Examining Macroecological Patterns in Mammals: Space Use, Diet and Energetics

Home , Giant kangaroo rat, Island Spotted Skunk, Jan Mayen, Japanese squirrel, King Haakon VII Sea, Lagostomus

Examining Macroecological Patterns in Mammals: Space Use, Diet and Energetics.

Marlee Tucker

Evolution and Ecology Research Centre School of Biological, Earth and Environmental Sciences University of New South Wales Sydney, N.S.W 2052, Australia

______Thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy within the University of New South Wales September 2014 THE UNIVERSITY OF NEW SOUTH WALES Thesis/Dissertation Sheet

Surname or Family name: Tucker

First name: Marlee Other name/s: Anne

Abbreviation for degree as given in the University calendar: PhD

School: Biological, Earth and Environmental Sciences Faculty: Science

Title: Examining Macroecological Patterns in Mammals: Space Use, Diet and Energetics.

Investigating large-scale patterns in ecology, biogeography and evolution is important to aid our knowledge of species diversity. With the current natural and anthropogenic environmental changes, it is necessary to gather information that can be used for developing models of global ecosystems to assist with conservation. To achieve this, we need to establish basic ecological theories and re-examine older theories to ensure that our current understanding—which is often based on small datasets consisting of a couple of individuals or species—is applicable when expanded across communities, populations and species. The aim of this thesis was to examine the driving influences behind macroecological patterns in mammals, including spatial behaviour and foraging ecology. The investigation of spatial behaviour and foraging ecology will provide useful information on the area required by species, trophic interactions and community structure. More specifically, I was interested in how behavioural changes that have occurred following the colonisation of the marine environment has influenced patterns in home range size, predator-prey relationships and trophic level position. Using published and empirical data and comparative methodologies, I examine the effect of body size, diet, energetics and environment upon home range size, predator-prey relationships and trophic position across mammals. I identify that body mass has been the key factor driving of home range size, prey size, energetics and trophic position in mammals, explaining between 46 and 85% of the variance. However, whether a species lives within the marine or terrestrial environment has also influenced macroecological patterns, with marine mammals having home ranges 1.2 times larger, sitting 1.3 trophic levels higher and have evolved two distinct feeding strategies compared to their terrestrial counterparts. I demonstrate the ability to utilise published data to re-examine ecological theories and highlights that when developing integrative models, we need to incorporate the possibility of phylogenetic effects, a range of ecological variables, and species representative of the diversity within a group should be included. I identify the driving influences of macroecological patterns and show how living in different environments has impacted upon mammalian spatial behaviour, foraging, food web structure and energetics.

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I dedicate this thesis to my mother, Jenny, who has believed in me

since day one.

Acknowledgements

Firstly, I would like to sincerely thank Tracey for all of your help, support and guidance throughout my PhD. I genuinely appreciate this opportunity to work with you. To Terry, a huge thank you for your invaluable assistance with statistical analyses, revisions, the crash course into phylogenetic trees/analyses and providing me a space when I had forgotten my keys! I would like to thank everyone on my panel; Alistair Poore, Adriana

Verges and Gerry Cassis, for your suggestions and input throughout my PhD.

Especially to Alistair for his statistical advice, providing feedback and for always making time to see me. Also to Angela Moles and Rob Brooks for your support and advice.

This thesis has been primarily based upon data from other researchers. The majority of the data were collected from published studies and are open access. However, I would like to acknowledge and thank Douglas Kelt (UC Davis), Dirk van Vuren (UC Davis),

Horst Bornemann (AWI), Joachim Plötz (AWI), Nick Gales (AAD), PJ Nico deBruyn

(U.Pretoria), Cheryl Tosh (U.Pretoria), Colin Southwell (AAD) and Iain Staniland (BAS) for making their datasets available to me (Chapter 2). All research related to animal handling (Chapter 2) was approved by the University of New South Wales Animal Care and Ethics Committee (08/103B and 11/112A). Some of the data used Chapter 2 were obtained from the Australian Antarctic Data Centre (IDN Node AMD/AU), a part of the

Australian Antarctic Division (Commonwealth of Australia). The data are described in the ARGOS satellite tracking record "1994 to 2000 - Antarctic Pack Ice Seals (APIS)

Survey" (Southwell, 2007). I wish to thank the personnel from the Instituto Antártico

Argentino IAA at Primavera Station in the years 2007-2011 for field work support.

Logistics support was provided by a grant from the IAA to my collaborator Alejandro

Carlini. The research (Chapters 2-5) was supported by an Australian Research Council

(ARC) grant LP0989933 awarded to my PhD supervisor Tracey Rogers.

Thank you to everyone in the lab (both past and current) - Michaela, Jess, Tempe,

Naysa, Alicia, Kobé, Belinda, Jeff, Lisa, Tiffanie, Nadine, Marie and Joy for providing valuable advice and feedback. I have enjoyed our cake and questions sessions as well as lab discussions, workshops and the occasional fieldtrips/extreme walks.

To my fellow Beesians (Rhiannon, Habacuc, Rachel, Sam, Andy, Flo, Tom, Melanie,

Angela and Ellie, among numerous others), who have helped along the way including coffee meetings, beverages, and of course serious work involving discussion groups and workshops. A big thank you to Jonathan, with his endless wealth of knowledge, has helped immensely with the administration side of my PhD.

To my fellow Antarctic adventurers who have taught me so much and have helped to keep me safe and well: Fernando Isla, Diego Gonzalez Zevallos, Jorge Gomez, Victor

Hugo Merlo Alvarez, Jorge Augusto Mennucci, Victor Llampa, Walter Edgardo Varela,

Edgardo Hector Toso, Ricardo Ceferino Larrea, Miguel Angel Schell, Fabian Villalba,

Carla Asti, David Slip, Ben Wallis, Skye Marr-Whelan, Magnus, Nicky, Dick, Mari,

Wouter and Rod.

Thank you to my friends who have helped to keep my social skills alive, especially

Alison, Theresa, Emma, Sam, Nicole, DR and Mary. Also a big thank you to everyone on my roller derby teammates who have helped me to keep me active and sane during the last year and a half.

And last but by no means least, a huge and heartfelt thank you to my parents. You have supported and encouraged me throughout my PhD and have experienced every low and high with me; especially during the several months I was down south with no means of contact.

Preface

Several chapters from my thesis have been published elsewhere:

Chapter 2 has been previously published as:

Tucker, M.A., Ord, T.J. & Rogers, T.L. (2014) Evolutionary predictors of mammalian home range size: body mass, diet and the environment. Global Ecology and Biogeography, 23, 1105-1114. (Appendix 1).

MAT, TLR and TJO conceived the study. MAT and TLR collected and compiled the data. MAT conducted the analyses. MAT, TJO and TLR wrote the paper.

Chapter 3 has been previously published as:

Tucker M.A. and Rogers T.L. (2014) Examining the Prey Mass of Terrestrial and Aquatic Carnivorous Mammals: Minimum, Maximum and Range. PLoS ONE 9(8): e106402. doi:10.1371/journal.pone.0106402

MAT and TLR conceived the study. MAT collected and compiled the data. MAT conducted the analyses. MAT and TLR wrote the paper.

vii

Abstract

The aim of this thesis was to examine the driving influences behind macroecological patterns in mammals, including spatial behaviour and foraging ecology. The investigation of spatial behaviour and foraging ecology will provide useful information on the area required by species, trophic interactions and community structure. More specifically, I was interested in how behavioural changes that have occurred following the colonisation of the marine environment has influenced patterns in home range size, predator-prey relationships and trophic level position.

Using published and empirical data and comparative methodologies, I examine the effect of body size, diet, energetics and environment upon home range size, predator-prey relationships and trophic position across mammals. I identify that body mass has been the key factor driving of home range size, prey size, energetics and trophic position in mammals, explaining between 46 and 85% of the variance. However, whether a species lives within the marine or terrestrial environment has also influenced macroecological patterns, with marine mammals having home ranges 1.2 times larger, sitting 1.3 trophic levels higher and have evolved two distinct feeding strategies compared to their terrestrial counterparts. I

1 demonstrate the ability to utilise published data to re-examine ecological theories and highlights that when developing integrative models, we need to incorporate the possibility of phylogenetic effects, a range of ecological variables, and species representative of the diversity within a group.

I identify the driving influences of macroecological patterns and show how living in different environments has impacted upon mammalian spatial behaviour, foraging, food web structure and energetics.

Table of Contents

Dedication ...... iv Acknowledgements ...... v Preface ...... vii Abstract...... viii Table of Contents ...... x List of Tables ...... xii List of Figures ...... xiv Appendices ...... xv

Chapter 1: General Introduction ...... 1 1.1 Body Size ...... 2 1.2 Spatial Behaviour ...... 10 1.3 Carnivory in Mammals ...... 11 1.4 Trophic Level ...... 12 1.5 Phylogenetic Data ...... 13 1.6 Phylogenetic Comparative Analyses ...... 13 1.7 Thesis Outline ...... 15

Chapter 2: Evolutionary predictors of mammalian home range size: body size, diet and the environment ...... 17 2.1 Summary ...... 17 2.2 Introduction ...... 18 2.3 Methods and Materials ...... 22 2.4 Results ...... 27 2.5 Discussion ...... 35 2.6 Conclusion ...... 39

Chapter 3: Examining the prey mass of terrestrial and aquatic carnivorous mammals: minimum, maximum and range...... 41 3.1 Summary ...... 41 3.2 Introduction ...... 42 3.3 Methods and Materials ...... 44 3.4 Results ...... 48 3.5 Discussion ...... 54 3.6 Conclusion ...... 59

Chapter 4: The cost of carnivory revisited ...... 61 4.1 Summary ...... 61 4.2 Introduction ...... 62 4.3 Methods and Materials ...... 66 4.4 Results ...... 70 4.5 Discussion ...... 78 4.6 Conclusion ...... 84

Chapter 5: Examining predator-prey body size, trophic level and body mass across marine and terrestrial mammals ...... 85 5.1 Summary ...... 85 5.2 Introduction ...... 86 5.3 Methods and Materials ...... 89 5.4 Results ...... 91 5.5 Discussion ...... 96 5.6 Conclusion ...... 105

Chapter 6: General Discussion ...... 107 6.1 Home Range Size ...... 108 6.2 Minimum, Maximum and Range of Prey Mass ...... 109 6.3 Carnivorous Strategies ...... 110 6.4 Trophic Level ...... 112 6.5 General Findings ...... 113 6.6 Conclusion ...... 115

References ...... 116 Appendix 1 ...... 133 Appendix 2 ...... 144 Appendix 3 ...... 195 Appendix 4 ...... 203 Appendix 5 ...... 219 Appendix 6 ...... 241

Frontispiece: All silhouettes were downloaded from http://phylopic.org.

List of Tables

Table 2.1 Model estimates and confidence intervals for the β0+βmass+βenvironment+βmethodology model across 312 mammals ...... 25

Table 2.2 Level of support for explanatory models of home range size evolution in terrestrial mammals ...... 28

Table 2.3 Level of support for explanatory models of home range size evolution in marine and terrestrial mammals ...... 31

Table 2.4 Level of support for explanatory models of home range size evolution in carnivorous mammals ...... 33

Table 3.1 Summary of the orders and families included in the study sample ...... 45

Table 3.2 Level of support for explanatory models of prey mass evolution in carnivorous mammals ...... 48

Table 3.3 Variance components analysis of prey mass across 108 carnivorous mammal species ...... 51

Table 3.4 Descriptive statistics for the prey mass distributions across 108 carnivorous mammals ...... 52

Table 3.5 Descriptive statistics for the prey mass distributions across 51 carnivorous terrestrial mammals ...... 54

Table 3.6 Descriptive statistics for the prey mass distributions across 57 carnivorous aquatic mammals ...... 54

Table 4.1 Best supported breakpoint models and associated coefficients for daily energetic intake (DEI) and daily energetic expenditure (DEE) in relation to predator mass (M) ...... 72

Table 4.2 Best supported breakpoint models and associated coefficients for prey mass (P) against predator mass (M) ...... 73

Table 4.3 Level of support for explanatory models of prey mass of predatory mammals. Results are from phylogenetic regression analyses ...... 77

Table 5.1 Level of support for explanatory models of trophic level evolution in mammals .. 92

List of Figures

Figure 2.1 Home range size as a function of species body mass compared for terrestrial carnivorous, herbivorous and omnivorous species (n=429 species) ...... 29

Figure 2.2 Home range size as a function of species body mass compared for carnivorous, herbivorous and omnivorous species (n=462 species) ...... 32

Figure 2.3 Carnivore home range size as a function of species body mass compared for species occupying terrestrial and marine environments (n=134 species) ...... 34

Figure 3.1 Minimum prey mass (A), maximum prey mass (B) and prey mass range (C) as a function of carnivore body mass compared for terrestrial and aquatic species ...... 50

Figure 3.2 Distributions of the minimum prey mass for (A) terrestrial carnivorous mammals and (B) aquatic carnivorous mammals, and the maximum prey mass for (C) for terrestrial carnivorous mammals and (D) for aquatic carnivorous mammals ...... 53

Figure 4.1 Estimates of (A) Daily energy intake (DEI) against carnivore body mass (n=48) and (B) daily energy expenditure (DEE) against carnivore body mass (n=27) in marine and terrestrial mammals combined ...... 71

Figure 4.2 Mean prey body mass as a function of carnivore body mass for 107 species across the marine and terrestrial environments ...... 75

Figure 5.1 (A) Trophic level as a function of species body mass compared for species occupying terrestrial and marine (n=107 species). (B) Schematic of general trophic level patterns for terrestrial mammals and marine mammals ...... 93

Figure 5.2 (A) The relationship between log10 predator-prey ratio as a function of predator trophic level, across marine and terrestrial mammals (n=107 species). (B) Examples of feeding strategies used by marine and terrestrial carnivorous mammals ...... 95

Appendices

Appendix 1: Tucker, M.A., Ord, T.J. & Rogers, T.L. (2014) Evolutionary predictors of mammalian home range size: body mass, diet and the environment. Global Ecology and Biogeography, 23, 1105-1114...... 133

Appendix 2: Supplementary information for Chapter 2 ...... 144

Appendix 3: Tucker, M.A, and Rogers, T.L. (2014) Examining the prey mass of terrestrial and aquatic carnivorous mammals: minimum, maximum and range PLoS ONE 9(8): e106402 ...... 195

Appendix 4: Supplementary information for Chapter 3 ...... 203

Appendix 5: Supplementary information for Chapter 4 ...... 219

Appendix 6: Supplementary information for Chapter 5 ...... 241

Chapter 1 General Introduction

Investigating large scale patterns in ecology, biogeography and evolution is important to aid our knowledge of species’ vulnerability to changing environments. Due to the current natural and anthropogenic environmental changes, it is necessary to gather information that can be used for developing models of whole ecosystems and global processes to assist with conservation. To achieve this, we need to establish ecological theories and re-examine older theories to ensure that our current understanding— which is often based on small datasets consisting of a few individuals or species—is applicable when expanded across communities, populations and species.

Macroecology uses statistical analyses to investigate the relationship between organisms and their environment at broad scales (Brown, 1995). Whilst small-scale investigations focus on a single species or on localised patterns, the focus of ecological studies is on ecological and evolutionary patterns that occur over large temporal or spatial scales (Smith & Lyons, 2011). Macroecology has enhanced our understanding of the mechanisms behind broad-scale patterns including species richness (Gotelli et al., 2009), species distribution (Pautasso et al., 2011), species-energy relationships

(Anderson & Jetz, 2005) and spatial behaviour (Jetz et al., 2004). One key area of study within macroecology is animal body size evolution and the broad effects that body size has on animal life history, ecology, abundance and assemblages (Peters,

1983; Gaston & Blackburn, 1996; Sibly & Brown, 2007; Chown & Gaston, 2010;

Cooper & Purvis, 2010; Smith & Lyons, 2011).

Chapter 1 – Introduction

1.1 BODY SIZE

Over the past 70 million years, evolution has led to huge variation in the evolution of mammalian body sizes. Body size has undergone a large transformation resulting in a broad range of sizes, from the 20g mouse to the 2,000,000g elephant (Evans et al.,

2012). Mammals are an ideal model to examine the drivers of macroecological patterns. They are a diverse group of species that have colonised a range of habitats across the terrestrial and marine environments, and fill a variety of feeding niches

(Smith & Lyons, 2011; Price et al., 2012). Additionally, mammals have evolved a range of locomotion behaviours including running and swimming, which has aided the exploitation of these different environments and associated resource niches. For example, mammals have colonised the marine ecosystem on seven separate occasions, with five extant groups still remaining (Uhen, 2007). The successful colonisation of new environments (e.g. water) provided access to new ecological resources, but also exposure to a system with completely different physical properties.

Living in an aquatic environment has resulted in altered morphology (e.g. body shape;

Gatesy et al., 2012), physiology (e.g. increased levels of globins for more efficient oxygen transfer; Williams et al., 2008) and behaviour (e.g. altered locomotion; Gatesy et al., 2012).

A large amount of research effort has been dedicated to examining the patterns of body size in animals and attempting to tease apart the drivers behind these patterns.

There is extensive variation in body size across mammals, both temporally (going back in time) and spatially (across continents) (Smith & Lyons, 2013). It has been shown that variation in body size is influenced by a range of factors including physiology

(acquisition and allocation constraints), evolution (selection and diversification forces) and ecology (biotic and abiotic setting) (Maurer & Marquet, 2013). Physiological factors include biomechanical and thermoregulatory constraints on maximum body size

Chapter 1 – Introduction

(Schmidt-Nielsen, 1984), and the trade-off between energy acquisition and allocation for reproduction and its effects on the shape of the body size distribution of mammals

(Brown et al., 1993). Evolutionary factors include higher extinction risk in larger mammals limiting the maximum size that can be obtained (Dial & Marzluff, 1989;

Cardillo et al., 2005) and constraints on natural selection that influence the structure of body size patterns (e.g. constraints on the ability of individuals to transform resources into offspring; Maurer, 1998). Ecological factors include competition between species or individual impacting upon minimum body size (Brown et al., 1978) and the interaction between space use, land mass area and energetic requirements impacting upon both minimum and maximum sizes (Marquet & Taper, 1998).

Several ‘rules’ have been developed in order to explain the patterns in body size across mammals. Bergmann’s rule attempts to explain one of the ‘general’ patterns in body size where individuals of a species have larger body size in colder environments

(i.e. away from the equator) (Bergmann, 1847). There have been several suggestions as to why this pattern is expected. First it was suggested that variation in body size is driven by ectothermic thermoregulation and geometric heat loss, where species with large body size have a smaller surface area to volume ratio compared to smaller species, meaning that smaller species would lose more heat per unit mass than those with larger body sizes (Mayr, 1963). However, it was later suggested that due to the greater importance of insulation and heat-conserving properties for large-bodied mammals, that pelage characteristics (i.e. hair and its insulation properties) were more important than body size (McNab, 1971; Steudel et al., 1994). The results from studies examining the validity of Bergmann’s rule suggested that the majority of mammals follow this pattern. Today Bergmann’s rule is accepted as an ecological generalisation for mammals (Ashton et al., 2000; Meiri & Dayan, 2003; Meiri, 2011).

Chapter 1 – Introduction

Cope’s rule is another ecological generalisation related to body size and attempts to explain patterns whereby organisms within a lineage evolve towards a larger body size

(Cope, 1986). There are benefits associated with large body size including decreased predation risk, extended longevity and resistance to climatic variation or extremes

(Hone & Benton, 2005). However, the evolution of increased body size is only advantageous when these benefits outweigh the negatives (e.g. increased extinction rate, increased resource requirements and low fecundity). Cope’s rule has been demonstrated across taxa including birds, plants, insects and mammals (Kingsolver &

Pfennig, 2004).

Rensch’s rule describes sexual dimorphism in species, where the magnitude of sexual dimorphism increases with body size (Rensch, 1950). This pattern is explained by a combination of life history and energetic drivers associated with body size, and are observed in herbivorous mammals such as bovids. For example, small species such as

Kirk's dik-dik (Madoqua kirkii) live in pairs, mature rapidly at similar sizes across the sexes and males have small weaponry, compared with large species such as Spanish ibex (Capra pyrenaica) where time to maturity is slower, male weaponry and body size is larger, and polygyny increases (Jarman, 1983). In addition, a relationship has been identified between female groups size (i.e. size of herd) and the body size of males in mammals (Sibly et al., 2012). Large polygynous males tend to have larger weaponry, which means that they can outcompete smaller males for access to large groups of females (and potentially increase the number of offspring sired). This suggests that female group size is an important parameter for Rensch’s rule (Sibly et al., 2012).

The island rule describes the phenomenon of insular species (isolated on islands) evolving body sizes which differ significantly from their mainland relatives (Van Valen,

1973; Lomolino, 1985; Lomolino, 2005). For example, the Sardinian dhole

(Cynotherium sardous) had evolved towards a smaller body size compared with its

Chapter 1 – Introduction

mainland relatives (Lyras et al., 2010). These changes in body size are thought to be driven by the reduction in predation pressure and lower competition for resources.

Measuring body size patterns between mainland and island species for birds, lizards and mammals has produced mixed results (Lomolino, 2005; Meiri et al., 2005; Raia et al., 2010). The most recent studies suggest that the island effect can be detected at the genus level for mammals, where large species have become smaller, but there was no evidence of small insular species becoming larger (Meiri et al., 2011).

There is a relationship between body size and life history traits in mammals, with large species generally having low productivity and long lifespans (slow life-history continuum) compared to small species which have high production rates and short lifespans (fast life-history continuum) (Sibly & Brown, 2007; Okie et al., 2013). This relationship between body size and life history is driven by the physiological factors impacting upon birth and death rates (e.g. mass-specific metabolic rate). Lifestyle, the interaction between physiology, ecology and anatomy, also has a substantial impact on a species’ life history (Sibly & Brown, 2007). For example, species that specialise on an abundant resource such as grazing herbivores or marine mammals often have higher production rates due to their access to abundant and reliable resources which can support higher mass-specific productivity (Okie et al., 2013). An example of how death rate impacts the life history of mammalian species is the evolution of behaviours that minimise predation. Adaptations including the evolution of flight (e.g. bats), an arboreal lifestyle (e.g. primates) or extreme body size (e.g. megaherbivores) have all increased the longevity of various species due to the reduced predation risk associated with these adaptations, resulting in a lower mass-specific productions rate (Sibly & Brown, 2007).

Birth rate is another driver impacting mammal life history, where the size and frequency of litters has been shaped by a range of factors including body mass constraints and offspring success rates (Sibly & Brown, 2009). Species with large body mass tend to produce large single offspring (or few large offspring) compared with smaller mammals

Chapter 1 – Introduction

that produce small and numerous offspring. Species that produce numerous offspring face greater predation risk and have evolved behaviours to minimise this risk. For example, species that produce large litters often utilise a burrow which provides protection for the offspring from predation (e.g. lagomorphs). In comparison, species that experience high exposure to predation (e.g. pinnipeds), or those that need to transport their young (e.g. primates) often produce few or single offspring. Marsupials provide an interesting example as they can alter their reproductive capabilities according to the resource availability. For example, kangaroos and wallabies can pause the development of the embryo when environmental conditions are poor (e.g. a drought) and then can continue the development process when conditions have improved (Clark & Poole, 1967).

There have been extensive investigations into the relationship between body size and abundance (Damuth, 1981; Damuth, 1993; Marquet et al., 1995; Ernest et al., 2003a;

White et al., 2007). There are four main measures of abundance including global size– density relationships (GSDR), local size-density relationships (LSDR), individual size distributions (ISD) and cross-community scaling relationships (CCSR) (White et al.,

2007). GSDRs are one of the most studied relationships and is a measure of body size and species population densities calculated from global aggregates (White et al.,

2007). GSDRs demonstrate that population densities decrease with increasing body mass because of underlying energetic processes such as resource use and availability, energy transfer between trophic levels and metabolic constraints (Damuth, 1981). This has been deemed the energy-equivalence rule (EER) because as population density declines with increasing body mass, individual energy demands of populations increase with body mass, resulting in the energy use of local populations to be approximately independent of body size (Nee et al., 1991). However, there is debate over whether the EER is a valid ‘rule’ and if global patterns in abundance are actually driven by resources and/or energetics because resources are driven by local

Chapter 1 – Introduction

processes, not a global process (Blackburn & Gaston, 1999; Isaac et al., 2013). It is currently thought that both ecological and evolutionary drivers have had a role in

GSDRs (Damuth, 2007; Isaac et al., 2013).

It is well established that metabolic rate, whether it be basal, field or maximal metabolic rate, increases with body size (Nagy, 1987; Karasov, 1992; Ernest et al., 2003b; Nagy,

2005; Clarke et al., 2010). The metabolic theory of ecology (MTE) describes how metabolism varies with body size and temperature, and is used to link ecological patterns and processes to various constraints placed upon individuals (e.g. biological, physical and chemical) (Brown et al., 2004a; Humphries & McCann, 2014). Patterns explained range from life history traits such as life span, to population interactions including patterns of species diversity, and ecosystem processes such as biomass production (Brown et al., 2004b; Humphries & McCann, 2014). Body size accounts for a large portion of the variation in metabolism (in addition to temperature), which further demonstrates the fundamental importance of size on ecology and biology. An example of this is the relationship between body size, metabolism and animal behaviour. Across animal taxa, including mammals, birds, fish and invertebrates, it has been demonstrated that variation in migration distance can be explained by metabolic rate and therefore the energetic costs of migration (Hein et al., 2012), where flying animals generally travel further than swimming and walking animals of a similar body mass

(Hein et al., 2012).

Behavioural impacts of body size can be observed in the foraging behaviour of animals. In herbivorous mammals, body size influences diet type and distribution

(Hopcraft et al., 2012). When herbivores are small, they tend to feed on high quality resources and are found in areas of low predation risk, compared to large herbivores that feed on resources of mixed quality and in areas of mixed predation risk (Clauss et al., 2003; Hopcraft et al., 2012; Clauss et al., 2013). These patterns explain why

Chapter 1 – Introduction

herbivore assemblages generally consist of species with varying body sizes to minimise the competition between species while maximising the available energy. The foraging and escape behaviour of animals is also influenced by body size. An example is the reaction time and response of an individual to approaching heterospecific individuals of differing sizes. In some species, such as the Yarrow's Spiny Lizard

(Sceloporus jarrovii) and Striped Plateau Lizard (Sceloporus virgatus), when the approaching individual is larger than the individual being approached, this will invoke a fear response (i.e. the individual being approached will flee), but when the approaching species is smaller, the individual being approached will wait and attack (assuming the approaching species to be prey; Cooper & Stankowich, 2010). Also, when mammals reach a certain size (e.g. elephants or giraffes), predation risk often decreases because it is too energetically expensive and often dangerous for predators to attack. However, there are exceptions with the juveniles of these large species still susceptible to predation, as well as the threat that humans pose to all mammals due to technological advances (i.e. guns).

There are numerous questions which need to be addressed about the evolution of body mass and the effects of body mass on behaviours and traits of animals. One of these questions is whether there is a general rule or a single process that is driving the broad-scale macroecological patterns we see in mammals. Body size is a fundamental trait for a broad suite of patterns including metabolic rate, longevity, life history traits and spatial patterns (Jetz et al., 2004; Sibly & Brown, 2007; Litchman et al., 2009;

Shattuck & Williams, 2010). Understanding allometric patterns and how they have evolved, will not only enhance our current knowledge of ecological theories (from individuals and their environment to entire ecosystems), but will also aid the development of models to predict how these patterns may change in the future

(Hendriks, 2007; Freckleton & Jetz, 2009).

Chapter 1 – Introduction

For mammals experiencing environmental changes that are altering their habitats and resources, it is necessary to gain an understanding of how these changes are influencing the mammal guild. Animal extinction risk is the focus of many current investigations (Bromham et al., 2012; Hanna & Cardillo, 2013; Dulvy et al., 2014;

McCain & King, 2014; Murray et al., 2014), with investigations encompassing a wide range of measurable traits or processes including life history traits, longevity, geographic range and ecosystem structure. Life history traits fall within a fast-slow continuum (Bielby et al., 2007) and species with traits at the slower end of this continuum (low reproductive rates) have a higher risk of extinction, both historically and at present (Johnson, 2002; García et al., 2008). As life history traits are often inherited from common ancestors, these traits are often similar among species that belong to specific taxa, meaning that extinction risk can be similar across related taxa (Davidson et al., 2012). Geographic range is another factor influencing the vulnerability of animals, with species restricted to small ranges highly susceptible to changes (e.g. anthropogenic impacts) within that range (Ceballos & Ehrlich, 2002; Laliberte & Ripple,

2004; Davidson et al., 2009). The trophic structure and productivity of an environment can influence the structure of an ecosystem and the susceptibility of the species within this system to extinction (Worm & Duffy, 2003). For example, species at higher trophic levels have higher extinction threats (e.g. carnivores; Borrvall et al., 2000; Duffy, 2003).

Additionally, it has been identified that the majority of models that predict extinction risk in mammals tend to treat all species as equally likely to respond to environmental changes (Moritz et al., 2008; McCain & Colwell, 2011). It was further demonstrated that this is an unrealistic assumption due to the body size and activity time of a species mediating their response to climate change (McCain & King, 2014). It is likely that other predictors, such as the physical environment, energetic requirements and diet will influence a species response to changes in their ecosystem. Through the examination of basic ecological theories of space use, feeding strategies and trophic structure, we

Chapter 1 – Introduction

can gather key information such as the drivers behind these macroecological patterns.

We can then incorporate this information into management plans and strategies, as well as providing base information for more complicated global models such as correlates of mammal extinction (Cardillo et al., 2008) or latitudinal gradients in diversity (Brown, 2014).

In this thesis, I have focused upon investigating spatial behaviour (home range) and foraging ecology (predator-prey relationships and trophic patterns) of mammals, all of which provide useful information on the area required by species, trophic interactions, and community structure.

1.2 SPATIAL BEHAVIOUR

Spatial behaviour provides information on how species interact with their environment

(Börger et al., 2006a). It is necessary to gain an understanding of the areas utilised and required by species if we wish to predict how environmental changes will impact mammalian species. A method used to characterise spatial behaviour is home range, which is the area covered by an individual during activities that allow it to survive and reproduce (Burt, 1943). Spatial movement patterns such as home range are tangible behavioural traits which can be monitored over time and result from the interaction of a range of predictors including environment and resource use (Börger et al., 2006a).

Average individual home range size at the species level is an ideal trait to examine as it has been demonstrated to have a strong relationship with body size within the terrestrial environment (Jetz et al., 2004) and ranges of different species can differ by several orders of magnitude, for example, the woodland vole, Microtus pinetorum, has a range less than 1 km2 (Gettle, 1975), compared with the polar bear (Ursus maritimus), which has a range of 125 100 km2 (Ferguson et al., 1999). In addition, across species of similar mass, home range can vary significantly (Kelt & van Vuren,

Chapter 1 – Introduction

2001), raising questions on what could be driving these differences and whether these drivers are uniform across all mammals.

1.3 CARNIVORY IN MAMMALS

Carnivorous mammal populations are highly vulnerable to extinction (Cardillo et al.,

2005; Carbone et al., 2011). This is due to the high energetic requirements of carnivores (Nagy, 2005), and therefore the need for a readily available and steady source of prey to sustain these populations. This is particularly pertinent for carnivorous mammals that experience energetic constraints caused by the amount of energy expended whilst locating and hunting sparsely distributed prey species (Carbone et al.,

1999). If prey populations decline, carnivores must spend more time and energy hunting and have less energy for reproduction, resulting in population declines of carnivores. It is therefore necessary to examine carnivorous strategies across the entire guild of carnivorous mammals in order to better predict how species will respond to changes within their environment.

We can utilise predator-prey relationships to gain insights into carnivore requirements

(e.g. prey and energetics) and their role within their ecosystem. More specifically, by studying the size of prey consumed by predators we can gather information on predation pressure (e.g. on specific size guilds; Hayward & Kerley, 2005) and the potential for trophic cascades (Fortin et al., 2005). It is important that when we investigate prey size we examine both the mean and the extremes (i.e. the minimum and maximum). Mean prey size patterns provide information on general patterns of prey size consumed by predators and this information is often used for predicting the susceptibility of carnivores to population declines and the role of carnivores within community structure (Carbone et al., 2007a). The extremes of prey size indicates the upper and lower limits of carnivore prey selection and this information is used to build

Chapter 1 – Introduction

our knowledge of how species respond to variation in the availability of food resources and optimal foraging theory (Costa et al., 2008). There has been little research on prey size patterns outside of the terrestrial environment (mean or extremes). This has limited the information we have on the entire guild of carnivorous mammals and whether they all follow similar foraging strategies regardless of the ecosystem they inhabit and the trophic structure of that ecosystem.

1.4 TROPHIC LEVEL

Understanding ecosystem structure and energy flow provides information useful for monitoring changes within a particular ecosystem (Jennings et al., 2002). The primary productivity of an ecosystem drives the amount of energy available to the organisms within that system (Arendt & Reznick, 2005). Additionally, the ecosystem characteristics (i.e. physical structure (Almany, 2004) and diversity (Duffy &

Stachowicz, 2006) influence the strength of biological interactions. Both energy availability and biological interactions play a role in the life history of an organism, highlighting the importance of understanding food web structure and trophic position.

We can use body size to model trophic position and food web interactions (e.g. predator-prey relationships), because energetic requirements and metabolic function dictate the flow of energy through an ecosystem (Petchey et al., 2008). In addition, information about food web complexity, ecosystem stability and community structure can be gathered using predator-prey body-mass ratios (Weitz & Levin, 2006; Petchey et al., 2008). Ecosystem stability is achieved when large species consume small species, leading to size structured trophic levels and food webs (Jennings &

Mackinson, 2003; Brose et al., 2006). As slight changes within a food web can result in trophic cascades (e.g. whales–otter–urchins–kelp; Pace et al., 1999; Estes et al.,

2011), we need to understand how trophic-level body-mass patterns in mammals have evolved, to better predict how the system may respond to such changes.

Chapter 1 – Introduction

1.5 PHYLOGENETIC DATA

When using standard statistical analyses to make comparisons across multiple species, issues related to non-independence can arise. This is caused by the fact that most standard statistical methods, such as analysis of variance, have key assumptions that the data points are independent. Generally, the data will not be independent if the species share a common evolutionary history (Ricklefs & Starck, 1996). Ignoring species relationships can result in the detection of relationships based upon non- independent points or the masking of within group relationships by phylogenetic differences across groups (Type II error; Orme et al., 2012). To overcome the issue of non-independence, it has been suggested that studies examining cross species patterns should include phylogenetic information, as traits are not randomly distributed across species (Harvey, 1996). Very few previous investigations of home range, predator-prey relationships and trophic level patterns have actually considered the possible bias of phylogenetic relatedness when examining traits. Mammals are a well- studied clade and this has aided the construction of a phylogeny that is relatively well resolved compared with other taxa (e.g. reptiles). To overcome statistical issues and to examine the effect of phylogeny upon mammalian spatial and foraging patterns, I have incorporated analyses that combine both trait and phylogenetic data into each data chapter of this thesis.

1.6 PHYLOGENETIC COMPARATIVE ANALYSES

The presence of large datasets and phylogenetic trees have led to numerous high impact studies investigating broad patterns in ecology and evolution at both the temporal and spatial scales, including species richness, biogeography and extinction risk (Fritz et al., 2009; Huang et al., 2012; Price et al., 2012; FitzJohn et al., 2014; Liow

& Finarelli, 2014). When combining phylogenetic information with species trait data we can use comparative methods to examine a large range of questions including

Chapter 1 – Introduction

examining character diversification across species, investigate convergent evolution, examine the tempo and mode of evolutionary traits and traits simulation (e.g. reconstruct ancestral states).

As my focus is to examine the relationships between traits and environments, the main analysis I use is phylogenetic regression. This type of analysis incorporates different sources of error including within-species variation and measurement error, error due to the evolutionary process, and error due to unknown or uncertain phylogenetic information (Martins & Hansen, 1997). Additionally, phylogenetic regression also allows for the estimation of phylogenetic signal within the data. This can be measured in various ways depending on the hypothesis. As I am interested in the correlation between species’ traits and their evolutionary history, I will use both alpha (α) and lambda (λ). α estimates the extent phenotypic variation among species is correlated to phylogeny. When α is close to 0, phenotypic differentiation among present-day taxa reflects the phylogenetic relationships among those species and is the product of

Brownian evolution. Brownian motion is a model of evolution that assumes that trait evolution proceeds as a random walk through trait space and Brownian motion has been proposed as a null model of evolution for testing hypotheses of trait evolution

(Felsenstein, 1985). When α is large (e.g., 15.50) phenotypic differentiation is unrelated to phylogeny (Martins & Hansen, 1997). Similarly, λ can also be used to quantify phylogenetic signal in the data and the extent to which correlations in traits reflect their shared evolutionary history (Pagel, 1999). The values of λ sit between 0 and 1, where values of 1 suggest a strong correlation between traits and their evolutionary history and 0 suggests there is no correlation.

Chapter 1 – Introduction

1.7 THESIS OUTLINE

Previous macroecology studies have examined whether there are general rules in ecology spanning spatial behaviour, feeding strategies and trophic structure (Brown,

1995; Carbone et al., 2007b; Boyer et al., 2010; Meiri, 2011). However, the majority of this previous research has either used data from predominantly terrestrial mammal species or have not included representatives across the entire span of mammal body mass (2 to 200,000,000 g). As a result, ecologists have an incomplete knowledge of general ecological patterns across all mammals. Including data on species from environments other than the terrestrial system, thereby including the full range of body sizes, can provide information on the driving factors behind large-scale patterns and general ecological rules. The aim of this thesis is to examine the effect of environment on spatial behaviour, carnivorous strategies and trophic structure of mammals in relation to body size and phylogenetic relatedness.

In Chapter 2 I investigate the driving factors of mammal home range size using data from the literature along with empirically derived values on home range size. First, I examine the relationship between diet, body mass and home range size in terrestrial mammals within an explicit phylogenetic framework. Second, I used a more comprehensive dataset that includes data on marine as well as terrestrial species to examine the effect of diet, body mass and environment (marine versus terrestrial) on home range size evolution across all mammals. Chapter 2 has been published in

Global Ecology and Biogeography, and a reprint of the published article is included in

Appendix 1 at the end of this thesis.

In Chapter 3 I examine the relationship between predator body mass and the minimum, maximum and range of their prey’s body mass. To achieve this, I test whether mammals show a positive relationship between prey and predator body mass, as found

Chapter 1 – Introduction

across reptiles and birds and predicted by optimal foraging strategy. I then examine the role that environment (i.e. aquatic and terrestrial) and phylogenetic relatedness have had in these predator-prey relationships. Chapter 3 has been published in PloS one, and a reprint of the published article is included in Appendix 3 at the end of this thesis.

In Chapter 4 I investigate the effects of living within the marine environment on carnivorous mammal feeding strategies. I first establish the energetic requirements of mammals on land and in water by examining the relationships between daily energy intake and body mass, and daily energetic expenditure and body mass. I then determine whether changes in energy intake and expenditure are associated with corresponding changes in feeding ecology.

Using diet information and trophic level data for terrestrial and marine mammals, I investigate how the colonisation of the marine and terrestrial environments has impacted the relationship between body size, trophic level and predator-prey ratio across mammals (Chapter 5). I also examine how differences between consumers within terrestrial and marine environments have influenced the trophic and food web structure of mammals. Here I had three objectives: (1) to determine what has driven the evolution of trophic-level body-mass patterns in mammals; (2) to determine whether living in different environments has resulted in the diversification of particular diet categories among mammalian taxa; and (3) to identify the drivers behind these patterns.

Chapter 2

Evolutionary predictors of mammalian

home range size: body size, diet and the

environment

This chapter has been published in Global Ecology and Biogeography (Appendix 1): Tucker, M.A., Ord, T.J. & Rogers, T.L. (2014) Evolutionary predictors of mammalian home range size: body mass, diet and the environment. 23, 1105-1114.

2.1 SUMMARY

Mammalian home range patterns provide information on spatial behaviour and ecological patterns, such as resource use, that is often used by conservation managers in a variety of contexts. However, there has been little research on home range patterns outside of the terrestrial environment, potentially limiting the relevance of current home range models for marine mammals, a group of particular conservation concern. To address this gap, I investigated how variation in mammalian home range size among marine and terrestrial species was related to diet, environment and body mass. I compiled data on home range size, environment (marine and terrestrial), diet and body mass from the literature and empirical studies to obtain a dataset covering

462 mammalian species. I then used phylogenetic regression analyses (to address non-independence between species) to examine the relative contribution of these factors to home range size variation among species. Body size explained the majority of differences among species in home range size (53-85%), with larger species occupying larger home ranges. The type of food exploited by species was also an 17

Chapter 2 – Mammalian Home Range

important predictor of home range size (an additional 15% of variation), as was the environment, but to a much lesser degree (1.7%). The factors contributing to home range evolution have been more complex than assumed. I demonstrate that both diet and body size are influential factors on home range patterns, but differ in their relative contribution, and show that the colonisation of the marine environment has resulted in the expansion of home range size. Broad-scale models are often used to inform conservation strategies. I propose that future integrative models incorporate the possibility of phylogenetic effects, a range of ecological variables, and that they include species representative of the diversity within a group.

2.2 INTRODUCTION

In animals, a broad range of physiological, ecological and behavioural factors scale with body size (Peters, 1983). Body mass, a measure of body size, accounts for a large proportion of the variation in home range size among terrestrial mammals (Kelt & van

Vuren, 2001; Jetz et al., 2004). Of all the potential consequences of allometry, the size of an animal’s home range provides valuable information on a variety of ecological variables, including resource use, social behaviour and other activities (Knight et al.,

2009). The strong positive relationship between home range size and body mass reflects the balance between the cost of locomotion and metabolic requirements with increasing body mass (McNab, 1963). Larger individuals can travel further than smaller individuals, but larger individuals have higher absolute energetic demands and need to travel further to gain the resources to meet those demands (McNab, 1963).

In addition to an animal’s size, diet is another important factor believed to dictate home range patterns. Carnivores, omnivores and herbivores have differences in their foraging costs (i.e., food acquisition and processing costs) due to their reliance on different food resources, which are also temporally and spatially different in distribution.

Chapter 2 – Mammalian Home Range

Carnivores feed on resources that are sparsely distributed, mobile and unpredictable across the landscape, requiring a large home range (Kelt & van Vuren, 2001; Carbone et al., 2007a). There are also additional costs for carnivores such as the time and energy required to hunt for food (Carbone et al., 1999). In contrast, herbivores tend to have the smallest home ranges because they feed on vegetation which is fixed in time and space and is generally abundant. However, there are additional energetic costs associated with processing plant material (e.g. Clauss et al., 2003), which limits their ability to forage widely. Omnivores have an intermediate-sized home range that reflects their mixed diet (meat and vegetation) (Kelt & van Vuren, 2001) and the intermediate costs associated with processing these foods (McNab, 1986).

Despite the large body of work on the physiological and ecological variables that might impact an animal’s home range size (e.g., body mass and diet), gaps remain in our understanding of which factors (or combination of factors) actually drive mammalian home range patterns. While it is clear that diet and body mass are important, past studies have examined these factors separately (Kelt & van Vuren, 2001; Jetz et al.,

2004) and we have little idea of the relative contribution each has on mammalian home range size. Furthermore, home range data have been historically biased towards terrestrial mammals, resulting in the exclusion of the larger mammals (>4000 kg).

Marine mammals represent a prominent group of large carnivores. It is also unclear whether the factors driving home range size in mammals are the same in terrestrial and marine environments. Furthermore, previous studies have failed to consider the phylogeny of species being studied. On methodological grounds, not incorporating information on the phylogenetic relatedness among species violates the statistical assumption that data points are independent of one another. This results in inflated

Type I error rates and correlations between variables that may not actually exist (Stone et al., 2011). On biological grounds, while closely related species are more likely to share characteristics through common ancestry (and are therefore not independent of 19

Chapter 2 – Mammalian Home Range

one another), variation among species can also be generated through the inherently stochastic process of evolutionary differentiation (e.g., drift) or phenotypic correlations that track the phylogeny and indirectly effect home range rather than adaptation in home range specifically. That is, variation in home range size among mammals may have little adaptive significance and might simply reflect a history of stochastic differentiation or other factors associated with phylogeny.

In this study, I set out to clarify these issues by conducting an inclusive analyses across both terrestrial and marine mammals to test the diet and the body mass hypotheses alongside each other (i.e., that home ranges will increase with increasing meat in diets in addition to—and independently of—increasing body mass) and against an evolutionary null model (stochastic variation). As part of these analyses, I also examined whether the same relative contribution of these factors has impacted home range evolution in the same way in both terrestrial and marine mammals.

The colonisation of the marine environment has been accompanied by fundamental shifts in physiology and ecology that may have changed the way in which body mass and diet affect home range size in marine species. One example of this is the ability of marine mammals to utilise buoyancy. Marine mammals have evolved various mechanisms to achieve neutral buoyancy such as increases in bone density and large blubber stores (Wall, 1983). Buoyancy is a key strategy for marine mammals to minimise costs associated with diving. An example of this is the North Atlantic right whale (Eubalaena glacialis) which utilises positive buoyancy when ascending

(Nowacek et al., 2001). Marine mammals have also evolved other adaptations that allow them to survive in the ocean and decrease their cost of transport (COT) per unit weight (Williams, 1999). These include a mixture of adaptations that are physiological

(e.g. increased levels of globins for more efficient oxygen transfer; Williams et al.,

2008) and behavioural (e.g. alternate forms of locomotion during diving; Williams, 20

Chapter 2 – Mammalian Home Range

1999) . The subsequent decrease in COT per unit weight, combined with passive movement via oceanic currents (Tremblay et al., 2006), results in the relaxation of energetic costs in marine environments compared with the terrestrial environment.

Given that marine COT is approximately half that of land COT (e.g. Californian sea lion

2.5 J kg-1m-1 (Williams, 1999) vs. grey wolf 4.6 J kg-1m-1 (Pontzer, 2007)), marine mammals on average should have home ranges at least twice as large as terrestrial mammals for any given body mass. Moreover, as the marine system is fluid with few boundaries to limit movement, food resources tend to be highly mobile across the ecosystem (Sims et al., 2008). In response, marine mammals are highly mobile, and this should result in further increases in home range size. Therefore, I anticipated that a regression of home range size on body mass should compute a higher intercept for marine mammals (larger home ranges) compared to terrestrial mammals. However, as the COT per unit weight decreases with body mass at a similar rate in both marine and terrestrial mammals (Hildebrand & Goslow, 1995; Pontzer, 2007), the scaling relationship of home range size and body mass should remain the same across both environments.

This study was conducted in two parts. First, I revisited the relationship between diet, body mass and home range size in terrestrial mammals within an explicit phylogenetic framework and assessed the relative contribution of each factor in shaping home range size. Second, I combined data on marine and terrestrial species to examine the effect of diet and body mass on home range size evolution across non-flying mammals, while also evaluating the role of the environment (marine versus terrestrial). Each of the factors—diet, environment and body mass—were formulated into mathematical functions and tested against an evolutionary null model. This null model provides a biological benchmark to establish the extent “neutral” evolutionary differentiation in home range evolution can be excluded. In this second part of the study, I tested two main hypotheses: (1) diet type underpins home range patterns in mammals because of 21

Chapter 2 – Mammalian Home Range

differences in the distribution and assimilation of food types; and (2) the home range- body mass relationship differs between marine and terrestrial mammals because of differences in the physiology of species and the physical properties of the two environments. However, I predicted that body mass would be the primary variable determining home range size evolution across all species. This is due to the metabolic and energetic costs associated with body mass driving the food requirements of individuals, which are a key determinant of spatial movements in mammals (Kelt & van

Vuren, 2001). Given this overarching effect of body mass, I then predicted that the environment would have an important secondary effect on home range size because it influences both the physiology of animals and the distribution of resources. Finally, within a given environment (e.g., terrestrial), I predict that diet type would generate additional variation in home range size among species, reflecting the interaction of diet with the metabolic and energetic costs associated with a given body mass.

2.3 MATERIALS AND METHODS

2.3.1 Database

A database of 462 mammalian species, representing 293 genera, 89 families and 24 orders, was collated. I collected body mass and home range values, physical environment (marine versus terrestrial) and diet (carnivore, omnivore and herbivore) information. The home range values for individual species were calculated as weighted averages which included both sexes, but did not incorporate sex ratios or averaged population densities. All body mass and home range data for terrestrial mammals was obtained from Kelt and van Vuren (2001) and the panTHERIA database (Jones et al.,

2009). Body mass and home range data for marine species was collected from published literature and unpublished empirical data (Appendix 2, Table 2.1). Home range was defined as the area covered by an animal during its daily activities such as mating and foraging (Burt, 1943), and used across the marine and terrestrial

Chapter 2 – Mammalian Home Range

environments. Marine mammals were defined as species that rely upon the ocean to survive (e.g. foraging etc.). Carnivores were defined as those species with diets comprising of at least 90% meat, herbivores at least 90% vegetation, and omnivores between 10 and 90% vegetation (Kelt & van Vuren, 2001). Insectivores were classified as “carnivores”, while frugivores and folivores were classified as “herbivores”. Home range and body mass data were log10 transformed prior to analysis.

To supplement data for six species not well represented in the published literature, I calculated home range size from satellite tracking data. These species were the leopard seal (Hydrurga leptonyx), Weddell seal (Leptonychotes weddellii), crabeater seal (Lobodon carcinophaga), southern elephant sela (Mirounga leonina), Subantarctic fur seal (Arctocephalus tropicalis) and Antarctic fur seal (Arctocephalus gazella). For information on sample size, data collection and sampling protocols see Appendix 2,

Tables S2.2 - S2.5. The satellite tracking data were filtered using a Speed-Distance-

Angle-filter (Freitas & Lydersen, 2008), resulting in the use of location classes A, B, 1,

2, 3. These classes represent the accuracy of the positional data where 3 has an accuracy of 0.49 km, 2 with 1.01 km, 1 with 4.18 km, A with 6.19 km and B with 10.28 km (Costa et al., 2010). The average daily position was calculated for each individual based upon all location data for a given day and only adult individuals were used.

Home range was calculated via the fixed kernel density method (KDE) (Seaman &

Powell, 1996) using the ArcGIS extension Hawth’s Tools (Beyer, 2004). I chose kernel density estimation to calculate home range size, as reviews into the benefits and bias’ of home range methods including kernels and minimum convex polygons (Laver &

Kelly, 2008) suggest that kernels are preferable over polygons which are biased by outliers and low numbers of location fixes (Börger et al., 2006b).

Chapter 2 – Mammalian Home Range

2.3.2 Phylogenetic Information

Due to the absence of a single phylogeny including all species of interest, a composite tree was created by combining information from several sources. The majority of the phylogeny was based on the mammalian supertree from Fritz et al. (2009) in which branch lengths were proportional to time since divergence. The following species were added to the Fritz et al. (2009) supertree using Mesquite ver 2.74 (Maddison &

Maddison, 2010) and species were positioned based on the topologies of the following sources; Callosciurus erythraeus (Steppan et al., 2004); Canis familiaris (Agnarsson et al., 2010); Eremitalpa granti (Kuntner et al., 2011); Orcaella heinsohni (McGowen,

2011); Sciurus aberti (Grill et al., 2009); and Sotalia guianensis (Caballero et al., 2008).

The Fritz et al. (2009) supertree included polytomies which are defined as a node where more than two species diverge at a single point in time (multifurcations). In this instance, these are soft polytomies due to insufficient phylogenetic information. To resolve the branch lengths and the polytomies present, I randomly generated 1,000 alternative branch lengths using the ‘randomly resolve polytomies’ function in Mesquite ver 2.74 (Maddison & Maddison, 2010). This produced 1000 alternative phylogenies and provided the basis for all of the phylogenetic comparative analyses.

2.3.3 Home Range Methodology

I have made an attempt to minimise any effects from different tracking methods (e.g.,

GPS, satellite and radio telemetry), analysis methodologies (kernels and polygons) and environments (terrestrial and marine) (Börger et al., 2006b; Frair et al., 2010), yet published studies differ in the methods used, resulting in the final database including mixed home range values by necessity. To examine the potential effect of different home range methodologies on a study of this scale (incorporating over 100 species), I ran a phylogenetic least squares (PGLS) regression analysis using the home range data collected (including a mixture of the home range estimation methods; kernel density estimation (n=26) and minimum convex polygons (n=286) and the phylogenetic 24

Chapter 2 – Mammalian Home Range

trees compiled (see above). Body mass and environment (i.e. marine or terrestrial) was included in this analysis as body size is a key driver of home range size (McNab, 1963;

Jetz et al., 2004) and the incorporation both marine and terrestrial species. PGLS analysis (β0+βmass+βenvironment+βmethodology) was then run across the 1000 trees including home range size (β0), body mass (βmass), environment (βenvironment, binary coded as 0 for terrestrial species and 1 for marine species) and estimation method (βmethodology, binary coded as 0 for MCP and 1 for KDE). The results from the phylogenetic regression demonstrate that methodology had no effect on home range size when comparing data on mammalian species from the marine and terrestrial environments (Table 2.1).

However, body mass and environment have a significant effect (Table 2.1) on home range size in mammals. This suggests that methodology has no effect on home range comparisons across a large number of species and physical environments.

Table 2.1 Model estimates and confidence intervals for the

β0+βmass+βenvironment+βmethodology model across 312 mammals. Results are from phylogenetic regressions computed for 1000 alternative resolutions of the mammalian phylogeny.

Model Term β(lower 95% CI, upper 95% CI) β0 -1.07 (-1.25,-0.89)* βmass 1.04 (0.93,1.16)* βenvironment 1.31 (0.54,2.08)* βmethodology 0.43 (-0.26,1.13) *Confidence intervals statistically different from zero and equivalent to p<0.05.

2.3.4 Analysis

I applied a model selection approach to test the level of support for alternative models of home range evolution. The best model was selected using second-order Akaike’s information criterion with a correction for sample size (AICc; Johnson & Omland, 2004).

The model with the lowest AICc value reflects the model with the highest support,

Chapter 2 – Mammalian Home Range

although any other model within two units of the lowest AICc value was also considered to be likely candidates (i.e. ∆AIC < 2.0; Burnham & Anderson, 2002). To compute AICc values, I applied each model as a phylogenetic generalized least squares (PGLS) regression using COMPARE ver 4.6b (Martins, 2004) to each of the

1000 trees (see previous section). Computed log-likelihood estimates from these analyses were converted into AICc values using equations presented in (Burnham &

Anderson, 2002). PGLS regression also computes an α parameter using maximum likelihood that estimates the extent phenotypic variation among species (e.g., mean body mass and associated home range size) is correlated to phylogeny. When α is close to 0, phenotypic differentiation among present-day taxa reflects the phylogenetic relationships among those species and is the product of Brownian evolution. When α is large (e.g., 15.50) phenotypic differentiation is unrelated to phylogeny and might be the outcome of adaptive evolution (Martins & Hansen, 1997; but also see; Revell et al.,

2008).

First, I assessed the level of support for the relationship between diet and home range among 429 species of terrestrial mammals relative to the level of variation in home range size generated solely by body mass or the evolutionary null model. These models were formulated as: (a) β0+βmass+βdiet_H+βdiet_O, where diet was scored as binary dummy variables with the resulting parameters β0, βdiet_H and βdiet_O corresponding to carnivores, herbivores, and omnivores, respectively (this was effectively a phylogenetic

ANCOVA); (b) β0+βmass, which predicted that differences in home range size among species were exclusively explained by body mass; and (c) β0, the evolutionary null model in which no predictor variable was included and therefore modelled variance in species home range size as the outcome of Brownian evolution and stochastic factors associated with evolutionary differentiation.

Chapter 2 – Mammalian Home Range

Second, I expanded the analyses to cover both marine and terrestrial species in order to examine the relationship between environment and home range, and the extent to which environment overrides the influence of diet. This analysis included new empirical data on several marine species (see ‘Database’ above) and covered 462 species.

Models were formulated as: (a) β0+βmass+βenvironment, where environment was entered as a binary variable in which species were coded as living in either a terrestrial (0) or marine (1) environment; (b) β0+βmass+βdiet_H+βdiet_O, the diet model which is described above for the terrestrial mammal analysis; (c) β0+βmass+βdiet_H+βdiet_O+βenvironment, where both diet and environment were included together in the same model; (d) β0+βmass, which assumed body mass was the only variable predicting home range size; and (e)

β0, the evolutionary null model described above for the terrestrial mammal analysis.

2.4 RESULTS

I found that diet and body mass together accounted for a portion of the variation in home range size observed among terrestrial mammals (Table 2.2, Fig. 2.1).

Carnivores, omnivores and herbivores demonstrated the predicted difference in intercept values. Carnivores showed the predicted large home ranges with an intercept that was significantly higher than omnivores and herbivores. Omnivores had the intermediate home range sizes that were significantly larger than herbivores and herbivores had the smallest home ranges across the three diet categories (Fig. 2.1).

However, where body mass accounted for 52% of the variance in home range size among terrestrial species (r = 0.72), the inclusion of diet improved the explanatory power of the model by 15% (r = 0.82). There was also a substantial improvement in the computed AICc value between the diet model and the body mass only model (∆AICc

40.6). The inclusion of phylogeny was important for these analyses as the estimated phylogenetic signal in home range size among species was high (the null model,

α=2.9; NB: values approaching 0 indicate high phylogenetic signal in species data).

Chapter 2 – Mammalian Home Range

That is, closely related species tended to share similar home range sizes and this could not be explained by phylogenetic inertia in body mass (i.e., α is a combined estimate of phylogenetic signal across all the variables entered into the model, and when body mass was included α was 8.36 suggesting that the level of phylogenetic signal exhibited by body mass was potentially lower than for home range size, otherwise the estimate would be similar or even lower than that estimated by the null model).

Table 2.2 Level of support for explanatory models of home range size evolution in land mammals. Results are from phylogenetic generalized least squares (PGLS) regression computed for 1000 alternative resolutions of the mammalian phylogeny. Model terms include herbivores (diet_H), omnivores (diet_O), body mass (mass) and intercept (0).

Model ∆AICc ∆AICc 95% CI PGLS Effect (upper, lower) α size (r) β0+βmass+βdiet_H+βdiet_O 0.0 NA 14.8 0.82 β0+βmass 40.6 34.8, 51.0 8.4 0.72 β0 281.5 268.5, 298.4 2.9 -

Chapter 2 – Mammalian Home Range

Figure 2.1 Home range size as a function of species body mass compared for terrestrial carnivorous (red circles), herbivorous (yellow circles) and omnivorous species (blue circles). Each datum represents a species mean value (n=429 species).

The solid red line is the phylogenetic regression of carnivorous mammals: logY=1.12(logX)-0.48, the dashed black line is the phylogenetic regression of omnivorous mammals: logY=1.12(logX)-0.94, while the solid blue line is the phylogenetic regression of herbivorous mammals: logY=1.12(logX)-1.45. Bottom right insert: intercept values and confidence intervals (CI) for terrestrial herbivores, omnivores and carnivores. Values were calculated from phylogenetic least squares

(PGLS) regression analyses applied to 1000 alternative resolutions of the mammalian phylogeny.

Chapter 2 – Mammalian Home Range

When the analysis was expanded to all mammals in both terrestrial and marine environments, the model that included environment, diet and body mass was by far the best-supported model and explained 74% of the variance in home range size among species (r = 0.86; Table 2.3). There was virtually no support for any of the alternative models (∆AICc > 10), although it was noteworthy that the second best model of diet and mass provided a similarly high level of explanatory power (72% variance explained; r = 0.85; Table 2.3). The majority of marine species are large and carnivorous (~95% carnivorous species) and this lead us to question whether the environment specifically influenced the best supported model or whether it was the inclusion of larger carnivores into the data set. To explore this, I examined the parameter estimates for the second best supported model which included only diet and body mass. These estimates confirmed the expected positive relationship between home range and body mass and showed that each of the diet categories were significantly different from one another: carnivores had the largest home ranges, omnivores had intermediate home ranges and herbivores had the smallest home ranges (Fig.2.2). That is, with the inclusion of the marine mammals, the primary effect seems to have been a divergence in intercept values between the carnivores and omnivores (compare Figs 2.1 and 2.2).

Chapter 2 – Mammalian Home Range

Table 2.3 Level of support for explanatory models of home range size evolution in mammals. Results are from phylogenetic generalized least squares (PGLS) regression computed for 1000 alternative resolutions of the mammalian phylogeny. Model terms include herbivores (diet_H), omnivores (diet_O), environment (marine or terrestrial), body mass (mass) and intercept (0).

Model ∆AICc ∆AICc 95% CI PGLS Effect (upper, lower) α size (r) β0+βmass+βdiet_H+βdiet_O+βenvironment 0.0 NA 14.6 0.86 β0+βmass+βdiet_H+βdiet_O 21.3 7.0, 44.3 14.1 0.85 β0+βmass+βenvironment 43.9 24.2, 61.8 8.9 0.79 β0+βmass 77.9 58.8, 100.8 7.2 0.73 β0 322.9 302.3, 354.2 2.4 -

Chapter 2 – Mammalian Home Range

Figure 2.2 Home range size as a function of species body mass compared for carnivorous (red circles), herbivorous (yellow circles) and omnivorous species (blue circles). Each datum represents a species mean value (n=462 species). The red line is the phylogenetic regression of carnivorous mammals: logY=1.19(logX)-0.29, the blue line is the phylogenetic regression of omnivorous mammals: logY=1.19(logX)-0.91, while the yellow line is the phylogenetic regression of herbivorous mammals: logY=1.19(logX)-1.47. Bottom right insert: intercept values and confidence intervals

(CI) for carnivores (C), omnivores (O) and herbivores (H). Values were calculated from phylogenetic least squares (PGLS) regression analyses applied to 1000 alternative resolutions of the mammalian phylogeny. Panthera and Macaca silhouettes are uncredited and the Loxodonta silhouette is by Steven Traver, all images are available for reuse under the Public Domain Mark 1.0 license.

Chapter 2 – Mammalian Home Range

To examine whether the environment has had any impact on home range size, I restricted the analyses to only carnivorous marine and terrestrial mammals and refitted the environment and body mass model (β0+βmass+βenvironment), the body mass only model

(β0+βmass) and evolutionary null model (β0). The environment model was the best supported model of the three, but only explained an additional 1.7% of the variance in home range size above the 72% explained by body mass only (Table 2.4). In general, however, marine carnivores have home ranges 1.2 times larger than terrestrial species of a similar mass (Fig. 2.3).

Table 2.4 Level of support for explanatory models of home range size evolution in carnivorous mammals. Results are from phylogenetic generalized least squares

(PGLS) regression computed for 1000 alternative resolutions of the mammalian phylogeny. Model terms include environment (marine or terrestrial), body mass (mass) and intercept (0).

Model ∆AICc ∆AICc 95% CI PGLS Effect (upper, lower) α size (r) β0+βmass+βenvironment 0.0 NA 11.6 0.86 β0+βmass 4.0 3.6, 4.6 11.0 0.85 β0 93.7 90.3, 101.5 1.5 -

Chapter 2 – Mammalian Home Range

Figure 2.3 Carnivore home range size as a function of species body mass compared for species occupying terrestrial (green circles) and marine (blue circles) environments.

Each datum represents a species mean value (n=134 species). The green line is the phylogenetic regression of terrestrial mammals: logY=1.2(logX)+0.39, while the blue line is the PGLS phylogenetic regression line of marine mammals: logY=1.2(logX)-

0.44. The river otter (9kg) and Southern humpback whale (32 000kg) are the smallest and largest marine mammal, while the masked shrew (4.2g) and lion (204kg) are the smallest and largest terrestrial mammals. Bottom right insert: intercept values and confidence intervals (CI) for terrestrial and marine mammals. Values were calculated from phylogenetic least squares (PGLS) regression analyses applied to 1000 alternative resolutions of the mammalian phylogeny. Eubalaena silhouette by Chris

Huh and available for reuse under the Creative Commons Attribution-ShareAlike 3.0

Unported license; Panthera silhouette is uncredited and is available for reuse under the

Public Domain Mark 1.0 license.

Chapter 2 – Mammalian Home Range

Overall, the results confirmed the overarching effect of body mass on mammalian home range size. In addition to body mass, diet and the physical environment both explained additional variance in home range size among species, but their influence was less than that of body mass. There was evidence to suggest that diet might have had a greater impact on home range size than the physical environment (19% additional variance explained for diet compared to 9% for the environment). In no instance was the evolutionary null model a compelling alternative explanation for differences in home range size among species, but home range size was found to exhibit a strong phylogenetic signal in all analyses (α =1.50-2.90; Tables 2.2-2.4).

2.5 DISCUSSION

Body mass was the principal predictor of home range size in mammals, accounting for

53-85% of the observed variation in home range size among species. The evolution of home range size appears to have been driven, for the most part, by the energetic requirements and costs or benefits associated with a given body mass. Energetic requirements, such as metabolic rate (kJ day-1), are positively correlated with body mass (Nagy, 2005). As large species have higher absolute energy needs, they must consume more resources and cover larger areas in order to gain enough resources to meet their energetic demands (McNab, 1963). In contrast, energetic costs associated with movement are greater in smaller species (Pontzer, 2007), which tends to constrain their movements and results in smaller home range sizes. In addition to the effects of body mass, I found the amount of meat included in diets was a second-order predictor of home range, followed closely by the physical environment (terrestrial versus marine).

However, while providing significant improvements in the level of support for models, there were varying effects of diet and physical environment on home range size. Both could only explain a further 1-19% of the variation in home range size among species beyond the effect of body mass. Such a small effect was surprising for diet as several

Chapter 2 – Mammalian Home Range

past studies have concluded diet as the key determinant of the home range-body mass relationship among terrestrial mammals (Swihart et al., 1988; Kelt & van Vuren, 2001).

This seems reasonable considering that what species eat has a direct impact on both the energetic requirements species and the type of costs incurred in obtaining and processing food resources. However, while the results confirm that diet has been a factor shaping mammalian home ranges (support was high for models that included a parameter for diet), it has nevertheless been far less influential. Previous studies of diet and home range use were based on datasets with limited species coverage across physical environments (i.e. marine and terrestrial), which can result in model bias and cause issues when these models are extrapolated over a broader range of species

(Sibly et al., 2012). Furthermore, phylogenetic information was not incorporated into previous analyses and the results showed that home range size does exhibit a large amount of phylogenetic signal (and this was not likely the by-product of phylogenetic inertia in body mass).

When the analyses were applied to all species, an apparent dual role of both diet and the environment seemed to be supported (Table 2.3). However, the precise relationship with the physical environment was unclear because the majority of marine mammals were large carnivores with very large home ranges. The specific relevance of the marine environment on home range evolution was therefore unclear. When the effect of diet was controlled for by focusing on carnivorous mammals across terrestrial and marine environments, I found that home ranges were significantly larger in marine environments for a given body mass than they were on land (Table 2.4), but the effect was arguably smaller than diet (environment only accounted for an additional 1.7% of the variation in home range size among species over body mass). The combination of living in an open environment, feeding on mobile resources and lower transport costs have resulted in the evolution of large home range sizes in marine carnivorous mammals (roughly 1.2 times larger), but the impact of these factors have been minimal 36

Chapter 2 – Mammalian Home Range

compared to the energetic requirements/costs driven by body mass. Unfortunately I was unable to examine the relationship between home range, diet and environment more closely for herbivores and omnivores, due to the predominance of carnivory within the marine environment.

Large carnivorous mammals have high daily energetic requirements and one strategy to meet these requirements is to utilise pack hunting (Carbone et al., 2007a). Pack hunting enables prey with large body mass to be hunted whilst minimising energy expended during the hunt. There is potential that pack hunting may alter home range size due to the increased density of individuals within an area. The data did not suggest any difference in home range size between carnivores that utilise pack hunting and those that do not (Appendix 2, Table S2.6 and Fig. S2.4). It would be ideal to have more complete home range information on whales. With the addition of more whale species, I would expect to see a different home range relationship with body mass, such as an increase in the scaling of home range size with body mass, resulting in extreme home range sizes with large body mass. This would be the case, especially with the inclusion of the various whale migrations, which cover a large area (e.g., the length of a migration (i.e. one direction, single track) can be greater than 5000 km, without accounting for the “width” of the home range (Alerstam et al., 2003). At present, there is a limited amount of tracking data on whales available, especially long term data that also includes their migration.

Like mammals, birds provide an interesting comparison to the home range size of marine mammals. Birds also live within a three dimensional environment (excluding the flightless species) and home range sizes in non-migratory birds tend to be larger than mammals for their size (Haskell et al., 2002). The literature suggests that body mass and food resources are the main drivers of bird home range size, similar to mammals.

Body mass was attributed to energy requirements, where large birds “require more 37

Chapter 2 – Mammalian Home Range

food per unit area than smaller birds” (Schoener, 1968). Also, birds with an increasing amount of vertebrate prey in their diet will have larger home range sizes due to lower densities of their prey compared to that of herbivores and omnivores (Schoener, 1968).

The effects of diet on the relationship between home range size and body mass in this study is likely to only detect large scale effects of resource use and distribution constraints, across the broad diet categories of carnivores, omnivores and herbivores.

This is due to resource use and resource distribution constraints having varied effects on home range size. Changes in the type of resources used and their abundance can vary on different temporal scales. For example, resource distribution and availability in the Arctic are highly seasonal, with a distinct set of resources available during winter versus summer. This would have a strong effect on home range size of individuals living in this region (e.g. polar bears; Ferguson et al., 1999). However, an individual may also change which resources they use on a much smaller temporal scale, such as on a day to day. Shifts in resource use or distribution on this small scale are unlikely to be detected in home range analyses due to home range size being calculated over longer periods (i.e. generallyseasonally or yearly). Small scale studies with a focus on a single species and a more direct approach, such as state-space models (Bestley et al., 2013), would be ideal to investigate dietary effects on these shorter periods.

The sample sizes were biased towards terrestrial mammals despite the data including all available information on home range size for marine species (Fig. 2.1). This partly reflects the difference in the number of mammalian species on land versus in the water that were included in the analyses. Calculating home range for marine species is difficult because of issues associated with tracking marine species (often requiring satellite tracking). For example, home ranges are often calculated over shorter tracking periods in marine species compared to those on land. As tracking technology improves, and methodologies become more sophisticated for estimating home ranges 38

Chapter 2 – Mammalian Home Range

in marine species, the number of species for which home range information is available should increase. Nevertheless, mammalian species diversity in marine environments is much lower than on land, so this bias in sampling partly reflects biological reality and this will not change with improved methods of home range estimation.

It should also be noted that the home range values of marine species used in this study may be conservative, as they were measured in two dimensions, but marine mammals use a three dimensional environment (Pawar et al., 2012). However, Carbone et al.

(2007b) investigated abundance scaling in mammals in three dimensional environments, and their models predict -2/3 scaling similar to abundance scaling within two dimensional environments. As there is a relationship between animal abundance scaling and home range size (Jetz et al., 2004), we may expect to see a similar pattern in the scaling of home range size in mammals. The effect of dimensions of environments would be an interesting concept to examine in a future study, using similar mathematical methods to those used in Carbone et al. (2007b).

It is unlikely that differences in home range size across the marine and terrestrial environments are driven by how species are related (i.e. collinearity between environment and relatedness). Marine mammals are interspersed across the mammalian clade (see Fig. S2.1). For example, within carnivora sit both marine (e.g. pinnipeds, Ursus maritimus and Enhyrda lutris) and terrestrial (e.g. canidae, mephitidae, procyonidae) representatives.

2.6 CONCLUSION

Home range is a complex behaviour influenced by a range of variables, including body mass, diet and environment. My aim was to clarify the role and extent to which these variables impact home range size in mammals. I highlight that across the mammalian

Chapter 2 – Mammalian Home Range

radiation the evolution of home range has been driven by a hierarchy of variables, but some variables have clearly been more influential than others. The key explanatory variable of home range size was body mass, followed by the secondary variables of diet and then environment. To better understand the evolution of mammalian home range size we need to investigate the proximate mechanisms (here, proximate mechanisms are the physiological and morphological drivers) of its relationship to body size. Furthermore, because the effects of diet and environment on home range use were small, it would be prudent to reconsider past assumptions regarding the influence of differing resource bases (meat versus plant), modes of transport (swimming versus walking and running) and altered physical properties (water versus air) as underlying mechanisms of home range use.

Broad models developed using information from many species, such as the allometric model of home range size (Jetz et al., 2004; this study), are often used to guide conservation and management strategies. It is critical then that the underlying assumptions of these models are biologically appropriate. With previous models focusing exclusively on select groups of species (e.g. terrestrial mammals), I have developed an important amendment to these models to show that home range drivers once thought as highly influential are not so. I have demonstrated that by using an integrative model that incorporates an inclusive list of predictor variables, species and phylogenetic information, our knowledge of home range patterns across mammals can be significantly enhanced.

Chapter 3 Examining the prey mass of terrestrial

and aquatic carnivorous mammals:

minimum, maximum and range.

This chapter has been published in PLoS ONE (Appendix 3): Tucker, M.A. and Rogers, T.L. (2014) Examining the prey mass of terrestrial and aquatic carnivorous mammals: minimum, maximum and range. PLoS ONE 9(8): e106402.

3.1 SUMMARY

Predator-prey body mass relationships are a vital part of food webs across ecosystems and provide key information for predicting the susceptibility of populations of carnivores to extinction. Despite this, there has been limited research on the minimum and maximum prey size of mammalian carnivores. Without information on large-scale patterns of prey mass, we limit our understanding of predation pressure, trophic cascades and susceptibility of carnivores to decreasing prey populations. The majority of studies that examine predator-prey body mass relationships focus on either a single or a subset of mammalian species, which limits the strength of our models as well as their broader application. I examine the relationship between predator body mass and the minimum, maximum and range of their prey’s body mass across 108 mammalian carnivores, from weasels to baleen whales (Carnivora and Cetacea). I test whether mammals show a positive relationship between prey and predator body mass, as in reptiles and birds, as well as examine how environment (aquatic and terrestrial) and

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

phylogenetic relatedness play a role in this relationship. I found that phylogenetic relatedness is a strong driver of predator-prey mass patterns in carnivorous mammals and accounts for a higher proportion of variance compared with the biological drivers of body mass and environment. The results show a positive predator-prey body mass pattern for terrestrial mammals as found in reptiles and birds, but no relationship for aquatic mammals. The results will benefit our understanding of trophic interactions, the susceptibility of carnivores to population declines and the role of carnivores within ecosystems.

3.2 INTRODUCTION

Examining patterns in predator-prey relationships provides information on predation pressure (e.g. on specific size guilds; Hayward & Kerley, 2005; Hayward, 2006), the impact of decreasing prey species on predators (Novaro et al., 2000) and the potential for trophic cascades and the collapse of prey populations (Fortin et al., 2005; Daskalov et al., 2007; Johnson et al., 2007). However, previous research on predator-prey body mass relationships in mammalian carnivores has focused upon the mean mass of prey, largely ignoring the minimum and maximum body mass of prey consumed by predators. It is important to include the minimum, maximum and range of prey mass consumed as it allows the examination of the upper and lower limits of carnivore prey selection. In addition, prey selection provides information such as energetic requirements (e.g. intake rates), which is often used for predicting the susceptibility of carnivores to population declines, the role of carnivores within ecosystems and community structure (Carbone et al., 2007a).

Larger-sized predators can utilise a wide variety of prey types because they have large home ranges (Tucker et al., 2014) that provide access to a diversity between prey species (Ottaviani et al., 2006), as well as a wide gape size that allows them to feed on

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

prey of a variety of sizes. Despite this, large predators tend to eat larger-sized prey

(Carbone et al., 2007a). It is not always profitable for large species to feed on small- sized prey due to capture inefficiency as it is costly to pursue small-sized prey in relation to the small energetic benefit gained (Brose, 2010). The minimum and maximum size of prey should scale positively with predator body mass, resulting in there being no relationship between predator body mass and diversity of prey size (i.e. dietary niche breadth - DNB) (Brandl et al., 1994; Costa et al., 2008). However, if maximum prey size scales positively with predator mass and minimum prey size does not this will result in a larger diversity of prey size for larger predators (i.e. wider DNB).

Our knowledge of mammalian broad-scale patterns of prey-size range is limited. There has been limited work investigating the prey mass of African predators and its effect on the system (Sinclair et al., 2003). However, this work largely focuses upon predation pressure on prey species, particularly herbivorous mammals. The remaining predator- prey body mass research is based on the mean prey mass of predators (Carbone et al., 2007a; Riede et al., 2011). Investigations into other animal groups include predatory fish (Scharf et al., 2000; Costa, 2009), reptiles (King, 2002; Costa et al.,

2008) and birds (Brandl et al., 1994), where there is a general consensus that there is a positive relationship between predator body mass and prey minimum, maximum and range in mass, except for fish where the evidence is conflicting (positive or no relationship between predator mass and minimum prey mass).

Using minimum, maximum and range of prey mass for 108 carnivorous mammals from the orders Carnivora and Cetacea, I investigated the nature of the relationship between carnivore body mass and prey body mass and how living in either the marine or terrestrial environment has impacted this relationship. This study has two objectives: first to examine the influence of physical environment on minimum, maximum and range of prey mass; and second to investigate the influence physical environment has

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

had on the distribution of minimum, maximum and range of prey mass. Based on previous research (Carbone et al., 2007a; Costa et al., 2008), I predict that prey mass

(minimum, maximum and range) will be positively correlated with predator body mass for terrestrial carnivores. However, for marine carnivores there could be two possible outcomes: first, prey mass (minimum, maximum and range) could be positively correlated with body mass similar to terrestrial carnivores and other marine non- mammalian predators (Costa, 2009); or second, there could be no relationship between prey mass (minimum, maximum and range) and predator body mass. No relationship between predator mass and prey mass is a possibility due to the high abundance of small species that form dense aggregations in aquatic environments

(e.g. krill or fish) which lead to an increase in the encounter rates between aquatic predators and these small prey species. With both small and large predators exposed to these abundant food resources, this would result in both small and large predators feeding upon small prey species and therefore suggest no relationship between predator mass and prey mass in aquatic systems.

By examining the moments (e.g. mean, mode, skewness etc.) of the prey mass distributions, we can gather information on how the mass of the prey consumed by carnivorous mammals differs or is similar across different environments. This information is important for building our knowledge of predator-prey relationships and the drivers behind these relationships.

3.3 MATERIALS AND METHODS

3.3.1 Database

Data were collated on the minimum and maximum prey mass (kg) consumed by 108 carnivorous mammal species (Appendix 4). Table 3.1 provides a summary of the orders and families sampled. Prey mass range was calculated by subtracting the

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

minimum prey mass from the maximum prey mass. Mean body mass (kg) was also collected for these 108 predator species using the database PanTHERIA (Jones et al.,

2009). All carnivores were classified as terrestrial or aquatic, where aquatic species forage in water to survive (e.g. foraging) and terrestrial species forage on land to survive. All values including carnivore mass and prey mass were log10 transformed prior to all analyses.

Table 3.1 Summary of the orders and families included in the study sample.

Order Family Carnivora Canidae Felidae Herpestidae Hyaenidae Mephitidae Mustelidae Otariidae Phocidae Procyonidae Ursidae Viverridae Cetacea Balaenidae Balaenopteridae Cetotheriidae Delphinidae Eschrichtiidae Kogiidae Monodontidae Phocoenidae Physeteridae Pontoporiidae Ziphiidae

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

3.3.2 Phylogenetic Information

I required a single phylogenetic tree to examine minimum prey mass, maximum prey mass and prey mass range in carnivorous mammals. Phylogenetic information was obtained from the Fritz et al. (2009) mammal supertree containing 5,020 species and branch lengths proportional to time since divergence. This tree was pruned using

Mesquite ver 2.74 (Maddison & Maddison, 2010) to create the tree (n=108) based on the data in the database. Sotalia guianensis (Guiana dolphin) was positioned within the pruned tree based on the topologies of Caballero et al. (2008). Due to insufficient phylogenetic information, the Fritz et al. (2009) tree included soft polytomies where more than two species diverge at a single point in time. To resolve the polytomies, I used a semi-automated polytomy resolver for dated phylogenies (Kuhn et al., 2011).

The polytomy resolution involved two steps; 1) R 3.0.2 (R Core Team, 2013) was used to create an XML input file containing topology constraints and input commands for

BEAST, and 2) the XML input file was run through the program BEAST 1.8 (Drummond et al., 2012) which uses a Bayesian Markov chain Monte Carlo (MCMC) algorithm to permute the unresolved relationships within the tree based on the birth-death model.

This produced 1,000 alternative phylogenetic trees to be used for the phylogenetic comparative analyses and the ancestral state reconstructions.

3.3.3 Analyses

Model selection using second-order Akaike’s information criterion with a correction for sample size (AICc) and phylogenetic generalised least squares (PGLS) regression

(see Analysis section in Chapter 2) were used to examine alternative models of prey mass. I performed three separate PGLS analyses for minimum prey mass, maximum prey mass and range of prey mass respectively. For each I examined the level of support of the relationship between prey mass (minimum, maximum or range), carnivore body mass and environment across 108 species. The models were

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

formulated as; (a) β0+βmass*βenvironment, where environment was coded as “terrestrial” or

“aquatic” and included an interaction term between carnivore mass and environment;

(b) β0+βmass, which assumed body mass was the only variable predicting prey mass; (c)

β0, the evolutionary null model in which no predictor variable was included and subsequently modelled variance in species prey mass as the outcome of Brownian evolution (i.e. under Brownian motion, trait evolution proceeds as a random walk through trait space and Brownian motion has been proposed as a null model of evolution for testing hypotheses of trait evolution (Felsenstein, 1985). The PGLS analyses were conducted using the CAPER package in R (Orme et al., 2012)

To examine the effect of phylogeny and ecology on the minimum and maximum prey mass of carnivores, I ran variance component analyses (Pinheiro & Bates, 2000).

Variance was examined among species, focusing on the contribution of order, family, genus, mass and environment (aquatic or terrestrial). Variance components analysis was performed using the lme4 package (Bates et al., 2013) in R version 2.13.2.

To gain an understanding on the shape of the prey mass distributions across species and environments, I extracted the descriptive statistics including the mean, median, mode, range, minimum, maximum, standard deviation (S.D.), skewness and kurtosis.

Skewness measures the degree of asymmetry of a distribution. If the skewness value is positive the data have a right skewed distribution and a negative value suggests left skewed data. Kurtosis measures height of the curve relative to its standard deviations.

Data with a peaked distribution with values around zero (i.e. normal distribution) have a positive kurtosis value, whereas negative values between 0 and -1 implies that the data have a flat distribution and values lower than -1.5 suggest a bimodal distribution.

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

3.4 RESULTS

3.4.1 Phylogenetic Generalized Least Squares Regression

The model including an interaction between body mass and environment (mass- environment) was the best supported model for minimum prey mass, maximum prey mass and prey mass range (Table 3.2). However, for the maximum prey mass and prey mass range there was less than 2 ∆AIC units between the mass model and the mass-environment model, suggesting that these models are equally supported. In both cases, the addition of environment explained a limited amount of additional variance

(3% for both maximum prey and prey range) however for minimum prey mass, environment explained an additional 7% of variance. The phylogenetic signal (λ) was consistently high for the mass model for minimum, maximum and prey size range

(>0.7). Lambda however, was mixed for the mass-environment models, where it was low (<0.5) for the maximum prey and prey range size, it was higher (0.62) for the minimum prey mass.

Table 3.2 Level of support for explanatory models of prey mass evolution in carnivorous mammals. Results are from phylogenetic least squares (PGLS) regression analyses computed for 1000 alternative resolutions of the mammalian phylogeny.

Model terms include carnivore body mass (βmass), environment either aquatic or terrestrial (βenvironment) and the intercept (β0).

Prey mass Model ∆AICc ∆AICc 95% CI Lambda Effect (upper, lower) size (r) Minimum β0+βmass* βenvironment 0.0 NA 0.62 0.28 β0+βmass 5.8 4.99, 6.58 0.71 0.10 β0 5.5 4.78, 6.28 0.64 NA Maximum β0+βmass* βenvironment 0.0 NA 0.48 0.28 β0+βmass 0.9 0.04, 2.07 0.74 0.23 β0 4.8 4.23, 5.29 0.57 NA Range β0+βmass* βenvironment 0.0 NA 0.30 0.28 β0+βmass 1.6 0.23, 3.1 0.73 0.23 β0 5.3 4.54, 5.84 0.57 NA

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

I found there was no significant difference (confidence intervals overlap 0) in intercept between terrestrial and aquatic carnivores for minimum (CI -2.22, 1.54; Fig. 3.1A), maximum (CI -2.48, 1.47; Fig. 3.1B) and range of prey mass (CI -2.70, 1.00; Fig. 3.1C).

There was a significant difference (confidence intervals do not overlap 0) in slope between terrestrial and aquatic carnivores for minimum (CI 0.37, 1.93), maximum (CI

0.24, 1.94) and range of prey mass (CI 0.49, 2.16). Despite the negative slopes of the aquatic regression lines, these values were not significantly different from 0 for minimum, maximum or prey mass range. The terrestrial regression slopes were positive and significantly different from 0 for minimum, maximum or prey mass range

(Fig. 3.1A, B and C).

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

Figure 3.1 Minimum prey mass (A), maximum prey mass (B) and prey mass range (C) as a function of carnivore body mass compared for terrestrial (green circles) and aquatic (blue circles) species. Each datum represents a species mean value. The solid green line is the phylogenetic regression of terrestrial mammals: (A) log(Y)=1.13log(X)- 3.3, (B) logY=1.12(logX)-1.01 and (C) logY=1.26(logX)-0.87. The solid blue line is the phylogenetic regression of aquatic mammals: (A) logY=-0.03(logX)-2.96, (B) logY=0.11(logX)+-0.50 and (C) logY=-0.07(logX)-0.02. Insert: intercept values and confidence intervals (CI) for aquatic (A) and terrestrial (T) species. Values were calculated from phylogenetic least squares (PGLS) regression analyses applied to 1000 alternative resolutions of the mammalian phylogeny. Error bars represent CI’s for the intercept values and are calculated using the standard error (SE) multiplied by 1.96.

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

3.4.2 Variance Components Analysis

Order, family and genus explained the maximum proportion of variance in prey mass of carnivores (58-73%; Table 3.3), providing additional support for the strong influence of phylogenetic relatedness on the prey mass consumed by carnivorous mammals. Body mass of the carnivore explained a relatively large degree of variance (32-39%), where environment had little influence over the mass of prey consumed (<0.01-3%).

Table 3.3 Variance components analysis of prey mass across 108 carnivorous mammal species. Categories include minimum prey mass (smallest prey size consumed), maximum prey size (largest prey size consumed) and range of prey mass

(maximum minus minimum prey mass).

Prey Mass Variance Variance Total Variance Source Component Explained (%) Minimum Total 3.17 100 Order 0.18 5.65 Family 1.13 35.65 Genus 0.52 16.65 Mass 1.23 38.83 Environment 0.11 3.43 Maximum Total 3.31 100 Order 0.43 13.79 Family 0.19 6.26 Genus 1.64 52.60 Mass 1.05 33.70 Environment <0.01 <0.01 Range Total 3.50 100 Order 0.40 11.33 Family 0.17 4.88 Genus 1.81 51.69 Mass 1.12 31.97 Environment <0.01 <0.01

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

3.4.3 Descriptive Statistics

Examining the descriptive statistics, the minimum prey mass distribution across all mammals is positively skewed (skew = 0.11), while maximum and range of prey mass is negatively skewed (-0.40 to -0.37; Table 3.4). The prey mass data have a normal distribution for minimum, maximum and range of prey mass with kurtosis values between 0.62 and 1.18 (Table 3.4).

Table 3.4 Descriptive statistics for the prey mass distributions across 108 carnivorous mammals. Minimum is the minimum prey mass consumed, maximum is the maximum prey mass consumed and range is the total range of prey mass consumed (maximum minus minimum).

Prey Skew Kurtosis Median Mean Mode S.D. Min Max Range Mass Minimum 0.11 0.62 -2.92 -2.71 -3.22 1.64 -7.52 1.65 9.18 Maximum -0.37 1.18 0.13 0.16 0.64 1.73 -6.10 4.11 10.21 Range -0.40 1.18 0.08 0.10 -1.30 1.78 -6.11 4.11 10.23

When examining the aquatic and terrestrial prey mass distributions, I found that aquatic carnivores tend to feed on smaller-sized prey, with mean prey mass for minimum, maximum and the range being lower than terrestrial carnivores (Fig. 3.2, Table 3.5 and

3.6). Aquatic carnivore prey mass distributions are all negatively skewed (-0.39 to -

0.63), but in terrestrial carnivores negatively-skewed distribution are only seen for maximum and range prey mass distributions (-0.25 and -0.35). The prey mass distribution for terrestrial carnivores is relatively flat as suggested by the negative kurtosis values (-0.25 to -0.75). For aquatic species, the prey mass distributions are normally distributed with kurtosis value between 0.88 and 3.17. Additionally, aquatic carnivores feed on prey spanning 12 900 kg, compared with 2 700 kg for terrestrial carnivores. 52

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

Figure 3.2 Distributions of the minimum prey mass for (A) terrestrial carnivorous mammals (white bars) and (B) aquatic carnivorous mammals (grey bars), and the maximum prey mass for (C) for terrestrial carnivorous mammals (white bars) and (D) for aquatic carnivorous mammals (grey bars). Silhouettes by uncredited and Chris Huh, available for reuse under the Public Domain Mark 1.0 license (Panthera) and the

Creative Commons Attribution-ShareAlike 3.0 Unported license (Eubalaena).

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

Table 3.5 Descriptive statistics for the prey mass distributions across 51 carnivorous terrestrial mammals. Minimum is the minimum prey mass consumed, maximum is the maximum prey mass consumed and range is the total range of prey mass consumed

(maximum minus minimum).

Prey Skew Kurtosis Median Mean Mode S.D. Min Max Range Mass Minimum 0.46 -0.25 -2.64 -2.23 -3.22 1.66 -5.61 1.65 7.27 Maximum -0.25 -0.75 0.54 0.70 2.74 1.66 -3.12 3.43 6.55 Range -0.35 -0.43 0.51 0.64 2.79 1.71 -3.78 3.43 7.22

Table 3.6 Descriptive statistics for the prey mass distributions across 57 carnivorous aquatic mammals. Minimum is the minimum prey mass consumed, maximum is the maximum prey mass consumed and range is the total range of prey mass consumed

(maximum minus minimum).

Prey Skew Kurtosis Median Mean Mode S.D. Min Max Range Mass Minimum -0.39 0.88 -3.22 -3.12 -3.30 1.52 -7.52 0.53 8.05 Maximum -0.59 3.17 -0.11 -0.33 0.64 1.65 -6.10 4.11 10.21 Range -0.63 3.10 -0.11 -0.36 -1.30 1.68 -6.11 4.11 10.22

3.5 DISCUSSION

The best model of prey mass evolution includes both carnivore mass and environment, although environment explains a small percentage (~8%) of variance in prey size. In spite of this, aquatic and terrestrial mammalian carnivores have different relationships suggesting different optimal foraging strategies. Aquatic mammalian carnivores have no relationship between prey (neither minimum nor maximum) and predator body mass, unlike terrestrial mammalian carnivores where there is a positive prey-predator

(both minimum and maximum) body mass relationship. In contrast to terrestrial predators, larger marine carnivores do not have to actively pursue prey with large body 54

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

mass to meet their energetic requirements (Carbone et al., 2007a). The abundance of small-sized prey in aquatic and marine environments (Fig. 3.2) is likely to have driven these patterns in marine carnivores. As well as prey availability, it is also important to note the effect of dimensionality on predator-prey relationships and consumption rates.

In 3D environments, it has been demonstrated that consumption rates are higher, not only the baseline rates but also the scaling exponent (Pawar et al., 2012). This not only has an impact on predator-prey relationships (e.g. larger consumer-resource body mass ratios) but also the strength of interactions between trophic levels and the stability of the community.

In addition to the effect of differences in prey availability and dimensionality, there are differences in body size patterns across aquatic and terrestrial carnivores. Marine mammals tend to have larger body sizes compared to terrestrial mammals because of the relaxation of biomechanical constraints and increased thermoregulatory constraints

(Smith & Lyons, 2011). This has an effect on the predator-prey relationships, which tend to be more accentuated in the marine environment due to this disparity in body size between predators and their prey. This has been illustrated by the presence of larger predator-prey mass ratios in aquatic environments (Brose et al., 2006b; Riede et al., 2011).

The lack of relationship between prey mass and predator mass could be because predator morphology is a large driver behind the prey choice of aquatic mammalian carnivores. Morphology is a limiting factor for aquatic carnivores physically unable to capture larger-sized prey (e.g. altered morphology of appendages to aid with swimming rather than grasping). Also, the combination of gape size and bite force in aquatic systems is believed to impact the number of trophic levels that predators can feed from

(Hairston & Hairston, 1993), where larger species often have a high trophic position

(Andersen et al., 2009b). When mammals feed on large prey, they tend to have a

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

larger gape and a stronger bite force (Santana et al., 2012). For example, leopard seals have large muscles for mastication (e.g. masseter mass) as they feed on a mixture of prey including large and small species, compared to a crabeater seals that have a similar gape, yet smaller muscles of mastication as they predominantly feed on small prey species (Jones et al., 2013). Dentition is also likely to be important as carnivores with highly overlapping ranges often have different tooth morphology driven by competition for resources (Jonathan Davies et al., 2007). In the aquatic system mammals have specialised feeding morphology including keratinized baleen plates for filter feeding (mysticete whales), multi-cuspidate interlocking teeth for krill sieving (e.g. crabeater and leopard seals), simple teeth with reduced serration for catching fish

(piscivory e.g. dolphins), reduced teeth (e.g. Ross seal), rounded teeth (e.g. walrus) for eating hard-shelled molluscs or even the loss of teeth (e.g. sperm whale and beaked whales) for eating soft-bodied molluscs. Having specialised dentition can minimise resource competition; however it can leave these specialist carnivores vulnerable to higher extinction pressure if their prey populations were to collapse or become extinct

(Renaud et al., 2005; Dell'Arte et al., 2007).

The addition of environment into the PGLS models explains greater variance and has the highest phylogenetic signal only for minimum prey mass and not for models of maximum or range in prey mass. This suggests there are differences between aquatic and terrestrial mammalian carnivores in the patterns of minimum prey body mass only.

There is a great number of large aquatic mammalian carnivores feeding on small-sized prey whereas all large terrestrial mammalian carnivores are tied to feeding upon large- sized prey to maximise their energetic intake while minimising their expenditure

(Carbone et al., 2007a). In aquatic environments, particularly the marine system, the combination of the high abundance of prey below 500g, and the schooling nature of these prey, makes it efficient for large carnivores to switch to feeding on smaller prey.

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

The combined results from the PGLS (phylogenetic signal; λ) and the variance components analysis suggest that phylogenetic relatedness is a major influence of prey mass distribution patterns across carnivorous mammals. The driving factor behind this result are the baleen whales, as they represent closely related species that share a common feeding strategy. This group represents some of the largest species today (up to 200 tonnes) and they feed on some of the smallest prey species (e.g. zooplankton).

Baleen whales consist of species from Balaenopteridae and Balaenidae, and all use filter feeding to capture their prey. There are also other feeding strategies, such as pack hunting, that are generally shared across taxonomic levels (i.e. at the family and genus level).

The most likely reason behind the scatter present in the relationship between body mass and prey mass of terrestrial carnivores (Fig. 3.1A-C), is related to carnivore feeding strategy. Terrestrial carnivores follows two feeding strategies: large prey consumers or small prey consumers (Carbone et al., 1999; Carbone et al., 2007a).

Terrestrial carnivore species weighing 21.5 kg or less feed on invertebrates and small vertebrate prey species (<10 kg) (Carbone et al., 1999). Above the 21.5 kg threshold, carnivores must shift to feeding on large vertebrate prey to meet their energetic requirements (Carbone et al., 1999). Several carnivore species that feed upon large vertebrate prey have evolved cooperative or pack hunting strategies, which confer several benefits. One benefit of hunting in a pack is the minimisation of the energy expended whilst hunting, but also maximising the size of the prey captured and prey capture efficiency (Creel, 1997; Rasmussen et al., 2008). An increase in the size of the prey captured, energetic intake and hunting success also follows an increase in the number of individuals within the group (Rasmussen et al., 2008). Another advantage of hunting cooperatively is that individuals may gain other benefits including increased body size or reproductive success. For example, individual male fossa (Cryptoprocta

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

ferox) that forage in groups tend to have larger body size, which also enables increased competition and mating success (Lührs et al., 2013).

There are various drivers influencing the patterns of prey mass consumed by carnivorous mammals. The size of prey chosen by carnivores is driven by the trade-off between energy acquisition and expenditure, the available ecological niches and the dimensions of the environment (Pawar et al., 2012). Foraging animals minimise their energetic costs while maximising energetic gains by moving towards an optimal foraging strategy. As different species evolved different foraging strategies, driven by their evolutionary history and environmental influences, this shapes the patterns of prey mass that are consumed by carnivores. Additionally, the mass of prey utilised by carnivores is influenced by the ecological niches available to them and the resource encounter rate, both of which have an effect on the foraging strategy and the prey availability (Moritz et al., 2008; Bromham et al., 2012; McCain & King, 2014).

Carnivore energetic costs and prey density both influence the minimum prey mass consumed. Carnivores tend to feed on prey above a certain mass due to the increasing inefficiency of feeding on small prey, because a low capture rate will arise when carnivores forage on prey much smaller than themselves (Brose, 2010). However, this can be overcome in instances where prey species are in high densities, as illustrated by marine carnivores (e.g. baleen whales) who can survive feeding upon prey less than

1 g (e.g. krill and other invertebrates). This is further highlighted by the lower minimum prey mass of aquatic carnivores compared to that of terrestrial carnivores (Fig. 3.2).

At the other end of the scale, maximum prey mass is driven by morphological constraints (i.e. gape and locomotion) and energetic costs. A carnivore feeding on prey considerably larger than their own mass will result in a mismatch of reaction time, where the carnivore will respond at a slower rate than that of the prey and will end with

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

the prey escaping and the carnivore in an energetic deficit (Brose, 2010). Additionally, while it would be ideal for all carnivores to feed on large-sized prey species (provided that all carnivores could successfully capture large prey), it would be considerably costly from an energetic perspective, not to mention the increased amount of time spent processing and ingesting the prey (Carbone et al., 2007a; McCain & Colwell,

2011).

Modal prey mass is influenced by environmental drivers. Based on the data used in the study, the minimum prey mass range (0.0001 to 0.01 kg) is the most commonly utilised by carnivorous species from the aquatic and terrestrial environments. The type of prey included within this weight range are invertebrates (aquatic and terrestrial), small mammals, fish and squid. The most common maximum prey range differs between environments, with terrestrial carnivores predominantly feeding on prey between 1 to

100 kg (i.e. small and large mammal prey), compared with 0.01 to 1 kg for aquatic carnivores (i.e. invertebrate, squid and fish prey). With the prey-weight categories of

0.0001 - 0.01kg, 1 - 100 kg and 0.01 - 1 kg being the most abundant, this suggests that feeding within these ranges is a common foraging strategy across carnivores.

Additionally, modal prey mass will also be driven by the characteristics of the environment, where primary productivity and trophic interactions will shape the size of prey available and the abundance of these prey species. For example, productivity within the marine environment is driven by small, single-celled organisms, allowing higher availability of productivity to consumers and higher predator-prey body mass ratios (Riede et al., 2011).

Chapter 3 – Examining the Prey Mass of Carnivorous Mammals

3.6 CONCLUSION

In summary, carnivorous mammals within my sample differ in the size of prey they consume and this is influenced by a suite of factors including phylogenetic relatedness, carnivore body mass, the characteristics of the environment in which the carnivore resides, and has evolved within, as well as carnivore energetics. Whilst phylogenetic relatedness and carnivore body mass are the dominant drivers of the prey mass consumed by mammals, the physical environment has a role in the minimum-size prey that can be consumed. Previous research has shown that there is a positive relationship between carnivore mass and the mass of their prey. However, I have demonstrated that this is not the case for aquatic mammalian carnivores. Differences in environmental characteristics including primary productivity and food-web structure are driving the differences in prey mass consumed across aquatic and terrestrial carnivores.

Optimal foraging strategies in mammalian carnivores differ not only across species but also physical environments, which needs to be accounted for when thinking about carnivore behaviour. Gaining a better understanding of the relationship between mammalian carnivores and their prey, predator strategies and the factors driving these patterns, will aid with predictions of carnivore susceptibility to population declines and the role of carnivores within ecosystems.

Chapter 4 The cost of carnivory revisited

4.1 SUMMARY

Predator-prey relationships play a key role in the evolution and ecology of carnivores, as well as the structure of ecosystems. An understanding of the relationship between predators and their prey and how this differs across species and environments provides information on how carnivorous strategies have evolved and how they may change into the future with environmental changes. Prey consumed by mammals is size-dependent, with terrestrial carnivores above 21kg feeding on larger-sized prey to meet increasing absolute energetic requirements. However, previous studies did not consider marine carnivores. This is an important omission because it is likely that an aquatic lifestyle has altered the predator-prey body-size relationship due to larger body sizes (up to 200 tonne), higher thermoregulation costs and differences in prey distributions. I reassess the predator-prey body-size relationship across mammalian carnivores, with the inclusion of marine mammals, to determine how the predator-prey body-size relationship relates to the energetic requirements in different environments and how it shapes the feeding strategies adopted by different predatory mammals. I compiled data on prey mass, daily energetic intake and daily energetic expenditure from the literature. Using a phylogenetic framework and piecewise regression, I investigated the relationship between predator-prey size, and energetic requirements across 107 carnivorous mammals, including 51 terrestrial and 56 marine mammals. I found that marine and terrestrial carnivores have evolved opposing predatory

Chapter 4 – The Cost of Carnivory Revisited

behaviours likely to minimise energy expenditure while maximising energy intake.

Large marine carnivores (>11 000 kg) feed on prey equal to 0.01% of the carnivore’s body size on average, compared to 45% or greater in large terrestrial carnivores (>21 kg). Differences in primary productivity and ecosystem structure across the marine and terrestrial environments seem to have altered the type of prey available to mammals, which has subsequently led to the evolution of novel foraging strategies. The results provide important insights into the selection pressures early marine mammals may have faced that ultimately led to the evolution of a range of feeding strategies (e.g. bulk feeding) and other behaviour (e.g. extreme diving capabilities), and may also explain the massive body sizes many marine mammals have obtained.

4.2 INTRODUCTION

There is a strong link between physiology and behaviour in carnivorous mammals. For example, much of the variation in ranging behaviour of carnivorous mammals can be attributed to the energetic requirements of being a carnivore and the distribution of preferred prey (Kelt & van Vuren, 2001; Carbone et al., 2005). Carnivore body mass is a strong predictor of average prey size in terrestrial environments, where small carnivores less than 14.5-21 kg feed on small prey and carnivores above this weight range feed on large prey (>45% of their own body weight; Carbone et al., 1999). The population dynamics of predators is impacted by prey choice and the population fluctuations of those prey species. This is because a drop in prey density will result in a drop in carnivore density, especially in large-sized predator species who require large quantities of prey to survive (Carbone & Gittleman, 2002; Carbone et al., 2011).

Carnivorous mammals generally have low population densities and slow growth rates, which make them highly susceptible to population declines whenever changing environmental conditions start to impact the distribution of their prey (Cardillo et al.,

Chapter 4 – The Cost of Carnivory Revisited

2005; Davidson et al., 2009; Carbone et al., 2011; Angerbjörn et al., 2013). The trophic importance and key role of carnivores within their ecosystems (e.g. indirect influence on carbon storage and disease regulation; Miller, 1996), renders them an important group to investigate predator-prey interactions on a global scale.

Information on prey choice in mammals and the evolutionary processes that have led to these patterns is important for two reasons. First, building our knowledge of carnivore behaviour is essential for linking patterns and processes of ecosystem structure and function, foraging patterns and predator-prey interactions (Gaston &

Blackburn, 1996; Carbone et al., 2011). For example, examining the behaviour of wolves within Yellowstone National Park has illustrated the direct and indirect impacts of their behaviour on this ecosystem, including the population dynamics of herbivorous mammals, plants and scavenger species (Brown et al., 2002; Warton et al., 2012;

Banbury & O'Meara, 2014). Second, with improved information on carnivore behaviour we can develop broad-scale models of predator-prey relationships that feed back into our understanding of species diversity, in terms of the number of species present in an ecosystem, and the function of carnivore species in an ecosystem (e.g. Yellowstone wolves). Despite previous investigations into mammalian predator-prey relationships

(Carbone et al., 2007a; Barnes et al., 2010), we still lack a global understanding of the nature of mammalian predator-prey relationships because of the bias toward terrestrial carnivorous mammals.

Marine carnivorous mammals provide an interesting comparison to terrestrial carnivores for several reasons. Marine mammals can reach sizes several orders of magnitude larger than the largest terrestrial carnivore (Smith et al., 2010). Marine mammals have achieved impressive sizes in part because there are fewer mechanical constraints in an aquatic environment and the associated advantages of large body size in a marine environment (e.g. thermoregulation; Clauset, 2013). Despite the 63

Chapter 4 – The Cost of Carnivory Revisited

relaxation of mechanical constraints in water, marine mammals still demonstrate a positive allometric relationship in energy requirements with body size (Nagy, 2005).

Any increase in energetic expenditure will therefore lead to an increase in energy intake and directly impact the feeding strategies adopted by marine mammals.

Physiological adaptations could offset some of these increased absolute energy requirements by allowing more efficient assimilation of food. Marine carnivores have longer small intestines than their terrestrial relatives (Williams et al., 2001) to enhance the digestion and assimilation of food (Slijper, 1976; Stevens & Hume, 1995). Marine mammals also have behaviours that enable them to deal with changes in energy expenditure and intake that include adjusting their reproductive output and foraging effort (Boyd & Murray, 2001; Costa, 2007). Furthermore, I predict that strategies that are suitable for a given sized predator on land might not be viable in marine environments because prey are distributed differently on land compared to at sea

(Brose et al., 2006b). I reassess the predator-prey body-mass relationship across mammalian carnivores, with the inclusion of marine species, to determine how the predator-prey body-mass relationship relates to the energetic requirements in different environments and how it shapes the feeding strategies adopted by different predatory mammals.

So far two feeding strategies have been formally identified and modelled for terrestrial carnivores, and these reflect the different energetic requirements of different sized predators (Carbone et al., 1999). Small carnivores are able to meet their energetic requirements while minimising the energetic costs of feeding by eating invertebrates.

As carnivores increase in body size, their absolute energy requirements also increase and a feeding strategy relying exclusively on invertebrates becomes inefficient

(Carbone et al., 2007a). As body size converges on 15-21 kg, there is a sudden two- fold increase in both energy intake and energy expenditure and this in turn corresponds with a shift to feeding on larger prey (Carbone et al., 2007a). 64

Chapter 4 – The Cost of Carnivory Revisited

Previous investigations, including terrestrial and some marine mammals, have identified an increase in energetic expenditure with increasing body size across mammals (Nagy, 2005). Despite the similarities in the patterns of energetics and body mass across marine and terrestrial mammals, we might expect the nature of the predator-prey relationships in the marine environment to be potentially very different to those seen in terrestrial carnivores. This is because of the differences in primary productivity and food web structure across the marine and terrestrial environments

(Shurin et al., 2006; Brose, 2010), which has driven the abundance of small species that form dense aggregations (e.g. invertebrates and vertebrates). The abundance of small prey has resulted in an increase in the encounter rates between marine carnivores and small prey species, as well as providing a resource with sufficient energy to support populations of marine carnivores (Scharf et al., 2000; Goldbogen et al., 2011). This has enabled both smaller carnivores (e.g. crabeater seals) and large carnivores (e.g. blue whales) to consume small prey species (<50 g) (Dalla Rosa et al.,

2008; Brierley & Cox, 2010; Hückstädt et al., 2012). With the exposure of marine carnivores of various body sizes to both small (<10 kg) and large (>10 kg) prey species, it is possible there is no relationship between marine carnivore mass and prey mass. Previous work by Tucker and Rogers (2014) examined the minimum, maximum and range of prey masses consumed by mammalian carnivores, and found that there was no relationship between prey mass and carnivore mass for marine mammals (see also Chapter 3). If there is also no relationship for mean prey mass, then it is likely that the quantity of prey consumed by marine carnivores will become more important than the size of the prey in order to meet the increase in the energy required by larger marine carnivores.

Chapter 4 – The Cost of Carnivory Revisited

4.3 MATERIALS AND METHODS

To investigate the relationship between mammalian carnivore body mass, prey body mass and the energetic expenditure and gain, I compiled data on predator and prey mass, daily energy intake and expenditure for 107 mammal species across the marine and terrestrial environments. I began by first establishing the energetic requirements of mammals on land and in water by examining the relationships between daily energy intake (DEI) and body mass, and daily energetic expenditure (DEE) and body mass.

Based on the two-fold increase in energy intake and expenditure above a mass of 21kg in terrestrial carnivores, my first objective was to identify what this threshold, or

“breakpoint”, might be for marine carnivores. I applied a piecewise or segmented regression (McGee & Carleton, 1970) within a phylogenetic framework to test whether species above a certain mass had a corresponding jump in DEI or DEE. Once these energetic relationships were established, I used the same phylogenetic piecewise regression approach for my second objective, which was to determine whether changes in energy intake and expenditure were associated with corresponding changes in prey mass. I expected that for at least terrestrial mammals, predators above

21kg would exhibit the previously identified shift to consuming larger-sized prey

(Carbone et al., 1999). In the case of marine mammals, however, the specific relationship between predator mass and prey mass, and how this relationship relates to the energetics of marine mammals, has not been examined and it was subsequently unclear what the impacts of large size might be for prey choice in marine carnivores.

4.3.1 Data

I analysed prey mass and predator mass for 107 carnivorous mammal species across the marine and terrestrial environments (Appendix 5, Table S5.1). Carnivores were defined as those species with diets compromising of at least 90% meat. This classification included insectivores as carnivores (Kelt & van Vuren, 2001). Insectivores

Chapter 4 – The Cost of Carnivory Revisited

were also included as they represent a carnivorous strategy for species below ~10 kg and contribute towards the breakpoint in terrestrial predators (Carbone et al., 2007a).

Mean prey mass data was obtained in two ways; (1) from published prey mass values

(n=53), and (2) using data from the literature to calculate mean prey mass values based on the proportion of prey species consumed by that carnivore (n=54). When prey preference information was not available, the mean prey mass was calculated from the listed prey species (n=2). Mean prey mass values were calculated using information on both sexes and dietary information across populations. Published information on adult daily energy intake (DEI) and expenditure (DEE) in kJ day-1 were also collected for species where this data was available (Appendix 5, Table S5.1). The values of DEI and DEE consisted of a mixture of directly measured values (e.g. accelerometry) and estimated values using allometric equations (e.g. Sigurjónsson &

Vikingsson, 1997). I have had to include estimated energetic values because of the difficulties associated with measuring energetic intake and expenditure in large marine carnivores (e.g. cetaceans), resulting in little or no published data available for these species. In this study, the main purpose of the energetic data is to examine whether patterns in mean prey mass are similar to those of DEI/DEE, not whether there is a relationship between DEI/DEE and body mass. Additionally, I am aware that there are different methodologies utilised to directly measure energetics in mammals including accelerometry, doubly labelled water and calorimeter/respirometry chambers, and there is variability across these methodologies (e.g. Dalton et al., 2014). However, at the scale of this study and with all of the data undergoing log10 transformation prior to analysis, these effects are likely to have little effect on the results.

4.3.2 Phylogenetic Information

Phylogenetic information was based on a pruned version of the mammalian supertree of Fritz et al. (2009) in which branch lengths were proportional to time since divergence. Divergence times were calculated using molecular clock analysis and the 67

Chapter 4 – The Cost of Carnivory Revisited

tree included fossil data for calibration (Bininda-Emonds et al., 2007). Sotalia guianensis was positioned onto this phylogeny based on the typology from Caballero et al. (2008) and the branch length was time-scaled based on the cetacean phylogeny by

Slater et al. (2010). Carnivora and cetacean positioning was updated using the recently published trees by Slater et al. (2010) and Nyakatura & Bininda-Emonds (2012), respectively. All tree manipulations were performed using Mesquite ver 2.74 (Maddison

& Maddison, 2010).

4.3.3 Analysis

Model selection using second-order Akaike’s information criterion with a correction for sample size (AICc) and phylogenetic generalised least squares (PGLS) regression

(see Analysis section in Chapter 2) were used to examine alternative models of DEE,

DEI and mean prey mass. The PGLS analyses were conducted using COMPARE ver

4.6b (Martins, 2004). Daily energetic expenditure and intake have been demonstrated to drive predator behaviour (Carbone et al., 2007a). To establish the energetic requirements of mammals with the addition of marine mammals, I investigated DEE and DEI with body mass using Piecewise regression. Piecewise regression tests whether the (McGee & Carleton, 1970). The value where one interval transitions to the next interval is the breakpoint. Piecewise regression can be described by;

푏1 ln(푥) + 푐, ln(푥) ≤ 퐵푃 ln(푦) = { (1) 푏2 ln(푥) + 푑, ln(푥) > 퐵푃

where, b1 is the slope when x is equal to or below the breakpoint value of BP , b2 is the slope when x sits above the breakpoint value of BP , c is the intercept when x is equal to or below the breakpoint (BP) and d is the intercept when x sits above the

Chapter 4 – The Cost of Carnivory Revisited

breakpoint (BP). The breakpoint analyses for DEE and DEI were performed using

βintercept+βmass+βbreak_x+βmass*βbreakpt_x, a model to examine the DEE or DEI of predators, including predator mass (βmass) and the potential breakpoint (βbreak_x), where x represented a range of percentages between 0 to 0.95 at 0.05 increments. An interaction term was included (βmass*βbreakpt_x) to test for the slope of the relationship (i.e.

DEE or DEI vs. predator body mass) above the breakpoint. The upper and lower credible support limits associated with the best-supported breakpoint were determined by the minimum and maximum breakpoint values within two AICc units of the best- supported model.

I then looked at the relationship between predator body mass and prey body mass, specifically looking for a change in intercept to identify whether there has been a major shift in predatory behaviour across mammals with the inclusion of marine species. To begin with, I used three sets of piecewise analyses using data on all species (marine and terrestrial), only marine species and only terrestrial species. Using a similar model to the energetic models, mean prey mass consumed by predators was examined using

βintercept+βmass+βbreak_x+βmass*βbreakpt_x, a model to examine the average prey size consumed by predators, including predator mass (βmass) and the potential breakpoint

(βbreakpt_x), where x represented a range of percentages between 0 to 0.95 at 0.05 increments. An interaction term was included (βmass*βbreakpt_x) to test for the slope of the relationship (i.e. predator mass vs. predator body mass) above the breakpoint.

To clarify the presence of 3 separate trends of predator and prey body mass, I assessed the fit of four additional models: (1) βintercept+βmass+βenvironment+βmass*βenvironment, a model where both predator body mass and whether species occupied a terrestrial or marine environment (coded as 0 or 1 respectively) explained differences in prey mass;

(2) β0, a null model with no predictor variables that assumed variance in prey body mass consumed by predators simply reflected the process of Brownian motion and 69

Chapter 4 – The Cost of Carnivory Revisited

stochastic factors associated with evolutionary differentiation; (3)

βintercept+βmass+βterrestrial_large+βmarine_small+βmarine_large, a model which includes predator body mass and four dummy variables (terrestrial and marine below breakpoint, terrestrial and marine above breakpoint); and (4) βintercept+βmass+βterrestrial_large+βmarine_large, a model which includes predator body mass and 3 dummy variables (terrestrial and marine above breakpoint and the remaining species). All dummy variables were coded as either 0 or 1, where 0 represents a species below the associated body mass breakpoint

(i.e. marine or terrestrial breakpoint) and 1 represents a species above the body mass breakpoint. Models 3 and 4 also included all possible combinations of interaction terms

(i.e., βintercept+ βmass+βx+βmass*βx) to test for differences in the scaling of predator-prey mass for each group (e.g. marine above breakpoint versus terrestrial above breakpoint).

4.4 RESULTS

4.4.1 Energetics

The DEI model with the lowest AIC value revealed a single breakpoint at 18kg (45th percentile, with a two unit credible range of 35th to 50th percentile or 11 to 37 kg; Fig.

4.1A and S5.1A) and the estimated parameter values of this model showed an approximately 3-fold jump in energy intake above the breakpoint (Table 4.1). The DEE model with the lowest AIC inferred a single breakpoint at 49kg (55th percentile, with a two unit credible range of 50th to 60th percentile or 40 to 79 kg; Fig. 4.1B and S5.2A) and an approximately 3-fold jump in energy expenditure above the breakpoint (Table

4.1). I did not find any support for a second breakpoint for large marine carnivores (>

10 000 kg) for either DEI or DEE.

Chapter 4 – The Cost of Carnivory Revisited

Fig. 4.1 Estimates of (A) Daily energy intake (DEI) against carnivore body mass (n=48) and (B) daily energy expenditure (DEE) against carnivore body mass (n=27) in marine and terrestrial mammals combined. The solid lines represent the breakpoint regression fit and the dotted lines represent the breakpoint at 18.73kg and 49.71kg for DEI and

DEE respectively. Eubalaena silhouette by Chris Huh and available for reuse under the

Creative Commons Attribution-ShareAlike 3.0 Unported license. Panthera silhouette is uncredited and is available for reuse under the Public Domain Mark 1.0 license.

Chapter 4 – The Cost of Carnivory Revisited

Table 4.1 Best supported breakpoint models and associated coefficients for daily energetic intake (DEI) and daily energetic expenditure (DEE) in relation to predator mass (M). The breakpoint (BP) represents the percentile threshold of the log10- transformed body mass above which expenditure or intake shifts to the higher intercept

(βintercept, >BP) or differing slope (βmass, >BP), compared to the intercept (βintercept,

Parameter Parameter Coefficients (95% CI)

βmass,

DEI βmass, >BP 0.53 (0.33,0.73)

βintercept,

βintercept, >BP 3.62 (3.34,3.90) BP 1.27

βmass,

βmass, >BP 0.52 (0.259,0.781)

DEE βintercept,

βintercept, >BP 3.67 (3.23,4.11) BP 1.70

4.4.2 Prey Size

Across all species (terrestrial and marine species combined), the PGLS model with the lowest AIC value included a breakpoint at ~11.1 kg (35th percentile, with a two unit credible range of 30th to 45th percentile or 11 to 36 kg; Table 4.2 and Fig. S5.3C) and a shift to feeding on prey 58 times larger (0.03 kg to 1.56 kg). By design this analysis only identified a single breakpoint and I had predicted that there were likely unique breakpoints (or no breakpoints) for terrestrial and marine mammals. I therefore looked for breakpoints using a second analysis that treated terrestrial and marine species separately. For terrestrial mammals, a similar breakpoint to the initial inclusive analysis was highlighted at ~11 kg (70th percentile, with a two unit credible range of 60th to 80th 72

Chapter 4 – The Cost of Carnivory Revisited

percentile or 10 to 21 kg; Table 4.2 and Fig. S5.3A) that was associated with a shift to feeding on prey 37 times larger (from 0.09 kg to 3.23 kg). However, for marine mammals there was a unique breakpoint at ~11 000 kg (80th percentile, with a two unit credible range of 60th to 85th percentile or 1412 to 19498 kg; Table 4.2, Fig. S5.3B) that was associated with a dramatic drop in prey size (~1300 times smaller, from 0.22 kg to

0.0002 kg). The phylogenetic effect size (r) of the piecewise analyses also increased when terrestrial and marine species were examined separately (all species = 0.34, marine = 0.50 and land = 0.78), suggesting these separate analyses had a greater explanatory power.

Table 4.2 Best supported breakpoint models and associated coefficients for prey mass

(P) against predator mass (M). The breakpoint (BP) represents the percentile threshold of the log10-transformed body mass above which prey mass shifts to the new intercept

(βintercept, >BP) or differing slope (βmass, >BP), compared to the intercept (βintercept,

Parameter Parameter Coefficients (95% CI)

βmass,

βmass, >BP -0.56 (-1.76,0.64) All Species βintercept,

βintercept, >BP 0.78 (-0.52,2.08) BP 1.05

βmass,

βmass, >BP -0.19 (-2.70,2.32)

Marine βintercept,

βintercept, >BP -3.01 (-14.33,8.31) BP 4.06

βmass,

βmass, >BP 1.74 (0.69, 2.79)

Terrestrial βintercept,

βintercept, >BP -1.30 (-2.57, -0.02) BP 1.04

Chapter 4 – The Cost of Carnivory Revisited

These results confirmed the existence of contrasting feeding strategies in mammals that were associated with differing predator mass thresholds depending on the type of environment in which predators lived (Fig. 4.2). Small terrestrial mammals (<11 kg) feed on small prey, while large terrestrial mammals (>11 kg) make an abrupt transition to feeding on large prey (see also Carbone et al., 1999). However, within the same size range of these large terrestrial mammals, marine mammals have continued to feed predominantly on smaller-sized prey, up to a point, after which the largest marine mammals make a major shift to feeding on very small prey (< 0.0001 kg). Looking at the distribution of data in Figure 4.2, smaller marine species seem to exploit similar sized prey to the smaller class of terrestrial species (0.01-1 kg).

Chapter 4 – The Cost of Carnivory Revisited

Figure 4.2 Mean prey body mass as a function of carnivore body mass for 107 species across the marine and terrestrial environments. The blue and green lines are the breakpoint regression fit for marine and terrestrial species respectively. The dotted vertical lines represents the 11 kg threshold where terrestrial carnivores shift from feeding on small prey to large prey, and the 11 380 kg threshold where marine carnivores shift from feeding large prey to feeding on smaller prey. Letters a-e represent outlying species; (a) Zalophus californianus, (b) Hydrurga leptonyx, (c) Ursus maritimus, (d) Orcinus orca and (e) odontocete whales including Physeter macrocephalus and Berardius_bairdii.

Chapter 4 – The Cost of Carnivory Revisited

To determine whether small terrestrial mammals and small marine mammals were in fact selecting similar sized prey, I formulated a series of models to detect similarities or differences in slope and intercept of the relationship between predator mass and prey mass among four subgroups: small terrestrial mammals (< 11 kg), large terrestrial mammals (>11 kg), small marine mammals (10-10 999 kg) and large marine mammals

(> 11 000 kg). The results were mixed, with various models obtaining equivalent support (models at or near a ∆AIC value of 2; Table 4.3 and Fig. 4.2). In general, the supported models were those that assumed some combination of difference in intercept and slope among the four subgroups (Table 4.3). Despite impressions from

Figure 4.2 that assumed similarities in prey preference between small terrestrial mammals and small marine mammals, and also that breakpoints were specifically associated with the transition to the marine environment and not body mass per se, the models which tested these impressions received little support (Table 4.3).

Chapter 4 – The Cost of Carnivory Revisited

Table 4.3 Level of support for explanatory models of prey mass of predatory mammals.

Results are from phylogenetic regression analyses. Models with the strongest support have small AIC values.

Model * Rank ∆AIC

Linear βintercept+βmass+βenvironment+βmass*βenvironment 9 23.01

Null βintercept 14 42.58

βintercept + βmass + βterrestrial_large + βterrestrial_large * βmass +

βmarine_small + βmarine_large 1 0

βintercept + βmass + βterrestrial_large + βmarine_small + βmarine_small * βmass

+ βmarine_large 2 0.60

βintercept + βmass + βterrestrial_large + βterrestrial_large * βmass + βmarine_small

Piecewise + βmarine_small * βmass + βmarine_large 3 1.01

4 groups βintercept + βmass + βterrestrial_large + βmarine_small + βmarine_large 4 1.01

βintercept + βmass + βterrestrial_large + βterrestrial_large * βmass + βmarine_small +

βmarine_large + βmarine_large * βmass 5 2.03

βintercept + βmass + βterrestrial_large + βterrestrial_large * βmass + βmarine_small +

βmarine_large + βmarine_large * βmass 6 2.33

βintercept + βmass + βterrestrial_large + βterrestrial_large * βmass + βmarine_small +

βmarine_small * βmass + βmarine_large + βmarine_large * βmass 7 2.89

βintercept + βmass + βterrestrial_large + βmarine_small + βmarine_large +

βmarine_large * βmass 8 2.99

βintercept + βmass + βterrestrial_large + βterrestrial_large * βmass + βmarine_large 10 23.28

βintercept + βmass + βterrestrial_large + βterrestrial_large * βmass + βmarine_large

Piecewise + βmarine_large * βmass 11 25.27

3 groups βintercept + βmass + βterrestrial_large + βmarine_large 12 28.11

βintercept + βmass + βterrestrial_large + βmarine_large + βmarine_large * βmass 13 30.05

* terrestrial/marine_large = species above 11kg/11000kg breakpoints, terrestrial/marine_small = species below the 11kg/11000kg breakpoints

Chapter 4 – The Cost of Carnivory Revisited

4.5 DISCUSSION

I show that four distinct predator feeding strategies have evolved in mammals (not two, as previously thought; Carbone 1999): small terrestrial carnivores (less than 11kg) feed on small terrestrial prey less than 1 kg, large terrestrial carnivores (above 11 kg) feed on large terrestrial prey above 3 kg, small marine mammals (below 11 000 kg) feed on small marine prey less than 2 kg, and larger marine carnivores (above 11 000 kg) feed on very small marine prey less than 0.0005 kg (or 0.5 g). Following the colonisation of the marine environment, mammals below 11 000 kg in general seem to behave in a manner broadly similar to terrestrial carnivores below 11kg as they feed predominantly on small sized prey (for marine species this includes squid and fish, but may also include zooplankton and some large vertebrates such as seals). However, marine mammals larger than 11 000 kg have switched to a strategy of consuming tiny prey items, and in huge quantities to meet their massive energy requirements.

Based on my data, I did not find a second DEI or DEE breakpoint for marine carnivores, suggesting that there may not be a shift up or down in energetics for large marine carnivores. This finding may be an actual trend, but this could also be an artefact of my data. Due to the small sample sizes across marine and terrestrial species I could not split the species by their environment and examine the energetic thresholds independently. The results did suggest that there might be a difference between the DEI and DEE breakpoints across marine and terrestrial carnivores (18 kg vs. 49 kg). The DEI breakpoint overlaps with the previously identified threshold for terrestrial mammals of 15-21 kg (Carbone et al., 1999), but the DEE breakpoint is nearly 3 times larger. However, a possible reason for this disparity between the breakpoints again relates to the potential limitations of data on energetic intake and expenditure of marine mammals resulting from the difficulties associated with collecting energetic information on animals living permanently in water. Probably as a result of

Chapter 4 – The Cost of Carnivory Revisited

this, the species included in these two analyses did not overlap exactly (n = 48 for DEI, n = 27 for DEE). Improving tagging technologies will hopefully allow more energetic information to become available in the near future and clarify the nature of this disparity between DEI and DEE, as well as improving our ability to examine the energetic thresholds across marine and terrestrial carnivores.

Nevertheless, the results are clear in showing that terrestrial mammals manage the jump in energy demand associated with their large size by making an abrupt transition to consuming much larger prey (prey> 45% of predator body mass; Carbone et al.,

1999), for example lions (Panthera leo) on average can consume about 6kg of prey, which is equivalent to ~ 0.07 wildebeest per day (Fryxell et al., 2007). However, this same transition to consuming larger prey has not occurred in marine mammals. Once marine carnivores reach 11 000 kg there is a major shift in feeding ecology, but to the transition of feeding on massive quantities of very small prey (~0.01% of the predator’s body mass; this study), including invertebrates such as zooplankton. For example, minke whales (Balaenoptera bonaerensis) consume up to 300kg of prey per day, which is equal to enormous quantities of individual krill (i.e. thousands of individuals; Reilly et al., 2004).

There are several drivers behind the different strategies identified across the marine and terrestrial carnivores. There are differences in the availability of protein to predators between the two environments. In the ocean, protein is available as dense aggregations of small species (Tarling & Thorpe, 2014). Around 34 million years ago changes in the climate and the ocean altered marine productivity and saw the emergence of large quantities of small marine invertebrates. For these marine invertebrates, refuge from predators was available in coastal waters (among sea-grass, coral and kelp forests or in the sediment) and in polar regions (under-ice habitats), however in the pelagic deep oceans, which are dominant habitats within the earth’s 79

Chapter 4 – The Cost of Carnivory Revisited

landscape, there are few refugia. Around this time one of the earliest mysticete-like whales, Llanocetus, was presumed to be filter-feeding as mysticetes do today

(Clementz et al., 2014).

Marine invertebrates living within a deep-sea habitat (e.g. krill) avoid predation by aggregating in swarms (Brierley & Cox, 2010) and vertical migration (Cox et al., 2009).

Marine mammals evolved strategies to exploit this swarming behaviour. Archaeocetes

(a group of primitive cetaceans in the early Eocene), crabeater seals and leopard seals have specialised molar teeth for krill-sieving and oral cavity adaptations for suction feeding (Kissling et al., 2014). Mysticete whales saw further anatomical adaptations.

This included the loss of teeth completely and the development of baleen (keratinized plates that hang from the rostrum and are used for filter-feeding; Goldbogen et al.,

2013) and a specialised joint between the frontal bone and the mandible (the frontomandibular stay; Lambertsen et al., 1995), which allows the oral cavity to open wider (~ 75 degrees compared with ~55 degrees in terrestrial carnivores; Falkowski &

Raven, 1997; Andersson et al., 2011) to allow the rapid influx of prey-laden water.

Pleating of the buccal region allowed for further expansion, the buccal cavity

(Courchamp & Macdonald, 2001; Van Valkenburgh, 2007; Burnham et al., 2011), providing additional capacity for rapid bulk feeding as animals swam through swarming prey. The structure of the hyolingual apparatus in mysticete whales differs depending on their feeding method. In the balaenopterids, for example, the tongue is less muscular and facilitates the expansion of the buccal cavity (Werth, 2007).

In the three-dimensional pelagic waters (where nutrients are available) the presence of phytoplankton communities, and the zooplankton communities (e.g. protozoans) that feed on the phytoplankton, supports enormous densities of predatory marine invertebrates (e.g. krill, copepods and amphipods). For example, in the Southern

Ocean the density of krill has been measured up to 2559 individuals m-3, with the 80

Chapter 4 – The Cost of Carnivory Revisited

swarm measuring up to 18 km long and spanning an area of 132,798 m2 (Tarling &

Thorpe, 2014).

The ability to harvest greater resources (swarming invertebrates) may have led to greater body size, which in turn allowed these mammals to dive to greater depths. At these depths whales had the ability to overcome the vertical-migration anti-predator strategy of the swarming marine invertebrates and exploit a new niche. Marine carnivores evolved physiological and behavioural adaptations to enhance deep diving.

These include apnoea (breath holding), bradycardia (slowed heart rate), redistribution of blood to vital organs, hypometabolism, cooperative feeding and gliding for deeper diving (Boyd, 1997).

In the terrestrial system there is no similar invertebrate schooling biomass. This same schooling behaviour is not seen in protein-rich terrestrial systems perhaps due to the heterogeneity of the terrestrial landscapes, which provides adequate refugia for invertebrates. There are aggregations of terrestrial invertebrates in mounds (e.g. termites, densities of 2139 individuals m2; Bodine & Ueckert, 1975) that are exploited by a range of mammal species (e.g. aardwolf, anteater and pangolin) and insects in the air that are exploited by bats (e.g. microbats). However, invertebrates can only support terrestrial carnivores up to 11-21kg (this study; (Carbone et al., 1999). This is due to the lower abundance of these aggregations and the associated increase in energy expenditure when capturing these small prey items and the decrease in energy assimilated (Carbone et al., 2007a).

Another factor behind the different strategies across carnivorous mammals is related to the differences in energy allocation across species from the marine and terrestrial environments. Terrestrial mammals allocate a higher proportion of their energy to locomotion (~90%), compared with marine mammals which allocate more of their 81

Chapter 4 – The Cost of Carnivory Revisited

energy to maintenance (~40%; Williams, 1999). Additionally, it has been illustrated that marine carnivores have a higher hunting efficiency than terrestrial carnivores (energy ingested > energy expended; Williams & Yeates, 2004). Despite these differences, terrestrial and marine carnivores have adopted strategies that minimise energy expenditure whilst hunting, whether it is consuming prey of increasing body mass on land or feeding on large quantities of small prey in the ocean. Carnivores towards the maximum body size in both environments have additional strategies to cope with their high absolute energy requirements and the elevated costs associated with prey capture. On land, lions spend the majority of their time resting in addition to cost- minimising strategies during the hunt (Schaller, 1972; Carbone et al., 2007a). In the ocean, there are high costs associated with lunge feeding including bursts of high energy muscle activity and elevated metabolic demands (Potvin et al., 2012). However, these costs are mitigated by decreasing the number of lunges per dive, passive feeding

(e.g. cooperative feeding at the surface) and an increased recovery period post diving

(Potvin et al., 2012).

There are a couple of exceptions to the feeding strategies identified in this study. I have discussed at length the feeding adaptations in the mysticete whales, but there is an alternate feeding method for large-bodied marine carnivores demonstrated by odentocete whales. Most odontocetes have retained their teeth and generally utilise swarms of larger-sized prey species including fish (e.g. Genypterus blacodes (Gaskin

& Cawthorn, 1967) and Merluccius merluccius (Agosta & Bernardo, 2013)) and squid

(e.g. Nototodarus sloanei (Gaskin & Cawthorn, 1967) and Gonatus steenstrupi (Hanna

& Cardillo, 2014)). In the extreme case, some odontocetes can consume prey over 30 kg (Dalerum, 2013; Clarke & O'Connor, 2014), such as sperm whales (Physeter macrocephalus). Killer whales (Orcinus orca) that specialise on feeding on whales and seals are an example of a large marine predator that feeds on large prey and in some cases prey that are larger than the killer whales themselves (e.g. minke whales). Killer 82

Chapter 4 – The Cost of Carnivory Revisited

whales are similar to the terrestrial carnivores such a lion that employs cooperative hunting behaviour to capture large prey (Pitman & Durban, 2012). I should also point out that there are also other species within the marine environment which utilise cooperative hunting to maximise capture efficiency including dolphins and baleen whales (Gazda et al., 2005; Wiley et al., 2011). However, these species tend to capture smaller prey that form schools or swarms (e.g. plankton or fish). The polar bear (Ursus maritimus) is another unusual large marine predator that feeds on large prey (e.g., seals; Derocher et al., 2002). However, the polar bear is a comparably recent convert to a marine lifestyle (~1.1 Myr; Nyakatura & Bininda-Emonds, 2012), so it is perhaps not too surprising that they retain a terrestrial-like feeding ecology. The remaining two exceptions that sit within the lower limits of large land predators are the leopard seal

(Hydrurga leptonyx) which feeds on a mixture of vertebrates, fish and zooplankton but predominantly vertebrate prey (Kleiber, 1961), and the Californian sea lion (Zalophus californianus) which feeds on fish and squid (Pauly et al., 1998) act as top predators within their ecosystems (Rogers et al., 2005; Block et al., 2011).

While I have examined patterns in mean prey mass, there are additional questions on predator-prey relationships that are still to be answered. One avenue that is yet to be explored is the variability in prey size consumed by the same carnivore, and the extent to which and why this variability differs among carnivore species. For example, leopard seals can consume a range of prey species from krill through to 100 kg seal pups (Hall-

Aspland & Rogers, 2004). Examining whether there are patterns in dietary niche breadth can provide insights into prey choice and optimal foraging strategies (Costa et al., 2008). In addition, this previous work on dietary niche breadth has been largely based on non-mammalian predators such as reptiles and birds (Braendle et al., 2002;

Costa, 2009), providing an opportunity to examine these patterns in mammals in comparison with other predatory taxa.

Chapter 4 – The Cost of Carnivory Revisited

4.6 CONCLUSION

This study has added an extra dimension to our understanding of predator energetics and prey requirements to include both marine and terrestrial carnivorous mammals.

The colonisation of the marine environment by mammals has had a profound effect on carnivore diets, resulting in the evolution of feeding and behavioural strategies that differ to those demonstrated by terrestrial carnivores. Understanding mammalian diets is important for three reasons. First, it provides a clearer understanding of the selective forces that have shaped predator-prey relationships and the associated behavioural/foraging strategies adopted by extant carnivorous mammals. Second, it provides critical information on how species interact (i.e. consumers and their resources), how energy is transferred through an ecosystem (i.e. from small species to large species) and how trophic structures are shaped across different environments

(i.e. food chain length). Third, information on the prey consumed by carnivores and the physiological underpinnings of carnivore behavioural strategies that I have identified have potentially important conservation implications, such as the identification of scenarios where conflict may arise between human activities and mammals. For large marine carnivores, the combination of elevated energetic requirements, the reliance upon dense aggregations of small prey species and the fact that these same prey species are also being commercially harvested, highlights one of the many threatening processes currently faced by marine mammals. More generally, given that both marine and terrestrial carnivorous mammals are under threat from climate change and increasing human activities at a global scale (Ripple et al., 2014), understanding the dynamics behind carnivore diets could provide the information needed to help minimise some of these negative impacts faced by carnivorous mammals.

Chapter 5 Examining predator-prey body size,

trophic level and body mass across

marine and terrestrial mammals

5.1 SUMMARY

Predator-prey relationships and trophic levels are indicators of community structure and are important for monitoring ecosystem changes. Mammals colonised the marine environment on seven separate occasions (beginning in the early Eocene ~55 million years ago), which resulted in differences in species’ physiology, morphology and behaviour. It is likely that these changes have had a major effect upon predator-prey relationships and trophic position; however the effect of environment is yet to be clarified. I compiled a dataset, based on the literature, to explore the relationship between body mass, trophic level and predator-prey ratio across terrestrial (n=51) and marine (n=56) mammals. I did not find the expected positive relationship between trophic level and body mass, but I did find that marine carnivores sit 1.3 trophic levels higher than terrestrial carnivores. Also, marine mammals are largely carnivorous and have significantly larger predator-prey ratios compared to their terrestrial counterparts. I propose that primary productivity, and its availability, is important for mammalian trophic structure and body size. Also, energy flow and community structure in the marine environment is influenced by differences in energy efficiency and increased food web stability. Enhancing our knowledge of feeding ecology in mammals has the

Chapter 5 – Predator-Prey Relationships and Trophic Level

potential to provide insights into the structure and functioning of marine and terrestrial communities.

5.2 INTRODUCTION

Mammals are a diverse group of organisms spanning eight orders of magnitude in body mass, exploiting a variety of habitats and niches, and encompass a range of feeding ecologies (Smith & Lyons, 2011; Price et al., 2012). These characteristics make mammals ideal to investigate patterns in trophic level. Mammals have re-entered the marine environment on seven separate occasions, and there are five extant clades:

Cetacea, Sirenia, Pinnipedia, Ursus maritimus and Enhydra lutris (Uhen, 2007).

Cetacea and Sirenia re-entered the water during the early Eocene (~55 million years ago) and Pinnipedia returned to the water during the Oligocene (~30 million years ago)

(Uhen, 2007). This provides a unique opportunity to explore the possible changes that have occurred as mammals moved into an environment where not only physiological and morphological modifications have taken place, but additional behavioural changes were associated with foraging ecology.

Two relationships used to investigate the feeding ecology of carnivorous species include the association between trophic level and body mass, as well as the relationship between trophic level and the predator-prey body-mass ratios. Depending on the complexity of the ecosystem, carnivores are not always secondary consumers.

For example, a carnivore from a complex food web with more than five trophic levels, will sit higher in the food chain than a carnivore in a simple food web with just three trophic levels (Pauly & Christensen, 1995). Also, as large mammalian carnivores tend to feed on larger-sized prey, a requirement of their high energetic requirements

(Carbone et al., 2007a), larger carnivores also tend to have higher trophic positions.

Chapter 5 – Predator-Prey Relationships and Trophic Level

This is linked with the idea that food webs are size structured, for example a large carnivore targeting larger-sized prey (e.g. fish) will have a higher trophic level than a carnivore feeding upon smaller-sized prey (e.g. zooplankton).

Productivity differs between the marine and terrestrial environments. In the ocean, primary producers represent around 0.2% of the global primary-producer biomass however turnover rate (i.e. carbon productivity) is greater in the marine environment

(up to 1000 times higher; Field et al., 1998; Shurin et al., 2006). With the combination of the dominance of single-celled plants such as phytoplankton, energy flow is faster and more easily accessible to consumers within the marine environment. Where terrestrial primary producers represent a higher proportion of producers (~99.8%) the net turnover rate is much slower on land than within the oceans (e.g. carbon turnover

19 years (terrestrial) vs. 2-6 days (marine); Falkowski & Raven, 1997; Thompson &

Randerson, 1999) . Multicellular plants are dominant on land and are more difficult for consumers to process and extract energy from compared with single-celled species. As the majority of primary production is driven by small, single-celled organisms in the marine environment, aquatic systems tend to be heavily size structured so that trophic interactions are driven by large consumers feeding on small species (Andersen et al.,

2009b).

The relationship between trophic level and body mass across mammals has three possible patterns that I aim to test. (1) Differences in the environmental characteristics are driving trophic-level patterns across mammals, with a positive relationship expected between trophic level and body mass in both marine and terrestrial species, as demonstrated by Riede et al. (2011). This would mean that differences in the food-web structure and the number of trophic levels (see Brose, 2010) would result in marine mammals having a higher intercept for trophic level than terrestrial mammals. (2) Body mass, regardless of environment, is driving trophic-level patterns. If body mass is the 87

Chapter 5 – Predator-Prey Relationships and Trophic Level

key driver for trophic-level patterns, then the relationship should remain the same with the addition of marine species. (3) The trophic level-body mass relationship would be quadratic (i.e. hump-shaped) because the addition of the marine species complicates the relationship. The positive relationship between trophic level and body mass holds up to a maximum threshold, where the relationship then shifts and becomes negative due to the largest mammals, the mysticete whales, feeding largely upon small invertebrates situated at low trophic levels (Pauly et al., 1998). In this scenario, the terrestrial carnivores would contribute to the initial positive relationship between trophic level and body size (Riede et al., 2011).

Predator-prey body-mass ratios (PP ratios) provide information on food web complexity, ecosystem stability and community structure (Weitz & Levin, 2006; Petchey et al., 2008). Food webs are usually more stable when predators are larger than their prey (Jennings & Mackinson, 2003; Brose et al., 2006b), as this minimises the chance that new predators invade and outcompete current predatory species (Weitz & Levin,

2006; Kartascheff et al., 2010). There are however exceptions, such as pack-hunting mammalian carnivores (e.g. wolves) and large cats (e.g. tigers). It has been demonstrated across whole food webs that PP ratios vary with the trophic position of the predator, where the PP ratio approaches one with increasing trophic level (Riede et al., 2011) (i.e. the predators with high trophic positions consume prey more similar to their own body size).

Using diet information and trophic level data for terrestrial and marine mammals I investigate how living within the marine or the terrestrial environment has impacted the relationship between body size, trophic level and PP ratio across mammals. To achieve this I (1) examine how the differences between consumers within terrestrial and marine environments influence the trophic and food-web structure of mammals; and (2) I test if

Chapter 5 – Predator-Prey Relationships and Trophic Level

the negative relationship between PP ratio and predator trophic level is a general rule across mammals by examining this relationship with the addition of marine mammals.

5.3 MATERIALS AND METHODS

5.3.1 Database

I analysed trophic level and species’ body masses from 107 carnivorous mammal species across marine (n=56) and terrestrial (n=51) environments. I chose these 107 species based upon the availability of detailed dietary information within the literature, which also means that the data is skewed towards species that have been well studied.

Carnivores were defined as those species with diets compromising at least 90% meat, with insectivores also classified as carnivores (Kelt & van Vuren, 2001). Trophic level positions for marine mammals is readily available in the literature (Pauly et al., 1998) however, this information is more difficult to obtain for terrestrial mammals and had to be calculated. To achieve this, terrestrial prey-preference data were collected from the literature (i.e. the proportion of prey species consumed by that carnivore), and this data included all species preyed upon by the carnivore species. Each prey species was assigned a trophic position, where herbivorous prey species were assigned a trophic level of 2, omnivorous prey species were assigned 2.5 and carnivorous prey species were assigned 3. Combining the information on carnivore prey preference and the trophic level of the prey, the carnivore trophic level was then calculated using the equation from Pauly et al. (1998):

푛 푛

TLi = 1 + (∑ DCij∙TLj / ∑ DCij) (ퟏ) 푗=1 푗=1

where DCij , is the diet composition with the proportion of prey (j) in the diet of species

(i), TLj is the trophic level of prey (j), and n is the number of groups in the system. Body mass data were log10 transformed prior to analysis.

Chapter 5 – Predator-Prey Relationships and Trophic Level

Predator and prey body masses were extracted from the literature (n=107). Where predators consume more than one prey item, I calculated mean prey size that represented the common prey items consumed by that species. Predator-prey body mass ratio (PP ratio) was calculated for the carnivorous species, by dividing the average mass of each predator species by their average prey mass.

5.3.2 Phylogenetic Information

Due to the absence of a single phylogeny with all species of interest, a composite tree was created by combining information from several sources (see Figure S6.1). The majority of the phylogenetic information was based on the mammalian supertree of

Fritz et al. (2009) in which branch lengths were proportional to time since divergence.

Divergence times were based on molecular clock analysis and the tree included fossil data for calibration (Bininda-Emonds et al., 2007). Two species were positioned within the pruned trees based on the topologies of the following sources: Sciurus aberti (Grill et al., 2009); and Sotalia guianensis (Caballero et al., 2008). Carnivora and cetacea positioning were updated using the recently published trees by Slater et al. (2010) and

Nyakatura & Bininda-Emonds (2012) respectively. All tree manipulations were performed using Mesquite ver 2.74 (Maddison & Maddison, 2010).

5.3.3 Analysis

A model selection approach was applied to test the level of support for alternative models of trophic level patterns in carnivorous mammals: (a) Body mass and environment model (β0+βmass+βenvironment) where both body mass and environment (i.e. whether species occupied a terrestrial or marine environment) explained differences in trophic level position (environment was coded in a binary fashion as living in either the terrestrial (0) or marine (1) environment), (b) Body mass and environment model with an interaction term (β0+βmass+βenvironment+βmass*βenvironment) which is the same as the previous model but with an interaction term (i.e., βmass*βenvironment) to test for differences 90

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in allometry in relation to the physical environment; (c) Quadratic model (β0+βmass+

2 2 βmass ) where a quadratic term was added (βmass ) to explained differences in trophic level position and body mass across all species as a quadratic relationship; (d) Body mass model (β0+βmass) which predicted differences in trophic level among species was exclusively explained by body size; and (5) Null model (β0) where no predictor variable was included and I subsequently modelled the variance in species trophic level as the outcome of both Brownian evolution and stochastic factors associated with evolutionary differentiation. The model selection and phylogenetic least squares (PGLS) regression analyses were run as per Chapter 2 (see Analysis section), using COMPARE ver 4.6b

(Martins, 2004).

The relationship between trophic level and PP ratio was investigated using PGLS regression. For all PGLS regression results, significance was deemed when the confidence intervals (CI’s) did not overlap 0. Differences in body mass associated with diet across the two environments were examined using ANOVA respectively, using R

2.13.2 (R Development Core Team, 2011). Sample sizes for the diet categories in each environment were as follows: marine carnivores (n=56), marine herbivores (n=5), terrestrial carnivores (n=51) and terrestrial herbivores (n=99).

5.4 RESULTS

5.4.1 Trophic Level Patterns

A model including body mass and physical environment (marine vs. terrestrial) was the best supported model for predicting the evolution of trophic level in carnivorous mammals, explaining 46% of the variance in trophic level among species (Table 5.1).

The second most supported model which included the interaction term of

βmass*βenvironment, was within 2 units of the best model, and was therefore considered to

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be equally supported (Table 5.1). The remaining models had virtually no support with

∆AICc being greater than 2. Examining the parameters of the

β0+βmass+βenvironment+βmass*βenvironment model, the interaction term was not significant (CI’s

-0.24, 0.14), indicating that the slope of the relationship between trophic level and body mass is the same across the two environments. This means that the results of the two best supported models (β0+βmass+βenvironment and β0+βmass+βenvironment+βmass*βenvironment) are essentially identical.

Table 5.1 Level of support for explanatory models of trophic level evolution in mammals. Results are from phylogenetic least square (PGLS) regressions computed for the mammalian phylogeny.

Model ∆AICc PGLS Effect α size (r)

β0+βmass+βenvironment 0.00 8.55 0.69

β0+βmass+βenvironment+βmass*βenvironment 1.68 8.71 0.69

β0+βmass 27.30 2.65 0.11 2 β0+βmass+ βmass 32.07 2.00 0.08

β0 44.36 0.78 -

When investigating the parameters of the environment model, there is a significant difference in intercept of trophic level between marine and terrestrial species (CI’s 0.71,

1.39; Fig. 5.1A), with a mean trophic level for terrestrial carnivores of 2.7 and marine carnivores of 3.9. The relationship between mass and trophic level was not significant

(CI’s -0.08, 0.06), indicating that there is no relationship between mass and trophic level in either environment.

Chapter 5 – Predator-Prey Relationships and Trophic Level

Figure 5.1 (A) Trophic level as a function of species body mass compared for species occupying terrestrial (grey circles) and marine (coloured circles) environments. Each datum represents a species mean value (n = 107 species). The solid black lines are the PGLS regression lines for terrestrial mammals: log Y = 0.01(log X) +2.98 and for marine mammals: log Y = 20.02(log X) + 4.03. River otter (9 kg) and blue whale (155 000 kg) are the smallest and largest marine mammal, respectively, whereas the collared pika (120 g) and brown bear (217 kg) are the smallest and largest terrestrial mammals, respectively. Note that body mass is on a log10 scale. (B) Schematic of general trophic-level patterns for terrestrial mammals (grey), odontocetes (red) and mysticetes (blue). Images: Chris Huh (marine mammals), Hans Hillewaert (Amphipoda) and Lukasiniho (Alcelaphus) and uncreditied (Panthera) were downloaded from http://phylopic.org. Fish and grass silhouettes by Marlee Tucker.

Chapter 5 – Predator-Prey Relationships and Trophic Level

5.4.2 Predator-Prey Ratios

The PP ratio decreases with increasing trophic level in both marine and terrestrial environments (Fig. 5.2A). There was no significant interaction between trophic level and environment (CI’s -34.13, 0.61), suggesting that the scaling of the relationship between predator-prey ratio and trophic level is the same in both environments.

However, the intercept values for marine and terrestrial mammals were significantly different (CI’s 5.16, 23.06), with marine species having larger PP ratios than terrestrial species of a similar mass.

Chapter 5 – Predator-Prey Relationships and Trophic Level

Figure 5.2 (A) The relationship between log10 predator–prey ratio as a function of predator trophic level, across marine (coloured circles) and terrestrial mammals (grey circles), n = 107. The solid black lines are the PGLS regression line for terrestrial mammals: log Y = - 13.08(log X) + 7.83 and for marine mammals: log Y = -26.83(log X) + 20.54. (B) Examples of feeding strategies used by marine (blue) and terrestrial (green) carnivorous mammals. Marine (left to right): bulk feeding (mysticetes), small vertebrate feeders (odontocetes) and large vertebrate feeders (orcas and polar bears). Terrestrial (left to right): small insectivores (echidnas), small vertebrate feeders (mustelids) and large vertebrate feeders (lions). Images: Chris Huh (marine mammals), Hans Hillewaert (Amphipoda), Lukasiniho (Alcelaphus), Tracy Heath (Phocid and U. maritimus), Nobu Tamura/T. Michael Keesey (Tachyglossus) and uncredited (Mustelid and Panthera) were downloaded from http://phylopic.org. Fish and bird silhouettes by Marlee Tucker.

Chapter 5 – Predator-Prey Relationships and Trophic Level

5.4.3 Diet and body size There was a significant difference between the average mass of herbivores

(F1,102=10.66, p<0.01) and carnivores (F1,105=134.12, p<<0.01) between the marine and terrestrial environments (Fig.S6.2), with marine mammals having larger body masses in both diet categories. A caveat of this analysis across terrestrial and marine mammals is the presence of a dietary bias. In the marine environment, mammals are predominantly carnivorous and there are fewer than five herbivorous mammals. This limits the number of species that can be compared across diet categories, specifically for marine mammals.

When investigating the relationship between diet niche and body mass, there is a broader range of mass values across terrestrial herbivores (0.03 – 3981 kg), compared with terrestrial carnivores (0.09 – 177 kg; Fig. S6.2). Conversely, the opposite is found in the marine system with marine carnivores ranging from 9 to 155 000 kg, and marine herbivores ranging from 195 to 19 200 kg (Fig. S6.2).

5.5 DISCUSSION

5.5.1 The effects of body mass on trophic position

The evolution of trophic position in mammalian carnivores appears to be driven by the environment in which they live. Marine carnivores sit on average 1.3 trophic levels higher than mammals that live on land. This trophic shift is driven by the more complex nature of marine food webs where there are higher numbers of trophic levels (Fig. 5.1A and B) as well as interactions between these trophic levels (Brose, 2010; Riede et al.,

2011). The absence of a relationship between changes in body mass and trophic level was present for both terrestrial and marine mammals. Our results contradict previous studies which combined data from endothermic vertebrates (i.e. mammals and birds) and showed a strong positive relationship between body mass and trophic level in

Chapter 5 – Predator-Prey Relationships and Trophic Level

vertebrates (Riede et al., 2011). This study examined the relationship between body mass and trophic level within mammals only and I used different methodologies (e.g. data normalisation; see Riede et al., 2011). Ideally I would like to examine trophic-level patterns in mammals across food webs more broadly however at present data using complete food webs is limited.

It was surprising that there was no positive relationship between body mass and trophic level for terrestrial mammals. The strong negative body mass and trophic level relationship described previously appears to be seen only when using data from whole food webs and a smaller sample size of mammals (Riede et al., 2011). Similar to this study, a weak relationship between body mass and trophic level is also seen in fish

(Jennings et al., 2001). By including the largest species, the marine mammals, I demonstrate that the trophic-level body-mass relationship may not be uniform across animals. The mysticete whales cluster towards the bottom right of the trophic-level body-mass relationship (having large body mass and yet feed at low trophic levels; Fig.

5.1B). As previous studies did not include the largest mammals (e.g. mysticete whales), the species that feed on prey within the lower trophic levels (~ 3 to 3.5), important information on trophic level patterns and the drivers behind these patterns have been missed.

5.5.2 Environmental Effects on Herbivory

Productivity appears to drive the differences in trophic-level patterns and food-web structures across the two environments. Marine productivity is driven by high quantities of small, single-celled primary producers, which is the reverse of the trophic-level patterns and food-web structures found on land. Vegetation on land (typically composed of complex long-chain chemical structures e.g. lignin), is generally multi- cellular, with a high proportion of structural tissues and chemical defences to protect themselves against herbivores (Shurin et al., 2006; Cebrian et al., 2009). Terrestrial 97

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vegetation has to compete for sunlight, nutrients and against the effects of gravity and a diverse array of vegetation types; fast (i.e. grasses) to slow (i.e. woody plants) growth rate (Polis & Strong, 1996) plant types have arisen. This provides terrestrial herbivores with a number of niches form browsers (woody-plant foliage specialists), granivores

(grain specialists) and frugivores (fruit specialists). The presence of numerous herbivorous niches has also driven the diversification and abundance of herbivorous mammals on land.

Although the primary productivity in the ocean supports complex food-webs and a greater range of trophic levels (Polis & Strong, 1996; Takimoto et al., 2012), herbivory is rare in marine mammals. Only one group of mammals, the sirenians (including dugongs, manatees and sea cows) are truly herbivorous. Marine mammal herbivores have restricted food resources on which they can feed: seagrass, multi-cellular algae or phytoplankton. The sirenians feed mostly on seagrasses but use multi-cellular algae (of marine origin) and mangrove leaves (of terrestrial origin) as well. Seagrasses are marine flowering plants that grow in meadows under restricted conditions, as they require shallow and sheltered coastal waters with a sandy or soft-mud substrate

(restricted to temperate and tropical coastlines across the globe) (Short et al., 2007).

The limited availability of seagrass habitat, and consequently seagrass, may have restricted herbivory in marine mammals. In comparison, the typically single-celled phytoplankton lack well-developed chemical defences, have fast growth rates and a high proportion of photosynthetic tissues which are high in phosphorous and nitrogen

(Shurin et al., 2006). The differences in structure and chemical stoichiometry of terrestrial and marine primary production means that marine herbivores feed on an abundant, nutrient-rich (high in phosphorous and nitrogen) and easily digested resource compared with terrestrial herbivores. Mammals have not specialised to use phytoplankton or multi-cellular algae as a primary food resource although phytoplankton may be ingested incidentally while filter feeding. 98

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5.5.3 Environmental Effects on Carnivory

The abundance of protein-rich resources (composed of amino acids) in the ocean supports a greater number of carnivorous marine mammals. The great quantities of phytoplankton in the ocean and aquatic bodies, support large communities of small zooplankton (passively moving aquatic organisms e.g. protozoans including foraminiferans, radiolarians and dinoflagellates). These tiny primary consumers eat the phytoplankton, along with bacterioplankton (the bacterial component of the plankton), detritus and other zooplankton. The zooplankton themselves become a source of energy for larger metazoan zooplankton (e.g. cnidarians such as jellyfish; crustaceans such as copepods and larval krill; molluscs such as pteropods; and chordates such as salps and juvenile fish). The metazoan zooplankton are in turn eaten by larger-sized metazoan zooplankton and/or nektonic species (actively swimming aquatic organisms e.g. molluscs such as squid and octopus; crustaceans such as krill and amphipods; and vertebrates such as fish, turtles, seals and whales). The small size and fast generation times of zooplanktonic species means that their communities can reproduce and grow rapidly to exploit increases in phytoplankton abundance, harnessing rapid spikes in primary productivity typical of phytoplanktonic blooms. This high abundance of small-sized primary producers and primary consumers supports a high diversity of small carnivorous species within the metazoan zooplanktonic, and in turn in the nektonic communities. The high abundance of small-sized organisms forming the base of marine food webs facilitates the presence of numerous steps within marine food chains, as larger species feed upon smaller species (Polis & Strong, 1996; Takimoto et al., 2012). The abundance of protein-rich resources spanning a range of body sizes from extremely small (30 µm) to large (13 000 kg) results in a wide range of available niches for carnivorous marine mammals, from invertebrate feeders (krill, amphipods, squid, shellfish etc.) to vertebrate consumers (fish, birds, mammals).

Chapter 5 – Predator-Prey Relationships and Trophic Level

5.5.4 Body Size, Diet and Environment

For mammals, changes in body mass have followed reverse patterns of diet dominance in the marine and terrestrial environments. Theory predicts that for mammals with increasing body mass the number of prey items they consume should decrease [11]. This is based on the imbalance between the increase in resources that larger carnivorous mammals require against the finite resources that are available to meet their requirements (Riede et al., 2011). This is the case for mammals living on land, where the majority of large mammals are herbivorous (Fig. S6.2). In the terrestrial environment, where vegetation is an abundant resource, most of the net primary productivity is lignocellulose, which is difficult for mammals to digest, and there is relatively little easily digestible material (Polis & Strong, 1996). Herbivorous land mammals have long, complex digestive systems to digest and assimilate nutrients from large quantities of poor-quality vegetation. They have symbiotic relationships with microbes and protozoa in their gut which assists in the further extraction of nutrients from their poor-quality diet (Polis & Strong, 1996; Smith et al., 2010) (Demment &

Soest, 1985). Herbivores retain vegetation within their digestive systems for long periods (up to 92 hours; Clauss et al., 2009) to allow enzymatic and microbial action to maximise the breakdown and then assimilation of nutrients (Demment & Soest, 1985).

In some instances, large body size has evolved to accommodate these long and complex digestive systems as well as the large quantities of poor-quality vegetation that need to be processed over long periods of time. This has resulted in the trend towards large body mass in terrestrial herbivorous mammals.

By contrast, there has been an increase in carnivore body size in the marine environment (Fig. S6.2). For marine carnivorous mammals, the combination of the thermal advantages, prey availability and hunting efficiency have resulted in large body size. Utilising dense aggregations of prey (up to 770 000 m-3; Nicol, 1986) has aided the evolution and maintenance of extreme body size in mysticete (~ 0.9 to 5 cm 100

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swarming prey) and odontocete (~ 1 to > 37 cm cephalopod prey) whales (Goldbogen et al., 2011). Large marine carnivores are more efficient at hunting than their terrestrial counterparts. Terrestrial carnivores spend long periods of time foraging (up to several hours) and expend large amounts of energy hunting (including capture and prey consumption; Williams & Yeates, 2004). Marine carnivores, particularly those above

100kg, have a higher hunting efficiency (Williams & Yeates, 2004). They have evolved physiological (e.g. increased levels of globins for more efficient oxygen transfer;

Williams et al., 2008), morphological (e.g. feeding apparatus such as baleen) and behavioural traits (e.g. alternate forms of locomotion during diving; Williams, 1999) to become more energy efficient hunters. Marine vegetation contains small amounts of lignin and cellulose so that higher amounts of nutrients are available to marine consumers (including zooplankton, fish and sirenians) which passes up through the food web (Polis & Strong, 1996; Shurin et al., 2006). This greater productivity provides support for large populations of consumers, resulting in the reverse patterns to that seen on land (Riede et al., 2011). Where marine clades (cetaceans, pinnipeds and sirenians) tend to stick to a single diet type (i.e. either carnivory or herbivory), some terrestrial carnivorous mammals switch between diets depending on food availability

(e.g. bears shift between omnivory and carnivory; Price et al., 2012).

Not only have there been changes in body mass across different diets, we also see changes in minimum and maximum body size trends across marine and terrestrial mammals. This is driven by the combined effects of environmental characteristics, physiology and vegetation/prey availability. Terrestrial mammals can reach smaller body sizes compared to marine mammals (~0.001 kg vs. ~10 kg; Smith & Lyons,

2011). Mammals living in the water experience high thermoregulation costs and this constrains how small a marine mammal can be. This is accentuated at birth when the surface area to body volume is high, resulting in an increased rate of heat loss and energy spent on maintaining body temperature (Downhower & Blumer, 1988; Smith & 101

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Lyons, 2011). Four of the six marine mammal lineages have retained giving birth and raising their young out of the water, either on land or ice (mustelids, otariids, phocids, and ursids). For both young and adults, it is a thermal advantage to have larger body size in the marine environment. Marine mammals reach much larger body sizes than terrestrial mammals (~ 4 tonne vs. ~ 200 tonne; Smith & Lyons, 2011).

On land, resource availability constrains how large mammals can become because having a large body size has high energetic costs and requires abundant and reliable resources. In particular, the interaction between resource availability, land mass area, and the cost of gathering sufficient resources limits how large a terrestrial mammal can become (Burness et al., 2001). In the ocean, similar constraints are present, but take effect at a much larger body size. For example, the size of the blue whale is likely to be constrained by biomechanical limitations (e.g. gape size and lunge feeding costs) and prey availability (e.g. prey density; Goldbogen et al., 2011).

5.5.5 Trophic level and predator-prey ratio relationships

A general rule for the relationship between PP ratio and the trophic level of carnivorous mammals appears to apply to both the marine and terrestrial environments. With increasing trophic level, carnivores shift to feeding on prey that have a body mass more similar to that of the carnivore’s own body mass (i.e. PP ratio approaching ≥ 1). The underlying drivers behind this negative relationship are believed to be the combined effects of increasing body mass with trophic level for endotherms, and increasing prey mass with increasing carnivore body mass (Riede et al., 2011). However, this study suggests that there are issues with this reasoning as: (1) I did not find a relationship between trophic level and carnivore body mass; and (2) whilst terrestrial carnivores demonstrate a positive relationship between carnivore body size and prey body size

(Carbone et al., 1999), this is not the case for many marine carnivores (e.g. mysticete whales feeding on krill). 102

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The large predator-prey body-mass ratios found in the marine system are not plausible on land, as small prey (excluding invertebrates) do not form large swarms or groups that are easily accessible as they do in the ocean. In the marine system, small prey such as plankton or fish form large aggregations (schools or swarms) as protection from predation. Large marine mammals, such as the mysticetes and smaller marine mammals such as seals, have morphological adaptations for bulk feeding (e.g. baleen instead of teeth in mysticete whales and specialised multi-cuspidate teeth in pinnipeds) and behavioural (bubble netting, group feeding, lunge diving) specialisations to capture large quantities of small prey in a single feeding event. Harvesting small-sized swarming prey requires minimal capture (individual pursuit and capture) and processing (e.g. butchering) time. There are invertebrate-feeding specialists on land, yet this type of diet can support animals only up to the restricted weight range of under

20kg due to the increasing costs associated with larger body mass (Carbone et al.,

2007a). For terrestrial mammalian carnivores the abundance, distribution and energy content of terrestrial invertebrates are not sufficient to support body masses above

20kg (Carbone et al., 2007a).

An implication, arising from the combination of a mean trophic level position of 3.9 for marine carnivores and the abundance of higher PP ratios in the marine environment, is its effect on trophic efficiency. Trophic efficiency includes the exchange of energy between trophic levels based on predator-prey interactions, but excludes growth (i.e. somatic) (Andersen et al., 2009a). When PP ratios are large, trophic efficiency decreases (Andersen et al., 2009a). For example, a marine organism with a PP ratio of

1000 has an efficiency of ~13%, compared with a marine organism with a PP ratio of

10 that has an efficiency of 50% (irrespective of size or trophic position; Andersen et al., 2009b). This has follow-on effects for the energy flow through an ecosystem, as well as community structure and dynamics. However, this is less of an issue in the marine environment, where large PP ratios (i.e. predators are larger than their prey) 103

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increase the stability of marine food webs (Brose et al., 2006a; Kartascheff et al., 2010;

Heckmann et al., 2012). Large PP ratios cause a reduction in the interaction strengths between predators and their prey (per unit biomass) (Yodzis & Innes, 1992; Brose et al., 2005). In addition, there are benefits for carnivores that feed from lower trophic levels. The similarity between the tissue composition of carnivores and their prey

(amino acids) has been shown to result in higher energy transfer efficiencies (Sterner &

Elser, 2002; Dickman et al., 2008). When herbivores are included in a food chain, this can limit the energy efficiency between trophic levels. This is because of the decreased assimilation efficiency of herbivores who have greater difficulty extracting energy from plants with high carbon-nitrogen ratios (Frost et al., 2006).

This study provides insights into the drivers behind mammalian predator-prey body- mass ratios, trophic-level positions and body mass. I caution that my approach is simplistic, yet ecosystems are often complex. Collecting prey-preference and trophic level information from the literature has limitations. Historical studies may have over simplified food webs (Polis, 1991). While I attempted to select studies that did not oversimplify food-web data, as I examined patterns across mammals and from a wide range of food webs with different structures, this may not have always been the case.

Into the future I propose using equations that incorporate complete food web data to calculate trophic levels (Williams & Martinez, 2004).

At present we are restricted by the limited amount of detailed food web data available.

To gather information across 107 species I was reliant upon published dietary studies and this biased data toward well-studied species. Unfortunately this cannot be avoided at present and can only be overcome by further research into lesser known species, which are often difficult to study (e.g. beaked whales). This study provides a framework for exploring how environment impacts upon the broad patterns in ecology across the marine and terrestrial systems. 104

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5.6 CONCLUSION

These results demonstrate that primary productivity, and its availability, is important for the mammalian trophic structure of food webs, body size and prevalence of carnivory and herbivory. Marine and terrestrial mammals share the same relationship between trophic level and mass, with the trophic level of marine species shifting 1.3 levels higher. Interestingly, carnivorous mammals do not follow strictly the expected patterns for the relationship between trophic level and body mass (i.e. positive or quadratic).

While there is a distinct shift in trophic position between marine and terrestrial carnivores (Fig. 1A), I did not find a positive relationship or a quadratic relationship.

The marine environment has a higher abundance of carnivorous mammals and a shift towards larger minimal and maximal body size. The terrestrial system has greater diversification of herbivores and a general trend towards a smaller minimal and maximal body size. The relationship between body mass and diet on land has been reversed in the marine system, where carnivores tend to be larger and herbivores smaller, the opposite to terrestrial mammals. The patterns in trophic level and PP ratio are stronger within each environment than across mammals in general, further suggesting the importance of environment.

When mammals colonised the marine environment, the shift from a plant-dominated landscape to a habitat rich in protein-rich resources, with little competition, resulted in changes to the trophic-level relationships, dietary niches and foraging ecology. Large body mass, the shift in available resources and altered physiology have driven marine mammals to be largely carnivorous. Marine carnivores consume highly mobile prey that sit within a wide range of trophic levels and have smaller body masses compared with terrestrial carnivores which in the main consume larger prey, to meet their metabolic requirements. This study illustrates the influence this shift in environment has had on

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mammalian ecology and the importance of utilising this information to examine the structure and function of marine and terrestrial communities.

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Chapter 6 General Conclusion

Body size is a fundamental trait of animals which has driven the macroecological patterns of mammalian spatial behaviour, carnivorous strategies and trophic level, providing the basis for many ecological theories. It was necessary to re-examine these macroecological patterns because previous research had been performed on a restricted group of mammalian representatives, largely excluding both aquatic and aerial species. This causes issues for the broad application of the ecological theories due to the effect that environment can have on macroecological patterns. With extinction rates across mammals increasing due to the conflict between human activities and mammals (González-Suárez & Revilla, 2014), it is crucial that we are confident about our broad-scale ecological theories, where information is extracted by conservation managers in order to construct management plans.

I have demonstrated that whilst body mass is a key factor driving home range size, carnivore feeding strategies and trophic structure are also influenced by diet and the environment in which a species resides. As information on spatial behaviour, predator- prey relationships and trophic structure is often incorporated into conservation plans or managements strategies, we need to be confident that the ecological theories are providing accurate information (Margules & Pressey, 2000).

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6.1 HOME RANGE SIZE

There have been numerous studies examining home range patterns in mammals at a macroecological level (Burt, 1943; McNab, 1963; Lindstedt et al., 1986; Swihart et al.,

1988; Kelt & Van Vuren, 1999), however, the most recent of these was by Jetz et al.

(2004). Most home range investigations that have been carried out over the past 9 years have been focused on a single species (Andres et al., 2013; Newsome et al.,

2013; Niemi et al., 2013; Pearce et al., 2013). With the combination of phylogenetic information, over 600 species spanning various diets and environments I revisited home range patterns in mammals (Chapter 2). The objectives of Chapter 2 were achieved: (1) the level of support for the relationship between diet and home range among 279 species of terrestrial mammals was re-examined; and (2) the dataset was expanded to cover both marine and terrestrial species, to examine the effects of living within fundamentally different environments including physiology, morphology and ecology. The results demonstrated that home range is a complex behaviour influenced by a range of factors including body size and its influence on energetic costs and intake, diet and its influence on resource distribution and lastly environment and its overarching influence on body size and food resources. Despite diet being suggested as one of the main driving forces behind home range size (Kelt & van Vuren, 2001), I found that its influence is limited compared to the effect of body size. If we are to delve into how home range has evolved, we need to examine physiological drivers and how this influences animal movements (e.g. cost of transport vs. home range size).

The macroecological approach I have taken to investigate home range patterns is only one way of exploring the driving factors of animal space use. There is also an active field of research using smaller scale approaches including the combination of spatial learning or cognitive maps and state-space modelling. For example, use of the mechanistic optimality models of Bayesian foraging and correlated random-walk

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models has led to insights into why home range exists as well as into home range structure and stability, home range overlap and territoriality and the cognitive mechanisms behind these patterns (Spencer, 2012; Bestley et al., 2013). The majority of the approach utilises data from either a couple of species or computer simulations to predict and build the underlying theories of space use in animals. I think there is benefit from using both methodology types, macroecology and mechanistic models, as approaching the task from different angles allows us to better understand what is driving animal movement patterns at varying spatial scales.

6.2 MINIMUM, MAXIMUM AND RANGE OF PREY MASS

Carnivorous mammals are a diverse group of species which have evolved to consume a wide range of resources from invertebrates through to large mammals. A large quantity of research has been performed on carnivores and their vulnerability to changes within their environment (Purvis et al., 2000; Gittleman & Gompper, 2005;

Cardillo et al., 2008; Lau et al., 2010; Carbone et al., 2011; Angerbjörn et al., 2013).

Carnivores across the globe are having to adapt to change, whether it be habitat loss and harvesting on land (Schipper, 2008) or fisheries and ocean acidification within the ocean (Hilborn et al., 2003; Hoegh-Guldberg & Bruno, 2010; Schiermeier, 2010).

As our knowledge on the broad scale relationship between carnivore mass and the minimum, maximum and range of prey mass is limited, the aim of Chapter 3 was to investigate how environment and phylogenetic relatedness influences predator-prey relationships across over 100 carnivorous mammal species. I demonstrate that in the terrestrial environment carnivores have a positive relationship between prey mass

(minimum, maximum and range) and carnivore mass, as previously demonstrated in birds and lizards. In contrast, there is no relationship between prey mass and carnivore mass in aquatic carnivores. Differences in the environmental characteristics (e.g.

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trophic structure and dimensionality) across the terrestrial and aquatic environments are likely to be driving these differences. My findings are important for understanding the relationship between mammalian carnivore foraging strategies and body size, and the role of environment and evolutionary history has had on these patterns. This information will aid with predictions of carnivore susceptibility to population declines and the role of carnivores across different ecosystems. To my knowledge, my work in

Chapter 3 is the first attempt to examine the upper/lower limits and range of prey mass consumed by mammalian carnivores.

In Chapter 3, I utilised data extracted from the vast literature investigating mammalian diets. Despite the abundant publications, information on diet across mammals are incomplete with data lacking for species that a difficult to study (e.g. rare or pelagic species). There costs (both monetary and time) associated with collecting this type of data, which also limits the information available. With improving technologies, such as the increasing use of stable isotopes (Marques et al., 2014; Middelburg, 2014;

Teunissen van Manen et al., 2014), data collection issues will be minimised and a more complete picture of diet information will be obtained.

6.3 CARNIVOROUS STRATEGIES

The objective of Chapter 4 was to examine how marine mammals might have adapted their feeding strategies to compensate for living within a three-dimensional aquatic environment. Chapter 4 expands our current knowledge on the relationship between carnivores and their prey by demonstrating that differences in food web structure between the marine and terrestrial environment has driven the evolution of quite different feeding strategies. Due to the evolution of varying carnivorous strategies, where marine and terrestrial carnivores are exploiting prey of different body sizes and trophic positions, it is probable that carnivores will respond to changes differently

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depending on their environment and its food web structure. For example, Antarctic whales are impacted directly by changes within the lower trophic levels such as the drastic drop in krill over the past 40 years which is driven by increasing ocean temperatures and decreasing sea ice cover (Reid & Croxall, 2001; Atkinson et al.,

2004). This is particularly pertinent as the majority of Antarctic whales migrate to reproduce and mate, relying on the Antarctic summer to feed and store reserves for the migration.

Additionally, carnivores have varying top-down effects on food webs within their respective systems depending on their trophic position. Apex predators, carnivores that are at the top of the food chain and have no or few predators of their own, can have wide scale impacts by influencing mesoconsumers and their associated resources

(Heithaus et al., 2008). This includes the mediation of mortality rates (including density), prey behaviour and habitat structure (Heithaus et al., 2008), which can have severe effects on the ecosystem such as a trophic cascade if the apex predator is removed. Examples of this effect can be found in both marine and terrestrial environments. For example, morwong (a temperate reef fish, Chelilodactulus nigripes) decrease their foraging effort leading to the reduced grazing of turf algae in the presence of New Zealand fur seals (Arctocephalus forsteri) (Connell, 2002). In the terrestrial system, the reintroduction of wolves (Canis lupis) into Yellowstone National

Park has resulted in the population control of elk (Cervus elaphus), decreasing the herbivory effect of the elk on the aspen population (Populus tremuloides) (Ripple &

Beschta, 2007).

Carnivores can also be classified as mesopredators and include species that feed on small birds and mammals. Mesopredator populations are controlled by apex predators, but problems can arise when apex predators are removed, allowing mesopredator populations to increase resulting in prey declines and ecosystem destabilisation (Prugh 111

Chapter 6 - Discussion

et al., 2009). For example, the use of dingoes to control fox populations to enable to success of small native Australian mammals (Letnic et al., 2011). Lastly, mammalian insectivores play a large role in terrestrial plant-arthropod communities, where is has been demonstrated that insectivores can reduce herbivory by 40% (Mooney et al.,

2010). In the marine system, whales have been identified as major forces impacting the trophic structure of the Southern Ocean (Ainley et al., 2010). This was based on whales feeding upon krill and fish and therefore competing with penguin populations for a potentially limited resource (Ainley et al., 2010).

6.4 TROPHIC LEVEL

Improving our knowledge of the trophic level concept is important for informing our understanding of energy flow as well as top-down and bottom-up control of food webs.

This information then feeds into real world applications including predicting human impacts of food webs and constructing and producing ecosystem models. The objective of Chapter 5 was to investigate how the colonisation of the marine and terrestrial environments has impacted upon the relationship between body size, trophic level and predator-prey ratio (PP ratio) across mammals. This was accomplished using diet information (including predator mass, prey mass and diet niche) and trophic level data for terrestrial and marine mammals. Difference in primary productivity between the marine and terrestrial environments are driving differences in the trophic position, PP ratios and body size of mammals and the resources utilised by them.

Whilst incorporating the prevalence of herbivory and carnivory within this thesis, the analysis of trophic structure is simplified, focusing largely upon carnivorous species and excluding omnivorous species. Omnivory has been proven to be important in food web structure particularly in long food chain (Thompson et al., 2007). The next step of this research would be increase the complexity of the analysis and alter the

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classification of diet to include omnivores to refine the analysis and patterns found in

Chapter 5.

Trophic level patterns and information are useful for predicting the movement of compounds such as iron, copper and zinc, which are useful dietary tracers, and other substances such as toxins, which are transferred through foodwebs (Jaouen et al.,

2013). Gathering further information on trophic interactions is important for improving our understanding of top-down and bottom-up drivers of trophic levels, as well as their role in structuring ecosystems (past, present and future) (Sandom et al., 2013).

6.5 GENERAL FINDINGS

With the incorporation of phylogenetic information into the analyses, I was able to identify the importance and influence of phylogenetic signal (as seen in null and mass models in Chapters 2, 3 and 5). This adds additional weight to the argument that phylogenetic information should be included when comparing a wide range of species

(Harvey, 1996; Chamberlain et al., 2012). The effect of phylogenetic information was highlighted in Chapter 2, where the scaling of home range size with body mass was equal across diet categories of terrestrial mammals, contrary to previous studies using the same data. Currently the mammalian phylogeny includes unresolved relationships between species resulting in uncertainties across the tree. Within this thesis, I have attempted to incorporate this uncertainty into my analyses however, with future research the uncertainty within the mammalian phylogeny may be resolved, further clarifying any patterns found.

Dimension is likely to play a large role in the patterns found within this thesis (Chapter

2 to 5). Recently some theoretical work has demonstrated that within a 3-dimensional environment there are increased encounter rates with resources when compared with a 113

Chapter 6 - Discussion

2-dimenstional environment (Pawar et al., 2012). Additionally, there are further implications of dimension for food-web dynamics and consumer-resource dynamics

(Pawar et al., 2012; Dell et al., 2013). A closer examination of the effect of dimension would be a next step to the work carried out in this thesis, to determine whether there are dimensionality influences on scaling or other ecological traits. This would be accomplished using a theoretical approach and mechanistic models (as seen in

Carbone et al., 2007b).

A suite of studies have been carried out looking at changes in body size over time

(Smith et al., 2010; Evans et al., 2012; Smith & Lyons, 2013), however it would be of interest to examine changes in space use, carnivorous strategies and trophic level not only across space, but also time. How have these patterns change historically? This would provide useful information not only on human impacts but also the effect of other processes such glacial periods and changes in atmospheric oxygen.

Lastly, in Chapters 2 and 5 there is still some residual variance for home range size and trophic level that was not explained by body size or environment. As a next step, it would be worth exploring what is behind this variance, as it accounts for between 32 and 52% to the total variance. Potential factors may include resource density (e.g. units per km2), available area (or geographic range) and population abundance. The incorporation of more information would involve shifting from phylogenetic regression models towards linear mixed models.

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6.6 CONCLUSION

This thesis demonstrated the value in harnessing the plethora of published data to re- examine ecological theories and identify the driving influences of macroecological patterns. I show that living in different environments impacts upon spatial behaviour, foraging, food web structure and energetics. When developing general rules, we need to account for and include information on intrinsic and extrinsic factors such as diet, environment, and phylogenetic relatedness. Into the future, the combination of continual data collection and the formation of large global databases will enable us to delve into large-scale ecological patterns and processes.

115

References

Agnarsson, I., Kuntner, M. & May-Collado, L.J. (2010) Dogs, cats, and kin: A molecular species-level phylogeny of Carnivora. Molecular Phylogenetics and Evolution, 54, 726-745. Agosta, S.J. & Bernardo, J. (2013) New macroecological insights into functional constraints on. Ainley, D., Ballard, G., Blight, L.K., Ackley, S., Emslie, S.D., Lescroël, A., Olmastroni, S., Townsend, S.E., Tynan, C.T., Wilson, P. & Woehler, E. (2010) Impacts of cetaceans on the structure of Southern Ocean food webs. In, pp. 482-498. Wiley-Blackwell Alerstam, T., Hedenström, A. & Åkesson, S. (2003) Long‐distance migration: evolution and determinants. Oikos, 103, 247-260. Almany, G.R. (2004) Differential effects of habitat complexity, predators and competitors on abundance of juvenile and adult coral reef fishes. Oecologia, 141, 105-113. Andersen, K.H., Beyer, J. & Lundberg, P. (2009a) Trophic and individual efficiencies of size-structured communities. Proceedings of the Royal Society B: Biological Sciences, 276, 109-114. Andersen, K.H., Beyer, J.E. & Lundberg, P. (2009b) Trophic and individual efficiencies of size-structured communities. Proceedings of the Royal Society B: Biological Sciences, 276, 109-114. Anderson, K.J. & Jetz, W. (2005) The broad-scale ecology of energy expenditure of endotherms. Ecology Letters, 8, 310-318. Andersson, K., Norman, D. & Werdelin, L. (2011) Sabretoothed Carnivores and the Killing of Large Prey. PLoS ONE, 6, e24971. Andres, D., Clutton-Brock, T.H., Kruuk, L.E., Pemberton, J.M., Stopher, K.V. & Ruckstuhl, K.E. (2013) Sex differences in the consequences of maternal loss in a long-lived mammal, the red deer (Cervus elaphus). Behavioral Ecology and Sociobiology, 1-10. Angerbjörn, A., Eide, N.E., Dalén, L., Elmhagen, B., Hellström, P., Ims, R.A., Killengreen, S., Landa, A., Meijer, T., Mela, M., Niemimaa, J., Norén, K., Tannerfeldt, M., Yoccoz, N.G. & Henttonen, H. (2013) Carnivore conservation in practice: replicated management actions on a large spatial scale. Journal of Applied Ecology, 50, 59-67. Arendt, J.D. & Reznick, D.N. (2005) Evolution of juvenile growth rates in female guppies (Poecilia reticulata): predator regime or resource level? Proceedings of the Royal Society B: Biological Sciences, 272, 333-337. Ashton, K.G., Tracy, M.C. & Queiroz, A.d. (2000) Is Bergmann’s Rule Valid for Mammals? The American Naturalist, 156, 390-415. Atkinson, A., Siegel, V., Pakhomov, E. & Rothery, P. (2004) Long-term decline in krill stock and increase in salps within the Southern Ocean. Nature, 432, 100-103. Banbury, B.L. & O'Meara, B.C. (2014) Reol: R interface to the Encyclopedia of Life. Ecology and Evolution, 4, 2577-2583. Barnes, C., Maxwell, D., Reuman, D.C. & Jennings, S. (2010) Global patterns in predator-prey size relationships reveal size dependency of trophic transfer efficiency. Ecology, 91, 222-232. Bates, D., Maechler, M., Bolker, B. & Walker, S. (2013) lme4: Linear mixed-effects models using Eigen and S4. R package version 1.0-5. http://CRAN.R- project.org/package=lme4.

116

References

Bergmann, C. (1847) Ueber die Verhaeltnisse der Waermeoekonomie der Thiere zu ihre Groesse. Goettinger Studien, Pt. 1, 595-708. Bestley, S., Jonsen, I.D., Hindell, M.A., Guinet, C. & Charrassin, J.-B. (2013) Integrative modelling of animal movement: incorporating in situ habitat and behavioural information for a migratory marine predator. Proceedings of the Royal Society B: Biological Sciences, 280 Beyer, H. (2004) Hawth's Tools: An extension for ArcGIS. Available at: http://www.spatialecology.com. Last accessed 06 March 2010. Available at: (accessed Bielby, J., Mace, G., Bininda‐Emonds, O., Cardillo, M., Gittleman, J., Jones, K., Orme, C. & Purvis, A. (2007) The Fast‐Slow Continuum in Mammalian Life History: An Empirical Reevaluation. The American Naturalist, 169, 748-757. Bininda-Emonds, O.R., Cardillo, M., Jones, K.E., MacPhee, R.D., Beck, R.M., Grenyer, R., Price, S.A., Vos, R.A., Gittleman, J.L. & Purvis, A. (2007) The delayed rise of present-day mammals. Nature, 446, 507-512. Blackburn, T.M. & Gaston, K.J. (1999) The relationship between animal abundance and body size: a review of the mechanisms. Advances in ecological research, 28, 181-210. Block, B., Jonsen, I., Jorgensen, S., Winship, A., Shaffer, S., Bograd, S., Hazen, E., Foley, D., Breed, G. & Harrison, A.-L. (2011) Tracking apex marine predator movements in a dynamic ocean. Nature, 475, 86-90. Bodine, M.C. & Ueckert, D.N. (1975) Effect of desert termites on herbage and litter in a shortgrass ecosystem in west Texas. Journal of Range Management Archives, 28, 353-358. Börger, L., Franconi, N., Ferretti, F., Meschi, F., De Michele, G., Gantz, A. & Coulsen, T. (2006a) An integrated approach to identify spatio-temporal and individual- level determinants of animal home range size. American Naturalist, 168, 471- 485. Börger, L., Franconi, N., De Michele, G., Gantz, A., Meschi, F., Manica, A., Lovari, S. & Coulson, T.I.M. (2006b) Effects of sampling regime on the mean and variance of home range size estimates. Journal of Animal Ecology, 75, 1393-1405. Borrvall, C., Ebenman, B. & Tomas Jonsson, T.J. (2000) Biodiversity lessens the risk of cascading extinction in model food webs. Ecology Letters, 3, 131-136. Boyd, I. (1997) The behavioural and physiological ecology of diving. Trends in Ecology & Evolution, 12, 213-217. Boyd, I.L. & Murray, A.W.A. (2001) Monitoring a marine ecosystem using responses of upper trophic level predators. Journal of Animal Ecology, 70, 747-760. Boyer, A.G., Cartron, J.L.E. & Brown, J.H. (2010) Interspecific pairwise relationships among body size, clutch size and latitude: deconstructing a macroecological triangle in birds. Journal of Biogeography, 37, 47-56. Braendle, M., Prinzing, A., Pfeifer, R. & Brandl, R. (2002) Dietary niche breadth for Central European birds: correlations with species-specific traits. Evolutionary Ecology Research, 4, 643-657. Brandl, R., Kristín, A. & Leisler, B. (1994) Dietary niche breadth in a local community of passerine birds: an analysis using phylogenetic contrasts. Oecologia, 98, 109- 116. Brierley, A.S. & Cox, M.J. (2010) Shapes of Krill Swarms and Fish Schools Emerge as Aggregation Members Avoid Predators and Access Oxygen. Current Biology, 20, 1758-1762. Bromham, L., Lanfear, R., Cassey, P., Gibb, G. & Cardillo, M. (2012) Reconstructing past species assemblages reveals the changing patterns and drivers of extinction through time. Proceedings of the Royal Society B: Biological Sciences, 279, 4024-4032.

117

References

Brose, U. (2010) Body-mass constraints on foraging behaviour determine population and food-web dynamics. Functional Ecology, 24, 28-34. Brose, U., Berlow, E.L. & Martinez, N.D. (2005) Scaling up keystone effects from simple to complex ecological networks. Ecology Letters, 8, 1317-1325. Brose, U., Williams, R.J. & Martinez, N.D. (2006a) Allometric scaling enhances stability in complex food webs. Ecology Letters, 9, 1228-1236. Brose, U., Jonsson, T., Berlow, E.L., Warren, P., Banasek-Richter, C., Bersier, L.-F., Blanchard, J.L., Brey, T., Carpenter, S.R., Blandenier, M.-F.C., Cushing, L., Dawah, H.A., Dell, T., Edwards, F., Harper-Smith, S., Jacob, U., Ledger, M.E., Martinez, N.D., Memmott, J., Mintenbeck, K., Pinnegar, J.K., Rall, B.C., Rayner, T.S., Reuman, D.C., Ruess, L., Ulrich, W., Williams, R.J., Woodward, G. & Cohen, J.E. (2006b) Consumer–resource body-size relationships in natural food webs. Ecology, 87, 2411-2417. Brown, J.H. (1995) Macroecology. University of Chicago Press, Chicago. Brown, J.H. (2014) Why are there so many species in the tropics? Journal of Biogeography, 41, 8-22. Brown, J.H., Calder, W.A. & Kodric-Brown, A. (1978) Correlates and consequences of body size in nectar-feeding birds. American Zoologist, 18, 687-738. Brown, J.H., Marquet, P.A. & Taper, M.L. (1993) Evolution of body size: consequences of an energetic definition of fitness. American Naturalist, 573-584. Brown, J.H., Gillooly, J.F., Allen, A.P., Savage, V.M. & West, G.B. (2004a) Response to forum commentary on “toward a metabolic theory of ecology”. Ecology, 85, 1818-1821. Brown, J.H., Gillooly, J.F., Allen, A.P., Savage, V.M. & West, G.B. (2004b) Toward a metabolic theory of ecology. Ecology, 85, 1771-1789. Brown, J.H., Gupta, V.K., Li, B.-L., Milne, B.T., Restrepo, C. & West, G.B. (2002) The Fractal Nature of Nature: Power Laws, Ecological Complexity and Biodiversity. Philosophical Transactions: Biological Sciences, 357, 619-626. Burness, G.P., Diamond, J. & Flannery, T. (2001) Dinosaurs, dragons, and dwarfs: The evolution of maximal body size. Proceedings of the National Academy of Sciences, 98, 14518-14523. Burnham, K.P. & Anderson, D.R. (2002) Model Selection and Multimodal Inference: A practical Information-Theoretical Approach. Springer, New York. Burnham, K.P., Anderson, D.R. & Huyvaert, K.P. (2011) AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons. Behavioral Ecology and Sociobiology, 65, 23-35. Burt, W.H. (1943) Territoriality and Home Range Concepts as Applied to Mammals. Journal of Mammalogy, 24, 346-352. Caballero, S., Jackson, J., Mignucci-Giannoni, A.A., Barrios-Garrido, H., Beltrán- Pedreros, S., Montiel-Villalobos, M.G., Robertson, K.M. & Baker, C.S. (2008) Molecular systematics of South American dolphins Sotalia: Sister taxa determination and phylogenetic relationships, with insights into a multi-locus phylogeny of the Delphinidae. Molecular Phylogenetics and Evolution, 46, 252- 268. Carbone, C. & Gittleman, J.L. (2002) A common rule for the scaling of carnivore density. Science, 295, 2273-2276. Carbone, C., Teacher, A. & Rowcliffe, J., M. (2007a) The costs of carnivory. PLoS Biology, 5, 363-368. Carbone, C., Pettorelli, N. & Stephens, P.A. (2011) The bigger they come, the harder they fall: body size and prey abundance influence predator–prey ratios. Biology Letters, 7, 312-315. Carbone, C., Mace, G.M., Roberts, S.C. & Macdonald, D.W. (1999) Energetic constraints on the diet of terrestrial carnivores. Nature, 402, 286-288.

118

References

Carbone, C., Cowlishaw, G., Isaac, N.J.B. & Rowcliffe, J.M. (2005) How far do animals go? Determinants of day range in mammals. The American Naturalist, 165, 290-297. Carbone, C., Rowcliffe, M.J., Cowlishaw, G. & Isaac, N.J.B. (2007b) The scaling of abundance in consumers and their resources: Implications for the energy equivalence rule. The American Naturalist, 170, 479-484. Cardillo, M., Mace, G.M., Gittleman, J.L., Jones, K.E., Bielby, J. & Purvis, A. (2008) The predictability of extinction: biological and external correlates of decline in mammals. Proceedings of the Royal Society B: Biological Sciences, 275, 1441- 1448. Cardillo, M., Mace, G.M., Jones, K.E., Bielby, J., Bininda-Emonds, O.R., Sechrest, W., Orme, C.D.L. & Purvis, A. (2005) Multiple causes of high extinction risk in large mammal species. Science, 309, 1239-1241. Ceballos, G. & Ehrlich, P.R. (2002) Mammal population losses and the extinction crisis. Science, 296, 904-907. Cebrian, J., Shurin, J.B., Borer, E.T., Cardinale, B.J., Ngai, J.T., Smith, M.D. & Fagan, W.F. (2009) Producer nutritional quality controls ecosystem trophic structure. PLos One, 4, e4929. Chamberlain, S.A., Hovick, S.M., Dibble, C.J., Rasmussen, N.L., Van Allen, B.G., Maitner, B.S., Ahern, J.R., Bell-Dereske, L.P., Roy, C.L., Meza-Lopez, M., Carrillo, J., Siemann, E., Lajeunesse, M.J. & Whitney, K.D. (2012) Does phylogeny matter? Assessing the impact of phylogenetic information in ecological meta-analysis. Ecology Letters, 15, 627-636. Chown, S.L. & Gaston, K.J. (2010) Body size variation in insects: a macroecological perspective. Biological Reviews, 85, 139-169. Clark, M.J. & Poole, W. (1967) The reproductive system and embryonic diapause in the female kangaroo, Marcopodus giganteus. Australian Journal of Zoology, 15, 441-459. Clarke, A. & O'Connor, M.I. (2014) Diet and body temperature in mammals and birds. Global Ecology and Biogeography, Clarke, A., Rothery, P. & Isaac, N.J.B. (2010) Scaling of basal metabolic rate with body mass and temperature in mammals. Journal of Animal Ecology, 79, 610-619. Clauset, A. (2013) How large should whales be? arXiv preprint arXiv:1207.1478, Clauss, M., Nunn, C., Fritz, J. & Hummel, J. (2009) Evidence for a tradeoff between retention time and chewing efficiency in large mammalian herbivores. Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology, 154, 376-382. Clauss, M., Steuer, P., Müller, D.W.H., Codron, D. & Hummel, J. (2013) Herbivory and Body Size: Allometries of Diet Quality and Gastrointestinal Physiology, and Implications for Herbivore Ecology and Dinosaur Gigantism. PLoS ONE, 8, e68714. Clauss, M., Frey, R., Kiefer, B., Lechner-Doll, M., Loehlein, W., Polster, C., Rössner, G. & Streich, W.J. (2003) The maximum attainable body size of herbivorous mammals: morphophysiological constraints on foregut, and adaptations of hindgut fermenters. Oecologia, 136, 14-27. Clementz, M.T., Fordyce, R.E., Peek, S.L. & Fox, D.L. (2014) Ancient marine isoscapes and isotopic evidence of bulk-feeding by Oligocene cetaceans. Palaeogeography, Palaeoclimatology, Palaeoecology, 400, 28-40. Connell, S.D. (2002) Effects of a predator and prey on a foraging reef fish: implications for understanding density‐dependent growth. Journal of Fish Biology, 60, 1551- 1561. Cooper, N. & Purvis, A. (2010) Body Size Evolution in Mammals: Complexity in Tempo and Mode. The American Naturalist, 175, 727-738.

119

References

Cooper, W.E. & Stankowich, T. (2010) Prey or predator? Body size of an approaching animal affects decisions to attack or escape. Behavioral Ecology, 21, 1278- 1284. Cope, E.D. (1986) The primary factors of organic evolution. Open Court Publishing, Chicago, IL. Costa, D.P. (2007) A conceptual model of the variation in parental attendance in response to environmental fluctuation: foraging energetics of lactating sea lions and fur seals. Aquatic Conservation: Marine and Freshwater Ecosystems, 17, S44-S52. Costa, D.P., Robinson, P.W., Arnould, J.P.Y., Harrison, A., Simmons, S.E., Hassrick, J.L., Hoskins, A.J., Kirkman, S.P., Oosthuizen, H., Villegas-Amtmann, S. & Crocker, D.E. (2010) Accurcy of ARGOS locations of pinniped at-sea eastimated using Fastloc GPS. PLos One, 5, e8677. Costa, G.C. (2009) Predator Size, Prey Size, and Dietary Niche Breadth Relationships in Marine Predators. Ecology, 90, 2014-2019. Costa, G.C., Vitt, L.J., Pianka, E.R., Mesquita, D.O. & Colli, G.R. (2008) Optimal foraging constrains macroecological patterns: body size and dietary niche breadth in lizards. Global Ecology and Biogeography, 17, 670-677. Courchamp, F. & Macdonald, D.W. (2001) Crucial importance of pack size in the African wild dog Lycaon pictus. Animal Conservation, 4, 169-174. Cox, M.J., Demer, D.A., Warren, J.D., Cutter, G.R. & Brierley, A.S. (2009) Multibeam echosounder observations reveal interactions between Antarctic krill and air- breathing predators. Marine Ecology Progress Series, 378, 199-209. Creel, S. (1997) Cooperative hunting and group size: assumptions and currencies. ANimal behaviour, 54, 1319-1324. Dalerum, F. (2013) Phylogenetic and functional diversity in large carnivore. Dalla Rosa, L., Secchi, E.R., Maia, Y.G., Zerbini, A.N. & Heide-Jorgensen, M.P. (2008) Movements of satellite-monitored humpback whales on their feeding ground along the Antarctic Peninsula. Polar Biology, 31, 771-781. Dalton, A.J.M., Rosen, D.A.S. & Trites, A.W. (2014) Season and time of day affect the ability of accelerometry and the doubly labeled water methods to measure energy expenditure in northern fur seals (Callorhinus ursinus). Journal of Experimental Marine Biology and Ecology, 452, 125-136. Damuth, J. (1981) Population density and body size in mammals. Nature, 290, 699- 700. Damuth, J. (1993) Cope's rule, the island rule and the scaling of mammalian population density. Damuth, J. (2007) A macroevolutionary explanation for energy equivalence in the scaling of body size and population density. The American Naturalist, 169, 621- 631. Daskalov, G.M., Grishin, A.N., Rodionov, S. & Mihneva, V. (2007) Trophic cascades triggered by overfishing reveal possible mechanisms of ecosystem regime shifts. Proceedings of the National Academy of Sciences, 104, 10518-10523. Davidson, A.D., Hamilton, M.J., Boyer, A.G., Brown, J.H. & Ceballos, G. (2009) Multiple ecological pathways to extinction in mammals. Proceedings of the National Academy of Sciences, 106, 10702-10705. Davidson, A.D., Boyer, A.G., Kim, H., Pompa-Mansilla, S., Hamilton, M.J., Costa, D.P., Ceballos, G. & Brown, J.H. (2012) Drivers and hotspots of extinction risk in marine mammals. Proceedings of the National Academy of Sciences, 109, 3395-3400. Dell'Arte, G.L., Laaksonen, T., Norrdahl, K. & Korpimäki, E. (2007) Variation in the diet composition of a generalist predator, the red fox, in relation to season and density of main prey. acta oecologica, 31, 276-281.

120

References

Dell, A.I., Pawar, S. & Savage, V.M. (2013) Temperature dependence of trophic interactions are driven by asymmetry of species responses and foraging strategy. Journal of Animal Ecology, Demment, M.W. & Soest, P.J.V. (1985) A Nutritional Explanation for Body-Size Patterns of Ruminant and Nonruminant Herbivores. The American Naturalist, 125, 641-672. Derocher, A.E., Wiig, Ø. & Andersen, M. (2002) Diet composition of polar bears in Svalbard and the western Barents Sea. Polar Biology, 25, 448-452. Dial, K.P. & Marzluff, J.M. (1989) Nonrandom Diversification with in Taxonomic Assemblages. Systematic Biology, 38, 26-37. Dickman, E.M., Newell, J.M., González, M.J. & Vanni, M.J. (2008) Light, nutrients, and food-chain length constrain planktonic energy transfer efficiency across multiple trophic levels. Proceedings of the National Academy of Sciences, 105, 18408- 18412. Downhower, J.F. & Blumer, L.S. (1988) Calculating just how small a whale can be. Nature, 335, 675. Drummond, A.J., Suchard, M.A., Xie, D. & Rambaut, A. (2012) Bayesian phylogenetics with BEAUti and the BEAST 1.7. Molecular Biology and Evolution, Duffy, J. & Stachowicz, J.J. (2006) Why biodiversity is important to oceanography: potential roles of genetic, species, and trophic diversity in pelagic ecosystem processes. Marine Ecology Progress Series, 311, 179-189. Duffy, J.E. (2003) Biodiversity loss, trophic skew and ecosystem functioning. Ecology Letters, 6, 680-687. Dulvy, N.K., Fowler, S.L., Musick, J.A., Cavanagh, R.D., Kyne, P.M., Harrison, L.R., Carlson, J.K., Davidson, L.N., Fordham, S.V. & Francis, M.P. (2014) Extinction risk and conservation of the world’s sharks and rays. eLife, 3 Ernest, S., Enquist, B.J., Brown, J.H., Charnov, E.L., Gillooly, J.F., Savage, V.M., White, E.P., Smith, F.A., Hadly, E.A. & Haskell, J.P. (2003a) Thermodynamic and metabolic effects on the scaling of production and population energy use. Ecology Letters, 6, 990-995. Ernest, S.K.M., Enquist, B.J., Brown, J.H., Charnov, E.L., Gillooly, J.F., Savage, V.M., White, E.P., Smith, F.A., Hadly, E.A., Haskell, J.P., Lyons, S.K., Maurer, B.A., Niklas, K.J. & Tiffney, B. (2003b) Thermodynamic and metabolic effects on the scaling of production and population energy use. Ecology Letters, 6, 990-995. Estes, J.A., Terborgh, J., Brashares, J.S., Power, M.E., Berger, J., Bond, W.J., Carpenter, S.R., Essington, T.E., Holt, R.D. & Jackson, J.B. (2011) Trophic downgrading of planet Earth. science, 333, 301-306. Evans, A.R., Jones, D., Boyer, A.G., Brown, J.H., Costa, D.P., Ernest, S.K.M., Fitzgerald, E.M.G., Fortelius, M., Gittleman, J.L., Hamilton, M.J., Harding, L.E., Lintulaakso, K., Lyons, S.K., Okie, J.G., Saarinen, J.J., Sibly, R.M., Smith, F.A., Stephens, P.R., Theodor, J.M. & Uhen, M.D. (2012) The maximum rate of mammal evolution. Proceedings of the National Academy of Sciences, Falkowski, P.G. & Raven, J.A. (1997) Aquatic photosynthesis. Blackwell, Oxford, UK. Felsenstein, J. (1985) Phylogenies and the Comparative Method. The American Naturalist, 125, 1-15. Ferguson, S.H., Taylor, M.K., Born, E.W., Rosing-Asvid, A. & Messier, F. (1999) Determinants of home range size for polar bears (Ursus maritimus). Ecology Letters, 2, 311-318. Field, C.B., Behrenfeld, M.J., Randerson, J.T. & Falkowski, P. (1998) Primary production of the biosphere: integrating terrestrial and oceanic components. Science, 281, 237-240. FitzJohn, R.G., Pennell, M.W., Zanne, A.E., Stevens, P.F., Tank, D.C. & Cornwell, W.K. (2014) How much of the world is woody? Journal of Ecology, n/a-n/a.

121

References

Fortin, D., Beyer, H.L., Boyce, M.S., Smith, D.W., Duchesne, T. & Mao, J.S. (2005) Wolves influence elk movements: behavior shapes a trophic cascade in Yellowstone National Park. Ecology, 86, 1320-1330. Frair, J.L., Fieberg, J., Hebblewhite, M., Cagnacci, F., DeCesare, N.J. & Pedrotti, L. (2010) Resolving issues of imprecise and habitat-biased locations in ecological analyses using GPS telemetry data. Philosophical Transactions of the Royal Society B: Biological Sciences, 365, 2187-2200. Freckleton, R.P. & Jetz, W. (2009) Space versus phylogeny: disentangling phylogenetic and spatial signals in comparative data. Proceedings of the Royal Society B: Biological Sciences, 276, 21-30. Freitas, C. & Lydersen, C. (2008) A simple new algorithm to filter marine mammal Argos locations. Marine Mammal Science, 24, 315-325. Fritz, S.A., Bininda-Emonds, O.R.P. & Purvis, A. (2009) Geographical variation in predictors of mammalian extinction risk: big is bad, but only in the tropics. Ecology Letters, 12, 538-549. Frost, P.C., Benstead, J.P., Cross, W.F., Hillebrand, H., Larson, J.H., Xenopoulos, M.A. & Yoshida, T. (2006) Threshold elemental ratios of carbon and phosphorus in aquatic consumers. Ecology Letters, 9, 774-779. Fryxell, J.M., Mosser, A., Sinclair, A.R. & Packer, C. (2007) Group formation stabilizes predator–prey dynamics. Nature, 449, 1041-1043. García, V.B., Lucifora, L.O. & Myers, R.A. (2008) The importance of habitat and life history to extinction risk in sharks, skates, rays and chimaeras. Proceedings of the Royal Society B: Biological Sciences, 275, 83-89. Gaskin, D.E. & Cawthorn, M.W. (1967) Diet and feeding habits of the sperm whale (Physeter catodon L.) in the Cook Strait region of New Zealand. New Zealand Journal of Marine and Freshwater Research, 1, 156-179. Gaston, K.J. & Blackburn, T.M. (1996) Global scale macroecology: interactions between population size, geographic range size and body size in the Anseriformes. Journal of Animal Ecology, 701-714. Gatesy, J., Geisler, J.H., Chang, J., Buell, C., Berta, A., Meredith, R.W., Springer, M.S. & McGowen, M.R. (2012) A phylogenetic blueprint for a modern whale. Molecular Phylogenetics and Evolution, Gazda, S.K., Connor, R.C., Edgar, R.K. & Cox, F. (2005) A division of labour with role specialization in group–hunting bottlenose dolphins (Tursiops truncatus) off Cedar Key, Florida. Proceedings of the Royal Society B: Biological Sciences, 272, 135-140. Gettle, A.S. (1975) Densities, movements, and activities of pine voles (Microtus pinetorum) in Pennsylvania. . Masters Thesis, Pennsylvania State University, p.66, Gittleman, J.L. & Gompper, M.E. (2005) Plight of predators: The imporatance of carnivores for understanding pattersn of biodiversity and extinction risk. . Ecology of predator-prey interactions (ed. by I. Barbosa, P. and I. Catellanos), pp. 370-388. Oxford University Press, Oxford. Goldbogen, J., Calambokidis, J., Oleson, E., Potvin, J., Pyenson, N.D., Schorr, G. & Shadwick, R. (2011) Mechanics, hydrodynamics and energetics of blue whale lunge feeding: efficiency dependence on krill density. Journal of Experimental Biology, 214, 131-146. Goldbogen, J.A., Friedlaender, A.S., Calambokidis, J., Mckenna, M.F., Simon, M. & Nowacek, D.P. (2013) Integrative Approaches to the Study of Baleen Whale Diving Behavior, Feeding Performance, and Foraging Ecology. BioScience, 63, 90-100. González-Suárez, M. & Revilla, E. (2014) Generalized Drivers in the Mammalian Endangerment Process. PLoS ONE, 9, e90292.

122

References

Gotelli, N.J., Anderson, M.J., Arita, H.T., Chao, A., Colwell, R.K., Connolly, S.R., Currie, D.J., Dunn, R.R., Graves, G.R. & Green, J.L. (2009) Patterns and causes of species richness: a general simulation model for macroecology. Ecology Letters, 12, 873-886. Grill, A., Amori, G., Aloise, G., Lisi, I., Tosi, G., Wauters, L.A. & Randi, E. (2009) Molecular phylogeography of European Sciurus vulgaris: refuge within refugia? Molecular Ecology, 18, 2687-2699. Hairston, J.N.G. & Hairston, S.N.G. (1993) Cause-effect relationships in energy flow, trophic structure, and interspecific interactions. The American Naturalist, 142, 379-411. Hall-Aspland, S. & Rogers, T.L. (2004) Summer diet of leopard seals (Hydrurga leptonyx) in Prydz Bay, Eastern Antarctica. Polar Biology, 27, 729-734. Hanna, E. & Cardillo, M. (2013) A comparison of current and reconstructed historic geographic range sizes as predictors of extinction risk in Australian mammals. Biological Conservation, 158, 196-204. Hanna, E. & Cardillo, M. (2014) Clarifying the relationship between torpor and anthropogenic extinction risk in mammals. Journal of Zoology, Harvey, P.H. (1996) Phylogenies for Ecologists. Journal of Animal Ecology, 65, 255- 263. Haskell, J.P., Ritchie, M.E. & Olff, H. (2002) Fractal geometry predicts varying body size scaling relationships for mammal and bird home ranges. Ecology, 418, 527-530. Hayward, M.W. (2006) Prey preferences of the spotted hyaena (Crocuta crocuta) and degree of dietary overlap with the lion (Panthera leo). Journal of Zoology, 270, 606-614. Hayward, M.W. & Kerley, G.I.H. (2005) Prey preferences of the lion (Panthera leo). Journal of Zoology, 267, 309-322. Heckmann, L., Drossel, B., Brose, U. & Guill, C. (2012) Interactive effects of body‐size structure and adaptive foraging on food‐web stability. Ecology letters, 15, 243- 250. Hein, A.M., Hou, C. & Gillooly, J.F. (2012) Energetic and biomechanical constraints on animal migration distance. Ecology Letters, 15, 104-110. Heithaus, M.R., Frid, A., Wirsing, A.J. & Worm, B. (2008) Predicting ecological consequences of marine top predator declines. Trends in Ecology & Evolution, 23, 202-210. Hendriks, J.A. (2007) The power of size: A meta-analysis reveals consistency of allometric regressions. Ecological Modelling, 205, 196-208. Hilborn, R., Branch, T.A., Ernst, B., Magnusson, A., Minte-Vera, C.V., Scheuerell, M.D. & Valero, J.L. (2003) State of the world's fisheries. Annual review of Environment and Resources, 28, 359-399. Hildebrand, M. & Goslow, G.E. (1995) Analysis of vertebrate structure, 4th edn. John Wiley, New York. Hoegh-Guldberg, O. & Bruno, J.F. (2010) The impact of climate change on the world’s marine ecosystems. Science, 328, 1523-1528. Hone, D.W. & Benton, M.J. (2005) The evolution of large size: how does Cope's Rule work? Trends in Ecology & Evolution, 20, 4-6. Hopcraft, J.G.C., Anderson, T.M., Pérez-Vila, S., Mayemba, E. & Olff, H. (2012) Body size and the division of niche space: food and predation differentially shape the distribution of Serengeti grazers. Journal of Animal Ecology, 81, 201-213. Huang, S., Davies, T.J. & Gittleman, J.L. (2012) How global extinctions impact regional biodiversity in mammals. Biology Letters, 8, 222-225. Hückstädt, L., Burns, J., Koch, P., McDonald, B., Crocker, D. & Costa, D. (2012) Diet of a specialist in a changing environment: the crabeater seal along the western Antarctic Peninsula. Marine Ecology Progress Series, 455, 287.

123

References

Humphries, M.M. & McCann, K.S. (2014) Metabolic ecology. Journal of Animal Ecology, 83, 7-19. Isaac, N.J., Storch, D. & Carbone, C. (2013) The paradox of energy equivalence. Global Ecology and Biogeography, 22, 1-5. Jaouen, K., Pons, M.-L. & Balter, V. (2013) Iron, copper and zinc isotopic fractionation up mammal trophic chains. Earth and Planetary Science Letters, 374, 164-172. Jarman, P. (1983) Mating System And Sexual Dimorphism In Large Terrestrial, Mammalian Herbivores. Biological Reviews, 58, 485-520. Jennings, S. & Mackinson, S. (2003) Abundance–body mass relationships in size- structured food webs. Ecology Letters, 6, 971-974. Jennings, S., Warr, K.J. & Mackinson, S. (2002) Use of size-based production and stable isotope analyses to predict trophic transfer efficiencies and predator-prey body mass ratios in food webs. Marine Ecology Progress Series, 240, 11-20. Jennings, S., Pinnegar, J.K., Polunin, N.V.C. & Boon, T.W. (2001) Weak cross-species relationships between body size and trophic level belie powerful size-based trophic structuring in fish communities. Journal of Animal Ecology, 70, 934-944. Jetz, W., Carbone, C., Fulford, J. & Brown, J.H. (2004) The scaling of animal space use. Science, 306, 266-268. Johnson, C.N. (2002) Determinants of loss of mammal species during the Late Quaternary ‘megafauna’ extinctions: life history and ecology, but not body size. Proceedings of the Royal Society of London. Series B: Biological Sciences, 269, 2221-2227. Johnson, C.N., Isaac, J.L. & Fisher, D.O. (2007) Rarity of a top predator triggers continent-wide collapse of mammal prey: dingoes and marsupials in Australia. Proceedings of the Royal Society B: Biological Sciences, 274, 341-346. Johnson, J.B. & Omland, K.S. (2004) Model selection in ecology and evolution. Trends in Ecology and Evolution, 19, 101-108. Jonathan Davies, T., Meiri, S., Barraclough, T.G. & Gittleman, J.L. (2007) Species co‐ existence and character divergence across carnivores. Ecology Letters, 10, 146-152. Jones, K.E., Ruff, C.B. & Goswami, A. (2013) Morphology and Biomechanics of the Pinniped Jaw: Mandibular Evolution Without Mastication. The Anatomical Record, 296, 1049-1063. Jones, K.E., Bielby, J., Cardillo, M., Fritz, S.A., O'Dell, J., Orme, C.D.L., Safi, K., Sechrest, W., Boakes, E.H., Carbone, C., Connolly, C., Cutts, M.J., Foster, J.K., Grenyer, R., Habib, M., Plaster, C.A., Price, S.A., Rigby, E.A., Rist, J., Teacher, A., Bininda-Emonds, O.R.P., Gittleman, J.L., Mace, G.M., Purvis, A. & Michener, W.K. (2009) PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology, 90, 2648-2648. Karasov, W.H. (1992) Daily Energy Expenditure and the Cost of Activity in Mammals. American Zoologist, 32, 238-248. Kartascheff, B., Heckmann, L., Drossel, B. & Guill, C. (2010) Why allometric scaling enhances stability in food web models. Theoretical Ecology, 3, 195-208. Kelt, D.A. & Van Vuren, D. (1999) Energetic Constraints and the Relationship between Body Size and Home Range Area in Mammals. Ecology, 80, 337-340. Kelt, D.A. & van Vuren, D.H. (2001) The Ecology and Macroecology of Mammalian Home Range Area. The American Naturalist, 157, 637-645. King, R.B. (2002) Predicted and observed maximum prey size – snake size allometry. Functional Ecology, 16, 766-772. Kingsolver, J.G. & Pfennig, D.W. (2004) Individual‐level selection as a cause of Cope's rule of phyletic size increase. Evolution, 58, 1608-1612. Kissling, W.D., Dalby, L., Fløjgaard, C., Lenoir, J., Sandel, B., Sandom, C., Trøjelsgaard, K. & Svenning, J.C. (2014) Establishing macroecological trait

124

References

datasets: digitalization, extrapolation, and validation of diet preferences in terrestrial mammals worldwide. Ecology and Evolution, Kleiber, M. (1961) The fire of life. An introduction to animal energetics. The fire of life. An introduction to animal energetics., Knight, C.M., Kenward, R.E., Gozlan, R.E., Hodder, K.H., Walls, S.S. & Lucas, M.C. (2009) Home range estiamtion within complex restricted environments: importance of method selection in detecting seasonal changes. Wildlife Research, 36, 213-224. Kuhn, T.S., Mooers, A.Ø. & Thomas, G.H. (2011) A simple polytomy resolver for dated phylogenies. Methods in Ecology and Evolution, 2, 427-436. Kuntner, M., May-Collado, L.J. & Agnarsson, I. (2011) Phylogeny and conservation priorities of afrotherian mammals (Afrotheria, Mammalia). Zoologica Scripta, 40, 1-15. Laliberte, A.S. & Ripple, W.J. (2004) Range contractions of North American carnivores and ungulates. BioScience, 54, 123-138. Lambertsen, R., Ulrich, N. & Straley, J. (1995) Frontomandibular stay of Balaenopteridae: a mechanism for momentum recapture during feeding. Journal of Mammalogy, 877-899. Lau, M.W.-N., Fellowes, J.R. & Chan, B.P.L. (2010) Carnivores (Mammalia: Carnivora) in South China: a status review with notes on the commercial trade. Mammal Review, 40, 247-292. Laver, P.N. & Kelly, M.J. (2008) A critical review of home range studies. Journal of Wildlife Management, 72, 290-298. Letnic, M., Greenville, A., Denny, E., Dickman, C.R., Tischler, M., Gordon, C. & Koch, F. (2011) Does a top predator suppress the abundance of an invasive mesopredator at a continental scale? Global Ecology and Biogeography, 20, 343-353. Lindstedt, S.L., Miller, B.J. & Buskirk, S.W. (1986) Home range, time and body size in mammals. Ecology, 67, 413-418. Liow, L.H. & Finarelli, J.A. (2014) A dynamic global equilibrium in carnivoran diversification over 20 million years. Proceedings of the Royal Society B: Biological Sciences, 281 Litchman, E., Klausmeier, C.A. & Yoshiyama, K. (2009) Contrasting size evolution in marine and freshwater diatoms. Proceedings of the National Academy of Sciences, 106, 2665-2670. Lomolino, M.V. (1985) Body size of mammals on islands: the island rule reexamined. American Naturalist, 310-316. Lomolino, M.V. (2005) Body size evolution in insular vertebrates: generality of the island rule. Journal of Biogeography, 32, 1683-1699. Lührs, M.-L., Dammhahn, M. & Kappeler, P. (2013) Strength in numbers: males in a carnivore grow bigger when they associate and hunt cooperatively. Behavioral Ecology, 24, 21-28. Lyras, G.A., van der Geer, A.A. & Rook, L. (2010) Body size of insular carnivores: evidence from the fossil record. Journal of biogeography, 37, 1007-1021. Maddison, W.P. & Maddison, D.R. (2010) Mesquite: A modular system for evolutionary analysis. Version 2.74 Available at: (accessed Margules, C.R. & Pressey, R.L. (2000) Systematic conservation planning. Nature, 405, 243-253. Marques, T.S., Lara, N.R., Camargo, P.B., Verdade, L.M. & Martinelli, L.A. (2014) The Use of Stable Isotopes Analysis in Wildlife Studies. Applied Ecology and Human Dimensions in Biological Conservation, pp. 159-174. Springer. Marquet, P. & Taper, M. (1998) On size and area: Patterns of mammalian body size extremes across landmasses. Evolutionary Ecology, 12, 127-139.

125

References

Marquet, P.A., Navarrette, S. & Castilla, J.C. (1995) Body size, population density, and the energetic equivalence rule. Journal of Animal Ecology, 64, 325-332. Martins, E.P. (2004) COMPARE, version 4.6b. Computer programs for the statistical analysis of comparative data. Distributed by the author at http://compare.bio.indiana.edu/. Department of Biology, Indiana University. Martins, E.P. & Hansen, T.F. (1997) Phylogenies and the comparative method: A general approach to incorporating phylogenetic information inot analysis of interspecific data. American Naturalist, 149, 646-667. Maurer, B.a. (1998) The evolution of body size in birds. I. Evidence for non-random diversification. Evolutionary Ecology, 12, 925-934. Maurer, B.A. & Marquet, P.A. (2013) Processes Responsible for Patterns in Body Mass Distributions. Animal Body Size: Linking Pattern and Process across Space, Time and Taxonomic Group (ed. by F.A. Smith and S.K. Lyons), pp. 168-186. University of Chicago Press, Chicago and London. Mayr, E. (1963) Animal species and evolution. Harvard University Press, Cambridge ,Mass. McCain, C.M. & Colwell, R.K. (2011) Assessing the threat to montane biodiversity from discordant shifts in temperature and precipitation in a changing climate. . Ecology Letters, 14, 1236-1245. McCain, C.M. & King, S.R.B. (2014) Body size and activity times mediate mammalian responses to climate change. Global Change Biology, McGee, V.E. & Carleton, W.T. (1970) Piecewise Regression. Journal of the American Statistical Association, 65, 1109-1124. McGowen, M.R. (2011) Toward the resolution of an explosive radiation—A multilocus phylogeny of oceanic dolphins (Delphinidae). Molecular Phylogenetics and Evolution, 60, 345-357. McNab, B.K. (1963) Bioenergetics and the Determination of Home Range Size. The American Naturalist, 97, 133-140. McNab, B.K. (1971) On the ecological significance of Bergmann's rule. Ecology, 52, 845-854. McNab, B.K. (1986) The Influence of Food Habits on the Energetics of Eutherian Mammals. Ecological Monographs, 56, 1-19. Meiri, S. (2011) Bergmann's Rule – what's in a name? Global Ecology and Biogeography, 20, 203-207. Meiri, S. & Dayan, T. (2003) On the validity of Bergmann's rule. Journal of Biogeography, 30, 331-351. Meiri, S., Dayan, T. & Simberloff, D. (2005) Area, isolation and body size evolution in insular carnivores. Ecology Letters, 8, 1211-1217. Meiri, S., Raia, P. & Phillimore, A.B. (2011) Slaying dragons: limited evidence for unusual body size evolution on islands. Journal of Biogeography, 38, 89-100. Middelburg, J. (2014) Stable isotopes dissect aquatic food webs from the top to the bottom. Biogeosciences, 11, 2357-2371. Miller, P.J. (1996) Miniature Vertebrates: The Implications Of Small Body Size (Symposia Of The Zoological Society Of London) Author: Peter J. Mooney, K.A., Gruner, D.S., Barber, N.A., Van Bael, S.A., Philpott, S.M. & Greenberg, R. (2010) Interactions among predators and the cascading effects of vertebrate insectivores on arthropod communities and plants. Proceedings of the National Academy of Sciences, 107, 7335-7340. Moritz, C., Patton, J.L., Conroy, C.J., Parra, J.L., White, G.C. & Beissinger, S.R. (2008) Impact of a century of climate change on small-mammal communities in Yosemite National Park, USA. Science, 322 , 261-264. Murray, K.A., Verde Arregoitia, L.D., Davidson, A., Di Marco, M. & Di Fonzo, M.M. (2014) Threat to the point: improving the value of comparative extinction risk analysis for conservation action. Global change biology, 20, 483-494.

126

References

Nagy, A.N. (2005) Field metabolic rate and body size. The Journal of Experimental Biology, 208, 1621-1625. Nagy, K.A. (1987) Field metabolic rate and food requirement scaling in mammals and birds. Ecological monographs, 112-128. Nee, S., Read, A.F., Greenwood, J.J. & Harvey, P.H. (1991) The relationship between abundance and body size in British birds. Nature, 351, 312-313. Newsome, T.M., Ballard, G.A., Dickman, C.R., Fleming, P.J. & van de Ven, R. (2013) Home range, activity and sociality of a top predator, the dingo: a test of the Resource Dispersion Hypothesis. Ecography, Nicol, S. (1986) Shape, size and density of daytime surface swarms of the euphausiid Meganyctiphanes norvegica in the Bay of Fundy. Journal of Plankton Research, 8, 29-39. Niemi, M., Auttila, M., Viljanen, M. & Kunnasranta, M. (2013) Home range, survival, and dispersal of endangered Saimaa ringed seal pups: Implications for conservation. Marine Mammal Science, 29, 1-13. Novaro, A.J., Funes, M.n.C. & Susan Walker, R. (2000) Ecological extinction of native prey of a carnivore assemblage in Argentine Patagonia. Biological Conservation, 92, 25-33. Nowacek, D.P., Johnson, M.P., Tyack, P.L., Shorter, K.A., McLellan, W.A. & Pabst, A. (2001) Buoyant balaenids: the ups and downs of buoyancy in right whales. Proceedings of the Royal Society of London. Series B: Biological Sciences, 268, 1811-1816. Nyakatura, K. & Bininda-Emonds, O.R.P. (2012) Updating the evolutionary history of Carnivora (Mammalia): a new species-level supertree complete with divergence time estimates. BMC biology, 10, 12. Okie, J.G., Boyer, A.G., Brown, J.H., Costa, D.P., Ernest, S.M., Evans, A.R., Fortelius, M., Gittleman, J.L., Hamilton, M.J. & Harding, L.E. (2013) Effects of allometry, productivity and lifestyle on rates and limits of body size evolution. Proceedings of the Royal Society B: Biological Sciences, 280, 20131007. Orme, D., Freckleton, R., Thomas, G., Petzoldt, T., Fritz, S., Isaac, N. & Pearse, W. (2012) caper: Comparative Analyses of Phylogenetics and Evolution in R. R package version 0.5. http://CRAN.R-project.org/package=caper. Ottaviani, D., Cairns, S.C., Oliverio, M. & Boitani, L. (2006) Body mass as a predictive variable of home-range size among Italian mammals and birds. Journal of Zoology, 269, 317-330. Pace, M.L., Cole, J.J., Carpenter, S.R. & Kitchell, J.F. (1999) Trophic cascades revealed in diverse ecosystems. Trends in Ecology & Evolution, 14, 483-488. Pagel, M. (1999) Inferring the historical patterns of biological evolution. Nature, 401, 877-884. Pauly, D. & Christensen, V. (1995) Primary production required to sustain global fisheries. Nature, 374, 255-257. Pauly, D., Trites, A.W., Capuli, E. & Christensen, V. (1998) Diet composition and trophic levels of marine mammals. ICES Journal of Marine Science: Journal du Conseil, 55, 467-481. Pautasso, M., Böhning-Gaese, K., Clergeau, P., Cueto, V.R., Dinetti, M., Fernández- Juricic, E., Kaisanlahti-Jokimäki, M.L., Jokimäki, J., McKinney, M.L., Sodhi, N.S., Storch, D., Tomialojc, L., Weisberg, P.J., Woinarski, J.C.Z., Fuller, R.A. & Cantarello, E. (2011) Global macroecology of bird assemblages in urbanized and semi‐natural ecosystems. Global Ecology and Biogeography, 20, 426-436. Pawar, S., Dell, A.I. & Savage, V.M. (2012) Dimensionality of consumer search space drives trophic interaction strengths. Nature, 486, 485-489. Pearce, F., Carbone, C., Cowlishaw, G. & Isaac, N.J. (2013) Space-use scaling and home range overlap in primates. Proceedings of the Royal Society B: Biological Sciences, 280

127

References

Petchey, O.L., Beckerman, A.P., Riede, J.O. & Warren, P.H. (2008) Size, foraging, and food web structure. Proceedings of the National Academy of Sciences, 105, 4191-4196. Peters, R.H. (1983) The Ecological Implications of Body Size. Cambridge University Press, Cambridge. Pinheiro, J.C. & Bates, D.M. (2000) Mixed-effects models in S and S-Plus. Springer, New York. Pitman, R.L. & Durban, J.W. (2012) Cooperative hunting behavior, prey selectivity and prey handling by pack ice killer whales (Orcinus orca), type B, in Antarctic Peninsula waters. Marine Mammal Science, 28, 16-36. Polis, G.A. (1991) Complex Trophic Interactions in Deserts: An Empirical Critique of Food-Web Theory. The American Naturalist, 138, 123-155. Polis, G.A. & Strong, D.R. (1996) Food web complexity and community dynamics. The American Naturalist, 147, 813-846. Pontzer, H. (2007) Effective limb length and the scaling of locomotor costs in terrestrial animals. The Journal of Experimental Biology, 210, 1752-1761. Potvin, J., Goldbogen, J.A. & Shadwick, R.E. (2012) Metabolic Expenditures of Lunge Feeding Rorquals Across Scale: Implications for the Evolution of Filter Feeding and the Limits to Maximum Body Size. PLos One, 7, e44854. Price, S.A., Hopkins, S.S.B., Smith, K.K. & Roth, V.L. (2012) Tempo of trophic evolution and its impact on mammalian diversification. Proceedings of the National Academy of Sciences, 109, 7008-7012. Prugh, L.R., Stoner, C.J., Epps, C.W., Bean, W.T., Ripple, W.J., Laliberte, A.S. & Brashares, J.S. (2009) The rise of the mesopredator. BioScience, 59, 779-791. Purvis, A., Gittleman, J.L., Cowlishaw, G. & Mace, G.M. (2000) Predicting extinction risk in declining species. Proceedings of the Royal Society of London. Series B: Biological Sciences, 267, 1947-1952. Raia, P., Carotenuto, F. & Meiri, S. (2010) One size does not fit all: no evidence for an optimal body size on islands. Global Ecology and Biogeography, 19, 475-484. Rasmussen, G.S.A., Markus Gusset, Franck Courchamp & David W. Macdonald (2008) Achilles' Heel of Sociality Revealed by Energetic Poverty Trap in Cursorial Hunters. The American Naturalist, 172, 508-518. R Core Development Team (2013) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, http://www.R-project.org/. R Core Development Team (2011) R: A Language and Environment for Statistical Computing. . Vienna, Austria, ISBN 3-900051-07-0, http://www.R-project.org/. Reid, K. & Croxall, J.P. (2001) Environmental response of upper trophic-level predators reveals a system change in an Antarctic marine ecosystem. Proceedings of the Royal Society of London. Series B: Biological Sciences, 268, 377-384. Reilly, S., Hedley, S., Borberg, J., Hewitt, R., Thiele, D., Watkins, J. & Naganobu, M. (2004) Biomass and energy transfer to baleen whales in the South Atlantic sector of the Southern Ocean. Deep Sea Research Part II: Topical Studies in Oceanography, 51, 1397-1409. Renaud, S., Michaux, J., Schmidt, D.N., Aguilar, J.-P., Mein, P. & Auffray, J.-C. (2005) Morphological evolution, ecological diversification and climate change in rodents. Proceedings of the Royal Society B: Biological Sciences, 272, 609- 617. Rensch, B. (1950) Die Abhängigkeit der relativen sexual differenz von der Körpergröße. Bonner Zoologische Beiträge, 1, 58-69. Revell, L.J., Harmon, L.J. & Collar, D.C. (2008) Phylogenetic Signal, Evolutionary Process, and Rate. Systematic Biology, 57, 591-601. Ricklefs, R.E. & Starck, J.M. (1996) Applications of Phylogenetically Independent Contrasts: A Mixed Progress Report. Oikos, 77, 167-172.

128

References

Riede, J.O., Brose, U., Ebenman, B., Jacob, U., Thompson, R., Townsend, C.R. & Jonsson, T. (2011) Stepping in Elton’s footprints: a general scaling model for body masses and trophic levels across ecosystems. Ecology Letters, 14, 169- 178. Ripple, W.J. & Beschta, R.L. (2007) Restoring Yellowstone’s aspen with wolves. Biological Conservation, 138, 514-519. Ripple, W.J., Estes, J.A., Beschta, R.L., Wilmers, C.C., Ritchie, E.G., Hebblewhite, M., Berger, J., Elmhagen, B., Letnic, M. & Nelson, M.P. (2014) Status and Ecological Effects of the World’s Largest Carnivores. Science, 343, 1241484. Rogers, T.L., Hogg, C.J. & Irvine, A. (2005) Spatial movement of adult leopard seals (Hydrurga leptonyx) in Prydz Bay, Eastern Antarctica. Polar Biology, 28, 456- 463. Sandom, C., Dalby, L., Fløjgaard, C., Kissling, W.D., Lenoir, J., Sandel, B., Trøjelsgaard, K., Ejrnæs, R. & Svenning, J.-C. (2013) Mammal predator and prey species richness are strongly linked at macroscales. Ecology, 94, 1112- 1122. Santana, S.E., Grosse, I.R. & Dumont, E.R. (2012) Dietary hardness, loading behavior, and the evolution of skull form in bats. Evolution, 66, 2587-2598. Schaller, G.B. (1972) The Serengeti lion: A study of predator-prey relations. University of Chicago Press, Chicago (480 pp). Scharf, F.S., Juanes, F. & Rountree, R.A. (2000) Predator size-prey size relationships of marine fish predators: interspecific variation and effects of ontogeny and body size on trophic-niche breadth. Marine Ecology Progress Series, 208, 229- 248. Schiermeier, Q. (2010) Ecologists fear Antarctic krill crisis. Nature, 467, 15. Schipper, J. (2008) The status of the world's land and marine mammals: Diversity, threat and knowledge. Science, 322, 225-230. Schmidt-Nielsen, K. (1984) Scaling: Why is animal size so important? Cambridge University Press, New York. Schoener, T.W. (1968) Sizes of Feeding Territories among Birds. Ecology, 49, 123- 141. Seaman, D.E. & Powell, R.A. (1996) An Evaluation of the accuracy of kernel density estimators for home range analysis. Ecology, 77, 2075-2085. Shattuck, M.R. & Williams, S.A. (2010) Arboreality has allowed for the evolution of increased longevity in mammals. Proceedings of the National Academy of Sciences, 107, 4635-4639. Short, F., Carruthers, T., Dennison, W. & Waycott, M. (2007) Global seagrass distribution and diversity: A bioregional model. Journal of Experimental Marine Biology and Ecology, 350, 3-20. Shurin, J.B., Gruner, D.S. & Hillebrand, H. (2006) All wet or dried up? Real differences between aquatic and terrestrial food webs. Proceedings of the Royal Society B: Biological Sciences, 273, 1-9. Sibly, R.M. & Brown, J.H. (2007) Effects of body size and lifestyle on evolution of mammal life histories. Proceedings of the National Academy of Sciences, 104, 17707-17712. Sibly, R.M. & Brown, J.H. (2009) Mammal reproductive strategies driven by offspring mortality-size relationships. The American Naturalist, 173, E185. Sibly, R.M., Zuo, W., Kodric-Brown, A. & Brown, J.H. (2012) Rensch’s Rule in large herbivorous mammals derived from metabolic scaling. The American Naturalist, 179, 169-177. Sigurjónsson, J. & Vikingsson, G.A. (1997) Seasonal abundance of and estimated prey consumption by cetaceans in Icelandic and adjacent waters. Journal of Northwest Atlantic Fish Science, 22

129

References

Sims, D.W., Southall, E.J., Humphries, N.E., Hays, G.C., Bradshaw, C.J.A., Pitchford, J.W., James, A., Ahmed, M.Z., Brierley, A.S., Hindell, M.A., Morritt, D., Musyl, M.K., Righton, D., Shepard, E.L.C., Wearmouth, V.J., Wilson, R.P., Witt, M.J. & Metcalfe, J.D. (2008) Scaling laws of marine predator search behaviour. Nature, 451, 1098-1102. Sinclair, A.R.E., Mduma, S. & Brashares, J.S. (2003) Patterns of predation in a diverse predator-prey system. Nature, 425, 288-290. Slater, G.J., Price, S.A., Santini, F. & Alfaro, M.E. (2010) Diversity versus disparity and the radiation of modern cetaceans. Proceedings of the Royal Society B: Biological Sciences, 277, 3097-3104. Slijper, E.J. (1976) Whales and Dolphins. The University of Michigan Press (170pp), Ann Arbor, MI. Smith, F.A. & Lyons, S.K. (2011) How big should a mammal be? A macroecological look at mammalian body size over space and time. Philosophical Transactions of the Royal Society B: Biological Sciences, 366, 2364-2378. Smith, F.A. & Lyons, S.K. (ed.^eds) (2013) Animal body size: linking patterns and process across space, time and taxonomic group. University of Chicago Press, Chicago and London. Smith, F.A., Boyer, A.G., Brown, J.H., Costa, D.P., Dayan, T., Ernest, S.K.M., Evans, A.R., Fortelius, M., Gittleman, J.L., Hamilton, M.J., Harding, L.E., Lintulaakso, K., Lyons, S.K., McCain, C., Okie, J.G., Saarinen, J.J., Sibly, R.M., Stephens, P.R., Theodor, J. & Uhen, M.D. (2010) The Evolution of Maximum Body Size of Terrestrial Mammals. Science, 330, 1216-1219. Southwell, C. (2007) 1994 to 2000 - Antarctic Pack Ice Seals (APIS) Survey, Australian Antarctic Data Centre - ARGOS satellite tracking record http://data.aad.gov.au/aadc/argos/profile_list.cfm?taxon_id=25 Spencer, W.D. (2012) Home ranges and the value of spatial information. Journal of Mammalogy, 93, 929-947. Steppan, S.J., Storz, B.L. & Hoffmann, R.S. (2004) Nuclear DNA phylogeny of the squirrels (Mammalia: Rodentia) and the evolution of arboreality from c-myc and RAG1. Molecular Phylogenetics and Evolution, 30, 703-719 Sterner, R.W. & Elser, J.J. (2002) Ecological Stoichiometry: The Biology of Elements From Molecules to the Biosphere. Princeton University Press, Princeton.

Steudel, K., Porter, W. & Sher, D. (1994) The biophysics of Bergmann's rule: a comparison of the effects of pelage and body size variation on metabolic rate. Canadian Journal of Zoology, 72, 70-77. Stevens, C.E. & Hume, I.D. (1995) Comparative Physiology of the Vertebrate Digestive System. Cambridge University Press, Cambridge (400pp). Stone, G.N., Nee, S. & Felsenstein, J. (2011) Controlling for non-independence in comparative analysis of patterns across populations within species. Philosophical Transactions of the Royal Society B: Biological Sciences, 366, 1410-1424. Swihart, R.K., Slade, N.A. & Bergstrom, B.J. (1988) Relating body size to the rate of home range use in mammals. Ecology, 69, 393-399. Takimoto, G., Post, D., Spiller, D. & Holt, R. (2012) Effects of productivity, disturbance, and ecosystem size on food-chain length: insights from a metacommunity model of intraguild predation. Ecological Research, 27, 481-493. Tarling, G.A. & Thorpe, S.E. (2014) Instantaneous movement of krill swarms in the Antarctic Circumpolar Current. Limnology and Oceanography, 59, 872-886. Teunissen van Manen, J.L., Muller, L.I., Li, Z.-h., Saxton, A.M. & Pelton, M.R. (2014) Using stable isotopes to assess dietary changes of American black bears from 1980 to 2001. Isotopes in environmental and health studies, 1-17.

130

References

Thompson, M.V. & Randerson, J.T. (1999) Impulse response functions of terrestrial carbon cycle models: method and application. Global Change Biology, 5, 371- 394. Thompson, R.M., Hemberg, M., Starzomski, B.M. & Shurin, J.B. (2007) Trophic levels and trophic tangles: the prevalence of omnivory in real food webs. Ecology, 88, 612-617. Tremblay, Y., Shaffer, S.A., Fowler, S.L., Kuhn, C.E., McDonald, B.I., Weise, M.J., Bost, C.A., Weimerskirch, H., Crocker, D.E., Goebel, M.E. & Costa, D.P. (2006) Interpolation of animal tracking data in a fluid environment. The Journal of Experimental Biology, 209, 128-140. Tucker, M.A. & Rogers, T.L. (2014) Examining the Prey Mass of Terrestrial and Aquatic Carnivorous Mammals: Minimum, Maximum and Range. PLoS ONE, 9, e106402. Tucker, M.A., Ord, T.J. & Rogers, T.L. (2014) Evolutionary predictors of mammalian home range size: body mass, diet and the environment. Global Ecology and Biogeography, 23, 1105-1114. Uhen, M. (2007) Evolution of marine mammals: Back to the sea after 300 million years The Anatomical Record, 290, 514-522. Van Valen, L. (1973) A new evolutionary law. Evolutionary theory, 1, 1-30. Van Valkenburgh, B. (2007) Déjà vu: the evolution of feeding morphologies in the Carnivora. Integrative and Comparative Biology, 47, 147-163. Wall, W.P. (1983) The correlation between high limb-bone density and aquatic habits in recent mammals. Journal of Paleontology, 57, 197-207. Warton, D.I., Duursma, R.A., Falster, D.S. & Taskinen, S. (2012) smatr 3–an R package for estimation and inference about allometric lines. Methods in Ecology and Evolution, 3, 257-259. Weitz, J.S. & Levin, S.A. (2006) Size and scaling of predator–prey dynamics. Ecology Letters, 9, 548-557. Werth, A.J. (2007) Adaptations of the cetacean hyolingual apparatus for aquatic feeding and thermoregulation. The Anatomical Record, 290, 546-568. White, E.P., Ernest, S., Kerkhoff, A.J. & Enquist, B.J. (2007) Relationships between body size and abundance in ecology. Trends in ecology & evolution, 22, 323- 330. Wiley, D., Ware, C., Bocconcelli, A., Cholewiak, D., Friedlaender, A., Thompson, M. & Weinrich, M. (2011) Underwater components of humpback whale bubble-net feeding behaviour. Behaviour, 148, 575-602. Williams, Richard J. & Martinez, Neo D. (2004) Limits to Trophic Levels and Omnivory in Complex Food Webs: Theory and Data. The American Naturalist, 163, 458- 468. Williams, T.M. (1999) The evolution of cost efficient swimming in marine mammals: limits to energetic optimization. Philosophical Transactions of the Royal Society B, 354, 193-201. Williams, T.M. & Yeates, L. (2004) The energetics of foraging in large mammals: a comparison of marine and terrestrial predators. International Congress Series, 1275, 351-358. Williams, T.M., Haun, J., Davis, R., Fuiman, L. & Kohin, S. (2001) A killer appetite: metabolic consequences of carnivory in marine mammals. Comparative Biochemistry and Physiology-Part A: Molecular & Integrative Physiology, 129, 785-796. Williams, T.M., Zavanelli, M., Miller, M.A., Goldbeck, R.A., Morledge, M., Casper, D., Pabst, D.A., McLellan, W., Cantin, L.P. & Kliger, D.S. (2008) Running, swimming and diving modifies neuroprotecting globins in the mammalian brain. Proceedings of the Royal Society B: Biological Sciences, 275, 751-758.

131

References

Worm, B. & Duffy, J.E. (2003) Biodiversity, productivity and stability in real food webs. Trends in Ecology & Evolution, 18, 628-632. Yodzis, P. & Innes, S. (1992) Body size and consumer-resource dynamics. American Naturalist, 1151-1175.

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Appendix 1

Tucker, M.A, Ord, T.O. and Rogers, T.L. (2014) Evolutionary predictors of mammalian home range size: body mass, diet and the environment. Global Ecology and

Biogeography. doi: 10.1111/geb.12194.

133

Global Ecology and Biogeography, (Global Ecol. Biogeogr.) (2014)

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RESEARCH Evolutionary predictors of mammalian PAPER home range size: body mass, diet and the environment

Marlee A. Tucker*, Terry J. Ord and Tracey L. Rogers

Evolution and Ecology Research Centre, School ABSTRACT of Biological, Earth and Environmental Aim Mammalian home range patterns provide information on spatial behaviour Sciences, University of New South Wales, Sydney, NSW, 2052, Australia and ecological patterns, such as resource use, that is often used by conservation managers in a variety of contexts. However, there has been little research on home range patterns outside of the terrestrial environment, potentially limiting the relevance of current home range models for marine mammals, a group of particular conservation concern. To address this gap, we investigated how variation in mammalian home range size among marine and terrestrial species was related to diet, environment and body mass. Location Global. Methods We compiled data on home range size, environment (marine and terrestrial), diet and body mass from the literature and empirical studies to obtain a dataset covering 462 mammalian species. We then used phylogenetic regression analyses (to address non-independence between species) to examine the relative contribution of these factors to variation of home range size among species. Results Body size explained the majority of the difference in home range size among species (53–85%), with larger species occupying larger home ranges. The type of food exploited by species was also an important predictor of home range size (an additional 15% of variation), as was the environment, but to a much lesser degree (1.7%). Main conclusions The factors contributing to the evolution of home ranges are more complex than has been assumed. We demonstrate that diet and body size both inﬂuence home range patterns but differ in their relative contribution, and show that colonization of the marine environment has resulted in the expansion of home range size. Broad-scale models are often used to inform conservation strategies. We propose that future integrative models should incorporate the possibility of phylogenetic effects and a range of ecological variables, and that they should *Correspondence: Marlee Tucker, School of include species representative of the diversity within a group. Biological, Earth and Environmental Sciences, Keywords University of New South Wales, Sydney, NSW, 2052, Australia. evolutionary allometry, marine, phylogenetic comparative analysis, spatial E-mail [email protected] behaviour, terrestrial.

consequences of allometry, the size of an animal’s home range INTRODUCTION provides valuable information on a variety of ecological vari- In animals, a broad range of physiological, ecological and behav- ables, including resource use, social behaviour and other activ- ioural factors scale with body size (Peters, 1983). Body mass, a ities (Knight et al., 2009). The strong positive relationship measure of body size, accounts for a large proportion of the between home range size and body mass reﬂects the balance variation in home range size among terrestrial mammals (Kelt & between the cost of locomotion and metabolic requirements van Vuren, 2001; Jetz et al., 2004). Among the various potential with increasing body mass (McNab, 1963). Larger individuals

© 2014 John Wiley & Sons Ltd DOI: 10.1111/geb.12194 http://wileyonlinelibrary.com/journal/geb 1 M. A. Tucker et al. can travel further than smaller individuals, but larger individ- In this study, we set out to clarify these issues by conducting uals have higher absolute energetic demands and need to travel inclusive analyses across both terrestrial and marine mammals further to gain the resources to meet those demands (McNab, to test the diet and the body mass hypotheses alongside each 1963). other (i.e. that home ranges will increase with increasing pro- In addition to an animal’s size, diet is another important portion of meat in the diet in addition to, and independently of, factor that is believed to dictate home range patterns. Carni- increasing body mass) and against an evolutionary null model vores, omnivores and herbivores have differences in their forag- (stochastic variation). As part of these analyses, we examined if ing costs (i.e. food acquisition and processing costs) due to their when the relative contribution of these factors is the same it has reliance on different food resources, which also have temporally affected the evolution of home range in the same way in terres- and spatially different distributions. Carnivores feed on trial and marine mammals. resources that are sparsely distributed, mobile and unpredict- Colonization of the marine environment has been accompa- able across the landscape, and so they require a large home range nied by fundamental shifts in physiology and ecology that may (Kelt & van Vuren, 2001; Carbone et al., 2007a). There are also have changed the way in which body mass and diet affect home additional costs for carnivores such as the time and energy range size in marine species. One example of this is the ability of required to hunt for food (Carbone et al., 1999). In contrast, marine mammals to utilize buoyancy. Marine mammals have herbivores tend to have the smallest home ranges because they evolved various mechanisms to achieve neutral buoyancy, such feed on vegetation which is fixed in time and space and is gen- as increases in bone density and large blubber stores (Wall, erally abundant. However, there are additional energetic costs 1983). Buoyancy is a key strategy for marine mammals to mini- associated with processing plant material (e.g. Clauss et al., mize the costs associated with diving. An example of this is the 2003), which limit the ability of herbivores to forage widely. North Atlantic right whale (Eubalaena glacialis) which utilizes Omnivores have an intermediate-sized home range that reflects positive buoyancy when ascending (Nowacek et al., 2001). their mixed diet (meat and vegetation) (Kelt & van Vuren, 2001) Marine mammals have also evolved other adaptations that allow and the intermediate costs associated with processing these them to survive in the ocean and decrease their cost of transport foods (McNab, 1986). (COT) per unit weight (Williams, 1999). These include a Despite the large body of work on the physiological and eco- mixture of adaptations that are physiological (e.g. increased logical variables that might affect the size of an animal’s home globin levels for more efficient oxygen transfer; Williams et al., range (e.g. body mass and diet), gaps remain in our understand- 2008) and behavioural (e.g. alternative forms of locomotion ing of which factors (or combination of factors) actually drive during diving; Williams, 1999). The subsequent decrease in mammalian home range patterns. While it is clear that diet and COT per unit weight, combined with passive movement via body mass are important, past studies have examined these oceanic currents (Tremblay et al., 2006), results in the relaxation factors separately (e.g. Kelt & van Vuren, 2001; Jetz et al., 2004) of energetic costs in marine environments compared with the and we have little idea of the relative contribution each makes to terrestrial environment. Given that marine COT is approxi- mammalian home range size. Furthermore, home range data mately half that of land COT, e.g. COT for a Californian sea lion have been historically biased towards terrestrial mammals, is 2.5 J kg−1 m−1 (Williams, 1999) versus COT for a grey wolf of resulting in the exclusion of the larger mammals (> 4000 kg). 4.6 J kg−1 m−1 (Pontzer, 2007), marine mammals on average Marine mammals represent a prominent group of large carni- should have home ranges at least twice as large as terrestrial vores. It is also unclear whether the factors driving home range mammals for any given body mass. Moreover, as the marine size in mammals are the same in terrestrial and marine environ- system is fluid with few boundaries to limit movement, food ments. Furthermore, previous studies have failed to consider the resources tend to be highly mobile across the ecosystem (Sims phylogeny of the species being studied. On methodological et al., 2008). In response, marine mammals are highly mobile, grounds, not incorporating information on the phylogenetic and this should result in further increases in home range size. relatedness among species violates the statistical assumption Therefore, we anticipated that a regression of home range size that data points are independent of one another. This results in on body mass should give a higher intercept for marine inflated Type I error rates and correlations between variables mammals (larger home ranges) than for terrestrial mammals. that may not actually exist (Stone et al., 2011). On biological However, as the COT per unit weight decreases with body mass grounds, while closely related species are more likely to share at a similar rate in both marine and terrestrial mammals characteristics through common ancestry (and are therefore not (Hildebrand & Goslow, 1995; Pontzer, 2007), the scaling rela- independent of one another), variation among species can also tionship of home range size and body mass should remain the be generated through the inherently stochastic process of evo- same across both environments. lutionary differentiation (e.g. drift) or phenotypic correlations Our study was conducted in two parts. First, we revisited the that track the phylogeny and indirectly affect home range rather relationship between diet, body mass and home range size in than through adaptation in the home range specifically. That is, terrestrial mammals within an explicit phylogenetic framework variation in home range size among mammals may have little and assessed the relative contribution of each factor to shaping adaptive significance and might simply reflect a history of home range size. Second, we combined data on marine and stochastic differentiation or other factors associated with terrestrial species to examine the effect of diet and body mass on phylogeny. the evolution of home range size across all mammals, while also

2 Global Ecology and Biogeography, © 2014 John Wiley & Sons Ltd Home range-body mass patterns: are all mammals equal? evaluating the role of the environment (marine versus terres- from satellite tracking data. These species were Hydrurga trial). Each of the factors – diet, environment and body mass – leptonyx, Leptonychotes weddellii, Lobodon carcinophaga, was formulated into mathematical functions and tested against Mirounga leonina, Arctocephalus tropicalis and Arctocephalus an evolutionary null model. This null model provides a biologi- gazella. For information on sample size, data collection and cal benchmark to establish the extent to which ‘neutral’ evolu- sampling protocols see Appendix S2. The satellite tracking data tionary differentiation in home range evolution can be were filtered using a speed–distance–angle filter (Freitas & excluded. In this second part of our study we tested two main Lydersen, 2008), resulting in the use of location classes A, B, 1, 2, hypotheses: (1) diet type underpins home range patterns in 3. These classes represent the accuracy of the positional data mammals because of differences in the distribution and assimi- where 3 has an accuracy of 0.49 km, 2 of 1.01 km, 1 of 4.18 km, lation of food types; and (2) the home range–body mass rela- A of 6.19 km and B of 10.28 km (Costa et al., 2010). The average tionship differs between marine and terrestrial mammals daily position was calculated for each individual based upon all because of differences in the physiology of species and the physi- location data for a given day and only adult individuals were cal properties of the two environments. However, we predicted used. Home range was calculated via the fixed kernel density that body mass would be the primary variable determining the estimation (KDE) method (Seaman & Powell, 1996) using the evolution of home range size across all species. This is due to the ArcGIS extension Hawth’s Tools (Beyer, 2004). We chose KDE metabolic and energetic costs associated with body mass driving to calculate home range size, as reviews into the benefits and the food requirements of individuals, which are a key determi- biases of home range methods, including kernels and minimum nant of spatial movements in mammals (Kelt & van Vuren, convex polygons (Laver & Kelly, 2008), suggest that kernels are 2001). Given this overarching effect of body mass, we then pre- preferable to polygons which are biased by outliers and low dicted that the environment would have an important second- numbers of location fixes (Börger et al., 2006). ary effect on home range size because it influences both the We made an attempt to minimize any effects from different physiology of animals and the distribution of resources. Finally, tracking methods (e.g. GPS, satellite and radiotelemetry), analy- within a given environment (e.g. terrestrial), we predicted that sis methodologies (kernels and polygons) and environments diet type would generate additional variation in home range size (terrestrial and marine) (Börger et al., 2006; Frair et al., 2010), among species, reflecting the interaction of diet with the meta- yet published studies differ in the methods used, meaning that bolic and energetic costs associated with a given body mass. our final database included mixed home range values by necessity. However, these types of methodological effects are minimal at the scale of our study (Appendix S3), which aims to investi- MATERIALS AND METHODS gate large-scale home range patterns across 462 species from across the globe. Database

A database of 462 mammalian species, representing 293 genera, Phylogeny construction 89 families and 24 orders, was collated. We collected information on body mass and home range values, physical environment Due to the absence of a single phylogeny including all species of (marine versus terrestrial) and diet (carnivore, omnivore or her- interest, a composite tree was created by combining information bivore). The home range values for individual species were cal- from several sources (see Fig. S1). The majority of the phylogeny culated as weighted averages which included both sexes, but did was based on the mammalian supertree from Fritz et al. (2009) not incorporate sex ratios or averaged population densities. All in which branch lengths were proportional to time since diver- body mass and home range data for terrestrial mammals was gence. The following species were added to the Fritz et al. (2009) obtained from Kelt & van Vuren (2001) and the PanTHERIA supertree using Mesquite version 2.74 (Maddison & Maddison, database (Jones et al., 2009). Body mass and home range data for 2010) and species were positioned based on the topologies of the marine species were collected from published literature and following sources: Callosciurus erythraeus (Steppan et al., 2004), unpublished empirical data (Appendix S1 in Supporting Infor- Canis familiaris (Agnarsson et al., 2010), Eremitalpa granti mation). Home range was defined as the area covered by an (Kuntner et al., 2011), Orcaella heinsohni (McGowen, 2011), animal during its daily activities such as mating and foraging Sciurus aberti (Grill et al., 2009) and Sotalia guianensis (Burt, 1943), and was used across the marine and terrestrial (Caballero et al., 2008). The Fritz et al. (2009) supertree environments. Marine mammals were defined as species that included polytomies, which are defined as a node where rely upon the ocean to survive (e.g. foraging etc.). Carnivores more than two species diverge at a single point in time were defined as those species with diets comprising at least 90% (multifurcations). In this instance, these are soft polytomies due meat, herbivores at least 90% vegetation and omnivores between to insufficient phylogenetic information. To resolve the branch 10 and 90% vegetation (Kelt & van Vuren, 2001). Insectivores lengths and the polytomies present, we randomly generated were classified as ‘carnivores’,while frugivores and folivores were 1000 alternative branch lengths using the ‘randomly resolve classified as ‘herbivores’. Home range and body mass data were polytomies’ function in Mesquite version 2.74 (Maddison & log10-transformed prior to analysis. Maddison, 2010). This produced 1000 alternative phylogenies To supplement data for six species that were not well repre- and provided the basis for all of the phylogenetic comparative sented in the published literature, we calculated home range size analyses.

Table 1 Level of support for explanatory models of evolution of Analysis home range size in land mammals. Results are from phylogenetic We applied a model selection approach to test the level of generalized least squares (PGLS) regression computed for 1000 support for alternative models of home range evolution. The alternative resolutions of the mammalian phylogeny. Model terms best model was selected using the second-order Akaike informa- include herbivores (diet_H), omnivores (diet_O), body mass (mass) and intercept (0). tion criterion with a correction for sample size (AICc; Johnson & Omland, 2004). The model with the lowest AICc value reﬂects ΔAICc 95% the model with the highest support, although any other model CI (upper, PGLS Effect within two units of the lowest AICc value was also considered to Model ΔAICc lower) α size (r) be a likely candidate (i.e. ΔAIC < 2.0; Burnham & Anderson,

2002). To compute AICc values, we applied each model as a β0 +βmass +βdiet_H +βdiet_O 0.0 n.a. 14.8 0.82 β +β phylogenetic generalized least squares (PGLS) regression, using 0 mass 40.6 34.8, 51.0 8.4 0.72 β compare version 4.6b (Martins, 2004), to each of the 1000 trees 0 281.5 268.5, 298.4 2.9 – (see Phylogeny construction). Computed log-likelihood estimates from these analyses were converted into AICc values using AICc, Akaike information criterion with a correction for sample size; n.a., not applicable. equations presented in Burnham & Anderson (2002). PGLS regression also computes an α parameter using maximum likelihood that estimates the extent to which phenotypic variation RESULTS among species (e.g. mean body mass and associated home range size) is correlated to phylogeny. When α is close to 0, phenotypic We found that diet and body mass together accounted for a differentiation among present-day taxa reflects the phylogenetic portion of the variation in home range size observed among relationships among those species and is the product of Brown- terrestrial mammals (Table 1, Fig. 1). Carnivores, omnivores ian evolution. When α is large (e.g. 15.50) phenotypic differen- and herbivores demonstrated the predicted difference in inter- tiation is unrelated to phylogeny and might be the outcome of cept values. Carnivores showed the predicted large home ranges adaptive evolution (Martins & Hansen, 1997; but also see Revell with an intercept that was significantly higher than omnivores et al., 2008). and herbivores. Omnivores had intermediate home range sizes First, we assessed the level of support for the relationship that were significantly larger than those of herbivores, and her- between diet and home range among 429 species of terrestrial bivores had the smallest home ranges across the three dietary mammals relative to the level of variation in home range size categories (Fig. 1). However, whereas body mass accounted for generated solely by body mass or the evolutionary null model. 52% of the variance in home range size among terrestrial species

These models were formulated as: (1) β0 +βmass+βdiet_H +βdiet_O, (r = 0.72), the inclusion of diet improved the explanatory power where diet was scored as binary dummy variables with the of the model by 15% (r = 0.82). There was also a substantial resulting parameters β0, βdiet_H and βdiet_O corresponding to car- improvement in the computed AICc value between the diet nivores, herbivores and omnivores, respectively (this was effec- model and the body mass only model (ΔAICc = 40.6). The tively a phylogenetic ANCOVA); (2) β0 +βmass, which predicted inclusion of phylogeny was important for these analyses as the that differences in home range size among species were exclu- estimated phylogenetic signal in home range size among species sively explained by body mass; and (3) β0, the evolutionary null was high (the null model, α=2.9; note that values approaching model in which no predictor variable was included, and which 0 indicate a high phylogenetic signal in species data). That is, therefore modelled variance in species home range size as the closely related species tended to share similar home range sizes outcome of Brownian evolution and stochastic factors associ- and this could not be explained by phylogenetic inertia in body ated with evolutionary differentiation. mass (i.e. α is a combined estimate of phylogenetic signal across Second, we expanded our analyses to cover both marine and all the variables entered into the model, and when body mass terrestrial species in order to examine the relationship between was included α was 8.36, suggesting that the level of environment and home range, and the extent to which environ- phylogenetic signal exhibited by body mass was potentially ment overrides the inﬂuence of diet. This analysis included new lower than for home range size, otherwise the estimate would be empirical data on several marine species (see Database) and similar to or even lower than that estimated by the null model). covered 462 species. Models were formulated as: (1) β0 +βmass When the analysis was expanded to all mammals in both

+βenvironment, where environment was entered as a binary variable terrestrial and marine environments, the model that included in which species were coded as living in either a terrestrial (0) or environment, diet and body mass was by far the best-supported marine (1) environment; (2) β0 +βmass+βdiet_H +βdiet_O, the diet model and explained 74% of the variance in home range size model which is described above for the terrestrial mammal analy- among species (r = 0.86; Table 2). There was virtually no sis; (3) β0 +βmass +βdiet_H +βdiet_O +βenvironment, where both diet support for any of the alternative models (ΔAICc > 10), and environment were included together in the same model; (4) although it was noteworthy that the second best model of diet

β0 +βmass, which assumed body mass was the only variable pre- and body mass provided a similarly high level of explanatory dicting home range size; and (5) β0, the evolutionary null model power (72% variance explained; r = 0.85; Table 2). The majority described above for the terrestrial mammal analysis. of marine species are large and carnivorous (c. 95% carnivorous

Figure 1 Home range size as a function of species body mass compared for terrestrial carnivorous (black circles), herbivorous (white circles) and omnivorous (grey circles) species. Each datum represents a species mean value (n = 429 species). The solid black line is the phylogenetic regression of carnivorous mammals: logY = 1.12logX – 0.48. The dashed black line is the phylogenetic regression of omnivorous mammals: logY = 1.12logX – 0.94. The solid grey line is the phylogenetic regression of herbivorous mammals: logY = 1.12logX – 1.45. Bottom right insert: intercept values and conﬁdence intervals for terrestrial herbivores (H), omnivores (O) and carnivores (C). Values were calculated from phylogenetic least squares regression analyses applied to 1000 alternative resolutions of the mammalian phylogeny.

Table 2 Level of support for explanatory models of home range another: carnivores had the largest home ranges, omnivores had size evolution in mammals. Results are from phylogenetic intermediate home ranges and herbivores had the smallest generalized least squares (PGLS) regression computed for 1000 home ranges (Fig. 2). That is, with the inclusion of the marine alternative resolutions of the mammalian phylogeny. Model terms mammals, the primary effect seems to have been a divergence in include herbivores (diet_H), omnivores (diet_O), environment intercept values between the carnivores and omnivores (marine or terrestrial), body mass (mass) and intercept (0). (compare Figs 1 & 2). To examine whether the environment has had any impact on ΔAICc 95% CI (upper, PGLS Effect home range size, we restricted our analyses to only carnivorous Model ΔAICc lower) α size (r) marine and terrestrial mammals and reﬁtted the environment and body mass model (β0 +βmass +βenvironment), the body mass

β0 +βmass +βdiet_H +βdiet_O + 0.0 n.a. 14.6 0.86 only model (β0 +βmass) and the evolutionary null model (β0). β environment The environment model was the best-supported model of the β +β +β +β 0 mass diet_H diet_O 21.3 7.0, 44.3 14.1 0.85 three, but only explained an additional 1.7% of the variance in β +β +β 0 mass environment 43.9 24.2, 61.8 8.9 0.79 home range size above the 72% explained by body mass only β +β 0 mass 77.9 58.8, 100.8 7.2 0.73 (Table 3). In general, however, marine carnivores have home β 0 322.9 302.3, 354.2 2.4 – ranges that are 1.2 times larger than those of terrestrial species of a similar mass (Fig. 3). AICc, Akaike information criterion with a correction for sample size; n.a., not applicable. Overall, our results confirmed the overarching effect of body mass on mammalian home range size. In addition to body mass, diet and the physical environment, both explained additional variance in home range size among species, but their influence species) and this led us to question whether the environment was less than that of body mass. There was evidence to suggest specifically influenced the best-supported model or whether it that diet might have had a greater impact on home range size was due to the inclusion of larger carnivores in the data set. To than the physical environment (19% additional variance explore this, we examined the parameter estimates for the explained for diet compared with 9% for the environment). In second best-supported model which included only diet and no instance was the evolutionary null model a compelling alter- body mass. These estimates confirmed the expected positive native explanation for differences in home range size among relationship between home range and body mass and showed species, but home range size was found to exhibit a strong that all the diet categories were significantly different from one phylogenetic signal in all analyses (α=1.50–2.90; Tables 1–3).

Figure 2 Home range size as a function of species body mass compared for carnivorous (black circles), herbivorous (white circles) and omnivorous (grey circles) species. Each datum represents a species mean value (n = 462 species). The solid black line is the phylogenetic regression of carnivorous mammals: logY = 1.19logX – 0.29. The dashed black line is the phylogenetic regression of omnivorous mammals: logY = 1.19logX – 0.91. The solid grey line is the phylogenetic regression of herbivorous mammals: logY = 1.19logX – 1.47. Bottom right insert: intercept values and conﬁdence intervals for carnivores (C), omnivores (O) and herbivores (H). Values were calculated from phylogenetic least squares regression analyses applied to 1000 alternative resolutions of the mammalian phylogeny.

Table 3 Level of support for explanatory models of home range trast, the energetic costs associated with movement are greater in size evolution in carnivorous mammals. Results are from smaller species (Pontzer, 2007), which tends to constrain their phylogenetic generalized least squares (PGLS) regression movements and results in smaller home range sizes. In addition computed for 1000 alternative resolutions of the mammalian to the effects of body mass, we found that the amount of meat phylogeny. Model terms include environment (marine or included in diets was a second-order predictor of home range, terrestrial), body mass (mass) and intercept (0). followed closely by the physical environment (terrestrial versus marine). ΔAICc 95% CI (upper, PGLS Effect However, while providing signiﬁcant improvements in the Model ΔAICc lower) α size (r) level of support for models, there were varying effects of diet and physical environment on home range size. Both could only

β0 +βmass +βenvironment 0.0 n.a. 11.6 0.86 explain a further 1–19% of the variation in home range size β +β 0 mass 4.0 3.6, 4.6 11.0 0.85 among species beyond the effect of body mass. Such a small β 0 93.7 90.3, 101.5 1.5 – effect was surprising for diet because several past studies have concluded diet to be the key determinant of the home range– AICc, Akaike information criterion with a correction for sample size; body mass relationship in terrestrial mammals (Swihart et al., n.a., not applicable. 1988; Kelt & van Vuren, 2001). This seems reasonable considering that what species eat has a direct impact on both their energetic requirements and the types of costs incurred in DISCUSSION obtaining and processing food resources. However, while our Body mass was the principal predictor of home range size in results confirm that diet has been a factor in shaping mamma- mammals, accounting for 53–85% of the observed variation in lian home ranges (support was high for models that included a home range size among species. The evolution of home range parameter for diet) it has nevertheless been far less influential size appears to have been driven, for the most part, by the than body mass. Previous studies of diet and home range use energetic requirements and costs or benefits associated with a were based on datasets with limited species coverage across given body mass. Energetic requirements, such as metabolic rate physical environments (i.e. marine and terrestrial), which can (kJ day−1), are positively correlated with body mass (Nagy, 2005). result in model bias and cause issues when these models are As large species have higher absolute energy needs, they must extrapolated over a broader range of species (Sibly et al., 2012). consume more resources and cover larger areas in order to be Furthermore, phylogenetic information was not incorporated able to meet their energetic demands (McNab, 1963). By con- into previous analyses and our results showed that home range

Figure 3 Carnivore home range size as a function of species body mass compared for species occupying terrestrial (white circles) and marine (black circles) environments. Each datum represents a species mean value (n = 134 species). The solid black line is the phylogenetic regression of terrestrial mammals: logY = 1.2logX + 0.39. The dashed black line is the phylogenetic least squares (PGLS) regression line of marine mammals: logY = 1.2logX – 0.44. The river otter (9 kg) and southern humpback whale (32,000 kg) are the smallest and largest marine mammals, while the masked shrew (4.2 g) and lion (204 kg) are the smallest and largest terrestrial mammals. Bottom right insert: intercept values and confidence intervals for terrestrial (T) and marine (M) mammals. Values were calculated from PGLS regression analyses applied to 1000 alternative resolutions of the mammalian phylogeny. size does exhibit a large amount of phylogenetic signal (and this mizing energy expended during the hunt. There is the potential was not likely to be the by-product of phylogenetic inertia in that pack hunting may alter home range size due to the body mass). increased density of individuals within an area. Our data did not When our analyses were applied to all species,an apparent dual suggest any difference in home range size between carnivores role of both diet and the environment seemed to be supported that utilize pack hunting and those that do not (Appendix S3). It (Table 2). However, the precise relationship with the physical would be ideal to have more complete home range information environment was unclear because the majority of marine on whales. With the addition of more whale species, we would mammals were large carnivores with very large home ranges. The expect to see a different home range relationship with body specific relevance of the marine environment to home range mass, such as an increase in the scaling of home range size with evolution was therefore unclear. When the effect of diet was body mass, resulting in extreme home range sizes with large controlled for by focusing on carnivorous mammals across ter- body mass. This would especially be the case with the inclusion restrial and marine environments, we found that home ranges of the various whale migrations, which cover a large area, for were significantly larger in marine environments for a given body example the length of a migration (i.e. one direction, single mass than they were on land (Table 3),but the effect was arguably track) can be greater than 5000 km, without accounting for the smaller than that of diet (environment only accounted for an ‘width’ of the home range (Alerstam et al., 2003). At present, additional 1.7% of the variation in home range size among there are a limited number of tracking data available for whales, species over body mass). The combination of living in an open especially long-term data that also include their migration. environment, feeding on mobile resources and lower transport Like mammals, birds provide an interesting comparison with costs has resulted in the evolution of large home range sizes in the home range size of marine mammals. Birds also live within marine carnivorous mammals (roughly 1.2 times larger than a three-dimensional environment (excluding the flightless those of terrestrial carnivorous mammals), but the impact of species) and home range sizes in non-migratory birds tend to be these factors has been minimal compared with the energetic larger than those of mammals for their size (Haskell et al., 2002). requirements/costs driven by body mass. Unfortunately we were The literature suggests that body mass and food resources are unable to examine the relationship between home range,diet and the main drivers of home range size in birds, similar to environment more closely for herbivores and omnivores due to mammals. Body mass was attributed to energy requirements, as the predominance of carnivory within the marine environment. large birds ‘require more food per unit area than smaller birds’ Large carnivorous mammals have high daily energy require- (Schoener, 1968). Also, birds with an increasing amount of ver- ments, and one strategy for meeting these requirements is to tebrate prey in their diet will have larger home range sizes due to utilize pack hunting (Carbone et al., 2007a). Pack hunting lower densities of their prey compared with that of herbivores enables prey with a large body mass to be hunted whilst mini- and omnivores (Schoener, 1968).

The effects of diet on the relationship between home range size clade (see Fig. S1). For example, within Carnivora there are and body mass found by this study are likely to only be large-scale both marine (e.g. pinnipeds, Ursus maritimus and Enhyrda effects of resource use and distribution constraints across the lutris) and terrestrial (e.g. Canidae, Mephitidae, Procyonidae) broad diet categories of carnivores, omnivores and herbivores. representatives. This is because resource use and resource distribution constraints have varied effects on home range size. Changes in the type of Conclusion resources used and their abundance can vary on different temporal scales. For example, resource distribution and availability Home range is a complex factor influenced by a range of vari- in the Arctic are highly seasonal, with a distinct set of resources ables, including body mass, diet and environment. Our aim was available during winter compared with summer.This would have to clarify the role of these variables and extent to which they a strong effect on the home range size of individuals living in this affect home range size in mammals. We highlight that across the region (e.g. polar bears; Ferguson et al., 1999). However, an mammalian radiation the evolution of home range has been individual may also change which resources they use on a much driven by a hierarchy of variables, but some variables have shorter temporal scale, such as on a day to day basis. Shifts in clearly been more influential than others. The key explanatory resource use or distribution on this small scale are unlikely to be variable for home range size was body mass, followed by the detected in home range analyses due to home range size being secondary variables of diet and then environment. To better calculated over longer periods (i.e. generally on a seasonal or understand the evolution of mammalian home range size we yearly scale). Small-scale studies with a focus on a single species need to investigate the proximate mechanisms (here, proximate and a more direct approach, such as state-space models (Bestley mechanisms are the physiological and morphological drivers) of et al., 2013), would be ideal for investigating dietary effects over its relationship to body size. Furthermore, because the effects of these shorter periods. diet and environment on home range use were small, it would be Our sample sizes were biased towards terrestrial mammals prudent to reconsider past assumptions regarding the influence despite our data including all available information on home of differing resource bases (meat versus plant), modes of trans- range size for marine species (Fig. 1). This partly reflects the port (swimming versus walking and running) and altered physi- difference in the number of mammal species on land versus cal properties (water versus air) as underlying mechanisms of those in the water that were included in our analyses. Calculat- home range use. ing home range for marine species is difficult because of issues Broad models developed using information from many associated with tracking marine species (satellite tracking often species, such as the allometric model of home range size (Jetz being required). For example, home ranges are often calculated et al., 2004; this study), are often used to guide conservation and over shorter tracking periods in marine species compared with management strategies. It is critical then that the underlying those on land. As tracking technology improves, and methodol- assumptions of these models are biologically appropriate. Pre- ogies for estimating home ranges in marine species become vious models have focused exclusively on select groups of more sophisticated, the number of species for which home species (e.g. terrestrial mammals), and we have developed an range information is available should increase. Nevertheless, important amendment to these models to show that home range mammalian species diversity in marine environments is much drivers once thought to be highly influential are not so. We have lower than on land, so this bias in sampling partly reflects bio- demonstrated that by using an integrative model which incor- logical reality and this will not change with improved methods porates an inclusive list of predictor variables, species and of home range estimation. phylogenetic information, our knowledge of home range pat- It should also be noted that the home range values of marine terns across mammals can be significantly enhanced. species used in this study may be conservative because they were measured in two dimensions while marine mammals use a ACKNOWLEDGEMENTS three-dimensional environment (Pawar et al., 2012). However, Carbone et al. (2007b) investigated abundance scaling in We wish to thank two anonymous referees for their constructive mammals in three-dimensional environments and their models suggestions that have strengthened the manuscript.We acknowl- predict a −2/3 scaling similar to abundance scaling within two- edge and sincerely thank Horst Bornemann (Alfred Wegener dimensional environments. As there is a relationship between Institute), Joachim Plötz (Alfred Wegener Institute), Nick Gales animal abundance scaling and home range size (Jetz et al., (Australian Antarctic Division), P.J. Nico deBruyn (University of 2004), we may expect to see a similar pattern in the scaling of Pretoria), Cheryl Tosh (University of Pretoria), Colin Southwell home range size in mammals. The effect of the dimensionality (Australian Antarctic Division), Iain Staniland (British Antarctic of environments would be an interesting concept to examine in Survey), Douglas Kelt (UC Davis) and Dirk van Vuren (UC a future study, using similar mathematical methods to those Davis) for their data contributions. Some of the data used within used in Carbone et al. (2007b). this paper were obtained from the Australian Antarctic Data It is unlikely that differences in home range size across the Centre (IDN Node AMD/AU), part of the Australian Antarctic marine and terrestrial environments are driven by how species Division (Commonwealth of Australia). The data are described are related (i.e. collinearity between environment and related- in the ARGOS satellite tracking record ‘1994 to 2000 – Antarctic ness). Marine mammals are interspersed across the mammalian Pack Ice Seals (APIS) Survey’(Southwell,2007).Wewish to thank

8 Global Ecology and Biogeography, © 2014 John Wiley & Sons Ltd Home range-body mass patterns: are all mammals equal? the personnel from the Instituto Antártico Argentino at Ferguson, S.H., Taylor, M.K., Born, E.W., Rosing-Asvid, A. & Primavera Station in the years 2007–11 for field work support. Messier, F. (1999) Determinants of home range size for polar Logistics support provided by the grant from Instituto Antártico bears (Ursus maritimus). Ecology Letters, 2, 311–318. Argentino (IAA) to Alejandro Carlini, and the Australian Frair, J.L., Fieberg, J., Hebblewhite, M., Cagnacci, F., DeCesare, Research Council (ARC) grant # LP0989933 to T.L.R. N.J. & Pedrotti, L. (2010) Resolving issues of imprecise and habitat-biased locations in ecological analyses using GPS telemetry data. Philosophical Transactions of the Royal Society REFERENCES B: Biological Sciences, 365, 2187–2200. Agnarsson, I., Kuntner, M. & May-Collado, L.J. (2010) Dogs, Freitas, C. & Lydersen, C. (2008) A simple new algorithm to filter cats, and kin: a molecular species-level phylogeny of Car- marine mammal Argos locations. Marine Mammal Science, nivora. Molecular Phylogenetics and Evolution, 54, 726–745. 24, 315–325. Alerstam, T., Hedenström, A. & Åkesson, S. (2003) Long- Fritz, S.A., Bininda-Emonds, O.R.P. & Purvis, A. (2009) Geo- distance migration: evolution and determinants. Oikos, 103, graphical variation in predictors of mammalian extinction 247–260. risk: big is bad, but only in the tropics. Ecology Letters, 12, Bestley, S., Jonsen, I.D., Hindell, M.A., Guinet, C. & Charrassin, 538–549. J.-B. (2013) Integrative modelling of animal movement: Grill, A., Amori, G., Aloise, G., Lisi, I., Tosi, G., Wauters, L.A. & incorporating in situ habitat and behavioural information for Randi, E. (2009) Molecular phylogeography of European a migratory marine predator. Proceedings of the Royal Society Sciurus vulgaris: refuge within refugia? Molecular Ecology, 18, B: Biological Sciences, 280, 20122262. 2687–2699. Beyer, H. (2004) Hawth’s tools: an extension for ArcGIS. Available Haskell, J.P., Ritchie, M.E. & Olff, H. (2002) Fractal geometry at: http://www.spatialecology.com (accessed 6 March 2010). predicts varying body size scaling relationships for mammal Börger, L., Franconi, N., De Michele, G., Gantz, A., Meschi, F., and bird home ranges. Ecology, 418, 527–530. Manica, A., Lovari, S. & Coulson, T.I.M. (2006) Effects of Hildebrand, M. & Goslow, G.E. (1995) Analysis of vertebrate sampling regime on the mean and variance of home range size structure, 4th edn. John Wiley, New York. estimates. Journal of Animal Ecology, 75, 1393–1405. Jetz, W., Carbone, C., Fulford, J. & Brown, J.H. (2004) The Burnham, K.P. & Anderson, D.R. (2002) Model selection and scaling of animal space use. Science, 306, 266–268. multimodal inference: a practical information-theoretical Johnson, J.B. & Omland, K.S. (2004) Model selection in ecology approach. Springer, New York. and evolution. Trends in Ecology and Evolution, 19, 101–108. Burt, W.H. (1943) Territoriality and home range concepts as Jones, K.E., Bielby, J., Cardillo, M. et al. (2009) PanTHERIA: a applied to mammals. Journal of Mammalogy, 24, 346–352. species-level database of life history, ecology, and geography Caballero, S., Jackson, J., Mignucci-Giannoni, A.A., of extant and recently extinct mammals. Ecology, 90, 2648– Barrios-Garrido, H., Beltrán-Pedreros, S., Montiel-Villalobos, 2648. M.G., Robertson, K.M. & Baker, C.S. (2008) Molecular sys- Kelt, D.A. & van Vuren, D.H. (2001) The ecology and tematics of South American dolphins Sotalia: sister taxa deter- macroecology of mammalian home range area. The American mination and phylogenetic relationships, with insights into a Naturalist, 157, 637–645. multi-locus phylogeny of the Delphinidae. Molecular Knight, C.M., Kenward, R.E., Gozlan, R.E., Hodder, K.H., Walls, Phylogenetics and Evolution, 46, 252–268. S.S. & Lucas, M.C. (2009) Home range estimation within Carbone, C., Mace, G.M., Roberts, S.C. & Macdonald, D.W. complex restricted environments: importance of method (1999) Energetic constraints on the diet of terrestrial carni- selection in detecting seasonal changes. Wildlife Research, 36, vores. Nature, 402, 286–288. 213–224. Carbone, C., Teacher, A. & Rowcliffe, J.M. (2007a) The costs of Kuntner, M., May-Collado, L.J. & Agnarsson, I. (2011) Phylog- carnivory. PLoS Biology, 5, 363–368. eny and conservation priorities of afrotherian mammals Carbone, C., Rowcliffe, M.J., Cowlishaw, G. & Isaac, N.J.B. (Afrotheria, Mammalia). Zoologica Scripta, 40, 1–15. (2007b) The scaling of abundance in consumers and their Laver, P.N. & Kelly, M.J. (2008) A critical review of home range resources: implications for the energy equivalence rule. The studies. Journal of Wildlife Management, 72, 290–298. American Naturalist, 170, 479–484. McGowen, M.R. (2011) Toward the resolution of an explosive Clauss, M., Frey, R., Kiefer, B., Lechner-Doll, M., Loehlein, W., radiation–amultilocusphylogenyofoceanic dolphins (Del- Polster, C., Rössner, G. & Streich, W.J. (2003) The maximum phinidae). Molecular Phylogenetics and Evolution, 60, 345–357. attainable body size of herbivorous mammals: McNab, B.K. (1963) Bioenergetics and the determination of morphophysiological constraints on foregut, and adaptations home range size. The American Naturalist, 97, 133–140. of hindgut fermenters. Oecologia, 136, 14–27. McNab, B.K. (1986) The influence of food habits on the energet- Costa, D.P., Robinson, P.W., Arnould, J.P.Y., Harrison, A., ics of eutherian mammals. Ecological Monographs, 56, 1–19. Simmons, S.E., Hassrick, J.L., Hoskins, A.J., Kirkman, S.P., Maddison, W.P. & Maddison, D.R. (2010) Mesquite: a modular Oosthuizen, H., Villegas-Amtmann, S. & Crocker, D. (2010) system for evolutionary analysis. Version 2.74. Accurcy of ARGOS locations of pinniped at-sea estimated Martins, E.P. (2004) COMPARE, version 4.6b. Computer using Fastloc GPS. PLoS One, 5, e8677. programs for the statistical analysis of comparative data.

Distributed by the author at http://compare.bio.indiana.edu/. tracking data in a fluid environment. Journal of Experimental Department of Biology, Indiana University. Biology, 209, 128–140. Martins, E.P. & Hansen, T.F. (1997) Phylogenies and the com- Wall, W.P. (1983) The correlation between high limb-bone parative method: a general approach to incorporating density and aquatic habits in recent mammals. Journal of phylogenetic information into analysis of interspecific data. Paleontology, 57, 197–207. The American Naturalist, 149, 646–667. Williams, T.M. (1999) The evolution of cost efficient swimming Nagy, A.N. (2005) Field metabolic rate and body size. Journal of in marine mammals: limits to energetic optimization. Philo- Experimental Biology, 208, 1621–1625. sophical Transactions of the Royal Society B: Biological Sciences, Nowacek, D.P., Johnson, M.P., Tyack, P.L., Shorter, K.A., 354, 193–201. McLellan, W.A. & Pabst, A. (2001) Buoyant balaenids: the ups Williams, T.M., Zavanelli, M., Miller, M.A., Goldbeck, R.A., and downs of buoyancy in right whales. Proceedings of the Morledge, M., Casper, D., Pabst, D.A., McLellan, W., Cantin, Royal Society B: Biological Sciences, 268, 1811–1816. L.P. & Kliger, D.S. (2008) Running, swimming and diving Pawar, S., Dell, A.I. & Savage, V.M. (2012) Dimensionality of modifies neuroprotecting globins in the mammalian brain. consumer search space drives trophic interaction strengths. Proceedings of the Royal Society B: Biological Sciences, 275, Nature, 486, 485–489. 751–758. Peters, R.H. (1983) The ecological implications of body size. Cam- bridge University Press, Cambridge. Additional references to the data sources may be found at the Pontzer, H. (2007) Effective limb length and the scaling of loco- end of Appendices S1 & S2 at [http://onlinelibrary.wiley.com/ motor costs in terrestrial animals. Journal of Experimental doi/10.1111/geb.12194/suppinfo]. Biology, 210, 1752–1761. Revell, L.J., Harmon, L.J. & Collar, D.C. (2008) Phylogenetic SUPPORTING INFORMATION signal, evolutionary process, and rate. Systematic Biology, 57, 591–601. Additional supporting information may be found in the online Schoener, T.W. (1968) Sizes of feeding territories among birds. version of this article at the publisher’s web-site. Ecology, 49, 123–141. Appendix S1 Database of home range and body mass values for Seaman, D.E. & Powell, R.A. (1996) An evaluation of the accu- 462 species of mammal, including sources. racy of kernel density estimators for home range analysis. Appendix S2 Additional information on sample size, data col- Ecology, 77, 2075–2085. lection and sampling protocols for data used in home range Sibly, R.M., Zuo, W., Kodric-Brown, A. & Brown, J.H. (2012) calculation. Rensch’s rule in large herbivorous mammals derived Appendix S3 Additional analyses and results. from metabolic scaling. The American Naturalist, 179, 169– Figure S1 The phylogeny of 462 extant species of mammal and 177. their home range size. Sims, D.W., Southall, E.J., Humphries, N.E., Hays, G.C., Bradshaw, C.J.A., Pitchford, J.W., James, A., Ahmed, M.Z., BIOSKETCHES Brierley, A.S., Hindell, M.A., Morritt, D., Musyl, M.K., Righton, D., Shepard, E.L.C., Wearmouth, V.J., Wilson, R.P., Marlee Tucker is a PhD candidate under the Witt, M.J. & Metcalfe, J.D. (2008) Scaling laws of marine supervision of Tracey Rogers. Marlee’s research predator search behaviour. Nature, 451, 1098–1102. encompasses macroecological patterns in mammals, Southwell, C. (2007) 1994 to 2000 - Antarctic Pack Ice Seals specifically changes in behaviours and patterns that (APIS) Survey, Australian Antarctic Data Centre - ARGOS sat- have occurred with the colonization of the marine ellite tracking record. Available at http://data.aad.gov.au/aadc/ environment. argos/profile_list.cfm?taxon_id=25 (accessed 6 May 2014). Steppan, S.J., Storz, B.L. & Hoffmann, R.S. (2004) Nuclear DNA Terry Ord is an evolutionary ecologist with broad phylogeny of the squirrels (Mammalia: Rodentia) and the interests in animal behaviour, adaptation and evolution of arboreality from c-myc and RAG1. Molecular macroevolution. Phylogenetics and Evolution, 30, 703–719. Tracey Rogers is an ecologist interested in how Stone, G.N., Nee, S. & Felsenstein, J. (2011) Controlling for mammals respond to environmental change including non-independence in comparative analysis of patterns across broad-scale patterns in ecology related to body size, diet populations within species. Philosophical Transactions of the and trophic level. Royal Society B: Biological Sciences, 366, 1410–1424. Swihart, R.K., Slade, N.A. & Bergstrom, B.J. (1988) Relating Author contributions: M.A.T., T.L.R. and T.J.O. body size to the rate of home range use in mammals. Ecology, conceived the study. M.A.T. and T.L.R. collected and 69, 393–399. compiled the data. M.A.T. conducted the analyses. Tremblay, Y., Shaffer, S.A., Fowler, S.L., Kuhn, C.E., McDonald, M.A.T., T.J.O. and T.L.R. wrote the paper. B.I., Weise, M.J., Bost, C.A., Weimerskirch, H., Crocker, D.E., Goebel, M.E. & Costa, D.P. (2006) Interpolation of animal Editor: Marcel Cardillo

Appendix 2

Supplementary Information for Chapter 2

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Table 2.1 Database of home range and body mass values for 462 mammal species, including sources.

log10 log10 Home Taxon Mass Diet Environment References range (kg) (km2) Abrothrix_olivaceus -3.33 -1.61 Omnivore Terrestrial Jones et al. 2009 Acinonyx_jubatus 2.91 1.70 Carnivore Terrestrial Caro 1994 Aepyceros_melampus 0.51 1.80 Herbivore Terrestrial duToit 1990, Murray 1982 Ailuropoda_melanoleuca 0.62 1.94 Herbivore Terrestrial Schaller et al. 1985 Ailurus_fulgens 0.01 0.73 Herbivore Terrestrial Reid et al. 1991 Alcelaphus_buselaphus 0.34 2.13 Herbivore Terrestrial Ables and Ables 1971 Addison et al. 1980, Ballard et al. 1991, Bangs and Bailey 1980b, Bangs et al. 1984, Cederlund and Okarma 1988, Cederlund and Sand 1994, Doerr 1983, Grauvogel 1984, Hauge and Keith Alces_alces 1.97 2.49 Herbivore Terrestrial 1981, Leptich and Gilbert 1989, MacCracken et al. 1997, Stenhouse et al. 1994, Van Dyke et al. 1995 Alouatta_seniculus -0.80 0.81 Omnivore Terrestrial Jones et al. 2009 Amblysomus_hottentotus -3.33 -1.20 Omnivore Terrestrial Jones et al. 2009 Ammospermophilus_leucurus -1.30 -0.98 Omnivore Terrestrial Jones et al. 2009 Ammospermophilus_nelsoni -1.40 -0.79 Omnivore Terrestrial Jones et al. 2009 Ammotragus_lervia 0.96 2.22 Herbivore Terrestrial Hampy 1978 Antechinus_stuartii -1.46 -1.56 Carnivore Terrestrial Lazenby-Cohen and Cockburn 1991 Antilocapra_americana 1.01 1.66 Herbivore Terrestrial Bayless 1969, Reynolds 1984 Aonyx_capensis 2.08 1.29 Omnivore Terrestrial Jones et al. 2009 Aotus_trivirgatus -1.30 -0.04 Omnivore Terrestrial Jones et al. 2009 Aplodontia_rufa -2.98 0.05 Herbivore Terrestrial Martin 1971 Apodemus_flavicollis -2.12 -1.50 Herbivore Terrestrial Scharzenberger and Klingel 1995 Apodemus_sylvaticus -1.88 -1.67 Herbivore Terrestrial Attuquayefio et al. 1986, Corp et al. 1997, Wolton 1985 Apomys_musculus -2.63 -1.67 Omnivore Terrestrial Jones et al. 2009 Arctocephalus_gazella 3.75 1.53 Carnivore Marine Personal communication; Staniland et al., 2010 Arctocephalus_tropicalis 5.34 1.52 Carnivore Marine This study

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Atherurus_africanus -0.82 0.44 Herbivore Terrestrial Emmons 1983 Atilax_paludinosus 0.35 0.56 Carnivore Terrestrial Ray 1997 Axis_axis 0.56 1.80 Herbivore Terrestrial Ables et al. 1977, Moe and Wegge 1994 Balaena_mysticetus 4.39 4.49 Carnivore Marine Heide-Jorgensen et al., 2007 Bassariscus_astutus -0.08 0.01 Omnivore Terrestrial Toweill and Teer 1981, Trapp 1978 Bathyergus_suillus -2.57 -0.20 Herbivore Terrestrial Davies and Jarvis 1986 Bettongia_gaimardi -0.34 0.22 Herbivore Terrestrial Taylor 1993 Bison_bison 2.42 2.80 Herbivore Terrestrial Larter and Gates 1994, Lott and Minta 1983, Van Vuren 1983 Bison_bonasus 1.01 2.80 Herbivore Terrestrial Krasinska and Krasinski 1995 Brachylagus_idahoensis -2.31 -0.47 Herbivore Terrestrial Katzner and Parker 1997 Brachyteles_arachnoides 0.33 1.02 Omnivore Terrestrial Jones et al. 2009 Bradypus_torquatus -1.35 0.59 Herbivore Terrestrial Chiarello 1998 Bunopithecus_hoolock -0.64 0.83 Omnivore Terrestrial Jones et al. 2009 Callicebus_moloch -1.52 -0.02 Omnivore Terrestrial Jones et al. 2009 Callimico_goeldii -0.35 -0.25 Omnivore Terrestrial Jones et al. 2009 Callithrix_humeralifera -0.89 -0.43 Omnivore Terrestrial Jones et al. 2009 Callithrix_pygmaea -2.51 -0.91 Omnivore Terrestrial Jones et al. 2009 Callosciurus_erythraeus -1.85 -0.44 Omnivore Terrestrial Tamura et al. 1989 Caluromys_philander -1.50 -0.58 Omnivore Terrestrial Julien-Laferriere 1995 Canis_adustus 0.04 0.98 Omnivore Terrestrial Fuller et al. 1989 Canis_aureus 0.17 0.96 Omnivore Terrestrial Fuller et al. 1989, Poche et al. 1987 Daniels and Bekoff 1989, Gipson 1983, Harden 1985, Nakada et al. 1996, Scott and Causey Canis_familiaris 1.46 1.15 Omnivore Terrestrial 1973, Thomson 1992 Althoff 1978, Andelt 1985, Andelt and Gipson 1979, Babb and Kennedy 1988, Berg and Chesness 1978, Bowen 1982, Bradley and Fagre 1988, Danner and Smith 1980, Fuller and Keith 1981, Gese et al. 1988, Harrison et al. 1989, Hibler 1977, Holzman et al. 1992, Laundre Canis_latrans 1.46 1.20 Omnivore Terrestrial and Keller 1983, Litvaitis and Shaw 1980, Major and Sherburne 1987, Mills and Knowlton 1991, Person and Hirth 1991, Pyrah 1984, Roy and Dorrance 1985, Sargeant et al. 1987, Servin and Huxley 1995, Springer 1982, Sumner et al. 1984, White et al. 1994, Windberg and Knowlton

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1988, Windberg et al. 1997, Witmer and de Calesta 1986, Woodruff and Keller 1982 Ballard et al. 1997, Bjorge and Gunson 1989, Carbyn 1983, Ciucci et al. 1997, Fritts and Mech Canis_lupus 2.67 1.63 Carnivore Terrestrial 1981, Fuller 1989, Messier 1985, Okarma et al. 1998, Peterson et al. 1984, Potvin 1987, VanBallenberghe et al. 1975 Canis_mesomelas 1.20 1.00 Omnivore Terrestrial Ferguson et al. 1983, Fuller et al. 1989 Canis_simensis 0.73 1.44 Carnivore Terrestrial Sillero Zubiri and Gottelli 1995 Capra_hircus 1.81 1.71 Herbivore Terrestrial King 1992, OBrien 1984 Capra_pyrenaica -0.15 1.84 Herbivore Terrestrial Escos and Alados 1992 Capreolus_capreolus -0.17 1.38 Herbivore Terrestrial Bideau et al. 1993, Cederlund 1983, Chapman et al. 1993, Guillet et al. 1996 Avenant and Nel 1998, Bothma and ldRiche 1994, Norton and Lawson 1985, vanHeezik and Caracal_caracal 2.58 1.11 Carnivore Terrestrial Seddon 1998 Castor_canadensis -1.11 1.31 Herbivore Terrestrial Davis and Guynn 1993, Wheatley 1997 Catagonus_wagneri 1.04 1.54 Herbivore Terrestrial Taber et al. 1994 Cebus_capucinus -0.20 0.48 Omnivore Terrestrial Jones et al. 2009 Cephalophus_callipygus -0.38 1.26 Herbivore Terrestrial Feer 1989 Cephalophus_dorsalis -0.45 1.31 Herbivore Terrestrial Feer 1989 Cephalorhynchus_heavisidii 2.78 1.88 Carnivore Marine Elwin et al., 2006 Ceratotherium_simum 1.20 3.35 Herbivore Terrestrial Pienaar et al. 1993 Cercartetus_nanus -2.15 -1.62 Omnivore Terrestrial Laidlaw and Wilson 1996 Cercopithecus_cephus -0.46 0.54 Omnivore Terrestrial Jones et al. 2009 Cercopithecus_diana 0.28 0.64 Omnivore Terrestrial Jones et al. 2009 Cercopithecus_mitis -0.80 0.70 Omnivore Terrestrial Jones et al. 2009 Cercopithecus_nictitans 0.24 0.72 Omnivore Terrestrial Jones et al. 2009 Cerdocyon_thous 0.48 0.76 Omnivore Terrestrial MacDonald and Courtenay 1996, Sunquist et al. 1989 Catt and Staines 1987, Cole et al. 1997, Craighead et al. 1973, Edge et al. 1985, Franklin and Cervus_elaphus 1.87 2.37 Herbivore Terrestrial Lieb 1979, Georgii 1980, Irwin and Peek 1983, Jenkins and Starkey 1982, McCorquodale et al. 1989, Strohmeyer and Peek 1996, Waldrip and Shaw 1979 Cervus_nippon -0.07 1.47 Herbivore Terrestrial Borkowsky and Furubayashi 1998, Feldhamer et al. 1982 Cheirogaleus_major -1.40 -0.35 Omnivore Terrestrial Jones et al. 2009

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Chrysocyon_brachyurus 1.43 1.38 Omnivore Terrestrial Dietz 1984 Chrysospalax_trevelyani -3.21 -0.36 Carnivore Terrestrial Jones et al. 2009 Clethrionomys_californicus -1.80 -1.65 Herbivore Terrestrial Tallmon and Mills 1994 Coendou_prehensilis -0.73 0.63 Herbivore Terrestrial Montgomery and Lubin 1978 Condylura_cristata -2.44 -1.32 Carnivore Terrestrial Jones et al. 2009 Conepatus_humboldtii -0.79 0.12 Omnivore Terrestrial Fuller et al. 1987 Conepatus_semistriatus -0.45 0.38 Omnivore Terrestrial Sunquist et al. 1989 Crocidura_russula -3.63 -2.00 Carnivore Terrestrial Jones et al. 2009 Crocuta_crocuta 2.24 1.81 Carnivore Terrestrial Gasaway et al. 1989, Sillero Zubiri and Gottelli 1992 Cryptomys_damarensis -1.89 -0.83 Herbivore Terrestrial Lovegrove 1988 Cryptomys_hottentotus -2.80 -1.19 Herbivore Terrestrial Davies and Jarvis 1986 Cryptoprocta_ferox -0.05 0.98 Carnivore Terrestrial Jones et al. 2009 Cryptotis_parva -2.76 -2.30 Omnivore Terrestrial Jones et al. 2009 Cuon_alpinus 1.84 1.20 Carnivore Terrestrial Venkataraman et al. 1995 Cyclopes_didactylus -1.40 -0.58 Carnivore Terrestrial Jones et al. 2009 Cynictis_penicillata -0.23 -0.21 Carnivore Terrestrial Cavallini 1993 Cystophora_cristata 4.72 2.56 Carnivore Marine Bajzak et al. 2009 Dactylopsila_trivirgata -1.10 -0.38 Omnivore Terrestrial Jones et al. 2009 Dama_dama -0.01 1.85 Herbivore Terrestrial Nugent 1994 Dasypus_novemcinctus -1.52 0.60 Omnivore Terrestrial Jones et al. 2009 Dasyurus_geoffroii 0.36 0.04 Carnivore Terrestrial Jones et al. 2009 Dasyurus_maculatus 0.16 0.52 Omnivore Terrestrial Jones et al. 2009 Dasyurus_viverrinus -0.44 0.04 Omnivore Terrestrial Jones et al. 2009 Daubentonia_madagascariensi -0.96 0.44 Omnivore Terrestrial Jones et al. 2009 s Delphinapterus_leucas 3.52 3.18 Carnivore Marine Hobbs et al., 2005 Dendrolagus_lumholtzi -1.71 0.82 Herbivore Terrestrial Newell 1999

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Desmana_moschata -2.28 -0.37 Omnivore Terrestrial Jones et al. 2009 Diceros_bicornis 1.62 3.02 Herbivore Terrestrial Frame 1980, Goddard 1967, Kiwia 1989, Mukinya 1973 Didelphis_marsupialis -0.25 0.04 Omnivore Terrestrial Sunquist et al. 1987 Didelphis_virginiana -0.28 0.70 Omnivore Terrestrial Gillette 1980, Shirer and Fitch 1970 Dipodomys_ingens -3.36 -0.81 Herbivore Terrestrial Braun 1985 Dipodomys_merriami -2.13 -1.38 Herbivore Terrestrial Jones 1989, Schroder 1987 Dipodomys_ordii -1.75 -1.25 Herbivore Terrestrial Schroder 1987 Dipodomys_spectabilis -2.52 -0.84 Herbivore Terrestrial Schroder 1979, Schroder 1987 Dipodomys_stephensi -2.83 -1.12 Herbivore Terrestrial Kelly and Price 1995 Dolichotis_patagonum -0.01 0.90 Herbivore Terrestrial Taber and MacDonald 1992 Dugong_dugon 2.12 2.30 Herbivore Marine Sheppard et al., 2006 Echymipera_clara -2.00 0.08 Omnivore Terrestrial Jones et al. 2009 Echymipera_kalubu -1.70 -0.08 Omnivore Terrestrial Jones et al. 2009 Eira_barbara 1.16 0.65 Carnivore Terrestrial Konecny 1989, Sunquist et al. 1989 Elephantulus_rufescens -2.47 -1.24 Carnivore Terrestrial Rathbun 1979 Elephas_maximus 2.04 3.60 Herbivore Terrestrial Sukumar 1989 Enhydra_lutris 0.18 1.44 Carnivore Marine Garshelis and Garshelis 1984 Equus_burchelli 2.21 2.38 Herbivore Terrestrial Smuts 1975 Equus_caballus 1.35 2.63 Herbivore Terrestrial Berger 1987 Equus_zebra 0.97 2.46 Herbivore Terrestrial Penzhorn 1982 Eremitalpa_granti -1.33 -1.64 Carnivore Terrestrial Fielden 1991 Erethizon_dorsatum -0.44 0.94 Herbivore Terrestrial Roze 1987 Erinaceus_europaeus -0.71 -0.10 Carnivore Terrestrial Boitani and Reggiani 1984, Morris 1988, Reeve 1982, Schoenfeld and YomTov 1985 Erythrocebus_patas 1.61 0.90 Omnivore Terrestrial Jones et al. 2009 Eulemur_mongoz -1.15 0.25 Omnivore Terrestrial Jones et al. 2009 Eumetopias_jubatus 4.68 2.44 Carnivore Marine Merrick et al., 1997

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Euphractus_sexcinctus -0.03 0.67 Omnivore Terrestrial Jones et al. 2009 Apps 1986, Fitzgerald and Karl 1986, Genovesi et al. 1995, Hall et al. 2000, Jones and Coman Felis_catus 0.17 0.53 Carnivore Terrestrial 1982, Konecny 1987, Norbury et al. 1998, Page et al. 1992, Weber and Dailly 1998 Felis_silvestris 0.45 0.68 Carnivore Terrestrial Stahl et al. 1988 Fossa_fossana -0.05 0.27 Omnivore Terrestrial Jones et al. 2009 Funambulus_pennantii -2.74 -0.99 Herbivore Terrestrial Prakash et al. 1968 Galago_senegalensis -0.96 -0.67 Omnivore Terrestrial Jones et al. 2009 Galemys_pyrenaicus -2.86 -1.22 Carnivore Terrestrial Jones et al. 2009 Galerella_pulverulenta -0.23 -0.23 Omnivore Terrestrial Cavallini and Nel 1990 Galictis_vittata 0.62 0.24 Carnivore Terrestrial Sunquist et al. 1989 Galidia_elegans -0.70 -0.09 Omnivore Terrestrial Jones et al. 2009 Gazella_gazella 0.27 1.33 Herbivore Terrestrial Dunham 1998 Genetta_genetta 0.89 0.24 Carnivore Terrestrial Palomares and Delibes 1994 Genetta_tigrina -1.24 0.33 Carnivore Terrestrial Ikeda et al. 1982 Georychus_capensis -3.57 -0.62 Herbivore Terrestrial Jarvis and Beviss-Challinor unpublished data, cited in Reichman and Smith 1990 Gerbillurus_paeba -2.00 -1.59 Omnivore Terrestrial Jones et al. 2009 Giraffa_camelopardalis 2.14 3.13 Herbivore Terrestrial Berry 1978, duToit 1990, Langman 1973, Leuthold and Leuthold 1978 Glaucomys_sabrinus -1.10 -0.83 Herbivore Terrestrial Fridell and Litvaitis 1991, Witt 1992 Glaucomys_volans -1.53 -1.19 Herbivore Terrestrial Bendel and Gates 1987, Madden 1974, Stone et al. 1997 Graphiurus_ocularis -0.96 -1.16 Herbivore Terrestrial vanHensbergen and Channing 1989 Banci and Harestad 1990, Gardner 1985 MS Alaska, Hornocker and Hash 1981, Landa et al. Gulo_gulo 2.56 1.33 Carnivore Terrestrial 1998, Magoun 1985, Whitman et al. 1986 Halichoerus_grypus 3.42 1.92 Carnivore Marine Sjoberg and Ball, 2000 Heliophobius_argenteocinereus -3.76 -0.81 Herbivore Terrestrial Jarvis and Sale 1971 cited in Reichman and Smith 1990 Helogale_parvula -0.55 -0.55 Carnivore Terrestrial Jones et al. 2009 Hemiechinus_auritus -1.39 -0.53 Carnivore Terrestrial Schoenfeld and YomTov 1985 Herpestes_ichneumon 0.45 0.47 Omnivore Terrestrial Delibes and Beltran 1985

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Herpestes_javanicus -1.50 -0.36 Omnivore Terrestrial Nellis and Everard 1983 Herpestes_naso -0.28 0.56 Omnivore Terrestrial Ray 1997 Heterocephalus_glaber -2.27 -1.41 Herbivore Terrestrial Jarvis 1985 cited in Reichman and Smith 1990 Hyaena_brunnea 1.32 1.68 Carnivore Terrestrial Viljoen 1986 Hyaena_hyaena 1.77 1.60 Carnivore Terrestrial Kruuk 1976, vanAarde et al. 1988 Hydrurga_leptonyx 4.18 2.54 Carnivore Marine This study Hyemoschus_aquaticus -0.72 1.04 Herbivore Terrestrial Dubost 1978citedinEmmons 1983 Hylaeamys_megacephalus -2.11 -1.18 Herbivore Terrestrial Guillotin 1982 Hylobates_agilis -0.57 0.77 Omnivore Terrestrial Jones et al. 2009 Hylobates_klossii -0.68 0.77 Omnivore Terrestrial Jones et al. 2009 Hylobates_lar -0.34 0.75 Omnivore Terrestrial Jones et al. 2009 Hylobates_moloch -0.77 0.77 Omnivore Terrestrial Jones et al. 2009 Hylobates_muelleri -0.42 0.77 Omnivore Terrestrial Jones et al. 2009 Hylobates_pileatus -0.48 0.74 Omnivore Terrestrial Jones et al. 2009 Hylomys_suillus -2.74 -1.24 Omnivore Terrestrial Jones et al. 2009 Hypogeomys_antimena -1.46 0.07 Herbivore Terrestrial Cook et al. 1991 Hystrix_africaeaustralis 0.23 1.23 Herbivore Terrestrial Corbet and vanAarde 1996 Hystrix_cristata -0.24 1.13 Omnivore Terrestrial Jones et al. 2009 Hystrix_indica 0.15 1.18 Herbivore Terrestrial Saltz and Alkon 1989 Ichneumia_albicauda -0.41 0.56 Carnivore Terrestrial Ikeda et al. 1982, Waser and Waser 1985 Isoodon_auratus -0.93 -0.41 Carnivore Terrestrial Southgate et al. 1996 Isoodon_macrourus -1.70 0.18 Omnivore Terrestrial Jones et al. 2009 Isoodon_obesulus -1.68 -0.11 Carnivore Terrestrial Broughton and Dickman 1991 Lagostomus_maximus -2.00 0.72 Herbivore Terrestrial Branch 1993 Lagothrix_lagotricha 0.60 0.80 Omnivore Terrestrial Jones et al. 2009 Lasiorhinus_krefftii -0.60 1.41 Herbivore Terrestrial Johnson 1991

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Lemmus_sibiricus -2.08 -1.04 Herbivore Terrestrial Banks et al. 1975 Leontopithecus_chrysopygus 0.07 -0.18 Omnivore Terrestrial Jones et al. 2009 Leontopithecus_rosalia -0.43 -0.23 Omnivore Terrestrial Jones et al. 2009 Leopardus_geoffroyi 0.85 0.56 Carnivore Terrestrial Johnson and Franklin 1991 Crawshaw and Quigley 1989, Emmons 1988, Konecny 1989, Lopez 1985, Ludlow and Sunquist Leopardus_pardalis 0.84 1.00 Carnivore Terrestrial 1987, Sunquist et al. 1989 Leopardus_wiedii 1.04 0.56 Carnivore Terrestrial Konecny 1989 Lepilemur_edwardsi -2.02 -0.09 Omnivore Terrestrial Jones et al. 2009 Leptailurus_serval 0.38 1.08 Carnivore Terrestrial vanAarde and Skinner 1986 Leptonychotes_weddelli 1.98 2.62 Carnivore Marine This study Lepus_americanus -1.49 0.13 Herbivore Terrestrial Boutin 1979, Ferron and Ouellet 1992 Lepus_arcticus 0.46 0.61 Herbivore Terrestrial Hearn et al. 1987 Lepus_californicus 0.20 0.36 Herbivore Terrestrial Smith 1990 Lepus_capensis -0.28 0.55 Herbivore Terrestrial Parkes 1984 Lepus_europaeus -0.54 0.72 Herbivore Terrestrial Broekhuizen and Maaskamp 1982 Lepus_nigricollis -1.86 0.50 Herbivore Terrestrial Kirk and Bathe 1994 Lepus_timidus -0.34 0.45 Herbivore Terrestrial Flux 1970, Hewson and Hinge 1990, Hulbert et al. 1996 Liomys_salvini -2.76 -1.38 Omnivore Terrestrial Jones et al. 2009 Lobodon_carcinophagus 5.57 2.40 Carnivore Marine This study Lophocebus_albigena 0.61 0.87 Omnivore Terrestrial Jones et al. 2009 Loris_tardigradus -2.00 -0.60 Omnivore Terrestrial Jones et al. 2009 DeVilliers and Kok 1997, Dunham 1986, Leuthold 1977, Lindeque and Lindeque 1991, Tchamba Loxodonta_africana 3.24 3.60 Herbivore Terrestrial et al. 1994, Thouless 1996, Viljoen 1989 Lutra_canadensis 1.63 0.97 Carnivore Marine Blundell et al., 2000 Lutra_lutra 1.41 0.95 Carnivore Terrestrial Jones et al. 2009 Lutreolina_crassicaudata -2.73 -0.26 Carnivore Terrestrial Jones et al. 2009 Lutrogale_perspicillata 0.80 0.95 Carnivore Terrestrial Jones et al. 2009

152

Lycaon_pictus 2.64 1.43 Carnivore Terrestrial Anderka et al. 1999, Fuller and Kat 1990 Lynx_canadensis 1.92 1.01 Carnivore Terrestrial Bailey et al. 1986, Koehler 1990, Poole 1994, Slough and Mowat 1996 Lynx_lynx 2.26 1.48 Carnivore Terrestrial Haller and Breitenmoser 1986, Schmidt et al. 1997 Lynx_pardinus 0.98 1.04 Carnivore Terrestrial Ferreras et al. 1997 Bailey 1974, Berg 1981, Bradley and Fagre 1988, Buie et al. 1979, Conner et al. 1992, Fuller et al. 1985, Knick 1990, Koehler and Hornocker 1989, Litvaitis et al. 1987, Lovallo and and erson Lynx_rufus 1.60 1.05 Carnivore Terrestrial 1996, Major and Sherburne 1987, Rolley 1983, Rucker et al. 1989, Whitaker et al. 1987, Witmer and deCalesta 1986, Zezulak and Schwab 1979, Zwank et al. 1985 Macaca_silenus -0.07 0.78 Omnivore Terrestrial Jones et al. 2009 Macropus_antilopinus -0.19 1.44 Herbivore Terrestrial Croft 1987 Macropus_dorsalis -0.04 1.05 Herbivore Terrestrial Evans 1996 Macropus_fuliginosus 0.51 1.34 Herbivore Terrestrial Arnold et al. 1992, Coulson 1993, Priddell et al. 1988 Macropus_giganteus 0.79 1.02 Herbivore Terrestrial Jarman and Taylor 1983 Macropus_robustus -0.01 1.33 Herbivore Terrestrial Clancy and Croft 1990, Croft 1987, Jarman and Taylor 1983 Macropus_rufogriseus -0.79 1.23 Herbivore Terrestrial Johnson 1987 Macropus_rufus 0.89 1.67 Herbivore Terrestrial Priddell et al. 1988 Macroscelides_proboscideus 0.00 -1.41 Omnivore Terrestrial Jones et al. 2009 Madoqua_guentheri -1.56 0.66 Herbivore Terrestrial Ono et al. 1988 Manis_temminckii 1.12 1.10 Carnivore Terrestrial Heath and Coulson 1997 Marmosa_robinsoni -2.66 -1.22 Omnivore Terrestrial Jones et al. 2009 Marmota_flaviventris -1.24 0.53 Herbivore Terrestrial Salsbury and Armitage 1994, Van Vuren unpubl. data Marmota_monax -0.78 0.53 Herbivore Terrestrial Ferron and Oellet 1989, Meier 1992, Swihart 1992 Archibald and Jessup 1984, Bateman 1986, Burnett 1981, Buskirk 1983, Clark et al. 1989, Davis 1983, Katnik et al. 1994, Major 1979, Mech and Rogers 1977, Simon 1980, Slough 1989, Martes_americana 0.85 -0.05 Carnivore Terrestrial Spencer 1981, Steventon 1979, Steventon and Major 1982, Thompson and Colgan 1987, Wynne and Sherburne 1984 Martes_foina 0.64 0.26 Carnivore Terrestrial Genovesi et al. 1997 Martes_martes 0.96 0.39 Carnivore Terrestrial Clevenger 1993, Pulliainen 1984, Schropfer et al. 1997, Zalewski et al. 1995 Martes_pennanti 1.22 0.50 Carnivore Terrestrial Arthur et al. 1989, Garant and Crete 1997

153

Mastomys_natalensis -2.93 -1.18 Omnivore Terrestrial Leirs et al. 1996 Megaptera_novaeangliae 4.68 4.52 Carnivore Marine Dalla Rosa et al., 2008 Meles_meles 0.34 1.09 Omnivore Terrestrial Broseth et al. 1997, Kruuk 1987 Melursus_ursinus 1.00 1.99 Carnivore Terrestrial Melquist 1982 Mephitis_mephitis 0.47 0.66 Omnivore Terrestrial Lariviere and Messier 1998, Shirer and Fitch 1970, Storm 1972 Meriones_hurrianae -3.88 -1.05 Herbivore Terrestrial Fitzwater and Prakash 1969 Microdipodops_megacephalus -2.33 -1.91 Omnivore Terrestrial Jones et al. 2009 Microtus_agrestis -3.15 -1.42 Herbivore Terrestrial Agrell et al. 1996 Microtus_californicus -4.07 -1.15 Herbivore Terrestrial Heske 1987 Microtus_montanus -3.82 -1.25 Herbivore Terrestrial Douglas 1976 Danielson and Swihart 1987, Gaulin and FitzGerald 1988, Harvey and Barbour 1965, Jike et al. Microtus_ochrogaster -3.17 -1.45 Herbivore Terrestrial 1988 Collins and Barrett 1997, Douglas 1976, Gaulin and FitzGerald 1988, Jones 1990, Jones and Microtus_pennsylvanicus -3.39 -1.30 Herbivore Terrestrial Sherman 1983 Microtus_pinetorum -4.44 -1.53 Herbivore Terrestrial Gettle 1975 Microtus_richardsoni -3.38 -1.07 Herbivore Terrestrial Ludwig 1981 Miopithecus_talapoin 0.08 0.10 Omnivore Terrestrial Jones et al. 2009 Mirounga_angustirostris 3.90 3.08 Carnivore Marine LeBoeuf et al., 2000 Mirounga_leonina 5.69 3.18 Carnivore Marine This study Mirza_coquereli -1.40 -0.49 Omnivore Terrestrial Jones et al. 2009 Monachus_schauinslandi 4.00 2.31 Carnivore Marine Curtice et al., 2011 Monodelphis_americana -3.33 -1.71 Carnivore Terrestrial Jones et al. 2009 Monodon_monoceros 4.72 3.11 Carnivore Marine Dietz et al., 2008 Mungos_mungo 0.33 0.10 Carnivore Terrestrial Jones et al. 2009 Muntiacus_reevesi -0.79 1.13 Herbivore Terrestrial Chapman et al. 1993 Mus_musculus -3.21 -1.71 Carnivore Terrestrial Jones et al. 2009 Muscardinus_avellanarius -2.36 -1.51 Herbivore Terrestrial Bright and Morris 1991

154

Mustela_erminea 0.12 -0.57 Carnivore Terrestrial Alterio 1998, Murphy and Dowding 1994, Murphy and Dowding 1995 Mustela_frenata -0.75 -0.82 Carnivore Terrestrial DeVan 1982 Mustela_lutreola -0.68 -0.25 Carnivore Terrestrial Jones et al. 2009 Mustela_nigripes 0.00 -0.04 Carnivore Terrestrial Jones et al. 2009 Mustela_nivalis -0.19 -1.06 Carnivore Terrestrial Norbury et al. 1998 Mustela_putorius_furo -0.05 -0.09 Carnivore Terrestrial Jedrzejewski et al. 1995 Mustela_sibirica 0.61 -0.28 Carnivore Terrestrial Jones et al. 2009 Myocastor_coypus -1.52 0.80 Omnivore Terrestrial Jones et al. 2009 Myodes_californicus -2.80 -1.65 Herbivore Terrestrial Tallmon and Mills 1994 Myodes_gapperi -3.26 -1.70 Omnivore Terrestrial Jones et al. 2009 Myodes_glareolus -2.92 -1.68 Omnivore Terrestrial Jones et al. 2009 Myopus_schisticolor -3.01 -1.52 Herbivore Terrestrial Andreassen and Bondrup Nielsen 1991 Myrmecobius_fasciatus -0.46 -0.29 Carnivore Terrestrial Jones et al. 2009 Myrmecophaga_tridactyla 0.51 1.48 Carnivore Terrestrial Shaw et al. 1987 Nasua_narica 0.24 0.67 Omnivore Terrestrial Gompper 1997, Lanning 1976, Ratnayeke et al. 1994 Nasua_nasua -0.02 0.58 Omnivore Terrestrial Jones et al. 2009 Nectomys_squamipes -2.66 -0.73 Omnivore Terrestrial Jones et al. 2009 Neomys_fodiens -3.77 -1.82 Omnivore Terrestrial Jones et al. 2009 Neophoca_cinervea 2.78 1.95 Carnivore Marine Fowler et al. 2007 Neotoma_cinerea -1.32 -0.40 Herbivore Terrestrial Topping and Millar 1996 Neotoma_fuscipes -2.60 -0.51 Herbivore Terrestrial Cranford 1977, Kelly 1990, Lynch et al. 1994, Sakai and Noon 1997 Neotoma_lepida -3.27 -0.88 Herbivore Terrestrial Thompson 1982 Neotoma_micropus -3.24 -0.59 Herbivore Terrestrial Condit and Ribble 1997 Nesomys_audeberti -2.02 -0.67 Herbivore Terrestrial Ryan et al. 1994 Nesomys_rufus -2.30 -0.78 Herbivore Terrestrial Ryan et al. 1994 Nyctereutes_procyonoides 0.40 0.81 Omnivore Terrestrial Ikeda et al. 1979, Kauhala et al. 1993, Ward and Wurster Hill 1989

155

Ochotona_curzoniae -2.86 -0.81 Herbivore Terrestrial Smith et al. 1986 Ochotona_princeps -2.73 -0.83 Herbivore Terrestrial Kawamichi 1976, Smith and Ivins 1984 Ochrotomys_nuttalli -2.38 -1.64 Omnivore Terrestrial Jones et al. 2009 Dickinson and Garner 1979, Eberhardt et al. 1984, Hayes and Krausman 1993, Kohl et al. 1987, Odocoileus_hemionus 1.54 1.73 Herbivore Terrestrial Kufeld et al. 1989, Leach and Edge 1994, Livesey 1991, Loft et al. 1989, Nicholson et al. 1997, Schoen and Kirchhoff 1985, Stephenson et al. 1996 Beier and McCullough 1990, Holzenbein and Marchinton 1992, Hoskinson and Mech 1976, Ivey and Causey 1981, McShea and Schwede 1993, Mooty et al. 1987, Nelson and Mech 1981, Odocoileus_virginianus 0.40 1.94 Herbivore Terrestrial Sargent and Labisky 1995, Scanlon and Vaughan 1985, Tierson et al. 1985, Vanderhoof and Jacobson 1993, Vercauteren and Hygnstrom 1998, Wiles and Weeks 1986 Okapia_johnstoni 0.77 2.36 Herbivore Terrestrial Hart and Hart 1989 Ondatra_zibethicus -2.47 0.00 Omnivore Terrestrial Jones et al. 2009 Ondatra_zibethicus_ -2.22 0.13 Herbivore Terrestrial Dell et al. 1983 Onychogalea_fraenata -0.37 0.70 Herbivore Terrestrial Evans 1996 Onychomys_torridus -1.59 -1.66 Carnivore Terrestrial Frank and Heske 1992 Orcaella_heinsohni 2.28 2.11 Carnivore Marine Parra, 2006 Orcinus_orca 3.72 3.75 Carnivore Marine Andrews et al., 2008 Oreamnos_americanus 1.37 2.80 Herbivore Terrestrial Rideout 1975 Ornithorhynchus_anatinus -1.16 0.18 Carnivore Terrestrial Gust and Handasyde 1995 Oryctolagus_cuniculus -1.20 0.20 Herbivore Terrestrial Hulbert et al. 1996 Oryzomys_palustris -2.56 -1.27 Omnivore Terrestrial Jones et al. 2009 Otaria_flavescens 3.86 2.37 Carnivore Marine Campagna et al., 2001 Otocyon_megalotis 0.55 0.62 Carnivore Terrestrial Malcolm 1986 Otolemur_crassicaudatus -1.15 0.08 Omnivore Terrestrial Jones et al. 2009 Otolemur_garnettii -0.89 -0.09 Omnivore Terrestrial Jones et al. 2009 Ovis_ammon 0.77 2.06 Herbivore Terrestrial DuBois et al. 1993 Bissonette and Steinkamp 1996, Bristow et al. 1996, Krausman et al. 1989, Leslie and Douglas Ovis_canadensis 1.44 1.96 Herbivore Terrestrial 1979, Payer and Coblentz 1997 Ozotoceros_bezoarticus 0.90 1.54 Herbivore Terrestrial Leeuwenberg et al. 1997

156

Paguma_larvata 0.57 0.48 Omnivore Terrestrial Rabinowitz 1991 Pan_troglodytes 1.10 1.65 Omnivore Terrestrial Jones et al. 2009 Panthera_leo 2.31 2.31 Carnivore Terrestrial Schaller 1972 Panthera_onca 1.92 1.92 Carnivore Terrestrial Crawshaw and Quigley 1991, Rabinowitz and Nottingham 1986 Panthera_pardus 2.70 1.68 Carnivore Terrestrial Bailey 1993, Bothma et al. 1997, Jenny 1996, Norton and Lawson 1985, Stander et al. 1997 Panthera_tigris 1.73 2.05 Carnivore Terrestrial McDougal 1977, Schaller 1967, Sunquist 1981 Paradoxurus_hermaphroditus 0.73 0.54 Omnivore Terrestrial Dhungel and Edge 1985, Rabinowitz 1991 Parascalops_breweri -4.35 -1.29 Omnivore Terrestrial Jones et al. 2009 Paraxerus_cepapi -2.41 -0.65 Omnivore Terrestrial Jones et al. 2009 Paraxerus_palliatus -1.56 -0.43 Herbivore Terrestrial Skinner and van Aarde 1987 Pecari_tajacu 0.40 1.37 Herbivore Terrestrial Bellantoni and Krausman 1993, Ilse and Hellgren 1995, Schweinsburg 1971, Taber et al. 1994 Perameles_bougainville -1.15 -0.64 Omnivore Terrestrial Jones et al. 2009 Perodicticus_potto -0.92 0.03 Omnivore Terrestrial Jones et al. 2009 Perognathus_inornatus -3.75 -1.99 Omnivore Terrestrial Jones et al. 2009 Perognathus_merriami -2.05 -2.16 Omnivore Terrestrial Jones et al. 2009 Perognathus_parvus -2.73 -1.67 Omnivore Terrestrial Jones et al. 2009 Peromyscus_attwateri -2.74 -1.55 Omnivore Terrestrial Jones et al. 2009 Peromyscus_boylii -2.44 -1.55 Omnivore Terrestrial Ribble and Stanley 1998 Peromyscus_californicus -2.92 -1.34 Omnivore Terrestrial Ribble and Salvioni 1990 Peromyscus_crinitus -2.47 -1.79 Omnivore Terrestrial Jones et al. 2009 Peromyscus_gossypinus -2.30 -1.56 Carnivore Terrestrial Jones et al. 2009 Peromyscus_leucopus -1.91 -1.64 Omnivore Terrestrial Mineau and Madison 1977, Ormiston 1985 Peromyscus_maniculatus -2.88 -1.57 Omnivore Terrestrial Mullican 1988 Peromyscus_truei -1.85 -1.60 Omnivore Terrestrial Hall and Morrison 1997, Ribble and Stanley 1998 Petauroides_volans -1.81 0.11 Herbivore Terrestrial Comport et al. 1996 Petaurus_australis -0.34 -0.24 Omnivore Terrestrial Goldingay and Kavanagh 1993

157

Petaurus_breviceps -1.37 -1.14 Omnivore Terrestrial Quin 1995, Quin et al. 1992 Petaurus_norfolcensis -1.42 -0.64 Omnivore Terrestrial Quin 1995 Petrodromus_tetradactylus -1.92 -0.70 Carnivore Terrestrial FitzGibbon 1995 Petrogale_assimilis -0.92 0.67 Herbivore Terrestrial Horsup 1994 Phacochoerus_aethiopicus 0.24 1.91 Herbivore Terrestrial Cumming 1975 Philander_opossum -2.51 -0.37 Omnivore Terrestrial Jones et al. 2009 Phoca_vitulina 2.60 1.50 Carnivore Marine Smith et al., 2006 Phocarctos_hookeri 2.41 2.11 Carnivore Marine Auge et al. 2011 Phocoena_phocoena 4.28 1.74 Carnivore Marine Johnston et al., 2005 Piliocolobus_badius -0.15 0.93 Omnivore Terrestrial Jones et al. 2009 Podomys_floridanus -2.52 -1.51 Omnivore Terrestrial Jones et al. 2009 Pongo_pygmaeus 0.74 1.73 Omnivore Terrestrial Jones et al. 2009 Potorous_longipes -0.43 0.28 Herbivore Terrestrial Green et al. 1998 Potos_flavus -0.55 0.46 Herbivore Terrestrial Julien-LaFerriere 1993, Kays and Gittleman 1995 Priodontes_maximus 0.66 1.61 Carnivore Terrestrial Jones et al. 2009 Prionailurus_bengalensis 0.38 0.40 Carnivore Terrestrial Rabinowitz 1990 Fritzell 1978, Gehrt and Fritzell 1997, Hoffman and Gottschang 1977, Sherfy and Chapman Procyon_lotor 0.52 1.03 Omnivore Terrestrial 1980, Shirer and Fitch 1970, Urban 1970 Proechimys_brevicauda -2.30 -0.55 Omnivore Terrestrial Jones et al. 2009 Proechimys_cuvieri -2.24 -0.46 Herbivore Terrestrial Guillotin 1982 Proechimys_longicaudatus -2.68 -0.69 Omnivore Terrestrial Jones et al. 2009 Proechimys_semispinosus -2.98 -0.37 Herbivore Terrestrial Seamon and Adler 1999 Proechimys_simonsi -2.50 -0.55 Omnivore Terrestrial Jones et al. 2009 Proteles_cristatus 0.58 1.00 Carnivore Terrestrial Skinner and van Aarde 1986 Pseudalopex_culpaeus 0.69 0.87 Carnivore Terrestrial Johnson and Franklin 1994, Salvatori et al. 1999 Pseudalopex_griseus 0.30 0.60 Carnivore Terrestrial Johnson and Franklin 1994 Pseudomys_chapmani -1.13 -2.00 Omnivore Terrestrial Anstee et al. 1997

158

Pseudomys_fuscus -3.20 -0.91 Herbivore Terrestrial Bubela et al. 1991 Pseudomys_higginsi -2.67 -1.20 Omnivore Terrestrial Jones et al. 2009 Pteromys_volans -1.40 -0.84 Omnivore Terrestrial Jones et al. 2009 Pteronura_brasiliensis 2.01 1.41 Carnivore Terrestrial Jones et al. 2009 Pudu_puda -0.70 0.88 Herbivore Terrestrial Eldridge et al. 1987 Belden et al. 1988, Hemker et al. 1984, Logan et al. 1986, Maehr et al. 1991, Pittman et al. Puma_concolor 2.49 1.95 Carnivore Terrestrial 1995, Ross and Jalkotzy 1992, Seidensticker et al. 1973, Spreadbury et al. 1996 Puma_yagouaroundi_ 1.83 0.83 Carnivore Terrestrial Konecny 1989 Pygeretmus_pumilio -2.50 -1.28 Herbivore Terrestrial Rogovin et al. In press Rangifer_tarandus 3.55 2.01 Herbivore Terrestrial Bradshaw et al. 1995, Edmonds 1988, Stuart Smith et al. 1997 Raphicerus_campestris -0.21 1.05 Herbivore Terrestrial du Toit 1990 Rattus_everetti -2.37 -0.60 Omnivore Terrestrial Jones et al. 2009 Rattus_exulans -3.10 -1.30 Omnivore Terrestrial Jones et al. 2009 Rattus_rattus -2.70 -0.85 Omnivore Terrestrial Jones et al. 2009 Rattus_verecundus -2.82 -1.01 Omnivore Terrestrial Jones et al. 2009 Reithrodontomys_fulvescens -2.77 -1.94 Omnivore Terrestrial Jones et al. 2009 Reithrodontomys_montanus -2.61 -1.96 Omnivore Terrestrial Jones et al. 2009 Reithrodontomys_raviventris -2.67 -1.96 Herbivore Terrestrial Bias and Morrison 1999 Rhynchocyon_chrysopygus -1.54 -0.27 Carnivore Terrestrial FitzGibbon 1995, Rathbun 1979 Rupicapra_rupicapra 0.53 1.49 Herbivore Terrestrial Clarke and Henderson 1984 Saguinus_fuscicollis -0.48 -0.40 Omnivore Terrestrial Jones et al. 2009 Saguinus_midas -1.05 -0.27 Omnivore Terrestrial Jones et al. 2009 Saguinus_oedipus -0.77 -0.34 Omnivore Terrestrial Jones et al. 2009 Saimiri_sciureus -0.19 -0.13 Omnivore Terrestrial Jones et al. 2009 Scalopus_aquaticus -2.13 -0.99 Carnivore Terrestrial Harvey 1976 Scapanus_orarius -2.82 -1.21 Omnivore Terrestrial Jones et al. 2009 Sciurus_aberti -0.88 -0.10 Herbivore Terrestrial Farentinos 1979, Hall 1981, Patton 1975, Patton et al. 1985

159

Sciurus_carolinensis -2.31 -0.27 Herbivore Terrestrial Doebel and McGinnes 1974 Sciurus_granatensis -2.00 -0.50 Omnivore Terrestrial Jones et al. 2009 Sciurus_lis -0.77 -0.58 Herbivore Terrestrial Tamura 1998 Sciurus_niger -0.89 -0.02 Herbivore Terrestrial Benson 1980, Kantola and Humphrey 1990, Sheperd and Swihart 1995 Sciurus_vulgaris -1.13 -0.48 Herbivore Terrestrial Wauters et al. 1994, Wiegand 1995 Sigmodon_hispidus -2.55 -0.96 Omnivore Terrestrial Jones et al. 2009 Sminthopsis_leucopus -1.94 -1.64 Carnivore Terrestrial Laidlaw et al. 1996 Sorex_araneus -3.28 -2.04 Omnivore Terrestrial Jones et al. 2009 Sorex_arcticus -2.32 -2.09 Carnivore Terrestrial Jones et al. 2009 Sorex_cinereus -2.30 -2.38 Carnivore Terrestrial Jones et al. 2009 Sorex_coronatus -3.43 -2.03 Carnivore Terrestrial Jones et al. 2009 Sorex_gracillimus -3.56 -2.36 Carnivore Terrestrial Jones et al. 2009 Sorex_minutus -2.85 -2.36 Omnivore Terrestrial Jones et al. 2009 Sorex_monticolus -2.78 -2.16 Omnivore Terrestrial Jones et al. 2009 Sorex_palustris -2.59 -1.88 Omnivore Terrestrial Jones et al. 2009 Sorex_unguiculatus -4.11 -1.85 Carnivore Terrestrial Jones et al. 2009 Sotalia_fluviatilis 1.18 1.74 Carnivore Marine Flores et al., 2004 Sotalia_guianensis 0.90 1.90 Carnivore Marine Oshima et al., 2010 Sousa_chinensis 2.29 2.33 Carnivore Marine Parra, 2006 Spalacopus_cyanus -4.39 -1.00 Herbivore Terrestrial TorresMura 1990 Spermophilus_beecheyi -3.28 -0.14 Herbivore Terrestrial Boellstorff and Owings 1995 Spermophilus_columbianus -3.27 -0.24 Herbivore Terrestrial Festa Bianchet and Boag 1982 Spermophilus_franklinii -0.77 -0.20 Herbivore Terrestrial Choromanski Norris et al. 1989 Spermophilus_parryii -1.52 -0.10 Herbivore Terrestrial Hubbs and Boonstra 1998 Spermophilus_spilosoma -1.82 -0.97 Herbivore Terrestrial Streubel 1975 Spermophilus_tereticaudus -2.00 -0.83 Omnivore Terrestrial Jones et al. 2009

160

Spermophilus_tridecemlineatus -1.81 -0.70 Herbivore Terrestrial Streubel 1975 Spermophilus_variegatus -1.37 -0.13 Herbivore Terrestrial Ortega 1990, Shriner and Stacey 1991 Spilogale_putorius -0.63 -0.23 Omnivore Terrestrial Crooks and Van Vuren 1995 Stylodipus_telum -2.35 -1.22 Herbivore Terrestrial Heske et al. 1995 Suricata_suricatta 1.15 -0.14 Carnivore Terrestrial Jones et al. 2009 Baber and Coblentz 1986, Boitani et al. 1994, Caley 1997, Coblentz and Baber 1987, Ilse and Sus_scrofa 0.90 1.92 Omnivore Terrestrial Hellgren 1995, Massei et al. 1997, Saunders and Kay 1996, Van Vuren and Coblentz 1989, Wood and Brenneman 1980 Sylvilagus_aquaticus -1.74 0.33 Herbivore Terrestrial Kjolhaug and Woolf 1988 Sylvilagus_floridanus -1.54 0.13 Herbivore Terrestrial Allen et al. 1982, Althoff and Storm 1989, Anderson and Pelton 1976, Trent and Rongstad 1974 Sylvilagus_palustris -1.40 0.13 Herbivore Terrestrial Forys and Humphrey 1996 Synaptomys_cooperi -2.34 -1.42 Herbivore Terrestrial Danielson and Swihart 1987 Syncerus_caffer 1.91 2.77 Herbivore Terrestrial Funston et al. 1994, Leuthold 1972, Stark 1986 Tachyglossus_aculeatus -0.35 0.65 Carnivore Terrestrial Abensperg Traun 1991, Augee et al. 1992, Wilkinson et al. 1998 Tachyoryctes_splendens -4.00 -0.59 Herbivore Terrestrial Jarvis 1973 cited in Reichman and Smith 1990 Talpa_europaea -2.52 -1.02 Carnivore Terrestrial Macdonald et al. 1997 Talpa_romana -2.55 -1.09 Carnivore Terrestrial Loy et al. 1994 Tamandua_mexicana -0.60 0.62 Carnivore Terrestrial Jones et al. 2009 Tamandua_tetradactyla 0.48 0.68 Carnivore Terrestrial Jones et al. 2009 Tamias_amoenus -2.09 -1.57 Herbivore Terrestrial Martinsen 1968 Tamias_minimus -1.83 -1.37 Herbivore Terrestrial Bergstrom 1988, Martinsen 1968, Sheppard 1972 Tamias_quadrimaculatus -2.22 -1.08 Omnivore Terrestrial Jones et al. 2009 Tamias_quadrivittatus -1.27 -1.37 Herbivore Terrestrial Bergstrom 1988 Tamias_senex -2.00 -1.05 Omnivore Terrestrial Jones et al. 2009 Tamias_sibiricus -2.71 -1.02 Herbivore Terrestrial Geinitz 1980 Tamias_speciosus -2.00 -1.22 Omnivore Terrestrial Jones et al. 2009 Tamias_townsendii -2.14 -1.10 Omnivore Terrestrial Jones et al. 2009

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Tamias_umbrinus -1.49 -1.37 Herbivore Terrestrial Bergstrom 1988 Tamiasciurus_douglasii -2.49 -0.65 Omnivore Terrestrial Jones et al. 2009 Tamiasciurus_hudsonicus -2.32 -0.65 Herbivore Terrestrial Benhamou 1996, Boutin and Schweiger 1988 Tarsius_bancanus -1.70 -0.94 Omnivore Terrestrial Jones et al. 2009 Tarsius_tarsier -1.70 -0.77 Omnivore Terrestrial Jones et al. 2009 Tatera_indica -2.76 -0.86 Omnivore Terrestrial Jones et al. 2009 Taxidea_taxus 0.58 0.94 Carnivore Terrestrial Lindzey 1978, Messick and Hornocker 1981, Minta 1990 Tayassu_pecari 1.16 1.31 Herbivore Terrestrial Fragoso 1998 Thomomys_bottae -4.15 -0.80 Herbivore Terrestrial Gettinger 1984, Reichman et al. 1982 Thylamys_elegans -3.15 -1.54 Carnivore Terrestrial Jones et al. 2009 Thylogale_stigmatica -1.45 0.67 Herbivore Terrestrial Vernes et al. 1995 Thylogale_thetis -0.86 0.73 Herbivore Terrestrial Johnson 1980 Tragelaphus_oryx 1.72 2.80 Herbivore Terrestrial Hillman 1988 Tragelaphus_scriptus -1.43 1.74 Herbivore Terrestrial Allsopp 1978 Tragelaphus_strepsiceros 3.03 2.30 Herbivore Terrestrial Allen Rowlandson 1980, duToit 1990 Trichosurus_vulpecula -1.30 0.46 Herbivore Terrestrial Statham and Statham 1997 Tupaia_glis -2.06 -0.88 Omnivore Terrestrial Jones et al. 2009 Tursiops_aduncus 2.00 2.33 Carnivore Marine Hung et al., 2004 Tursiops_truncates 1.71 2.56 Carnivore Marine Gubbins et al. 2002 Uncia_uncia 1.24 1.48 Carnivore Terrestrial Jackson and Ahlborn 1989, Oli 1997, Schaller et al. 1994 Urocyon_cinereoargenteus 0.44 0.66 Omnivore Terrestrial Fuller 1978, Hallberg 1973, Haroldson and Fritzell 1984 Urocyon_littoralis -0.71 0.29 Omnivore Terrestrial Crooks and Van Vuren 1995 Urotrichus_talpoides -2.66 -1.74 Omnivore Terrestrial Jones et al. 2009 Amstrup and Beecham 1976, Garshelis and Pelton 1981, Hellgren and Vaughan 1989, Hellgren and Vaughan 1990, Lindzey and Meslow 1977, Novick and Stewart 1982, Piekielek and Burton Ursus_americanus 1.59 2.18 Omnivore Terrestrial 1975, Warburton and Powell 1985, Young and Ruff 1982, Blanchard and Knight 1991, Huber and Roth 1993, Mace and Waller 1998, Servheen 1983, Wielgus et al. 1994 Ursus_arctos 2.91 2.34 Omnivore Terrestrial Blanchard and Knight 1991, Huber and Roth 1993, Mace and Waller 1998, Servheen 1983,

162

Wielgus et al. 1994 Ursus_maritimus 5.10 2.41 Carnivore Marine Ferguson et al., 1999 Viverra_zibetha 1.08 0.90 Carnivore Terrestrial Rabinowitz 1991 Viverricula_indica 0.49 0.53 Omnivore Terrestrial Rabinowitz 1991 Vombatus_ursinus -0.97 1.41 Herbivore Terrestrial Taylor 1993 Vulpes_lagopus 1.45 0.70 Carnivore Terrestrial Anthony 1997, Eberhardt et al. 1982, Landa et al. 1998, Prestrud 1992 Vulpes_macrotis 0.94 0.65 Carnivore Terrestrial O'Neal et al. 1987, Spiegel and Bradbury 1992, White and Ralls 1993, Zoellick and Smith 1992 Vulpes_rueppelli 1.48 0.51 Carnivore Terrestrial Lindsaey and MacDonald 1986 Vulpes_velox 0.74 0.32 Carnivore Terrestrial Jones et al. 2009 Ables 1969, Adkins and Stott 1998, Blanco 1986, Boitani et al. 1984, Cavallini 1992, Cavallini and Lovari 1994, Coman et al. 1991, Goszczynski 1989, Harrison et al. 1989, Jones and Theberge 1982, Kolb 1986, Lindsaey and MacDonald 1986, Lovari et al. 1994, Major and Vulpes_vulpes 0.69 0.81 Omnivore Terrestrial Sherburne 1987, Meia and Weber 1995, Pandolfi et al. 1997, Phillips and Catling 1991, Poulle et al. 1994, Sargeant et al. 1987, Servin et al. 1991, Travaini et al. 1993b, White et al. 1996, Woollard and Harris 1990 Wallabia_bicolor -0.82 1.18 Herbivore Terrestrial Troy and Coulson 1993 Xerus_erythropus -0.91 -0.30 Herbivore Terrestrial Linnandkey 1996 Xerus_rutilus -1.38 -0.50 Omnivore Terrestrial O'Shea 1976 Zalophus_californianus 3.72 1.93 Carnivore Marine Kuhn et al., 2006 Zapus_hudsonius -2.64 -1.73 Omnivore Terrestrial Jones et al. 2009 Zapus_princeps -2.61 -1.57 Omnivore Terrestrial Jones et al. 2009

Table S2.1 References

Abensperg-Traun, M. 1991. A study of home-range, movements and shelter use in adult and juvenile echidnas, Tachyglossus aculeatus (Monotremata: Tachyglossidea), in western Australian wheatbelt reserves. Australian Mammalogy 14:13-21. Ables, E. D. 1969. Home-range studies of red foxes (Vulpes vulpes). Journal of Mammalogy 50:108-120. Ables, E. D., and J. Ables. 1971. Radio-tracking studies of a Kenya hartebeest. E. Afr. Wildl. J. 9:145-146.

163

Ables, E. D., E. R. Fuchs, T. J. Galvin, L. P. Jones, R. M. Robinson, W. B. Russ, and J. C. Smith. 1977. The axis deer in Texas. The Caesar Kleberg Research Program in Wildlife Ecology, The Texas A&M University System, College Station, 86 pp. Addison, R. B., J. C. Williamson, B. P. Saunders, and D. Fraser. 1980. Radiotracking of moose in the boreal forest of northwestern Ontario. Can. Field-Nat. 94:269-276. Cited in Hundertmark 1997 Adkins, C. A., and P. Stott. 1998. Home ranges, movements and habitat associations of red fox Vulpes vulpes in suburban Toronto, Ontario, Canada. J. Zool. (Lond.) 244:335-346. Agrell, J., S. Erlinge, J. Nelson, and M. Sandell. 1996. Shifting spacing behaviour of male field voles (Microtus agrestis) over the reproductive season. Ann. Zool. Fennici 33:243-248. Allen-Rowlandson, T. S. 1980. The social and spatial organisation of the greater kudu (Tragelaphyus strepsiceros Pallas 1766) in the Andries Vosloo Kudu Reserve, eastern Cape. Unpubl. Ph.D. thesis, Rhodes Univ, Grahamstown, South Africa. Allen, S. L., R. A. Lancia, and C. W. Betsill. 1982. Habitat preferences of cottontail rabbits on an intensive farm and a traditional farm. Proc. Ann. Conf. S. E. Assoc. Fish and Wildlife Agencies 36:614-626. Allsopp, R. 1978. Social biology of bushbuck (Tragelaphus scriptus Pallas 1776) in the Nairobi National Park, Kenya. E. Afr. Wildl. J. 16:153-165. Alterio, N. 1998. Spring home range, spatial organisation and activity of stoats Mustela erminea in a South Island Nothofagus forest, New Zealand. Ecography 21:18-24. Althoff 1978 Social and spatial relationship of coyote families and neightboring coyotes. MS Thesis, Univ. Nebraska, Lincoln. 80 pp Althoff, D. P., and G. L. Storm. 1989. Daytime spatial characteristics of cottontail rabbits in central Pennsylvania. Journal of Mammalogy 70:820-824. Amstrup and Beecham 1976. Activity patterns of radio-collared black-bears in Idaho. Journal of Widlife Management 40:340-348. Andelt, W. F. 1985. Behavioral ecology of coyotes in south Texas. Wildlife Monographs 94:1-45. Andelt, W. F., and P. S. Gipson. 1979. Home range, activity, and daily movements of coyotes. Journal of Wildlife Management 43:944-951. Anderka, G., I. J. Linn, M. R. Perrin, and A. H. Maddock. 1999. Range use by the wild dog in the Hluhuwe-Umfolozi Park, South Africa. S. Afr. J. Wildl. Res. 29:1-9. Anderson, B. F., and M. R. Pelton. 1976. Movements, home range, and cover use: factors affecting the susceptibility of cottontails to hunting. Proc. Accl. Conf. S. E. Assoc. Fish and Wildlife Agencies 30:525-535. Andreassen, H. P., and S. Bondrup-Nielsen. 1991. Home range size and activity of the wood lemming, Myopus schisticolor. Holarctic Ecology 14:138-141. Andrews, R. D., R. L. Pitman, and L. T. Ballance. 2008. Satellite tracking reveals distinct movement patterns for Type B and Type C killer whales in the southern Ross Sea, Antarctica. Polar Biology 31:1461-1468. Anstee, S. D., J. D. Roberts, and J. E. O'Shea. 1997. Social structure and patterns of movement of the western pebble-mound mouse, Pseudomys chapmani, at Marandoo, Western Australia. Wildl. Res. 24:295-305. Anthony, R. M. 1997. Home ranges and movements of arctic fox (Alopex lagopus) in western Alaska. Arctic. 50:147-157. Apps, P. J. 1986. Home ranges of feral cats on Dassen Island. Journal of Mammalogy 67:199-200. Archibald, W. R., and R. H. Jessup. 1984. Population dynamics of the pine marten (Martes americana) in the Yukon Territory. Pp. 81-97 in Olson et al. (eds.) Northern ecology and resource management. Univ. Alberta Press, Edmonton. Arnold, G. W., D. E.Steven, A. Grassia, and J. Weeldenburg. 1992. Home-range size and fidelity of western grey kangaroos (Macropus fuliginosus) living in remnants of wandoo woodland and adjacent farmland. Wildl. Res. 19:137-143. Arthur, S. M., W. B. Krohn, and J. R. Gilbert. 1989. Home rane characteristics of adult fishers. Journal of Wildlife Management 53:674-679.

164

Attuquayefio, D. K., M. L. Gorman, and R. J. Wolton. 1986. Home range sizes in the wood mouse Apodemus sylvaticus: habitat, sex and seasonal differences. J. Zool. (Lond.) 210:45-53. Auge, A. A., B. L. Chilvers, A. B. Moore, and L. S. Davis. 2011. Foraging behaviour indicates marginal marine habitat for New Zealand sea lions: remnant versus recolonising populations. Marine Ecology Progress Series 432:247-256. Augee, M. L., L. A. Beard, G. C. Grigg, and J. K. Raison. 1992. Home range of echidnas in the Snowy Mountains. Pp. 225-231 in "Platypus and echidnas" (M. L. Augee, ed.). The Royal Zool. Soc. NSW, Sydney. Avenant, N. L., and J. A. J. Nel. 1998. Home-range use, activity, and density of caracal in relation to prey density. Afr. J. Ecol. 36:347-359. Babb, J. G., nad M. L. Kennedy. 1988. Home range of the coyote in western Tennessee. Proc. Ann. Conf. S. E. Assoc. Fish and Wildlife Agencies 42:443-447. Baber, D. W., and B. E. Coblentz. 1986. Density, home range, habitat use, and reproduction in feral pigs on Santa Catalina Island. Journal of Mammalogy 67:512-525. Bailey, T. N. 1974. Social organization in a bobcat population. Journal of Wildlife Management 38:435-446. Bailey, T. N. 1993. The African leopard: ecology and behavior of a solitary felid. Coumbia Univ. Press, New York. Bailey, T. N., E. E. Bangs, M. F. Portner, J. C. Malloy, and R. J. McAvinchey. 1986. An apparent overexploited lynx populatoin on the Kenai Peninsula, Alaska. Journal of Wildlife Management 50:279-290. Bajzak, C. E., C. Cotté, M. O. Hammill, and G. Stenson. 2009. Intersexual differences in the postbreeding foraging behaviour of the Northwest Atlantic hooded seal. Marine Ecology Progress Series 385:285-294. Ballard, W. B., J. S. Whitman, and C. L. Gardner. 1987. Ecology of an exploited wolf population in south-central Alaska. Wildlife Monographs 98:1-54. Ballard, W. B., J. S. Whitman, and D. J. Reed. 1991. Population dynamics of moose in south-central Alaska. Wildlife Monographs 114:1-49. Ballard, W. B., L. A. Ayres, P. R. Krausman, D. J. Reed, and S. G. Fancy. 1997. Ecology of wolves in relation to a migratory caribou herd in northwest Alaska. Wildlife Monographs 135:1-47. Banci, V., and A. S. Harestad. 1990. Home range and habitat use of wolverines Gulo gulo in Yukon, Canada. Holarctic Ecology 13:195-200. Bangs, E. E., and T. N. Bailey. 1980. Moose movements and distribution in response to winter seismological exploration on the Kenai National Wildlife Refuge, Alaska. Kenai Natl. Wildl. Refuge Rept. USFWS, Kenai, AK. 47 pp. Cited in Hundertmark 1997. Bangs, E. E., T. N. Bailey, and M. F. Portner. 1984. Bull moose behavior and movements in relation to harvest on the Kenai National Moose Range, Alaska. Alces 20:187- 208. Banks, E. M., R. J. Brooks, and J. Schnell. 1975. A radiotracking study of home range and activity of the brown lemming (Lemmus trimucronatus). Journal of Mammalogy 56:888-901. Bateman, M. C. 1986. Winter habitat use, food habits, and home range size of the marten, Martes americana, in western Newfoundland. Can. Field-Nat. 100:58-62. Bayless, S. R. 1969. Winter food habits, range use, and home range of antelope in Montana. J. Wildl. Mgmt. 33:538-551. Beier, P., and D. R. McCullough. 1990. Factors influencing white-tailed deer activity patterns and habitat use. Wildlife Monographs 109:1-51. Belden, R. C., W. B. Frankenberger, R. T. McBride, and S. T. Schwidert. 1988. Panther habitat use in southern Florida. Journal of Wildlife Management 52:660-663. Bellantoni, E. S., and P. R. Krausman. 1993. Habitat use by collared peccaries in an urban environment. Southwest. Nat. 38:345-351. Bendel, P. R., and J. E. Gates. 1987. Home range and microhabitat partitioning of the southern flying squirrel (Glaucomys volans). Journal of Mammalogy 68:243-255. Benhamou, S. 1996. Space use and foraging movements in the American red squirrel (Tamiasciurus hudsonicus) Behavioral Processes 37:89-102. Benson, B. N. 1980. Dominance relationships, mating behaviour and scent marking in fox squirrels (Sciurus niger). Mammalia 44:143-160

165

Beolchini, F., E. Dupre, and A. Loy. 1996. Territorial behaviour of Talpa romana in two different habitats: food resources and reproductive needs as potential causes of variation. Zeit. Fur Saugetierk. 61:193-201. Berg 1981. Ecology of bobcats in northern Minnesota. Natl. Wild. Fed. Sci. Tech Ser. 6:55-61. Berg, W. E., and R. A. Chesness. 1978. Ecology of coyotes in northern Minnesota. Pp. 229-247 in Bekoff, M. (ed.) Coyotes: biology, behavior, and management. Academic Press, New York, NY. Berger, J 1987. Reproductive fates of dispersers in a harem-dwelling ungulate: the wild horse. Pp. 41-54 in Mammalian dispersal patterns (Chepko-Sade, B. D., and Z. T. Halpin, eds.). University of Chicago Press, Chicago, IL Bergstrom, B. J. 1988. Home ranges of three species of chipmunks (Tamias) as assessed by radiotelemetry and grid trapping. Journal of Mammalogy 69:190-193. Berry, P. S. M. 1978. Range movements of giraffe in the Luangwa Valley, Zambia. E. Afr. Wildl. J. 16:77-83. Bias, M. A., and M. L. Morrison. 1999. Movements and home range of salt marsh harvest mice. Southwestern Naturalist 44:348-353. Bideau, E., J. F. Gerard, J. P. Vincent, and M. L. Maublanc. 1993. Effects of age and sex on space occupation by European roe deer. Journal of Mammalogy 74:745-751. Bissonette, J. A., and M. J. Steinkamp. 1996. Bighorn sheep response to ephemeral habitat fragmentation by cattle. Gt. Basin Nat. 56:319-325. Bjorge, R. R., and J. R. Gunson. 1989. Wolf, Canis lupus, population characteristics and prey relationships near Simonette River, Alberta. Can Field-Nat 103:327. Blanchard, B. M., and R. R. Knight. 1991. Movements of Yellostone grizzly bears. Biol. Conserv. 58:41-67. Blanco, J. C. 1986. On the diet, size and use of home range and activity patterns of a red fox in central Spain. Acta Theriologica 31:547-556. Blundell, G. M., R. T. Bowyer, M. Ben-David, T. A. Dean, and S. C. Jewett. 2000. Effects of food resources on spacing behaviour of river otters: does forage abundance control home range size? Pages 325-333 in Biotelemetry 15: Proceedings of 15th International Conference on Biotelemetry. International Society of Biotelemetry, Juneau, Alaska, USA. Boellstorff, D. E.,and D. H. Owings. 1995. Home range, population structure, and spatial organization of California ground squirrels. Journal of Mammalogy 76:551-561. Boitani, L., and G. Reggiani. 1984. Movements and activity patterns of hedgehogs (Erinaceus europaeus) in Mediterranean coastal habitats. Zeit. fur Saugetierk. 49:193- 206. Boitani, L., P. Barrasso, and I. Grimod. 1984. Ranging behaviour of the red fox in the Gran Paradiso National Park (Italy). Boll. Zool. 51:275-284. Borkowski, J., and K. Furubayashi. 1998. Home range size and habitat use in radio-collared female sika deer at high altitudes in the Tanzawa Mountains, Japan. Annales Zoologici Fennici 35:181-186. Bothma, J. du P., and E. A. N. Le Riche. 1994. Range use by an adult male caracal in the southern Kalahari. Koedoe 37:105-108. Bothma, J. du P., M. H. Knight, E. A. N. le Riche, and H. J. van Hensbergen. 1997. Range size of southern Kalahari leopards. S. Afr. J. Wildl. Res. 27:94-99. Boutin, S. 1979. Spacing behavior of snowshoe hares in relation to their population dynamics. M.Sc. Thesis, Univ. British Columbia, Vancouver. Cited from Boutin 1980. Boutin, S. and S. Schweiger. 1988. Manipulation of intruder pressure in red squirrel s (Tamiasciurus hudsonicus): effects on territory size and acquisition. Can. J. Zool. 66:2270-2274. Bowen, W. D. 1982. Home range and spatial organization of coyotes in Jasper National Park, Alberta. Journal of Wildlife Management 46:201-216. Bradley, L. C., and D. B. Fagre. 1988. Movements and habitat use by coyotes and bobcats on a ranch in southern Texas. Proc. Ann. Conf. S. E. Assoc. Fish and Wildlife Agencies 42:411-430. Bradshaw, C. J. A., D. M. Hebert, A. B. Rippin, and S. Boutin. 1995. Winter peatland habitat selection by woodland caribou in northeastern Alberta. Can. J. Zool. 73:1576- 1574. Branch, L. C. 1993. Intergroup and intragroup spacing in the Plains vizcacha, Lagostomus maximus. Journal of Mammalogy 74:890-900. 166

Braun, S. E. 1985. Home range and activity patterns of the giant kangaroo rat, Dipodomys ingens. Journal of Mammalogy 66:1-12. Bright, P. W., and P. A. Morris. 1991. Ranging and nesting behaviour of the dormouse, Muscardinus avellanarius, in diverse low-growing woodland. J. Zool. 224:177-190. Bristow, K. D., J. A. Wennerlund, R. E. Schweinsburg, R. J. Olding, and R. E. Lee. 1996. Habitat use and movements of desert bighorn sheep near the Silver Bell Mine, Arizona. Arizona Game and Fish Dept., Tech. Rept. 25:1-57. Broekhuizen, S., and F. Maaskamp. 1982. Movement, home range and clustering in the European hare (Lepus europaeus Pallas) in The Netherlands. Zeit. Fur Saugetierk. 22-32. Broseth, H., B. Knutsen, and K. Bevanger. 1997. Spatial organization and habitat utilization of badgers Meles meles: effects of food patch dispersion in the boreal forest of central Norway. Zeit. Fur Saugetierk. 62:12-22. Broughton, S. K., and C. R. Dickman. 1991. The effectof supplementary food on home range of the southern brown bandicoot, Isoodon obesulus (Marsupialia: Peramelidae). Aust. J. Ecol. 16:71-78. Bubela, T. M., D. C. D. Happold, and L. S. Broome. 1991. Home range and activity of the broad-toothed rat, Mastacomys fuscus, in subalpine heathland. Wildl. Res. 18:39- 48. Buie, D. E., T. T. Fendley, and H/. McNab. 1979. Fall and winter home ranges of adult bobcats on the Savannah River Plant, South Carolina. Nat. Wildl. Fed. Sci. Tech. Ser. 6:42-46. Burnett, G. W. 1981. Movements and habitat use of American marten in Glacier National Park, Montana. Unpubl. M.S. Thesis, Univ. Montana, Missoula. 130 pp. Buskirk, S. W. 1983. The ecology of marten in southcentral Alaska. Unpubl. Ph.D. thesis, Univ. Alaska, Fairbanks. 131 pp. Caley, P. 1997. Movement, activity patterns and habitat use of feral pigs (Sus scrofa) in a tropical habitat. Wildl. Res. 24:77-87. Campagna, C., R. Werner, W. Karesh, M. R. Marín, F. Koontz, R. Cook, and C. Koontz. 2001. Movements and location at sea of South American sea lions (Otaria flavescens). Journal of Zoology 255:205-220. Carbyn, L. N. 1983. Wolf predation on elk in Riding Mountain National Park, Manitoba. Journal of Wildlife Management 47:963-976. Caro, T. M. 1994. Cheetahs of the Serengeti Plains: group living in an asocial species. University of Chicago Press. Catt, D. C., and B. W. Staines. 1987. Home range use and habitat selection by red deer (Cervus elaphus) in a Sitka spruce plantation as determined by radio-tracking. J. Zool. (Lond.) 211:681-693, Cavallini, P. 1992. Ranging behavior of the red fox (Vulpes vulpes) in rural southern Japan. Joural of Mammalogy 73:321-325. Cavallini, P. 1993. Spatial organization of the yellow mongoose Cynictis penicillata in a coastal area. Ethology, Ecology, & Evolution 5:501-509. Cavallini, P., and J. A. J. Nel. 1990. Ranging behaviour of the Cape grey mongoose Galerella pulverulenta in a coastal area. J. Zool. (Lond.) 222:353-362. Cavallini, P., and S. Lovari. 1994. Home range, habitat selection and activity of the red fox in a Mediterranean coastal ecotone. Acta Theriologica 39:279-287. Cederlund, G. 1983. Home range dynamics and habitat selection by roe deer in a boreal area in central Sweden. Acta Theriologica 28:443-460. Cederlund, G. N., and H. Okarma. 1988. Home range and habitat use of adult female moose. Journal of Wildlife Management 52:336-343. Cederlund, G., and H. Sand. 1994. Home-range size in relation to age and sex in moose. Journal of Mammalogy 75:1005-1012. Chapman, N. G., et al. 1993. Sympatric populations of mutjac (Muntiacus reevesi) and roe deer (Capreolus capreolus): a comparative analysis of their ranging behaviour, social organization and activity. J. Zool. (Lond.) 229:623-640. Chiarello, A. G. 1998. Activity budgets and ranging patterns of the Atlantic forest maned sloth Bradypus torquatus (Xenarthra: Bradypodidae). J. Zool. (Lond.) 246:1-10. Choromanski-Norris, J., E. K. Fritzell., and A. B. Sargeant. 1989. Movements and habitat use of Franklin's ground squirrel in duck-nesting habitat. Journal of Wildlife Management 53:324-331. 167

Ciucci, P., L. Boitani, F. francisci, and G. Andreoli. 1997. Home range, activity and movements of a wolf pack in central Italy. J. Zool. (Lond.) 243:803-819. Clancy, T. F., and D. B. Croft. 1990. Home range of the common wallaroo, Macropus robustus erubescens, in far western New South Wales. Aust. Wildl. Res. 17:659-673. Clark, T. W., T. M. Campbell, III, and T. N. Hauptman. 1989. Demographic characteristics of American marten populations in Jackson Hole, Wyoming. Gt. Bas. Nat. 49:587- 596. Clarke, C. M. H., and R. J. Henderson. 1984. Home range size and utilization by femal chamois (Rupicapra rupicapra L.) in the Southern Alps, New Zealand. Acta Zool. Fennica 171:287-291. Clevenger, A. P. 1993. Pine marten (Martes martes L.) home ranges and activity patterns on the island of Minorca, Spain. Z. Saugetierk. 58:137-143. Coblentz, B. E., and D. W. Baber. 1987. Biology and control of feral pigs on Isla Santiago, Galapagos, Ecuador. J. Anim. Ecol. 24:403-418. Cole, E. K., M. D. Pope, and R. G. Anthony. 1997. Effects of road management on movement and survival of Roosevelt elk. Journal of Wildlife Management 61:1115-1126. Collins, R. J., and G. W. Barrett. 1997. Effects of habitat fragmentation on meadow vole (Microtus pennsylvanicus) populatoin dynamics in experiment landscape patches. Landscape Ecol. 12:63-76. Coman, B. J., J. Robinson, and C. Beaumont. 1991. Home range, dispersal and density of red foxes (Vulpes vulpes L.) in central Victoria. Wildl. Res. 18:215-223. Comport, S. S., S. J. Ward, and W. J. Foley. 1996. Home ranges, time budgets and food-tree use in a high-density tropical population of greater gliders, Petauroides volans minor (Pseudocheiridae: Marsupialia). Wildl. Res. 23:401-419. Condit, S. A., and D. O. Ribble. 1997. Social organization of Neotoma micropus, the southern plains woodrat. Amer. Midl. Nat. 137:290-297. Conner, L. M., B. D. Leopold, and K. J. Sullivan. 1992. Bobcat home range, density, and habitat use in east-central Mississippi. Proc. Annl. Conf. S. E. Assoc. Fish and Wildlife Agencies 46:147-158. Cook, J. M., R. Trevelyan, S. S. Walls, M. Hatcher, and F. Rakotondraparany. 1991. The ecology of Hypogeoemys antimena, an endemic Madagascan rodent. J. Zool. (Lond.) 224:191-200. Corbet, N. U., and R. J. Van Aarde. 1996. Social organization and space use in the Cape porcupine in a southern African savanna. Afr. J. Ecol. 34:1-14. Corp, N., M. L. Gorman, and J. R. Speakman. 1997. Ranging behaviour and time budgets of male wood mice Apodemus sylvaticus in different habitats and seasons. Oecologia 109:242-250. Coulson, G. 1993. Use of heterogeneous habitat by the western grey kangaroo, Macropus fuliginosus. Wildl. Res. 20:137-149. Craighead, J. J., F. C. Craighead, Jr., R. L. Ruff, and B. W. O'Gara. 1973. Home ranges and activity patterns of nonmigratory elk of the Madison Drainage herd as determined by biotelemetry. Wildlife Monographs 33:1-50. Cranford, J. A. 1977. Home range and habitat utilization by Neotoma fuscipes as determined by radiotelemetry. Journal of Mammalogy 58:165-172. Crawshaw, P. G., Jr., and H. B. Quigley. 1989. Notes on ocelot movement and activity in the Pantanal Region, Brazil. Biotropica 21:377-379. Crawshaw, P. G., Jr., and H. B. Quigley. 1991. Jaguar spacing, activity and habitat use in a seasonally flooded environment in Brazil. J. Zool. (Lond.) 223:357-370. Croft, D. B. 1987. Socio-ecology of the Antilopine wallaroo, Macropus antilopinus, in the Northern Territory, with observations on sympatric M. robustus woodwardii and M. agilis. Aust. Wildl. Res. 14:243-255. Crooks, K. R., and D. Van Vuren. 1995. Resource utilization by two insular endemic mammalian carnivores, the island fox and island spotted skunk. Oecologia 104:301- 307. Cumming, D. H. M. 1975. A field study of the ecology and behaviour of warthog. Museum Memoir (National Museums and Monuments of Rhodesia) 7:1-179. Curtice, C., R. S. Schick, D. C. Dunn, and P. N. Halpin. 2011. Home range analysis of Hawaiian monk seals (Monachus schauinslandi) based on colony, age and sex. Aquatic Mammals 37:360-371. 168

Dalla Rosa, L., E. R. Secchi, Y. G. Maia, A. N. Zerbini, and M. P. Heide-Jorgensen. 2008. Movements of satellite-monitored humpback whales on their feeding ground along the Antarctic Peninsula. Polar Biology 31:771-781. Daniels, T. J., and M. Bekoff. 1989. Spatial and temporal resource use by feral and abandoned dogs. Ethology 81:300-312. Danielson, B. J., and R. K. Swihart. 1987. Home range dynamics and activity patterns of Microtus ochrogaster and Synaptomys cooperi in syntopy. Journal of Mammalogy 68:160-165. Danner, D. A., and N. S. Smith. 1980. Coyote home range, movement, and relative abundance near a cattle feedyard. Journal of Wildlife Management 44:484-487. Davies, K. C., and J. U. M. Jarvis. 1986. The burrow systems and burrowing dynamics of the moe-rats Bathyergus suillus and Cryptomoys hottentotus in the fynbos of the south-western Cape, South Africa. J. Zool. (Lond). 209:125-147. Davis, J. R., and D. C. Guynn, Jr. 1993. Activity and habitat utilization of beaver colonies in South Carolina. Proc. Accl. Conf. S. E. Assoc. Fish and Wildlife Agencies 47:299-310. Davis, M. H. 1983 Post-release movements of introduced marten. Journal of Wildlife Management 47:59-66. de Villiers, P. A., and O. B. Kok. 1997. Home range, association and related aspects of elephants in the eastern Transvaal lowveld. Afr. J. Ecol. 35:224-236. Delibes, M., and J. F. Beltran. 1985. Activity, daily movements and home range of an Ichneumon or Egyptian mongoose (Herpestes ichneumon) in southern Spain. J. Zool. (Lond.) 207:610-613. Dell, D. A., R. H. Chabreck, and R. G. Linscombe. 1983. Spring and summer movements of muskrats in a Louisiana coastal marsh. Proc. Annl. Conf. S. E. Assoc. Fish and Wildlife Agencies 37:210-218. DeVan, R. 1982. The ecology and life history of the long-tailed weasel (Mustela frenata). Unpubl. Ph.D. dissert., Univ. Cincinnati. 300 pp. Dhungel, S. K., and W. D. Edge. 1985. Notes on the natural history of Paradoxurus hermaphroditus. Mammalia 49:302-303. Dickinson, T. G., and G. W. Garner. 1979. Home range use and movements of desert mule deer in southewestern Texas. Proc. Annl Conf. S. E. Assoc. Fish and Wildlife Agencies 33:267-278. Dietz, J. M. 1984. Ecology and social organization of the maned wold (Chrysocyon brachyurus). Smithsonian Contributions to Zoology 392:1-51. Dietz, R., M. P. Heide-Jorgensen, P. Richard, J. Orr, K. L. Laidre, and H. C. Schmidt. 2008. Movements if narwhals (Monodon monoceros) from Admiralty Inlet monitored by satellite telemetry. Polar Biology 31:1295-1306. Doebel, J. H., aB. S. McGinnis. 1974. Home range and activity of gray squirrel population. Journal of Wildlife Management 38:860-867. Doerr, J. G. 1983. Home range size, movements and habitat use in two moose population sin souteastern Alaska. Can. Field-Nat. 97:79-88. Cited in Hundertmark 1997 Douglas, R. J. 1976. Spatial interactions and microhabitat selections of two locally sympatric voles, Microtus montanus and Microtus pennsylvanicus. Ecology 57:346-352. du Toit, J. T. 1990. Home range - body mass relations: a field study on African browsing ruminants. Oecologia 85:301-303. DuBois, M., P-Y Quenette, E. Bideau, and M-P Magnac. 1993. Seasonal range use by European mouflon rams in medium altitude mountains. Acta Theriologica 38:185- 198. Dubost, G. 1978. Un apercu sur l'ecologie du chevrotain africain, Hyemoschus aquaticus Ogilby (Artiodactyle Tragulide). Mammalia 42:1-62. Cited in Emmons 1983 Dunham, K. M. 1986. Movements of elephant cows in the unflooded Middle Zambezi Valley, Zimbabwe. Afr. J. Ecol. 24:287-291. Dunham, K. M. 1998. Spatial organization of mountain gazelles Gazella gazella reintroduced to central Arabia. J. Zool. (Lond.) 245:371-384. Eberhardt, L. E., W. C. Hanson, and L. L. Cadwell. 1984. Movement and activity patterns of mule deer in the sagebrush-steppe region. Journal of Mammalogy 65:404-409. Eberhardt, L. E., W. C. Hanson, J. L. Bengtson, R. A. Garrott, and E. E. hanson. 1982. Arctic fox home range characteristics in an oil-development area. Journal of Wildlife Management 46:183-190. 169

Edge, W. D., C. L. Marcum, and S. l. Olson. 1985. Effects of logging activities on home-range fidelity of elk. Journal of Wildlife Management 49:741-744 Edmonds, E. J. 1988. Population status, distribution, and movements of woodland caribou in west central Alberta. Can. J. Zool. 66:817-826. Eldridge, W. D., M. M. MacNamara, and N. V. Pacheco. 1987. Activity patterns and habitat utilization of pudus (Pudu puda) in south-central Chile. Pp. 352-370 in Biology and management of the Cervidae (Wemmer, C. M., ed.). Smithsonian Institution Press Elwin, S., M. A. Meyer, P. B. Best, P. G. H. Kotze, M. Thronton, and S. Swanson. 2006. Range and movements of female Heaviside's dolphins (Cephalorhynchus heavisidii), as determined by satellite-linked telemetry. Journal of Mammalogy 87:866-877. Emmons, L. H. 1983. A field study of the African brush-tailed porcupine, Atherurus africanus, by radiotelemetry. Mammalia 47:183-194. Emmons, L. H. 1988. A field study of ocelots (Felis pardalis) in Peru. Revue d'Ecologie 43:133-157. Escos, J., and C. L. Alados. 1992. The home-range o f the Spanish ibex in spring and fall. Mammalia 56:57-63. Evans, M. 1996. Home ranges and movement schedules of sympatric bridled nailtail and black-striped wallabies. Wildl. Res. 23:547-556. Farentinos, R. C. 1979. Seasonal changes in home range size of tassel-eared squirrels (Sciurus aberti). Southwest. Nat. 24:49-62. Feer, F. 1989. Occupation de l'espace par deux bovides sympatriques de la foret dense Africaine (Cephalophus callipygus et C. dorsalis): influence du tythme d'activite. Rev. Ecol. (Terre Vie) 44:225-248. Feldhamer, G. A., K. R. Dixon, and J. A. Chapman. 1982. Home range and movement of sika deer (Cervus nippon) in Maryland. Zeit. Fur Saugetierk. 47:311-316. Ferguson, J. W. H., J. A. J. Nel, and M. J. de Wet. 1983. Social organization and movement patterns of black-backed jackals Canis mesomelas in South Africa. J. Zool. (Lond.) 199:487-502. Ferguson, S. H., M. K. Taylor, E. W. Born, A. Rosing-Asvid, and F. Messier. 1999. Determinants of home range size for polar bears (Ursus maritimus). Ecology Letters 2:311- 318. Ferreras, P., J. F. Beltran, J. J. Aldama, and M. Delibes. 1997. Spatial organization and land tenure system of the endangered Iberian lynx (Lunz pardinus). Journal of Zoology (London) 243:163-189. Ferron, J., and J. P. Ouellet. 1989. Temporal and intersexual variations in the use of space with regard to social organization in the woodchuck (Marmota movax). Can. J. Zool. 67:1642-1649. Ferron, J., and J. P. Ouellet. 1992. Daily partitioning of summer habitat and use of space by the snowshoe hare in southern boreal forest. Can. J. Zool. 70:2178-2183. Festa-Bianchet, M., and D. A. Boag. 1982. Territoriality in adult female Columbian ground squirrels. Can. J. Zool. 60:1060-1066. Fielden, L. J. 1991. Home range and movements of the Namib Desert golden mole, Eremitalpa granti namibensis (Chrysochloridae). J. Zool. (Lond.) 223:675-686. Fitzgerald, B. M., and B. J. Karl. 1986. Home range of feral house cats (Felis catus L.) in forest of the Orongorongo Valley, Wellington, New Zealand. New Zealand J. Ecol. 9:71-81. FitzGibbon, C. D. 1995. Comparative ecology of two elephant-shrew species in a Kenyan coastal forest. Mammal Rev. 25:19-30. Fitzwater, W. D., and I. Prakash. 1969. Observations on the burrows, behavior and home range of the Indian desert gerbil, Meriones hurrianae Jerdon. Mammalia 33:598- 606. Flores, P. A. and M. Bazzalo. 2004. Home ranges and movement patterns of the marine tucuxi dolphin, Sotalia fluviatilis, in Baia Norte, Southern Brazil. Latin American Journal of Aquatic Mammals 3:37-52. Flux, J. E. C. 1970. Life history of the mountain hare (Lepus timidus scoticus) in north-east Sctoland. J. Zool. (Lond.) 161:75-123. Forys, E. A., and S. R. Humphrey. 1996. Home range and movements of the lower keys marsh rabbit in a highly fragmented habitat. Journal of Mammalogy 77:1042-1048. Fowler, S. L., D. P. Costa, and J. P. Y. Arnould. 2007. Ontogeny of movements and foraging ranges in the Australian sea lion. Marine Mammal Science 23:598-614. 170

Fragoso, J. M. V. 1998. Home range and movement patterns of white-lipped peccary (Tayassu pecari) herds in the northern Brazilian Amazon. Biotropica 30:458-469. Frame, G. W. 1980. Black rhinoceros (Diceros bicornis L.) sub-population on the Serengeti Plains, Tanzania. Afr. J. Ecol. 18:155-166. Frank, D. H., and E. J. Heske. 1992. Seasonal chenges in space use patterns in the southern grasshopper mouse, Onychomys torridus torridus. Journal of Mammalogy 73:292-298. Franklin, W. L., and J. W. Lieb. 1979. The social organization of a sedentary population of North American elk: a model . . . Pp. 185-198 in Boyce, M. S. and L. D. Hayden- Wing (eds.) North American Elk: ecology, behavior, and management. Univ. Wyoming Fridell, R. A., and J. A. Litvaitis. 1991. Influence of resource distribution and abundance on home-range characteristics of southern flying squirrels. Can. J. Zool. 69:2589- 2593. Fritts, S. H., and L. D. Mech. 1981. Dynamics, movements, and feeding ecology of a newly protected wolf population in northwestern Minnesota. Wildlife Monogr. 80:1-79. Fritzell, E. K. 1978. Habitat use by prairie raccoons during the waterfowl breeding season. Journal of Wildlife Management 42:118-127. Fuller, T, K., and L. B. Keith. 1981. Non-overlapping ranges of coyotes and wolves in northeastern Alberta. J. Mamm. 62:403-405. Fuller, T. K. 1978. Variable home-range sizes of female gray foxes. J. Mamm. 59:446-449. Fuller, T. K. 1989. Population dynamics of wolves in north-central Minnesota. Wildlife Monographs 105:1-41. Fuller, T. K., A. R. Biknevicius, P. W. Kat, B. van valkenburgh, and R. K. Wayne. 1989. The ecology of three sympatric jackal species in the Rift Valley of Kenya. Afr. J. Ecol. 27:313-323. Fuller, T. K., and P. W. Kat. 1990. Movements, activity, and prey relationswhips of African wild dogs (Lycaon pictus) near Aitong, southwestern Kenya. Afr. J. Ecol. 28:330- 350. Fuller, T. K., W. E. Berg, and D. W. Kuehn. 1985. Bobcat home range size and daytime cover-type use in northcentral Minesota. Journal of Mammalogy 66:568-571. Fuller, T. K., W. E. Johnson, W. L. Franklin, and K. A. Johnson. 1987. Notes on the Patagonian hog-nosed skunk (Conepatus humboldti) in southern Chile. J. Mamm. 68:864-867. Funston, P. J., J. D. Skinner, and H. M. Dott. 1994. Seasonal variation in movement patterns, home range and habitat selection of buffaloes in a semi-arid habitat. Afr. J. Ecol. 32:100-114. Garant, Y., and M. Crete. 1997. Fisher, Martes pennanti, home range characteristics in a high density untrapped population in southern Quebec. Can. Field-Nat. 111:359- 364. Gardner, C. L. 1985. The ecology of wolverines in southcentral Alaska. Unpubl. M.S. thesis, Univ. of Alaska, Fairbanks, 82 pp. Garshelis, D. L., and J. A. Garshelis. 1984. Movements and management of sea otters in Alaska. Journal of Wildlife Management 48:665-678. Garshelis, D. L., and M. R. Pelton. 1981. Movements of black bears in the Great Smoky Mountains National Park. Journal of Wildlife Management 45:912-925. Gasaway, W. C., K. T. Mossestad, and P. E. Stander. 1989. Demography of spotted hyaenas in an arid savanna, Etosha National Park, South West Africa/Namibia. Madoqua 16:121-127. Gaulin, S. J. C., and R. W. FitzGerald. 1988. Home-range size as a predictor of mating systems in Microtus. Journal of Mammalogy 69:311-319. Gehrt, S. D., and E. K. Fritzell. 1997. Sexual differences in home ranges of raccoons. Journal of Mammalogy 78:921-931. Geinitz, C. Ch. 1980. Contribution to the biology of Sibirian chipmunk (Eutamias sibiricus Laxmann, 1769) in a cemetary in Freiburg (Southern Germany). Zeit. Fur Saugetierk. 1980:279-287. Genovesi, P., I. Sinibaldi, and L. Boitani. 1997. Spacing patterns and territoriality of the stone marten. Can. J. Zool. 75:1966-1971. Genovesi, P., M. Besa, and S. Toso. 1995. Ecology of a feral cat Felis catus population in an agricultural area of northern Italy. Wildlife Biology 1:233-237. 171

Georgii, B. 1980. Home range patterns of female red deer (Cervus elaphys L.) in the Alps. Oecologia 47:278-285. Gese, E. M., O. J. Rongstad, and W. R. Mytton. 1988. Home range and habitat use of coyotes in southeastern Colorado. Journal of Wildlife Management 52:640-646. Gettinger, R. D. 1984. A field study of activity patterns of Thomomys bottae. Journal of Mammalogy 65:76-84 Gettle, A. S. 1975. Densities, movements, and activities of pine voles (Microtus pinetorum) in Pennsylvania. Unpubl. MS Thesis, Pennsylvania State University, 66 pp. Gillette, L. N. 1980. Movement patterns of radio-tagged opossums in Wisconsin. American Midland Naturalist 104:1-12. Gipson, P. S. 1983. Evaluation and control implication of behavior of feral dogs in interior Alaska. Pp. 285-294 in Kaukeinen, D. E. *(ed.) Vertebrate pest control and management materials: fourth symposium. ASTM Spec. Tech. Publ. Philadelphia. Goddard, J. 1967. Home range, behaviour, and recruitment rates of two black rhinoceros populations. E. Afr. Wildl. J. 5:133-150. Goldingay, R. L., and R. P. Kavanagh. 1993. Home-range estimates and habitat of the yellow-bellied glider (Petaurus australis) at Waratah Creek, New South Wales. Wildl. Res. 20:387-404. Gompper, M. E. 1997. Population ecology of the white-nosed coati (Nasua narica) on Barro Colorado Island, Panama. J. Zool. (London) 241:441-455. Goszczynski, J. 1989. Spatial distribution of red foxes Vulpes vulpes in winter. Acta Theriologica 34:361-372. Grauvogel, C. A. 1984. Seward Peninsula moose population identity study. Fed. Aid Wildl. Restor. Final Repot. Alaska Dept. Fish and Game, Juneau. 93 pp. Cited in Hundertmark 1997 Green, K., A. T. Mitchell, and P. Tennant. 1998. Home range and microhabitat use by the long-footed potoroo, Potorous longipes. Wildlife Research 25:357-372. Gubbins, C. 2002. Use of home ranges by resident Bottlenose dolphins (Tursiops truncatus) in a South Carolina Estuary. Journal of Mammalogy 83:178-187. Guillet, C., R. Bergstrom, and G. Cederlund. 1996. Size of winter home range of roe deer Capreolus capreolus in two forest areas with artificial feeding in Sweden. Wildlife Biology 2:107-111. Guillotin, M. 1982. Rythmes d'activite et regimes alimentaires de Proechimys cuvieri et d'Oryzomys capito velutinus (Rodentia) en foret Guyenaise. Rev. Ecol. (Terre Vie) 36:337-371. Gust, N., and K. Handasyde. 1995. Seasonal variation in the ranging behaviour of the platypus (Ornithorhynchus anatinus) on the Goulbrun River, Victoria. Aust. J. Zool. 43:193-208. Hall, J. G. 1981. A field study of the Kaibab squirrel in Grand Canyon National Park. Wildlife Monographs 75:1-54. Hall, L. S., and M. L. Morrison. 1997. Den and relocation site characteristics and home ranges of Peromyscus truei in the White Mountains of California. Gt. Basin Nat. 57:124-130. Hall, L. S., M. A. Kasparian, D. Van Vuren, and D. A. Kelt. 2000. Spatial organization and habitat use of feral cats (Felis catus L.) in Mediterranean California. Mammalia 64:19-28. Hallberg, D. L. 1973. A contribution to the better understanding of the gray fox (Urocyon cinereoargenteus): spatial and temporal natural history. Unpubl. MS Thesis, CSU Sacramento. 280 pp. Haller, V. H., and U. Breitenmoser. 1986. Spatial organization of the reintroduced population of the lynx (Lynx lynx) in the Swiss Alps. Zeit. Fur Sauget. 51:289-311 (in German). Hampy, D. B. 1978. Home range and seasonal movement of Barbary sheep in the Palo Duro Canyon. Unpubl. M.S. Thesis, Texas Tech Univ., Lubbock. 83 pp. Harden, R. H. 1985. The ecology of the dingo in north-eastern New South Wales I. Movements and home range. Aust. Wildl. Res. 12:25-37. Haroldson, K. J., and E. K. Fritzell. 1984. Home ranges, activity, and habitat use by gray foxes in an oak-hickory forest. Journal of Wildlife Management 48:222-227.

172

Harrison, D. J., J. A. Bissonette, and J. A. Sherburne. 1989. Spatial relationships between coyotes and red foxes in eastern Maine. Journal of Wildlife Management 53:181- 185. Harrison, R. L. 1997. A comparison of gray fox ecology between residential and undeveloped rural landscapes. Journal of Wildlife Management 61:112-122. Hart, J. A., and T. B. Hart. 1989. Ranging and feeding bahaviour of okapi (Okapia johnstoni) in the Ituri Forest of Zaire: food limitation in a rain-forest herbivore? Symp. Zool. Soc. London 61:31-50. Harvey, M. J. 1976. Home range, movements, and diel activity of the eastern mole, Scalopus aquaticus. Amer. Midl. Nat. 95:436-445. Harvey, M. J., and R. W. Barbour. 1965. Home range of Microtus ochrogaster as determined by a modified minimum are method. J. Mamm. 46:398-402. Hauge, T. M., and L. B. Keith. 1981. Dynamics of moose populations in northeastern Alberta. Journal of Wildlife Management 45:573-597. Hayes, C. L., and P. R. Krausman. 1993. Nocturnal activity of female desert mule deer. Journal of Wildlife Management 57:897-904. Hearn, B. J., L. B. Keith, and O. J. Rongstad. 1987. Demography and ecology of th earctic hare (Lepus arcticus) in southwestern Nerfoundland. Can. J. Zool. 65:852-861. Heath, M. E., and I. M. Coulson. 1997. Home range size and distribution in a wild population of Cape pangolins, Manis temminckii, in north-west Zimbabwe. African Journal of Ecology 35:94-109. Heide-Jørgensen, M. P., K. Laidre, D. Borchers, F. Samarra, and H. Stern. 2007. Increasing abundance of bowhead whales in West Greenland. Biology Letters 3:577-580. Hellgren, E. C., and M. R. Vaughan. 1989. Demographic analysis of a black bear population in the Great Dismal Swamp. J. Wildlife Mgmt. 53:969-977 Hellgren, E. C., and M. R. Vaughan. 1990. Range characteristics of black bears in Great Dismal Swamp, Virginia - North Carolina. Proc. Annu./ Copnf. SE Assoc. F&W Agencies 44:268-278. Hemker, T. P., F. G. Lingzey, and B. A. Ackerman. 1984. Population characteristics and movement patterns of cougars in soutehrn Utah. Journal of Wildlife Management 48:1275-1284. Heske, E. J. 1987. Spatial structuring and dispersal in a high density population of the California vole Microtus californicus. Holarct. Ecol. 10:137-148. Heske, E. J., G. I. Shenbrot, and K. A. Rogovin. 1995. Spatial organization of Stylodipus telum (Dipodidae, Rodentia) in Dagestan, Russia. Journal of Mammalogy 76:800- 808. Hewson, R., and M. D. C. Hinge. 1990. Characteristics of the home range of mountain hares Lepus timidus. J. Appl. Ecol. 27:651-666. Hibler 1977. Coyote movement patterns with emphasis on home range characteristics. MS Thesis, Utah State Univ. Logan, 125 p. Hillman, J. C. 1988. Home range and movement of the common eland (Taurotragus oryx Pallas 1766) in Kenya. Afr. J. Ecol. 26:135-148. Hobbs, R. C., K. L. Laidre, D. J. Vos, B. A. Mahoney, and M. Eagleton. 2005. Movements and Area Use of Belugas, Delphinapterus lencas, in a Subarctic Alaskan Estuary. Arctic 58:331-340. Hoffman, C. O., and J. L. Gottschang. 1977. Numbers, distribution, and movements of a raccoon population in a suburban residential community. Journal of Mammalogy 58:623-636. Holzenbein, S., and R. L. Marchinton. 1992. Spatial integration of maturing-male white-tailed deer into the adult population. Journal of Mammalogy 73:326-334. Holzman, S., M. J. Conroy, and J. Pickering. 1992. Home range, movemenets, and habitat use of coyotes in southcentral Georgia. Journal of Wildlife Management 56:139- 146. Hornocker, M. G., and H. S. hash. 1981. Ecology of the wolverine in northwestern Montana. Can. J. Zool. 59:1286-1301. Horsup, A. 1994. Home range of the Allied rock-wallaby, Petrogale assimilis. Wildl. Res. 21:65-84. Hoskinson, R. L., and L. D. Mech. 1976. White-tailed deer migration and its role in wolf predation. Journal of Wildlife Management 40:429-441.

173

Hubbs, A. H., and R. Boonstra. 1998. Effects of food and predators on the home-range sizes of Arctic ground squirrels (Spermophilus parryii). Canadian J. Zool. 76:592- 596. Huber, D., and H. U. Roth. 1993. Movements of European brown bears in Croatia. Acta Theriologica 38:151-159. Hulbert, I. A. R., G. R. Iason, D. A. Elston, and P. A. Racey. 1996. Home-range sizes in a stratified upland landscape of two lagomorphs with different feeding strategies. J. Animal Ecol. 33:1479-1488. Hung, S. K. and T. A. Jefferson. 2004. Raning patterns of Indo-Pacific hupback dolphins (Sousa chinensis) in the Pearl River Estuary, People's Republic of China. Aquatic Mammals 30:159-174. Ikeda, H., K. Eguchi, and Y. Ono. 1979. Home range utilization of a raccoon dog, Nyctereutes procyonoides viverrinus, Temminck, in a small islet in western Kyushu. Jap. J. Ecol. 29:35-48. Ikeda, H., Y. Ono, M. Baba, T. Doi, and T. Iwamoto. 1982. Ranging and activity patterns of three nocturnal viverrids in Omo National Park, Ethiopia. Afr. J. Ecol. 20:179-186. Ilse, L. M., and E. C. Hellgren. 1995. Spatial use and group dynamics of sympatric collared peccaries and feral hogs in southern Texas. Journal of Mammalogy 76:993- 1002. Irwin, L. J., and J. M. Peek. 1983. Elk habitat use relative to forest succession in Idaho. Journal of Wildlife Management 47:664-672. Ivey, T. L., and M. K. Causey. 1981. Movements and activity patterns of female white-tailed deer during rut. Proc. Accl. Conf. S. E. Assoc. Fish and Wildlife Agencies 35:149-166. Jackson, R., and G. Ahlborn. 1989. Snow leopards (Panthera uncia) in Nepal -- home range and movements. Natl. Geogr. Res. 5:161-175. Jarman, P. J., and R. J. Taylor. 1983. Ranging of eastern grey kangaroos and wallaroos on a New England pastoral property. Aust. Wildl. Res. 10:33-38. Jarvis, J. U. M. 1973. Activity patterns in the mole-rats Tachyoryctes splendens and Heliophobius argenteocinereus. Zool. Africana 8:101-119. Jarvis, J. U. M. 1985. Ecological studies on Heterocephalus glaber, the naked mole-rat, in Kenya. National Geographic Research 20:429-437. Jarvis, J. U. M., and J. B. Sale. 1971. Burrowing and burrow patterns of east African mole rats Tachyoryctes, Heliophobius, and Heterocephalus. J. Zool. Lond. 163:451- 479. Jedrzejewski, W., B. Jedrzejewska, and L. Szymura. 1995. Weasel population response, home range, and predation on rodents in a deciduous forest in Poland. Ecology 76:179-195. Jenkins, K. J., and E. E. Starkey. 1982. Social organization of Roosevelt eld in an old-growth forest. Journal of Mammalogy 63:331-334. Jenny, D. 1996. Spatial organization of leopards Panthera pardus in Tai National Park, Ivory Coast: is rainforest a 'tropical haven'? J. Zool. (Lond.) 240:427-440. Jike, L., G. O. Batzli, and L. L. Getz. 1988. Home ranges of prairie voles as determined by radiotracking and by powdertracking. Journal of Mammalogy 69:183-186 Johnson, C. N. 1987. Macropod studies at Wallaby Creek. IV. Home range and movements of the red-necked wallaby. Aust. Wildl. Res. 14:125-132. Johnson, C. N. 1991. Utilization of habitat by the northern hairy-nosed wombat Lasiorhinus krefftii. Journal of Zoology 225:495-507. Johnson, K. A. 1980. Spatial and temporal use of habitat by the red-necked pademelon, Thylogale thetis (Marsupialia: Macropodidae). Aust. Wildl. Res. 7:157-166. Johnson, W. E., and W. L. Franklin. 1991. Feeding and spatial ecology of Felis geoffroyi in southern Patagonia. Journal of Mammalogy 72:815-820. Johnson, W. E., and W. L. Franklin. 1994. Spatial resource partitioning by sympatric grey fox (Dusicyon griseus) and culpeo fox (Dusicyon culpaeus) in southern Chile. Can. J. Zool. 72:1788-1793. Johnston, D. W., A. J. Westgate, and A. J. Read. 2005. Effects of fine-scale oceanographic features on the distribution and movements of harbour porpoises Phocoena phocoena in the Bay of Fundy. Marine Ecology Progress Series 295:279-293. Jones, C. A. 1990. Microhabitat use by Podomys floridanus in the high pine lands of Putnam County, Fdlorida. Unpubl. Ph.D. dissert. Univ. Florida, Gainesville. 158 pp. 174

Jones, D. M., and J. B. Theberge. 1982. Summer home range and habitat utilisation of the red forx (Vulpes vulpes) in a tundra habitat, northwest British Columbia. Can. J. Zool. 60:807-812. Jones, E. N., and L. J. Sherman. 1983. A comparison of meadow vole home ranges derived from grid trapping and radiotelemetry. Journal of Wildlife Management 47:558- 561. Jones, E., and B. J. Coman. 1982. Ecology of the feral cat, Felis catus (L.), in south-eastern Australia III. Home ranges and population ecology in semiarid north-west Victoria. Aust. Wildl. Res. 9:409-420. Jones, W. T. 1989. Dispersal distance and the range of nightly movements in Merriam's kangaroo rats. Journal of Mammalogy 70:27-34. Jones, K. E., Bielby, J., Cardillo, M., Fritz, S. A., O'Dell, J., Orme, C. D. L., . . . Michener, W. K. (2009). PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology, 90(9), 2648-2648. doi: 10.1890/08-1494.1 Julien-Laferriere, D. 1993. Radio-tracking observations on ranging and foraging patterns by kinkajous (Potos flavus) in French Guiana. J. Trop. Ecol. 9:19-32. Julien-Laferriere, D. 1995. Use of space by the wooly opossum Caluromys philander (Marsupialia, Didelphidae) in French Guiana. Can. J. Zool. 1280-1289. Kantala, A. T., and S. R. Humphrey. 1990. Habitat use by Sherman's fox squirrel (Sciurus niger shermani) in Florida. Journal of Mammalogy 71:411-419. Katnik, D. D., D. J. Harroson, and T. P. Hodgman. 1994. Spatial relations in a harvested population of marten in Maine. Journal of Wildlife Management 58:600-607. Katzner, T. E., and K. L. Parker. 1997. Vegetative characteristics and size of home ranges used by pygmy rabbits (Brachylagus idahoensis) during winter. Journal of Mammalogy 78:1063-1072. Kauhala, K., E. Helle, and K. Taskinen. 1993. Home range of the raccoon dog (Nyctereutes procyonoides) in southern Finland. J. Zool. (Lond.) 231:95-106. Kawamichi, T. 1976. Hay territory and dominance rank of pikas (Ochotona princeps). Journal of Mammalogy 57:133-148. Kays, R. W., and J. L. Gittleman. 1995. Home range size and social behavior of kinkajous (Potos flavus) in the republic of Panama. Biotropica 27:530-534. Kelly, P. A. 1990. Population ecology and social organization of dusky-footed woodrats, Neotoma fuscipes. Unpub. Ph.D. dissert, Univ. California Berkeley. 191 pp. Kelly, P. A., and M. V. Price. 1992. Home range use of Stephen's kangaroo rats: implications for density estimation. Final Report submitted to Riverside County Habitat Conservation Agency, Riverside, CA. 26 pp. King, D. 1992. Home ranges of feral goats in a pastoral area in Western Australia. Wildl. Res. 19:643-649. Kirk, D. A., and G. M. Bathe. 1994. Population size and home range of black-naped hares Lepus nigricollis nigricollis on Cousin Island (Seychelles, Indian Ocean). Mammalia 58:557-562. Kiwia, H. Y. D. 1989. Ranging patterns of the black rhinoceros (Diceron bicornis (L.)) in Ngorogoro Crater, Tanzania. Afr. J. Ecol. 27:305-312. Kjolhaug, M. S., and A. Woolf. 1988. Home range of the swamp rabbit in southern Illinois. Journal of Mammalogy 69:194-197. Knick, S. T. 1990. Ecology of bobcats relative to exploitation and a prey decline in southeastern Idaho. Wildlife Monographs 108:1-42. Koehler, G. M. 1990. Population and habitat characteristics of lynx and snowshoe hare in north central Washington. Canadian Journal of Zoology 68:845-851. Koehler, G. M., and M. G. Hornocker. 1989. Influences of seasons on bobcats in Idaho. Journal of Wildlife Management 53:197-202. Kohl, T. F., C. A. DeYoung, and A. Garza, Jr. 1987. Effects of short duration grazingon deer home ranges. Proc. Ann. Conf. S. E. Assoc. Fish and Wildlife Agencies 41:299- 302. Kolb, H. H. 1986. Some observations on the home ranges of vixens (Vulpes vulpes) in the suburbs of Edinburgh. J. Zool. (Lond.) 210:636-639 Konecny, M. J. 1987. Home range and activity patterns of feral house cats in the Galapagos Islands. Oikos 50:17-23. Konecny, M. J. 1989. Movement patterns and food habits of four sympatric carnivore species in Belize, Central America. Advances in Neotropical Mammalogy 1989:243- 264. 175

Krasinska, M., and Z. A. Krasinski. 1995. Composition, group size, and spatial distribution of European bison bulls in Bialowieza Forest. Acta Theriologica 40:1-21. Krausman, P. R., B. D. Leopold, R. F. Seegmiller, and S. G. Torres. 1989. Relationships between desert bighorn sheep and habitat in western Arizona. Wildlife Monographs 102:1-66. Kruuk, H. 1976. E. Afr. Wildl. J. 14:91-111, Cited in van Aarde et al. 1988 Kruuk, H. 1987. Spatial organization and territorial behaviour of the Eurpoean badger Meles meles. J. Zool. (Lond.) 184:1-19. Kufeld, R. C., D. C. Bowden, and D. L. Schrupp. 1989. Distribution and movements of female mule deer in the Rocky Mountain foothills. Journal of Wildlife Management 53:871-877. Kuhn, C. E. 2006. Measuring At Sea Feeding to Understand the Foraging Behavior of Pinnipeds. PhD Thesis, University of California, Santa Cruz. Laidlaw, W. S., and B. A. Wilson. 1996. The home range and habitat utilisation of Cercartetus nanus (Marsupialia: Burramyidae) in coastal heathland, Anglesea, Victoria. Australian Mammalogy 19:63-68. Laidlaw, W. S., S. Hutchings, and G. R. Newell. 1996. Home range and movement patterns of Sminthopsis leucopus (Marsupialia: Dasyuridae) in coastal dry heathland, Anglesea, Victoria. Australian Mammalogy 19:1-9. Landa, A., O. Strand, J. D. C. Linnell, and T. Skogland. 1998. Home-range sizes and altitude selection for arctic foxes and wolverine in an alpine landscape. Can. J. Zool. 76:448-457. Langman, V. A. 1973. Radio-tracking giraffe for ecological studies. J. S. Afr. Wildl. Mgmt. Ass. 3:75-78. Lanning, D. V.. 1976. Density and movements of the coati in Arizona. Journal of Mammalogy 57:609-611. Lardet, J-P. 1988. Spatial behaviour and activity patterns of the water shrew Neomys fodiens in the field. Acta Theriologica 33:293-303. Lariviere, S. and F. Messier. 1998. Spatial organization of a prairie striped skunk population during the waterfowl nesting season. Journal of Wildlife Management 62:199- 204. Larter, N. C., and C. C. Gates. 1994. Home range size of wood bison: effects of age, sex, and forage availability. Journal of Mammalogy 75:142-149. Laundre, J. W., and B. L. Keller. 1983. Trappability of coyotes relative to home range boundaries. Can. J. Zool. 61:1932-1934. Lazenby-Cohen, K. A., and A. Cockburn. 1991. Social and foraging components of the home range in Antechinus stuartii (Dasyuridae: Marsupialia). Aust. J. Ecol. 16:301- 307. Leach, R. H., and W. D. Edge. 1994. Summer home range and habitat selection by white-tailed deer in the Swan Velley, Montana. Northwest Sci. 68:31-34. LeBoeuf, B. J., D. E. Crocker, D. P. Costa, S. B. Blackwell, P. M. Webb, and D. S. Houser. 2000. Foraging ecolog of Northern Elephant Seals. . Ecological Monographs 70:353-382. Leeuwenberg, F. J., S. L. Resende, F. H. G. Rodrigues, and M. X. A. Bizerril. 1997. Home range, activity and habitat use of the pampas deer Ozotoceros bezoarticus L., 1758 (Artiodactyla, Cervidae) in the Brazilian Cerrado. Mammalia 61:487-495. Leirs, H., W. Verheyen, and R. Verhagen. 1996. Spatial patterns in Mastomys natalensis in Tanzania (Rodentia, Muridae). Mammalia 60:545-555. Leptich, D. J., and J. R. Gilbert. 1989. Summer home range and habitat use by moose in northern Maine. Journal of Wildlife Management 53:880-885. Leslie, D. M., Jr., and C. L. Douglas. 1979. Desert bighorn sheep of the River Mountains, Nevada. Wildlife Monographs 66:1-56. Leuthold, B. M., and W. Leuthold. 1978. Ecology of the giraffe in Tsavo East National Park, Kenya. E. Afr. Wildl. J. 16:1-20. Leuthold, W. 1972. Home range, movements and food of a buffalo herd in Tsavo National Park. E. Afr. Wild. J. 10:237-243. Leuthold, W. 1977. Spatial organization and strategy of habitat utilization of elephants in Tsavo National Park, Kenya. Zeit. Fur Suagetierk. 42:358-379. Lindeque, M., and P. M. Lindeque. 1991. Satellite tracking of elephants in northwestern Namibia. Afr. J. Ecol. 29:196-206. 176

Lindsay, I. M., and D. W. MacDonald. 1986. Behaviour and ecology of the Ruppell's fox, Vulpes ruppelli, in Oman. Mammalia 50:461-474. Lindzey, F. G. 1978. Movement patterns of badgers in northwestern Utah. Journal of Wildlife Management 42:418-422. Lindzey, F. G., and E. C. Meslow. 1977. Home range and habitat use by black bears in southwestern Washington. Journal of Wildlife Management 41:413-425. Linn, I., and G. Key. 1996. Use of space by the African striped ground squirrel Xerus erythropus. Mammal Rev. 26:9-26. Litvaitis, J. A., and J. A. Shaw. 1980. Coyote movements, habitat use, and food habits in southwestern Oklahoma. Journal of Wildlife Management 44:62-68. Litvaitis, J. A., J. T. Major, and J. A. Sherburne. 1987. Influence of season and human-induced mortality on spatial organization of bobcats (Felis rufus) in Maine. Journal of Mammalogy 68:100-106. Livesey, K. B. 1991. Home range, habitat use, disturbance, and mortality of Columbian black-tailed deer in Mendocino National Forest. Calif. Fish and Game 77:201-209. Loft, E. R., R. C. Bertram, and B. L. Bowman. 1989. Migration patterns of mule deer in the central Sierra Nevada. Calif. Fish and Game 75:11-19. Logan, K. A., L. L. Irwin, and R. Skinner. 1986. Characteristics of a hunted mountain lion population in Wyoming. Journal of Wildlife Management 50:648-654. Lopez, D. N. 1985. Status and distributin of the ocelot (Felis pardalis) in south Texas. Unpubl. MS Thesis, Texas A&I University, Lott, D. F., and S. Minta. 1983. Home ranges of American bison cows on Santa Catalina Island, California. Journal of Mammalogy 64:161-162. Lovallo, M. J., and E. M. Anderson. 1996. Bobcat (Lynx rufus) home range size and habitat use in northwest Wisconsin. Amer. Midl. Nat. 135:241-252. Lovari, S., P. Valier, and M. R. Lucchi. 1994. Ranging behaviour and activity of red fozes (Vulpes vulpes: Mammalia) in relation to environmental variables, in a Mediterranean mixes pinewood. J. Zool. (Lond.) 232:323-339. Lovegrove, B. G. 1988. Colony size and structure, activity patterns and foraging behaviour of a colony of the social mole-rat Cryptomys damarensis (Bathyergidae). J. Zool. (Lond.) 216:391-402. Loy, A., E. Dupre, and E. Capanna. 1994. Territorial behavior in Talpa romana, a fossorial insectivore from southcentral Italy. Journal of Mammalogy 75:529-535. Ludlow, M., and M. Sunquist. 1987. Ecology and behavior of ocelots in Venezuela. Natl. Geogr. Res. 3:447-461. Ludwig, D. R. 1981. The population biology and life history of the water vole, Microtus richardsoni. Unpubl. Ph.D. diss, Univ. Calgary, Alberta. 274 pp. Lynch, M. F., A. L. Fesnock, and D. Van Vuren. 1994. Home range and social structure of the dusky-footed woodrat (Neotoma fuscipes). Northwestern Naturalist 75:73-75. MacCracken, J. G., V. Van Ballenberghe, and J. M. Peek. 1997. Habitat relationships of moose on the Copper River Delta in coastal south-central Alaska. Wildlife Monographs 136:1-52. MacDonald, D. W. and O. Courtenay. 1996. Enduring social relationships ina population of crab-eating zorros, Cerdocyon thous, in Amazonian Brazil (Carnivora, Canidae). J. Zool. (Lond.) 239:329-355. Macdonald, D. W., R. P. D. Atkinson, and G. Blanchard. 1997. Spatial and temporal patterns in the activity of European moles. Oecologia 109:88-97. Mace, R. D., and J. S. Waller. 1998. Spatial and temporal interaction of male and female grizzly bears in northwestern Montana. Journal of Wildlife Management 61:39-52. Madden, J. R. 1974. Female territoriality in a Suffolk County, Long Island, population of Glaucomys volans. Journal of Mammalogy 55:647-652 Maehr, D. S., E. D. Land, and J. C. Roof. 1991. Florida panthers. Natl. Geog. Research and Exploration 7:414-431. Magoun, A. J. 1985. Population characteristics, ecology, and management of wolverines in northwestern Alaska. Unpubl. Ph.D. thesis, Univ. of Alaska, Fairbanks. Major J. T. 1979. Marten use of habitat in a commercially clear-cut forest during summer. Unpubl. M.S. thesis, Univ. Maine, Orono. 31 pp. Major, J. T., and J. A. Sherburne. 1987. Interspecific relationships of coyotes, bobcats, and red foxes in western Maine. Journal of Wildlife Management 51:606-616. Malcolm, J. R. 1986. Socio-ecology of bat-eared foxes (Otocyon megalotis). J. Zool. (Lond.) 208:457-467. Martin, P. 1971. Movements and activities of the Mountain beaver (Aplodontia rufa). Journal of Mammalogy 52:717-723. Martinsen, D. L. 1968. Temporal patterns in the home ranges of chipmunks (Eutamias). J. Mamm. 49:83-91. 177

Massei, G., P. V. Genov, B. W. Staines, and M. L. Gorman. 1997. Factors influencing home range and activity of wild boar (Sus scrofa) in a Mediterranian coastal area. J. Zool. (Lond.) 242:411-423. McCorquodale, S. M., K. J. Raedeke, and R. D. Taber. 1989. Home ranges of elk in an arid environment. Northwest Sci. 63:29-34. McDougal 1977 in Sunquist Smith Cont Zool 336:1-98 McShea, W. J., and G. Schwede. 1993. Variable acorn crops: responses of white-tailed deer and other mast consumers. J. Mamm. 74:999-1006. Mech, L. D., and L. L. Rogers. 1977. Status, distribution, and movements of martens in northeastern Minnesota. U.S. Forest Service Research Paper NE-143. 7 pp. Meia, J-S., and J-M. Weber. 1995. Home range and movements of red foxes in central Europe: stability despite environmental changes. Can. J. Zool. 73:1960-1966. Meier, P. T. 1992. Social organization of woodchucks (Marmota monax). Behav. Ecol. And Sociobiol. 31:393-400. Merrick, R. L. and T. R. Loughlin. 1997. Foraging behaviour of adult female and young-of-the-year Steller sea lions in Alaskan waters. Canadian Journal of Zoology 75:776- 786. Messick, J. P., and M. G. Hornocker. 1981. Ecology of the badger in southwestern Idaho. Wildlife Monographs 76:1-53 Messier, F. 1985. Social organization, spatial distribution, and population trends of wolves in relation to moose density. Can. J. Zool. 63:1068-1077. Mills, L. S., and F. F. Knowlton. 1991. Coyote space use in relation to prey abundance. Can. J. Zool. 69:1516-1521. Mineau, P., and D. Madison. 1977. Radio-tracking of Peromyscus leucopus. Can. J. Zool. 55:465-468. Minta, S. C. 1990. The badger, Taxidea taxus (Carnivora, Mustelidae): spatial-temporal analysis, dimorphic territorial polygyny, population characteristics, and human influences on ecology. Unpubl. Ph.D. Dissertation, Univ. California, Davis. Moe, S. R., and P. Wegge. 1994. Spacing behaviour and habitat use of axis deer (Axis axis) in lowland Nepal. Can. J. Zool. 72:1735-1744. Montgomery, G. G., and Y. D. Lubin. 1978. Movements of Coendou prehensilis in the Venezuelan Llanos. J. Mamm. 59:887-888. Mooty, J. J., P. D. Karns, and T. K. Fuller. 1987. Habitat use and seasonal range size of white-tailed deer in northcentral Minnesota. Journal of Wildlife Management 51:644- 648. Morris, P. A. 1988. A study of home range and movements in the hedgehog (Erinaceus europaeus). J. Zool. (Lond.) 214:433-449. Mukinya, J. G. 1973. Density, distribution, population structure and social organization of the black rhinoceros in Masai Mara Game reserve. E. Afr. Wildl. J. 11:385-400. Mullican, T. R. 1988. Radio telemetry and fluorescent pigments: a comparison of techniques. Journal of Wildlife Management 52:627-631. Murphy, E. C., and J. E. Dowding. 1994. Range and diet of stoats (Mustela erminea) in a New Zealand beech forest. New Zealand J. Ecol. 18:11-18. Murphy, E. C., and J. E. Dowding. 1995. Ecology of the stoat in Nothofagus forest: home range, habitat use and diet at different stages of the beech mast cycle. New Zealand J. Ecol. 19:97-109. Murray, M. G. 1982. Home range, dispersal and the clan system of impala. Afr. J. Ecol. 20:253-269. Nakada, A., T. Fujuta, and H. Sato. 1996. A case study of home range and habitat use in 3 free-ranging dogs: effects of past histories. Journal of Ethology 14:139-143. Nellis, D. W., and C. O. R. Everard. 1983. The biology of the mongoose in the Caribbean. Stud. Fauna Curacao Caribbean Islands 64:1-162. Nelson, M. E., and L. D. Mech. 1981. Deer social organization and wold predation in northeastern Minnesota. Wildlife Monographs 77:1-53 Newell, G. R. 1999. Home range and habitat use by Lumholtz's tree-kangaroo (Dendrolagus lumholtzi) within a rainforest fragment in north Queensland. Wildlife Research 26:129-145. Nicholson, M. C., R. T. Bowyer, and J. G. Kie. 1997. Habitat selection and survival of mule deer: tradeoffs associated with migration. Journal of Mammalogy 78:483-504. Norbury, G. L., D. C. Norbury, and R. P. Heyward. 1998. Space use and denning behaviour of wild ferrets (Mustela furo) and cats (Felis catus). New Zealand J. Ecology 22:149-159. 178

Norton, P. M., and A. B. Lawson. 1985. Radio tracking of leopards and caracals in the Stellenbosch area, Cape Province. S.Afr. J. Wildl. Res., 15:17-24 Novick, H. J., and G. R. Stewart. 1982. Home range and habitat preferences of black bears in the San Bernardino Mountains of southern California. Calif. Fish and Game 67:21-35. Nugent, G. 1994. Home range size and its development for fallow deer in the Blue Mountains, New Zealand. Acta Theriologica 39:159-175. O'Brien, P. H. 1984. Feral goat home range: influence of social class and environmental variables. Applied Animal Behaviour Science 12:373-385. O'Neal, G. T., J. T. Flinders, and W. P. Clary. 1987. Behavioral ecology of the Nevada kit fox (Vulpes macrotis nevadensis) on a managed desert rangeland. Pp. 443-481 in Current Mammalogy (H. H. Genoways, ed.). Plenum Press, New York. O'Shea, T. J. 1976. Home range, social behavior, and dominance relationships in the African unstriped ground squirrel, Xerus rutilus. Journal o fMammalogy 57:450-460. Okarma, H.,, W. Jedrzejewski, K. Schmidt, S. Sniezko, A. N. Bunevich, and B. Jedrzejewska. 1998. Home ranges of wolves in Bialowieza primeval forest, Poland, compared with other Eurasian populations. J. Mamm. 79:842-852. Oli, M. K. 1997. Winter home range of snow leopards in Nepal. Mammalia 61:355-360. Ono, Y., T. Doi, H. Ikeda, M. Baba, M. Takeishi, M. Izawa, and T. Iwamoto. 1988. Territoriality of Guenther's dikdik in the Omo National Park, Ethiopia. Afr. J. Ecol. 26:33- 49. Ormiston, B. G. 1985. Effects of a subminiature radio colar on activity of free-living white-footed mice. CJZool 63:733-735. Ortega, J. C. 1990. Home-range size of adult rock squirrels (Spermophilus variegatus) in southeastern Arizona. Journal of Mammalogy 71:171-176. Oshima, J., M. C. Santos, M. Bazzalo, P. A. Flores, and F. Pupim. 2010. Home ranges of Guiana dolphins (Sotalia guianensis) (Cetacea: Delphinidae) in the Cananéia estuary, Brazil. Journal of the Marine Biological Association of the United Kingdom 90:1641-1647. Page, R. J. C., J. Ross, and D. H. Bennett. 1992. A study of the home ranges, movements and behaviour of the feral cat population at Avonmouth docks. Wildl. Res. 19:263-277. Palomares, F., and M. Delibes. 1994. Spatio-temporal ecology and behavior of European genets in southwestern Spain. J. Mamm. 75:714-724. Pandolfi, M., P. Forconi, and L. Montecchiari. 1997. Spatial behaviour of the red fox (Vulpes vulpes) in a rural area of central Italy. Ital. J. Zool. 64:351-358. Parkes, J. P. 1984. Home ranges of radio-telemetred hares (Lepus capensis) in a sub-alpine population in New Zealand: implications for control. Acta Zoologica Fennica 171:279-281. Parra, G. J. 2006. Resource partitioning in sympatric delphinids: space use and habitat preferences of Australian snubfin and Indo-Pacific humpback dolphins. Journal of Animal Ecology 75:862-874. Patton, D. R. 1975. Nest use and home range of three Abert squirrels as determined by radio tracking. USDA Forest Service Research Note RM-281. 3 pp. Patton, D. R., R. L. Wadleigh, and H. G. Hudak. 1985. The effects of timber harvesting on the Kaibab squirrel. Journal of Wildlife Management 49:14-19. Payer, D. C., and B. E. Coblentz. 1997. Seasonal variation in California bighorn ram (Ovis canadensis californiana) habitat use and group size. Northwest Sci. 71:281-288. Penzhorn, B. L. 1982. Home range sizes of Cape mountain zebras Equus zebra zebra in the Mountain zebra national park. Koedoe 25:103-108. Person, D. K., and D. H. Hirth. 1991. Home range and habitat use of coyotes in a farm region of Vermont. Journal of Wildlife Management 55:433-441. Peterson, R. O., J. D. Woolington, T. N. Bailey. 1984. Wolves of the Kenai Peninsula, Alaska. Wildlife Monographs 88:1-52. Phillips, M., and P. C. Catling. 1991. Home range and activity patterns of red foxes in Nadgee Nature Reserve. Wildl. Res. 18:677-686. Piekielek, W., and T. S. Burton. 1975. A black bear population study in northern California. Calif. Fish and Game 61:4-25. Pienaar, D. J., J. du P. Bothma, and G. K. Theron. 1993. White rhinoceros range size in the south-western Kruger National Park. J. Zool. (Lond.) 229:641-649.

179

Pittman, M. T., B. P. McKinney, and G. Guzman. 1995. Ecology of the mountain lion on Big Bend rangch state park in Trans-Pecos Texas. Proc. Accl. Conf. S. E. Assoc. Fish and Wildlife Agencies 49:552-559. Poche, R. M., S. J. Evans, P. Sultana, M. E. Hague, R. Sterner, and M. A. Siddique. 1987. Notes on the golden jackal (Canis aureus) in Bangladesh. Mammalia 51:259-270. Poole, K.G. 1994. Characteristics of an unharvested lynx population during a snowshoe hare decline. Journal of Wildlife Management 58:608-618 Potvin, F. 1987. Wolf movements and population dynamics in Papineau-Labelle reserve, Quebec. Can. J. Zool. 66:1266-1273. Poulle, M. L., M. Artois, and J. J. Roeder. 1994. Dynamics of spatial relationships among members of a fox group (Vulpes vulpes: Mammalia: Carnivora). J. Zool. (Lond.) 233:93-106. Prakash, I., L. R. Kametkar, and K. G. Purohit. 1968. Home range and territoriality of the northern palm squirrel, Funambulus pennanti Wroughton. Mammalia 32:603-611. Prestrud, P. 1992. Denning and home-range characteristics of breeding arctic foxes in Svalbard. Can. J. Zool. 70:1276-1283. Priddell, D., N. Shepherd, and G. Wellard. 1988. Home ranges of sympatric red kangaroos Macropus rufus, and western grey kangaroos M. fuliginosus, in western New South Wales. Aust. Wildl. Res. 15:405-411. Pulliainen, E. 1984. Use of the home range by pine martens (Martes martes L.). Acta Zool. Fennica 171:271-274. Pyrah, D. 1984. Social distribution and population estimates of coyotes in north-central Montana. J. Wildlife Management 48:670-690. Quin, D. G. 1995. Population ecology of the squirrel glider (Petaurus norfolcensis) and the sugar glider (P. breviceps) (Marsupialia: Petauridae) at Limeburners Creek, on the central north coast of New South Wales. Wildl. Res. 22:471-505. Quin, D. G., A. P. Smith, S. W. Green, and H. B. Hines. 1992. Estimating the home ranges of sugar gliders (Petaurus breviceps) (Marsupialia: Petauridae), from grid-trapping and radiotelemetry. Wildl. Res. 19:471-487. Rabinowitz, A. 1990. Notes on the bahavior and movements of leopard cats, Felis bengaliensis, in a dry tropical forest mosaic in Thailand. Biotropica 22:397-403. Rabinowitz, A. R. 1991. Behaviour and movements of sympatric civet species in Huai Kha Khaeng Wildlife Sanctuary, Thailand. J. Zool. (Lond.) 223:281-298. Rabinowitz, A., and B. G. Nottingham, Jr. 1986. Ecology and behaviour of the jaguar (Panthera onca) in Belize, Central America. J. Zool. (London) 210:149-159. Rathbun, G. B. 1979. The social structure and ecology of elephant-shrews. Advances in Ecology 20:1-76. Ratnayeke, S., A. Bixler, and J. L. Gittleman. 1994. Home range movements of solitary, reproductive female coatis, Nasua narica, in south-eastern Arizona. J. Zool. (Lond.) 233:322-326. Ray, J. C. 1997. Comparative ecology of two African forest mongooses, Herpestes naso and Atilax paludinosus. Afr. J. Ecol. 35:237-253. Reeve, N. J. 1982. The home range of the hedgehog as revealed by a radio tracking study. Symp. Zool. Soc. (Lond) 49> Reichman, O. J., T. G. Whitham, and G. A. Ruffner. 1982. Adaptive geometry of burrow spacing in two pocket gopher populations. Ecology 63:687-695. Reid, D. G., H. Jinchu, and H. Yan. 1991. Ecology of the red panda Ailurus fulgens in the Wolong Reserve, China. J. Zool. (Lond.) 225:347-364. Reynolds, T. D. 1984. Daily summer movemente, activity patterns, and home range of pronghorn. Northwest Science 58:300-311. Ribble, D. O., and M. Salvioni. 1990. Social organization and nest co-occupancy in Peromyscus californicus, a monogamous rodent. Behav. Ecol. Sociobiol. 26:9-15. Ribble, D. O., and S. Stanley. 1998. Home ranges and social organization of syntopic Peromyscus boylii and P. truei. J. Mamm. 79:932-941. Rideout, C. B. 1974. A radio telemetry study of the ecology and behavior of the Rocky Mountain goat in western Montana. Unpubl. Ph.D. dissert., Univ. Kansas.146 pp. Rogovin, K. A., E. J. Heske, and G. I. Shenbrot. 1996. Patterns of spatial organization and behaviour of Pygeretmus pumilio Kerer, 1792 (Dipodidae, Rodentia): radiotelemtry study in the Dagestan Desert, Russia. Journal of Arid Environments 33:355-366. Rolley, R. E. 1983. Behavior and population dynamics of bobcats in Oklahoma. Unpubl. Ph.D. Diss. Oklahoma State Univ., Stillwater. 98 pp. Ross, P. I., and M. G. Jalkotzy. 1992. Characteristics of a hunted population of cougars in southwestern Alberta. Journal of Wildlife Management 56:417-426. 180

Roy, L. D., and M. J. Dorrance. 1985. Coyote movements, habitat use, and vulnerability in central Alberta. Coyote movements, habitat use, and vulnerability in central Alberta. Journal of Wildlife Management 49:307-313. Roze, U. 1987. Denning and winter range of the porcupine. Can. J. Zool. 65:981-986. Rucker, R. A., M. L. Kennedy, G. A. Heidt, and M. J. Harvey. 1989. Population density, movements, and habitat use of bobcats in Arkansas. SW Nat 34:101-108.1992 Ryan, J. M., G. K. Creighton, and L. H. Emmons. 1993. Activity patterns of two species of Nesomys (Muridae: Nesomyinae) in a Madagascar rain forest. J. Trop. Ecol. 9:101-107. Sakai, H. F., and B. R. Noon. 1997. Between-habitat movement of dusky-footed woodrats and vulnerability to predation. Journal of Wildlife Management 61:343-350. Salsbury, C. M., and K. B. Armitage. 1994. Home-range size and exploratory excursions of adult, male yellow-bellied marmots. Journal of Mammalogy 75:648-656. Saltz, D., and P. U. Alkon. 1989. On the spatial behaviour of Indian crested porcupines (Hystrix indica). J. Zool. (Lond.) 217:255-266. Salvatori, V., G. Vaglio-Laurin, P. L. Meserve, L. Boitani, and A. Campanella. 1999. Spatial organization, activity, and social interactions of cupleo foxes (Pseudalopex culpaeus) in north-central Chile. Journal of Mammalogy 80:980-985. Sargeant, A. B., S. H. Allen, J. O. Hastings. 1987. Spatial relationships between sympatric coyotes and red foxes in North Dakota. Journal of Wildlife Management 51:285- 293. Sargent, R. A., and R. F. Labisky. 1995. Home range of male white-tailed deer in hunted and non-hunted populations. Proc. Ann. Conf. S. E. Assoc. Fish and Wildlife Agencies 49:389-398. Saunders, G., and B. Kay. 1996. Movements and home ranges of feral pigs (Sus scrofa) in Kosciusko National Park, New South Wales. Wildl. Res. 23:711-719. Sawyer, D. T., and T. T. Fendley. 1990. Seasonal home range size and movement behavior of the gray fox on the Savannah River site, South Carolina. Proc. Accl. Conf. S. E. Assoc. Fish and Wildlife Agencies 44:379-389. Scanlon, J. J., and M. R. Vaughan. 1985. Movements of white-tailed deer in Shenandoah National Park, Virginia. Proc. Ann. Conf. S. E. Assoc. Fish and Wildlife Agencies 39:396-402. Schaller, G. B. 1967. The deer and the tiger. UCPress Schaller, G. B. 1972. The Serengeti lion. Univ. Chicago Press. Schaller, G. B., H. Jinchu, P. Wenshi, and Z. Jing. 1985. The giant pandas of Wolong, Univ. Chicago Press, Chicago, IL Schaller, G. B., J. Tserindeleg, and G. Amarsanaa. 1994. Observations on snow leopards in Mongolia. Pp. 33-43 in Proc. Seventh Intnl. Snow Leopard Symp., Fox, J. L., and J. Du, eds. Snow Leopard Trust, Seattle, WA, and Chicago Zool. Soc., Chicago, IL Schmidt, K. W. Jedrzejewski, and H. Okarma. 1997. Spatial organization and social relations in the Eurasian lynx population in Bialowieza Primeval Forest, Poland. Acta Theriologica 42:289-312. Schoen, J. W., and M. D. Kirchhoff. 1985. Seasonal distribution and home-range patterns of Sitka black-tailed deer on Admiralty Island, southeast Alaska. Journal of Wildlife Management 49:96-103. Schoenfeld, M., and Y. Yom-Tov. 1985. The biology of two species of hedgehogs, Erinaceus europaeus concolor and Hemiechinus auritus aeguptius, in Israel. Mammalia 40:339-355. Schroder, G. D. 1979. Foraging behavior and home range utilization of the Bannertail kangaroo rat (Dipodomys spectabilis). Ecology 60:657-665. Schroder, G. D. 1987. Mechanisms for coexistence among three species of Dipodomys: habitat selection and an alternative. Ecology 68:1071-1083. Schropfer, R., P. Wiegand, and H.-H. Hogrefe. 1997. The implications of territoriality for the social system of the European pine marten (Martes martes (L., 1758). Zeit. Fur Saugetierk. 62:209-218. 181

Schwarzenberger, V. t., and H. Klingel. 1995. Telemetrische Untersuchungen zur Raumnutzung und Aktivitatsrhythmik freilebender Gelbhalsmause Apodemus flavicollis Melchior, 1834. Z. Saugetierk. 60:20-32. (Range utilisation and activity of readio-collar Schweinsburg, R. E. 1971. Home range, movements, and herd integrity of the collared peccary. Journal of Wildlife Management 35:45-460 Scott, M. D., and K. Causey. 1973. Ecology of feral dogs in Alabama. J. Wildl. Management 37:253-265. Seamon, J. O., and G. H. Adler. 1999. Short-term use of space by a neotropical forest rodent, Proechimys semispinosus. Journal of Mammalogy 80:899-904. Seidensticker, J. C., IV, M. G. Hornocker, W. V. Wiles, and J. P. Messick. 1973. Mountain lion social organization in the Idaho primitive area. Wildlife Monographs 35:1-60. Servheen, C. 1983. Grizzly bear food habits, movements, and habitat selection in the Mission Mountains, Montana. Journal of Wildlife Management 47:1026-1035. Servin, J., and C. Huxley. 1995. Coyote home range size in Durango, Mexico. Zeit. Fur Saugetierk. 60:119-120. Servin, J., J. R. Rau, and M. Delibes. 1991. Activity pattern of the red fox Vulpes vulpes in Donana, SW Spain. Acta Theriologica 36:369-373. Shaw, J. H., J. Machado-Neto, and T. S. Carter. 1987. Behavior of free-living giant anteaters (Myrmecophaga tridactyla). Biotropica 19:255-259. Sheperd, B. F., and R. K. Swihart. 1995. Spatial dynamics of fox squirrels (Sciurus niger) in fragmented landscapes. Can. J. Zool. 73:2098-2105. Sheppard, D. H. 1972., Home ranges of chipmunks (Eutamias) in Alberta. J. Mamm. 53:379-380. Sheppard, J. K., A. R. Preen, H. Marsh, I. R. Lawler, S. D. Whiting, and R. E. Jones. 2006. Movement heterogeneity of dugongs, Dugong dugon (Müller), over large spatial scales. Journal of Experimental Marine Biology and Ecology 334:64-83. Sherfy, F. C., and J. A. Chapman. 1980. Seasonal home range and habitat utilization of raccoons in Maryland. Carnivore 3:8-18. Shirer, H. W., and H. S. Fitch. 1970. Comparison from radiotracking of movements and denning habits of the raccood, striped skunk, and opossum in northeastern Kansas. J. Mamm. 51:491-503. Shriner, W. M., and P. B. Stacey. 1991. Spatial relationships and dispersal patterns in the rock squirrel, Spermophilus variegatus. J. Mamm. 72:601-606. Sillero-Zubiri, C., and D. Gottelli. 1992. Population ecology of spotted hyaena in an equatorial mountain forest. Afr. J. Ecol. 30:292-300. Simon, T. L. 1980. An ecological study of the marten in the Tahoe National Forest, California. Unpubl. M.S. thesis, CSU Sacramento. 159 pp. Sjöberg, M. and J. P. Ball. 2000. Grey seal, Halichoerus grypus, habitat selection around haulout sites in the Baltic Sea: bathymetry or central-place foraging? Canadian Journal of Zoology 78:1661-1667 Skinner, J. D., and R. J. van Aarde. 1986. The use of space by the Aardwolf Proteles cristatus. J. Zool. (Lond.) Ser. A 209:299-301. Skinner, J. D., and R. J. van Aarde. 1987. Range use by brown hyaenas Hyaena brunnea relocated in an agricultural area of the Transvaal. J. Zool. (Lond.) 212:350-352. Slough, B. G. 1989. Movements and habitat use by transplanted marten in the Yukon territory. Journal of Wildlife Management 53:991-997. Slough, B. G., and G. Mowat. 1996. Lynx population dynamics in an untrapped refugium. Journal of Wildlife Management 60:946-961. Smith, A. T., and B. L. Ivins. 1984. Spatial relationships and social organization in adult pikas: a facultatively monogamous mammal. Zeit. fur Saugetierkunde 66:289-308. Smith, A. T., H. J. Smith, W. X. Gao, Y. Xiangchu, and L. Junxiun. 1986. Social behavior of the steppe-dwelling black-lipped pika. Natl. Geog. Research 2:57-74. Smith, G. W. 1990. Home range and activity patterns of black-tailed jackrabbits. Gt. Basin. Nat. 50:249-256. Smith, R. J., T. M. Cox, and A. J. Westgate. 2006. Movements of harbor seals (Phoca vitulina mellonae) in Lacs des Loups Marins, Quebec. Marine Mammal Science 22:480- 485. Smuts, G. L. 1975. Home range sizes for Burchell's zebra Equus burchelli antiquorum from the Kruger National Park. Koedoe 18:139-146. Southgate, R., C. Palmer, M. Adams, P. Masters, B. Triggs, and J. Woinarski. 1996. Population and habitat characteristics of the golden bandicoot (Isoodon auratus) on Marchinbar Island, Northern Territory. Wildl. Res. 23:647-664. Spencer, W. D. 1981. Pine marten habitat preferences at Sagehen Creek, California. Unpubl. M.S. thesis, UC Berkeley. 121 pp. 182

Spiegel, L. K., and M. Bradbury. 1992. Home range characteristics of the San Joaquin kit fox in western Kern County, California. Trans Western Section Wildlife Soc. 28:83- 92. Spreadbury, B. R., K. Musil, J. Musil, C. Kaisner, and J. Kovak. 1996. Cougar population characteristics in southeastern British Columbia. Journal of Wildlife Management 60:962-969. Springer, J. T. 1982. Movement patterns of coyote in south central Washington Journal of Wildlife Management 46:191-200. Stahl, P., M. Artois, and M. F. A. Aubert. 1988. Organization spatiale et deplacements de chats forestiers adultes (Felis silvestris, Schreber, 1777) en Lorraine. Rev. Ecol. (Terre Vie) 43:113-132. Stander, P. E., P. J. Haden, //. Kaqece, and //. Ghau. 1997. The ecology of asociality in Namibian leopards. J. Zool. (Lond.) 242:343-364. Staniland, I., N. Gales, N. Warren, S. Robinson, S. Goldsworthy, and R. Casper. 2010. Geographical variation in the behaviour of a central place forager: Antarctic fur seals foraging in contrasting environments. Marine Biology 157:2383-2396. Stark, M. A. 1986. Daily movement, grazing activity and diet of savanna buffalo, Syncerus caffer brachyceros, in Benoue National Park, Cameroon. Afr. J. Ecol. 24:255-262. Statham, M., and H. L. Statham. 1997. Movements and habits of brushtail possums (Trichosurus vulpecula) in an urban area. Wildl. Res. 24:715-726. Stenhouse, G. B., P. B. Latour, L. Kutny, N. MacLean, and G. Glover. 1994. Productivity, survival, and movements of female moose in a low-density population, Northwest Territories, Canada. Arctic 48:57-62. Cited in Hundertmark 1997 Stephenson, T. R., M. R. Vaughan, and D. E. Anderen. 1996. Mule deer movements in response to military activity in southeast Colorado. Journal of Wildlife Management 60:777-787. Steventon, J. D. 1979. Influence of timber harvesting upon winter habitat use by marten. Unpubl. M.S. thesis, Univ. Maine, Orono. 24 pp. Steventon, J. D., and J. T. Major. 1982. Marten use of habitat in a commercially clear-cut forest. Journal of Wildlife Management 46:175-182. Stone, K. D., G. A. Heidt, P. T. Caster, and M. L. Kennedy. 1997. Using geographic information systems to determine home range of the southern flying squirrel (Glaucomys volans). Amer. Midl. Nat. 137:106-111. Storm, G. L. 1972. Daytime retreats and movements of skunks on farmlands in Illinois. Journal of Wildlife Management 36:31-45. Streubel, D. P. 1975. Behavioral features of sympatry of Spermophilus spilosoma and Spermophilus tridecemlineatus and some aspects of the life history of S. spilosoma. Unpubl. Ph.D. dissertation, Univ. Northern Colorado, Greeley, CO. 30 pp. Strohmeyer, D. C., and J. M. Peek. 1996. Wapiti home range and movement patterns in a sagebrush desert. Northwest Sci. 70:79-87. Stuart-Smith, A. K., C. J. A. Bradshaw, S. Boutin, D. M. Hevert, and A. B. Rippin. 1997. Wodland caribou relative to landscape patterns in northeastern Alberta. Journal of Wildlife Management 61:622-633. Sukumar, R. 1989. Ecology of the Asian elephant in southern India. I. Movement and habitat utilization patterns. J. Trop. Ecol. 5:1-18. Sumner, P. W., E. P. Hill, and J. b. Wooding. 1984. Activity an dmovements of coyotes in Mississippi and Alabama. Proc. Annl. Conf. S. E. Assoc. Fish and Wildlife Agencies 38:174-181. Sunquist, M. E. 1981. The social organization of tigers (Panthera tigris) in Royal Chitawan National Park, Nepal. Smisthsonian Contrib. Zool. 336:1-98. Sunquist, M. E. 1982. Movements and habitat use of a sloth bear. Mammalia 46:545-547. Sunquist, M. E., F. Sunquist, and D. E. Daneke. 1989. Ecological separation in a Venezuelan llanos carnivore community. Advances in Neotropical Mammalogy 1989:197- 232. Sunquist, M. E., S. N. Austad, and F. Sunquist. 1987. Movement patterns and home range in the common opossum (Didelphis marsupialis). Journal of Mammalogy 68:173- 176. 183

Swihart, R. K. 1992. Home-range attributes and spatial structure of woodchuck populations. Journal of Mammalogy 73:604-618. Taber, A. B., and D. W. MacDonald. 1992. Spatial organization and monogamy in the mara Dolichotis patagonum. J. Zool. (Lond). 227:417-438. Taber, A. B., C. P. Doncaster, N. N. Neris, and F. Colman. 1994. Ranging behaviour and activity patterns of two sympatric peccaries, Catagonus wagneri and Tayassu tajacu, in the Paraguayan Chaco. Mammalia 58:61-71. Tallmon, D., and L. S. Mills. 1994. Use of logs within home ranges of California red-backed voles on a remnant of forest. Journal of Mammalogy 75:97-101. Tamura, N. 1998. Forest type selection by the Japanese squirrel, Sciurus lis. Japanese Journal of Ecology 48:123-127 (in Japanese with English Abstract and Tables). Tamura, N., F. Hayashi, and K. Miyashita. 1989. Spacing and kinship in the Formosan squirrel living in different habitats. Oecologia 79:344-352. Taylor, R. J. 1993. Home range, nest use and activity of the Tasmanian bettong, Bettongia gaimardi. Wildl. Res. 20:87-95. Tchamba, M. N., H. Bauer, A. Hunia, H. H. de Longh, and H. Planton. 1994. Some observations on the movements and home range of elephants in Waza National Park, Cameroon. Mammalia 58:527-533. Thompson, I. D., and P. W. Colgan. 1987. Numerical responses of martens to a food shrotage in northcentral Ontario. Journal of Wildlife Management 51:824-835. Thompson, S. D. 1982. Spatial utilization and foraging behavior of the desert woodrat, Neotoma lepida lepida. J. Mamm. 63:570-581. Thomson, P. C. 1992. The behavioural ecology of dingoes in north-western Australia. IV. Social and spatial organisation, and movements. Wildl. Res. 19:543-563. Thouless, C. R. 1996. Home ranges and social organization of female elephants in northern Kenya. Afr. J. Ecol. 34:284-297. Tierson, W. C., G. F. Mattfeld, R. W. Sage, Jr., and D. H. Behrend. 1985. Seasonal movements and home ranges of white-tailed deer inth eAdirondacks. Journal of Wildlife Management 49:760-769. Topping, M. G., and J. S. Millar. 1996. Home range size of bushy-tailedd woodrats, Neotoma cinerea, in southwestern Alberta. Canadian Field-Naturalist 110:351-353. Torres-Mura, J. C. 1990. Uso del espacio en el roedor fosorial Apalacopus cyanus (Octodontidae). Unpubl. M.S. thesis, Univ. de Chile. 64 pp. Toweill, D. E., and J. G. Teer. 1981. Home range and den habits of Texas ringtails (Bassariscus astutus flavus). Pp. 1103-1120 in Worldwide Furbearer Conference Proceedings Vol. II (J. A. Champan and D. Pursley, eds.). Trapp, G. R. 1978. Comparative behavioural ecology of the ringtail and gray fox in southwestern Utah. Carnivore 1(2):3-32. Travaini, A., J. J. Aldama, and M. Delibes. 1993b. Red fox capture locations in relation to home range boundaries. Mammalia 57:448-451. Trent, T. T., and O. J. Rongstad. 1974. Home range and survival of cottontail rabbits in southwestern Wisconsin. Journal of Wildlife Management 38:459-472. Troy, S., and G. Coulson. 1993. Home range of the swamp wallaby, Wallabia bicolor. Wildl. Res. 20:571-577. Tucker, R. L., H. A. Jacobson, and M. R. Spencer. 1993. Territoriality and pairbonding of gray foxes in Mississippi. Proc. Accl. Conf. S. E. Assoc. Fish and Wildlife Agencies 47:90-98. Urban, D. 1970. Raccoon populations, movement patterns, and predation on a managed waterfowl marsh. Journal of Wildlife Management 34:372-382. van Aarde, R. J., and J. D. Skinner. 1986. Pattern of space use by relocated servals Felis serval. Afr. J. Ecol. 24:97-101. van Aarde, R. J., J. D. Skinner, M. H. Knight, and D. C. Skinner. 1988. Range use by a striped hyaena (Hyaena hyaena) in the Negev Desert. J. Zool. (Lond.) 216:575-577. Van Ballenberghe, V., A. W. Erickson, and D. Byman. 1975. Ecology of the timber wolf in northeastern Minnesota. Wildlife Monographs 43:1-43. Van Dyke, F, B. L. Probert, and F. M. Van Dyke. 1995. Moose home range fidelity and core area characteristics in south-central Montana. Alces 31:93-104. van Heezik, Y. M., and P. J. Seddon. 1998. Range size and habitat use of an adult male caracal in northern Saudi Arabia. J. Arid Envir. 40:109-112. van Hensbergen, H. J., and A. Channing. 1989. Habitat preference and use of space by the namtap Graphiurus ocularis (Rodentia: Gliridae). Mammalia 53:25-33. Van Vuren, D. 1983. Group dynamics and summer home range of bison in southern Utah. J. Mamm. 64:329-336. Van Vuren, D., and B. E. Coblentz. 1989. Population characteristics of feral sheep on Snata Cruz Island. JWM 53:306-313. 184

Vanderhoof, R. E., and H. A. Jacobson. 1993. Food plots and deer home range movements in the southern coastal plain. Proc. Annl. Conf. S. E. Assoc. Fish and Wildlife Agencies 47:33-42. Venkataraman, A. B., R. Arumaugam, and R. Sukumar. 1995. The foraging ecology of dhole (Cuon alpinus) in Mudumalai Sanctuary, southern India. J. Zool. (Lond.) 237:543-561. Vercauteren, K. C., and S. E. Hygnstrom. 1998. Effects of agricultural activities and hunting on home ranges of female white-tailed deer. Journal of Wildlife Management 62:280-285. Vernes, K., H. Marsh, and J. Winter. 1995. Home-range characteristics and movement patterns of the red-legged pademelon (Thylogale stigmatica) in a fragmented tropical rainforest. Wildl. Res. 22:699-708. Viljoen, P. J. 1989. Spatial distribution and movements of elephants (Loxodonta africana) in the northern Namib Desert region of the Kaokoveld, South West Africa/Namibia. J. Zool. (Lond.) 219:1-19. Viljoen, S. 1986. Use of space in southern African tree squirrels. Mammalia 50:293-309. Waldrip, G. P., and J. H. Shaw. 1979. Movements and habitat use by cow and calf elk at the Wichita Mountains National Wildlife Refuge. Pp. 177-184 in Boyce, M. S., and L. D. Hayden-Wing (eds.). North American elk: ecology, behavior and management. Warburton, G. S., and R. A. Powell. 1985. Movements of black bears on the Pisgah National Forest. Proc. Ann. Conf. S. E. Assoc. Fish and Wildlife Agencies 39:351-361. Ward, O. G., and D. H. Wurster-Hill. 1989. Ecological studies of Japanese raccoon dogs, Nyctereutes procyonoides viverrinus. J. Mamm. 70:330-334. Waser, P. M., and M. S. Waser. 1985. Ichneumia albicauda and the evolution of viverrid gregariousness. Zeit. fur Tierpsychol. 68:137-151. Wauters, L., P. Casale, and A. A. Dhondt. 1994. Space use and dispersal of red squirrels in fragmented habitats. Oikos 69:140-146. Weber, L.-M., and L. Dailly. 1998. Food habits and ranging behaviour of a group of farm cats (Felis catus) in a Swiss mountainous area. J. Zool. (Lond.) 245:234-237. Wheatley, M. 1997. Beaver, Castor canadensis, home range size and patterns of use in the taiga of southeastern Manitoba: I. Seasonal variation. Canadian Field-Nat. 111:204-210. Whitaker, J., R. B. Frederick, and T. L. Edwards. 1987. Home-range size and overlap of eastern Kentucky bobcats. Proc. Ann. Conf. S. E. Assoc. Fish and Wildlife Agencies 41:417-423. White, P. C. L., G. Saunders, and S. Harris. 1996. Spatio-temporal patterns of home range use by foxes (Vulpes vulpes) in urban environments. J. Anim. Ecol 65:121-125. White, P. J., and K. Ralls. 1993. Reproductive and spacing patterns of kit foxes relative to changing prey availability. Journal of Wildlife Management 57:861-867. White, P. J., K. Ralls, and R. A. Garrott. 1994. Coyote - kit fox interactions as revealed by telemetry. Can. J. Zool. 72:1831-1836. Whitman, J. S., W. B. Ballard, and C. l. Gardner. 1986. Home range and habitat use by wolverines in southcentral Alaska. Journal of Widlife Management 50:460-463. Wiegand, V. P. 1995. Habitat utilization in subpopulations of the red squirrel (Sciurus vulgaris L., 1758) [in German]. Zeit. Fur Saugetierk. 60:265-276. Wielgus, R. B., F. L. Bunnell, W. L. Wakkinen, P. E. Zager. 1994. Population dynamics of Selkirk Mountain grizzly bears. J. Wildlife Mgmt. 58:266-272. Wiles, G. J., and Weeks, H. P., Jr. 1986. Movements and use patterns of white-tailed deer visiting natural licks. Journal of Wildlife Management 50:487-496. Wilkinson, D. A., G. C. Grigg, and L. A. Beard. 1998. Shelter selection and home range of echidnas, Tachyglossus aculeatus, in the highlands of south-east Queensland. Wildlife Research 25:219-232. Windberg, L. A., and F. F. Knowlton. 1988. Management implications of coyote spacing patterns in southern Texas. Journal of Wildlife Management 52:632-640. Windberg, L. A., S. M. Ebbert, and B. T. Kelly. 1997. Population characteristics of coyotes (Canis latrans) in the northern Chihuahuan Desert of New Mexico. Amer. Midl. Nat. 138:197-207. Witmer, G. W., and D. S. deCalesta. 1986. Resource use by unexploited sympatric bobcats and coyotes in Oregon. Can. J. Zool. 64:2333-2338. 185

Witt, J. W. 1992. Home range and density estimates for the northern flying squirrel, Glaucomyus sabrinus, in western Oregon. Journal of Mammalogy 73:921-929. Wolton, R. J. 1985. The ranging and nesting behaviour of wood mice, Apodemus sylvaticus (Rodentia: Muridae), as revealed by radio-tracking. J. Zool. (Lond.) 206:203- 224. Wood, G. W., and R. E. Brenneman. 1980. Feral hog movements and habitat use in coastal South Carolina. J. Wildl. Mgmt. 44:420-427. Woodruff, R. A., and B. L. Keller. 1982. Dispersal, daily activity, and home range of coyotes in southeastern Idaho. Northwest Sci. 56:199-207. Woollard, T., and S. Harris. 1990. A behavioural comparison of dispersing and non-dispersing foxes (Vulpes vulpes) and an evaluation of some dispersal hypotheses. J. Anim. Ecol. 59:709-722. Wynne, K. M., and J. A. Sherburne. 1984. Summer home range use by adult marten in northwestern Maine. CJZool. 62:941-943. Young, B. F., and R. l. Ruff. 1982. Population dynamics and movements of black bears in east central Alberta. Journal of Wildlife Management 46:845-860. Zalewski, A., W. Jedrzejewski, and B. Jedrzejewska. 1995. Pine marten home ranges, numbers and predation on vertebrates in a deciduous forest (Bialowieza National Park, Poland). Ann. Zool. Fennici 32:131-144. Zezulak, D. S., and R. G. Schwab. 1981. A comparison of density, home range and habitat utilization of bobcat populations at Lava Beds and Joshua Tree National Monuments,California. Nat. Wild. Fed. Sci. Tech. Ser. 6:74-79. Zoellick, B. W., and N. S. Smith. 1992. Size and spatial organization of home ranges of kit foxes in Arizona. Journal of Mammalogy 73:83-88. Zwank, P. J., B. L. Shiflet, and J. D. Newsom. 1985. Habitat use by bobcats in upland forests of Louisiana. Proc. Ann. Conf. S. E. Assoc. Fish and Wildlife Agencies 39:313- 320.

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Table S2.2 Summary tracking information for leopard seals, Weddell seals, crabeater seals, southern elephant seals, Sub-Antarctic fur seals and Antarctic fur seals.

Species No. Sex No. Location Source Individuals days (min- max) Hydrurga leptonyx 26 M,F 23 – Western (Rogers et al., (Leopard seal) 347 Antarctic 2005) Peninsula & East Antarctica Leptonychotes 4 M,F 25 – 81 Neumayer See Table S4 weddellii Station, (Weddell seal) Ekström Shelf Ice, Atka Bay, Antarctica Lobodon 26 M,F 30 - 95 Neumayer See Table S5 carcinophagus Station, (Crabeater seal) Ekström Shelf Ice, Atka Bay, Antarctica & East Antarctica Mirounga leonina 21 M,F 25 - 412 King George (Bornemann et al., (Southern Island, 2000) elephant seal) Antarctica Arctocephalus 8 F 23 – Marion Island (de Bruyn et al., tropicalis 121 2009) (Sub-Antarctic fur seals) Arctocephalus 87 F 2 – 16 Heard Island (Staniland et al., gazella and Bird 2010) (Antarctic fur Island seals)

S2.2.1 Leopard Seals Satellite telemetry data was collected from two locations in Antarctica; one population off the Western Antarctic Peninsula (64°09′S, 60°57′E) and one population in Prydz Bay, eastern Antarctica (69°00’S, 76°00’E).

Protocols and ethics for the data from the eastern population (n=10) as per (1).

16 seals from the west population were instrumented (Table S3). The satellite tags and deployment procedure is the same used in Rogers, Hogg and Irvive (2005). However, there were modifications to the anaesthetic protocol from Higgins et al. (2002), see Table S3.

This study was conducted under the approval of the University of New South Wales Animal Care and Ethics Committee, ACEC number 08/103B and 11/112A.

187

Table S2.3 Western Antarctic leopard seal ID, sex, length and satellite transmission summary.

Date Days Seal ID Sex Tag Anesthetic Protocol Transmitting attached LS0719 M 28/02/2008 328 Zoletil/Atropine LS0801 M 10/02/2009 29 Midazolam/Flumazenil LS1707 M 27/02/2008 84 Zoletil/Atropine LS1607 F 20/02/2008 137 Zoletil/Atropine LS0907 M 18/02/2008 23 Zoletil/Atropine LS0803 F 11/02/2009 258 Midazolam/Isoflurane LS0720 F 12/02/2009 47 Midazolam LS0808 M 03/01/2009 336 Zoletil/Adrenalin LS0812 M 03/01/2009 341 Zoletil/Ketamine

LS0814 M 20/02/2009 52 Zoletil/Ketamine

LS0715 M 21/02/2009 86 Zoletil/Ketamine

LS0816 F 03/01/2009 337 Zoletil/Ketamine

LS0817 F 26/02/2009 311 Zoletil LS0818 F 27/02/2009 53 Zoletil/Ketamine LS0819 F 27/02/2009 303 Zoletil/Ketamine LS1012 F 05/02/2011 105 Zoletil/Ketamine/Midazolam

S2.3.2 Weddell seals

Weddell seal raw telemetry data was obtained from Plötz et al. (2009), and is available via open access through the data library PANGAEA– Publishing Network for Geoscientiﬁc and Environmental data (see Table S4).

Table S2.4 Weddell seal data sources

ID Source Institution* 714633 DOI: AWI 10.1594/PANGAEA.714633 714634 DOI: AWI 10.1594/PANGAEA.714634 714635 DOI: AWI 10.1594/PANGAEA.714635 714636 DOI: AWI 10.1594/PANGAEA.714636 * AWI: Alfred Wegener Institute

188

S2.2.3 Crabeater Seals

Crabeater seal raw telemetry data was obtained from two sources; Bornemann & Plötz (2005), data is available via open access through the data library PANGAEA– Publishing Network for Geoscientiﬁc and Environmental data Table S4). The second source is from Southwell (2007), data may be accessed from Australian Antarctic Data Centre http://data.aad.gov.au/aadc/argos/profile_list.cfm?taxon_id=25), see Table S5. For the tagging protocol and ethics of Southwell (2007), see Wall et al. (2007).

Table S2.5 Crabeater seal data sources.

ID Source Institution* 19126 Southwell (2007) AAD 19127 Southwell (2007) AAD 19129 Southwell (2007) AAD 19130 Southwell (2007) AAD 19131 Southwell (2007) AAD 19132 Southwell (2007) AAD 19133 Southwell (2007) AAD 20709 Southwell (2007) AAD 23196 Southwell (2007) AAD 23197 Southwell (2007) AAD 23198 Southwell (2007) AAD 23199 Southwell (2007) AAD 26438 Southwell (2007) AAD 26439 Southwell (2007) AAD 26441 Southwell (2007) AAD 26442 Southwell (2007) AAD 26443 Southwell (2007) AAD 26444 Southwell (2007) AAD 26445 Southwell (2007) AAD 26447 Southwell (2007) AAD 26448 Southwell (2007) AAD 4781 Southwell (2007) AAD 26125 DOI: 10.1594/PANGAEA.261725 AWI 26126 DOI: 10.1594/PANGAEA.261726 AWI 26127 DOI: 10.1594/PANGAEA.261727 AWI 26129 DOI: 10.1594/PANGAEA.261729 AWI *AAD: Australian Antarctica Division; AWI: Alfred Wegener Institute

189

Appendix S2.2 References Bornemann, H. & Plötz, J. (2005) At surface behaviour at location on spot of crabeater seal DRE1998_cra_y_m_15 from Drescher Inlet. doi:10.1594/PANGAEA.264706. Bornemann, H., Kreyscher, M., Ramdohr, S., Martin, T., Carlini, A., Sellmann, L. & Plötz, J. (2000) Southern elephant seal movements and Antarctic sea ice. Antarctic Science, 12, 3-15. de Bruyn, P.J.N., Tosh, C.A., Oosthuizen, W.C., Bester, M.N. & Arnould, J.P.Y. (2009) Bathymetry and frontal system interactions influence seasonal foraging movements of lactating subantarctic fur seals from Marion Island. Marine Ecology Progress Series, 394, 263-276. Higgins, D.P., Rogers, T.L., Irvine, A.D. & Hall-Aspland, S.A. (2002) Use of midazolam/pethidine and tiletamine/zolazepam combinations for the chemical restraint of leopard seals (Hydrurga leptonyx). Marine Mammal Science, 18, 483-499. Plötz, J., McIntyre, T., Bester, M.N. & Bornemann, H. (2009) At surface behaviour at location on spot of Weddell seal NEU2008_wed_u_m_17 from Atka Bay. Alfred Wegener Institute for Polar and Marine Research, Bremerhaven. doi:10.1594/PANGAEA.714638. Rogers, T.L., Hogg, C.J. & Irvine, A. (2005) Spatial movement of adult leopard seals (Hydrurga leptonyx) in Prydz Bay, Eastern Antarctica. Polar Biology, 28, 456- 463. Southwell, C. (2007) 1994 to 2000 - Antarctic Pack Ice Seals APIS) Survey, Australian Antarctic Data Centre - ARGOS satellite tracking record < http://data.aad.gov.au/aadc/argos/profile_list.cfm?taxon_id=25 >. Staniland, I., Gales, N., Warren, N., Robinson, S., Goldsworthy, S. & Casper, R. (2010) Geographical variation in the behaviour of a central place forager: Antarctic fur seals foraging in contrasting environments. Marine Biology, 157, 2383-2396. Wall, S.M., Bradshaw, C.J.A., Southwell, C.J., Gales, N.J. & Hindell, M.A. (2007) Crabeater seal diving behaviour in eastern Antarctica. Marine Ecology Progress Series, 337, 265-277.

190

1 1 5 5

1(W 1WW (W W W 1 1WWWzWWW

zzzz 1WEzzk

S2.3.1 Pack hunting

To examine the effects of pack hunting on range size in large carnivores, we compared home range size across 54 carnivorous mammal species. Using the data in our home range database, we defined species over 11kg as either utilising pack hunting or solitary hunting. Pack hunting was defined as a species that predominantly forages for prey in a group (i.e. 3 or more individuals) and solitary hunting was defined as a species that predominantly forage for prey as single individuals. We trimmed the Fritz et al. (2009) mammal supertree so that it only included our 54 species of interest. The resulting tree was fully resolved and did not include any polytomies. We ran a phylogenetic least squares (PGLS) regression analysis

(βintercept+βmass+βhunt_style+βmass*hunt_style), which included home range size (βintercept), body mass (βmass), hunting style (βhunt_style, pack or solitary) and an interaction term including both body mass and hunting style (βmass*hunt_style). The 95% confidence intervals (CI) were constructed around the slopes in order to determine whether a relationship was deemed significant (i.e. CI’s did not overlap 0; Martins, 2004).

Our results suggest that there is no significant difference in home range size between large carnivores that utilise pack versus solitary hunting methods (Table S6, Fig. S4).

There was also no difference in the scaling of home range size with body mass with either hunting strategy (Table S2.6, Fig. S2.4).

192

Table S2.6. Model estimates and confidence intervals for the

βintercept+βmass+βhunt_style+βmass*hunt_style model across 54 carnivorous mammals.

Model Term β(lower 95% CI, upper 95% CI) βintercept 0.13 (-0.57,0.83) βmass 1.11 (0.84,1.38)* βhunt_style 0.23 (-0.73,1.91) βmass*hunt_style -0.11 (-0.51,0.29) *Confidence intervals statistically different from zero and equivalent to p<0.05.

Fig.S2.4 Carnivore home range size as a function of species body mass compared for species utilising pack hunting (black circles) and solitary hunting (white circles) strategies. Each datum represents a species mean value (n=54 species). The solid black line is the phylogenetic regression of pack hunters: logY=1(logX)+0.36, while the dashed black line is the PGLS phylogenetic regression line of solitary hunters:

(logY=1.1(log(X))+0.13). Values were calculated from a phylogenetic least squares

(PGLS) regression analysis applied to the mammalian phylogeny.

193

Appendix S2.3 References

Fritz, S.A., Bininda-Emonds, O.R.P. & Purvis, A. (2009) Geographical variation in predictors of mammalian extinction risk: big is bad, but only in the tropics. Ecology Letters, 12, 538-549. Martins, E.P. (2004) COMPARE, version 4.6b. Computer programs for the statistical analysis of comparative data. Distributed by the author at http://compare.bio.indiana.edu/. Department of Biology, Indiana University.

194

Appendix 3

Tucker MA, Rogers TL (2014) Examining the Prey Mass of Terrestrial and Aquatic

Carnivorous Mammals: Minimum, Maximum and Range. PLoS ONE 9(8): e106402. doi:10.1371/journal.pone.0106402

195

Examining the Prey Mass of Terrestrial and Aquatic Carnivorous Mammals: Minimum, Maximum and Range

Marlee A. Tucker*, Tracey L. Rogers Evolution and Ecology Research Centre, School of Biological, Earth and Environmental Sciences, The University of New South Wales, Sydney, New South Wales, Australia

Abstract Predator-prey body mass relationships are a vital part of food webs across ecosystems and provide key information for predicting the susceptibility of carnivore populations to extinction. Despite this, there has been limited research on the minimum and maximum prey size of mammalian carnivores. Without information on large-scale patterns of prey mass, we limit our understanding of predation pressure, trophic cascades and susceptibility of carnivores to decreasing prey populations. The majority of studies that examine predator-prey body mass relationships focus on either a single or a subset of mammalian species, which limits the strength of our models as well as their broader application. We examine the relationship between predator body mass and the minimum, maximum and range of their prey’s body mass across 108 mammalian carnivores, from weasels to baleen whales (Carnivora and Cetacea). We test whether mammals show a positive relationship between prey and predator body mass, as in reptiles and birds, as well as examine how environment (aquatic and terrestrial) and phylogenetic relatedness play a role in this relationship. We found that phylogenetic relatedness is a strong driver of predator-prey mass patterns in carnivorous mammals and accounts for a higher proportion of variance compared with the biological drivers of body mass and environment. We show a positive predator-prey body mass pattern for terrestrial mammals as found in reptiles and birds, but no relationship for aquatic mammals. Our results will benefit our understanding of trophic interactions, the susceptibility of carnivores to population declines and the role of carnivores within ecosystems.

Citation: Tucker MA, Rogers TL (2014) Examining the Prey Mass of Terrestrial and Aquatic Carnivorous Mammals: Minimum, Maximum and Range. PLoS ONE 9(8): e106402. doi:10.1371/journal.pone.0106402 Editor: Kornelius Kupczik, Max Planck Institute for Evolutionary Anthropology, Germany Received April 16, 2014; Accepted August 5, 2014; Published August 27, 2014 Copyright: ß 2014 Tucker, Rogers. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: The authors confirm that all data underlying the findings are fully available without restriction. The data used in this publication can be accessed from figshare: http://dx.doi.org/10.6084/m9.figshare.999069 Funding: This work is supported by the Australian Research Council grant # LP0989933 to TLR. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * Email: [email protected]

Introduction relation to the small energetic benefit gained [9]. The minimum and maximum size of prey should scale positively with predator Examining patterns in predator-prey relationships provides body mass, resulting in there being no relationship between information on predation pressure (e.g. on specific size guilds) predator body mass and diversity of prey size (i.e. dietary niche [1,2], the impact of decreasing prey species on predators [3] and breadth - DNB) [10,11]. However, if maximum prey size scales the potential for trophic cascades and the collapse of prey positively with predator mass and minimum prey size does not this populations [4–6]. However, previous research on predator-prey will result in a larger diversity of prey size for larger predators (i.e. body mass relationships in mammalian carnivores has focused wider DNB). upon the mean mass of prey, largely ignoring the minimum and Our knowledge of mammalian broad-scale patterns of prey-size maximum body mass of prey consumed by predators. It is range is limited. There has been limited work investigating the important to include the minimum, maximum and range of prey prey mass of African predators and its effect on the system [12]. mass consumed as it allows the examination of the upper and However, this work largely focuses upon predation pressure on lower limits of carnivore prey selection. In addition, prey selection prey species, particularly herbivorous mammals. The remaining provides information such as energetic requirements (e.g. intake predator-prey body mass research is based the mean prey mass of rates), which is often used for predicting the susceptibility of predators [13,14]. Investigations into other animal groups include carnivores to population declines, the role of carnivores within predatory fish [15,16], reptiles [11,17] and birds [10], where there ecosystems and community structure [13]. is a general consensus that there is a positive relationship between Larger-sized predators can utilise a wide variety of prey types predator body mass and prey minimum, maximum and range in because they have large home ranges [7] that provide access to a mass, except for fish where the evidence is conflicting (positive or diversity prey species [8], as well as a wide gape size that allows no relationship between predator mass and minimum prey mass). them to feed on prey of a variety of sizes. Despite this, large Using minimum, maximum and range of prey mass for 108 predators tend to eat larger-sized prey [13]. It is not always carnivorous mammals from the orders Carnivora and Cetacea, we profitable for large species to feed on small-sized prey due to investigated the nature of the relationship between carnivore body capture inefficiency as it is costly to pursue small-sized prey in mass and prey body mass and how living in either the marine or

PLOS ONE | www.plosone.org 1 August 2014 | Volume 9 | Issue 8 | e106402 Examining the Prey Mass of Terrestrial and Aquatic Carnivorous Mammals terrestrial environment has impacted this relationship. This study resolution involved two steps; 1) R 3.0.2 [23] was used to create an has two objectives: first to examine the influence of physical XML input file containing topology constraints and input environment on minimum, maximum and range of prey mass; and commands for BEAST, and 2) the XML input file was run second to investigate the influence physical environment has had through the program BEAST 1.8 [24] which uses a Bayesian on the distribution of minimum, maximum and range of prey Markov chain Monte Carlo (MCMC) algorithm to permute the mass. Based on previous research [11,13], we predict that prey unresolved relationships within the tree based on the birth-death mass (minimum, maximum and range) will be positively correlated model. This produced 1,000 alternative phylogenetic trees to be with predator body mass for terrestrial carnivores. However, for used for the phylogenetic comparative analyses and the ancestral marine carnivores there could be two possible outcomes: first, prey state reconstructions. mass (minimum, maximum and range) could be positively correlated with body mass similar to terrestrial carnivores and Analyses other marine non-mammalian predators [16]; or second, there We applied a model selection approach to test the level of could be no relationship between prey mass (minimum, maximum support for alternative models of prey mass evolution. The best and range) and predator body mass. No relationship between model was selected using second-order Akaike’s information predator mass and prey mass is a possibility due to the high criterion with a correction for sample size (AICc; [25]). The abundance of small species that form dense aggregations in model with the lowest AICc value reflects the model with the aquatic environments (e.g. krill or fish), which lead to an increase highest support, although any other models within two units of the in the encounter rates between aquatic predators and these small lowest model were also considered to be likely candidates. We prey species. With both small and large predators exposed to these selected the cut-off of ,2.0 DAIC based on previous studies who abundant food resources, this would result in both small and large have identified that models below this threshold are generally predators feeding upon small prey species and therefore suggest no equally supported, models between 4–7 DAIC have some support relationship between predator mass and prey mass in aquatic and models .10 DAIC have no support [26–28]. To compute systems. AICc values, we applied each model as a phylogenetic generalized By examining the moments (e.g. mean, mode, skewness etc.) of least squares (PGLS) regression using the CAPER package in R the prey mass distributions, we can gather information on how the [29] to each of the 1000 trees (see previous section). PGLS mass of the prey consumed by carnivorous mammals differs or is regression also computes a l parameter using maximum likelihood similar across different environments. This information is impor- that estimates whether the extent of phenotypic variation among tant for building our knowledge of predator-prey relationships and species (e.g., mean body mass and associated home range size) is the drivers behind these relationships. correlated to phylogeny. When l is close to 1, phenotypic differentiation among present-day taxa reflects the phylogenetic Materials and Methods relationships among those species and is the product of Brownian evolution. When l is close to 0 phenotypic differentiation is Ethics statement unrelated to phylogeny and might be the outcome of adaptive All data in this study were extracted from published sources; evolution [30]. hence no permission or approval for obtaining the data was We performed three separate PGLS analyses for minimum prey required. mass, maximum prey mass and range of prey mass respectively. For each we examined the level of support of the relationship Database between prey mass (minimum, maximum or range), carnivore Data were collated on the minimum and maximum prey mass body mass and environment across 108 species. The models were (kg) consumed by 108 carnivorous mammal species (Appendix S1). formulated as; (a) b0+bmass* benvironment, where environment was Table 1 provides a summary of the orders and families sampled. coded as ‘‘terrestrial’’ or ‘‘aquatic’’ and included an interaction Prey mass range was calculated by subtracting the minimum prey term between carnivore mass and environment; (b) b0+bmass, mass from the maximum prey mass. Mean body mass (kg) was also which assumed body mass was the only variable predicting prey collected for these 108 predator species using the database mass; (c) b0, the evolutionary null model in which no predictor PanTHERIA [18]. All carnivores were classified as terrestrial or variable was included and subsequently modelled variance in aquatic, where aquatic species forage in water to survive (e.g. species prey mass as the outcome of Brownian evolution (i.e. under foraging) and terrestrial species forage on land to survive. All Brownian motion, trait evolution proceeds as a random walk values including carnivore mass and prey mass were log10 through trait space and Brownian motion has been proposed as a transformed prior to all analyses. null model of evolution for testing hypotheses of trait evolution [31]). Phylogeny To examine the effect of phylogeny and ecology on the We required a single phylogenetic tree to examine minimum minimum and maximum prey mass of carnivores, we ran variance prey mass, maximum prey mass and prey mass range in component analyses [32]. Variance was examined between carnivorous mammals. Phylogenetic information was obtained species, focusing on the contribution of order, family, genus, mass from the Fritz et al. [19] mammal supertree containing 5,020 and environment (aquatic or terrestrial). Variance components species and branch lengths proportional to time since divergence. analysis was performed using the lme4 package [33] in R version This tree was pruned using Mesquite ver 2.74 [20] to create the 2.13.2. tree (n = 108) based on the data in our database. Sotalia guianensis To gain an understanding on the shape of the prey mass (Guiana dolphin) was positioned within the pruned tree based on distributions across species and environments, we extracted the the topologies of Caballero et al. [21]. Due to insufficient descriptive statistics including the mean, median, mode, range, phylogenetic information, the Fritz et al. [19] tree included soft minimum, maximum, standard deviation (S.D.), skewness and polytomies where more than two species diverge at a single point kurtosis. Skewness measures the degree of asymmetry of a in time. To resolve the polytomies, we used a semi-automated distribution. If the skewness value is positive the data has a right polytomy resolver for dated phylogenies [22]. The polytomy skewed distribution and a negative value suggests left skewed data.

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Table 1. Summary of the orders and families included in our (CI -2.48, 1.47; Fig. 1B) and range of prey mass (CI -2.70, 1.00; study sample. Fig. 1C). There was a significant difference (confidence intervals do not overlap 0) in slope between terrestrial and aquatic carnivores for minimum (CI 0.37, 1.93), maximum (CI 0.24, Order Family 1.94) and range of prey mass (CI 0.49, 2.16). Despite the negative slopes of the aquatic regression lines, these values were not Carnivora Canidae significantly different from 0 for minimum, maximum or prey Felidae mass range. The terrestrial regression slopes were positive and Herpestidae significantly different from 0 for minimum, maximum or prey Hyaenidae mass range (Fig. 1A, B and C). Mephitidae Variance Components Analysis Mustelidae Order, family and genus explained the maximum proportion of Otariidae variance in prey mass of carnivores (58–73%; Table 3), providing Phocidae additional support for the strong influence of phylogenetic Procyonidae relatedness on the prey mass consumed by carnivorous mammals. Ursidae Body mass of the carnivore explained a relatively large degree of Viverridae variance (32–39%), where environment had little influence over the mass of prey consumed (,0.01–3%). Cetacea Balaenidae Balaenopteridae Descriptive Statistics Cetotheriidae Examining the descriptive statistics, the minimum prey mass Delphindae distribution across all mammals is positively skewed (skew = 0.11), Delphinidae while maximum and range of prey mass is negatively skewed Eschrichtiidae (20.40 to 20.37; Table S1). The prey mass data has a normal distribution for minimum, maximum and range of prey mass with Kogiidae kurtosis values between 0.62 and 1.18 (Table S1). Monodontidae When examining the aquatic and terrestrial prey mass Phocoenidae distributions, we find that aquatic carnivores tend to feed on Physeteridae smaller-sized prey, with mean prey mass for minimum, maximum Pontoporiidae and the range being lower than terrestrial carnivores (Fig. 2, Table Ziphiidae S2 and S3). Aquatic carnivore prey mass distributions are all negatively skewed (20.39 to 20.63), but in terrestrial carnivores doi:10.1371/journal.pone.0106402.t001 negatively-skewed distribution are only seen for maximum and range prey mass distributions (20.25 and 20.35). The prey mass Kurtosis measures height of the curve relative to its standard distribution for terrestrial carnivores is relatively flat as suggested deviations. Data with a peaked distribution with values around by the negative kurtosis values (20.25 to 20.75). For aquatic zero (i.e. normal distribution) have a positive kurtosis value, species, the prey mass distributions are normally distributed with whereas negative values between 0 and -1 implies that the data has kurtosis value between 0.88 and 3.17. Additionally, aquatic a flat distribution and values lower than 21.5 suggest a bimodal carnivores feed on prey spanning 12 900 kg, compared with 2 distribution. 700 kg for terrestrial carnivores.

Results Discussion Phylogenetic Generalized Least Squares Regression The best model of prey mass evolution includes both carnivore The model including an interaction between body mass and mass and environment, although environment explains a small , environment (mass-environment) was the best supported model for percentage ( 8%) of variance in prey size. In spite of this, aquatic and terrestrial mammalian carnivores have different relationships minimum prey mass, maximum prey mass and prey mass range suggesting different optimal foraging strategies. Aquatic mamma- (Table 2). However, for the maximum prey mass and prey mass lian carnivores have no relationship between prey (neither range there was less than 2 DAIC units between the mass model minimum nor maximum) and predator body mass, unlike and the mass-environment model, suggesting that these models are terrestrial mammalian carnivores where there is a positive prey- equally supported. In both cases, the addition of environment predator (both minimum and maximum) body mass relationship. explained a limited amount of additional variance (3% for both In contrast to terrestrial predators, larger marine carnivores do not maximum prey and prey range) however for minimum prey mass, have to actively pursue prey with large body mass to meet their environment explained an additional 7% of variance. The energetic requirements [13]. The abundance of small-sized prey in phylogenetic signal (l) was consistently high for the mass model aquatic and marine environments (Fig. 2) is likely to have driven . for minimum, maximum and prey size range ( 0.7). Lambda these patterns in marine carnivores. As well as prey availability, it however, was mixed for the mass-environment models, where it is also important to note the effect of dimensionality on predator- was low (,0.5) for the maximum prey and prey range size, it was prey relationships and consumption rates. In 3D environments, it higher (0.62) for the minimum prey mass. has been demonstrated that consumption rates are higher, not We found there was no significant difference (confidence only the baseline rates but also the scaling exponent [34]. This not intervals overlap 0) in intercept between terrestrial and aquatic only has an impact on predator-prey relationships (e.g. larger carnivores for minimum (CI -2.22, 1.54; Fig. 1A), maximum consumer-resource body mass ratios) but also the strength of

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Table 2. Level of support for explanatory models of prey mass evolution in carnivorous mammals.

Prey mass Model DAICc DAICc 95% CI (upper, lower) Lambda Effect size (r)

Minimum b0+bmass x benvironment 0.0 NA 0.62 0.28

b0+bmass 5.8 4.99, 6.58 0.71 0.10

b0 5.5 4.78, 6.28 0.64 NA

Maximum b0+bmass x benvironment 0.0 NA 0.48 0.28

b0+bmass 0.9 0.04, 2.07 0.74 0.23

b0 4.8 4.23, 5.29 0.57 NA

Range b0+bmass x benvironment 0.0 NA 0.30 0.28

b0+bmass 1.6 0.23, 3.1 0.73 0.23

b0 5.3 4.54, 5.84 0.57 NA

Results are from phylogenetic least squares (PGLS) regression analyses computed for 1000 alternative resolutions of the mammalian phylogeny. Model terms include carnivore body mass (bmass), environment either aquatic or terrestrial (benvironment) and the intercept (b0). doi:10.1371/journal.pone.0106402.t002 interactions between trophic levels and the stability of the large-sized prey to maximise their energetic intake while community. minimising their expenditure [13]. In aquatic environments, In addition to the effect of differences in prey availability and particularly the marine system, the combination of the high dimensionality, there are differences in body size patterns across abundance of prey below 500 g, and the schooling nature of these aquatic and terrestrial carnivores. Marine mammals tend to have prey, makes it efficient for large carnivores to switch to feeding on larger body sizes compared to terrestrial mammals because of the smaller prey. relaxation of biomechanical constraints and increased thermoreg- The combined results from the PGLS (phylogenetic signal; l) ulatory constraints [35]. This has an effect on the predator-prey and the variance components analysis suggest that phylogenetic relationships, which tend to be more accentuated in the marine relatedness is a major influence of prey mass distribution patterns environment due to this disparity in body size between predators across carnivorous mammals. The driving factor behind this result and their prey. This has been illustrated by the presence of larger are the baleen whales, as they represent closely related species that predator-prey mass ratios in aquatic environments [14,36]. share a common feeding strategy. This group represents some of The lack of relationship between prey mass and predator mass the largest species today (up to 200 tonnes) and they feed on some could be because predator morphology is a large driver behind the of the smallest prey species (e.g. zooplankton). Baleen whales prey choice of aquatic mammalian carnivores. Morphology, such consist of species from Balaenopteridae and Balaenidae, and all as gape size, is a limiting factor for aquatic carnivores physically use filter feeding to capture their prey. There are also other unable to capture larger-sized prey (e.g. altered morphology of feeding strategies, such as pack hunting, that are generally shared appendages to aid with swimming rather than grasping). across taxonomic levels (i.e. at the family and genus level). Additionally, gape limitation in aquatic systems is believed to The most likely reason behind the scatter present in the impact the number of trophic levels that predators can feed from relationship between body mass and prey mass of terrestrial [37]. This is due to aquatic ecosystems being size structured, where carnivores (Fig. 1A–C), is related to carnivore feeding strategy. body size generally increases with trophic level [38]. Dentition is Terrestrial carnivores following two feeding strategies: large prey also likely to be important as carnivores with highly overlapping consumers or small prey consumers [13,42]. Terrestrial carnivore ranges often have different tooth morphology driven by compe- species weighing 21.5 kg or less feed on invertebrates and small tition for resources [39]. In the aquatic system mammals have vertebrate prey species (,10 kg) [42]. Above the 21.5 kg specialised feeding morphology including keratinized baleen plates threshold, carnivores must shift to feeding on large vertebrate for filter feeding (mysticete whales), multi-cuspidate interlocking prey to meet their energetic requirements [42]. Several carnivore teeth for krill sieving (e.g. crabeater and leopard seals), simple teeth species that feed upon large vertebrate prey have evolved with reduced serration for catching fish (piscivory e.g. dolphins), cooperative or pack hunting strategies, which confer several reduced teeth (e.g. Ross seal), rounded teeth (e.g. walrus) for eating benefits. One benefit of hunting in a pack is the minimisation of hard-shelled molluscs or even the loss of teeth (e.g. sperm whale the energy expended whilst hunting, but also maximising the size and beaked whales) for eating soft-bodied molluscs. Having of the prey captured and prey capture efficiency [43,44]. An specialised dentition can minimise resource competition; however increase in the size of the prey captured, energetic intake and it can leave these specialist carnivores vulnerable to higher hunting success also follows an increase in the number of extinction pressure if their prey populations were to collapse or individuals within the group [43]. Another advantage of hunting become extinct [40,41]. cooperatively is that individuals may gain other benefits including The addition of environment into the PGLS models explains increased body size or reproductive success. For example, greater variance and has the highest phylogenetic signal only for individual male fosa (Cryptoprocta ferox) that forage in groups minimum prey mass and not for models of maximum or range in tend to have larger body size, which also enables increased prey mass. This suggests there are differences between aquatic and competition and mating success [45]. terrestrial mammalian carnivores in the patterns of minimum prey There are various drivers influencing the patterns of prey mass body mass only. There are a great number of large aquatic consumed by carnivorous mammals. The size of prey chosen by mammalian carnivores feeding on small-sized prey whereas all carnivores is driven by the trade-off between energy acquisition large terrestrial mammalian carnivores are tied to feeding upon and expenditure, the available ecological niches and the dimen-

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Figure 1. Minimum prey mass (A), maximum prey mass (B) and prey mass range (C) as a function of carnivore body mass compared for terrestrial (green circles) and aquatic (blue circles) species. Each datum represents a species mean value. The solid green line is the phylogenetic regression of terrestrial mammals: (A) log(Y) = 1.13log(X)-3.3, (B) log(Y) = 1.12log(X)-1.01 and (C) log(Y) = 1.26log(X)-0.87. The solid blue line is the phylogenetic regression of aquatic mammals: (A) log(Y) = 20.03log(X)-2.96, (B) log(Y) = 0.11log(X)+-0.50 and (C) log(Y) = 20.07log(X)-0.02. Insert: intercept values and confidence intervals (CI) for aquatic (A) and terrestrial (T) species. Values were calculated from phylogenetic least squares (PGLS) regression analyses applied to 1000 alternative resolutions of the mammalian phylogeny. Error bars represent CI’s for the intercept values and are calculated using the standard error (SE) multiplied by 1.96. doi:10.1371/journal.pone.0106402.g001 sionality of the environment [34]. Foraging animals minimise their own mass will result in a mismatch of reaction time, where the energetic costs while maximising energetic gains by moving carnivore will respond at a slower rate than that of the prey and towards an optimal foraging strategy. As different species evolved will end with the prey escaping and the carnivore in an energetic different foraging strategies, driven by their evolutionary history deficit [9]. Additionally, while it would be ideal for all carnivores to and environmental influences, this shapes the patterns of prey feed on large-sized prey species (providing all carnivores could mass that are consumed by carnivores. Additionally, the mass of successfully capture large prey), it would be considerably costly prey utilised by carnivores is influenced by the ecological niches from an energetic perspective, not to mention the increased available to them and the resource encounter rate, both of which amount of time spent processing and ingesting the prey [13,49]. have an effect on the foraging strategy and the prey availability Modal prey mass is influenced by environmental drivers. Based [46–48]. on the data used in the study, the minimum prey mass range Carnivore energetic costs and prey density both influence the (0.0001 to 0.01 kg) is the most commonly utilised by carnivorous minimum prey mass consumed. Carnivores tend to feed on prey species from the aquatic and terrestrial environments. The type of above a certain mass due to the increasing inefficiency of feeding prey included within this weight range are invertebrates (aquatic on small prey, because a low capture rate will arise when and terrestrial), small mammals, fish and squid. The most common carnivores forage on prey much smaller than themselves [9]. maximum prey range differs between environments, with terres- However, this can be overcome in instances where prey species are trial carnivores predominantly feeding on prey between 1 to in high densities, as illustrated by marine carnivores (e.g. baleen 100 kg (i.e. small and large mammal prey), compared with 0.01 to whales) who can survive feeding upon prey less than 1 g (e.g. krill 1 kg for aquatic carnivores (i.e. invertebrate, squid and fish prey). and other invertebrates). This is further highlighted by the lower With the prey-weight categories of 0.0001–0.01 kg, 1–100 kg and minimum prey mass of aquatic carnivores compared to that of 0.01–1 kg being the most abundant, this suggests that feeding terrestrial carnivores (Fig. 2). within these ranges is a common foraging strategy across On the other end of the scale, maximum prey mass is driven by carnivores. Additionally, modal prey mass will also be driven by morphological constraints (i.e. gape and locomotion) and energetic the characteristics of the environment, where primary productivity costs. A carnivore feeding on prey considerably larger than their and trophic interactions will shape the size of prey available and

Table 3. Variance components analysis of prey mass across 108 carnivorous mammal species.

Prey Mass Variance Source Variance Component Total Variance Explained (%)

Minimum Total 3.17 100 Order 0.18 5.65 Family 1.13 35.65 Genus 0.52 16.65 Mass 1.23 38.83 Environment 0.11 3.43 Maximum Total 3.31 100 Order 0.43 13.79 Family 0.19 6.26 Genus 1.64 52.60 Mass 1.05 33.70 Environment ,0.01 ,0.01 Range Total 3.50 100 Order 0.40 11.33 Family 0.17 4.88 Genus 1.81 51.69 Mass 1.12 31.97 Environment ,0.01 ,0.01

Categories include minimum prey mass (smallest prey size consumed), maximum prey size (largest prey size consumed) and range of prey mass (maximum minus minimum prey mass). doi:10.1371/journal.pone.0106402.t003

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Figure 2. Distributions of the minimum prey mass for (A) terrestrial carnivorous mammals (green bars) and (B) aquatic carnivorous mammals (blue bars), and the maximum prey mass for (C) for terrestrial carnivorous mammals (green bars) and (D) for aquatic carnivorous mammals (blue bars). Silhouettes by uncredited and Chris Huh were downloaded from http://phylopic.org. doi:10.1371/journal.pone.0106402.g002 the abundance of these prey species. For example, productivity susceptibility of carnivores to population declines and the role of within the marine environment is driven by small, single-celled carnivores within ecosystems. organisms, allowing higher availability of productivity to consumers and higher predator-prey body mass ratios [14]. Supporting Information In summary, carnivorous mammals within our sample differ in the size of prey they consume and this is influenced by a suite of Table S1 Descriptive statistics for the prey mass distributions factors including phylogenetic relatedness, carnivore body mass, across 108 carnivorous mammals. the characteristics of the environment in which the carnivore (PDF) resides, and has evolved within, as well as carnivore energetics. Table S2 Descriptive statistics for the prey mass distributions Whilst phylogenetic relatedness and carnivore body mass are the across 51 carnivorous terrestrial mammals. dominant drivers of the prey mass consumed by mammals, the (PDF) physical environment has a role in the minimum-size prey that can Table S3 Descriptive statistics for the prey mass distributions be consumed. Previous research has shown that there is a positive across 57 carnivorous aquatic mammals. relationship between carnivore mass and the mass of their prey. (PDF) However, we have demonstrated that this is not the case for aquatic mammalian carnivores. Differences in environmental Appendix S1 Database of predator body mass values and prey characteristics including primary productivity and food-web body mass values, including sources. structure are driving the differences in prey mass consumed across (PDF) aquatic and terrestrial carnivores. Optimal foraging strategies in mammalian carnivores differ not Acknowledgments only across species but also physical environments, which needs to We would like to thank T. Ord for statistical advice. All silhouettes in be accounted for when thinking about carnivore behaviour. Figure 2 were downloaded from http://phylopic.org and are available for Gaining a better understanding of the relationship between reuse under the Public Domain Mark 1.0 license (Panthera) and the mammalian carnivores and their prey, predator strategies and Creative Commons Attribution-ShareAlike 3.0 Unported license (Euba- the factors driving these patterns, aids with predictions of the laena).

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Author Contributions materials/analysis tools: MAT TLR. Contributed to the writing of the manuscript: MAT TLR. Conceived and designed the experiments: MAT TLR. Performed the experiments: MAT. Analyzed the data: MAT. Contributed reagents/

References 1. Hayward MW, Kerley GIH (2005) Prey preferences of the lion (Panthera leo). 26. Symonds MR, Moussalli A (2011) A brief guide to model selection, multimodel Journal of Zoology 267: 309–322. inference and model averaging in behavioural ecology using Akaike’s 2. Hayward MW (2006) Prey preferences of the spotted hyaena (Crocuta crocuta) information criterion. Behavioral Ecology and Sociobiology 65: 13–21. and degree of dietary overlap with the lion (Panthera leo). Journal of Zoology 27. Burnham KP, Anderson DR (2002) Model Selection and Multimodal Inference: 270: 606–614. A practical Information-Theoretical Approach. New York: Springer. 3. Novaro AJ, Funes MnC, Susan Walker R (2000) Ecological extinction of native 28. Burnham KP, Anderson DR, Huyvaert KP (2011) AIC model selection and prey of a carnivore assemblage in Argentine Patagonia. Biological Conservation multimodel inference in behavioral ecology: some background, observations, 92: 25–33. and comparisons. Behavioral Ecology and Sociobiology 65: 23–35. 4. Johnson CN, Isaac JL, Fisher DO (2007) Rarity of a top predator triggers 29. Orme D, Freckleton R, Thomas G, Petzoldt T, Fritz S, et al. (2012) caper: continent-wide collapse of mammal prey: dingoes and marsupials in Australia. Comparative Analyses of Phylogenetics and Evolution in R. R package version Proceedings of the Royal Society B: Biological Sciences 274: 341–346. 0.5. http://CRAN.R-project.org/package = caper. 5. Daskalov GM, Grishin AN, Rodionov S, Mihneva V (2007) Trophic cascades 30. Freckleton RP, Harvey PH, Pagel M (2002) Phylogenetic Analysis and triggered by overfishing reveal possible mechanisms of ecosystem regime shifts. Comparative Data: A Test and Review of Evidence. The American Naturalist Proceedings of the National Academy of Sciences 104: 10518–10523. 160: 712–726. 6. Fortin D, Beyer HL, Boyce MS, Smith DW, Duchesne T, et al. (2005) Wolves 31. Felsenstein J (1985) Phylogenies and the Comparative Method. The American influence elk movements: behavior shapes a trophic cascade in Yellowstone Naturalist 125: 1–15. National Park. Ecology 86: 1320–1330. 32. Pinheiro JC, Bates DM (2000) Mixed-effects models in S and S-Plus. New York: 7. Tucker MA, Ord TJ, Rogers TL (2014) Evolutionary predictors of mammalian Springer. home range size: body mass, diet and the environment. Global Ecology and Biogeography: doi: 10.1111/geb.12194. 33. Bates D, Maechler M, Bolker B, Walker S (2013) lme4: Linear mixed-effects 8. Ottaviani D, Cairns SC, Oliverio M, Boitani L (2006) Body mass as a predictive models using Eigen and S4. R package version 1.0-5. http://CRAN.R-project. variable of home-range size among Italian mammals and birds. Journal of org/package = lme4. Zoology 269: 317–330. 34. Pawar S, Dell AI, Savage VM (2012) Dimensionality of consumer search space 9. Brose U (2010) Body-mass constraints on foraging behaviour determine drives trophic interaction strengths. Nature 486: 485–489. population and food-web dynamics. Functional Ecology 24: 28–34. 35. Smith FA, Lyons SK (2011) How big should a mammal be? A macroecological 10. Brandl R, Kristı´n A, Leisler B (1994) Dietary niche breadth in a local look at mammalian body size over space and time. Philosophical Transactions of community of passerine birds: an analysis using phylogenetic contrasts. the Royal Society B: Biological Sciences 366: 2364–2378. Oecologia 98: 109–116. 36. Brose U, Jonsson T, Berlow EL, Warren P, Banasek-Richter C, et al. (2006) 11. Costa GC, Vitt LJ, Pianka ER, Mesquita DO, Colli GR (2008) Optimal foraging Consumer–resource body-size relationships in natural food webs. Ecology 87: constrains macroecological patterns: body size and dietary niche breadth in 2411–2417. lizards. Global Ecology and Biogeography 17: 670–677. 37. Hairston JNG, Hairston SNG (1993) Cause-effect relationships in energy flow, 12. Sinclair ARE, Mduma S, Brashares JS (2003) Patterns of predation in a diverse trophic structure, and interspecific interactions. The American Naturalist 142: predator-prey system. Nature 425: 288–290. 379–411. 13. Carbone C, Teacher A, Rowcliffe JM (2007) The costs of carnivory. PLoS 38. Andersen KH, Beyer JE, Lundberg P (2009) Trophic and individual efficiencies Biology 5: 363–368. of size-structured communities. Proceedings of the Royal Society B: Biological 14. Riede JO, Brose U, Ebenman B, Jacob U, Thompson R, et al. (2011) Stepping Sciences 276: 109–114. in Elton’s footprints: a general scaling model for body masses and trophic levels 39. Jonathan Davies T, Meiri S, Barraclough TG, Gittleman JL (2007) Species co- across ecosystems. Ecology Letters 14: 169–178. existence and character divergence across carnivores. Ecology Letters 10: 146– 15. Scharf FS, Juanes F, Rountree RA (2000) Predator size-prey size relationships of 152. marine fish predators: interspecific variation and effects of ontogeny and body 40. Dell’Arte GL, Laaksonen T, Norrdahl K, Korpima¨ki E (2007) Variation in the size on trophic-niche breadth. Marine Ecology Progress Series 208: 229–248. diet composition of a generalist predator, the red fox, in relation to season and 16. Costa GC (2009) Predator Size, Prey Size, and Dietary Niche Breadth density of main prey. acta oecologica 31: 276–281. Relationships in Marine Predators. Ecology 90: 2014–2019. 41. Renaud S, Michaux J, Schmidt DN, Aguilar J-P, Mein P, et al. (2005) 17. King RB (2002) Predicted and observed maximum prey size – snake size Morphological evolution, ecological diversification and climate change in allometry. Functional Ecology 16: 766–772. rodents. Proceedings of the Royal Society B: Biological Sciences 272: 609–617. 18. Jones KE, Bielby J, Cardillo M, Fritz SA, O’Dell J, et al. (2009) PanTHERIA: a 42. Carbone C, Mace GM, Roberts SC, Macdonald DW (1999) Energetic species-level database of life history, ecology, and geography of extant and constraints on the diet of terrestrial carnivores. Nature 402: 286–288. recently extinct mammals. Ecology 90: 2648–2648. 43. Rasmussen GSA, Gusset M, Courchamp F, Macdonald DW (2008) Achilles’ 19. Fritz SA, Bininda-Emonds ORP, Purvis A (2009) Geographical variation in Heel of Sociality Revealed by Energetic Poverty Trap in Cursorial Hunters. The predictors of mammalian extinction risk: big is bad, but only in the tropics. American Naturalist 172: 508–518. Ecology Letters 12: 538–549. 44. Creel S (1997) Cooperative hunting and group size: assumptions and currencies. 20. Maddison WP, Maddison DR (2010) Mesquite: A modular system for evolutionary analysis. Version 2.74 ,http://mesquiteproject.org/mesquite/ ANimal behaviour 54: 1319–1324. mesquite.html.. 45. Lu¨hrs M-L, Dammhahn M, Kappeler P (2013) Strength in numbers: males in a 21. Caballero S, Jackson J, Mignucci-Giannoni AA, Barrios-Garrido H, Beltra´n- carnivore grow bigger when they associate and hunt cooperatively. Behavioral Pedreros S, et al. (2008) Molecular systematics of South American dolphins Ecology 24: 21–28. Sotalia: Sister taxa determination and phylogenetic relationships, with insights 46. Bromham L, Lanfear R, Cassey P, Gibb G, Cardillo M (2012) Reconstructing into a multi-locus phylogeny of the Delphinidae. Molecular Phylogenetics and past species assemblages reveals the changing patterns and drivers of extinction Evolution 46: 252–268. through time. Proceedings of the Royal Society B: Biological Sciences 279: 22. Kuhn TS, Mooers AØ, Thomas GH (2011) A simple polytomy resolver for 4024–4032. dated phylogenies. Methods in Ecology and Evolution 2: 427–436. 47. McCain CM, King SRB (2014) Body size and activity times mediate 23. R Core Team (2013) R: A Language and Environment for Statistical mammalian responses to climate change. Global Change Biology. Computing. R Foundation for Statistical Computing, Vienna, Austria: http:// 48. Moritz C, Patton JL, Conroy CJ, Parra JL, White GC, et al. (2008) Impact of a www.R-project.org/. century of climate change on small-mammal communities in Yosemite National 24. Drummond AJ, Suchard MA, Xie D, Rambaut A (2012) Bayesian phylogenetics Park, USA. Science 322: 261–264. with BEAUti and the BEAST 1.7. Molecular Biology and Evolution. 49. McCain CM, Colwell RK (2011) Assessing the threat to montane biodiversity 25. Johnson JB, Omland KS (2004) Model selection in ecology and evolution. from discordant shifts in temperature and precipitation in a changing climate. Trends in Ecology and Evolution 19: 101–108. Ecology Letters 14: 1236–1245.

PLOS ONE | www.plosone.org 8 August 2014 | Volume 9 | Issue 8 | e106402 Appendix 4

Supplementary information for Chapter 3

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Table S4.1 Database of predator body mass values and prey body mass values, including sources.

log10 log 10 log10 log10 Species Minimum Prey Mass Maximum Prey Prey Mass Predator Environment Prey Mass Souce Predator Diet Source (kg) Mass(kg) Range (kg) Mass (kg) Ross et al. 2004; Culik et al. Arctocephalus_gazella -3.222 0.647 0.647 2.532 Marine Ciaputa et al 2006 1994 Ross et al. 2004; Nel et al. Ciaputa et al 2006; Arctocephalus_tropicalis -3.222 -0.493 -0.493 2.520 Marine 2001 Robinson et al. 2003 Balaena_mysticetus -5.000 -0.088 -0.088 5.492 Marine Pomerleau et al. 2011 Pomerleau et al. 2011 Mizdalski 1988; Cardinale & Smout et al. 2007; Balaenoptera_acutorostrata -4.641 -1.301 -1.301 3.747 Marine Arrhernius, 2000 Weslawski et al. 2006 Mizdalski 1988; Cardinale & Balaenoptera_borealis -4.641 -1.301 -1.301 4.345 Marine Flinn et al. 2002 Arrhernius, 2000 Gomez-Gutierrez et al. Froese and Pauly, 2011; Balaenoptera_edeni -4.469 -0.426 -0.426 4.301 Marine 1996; Cervigon et al. 1992; Hart et al. 1973; Tershy Froese and Pauly, 2011 1992; Weslawski et al. 2006 Omori 1969; Ross et al. Balaenoptera_musculus -5.117 -3.222 -3.227 5.188 Marine Mizdalski 1988; Fiedler 1998 2004 Gomez-Gutierrez et al. Tershy et al. 1993; Balaenoptera_physalus -4.469 -1.564 -1.564 4.677 Marine 1996; Van Pelt et al. 1997 Weslawski et al 2006 Jefferson et al. 1993; Culik Berardius_arnuxii -1.538 -0.438 -0.474 3.845 Marine Walker 2002 2010 Berardius_bairdii -1.538 -0.438 -0.474 4.056 Marine Walker 2002 Walker et al. 2002 Callorhinus_ursinus -3.620 0.216 0.216 1.744 Marine Kurle et al. 2001 Kurle et al. 2001 Mizdalski 1988; Ross et al. Caperea_marginata -7.042 -3.222 -3.222 4.505 Marine Kemper et al. 2002 2004 Cephalorhynchus_commersonii -1.602 -1.387 -1.796 1.860 Marine Clarke et al .1994 Clarke et al .1994 Augustyn 1990; Eder et al. Sekiguchi et al. 1992; Elwin Cephalorhynchus_heavisidii -0.398 0.559 0.509 1.875 Marine 2005 et al. 2006; Eder et al. 2005 Cephalorhynchus_hectori -4.000 0.108 0.108 1.699 Marine Rayment & Webster 2009 Rayment & Webster 2009 Gomez-Gutierrez et al. Cystophora_cristata -4.469 0.845 0.845 3.565 Marine Hammil 2000 1996; Julshamn et al. 2004 Weslawski et al. 2006; Delphinapterus_leucas -3.301 -1.476 -1.483 4.176 Marine Dahl et al. 2000 Welch et al. 1993 Bykov 1983 ; Eder et al. Delphinus_delphis -1.602 0.163 0.156 1.899 Marine Romero et al. 2011 2005 Kvitek et al. 1992; Harrison Enhydra_lutris -2.564 1.079 1.079 2.439 Marine Wolt et al. 2012 et al. 1965 Erignathus_barbatus -4.301 -3.301 -3.347 2.447 Marine Weslawski et al. 2006 Hjelset et al. 1990

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Weslawski et al 2006; Eschrichtius_robustus -5.921 -1.367 -1.367 4.238 Marine Dunham et al. 2002 Pritchard et al. 1979 Cohen et al. 1981; Eubalaena_glacialis -7.523 -6.097 -6.114 4.602 Marine Mayo et al. 1990 Weslawski et al. 2006 Sinclair et al. 2002; Womble Eumetopias_jubatus -3.620 0.020 0.019 3.436 Marine Kurle et al. 2001 et al. 2006 Santos et al. 1997; Santos Feresa_attenuata -2.959 -0.112 -0.113 2.230 Marine Zerbini et al. 1997 et al. 1998 Globicephala_melas -2.347 0.357 0.356 3.097 Marine Jackson et al. 2000 Clarke et al. 1994 Hammill et al. 2000; Van Pelt et al. 1997; Kjesbu Weslawski et al. 2006; Halichoerus_grypus -2.921 0.643 0.643 2.920 Marine 1989 Vilhjálmsson et al. 2002; Van Pelt et al. 1997 Hydrurga_leptonyx -3.300 2.305 2.305 3.536 Marine Mizdalski 1988; Adam 2005 Hall Apsland et al. 2004 Hyperoodon_ampullatus -2.921 -0.072 -0.073 3.826 Marine Pusineri et al. 2007 Hooker et al. 1999 Kogia_breviceps -3.398 0.316 0.316 2.560 Marine West et al. 2009 West et al. 2009 Vilhjalmsson 2002; Kurle et Lagenorhynchus_obliquidens -1.658 -0.559 -0.595 2.079 Marine Morton et al. 2000 al. 2001 Casaux et al. 2006; Mizdalski 1988; Artigues et O'Droscoll et al. 2011; Kock Leptonychotes_weddellii -3.300 0.011 0.011 3.615 Marine al. 2003 et al 2008; Artigues et al. 2003 Lissodelphis_borealis -2.854 -1.097 -1.105 2.061 Marine Watanabe et al. 1999 Jefferson et al. 2003 Artigues et al. 2003; Mizdalski 1988; Artigues et Lobodon_carcinophaga -3.300 -0.919 -0.921 3.398 Marine Huckstadt et al. 2012; al. 2003 Mizdalski 1988 Miron et al. 1990; Kjesbu Reid et al. 1994; Noguchi et Lontra_canadensis -4.602 0.643 0.643 1.973 Marine 1989 al. 1991; Palace et al. 2001 Friedlaender et al. 2008; Megaptera_novaeangliae -4.653 -4.459 -4.903 5.518 Marine Mizdalski 1988; Omori 1969 Mizdalski 1988 Mesoplodon_carlhubbsi -1.097 -0.479 -0.599 3.176 Marine Clarke et al. 1998 MacLeod et al. 2003 Clarke et al. 1994; MacLeod Childress 1971; Nakamura et al. 2003; Belman et al. Mesoplodon_densirostris -3.854 0.362 0.362 3.000 Marine and Parin, 1993 1976; Ruiz-Capilla et al. 2001 Mesoplodon_layardii -1.449 -0.247 -0.275 3.114 Marine MacLeod et al. 2003 MacLeod et al. 2003 MacLeod et al. 2003; Beasly McLeod et al. 2003; Clarke Mesoplodon_mirus -1.983 -1.018 -1.067 3.146 Marine et al. 2013 et al. 1994 Mizdalski 1988; Kohler et al. Antonelis et al. 1987; Condit Mirounga_angustirostris -3.300 1.732 1.732 4.084 Marine 1995 et al. 1984

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Mirounga_leonina -3.300 -0.100 -0.100 4.182 Marine Mizdalski 1988; Slip 1995 Slip 1995 Weslawski et al. 1994; Monodon_monoceros -3.155 -0.509 -0.510 4.114 Marine Finley et al 1982 Lucassen et al. 2006 Ommatophoca_rossii -2.046 -0.060 -0.064 2.301 Marine Skinner et al. 1994 Skinner et al. 1994 Artigues et al. 2003; Jones Orcinus_orca 0.527 3.747 3.747 4.752 Marine Pitman et al. 2003 et al. 2009 Thompson et al. 1998; Eder Otaria_flavescens -3.699 -0.366 -0.366 3.371 Marine Clausen et al. 2003 et al. 2005; Clarke et al. 1994; Clausen et al. 2003 Phoca_vitulina -2.824 -0.697 -0.700 2.498 Marine Bowen et al. 1994 Bowen et al. 1994 Phocarctos_hookeri -2.699 0.787 0.786 3.107 Marine Meynier et al. 2009 Meynier et al. 2009 Smith 1963; Julshamn et al. Phocoena_phocoena -3.301 0.580 0.580 2.740 Marine Santos et al. 2004 2004 Physeter_catodon -1.301 0.248 0.236 4.428 Marine Gaskin et al. 1967 Gaskin et al. 1967 Santos et al. 1998; Bolasina Pontoporia_blainvillei -2.796 -0.824 -0.829 1.473 Marine Rodriguez et al. 2002 2006 Godoy et al. 2002; Lapa- Sotalia_fluviatilis -1.301 -0.767 -0.917 2.740 Marine Borobia et al. 1989 Guimaraes et al. 2005 Godoy et al. 2002; Lapa- Godoy et al. 2002; Lapa- Sotalia_guianensis -1.523 -0.767 -0.850 2.903 Marine Guimares et al. 2005; Di Guimaraes et al. 2005 Beneditto et al. 2007 Santos et al. 2001; Skog et Tursiops_truncatus -3.301 0.643 0.643 3.556 Marine Smith 1969; Kjesbut 1989 al. 2003; Kjesbu et al. 1989; Anderson et al. 2005 Taylor 1994; Jones et al. Ursus_maritimus -0.783 4.114 4.114 2.486 Marine Iverson et al. 2013 2009 Lowry et al. 1991; Hunter et Hunter et al. 1980; Kohler et Zalophus_californianus -1.745 1.732 1.732 2.927 Marine al. 1980; Williamson et al. al. 1995 1984; Quitral et al. 2009 Santos et al. 2001; Pusineri Pusineri et al. 2007; Lordan Ziphius_cavirostris -2.745 0.541 0.541 3.470 Marine et al. 2007; Xavier et al. et al. 2001 2002 Pusa_hispida -4.000 -2.000 -2.004 1.852 Marine Weslawski et al. 1994 Weslawski et al. 1994 Acinonyx_jubatus -0.301 2.740 2.740 1.699 Terrestrial Hayward et al. 2006 Hayward et al. 2006 Bassariscus_sumichrasti NA 0.363 NA -0.125 Terrestrial Jones et al. 2009 Estrada et al. 1985 Redford et al. 1984; Jones Canis_adustus -5.614 0.415 0.415 0.932 Terrestrial Atkinson et al. 2002 et al. 2009 Canis_aureus -1.714 -0.234 -0.249 0.995 Terrestrial Jones et al. 2009 Jaeger et al. 2007

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Canis_latrans -0.127 2.665 2.664 1.128 Terrestrial Jones et al. 2009 Theberge et al. 1989 Metz et al. 2012; Nowak et Canis_lupus 0.582 2.796 2.793 1.633 Terrestrial Jones et al. 2009 al. 2011 Canis_simensis -1.135 2.791 2.791 1.161 Terrestrial Jones et al. 2009 Marino et al . 2010 Wolcott 1978; Jones et al. Cerdocyon_thous -1.602 -0.006 -0.017 1.114 Terrestrial Gatti et al. 2006 2009 Crocuta_crocuta 1.021 3.186 3.183 0.760 Terrestrial Jones et al. 2009 Hayward et al. 2006 Paoletti et al. 2000; Jones et Eira_barbara -2.699 -0.125 -0.126 1.813 Terrestrial Presley et al 2000 al. 2009 Varma et al. 1990; Jones et Caracal_caracal -3.457 1.194 1.194 0.650 Terrestrial Avenant et al. 2002 al. 2009 Brooks et al. 1996. ; Kutt Kutt 2012; Paltridge et al. Felis_catus -3.631 0.544 0.544 0.531 Terrestrial 2012 1997 de los Sanots Gomez 2013; Mukherjee et al. 2004; Felis_chaus -3.545 -0.860 -0.861 0.817 Terrestrial Jones et al. 2009 Mohammad 2008 Ray et al. 2001; Sanchez et Genetta_tigrina NA 0.687 NA 0.332 Terrestrial Jones et al. 2009 al. 2009 Gulo_gulo -2.147 2.682 2.682 1.333 Terrestrial Jones et al. 2009 Myhre et al. 1975 Meza et al. 2002; Jones et Leopardus_pardalis -2.097 0.602 0.601 1.000 Terrestrial Wang 2002 al. 2009 Leopardus_wiedii -1.367 0.579 0.574 0.560 Terrestrial Jones et al. 2009 Wang 2002 Defoliarte 1995; Jones et al. Leptailurus_serval -3.222 -0.652 -0.653 1.079 Terrestrial Thiel 2011 2009 Lycaon_pictus 0.246 2.750 2.749 1.431 Terrestrial Jones et al. 2009 Hayward et al. 2006 Lynx_canadensis -1.714 1.258 1.257 1.009 Terrestrial Jones et al. 2009 Poole 2003 Lynx_lynx -2.037 2.682 2.682 1.477 Terrestrial Jones et al. 2009 Odden et al. 2006 Lynx_pardinus NA 2.382 NA 1.043 Terrestrial Jones et al. 2009 Gil-Sanchez et al. 2006 Lynx_rufus -2.180 0.460 0.459 1.055 Terrestrial Robertson et al. 1982 Delibes et al. 1988 Speiser et al. 2001; Jones et Martes_foina -2.866 1.676 1.676 0.255 Terrestrial Bakaloudis et al. 2011 al. 2009 Clark et al. 1973; Jones et Martes_martes -3.721 2.167 2.167 0.394 Terrestrial Caryl 2008 al. 2009 Martes_pennanti -1.714 2.167 2.167 0.502 Terrestrial Jones et al. 2009 Giuliano et al. 1989 Ma et al. 1993; Jones et al. Virgos et al. 2004; Meles_meles -2.727 -1.058 -1.067 0.972 Terrestrial 2009 Goszczynski et al.2000 Defoliarte 1995; Dejean et Mungos_mungo -3.222 -2.456 -2.538 0.158 Terrestrial Rood 1975 al. 2001

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Mustela_erminea -3.921 -1.467 -1.469 -0.568 Terrestrial Martinoli et al. 2001 Martinoli et al. 2001 Mustela_frenata -1.738 0.407 0.404 -0.823 Terrestrial Jones et al. 2009 Wilson et al. 1996 Mustela_nivalis -1.684 -1.500 -1.963 -1.055 Terrestrial Jones et al. 2009 Jedrzejewska et al. 1995 Mustela_putorius -2.585 -1.570 -1.614 -0.092 Terrestrial Jones et al. 2009 Lode 1997 Coutts et al. 1973; Wright Neovison_vison -3.509 0.272 0.272 0.037 Terrestrial Jedrzejewska et al. 2001 1990 Defoliarte 1995; Jones et al. Nasua_nasua -3.222 0.041 0.041 0.672 Terrestrial Alves-Costa et al. 2004 2009 Ma et al. 1993; Jones et al. Nyctereutes_procyonoides -2.727 -1.358 -1.376 0.783 Terrestrial Baltrunaite 2002 2009 Otocyon_megalotis -3.222 -3.117 -3.785 0.618 Terrestrial Defoliarte 1995; Kuntzsch et al. 1992 Panthera_leo 1.653 2.740 2.703 2.312 Terrestrial Hayward et al. 2005 Hayward et al. 2005 Panthera_onca 0.305 2.464 2.461 1.924 Terrestrial Jones et al. 2009 Weckel et al. 2006 Panthera_pardus 0.000 2.635 2.634 1.685 Terrestrial Hayward et al. 2006 Hayward et al. 2006 Panthera_tigris 0.699 3.435 3.434 2.049 Terrestrial Hayward et al. 2012 Hayward et al. 2012 Smith 2002; Delapane et al. Procyon_lotor -3.883 0.653 0.653 1.028 Terrestrial Schoonover et al. 1951 1999 Proteles_cristata -3.222 -2.405 -2.476 1.000 Terrestrial Defoliarte 1995; Punzo 1998 deVries et al. 2011 Puma_concolor -0.445 1.325 1.318 1.954 Terrestrial Jones et al. 2009 Moreno et al. 2006 Defoliarte 1995; Jones et al. Munoz-Garcia et al 2005; Spilogale_putorius -3.222 0.082 0.082 -0.222 Terrestrial 2009 Crabb 1941 Magnarelli 1983; Jones et al. Michiner et al. 2004; Sovada Taxidea_taxus -5.319 -0.488 -0.488 0.935 Terrestrial 2009 et al 1999 Defoliarte 1995; Jones et al. Vulpes_cana -3.222 0.311 0.311 -0.013 Terrestrial Geffen et al. 1992 2009 Ring et al. 1980; Jones et al. Haim et al. 2004; Elmhagen Vulpes_lagopus -4.169 2.038 2.038 0.698 Terrestrial 2009 et al. 2000 Legaspi et al. 1993; Jones et Munoz-Garcia et al. 2005; Vulpes_macrotis -4.171 0.477 0.477 0.653 Terrestrial al. 2009 List et al. 2003 Defoliarte 1995; Jones et al. Vulpes_ruepellii -3.222 -1.155 -1.159 0.512 Terrestrial Williams et al. 2002 2009 Vulpes_velox -1.803 1.676 1.676 0.322 Terrestrial Jones et al. 2009 Sovada et al. 2001 Warburg 1968; Jones et al. Vulpes_vulpes -3.635 -1.071 -1.072 0.814 Terrestrial Jedrzejewski et al. 1992 2009

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Table S4.1 References

Adam, P.J. (2005) Lobodon carcinophaga. Mammalian Species, 1-14. Alves-Costa, C.P., Da Fonseca, G.A.B. & Christófaro, C. (2004) Variation in the diet of the brown-nosed coati (Nasua nasua) in southeastern Brazil. Journal of Mammalogy, 85, 478-482. Anderson, K.J. & Jetz, W. (2005) The broad-scale ecology of energy expenditure of endotherms. Ecology Letters, 8 , 310-318. Antonelis Jr, G.A., Lowry, M.S., DeMaster, D.P. & Fiscus, C.H. (1987) Assessing northern elephant seal feeding habits by stomach lavage. Marine Mammal Science, 3 , 308-322. Artigues, B., Morales-Nin, B. & Balguerias, E. (2003) Fish length-weight relationships in the Weddell Sea and Bransfield Strait. Polar Biology, 26, 463-467. Atkinson, R.P.D., Macdonald, D.W. & Kamizola, R. (2002) Dietary opportunism in side-striped jackals Canis adustus Sundevall. Journal of Zoology, 257, 129- 139. Augustyn, C. (1990) Biological studies on the chokker squid Loligo vulgaris reynaudii (Cephalopoda; Myopsida) on spawning grounds off the south-east coast of South Africa. South African Journal of Marine Science, 9 , 11-26. Avenant, N.L. & Nel, J.A.J. (2002) Among habitat variation in prey availability and use by caracal Felis caracal. Mammalian Biology - Zeitschrift für Säugetierkunde, 67 , 18-33. Bakaloudis, D.E., Vlachos, C.G., Papakosta, M.A., Bontzorlos, V.A. & Chatzinikos, E.N. (2012) Diet Composition and Feeding Strategies of the Stone Marten (Martes foina) in a Typical Mediterranean Ecosystem. The Scientific World Journal, 2012 Baltrūnaitė, L. (2002) Diet composition of the red fox (Vulpes vulpes L.), pine marten (Martes martes L.) and raccoon dog (Nyctereutes procyonoides Gray) in clay plain landscape, Lithuania. Acta Zoologica Lituanica, 12 , 362-368. Beasley, I., Cherel, Y., Robinson, S., Betty, E. & Gales, R. (2013) Pygmy sperm whale (Kogia breviceps) stranding record in Tasmania, Australia, and diet of a single specimen. Papers and Proceedings of the Royal Society of Tasmania (ed by, p. 25. Belman, B.W. & Childress, J.J. (1976) Circulatory adaptations to the oxygen minimum layer in the bathypelagic mysid Gnathophausia ingens. Biological Bulletin, 15-37. Bolasina, S.N. (2006) Cortisol and hematological response in Brazilian codling, Urophycis brasiliensis (Pisces, Phycidae) subjected to anesthetic treatment. Aquaculture International, 14 , 569-575. Borobia, M. & Barros, N.B. (1989) Notes on the diet of marine Sotalia fluviatilis. Marine Mammal Science, 5 , 395-399. Bowen, W. & Harrison, G. (1994) Offshore diet of grey seals Halichoerus grypus near Sable Island, Canada. Marine ecology progress series. Oldendorf, 112, 1-11. Brooks, S.J., Calver, M.C., Dickman, C.R., Meathrel, C.E. & Bradley, J.S. (1996) Does intraspecific variation in the energy value of a prey species to its predators matter in studies of ecological energetics? A case study using insectivorous vertebrates. Ecoscience, 3 , 247-251. Bykov, V.P. (1983) Marine Fishes: Chemical composition and processing properties. Amerind Publishing Co. Pvt. , New Delhi. Cardinale, M. & Arrhenius, F. (2000) Decreasing weight-at-age of Atlantic herring (Clupea harengus) from the Baltic Sea between 1986 and 1996: a statistical analysis. ICES Journal of Marine Science: Journal du Conseil, 57, 882-893. Caryl, F.M. (2008) Pine marten diet and habitat use within a managed coniferous forest. PhD Thesis, University of Sterling, Crawley, Casaux, R., Baroni, A. & Ramon, A. (2006) The diet of the weddell seal Leptonychotes weddellii at the Danco Coast, Antarctic Peninsula. Polar Biology, 29, 257-262.

209

Cervigón, F., Cipriani, R., Fischer, W., Garibaldi, L., Hendrickx, M., Lemus, A., Márquez, R., Poutiers, J., Robaina, G. & Rodríguez, B. (1992) Fichas FAO de identificación de especies para los fines de la pesca: Guía de campo de las especies comerciales marinas y de aguas salobres de la costa septentrional de Sur América. Rome, FAO, 513p, Childress, J.J. (1971) Respiratory adaptations to the oxygen minimum layer in the bathypelagic mysid Gnathophausia ingens. The Biological Bulletin, 141, 109-121. Ciaputa, P. & Siciński, J. (2006) Seasonal and annual changes in Antarctic fur seal (Arctocephalus gazella) diet in the area of Admiralty Bay, King George Island, South Shetland Islands. Polish Polar Research, 27, 171-184. Clark, M.G., Bloxham, D.P., Holland, P.C. & Lardy, H.A. (1973) Estimation of the fructose diphosphatase-phosphofructokinase substrate cycle in the flight muscle of< italic> Bombus affinis. Biochem. J, 134, 589-597. Clarke, M. & Goodall, N. (1994) Cephalopods in the diets of three odontocete cetacean species stranded at Tierra del Fuego, Globicephala melaena (Traill, 1809), Hyperoodon planifrons (Flower, 1882) and Cephalorhynchus commersonii (Lacepede, 1804). Antarctic Science-Institutional Subscription, 6, 149-154. Clarke, M. & Roeleveld, M. (1998) Cephalopods in the diet of sperm whales caught commercially off Durban, South Africa. South African Journal of Marine Science, 20 , 41-45. Clausen, A. & Pütz, K. (2003) Winter diet and foraging range of gentoo penguins (Pygoscelis papua) from Kidney Cove, Falkland Islands. Polar Biology, 26, 32-40. Cohen, R. & Lough, R. (1981) Length-weight relationships for several copepods dominant in the Georges Bank-Gulf of Maine area. J. Northw. Atl. Fish. Sci, 2, 47-52. Condit, R. & Le Boeuf, B.J. (1984) Feeding habits and feeding grounds of the northern elephant seal. Journal of Mammalogy, 281-290. Coutts, R.A., Fenton, M.B. & Glen, E. (1973) Food Intake by Captive Myotis lucifugus and Eptesicus fuscus (Chiroptera: Vespertilionidae). Journal of Mammalogy, 54, 985-990. Crabb, W.D. (1941) Food habits of the prairie spotted skunk in southeastern Iowa. Journal of Mammalogy, 22 , 349-364. Culik, B. (2010) Odontocetes. The toothed whales: "Berardius bairdii". UNEP/CMS Secretariat, Bonn, Germany. Accessed 5 November 2012. Culik, B., Wilson, R. & Bannasch, R. (1994) Underwater swimming at low energetic cost by pygoscelid penguins. Journal of Experimental Biology, 197, 65-78. Dahl, T.M., Lydersen, C., Kovacs, K.M., Falk-Petersen, S., Sargent, J., Gjertz, I. & Gulliksen, B. (2000) Fatty acid composition of the blubber in white whales (Delphinapterus leucas). Polar Biology, 23 , 401-409. de los Santos Gómez, A. (2013) Indicating assemblage vulnerability and resilience in the face of climate change by means of adult ground beetle length– weight allometry over elevation strata in Tenerife (Canary Islands). Ecological Indicators, 34, 204-209. de Vries, J.L., Prik, C.W.W., Bateman, P.W., Cameron, E.Z. & Dalerum, F. (2011) Extension of the diet of an extreme foraging specialist, the aardwolf (Proteles cristata). African Zoology, 46 , 194-196. DeFoliart, G.R. (1995) Edible insects as minilivestock. Biodiversity & Conservation, 4 , 306-321. Dejean, A., Suzzoni, J. & Schatz, B. (2001) Behavioral adaptations of an African ponerine ant in the capture of millipedes. Behaviour, 138, 981-996. Delaplane, K.S. & Hood, W.M. (1999) Economic threshold for Varroa jacobsoni Oud. in the southeastern USA. Apidologie, 30, 383-395. Delibes, M., Zapata, S.C., Blázquez, M.C. & Rodríguez-Estrella, R. (1997) Seasonal food habits of bobcats (Lynx rufus) in subtropical Baja California Sur, Mexico. Canadian Journal of Zoology, 75, 478-483.

210

Di Beneditto, A.P.M. & Siciliano, S. (2007) Stomach contents of the marine tucuxi dolphin (Sotalia guianensis) from Rio de Janeiro, south-eastern Brazil. Journal of the Marine Biological Association of the United Kingdom, 87, 253-254. Dunham, J.S. & Duffus, D.A. (2002) Foraging patterns of gray whales in central Clayoquot Sound, British Columbia, Canada. Marine Ecology Progress Series, 223, 299-310. Eder, E. & Lewis, M. (2005) Proximate composition and energetic value of demersal and pelagic prey species from the SW Atlantic Ocean. Marine Ecology Progress Series, 291, 43-52. Elmhagen, B., Tannerfeldt, M., Verucci, P. & Angerbjörn, A. (2000) The arctic fox (Alopex lagopus): an opportunistic specialist. Journal of Zoology, 251, 139- 149. Elwin, S., Meyer, M.A., Best, P.B., Kotze, P.G.H., Thronton, M. & Swanson, S. (2006) Range and movements of female Heaviside's dolphins (Cephalorhynchus heavisidii), as determined by satellite-linked telemetry. Journal of Mammalogy, 87 , 866-877. Estrada, A. & Coates-Estrada, R. (1985) A preliminary study of resource overlap between howling monkeys (Alouatta palliata) and other arboreal mammals in the tropical rain forest of Los Tuxtlas, Mexico. American Journal of Primatology, 9 , 27-37. Fiedler, P.C., Reilly, S.B., Hewitt, R.P., Demer, D., Philbrick, V.A., Smith, S., Armstrong, W., Croll, D.A., Tershy, B.R. & Mate, B.R. (1998) Blue whale habitat and prey in the California Channel Islands. Deep Sea Research Part II: Topical Studies in Oceanography, 45, 1781-1801. Finley, K.J. & Gibb, E.J. (1982) Summer diet of the narwhal (Monodon monoceros) in Pond Inlet, northern Baffin Island. Canadian Journal of Zoology, 60, 3353-3363. Flinn, R.D., Trites, A.W., Gregr, E.J. & Perry, R.I. (2002) Diets of fin, sei, and sperm whales in British Columbia: an analysis of commercial whaling records, 1963–1967. Marine Mammal Science, 18 , 663-679. Friedlaender, A.S., Fraser, W.R., Patterson, D., Qian, S.S. & Halpin, P.N. (2008) The effects of prey demography on humpback whale (Megaptera novaeangliae) abundance around Anvers Island, Antarctica. Polar Biology, 31 , 1217-1224. Froese, R. & Pauly, D. (2011) FishBase. World Wide Web electronic publication. www.fishbase.org Accessed 15 January 2014. Gaskin, D.E. & Cawthorn, M.W. (1967) Diet and feeding habits of the sperm whale (Physeter catodon L.) in the Cook Strait region of New Zealand. New Zealand Journal of Marine and Freshwater Research, 1, 156-179. Gatti, A., Bianchi, R., Rosa, C.R.X. & Mendes, S.L. (2006) Diet of two sympatric carnivores, Cerdocyon thous and Procyon cancrivorus, in a restinga area of Espirito Santo State, Brazil. Journal of Tropical Ecology, 22, 227-230. Geffen, E., Hefner, R., MacDonald, D.W. & Ucko, M. (1992) Diet and foraging behavior of Blanford's foxes, Vulpes cana, in Israel. Journal of Mammalogy, 395-402. Gil-Sánchez, J., Ballesteros-Duperón, E. & Bueno-Segura, J. (2006) Feeding ecology of the Iberian lynxLynx pardinus in eastern Sierra Morena (Southern Spain). Acta Theriologica, 51, 85-90. Giuliano, W.M., Litvaitis, J.A. & Stevens, C.L. (1989) Prey Selection in Relation to Sexual Dimorphism of Fishers (Martes pennanti) in New Hampshire. Journal of Mammalogy, 70 , 639-641. Godoy, E.A.S., Almeida, T.C.M. & Zalmon, I.R. (2002) Fish assemblages and environmental variables on an artificial reef north of Rio de Janeiro, Brazil. ICES Journal of Marine Science: Journal du Conseil, 59, S138-S143. Gómez-Gutiérrez, J., De Silva-Dávila, R. & Lavaniegos-Espejo, B. (1996) Growth production of the euphausiid Nyctiphanes simplex on the coastal shelf off Bahía Magdalena, Baja California Sur, México. Marine ecology progress series. Oldendorf, 138 , 309-314. Goszczyński, J., Jedrzejewska, B. & Jedrzejewski, W. (2000) Diet composition of badgers (Meles meles) in a pristine forest and rural habitats of Poland

211

compared to other European populations. Journal of Zoology, 250 , 495-505. Haim, A., Saarela, S., Hohtola, E. & Zisapel, N. (2004) Daily rhythms of oxygen consumption, body temperature, activity and melatonin in the Norwegian lemming Lemmus lemmus under northern summer photoperiod. Journal of Thermal Biology, 29 , 629-633. Hall-Aspland, S. & Rogers, T.L. (2004) Summer diet of leopard seals (Hydrurga leptonyx) in Prydz Bay, Eastern Antarctica. Polar Biology, 27, 729-734. Hammill, M. & Stenson, G. (2000) Estimated prey consumption by harp seals (Phoca groenlandica), hooded seals (Cystophora cristata), grey seals (Halichoerus grypus) and harbour seals (Phoca vitulina) in Atlantic Canada. Journal of Northwest Atlantic Fishery Science, 26 , 1-24. Harrison, F. & Martin, A. (1965) Excretion in the cephalopod, Octopus dofleini. Journal of Experimental Biology, 42, 71-98. Hart, J.L. (1973) Pacific fishes of Canada. Fisheries Research Board of canada(Bull. 180), Ottawa, Canada. 749, 1973. Hayward, M.W. (2006) Prey preferences of the spotted hyaena (Crocuta crocuta) and degree of dietary overlap with the lion (Panthera leo). Journal of Zoology, 270, 606-614. Hayward, M.W. & Kerley, G.I.H. (2005) Prey preferences of the lion (Panthera leo). Journal of Zoology, 267 , 309-322. Hayward, M., Jędrzejewski, W. & Jędrzewska, B. (2012) Prey preferences of the tiger Panthera tigris. Journal of Zoology, Hayward, M., Hofmeyr, M., O'brien, J. & Kerley, G. (2006) Prey preferences of the cheetah (Acinonyx jubatus)(Felidae: Carnivora): morphological limitations or the need to capture rapidly consumable prey before kleptoparasites arrive? Journal of Zoology, 270 , 615-627. Hayward, M.W., O'Brien, J., Hofmeyr, M. & Kerley, G.I. (2006) Prey preferences of the African wild dog Lycaon pictus (Canidae: Carnivora): ecological requirements for conservation. Journal of Mammalogy, 87, 1122-1131. Hayward, M., Henschel, P., O'brien, J., Hofmeyr, M., Balme, G. & Kerley, G. (2006) Prey preferences of the leopard (Panthera pardus). Journal of Zoology, 270, 298-313. Hjelset, A., Andersen, M., Gjertz, I., Lydersen, C. & Gulliksen, B. (1999) Feeding habits of bearded seals (Erignathus barbatus) from the Svalbard area, Norway. Polar Biology, 21, 186-193. Hooker, S.K. & Baird, R.W. (1999) Deep–diving behaviour of the northern bottlenose whale, Hyperoodon ampullatus (Cetacea: Ziphiidae). Proceedings of the Royal Society of London. Series B: Biological Sciences, 266, 671-676. Hückstädt, L., Burns, J., Koch, P., McDonald, B., Crocker, D. & Costa, D. (2012) Diet of a specialist in a changing environment: the crabeater seal along the western Antarctic Peninsula. Marine Ecology Progress Series, 455, 287. Hunter, J. & Macewicz, B.J. (1980) Sexual maturity, batch fecundity, spawning frequency, and temporal pattern of spawning for the northern anchovy, Engraulis mordax, during the 1979 spawning season. CalCOFI Rep, 21, 139-149. Iversen, M., Aars, J., Haug, T., Alsos, I.G., Lydersen, C., Bachmann, L. & Kovacs, K.M. (2013) The diet of polar bears (Ursus maritimus) from Svalbard, Norway, inferred from scat analysis. Polar biology, 36, 561-571. Jackson, G.D., Buxton, N.G. & George, M.J. (2000) Diet of the southern opah Lampris immaculatus on the Patagonian Shelf; the significance of the squid Moroteuthis ingens and anthropogenic plastic. Marine Ecology Progress Series, 206 , 261-271. Jaeger, M.M., Haque, E., Sultana, P. & Bruggers, R.L. (2007) Daytime cover, diet and space-use of golden jackals (Canis aureus) in agro-ecosystems of Bangladesh. Mammalia, 71, 1-10. Jędrzejewska, B., Sidorovich, V.E., Pikulik, M.M. & Jędrzejewska, W. (2001) Feeding habits of the otter and the American mink in Białowieża Primeval Forest (Poland) compared to other Eurasian populations. Ecography, 24 , 165-180. Jędrzejewski, W. & Jędrzejewska, B. (1992) Foraging and diet of the red fox Vulpes vulpes in relation to variable food resources in Biatowieza National Park, Poland. Ecography, 15, 212-220.

212

Jędrzejewski, W., Jędrzejewska, B. & Szymura, L. (1995) Weasel Population Response, Home Range, and Predation on Rodents in a Deciduous Forest in Poland. Ecology, 76, 179-195. Jefferson, T.A., Leatherwood, S. & Webber, M.A. (2003) FAO species identification guide. Marine mammals of the world., Rome. Jones, K.E., Bielby, J., Cardillo, M., Fritz, S.A., O'Dell, J., Orme, C.D.L., Safi, K., Sechrest, W., Boakes, E.H., Carbone, C., Connolly, C., Cutts, M.J., Foster, J.K., Grenyer, R., Habib, M., Plaster, C.A., Price, S.A., Rigby, E.A., Rist, J., Teacher, A., Bininda-Emonds, O.R.P., Gittleman, J.L., Mace, G.M., Purvis, A. & Michener, W.K. (2009) PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology, 90 , 2648-2648. Julshamn, K., Lundebye, A.K., Heggstad, K., Berntssen, M. & Boe, B. (2004) Norwegian monitoring programme on the inorganic and organic contaminants in fish caught in the Barents Sea, Norwegian Sea and North Sea, 1994–2001. Food additives and contaminants, 21, 365-376. Kemper, C.M. (2002) Distribution of the pygmy right whale, Caperea marginata, in the Australasian region. Marine Mammal Science, 18, 99-111. Kjesbu, O. (1989) The spawning activity of cod, Gadus morhua L. Journal of fish biology, 34, 195-206. Kock, K.H., Pshenichnov, L., Jones, C.D., Gröger, J. & Riehl, R. (2008) The biology of the spiny icefish Chaenodraco wilsoni Regan, 1914. Polar Biology, 31, 381-393. Kohler, N.E., Casey, J.G. & Turner, P.A. (1995) Length-weight relationships for 13 species of sharks from the western North Atlantic. Fishery Bulletin, 93, 412- 418. Kuntzsch, V. & Nel, J. (1992) Diet of bat-eared foxes Otocyon megalotis in the Karoo. Koedoe-African Protected Area Conservation and Science, 35, 37-48. Kurle, C.M. & Worthy, G.A.J. (2001) Stable isotope assessment of temporal and geographic differences in feeding ecology of northern fur seals (Callorhinus ursinus) and their prey. Oecologia, 126, 254-265. Kutt, A.S. (2012) Feral cat (Felis catus) prey size and selectivity in north-eastern Australia: implications for mammal conservation. Journal of Zoology, 287, 292-300. Kvitek, R., Oliver, J., DeGange, A. & Anderson, B. (1992) Changes in Alaskan soft-bottom prey communities along a gradient in sea otter predation. Ecology, 413-428. Lapa-Guimarães, J., de Felício, P.E. & Guzmán, E.S.C. (2005) Chemical and microbial analyses of squid muscle (Loligo plei) during storage in ice. Food chemistry, 91 , 477-483. Legaspi, J.C. & O'Neil, R.J. (1993) Life history of Podisus maculiventris given low numbers of Epilachna varivestis as prey. Environmental entomology, 22, 1192-1200. List, R. & Macdonald, D.W. (2003) Home range and habitat use of the kit fox (Vulpes macrotis) in a prairie dog (Cynomys ludovicianus) complex. Journal of Zoology, 259, 1-5. Lodé, T. (1997) Trophic status and feeding habits of the European Polecat Mustela putorius L. 1758. Mammal Review, 27, 177-184. Lordan, C., Collins, M.A., Key, L.N. & Browne, E.D. (2001) The biology of the ommastrephid squid, Todarodes sagittatus, in the north-east Atlantic. Journal of the Marine Biological Association of the UK, 81 , 299-306. Lowry, M.S., Francis, M., Yochem, P.K., Stewart, B.S. & Heath, C.B. (1991) Seasonal and annual variability in the diet of California sea lions, Zalophus californianus, at San Nicolas Island, California, 1981− 86. Fish. Bull, 89, 331-336. Lucassen, M., Koschnick, N., Eckerle, L.G. & Pörtner, H.-O. (2006) Mitochondrial mechanisms of cold adaptation in cod (Gadus morhua L.) populations from different climatic zones. Journal of Experimental Biology, 209 , 2462-2471. Ma, W.-c. & Bodt, J. (1993) Differences in toxicity of the insecticide chlorpyrifos to six species of earthworms (Oligochaeta, Lumbricidae) in standardized soil

213

tests. Bulletin of Environmental Contamination and Toxicology, 50 , 864-870. MacLeod, C., Santos, M. & Pierce, G. (2003) Review of data on diets of beaked whales: evidence of niche separation and geographic segregation. Journal of the Marine Biological Association of the UK, 83 , 651-665. Magnarelli, L.A. (1983) Nectar sugars and caloric reserves in natural populations of Aedes canadensis and Aedes stimulans (Diptera: Culicidae). Environmental entomology, 12, 1482-1486. Marino, J., Mitchell, R. & Johnson, P.J. (2010) Dietary specialization and climatic-linked variations in extant populations of Ethiopian wolves. African Journal of Ecology, 48 , 517-525. Martinoli, A., Preatoni, D.G., Chiarenzi, B., Wauters, L.A. & Tosi, G. (2001) Diet of stoats (Mustela erminea) in an Alpine habitat:The importance of fruit consumption in summer. Acta Oecologica, 22, 45-53. Mayo, C.A. & Marx, M.K. (1990) Surface foraging behaviour of the North Atlantic right whale, Eubalaena glacialis, and associated zooplankton characteristics. Canadian Journal of Zoology, 68 , 2214-2220. Metz, M.C., Smith, D.W., Vucetich, J.A., Stahler, D.R. & Peterson, R.O. (2012) Seasonal patterns of predation for gray wolves in the multi-prey system of Yellowstone National Park. Journal of Animal Ecology, 81, 553-563. Meynier, L., Mackenzie, D.D.S., Duignan, P.J., Chilvers, B.L. & Morel, P.C.H. (2009) Variability in the diet of New Zealand sea lion (Phocarctos hookeri) at the Auckland Islands, New Zealand. Marine Mammal Science, 25 , 302-326. Meza, A.d.V., Meyer, E.M. & González, C.A.L. (2002) Ocelot (Leopardus Pardalis) Food Habits in a Tropical Deciduous Forest of Jalisco, Mexico. American Midland Naturalist, 148, 146-154. Michener, G.R. (2004) Hunting techniques and tool use by North American badgers preying on Richardson's ground squirrels. Journal of Mammalogy, 85, 1019-1027. Miron, G. & Desrosiers, G. (1990) Distributions and population structures of two intertidal estuarine polychaetes in the lower St. Lawrence Estuary, with special reference to environmental factors. Marine Biology, 105, 297-306. Mizdalski, E. (1988) Weight and length data of zooplankton in the Weddell Sea in austral spring 1986 (ANT V/3). Berichte zur Polarforschung (Reports on Polar Research), 55 Mohammad, M.K. (2008) The Parasitic Fauna And The Food Habits Of The Wild Jungle Cat Felis chaus Furax De Winton, 1898 In Iraq. Bull. Iraq nat. Hist. Mus, 10, 65-78. Moreno, R.S., Kays, R.W. & Samudio Jr, R. (2006) Competitive release in diets of ocelot (Leopardus pardalis) and puma (Puma concolor) after jaguar (Panthera onca) decline. Journal of Mammalogy, 87, 808-816. Morton, A. (2000) Occurrence, Photo‐Identification and Prey of Pacific White‐Sided Dolphins (Lagenorhyncus obliquidens) in the Broughton Archipelago, Canada 1984–1998. Marine Mammal Science, 16 , 80-93. Mukherjee, S., Goyal, S.P., Johnsingh, A.J.T. & Leite Pitman, M.R.P. (2004) The importance of rodents in the diet of jungle cat (Felis chaus), caracal (Caracal caracal) and golden jackal (Canis aureus) in Sariska Tiger Reserve, Rajasthan, India. Journal of Zoology, 262, 405-411. Muñoz, G.A. & Williams, J.B. (2005) Basal metabolic rate in carnivores is associated with diet after controlling for phylogeny. Physiological and Biochemical Zoology, 78 , 1039-1056. Myhre, R. & Myrberget, S. (1975) Diet of Wolverines (Gulo gulo) in Norway. Journal of Mammalogy, 56, 752-757. Nakamura, I. & Parin, N.V. (1993) An Annotated and Illustrated Catalogue of the Snake Mackerels, Snoeks, Escolars, Gemfishes, Sackfishes, Domine, Oilfish, Cutlassfishes, Scabbardfishes, Hairtails, and Frostfishes Known to Date. FAO Fisheries Synopsis No. 125, Vol. 15,

214

Nel, D., Lutjeharms, J., Pakhomov, E., Ansorge, I., Ryan, P. & Klages, N. (2001) Exploitation of mesoscale oceanographic features by grey-headed albatross Thalassarche chrysostoma in the southern Indian Ocean. Marine Ecology Progress Series, 217 , 15-26. Noguchi, G.E. & Hesselberg, R.J. (1991) Parental transfer of organic contaminants to young-of-the-year spottail shiners, Notropis hudsonius. Bulletin of environmental contamination and toxicology, 46, 745-750. Nowak, S., Mysłajek, R.W., Kłosińska, A. & Gabryś, G. (2011) Diet and prey selection of wolves (Canis lupus) recolonising Western and Central Poland. Mammalian Biology - Zeitschrift für Säugetierkunde, 76, 709-715. Odden, J., Linnell, J.C. & Andersen, R. (2006) Diet of Eurasian lynx, Lynx lynx, in the boreal forest of southeastern Norway: the relative importance of livestock and hares at low roe deer density. European Journal of Wildlife Research, 52 , 237-244. O'Driscoll, R.L., Macaulay, G.J., Gauthier, S., Pinkerton, M. & Hanchet, S. (2011) Distribution, abundance and acoustic properties of Antarctic silverfish (Pleuragramma antarcticum) in the Ross Sea. Deep Sea Research Part II: Topical Studies in Oceanography, 58, 181-195. Omori, M. (1969) Weight and chemical composition of some important oceanic zooplankton in the North Pacific Ocean. Marine Biology, 3, 4-10. Palace, V.P., Allen-Gil, S.M., Brown, S.B., Evans, R.E., Metner, D.A., Landers, D.H., Curtis, L.R., Klaverkamp, J.F., Baron, C.L. & Lyle Lockhart, W. (2001) Vitamin and thyroid status in arctic grayling (Thymallus arcticus) exposed to doses of 3, 3′, 4, 4′-tetrachlorobiphenyl that induce the phase I enzyme system. Chemosphere, 45 , 185-193. Paltridge, R., Gibson, D. & Edwards, G. (1997) Diet of the Feral Cat (Felis catus) in Central Australia. Wildlife Research, 24 , 67-76. Paoletti, M.G., Dufour, D.L., Cerda, H., Torres, F., Pizzoferrato, L. & Pimentel, D. (2000) The Importance of Leaf- and Litter-Feeding Invertebrates as Sources of Animal Protein for the Amazonian Amerindians. Proceedings: Biological Sciences, 267, 2247-2252. Pitman, R.L. & Ensor, P. (2003) Three forms of killer whales (Orcinus orca) in Antarctic waters. Journal of Cetacean Research and Management, 5, 131-140. Pomerleau, C., Ferguson, S.H. & Walkusz, W. (2011) Stomach contents of bowhead whales (Balaena mysticetus) from four locations in the Canadian Arctic. Polar Biology, 34, 615-620. Poole, K.G. (2003) A review of the Canada lynx, Lync canadensis, in Canada. The Canadian Field- Naturalist, 117, 360-376. Presley, S.J. (2000) Eira barbara. Mammalian species, 1-6. Pritchard, A. & Eddy, S. (1979) Lactate formation in Callianassa californiensis and Upogebia pugettensis (Crustacea: Thalassinidea). Marine Biology, 50 , 249- 253. Punzo, F. (1998) The effects of reproductive status on sprint speed in the solifuge, Eremobates marathoni (Solifugae, Eremobatidae). Journal of Arachnology, 113-116. Pusineri, C., Magnin, V., Meynier, L., Spitz, J., Hassani, S. & Ridoux, V. (2007) Food and feeding ecology of the common dolphin (Delphinus delphis) in the oceanic Northeast Atlantic and comparison with its diet in neritic areas. Marine Mammal Science, 23 , 30-47. Quitral, V., Donoso, M.L., Ortiz, J., Herrera, M.V., Araya, H. & Aubourg, S.P. (2009) Chemical changes during the chilled storage of Chilean jack mackerel (Trachurus murphyi): Effect of a plant-extract icing system. LWT-Food Science and Technology, 42 , 1450-1454. Ray, J. & Sunquist, M. (2001) Trophic relations in a community of African rainforest carnivores. Oecologia, 127, 395-408. Rayment, W. & Webster, T. (2009) Observations of Hector's dolphins (Cephalorhynchus hectori) associating with inshore fishing trawlers at Banks Peninsula, New Zealand. Redford, K.H. & Dorea, J.G. (1984) The nutritional value of invertebrates with emphasis on ants and termites as food for mammals. Journal of Zoology, 203, 385-395. Reid, D., Code, T., Reid, A. & Herrero, S. (1994) Food habits of the river otter in a boreal ecosystem. Canadian Journal of Zoology, 72, 1306-1313.

215

Ring, R.A. & Tesar, D. (1980) Cold-hardiness of the arctic beetle, Pytho americanus Kirby Coleoptera, Pythidae (Salpingidae). Journal of Insect Physiology, 26, 763-774. Robertson, H., Nicolson, S. & Louw, G. (1982) Osmoregulation and temperature effects on water loss and oxygen consumption in two species of African scorpion. Comparative Biochemistry and Physiology Part A: Physiology, 71, 605-609. Robinson, S., Goldsworthy, S., Van den Hoff, J. & Hindell, M. (2003) The foraging ecology of two sympatric fur seal species, Arctocephalus gazella and Arctocephalus tropicalis, at Macquarie Island during the austral summer. Marine and Freshwater Research, 53 , 1071-1082. Rodríguez, D., Rivero, L. & Bastida, R. (2002) Feeding ecology of the franciscana (Pontoporia blainvillei) in marine and estuarine waters of Argentina. Latin American Journal of Aquatic Mammals, 1, 77-94. Romero, M.A., Dans, S.L., García, N., Svendsen, G.M., González, R. & Crespo, E.A. (2011) Feeding habits of two sympatric dolphin species off North Patagonia, Argentina. Marine Mammal Science, 28, 364-377. Rood, J.P. (1975) Population dynamics and food habits of the banded mongoose. African Journal of Ecology, 13 , 89-111. Ross, R.M., Quetin, L.B., Newberger, T. & Oakes, S.A. (2004) Growth and behavior of larval krill (Euphausia superba) under the ice in late winter 2001 west of the Antarctic Peninsula. Deep Sea Research Part II: Topical Studies in Oceanography, 51 , 2169-2184. Ruiz-Capillas, C. & Moral, A. (2001) Residual effect of CO2 on hake (Merluccius merluccius L.) stored in modified and controlled atmospheres. European Food Research and Technology, 212, 413-420. Sánchez, M., Rodrigues, P., Ortuño, V. & Herrero, J. (2009) Feeding habits of the genet Genetta genetta in an Iberian continental wetland. Hystrix, the Italian Journal of Mammalogy, 19 Santos, R. & Haimovici, M. (1997) Reproductive biology of winter-spring spawners of Illex argentinus (Cephalopoda: Ommastrephidae) off southern Brazil. Scientia Marina(Barcelona), 61, 53-64. Santos, R. & Haimovici, M. (1998) Trophic relationships of the long-finned squid Loligo sanpaulensis on the southern Brazilian shelf. South African Journal of Marine Science, 20, 81-91. Santos, M., Pierce, G., Herman, J., Lopez, A., Guerra, A., Mente, E. & Clarke, M. (2001) Feeding ecology of Cuvier's beaked whale (Ziphius cavirostris): a review with new information on the diet of this species. JMBA-Journal of the Marine Biological Association of the United Kingdom, 81, 687-694. Santos, M., Pierce, G., Learmonth, J., Reid, R., Ross, H., Patterson, I., Reid, D. & Beare, D. (2004) Variability in the diet of harbor porpoises (Phocoena phocoena) in Scottish waters 1992–2003. Marine Mammal Science, 20, 1-27. Schoonover, L.J. & Marshall, W.H. (1951) Food Habits of the Raccoon (Procyon lotor hirtus) in North-Central Minnesota. Journal of Mammalogy, 32, 422-428. Sekiguchi, K., Klages, N. & Best, P. (1992) Comparative analysis of the diets of smaller odontocete cetaceans along the coast of southern Africa. South African Journal of Marine Science, 12, 843-861. Sinclair, E.H. & Zeppelin, T.K. (2002) Seasonal and spatial differences in diet in the western stock of Steller sea lions (Eumetopias jubatus). Journal of Mammalogy, 83, 973-990. Skinner, J. & Klages, N. (1994) On some aspects of the biology of the Ross seal Ommatophoca rossii from King Haakon VII Sea, Antarctica. Polar Biology, 14, 467-472. Skog, T.E., Hylland, K., Torstensen, B.E. & Berntssen, M.H.G. (2003) Salmon farming affects the fatty acid composition and taste of wild saithe Pollachius virens L. Aquaculture Research, 34, 999-1007. Slip, D.J. (1995) The diet of southern elephant seals (Mirounga leonina) from Heard Island. Canadian Journal of Zoology, 73, 1519-1528. Smith, R.I. (1963) A comparison of salt loss rate in three species of brackish-water nereid polychaetes. Biological Bulletin, 125, 332-343.

216

Smith, P.W. (2002) The Fishes of Illinois. University of Illinois Press, Illinois, pg 152. Smout, S. & Lindstrøm, U. (2007) Multispecies functional response of the minke whale Balaenoptera acutorostrata based on small-scale foraging studies. Marine Ecology Progress Series, 341 , 277-291. Sovada, M.A., Roaldson, J.M. & Sargeant, A.B. (1999) Foods of American badgers in west-central Minnesota and southeastern North Dakota during the duck nesting season. The American midland naturalist, 142 , 410-414. Speiser, B., Zaller, J.G. & Neudecker, A. (2001) Size-specific susceptibility of the pest slugs Deroceras reticulatum and Arion lusitanicus to the nematode biocontrol agent Phasmarhabditis hermaphrodita. BioControl, 46, 311-320. Taylor, J.R. (1994) Changes in body mass and body reserves of breeding Little Auks (Alle alle L.). Polish Polar Res, 123 , 149-168. Tershy, B.R. (1992) Body size, diet, habitat use, and social behavior of Balaenoptera whales in the Gulf of California. Journal of Mammalogy, 477-486. Tershy, B.R., Acevedo, G., Breese, D. & Strong, C.S. (1993) Diet and feeding behavior of fin and Bryde's whales in the central Gulf of California, Mexico. Rev Inv Cient, 1, 31-38. Theberge, J.B. & Wedeles, C.H.R. (1989) Prey selection and habitat partitioning in sympatric coyote and red fox populations, southwest Yukon. Canadian Journal of Zoology, 67 , 1285-1290. Thiel , C. (2011) Ecology and population status of the Serval Leptailurus serval (Schriber, 1776) in Zambia. PhD Thesis, Universitäts-und Landesbibliothek, Bonn, Thompson, D., Duck, C.D., McConnell, B.J. & Garrett, J. (1998) Foraging behaviour and diet of lactating female southern sea lions (Otaria flavescens) in the Falkland Islands. Journal of Zoology, 246 , 135-146. Van Pelt, T.I., Piatt, J.F., Lance, B.K. & Roby, D.D. (1997) Proximate composition and energy density of some North Pacific forage fishes. Comparative Biochemistry and Physiology Part A: Physiology, 118, 1393-1398. Varma, M., Heller-Haupt, A., Trinder, P. & Langi, A. (1990) Immunization of guinea-pigs against Rhipicephalus appendiculatus adult ticks using homogenates from unfed immature ticks. Immunology, 71, 133. Vilhjálmsson, H. (2002) Capelin (Mallotus villosus) in the Iceland–East Greenland–Jan Mayen ecosystem. ICES Journal of Marine Science: Journal du Conseil, 59, 870-883. Virgós, E., Mangas, J.G., Blanco-Aguiar, J.A., Garrote, G., Almagro, N. & Viso, R.P. (2004) Food habits of European badgers (Meles meles) along an altitudinal gradient of Mediterranean environments: a field test of the earthworm specialization hypothesis. Canadian Journal of Zoology, 82 , 41-51. Walker, W.A., Mead, J.G. & Brownell, R.L. (2002) Diets of Baird's beaked whales, Berardius bairdii, in the southern sea of Okhotsk and off the pacific coast of Honshu, Japan. Marine Mammal Science, 18 , 902-919. Wang, E. (2002) Diets of Ocelots (Leopardus pardalis), Margays (L. wiedii), and Oncillas (L. tigrinus) in the Atlantic Rainforest in Southeast Brazil. Studies on Neotropical Fauna and Environment, 37, 207-212. Warburg, M. (1968) Simultaneous measurement of body temperature and water loss in isopods. Crustaceana, 14 , 39-44. Watanabe, H., Moku, M., Kawaguchi, K., Ishimaru, K. & Ohno, A. (1999) Diel vertical migration of myctophid fishes (Family Myctophidae) in the transitional waters of the western North Pacific. Fisheries Oceanography, 8 , 115-127. Weckel, M., Giuliano, W. & Silver, S. (2006) Jaguar (Panthera onca) feeding ecology: distribution of predator and prey through time and space. Journal of Zoology, 270, 25-30. Welch, H.E., Crawford, R.E. & Hop, H. (1993) Occurrence of Arctic cod (Boreogadus saida) schools and their vulnerability to predation in the Canadian High Arctic. Arctic, 331-339.

217

Węsławski, J.M., Kwaśniewski, S., Stempniewicz, L. & Błachowiak-Samołyk, K. (2006) Biodiversity and energy transfer to top trophic levels in two contrasting Arctic fjords. Polish Polar Research, 27 , 259-278. Williams, J.B., Lenain, D., Ostrowski, S., Tieleman, B.I. & Seddon, P.J. (2002) Energy expenditure and water flux of Rüppell’sfoxes in Saudi Arabia. Physiological and Biochemical Zoology, 75, 479-488. Williamson, N.J. & Traynor, J.J. (1984) In situ target-strength estimation of Pacific whiting (Merluccius productus) using a dual-beam transducer. Journal du Conseil, 41, 285-292. Wilson, T.M. & Carey, A.B. (1996) Observations of Weasels in Second-Growth Douglas-Fir Forests in the Puget Trough, Washington. Northwestern Naturalist, 77, 35-39. Wolcott, T.G. (1978) Ecological rôle of ghost crabs, Ocypode quadrata (Fabricius) on an ocean beach: Scavengers or predators? Journal of Experimental Marine Biology and Ecology, 31, 67-82. Wolt, R.C., Gelwick, F.P., Weltz, F. & Davis, R.W. (2012) Foraging behavior and prey of sea otters in a soft-and mixed-sediment benthos in Alaska. Mammalian Biology-Zeitschrift für Säugetierkunde, Womble, J.N. & Sigler, M.F. (2006) Seasonal availability of abundant, energy-rich prey influences the abundance and diet of a marine predator, the Steller sea lion Eumetopias jubatus. Marine Ecology Progress Series, 325 , 281-293. Wright, R.M. (1990) Aspects of the ecology of bream, Abramis brama (L.), in a gravel pit lake and the effects of reducing the population density. Journal of Fish Biology, 37, 629-634. Xavier, J., Rodhouse, P., Purves, M., Daw, T., Arata, J. & Pilling, G. (2002) Distribution of cephalopods recorded in the diet of the Patagonian toothfish (Dissostichus eleginoides) around South Georgia. Polar Biology, 25 , 323-330. Zerbini, A.N. & Santos, M. (1997) First record of the pygmy killer whale Feresa attenuata (Gray, 1874) for the Brazilian coast. Aquatic Mammals, 23 , 105-110.

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Appendix 5

Supplementary information for Chapter 4

219

Table S5.1 Daily energetic expenditure (DEE), mean daily energetic intake (DEI) and mean prey body size for 107 carnivorous mammal species.

DEE DEI Predator Predator Mass Prey Mass Prey Mass Species Habitat (log10 (log10 Mass DEE sources DEI sources (log10) (log10) -1 -1 Sources kJ day ) kJ day ) Sources Nagy et al. Nagy et al. Arctocephalus galapagoensis marine 1.573 3.679 1999 1999 Ciaputa et al. Staniland et Boyd and Arctocephalus_gazella marine 1.532 -1.798 5.288 2006 al. 2010 Croxall 1996 Ciaputa et al. DeBruyn et al. Arctocephalus_tropicalis marine 1.520 -1.337 2006, Robinson 2009 et al. 2002 Heide- Pomerleau et al. Balaena_mysticetus marine 4.492 -3.885 Jorgensen et 2011 al. 2007 Smout et al. Sigujonsson Jones et al. Nordoy et al. Balaenoptera_acutorostrata marine 3.747 -3.996 5.672 5.850 2007, Weslawski & Vikingsson 2009 1995 et al. 2006 1997 Weslawski et al. Sigujonsson Jones et al. Balaenoptera_borealis marine 4.345 -4.756 6.272 2006, Kenney et & Vikingsson 2009 al. 1997 1997 Froese & Pauly 2011, Hart et al. Jones et al. Balaenoptera_edeni marine 4.301 -0.667 1973, Tershy 2009 1992, Weslawski et al. 2006 Sigujonsson Mizdalski 1988, Jones et al. Balaenoptera_musculus marine 5.188 -3.304 6.668 & Vikingsson Fiedler 1998 2009 1997 Tershey et al. Sigujonsson Jones et al. Balaenoptera_physalus marine 4.677 -4.077 6.511 1973, Weslawski & Vikingsson 2009 et al. 2006 1997 Jefferson et al. Jones et al. Berardius_arnuxii marine 3.845 -0.174 1993, Culik 2010 2009 Walker et al. Jones et al. Berardius_bairdii marine 4.056 -0.174 2002 2009 Jones et al. Nagy et al. Callorhinus_ursinus marine 1.744 -0.549 4.558 Kurle et al. 2001 2009 1999

220

Mizdalski 1988, Jones et al. Caperea_marginata marine 4.505 -5.116 Jefferson 1993 2009 Jones et al. Cephalorhynchus_commersonii marine 1.860 -0.555 Clarke et al. 1994 2009 Elwin et al. 2006, Elwin et al. Cephalorhynchus_heavisidii marine 1.875 -0.323 Eder et al. 2005 2006 Meynier et al. Jones et al. Cephalorhynchus_hectori marine 1.699 -0.136 2009, Wilcox et 2009 al. 2001 Vilhjamsson Bajzak et al. Cystophora_cristata marine 2.565 -3.896 2002, Hammil 2009 2000 Dahl et al. 2000, Hobbs et al. Delphinapterus_leucas marine 4.176 -3.924 Weslawski et al. 2005 2006 Eder et al. 2005, Jones et al. Delphinus_delphis marine 1.899 -0.470 Romero et al. 2009 2012, Wolt et al. 2012, Kvitek et al. Ralls et al. Finerty et al. Enhydra_lutris marine 1.439 -0.731 4.280 1992, Mc Mahon 1996 2009 1979, Menge 1979, Weslawski et al. Jones et al. Erignathus_barbatus marine 2.447 -3.666 2006, Hjelset et 2009 al. 1990 Pritchard et al. 1979, Weslawski et al. 2006, Eschrichtius_robustus marine 4.238 -6.019 Lockyer 1976 Dunham et al. 2002, Griffen et al. 2004 Baumgartner et al. 2005, Eubalaena_glacialis marine 4.602 -7.056 Weslawski et al. Kenney 1986

2006, Mayo et al. 1990 Kurle et al. 2001, Merrick et al. Eumetopias_jubatus marine 3.436 -0.658 Sinclair et al. 1997 2002, Van Pelt et 221

al. 1997, Smith et al. 1988 Zerbini et al. Stuart & Feresa_attenuata marine 2.230 -0.638 1997, Santos et Stuart 2001 al. 1997, Heide Sigujonsson Globicephala_melas marine 3.097 -0.706 5.556 Clarke et al. 1994 jorgenson & Vikingsson

2002 1997 Hammill et al. 2000, Weslawski et al. 2006, Sjoberg and Ronald et al. Halichoerus_grypus marine 1.920 1.006 4.299 Vihjlmsson et al. Ball 2000 1984 2002, Van Pelt et al. 1997 Hall Apsland et al. 2004, Hydrurga_leptonyx marine 2.536 1.711 Rogers et al. Mizdalski 1988, Adam 2005 Hooker et al. Hyperoodon_ampullatus marine 3.826 -1.014 5.663 Ainley et al. 2004 Noren 2000 2002 Kogia_breviceps marine 2.560 -0.709 West et al. 2009 Noren 2000

Sigujonsson & Sigujonsson Lagenorhynchus acutus marine 2.279 5.112 Vikingsson & Vikingsson

1997 1997 Sigujonsson & Sigujonsson Lagenorhynchus albirostris marine 2.352 5.164 Vikingsson & Vikingsson

1997 1997 Morton et al. 2000, Lagenorhynchus_obliquidens marine 2.079 -1.003 Vilhjamsson Noren 2000

2002, Kurle et al. 2001 Casaux et al. 2008, O'Droscoll et al. 2011, Kock Bornemann et Leptonychotes_weddellii marine 2.615 -0.846 et al. 2008, al. 2003 Artigues et al. 2003 Jefferson et al. Lissodelphis_borealis marine 2.061 -1.311 Noren 2000 1993, Clarke et 222

al. 1994, Watanabe et al. 1999 Artigues et al. Bornemann et 2003, Huckstadt al. 2005, Lobodon_carcinophaga marine 2.398 -1.815 4.849 Adam 2005 et al. 2012, Southwell Mizdalski 1988 2003 Reid et al. 1994, Noguchi et al. Blundell et al. Lontra_canadensis marine 0.973 -1.007 1991, Palace et 2000 al. 2001 Friedlaender et Sigujonsson Dall Rosa et Megaptera_novaeangliae marine 4.518 -3.300 6.420 al. 2008, & Vikingsson al. 2008 Mizdalski 1988 1997 Clarke et al. 1998, Clarke et Jefferson Mesoplodon_carlhubbsi marine 3.176 -0.732 al. 1994, 2008 MacLeod et al. 2003 Clarke et al. 1994, MacLeod et al. 2003, Jefferson Mesoplodon_densirostris marine 3.000 -0.770 Belman et al. 2008 1976, Ruiz- Capilla et al. 2001 MacLeod et al. Jefferson Mesoplodon_layardii marine 3.114 -0.749 2003 2008 McLeod et al. Reidenberg & Mesoplodon_mirus marine 3.146 -1.824 2003, Clarke et Laitman 2009 al. 1994 Clarke et al. 1994, Eder et al. 2005, Seibel et LeBoeuf et al. Anderson et Sakamoto et Mirounga_angustirostris marine 3.084 -0.787 4.489 4.288 al. 1997, Glaser 2000 al. 2005 al. 1989 2010, Antonelis et al. 1987, Condit et al. 1984 Glaser 2010, Bornemann et Boyd and Mirounga_leonina marine 3.182 -0.108 5.076 Artigues et al. al. 2003 Croxall 1996

223

2003, Ainley et al. 2008, Cherel et al. 2004, Slip 1995 Goodman- Goodman- Monachus schauinslandi marine 2.312 4.316 Lowe et al. Lowe et al.

1999 1999 Zumholz et al. 2007, Finley et al. Dietz et al. Monodon_monoceros marine 3.114 -0.849 1982, Van Pelt et 2008 al. 1997, Koie et al. 2008 Nagy et al. Nagy et al. Neophoca cinerea marine 1.922 4.597 1999 1999 Skinner et al. Southwell et Ommatophoca_rossii marine 2.301 -0.526 1994 al. 2005 Artigues et al. 2003, Pitman et al. 2003, Ford et al. 1998, Andrews et al. Baird and Orcinus_orca marine 3.752 3.957 5.464 Bornemann et al. 2008 Dill. 1996 2005, Southwell 2003, Jones et al. 2009 Thompson et al. 1998, Eder et al. Campagna et Otaria_flavescens marine 2.371 -0.683 2005, Clarke et al. 2001 al. 1994, Clausen et al. 2003 Hammill et Phoca groenlandica marine 2.114 4.434 Innes 1981 al. 2010 Vilhjamsson Smith et al. Nagy et al. Phoca_vitulina marine 1.498 -3.896 4.720 2002, Weslawski 2006 1999 2006 Maynier et al. Auge et al. Anderson et Phocarctos_hookeri marine 2.107 0.104 4.721 2009 2011 al. 2005 Santos et al. Sigujonsson 2004, Andersen Johnston et Otani et al. Phocoena_phocoena marine 1.740 -1.063 4.060 4.622 & Vikingsson & Beyer 2005, al. 2005 2002 1997 Julshamn et al. 224

2004 Gaskin et al. Physeter_catodon marine 4.428 -0.082 Lockyer 1976 1967 Sigujonsson & Sigujonsson Physeter macrocephalus marine 4.536 5.739 Vikingsson & Vikingsson

1997 1997 Naya et al. 2002, Rodriguez et al. 2002, Amado et Danilewicz et Pontoporia_blainvillei marine 1.473 -1.082 al. 2006, Santos al. 2002 et al. 1998, Bolasina 2006 Naya et al. 2002,Godoy et al. 2002, Borobia et Flores et al. Sotalia_fluviatilis marine 1.740 -0.880 al. 1989, Lapa- 2004 Guimaraes et al. 2005 Godoy et al. 2002, Lapa- Guimares et al. Oshima et al. Sotalia_guianensis marine 1.903 -0.522 2005, Di 2010 Beneditto et al. 2007 Santos et al. 2001, Skog et al. 2003, Kjesbu et Gubbins et al. Tursiops_truncatus marine 2.556 0.222 al. 1989, 2002 Anderson et al. 2005 Carbone et al. Ferguson et Ursus_maritimus marine 2.408 2.106 2007 al. 1999 Lowry et al. 1991, Hunter et al. Williams et al. Zalophus_californianus marine 1.927 -0.421 4.263 1980, Williamson Kuhn 2006 2007 et al. 1984, Quitral et al. 2009 Santos et al. Ziphius_cavirostris marine 3.470 -1.040 2001, Pusineri et Noren 2000

al. 2007, Xavier 225

et al. 2002 Kelt and Carbone et al. Carbone et Acinonyx_jubatus terrestrial 1.699 1.528 4.729 VanVuren 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et al. Bassariscus_sumichrasti terrestrial -0.125 -1.523 2.674 VanVuren 2007 2007 2001 Kelt and Carbone et al. Carbone et Canis_adustus terrestrial 0.932 -0.108 4.013 VanVuren 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et Canis_aureus terrestrial 0.995 -0.770 3.787 VanVuren 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et al. Carbone et Canis_latrans terrestrial 1.128 1.613 3.654 3.711 VanVuren 2007 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et al. Carbone et Canis_lupus terrestrial 1.547 1.910 4.248 4.660 VanVuren 2007 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et Canis_simensis terrestrial 1.161 -0.721 3.896 VanVuren 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et Caracal_caracal terrestrial 1.045 1.217 3.836 VanVuren 2007 al. 2007 2001 Kelt and Carbone et al. Cerdocyon_thous terrestrial 0.760 -0.952 VanVuren 2007 2001 Kelt and Carbone et Crocuta_crocuta terrestrial 1.813 2.031 4.547 Carbone 2007 VanVuren al. 2007 2001 Kelt and McNab 1995, Eira_barbara terrestrial 0.650 0.570 VanVuren Milton et al. 1976 2001 Kelt and Felis_catus terrestrial 0.530 -1.222 Kutt 2012 VanVuren

2001 Carbone et al. Kelt and Carbone et Felis_chaus terrestrial 0.817 -0.032 3.357 2007 VanVuren al. 2007

226

2001 Kelt and Genetta_tigrina terrestrial 0.330 0.214 Ray et al. 2001 VanVuren

2001 Reimers et al. 1983, Kelt and Gulo_gulo terrestrial 1.330 1.934 Christiansen VanVuren

2006, Kelt and 2001 VanVuren 2001 Kelt and Carbone et Leopardus_pardalis terrestrial 1.000 0.260 3.680 Carbone 2007 VanVuren al. 2007 2001 Kelt and Leopardus_wiedii terrestrial 0.560 0.260 Wang 2002 VanVuren

2001 Kelt and Carbone et al. Carbone et Leptailurus_serval terrestrial 1.025 -1.301 3.766 VanVuren 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et al. Carbone et Lycaon_pictus terrestrial 1.398 1.528 4.184 4.400 VanVuren 2007 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et Lynx_canadensis terrestrial 0.972 0.146 3.800 VanVuren 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et Lynx_lynx terrestrial 1.398 1.301 4.118 VanVuren 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et al. Lynx_pardinus terrestrial 1.040 0.176 3.520 VanVuren 2007 2007 2001 Swihart 1986, Kelt and Lynx_rufus terrestrial 1.050 -0.178 Djawden et al. VanVuren

1988 2001 Dwarakanath Kelt and Martes_foina terrestrial 0.255 -2.455 1971; Reichle VanVuren

1968 2001 Kelt and Carbone et al. Carbone et Martes_martes terrestrial 0.140 -1.301 3.114 VanVuren 2007 al. 2007 2001

227

Kelt and Carbone et al. Carbone et al. Martes_pennanti terrestrial 0.646 -0.108 3.063 VanVuren 2007 2007 2001 Kelt and Carbone et al. Carbone et Meles_meles terrestrial 0.972 -1.523 3.615 VanVuren 2007 al. 2007 2001 Carbone et al. Carbone et al. Carbone et Mungos_mungo terrestrial 0.972 -2.000 2.908 2007 2007 al. 2007 Kelt and Carbone et al. Carbone et Mustela_erminea terrestrial -0.568 -1.301 2.544 VanVuren 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et Mustela_frenata terrestrial -0.823 -1.699 2.326 VanVuren 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et al. Carbone et Mustela_nivalis terrestrial -1.050 -1.523 2.334 3.079 VanVuren 2007 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et Mustela_putorius terrestrial -0.046 -1.000 3.181 VanVuren 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et Mustela_vison terrestrial 0.037 -1.000 2.836 VanVuren 2007 al. 2007 2001 Tiunov et al. 2004, De Mischis Kelt and Nasua_nasua terrestrial 0.672 -3.677 et al. 1997, VanVuren

Reichle et al. 2001 1968 Kelt and Carbone et al. Carbone et Nyctereutes_procyonoides terrestrial 0.783 -1.301 3.314 VanVuren 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et Otocyon_megalotis terrestrial 0.620 -3.000 3.266 VanVuren 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et al. Carbone et Panthera_leo terrestrial 2.161 2.138 4.565 4.534 VanVuren 2007 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et Panthera_onca terrestrial 1.813 1.610 4.579 VanVuren 2007 al. 2007 2001 228

Kelt and Carbone et al. Carbone et Panthera_pardus terrestrial 1.593 1.519 4.855 VanVuren 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et Panthera_tigris terrestrial 2.249 2.277 4.434 VanVuren 2007 al. 2007 2001 Hartnoll et al. Kelt and Procyon_lotor terrestrial 1.028 -2.721 2006, Carrillo et VanVuren

al. 2001 2001 Kelt and Carbone et al. Carbone et al. Carbone et Proteles_cristata terrestrial 0.929 -3.000 3.374 3.635 VanVuren 2007 2007 al. 2007 2001 Kelt and Carbone et al. Carbone et Puma_concolor terrestrial 1.712 1.881 4.570 VanVuren 2007 al. 2007 2001 Crabb 1941, Kelt Kelt and Spilogale_putorius terrestrial -0.222 -0.591 and VanVuren VanVuren

2001 2001 Sovada et al. 1999, Harestadt Kelt and Carbone et al. Taxidea_taxus terrestrial 0.935 -0.868 et al. 1979, VanVuren 2007 Bradley et al. 2001 1975 Kelt and Carbone et al. Vulpes_cana terrestrial -0.013 -1.523 2.808 VanVuren 2007 2001 Haim et al. 2004, Kelt and Carbone et al. Vulpes_lagopus terrestrial 0.698 -1.389 Elmhagen et al. VanVuren 2007 2000 2001 Kelt and Carbone et al. Carbone et al. Vulpes_macrotis terrestrial 0.653 -0.155 3.072 VanVuren 2007 2007 2001 Scott et al. 2000, Kelt and Carbone et al. Vulpes_rueppellii terrestrial 0.188 -1.579 3.006 Reichle et al. VanVuren 2007 1968 2001 Kelt and Carbone et al. Carbone et Vulpes_velox terrestrial 0.322 0.130 3.250 VanVuren 2007 al. 2007 2001 Carbone et al. Kelt and Vulpes_vulpes terrestrial 0.659 -0.319 3.248 2007 VanVuren 229

2001

Table 5.1 References

Adam, P.J. (2005) Lobodon carcinophaga. Mammalian Species, 1-14. Ainley, D.G., Ribic, C.A., Ballard, G., Heath, S., Gaffney, I., Karl, B.J., Barton, K.J., Wilson, P.R. & Webb, S. (2004) Geographic structure of Adélie penguin populations: overlap in colony-specific foraging areas. Ecological Monographs, 74, 159-178. Amado, L.L., Rosa, C.E., Leite, A.M., Moraes, L., Pires, W.V., Pinho, G.L.L., Martins, C.M.G., Robaldo, R.B., Nery, L.E.M. & Monserrat, J.M. (2006) Biomarkers in croakers Micropogonias furnieri (Teleostei: Sciaenidae) from polluted and non-polluted areas from the Patos Lagoon estuary (Southern Brazil): Evidences of genotoxic and immunological effects. Marine pollution bulletin, 52, 199-206. Andersen, N.G. & Beyer, J. (2005) Gastric evacuation of mixed stomach contents in predatory gadoids: an expanded application of the square root model to estimate food rations. Journal of fish biology, 67, 1413-1433. Anderson, K.J. & Jetz, W. (2005) The broad-scale ecology of energy expenditure of endotherms. Ecology Letters, 8, 310-318. Antonelis Jr, G.A., Lowry, M.S., DeMaster, D.P. & Fiscus, C.H. (1987) Assessing northern elephant seal feeding habits by stomach lavage. Marine Mammal Science, 3, 308-322. Artigues, B., Morales-Nin, B. & Balguerias, E. (2003) Fish length-weight relationships in the Weddell Sea and Bransfield Strait. Polar Biology, 26, 463-467. Baumgartner, M.F. & Mate, B.R. (2005) Summer and fall habitat of North Atlantic right whales (Eubalaena glacialis) inferred from satellite telemetry. Canadian Journal of Fisheries and Aquatic Sciences, 62, 527-543. Bolasina, S.N. (2006) Cortisol and hematological response in Brazilian codling, Urophycis brasiliensis (Pisces, Phycidae) subjected to anesthetic treatment. Aquaculture International, 14, 569-575. Borobia, M. & Barros, N.B. (1989) Notes on the diet of marine Sotalia fluviatilis. Marine Mammal Science, 5, 395-399. Boyd, I. & Croxall, J. (1996) Dive durations in pinnipeds and seabirds. Canadian Journal of Zoology, 74, 1696-1705. Bradley, W. & Yousef, M. (1975) Thermoregulatory responses in the plains pocket gopher, Geomys bursarius. Comparative Biochemistry and Physiology Part A: Physiology, 52, 35-38. Carbone, C., Teacher, A. & Rowcliffe, J., M. (2007) The costs of carnivory. PLoS Biology, 5, 363-368. Carrillo, E., Wong, G. & Rodriguez, M. (2001) Feeding habits of the raccoon (Procyon lotor)(Carnivora: Procyonidae) in a coastal, tropical wet forest of Costa Rica. Revista de Biología Tropical, 49, 1193-1197. Casaux, R., Baroni, A. & Ramon, A. (2006) The diet of the weddell seal Leptonychotes weddellii at the Danco Coast, Antarctic Peninsula. Polar Biology, 29, 257-262. Cherel, Y. & Duhamel, G. (2004) Antarctic jaws: cephalopod prey of sharks in Kerguelen waters. Deep Sea Research Part I: Oceanographic Research Papers, 51, 17-31. Christiansen, P. & Adolfssen, J.S. (2006) Bite forces, canine strength and skull allometry in carnivores (Mammalia, Carnivora). Journal of Zoology, 266, 133- 151. Ciaputa, P. & Siciński, J. (2006) Seasonal and annual changes in Antarctic fur seal (Arctocephalus gazella) diet in the area of Admiralty Bay, King George Island, South Shetland Islands. Polish Polar Research, 27, 171-184.

230

Clarke, M. & Goodall, N. (1994) Cephalopods in the diets of three odontocete cetacean species stranded at Tierra del Fuego, Globicephala melaena (Traill, 1809), Hyperoodon planifrons (Flower, 1882) and Cephalorhynchus commersonii (Lacepede, 1804). Antarctic Science-Institutional Subscription, 6, 149-154. Clarke, M. & Roeleveld, M. (1998) Cephalopods in the diet of sperm whales caught commercially off Durban, South Africa. South African Journal of Marine Science, 20, 41-45. Clausen, A. & Pütz, K. (2003) Winter diet and foraging range of gentoo penguins (Pygoscelis papua) from Kidney Cove, Falkland Islands. Polar Biology, 26, 32-40. Condit, R. & Le Boeuf, B.J. (1984) Feeding habits and feeding grounds of the northern elephant seal. Journal of Mammalogy, 281-290. Crabb, W.D. (1941) Food habits of the prairie spotted skunk in southeastern Iowa. Journal of Mammalogy, 22, 349-364. Culik, B. (2010) Odontocetes. The toothed whales: "Berardius bairdii". UNEP/CMS Secretariat, Bonn, Germany. Accessed 5 November 2012. Dahl, T.M., Lydersen, C., Kovacs, K.M., Falk-Petersen, S., Sargent, J., Gjertz, I. & Gulliksen, B. (2000) Fatty acid composition of the blubber in white whales (Delphinapterus leucas). Polar Biology, 23, 401-409. De Mischis, C.C. (1997) Earthworms (Annelida, Oligochaeta) of a provincial reserve in Cordoba, Argentina: A preliminary survey. Soil Biology and Biochemistry, 29, 235-236. Di Beneditto, A.P.M. & Siciliano, S. (2007) Stomach contents of the marine tucuxi dolphin (Sotalia guianensis) from Rio de Janeiro, south-eastern Brazil. Journal of the Marine Biological Association of the United Kingdom, 87, 253-254. Djawdan, M. & Garland Jr, T. (1988) Maximal running speeds of bipedal and quadrupedal rodents. Journal of Mammalogy, 765-772. Dunham, J.S. & Duffus, D.A. (2002) Foraging patterns of gray whales in central Clayoquot Sound, British Columbia, Canada. Marine Ecology Progress Series, 223, 299-310. Dwarakanath, S. (1971) The influence of body size and temperature upon the oxygen consumption in the millipede,Spirostreptus asthenes(Pocock). Comparative Biochemistry and Physiology Part A: Physiology, 38, 351-358. Eder, E. & Lewis, M. (2005) Proximate composition and energetic value of demersal and pelagic prey species from the SW Atlantic Ocean. Marine Ecology Progress Series, 291, 43-52. Elmhagen, B., Tannerfeldt, M., Verucci, P. & Angerbjörn, A. (2000) The arctic fox (Alopex lagopus): an opportunistic specialist. Journal of Zoology, 251, 139- 149. Elwin, S., Meyer, M.A., Best, P.B., Kotze, P.G.H., Thronton, M. & Swanson, S. (2006) Range and movements of female Heaviside's dolphins (Cephalorhynchus heavisidii), as determined by satellite-linked telemetry. Journal of Mammalogy, 87, 866-877. Fiedler, P.C., Reilly, S.B., Hewitt, R.P., Demer, D., Philbrick, V.A., Smith, S., Armstrong, W., Croll, D.A., Tershy, B.R. & Mate, B.R. (1998) Blue whale habitat and prey in the California Channel Islands. Deep-Sea Research Part II, 45, 1781-1801. Finerty, S.E., Wolt, R.C. & Davis, R.W. (2009) Summer activity pattern and Field Metabolic Rate of adult male sea otters (Enhydra lutris) in a soft sediment habitat in Alaska. Journal of Experimental Marine Biology and Ecology, 377, 36-42. Finley, K.J. & Gibb, E.J. (1982) Summer diet of the narwhal (Monodon monoceros) in Pond Inlet, northern Baffin Island. Canadian Journal of Zoology, 60, 3353-3363. Ford, J.K.B., Ellis, G.M., Barrett-Lennard, L.G., Morton, A.B., Palm, R.S. & Balcomb III, K.C. (1998) Dietary specialization in two sympatric populations of killer whales (Orcinus orca) in coastal British Columbia and adjacent waters. Canadian Journal of Zoology, 76, 1456-1471.

231

Friedlaender, A.S., Fraser, W.R., Patterson, D., Qian, S.S. & Halpin, P.N. (2008) The effects of prey demography on humpback whale (Megaptera novaeangliae) abundance around Anvers Island, Antarctica. Polar Biology, 31, 1217-1224. Froese, R. & Pauly, D. (2011) Fishbase < www.fishbase.org > Accessed 20 August 2012 Gaskin, D.E. & Cawthorn, M.W. (1967) Diet and feeding habits of the sperm whale (Physeter catodon L.) in the Cook Strait region of New Zealand. New Zealand Journal of Marine and Freshwater Research, 1, 156-179. Glaser, S.M. (2010) Interdecadal variability in predator-prey interactions of juvenile North Pacific albacore in the California Current System. Marine Ecology Progress Series, 414, 209-221. Godoy, E.A.S., Almeida, T.C.M. & Zalmon, I.R. (2002) Fish assemblages and environmental variables on an artificial reef north of Rio de Janeiro, Brazil. ICES Journal of Marine Science: Journal du Conseil, 59, S138-S143. Goodman-Lowe, G.D., Carpenter, J.R. & Atkinson, S. (1999) Assimilation efficiency of prey in the Hawaiian monk seal (Monachus schauinslandi). Canadian Journal of Zoology, 77, 653-660. Griffen, B.D., DeWitt, T.H. & Langdon, C. (2004) Particle removal rates by the mud shrimp Upogebia pugettensis, its burrow, and a commensal clam: effects on estuarine phytoplankton abundance. Marine Ecology Progress Series, 269, 223. Haim, A., Saarela, S., Hohtola, E. & Zisapel, N. (2004) Daily rhythms of oxygen consumption, body temperature, activity and melatonin in the Norwegian lemming Lemmus lemmus under northern summer photoperiod. Journal of Thermal Biology, 29, 629-633. Hall-Aspland, S. & Rogers, T.L. (2004) Summer diet of leopard seals (Hydrurga leptonyx) in Prydz Bay, Eastern Antarctica. Polar Biology, 27, 729-734. Hammill, M. & Stenson, G. (2000) Estimated prey consumption by harp seals (Phoca groenlandica), hooded seals (Cystophora cristata), grey seals (Halichoerus grypus) and harbour seals (Phoca vitulina) in Atlantic Canada. Journal of Northwest Atlantic Fishery Science, 26, 1-24. Harestad, A.S. & Bunnel, F.L. (1979) Home range and body weight- a reevaluation. Ecology, 60, 389-402. Hart, J.L. (1973) Pacific fishes of Canada. Bulletin. Fisheries Research Board of Canada., 180 Hartnoll, R.G., Baine, M.S.P., Grandas, Y., James, J. & Atkin, H. (2006) Population biology of the black land crab, Gecarcinus ruricola, in the San Andres Archipelago, Western Caribbean. Journal of Crustacean Biology, 26, 316-325. Hjelset, A., Andersen, M., Gjertz, I., Lydersen, C. & Gulliksen, B. (1999) Feeding habits of bearded seals (Erignathus barbatus) from the Svalbard area, Norway. Polar Biology, 21, 186-193. Hooker, S.K., Whitehead, H. & Gowans, S. (2002) Ecosystem consideration in conservation planning: energy demand of foraging bottlenose whales (Hyperoodon ampullatus) in a marine protected area. Biological Conservation, 104, 51-58. Hückstädt, L., Burns, J., Koch, P., McDonald, B., Crocker, D. & Costa, D. (2012) Diet of a specialist in a changing environment: the crabeater seal along the western Antarctic Peninsula. Marine Ecology Progress Series, 455, 287. Hunter, J. & Macewicz, B.J. (1980) Sexual maturity, batch fecundity, spawning frequency, and temporal pattern of spawning for the northern anchovy, Engraulis mordax, during the 1979 spawning season. CalCOFI Rep, 21, 139-149. Jefferson, T.A., Leatherwood, S. & Webber, M.A. (2003) FAO species identification guide. Marine mammals of the world., Rome. Jones, K.E., Bielby, J., Cardillo, M., Fritz, S.A., O'Dell, J., Orme, C.D.L., Safi, K., Sechrest, W., Boakes, E.H., Carbone, C., Connolly, C., Cutts, M.J., Foster, J.K., Grenyer, R., Habib, M., Plaster, C.A., Price, S.A., Rigby, E.A., Rist, J., Teacher, A., Bininda-Emonds, O.R.P., Gittleman, J.L., Mace, G.M., Purvis, A. & Michener, W.K. (2009) PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology, 90, 2648-2648.

232

Julshamn, K., Lundebye, A.K., Heggstad, K., Berntssen, M. & Boe, B. (2004) Norwegian monitoring programme on the inorganic and organic contaminants in fish caught in the Barents Sea, Norwegian Sea and North Sea, 1994–2001. Food additives and contaminants, 21, 365-376. Kelt, D.A. & van Vuren, D.H. (2001) The Ecology and Macroecology of Mammalian Home Range Area. The American Naturalist, 157, 637-645. Kenney, R.D., Scott, G.P., Thompson, T.J. & Winn, H.E. (1997) Estimates of prey consumption and trophic impacts of cetaceans in the USA northeast continental shelf ecosystem. Journal of Northwest Atlantic Fishery Science, 22, 155-171. Kjesbu, O. (1989) The spawning activity of cod, Gadus morhua L. Journal of fish biology, 34, 195-206. Kock, K.H., Pshenichnov, L., Jones, C.D., Gröger, J. & Riehl, R. (2008) The biology of the spiny icefish Chaenodraco wilsoni Regan, 1914. Polar Biology, 31, 381-393. Køie, M., Steffensen, J.F., Møller, P.R. & Christiansen, J.S. (2008) The parasite fauna of Arctogadus glacialis (Peters)(Gadidae) from western and eastern Greenland. Polar Biology, 31, 1017-1021. Kurle, C.M. & Worthy, G.A.J. (2001) Stable isotope assessment of temporal and geographic differences in feeding ecology of northern fur seals (Callorhinus ursinus) and their prey. Oecologia, 126, 254-265. Kutt, A.S. (2012) Feral cat (Felis catus) prey size and selectivity in north-eastern Australia: implications for mammal conservation. Journal of Zoology, 287, 292-300. Kvitek, R., Oliver, J., DeGange, A. & Anderson, B. (1992) Changes in Alaskan soft-bottom prey communities along a gradient in sea otter predation. Ecology, 413-428. Lapa-Guimarães, J., de Felício, P.E. & Guzmán, E.S.C. (2005) Chemical and microbial analyses of squid muscle (Loligo plei) during storage in ice. Food chemistry, 91, 477-483. Lowry, M.S., Francis, M., Yochem, P.K., Stewart, B.S. & Heath, C.B. (1991) Seasonal and annual variability in the diet of California sea lions, Zalophus californianus, at San Nicolas Island, California, 1981− 86. Fish. Bull, 89, 331-336. Mayo, C.A. & Marx, M.K. (1990) Surface foraging behaviour of the North Atlantic right whale, Eubalaena glacialis, and associated zooplankton characteristics. Canadian Journal of Zoology, 68, 2214-2220. McMahon, B., McDonald, D. & Wood, C. (1979) Ventilation, oxygen uptake and haemolymph oxygen transport, following enforced exhausting activity in the Dungeness crab Cancer magister. Journal of Experimental Biology, 80, 271-285. McNab, B.K. (1995) Energy expenditure and conservation in frugivorous and mixed-diet carnivorans. Journal of Mammalogy, 76, 206-222. Menge, B.A. (1975) Brood or broadcast? The adaptive significance of different reproductive strategies in the two intertidal sea stars Leptasterias hexactis and Pisaster ochraceus. Marine Biology, 31, 87-100. Meynier, L., Mackenzie, D.D.S., Duignan, P.J., Chilvers, B.L. & Morel, P.C.H. (2009) Variability in the diet of New Zealand sea lion (Phocarctos hookeri) at the Auckland Islands, New Zealand. Marine Mammal Science, 25, 302-326. Milton, K. & May, M.L. (1976) Body weight, diet and home range area in primates. Nature, 259, 459. Mizdalski, E. (1988) Weight and length data of zooplankton in the Weddell Sea in austral spring 1986 (ANT V/3). Berichte zur Polarforschung (Reports on Polar Research), 55 Morton, A. (2006) Occurrence, photo-identification and prey of pacific white-sided dolphins (Lagenorhyncus obliquidens) in the Broughton Archipelago, Canada 1984–1998. Marine Mammal Science, 16, 80-93. Nagy, K.A., Girard, I.A. & Brown, T.K. (1999) Energetics of free-ranging mammals, reptiles and birds. Annual Review of Nutrition, 19, 247-277.

233

Naya, D.E., Arim, M. & Vargas, R. (2002) Diet of South American fur seals (Arctocephalus australis) in Isla de Lobos, Uruguay. Marine Mammal Science, 18, 734-745. Noguchi, G.E. & Hesselberg, R.J. (1991) Parental transfer of organic contaminants to young-of-the-year spottail shiners, Notropis hudsonius. Bulletin of environmental contamination and toxicology, 46, 745-750. Nordøy, E., Folkow, L., Mtensson, P.E. & Blix, A. (1995) Food requirements of Northeast Atlantic minke whales. Developments in Marine Biology, 4, 307-317. O'Driscoll, R.L., Macaulay, G.J., Gauthier, S., Pinkerton, M. & Hanchet, S. (2011) Distribution, abundance and acoustic properties of Antarctic silverfish (Pleuragramma antarcticum) in the Ross Sea. Deep Sea Research Part II: Topical Studies in Oceanography, 58, 181-195. Otani, S., Naito, Y., Kato, A. & Kawamura, A. (2002) Oxygen consumption and swim speed of the harbor porpoise Phocoena phocoena. Fisheries Science, 67, 894-898. Palace, V.P., Allen-Gil, S.M., Brown, S.B., Evans, R.E., Metner, D.A., Landers, D.H., Curtis, L.R., Klaverkamp, J.F., Baron, C.L. & Lyle Lockhart, W. (2001) Vitamin and thyroid status in arctic grayling (Thymallus arcticus) exposed to doses of 3, 3′, 4, 4′-tetrachlorobiphenyl that induce the phase I enzyme system. Chemosphere, 45, 185-193. Pitman, R.L. & Ensor, P. (2003) Three forms of killer whales (Orcinus orca) in Antarctic waters. Journal of Cetacean Research and Management, 5, 131-140. Pomerleau, C., Ferguson, S.H. & Walkusz, W. (2011) Stomach contents of bowhead whales (Balaena mysticetus) from four locations in the Canadian Arctic. Polar biology, 34, 615-620. Pritchard, A. & Eddy, S. (1979) Lactate formation in Callianassa californiensis and Upogebia pugettensis (Crustacea: Thalassinidea). Marine Biology, 50, 249- 253. Pusineri, C., Magnin, V., Meynier, L., Spitz, J., Hassani, S. & Ridoux, V. (2007) Food and feeding ecology of the common dolphin (Delphinus delphis) in the oceanic northeast Atlantic and comparison with its diet in neritic areas. Marine Mammal Science, 23, 30-47. Quitral, V., Donoso, M.L., Ortiz, J., Herrera, M.V., Araya, H. & Aubourg, S.P. (2009) Chemical changes during the chilled storage of Chilean jack mackerel (Trachurus murphyi): Effect of a plant-extract icing system. LWT-Food Science and Technology, 42, 1450-1454. Ray, J. & Sunquist, M. (2001) Trophic relations in a community of African rainforest carnivores. Oecologia, 127, 395-408. Reichle, D. (1968) Relation of body size to food intake, oxygen consumption, and trace element metabolism in forest floor arthropods. Ecology, 538-542. Reid, D., Code, T., Reid, A. & Herrero, S. (1994) Food habits of the river otter in a boreal ecosystem. Canadian Journal of Zoology, 72, 1306-1313. Reimers, E., Klein, D.R. & Sørumgård, R. (1983) Calving time, growth rate, and body size of Norwegian reindeer on different ranges. Arctic and Alpine Research, 107-118. Robinson, S., Goldsworthy, S., Van den Hoff, J. & Hindell, M. (2002) The foraging ecology of two sympatric fur seal species, Arctocephalus gazella and Arctocephalus tropicalis, at Macquarie Island during the austral summer. Marine and Freshwater Research, 53, 1071-1082. Rodríguez, D., Rivero, L. & Bastida, R. (2002) Feeding ecology of the franciscana (Pontoporia blainvillei) in marine and estuarine waters of Argentina. Latin American Journal of Aquatic Mammals, 1, 77-94. Romero, M.A., Dans, S.L., García, N., Svendsen, G.M., González, R. & Crespo, E.A. (2011) Feeding habits of two sympatric dolphin species off North Patagonia, Argentina. Marine Mammal Science, 28, 364-377. Ronald, K., Keiver, K., Beamish, F. & Frank, R. (1984) Energy requirements for maintenance and faecal and urinary losses of the grey seal (Halichoerus grypus). Canadian Journal of Zoology, 62, 1101-1105. Sakamoto, W., Naito, Y., Huntley, A. & Le Boeuf, B. (1989) Daily gross energy requirements of a female northern elephant seal Mirounga angustirostris at sea. Nippon Suisan Gakkaishi, 55, 2057-2063.

234

Santos, M., Pierce, G., Reid, R., Patterson, I., Ross, H. & Mente, E. (2001) Stomach contents of bottlenose dolphins (Tursiops truncatus) in Scottish waters. Journal of the Marine Biological Association of the UK, 81, 873-878. Santos, M., Pierce, G., Learmonth, J., Reid, R., Ross, H., Patterson, I., Reid, D. & Beare, D. (2004) Variability in the diet of harbor porpoises (Phocoena phocoena) in Scottish waters 1992–2003. Marine Mammal Science, 20, 1-27. Santos, R. & Haimovici, M. (1998) Trophic relationships of the long-finned squid Loligo sanpaulensis on the southern Brazilian shelf. South African Journal of Marine Science, 20, 81-91. Scott, D.M. & Dunstone, N. (2000) Environmental determinants of the composition of desert-living rodent communities in the north-east Badia region of Jordan. Journal of Zoology, 251, 481-494. Seibel, B.A., Thuesen, E.V., Childress, J.J. & Gorodezky, L.A. (1997) Decline in pelagic cephalopod metabolism with habitat depth reflects differences in locomotory efficiency. The Biological Bulletin, 192, 262-278. Sigurjónsson, J. & Víkingsson, G.A. (1997) Seasonal abundance of and estimated food consumption by cetaceans in Icelandic and adjacent waters. Journal of Northwest Atlantic Fishery Science, 22, 271-287. Sinclair, E.H. & Zeppelin, T.K. (2002) Seasonal and spatial differences in diet in the western stock of Steller sea lions (Eumetopias jubatus). Journal of Mammalogy, 83, 973-990. Skinner, J. & Klages, N. (1994) On some aspects of the biology of the Ross seal Ommatophoca rossii from King Haakon VII Sea, Antarctica. Polar Biology, 14, 467-472. Skog, T.E., Hylland, K., Torstensen, B.E. & Berntssen, M.H.G. (2003) Salmon farming affects the fatty acid composition and taste of wild saithe Pollachius virens L. Aquaculture Research, 34, 999-1007. Slip, D.J. (1995) The diet of southern elephant seals (Mirounga leonina) from Heard Island. Canadian Journal of Zoology, 73, 1519-1528. Smith, R., Paul, A. & Paul, J. (1988) Aspects of energetics of adult walleye pollock, Theragra chalcogramma (Pallas), from Alaska. Journal of fish biology, 33, 445-454. Smout, S.C. & Lindstrom, U. (2007) Multispecies functional response of the minke whale Balaenoptera acutorostrata based on small-scale foraging studies. Marine Ecology Progress Series, Southwell, C., Kerry, K., Ensor, P., Woeler, E.J. & Rogers, T. (2003) The timing of pupping by pack-ice seals in East Antarctica. Polar Biology, 26, 648-652. Sovada, M.A., Roaldson, J.M. & Sargeant, A.B. (1999) Foods of American badgers in west-central Minnesota and southeastern North Dakota during the duck nesting season. The American midland naturalist, 142, 410-414. Swihart, R.K. (1986) Home Range—Body Mass Allometry in Rabbits and Hares (Leporidae). Acta Theriologica, 31, 139-148. Tershy, B.R. (1992) Body size, diet, habitat use, and social behavior of Balaenoptera whales in the Gulf of California. Journal of mammalogy, 477-486. Thompson, D., Duck, C.D., McConnell, B.J. & Garrett, J. (1998) Foraging behaviour and diet of lactating female southern sea lions (Otaria flavescens) in the Falkland Islands. Journal of Zoology, 246, 135-146. Tiunov, A.V. & Scheu, S. (2004) Carbon availability controls the growth of detritivores (Lumbricidae) and their effect on nitrogen mineralization. Oecologia, 138, 83-90. Van Pelt, T.I., Piatt, J.F., Lance, B.K. & Roby, D.D. (1997) Proximate composition and energy density of some North Pacific forage fishes. Comparative Biochemistry and Physiology Part A: Physiology, 118, 1393-1398. Vilhjálmsson, H. (2002) Capelin (Mallotus villosus) in the Iceland–East Greenland–Jan Mayen ecosystem. ICES Journal of Marine Science: Journal du Conseil, 59, 870-883.

235

Walker, W.A., Mead, J.G. & Brownell, R.L. (2002) Diets of Baird's beaked whales, Berardius bairdii, in the southern sea of Okhotsk and off the pacific coast of Honshu, Japan. Marine Mammal Science, 18, 902-919. Wang, E. (2002) Diets of Ocelots (Leopardus pardalis), Margays (L. wiedii), and Oncillas (L. tigrinus) in the Atlantic Rainforest in Southeast Brazil. Studies on Neotropical Fauna and Environment, 37, 207-212. Watanabe, H., Moku, M., Kawaguchi, K., Ishimaru, K. & Ohno, A. (1999) Diel vertical migration of myctophid fishes (Family Myctophidae) in the transitional waters of the western North Pacific. Fisheries Oceanography, 8, 115-127. Węsławski, J.M., Kwaśniewski, S., Stempniewicz, L. & Błachowiak-Samołyk, K. (2006) Biodiversity and energy transfer to top trophic levels in two contrasting Arctic fjords. Polish Polar Research, 27, 259-278. West, K., Walker, W., Baird, R., White, W., Levine, G., Brown, E. & Schofield, D. (2009) Diet of Pygmy Sperm Whales (Kogia breviceps) in the Hawaiian Archipelago. Publications, Agencies and Staff of the US Department of Commerce, 18. Willcox, S., Lyle, J. & Steer, M. (2001) Tasmanian arrow squid fishery—status report 2001. Tasmanian Aquaculture and Fisheries Institute, Hobart, Williams, T.M., Rutishauser, M., Long, B., Fink, T., Gafney, J., Mostman-Liwanag, H. & Casper, D. (2007) Seasonal variability in otariid energetics: implications for the effects of predators on localized prey resources. Physiological and Biochemical Zoology, 80, 433-443. Williamson, N.J. & Traynor, J.J. (1984) In situ target-strength estimation of Pacific whiting (Merluccius productus) using a dual-beam transducer. Journal du Conseil, 41, 285-292. Wolt, R.C., Gelwick, F.P., Weltz, F. & Davis, R.W. (2012) Foraging behavior and prey of sea otters in a soft-and mixed-sediment benthos in Alaska. Mammalian Biology-Zeitschrift für Säugetierkunde, Xavier, J., Rodhouse, P., Purves, M., Daw, T., Arata, J. & Pilling, G. (2002) Distribution of cephalopods recorded in the diet of the Patagonian toothfish (Dissostichus eleginoides) around South Georgia. Polar Biology, 25, 323-330. Zumholz, K., Klügel, A., Hansteen, T. & Piatkowski, U. (2007) Statolith microchemistry traces environmental history of the boreoatlantic armhook squid Gonatus fabricii. Marine Ecology Progress Series, 333, 195-204.

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Figure S5.1 AIC plots (A) demonstrating potential breakpoints for daily energetic intake (DEI). The black solid line represents AIC values calculated from the phylogenetic generalized least square (PGLS) regression analysis. The grey shaded area represents values between 0 to 2 ΔAIC from best supported model, with any dip into this area representing an equally supported breakpoint. (B) Estimates of DEI against carnivore body mass (n=48). Solid lines represent the breakpoint regression fit and the broken lines represent the breakpoint at 18.73kg.

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Figure S5.2 AIC plot (A) demonstrating potential breakpoints for daily energetic expenditure (DEE). The black solid line represents AIC values calculated from the phylogenetic generalized least square (PGLS) regression analysis. The grey shaded area represents values between 0 to 2 ΔAIC from best supported model, with any dip into this area representing an equally supported breakpoint. (B) Estimates of DEE against carnivore body mass (n=27). Solid lines represent the breakpoint regression fit and the broken lines represent the breakpoint at 49.71kg.

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Figure S5.3 AIC plots demonstrating potential breakpoints for the terrestrial data (A), the marine data (B) and the combined data set (C). The blue line represents AIC values calculated from TIPS analysis (excluding phylogenetic influence) and the red line representing phylogenetic the generalized least square (PGLS) regression analysis. The grey shaded area represents values between 0 to 2 ΔAIC from best

239 supported model, with any dip into this area representing an equally supported breakpoint. Mean prey body mass as a function of carnivore body mass for 107 species across the marine and terrestrial environments (D). The broken and solid lines are the breakpoint regression fit for marine and terrestrial species respectively. The dotted line represents the 11 kg threshold where terrestrial carnivores shift from feeding on small prey to large prey, and the 11 380 kg threshold where marine carnivores shift from feeding large prey to feeding on smaller prey.

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Appendix 6

Supplementary information for Chapter 5

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Table 6.1 Database of predator mass, trophic level and predator-prey ratios including sources for 211 mammal species.

Predator Prey PP Predator Trophic Diet Niche Diet Prey mass Niche Taxon Mass mass ratio Environment Mass level Source Source Source (log10 kg) (log10 kg) (log10) Source Pauly et al. Staniland et al. Ciaputa et al. Pauly et al. Arctocephalus_gazella 3.7 1.5 -1.8 3.3 Carnivore Zooplankton Marine 1998 2010 2006 1998 Ciaputa et al. Pauly et al. DeBruyn et al. Pauly et al. Arctocephalus_tropicalis 4.1 1.5 -1.3 2.9 Carnivore Squid Marine 2006, Robinson 1998 2009 1998 et al. 2002 Heide- Pauly et al. Pomerleau et al. Pauly et al. Balaena_mysticetus 3.2 4.5 -3.9 8.4 Carnivore Zooplankton Marine Jorgensen et 1998 2011 1998 al. 2007 Smout et al. Pauly et al. Jones et al. Pauly et al. Balaenoptera_acutorostrata 3.4 3.8 -4.0 7.7 Carnivore Zooplankton Marine 2007, Weslawski 1998 2009 1998 et al. 2006 Weslawski et al. Pauly et al. Jones et al. Pauly et al. Balaenoptera_borealis 3.4 4.3 -4.7 9.1 Carnivore Zooplankton Marine 2006, Kenney et 1998 2009 1998 al. 1997 Froese & Pauly 2011, Hart et al. Pauly et al. Jones et al. Pauly et al. Balaenoptera_edeni 3.7 4.3 -0.7 5.0 Carnivore Fish Marine 1973, Tershy 1998 2009 1998 1992, Weslawski et al. 2006 Pauly et al. Jones et al. Mizdalski 1988, Pauly et al. Balaenoptera_musculus 3.2 5.2 -3.3 8.5 Carnivore Zooplankton Marine 1998 2009 Fiedler 1998 1998 Tershey et al. Pauly et al. Jones et al. Pauly et al. Balaenoptera_physalus 3.4 4.7 -4.1 8.8 Carnivore Zooplankton Marine 1973, Weslawski 1998 2009 1998 et al. 2006 Pauly et al. Jones et al. Jefferson et al. Pauly et al. Berardius_arnuxii 4.1 4.7 -0.2 4.9 Carnivore Fish Marine 1998 2009 1993, Culik 2010 1998 Pauly et al. Jones et al. Walker et al. Pauly et al. Berardius_bairdii 4.2 3.9 -0.2 4.0 Carnivore Squid Marine 1998 2009 2002 1998 Pauly et al. Jones et al. Pauly et al. Callorhinus_ursinus 4.2 4.1 -0.6 4.6 Carnivore Fish Marine Kurle et al. 2001 1998 2009 1998 Pauly et al. Jones et al. Mizdalski 1988, Pauly et al. Caperea_marginata 3.2 1.7 -5.1 6.8 Carnivore Zooplankton Marine 1998 2009 Jefferson 1993 1998 Pauly et al. Jones et al. Clarke et al. Pauly et al. Cephalorhynchus_commersonii 3.9 4.5 -0.6 5.1 Carnivore Fish Marine 1998 2009 1994 1998 Elwin et al. Pauly et al. Elwin et al. Pauly et al. Cephalorhynchus_heavisidii 4.3 1.9 -0.3 2.2 Carnivore Fish Marine 2006, Eder et al. 1998 2006 1998 2005 Pauly et al. Jones et al. Meynier et al. Pauly et al. Cephalorhynchus_hectori 4.2 1.9 -0.1 2.0 Carnivore Fish Marine 1998 2009 2009, Wilcox et 1998 242

al. 2001 Vilhjamsson Pauly et al. Bajzak et al. Pauly et al. Cystophora_cristata 4.2 1.7 -3.9 5.6 Carnivore Fish Marine 2002, Hammil 1998 2009 1998 2000 Dahl et al. 2000, Pauly et al. Hobbs et al. Pauly et al. Delphinapterus_leucas 4.0 2.6 -3.9 6.5 Carnivore Fish Marine Weslawski et al. 1998 2005 1998 2006 Eder et al. 2005, Pauly et al. Jones et al. Pauly et al. Delphinus_delphis 4.2 4.2 -0.5 4.7 Carnivore Fish Marine Romero et al. 1998 2009 1998 2012, Wolt et al. 2012, Kvitek et al. Benthic Pauly et al. Ralls et al. Pauly et al. Enhydra_lutris 3.4 1.9 -0.7 2.6 Carnivore Marine 1992, Mc Mahon Invertebrate 1998 1996 1998 1979, Menge 1979, Weslawski et al. Benthic Pauly et al. Jones et al. Pauly et al. Erignathus_barbatus 3.4 1.4 -3.7 5.1 Carnivore Marine 2006, Hjelset et Invertebrate 1998 2009 1998 al. 1990 Pritchard et al. 1979, Weslawski Benthic Pauly et al. et al. 2006, Pauly et al. Eschrichtius_robustus 3.3 2.5 -6.0 8.5 Carnivore Marine Lockyer 1976 Invertebrate 1998 Dunham et al. 1998 2002, Griffen et al. 2004 Baumgartner et al. 2005, Pauly et al. Pauly et al. Eubalaena_glacialis 3.2 4.2 -7.1 11.3 Carnivore Zooplankton Marine Kenney 1986 Weslawski et al. 1998 1998 2006, Mayo et al. 1990 Kurle et al. 2001, Sinclair et Pauly et al. Merrick et al. Pauly et al. Eumetopias_jubatus 4.2 4.6 -0.7 5.3 Carnivore Fish Marine al. 2002, Van 1998 1997 1998 Pelt et al. 1997, Smith et al. 1988 Zerbini et al. Pauly et al. Stuart & Stuart Pauly et al. Feresa_attenuata 4.4 3.4 -0.6 4.1 Carnivore Squid Marine 1997, Santos et 1998 2001 1998 al. 1997, Heide Pauly et al. Clarke et al. Pauly et al. Globicephala_melas 4.4 2.2 -0.7 2.9 Carnivore Squid Marine jorgenson 1998 1994 1998 2002 Hammill et al. Pauly et al. Sjoberg and 2000, Pauly et al. Halichoerus_grypus 4.0 3.1 1.0 2.1 Carnivore Fish Marine 1998 Ball 2000 Weslawski et al. 1998 2006,

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Vihjlmsson et al. 2002, Van Pelt et al. 1997 Hall Apsland et Tracey Pauly et al. al. 2004, Pauly et al. Hydrurga_leptonyx 4.1 1.9 1.7 0.2 Carnivore Mammal Marine Rogers, 1998 Mizdalski 1988, 1998 unpublished Adam 2005 Pauly et al. Ainley et al. Pauly et al. Hyperoodon_ampullatus 4.2 2.5 -1.0 3.6 Carnivore Squid Marine Noren 2000 1998 2004 1998 Pauly et al. Pauly et al. Kogia_breviceps 4.4 3.8 -0.7 4.5 Carnivore Squid Marine Noren 2000 West et al. 2009 1998 1998 Morton et al. 2000, Pauly et al. Pauly et al. Lagenorhynchus_obliquidens 4.1 2.6 -1.0 3.6 Carnivore Fish Marine Noren 2000 Vilhjamsson 1998 1998 2002, Kurle et al. 2001 Casaux et al. 2008, O'Droscoll Pauly et al. Plötz et al. et al. 2011, Kock Pauly et al. Leptonychotes_weddellii 4.0 2.1 -0.9 2.9 Carnivore Fish Marine 1998 2009 et al. 2008, 1998 Artigues et al. 2003 Jefferson et al. 1993, Clarke et Pauly et al. Pauly et al. Lissodelphis_borealis 4.4 2.6 -1.3 3.9 Carnivore Fish Marine Noren 2000 al. 1994, 1998 1998 Watanabe et al. 1999 Bornemann & Artigues et al. Pauly et al. Plötz 2005, 2003, Huckstadt Pauly et al. Lobodon_carcinophaga 3.3 2.1 -1.8 3.9 Carnivore Zooplankton Marine 1998 Southwell et et al. 2012, 1998 al. 2003 Mizdalski 1988 Reid et al. 1994, Benthic Pauly et al. Blundell et al. Noguchi et al. Pauly et al. Lontra_canadensis 3.5 2.4 -1.0 3.4 Carnivore Marine Invertebrate 1998 2000 1991, Palace et 1998 al. 2001 Friedlaender et Pauly et al. Dalla Rosa et Pauly et al. Megaptera_novaeangliae 3.6 1.0 -3.3 4.3 Carnivore Zooplankton Marine al. 2008, 1998 al. 2008 1998 Mizdalski 1988 Clarke et al. 1998, Clarke et Pauly et al. Pauly et al. Mesoplodon_carlhubbsi 4.4 4.5 -0.7 5.3 Carnivore Squid Marine Jefferson 2008 al. 1994, 1998 1998 MacLeod et al. 2003 Pauly et al. Clarke et al. Pauly et al. Mesoplodon_densirostris 4.4 3.2 -0.8 4.0 Carnivore Squid-fish Marine Jefferson 2008 1998 1994, MacLeod 1998 244

et al. 2003, Belman et al. 1976, Ruiz- Capilla et al. 2001 Pauly et al. MacLeod et al. Pauly et al. Mesoplodon_layardii 4.4 3.0 -0.8 3.8 Carnivore Squid Marine Jefferson 2008 1998 2003 1998 McLeod et al. Pauly et al. Reidenberg & Pauly et al. Mesoplodon_mirus 4.5 3.1 -1.8 4.9 Carnivore Squid Marine 2003, Clarke et 1998 Laitman 2009 1998 al. 1994 Clarke et al. 1994, Eder et al. 2005, Seibel et Pauly et al. LeBoeuf et al. al. 1997, Glaser Pauly et al. Mirounga_angustirostris 4.3 3.2 -0.8 3.9 Carnivore Squid Marine 1998 2000 2010, Antonelis 1998 et al. 1987, Condit et al. 1984 Glaser 2010, Artigues et al. Pauly et al. Bornemann et 2003, Ainley et Pauly et al. Mirounga_leonina 4.3 3.1 -0.1 3.2 Carnivore Squid Marine 1998 al. 2000 al. 2008, Cherel 1998 et al. 2004, Slip 1995 Zumholz et al. 2007, Finley et Pauly et al. Dietz et al. Pauly et al. Monodon_monoceros 4.2 3.2 -0.9 4.0 Carnivore Squid Marine al. 1982, Van 1998 2008 1998 Pelt et al. 1997, Koie et al. 2008 Pauly et al. Southwell et Skinner et al. Pauly et al. Ommatophoca_rossii 4.1 3.1 -0.5 3.6 Carnivore Squid Marine 1998 al. 2005 1994 1998 Artigues et al. 2003, Pitman et al. 2003, Ford et al. 1998, Pauly et al. Andrews et al. Pauly et al. Orcinus_orca 4.5 2.3 4.0 -1.7 Carnivore Mammal-fish Marine Bornemann et 1998 2008 1998 al. 2005, Southwell 2003, Jones et al. 2009 Thompson et al. 1998, Eder et al. Pauly et al. Campagna et Pauly et al. Otaria_flavescens 4.0 4.8 -0.7 5.4 Carnivore Fish Marine 2005, Clarke et 1998 al. 2001 1998 al. 1994, Clausen et al.

245

2003 Vilhjamsson Pauly et al. Smith et al. Pauly et al. Phoca_vitulina 4.0 2.4 -3.9 6.3 Carnivore Fish Marine 2002, Weslawski 1998 2006 1998 2006 Pauly et al. Auge et al. Maynier et al. Pauly et al. Phocarctos_hookeri 4.0 1.5 0.1 1.4 Carnivore Squid-fish Marine 1998 2011 2009 1998 Santos et al. 2004, Andersen Pauly et al. Johnston et al. Pauly et al. Phocoena_phocoena 4.1 2.1 -1.1 3.2 Carnivore Fish Marine & Beyer 2005, 1998 2005 1998 Julshamn et al. 2004 Pauly et al. Gaskin et al. Pauly et al. Physeter_catodon 4.4 1.7 -0.1 1.8 Carnivore Squid Marine Lockyer 1976 1998 1967 1998 Naya et al. 2002, Rodriguez et al. 2002, Pauly et al. Danilewicz et Pauly et al. Pontoporia_blainvillei 4.1 4.4 -1.1 5.5 Carnivore Fish Marine Amado et al. 1998 al 2002 1998 2006, Santos et al. 1998, Bolasina 2006 Naya et al. 2002,Godoy et al. 2002, Pauly et al. Flores et al. Pauly et al. Sotalia_fluviatilis 4.1 1.5 -0.9 2.4 Carnivore Fish Marine Borobia et al. 1998 2004 1998 1989, Lapa- Guimaraes et al. 2005 Godoy et al. 2002, Lapa- Pauly et al. Oshima et al. Guimares et al. Pauly et al. Sotalia_guianensis 4.1 1.7 -0.5 2.3 Carnivore Fish Marine 1998 2010 2005, Di 1998 Beneditto et al. 2007 Santos et al. 2001, Skog et al. Pauly et al. Gubbins et al. 2003, Kjesbu et Pauly et al. Tursiops_truncatus 4.2 1.9 0.2 1.7 Carnivore Fish Marine 1998 2002 al. 1989, 1998 Anderson et al. 2005 Pauly et al. Ferguson et Carbone et al. Pauly et al. Ursus_maritimus 5.0 3.5 -1.0 4.5 Carnivore Mammal Marine 1998 al. 1999 2007 1998 Lowry et al. Pauly et al. Pauly et al. Zalophus_californianus 4.1 2.6 2.1 0.5 Carnivore Fish Marine Kuhn 2006 1991, Hunter et 1998 1998 al. 1980,

246

Williamson et al. 1984, Quitral et al. 2009 Santos et al. Pauly et al. 2001, Pusineri et Pauly et al. Ziphius_cavirostris 4.3 1.9 -0.4 2.4 Carnivore Squid Marine Noren 2000 1998 al. 2007, Xavier 1998 et al. 2002 Hayward et al. Kelt & van Hayward Acinonyx_jubatus 3.0 1.7 1.5 0.2 Carnivore Mammal Terrestrial Carbone 2007 2006a Vuren 2001 2006 McNab 1995, Carbone Bassariscus_sumichrasti 3.1 -0.1 -1.5 1.4 Carnivore Invertebrate Terrestrial Estrada et al. Cabone 2007 Carbone 2007 2007 1985 Atkinson et al. Kelt & van Carbone Canis_adustus 2.9 0.9 -0.1 1.0 Carnivore Invertebrate Terrestrial Carbone 2007 2002 Vuren 2001 2007 Jaeger et al. Carbone et al. Carbone Canis_aureus 3.4 1.0 -0.8 1.8 Carnivore Mammal Terrestrial Carbone 2007 2007 2007 2007 Munoz-Garcia et al. 2005, Carbone et al. Carbone Canis_latrans 3.0 1.1 1.6 -0.5 Carnivore Mammal Terrestrial Parker 1986; Carbone 2007 2007 2007 Carrera et al. 2008 Metz et al. Carbone et al. Carbone Canis_lupus 3.1 1.5 1.9 -0.4 Carnivore Mammal Terrestrial 2012; Nowak et Carbone 2007 2007 2007 al. 2011 Marino et al. Carbone et al. Carbone Canis_simensis 3.0 1.2 -0.7 1.9 Carnivore Mammal Terrestrial Carbone 2007 2010 2007 2007 Avenant et al. Carbone et al. Carbone Caracal_caracal 3.0 1.0 1.2 -0.2 Carnivore Mammal Terrestrial Carbone 2007 2002 2007 2007 MacDonald et al. Munoz-Garcia Munoz- Mammal- Kelt & van 1996, Damuth Cerdocyon_thous 2.9 0.8 -1.0 1.7 Carnivore Terrestrial et al. 2005, Garcia et al. Invertebrate Vuren 2001 1987, Kelt & van Gatti et al. 2006 2005 Vuren 2001 Cooper 1990, Cooper et al. Carbone et al. Carbone Crocuta_crocuta 3.0 1.8 2.0 -0.2 Carnivore Mammal Terrestrial Carbone 2007 1999, Hayward 2007 2007 et al. 2006 McNab 1995, Munoz-Garcia Munoz- Kelt & van Milton et al. Eira_barbara 3.1 0.7 0.6 0.1 Carnivore Mammal Terrestrial et al. 2005, Garcia et al. Vuren 2001 1976, Damuth McNab 1995 2005 1987 Kutt 2012, Kutt 2012, Kelt & van Felis_catus 3.3 0.5 -1.2 1.8 Carnivore Mammal Terrestrial Paltridge et al. Kutt 2012 Paltridge et Vuren 2001 1997 al. 1997 Mukherjee et al. Carbone et al. Carbone Felis_chaus 3.4 0.8 0.0 0.8 Carnivore Mammal Terrestrial Carbone 2007 2004 2007 2007 247

Munoz-Garcia Kelt & van Popowics et Genetta_tigrina 3.0 0.3 0.2 0.1 Carnivore Invertebrate Terrestrial Ray et al. 2001 et al. 2005 Vuren 2001 al. 1997 Reimers et al. Munoz-Garcia 1983, Munoz- et al. 2005, Kelt & van Gulo_gulo 3.0 1.3 1.9 -0.6 Carnivore Mammal Terrestrial Christiansen Garcia et al. Myhre et al. Vuren 2001 2006, Kelt & van 2005 1975 Vuren 2001 Munoz-Garcia Munoz- Kelt & van Leopardus_pardalis 3.5 1.0 0.3 0.7 Carnivore Mammal Terrestrial et al. 2005, Carbone 2007 Garcia et al. Vuren 2001 Wang 2002 2005 Munoz- Munoz-Garcia Kelt & van Leopardus_wiedii 3.0 0.6 0.3 0.3 Carnivore Mammal Terrestrial Wang 2002 Garcia et al. et al. 2005 Vuren 2001 2005 Munoz-Garcia Carbone et al. Carbone Leptailurus_serval 3.5 1.0 -1.3 2.3 Carnivore Invertebrate Terrestrial 2005, Thiel Carbone 2007 2007 2007 2011 Hayward et al. Carbone et al. Carbone Lycaon_pictus 3.0 1.4 1.5 -0.1 Carnivore Mammal Terrestrial Carbone 2007 2008 2007 2007 Carbone et al. Carbone Lynx_canadensis 3.0 1.0 0.1 0.8 Carnivore Mammal Terrestrial Poole 2003 Carbone 2007 2007 2007 Odden et al. Carbone et al. Carbone Lynx_lynx 3.1 1.4 1.3 0.1 Carnivore Mammal Terrestrial Carbone 2007 2006 2007 2007 Gil-Sanchez et Kelt & van Gil-Sanchez Lynx_pardinus 3.1 1.0 0.2 0.9 Carnivore Mammal Terrestrial Carbone 2007 al. 2006 Vuren 2001 et al. 2006 Swihart 1986, Delibes et al. Kelt & van Delibes et Lynx_rufus 3.5 1.1 -0.2 1.2 Carnivore Mammal Terrestrial Djawden et al. 1988 Vuren 2001 al. 1988 1988 Dwarakanath Bakaloudis et Kelt & van Bakaloudis Martes_foina 3.1 0.3 -2.5 2.7 Carnivore Invertebrate Terrestrial 1971, Reichle al. 2011 Vuren 2001 et al. 2011 1968 Munoz-Garcia et al. 2005, Carbone et al. Carbone Martes_martes 2.9 0.1 -1.3 1.4 Carnivore Invertebrate Terrestrial Carbone 2007 Caryl et al. 2007 2007 2012 Giuliano et al. Carbone et al. Carbone Martes_pennanti 3.1 0.6 -0.1 0.8 Carnivore Mammal Terrestrial Carbone 2007 1989 2007 2007 Munoz-Garcia et al. 2005, Virgos et al. Carbone et al. Carbone Meles_meles 2.8 1.0 -1.5 2.5 Carnivore Invertebrate Terrestrial Carbone 2007 2004, 2007 2007 Goszczynski et al.2000 Carbone et al. Carbone Mungos_mungo 3.0 1.0 -2.0 3.0 Carnivore Invertebrate Terrestrial Rood 1975 Carbone 2007 2007 2007

248

Munoz-Garcia et al. 2005, Kelt & van Carbone Mustela_erminea 2.9 -0.6 -1.3 0.7 Carnivore Invertebrate Terrestrial Carbone 2007 Martinoli et al. Vuren 2001 2007 2001 Kelt & van Carbone Mustela_frenata 3.0 -0.8 -1.7 0.9 Carnivore Invertebrate Terrestrial Reid et al. 2008 Carbone 2007 Vuren 2001 2007 Munoz-Garcia et al. 2005, Kelt & van Carbone Mustela_nivalis 3.0 -1.1 -1.5 0.5 Carnivore Invertebrate Terrestrial Carbone 2007 Jedrzejewski et Vuren 2001 2007 al. 1995 Carbone et al. Carbone Mustela_putorius 3.5 0.0 -1.0 1.0 Carnivore Mammal Terrestrial Lode 1997 Carbone 2007 2007 2007 Munoz-Garcia et al. 2005, Carbone et al. Carbone Mustela_vison 3.5 0.0 -1.0 1.0 Carnivore Mammal Terrestrial Carbone 2007 Jedrzejewska 2007 2007 et al. 2001 Munoz-Garcia Tiunov et al. et al. 2005, 2004, De Munoz- Kelt & van Nasua_nasua 2.6 0.7 -3.7 4.3 Carnivore Invertebrate Terrestrial Hirsch 2009, Mischis et al. Garcia et al. Vuren 2001 Alves-Costa et 1997, Reichle et 2005 al. 2004 al. 1968 Sutor et al. Carbone et al. Carbone Nyctereutes_procyonoides 3.0 0.8 -1.3 2.1 Carnivore Invertebrate Terrestrial Carbone 2007 2010 2007 2007 Kuntzsch et al. Carbone et al. Carbone Otocyon_megalotis 2.5 0.6 -3.0 3.6 Carnivore Invertebrate Terrestrial Carbone 2007 2008 2007 2007 Carbone et al. Carbone Panthera_leo 3.0 2.2 2.1 0.0 Carnivore Mammal Terrestrial Hayward 2005 Carbone 2007 2007 2007 Weckel et al. Carbone et al. Carbone Panthera_onca 3.0 1.8 1.6 0.2 Carnivore Mammal Terrestrial Carbone 2007 2006 2007 2007 Hayward et al. Carbone et al. Carbone Panthera_pardus 3.0 1.6 1.5 0.1 Carnivore Mammal Terrestrial Carbone 2007 2006b 2007 2007 Kelt & van Carbone Panthera_tigris 3.1 2.2 2.3 0.0 Carnivore Mammal Terrestrial Hayward 2012 Carbone 2007 Vuren 2001 2007 Hartnoll et al. Munoz- Munoz-Garcia Kelt & van Procyon_lotor 2.7 1.0 -2.7 3.7 Carnivore Invertebrate Terrestrial 2006, Carrillo et Garcia et al. et al. 2005 Vuren 2001 al. 2001 2005 deVries et al. Carbone et al. Carbone Proteles_cristata 3.0 0.9 -3.0 3.9 Carnivore Invertebrate Terrestrial Carbone 2007 2011 2007 2007 Moreno et al. Carbone et al. Carbone Puma_concolor 3.0 1.7 1.9 -0.2 Carnivore Mammal Terrestrial Carbone 2007 2006 2007 2007 Munoz-Garcia Crabb 1941, Kelt Munoz- Mammal- Kelt & van Spilogale_putorius 3.0 -0.2 -0.6 0.4 Carnivore Terrestrial et al. 2005, & van Vuren Garcia et al. Invertebrate Vuren 2001 Crabb 1941 2001 2005 Munoz-Garcia Kelt & van Sovoda et al. Munoz- Taxidea_taxus 2.6 0.9 -0.9 1.8 Carnivore Mammal Terrestrial et al. 2005, Vuren 2001 1999, Harestadt Garcia et al. 249

Michiner et al. et al. 1979, 2005 2004, Sovada Bradley et al. et al. 1999 1975, Munoz-Garcia et al. 2005, Carbone et al. Carbone Vulpes_cana 2.8 0.0 -1.5 1.5 Carnivore Invertebrate Terrestrial Carbone 2007 Geffen et al. 2007 2007 1992 Haim et al. Munoz- Munoz-Garcia Kelt & van Vulpes_lagopus 3.0 0.7 -1.4 2.1 Carnivore Mammal Terrestrial 2004, Elmhagen Garcia et al. et al. 2005 Vuren 2001 et al. 2000 2005 Munoz-Garcia Kelt & van Carbone Vulpes_macrotis 3.0 0.7 -0.2 0.8 Carnivore Mammal Terrestrial et al. 2005, List Carbone 2007 Vuren 2001 2007 et al. 2003 Munoz-Garcia Scott et al. 2000, Munoz- et al. 2005, Carbone et al. Vulpes_ruepellii 2.9 0.2 -1.6 1.8 Carnivore Mammal Terrestrial Reichle et al. Garcia et al. Williams et al. 2007 1968, 2005 2002. Sovada et al. Carbone et al. Carbone Vulpes_velox 2.9 0.3 0.1 0.2 Carnivore Mammal Terrestrial Carbone 2007 2001 2007 2007 Jedrzejewski et Carbone et al. Carbone Vulpes_vulpes 3.0 0.7 -0.3 1.0 Carnivore Mammal Terrestrial Carbone 2007 al. 1992 2008 2007 Sheppard et Johnstone et Dugong_dugon 2.0 2.3 - - Herbivore Grazer Marine - - al. 2006 al. 1981 Domning et Hydrodamalis_gigas 2.0 4.3 - - Herbivore Grazer Marine - Scheffer 1972 - al. 2008 Rodrigo et al. Cantanhede Trichechus_inunguis 2.0 2.3 - - Herbivore Grazer Marine - - 2010 et al. 2005 Kipps et al. Deutsch et Trichechus_manatus 2.0 2.5 - - Herbivore Grazer Marine - - 2002 al. 2008 Powell & Thibault et al. Trichechus_senegalensis 2.0 2.6 - - Herbivore Grazer Marine - - Kouadio 2003 2008 Kelt & van Dunham et Aepyceros_melampus 2.0 1.8 - - Herbivore Grazer Terrestrial - - Vuren 2001 al. 1980 Kelt & van Carter et al. Ailuropoda_melanoleuca 2.0 1.9 - - Herbivore Browser Terrestrial - - Vuren 2001 1999 Munoz- Kelt & van Ailurus_fulgens 2.0 0.7 - - Herbivore Browser Terrestrial - - Garcia et al. Vuren 2001 2005 Kelt & van Alcelaphus_buselaphus 2.0 2.1 - - Herbivore Grazer Terrestrial - - Price, 1978 Vuren 2001 Kelt & van Alces_alces 2.0 2.5 - - Herbivore Browser Terrestrial - - Irwin, 1985 Vuren 2001 Browser- Kelt & van Popowics et Ammotragus_lervia 2.0 2.2 - - Herbivore Terrestrial - - grazer Vuren 2001 al. 1997 250

Browser- Kelt & van Popowics et Antilocapra_americana 2.0 1.7 - - Herbivore Terrestrial - - grazer Vuren 2001 al. 1997 Kelt & van Bennett et Bathyergus_suillus 2.0 -0.2 - - Herbivore Geophyte Terrestrial - - Vuren 2001 al. 1995 Kelt & van Bettongia_gaimardi 2.0 0.2 - - Herbivore Mychophagus Terrestrial - - Taylor, 1992 Vuren 2001 Kelt & van Popowics et Bison_bison 2.0 2.8 - - Herbivore Grazer Terrestrial - - Vuren 2001 al. 1997 Kelt & van Bodmer, Bison_bonasus 2.0 2.8 - - Herbivore Grazer Terrestrial - - Vuren 2001 1990 Kelt & van Katzner et Brachylagus_idahoensis 2.0 -0.5 - - Herbivore Grazer Terrestrial - - Vuren 2001 al. 1997 Kelt & van Chiarello, Bradypus_torquatus 2.0 0.6 - - Herbivore Browser Terrestrial - - Vuren 2001 1998 Kelt & van Bodmer, Capra_hircus 2.0 1.7 - - Herbivore Browser Terrestrial - - Vuren 2001 1990 Kelt & van Bodmer, Capra_pyrenaica 2.0 1.8 - - Herbivore Browser Terrestrial - - Vuren 2001 1990 Kelt & van Taber et al. Catagonus_wagneri 2.0 1.5 - - Herbivore Browser Terrestrial - - Vuren 2001 1993 Kelt & van Bodmer, Cephalophus_callipygus 2.0 1.3 - - Herbivore Frugivore Terrestrial - - Vuren 2001 1990 Kelt & van Bodmer, Cephalophus_dorsalis 2.0 1.3 - - Herbivore Frugivore Terrestrial - - Vuren 2001 1990 Kelt & van Popowics et Ceratotherium_simum 2.0 3.4 - - Herbivore Grazer Terrestrial - - Vuren 2001 al. 1997 Browser- Kelt & van Popowics et Cervus_elaphus 2.0 2.4 - - Herbivore Terrestrial - - grazer Vuren 2001 al. 1997 Browser- Kelt & van Bodmer, Cervus_nippon 2.0 1.5 - - Herbivore Terrestrial - - Grazer Vuren 2001 1990 Kelt & van Robinson et Coendou_prehensilis 2.0 0.6 - - Herbivore Granivore Terrestrial - - Vuren 2001 al. 1986 Kelt & van Bodmer, Dama_dama 2.0 1.9 - - Herbivore Browser Terrestrial - - Vuren 2001 1990 Kelt & van Meredith et Dendrolagus_lumholtzi 2.0 0.8 - - Herbivore Browser Terrestrial - - Vuren 2001 al. 2008 Kelt & van Popowics et Diceros_bicornis 2.0 3.0 - - Herbivore Browser Terrestrial - - Vuren 2001 al. 1997 Kelt & van Pradhan et Elephas_maximus 2.0 3.6 - - Herbivore Browser Terrestrial - - Vuren 2001 al. 2008 Kelt & van Bodmer, Equus_burchelli 2.0 2.4 - - Herbivore Grazer Terrestrial - - Vuren 2001 1990 Kelt & van Bodmer, Equus_caballus 2.0 2.6 - - Herbivore Grazer Terrestrial - - Vuren 2001 1990

251

Kelt & van Grobler, Equus_zebra 2.0 2.5 - - Herbivore Grazer Terrestrial - - Vuren 2001 1983 Browser- Kelt & van Bodmer, Gazella_gazella 2.0 1.3 - - Herbivore Terrestrial - - Grazer Vuren 2001 1990 Kelt & van Popowics et Giraffa_camelopardalis 2.0 3.1 - - Herbivore Browser Terrestrial - - Vuren 2001 al. 1997 Kelt & van Maser et al. Glaucomys_sabrinus 2.0 -0.8 - - Herbivore Mychophagus Terrestrial - - Vuren 2001 1985 Kelt & van Le Comber Heliophobius_argenteocinereus 2.0 -0.8 - - Herbivore Geophyte Terrestrial - - Vuren 2001 et al. 2002 Kelt & van Bodmer, Hyemoschus_aquaticus 2.0 1.0 - - Herbivore Frugivore Terrestrial - - Vuren 2001 1990 Kelt & van Alkon et al. Hystrix_indica 2.0 1.2 - - Herbivore Geophyte Terrestrial - - Vuren 2001 1988 Browser- Kelt & van Swihart Lepus_alleni 2.0 0.6 - - Herbivore Terrestrial - - Grazer Vuren 2001 1986 Browser- Kelt & van Swihart Lepus_americanus 2.0 0.6 - - Herbivore Terrestrial - - Grazer Vuren 2001 1986 Browser- Kelt & van Swihart Lepus_californicus 2.0 0.4 - - Herbivore Terrestrial - - Grazer Vuren 2001 1986 Browser- Kelt & van Swihart Lepus_capensis 2.0 0.6 - - Herbivore Terrestrial - - Grazer Vuren 2001 1986 Browser- Kelt & van Swihart Lepus_timidus 2.0 0.5 - - Herbivore Terrestrial - - Grazer Vuren 2001 1986 Kelt & van White et al. Loxodonta_africana 2.0 3.6 - - Herbivore Browser Terrestrial - - Vuren 2001 1993 Kelt & van Meredith et Macropus_antilopinus 2.0 1.4 - - Herbivore Grazer Terrestrial - - Vuren 2001 al. 2008 Browser- Kelt & van Meredith et Macropus_dorsalis 2.0 1.1 - - Herbivore Terrestrial - - Grazer Vuren 2001 al. 2008 Kelt & van Meredith et Macropus_fuliginosus 2.0 1.3 - - Herbivore Grazer Terrestrial - - Vuren 2001 al. 2008 Kelt & van Meredith et Macropus_giganteus 2.0 1.0 - - Herbivore Grazer Terrestrial - - Vuren 2001 al. 2008 Kelt & van Meredith et Macropus_robustus 2.0 1.3 - - Herbivore Grazer Terrestrial - - Vuren 2001 al. 2008 Browser- Kelt & van Meredith et Macropus_rufogriseus 2.0 1.2 - - Herbivore Terrestrial - - Grazer Vuren 2001 al. 2008 Kelt & van Meredith et Macropus_rufus 2.0 1.7 - - Herbivore Grazer Terrestrial - - Vuren 2001 al. 2008 Kelt & van Bodmer, Madoqua_guentheri 2.0 0.7 - - Herbivore Browser Terrestrial - - Vuren 2001 1990 Kelt & van Freeman et Microtus_californicus 2.0 -1.2 - - Herbivore Grazer Terrestrial - - Vuren 2001 al. 2008

252

Kelt & van Freeman et Microtus_montanus 2.0 -1.3 - - Herbivore Grazer Terrestrial - - Vuren 2001 al. 2008 Kelt & van Freeman et Microtus_ochrogaster 2.0 -1.5 - - Herbivore Grazer Terrestrial - - Vuren 2001 al. 2008 Kelt & van Freeman et Microtus_pennsylvanicus 2.0 -1.3 - - Herbivore Grazer Terrestrial - - Vuren 2001 al. 2008 Kelt & van Freeman et Microtus_pinetorum 2.0 -1.5 - - Herbivore Grazer Terrestrial - - Vuren 2001 al. 2008 Kelt & van Freeman et Microtus_richardsoni 2.0 -1.1 - - Herbivore Grazer Terrestrial - - Vuren 2001 al. 2008 Kelt & van Bodmer, Muntiacus_reevesi 2.0 1.1 - - Herbivore Frugivore Terrestrial - - Vuren 2001 1990 Dial. 1988; Kelt & van Neotoma_cinerea 2.0 -0.4 - - Herbivore Browser Terrestrial - - Dearing et Vuren 2001 al. 2000 Dial. 1988; Kelt & van Neotoma_fuscipes 2.0 -0.5 - - Herbivore Browser Terrestrial - - Dearing et Vuren 2001 al. 2000 Dial. 1988; Kelt & van Neotoma_lepida 2.0 -0.9 - - Herbivore Browser Terrestrial - - Dearing et Vuren 2001 al. 2000 Dial. 1988; Kelt & van Neotoma_micropus 2.0 -0.6 - - Herbivore Browser Terrestrial - - Dearing et Vuren 2001 al. 2000 Kelt & van Swihart Ochotona_collaris 2.0 -0.9 - - Herbivore Grazer Terrestrial - - Vuren 2001 1986 Kelt & van Swihart Ochotona_princeps 2.0 -0.7 - - Herbivore Grazer Terrestrial - - Vuren 2001 1986 Kelt & van Bodmer, Odocoileus_hemionus 2.0 1.7 - - Herbivore Browser Terrestrial - - Vuren 2001 1990 Kelt & van Bodmer, Odocoileus_virginianus 2.0 1.9 - - Herbivore Browser Terrestrial - - Vuren 2001 1990 Kelt & van Bodmer, Okapia_johnstoni 2.0 2.4 - - Herbivore Browser Terrestrial - - Vuren 2001 1990 Kelt & van Meredith et Onychogalea_fraenata 2.0 0.7 - - Herbivore Grazer Terrestrial - - Vuren 2001 al. 2008 Kelt & van Swihart Oryctolagus_cuniculus 2.0 0.2 - - Herbivore Grazer Terrestrial - - Vuren 2001 1986 Browser- Kelt & van Bodmer, Ovis_ammon 2.0 2.1 - - Herbivore Terrestrial - - Grazer Vuren 2001 1990 Browser- Kelt & van Bodmer, Ovis_canadensis 2.0 2.0 - - Herbivore Terrestrial - - Grazer Vuren 2001 1990 Browser- Kelt & van Bodmer, Ozotoceros_bezoarticus 2.0 1.5 - - Herbivore Terrestrial - - Grazer Vuren 2001 1990

253

Kelt & van Altrichter et Pecari_tajacu 2.0 1.4 - - Herbivore Frugivore Terrestrial - - Vuren 2001 al. 2001 Kelt & van Botha et al. Phacochoerus__aethiopicus 2.0 1.9 - - Herbivore Grazer Terrestrial - - Vuren 2001 2005 Kays et al. Kelt & van 1999, Julien- Potos_flavus 2.0 0.5 - - Herbivore Frugivore Terrestrial - - Vuren 2001 Laferri et al. 1999 Kelt & van Bodmer, Pudu_puda 2.0 0.9 - - Herbivore Browser Terrestrial - - Vuren 2001 1990 Kelt & van Popowics et Rangifer_tarandus 2.0 2.0 - - Herbivore Browser Terrestrial - - Vuren 2001 al. 1997 Kelt & van Bodmer, Raphicerus_campestris 2.0 1.1 - - Herbivore Browser Terrestrial - - Vuren 2001 1990 Browser- Kelt & van Bodmer, Rupicapra_rupicapra 2.0 1.5 - - Herbivore Terrestrial - - Grazer Vuren 2001 1990 Kelt & van Freeman et Sciurus_aberti 2.0 -0.1 - - Herbivore Granivore Terrestrial - - Vuren 2001 al. 2008 Kelt & van Freeman et Sciurus_carolinensis 2.0 -0.3 - - Herbivore Granivore Terrestrial - - Vuren 2001 al. 2008 Kelt & van Freeman et Sciurus_lis 2.0 -0.6 - - Herbivore Granivore Terrestrial - - Vuren 2001 al. 2008 Kelt & van Freeman et Sciurus_niger 2.0 0.0 - - Herbivore Granivore Terrestrial - - Vuren 2001 al. 2008 Kelt & van Freeman et Sciurus_vulgaris 2.0 -0.5 - - Herbivore Granivore Terrestrial - - Vuren 2001 al. 2008 Kelt & van Hayward Setonix_brachyurus 2.0 0.5 - - Herbivore Browser Terrestrial - - Vuren 2001 2005 Schitoskey Kelt & van Spermophilus_beecheyi 2.0 -0.1 - - Herbivore Legume Terrestrial - - Jr. et al. Vuren 2001 1978 Browser- Kelt & van Swihart Sylvilagus_aquaticus 2.0 0.3 - - Herbivore Terrestrial - - Grazer Vuren 2001 1986 Browser- Kelt & van Swihart Sylvilagus_audubonii 2.0 -0.1 - - Herbivore Terrestrial - - Grazer Vuren 2001 1986 Browser- Kelt & van Swihart Sylvilagus_bachmani 2.0 -0.2 - - Herbivore Terrestrial - - Grazer Vuren 2001 1986 Browser- Kelt & van Swihart Sylvilagus_floridanus 2.0 0.1 - - Herbivore Terrestrial - - Grazer Vuren 2001 1986 Browser- Kelt & van Swihart Sylvilagus_palustris 2.0 0.1 - - Herbivore Terrestrial - - Grazer Vuren 2001 1986 Browser- Kelt & van Swihart Sylvilagus_transitionalis 2.0 0.0 - - Herbivore Terrestrial - - Grazer Vuren 2001 1986 Kelt & van Bodmer, Syncerus_caffer 2.0 2.8 - - Herbivore Grazer Terrestrial - - Vuren 2001 1990 254

Kelt & van Keuroghlian Tayassu_pecari 2.0 1.3 - - Herbivore Frugivore Terrestrial - - Vuren 2001 et al. 2008 Kelt & van Meredith et Thylogale_thetis 2.0 0.7 - - Herbivore Browser Terrestrial - - Vuren 2001 al. 2008 Kelt & van Bodmer, Tragelaphus_oryx 2.0 2.8 - - Herbivore Browser Terrestrial - - Vuren 2001 1990 Browser- Kelt & van Popowics et Tragelaphus_scriptus 2.0 1.7 - - Herbivore Terrestrial - - grazer Vuren 2001 al. 1997 Kelt & van Bodmer, Tragelaphus_strepsiceros 2.0 2.3 - - Herbivore Browser Terrestrial - - Vuren 2001 1990 Kelt & van How et al. Trichosurus_vulpecula 2.0 0.5 - - Herbivore Browser Terrestrial - - Vuren 2001 2000 Browser- Kelt & van Rishworth et Vombatus_ursinus 2.0 1.4 - - Herbivore Terrestrial - - Grazer Vuren 2001 al. 1995 Kelt & van Meredith et Wallabia_bicolor 2.0 1.2 - - Herbivore Browser Terrestrial - - Vuren 2001 al. 2008

Table S6.1 References

Adam P.J. (2005). Lobodon carcinophaga. Mammalian Species, 1-14. Ainley D.G., Ribic C.A., Ballard G., Heath S., Gaffney I., Karl B.J., Barton K.J., Wilson P.R. & Webb S. (2004). Geographic structure of Adélie penguin populations: overlap in colony-specific foraging areas. Ecological Monographs, 74, 159-178. Alkon P.U. & Saltz D. (1988). Foraging time and the northern range limits of Indian crested porcupines (Hystrix indica Kerr). Journal of Biogeography, 403-408. Altrichter M., Carrillo E., Sáenz J. & K. Fuller T. (2001). White-lipped peccary (Tayassu pecari, Artiodactyla: Tayassuidae) diet and fruit availability in a Costa Rican rain forest. Revista de Biología Tropical, 49, 1183-1192. Alves-Costa C.P., Da Fonseca G.A.B. & Christófaro C. (2004). Variation in the diet of the brown-nosed coati (Nasua nasua) in southeastern Brazil. Journal of Mammalogy, 85, 478-482. Amado L.L., Rosa C.E., Leite A.M., Moraes L., Pires W.V., Pinho G.L.L., Martins C.M.G., Robaldo R.B., Nery L.E.M. & Monserrat J.M. (2006). Biomarkers in croakers Micropogonias furnieri (Teleostei: Sciaenidae) from polluted and non-polluted areas from the Patos Lagoon estuary (Southern Brazil): Evidences of genotoxic and immunological effects. Marine pollution bulletin, 52, 199-206. Andersen N.G. & Beyer J. (2005). Gastric evacuation of mixed stomach contents in predatory gadoids: an expanded application of the square root model to estimate food rations. Journal of fish biology, 67, 1413-1433. Andrews R.D., Pitman R.L. & Ballance L.T. (2008). Satellite tracking reveals distinct movement patterns for Type B and Type C killer whales in the southern Ross Sea, Antarctica. Polar Biology, 31, 1461-1468.

255

Antonelis Jr G.A., Lowry M.S., DeMaster D.P. & Fiscus C.H. (1987). Assessing northern elephant seal feeding habits by stomach lavage. Marine Mammal Science, 3, 308-322. Artigues B., Morales-Nin B. & Balguerias E. (2003). Fish length-weight relationships in the Weddell Sea and Bransfield Strait. Polar Biology, 26, 463-467. Atkinson R.P.D., Macdonald D.W. & Kamizola R. (2002). Dietary opportunism in side-striped jackals Canis adustus Sundevall. Journal of Zoology, 257, 129-139. Augé A.A., Chilvers B.L., Moore A.B. & Davis L.S. (2011). Foraging behaviour indicates marginal marine habitat for New Zealand sea lions: remnant versus recolonising populations. Marine Ecology Progress Series, 432, 247-256. Avenant N.L. & Nel J.A.J. (2002). Among habitat variation in prey availability and use by caracal Felis caracal. Mammalian Biology - Zeitschrift für Säugetierkunde, 67, 18-33. Bajzak C.E., Cotté C., Hammill M.O. & Stenson G. (2009). Intersexual differences in the postbreeding foraging behaviour of the Northwest Atlantic hooded seal. Marine Ecology Progress Series, 385, 285-294. Bakaloudis D.E., Vlachos C.G., Papakosta M.A., Bontzorlos V.A. & Chatzinikos E.N. (2012). Diet Composition and Feeding Strategies of the Stone Marten (Martes foina) in a Typical Mediterranean Ecosystem. The Scientific World Journal, 2012. Baumgartner M.F. & Mate B.R. (2005). Summer and fall habitat of North Atlantic right whales (Eubalaena glacialis) inferred from satellite telemetry. Canadian Journal of Fisheries and Aquatic Sciences, 62, 527-543. Belman B.W. & Childress J.J. (1976). Circulatory adaptations to the oxygen minimum layer in the bathypelagic mysid Gnathophausia ingens. Biological Bulletin, 15-37. Bennett N. & Jarvis J. (1995). Coefficients of digestibility and nutritional values of geophytes and tubers eaten by southern African mole‐rats (Rodentia: Bathyergidae). Journal of Zoology, 236, 189-198. Blundell G.M., Bowyer R.T., Ben-David M., Dean T.A. & Jewett S.C. (2000). Effects of food resources on spacing behaviour of river otters: does forage abundance control home range size? In: Biotelemetry 15: Proceedings of 15th International Conference on Biotelemetry. International Society of Biotelemetry Juneau, Alaska, USA, pp. 325-333. Bodmer R.E. (1990). Ungulate frugivores and the browser-grazer continuum. Oikos, 319-325. Bolasina S.N. (2006). Cortisol and hematological response in Brazilian codling, Urophycis brasiliensis (Pisces, Phycidae) subjected to anesthetic treatment. Aquaculture International, 14, 569-575. Bornemann H., Kreyscher M., Ramdohr S., Martin T., Carlini A., Sellmann L. & Plötz J. (2000). Southern elephant seal movements and Antarctic sea ice. Antarctic Science, 12, 3-15. Bornemann H. & Plötz J. (2005). At surface behaviour at location on spot of crabeater seal DRE1998_cra_y_m_15 from Drescher Inlet. doi:10.1594/PANGAEA.264706. Borobia M. & Barros N.B. (1989). Notes on the diet of marine Sotalia fluviatilis. Marine Mammal Science, 5, 395-399. Botha S. & Stock W. (2005). Stable isotope composition of faeces as an indicator of seasonal diet selection in wild herbivores in southern Africa. South African Journal of Science, 101, 371-374.

256

Bradley W. & Yousef M. (1975). Thermoregulatory responses in the plains pocket gopher, Geomys bursarius. Comparative Biochemistry and Physiology Part A: Physiology, 52, 35-38. Campagna C., Werner R., Karesh W., Marín M., iacute, Rosa a., Koontz F., Cook R. & Koontz C. (2001). Movements and location at sea of South American sea lions (Otaria flavescens). Journal of Zoology, 255, 205-220. Cantanhede A., Da silva V., Ferreira M., Farias I.P., Hrbek T., Lazzarini S. & Alves-Gomes J. (2004). Phylogeography and population genetics of the endangered Amazonian manatee, Trichechus inunguis Natterer, 1883 (Mammalia, Sirenia). Molecular Ecology, 14, 401-413. Carbone C., Teacher A. & Rowcliffe J., M. (2007). The costs of carnivory. PLoS Biology, 5, 363-368. Carrera R., Ballard W., Gipson P., Kelly B.T., Krausman P.R., Wallace M.C., Villalobos C. & Wester D.B. (2008). Comparison of Mexican Wolf and Coyote Diets in Arizona and New Mexico. The Journal of Wildlife Management, 72, 376-381. Carrillo E., Wong G. & Rodriguez M. (2001). Feeding habits of the raccoon (Procyon lotor)(Carnivora: Procyonidae) in a coastal, tropical wet forest of Costa Rica. Revista de Biología Tropical, 49, 1193-1197. Carter J., Ackleh A.S., Leonard B.P. & Wang H. (1999). Giant panda (Ailuropoda melanoleuca) population dynamics and bamboo (subfamily Bambusoideae) life history: a structured population approach to examining carrying capacity when the prey are semelparous. Ecological Modelling, 123, 207-223. Caryl F.M. (2008). Pine marten diet and habitat use within a managed coniferous forest. In. PhD Thesis, University of Sterling, Crawley. Casaux R., Baroni A. & Ramon A. (2006). The diet of the weddell seal Leptonychotes weddellii at the Danco Coast, Antarctic Peninsula. Polar Biology, 29, 257-262. Cherel Y. & Duhamel G. (2004). Antarctic jaws: cephalopod prey of sharks in Kerguelen waters. Deep Sea Research Part I: Oceanographic Research Papers, 51, 17-31. Chiarello A.G. (2006). Diet of the Atlantic forest maned sloth Bradypus torquatus (Xenarthra: Bradypodidae). Journal of Zoology, 246, 11-19. Christiansen P. & Adolfssen J.S. (2006). Bite forces, canine strength and skull allometry in carnivores (Mammalia, Carnivora). Journal of Zoology, 266, 133-151. Ciaputa P. & Siciński J. (2006). Seasonal and annual changes in Antarctic fur seal (Arctocephalus gazella) diet in the area of Admiralty Bay, King George Island, South Shetland Islands. Polish Polar Research, 27, 171-184. Clarke M. & Goodall N. (1994). Cephalopods in the diets of three odontocete cetacean species stranded at Tierra del Fuego, Globicephala melaena (Traill, 1809), Hyperoodon planifrons (Flower, 1882) and Cephalorhynchus commersonii (Lacepede, 1804). Antarctic Science- Institutional Subscription, 6, 149-154. Clarke M. & Roeleveld M. (1998). Cephalopods in the diet of sperm whales caught commercially off Durban, South Africa. South African Journal of Marine Science, 20, 41-45. Condit R. & Le Boeuf B.J. (1984). Feeding habits and feeding grounds of the northern elephant seal. Journal of Mammalogy, 281-290. Cooper S.M. (1990). The hunting behaviour of spotted hyaenas (Crocuta crocuta) in a region containing both sedentary and migratory populations of herbivores. African Journal of Ecology, 28, 131-141.

257

Cooper S.M., Holekamp K.E. & Smale L. (1999). A seasonal feast: long-term analysis of feeding behaviour in the spotted hyaena (Crocuta crocuta). African Journal of Ecology, 37, 149-160. Crabb W.D. (1941). Food habits of the prairie spotted skunk in southeastern Iowa. Journal of Mammalogy, 22, 349-364. Dahl T.M., Lydersen C., Kovacs K.M., Falk-Petersen S., Sargent J., Gjertz I. & Gulliksen B. (2000). Fatty acid composition of the blubber in white whales (Delphinapterus leucas). Polar Biology, 23, 401-409. Dalla Rosa L., Secchi E.R., Maia Y.G., Zerbini A.N. & Heide-Jorgensen M.P. (2008). Movements of satellite-monitored humpback whales on their feeding ground along the Antarctic Peninsula. Polar Biology, 31, 771-781. Damuth J. (1987). Interspecific allometry of population density in mammals and other animals: the independence of body mass and population energy‐use. Biological Journal of the Linnean Society, 31, 193-246. Danilewicz D., Rosas F., Bastida R., Marigo J., Muelbert M., Rodríguez D., Lailson-Brito Jr. J., Ruoppolo V., Ramos R., Bassoi M., Ott P.H., Caon G., Rocha A.M., Catão-Dias J.L. & Secchi E.R. (2002). Report of the working group on biology and ecology. de Bruyn P.J.N., Tosh C.A., Oosthuizen W.C., Bester M.N. & Arnould J.P.Y. (2009). Bathymetry and frontal system interactions influence seasonal foraging movements of lactating subantarctic fur seals from Marion Island. Marine Ecology Progress Series, 394, 263-276. De Mischis C.C. (1997). Earthworms (Annelida, Oligochaeta) of a provincial reserve in Cordoba, Argentina: A preliminary survey. Soil Biology and Biochemistry, 29, 235-236. de Vries J.L., Prik C.W.W., Bateman P.W., Cameron E.Z. & Dalerum F. (2011). Extension of the diet of an extreme foraging specialist, the aardwolf (Proteles cristata). African Zoology, 46, 194-196. Dearing M.D., Mangione A.M. & Karasov W.H. (2000). Diet breadth of mammalian herbivores: nutrient versus detoxification constraints. Oecologia, 123, 397-405. Delibes M., Zapata S.C., Blázquez M.C. & Rodríguez-Estrella R. (1997). Seasonal food habits of bobcats (Lynx rufus) in subtropical Baja California Sur, Mexico. Canadian Journal of Zoology, 75, 478-483. Deutsch C.J., Self-Sullivan C. & Mignucci-Giannoni A. (2008). Trichechus manatus. In: IUCN 2012. IUCN Red List of Threatened Species. Version 2012.2. < www.iucnredlist.org >. Downloaded on 19 October 2012. Di Beneditto A.P.M. & Siciliano S. (2007). Stomach contents of the marine tucuxi dolphin (Sotalia guianensis) from Rio de Janeiro, southeastern Brazil. Journal of the Marine Biological Association of the United Kingdom, 87, 253-254. Dial K.P. (1988). Three sympatric species of Neotoma: dietary specialization and coexistence. Oecologia, 76, 531-537. Dietz R., Heide-Jorgensen M.P., Richard P., Orr J., Laidre K.L. & Schmidt H.C. (2008). Movements if narwhals (Monodon monoceros) from Admiralty Inlet monitored by satellite telemetry. Polar Biology, 31, 1295-1306. Djawdan M. & Garland Jr T. (1988). Maximal running speeds of bipedal and quadrupedal rodents. Journal of Mammalogy, 765-772. Domning D., Anderson P.K. & Turvey S. (2008). Hydrodamalis gigas. In: IUCN 2012. IUCN Red List of Threatened Species. Version 2012.2. < www.iucnredlist.org >. Downloaded on 19 October 2012. Dunham J.S. & Duffus D.A. (2002). Foraging patterns of gray whales in central Clayoquot Sound, British Columbia, Canada. Marine Ecology Progress Series, 223, 299-310.

258

Dunham K.M. (1980). The diet of impala (Aepyceros melampus) in the Sengwa Wildlife Research Area, Rhodesia. Journal of Zoology, 192, 41- 57. Dwarakanath S. (1971). The influence of body size and temperature upon the oxygen consumption in the millipede,Spirostreptus asthenes(Pocock). Comparative Biochemistry and Physiology Part A: Physiology, 38, 351-358. Eder E. & Lewis M. (2005). Proximate composition and energetic value of demersal and pelagic prey species from the SW Atlantic Ocean. Marine Ecology Progress Series, 291, 43-52. Elmhagen B., Tannerfeldt M., Verucci P. & Angerbjörn A. (2000). The arctic fox (Alopex lagopus): an opportunistic specialist. Journal of Zoology, 251, 139-149. Elwin S., Meyer M.A., Best P.B., Kotze P.G.H., Thronton M. & Swanson S. (2006). Range and movements of female Heaviside's dolphins (Cephalorhynchus heavisidii), as determined by satellite-linked telemetry. Journal of Mammalogy, 87, 866-877. Estrada A. & Coates-Estrada R. (1985). A preliminary study of resource overlap between howling monkeys (Alouatta palliata) and other arboreal mammals in the tropical rain forest of Los Tuxtlas, Mexico. American Journal of Primatology, 9, 27-37. Ferguson S.H., Taylor M.K., Born E.W., Rosing-Asvid A. & Messier F. (1999). Determinants of home range size for polar bears (Ursus maritimus). Ecology Letters, 2, 311-318. Fiedler P.C., Reilly S.B., Hewitt R.P., Demer D., Philbrick V.A., Smith S., Armstrong W., Croll D.A., Tershy B.R. & Mate B.R. (1998). Blue whale habitat and prey in the California Channel Islands. Deep Sea Research Part II: Topical Studies in Oceanography, 45, 1781-1801. Finley K.J. & Gibb E.J. (1982). Summer diet of the narwhal (Monodon monoceros) in Pond Inlet, northern Baffin Island. Canadian Journal of Zoology, 60, 3353-3363. Flores P.A. & Bazzalo M. (2004). Home ranges and movement patterns of the marine tucuxi dolphin, Sotalia fluviatilis, in Baia Norte, Southern Brazil. Latin American Journal of Aquatic Mammals, 3, 37-52. Ford J.K.B., Ellis G.M., Barrett-Lennard L.G., Morton A.B., Palm R.S. & Balcomb III K.C. (1998). Dietary specialization in two sympatric populations of killer whales (Orcinus orca) in coastal British Columbia and adjacent waters. Canadian Journal of Zoology, 76, 1456- 1471. Freeman P.W. & Lemen C.A. (2008). A simple morphological predictor of bite force in rodents. Journal of Zoology, 275, 418-422. Friedlaender A.S., Fraser W.R., Patterson D., Qian S.S. & Halpin P.N. (2008). The effects of prey demography on humpback whale (Megaptera novaeangliae) abundance around Anvers Island, Antarctica. Polar Biology, 31, 1217-1224. Froese R. & Pauly D. (2011). Fishbase < www.fishbase.org > Accessed 20 August 2012 Gaskin D.E. & Cawthorn M.W. (1967). Diet and feeding habits of the sperm whale (Physeter catodon L.) in the Cook Strait region of New Zealand. New Zealand Journal of Marine and Freshwater Research, 1, 156-179. Gatti A., Bianchi R., Rosa C.R.X. & Mendes S.L. (2006). Diet of two sympatric carnivores, Cerdocyon thous and Procyon cancrivorus, in a restinga area of Espirito Santo State, Brazil. Journal of Tropical Ecology, 22, 227-230. Geffen E., Hefner R., MacDonald D.W. & Ucko M. (1992). Diet and foraging behavior of Blanford's foxes, Vulpes cana, in Israel. Journal of Mammalogy, 395-402.

259

Gil-Sánchez J., Ballesteros-Duperón E. & Bueno-Segura J. (2006). Feeding ecology of the Iberian lynxLynx pardinus in eastern Sierra Morena (Southern Spain). Acta Theriologica, 51, 85-90. Giuliano W.M., Litvaitis J.A. & Stevens C.L. (1989). Prey Selection in Relation to Sexual Dimorphism of Fishers (Martes pennanti) in New Hampshire. Journal of Mammalogy, 70, 639-641. Glaser S.M. (2010). Interdecadal variability in predator-prey interactions of juvenile North Pacific albacore in the California Current System. Marine Ecology Progress Series, 414, 209-221. Godoy E.A.S., Almeida T.C.M. & Zalmon I.R. (2002). Fish assemblages and environmental variables on an artificial reef north of Rio de Janeiro, Brazil. ICES Journal of Marine Science: Journal du Conseil, 59, S138-S143. Goszczyński J., Jedrzejewska B. & Jedrzejewski W. (2000). Diet composition of badgers (Meles meles) in a pristine forest and rural habitats of Poland compared to other European populations. Journal of Zoology, 250, 495-505. Griffen B.D., DeWitt T.H. & Langdon C. (2004). Particle removal rates by the mud shrimp Upogebia pugettensis, its burrow, and a commensal clam: effects on estuarine phytoplankton abundance. Marine Ecology Progress Series, 269, 223. Grobler J. (1983). Feeding habits of the Cape Mountain Zebra Equus zebra zebra LINN. 1758. Koedoe-African Protected Area Conservation and Science, 26, 159-168. Haim A., Saarela S., Hohtola E. & Zisapel N. (2004). Daily rhythms of oxygen consumption, body temperature, activity and melatonin in the Norwegian lemming Lemmus lemmus under northern summer photoperiod. Journal of Thermal Biology, 29, 629-633. Hall-Aspland S. & Rogers T.L. (2004). Summer diet of leopard seals (Hydrurga leptonyx) in Prydz Bay, Eastern Antarctica. Polar Biology, 27, 729-734. Hammill M. & Stenson G. (2000). Estimated prey consumption by harp seals (Phoca groenlandica), hooded seals (Cystophora cristata), grey seals (Halichoerus grypus) and harbour seals (Phoca vitulina) in Atlantic Canada. Journal of Northwest Atlantic Fishery Science, 26, 1- 24. Harestad A.S. & Bunnel F.L. (1979). Home range and body weight- a reevaluation. Ecology, 60, 389-402. Hart J.L. (1973). Pacific fishes of Canada. Fisheries Research Board of canada(Bull. 180), Ottawa, Canada. 749, 1973. Hartnoll R.G., Baine M.S.P., Grandas Y., James J. & Atkin H. (2006). Population biology of the black land crab, Gecarcinus ruricola, in the San Andres Archipelago, Western Caribbean. Journal of Crustacean Biology, 26, 316-325. Hayward M.W. (2006a). Prey preferences of the spotted hyaena (Crocuta crocuta) and degree of dietary overlap with the lion (Panthera leo). Journal of Zoology, 270, 606-614. Hayward M., Henschel P., O'brien J., Hofmeyr M., Balme G. & Kerley G. (2006b). Prey preferences of the leopard (Panthera pardus). Journal of Zoology, 270, 298-313. Hayward M., Jędrzejewski W. & Jędrzewska B. (2012). Prey preferences of the tiger Panthera tigris. Journal of Zoology. Hayward M.W. & Kerley G.I.H. (2005). Prey preferences of the lion (Panthera leo). Journal of Zoology, 267, 309-322. Hayward M.W. & Kerley G.I.H. (2008). Prey preferences and dietary overlap amongst Africa's large predators. South African Journal of Wildlife Research, 38, 93-108.

260

Heide-Jorgensen M.P., Dietz R., Laidre K.L. & Richard P. (2002). Autumn movements, home ranges, and winter density of narwhals (Monodon monoceros) tagged in Tremblay Sound, Baffin Island. Polar Biology, 25, 331-341. Heide-Jørgensen M.P., Laidre K., Borchers D., Samarra F. & Stern H. (2007). Increasing abundance of bowhead whales in West Greenland. Biology Letters, 3, 577-580. Hirsch B.T. (2009). Seasonal variation in the diet of ring-tailed coatis (Nasua nasua) in Iguazu, Argentina. Journal of Mammalogy, 90, 136-143. Hjelset A., Andersen M., Gjertz I., Lydersen C. & Gulliksen B. (1999). Feeding habits of bearded seals (Erignathus barbatus) from the Svalbard area, Norway. Polar Biology, 21, 186-193. Hobbs R.C., Laidre K.L., Vos D.J., Mahoney B.A. & Eagleton M. (2005). Movements and Area Use of Belugas, Delphinapterus lencas, in a Subarctic Alaskan Estuary. Arctic, 58, 331-340. How R. & Hillcox S. (2000). Brushtail possum, Trichosurus vulpecula, populations in south-western Australia: demography, diet and conservation status. Wildlife Research, 27, 81-89. Hückstädt L., Burns J., Koch P., McDonald B., Crocker D. & Costa D. (2012). Diet of a specialist in a changing environment: the crabeater seal along the western Antarctic Peninsula. Marine Ecology Progress Series, 455, 287. Hunter J. & Macewicz B.J. (1980). Sexual maturity, batch fecundity, spawning frequency, and temporal pattern of spawning for the northern anchovy, Engraulis mordax, during the 1979 spawning season. CalCOFI Rep, 21, 139-149. Irwin L.L. (1985). Foods of moose, Alces alces, and white-tailed deer, Odocoileus virginianus, on a burn in boreal forest. Canadian field- naturalist. Ottawa ON, 99, 240-245. Jaeger M.M., Haque E., Sultana P. & Bruggers R.L. (2007). Daytime cover, diet and space-use of golden jackals (Canis aureus) in agro- ecosystems of Bangladesh. Mammalia, 71, 1-10. Jarman S.N., Gales N.J., Tierney M., Gill P.C. & Elliott N.G. (2002). A DNA-based method for identification of krill species and its application to analysing the diet of marine vertebrate predators. Molecular Ecology, 11, 2679-2690. Jędrzejewska B., Sidorovich V.E., Pikulik M.M. & Jędrzejewska W. (2001). Feeding habits of the otter and the American mink in Białowieża Primeval Forest (Poland) compared to other Eurasian populations. Ecography, 24, 165-180. Jędrzejewski W. & Jędrzejewska B. (1992). Foraging and diet of the red fox Vulpes vulpes in relation to variable food resources in Biatowieza National Park, Poland. Ecography, 15, 212-220. Jędrzejewski W., Jędrzejewska B. & Szymura L. (1995). Weasel Population Response, Home Range, and Predation on Rodents in a Deciduous Forest in Poland. Ecology, 76, 179-195. Jefferson T.A., Leatherwood S. & Webber M.A. (2003). FAO species identification guide. Marine mammals of the world., Rome. Jefferson T.A., Webber M.A. & Pitman R.L. (2008). Marine mammals of the world., Amsterdam. Johnston D.W., Westgate A.J. & Read A.J. (2005). Effects of fine-scale oceanographic features on the distribution and movements of harbour porpoises Phocoena phocoena in the Bay of Fundy. Marine Ecology Progress Series, 295, 279-293. Johnstone I. & Hudson B. (1981). The dugong diet: mouth sample analysis. Bulletin of Marine Science, 31, 681-690.

261

Jones K.E., Bielby J., Cardillo M., Fritz S.A., O'Dell J., Orme C.D.L., Safi K., Sechrest W., Boakes E.H., Carbone C., Connolly C., Cutts M.J., Foster J.K., Grenyer R., Habib M., Plaster C.A., Price S.A., Rigby E.A., Rist J., Teacher A., Bininda-Emonds O.R.P., Gittleman J.L., Mace G.M., Purvis A. & Michener W.K. (2009). PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology, 90, 2648-2648. Julien-Laferrière D. (1999). Foraging strategies and food partitioning in the neotropical frugivorous mammals Caluromys philander and Potos flavus. Journal of Zoology, 247, 71-80. Julshamn K., Lundebye A.K., Heggstad K., Berntssen M. & Boe B. (2004). Norwegian monitoring programme on the inorganic and organic contaminants in fish caught in the Barents Sea, Norwegian Sea and North Sea, 1994–2001. Food additives and contaminants, 21, 365- 376. Katzner T.E. & Parker K.L. (1997). Vegetative characteristics and size of home ranges used by pygmy rabbits (Brachylagus idahoensis) during winter. Journal of Mammalogy, 1063-1072. Kays R.W. (1999). Food preferences of kinkajous (Potos flavus): a frugivorous carnivore. Journal of Mammalogy, 589-599. Kelt D.A. & van Vuren D.H. (2001). The Ecology and Macroecology of Mammalian Home Range Area. The American Naturalist, 157, 637-645. Kenney R.D., Hyman M.A.M., Owen R.E., Scott G.P. & Winn H.E. (1986). Estimation of prey densities required by western North Atlantic right whales. Marine Mammal Science, 2, 1-13. Kenney R.D., Scott G.P., Thompson T.J. & Winn H.E. (1997). Estimates of prey consumption and trophic impacts of cetaceans in the USA northeast continental shelf ecosystem. Journal of Northwest Atlantic Fishery Science, 22, 155-171. Keuroghlian A. & Eaton D. (2008). Importance of rare habitats and riparian zones in a tropical forest fragment: preferential use by Tayassu pecari, a wide-ranging frugivore. Journal of Zoology, 275, 283-293. Kjesbu O. (1989). The spawning activity of cod, Gadus morhua L. Journal of fish biology, 34, 195-206. Kock K.H., Pshenichnov L., Jones C.D., Gröger J. & Riehl R. (2008). The biology of the spiny icefish Chaenodraco wilsoni Regan, 1914. Polar Biology, 31, 381-393. Køie M., Steffensen J.F., Møller P.R. & Christiansen J.S. (2008). The parasite fauna of Arctogadus glacialis (Peters)(Gadidae) from western and eastern Greenland. Polar Biology, 31, 1017-1021. Kuhn C.E., McDonald B.I., Shaffer S.A., Barnes J., Crocker D.E., Burns J. & Costa D.P. (2006). Diving physiology and winter foraging behavior of a juvenile leopard seal (Hydrurga leptonyx). Polar Biology, 29, 303-307. Kuntzsch V. & Nel J. (2008). Diet of bat-eared foxes Otocyon megalotis in the Karoo. Koedoe-African Protected Area Conservation and Science, 35, 37-48. Kurle C.M. & Worthy G.A.J. (2001). Stable isotope assessment of temporal and geographic differences in feeding ecology of northern fur seals (Callorhinus ursinus) and their prey. Oecologia, 126, 254-265. Kutt A.S. (2012). Feral cat (Felis catus) prey size and selectivity in north-eastern Australia: implications for mammal conservation. Journal of Zoology, 287, 292-300.

262

Kvitek R., Oliver J., DeGange A. & Anderson B. (1992). Changes in Alaskan soft-bottom prey communities along a gradient in sea otter predation. Ecology, 413-428. Le Comber S.C., Spinks A.C., Bennett N.C., Jarvis J.U.M. & Faulkes C.G. (2002). Fractal dimension of African mole-rat burrows. Canadian Journal of Zoology, 80, 436-441. LeBoeuf B.J., Crocker D.E., Costa D.P., Blackwell S.B., Webb P.M. & Houser D.S. (2000). Foraging ecolog of Northern Elephant Seals. . Ecological Monographs, 70, 353-382. List R. & Macdonald D.W. (2003). Home range and habitat use of the kit fox (Vulpes macrotis) in a prairie dog (Cynomys ludovicianus) complex. Journal of Zoology, 259, 1-5. Lockyer C. (1976). Body weights of some species of large whales. Journal du Conseil, 36, 259-273. Lodé T. (1997). Trophic status and feeding habits of the European Polecat Mustela putorius L. 1758. Mammal Review, 27, 177-184. MacLeod C., Santos M. & Pierce G. (2003). Review of data on diets of beaked whales: evidence of niche separation and geographic segregation. Journal of the Marine Biological Association of the UK, 83, 651-665. Marino J., Mitchell R. & Johnson P.J. (2010). Dietary specialization and climatic-linked variations in extant populations of Ethiopian wolves. African Journal of Ecology, 48, 517-525. Martinoli A., Preatoni D.G., Chiarenzi B., Wauters L.A. & Tosi G. (2001). Diet of stoats (Mustela erminea) in an Alpine habitat:The importance of fruit consumption in summer. Acta Oecologica, 22, 45-53. Maser Z., Maser C. & Trappe J.M. (1985). Food habits of the northern flying squirrel (Glaucomys sabrinus) in Oregon. Canadian Journal of Zoology, 63, 1084-1088. Mayo C.A. & Marx M.K. (1990). Surface foraging behaviour of the North Atlantic right whale, Eubalaena glacialis, and associated zooplankton characteristics. Canadian Journal of Zoology, 68, 2214-2220. McMahon B., McDonald D. & Wood C. (1979). Ventilation, oxygen uptake and haemolymph oxygen transport, following enforced exhausting activity in the Dungeness crab Cancer magister. Journal of Experimental Biology, 80, 271-285. McNab B.K. (1995). Energy expenditure and conservation in frugivorous and mixed-diet carnivorans. Journal of Mammalogy, 76, 206-222. Menge B.A. (1975). Brood or broadcast? The adaptive significance of different reproductive strategies in the two intertidal sea stars Leptasterias hexactis and Pisaster ochraceus. Marine Biology, 31, 87-100. Meredith R.W., Westerman M. & Springer M.S. (2008). A phylogeny and timescale for the living genera of kangaroos and kin (Macropodiformes: Marsupialia) based on nuclear DNA sequences. Australian journal of zoology, 56, 395-410. Merrick R.L. & Loughlin T.R. (1997). Foraging behaviour of adult female and young-of-the-year Steller sea lions in Alaskan waters. Canadian Journal of Zoology, 75, 776-786. Metz M.C., Smith D.W., Vucetich J.A., Stahler D.R. & Peterson R.O. (2012). Seasonal patterns of predation for gray wolves in the multi-prey system of Yellowstone National Park. Journal of Animal Ecology, 81, 553-563. Meynier L., Mackenzie D.D.S., Duignan P.J., Chilvers B.L. & Morel P.C.H. (2009). Variability in the diet of New Zealand sea lion (Phocarctos hookeri) at the Auckland Islands, New Zealand. Marine Mammal Science, 25, 302-326.

263

Michener G.R. (2004). Hunting techniques and tool use by North American badgers preying on Richardson's ground squirrels. Journal of Mammalogy, 85, 1019-1027. Milton K. & May M.L. (1976). Body weight, diet and home range area in primates. Nature, 259, 459. Mizdalski E. (1988). Weight and length data of zooplankton in the Weddell Sea in austral spring 1986 (ANT V/3). Berichte zur Polarforschung (Reports on Polar Research), 55. Moreno R.S., Kays R.W. & Samudio Jr R. (2006). Competitive release in diets of ocelot (Leopardus pardalis) and puma (Puma concolor) after jaguar (Panthera onca) decline. Journal of Mammalogy, 87, 808-816. Morton A. (2006). Occurrence, photo-identification and prey of pacific white-sided dolphins (Lagenorhyncus obliquidens) in the Broughton Archipelago, Canada 1984–1998. Marine Mammal Science, 16, 80-93. Mukherjee S., Goyal S.P., Johnsingh A.J.T. & Leite Pitman M.R.P. (2004). The importance of rodents in the diet of jungle cat (Felis chaus), caracal (Caracal caracal) and golden jackal (Canis aureus) in Sariska Tiger Reserve, Rajasthan, India. Journal of Zoology, 262, 405- 411. Muñoz G.A. & Williams J.B. (2005). Basal metabolic rate in carnivores is associated with diet after controlling for phylogeny. Physiological and Biochemical Zoology, 78, 1039-1056. Myhre R. & Myrberget S. (1975). Diet of Wolverines (Gulo gulo) in Norway. Journal of Mammalogy, 56, 752-757. Naya D.E., Arim M. & Vargas R. (2002). Diet of South American fur seals (Arctocephalus australis) in Isla de Lobos, Uruguay. Marine Mammal Science, 18, 734-745. Noguchi G.E. & Hesselberg R.J. (1991). Parental transfer of organic contaminants to young-of-the-year spottail shiners, Notropis hudsonius. Bulletin of environmental contamination and toxicology, 46, 745-750. Noren S.R. & Williams T.M. (2000). Body size and skeletal muscle myoglobin of cetaceans: adaptations for maximizing dive duration. Comparative Biochemistry and Physiology - Part A: Molecular & Integrative Physiology, 126, 181-191. Nowak S., Mysłajek R.W., Kłosińska A. & Gabryś G. (2011). Diet and prey selection of wolves (Canis lupus) recolonising Western and Central Poland. Mammalian Biology - Zeitschrift für Säugetierkunde, 76, 709-715. O'Driscoll R.L., Macaulay G.J., Gauthier S., Pinkerton M. & Hanchet S. (2011). Distribution, abundance and acoustic properties of Antarctic silverfish (Pleuragramma antarcticum) in the Ross Sea. Deep Sea Research Part II: Topical Studies in Oceanography, 58, 181-195. Odden J., Linnell J.C. & Andersen R. (2006). Diet of Eurasian lynx, Lynx lynx, in the boreal forest of southeastern Norway: the relative importance of livestock and hares at low roe deer density. Eur J Wildl Res, 52, 237-244. Oshima J., E. D., Santos M.C., Bazzalo M., Flores P.A.d.C. & Pupim F.d.N. (2010). Home ranges of Guiana dolphins ( Sotalia guianensis) (Cetacea: Delphinidae) in the Cananéia estuary, Brazil. Journal of the Marine Biological Association of the United Kingdom, 90, 1641- 1647. Palace V.P., Allen-Gil S.M., Brown S.B., Evans R.E., Metner D.A., Landers D.H., Curtis L.R., Klaverkamp J.F., Baron C.L. & Lyle Lockhart W. (2001). Vitamin and thyroid status in arctic grayling (Thymallus arcticus) exposed to doses of 3, 3′, 4, 4′-tetrachlorobiphenyl that induce the phase I enzyme system. Chemosphere, 45, 185-193.

264

Paltridge R., Gibson D. & Edwards G. (1997). Diet of the Feral Cat (Felis catus) in Central Australia. Wildlife Research, 24, 67-76. Parker G.R. (1986). The seasonal diet of coyotes, Canis latrans, in northern New Brunswick. Canadian Field-Naturalist, 100, 74-77. Pauly D., Trites A.W., Capuli E. & Christensen V. (1998). Diet composition and trophic levels of marine mammals. ICES Journal of Marine Science: Journal du Conseil, 55, 467-481. Pitman R.L. & Ensor P. (2003). Three forms of killer whales (Orcinus orca) in Antarctic waters. Journal of Cetacean Research and Management, 5, 131-140. Plötz J., McIntyre T., Bester M.N. & Bornemann H. (2009). At surface behaviour at location on spot of Weddell seal NEU2008_wed_u_m_17 from Atka Bay. Alfred Wegener Institute for Polar and Marine Research, Bremerhaven. doi:10.1594/PANGAEA.714638. Pomerleau C., Ferguson S.H. & Walkusz W. (2011). Stomach contents of bowhead whales (Balaena mysticetus) from four locations in the Canadian Arctic. Polar Biology, 34, 615-620. Poole K.G. (2003). A review of the Canada lynx, Lync canadensis, in Canada. The Canadian Field- Naturalist, 117, 360-376. Popowics T.E. & Fortelius M. (1997). On the cutting edge: tooth blade sharpness in herbivorous and faunivorous mammals. In: Annales Zoologici Fennici. Helsinki: Suomen Biologian Seura Vanamo, 1964-, pp. 73-88. Powell J. & Kouadio A. (2008). Trichechus senegalensis. In: IUCN 2012. IUCN Red List of Threatened Species. Version 2012.2. < www.iucnredlist.org >. Downloaded on 19 October 2012. Pradhan N.M.B., Wegge P., Moe S.R. & Shrestha A.K. (2008). Feeding ecology of two endangered sympatric megaherbivores: Asianelephant Elephas maximus and greater one-horned rhinoceros Rhinoceros unicornis in lowland Nepal. Wildlife Biology, 14, 147-154. Price M.R.S. (1978). The nutritional ecology of Coke's hartebeest (Alcelaphus buselaphus cokei) in Kenya. Journal of Applied Ecology, 33-49. Pritchard A. & Eddy S. (1979). Lactate formation in Callianassa californiensis and Upogebia pugettensis (Crustacea: Thalassinidea). Marine Biology, 50, 249-253. Pusineri C., Magnin V., Meynier L., Spitz J., Hassani S. & Ridoux V. (2007). Food and feeding ecology of the common dolphin (Delphinus delphis) in the oceanic northeast Atlantic and comparison with its diet in neritic areas. Marine Mammal Science, 23, 30-47. Quitral V., Donoso M.L., Ortiz J., Herrera M.V., Araya H. & Aubourg S.P. (2009). Chemical changes during the chilled storage of Chilean jack mackerel (Trachurus murphyi): Effect of a plant-extract icing system. LWT-Food Science and Technology, 42, 1450-1454. Ralls K., Eagle T.C. & Siniff D.B. (1996). Movement and spatial use patterns of California sea otters. Canadian Journal of Zoology, 74, 1841- 1849. Ray J. & Sunquist M. (2001). Trophic relations in a community of African rainforest carnivores. Oecologia, 127, 395-408. Reichle D. (1968). Relation of body size to food intake, oxygen consumption, and trace element metabolism in forest floor arthropods. Ecology, 538-542. Reid D., Code T., Reid A. & Herrero S. (1994). Food habits of the river otter in a boreal ecosystem. Canadian Journal of Zoology, 72, 1306- 1313. Reid F. & Helgen K. (2008). Mustela frenata. In: IUCN 2012. IUCN Red List of Threatened Species. Version 2012.2. < www.iucnredlist.org >. Downloaded on 16 May 2012.

265

Reidenburg J.S. & Laitman J.T. (2009). Cetacean Prenatal Development. In: Encyclopedia of Marine Mammals, 2nd Edition (eds. Perrin WF, Wursig B & Thewissen HGM). Academic Press San Diego. Reimers E., Klein D.R. & Sørumgård R. (1983). Calving time, growth rate, and body size of Norwegian reindeer on different ranges. Arctic and Alpine Research, 107-118. Rishworth C., McIlroy J. & Tanton M. (1995). Diet of the Common Wombat, Vombatus Ursinus, in Plantations of Pinus Radiata. Wildlife Research, 22, 333-339. Ritz D.A. & Hosie G.W. (1982). Production of the euphausiid Nyctiphanes australis in Storm Bay, south-eastern Tasmania. Marine Biology, 68, 103-108. Robinson J.G. & Redford K.H. (1986). Body size, diet, and population density of Neotropical forest mammals. American Naturalist, 665-680. Robinson S., Goldsworthy S., Van den Hoff J. & Hindell M. (2003). The foraging ecology of two sympatric fur seal species, Arctocephalus gazella and Arctocephalus tropicalis, at Macquarie Island during the austral summer. Marine and Freshwater Research, 53, 1071-1082. Rodríguez D., Rivero L. & Bastida R. (2002). Feeding ecology of the franciscana (Pontoporia blainvillei) in marine and estuarine waters of Argentina. Latin American Journal of Aquatic Mammals, 1, 77-94. Romero M.A., Dans S.L., García N., Svendsen G.M., González R. & Crespo E.A. (2011). Feeding habits of two sympatric dolphin species off North Patagonia, Argentina. Marine Mammal Science, 28, 364-377. Rood J.P. (1975). Population dynamics and food habits of the banded mongoose. African Journal of Ecology, 13, 89-111. Ruiz-Capillas C. & Moral A. (2001). Residual effect of CO2 on hake (Merluccius merluccius L.) stored in modified and controlled atmospheres. European Food Research and Technology, 212, 413-420. Santos M., Pierce G., Herman J., Lopez A., Guerra A., Mente E. & Clarke M. (2001a). Feeding ecology of Cuvier's beaked whale (Ziphius cavirostris): a review with new information on the diet of this species. JMBA-Journal of the Marine Biological Association of the United Kingdom, 81, 687-694. Santos M., Pierce G., Learmonth J., Reid R., Ross H., Patterson I., Reid D. & Beare D. (2004). Variability in the diet of harbor porpoises (Phocoena phocoena) in Scottish waters 1992–2003. Marine Mammal Science, 20, 1-27. Santos M., Pierce G., Reid R., Patterson I., Ross H. & Mente E. (2001b). Stomach contents of bottlenose dolphins (Tursiops truncatus) in Scottish waters. Journal of the Marine Biological Association of the UK, 81, 873-878. Santos R. & Haimovici M. (1997). Reproductive biology of winter-spring spawners of Illex argentinus (Cephalopoda: Ommastrephidae) off southern Brazil. Scientia Marina(Barcelona), 61, 53-64. Santos R. & Haimovici M. (1998). Trophic relationships of the long-finned squid Loligo sanpaulensis on the southern Brazilian shelf. South African Journal of Marine Science, 20, 81-91. Schitoskey Jr F. & Woodmansee S.R. (1978). Energy requirements and diet of the California ground squirrel. The Journal of Wildlife Management, 373-382. Scott D.M. & Dunstone N. (2000). Environmental determinants of the composition of desert-living rodent communities in the north-east Badia region of Jordan. Journal of Zoology, 251, 481-494.

266

Seibel B.A., Thuesen E.V., Childress J.J. & Gorodezky L.A. (1997). Decline in pelagic cephalopod metabolism with habitat depth reflects differences in locomotory efficiency. The Biological Bulletin, 192, 262-278. Sinclair E.H. & Zeppelin T.K. (2002). Seasonal and spatial differences in diet in the western stock of Steller sea lions (Eumetopias jubatus). Journal of Mammalogy, 83, 973-990. Sjöberg M. & Ball J.P. (2000). Grey seal, Halichoerus grypus, habitat selection around haulout sites in the Baltic Sea: bathymetry or central- place foraging? Canadian Journal of Zoology, 78, 1661-1667. Skinner J. & Klages N. (1994). On some aspects of the biology of the Ross seal Ommatophoca rossii from King Haakon VII Sea, Antarctica. Polar Biology, 14, 467-472. Skog T.E., Hylland K., Torstensen B.E. & Berntssen M.H.G. (2003). Salmon farming affects the fatty acid composition and taste of wild saithe Pollachius virens L. Aquaculture Research, 34, 999-1007. Slip D.J. (1995). The diet of southern elephant seals (Mirounga leonina) from Heard Island. Canadian Journal of Zoology, 73, 1519-1528. Smith R., Paul A. & Paul J. (1988). Aspects of energetics of adult walleye pollock, Theragra chalcogramma (Pallas), from Alaska. Journal of fish biology, 33, 445-454. Smith R.J., Cox T.M. & Westgate A.J. (2006). Movements of harbor seals (phoca vitulina mellonae) in Lacs des Loups Marins, Quebec. Marine Mammal Science, 22, 480-485. Smout S. & Lindstrøm U. (2007). Multispecies functional response of the minke whale Balaenoptera acutorostrata based on small-scale foraging studies. Marine Ecology Progress Series, 341, 277-291. Southwell C. (2005). Diving behaviour of two Ross seals off east Antarctica. Wildlife Research, 32, 63-65. Southwell C. (2007). 1994 to 2000 - Antarctic Pack Ice Seals APIS) Survey, Australian Antarctic Data Centre - ARGOS satellite tracking record < http://data.aad.gov.au/aadc/argos/profile_list.cfm?taxon_id=25 >. Southwell C., Kerry K., Ensor P., Woeler E.J. & Rogers T. (2003). The timing of pupping by pack-ice seals in East Antarctica. Polar Biology, 26, 648-652. Sovada M.A., Roaldson J.M. & Sargeant A.B. (1999). Foods of American badgers in west-central Minnesota and southeastern North Dakota during the duck nesting season. The American midland naturalist, 142, 410-414. Staniland I., Gales N., Warren N., Robinson S., Goldsworthy S. & Casper R. (2010). Geographical variation in the behaviour of a central place forager: Antarctic fur seals foraging in contrasting environments. Marine Biology, 157, 2383-2396. Stuart C. & Stuart T. (2001). Field guide to mammals of Southern Africa, Third Edition. Struik Publishers, Cape Town. Sutor A., Kauhala K. & Ansorge H. (2010). Diet of the raccoon dog Nyctereutes procyonoides—a canid with an opportunistic foraging strategy. Acta Theriologica, 55, 165-176. Swihart R.K. (1986). Home Range—Body Mass Allometry in Rabbits and Hares (Leporidae). Acta Theriologica, 31, 139-148. Taber A.B., Doncaster C.P., Neris N.N. & Colman F.H. (1993). Ranging behavior and population dynamics of the Chacoan peccary, Catagonus wagneri. Journal of Mammalogy, 443-454.

267

Taylor R.J. (1992). Seasonal changes in the diet of the Tasmanian bettong (Bettongia gaimardi), a mycophagous marsupial. Journal of Mammalogy, 408-414. Tershy B.R. (1992). Body size, diet, habitat use, and social behavior of Balaenoptera whales in the Gulf of California. Journal of Mammalogy, 477-486. Thiel C. (2011). Ecology and population status of the Serval Leptailurus serval (Schriber, 1776) in Zambia. In. PhD Thesis, Universitäts-und Landesbibliothek, Bonn. Thompson D., Duck C.D., McConnell B.J. & Garrett J. (1998). Foraging behaviour and diet of lactating female southern sea lions (Otaria flavescens) in the Falkland Islands. Journal of Zoology, 246, 135-146. Tiunov A.V. & Scheu S. (2004). Carbon availability controls the growth of detritivores (Lumbricidae) and their effect on nitrogen mineralization. Oecologia, 138, 83-90. Van Pelt T.I., Piatt J.F., Lance B.K. & Roby D.D. (1997). Proximate composition and energy density of some North Pacific forage fishes. Comparative Biochemistry and Physiology Part A: Physiology, 118, 1393-1398. Vilhjálmsson H. (2002). Capelin (Mallotus villosus) in the Iceland–East Greenland–Jan Mayen ecosystem. ICES Journal of Marine Science: Journal du Conseil, 59, 870-883. Virgós E., Mangas J.G., Blanco-Aguiar J.A., Garrote G., Almagro N. & Viso R.P. (2004). Food habits of European badgers (Meles meles) along an altitudinal gradient of Mediterranean environments: a field test of the earthworm specialization hypothesis. Canadian Journal of Zoology, 82, 41-51. Walker W.A., Mead J.G. & Brownell R.L. (2002). Diets of Baird's beaked whales, Berardius bairdii, in the southern sea of Okhotsk and off the pacific coast of Honshu, Japan. Marine Mammal Science, 18, 902-919. Wang E. (2002). Diets of Ocelots (Leopardus pardalis), Margays (L. wiedii), and Oncillas (L. tigrinus) in the Atlantic Rainforest in Southeast Brazil. Studies on Neotropical Fauna and Environment, 37, 207-212. Watanabe H., Moku M., Kawaguchi K., Ishimaru K. & Ohno A. (2001). Diel vertical migration of myctophid fishes (Family Myctophidae) in the transitional waters of the western North Pacific. Fisheries Oceanography, 8, 115-127. Węsławski J.M., Kwaśniewski S., Stempniewicz L. & Błachowiak-Samołyk K. (2006). Biodiversity and energy transfer to top trophic levels in two contrasting Arctic fjords. Polish Polar Research, 27, 259-278. West K., Walker W., Baird R., White W., Levine G., Brown E. & Schofield D. (2009). Diet of Pygmy Sperm Whales (Kogia breviceps) in the Hawaiian Archipelago. Publications, Agencies and Staff of the US Department of Commerce, 18. White L.J.T., Tutin C.E.G. & Fernandez M. (2008). Group composition and diet of forest elephants, Loxodonta africana cyclotis Matschie 1900, in the Lopé Reserve, Gabon. African Journal of Ecology, 31, 181-199. Willcox S., Lyle J. & Steer M. (2001). Tasmanian arrow squid fishery—status report 2001. Tasmanian Aquaculture and Fisheries Institute, Hobart. Williams J.B., Lenain D., Ostrowski S., Tieleman B.I. & Seddon P.J. (2002). Energy expenditure and water flux of Rüppell’sfoxes in Saudi Arabia. Physiological and Biochemical Zoology, 75, 479-488.

268

Williamson N.J. & Traynor J.J. (1984). In situ target-strength estimation of Pacific whiting (Merluccius productus) using a dual-beam transducer. Journal du Conseil, 41, 285-292. Wolt R.C., Gelwick F.P., Weltz F. & Davis R.W. (2012). Foraging behavior and prey of sea otters in a soft-and mixed-sediment benthos in Alaska. Mammalian Biology-Zeitschrift für Säugetierkunde. Xavier J., Rodhouse P., Purves M., Daw T., Arata J. & Pilling G. (2002). Distribution of cephalopods recorded in the diet of the Patagonian toothfish (Dissostichus eleginoides) around South Georgia. Polar Biology, 25, 323-330. Zerbini A.N. & Santos M. (1997). First record of the pygmy killer whale Feresa attenuata (Gray, 1874) for the Brazilian coast. Aquatic Mammals, 23, 105-110. Zumholz K., Klügel A., Hansteen T. & Piatkowski U. (2007). Statolith microchemistry traces environmental history of the boreoatlantic armhook squid Gonatus fabricii. Marine Ecology Progress Series, 333, 195-204

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CephalorhynchusMheavisidii CephalorhynchusMcommersonii CephalorhynchusMhectori LagenorhynchusMobliquidens LissodelphisMborealis SotaliaMguianensis SotaliaMfluviatilis TursiopsMtruncatus DelphinusMdelphis FeresaMattenuata GlobicephalaMmelas OrcinusMorca PhocoenaMphocoena DelphinapterusMleucas MonodonMmonoceros PontoporiaMblainvillei MesoplodonMmirus MesoplodonMlayardii MesoplodonMdensirostris MesoplodonMcarlhubbsi HyperoodonMampullatus ZiphiusMcavirostris BerardiusMarnuxii BerardiusMbairdii KogiaMbreviceps PhyseterMcatodon BalaenaMmysticetus EubalaenaMglacialis CapereaMmarginata BalaenopteraMacutorostrata BalaenopteraMedeni BalaenopteraMborealis BalaenopteraMmusculus EschrichtiusMrobustus BalaenopteraMphysalus MegapteraMnovaeangliae MustelaMputorius MustelaMvison MustelaMnivalis MustelaMerminea MustelaMfrenata LontraMcanadensis EnhydraMlutris EiraMbarbara MartesMpennanti MartesMmartes MartesMfoina GuloMgulo MelesMmeles TaxideaMtaxus NasuaMnasua ProcyonMlotor BassariscusMsumichrasti SpilogaleMputorius ArctocephalusMgazella ArctocephalusMtropicalis PhocarctosMhookeri OtariaMflavescens EumetopiasMjubatus ZalophusMcalifornianus CallorhinusMursinus PhocaMvitulina HalichoerusMgrypus CystophoraMcristata ErignathusMbarbatus LobodonMcarcinophaga OmmatophocaMrossii HydrurgaMleptonyx LeptonychotesMweddellii MiroungaMangustirostris MiroungaMleonina UrsusMmaritimus CerdocyonMthous CanisMadustus CanisMsimensis CanisMlupus CanisMlatrans CanisMaureus LycaonMpictus OtocyonMmegalotis VulpesMrueppellii VulpesMvulpes VulpesMvelox VulpesMlagopus VulpesMmacrotis VulpesMcana NyctereutesMprocyonoides AcinonyxMjubatus PumaMconcolor LynxMcanadensis LynxMlynx LynxMpardinus LynxMrufus FelisMchaus FelisMcatus LeopardusMpardalis LeopardusMwiedii CaracalMcaracal LeptailurusMserval PantheraMleo PantheraMpardus PantheraMonca PantheraMtigris CrocutaMcrocuta ProtelesMcristata MungosMmungo GenettaMtigrina

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Figure S6.2 Log10 mean body mass for mammalian carnivores and herbivores living in terrestrial and marine environments ± S.E. Untransformed mean values for terrestrial carnivores (20kg), marine carnivores (9805kg), terrestrial herbivores (190kg) and marine herbivores (4067kg).

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