Social aspects of demographic stochasticity in an ...

Social aspects of demographic stochasticity in an endangered population of bottlenose dolphins (Tursiops truncatus)

David Robert Johnston

A thesis submitted for the fulfilment of the degree Master of Science in Marine Science at the University of Otago, New Zealand.

December 2016

Yoda.

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Abstract

Photography is one of the most widely used tools in conservation biology. In the analysis of social species, analyses of photographic identification data are used to infer the degree of association among uniquely marked individuals. The present study aimed to develop and assess the practicality of a new time-based method for defining associations among individuals, comparing results to the commonly used group membership method. The method was applied to archived photographs from long-term monitoring of the population of bottlenose dolphins of Doubtful Sound, New Zealand, to assess differences in seasonal association rates among individuals. The time-based method produced analyses of association at finer scales than the group membership method, and produced greater precision in association indices. Importantly the method can be applied retrospectively to any dataset in which individuals, marine or terrestrial, are uniquely identified via time-stamped photographs. Applied to the long-term dataset, results indicate differences in association rates between summer and winter seasons. During summer months the degree of sociality was generally higher; larger mixed-sex groups and greater rates of association among individuals were observed. Sociality in this population is female orientated; the majority of top-scoring individuals in centrality analyses were female. Explorations of whether a mother’s position in the social network influences the survival of her calves were inconclusive. Who the mother is significantly affects calf survival, but why this is so remains unclear. The most important influence on calf survival is birth timing; those born during the months of February, March and April have much higher chances of survival than calves born outside of this period. This is in agreement with previous studies on this population, though further research is required in order to tease apart the relative importance of driving factors of calf survival in this endangered and isolated population.

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Acknowledgments

Thanks need to go first and foremost to Steve Dawson, Will Rayment and Liz Slooten. I couldn’t have asked for more supportive and encouraging supervisors; your guidance and encouragement have made this whole experience one I will never forget. Your dedication and passion to conservation, wildlife and science are truly inspiring. This project was supported financially by the New Zealand Whale and Dolphin Trust, the Department of Conservation, the Fiordland Marine Mammal Viewing Permit Levy Group and the University of Otago. I was supported throughout this project by a University of Otago MSc scholarship. Thank you so much to the team at DOC Te Anau who provided financial, logistic and general support. In particular: Dave Johnson (D1) for the ramblings, Chloe Corne and Sarah Stirrup for putting up with the ramblings, and Richard Kinsey. You all made my experiences in Fiordland unforgettable and long may the adventures continue. For support while in the field, thanks go to the Deep Cove Outdoor Education trust, particularly to Billy and Vilma Williams, as well as Bob Hughes. In Dunedin, the staff from the Marine Science Department were invaluable. Thanks in particular go to Chris Fitzpatrick and Julie-Anne Parsons. Thanks also to Beate Zein for your assistance in the field. To my friends in the Marine Mammal Lab (the blubber-huggers): Tom Brough, Marta Guerra, Trudi Webster, Tamlyn (Dumpling) Somerford, Eva Leunissen and Lindsay Wickman; and to the honorary blubber-huggers: Rob Lewis and Stina Kolodzey. Thank you to the past students, researchers and volunteers of the Fiordland bottlenose dolphin research programme; your hard work and dedication over the many years have provided a valuable asset in the long term dataset. Particular thanks again need to go to Steve Dawson and Liz Slooten for having the foresight to begin the project over 25 years ago, and for overseeing research ever since. Special thanks go to a dear friend of mine; a friendship that began while in Doubtful Sound. There’s no one else out there from the same planet as I. Pollo, your continued support and smiles mean the world to me; long may they come my way. Wantiab.

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This thesis is dedicated to my parents, David and Patricia Johnston.

Without your endless love, support and guidance this would not have been possible.

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Table of Contents

Abstract

ii

Acknowledgments

iii

Dedication

iv

List of Figures

vi

List of Tables

vii

Chapter 1:

General Introduction

Chapter 2:

A time-based method for defining association using

1

photo-identification

13

Chapter 3:

Seasonal variation in rates of association

33

Chapter 4:

Influential factors upon heterogeneity in female

Chapter 5: References

reproductive success

50

General Discussion

65 74

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List of Figures Chapter 1 Figure 1.1

The Fiordland coastline

7

Figure 1.2

Doubtful Sound

9

Figure 2.1

Standard daily survey route in Doubtful Sound

17

Figure 2.2

An individual with both permanent and temporary dorsal marks

18

Figure 2.3

Hierarchical cluster analysis using the group membership method

22

Figure 2.4

Social network using the group membership method

23

Figure 2.5

Cophenetic correlation coefficient and stress analysis

24

Figure 2.6

Hierarchical cluster analysis using the time-based method

26

Figure 2.7

Social network using the time-based method

27

Figure 3.1

Group sizes for summer and winter periods since 2005

39

Figure 3.2

Average association indices for summer and winter periods since 2005

39

Figure 3.3

Average association indices separated for males and females

40

Figure 3.4

Hierarchical cluster analysis for the summer of 2015

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Figure 3.5

Hierarchical cluster analysis for the winter of 2015

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Figure 3.6

Social networks for summer and winter periods of 2015

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Chapter 2

Chapter 3

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Chapter 4 Figure 4.1

Model averaged estimates of parameters predicting calf survival

60

2.1

Association indices between mothers and offspring

25

2.2

Coefficient of variations from bootstrapping procedures

28

3.1

Survey effort for the years since 2005 included in analyses

36

3.2

Average association rates & Wilcoxon signed-rank test statistics

List of Tables Chapter 2

Chapter 3

For each season analysed since 2005 3.3

40

Genders of the top ten scoring individuals per year for Eigenvector centrality

41

Summary of the top ten scoring models

59

Chapter 4 4.1

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Chapter 1: General Introduction

Chapter 1 General Introduction

Sociality in animal populations Analyses of social structure attempt to capture and describe the underlying patterns of behaviour of individuals towards one another. In social species, an individual’s conspecifics are key elements within the environment; interactions may be co-operative, competitive, aggressive, reproductive or neutral. Interactions are especially important in highly social fission-fusion societies (Grellier et al. 2003) in which, depending on the context, small groups fuse into larger groups, which later split into smaller units (e.g. chimpanzees, Pan troglodytes, bottlenose dolphins, Tursiops truncatus; Lee, 1986; Grellier et al. 2003). Darwin recognised the problem social cooperation posed for the theory of natural selection. Why should an individual act to enhance the fitness of another? This question has been central to studies of social evolutionary theory and has paved the way for studies of the key social drivers of population dynamics. Though Darwin did not fully understand the mechanisms of heredity, he foresaw two of the major modern explanations for sociality: (1) direct increases in an individual’s personal reproductive success; and (2) indirect increases in the reproductive success of individuals genetically related to the focal animal (Darwin, 1871). While Darwin, for the time, had a high degree of understanding of social evolution, his writing paid less attention to how ecology and sociology may intersect. The theories of sociology and ecology were finally brought together in the writings of Kropotkin (1902) in his book Mutual Aid: A Factor in Evolution. Kropotkin attempted to counter the prevailing Darwinian view of the “harsh, pitiless struggle for life” by providing examples of cooperation from the natural world. He described the Siberian snowstorms as a much more powerful force than the struggles among members of the same species, forcing cooperation among individuals rather than competition. Though far less sophisticated than Darwin’s work, it served as a helpful antithesis to the prevailing focus on competition as a key evolutionary driver; highlighting that cooperation is common in the natural world, and that ecological conditions are central to social evolution. 1|Page


Fully understanding the social systems of animals requires aspects of both ethology and behavioural ecology. The ethologist, concerned with patterns of how interactions may be organised and change through time, adopts a largely bottom-up approach, “attempting to start their analyses from a secure base of description” (Hinde, 1982; p.19). Researchers must then assess Tinbergen’s four “whys” – causation, development, function, and evolution (Tinbergen, 1963). The behavioural ecologist is principally concerned with the function of an observed behaviour and how it might influence fitness and reproductive success (Krebs & Davies, 1991). With current analytical methods, such as graphical networking (Newman, 2003), representations of social structures and patterns can be easily produced – this is pure ethology. The behavioural ecologist is then concerned with looking for plausible explanations of the patterns observed. While there have been numerous concepts and definitions of social structure over the years (e.g. Rowell, 1972; Wilson, 1975; Kappeler & Van Schaik, 2002), the most consistent and frequently cited is that of Robert Hinde (1976). His framework arose from an ethological perspective, and was based largely upon observations of captive primates. The framework has three main components: interactions, relationships, and social structure. The interaction is how the behaviour, or even the presence, of one individual affects another. Relationships are the content, quality and patterning of such interactions, and the social structure of a population is the nature, quality and patterning of the relationships among all individuals (Hinde, 1976). Though Hinde’s framework provided a firm foundation for the study of social structure, it did not include any indication of causal factors. Social structure is ultimately the result of interactions among individuals, though the content, quality and patterning of such interactions are likely to be influenced by factors such as kinships, demography, and separate cultural groups within a population (Hinde, 1976). For example, conformism, an aspect of culture, can strongly influence the social structure of part or all of a population (Whitehead, 1993). Using Hindes’ framework, we can identify and construct quantitative representations of interactions among individuals. The challenge then becomes attempting to quantify aspects of the quality, content and patterning of interactions and relationships, and how these in turn may influence the society observed, and the dynamics that govern the population as a whole.

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Why do animals form groups? Group living is generally thought to be driven by the enhancement of survival and reproductive success of individuals within groups by trading off competing factors. Resource and risk distribution play important roles in determining the social strategies and patterns of populations (Cezilly & Benhamou, 1996; Geffen et al. 1996; Johnson et al. 2002). Potential benefits of group living include allopatric parental care (Johnston et al. 2002), reduced risk of infanticide (Dunn et al. 2002), reduction in parasitism, and an increase in mating opportunities (Gowans et al. 2008). One of the major drivers of group living, however, is the increased detection and exploitation of resources (Tristram, 1859; Miller, 1922; Scheel & Packer, 1991; Creel & Creel 1995). A single individual must forage for resources alone. A group of individuals foraging together, however, can rely upon one another to find resources. Early researchers noted that a single forager may search for resources unsuccessfully over extended periods of time, while a group of individuals searching at the same time reduces the chance of resources escaping detection (Pycraft, 1910; Miller, 1922). Other individuals within the group are then alerted by some cue to the resources found by successful individuals (Pitcher et al. 1982). This has been termed local enhancement (Thorpe, 1956) and has been documented in a vast number of taxa (Galef & Giraldeau, 2001). Grouped individuals may also forage at a faster rate than if foraging alone. This may be caused either by an increase in competition between individuals (Shaw et al. 1995), or because more time is allocated to foraging by grouped individuals (Caraco, 1979). This increase in foraging activity by members of a group has often been termed social facilitation (Zajonc, 1965), and, coupled with local enhancement, serve to increase foraging efficiency of individuals within a group compared to those alone. Offsetting the benefits are the costs associated with group living. There is a risk of increased parasite loadings and disease transmission (Alexander, 1974). Groups may also become more conspicuous to both predators and prey as size increases (Geist et al. 2005; Cooper et al. 2007; Beauchamp 2008; Sprague et al. 2008). Perhaps the strongest influence is an increase in competition among members of the group (Sutherland, 1996). When a resource of finite size is encountered by a foraging group, each member obtains a smaller share of the resource than if they were foraging alone, despite interactions among members or not. This is known as exploitative competition (Sutherland, 1996) and can be of greater importance to some individuals than others as unequal competition in groups is common. Exploiting large patches 3|Page


that satiate each forager before depletion helps to offset the costs of exploiting food in groups, though such patches can be rare. Whatever the cost of group living may be, its intensity often increases with group size (Beauchamp, 2014).

Quantifying Sociality In order to better understand the social patterns and behaviours of animals, they need to be abstracted into a form suitable for analysis. Social analyses are generally comprised of systematically collected records of data on interactions, associations among identified individuals within a group, or some other such metric. Interactions are the basis of Hinde’s (1976) framework – “the behaviour of one animal is affected by the presence or behaviour of another”. Interactions often cannot be observed however, for example in cetacean species in which observations are often restricted to surfacing events (Whitehead, 2008). In such instances associations among individuals are used: individuals are defined as associated if they are in a situation in which interactions can take place (Whitehead & Dufault, 1999). Spatial proximity of individuals to one another, plus some behavioural state if possible, is often used to define association (e.g. within x body lengths or metres from one another and heading in the same direction; Perry, 1996). Associations may either be symmetric (e.g. if A is associated with B, then B is associated with A to the same degree) or asymmetric. For example, the nearest-neighbour is a commonly used asymmetric method for defining association in which A may be the nearest neighbour to B, though C may be the nearest neighbour to A (Whitehead, 2008). Groups are often used to define association among individuals, in which there is an assumption that all individuals within a defined group are associated to the same degree. This assumption has been termed the “gambit of the group” (Whitehead & Dufault, 1999). Groups are often defined in the same way as associations (e.g. within x body lengths or metres of one another and some behavioural state), though given the possibility of violating the above assumption when using distance based criterion (A and B may meet the criterion, as well as B and C, but A and C do not), a chain-rule is often adopted in which, if A and B meet the criterion, as do B and C, then so do A and C automatically (Clutton-Brock et al. 1982; Smolker et al. 1992). Groups are often defined arbitrarily – what constitutes a “group” is based upon an anthropogenic perception. 4|Page


Ecology, biology and distribution of bottlenose dolphins One of the best known of all cetaceans, bottlenose dolphins (Tursiops spp.; Montagu, 1821) are found world-wide and inhabit a range of environments; from shallow coastal or estuarine environments, to offshore pelagic habitats (Wells & Scott, 2009). They have a global distribution and are found in tropical and temperate areas of both Northern and Southern Hemispheres (Ridgeway & Harrison, 1999). Behaviour, feeding ecology, reproductive strategies and habitat use varies substantially among populations (Wells & Scott, 2009). In some cases geographic isolation among populations may occur over small scales (a few 10s of km), serving to increase the rate at which behaviour diverges (Parsons et al. 2002). There is heated debate regarding the taxonomy of the Tursiops genus, though three species are presently accepted: the common bottlenose dolphin (Tursiops truncatus; Montagu, 1821), the indo-pacific bottlenose dolphin (Tursiops aduncus; Ehrenberg, 1833), and the recently discovered Burrunan dolphin (Tursiops australis; Charlton-Robb et al. 2011). These are defined by differences in genetic, morphological and osteological characteristics (CharltonRob et al. 2011). Ecological generalists, bottlenose dolphin diets are generally comprised of a large variety of squid and fish (Barros & Odell, 1990), though specialization by certain demographic groups (e.g. lactating mothers), or individuals on a particular prey species (Gannon & Waples, 2004; Gowans et al. 2008; Sargeant & Mann, 2009) has been documented. Bottlenose dolphins are slow to reach sexual maturity. Typically, males reach sexual maturity between 7 to 17 years, as opposed to 5 to 14 years for females (Mead & Potter, 1990). Long-term studies suggest substantial variability in age at maturity among populations (Urian et al. 1996; Wells & Scott, 2009). Sexual dimorphism is apparent in most populations, males being 2-10% longer and heavier than females (Cockroft & Ross, 1990; Tolley et al. 1995). Sharks are the most common predator of bottlenose dolphins. Depending on region, the main species involved are bull sharks (Carcharhinus leucas), great white sharks (Carcharadon carcharias), dusky sharks (Carcharhinus obscurus) and tiger sharks (Galeocerdo cuvier) (Wood et al. 1970). Avoidance of shark predation appears to be a significant factor in moulding habitat use by dolphins in Shark Bay, Western Australia (Heithaus and Dill, 2002). Shark predation is common enough, in an evolutionary sense, for the cestode Phyllobothrium delphini, whose adults are found in the spiral valve of sharks, to use dolphins as intermediate hosts (where they encyst in the blubber; Siqueir & Le Bas, 2003). 5|Page


Bottlenose dolphins are extremely social animals, with a high degree of cognitive ability (Connor et al. 2000; Connor 2007). This sociality has aided in the development of extreme behavioural flexibility (Herman, 2006); sophisticated and specialised behaviours are known to be culturally transmitted (Krützen et al. 2005). Unique socially learned behaviours can be population and/or site specific and include various acoustic (Janik & Slater, 1997; Tyack & Sayigh, 1997) and foraging skills (Lopez & Lopez, 1985; Weinrich et al. 1992; Guinet & Bouvier, 1995; Mann & Sargeant, 2003). Sargeant et al. (2005) describe a highly specialised method of foraging, beach hunting, not only unique to a certain population, but to specific individuals related to one another within that population. The strategy involves a dolphin surging onto a beach, causing partial or full emersion from the water, in order to catch a single chased fish. It appears to be primarily a vertically learnt social behaviour passed from mothers to their calves, though horizontal learning by individuals who frequent the same coastal regions also occurs (Sargeant et al. 2005). Other documented foraging strategies include disturbing shallow seagrass-dwelling prey by hitting their tails upon the surface of the water (Connor et al. 2000; Nowacek 2002), hitting fish directly with their tails (Shane, 1990; Nowacek, 2002), digging in the substrate with their rostra (Rossbach and Herzing, 1997; Nowacek, 2002; Mann and Sargeant 2003) and trapping fish by stirring up sediment (Lewis and Schroeder, 2003), among other behaviours (e.g. Würsig 1986; Smolker et al. 1997; Mann and Sargeant, 2003; Gazda et al. 2005).

The bottlenose dolphins of Fiordland Four main areas of New Zealand coast are inhabited by bottlenose dolphins: the north-east of the North Island (Constantine et al. 2004), around the Marlborough Sounds in the north of the South Island (Merriman et al. 2009), Fiordland (Williams et al. 1993; Currey et al. 2008) and Stewart Island/Southland (Brough et al. 2014). Fiordland is a World Heritage Area with 2.6 million ha of virgin temperate rainforest that drains into 14 major fiords (McLeod et al. 2010), located on the south-western coast of the South Island of New Zealand (Fig. 1.1). The bottlenose dolphins of Fiordland form three distinct coastal sub-populations, almost at the southern extreme of the species’ range (Bräger & Schneider, 1998; Lusseau et al. 2003). While the northern population is comparatively nomadic, ranging across seven of the 14 fiords, the Doubtful and Dusky Sound populations 6|Page


are largely restricted to their respective fiords (Currey et al. 2007) and are considered discrete (Rowe et al. 2010). They are also genetically isolated from other coastal populations of bottlenose dolphins in New Zealand (Tezanos-Pinto et al. 2008) and, though a globally abundant species, the Fiordland population has recently been classified as ‘critically endangered’ (IUCN, 2012) due to their low numbers and modelled declines in population (Currey et al. 2009; 2011). This thesis focuses on the population of Doubtful Sound.

Figure 1.1: Fiordland, located on the south western coast of the South Island of New Zealand, with Doubtful/Thompson Sound in bold. Colours indicate the approximate home-ranges of the three bottlenose dolphin populations.

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The bottlenose dolphin population of Doubtful Sound The Doubtful/Thompson Sound complex (Patea; 45°30’S, 167°00’E), known hereafter as Doubtful Sound, is the second largest of the 14 fiords of Fiordland (Fig. 1.2). While all fiords reach over 100m in depth, Doubtful Sound is deepest, reaching 434m within Malaspina Reach (Stanton & Pickard, 1981). The fiord complex has an area of 83.7km2, a mean depth of 200m (Stanton & Pickard, 1981), and a permanent year-round low-salinity-layer at the surface (LSL; Gibbs, 2001). This LSL is present in other fiords due to the high annual rainfall in Fiordland (6000 – 8000mm per year), though is exaggerated within Doubtful Sound due to increased levels of freshwater input from the Manapouri hydroelectric power-station. The station was commissioned in 1969 (Boyle et al. 2001) and has approximately tripled freshwater input into the fiord via a tailrace draining water from lake Manapouri (Gibbs, 2001). The consequent effects on sea-surface temperature have been proposed as contributing to seasonal changes in habitat use by the dolphin population, with warmer, inner portions of the complex being preferred during summer, and warmer, outer oceanic waters during winter (Schneider, 1999). A second tailrace was opened in 2002 (Currey et al. 2009). The bottlenose dolphin population of Doubtful Sound has been the focus of a long term photo-ID monitoring programme by Otago University’s Marine Mammal Research Group since 1990 (Williams et al. 1993). It is a relatively small population, the most recent estimate being 62 individuals in 2015 (CV = 0.0%; Johnston & Dawson, 2016). It has experienced periods of substantial decline over the last 25 years, with low calf survival the most likely explanation (0.622 in 2011, 95% CI: 0.435-0.830; Currey et al. 2009; Henderson et al. 2013). It is one of the most thoroughly studied populations of wild bottlenose dolphins in the world. Studies have included abundance and population dynamics (Williams et al. 1993; Currey et al. 2007; 2008; 2011), acoustic repertoire (Boisseau, 2005), habitat use (Henderson, 2012), social structure (Lusseau, 2003a; 2007; Lusseau et al. 2006), morphology (Rowe & Dawson, 2008) and impacts of tourism (e.g. Lusseau, 2003b; Guerra et al. 2014). Several human-induced threats to the population have been identified. The freshwater input from the Manapouri hydroelectric power station (Gibbs, 2001) has caused significant ecological change within the fiord. Loss of species diversity in sub-tidal communities, as well as alteration of the inner fiord benthic communities (Rutger & Wing, 2006), may have affected the feeding ecology of the dolphins present. Additionally, the outflow from the hydro-electric station acts to lower surface water temperatures at key times of the year, and 8|Page


may cause calves to become thermally compromised (Currey et al. 2008). Increased boatbased tourism (Lusseau et al. 2006) and historical fishing resulting in declined fish stocks (Beentjes & Carbines, 2005) have also likely had direct and/or indirect effects upon the dolphins present.

Figure 1.2: Doubtful Sound, Fiordland, on the south western coast of the South Island, New Zealand.

Female reproductive success It is not uncommon in populations for some individuals to contribute disproportionately to recruitment (Clutton-Brock, 1982). A number of factors may contribute to this, such as age (Riedman et al. 1994), habitat use (Mann et al. 2000), experience (i.e. how many previous calves; Atkinson & Ramsay, 1995), size (Reiter et al. 1981) or an individual’s position in the social hierarchy (Wauters & Dhondt, 1989). While male reproductive strategies focus on gaining and maintaining access to receptive females, the strategies of female bottlenose 9|Page


dolphins, at least in Shark Bay, Western Australia, appear to revolve around access to food resources and protection of calves from both predatory sharks and conspecifics (Mann et al. 2000). Females have been known to form coalitions with one another against males, as infanticide has been reported in some populations (Dunn et al. 2002). Therefore, it could be expected that female reproductive success could be correlated with her relative importance within the social network. In Doubtful Sound, variation in reproductive success of females has been shown to be highly correlated with timing of their births (Henderson et al. 2014). Calves born soon before water temperatures peak (i.e. in January) have a much greater chance of survival. It appears water temperature is a strong driver of the dynamics of this population, driving calf survival directly (Currey et al. 2007), and habitat use of the dolphins throughout the year (Henderson, 2013). Though the social structure of the Doubtful Sound population has been described before (Lusseau et al. 2003), attempting to relate the social patterns of successful vs unsuccessful mothers has not. This integrated approach could allow valuable insights into the relative importance of sociality and how it may affect a calf’s survival, an important driver of the populations’ dynamics as a whole.

Thesis objectives Since the effects of a mother’s sociality on her calf’s survival have not been studied in Doubtful Sound, or to my knowledge in any bottlenose dolphin population, an in-depth assessment of such effects is warranted. Additionally, no analysis has been attempted to see how association patterns change during a given year. These analyses will shed light on the importance of social patterns to calf survival, as well as the dynamics of the association patterns in this population of highly social animals.

The principal objectives in this study are to: i.

Develop and assess a time-based method for defining association patterns of the bottlenose dolphins of Doubtful Sound. Associations are usually defined in the field by the distance between the animals concerned (i.e. group membership). In order to extend analyses of association to historical data collected during regular monitoring 10 | P a g e


trips, an alternative association metric is needed. The method also attempts to avoid the assumption that all individuals within a group are associated to the same degree. This chapter explores the use of time stamps on digital identification photographs to quantify associations – the assumption being that individuals photographed close together in time were more than likely close together in space. Different time “windows” are used, and results compared with those of the traditional groupmembership method to assess its relative effectiveness. A version of this chapter is submitted to Animal Behaviour (co-authored by Johnston, Rayment, Slooten and Dawson) ii.

Quantify seasonal differences in association patterns in the Doubtful Sound bottlenose dolphin population. Grouping patterns are often in response to environmental pressures. Association rates are therefore likely to change over time in response to the ease of which resources are exploited, changing environmental conditions, or the presence and absence of seasonal predators. Association patterns among individuals are quantified using the time-based method in order to calculate pairwise indices from photos collected during summer and winter periods of a number of years since 2005. An in-depth assessment is also conducted for data collected during the 2015 summer and winter periods.

iii.

Investigate effects of the mother’s sociality on calf survival. Female bottlenose dolphins in Doubtful Sound exhibit great variation in reproductive success; some mothers are consistently successful while others are not. To assess the relative importance of potential factors influencing this, an information theoretic approach (e.g. Anderson et al. 2000; Gerrodette, 2011) is employed. The social network metric eigenvector centrality describes each mother’s relative importance within the social network. This metric is included in model selection procedures in an attempt to explain a calf’s survival to one year old. Additional non-social explanatory variables included are mother’s experience (i.e. how many calves she has had prior) and the timing of each birth.

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Thesis structure Each of the chapters in this thesis has been written as an independent manuscript. Some repetition, particularly in methodology, is therefore inevitable. I have attempted to reduce this by providing a general introduction in Chapter 1 and by combining all the references at the end of the thesis. In Chapter 5, the general discussion, I summarise the results from this study, discuss the implications for the population, consider some study limitations, and provide research recommendations for future studies on cetacean populations and sociality.

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Chapter 2: A time-based method for defining association rates

Chapter 2 A time-based method for defining associations using photo-identification

ABSTRACT Associations between individuals are a measure of sociality. Association analyses are thus important in increasing our understanding of how individuals behave towards one another, and therefore how their societies are structured. For species in which individuals are uniquely identifiable, photo-identification is an invaluable method for documenting associations. Based on the assumption that individuals photographed close together in time are physically close in space, the metadata associated with digital photography offers an opportunity to base association analyses on time between images. I tested this approach via analysis of association patterns within an isolated population of bottlenose dolphins (Tursiops truncatus) in Doubtful Sound, New Zealand. I compared the widely used group-membership analysis method and an alternative time-based method in which individuals were considered associated if photos of each fell within a specified time window. Windows of one to six minutes were trialled, with two minutes providing the best compromise between lowest stress from multidimensional scaling and highest cophenetic correlation coefficient from cluster analyses. Overall social structures between methods were similar; the group membership method yielded three sub-groups of mixed sex individuals while the time-based analysis produced four. All mother-offspring relationships were represented well in both methods. Additionally, coefficient of variation results from bootstrapping procedures indicated increased precision of calculated pairwise indices for the time-based method compared to the group membership. This study validated the approach of using time as a basis for analyses of associations, and suggests this approach can provide increased detail with similar field effort. Importantly, this method can be applied to any population of photographically identifiable individuals, and can be retrospectively applied to any photo-ID data set in which images are time-stamped by the camera.

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INTRODUCTION Quantifying how individual animals behave towards one another provides the basis for our understanding of animal sociality. For this to be possible, individuals need to be identifiable, ideally via natural marks. Photographic recording of uniquely marked individuals has provided data on sociality in a wide variety of taxa, including various primates (e.g. Chapman et al. 1995; Boesch & Boesch-Achermann, 2000; Stumpf, 2007), cetaceans (e.g. Connor et al. 2000; Gowans et al. 2001), elephants (Loxodonta affricana, e.g. Wittemyer et al. 2005), spotted hyenas (Crocuta crocuta, e.g. Holekamp et al. 1996), lions (Panthera lio, e.g. Mosser & Packer, 2009), meerkats (Suricata suricatta, e.g. Drewe et al. 2011) and grey kangaroos (Macropus giganteus, e.g. Best et al. 2013). The stability of social relationships is thought to increase when the net benefits of maintaining associations outweigh the costs (Krause & Ruxton, 2002). These benefits, brought about by long-term social bonds, can increase the reproductive fitness of individuals through a variety of mechanisms, such as reduced predation risk (Gowans et al. 2008), reduced infanticide (Dunn et al. 2002) and reduced aggression towards one another (Asensio et al. 2008), as well as an increased rate of information exchange (McComb et al. 2001) and/or culturally learned behaviours (Sargeant et al. 2005). The latter factors may play especially important roles for long-lived animals (Whitehead et al. 2005) and in low productivity environments (Alexander, 1974; Bertram, 1978). Most studies of association patterns use observations of co-occurrence in a group as the raw data, i.e. all members of the same group are considered associated at that time (Connor, 2000; Connor et al. 2000). Most definitions of what constitutes a group are based on distance between group members and common behaviour (Whitehead and Dufault, 1999). The assumption is that physical proximity reflects social closeness. While this measure has provided valuable insights into the social structures of many populations, it provides information at a relatively coarse scale, and does not distinguish between individuals socially associating with each other and those which are simply in the same place at the same time, perhaps due to a common purpose. This method assumes all individuals within a group are associated with one another to the same degree, the “gambit of the group” (Whitehead and Dufault, 1999), and may not be appropriate in socially dynamic species. For example, coalitions between male savanna baboons (Papio cynocephalus) are often formed within social groups in order to gain access to females (Bercovitch, 1988). These coalitions would not be identifiable using methods in which individuals within a group are assumed to be 14 | P a g e


equally associated. The assumption is also inappropriate for populations in which group sizes may be large. Many species are often found in groups of several hundred (e.g. Indian Ocean bottlenose dolphins, Tursiops aduncus; Connor et al. 2001) and it is unlikely that all individuals within such large groups associate to the same degree with one another. Finer resolution can be achieved by defining individuals as associated if they are within a certain distance of one another (e.g. Ficken et al. 1981; Connor et al. 2000; Wittemyer et al, 2005; Croft et al. 2007; Gibson & Mann, 2008; Wiszniewski et al. 2009; Chiyo et al. 2011), thus allowing for differing degrees of association within groups. A chain-rule is often adopted in which, if A and B meet some criterion (e.g. x body lengths apart), as do B and C, then A and C are also considered associated, even if these individuals do not meet the criterion themselves (Clutton-Brock et al. 1982; Smolker et al. 1992; Gowans et al. 2001; Machanda et al. 2013). Again, such analyses often yield a greater degree of association among individuals than might actually be present, biasing results. Time has been used as a measure of association; individuals that spend proportionately more time together than with others are considered more strongly associated (e.g. Sailer & Gaulin, 1984; Bigg et al. 1990). These analyses require data to have been collected in very specific ways however, meaning that data collected for other purposes (e.g. for abundance and survival rate analyses) often cannot be analysed using these methods. In this chapter a method for quantifying associations using the metadata associated with digital photographs is developed and tested. The key assumption is similar to the chain rule method; that individuals photographed close together in time are spatially close, and hence likely to be associated. Depending on the time window used, it offers the potential to avoid the assumption of the “gambit of the group”. Test data come from a small, isolated population of bottlenose dolphins (Tursiops truncatus) which is almost entirely restricted to the Doubtful Sound complex in Fiordland, New Zealand. Each individual in the population is identifiable via natural markings of the dorsal fin. Photographic identification surveys of this population have been conducted regularly since 1990 (e.g. Williams et al. 1993; Currey et al. 2007; Henderson et al. 2014). Unlike other studied populations of bottlenose dolphins, the Doubtful Sound population consists of large mixed-sex groups, with strong and long-lasting associations between sexes (Lusseau et al. 2003). This is thought to be a response to ecological constraints imposed by isolation in a dynamic environment close to the limit of the species’ latitudinal range 15 | P a g e


(Lusseau et al. 2003). As part of their survival strategy in this physiologically demanding system, the dolphins have developed a social system characterised by strong, long-lasting social bonds. METHODS Field techniques and data collection Photo-identification data were collected over the summer of 2015. The Doubtful Sound population of bottlenose dolphins is relatively small (63 individuals during this study). Surveys were conducted from a 5m outboard powered boat (70hp four-stroke Yamaha), following a systematic daily route in which the entire Doubtful Sound complex could be surveyed in a single day, given favourable weather conditions (Fig. 2.1). When a dolphin group was sighted, the vessel approached gradually to within 20m. To allow the best angle for photography, a course parallel to the direction of travel of the dolphins was maintained. Photographs were taken using a Nikon D7100 DSLR camera with an AF80– 200mm f2.8ED Nikkor lens. Groups were followed until there was reasonable confidence that the number of high-quality photographs obtained was at least four times the estimated number of individuals within that group (Würsig & Jefferson, 1990). This criterion also allowed a more robust estimation of group size (Würsig & Würsig, 1977). Photographs were taken of the dorsal fin of any dolphin within range (approximately 20m), regardless of the distinctiveness of an individual, or whether that individual had already been photographed. Once sufficient photos had been obtained, data collection for that group was ceased and the survey route resumed. Protocols are described in detail by Williams et al. (1993) and Currey et al. (2009).

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Figure 2.1: Standard daily survey route in Doubtful Sound, New Zealand.

Data analysis Photographs were first graded based on quality; we analysed images only if they were sharply focused, well exposed, and showed an unobscured lateral view of the dorsal fin (Wilson et al. 1999). Individuals were identified primarily using dorsal fin marks that were unlikely to change over time (nicks and tears), though given the high intensity of monitoring of this population, less permanent features, such as tooth rakes and lesions, are easily tracked and thus were also used (Currey et al. 2007; Fig. 2.2).

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Figure 2.2: PL, a male first sighted in 1995 with both permanent (nicks) and temporary (tooth rakes) marks.

Half-weight pairwise association indices (HWI) between individuals were calculated using two methods: the group membership (GM) method and a time-based (TB) method. For the GM method, individuals were considered associated if they were part of the same group or cluster of groups, where clusters were less than 200m apart (Slooten et al. 1993) and engaged in similar activities (Lusseau, 2007). For the TB analysis, metadata associated with every photograph, including time taken (to the nearest second), were extracted using the freely available software ExifTool (Harvey, 2015). Time windows of between one and six minute durations were trialled. Beginning with the first photograph of an identified individual, all other photographs of individuals which occurred within time windows of 1, 2, …, 6 minutes were considered associated; sampling windows in which individuals were associated occurred sequentially one after another. When several images of acceptable quality resulted from the same surfacing of an individual, only the first photo in the sequence was used in analyses. Additionally, all other photos of that individual up to one minute afterwards were discarded. This was in an attempt to maintain data independence, as it would allow time for that individual to reorganize within a group, or sampling window.

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Pairwise association indices using the GM and TB methods were calculated for all combinations of individuals using the programme SOCPROG v2.5 (Whitehead, 2009). The HWI is given as:

𝑋 𝑋 + 0.5 (𝑌𝑎 + 𝑌𝑏)

in which X is the number of times dolphins a and b were sighted together, Ya is the number of times only dolphin a was sighted, and Yb is the number of times only dolphin b was sighted (Cairns and Schwager, 1987; Bouveroux & Mallefet, 2010). The HWI can range from 0 (the two dolphins are never seen together) to 1 (the two dolphins are always seen together). The HWI is most frequently used for GM analysis as it accounts for an increased probability of encountering a group containing either individual A or B (due to there being two possible groups available to encounter), compared with a group in which both individuals are observed together (Quintana-Rizzo & Wells, 2001; Lusseau et al. 2003; Gero et al. 2005). The HWI was also used for the TB analyses to allow comparison of results with the GM. For each method I used average-linkage cluster analysis to produce dendrograms in which individuals are hierarchically organised based on their degree of association to one another. The average-linkage method (Romesburg, 1984) is recommended as large or small similarities in association rates, perhaps caused by unusual relationships, random error, or measurement error, have less of an effect than in analyses using single or complete linkage (Whitehead & Dufault, 1999), and is therefore more likely to mimic real structures of association data (Milligan & Cooper, 1987). Following Newman (2004), the likely number of sub-groups based upon the peak in a modularity coefficient was estimated. Modularity is the difference between the proportion of total association indices within the defined clusters and the expected proportion if individuals were distributed at random. The maximum modularity, and association index at this value, indicates at what point clusters are formed. Modularities greater than 0.3 are generally considered to indicate clear sub-groupings within the data (Newman, 2004). Clusters defined in this way were saved as supplemental data and represented by network analysis plots produced in UCINET (version 6.558; Borgatti et al. 2002) using non-metric multidimensional scaling (nm-MDS). In these plots individuals are arranged so that the more closely associated they are the closer in proximity to one another 19 | P a g e


they are plotted. The “best fit” of all combinations of dyads was found iteratively via minimising the plot’s stress value, which is the degree of failure in representing associations among individuals (Manly, 1994). Plots were visually represented in the programme Netdraw (version 2.157; Borgatti, 2002). To find the most appropriate time window for TB analyses, stress values from nm-MDS, and cophenetic correlation coefficients (c) from cluster analyses were compared. The c-value represents how faithfully dendrogram plots represent the hierarchically arranged pairwise distances between individuals; a high c-value representing reliable dendrograms. Therefore the time window providing the best compromise between lowest stress and highest c was considered to best represent the data, and thus provide the most accurate representation of association patterns. Assessment of each method’s precision was undertaken by first calculating the standard errors of pairwise indices through bootstrap procedures within SOCPROG (Whitehead, 2009). Sampling periods were bootstrapped 1,000 times with replacement to produce replicates. The approximations are:

SE(𝑎) = 𝑎√((1 − 𝑎)𝑤)

in which a is the association index and w is the number of sampling periods including an association (Whitehead, 2008). From these standard errors, coefficient of variations (CV) were produced and a random subset of 20 CVs compared between methods. The CV is a measure of spread describing the variability about a dataset’s mean. As it is unit-less, it offers a robust measure of precision for comparisons of datasets with different units or means.

RESULTS Surveys were conducted over 19 days with dolphins encountered on 15 (34 groups in total; mean group size = 35, SD = 18.0). The selection criteria outlined above resulted in 5,510 good quality photos of dolphins included in the association analyses. Individual dolphins were photographed between 38 and 134 times (mean = 87.5, SD = 26.4). Given that a weighted network measure was used, and that association indices were generally high for the 20 | P a g e


group membership method (mean = 0.79 ± SD 0.12), data were not filtered, thus all individuals and associations were included in analyses (Franks et al. 2010). Though associations were lower using the TB method (mean = 0.24 ± SD 0.11), to allow a relative comparison of results between methods data were also left unfiltered in this analysis. There was no correlation found between group size and average association rates in Pearson’s correlation tests (p > 0.05).

Group Membership analysis Cluster analyses using the GM method indicated three potential mixed-sex sub-groups (one large and two smaller) within the population. The peak in modularity was low however (0.019); with a cophenetic correlation coefficient of 0.722 (Fig. 2.3b). This suggests little support for the three defined sub-groups (modularity < 0.3; Newman, 2004). There were 18 instances of perfect association (two individuals always seen together); two of them between a mother and her calf (Hook and Shmee, Wave and Swell; Fig. 2.3a). Most mothers and their offspring (those individuals under the minimum weaning age for this species, < 3 years old; Henderson 2014) are defined closely associated with one another. Network analyses for the population were consistent with the dendrogram plots, with the three defined groups being largely separate from one another (Fig. 2.4). Most mother – offspring pairs are again plotted close to one another, indicating strong association. The relatively low level of association between Jack and G (AI = 0.20; the lowest association in this analysis) is also captured well.

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a

Tiger Zebra G Poxfin Granite Coral Moby Kringel Alysa SN96 Paua Jack Scratchy Itchy Wave Swell Spiral Helix Stripes Shmee Hook Alaska Patio Dart SN9 C3P0 SN4 R2D2 BZ-Blackmum Upbang Bafta Gallatin Mussel 2-Scallops Gerbil TR120 Splash Frenzy Eeyore Pooh Piglet Handy Chip Thumper Whitetip Knit W-Notch Number-1 Mus Five Tick-Tack Pie Seal Halley Ripplefluke Phant PL Flem Comet Chewy DN63 Glob Ellie

b

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

Association Index

Figure 2.3: (a) Cluster analysis using average-linkage method for the Doubtful Sound bottlenose dolphin population (n = 63), using the HWI group membership method. Black dashes indicate individuals always seen together. Colours represent the three different sub-groups. Mothers and their offspring are indicated by red connecting lines / boxes. (b) Sub-groups were defined by the peak in the modularity coefficient.

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Jack

Shmee Hook

Itchy Scratchy

Helix

Stripes SN96

2-Scallops

Mussel Bafta

Gerbil

Piglet

Chip Frenzy

Moby

Handy

Upbang

R2D2

C3P0

Spiral

Number-1

Gallatin

SN4 BZ-Blackmum

Thumper

SN9

Paua Pooh

W-Notch

Wave Swell

Alaska

Five Mus

TR120 Phant Glob DN63 Ellie Flem Ripplefluke PL Chewy Halley Comet

Whitetip Knit

Dart Patio Seal Tick-Tack

Pie Splash

Tiger

Eeyore Coral

Alysa

Kringel

Granite

Poxfin Zebra G

Stress: 0.2283

Figure 2.4: Social network of the Doubtful Sound bottlenose dolphin population (n = 63) using HWI based on group membership. Circles represent females, squares represent males and diamonds represent individuals of unknown gender. Colours represent sub-groups defined by the peak in the modularity. Individuals are plotted using non-metric MDS. Mother – offspring groups are indicated with dashed lines.

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Time-based analysis In the TB analyses, the two minute window to define associations had the best compromise between a relatively high c–value and low stress and was therefore used in further analyses (Fig. 2.5).

0.82 (c)

0.81

Stress

0.26

Stress

0.80 0.25

0.79 0.78

0.24 0.77 0.23

Cophenetic correlation coefficient (c)

0.27

0.76 0

1

2

3 4 Time (min)

5

6

7

Figure 2.5: Scatterplot showing stress values associated with non-metric MDS plots, and cophenetic correlation coefficient (c) values associated with cluster analysis outputs from SOCPROG, for the six sampling windows trialled. Error bars are 95% confidence intervals from 20 runs of nm-MDS analyses per trialled sampling window. The arrow represents a compromise between low stress and high c, and was the sampling period used in further analyses.

Based on the peak in the modularity coefficient, cluster analyses calculated using the two minute sampling period also indicate no definite and clear division of the population into clusters as modularity was < 0.3, although four potential mixed-sex groups were identified; one small, two larger, and one large group (Fig. 2.6a). This peak is at approximately 0.085, with a cophenetic correlation coefficient value for cluster analysis of 0.809 (Fig. 2.6b). There were no instances of perfect association, though all mother and offspring (< 3 years old) pairs were greater than the population average (AI = 0.24, SD = 0.11; Table 2.1).

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Chapter 2: A time-based method for defining association rates Table 2.1: Association indices (AI) between mothers and their offspring. Indices calculated using group membership (GM) and time-based (TB) sampling methods. Population averages for each method are in parentheses. Mother

Offspring

GM (0.75)

TB (0.24)

TR120

Chewy

0.97

0.69

Ellie

Phant

0.96

0.70

Spiral

Helix

0.96

0.76

Hook

Shmee

1.00

0.74

Scratchy

Itchy

0.96

0.56

Stripes

Jack

0.96

0.43

Wave

Swell

1.00

0.65

Glob

Flem

0.96

0.59

SN9

C3P0

0.97

0.68

Comet

Halley

0.96

0.66

SN4

R2D2

0.96

0.51

Network analyses were consistent with dendrogram plots using indices derived from the two minute sampling method. The close associations of mother – offspring pairs are all well represented, as well as the complete lack of association of G and Jack. There was also good separation of defined potential sub-groups within the population (Fig. 2.7).

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a Zebra Poxfin Granite G Tick-Tack Splash Seal Patio Dart Tiger Pie Coral Gerbil Bafta Frenzy Moby Chip Pooh Handy Eeyore Piglet Alaska Stripes Jack Scratchy Itchy Shmee Hook SN96 Paua Kringel Alysa W-Notch SN4 R2D2 SN9 C3P0 Upbang Gallatin Five Ripplefluke Glob Flem Phant Ellie Halley Comet PL TR120 Chewy Whitetip Knit DN63 BZ-Blackmum Thumper Number-1 Mus Mussel 2-Scallops Wave Swell Spiral Helix

b

SN4

0.20

0.30

0.40

0.50

0.60

0.70

0.80 R2D2 SN9 C3P0

Association Index

s

Figure 2.6: (a) Cluster analysis using average-linkage method for the Doubtful Sound bottlenose dolphin population (n = 63), using the HWI two-minute sampling period. Black dashes indicate individuals always seen together. Colours represent the three different sub-groups. Mothers and their offspring are indicated by red connecting lines / boxes. (b) Sub-groups were defined by the peak in the modularity coefficient.

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Poxfin G Granite Zebra

Tiger Moby Pooh

Splash Chip

Handy

Coral Seal

Eeyore

Piglet

Patio

Pie Tick-Tack

Dart

Frenzy Gerbil Bafta Alaska SN96

Halley Comet Chewy Flem TR120 Glob Ellie Phant Gallatin PL

Paua Upbang Itchy

Spiral Helix

Scratchy Stripes

Shmee

Wave Five

SN9

Knit

Swell

Thumper Alysa

Ripplefluke Number-1

Kringel

Whitetip R2D2

Jack

W-Notch

2-Scallops

Hook C3P0

Mussel

Mus

DN63

BZ-Blackmum

SN4

Stress: 0.220

Figure 2.7: Social network of the Doubtful Sound bottlenose dolphin population (n = 63) using HWI based on a 2 minute sampling period. Circles represent females, squares represent males and diamonds represent individuals of unknown gender. Colours represent sub-groups defined by the peak in the modularity. Individuals are plotted using non-metric MDS. Mother – offspring groups are indicated with dashed lines. Stress: 0.220

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Comparisons of CVs calculated from bootstrapped SEs for each method indicate an increase in precision of the TB method compared to the GM method. CVs are not only less for the TB method but appear more stable than those produced by the GM method (Table 2.2). Table 2.2: CV results produced by the group membership method and the time-based method for a sub-sample of 20 randomly selected pairwise associations. Pairwise index

GM CV

TB CV

1

2.465

0.282

2

1.517

0.282

3

1.793

0.282

4

2.191

0.225

5

1.972

0.225

6

1.972

0.225

7

1.517

0.282

8

1.972

0.225

9

1.972

0.225

10

1.517

0.225

11

2.191

0.225

12

1.793

0.188

13

1.972

0.225

14

2.465

0.188

15

1.972

0.225

16

1.517

0.188

17

1.972

0.188

18

1.643

0.282

19

1.517

0.225

20

1.972

0.188

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DISCUSSION Comparison of cluster and network analyses from the two methods show broadly similar results; for example, associations expected to be naturally high (i.e. mothers and their offspring) are captured well in both methods. I believe the time-based method has several advantages however. The use of a time window rather than group membership allows more flexibility in when to consider individuals associated. If the time window is shorter than the period over which groups are relatively stable, the time-based method allows resolution of associations over shorter time scales and finer spatial scales. In Doubtful Sound, groups are often spatially long but only a few individuals wide. While satisfying a chain rule, the group may be spread over several hundred metres. In this situation the time-based method would resolve that individuals at the back of the group are associated with each other, but not necessarily with those at the front of the group. The group membership method would lump all group members together. Hence the time-based method helps avoid the “gambit of the group”, if deemed inappropriate for a given study population. It is better able to resolve differences in associations over relatively small spatial scales, short periods (e.g. between seasons), or before/after significant events (e.g. births), given that multiple instances of association between two individuals can be captured in one group sighting. The time-based method is also easy to apply in the field, requiring only that researchers take time-stamped photographs of identifiable individuals. Free software facilitates easy extraction of photographic metadata and, most importantly, the time-based method allows retrospective analysis of associations from any photo-ID dataset, whether or not the intention was to study social structure. Because time is used as a proxy for distance, it is important that the photographer’s behaviour does not violate the assumption that individuals photographed close together in time were also close together in space. There are potential problems with a lack of independence in the association data produced by the time-based method however. In the group membership method, an encounter with a group can produce only one observation of association between a pair of individuals. In the timebased method the number of potential observations of association depends on the time window chosen. At some point, these observations must lose independence. This presents a less serious problem if the data are used to describe a system rather than to test a particular hypothesis. Care must be taken when deciding on the timeframe to use; too small a timeframe and autocorrelation will occur, biasing results. By restricting data, allowing time for

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reorganization of individuals within groups, and choosing a timeframe that is at least this restricted time interval, independence of data points will be maximised. The inability to define strong sub-clusters within the Doubtful Sound population using both methods reflects the fluidity of members among potential sub-groups, and the general high level of associations among members of the population as a whole. The same number of clusters was also identified in an earlier study of this population (Lusseau et al. 2003) using the group membership method. Perhaps the population displays a more or less permanent three-clustered social organization when applying this method, though members of clusters may vary over time. This is the very nature of a fission-fusion society (Grellier et al. 2003) in which group membership is dynamic. The extra sub-group defined using the time-based method may represent the finer resolution provided by analysis at this scale. Again, modularity values for the cluster analyses were low, indicating relatively weak sub-groups (Newman, 2004), though higher than produced by the group membership method. These results support observations in the field, in which groups were generally large, containing the majority of the population, and spread over hundreds of metres. Individuals spent almost all of the time socializing and milling, with a high degree of mixing occurring over large areas. The dolphins in Doubtful Sound, like other temperate populations (Urian et al. 1996; Whitehead & Mann, 2000; Haase & Schneider, 2001; Wells & Scott, 2009) exhibit strong seasonal breeding. Births, and behaviours associated with mating (e.g. socialising and milling), generally occur between November and February (Haase & Schneider, 2001; Henderson, 2013). During summer periods, group sizes are generally large, with higher degrees of association among individuals than during winter months. Therefore these results, that there is a lack of strongly definable sub-groups, are expected. In comparison to other studied bottlenose dolphin populations, Doubtful Sound has extraordinarily strong bonds among individuals. Average HWI were high for the present study when using the group membership method; other populations range from 0.1 to 0.2 (Wells et al. 1987; Smolker et al. 1992; Bräger et al. 1994; Connor et al. 2000; QuintanaRizzo & Wells, 2001). Lusseau et al. (2003) noted a smaller average HWI for this population (0.47; SD: 0.04), though this is still relatively high compared to other studied bottlenose dolphin populations. Average group sizes were generally large given the population’s relatively small size when compared to other studied bottlenose populations (Connor et al. 2000). This inverse 30 | P a g e


relationship between population size and group size is common, in which small populations tend to have fewer groups comprised of more individuals compared to larger populations with groups of fewer individuals (Lusseau et al. 2003). The lack of a relationship between group size and average association rate suggests that associations are generally high among individuals regardless of how many are in a group. The extreme philopatric nature in such a dynamic environment, and isolation from other populations, appears to have promoted a high degree of sociality among all individuals of the Doubtful Sound bottlenose dolphin population. The large decrease observed in the overall distribution of association indices when using the time-based method is the result of the smaller scale over which associations are considered. Within a single group encounter, in which all individuals are considered associated using the GM method, there is a decreasing probability of two individuals being considered associated with decreasing time interval in which associations are considered. This being the case, care should be taken when comparing results produced by this and other methods. I am aware that direct comparisons of results between the two methods used in this study are not appropriate, though the relative relationships among individuals, and the overall structures produced, are comparable. The increase in precision when using the time-based method is also expected, as the sample size used to calculate pairwise indices is greater than in the group membership method. The increased data utilization by the time-based method, using multiple instances of association per individual per group, allows similar field effort to yield more information on the association patterns of individuals within a population, compared to methods based on group membership. The time-based approach also facilitates analyses with increased confidence of results of social patterns over relatively short periods, making it possible to investigate how social dynamics change seasonally, or after socially important events (e.g. births, deaths). In contrast, analyses based on the group membership method often require many months of data gathering, restricting inference on association patterns to generalisations over the long term. There is, of course, no free lunch. The time-based method poses potential problems in lack of independence in the association data. Thus careful consideration of data restriction and time-frame used is required in order to prevent biasing results. Defining the time window for defining associations may be somewhat arbitrary, but can be made more objective by using a window that maximizes c, reduces stress, or gives the best compromise of the two. Researchers need be aware, however, that these measures often come 31 | P a g e


with their own assumptions. For example, c-values from cluster analyses assume that the data are hierarchically organised. While hierarchical social structures are common in many populations of a number of taxa (Foster 1981; Appleby 1982; Wells et al. 1987; Smolker et al. 1992; Piper 1997; Jennings et al. 2006; Pelletier and Festa-Bianchet 2006; Tavares et al. 2016), it may not describe the social structures of all. Thus careful consideration must be given to the appropriateness of such metrics when deciding on the best sampling period to use in methods such as the proposed time-based. By using time as a proxy for distance, the general assumption that association is inversely related to distance between individuals holds as long as the photographer concentrates on nearby dolphins, and that individuals (as well as the research vessel) are travelling at a constant speed. These latter assumptions are deemed appropriate in Doubtful Sound as groups are generally encountered travelling at a constant rate, or are relatively stationary and engaged in social activity. No quantitative assessment was undertaken in the present study in order to validate these assumptions however. Future researchers that use the outlined time based method (or similar) are encouraged to validate such assumptions, especially in the study of populations in which group behaviours are less predictable and more dynamic over a given encounter than in the dolphins of Doubtful Sound. The present study shows that association patterns can be assessed using metadata of photos taken of distinctive individuals as a proxy for distance. Time is but one metric with which associations can be quantified; information readily captured by default by even the most basic of digital cameras. Other metrics could just as easily be used in the study of association patters, for example many low-cost cameras now utilize the Global Positioning System (GPS) in order to record the coordinates of the camera every time a picture is taken. Importantly, these methods are not restricted to cetacean species; they can be applied to any population in which individuals are uniquely identifiable via photography, and can be applied retrospectively, using data not specifically collected for the study of sociality.

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Chapter 3: Seasonal variation in rates of association

Chapter 3 Seasonal patterns of association in a population of bottlenose dolphins, Tursiops truncatus.

ABSTRACT Many species display seasonal variability within various aspects of their life-histories, often in response to their environments. Data on these seasonal patterns are important to help understand the overall dynamics of a population. For social species, the relationships among individuals could also be expected to display seasonal variation as benefits and costs of group living change through time. Association rates among individuals in a population of wild bottlenose dolphins inhabiting Doubtful Sound, New Zealand, were calculated over summer and winter periods for a number of years since 2005. The social metric eigenvector centrality, a measure of relative social importance within the population, was also calculated for each individual and assessed for each season within each year tested. For all years, except 2012, overall association rates were significantly higher during summer periods. Assessment of the top ten scoring individuals in centrality indicates the population is primarily female orientated. Mothers form “nursery groups”, likely to provide protection for calves from predatory sharks, as well as from agonistic conspecifics. This study demonstrated seasonal variation of association networks for the dolphins of Doubtful Sound; a female orientated population. Additionally, the position of a female within her social environment may influence her calf’s chances of survival to one year old.

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INTRODUCTION A central focus of behavioural ecology is furthering our understanding of the relationship between ecological factors and the life histories of populations (Boutin, 1990; Chapman et al. 1995). For social species these factors are also central in shaping a populations’s social organization (Eisenberg et al. 1972; Würsig & Würsig, 1979; Sterck & Steenbeek, 1997), which can be a driving factor in population dynamics. Cycles in the life-histories of many populations are often influenced by the seasonality of the environments they inhabit (Murton & Westwood, 1977; Wingfield & Kenagy, 1991), especially when resources are variable in space and time. Resource and risk distribution plays an important role in determining the social strategies and patterns in populations of many social species (Cezilly & Benhamouv, 1996; Geffen et al. 1996; Johnson et al. 2002). Sociality could therefore be expected to fluctuate in response to changing environments. Group living is a trade-off between various costs and benefits, the intensity of which is often correlated with group size. There are a number of reasons for animals to form groups, such as the detection and reduction of predation (Turner & Pitcher, 1986; Krakauer, 1995), increased detection and exploitation of resources (Tristram, 1859; Scheel & Packer, 1991; Galef & Giraldeau, 2001; Couzin et al. 2005), increased mating opportunities (Gowans et al. 2008), and potential for information exchange (Perrin & Lehmann, 2001). Group living, however, can also be directly and indirectly detrimental to the fitness of individuals. These negative effects may include an increased conspicuousness to predators (Botham et al. 2005), prey (Geist et al. 2005; Cooper et al. 2007), increased inter-individual competition (Sutherland, 1996), and an increase in parasitism and disease transmission (Alexander, 1974). Temporal differences in social patterns have been documented in a number of species (e.g. MacDonald, 1983; Wrangham et al. 1993; Creel & MacDonald, 1995; Miller et al. 2010; Vermeulen et al. 2015). Fission-fusion social structures, in which group membership is dynamic in space and time (Lusseau et al. 2003), allows a degree of adaptability in social organization in response to these fluctuating costs and benefits; an individual’s ecology influencing its social strategy. Prey is often highly dynamic both spatially and temporally (Horwood & Cushing, 1978; Steele, 1985). For species that rely on strategies requiring a degree of cooperation for resource detection and exploitation (e.g. Caraco, 1979; Shaw et al. 1995), the degree of group living could fluctuate in accordance to the availability and ease of finding and catching prey. This relationship is often very difficult to quantify however, as 34 | P a g e


prey abundances and distributions are often hard to monitor, especially within the marine environment. Gender-based variation in social strategies can occur within and between populations. In Shark Bay, Western Australia, and Sarasota Bay, Florida, females often organise themselves into groups of several to 13 individuals, with evidence that vulnerability to shark predation is driving these formations (Connor et al. 2000). While female grouping patterns are thought to be influenced primarily by environmental constraints, male strategies are often driven by mating success (Trivers, 1972; Wrangham, 1980a; Connor et al. 2000). In Shark Bay, 17-year alliances have been documented among closely related males in which they sequester mature females, repeatedly copulating with them (Connor et al. 1992; Krützen et al. 2004). Males may also remain relatively solitary from one another, with large single males of Sarasota Bay often observed primarily in areas most frequented by sexually receptive females (Wells et al. 1987). Doubtful Sound, New Zealand, is home to a small population (63 individuals) of bottlenose dolphins (Tursiops truncatus) living almost at the southern extreme of the species’ range (Bräger & Schneider, 1998; Lusseau et al. 2003). The population exhibits extreme philopatry, with little to no mixing occurring with the other two populations of Fiordland (Currey et al. 2007; Rowe et al. 2010). It is a population that exhibits a social structure characterised by unusually strong and long-lasting bonds among individuals; a response to the ecological constraints imposed by the environment (Lusseau et al. 2003). Unlike those in Shark Bay and Sarasota, associations are strong within and between sexes; no clear alliances or bandings occur (Lusseau et al. 2003). The population also displays strongly seasonal breeding (Haase & Schneider, 2001; Brough et al. 2016), with births generally occurring during a narrow window of time during summer (Haase & Schneider, 2001). This is not uncommon for cooltemperate species (Bronson, 1989; Urian et al. 1996), and is likely to be driven by changes in sea surface temperatures; the warmer waters of summer months imposing less thermal stress on new calves that have low tolerance thresholds (Brough et al. 2016). This study aimed to test the hypothesis that association among individuals of the Doubtful Sound bottlenose dolphin population vary seasonally; with some possible explanations suggested. This will allow further insight into the social patterning of this population, shedding light on the dynamics of the social structure as a whole; an important aspect of the life-histories of these highly social animals. 35 | P a g e


METHODS Data Collection Photo-identification data have been collected on a small population of bottlenose dolphin inhabiting Doubtful Sound since (Williams et al. 1993). Three monitoring trips per year collect data during summer (January – April), winter (May – August) and spring (September – December) seasons, with additional research trips occurring year round. This study used data from summer and winter seasons over 7 years with a similar distribution of field effort between seasons within the same year. Years without the full complement of monitoring trips were excluded (Table 3.1). For details of photo-identification protocols, see Williams et al. (1993) and Currey et al. (2009). Surveys were boat based and followed a systematic daily route in which the entire Doubtful/Thompson Sound complex could be surveyed in a single day, given favourable weather conditions (Beaufort 3 or less). Photographs were taken using Nikon DSLR cameras using 80-200mm f2.8 and 300mm f4 AF Nikkor lenses.

Table 3.1: Summary of survey effort for the summer and winter periods for the various years in Doubtful Sound. Year

Period

Survey days

Days dolphins encountered

Groups encountered

No. dolphins

2005

Summer

15

14

35

identified 57

Winter

23

21

63

57

Summer

29

26

74

62

Winter

15

13

40

57

Summer

11

10

23

58

Winter

6

6

14

57

Summer

7

5

7

61

Winter

6

4

7

57

Summer

11

8

20

60

Winter

7

7

19

56

Summer

5

5

7

66

Winter

6

4

5

62

Summer

19

15

34

63

Winter

18

13

24

62

2006

2010

2011

2012

2014

2015

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Data Analyses Pairwise association indices, in which individuals were considered associated if they were photographed within sequential two-minute sampling periods, were calculated using the programme SOCPROG V2.6 (Whitehead, 2009). This time-frame was determined in prior analyses in which stress values associated with non-metric multidimensional scaling (nmMDS), and cophenetic correlation coefficient values (c) associated with cluster analyses, were optimised (See Chapter 2). Two-minute sequential sampling timeframes began from the first photograph of an encountered group and continued until all photographs within an encounter had fallen within a sampling period. The half-weight association index (HWI) method was used to calculate indices. Although the time-based method for defining associations used in this study is novel, the HWI is a standard method used in other studies of associations (Quintana-Rizzo & Wells, 2001; Lusseau et al. 2003; Gero et al. 2005). For surfacing events in which more than one photograph of an individual was taken, only the first was considered in defining associations. Additionally, only one photograph per minute of every individual was considered in order to allow individuals to reorganize within a group, increasing independence of data points. The time-based method allows utilisation of almost every photograph taken during a trip, thus maximizing data efficiency. Potential differences in group sizes between seasons were assessed through Wilcoxon signedrank tests (Wilcoxon, 1945) for each year comparing summer and winter periods. This is a non-parametric statistical hypothesis test that does not assume a normal distribution. This was validated for each period of each year by performing Shapiro-Wilk normality tests (p < 0.05); as well as visually assessing histograms of distributions and Q-Q plots in the open access program R Studio (version 0.99.41; R Core Team, 2016). Average association indices were also compared between seasons for each year; 95% confidence intervals calculated and Wilcoxon signed-rank tests performed. The social metric eigenvector centrality (Newman, 2004) for each individual was calculated within SOCPROG (Whitehead, 2009) for summer and winter seasons of each year. This is a measure not only of the strength of associations for a given individual, but also the strength of those individuals the focal animal is connected with. Strength is defined as the sum of the association indices with all other individuals (Barrat et al. 2004). Centrality is given as the first eigenvector of the association matrix. For each individual a number is produced that describes its connectedness within the social network. To have a high eigenvector centrality 37 | P a g e


indicates the individual has either high strength (the sum of its direct associations to others) or that it is connected to others that display high strength. Results were left un-standardised as network sizes were similar between summer and winter periods within each year. Also the primary interest was in the relative position of individuals to each other for each metric, rather than comparing metric scores. For data collected in 2015, average-linkage cluster analyses of dendrograms (Romesburg, 1984) were performed within SOCPROG in order to visualize the social structure of the population and the presence of any sub-groups within networks per season. To assess the fit of the dendrograms to the data, cophenetic correlation coefficients (c) were calculated. Potential sub-groups within the population were assessed by calculating a modularity following the definition of Newman (2004). Network plots were also produced via nonmetric multidimensional scaling (MDS), as cluster analyses are hierarchical models that may not be appropriate in describing non-hierarchical data. MDS analyses were conducted in the programme UCINET 6 (v. 6.558, Borgatti et al. 2002) and visually represented in the programme Netdraw (Borgatti, 2002).

RESULTS Historical analysis The number of groups encountered and the average association indices were not significantly correlated (Pearson’s correlation coefficient p > 0.05). In most years, groups were larger in summer than in winter (Fig. 3.1), but this difference was statistically significant only in 2005 and 2015 (Wilcoxon signed rank W = 1578.5 & 712.5 respectively; p < 0.05). Average association indices were significantly different between seasons of the same year (table 3.2), with rates of association indices higher in summer in all years assessed, except in 2012 (Fig. 3.2). Average association rates were similar for males and females (Fig. 3.3).

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*

Group Size

*

S

W

2005

S

W

2006

S

W

S

2010

W

2011

S

W

S

2012

W

2014

S

W

2015

Figure 3.1: Box and whisker plots of group sizes for the bottlenose dolphins of Doubtful Sound during the summer (S) and winter (W) seasons between 2005 and 2015. Median, quartile values, and ranges are displayed, with box widths proportional to the square root of the sample sizes (n = 2005 S:35, W:63; 2006 S:74, W:40; 2010 S:14, W:14; 2011 S:7, W:7; 2012 S:20, W:19; 2014 S:7, W:5; 2015 S:34, W:24). * indicates statistically significant differences between seasons of a given year.

0.25 Summer

Average Association Index

0.20

Winter

0.15

0.10

0.05

0.00 2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

Figure 3.2: Average pairwise association indices among the bottlenose dolphins of Doubtful Sound, calculated during the summer and winter periods of the seven years analysed. Error bars are 95% confidence intervals.

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0.30

F to F M to M

Average Association Index

0.25

M to F

0.20

0.15

0.10

0.05

0.00 S W S W S W S W S W S W S W S W S W S W S W 2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

Figure 3.3: Comparison of average pairwise association indices among males only, females only, and between genders in summer (S) and winter (W). Error bars are 95% confidence intervals.

Table 3.2: Mean association indices (µ) among all individuals for summer and winter for each year tested. Test statistic W results are displayed for each of the Wilcoxon signed-rank tests between seasons. All years produced significant results (p > 0.05). Year

Season

µ

W

2005

Summer

0.1468

1822000

Winter

0.0888

Summer

0.0913

Winter

0.0712

Summer

0.1687

Winter

0.1574

Summer

0.1603

Winter

0.1278

Summer

0.1090

Winter

0.1709

Summer

0.1278

Winter

0.1023

Summer

0.2374

Winter

0.1434

2006

2010

2011

2012

2014

2015

7097800

1379700

1734500

940410

940410

2700200

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Eigenvector Centrality & Modularity During summer and winter, the majority of individuals with the highest centrality scores were female (table 3.3), except in 2012 and 2015. Additionally, all females that appear as one of the top ten scoring individuals in a given season, and also gave birth in that year, had their calf survive to one year of age (eleven mothers); except one calf born during the winter of 2011 (Homer, calf of Zig). Modularity values (a measure of how confident we can be in plotted dendrograms; Newman, 2004) from cluster analyses were generally higher during winter seasons than summer, except in 2012.

Table 3.3: Gender (male, female or unknown) of the ten individuals with the highest centrality scores during summer and winter, for each year of data analysed. Summer

Winter

Year

M

F

U

Year

M

F

U

2005

3

7

0

2005

4

5

1

2006

2

8

0

2006

2

6

2

2010

4

5

1

2010

2

6

2

2011

1

7

2

2011

3

7

0

2012

5

4

1

2012

2

8

0

2014

2

7

1

2014

3

6

1

2015

3

5

2

2015

5

4

1

2015 analysis Group size and average association index were not significantly correlated (Pearson’s correlation coefficients > 0.05) in 2015 during either summer or winter. No strongly identifiable sub-groups were produced in cluster analyses for the summer period, though four sub-groups were identified in which individuals spent more time together than on average (> population average of 0.15; modularity of approximately 0.085). There were no instances of complete association (1) and three instances of complete disassociation (0; Fig. 3.4). For the winter period, again no strong sub-groups could be identified, although there were four subgroups in which individuals spent more time together than on average (> population average of 0.09; modularity of approximately 0.27). No instances of complete association were 41 | P a g e


observed. There were 437 instances of complete disassociation (Fig. 3.5). Mothers and their offspring (< three years old; Henderson 2014) were closely associated with one another in both summer and winter, with network plots cross-validating dendrograms well (Fig. 3.6a and b).

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a

Zebra Poxfin Granite G Tick-Tack Splash Seal Patio Dart Tiger Pie Coral Gerbil Bafta Frenzy Moby Chip Pooh Handy Eeyore Piglet Alaska Stripes Jack Scratchy Itchy Shmee Hook SN96 Paua Kringel Alysa W-Notch SN4 R2D2 SN9 C3P0 Upbang Gallatin Five Ripplefluke Glob Flem Phant Ellie Halley Comet PL TR120 Chewy Whitetip Knit DN63 BZ-Blackmum Thumper Number-1 Mus Mussel 2-Scallops Wave Swell Spiral Helix

b

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Association index Figure 3.4: (a) Cluster analysis for the summer period of 2015 calculated using average-linkage method for the Doubtful Sound bottlenose dolphin population (n = 63). Indices were calculated using the HWI time-based method. Colours represent the different sub-groups. Mothers and their offspring are indicated by red boxes. (b) Sub-groups were defined by the peak in the modularity coefficient.

a

Whitetip Spiral Helix Wave Swell Itchy Scratchy Shmee Hook Five Zebra Thumper SN4 R2D2 Number-1 Mus DN63 Splash Patio Tiger Coral Seal Pie Phant Ellie PL Knit Gallatin Glob Flem Halley Comet Poxfin Granite G Bafta Tick-Tack Alysa Dart W-Notch Upbang BZ-Blackmum Ripplefluke Frenzy Alaska Mussel 2-Scallops Handy Gerbil SN96 SN9 Paua Pooh Piglet Eeyore Moby Chip C3P0 TR120 Chewy Stripes Jack

b

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7 0.7

0.8

Association index Figure 3.5: (a) Cluster analysis for the winter period of 2015 calculated using average-linkage method for the Doubtful Sound bottlenose dolphin population (n = 62). Indices

52 |(b) P aSubge were calculated using the HWI time-based method. Colours represent the different sub-groups. Mothers and their offspring are indicated by red connecting lines / boxes. groups were defined by the peak in the modularity coefficient.


a – Summer

Poxfin Granite Zebra

G

Tiger Moby

Splash

Pooh

Chip Piglet

Hand Eeyore y

Coral

Seal

Patio

Pie Tick-Tack

Dart

Frenzy Gerbil Bafta Alaska

SN96

Paua

Itchy Scratchy Stripes

Shmee Hook

Jack

Halley Mussel Mus DN63Comet W-Notch Chewy TR120 Flem Thumper Upbang Gl 2-Scallops Ellie Alysa Phant ob Gallatin Ripplefluke PL Spiral WaveFive Knit Number-1 Helix SN9 Swell Whitetip BZR2D2 C3P0 Blackmum SN4

Kringel

Stress: 0.220

b – Winter

Whitetip

Helix Spiral G

Stress: 0.190

Coral R2D2 Seal Number-1 Mus Patio Tiger SN4 Splash DN63Thumper Zebra Pie Ellie Glob Knit FlemPhant PL Halley Paua Gallatin Comet Ripplefluke Frenzy SN9 Upbang Handy C3P0 W-Notch Gerbil SN96 2-Scallops Dart BZ-Blackmum Piglet Mussel Eeyore Stripes Tick -Tack Pooh Poxfin Bafta MobyChip GraniteAlaskaTR120Jack Alysa Chewy Swell Wave Hook Shmee Itchy Scratchy

Five

Figure 3.6: Social networks for summer (a) and winter (b) periods of 2015 for the Doubtful Sound bottlenose dolphin population (n = 63 (S) & 62 (W)). Circles are females, squares are males and diamonds are individuals of unknown gender. Colours represent sub-groups defined by the peak in the modularity. Mother-offspring groups are indicated by the dashed lines. Note: The strength of associations between individuals defined by thickness of connecting lines have been removed for clarity of the plot. Individuals are plotted using non-metric MDS.

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DISCUSSION This study showed seasonal variation in the association rates of the bottlenose dolphins of Doubtful Sound, with larger groups and stronger associations observed during summer. As in many temperate dolphin populations (Bronson, 1989; Urian et al. 1996), breeding in Doubtful Sound is highly seasonal; the majority of births occurring between December to April (Haase & Schneider, 2001; Brough et al. 2016). Reproduction often shows high seasonality, especially at higher latitudes (Murton & Westwood, 1977; Urian et al. 1996; Whitehead & Mann, 2000; Haase & Schneider, 2001; Stutchbury & Morton, 2001; Wells & Scott, 2009). With a 12 month gestation period (O’Brien & Robeck, 2012), mating and associated behaviours occur during the same period a year prior to birth. The higher degree of association among individuals, as well as the observed higher rate of social behaviours during summer months (e.g. tail slapping, mirroring, head-butting and other aerial behaviours) are therefore likely related to mating. The marine environment imposes constraints on animals that are not found to the same degree, or at all, in terrestrial environments. For example, air-breathing species, such as dolphins, need to routinely surface to breathe. Additionally, with a lack of obvious refuges in the marine environment, grouping together may be the best anti-predator strategy available to these animals (Norris & Dohl, 1980a). By grouping together, animals can increase their antipredator vigilance through a number of mechanisms. Galton noted over 130 years ago that many eyes and ears are able to detect predators sooner, and that a warning will sooner be sounded to others within the group (Galton, 1883). If an attack eventuates, mechanisms are present that reduce the risk of individuals from being predated upon, such as dilution effects (Bertram, 1978), or predator mobbing (Dominey, 1983; Arnold, 2000; Pitman et al. 2016). For larger predatory species, like bottlenose dolphins, the risk of predation may not be as substantial as for smaller species (Beauchamp, 2014). Therefore, while predation risk will no doubt play some role in determining the social strategies of the dolphins in Doubtful Sound, ecological factors, such as the availability of resources, are likely more important. Foraging in groups reduces the time needed to detect such resources (Tristram, 1859; Thorpe, 1956; Pitcher et al. 1982; Galef & Giraldeau, 2001). It is a strategy that has developed independently multiple times in many species; implying that, in an evolutionary context, the benefits often outweigh the costs.

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For the bottlenose dolphins of Doubtful Sound, defined sub-groups are weaker during summer, represented by lower modularity compared to winter months. This suggests a greater degree of mixing among all individuals of the population, a result of the increased social activity associated with breeding and potentially relaxed ecological constraints, during summers. During winter individuals spent more time in smaller and more stable groups. Various studies of primates that live in seasonally variable environments often show predictable responses to changing ecological conditions through time. When resources are scarce, groups become smaller in order to reduce competition among group members (Caldecott, 1986; Doran; 1996). In environments known to be relatively unproductive, information exchange is often important in maximizing the detection and exploitation of finite and patchy resources (Dall et al. 2005). The Information Centre Foraging model for breeding colonies of seabirds predicts a greater degree of philopatry and reciprocal interactions among individuals as ecological constraints increase (Allchin, 1992; Buckley, 1997; Barta & Giraldeau, 2001; Perrin & Lehmann, 2001). Fiordland is highly variable in its productivity, both in space and time (Peake et al. 2001; Miller et al. 2011). The energy requirements of the dolphins of Fiordland are also likely greater compared to other populations that live in lower, warmer, latitudes, or in more predictable environments. A higher degree of cooperation is therefore likely necessary in order for the dolphins of Fiordland not only to meet their own high energy demands, but also aid in the acquisition of resources for kin. Kin-selection is an important factor to consider in affiliative behaviour (Hamilton, 1964a, b). When group partners are closely related, individuals may gain inclusive, as well as direct, fitness benefits (Grafen, 1979; Hines & Maynard Smith, 1979). The influence of inclusive fitness on affiliative behaviour has been proposed for a wide range of taxa; including lions (Packer & Pusey, 1982; Packer, 1986; Pusey & Packer, 1987), chimpanzees (Busse, 1978), social spiders (Wickler, 1973; Roeloff & Reichert, 1988), eusocial insects (Reeve et al. 1990; Bourke, 1997), primates (Clutton-Brock, 2002; Perry et al. 2008; Langergraber et al. 2009) and other cetacean species (Baird & Whitehead, 2000; Krützen et al. 2003; Gero et al. 2009). Association among female kin in many mammalian species is thought to be the basis of the social system (Clutton-Brock et al. 1982; Packer, 1986; Gouzoules & Gouzoules, 1987). Given the small size of the Doubtful Sound bottlenose dolphin population (62 individuals), and that very few females contribute to recruitment via births (Henderson et al. 2014), there is likely a high degree of relatedness among individuals. This may help explain the lack of 47 | P a g e


strongly definable sub-groups observed in most seasons and years (modularity < 0.3; Newman, 2004); kin-selection perhaps playing a large role in driving the high degrees of association among most members of the population. The number of females with high scores for eigenvector centrality suggests a predominantly female-orientated social structure. The high number surviving calves to one year of age for those born during a year in which the mother scored highly suggests how central she is in the social network plays an important role in her calf’s survival. In many mammalian populations females often have stronger associations to one another than to males. While the normal benefits of forming groups may still be gained (e.g. increased access to resources, reduced risk of predation), additional benefits of females forming groups may include group infant care and protection from sexual coercion by males (Wrangham, 1980b; Wrangham & Rubenstein, 1986; Smuts & Smuts, 1993). For animals that are long-lived and slow to reproduce, the protection of young is especially important, as the cost to parents is generally greater per offspring compared to species with more rapid reproductive cycles, or those that can raise multiple offspring. The protection of young has been proposed to be a major influence on the social systems of a number of species (e.g. silverback jackals, Canis mesomelas, Moehlman, 1986; sperm whales, Physeter macrocephalus, Whitehead, 1996). The present study suggests that females with calves have stronger associations with one another than to those of the rest of the population. It is possible that mothers attempt to reduce calf mortality by banding together in “nursery groups” (Würsig & Würsig, 1980; Pryor & Shallenberger, 1991; Wells, 1991); a similar strategy is observed in a population of dusky dolphins (Lagenorhyncus obscurus) off Kaikoura, New Zealand (Weir et al. 2008). While infanticide has not been observed directly in bottlenose dolphin populations, there is compelling evidence that it does occur (e.g. Ross & Wilson, 1996; Patterson et al. 1998). Nursery groups may also provide protection to calves while individual mothers go off to forage (Mann & Smuts, 1998; Mann & Watson-Capps, 2005), providing ongoing protection from both predatory sharks (Mann et al. 2000) as well as agonistic males (Würsig & Würsig, 1980). Modelling of various animal social networks (including bottlenose dolphins) suggests the emergence of social structure can often be explained by social inheritance (Ilany & Akçay, 2016). Under this framework, the relative social importance of calves could be expected to relate to that of their mother; with any advantages this may imply conferred to the calf. This 48 | P a g e


may explain the apparent high survival rates of calves born to mothers who scored highly in centrality. The relationship between reproductive success and individual sociality (especially relating to social inheritance) are rarely explored, and therefore warrants further investigation (chapter 4). The year 2012 did not show the social patterns observed in other years. Overall group sizes were larger and association rates greater during winter than summer. It is also less female oriented, and had stronger sub-groups during the summer (thus less mixing) than in winter. If associations in Doubtful Sound are primarily in response to conditions within the environment, the change in 2012 may be related to the moderate La Niña experienced in 2011 (average ENSO index of 1.4; Ministry for the Environment website, accessed 24/08/2016). The mechanisms driving this change in social patterning, however, remain unclear. The year 2015 saw similar, though exaggerated, patterns of social organizations compared to previous years (except 2012). No births occurred in 2015; though 2016 saw six new calves born. The greater overall degree of association rates during the summer of 2015 therefore likely indicates a season of high breeding activity. In summary, this study showed that patterns of association changed seasonally in most years, with summer periods generally characterised by larger groups and higher rates of association among individuals. I propose that, while increased anti-predator vigilance will likely play some role in the high sociality observed among individuals, it is likely that ecological constraints (i.e. food resources) in a highly dynamic environment, is a main driver. Living in Doubtful Sound promotes a highly stable and social system, as well as a high degree of philopatry. Additionally, given the small size of the population, and the extreme heterogeneity in reproductive success among females, kin-selection may also be important. However, the lack of data on prey abundances and distributions, as well as genetic data to describe the relatedness of individuals, mean that these hypotheses are untested. These knowledge gaps provide avenues of future research into drivers of the unusually strong social structure of the bottlenose dolphins of Doubtful Sound. To my knowledge this is the first study of seasonal variation in association rates in cetaceans, an important endeavour if the drivers of population dynamics in social species are to be better understood.

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Chapter 4: Factors affecting female reproductive success

Chapter 4 Influential factors upon heterogeneity in female reproductive success

ABSTRACT The reproductive rate is one of the key vital rates for population growth, especially in closed populations, and is therefore critical to understand when assessing population viability. Reproductive success is often measured by whether the offspring of an individual survives to a given age, and can be influenced by many factors. For socially complex species, social position can have a profound impact on how successful an individual is during various stages of its life history, including while raising offspring. This was tested in a small, isolated population of bottlenose dolphins that inhabit Doubtful Sound, New Zealand, using an information theoretic approach. General linear mixed models were produced in which the relative importance of birth timing, maternal experience, and position within the populations’ social network (eigenvector centrality), were assessed in relation to her calf’s survival to 1 year old. Social position and experience were not significant predictors of calf survival to 1 in model averaging procedures, though the timing of birth was; those born during the period of February to April had a greater chance of survival than those born outside this period. This study provided further evidence that birth timing is an important predictor of calf survival, results produced by previous studies; though a shift to later months in the breeding season seems to be occurring. Although birth timing was identified as a potential important factor, R2 values indicated that other unidentified factors appear to play an important role in a calf’s survival, and thus a female’s reproductive success.

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INTRODUCTION Assessing the relative importance of factors that influence the reproductive success of individuals is essential for understanding the drivers of a population’s dynamics. This is particularly important for small populations in which the deviations of demographic factors (e.g. sex ratio, age structure, reproductive rate) from the mean are accentuated (Goodman, 1987; Lucy, 1993). Interactions among these stochastic factors are often complex and difficult to tease apart, and play a role in driving the high risk of extinction of several cetacean populations (e.g. Yangtze finless porpoise, Neophocaena asiaeorientalis, Mei et al. 2012; Irrawaddy dolphins, Orcaella brevirostris, Beasley et al. 2012; Amazon river dolphins, Inia geoffrensis, Huang et al. 2012;), as well as the actual extinction of others (e.g. Yangtze River dolphin, Lipotes vexillifer, Turvey et al. 2007). Quantifying these drivers will aid in predicting the trajectories of populations, allowing managers to develop and adopt management strategies that will promote population persistence. One of the most critical factors driving a population’s viability is the reproductive rate (Andrén, 1990, Fox & Kendall, 2002, Melbourne & Hastings, 2008). This varies among members of a population, influencing the degree of demographic stochasticity. Factors influencing the reproductive success of individuals can include physiology and morphology (e.g. larger individuals; Pomeroy et al. 1999), ecology (e.g. a greater availability of resources; Hildebrand et al. 1999), behaviour (e.g. Mann et al. 2000) and sociality (e.g. Côte & FestaBianchet, 2001; Stanton & Mann, 2012). Though many species live in groups, only a few develop complex relationships characterised by features such as flexible group membership, alliance formation and long-term associations (Lusseau, 2003). Species with complex social systems generally have large, metabolically expensive, brains (Dunbar & Schultz, 2007; Lehmann & Dunbar, 2009). These species also tend to be long-lived and slow to reproduce (Charnov & Berrigan, 1993; Connor et al. 1999). For complex social systems to evolve, the benefits presumably exceed the costs. Recent studies have linked dominance and alliance formation to increased reproductive success of adult males (e.g. primates, Wroblewski et al. 2009, Schülke et al. 2010; dolphins, Krützen et al. 2004), and persistent social bonds with increased longevity in adult females and increased survival of their offspring (e.g. baboons, Silk et al. 2003, 2009, 2010; horses, Cameron et al. 2009; rock hyraxes, Barocas et al. 2011). While there is a growing body of evidence that suggests a connection between adult social bonds and fitness (e.g. Uchino, 2006; Holt-Lunstad et al. 2010), the possibility that early 51 | P a g e


social environments can affect fitness remains relatively unexplored (for an exception see Gibson & Mann, 2008). Juveniles often remain highly associated with their mothers in socially complex species and those with lengthy development (Stanton & Mann, 2012). While still under the protection of their mothers, calves are able to develop the skills needed to negotiate their own social environments once weaned (Pagel & Harvey, 1993; Joffe, 1997). The mother’s social interactions are therefore likely to influence those of their young early in life; a time when social development is critical. Older females are generally thought to be better able to provide maternal care or protect their calves than younger mothers (Reiter et al. 1981; Lunn et al. 1994). Older, more experienced, individuals may also maintain a higher social rank (Thouless & Guinness, 1986; FestaBianchet, 1991; Locati & Lovari, 1991), providing increased exposure to better mating opportunities (Côté & Festa-Bianchet, 2001). In species in which males defend mates, high social rank often confers increased access to females (LeBoeuf, 1974; Clutton-Brock et al. 1982); with social rank among females having also been shown to correlate with reproductive success in various species (Clutton-Brock et al. 1984; Cassinello & Alados, 1996; Pusey et al. 1997). Strong birth seasonality has been described in many cetacean populations (Mann et al. 2000; Thayer et al. 2003), with suggestions that the timing of birth can play a large role in determining the survival of a calf and thus the reproductive success of the mother (Henderson et al. 2014; Fruet et al. 2015). For bottlenose dolphins, birth periods range from year round (Félix, 1994; Urian et al. 1996), to highly seasonal (Wells et al. 1987; Urian et al. 1996; Thayer et al. 2003; Kogi et al. 2004; Fortuna, 2007). Factors identified as important drivers of birth seasonality include prey availability (Mann et al. 2000), predation risk (Mann & Watson-Capps, 2005; Fearnbach et al. 2011) and the thermal limitations of smaller, younger individuals (Urian et al. 1996; Mann et al. 2000; Haase & Schneider, 2001). Strong birth seasonality is most commonly found in temperate regions where births usually coincide with warmer water temperatures (Wilson et al. 1997; Haase & Schneider, 2001; Thayer et al. 2003). Studies of reproductive biology in wild dolphin populations have focused primarily on birth seasonality (Urian et al. 1996; Thayer et al. 2003), inter-calf interval (Mann et al. 2000; Henderson et al. 2013) and reproductive rates (Mann et al. 2000; Henderson et al. 2014). Studies of the relationships between early social conditions of calves and their survival, 52 | P a g e


however, are limited (for exceptions see Gibson & Mann, 2008; Stanton & Mann, 2012). Bottlenose dolphins are an excellent model for assessing the influence of sociality on reproductive success, as, like humans and chimpanzees, they develop complex fission-fusion societies in which group composition is dynamic over time (Connor et al. 2000). The bottlenose dolphin population of Doubtful Sound is classified as Critically Endangered (Currey et al. 2009). The population has experienced declines in recent years (Currey et al. 2007), attributed to decreases in calf survival rates from 0.86 (95% CI: 0.68-0.95) prior to 2002 to 0.38 (95% CI: 0.21-0.58) for the period 2002 to 2007. Previous studies have demonstrated strong heterogeneity in reproductive success among females in this population (Henderson et al. 2014). For example, as of 2011, the six most successful breeding females produced 20 calves, 19 of which survived to one year old, and 14 to three years old. The least successful seven females produced a similar number of calves (21), only eight of which survived to one, and none to three years old (Henderson et al. 2014). In Fiordland, New Zealand, timing of birth is an important factor in calf survival. Those born in January, just prior to peaks in surface water temperature, appear to have a higher chance of surviving (Henderson et al. 2014, Brough et al. 2016). Calves are more susceptible to thermal stresses than adults, due to reduced blubber thickness and a greater surface area to volume ratio (Yeates & Howser, 2008). With the Doubtful Sound population being almost at the southern extreme of the species’ range, individuals are faced with far cooler temperatures than their lower latitude counterparts (Haase & Schneider, 2001). Being born during the short window of relatively warm water temperatures therefore appears to increase a calf’s chances of survival. The majority of insights into dynamics of reproduction in bottlenose dolphins are gleaned from captive studies and stranding events (Robeck et al. 1994; Urian et al. 1999). It is likely that data on survival and reproduction from these situations are biased, necessitating study of wild, healthy populations. For the dolphins in Doubtful Sound, the effect of birth timing on calf survival has been demonstrated, though the influence of sociality has yet to be investigated. Perhaps mothers learn about optimal timing for birth, either through their own experiences, or from being part of a social network of successful mothers. This study aimed to investigate demographic stochasticity by assessing the contribution of a range of measurable factors to calf survival in a small population of bottlenose dolphins. For each mother, eigenvector centrality, a social metric which describes how central to a social 53 | P a g e


network she is, was considered as a potential explanatory variable. Other factors considered included the mother’s reproductive experience and timing of birth. This was undertaken using an information theoretic approach in which calf survival to 1 year old was examined for each of the reproductively active females present from 2004 to 2014. Understanding the relative influence these various factors have on calf survival will help identify the drivers of population trends in Doubtful Sound. Additionally, these factors may be important for other small and endangered populations, especially those with similar fission-fusion social systems.

METHODS Study Site and Data Collection Photo-identification data have been collected from the population of bottlenose dolphins inhabiting Doubtful Sound as part of long-term monitoring and research efforts since 1990 (Williams et al. 1993). The present study included 220 survey days from 2004 to 2014 on which dolphins were encountered. Surveys were conducted from 4.8-5m aluminium boats powered by 50-70hp 4 stroke outboard engines. A systematic daily route was followed in which the entire Doubtful/Thompson Sound complex could be surveyed in a single day, given favourable weather conditions (Beaufort < 4). Photographs were taken using Nikon SLR and DSLR cameras using 80-200mm f2.8 and 300mm f4 AF Nikkor lenses. Protocols are described in detail in Williams et al. (1993) and Currey et al. (2009).

Reproductive Data Reproductive histories for all females in the Doubtful Sound population are known from 1994 to present; this study focused on reproductive data from 2004 onwards because the methods used to calculate association rates require time-stamped digital photographs of individuals. Digital photography was not adopted into the monitoring of this population until late 2003. High intensity of monitoring over months in which mothers usually give birth (September to April), allowed identification of birth month for most calves. If birth month was not known, it was estimated based on body condition and apparent stage of development at first sighting of a calf. Due to the natural high dependency of calves on their mothers prior to weaning, the female seen in close association (10 encounters or more) with a particular calf was assumed to be its mother. Though it is believed some expansion in home-range beyond Doubtful 54 | P a g e


Sound has occurred in recent years, the population is considered closed to immigration and emigration. Individuals within this population have very high re-sighting rates, with each typically sighted multiple times every trip (Henderson et al. 2013). Thus, if a mother was consistently re-sighted (10 encounters or more) without her most recent calf, that calf was assumed to have died. The reproductive histories of females were used to assign a birth month and fate for each calf (whether or not it survived to 1 year old), along with the identity and previous reproductive experience of the mother.

Social Networks Using the programme SOCPROG (version 2.5; Whitehead, 2009), social networks were produced for each mother over the 12 month period following each birth. A matrix of halfweighted pairwise association indices among all members of the population was created, in which two individuals were defined as associated if observed together within a given sampling period. Sampling periods began from the first photograph taken in a group encounter and blocked, one after the other, until the final photograph of the group encounter had been included in a sampling window. A sampling period of two minutes was considered the most appropriate based on results from Chapter 2. Associations were defined using the time-based method, rather than the commonly used group membership method, as variation in rates of association among individuals within groups is likely. The time-based method also maximizes the potential number of photos available for analysis, as multiple sampling periods per group encounter are used. This helps to offset the effects of years in which few groups were encountered, as fewer group encounters are required to obtain precise estimates of association indices. There were 45,770 independent and usable photographs available to calculate pairwise association indices among individuals. Five social metrics were calculated for each individual from their social networks after a birth: strength, eigenvector centrality, reach, clustering coefficient and affinity. Strength is the sum of all associations to an individual; eigenvector centrality is not only the strength of directly connected individuals but the strengths of those individuals also; reach is a measure of indirect connectedness; clustering coefficient is a measure of how connected an individuals’ associates are to one another; and affinity is a measure of the strength of an individuals’ associates weighted by the association index between them (see Whitehead, 2009, for detailed descriptions). Network metrics were all significantly correlated with each 55 | P a g e


other (p < 0.05). Including correlated variables can often lead to overly precise parameter estimates, and therefore lead to spurious conclusions in significance testing. The social metric eigenvector centrality (EC) was chosen as the single metric to use in further modelling procedures as it incorporates the other metric Strength and provides an interpretable measure of an individual’s position within the social network. This was calculated for each mother from their social network following the definition of Newman (2004). EC is determined by taking the appropriate element of the first eigenvector of the association matrix. An individual with high eigenvector centrality is considered to have relatively high importance within the social network; being well connected to individuals that are also well connected. I assumed that association rates among mothers did not change significantly during the one year period over which they were calculated, whether or not her calf survived.

Birth period In the Doubtful Sound population, calves born in January have a higher survival rate compared to those born in months outside of January (Henderson et al. 2014). Rates for calves born outside January show little variation among months (Henderson, 2013). Birth period data were therefore classified as a three levelled categorical variable (BP) based on whether the birth occurred before January (October, November or December), during January, or after (February, March or April) in a given reproductive season. No calves were observed to be born from May to September.

Mother experience Experience for each mother (Exp) at a given birth was coded as the number of births, regardless of whether the calf survived or not, prior to the focal birth. Preliminary analyses indicated a high correlation between the mother’s age and experience, and a previous study found that the mother’s age was not a significant predictor of calf survival (Brough et al. 2016). Therefore mother’s age was not included as a variable in the present study.

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Modelling Most calf mortalities occur within the first year, usually within the first month (Henderson et al. 2014). An additional increase in mortality occurs around three years old, thought to be associated with weaning (Henderson et al. 2014). Results from Gibson & Mann (2008) suggest that the first year of life is important in gaining social experience. Modelling was therefore restricted to assessing factors which may affect a calf’s survival to one year old. A modelling framework was used to investigate the effect of the explanatory variables on calf survival. The response variable was binary; coded as a “1” if the calf survived to 1 year old, or a “0” if it died. To enable comparison of networks of different size, eigenvector centrality was normalised based on the maximum value possible within that network (Stanton & Mann, 2012). Eigenvector centrality (EC), as well as birth period (BP) and mother experience (Exp), served as fixed explanatory variables in a logistic generalised linear mixed-effects model (GLMM; Bolker et al. 2009; Grueber et al. 2011). This modelling framework allows for the combination of fixed and random factors, as well as the use of continuous, categorical and binary data (Burnham & Anderson, 2002). Models were developed in the programme R Studio (version 0.99.491; The R Foundation) using the package lme4 (version 1.1-5; Bates et al. 2014). The glmer function of this package fits GLMMs by estimating model parameters via maximum likelihood using Laplace approximation (Bolker et al. 2009; Zuur et al. 2009). In order to allow for autocorrelation, the identity of the mother at each calving event was included as a random factor. Data were standardised using the centralizing mean method in the R package arm (version 1.6-10; Gelman & Su, 2003) in order to provide a more interpretable model in which one unit difference is the same across all variables, while not affecting statistical significance. The goodness-of-fit of models was assessed by calculating R2 values which describe the amount of variance explained. Though rarely presented, R2 is a very useful summary index of the fit of models as it is unit-less, allowing an objective evaluation of models across studies (Nakagawa & Schielzeth, 2013). Two values are produced for each model, marginal R2 (variance explained by fixed effects only) and conditional (variance explained by the complete model, including random factors). Values were calculated for each model using the sem.model.fits() function within the R package piecewiseSEM (Lefcheck, 2015). Correlation among explanatory variables was assessed via Pearson’s correlation coefficients, of which none were significant (p > 0.05). Multicollinearity was also assessed using variance 57 | P a g e


inflation factors (VIFs), with VIFs > 10 typically considered to indicate severe collinearity (Quinn & Keough, 2002). VIFs in the final model ranged from 2.16 to 4.31. The presence of convergence, over/under-dispersion and complete/quasi-complete separation of data were assessed independently using the checks performed by the lme4 package, with no occurrences. Mean monthly sea surface temperatures at birth were recorded from oceanographic moorings and were originally included in modelling procedures. This factor was later discarded however due to high correlation with birth period. Birth period was favoured over monthly temperature because the model including temperature yielded convergence warnings (likely caused by limited sample size).

Model Averaging An advantage of the information-theoretic approach is that the relative importance and accuracy of parameter estimates can be assessed through model averaging (Johnson and Olmand, 2004; Bolker et al. 2009). Instead of relying only on estimates from the top model, coefficients can be averaged across all models contributing some weight, providing more realistic parameter estimates (Burnham & Anderson, 2002). A suite of models was constructed with all possible combinations of explanatory variables, and relative performance was assessed via minimum AIC (Akaike, 1973). Models were selected if they contributed at least 1% in weight; averaging was performed within the R package Mumin (Barton, 2015). A summary of parameter estimates across models was produced, including an estimate of standard error. The degree that each predictor contributes to calf survival (the effect size) is indicated by the estimated coefficient, allowing predictor variables to be ranked. A confidence interval (CI) was estimated for each coefficient (Grueber et al. 2011; Nakagawa & Freckleton, 2011):

̂ 𝜃̂) 𝜃̂ ± 𝑧𝑑𝑓,𝛼 (𝑆𝑒 2

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Where 𝜃̂ is the averaged parameter estimate, Z is a test statistic with associated degrees of ̂ 𝜃̂) is the estimate of standard error for freedom (df) and level of significance (0.95), and (𝑆𝐸 the averaged parameter. The effect of the parameter is considered significant if the CI does not include 0 (Grueber et al. 2011; Nakagawa & Freckleton, 2011).

RESULTS From 2004 to 2014 there were 25 reproductively active female bottlenose dolphins in Doubtful Sound, 18 of which were still alive as of December 2014. Fifty four births occurred during the period of this study; the mother was not known for three of these and thus they were excluded from this analysis. This produced an effective sample size of 51 births, with 37 of the calves surviving to one year old. The mother’s experience ranged from 0 to 5 calves before the most recent birth. The most parsimonious model (indicated by lowest AICc and the highest weight) included the mother’s experience as the lone predictor. The second best model was the null model, indicating that who the mother is has a strong influence on whether the calf survives to 1. Eigenvector centrality first appears with mother experience with a weight of 0.09 (Table 4.1).

Table 4.1: Summary of the top models predicting calf survival to 1 year old. Model

AICc

ΔAICc

Weight

Marginal R2

Conditional R2

Exp

55.25

0.00

0.28

0.019

0.977

(Null)

55.92

0.67

0.20

0.000

0.961

BP

56.44

1.19

0.16

0.061

0.983

BP + Exp

56.88

1.63

0.13

0.048

0.984

EC + Exp

57.61

2.36

0.09

0.019

0.977

EC

58.18

2.93

0.07

0.000

0.961

BP + EC

58.89

3.64

0.05

0.060

0.983

BP + EC + Exp

59.46

4.21

0.03

0.048

0.984

There was little difference in weights of the four top scoring models, which are all substantially supported based upon ΔAICc scores of less than 2 (Burnham and Anderson 2002). There was considerably less support for eigenvector centrality alone (ΔAICc = 2.93). 59 | P a g e


Given there was little difference between the weights of the top scoring models, and that weights were < 0.9, model averaging was performed across all models selected to produce parameter estimates. Marginal R2 values indicate that the fixed terms accounted for little of the variance explained in all models (all < 0.1). Conditional R2 values suggest that the random term, mother ID, accounted for the majority of the variation explained in all models (all close to 1). As indicated by 95% confidence intervals that did not overlap with 0, month of birth was a significant predictor of calf survival to 1 year old (Fig. 4.1). A positive coefficient of 7.76 indicated that calves born after January (Feb – Apr) are more likely to survive than calves born in January or before (Oct – Dec).

Averaged coefficient value

15

10

5

0

-5

-10

Figure 4.1: Model averaged estimates of the predictor variables and their contribution to calf survival to 1 year. Averaged coefficients reflect magnitude of effects. Error bars are ± 95% confidence intervals using unconditional standard errors. * indicates the level of the categorical month factor used as the reference level with which all other levels of the factor month are compared.

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DISCUSSION Mother experience was identified as the lone fixed predictor in the top model. With age usually comes experience; older mothers having generally given birth to more offspring. With experience can come the knowledge of when parental care is most necessary to increase a calf’s chances of survival; when the probability of calf death is greatest (e.g. Green, 1990, 1993; Fairbanks, 1996). This is known as the targeted reproductive effort (TRE) hypothesis and predicts an increase in reproductive success of mothers, with similar or less effort, in subsequent offspring. This in turn may serve to decrease the time between births (the intercalf interval), as greater experience in when to target investment may lead to a net decrease in effort for each calf overall (e.g. Cameron et al. 2000). In Doubtful Sound the frequency of births is influenced by the fate of the previous calf (Henderson et al. 2014). For mothers who have lost a calf, the next birth generally occurs sooner than would be expected if the calf had survived. This is similar to what is observed in an oceanic population of bottlenose dolphins inhabiting Shark Bay, Australia. If calf loss occurs early, females are able to resume reproductive cycling at a time that will allow a subsequent calf to be born within season the following year (Mann et al. 2000). Though mother experience was the lone predictor in the top model, model averaging suggested that calf survival was best explained by the timing of birth; those born after January have a higher chance of survival. The importance of the timing of birth for bottlenose dolphin calves in Doubtful Sound was first identified by Henderson et al. (2014); 53% of births by the six most successful mothers occurred during January. Similarly, Brough et al. (2016) found that calves born between January and April were significantly more likely to survive to 1 year of age. The present study also provided supporting evidence of the importance of when a calf is born, with those born during the months of February to April having a greater chance of reaching 1 year of age. In warm temperate and tropical areas, birthing is generally year round (Scott et al. 1990; Urian et al. 1996). Broadly, births become more strongly seasonal with increasing latitude (Mann et al. 2000; Haase & Schneider, 2001). The birth seasonality observed in the bottlenose dolphins of Doubtful Sound is similar to others found in cool temperate environments (Wells et al. 1987; Wilson, 1995; Mann et at. 2000). Doubtful Sound is located almost at the southern range of known resident bottlenose dolphin populations (Bräger & Schneider, 1998; Brough et al. 2015). The area shows large seasonal variation in surface 61 | P a g e


water temperatures (Gibbs et al. 2000). A lack of birthing events during winter months (May – September) suggests that water temperatures during this period are too low to allow calves to survive. During this period, calm, cold weather can cause a drastic drop in sea-surface temperatures (Schneider, 1999), often causing inner portions of the fiords to freeze over (pers. obs.). Water temperatures may also decline due to storm events, a common occurrence during winter months in Doubtful Sound (Gibbs, 2001). Freshwater input may be exacerbated in Doubtful Sound by the presence of a hydroelectric power scheme which came online in 1969, tripling freshwater input into the fiords (Gibbs et al. 2000; Gibbs, 2001). A low salinity layer (LSL) forms within the inner reaches that can reach up to 10 m deep (Pickrill, 1987; Gibbs et al. 2000; Gibbs, 2001). The LSL is colder in winter and warmer in the summer than the underlying seawater (Gibbs, 2001), likely having a negative impact upon the smaller, thinly insulated calves (Ridgway, 1972). The lower critical tolerance of an animal is defined as the lower threshold at which individuals become thermally compromised (Eckert & Randall, 1983), and is inversely related to body mass (Yeates & Houser, 2008). Smaller, thinly insulated calves may therefore become thermally compromised at higher temperatures than larger, older individuals (Alexander, 1975). Low water temperatures likely act in combination with other factors, such as food resources. New Zealand fiords are relatively unproductive; variation in salinity and temperature, low light regimes and limited space make it difficult for primary producing macro algae to thrive (Peake et al. 2001; Tallis et al. 2004). The diets of the Doubtful Sound dolphins are composed primarily of demersal reef-dwelling fish species (Lusseau & Wing, 2006), though it is suggested that seasonal pelagic species, such as mackerel (Scomber australasicus and Trachurus declivis), may also form an important food source for pregnant or lactating mothers during the calving season (Brough et al. 2016). Other studies (e.g. Urian et al. 1996; Fruet et al. 2015) have also linked seasonally available resources to seasonal reproduction, though without robust data on potential prey species in Doubtful Sound this cannot be quantified. Eigenvector centrality was not identified as a significant predictor of calf survival to 1 year. The relative social position of successful mothers compared to unsuccessful mothers during the first year of a calf’s life does not appear to be influential. Eigenvector centrality is a measure of the importance of an individual within its social network (Bonacich, 2007). There was little variation in EC among mothers, and no indication that mothers with higher EC were 62 | P a g e


more successful at raising calves. In a study by Stanton and Mann (2012), EC of calves was identified as an important predictor of survival in males from weaning to 10 years old. In Doubtful Sound, most mortality events occur shortly after birth, hence the genders of most calves that perished are unknown. While maternal social environments have been shown to affect males and females differently (Gibson & Mann, 2008), it is likely that, during the first year of a calves’ life, differences in social environments between sexes will be negligible. Given the overall high degree of association rates among all members of the Doubtful Sound population (Lusseau et al. 2003), differences in how central a mother is within the populations’ social network do not appear to be large enough to affect calf survival. The study by Henderson et al. (2014) spanned a 16 year period from 1995 to 2011, while Brough et al. (2016) used data from 1994 to 2012. As methods in the present study required time-stamped digital photographs, it was restricted to analyses after 2003. This resulted in a smaller dataset (n = 51) over a shorter period (12 years, from 2004 to 2015) compared to Henderson et al. (2014; n = 71) and Brough et al. (2016; n = 55). The differences in results obtained by these studies could therefore be due to different analysis methods, different sample sizes, or the different sampling periods (possibly reflecting changes in ecological pressures, such as climate or prey availability). Mother size has been identified as a significant predictor of calf survival to 1 year in this population (Brough et al. 2016). While length data do not strictly represent breeding condition, they may be a useful proxy. Morphometric data were last taken in 2012 and not during the present study, thus inclusion of such a parameter would have further limited sample size. It is important for future studies concerned with determining the relative importance of drivers of calf survival to include such a parameter. Unmanned aerial vehicles (UAVs) are becoming increasingly utilised in ecological research. They offer low-cost and low-disturbance monitoring of animals that could be used in more robust estimation of breeding conditions (Durban et al. 2015). It should therefore be the aim in future research to test the use of UAVs in the collection and analysis of body condition. Though birth period was identified as an important predictor of calf survival, results indicate little of the variance is explained by any of the fixed effects (indicated by low marginal values). The inclusion of the random factor (mother ID) produced conditional values close to 1. This indicates that who the mother is does have a strong influence upon the fate of the calf; though the exact mechanisms are still unclear. It is likely that a combination of factors are 63 | P a g e


influencing the variation in reproductive success among mothers. It is therefore important for future research to continue to tease apart the relative importance of factors influencing the variation observed. The present study attempted to identify the relative importance of various factors on calf survival to 1 year of age. Adopting an information theoretic approach using general linear mixed modelling provided useful inference on the relative importance of predictor variables on calf survival. However, in other studies assessing calf survival of marine mammals (e.g. Mann et al. 2000; Kogi et al. 2004; Currey et al. 2008) it has been noted that there will be calving events missed by researchers. Births are more likely to be missed during times of the year when monitoring intensity is lowest. If this coincides with greater probability of stillbirths, or short calf survival times, then the data will be biased towards those that have survived to 1. It was the initial intention of this study to include the association rates of each mother towards different demographics of the population (e.g. adult males, adult females, juveniles and other mothers) in modelling procedures. Given the high correlation among all of these variables however it was decided that this was not feasible. Maternal socioecological strategies have been shown to influence the development of calf social patterns, especially female calves, of other bottlenose dolphin populations (e.g. Gibson and Mann 2008a, b). As mammalian social evolution is typically in response to ecological pressures (e.g. predation pressure and resource distribution), as well as social pressures (e.g. infanticide risk, competition), a calf’s learned/inherited social behaviour will no doubt influence its chances of survival to some degree. I believe, for the Doubtful Sound population, differences in association rates and social patterns among mothers and their effects upon calf survival is still an avenue worth investigating. Determining the best approach with which to tackle this question is beyond the scope of the current study however, and it is recommended that future studies dealing with potential drivers of calf survival include sociality as a possible predictor.

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Chapter 5: General Discussion

Chapter 5 General Discussion

This thesis aimed to provide new information on the conservation biology of bottlenose dolphins, with a focus on sociality. The principal field method used in this study was photographic identification of uniquely marked individuals, a long-established technique widely applied in research on marine and terrestrial species. In the present study, an alternative time-based method with which to define associations among individuals was developed. A key advantage of this method is that it can be easily and retrospectively applied to any photo-ID dataset in which photographs of uniquely identifiable individuals are timestamped. The bottlenose dolphin population of Doubtful Sound is highly philopatric, and features strong associations within and between sexes (Lusseau 2003; chapter 2). There is a high degree of mixing among all individuals, rather than clustering into strongly defined subgroups as has been found in Shark Bay (Smolker et al. 1992; Gibson & Mann, 2008), and Port Stephens, Australia (Wisznewski et al. 2009, 2010). Similarly strong mixed-sex social bonds have been observed in other dolphin populations with high degrees of site fidelity (e.g. spinner dolphins, Stenella longirostris, inhabiting Midway Atoll, Hawaii, Karczmarski et al. 2005; or among individuals within the two communities of Port Stephens; Wisznewski et al. 2010). Hamilton (1964) suggests that philopatry and altruism may form a self-reinforcing loop; that philopatry promotes strong bonds among individuals; the benefits of which favour fidelity to the natal group. Modelling studies suggest that as ecological constraints increase, we can expect the philopatric nature and the level of reciprocal interactions among individuals to increase also (Perrin & Lehmann, 2001). This is known as the “ecological-constraints” model (Emlen 1982; Jarvis et al. 1994; Spinks et al. 2000), and has been advocated as a main driver of sociality in many bird (Emlen, 1991; Koenig et al. 1992; Hatchwell & Komdeur, 2000) and Bathyergidae (naked mole rat and relatives) species (Jarvis & Bennett, 1991; Jarvis et al. 1994; Spinks et al. 2000). Comparative analyses of bonobo and chimpanzee populations have also shown that the fluidity of fission-fusion social dynamics is replaced by more stable and

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bisexually bonded societies when it is ecologically more beneficial for individuals to remain where they are (Boesch, 1996; 2002). Alternatively, the ‘benefits-of-philopatry’ model (Stacey & Ligon, 1990) proposes that high degrees of sociality can still occur even when there are few, if any, costs to dispersal. Increasing these costs may serve to favour philopatry; though no change in the degree of altruism is predicted. This latter hypothesis is likely to be more prevalent in species with high cognitive capacities, extended parental care, and high degrees of associative learning in which kin-recognition promotes altruistic behaviour (Perrin & Lehmann, 2001). In this model the benefits of sociality will ultimately outweigh the costs of competition with kin, providing incentives for natal fidelity over dispersal. For the dolphin population of Doubtful Sound it is likely that a combination of both intrinsic benefits and extrinsic constraints increase philopatry. Habitat saturation in neighbouring fiords that are home to other dolphin populations (e.g. Dusky Sound to the South, and from Lake McKerrow to Charles Sound to the north) may reduce the probability of individuals leaving the natal group. Additionally, given the long history of residency within Doubtful Sound by the dolphins, experience of this fiord and its ecological characteristics will have been gained. Lack of knowledge of neighbouring fiords may mean that it is more beneficial to remain in Doubtful Sound than to risk dispersal into a less well-known habitat. Through their highly social nature, these lessons are likely to be passed on to less experienced individuals (Krebs, 1974; Waltz, 1982), increasing foraging efficiency within the dynamic environment of Doubtful Sound. Although equal and stable association rates among most members of the Doubtful Sound dolphin population are observed, some seasonal variation in association rates and group sizes was apparent (chapter 3). In fission-fusion societies, temporal variation in group composition and size, as well as in the rates of association, are thought to be an adaptive response to changing ecological variables (Wrangham, 1983). Studies of chimpanzee and bonobo communities show that group sizes correlate highly with fruit availability; smaller parties are observed during months in which food is scarce (Wrangham et al. 1992; White, 1996; Malenky, 1993). Seasonal variation in prey availability may be affecting the association rates of the dolphins in Doubtful Sound, as observed in other populations of social species. There are no data on prey availability and abundances however, stressing the need for further investigation. 66 | P a g e


The presence of seasonally abundant predators has also been suggested to play an important role in driving patterns of association in socially complex species. Predation risk is considered to be a significant factor in the social evolution of primates (Hill & Lee, 1998), and has been argued to affect both habitat use and group sizes of various dolphin populations (e.g. Norris & Dohl, 1980b; Wells et al. 1980, 1987; Heithaus, 2001). If an individual is unsuccessful in a foraging event, it simply moves on and looks for the next meal. If an individual is unsuccessful in escaping a predator, the outcome is far more severe. Predation pressures therefore do not need to be high in order to affect the behaviours of individuals, and the nature of their sociality. Little is known about predator distributions in Fiordland, though satellite tagging of white sharks by Duffy et al. (2012) and Francis et al. (2015) suggests a possible migratory corridor that extends from Fiordland, along the southern margin of Lord Howe Rise, to northern New South Wales and southern Queensland, Australia. This should be a priority for future research, given that predation is likely an important driver of social structure, as well as other aspects of the dolphins life histories. Globally, several other bottlenose dolphin populations exhibit low numbers and restricted ranges (e.g. Scott et al. 1990; Wilson et al. 1999; Fruet et al. 2011). There are, however, no published reports of closed, resident populations as small as that in Doubtful Sound. This population is therefore more susceptible to demographic stochasticity, as well as perturbations in the environment (environmental stochasticity). Such stochastic effects have been known to cause significant declines of small populations (e.g. Laurie & Brown, 1990; Gaillard et al. 1998; Craig & Ragen, 1999; Baker et al. 2007; Melbourne & Hastings, 2008) and are usually contributory, if not driving, factors in extinctions (Simberloff, 1988). Variation in reproductive output can be a major contributor to demographic stochasticity. Chapter 4 explored how some individual females contribute disproportionately to reproduction; this is one aspect of what is known as demographic heterogeneity (Melbourne & Hastings, 2008). The survival rate of calves is a key driver of population trends in Doubtful Sound (Currey et al. 2009), with this population having experienced the lowest calf survival rates observed in any free-ranging bottlenose dolphin population (0.375; 95% CI: 0.208 – 0.578; Currey et al. 2009). High variability in calf survival may be a natural feature of the Fiordland population as a whole; calf survival is also variable in the less impacted (i.e. a lesser degree of human interactions) Dusky Sound dolphin population to the south. Failure to account for demographic stochasticity in population viability analyses may lead to inaccurate results, compromising predictive power, and resulting in excessively optimistic estimates of 67 | P a g e


probability of extinction (Slooten et al. 2000; Melbourne & Hastings, 2008). It is therefore important to continue to tease apart the drivers of stochasticity. The identification of birth timing as a significant predictor of calf survival in the present study is consistent with previous studies on this population (Henderson et al. 2014; Brough et al. 2016). Birth timing has also been identified as important to offspring survival in a range of other taxa, including birds (Daan et al. 1988), bats (Ransome & McOwat, 1994), and deer (Aanes & Anderson, 1996). Short birthing seasons have been attributed to a need for reproduction to coincide with favourable environmental conditions (Ims, 1990; Ransome & McOwat, 1994), or higher availability of food (Ransome & McOwat, 1994). The present study found the optimal time for birth was slightly later than identified by Henderson et al. (2014) and Brough et al. (2016). The reasons are unclear, but possible changes in water temperatures and/or prey availability warrant further investigation. Although maternal social environments no doubt influence the association patterns of offspring (Gibson & Mann, 2008), how central a mother is in her social network was not identified as an important predictor of calf survival in Doubtful Sound. During the first few years of life, calves remain highly associated with their mothers, encountering her associates regularly. During separations, however, such as maternal foraging bouts (Mann & Smuts, 1998; Mann & Watson-Capps, 2005), calves may encounter these same associates but pattern their own time with individuals differently (Gibson & Mann, 2008). Given the low variability in eigenvector centrality among mothers, and similar rates of association among all individuals, the social environments of calves may not differ substantially between those of “good” mothers and those of “poor” mothers. Historically the bottlenose dolphin populations of Fiordland have been considered discrete from one another. Recent observations, however, suggest that individuals are leaving Doubtful Sound more frequently than in the past (Henderson 2013; pers. obs.). During a recent monitoring trip, for example, a large portion of the Doubtful Sound population was encountered in Dagg Sound, a neighbouring fiord. Additionally, a mixed-sex group of 11 individuals from the Doubtful Sound population were photo-identified within Dusky Sound on a separate trip. These individuals were not interspersed among those of the Dusky Sound population and were seen back in Doubtful Sound two weeks later. These are the first instances individuals from one population have been photographed within the home ranges of the other. It may be that limiting resources within the natal fiords are causing individuals to 68 | P a g e


forage further afield more frequently (Henderson et al. 2013). This further highlights the need to investigate what drives the highly philopatric natures of these two populations. Social systems are not fixed features of a species; individuals presumably attempt to maximise their fitness under changing environmental conditions. Although this study did not identify mother social position as an important predictor of calf survival, the reproductive success of individuals in other taxa has been shown to be constrained by sociality (e.g. Durant, 1988; Komdeur & Deerenberg, 1997; Waite & Parker, 1997; Pettifor et al., 2000). It is therefore important that the nuances of social structure are teased apart and incorporated into analyses, such as predictive modelling (Pettifor et al. 2000) and population viability analyses (Durant, 2000), if we are to better understand the drivers of a population’s dynamics. This is especially important for small, endangered populations in which demographic stochasticity can have large consequences. The few studies that have attempted to incorporate aspects of social structure into population viability analysis (e.g. Young & Isbell, 1994; Martien et al. 1999) often do not consider relationships between the environment and behaviour; that social patterns change in response to conditions. Behaviour provides a powerful insight into populations: beyond “simply” understanding the social system, changes can be used to detect responses to perturbations within the environment (natural or anthropogenic; e.g. Nowaceck et al. 2001; Becker et al. 2011; Tyack et al. 2011; New et al. 2013; Guerra et al. 2014). For populations in which sociality is better understood, such as land mammals, ‘what if’ scenarios via sensitivity analyses have led to the development of more appropriate management strategies based upon varying environmental determinants (Komdeur & Deerenberg, 1997; Pettifor et al. 2000). There are interesting parallels in the dynamics of socially sophisticated mammals; even among species as distantly related as delphinids and primates. In this context, comparative analyses between such species could shed light on the ecological pressures that influence sociality. If we are to develop management strategies that ensure the persistence of highly social populations, a better understanding of the social patterns and their relationships with the environments they inhabit is essential.

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Implications of this research on the population of Doubtful Sound Results of the present study concur with those in previous work on this population; who a mother is affects the survival of calves. Recent research has identified extreme heterogeneity in reproductive success among females; only six mothers are responsible for most of the surviving calves in Doubtful Sound (Henderson et al. 2014). The potential for genetic variability is therefore limited. Coupled with its small size (c. 63 individuals) and discrete nature, the population of Doubtful Sound is therefore vulnerable to impacts (natural and anthropogenic), especially those that affect calves, mothers, and pregnant females. Previous work on this population suggests that groups with mother-calf pairs are particularly vulnerable to boat disturbance (Guerra et al. 2014). The present study has suggested that mothers and their calves often associate together in “nursery groups” (chapter 3). During years in which the few “good” mothers give birth at the same time (e.g. 2012), as well as subsequent years pre-weaning, there is a high probability that when one of these mother-calf pairs encounters a boat, so do the others. These interactions are also likely to occur more frequently during the earliest stages of a calf’s life; during summer when tour boat activity is highest. There is therefore an obvious need to provide strong protection to this demographic. The voluntary code of management established in 2008 in Doubtful Sound has been successful in reducing the frequency of dolphin-boat interactions (Guerra et al. 2014). There is a genuine concern for the dolphins of Doubtful Sound from tour operators, who show a high level of compliance and cooperation. While compliance is currently high, it could change for any number of reasons. Formalisation of the code of management into a legal requirement would help ensure that the current high level of compliance from operators persists. In recent years tour operators have taken increased interest in the public education about the dolphins of Doubtful Sound. During recent monitoring trips, tour guides and boat crew have been invited to join researchers in their work. This has not only aided in providing more robust information for public education, but also provides a greater appreciation of the research being conducted, and the importance of the population as a whole. Science communication and education are often major hurdles in effective management and public awareness. The continuation of including operators in monitoring and decision-making processes benefits relationships among all parties involved, and ultimately, the dolphins.

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Study limitations In any study there will be potential sources of bias and error. The study of animal behaviour, especially of social dynamics, is an exercise in approximation. No matter how careful, objective and quantitative our methods are, we seldom know whether our results reflect what is important to the animals. In the present study, the close association revealed between mothers and calves makes biological sense, and suggests that relationships among other groups are accurately captured. This yardstick cannot be used for species showing little or no dependency of the young upon a parent or parents. While the proposed methods can be easily applied to any population in which individuals can be identified via photography, care must be taken by researchers in assessing whether calculated rates of association are biologically meaningful. Based upon already established techniques, I aimed to develop a methodology that is as objective and consistent as possible. Studies of sociality often require large amounts of data, having likely been collected by multiple researchers. By using a long-term photo-ID dataset, there is an assumption that the standard of data collection among researchers did not vary. This is, of course, unlikely to be true. So long as photographers are vigilant in following prescribed photo-ID protocols however, bias will be minimised. Comparability among studies of association is often compromised by variation in methodologies; what constitutes a group in one species may not be appropriate in another. Likewise, given the plasticity of social behaviour among populations, what constitutes a group may vary among populations of the same species. The time-based method developed in Chapter 2, while still using co-occurrence of individuals to define association, is not directly comparable to other methodologies, such as the group-membership method. Results were, however, similar to those from previous studies of sociality in this population, and the method has great potential for revealing social relationships from photo-ID data collected for other purposes.

Future considerations This thesis has identified potential avenues for future research on the ecology of the bottlenose dolphins of Fiordland, and for research on sociality in general.

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The dolphins of Fiordland 

The feeding ecology of the dolphins of Fiordland remains unclear. The availability of prey species, and how and when the dolphins utilise them, are important to understanding what limits these endangered populations. This could be approached via a combination of methods. For example, collaboration with local commercial and recreational fishers may provide general data on species presence. Targeted research fishing is possible, as is the use of baited underwater video (Willis et al. 2000; Cappo et al. 2004; Watson et al. 2005). High resolution active sonar (side-scan or multibeam) also allows the detection of fish species via density differences in gasses of their swim bladders and the surrounding ocean (Misund, 1997); offering potential indication of prey abundances in areas deemed important.



The present study provided evidence of the importance of mother identity on calf survival within the Doubtful Sound population; though why this is so remains unclear. It is therefore important that future research attempt to identify the drivers of variation in reproductive success among females. Unmanned aerial vehicles offer a novel and exciting opportunity to collect data on aspects of both individuals (e.g. body sizes/shapes) and groups (e.g. association rates).



No attempts to describe and assess the social structure of the bottlenose dolphins of Dusky Sound have been made to date. Though this population is geographically close to Doubtful Sound, the extreme behavioural plasticity of bottlenose dolphins means that we should not assume similar results to those from Doubtful Sound. As the Dusky population experiences far less contact with human activity, it would be interesting to compare patterns of sociality between these two populations. Application of the new time-based method to the long term photo-ID dataset in Dusky Sound would allow this analysis to be conducted, providing comparable results to those produced in the present study.



From a research perspective, the populations of Doubtful and Dusky Sounds are considered closed to emigration and immigration. However, recent years have suggested individuals are leaving their natal fiords more frequently on temporary excursions to other fiords (Henderson 2013; pers. obs.). Excursions from Doubtful

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Sound have been documented since 2009, though where they go and why is largely still unknown. Therefore the ‘closed’ status of these populations may need to be reconsidered in future research. Wider considerations 

Continued monitoring of the populations in Doubtful and Dusky Sounds via photoidentification is critical if we are to further our understanding of these populations. This is important for the management of these particular populations, but also for our understanding of bottlenose dolphin ecology as a whole. It is only in recent years that, thanks to the long-term nature of the data-sets, questions related to aspects of these long-lived animals’ life histories have become feasible. The value of such projects will only increase as more data are added.



Although various shark species are known to frequent Fiordland, there is no information on their abundances and distributions. As predation pressures probably influence life-history traits, it would be valuable to quantify these. Deployment of baited underwater video stations would allow assessment of the presence/absence in various areas, as well as facilitate estimations of abundance, facilitate morphometric analyses, and even photo-identification in the case of species like the sevengill shark (Lewis et al. unpublished data).



Association indices, and the metrics derived from these, are difficult to include in analyses such as linear modelling, as there tends to be high correlation among parameters. Future studies concerned with reproductive success should still consider aspects of individual sociality as potential predictors, though novel ways in which metrics can be incorporated into such analyses need to be developed.

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