, but similarly to the discrete reproductive strategies, males can be categorized into groups along a spectrum and behavioural differences among males in such groups can easily be quantified. Adult male eastern grey kangaroos differ greatly in size, and I categorized adult males into three size categories to explore the differences among these males in their gregariousness, relationships with females and movement patterns (Chapter 2). I found differences among size classes, suggesting that size and age can be important factors when studying the reproductive strategies of males in species in which adult males differ greatly in size, as has been found for species in which males continue to grow through their lives (Whitehead 1994).
Male kangaroos exhibit such indeterminate growth, a rare attribute in mammals that provides a unique set of challenges for males. There is evidence of indeterminate growth or continued gain in weight after maturity for orangutans (Pongo pygmaeus) (Leigh and Shea 1995), elephant seals (Jolicoeur 1985), elephants (Laws 1966, Mumby et al. 2015), and some medium to large macropod species, including the eastern grey kangaroo (reviewed in Jarman 1983). When dominance is primarily predicted by size and males have indeterminate growth, then the oldest males and those males that invested most in growth will be the most dominant. In these systems, males may delay heavy investment in reproduction until they are large enough to compete for access to females in oestrous, with younger males focusing on growth and achieving paternity through opportunistic matings (Whitehead 1994). For example, male African elephants do not start exhibiting the competitive state of musth until an older adult age, but even though older males in musth are the most reproductively successful, younger non-musth adult males also sire offspring (Rasmussen et al. 2007). I found that male kangaroos’ space use differed among size classes, with smaller males
149 Chapter 6 using a smaller area within our site, likely to invest more time in foraging for growth, and large males using a larger area, likely to maximise the number of females they are exposed to (Chapter 2), a similar pattern to other species with high fission-fusion dynamics and indeterminate growth. Small adult males still achieved paternity of young (Chapter 3), which may have simply been opportunistic, but could be linked to other traits that can help increase males’ reproductive success.
Males’ social relationships when they are young could affect their dominance ranking and their eventual reproductive success. Even though male kangaroos’ dominance appears to be strongly related to size, small differences in size between two males may not matter as much as strength and skill in fighting, which may be linked to males’ fighting experience. Numerous non-mutually exclusive hypotheses for the function of play have been proposed, but the practice hypothesis (Groos 1898) is one of the most popular (Sharpe 2005). This hypothesis asserts that individuals benefit from play by training behaviours and refining skills that will be important in adulthood (Groos 1898). Outcomes of play fights predict future dominance rank in yellow-bellied marmots (Marmota flaviventris), even when controlling for a number of important factors that could affect this relationship (Blumstein et al. 2013). This extensive, long-term study of marmots may provide the strongest supporting evidence yet for the practice hypothesis, suggesting that, at least in yellow- bellied marmots, play behaviours are adaptive in that they positively affect future fighting abilities and therefore social ranking (Blumstein et al. 2013). Play fighting among young males occurs in kangaroos, and perhaps males benefit from increased future dominance ranking from sparring with male associates. This was not tested in my research, as males were not studied for a sufficiently long period to observe long-term effects on individuals’ dominance ranking.
Males’ social relationships as adults can also influence their dominance ranking and reproductive success (Smuts 1985). For example, a study of Assamese macaques (Macaca assamensis) found that the strength of male social bonds predicted their future dominance rank (Schulke et al. 2010). In vervet monkeys (Chlorocebus pygerythrus), males’ power trajectories are influenced by their associations with well-connected females (Young et al. 2017). Given that dominance is strongly related to reproductive success, any traits that help increase males’ dominance rank would be under sexual selection. However, males’ investment in social relationships can also have direct repercussions on their reproductive success. For example, male bottlenose dolphins can form alliances, which can improve males’ success in achieving coercive matings with females (Connor et al. 1992, Connor et al. 2001). My study did not find a relationship between males’ overall strengths
150 Chapter 6 of social relationships with females and their reproductive success (Chapter 3), and I discuss potential reasons for this below.
Implications for the study of the social bonds in mammals Kangaroos were previously thought to associate randomly and not exhibit any social structure (Caughley 1964). However, recent research has shown that female kangaroos have non-random social association patterns (Carter et al. 2009), and I found that males exhibit this pattern too (Chapter 2). Non-random association patterns between individuals are common in social species, as reported in fish (Croft et al. 2005, Croft et al. 2006), reptiles (Kerth and Konig 1999, Strickland et al. 2014), bats (Garroway and Broders 2007), ungulates (Cross et al. 2005, Wittemyer et al. 2005, VanderWaal et al. 2013), cetaceans (Connor et al. 2001, Reisinger et al. 2017), and primates (Smith-Aguilar et al. 2016). Indeed, non-random patterns of association may be a ubiquitous trait of social species (reviewed in Krause et al. 2007). The presence of social preferences in kangaroos along with significant consistency in measures of individuals’ sociability (Best et al. 2015, Menz et al. 2017) suggests that there must be benefits of having social bonds. Carter et al. (2009)’s study showed that the strength of association between pairs of kangaroos foraging in the same group was linked to their vigilance behaviour, with less time spent in vigilance behaviour when individuals were in groups with close associates, and thus foraging with social associates may provide energetic benefits. However, a previous study in my site found that females with more associates and more preferred associates actually had lower reproductive success, perhaps due to the increased cost of food competition with associates or because young can get separated from their mothers when in larger groups (Menz 2015). The fitness costs of having strong associations and associating with many different individuals found for my population of kangaroos may be because the main predator of kangaroos, the dingo (Canis familiaris), was not present in the research site and young kangaroos in my site may have been exposed to lower predation risk than kangaroos in areas with dingos.
My research contributed to our understanding of the fitness consequences of kangaroos’ social relationships by examining the survival of females, the reproductive success of males, and social buffering in males. Although I found that the strength of association between a male and female predicted their likelihood of having an offspring (Chapter 3), this could have been due simply to males being more likely to be present when the female was in oestrous, rather than a benefit driven by the social relationship between the two individuals. I did not find any evidence for stress buffering (Chapter 4) or increased survival probability (Chapter 5) for individuals with strong associations with particular individuals. Perhaps the benefits of social bonds in kangaroos are either
151 Chapter 6 solely linked to increased foraging time due to less vigilance, and this was not a strong effect in this low predation risk population, or were too weak to be detected due to limitations in sample size and duration of my study.
My findings for kangaroos contrast with those found for other mammals that live in groups with changing group membership, where individuals can choose the size of the groups they forage in and which individuals they associate with. In some species with high fission-fusion dynamics, there are strong positive relationships between the strengths of individuals’ social bonds and their reproductive success and survival. For example, in species where males can form alliances, engaging in this behaviour - forming alliances, having large alliances, or being integrated in the alliance network - is linked to increased reproductive success (Wiszniewski 2011, Gilby et al. 2013). As adult male kangaroos do not appear to form alliances, strong male-male bonds are unlikely to develop in this species. A study that assessed the survival of offspring in chacma baboons (Papio cynocephalus ursinus) found that offspring survival was higher for females with strong social bonds, showing that sociability is a predictor of females’ reproductive success in this species (Silk et al. 2009). My study focused on males, but a previous study in our site found that more sociable female kangaroos actually had lower survival of young-at-foot (Menz 2015). We do not know why kangaroos show these different patterns, and thus suggest that research on the differences between species that show strong fitness benefits of investing in social bonds and those that either show no relationship or a negative link could help us elucidate the factors that drive the fitness benefits of sociability.
Cooperation and affectionate touch as driving forces of the benefits of social bonding Despite living in groups and frequently associating with the same individuals, kangaroos do not exhibit any complex forms of cooperative behaviours such as alliance formation, communal care of young or allogrooming. Social bonds and cooperation go hand-in-hand; in repeated interactions in the Prisoner’s Dilemma, zebra finches (Taeniopygia guttata) cooperated with their social partner but not with another opponent (St-Pierre et al. 2009). Social bonds can predict future cooperative relationships; the social bonding of male macaques (Macaca sylvanus) in the nonmating season predicted their formation of coalitions in the mating season (Berghanel et al. 2011). A model examining the evolution of cooperation found that high levels of cooperation and choosiness become the stable states if there is high variation in individuals’ likelihood to cooperate and their choosiness (McNamara et al. 2008), which suggests that choosiness in social partners may be required for the evolution of cooperation in some circumstances. Kangaroos show differentiated
152 Chapter 6 social relationships but these are still quite weak, and perhaps more complex cooperative behaviours would coevolve with the strength of individuals’ social bonds.
Cooperation requires long-term memory of all the interactions with other individuals and is more likely to arise for long-lived species or populations with a low mortality rate where individuals interact repeatedly with the same partners (McNamara et al. 2008). In relatively long-lived species, males can engage in competitive alliances, which can improve their ability to establish dominance and secure mates (Van Hooff and Van Schaik 1994, Feh 1999, Mitani et al. 2000, Connor et al. 2001). Kangaroos are also relatively long-lived animals, but males do not appear to form alliances. Young male kangaroos play fight (Croft and Snaith 1990), which could be considered a cooperative behaviour, as it requires reciprocity through turn-taking and individuals to moderate their level of competition (Pellis and Pellis 2017). Play fighting can be beneficial for both parties (Groos 1898, Blumstein et al. 2013), but not much is known about play-fighting in kangaroos and whether it predicts future dominance or affects their social relationships with other males. Kangaroos in areas where dingos are no longer present have a relatively low mortality rate compared to what it must have been historically when more predators were present, and thus kangaroos may not have been exposed to low predation rates for long enough for more complex cooperative behaviours to form.
Adult kangaroos do not engage in affectionate touch or groom each other as a form of social exchange, which could be one of the reasons that I did not find evidence of strong fitness benefits of social bonds. Touch is considered an important form of contact between individuals, crucial for infant development and beneficial for adults of some species (Gliga et al. 2019). Affectionate touch in adults is evident in many of the species where positive fitness outcomes of having strong social bonds have been found. People hold hands and hug to show their affection for one another, and receiving affectionate touch has been linked to individuals’ physical and psychological wellbeing (reviewed in Jakubiak and Feeney 2016). Grooming in primates goes beyond the needs of parasite removal and cleanliness and it is widely accepted that it serves the function of social bonding (reviewed in Dunbar 2010). Both giving and receiving grooming have been linked to helping decrease female baboons’ stress levels, and female chacma baboons respond to the stressful loss of a close relative by increasing their grooming network (Engh et al. 2006, Shutt et al. 2007). Mutual grooming in ungulates has parasite removal as one of its purposes (Mooring et al. 2004), but this affiliative behaviour has been used as one of the measures of female feral horses’ social integration, finding that it is positively linked to aspects of their fitness, suggesting that it also serves to strengthen relationships (Cameron et al. 2009). Flipper rubbing in bottlenose dolphins (Tursiops sp)
153 Chapter 6 appears to be an affiliative behaviour that is more common among individuals of the same sex and age-class (Sakai et al. 2006), and females engage in contact swimming (Connor et al. 2006). Male bottlenose dolphins form stable, long-term bonds, which may help them coordinate behaviour to achieve matings (Connor et al. 1992, Connor et al. 2001), and females may associate to protect themselves from male harassment (Connor and Wells 2000), showing that the formation of strong social relationships may also be important predictors of fitness in this species.
Social bonds may not always be positively linked to fitness, even in species that exhibit affectionate touch. Yellow-bellied marmots display allogrooming, but amicable behaviours between adults of this species appears to occur only between closely related kin or are linked to reproduction, as this behaviour occurs between males and females (Armitage and Johns 1982). Studies on survival and reproductive success in this species found that there are negative fitness consequences of having strong social relationships (Wey and Blumstein 2012, Yang et al. 2017, Blumstein et al. 2018). Several metrics that describe marmots’ closeness to their social partners were negatively correlated with their longevity (Blumstein et al. 2018). The authors suggest that resident marmots may incur costs when outsiders join a group, and thus their increased connectivity is a detriment to their fitness (Blumstein et al. 2018). Furthermore, marmots are not a cooperative species (Blumstein 2013), and investing in strong social relationships does not have the benefit of building cooperative relationships with social partners. Further research on the roles of touch and cooperation in driving the benefits of social relationships could help us understand the fitness trade-offs of social bonds.
It is not known why adult kangaroos do not exhibit allogrooming as a form of social exchange. Kangaroos can be negatively impacted by ticks, through loss of blood and increased risk of infection with harmful tick-borne diseases (Donahoe et al. 2015). We would therefore expect that allogrooming would be beneficial for kangaroos. Mothers groom their young (Coulson 1997), but this behaviour stops once their young become more independent. It has been reported that male kangaroos allogroom females during courting (Coulson 1997), but this behaviour is short-lasting, not reciprocated, is unlikely to provide any tick removal benefits, and usually causes the female to move away from the male, suggesting it is not a behaviour that benefits the receiver. It is possible that allogrooming between adults has not evolved in kangaroos either because kangaroos are sufficiently adept at avoiding or removing ticks from themselves (Hart and Hart 2018) or because allogrooming is a time-consuming behaviour that is too costly for this herbivorous species (Mooring and Hart 1995). The evolution of allogrooming in ungulates is linked to habitat type, with species from lineages that inhabit closed woodland and forests being more likely to have evolved
154 Chapter 6 adult allogrooming, likely because that environment is more tick-dense (Mooring et al. 2004). Kangaroos tend to forage in open grasslands and perhaps their tick exposure is not high enough to drive natural selection of allogrooming behaviour. However, kangaroos in our site were frequently observed with numerous ticks on their ears and back (personal observation), and thus it seems that tick exposure could have been high and that our kangaroos were not, at least some times, highly proficient at tick removal.
Limitations and future research The kangaroos sampled in my study were not captured. This presented a set of limitations, including the inability to obtain data on kangaroos’ weight and body measurements. Without fine- scale data on males’ weight and height, I was unable to completely separate the effect of males’ body size from that of their dominance ranking. Male kangaroos have indeterminate growth and dominance in this species is linked to size, as shown in my research and previous studies. My size categories were too broad to examine minute differences in size among individuals; it is possible that the relationships I found with dominance could have been driven by males’ size rather than their relative dominance ranking. For example, the positive relationship between testosterone and dominance that I found in Chapter 4 could have been due to larger males having more circulating testosterone than smaller males irrespective of their dominance rank. My measure of dominance rank had males’ size category embedded within it, but I did not have fine-scale data on males’ size to directly examine the link between males’ size and testosterone levels.
Given that I did not capture the kangaroos, I was not able to collect blood to measure individuals’ circulating hormone levels, and tissue or blood for genetic analysis. Given that I did not collect blood from the kangaroos, I was not able to examine kangaroos’ immediate response to a stressor. I was also unable to assess the effect of induced stress from capture, which could have allowed us to determine whether individuals had a normally functioning HPA axis, however, this technique has drawbacks (reviewed in Beehner and Bergman 2017). Faecal samples for hormone analysis have the advantage of being easy to collect, which allowed me to collect multiple samples from 31 individuals over 17 months, instead of only a few samples from fewer captured males. Although DNA from faecal samples is more likely to degrade, this is not an issue when fresh samples are collected from individuals observed defecating (Fernando et al. 2003), as was the case in my study. Fernando et al. (2003)’s study showed that microsatellite markers analysed from scat samples are reliable and the level of error in typing alleles would not affect paternity exclusion analyses. Capturing animals is time-consuming, costly, and can cause stress, physical harm, and behavioural
155 Chapter 6 changes in the captured animal, including changes in individuals’ space-use (Chi et al. 1998, Morellet et al. 2009). Capturing kangaroos requires tranquilisation and macropods are susceptible to capture myopathy and some eastern grey kangaroos may die or lose their pouch young as a result of capture (King et al. 2011, Green-Barber et al. 2018). The non-invasive, and non-disruptive (Lefort et al. 2018), nature of my study minimized the impact on individuals’ fitness, space use and social behaviours, which allowed us to examine individuals’ social relationships with minimal bias.
The relatively small number of males that were included in analyses may have contributed to the non-significant and weak relationships I found. This limitation was due to the nature of studying social relationships in depth and the biased sex ratio in kangaroos that favours females (Jaremovic and Croft 1991), likely linked to greater dispersal and mortality of males (Zenger et al. 2003, Coghlan et al. 2017). Tracking individuals’ grouping patterns and collecting faecal samples are time-consuming, and thus I was confined to observing individuals within a set area. My 37.4 ha study site encompassed all the open pastures in the area, with the next closest pasture a 1.5 km straight path through the forest from the edge of my site. I was limited to studying the males that chose to visit my study area, as I studied wild animals that were free to roam within and outside of my site and could not control which animals I was able to sample on a daily basis. However, I obtained an in-depth view of kangaroos’ social behaviours from studying their social grouping patterns for 12 days each month for two years. It was not known what the kangaroos did outside of the study area, but their social relationships and behaviours within the site were heavily monitored.
Studying wild animals and species with high fission-fusion dynamics presents challenges. I estimated kangaroos’ social relationships from examining their grouping partners during foraging bouts, with the assumption that kangaroos had the opportunity to interact with all their group-mates. A previous study in my site found that kangaroos coordinated their vigilance behaviour with individuals within groups defined by the 15 metre chain rule (Favreau et al. 2010), and when kangaroos were startled, the whole group responded by fleeing the area. My study also focused on kangaroos’ strong social associates, and my method of determining the strength of social associations may not have reflected kangaroos’ actual social relationships. I believe that this would have been an issue for pairs of individuals that were infrequently observed, and that their strength of association could have been inflated due to chance encounters within the same group. In simple terms, strength of association was measured as the proportion of times that two kangaroos were observed in the same foraging group divided by the total number of times that each kangaroo was observed. If both kangaroos were infrequently observed, then a single event when the kangaroos
156 Chapter 6 were observed together had a greater impact on their social association score than for a pair that were more frequently observed in my site. This is further compounded by the variation in both the number of individuals present in my site and group size during the year. There were peaks in the number of individuals present in my site during the peak mating season, and group size also increased during this time. There was a higher probability that infrequently observed individuals would be present during these times, and as groups were larger, a higher probability that pairs of infrequently observed individuals would have been recorded in the same foraging group. These issues are particularly evident for species with individuals that frequently change their group membership and for studies where individuals are not confined within a study area. I only included individuals with a minimum of ten sightings, thus this effect was likely to be small in my study.
To minimise the issues associated with examining social relationships through group membership, future research on wild species with high fission-fusion dynamics could determine association through spatial proximity of pairs of individuals. Strong social relationships could also be determined through following behaviour (i.e. pairs of individuals joining and leaving groups together) if these can be observed. However, this method of determining social relationships would entail following a smaller subset of individuals and is not practical in a setting where the animals range widely within and outside of a study area. I opted to gather a larger amount of data to minimize the variation due to methodological limitations.
Animals’ social lives are complex, difficult to measure, and require long-term observation to obtain a full understanding of how current relationships were shaped from previous social interactions and these relationships affect their future behaviour and fitness. In this study, I focused on one particular measure of individuals’ social relationships, which was the strength of their association with their top ten partners. Broad conclusions on the fitness consequences of social relationships cannot be drawn from this one measure, as it cannot fully describe the complexity of relationships among individuals. Studies on primates have also examined the fitness consequences of having strong relationships with particular individuals. Social network metrics tend to be highly correlated, making it difficult to select the most appropriate metrics to use in analyses. Clustering coefficient is not correlated with other social network metrics, however this measure does not seem biologically relevant given that kangaroos do not cooperate.
The difficulty with studying males over only two years means that I did not have information on their behaviours before and after this time. It is unknown whether males that were not observed
157 Chapter 6 associating were actually actively avoiding each other after a dramatic conflict or were using different areas of the site for other reasons. Another issue is that when males were observed foraging in the same groups, it is not known whether the dominant males were simply tolerating the presence of subordinate males, and whether subordinates were gaining any benefits from learning from dominant males. I believe that studies examining the benefits of social relationships would benefit from longer-term studies.
Touch in humans and other animals has not been widely studied due to philosophical and methodological limitations (reviewed in Hertenstein et al. 2006). Further research in this area is needed to determine whether the observed physiological benefits of social bonding in humans and primates are related primarily to the touch aspect of the relationship or whether other aspects of the relationship may be contributing. The lack of publishing null results is a detriment to the building of knowledge in the scientific community, as in this case, we need to know what species show and do not show benefits of investing in stronger social relationships with particular individuals. It is not clear whether marmots are the only species where sociable adults suffer negative fitness consequences or whether other such findings have not been published. Touch may also be important in the relationship between testosterone and nurturance behaviour. The steroid/peptide theory stipulates that low testosterone would promote nurturance behaviour, described as behaviours such as huddling and grooming, which involve affiliative touch with conspecifics (van Anders et al. 2011).
One aspect of males’ reproductive success that I did not examine in my study is female choice. Female kangaroos appear to be able to exercise some choice in mating (Walker 1995). Males’ forelimb musculature is under sexual selection, which is likely linked to male-male competition, but could also be partly driven by female choice (Warburton et al. 2013). In chimpanzees (Pan troglodytes), females’ restriction of their mating when closer to their ovulation has been considered evidence for female choice, however, it may only be due to mate guarding, whereby a dominant male aggressively prevents the female from mating with other males (Muller et al. 2011). Male kangaroos also mate guard females, and perhaps females have a lowered ability to exercise choice in these contexts. However, given that dominant males do not monopolize matings (Chapter 3, Miller et al. 2010, Rioux-Paquette et al. 2015), research on female mate choice in this species could shed light on other factors that influence male reproductive success.
158 Chapter 6 This study, when pooled with others, could contribute to a large meta-analysis on the fitness consequences of animals’ social relationships. This will be a challenging analysis, as the ways that social relationships are measured differ by species, taxa, or study type, and thus complicate the comparisons among them. In primates, measures of individuals’ social relationships often include their grooming partners, and thus the effect of having strong social associates cannot be untangled from the benefits gained from grooming and touching. I suggest that a meta-analytic study could compare the benefits of strong relationships in species where conspecifics cooperate and those that do not, and species that groom each other as a social exchange and species that rarely touch conspecifics. Despite touch being an important method of communication in humans and other animals (Hertenstein et al. 2006), the benefits of touch in adults have not been widely explored. To specifically understand the benefits of touch, we must examine both species that do and do not engage in this behaviour. Further research on the social relationships of animals that do not engage in affiliative touch are needed.
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165 Appendices
Appendices
A1. Scientific Purposes Permit 2012-2015
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168 Appendices A2. Scientific Purposes Permit 2015-2018
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171 Appendices A3. Permit to take, use, keep or interfere with cultural or natural resources 2012-2015
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174 Appendices
A4. Permit to take, use, keep or interfere with cultural or natural resources 2015-2018
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177 Appendices A5. Animal Ethics 2012-2015
178 Appendices A6. Animal Ethics 2015-2018
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