Science, Faculty of
Oceans and Fisheries, Institute for the
DSpace
UBCV
Gill, Kathleen P.
Master of Science - MSc
University of British Columbia
Migratory movement is integral to the life histories of many animal species, as they travel in pursuit of essential resources, favourable environmental conditions, and reproductive opportunities. The migrations of marine mammals are among the most impressive, spanning vast expanses of open ocean over months at a time. How they navigate this seemingly featureless landscape remains largely unknown, as are the potential environmental cues that may guide them. Southern elephant seals (Mirounga leonina) provide a compelling model for studying open ocean navigation, as they spend most of their lives at sea and migrate thousands of kilometers to reach small, isolated breeding islands. Using ARGOS satellite locations from 271 southern elephant seals tracked across the Southern Ocean between 2009 and 2019, I quantified the characteristics of their long-distance movements and evaluated them against theoretical predictions that assumed reliance on lunar, solar, and geomagnetic environmental cues. I found that the migratory paths of southern elephant seals were remarkably precise and efficient when returning to breeding islands. Individuals maintained straight-line trajectories that accounted for the curvature of the Earth and corrected for drift caused by ocean currents, despite initiating travel from widely dispersed locations. These findings suggest that southern elephant seals are capable of sophisticated navigation, likely guided by specific environmental cues. My results indicate it is unlikely that lunar and solar cues are used for orientation, but the observed movement patterns closely align with predicted use of geomagnetic cues. Seals consistently followed gradients of geomagnetic inclination, total intensity, and declination, with many paths following a combination of two gradients. Sensitivity analyses suggest that successful navigation would require seals to possess high sensitivity to subtle changes in geomagnetic values, whether following individual cue gradients or using them in tandem. This study is among the first to quantitatively characterize the navigational abilities of southern elephant seals and provides some of the first evidence that pinnipeds may use geomagnetic information for navigation and goal-finding. These findings also highlight the utility of tracking information to investigate animal navigation in species that cannot be studied using traditional experimental approaches, advancing understanding of animal movement and ultimately informing conservation.
EVALUATING SOUTHERN ELEPHANT SEAL NAVIGATION THROUGH ANALYSIS OF MOVEMENT PATTERNS AND ASSOCIATED ENVIRONMENTAL CUES by Kathleen P. Gill B.Sc., The University of Washington, 2017 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Oceans and Fisheries) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) September 2025 © Kathleen P. Gill, 2025 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Evaluating Southern Elephant Seal Navigation Through Analysis of Movement Patterns and Associated Environmental Cues submitted by Kathleen P. Gill in partial fulfillment of the requirements for the degree of Master of Science in Oceans and Fisheries Examining Committee: David Rosen, Assistant Professor, Institute for Oceans and Fisheries, UBC Supervisor Andrew Trites, Professor, Institute for the Oceans and Fisheries, UBC Supervisory Committee Member Marie Auger-Méthé, Associate Professor, Institute for the Oceans and Fisheries, UBC Supervisory Committee Member iii Abstract Migratory movement is integral to the life histories of many animal species, as they travel in pursuit of essential resources, favourable environmental conditions, and reproductive opportunities. The migrations of marine mammals are among the most impressive, spanning vast expanses of open ocean over months at a time. How they navigate this seemingly featureless landscape remains largely unknown, as are the potential environmental cues that may guide them. Southern elephant seals (Mirounga leonina) provide a compelling model for studying open ocean navigation, as they spend most of their lives at sea and migrate thousands of kilometers to reach small, isolated breeding islands. Using ARGOS satellite locations from 271 southern elephant seals tracked across the Southern Ocean between 2009 and 2019, I quantified the characteristics of their long-distance movements and evaluated them against theoretical predictions that assumed reliance on lunar, solar, and geomagnetic environmental cues. I found that the migratory paths of southern elephant seals were remarkably precise and efficient when returning to breeding islands. Individuals maintained straight-line trajectories that accounted for the curvature of the Earth and corrected for drift caused by ocean currents, despite initiating travel from widely dispersed locations. These findings suggest that southern elephant seals are capable of sophisticated navigation, likely guided by specific environmental cues. My results indicate it is unlikely that lunar and solar cues are used for orientation, but the observed movement patterns closely align with predicted use of geomagnetic cues. Seals consistently followed gradients of geomagnetic inclination, total intensity, and declination, with many paths following a combination of two gradients. Sensitivity analyses suggest that successful navigation would require seals to possess high sensitivity to subtle changes in geomagnetic values, whether following individual cue gradients or using them in tandem. This study is among the first to quantitatively characterize the navigational abilities of southern elephant seals and provides some of the first evidence that pinnipeds may use geomagnetic information for navigation and goal-finding. These findings also highlight the utility of tracking information to investigate animal navigation in species that cannot be studied using traditional experimental approaches, advancing understanding of animal movement and ultimately informing conservation. iv Lay Summary My study used data obtained from satellite tags to investigate open ocean navigation in marine mammals, with a focus on how seals manage to travel to ocean-based feeding areas and how they successfully return to their land-based breeding colonies. I used locations of southern elephant seals to identify patterns in how they travel (following remarkably straight, efficient paths) and what environmental cues they use to navigate (most likely geomagnetic parameters). My work provides important clues to the mechanisms used by seals when navigating and characterizes long-distance movements of seals in the open ocean. v Preface This thesis represents my original work. The topic of pinniped navigation was proposed by my supervisor Dr. David Rosen and, together, we came up with the research questions and designed the study. I identified a model species and acquired satellite tagging data previously collected for this species from Australiaâs Integrated Marine Observing System (IMOS). IMOS is enabled by the National Collaborative Research Infrastructure Strategy (NCRIS) and is operated by a consortium of institutions as an unincorporated joint venture, with the University of Tasmania as Lead Agent. I adapted existing methodologies from the fields of animal navigation and statistics to process the tagging data and analyze patterns in movement and environmental cue use. Input from committee members Dr. Andrew Trites and Dr. Marie Auger-Méthé were incorporated into the study design and analysis. I formatted data chapters (Chapter 2 and Chapter 3) as manuscripts for submission to peer-reviewed journals. The writing of this thesis is my own and was reviewed and adapted with thanks to my supervisor Dr. David Rosen and my committee members Dr. Trites and Dr. Auger-Méthé. No generative AI was used for any aspect of the work presented. vi Table of Contents Abstract ......................................................................................................................................... iii Lay Summary ............................................................................................................................... iv Preface ............................................................................................................................................ v Table of Contents ......................................................................................................................... vi List of Tables ................................................................................................................................ ix List of Figures ................................................................................................................................ x Acknowledgements ..................................................................................................................... xii Dedication ................................................................................................................................... xiii Chapter 1: General Introduction ................................................................................................ 1 History of Navigation Research .................................................................................................. 2 Methods to Study Animal Navigation ........................................................................................ 4 Challenges Studying Marine Mammal Navigation ..................................................................... 5 Navigation in Marine Mammals ................................................................................................. 7 Southern Elephant Seal Biology ................................................................................................. 9 Thesis Objectives ...................................................................................................................... 10 Chapter 2: On the right track: southern elephant seals maintain accurate courses from diverse starting points during long-distance migration .......................................................... 12 Summary ................................................................................................................................... 12 Introduction ............................................................................................................................... 12 Methods..................................................................................................................................... 16 Instrument Deployment & Data Sources .............................................................................. 16 State-Space Modelling .......................................................................................................... 18 vii Behavioural Classification Using Hidden Markov Models .................................................. 19 Movement Pattern Analysis .................................................................................................. 24 Do seals show consistency in the migration routes they follow? ...................................... 24 How directly do seals return to islands along their migration routes? ............................ 26 What factors influence return timing of seals? ................................................................. 27 Results ....................................................................................................................................... 28 Do seals show consistency in the migration routes they follow? .......................................... 28 How directly do seals return to islands along their migration routes? ................................ 35 What factors influence return timing of seals? ..................................................................... 40 Discussion ................................................................................................................................. 44 Consistency in Movement Direction .................................................................................... 44 Movement Patterns and Navigation Methods ....................................................................... 46 Use of Environmental Cues .................................................................................................. 48 Experience in Navigation ...................................................................................................... 49 Timing of Movement ............................................................................................................ 50 Importance of Understanding Navigation ............................................................................. 54 Chapter 3: No sun, no moon, just magnetism? Evaluating potential cue use by navigating southern elephant seals ............................................................................................................... 57 Summary ................................................................................................................................... 57 Introduction ............................................................................................................................... 58 Methods..................................................................................................................................... 62 Tagging Data & Modelling ................................................................................................... 62 Lunar Cue Use ...................................................................................................................... 63 Solar Cue Use ....................................................................................................................... 64 viii Geomagnetic Cue Use ........................................................................................................... 65 Geomagnetic Cue Sensitivity ................................................................................................ 68 Results ....................................................................................................................................... 70 Lunar Cue Use ...................................................................................................................... 70 Solar Cue Use ....................................................................................................................... 72 Geomagnetic Cue Use ........................................................................................................... 75 Geomagnetic Cue Sensitivity ................................................................................................ 77 Discussion ................................................................................................................................. 82 Lunar Cue Use ...................................................................................................................... 83 Solar Cue Use ....................................................................................................................... 83 Geomagnetic Cue Use ........................................................................................................... 85 Geomagnetic Cue Sensitivity ................................................................................................ 86 Conclusion ............................................................................................................................ 87 Chapter 4: General Discussion .................................................................................................. 89 Summary of Findings ................................................................................................................ 89 Strengths and Limitations ......................................................................................................... 90 Future Directions ...................................................................................................................... 92 Importance of Work .................................................................................................................. 95 References .................................................................................................................................... 96 ix List of Tables Table 1. Counts of southern elephant seals by age class and sex. ................................................ 18 Table 2. Summary statistics of travel segment distances. ............................................................. 23 Table 3. Counts of travel segments by island. .............................................................................. 23 Table 4. Geomagnetic detection thresholds. ................................................................................. 69 x List of Figures Figure 1. Map of southern elephant seal tagging tracks. .............................................................. 19 Figure 2. Decoded behaviour states for one southern elephant seal resulting from the hidden Markov model. ...................................................................................................................... 21 Figure 3. Circular plots of outbound and return bearings in relation to four islands used by southern elephant seals. ........................................................................................................ 29 Figure 4. Circular plots of outbound and return bearings for southern elephant seal age classes. 31 Figure 5. Comparison of difference in outbound and return bearings between repeated trips taken by individual southern elephant seals. .................................................................................. 33 Figure 6. Directional consistency and path overlap between outbound and return tracks of southern elephant seals. ........................................................................................................ 35 Figure 7. Comparison of southern elephant seal return paths to both great circle paths and rhumb lines. ...................................................................................................................................... 36 Figure 8. Bearing changes in relation to distance along return paths of southern elephant seals. 38 Figure 9. Straightness indices of southern elephant seal return paths across age classes. ............ 39 Figure 10. Comparison of straightness indices between repeated trips taken by individual southern elephant seals. ........................................................................................................ 40 Figure 11. Arrival timing of adult female southern elephant seals to breeding beaches. ............. 42 Figure 12. Comparing return track distance and potential drivers of return timing in adult female southern elephant seals. ........................................................................................................ 43 Figure 13. Contour maps showing variation in geomagnetic field parameters across the study area. ....................................................................................................................................... 66 Figure 14. Lunar fraction proportion at the start and end of southern elephant seal migration segments. ............................................................................................................................... 71 xi Figure 15. Lunar fraction consistency between the start and end of southern elephant seal migration segments. .............................................................................................................. 72 Figure 16. Angular difference between southern elephant seal bearing and corresponding solar azimuth. ................................................................................................................................. 74 Figure 17. Change in bearing of southern elephant seal return paths binned by solar altitude. ... 75 Figure 18. Testing gradient or contour use of geomagnetic parameters by returning southern elephant seals. ....................................................................................................................... 76 Figure 19. Testing gradient or contour use of combined inclination and total intensity by returning southern elephant seals. ......................................................................................... 77 Figure 20. Sensitivity thresholds testing the detection of inclination by returning southern elephant seals. ....................................................................................................................... 79 Figure 21. Sensitivity thresholds testing the detection of total intensity by returning southern elephant seals. ....................................................................................................................... 80 Figure 22. Sensitivity thresholds testing the detection of declination by returning southern elephant seals. ....................................................................................................................... 81 Figure 23. Sensitivity thresholds testing the detection of combined inclination and total intensity by returning southern elephant seals. .................................................................................... 82 xii Acknowledgements I am deeply grateful to many individuals whose support, guidance, and encouragement have helped me throughout this journey. First and foremost, I would like to thank my supervisor Dr. David Rosen, who has been instrumental in helping me become a better researcher and writer. I am forever grateful for the opportunity he provided me to study at UBC and for the humour he shared along the way. I also wish to thank Dr. David Rosen and David Green for their financial contributions, without which this work would not have been possible. I next wish to thank my committee members, Dr. Andrew Trites and Dr. Marie Auger-Méthé, for bringing new perspectives to my work. Andrew, I am especially grateful for your critical eye and unwavering support in my academic success. Marie, I appreciate the opportunities you provided to learn new techniques for processing my data and for guiding me in their development. I would also like to thank Dr. Katie Florko for her assistance in troubleshooting R packages and for her personal communications that helped my movement models run. I would also like to acknowledge the many contributors who, over the years, collected, managed, and made publicly available the data used in my research. This work was possible due to the thousands of hours of effort dedicated over more than a decade, and I am truly grateful for access to it. Special thanks to Dr. Sophie Bestley and Dr. Rob Harcourt for their assistance in communicating about the data and facilitating access. I am also thankful to Dr. Jesse Granger and Dr. Will Schneider for their collaboration, feedback on my analyses, and discussions about animal navigation and geomagnetism. I further want to thank Dr. Jesse Granger for connecting me with other researchers in the field of animal navigation. I would like to thank Pamela Rosenbaum for all her help behind the scenes in ensuring I stayed on track and made progress towards graduation. I am also deeply appreciative of the support, advice, and friendship from all my fellow MMRU lab membersâyou have truly made this experience unforgettable. Finally, I am eternally grateful to my family and friends for their endless support. I would not be where I am today without you. xiii Dedication For my parents, Alejandro, and Ivyâwhose love and support kept me from drifting off course. 1 Chapter 1: General Introduction Many animals perform migrationsâseasonal or periodic movements from one region to anotherâas part of their life cycles. Some of the most well-known and widely observed migrations are those of birds that leave their summering regions and fly over continents to overwinter in lower latitudes. Among the longest of these avian migrations is that of the Arctic tern (Sterna paradisaea), which travels more than 80,000 kilometers from the Arctic to the Southern Ocean and back again, spending its life in perpetual summer (Egevang et al., 2010). Terrestrial mammals such as caribou in the northern tundra and herbivores in the African savannah navigate these landscapes to follow annual vegetation changes (Leclerc et al., 2021; Wiltschko & Wiltschko, 2023). Insects also migrate: bong moths (Agrotis infusa) escape the heat of Australian summers by travelling thousands of kilometers to cool mountain caves in the Australian Alps (Dreyer et al., 2018; Heinze & Warrant, 2016), while monarch butterflies (Danaus plexippus) require multiple generations to complete their migratory routes, with each generation covering only a portion of the entire journey. Many aquatic animals also migrate. Salmon return to their specific natal streams from ocean basins to reproduce at the end of their lives, while European eels (Anguilla anguilla) cross the Atlantic Ocean twice during their lives, migrating from their natal habitat in the Sargasso Sea into freshwater lakes and rivers, and then returning back to their breeding grounds (Bett & Hinch, 2016; Cresci et al., 2017; Putman et al., 2013). Marine turtles migrate between feeding grounds and nesting beaches, with some species travelling within ocean gyres for years before returning to lay their eggs (Ã kesson et al., 2003; Lohmann et al., 2001; Papi, 2006). Whales migrate from high latitude, productive feeding grounds in the summer to warmer, lower latitude waters in the winter to give birth to their calves (Abrahms et al., 2019; Boyd, 2004; Mate et al., 2015; Rosenbaum et al., 2014). Many pinniped species migrate between feeding grounds and terrestrial colonies or land-based haul-outs, where they give birth to their pups (Boyd, 2004; Le Boeuf et al., 2000). 2 History of Navigation Research The migrations of most animal species involve specific routes and defined end points. To move along these routes and reach their intended destinations, almost all animals rely on some form of directedâor orientedâmovement. This directed movement is referred to as navigation, and involves the neural processing of sensory inputs to determine a direction toward a goal (Gould, 2004). Long before scientists began studying animal navigation, Indigenous cultures around the world were carefully observing, interpreting, and integrating animal movements into their cultural and ecological knowledge systems (Berkes, 2018). This sophisticated understanding of animal movement patterns was used to track seasonal changes, coordinate resource gathering, predict environmental shifts, and navigate themselves on land and sea (Berkes, 2018; Fernandez-Velasco & Spiers, 2024). For example, Polynesian navigators relied on the flight patterns of seabirds to locate distant islands during long-distance ocean voyages (Lewis, 1971). Among the Maasai of East Africa, knowledge of animal movements from lived experience and oral traditions were used to inform decisions about livestock management, resource use, and environmental change to locate animals (Melubo, 2020). In ancient China under the Han dynasty, farmers documented bird migrations and insect emergence to guide planting and harvesting cycles (Gan, 2023). During the Islamic Golden Age, Arabic scholars wrote extensively on animal behaviour and movement patterns using both direct observation and compiled accounts (Egerton, 2002). During the Age of Exploration in the 19th century, the empirical scientific method was formalized in Europe, and systematic data began to be collected by European-based cultures on animal migrations. Movements previously explained through myth or speculation were increasingly understood through observation. Naturalists like Charles Darwin wrote about the remarkable abilities of sea turtles to find isolated nesting islands. Bird banding allowed ornithologists to capture and mark birds, discovering that individuals returned to the same locations after migrating long distances (Able, 1995). While this helped to describe the migratory abilities of animals, it did not directly address the question of how migrations were accomplished, though there was ample speculation. 3 Major advancements in the field of animal navigation occurred starting in the 1950s, when the field of behavioural science provided a new avenue to investigate how animals might achieve their migratory movements (Frisch, 1973; Kramer, 1953). The âwaggle dancesâ displayed by honeybees (Apis mellifera) were found to be used to communicate the direction and distance of foraging sites to other bees to coordinate their movements (Ã kesson et al., 2014; Freas & Cheng, 2022; Tautz et al., 2004). Experiments with homing pigeons led to the discovery of environmental cues or signals that could inform migratory movements, including celestial (solar, lunar, and stellar), geomagnetic, and olfactory cues (Able, 1977; Papi, 2001). From the 1970s to 1990s, growing evidence showed that geomagnetic cues were used by animals across a wide range of taxa, making magnetoreception a popular topic for navigation studies (Skiles, 1985; Walker & Bitterman, 1989). However, the underlying mechanisms used for geomagnetic orientationâsuch as the roles of magnetite and cryptochromesâremain debated to this day (Naisbett-Jones et al., 2020; Papi, 2001; Warrant, 2021). With the advent and advancement of GPS and satellite tagging in the 21st century, animal movements can now be tracked in real time with far greater precision. These technologies have enabled scientists to monitor animalsâ locations, and sometimes allows for simultaneous collection of environmental data (Chung et al., 2021). Increasing computational power has also allowed for more complex statistical analyses of tracking data and experimental results (Jonsen et al., 2023; McLaren et al., 2022), and tighter control of sensory manipulations has facilitated finer-scale investigations into cue use (Wynn & Liedvogel, 2023). A broader array of novel cues are now being considered in navigational experiments, including polarized light, infrasound, and gravitational changes (Greif et al., 2014; Horton et al., 2020; Marshall & Cronin, 2011; Patrick et al., 2021; Waterman, 2005). Today, the field of animal navigation still seeks to answer the central question: how do animals migrate? Modern research now benefits from a more complete toolkit than ever before. Research is largely interdisciplinary, combining fields such as ecology, neuroscience, statistics, biology, and conservation. There is also a growing recognition of the value of Indigenous perspectives, which have endured since time immemorial, and efforts are being made to incorporate traditional ecological knowledge into empirical approaches to help fill gaps in scientific understanding. 4 Methods to Study Animal Navigation There are a variety of scientific approaches used to study navigation in animals. The initial approach of most navigational work is first documenting the paths taken by individuals (understanding where and when animals navigate), then testing for potential cues and mechanisms underlying these movements (understanding how animals navigate). Direct observation is the simplest method to document where animals migrate, but this is only practical for animals moving short distances in accessible habitats that can be monitored throughout their journeys. Bird banding was one of the earliest scientific approaches that allowed for indirect observations of animal movements, providing snapshots of bird locations along their migratory paths (Able, 1995). Advancements in biologging and tracking technologies has since allowed for indirect observation along the entirety of animal navigational paths (Chung et al., 2021). Devices can now reliably track the movements of individuals without the need for researchers in the animalâs environment. These methods involve attaching tracking devices to animals that either store movement data or transmit it remotely. Systems such as GPS (Global Positioning System) provide highly accurate location data but cannot transmit without being paired with an additional transmission system or recapturing the animal (Harcourt et al., 2019). ARGOS (Advanced Research and Global Observation Satellite) offers lower accuracy but transmits data directly to satellites. These devices have produced a wealth of information on animal movement patterns and led to a better understanding of where navigating animals go (Mate et al., 2015). To understand how animals navigate, experiments have typically involved making some sort of intervention and measuring how the animal responds, with a particular focus on the distance or direction (bearing) relative to its goal. These interventions may be directed at the animal or its sensory systems, or at external environmental cues (Wynn & Liedvogel, 2023). This framework works to either disorient the navigating animal so that it does not move where expected, or test if it can re-orient to an expected direction following a manipulation (Wiltschko & Wiltschko, 2001). Disorientation experiments include moving animals to unfamiliar locations (known as displacement experiments) and observing or tracking their paths back to a known goal and 5 speculating on how they returned based on these paths (Ã kesson et al., 2003; Oliver, 1997; Rodda, 1984). Animals can also be disoriented by rendering their sensory systems inactive, such as damaging olfactory receptors in birds using chemicals (Padget et al., 2017; Pollonara et al., 2015), painting over celestial-sensing antennae in amphipods (Ugolini et al., 2016), or altering leg length in ants by removing segments or adding stilts (Wittlinger et al., 2006). If animals become disoriented with these physical alterations, it indicates the use of these systems in the navigational process. To test re-orientation in response to manipulated external cues, multiple experimental apparatuses have been constructed. One of the earliest was the Emlen funnel, in which migratory birds are placed inside an inverted paper cone with an ink pad at the bottom (Emlen & Emlen, 1966). As cues are altered, the birdâs orientation direction is recorded via ink marks along the funnel walls, a technique still used today with more modern materials (Bianco et al., 2016). Other experimental designs include shifting the internal clocks of animals by manipulating light cycles to test solar cues (Ã kesson et al., 2014), or placing animals such as sea turtles and salmon in artificial magnetic fields generated by magnetic coil systems that simulate geomagnetic conditions from other geographic locations (Goforth et al., 2025; Quinn & Groot, 1983). Challenges Studying Marine Mammal Navigation Most methodologies used to study navigation have focused on terrestrial-based species (especially insects and birds), as these animals are relatively easy to access in the field and are of a manageable size for laboratory-based studies (Lohmann et al., 2008b). For example, while Emlen funnels are appropriately sized for migratory songbirds (approximately 40 centimeters at their widest point), they are far too small for use with larger animals that could not even attempt to move in their intended direction in such a confined space. Similarly, magnetic coil systems become less effective as the size of the experimental space increases, leading to taxonomic biases in the model species that can be studied using these approaches. Studying navigation in marine mammals presents a unique set of challenges related to their size, behaviour, and environment. Marine mammals tend to be large. With larger size comes increased energetic demands, requiring marine mammals to spend more time foraging and necessitates that greater distances need to be travelled to find prey (Boyd, 2004). Many marine 6 mammal species therefore undertake impressive long-distance migrations that span thousands of kilometers to fulfill their life histories. Due to the scale of their natural environments and their physical size, bringing marine mammals into laboratory settings is impractical. Even when feasible, it is incredibly difficult to re-create the three-dimensional aquatic space in which they make navigational decisions and account for the space needed to make realistic movements. In the wild, marine mammals often migrate across open oceans far from land, and they spend much of their time diving beneath the surface in pursuit of prey, making their movements difficult to observe directly. This makes it logistically difficult to study their navigation in the field under natural conditions. Tagging technology offers a potential valuable tool for indirect tracking when animals cannot be followed in the field, but this approach comes with its own challenges. Capturing or encountering these animals to apply tags can pose safety, ethical, and conservation concerns, often limiting sample sizes or resulting in tagging efforts that focus on more accessible individualsâsuch as juveniles that are easier to capture and handle, or females with more predictable movement patterns. Recent advancements in tagging technology have increased their capacity for more accurate sensing, greater storage of data, and easier transmission of locations, leading to a rapid increase in available marine mammal movement data over the last three decades (Chung et al., 2021; McIntyre, 2014). Using the vast amount of data obtained from historical and ongoing tagging efforts remains one of the most promising methods for investigating marine mammal navigation. To date, most tagging studies have focused on identifying where marine mammals go and documenting their behaviours at goal locations (most often foraging and breeding). Much less attention has been given to the process of navigation and what mechanisms and cues marine mammals use during the journey itself. The following section summarizes what is currently known about how marine mammals navigate, exploring both the paths they take and the sensory cues that may guide them. 7 Navigation in Marine Mammals Tagging data has been crucial in revealing the impressive journeys that many marine mammal species undertake across the worldâs oceans. Humpback whales (Megaptera novaeangliae), gray whales (Eschrichtius robustus), and northern and southern elephant seals (Mirounga angustirostris and Mirounga leonina) have all been shown to migrate thousands of kilometers with notable consistency in the routes they follow (Horton et al., 2011, 2017; Le Boeuf et al., 2000; Mate et al., 2015; Rodríguez et al., 2017). Translocation studies of juvenile northern elephant seals have demonstrated a remarkable ability to return to their breeding colony, with 88% of individuals successfully reaching the colony while following direct routes (Oliver et al., 1998). Additional translocation studies have shown that displaced seals maintain straight headings even were diving, suggesting that navigational abilities are employed even when submerged (Davis et al., 2001; Matsumura et al., 2011). Northern elephant seals have also demonstrated an understanding of their position at sea (a âmap senseâ) that accounts for the time and distance needed to complete their migrations (Beltran et al., 2022; Condit et al., 2022), though the specific cues involved remain unclear. Other displacement events, including the relocation of pinnipeds over hundreds of kilometers as a deterrence strategy to reduce predation at dams or fish farms, or to remove individuals from populated urban areas, have yielded mixed results, with many individuals returning to areas from which they were removed (CBC, 2024; Hume et al., 2002; Thompson et al., 2021; van der Leeuw & Tidwell, 2022). These findings suggest that marine mammals possess strong navigational abilities. A variety of cues have been discussed or tested to explain these movements. For example, cetacean strandings have been linked to local magnetic minima (Kirschvink et al., 1986), and fin whale migrations have been associated with regions of low geomagnetic intensity (Walker et al., 1992), suggesting the use of geomagnetic cues. Use of geomagnetic cues have also been proposed when explaining the underwater movements of translocated northern elephant seals (Matsumura et al., 2011) and Weddell seals (Leptonychotes weddellii) navigating under fast ice (Fuiman et al., 2020, 2021), though this has yet to been tested experimentally in any pinniped. In contrast, geomagnetic cues do not show a strong correlation with humpback whale movements, but rather these whales seem to time their migratory departures according to lunar cycles (Horton et al., 2011, 2017). 8 Vision has also been investigated in the context of navigation. Northern elephant seals may use coastal landmarks to locate their colony (Matsumura et al., 2011), and harbour seals (Phoca vitulina) have shown the cognitive ability to learn geometric relationships between landmarks (Maaà et al., 2022). Weddell seals swimming beneath ice have been observed following linear disturbances in the snow above them (i.e., ice cracks) to guide them home (Fuiman et al., 2020), and on land, they follow features with high visual contrast (Fuiman et al., 2021). Harbour seals have demonstrated the ability to identify an artificial lodestar (a âguiding starâ) and use it to follow learned star courses, with the potential of associating this lodestar with relevant landmarks (Mauck et al., 2008). Ocean-based cues have also been considered. Northern fur seal (Callorhinus ursinus) migrations follow oceanic currents (Ream et al., 2005), although whether these currents serve as active cues or are passively used to reduce energy expenditure when swimming is unknown. Olfaction has been shown to play an important role in the lives of marine mammals. On land, olfaction is important in pup recognition in pinnipeds, with females being able to identify their own offspring by scent (Pitcher et al., 2011). Harbour seals possess a high sensitivity to dimethyl sulphide, a chemical produced by phytoplankton that is strongly associated with profitable foraging areas (Kowalewsky et al., 2006), indicating that olfaction may help with prey-finding. While the role of olfactory cues along migratory pathways has not yet been studied, their role at key locations in the life history of marine mammals suggests at their potential importance in navigation. A final cue of interest is acoustics. Sound travels efficiently underwater and plays a vital role in many aspects of marine mammal biology. However, excessive anthropogenic noise can be highly disruptive to these functions, including migration (Erbe et al., 2018). It has been suggested that female northern elephant seals migrating hundreds of kilometers apart may use vocalizations to help synchronize their movements, although the use of vocal cues while navigating remains unverified (Pei et al., 2023). Together, these studies highlight a wide range of cues that may contribute to the extraordinary navigational capabilities of marine mammals. However, the use of many of these cues remains speculative or insufficiently tested. It is evident that marine mammals are underrepresented in the field of animal navigation, and that significant gaps in knowledge 9 persist. For my study, I chose southern elephant seals as a model species to explore these gaps in knowledge. Among marine mammals, southern elephant seals undertake exceptionally long migratory trips that are supported by extensive amounts of available tracking data collected over the past few decades. Southern Elephant Seal Biology The most extreme of the pinniped migrators is the southern elephant seal, which travels thousands of kilometers across the Southern Ocean between productive foraging grounds and small, isolated oceanic islands where they breed. Activities at this breeding haul-out include parturition, lactation, copulation, and weaning (Kirkman et al., 2004). Breeding males arrive in late August to establish territories prior to the arrival of breeding females in September (Hindell & Burton, 1988). When adult females arrive, most give birth to pups they conceived during the prior breeding season. Mothers nurse their pups for a few weeks before breeding with sexually mature males. Following mating, the mother weans her pup and departs the island on a foraging trip lasting 2â4 months. Eventually, all seals, including the newly weaned pups, leave the islands and disperse widely across the Southern Ocean to feed. This wide distribution may serve to reduce competition by partitioning resources, or may reflect differing resource needs driven by the marked sexual dimorphism between males and femalesâadult males can weigh between 1,500 to 3,700 kg, while adult females typically only weigh 350 to 900 kg (Hindell et al., 2021). As deep divers, southern elephant seals exploit prey at depth, likely feeding on myctophids, squid, and toothfish (Cherel et al., 2008). While their dietary preferences are not well understood, they appear to vary with foraging location, time of year, and individual traits that influence foraging choices (Allegue et al., 2022; Cotté et al., 2015). Despite this variability, seals often display long-term fidelity to foraging areasâlikely a strategy that confers lifetime benefits and can lead to individual niche and dietary specialization (Bradshaw et al., 2004; McIntyre et al., 2017). Southern elephant seals generally forage in one of two habitats: shallow continental shelf areas, which are highly productive but pose greater risks due to sea ice formation and predation from killer whales or sleeper sharks; or the deep ocean, which offers more stable conditions and lower predation risk, but yields a lower overall energetic return (Allegue et al., 2022; Arce et al., 2022; Cox et al., 2020; Hindell et al., 2016). 10 After the initial post-breeding foraging trip, seals return to the islands for 3â5 weeks to complete a catastrophic molt (de Kock et al., 2021), an essential process in which they shed and replace their outer layer of skin and fur to maintain thermoregulation and overall health (Luschi, 2013). Once the molt is complete, they return to sea for the longest foraging period of the year, lasting 4â8 months. A few weeks following the molt while at sea, adult females undergo delayed implantation of the fertilized embryo from the previous breeding season (Kirkman et al., 2004). At the end of this foraging period, seals return once more to the islands to haul-out, give birth, breed, and repeat this annual cycle. (Hindell et al., 2016). Thesis Objectives I used location data from ARGOS satellite tags previously deployed on southern elephant seals migrating between foraging areas and breeding/haul-out islands in the Southern Ocean to characterize their movement patterns (Chapter 2) and evaluate the potential cues used during navigation (Chapter 3). In Chapter 2, I applied a state-space model to reduce location errors in ARGOS tag data and predict seal positions at regular time intervals. These predicted positions were then used in a hidden Markov model to identify and classify travelling behaviours, allowing me to isolate âoutboundâ and âreturnâ segments of seal migratory routes that involved navigation. I analyzed these migration segments to answer three questions. (1) Do seals show consistency in the migration routes they follow? (2) How directly do seals return to islands along their migration routes? (3) What factors influence return timing of seals? In Chapter 3, I analyzed the same migratory segments obtained in Chapter 2 to evaluate whether southern elephant movements align with specific predictions made if potentially using environmental cues. The cues examined included lunar, solar, and geomagnetic cues. My research is the first to examine migratory movement patterns of southern elephant seals within the context of animal navigation. My study demonstrates the value of satellite tagging data for investigating navigation in taxa that are difficult to study using traditional methods. It also shows an empirical methodology for exploring the potential use of navigational 11 cues based on tagging data. Finally, my study highlights the importance of considering movement data and its associated navigational insights when informing species conservation. 12 Chapter 2: On the right track: southern elephant seals maintain accurate courses from diverse starting points during long-distance migration Summary Many species of marine mammals travel long distances across vast expanses of open ocean to reach specific foraging or breeding areas. However, it remains largely unknown how they navigate this seemingly featureless environment and what cues they might use while migrating. I analyzed the migratory movements of 271 southern elephant seals (Mirounga leonina) tracked across the Southern Ocean from 2009â2019 to assess their navigational abilities and provide clues for the use of potential cues. I found that southern elephant seals travel with remarkable precision and efficiency when returning to their breeding islandsâdespite coming from a wide range of directions along a variety of routes. These results suggest that southern elephant seals detect and use cues when navigating that allow them to maintain constant courses and follow straight paths that account for the curvature of the Earth and potential drift. This study is one of the first to characterize the impressive movement patterns of southern elephant seals in the context of navigation and highlights the value of using tracking information to understand navigation for species that cannot be studied with traditional experimental techniques. Introduction A diverse array of animal taxa undertake long-distance migrations that traverse the worldâs aquatic, terrestrial, and aerial ecosystems (Bradbury et al., 2021; Egevang et al., 2010; Freas & Cheng, 2022; Leclerc et al., 2021). These impressive migratory journeys are used by animals to follow resources, find foraging opportunities, reach important breeding areas, or avoid adverse environmental conditions and predators (Shaw, 2016). Their destinations hold significant biological value for both individuals and for the continued success of the species, resulting in strong motivation and evolutionary pressure to reach them (Abrahms et al., 2021; Kappeler, 2021). While biologically important, long-distance migrations are also energetically taxing (Abrahms et al., 2018; Boyd, 2004). Travel costs can be reduced by minimizing the distance travelled to reach the goal, leading to selection for efficient travel routes. Migration timing is 13 also crucial, as use of these areas is often constrained seasonally or can be highly influenced by the temporal movements and life histories of other species sharing the same environment (Abrahms et al., 2021). This results in migratory movement patterns that are predictable, directional, persistent, and often defined by clear end pointsâall characteristics which set migrations apart from other forms of animal movement (Dingle & Drake, 2007). For marine species, the specific routes travelled during long-distance migrations often traverse vast expanses of open ocean (Horton et al., 2017; Piersma et al., 2022). Leatherback sea turtles (Dermochelys coriacea) in the Atlantic Ocean transit the northern basin before returning to their nesting island (Hays et al., 2006), while seabirds like the sooty shearwater (Ardenna grisea) cross the extent of the Pacific Ocean to fly between foraging grounds in Alaska and breeding colonies in New Zealand (Luschi, 2013). The record-holder of the longest mammal migration, the grey whale (Eschrichtius robustus), travels from reproductive areas off Baja California, Mexico to the productive waters of Russiaâs Sakhalin Island and back again (Mate et al., 2015), a trip that traverses 22,000 kilometers. All animals require some combination of sensory input to successfully undertake long-distance movement. The open ocean is a unique sensory environment, different from both terrestrial systems and other aquatic landscapes. Marine animals moving through open ocean are challenged by the absence of visual landmarks at the surface, while the rapid diminishing of light intensity below the seaâs surface renders information of submerged geography obtained through vision of limited value (Lohmann et al., 2008a). Oceanic travellers are also susceptible to the influence of tidal currents and wind-driven wave action (Lohmann et al., 2008a). These characteristics make moving in a constant, predetermined direction more challenging, as currents, waves, and wind can push an animal off its directed course (Cerritelli et al., 2019). Not only might animals be directed off course, but the lack of visual references makes it more difficult to gauge when drift occurs, and without landforms to act as resting or reset points, an animal cannot ground itself or pause to adjust for such deflections (Erni et al., 2002). Poor weather conditions are also frequent, as blowing winds are unobstructed by landforms, further contributing to potential drift and disorientation (Lohmann et al., 2008b; Young, 1999). While these inhospitable conditions and uniform features (at least from the human sensory perspective) might suggest that these open ocean environments are exceptionally challenging for marine species, animals migrating within this environment have the capacity to successfully reach 14 locations of interest (Block et al., 2011; Horton et al., 2011). This indicates that there are useful cues within these environments that marine animals can detect and utilize for the purposes of navigation (Gould, 2004), although this does not shed light on what those cues may be. Most studies of marine mammal migrations have focussed on describing the general migration paths that animals take, where they are headed, and for what biological purposes these migrations occur (Hays et al., 2016). Far fewer studies have addressed the fine-scale characteristics of these movements. This knowledge is important for understanding navigational abilities by investigating how marine animals accomplish these movements and what specific cues they use to guide themselves. Studies aimed at understanding these patterns of movement for other animal taxa have largely focused on experimental approaches where potential cues can be adjusted, or where the perception or location of study animals can be manipulated and directly observed (Ã kesson et al., 2014). These experimental techniques are well suited for many terrestrial groups such as insects and songbirds (Lohmann et al., 2008b). By comparison, long-distance marine navigators are often much larger in size, live in remote environments that are largely inaccessible, and are often cryptic by nature (Boyd, 2004). This results in traditional study techniques being difficult if not impossible to utilize for the purposes of understanding migratory movement in these species. Southern elephant seals (Mirounga leonina) are an example of a long-distance marine navigator whose movements cannot be studied using traditional experimental techniques. As the largest living pinniped species, elephant seals spend up to 80% of their time at sea, with individuals migrating thousands of kilometers across remote areas of the Southern Ocean in search of food (McIntyre et al., 2010). Southern elephant seals are the deepest diving pinniped species, routinely diving up to 1000 meters in search of mesopelagic fish and squid species or benthic prey such as toothfish (Cherel et al., 2008; Hindell et al., 2022; McGovern et al., 2019). Due to their deep diving capabilities, they spend much of their time underwater. Seals return to isolated oceanic islands in the sub-Antarctic to breed and give birth from September to November, followed by a post-breeding foraging migration that lasts 2â4 months (Hindell et al., 2016). Seals come ashore a second time to molt, then again depart on a second, longer foraging migration that lasts 4â8 months from February to October (Hindell et al., 2016). Since breeding and molting occurs seasonally, return migrations of southern elephant seals are highly predictable across time and undertaken by much of the population. 15 Advances in the technological capabilities of telemetry tracking devices has enabled remote observation of southern elephant seals in their natural environments and allowed for a better understanding of their movements throughout the Southern Ocean (Harcourt et al., 2019). Deployments of these devices have yielded abundant data along the entirety of their paths, yet interpretation of these movements have largely focused on prey-finding, characterizing where seals are foraging, and the association of these areas with oceanographic features (Chua et al., 2022; Cotté et al., 2015; Hindell et al., 2016, 2021; Labrousse et al., 2015). Few studies have addressed the movements of seals outside of their foraging habitats, especially when they are travelling for extended periods to return to their breeding islands. Characterizing this movement is an important step in searching for and identifying the external cues and mechanisms that seals might use during these migratory travels to guide their movements. In addition to spatial patterns, temporal dynamics are also a critical component of navigation. Knowing when to begin migratory movement is essential for animals to arrive at a desired location at the appropriate time to take advantage of the biological benefits. This is particularly true for adult female southern elephant seals, who must return to island beaches to give birth, nurse and wean their pups, and then breed. As such, migration timing is likely to be especially important for this demographic group, making it important to understand what factors influence the timing of these returns. To shed light on the enduring mystery of how marine animals navigate during extended travel periods, previously collected telemetry data was reanalyzed for the purposes of understanding how southern elephant seals move to and from sub-Antarctic islands during long-distance migrations. Specifically, tracks of tagged animals were characterized using a series of analyses to answer three main questions regarding the movement patterns of travelling elephant seals. (1) Do seals show consistency in the migration routes they follow? (2) How directly do seals return to islands along their migration routes? (3) What factors influence return timing of seals? For each question, patterns were analyzed at both the population levelâby comparing travel segments across different sealsâand at an individual levelâby examining travel segments from the same seal. This approach was designed to highlight the navigational abilities of southern elephant seals as they traverse the open ocean. The results from this study can also help to inform and refine future investigations that seek to identify and test the use of potential cues underlying these incredible journeys. 16 Methods Instrument Deployment & Data Sources Location data used for this study were obtained from telemetry transmissions from ARGOS satellite tags attached to southern elephant seals. Datasets were sourced from Australiaâs Integrated Marine Observing System (IMOS) via the open access portal of the Australian Ocean Data Network (AODN). Tags were attached to seals captured at five deployment sites around the Southern Ocean between 2009 and 2019 either at the end of the annual breeding season or at the end of the annual molt (locations detailed in Behavioural Classification Using Hidden Markov Models). Seals were chemically sedated, weighed and measured, and outfitted with CTD-SRDL_9000 (Conductivity-Temperature-Depth Satellite Relay Data Logger) tags from the Sea Mammal Research Unit (University of St. Andrews, UK). Detailed descriptions of capture, handling, sedation, and attachment techniques have been described previously (Field et al., 2002, 2012; McMahon et al., 2000). Satellite tags remained attached to seals until they either fell off or were shed during the next annual molt, resulting in an average period of deployment of 185 days. These tags sent regular at-sea location estimates to the ARGOS satellite tracking system when seals were above the waterâs surface. Each individually tagged seal in the downloaded data was given a unique identifier to associate it with the transmitted locations. Tags additionally recorded dive metrics via a pressure sensor, haul-out information via a wet-dry sensor, and high-resolution temperature and conductivity profiles. Sourced datasets included location and summary metrics for periods of diving and haul-out behaviour, along with demographic information recorded at the time of capture, including age and sex ( 17 Table 1). 18 Table 1. Counts of southern elephant seals by age class and sex. Sex and age distribution of southern elephant seals included in the analyses for this study following the implementation of the state-space model and hidden Markov model. Age classification is defined as followsâWeaner: less than 1 year; Juvenile: females 1â2 years old, males 1â5 years old; Subadult: non-breeding males 5â8 years old; Adult: breeding females 3+ years old, breeding males 8+ years old. Age Sex Weaner Juvenile Subadult Adult Female 1 3 0 105 Male 1 121 24 16 State-Space Modelling ARGOS location data are prone to error, especially for elephant seals that spend significant time underwater and have relatively short surface intervals (Costa et al., 2010; Vincent et al., 2002). To minimize these positional errors and predict seal locations at regular time intervals required for subsequent analyses, the aniMotum R package using R version 4.4.0 (Jonsen et al., 2023) was used to fit a correlated random walk state-space model to the irregularly sampled location data to produce predicted location data at consistent 6-hour intervals. Prior to applying the model, tracks were split into smaller segments when transmissions halted for more than 18 hours (three times that of the timestep used in the model) or removed altogether if they had less than 100 total location transmissions, as this led to model convergence issues. Tracks were also removed if the sealâs position did not move more than 50 kilometers away from the land mass it was tagged at. This value was based on an estimate of the distance away at which the tallest terrestrial reference points at the deployment sites would disappear over the horizon due to the curvature of the Earth. This was done to ensure that seals could not utilize visual references to land during at least some part of their tracks and thus were engaged in true open ocean movement. This buffer distance was also based on previous studies that noted that elephant seals often use nearshore waters within this range to thermoregulate or potentially feed while still being associated with their breeding islands prior to undertaking directed migratory movement (Foo et al., 2023; B. McConnell et al., 2002). In total, 403 track segments from 271 southern elephant seals were fit using the state-space model, resulting in 193,984 predicted locations (Figure 1). 19 Figure 1. Map of southern elephant seal tagging tracks. Figure shows all southern elephant seal location tracks used in this study. Plotted locations show the predicted values resulting from the aniMotum state-space model. Locations of breeding and natal islands used by the seals in the dataset are marked with black circles and labelled. Behavioural Classification Using Hidden Markov Models Predicted locations returned from the state-space model identified a sealâs corrected position along the entirety of its movement track at regular time intervals. Seals inevitably engage in different behaviours at the various points identified along their tracks, but these behaviours are masked (McClintock et al., 2020). For the purposes of this study, travel was determined to be the most useful type of behaviour to identify. When seals are travelling, they are most likely detecting and using cues from their environment specifically for the purposes of moving in a directed way towards a target location (i.e., navigating). This differs from 20 behaviours like foraging where seals are also detecting cues from their environment, but these cues are employed for other purposes such as catching prey, resulting in a movement goal different from that of navigation and likely incorporating different types of cues and movement mechanisms. To infer latent seal behaviour from the telemetry data to identify periods of travel along seal tracks, the momentuHMM R package (McClintock & Michelot, 2018) was used to apply a three-state hidden Markov model (HMM) to the location results of the state-space model. Speeds between positions were modelled using a Gamma distribution and turning angles were modelled using a von Mises distribution. Additional data streams constructed from the diving and haul-out data were also incorporated into the model, as inclusion of additional information has been shown to improve the resulting behavioural classifications from HMMs (Bestley et al., 2015; Saldanha et al., 2023). To conserve battery life and maximize deployments, ARGOS tags were programmed to function intermittently, with one dive sampled every ~2.25 hours (Cox et al., 2018). Dives were defined as any change in depth exceeding 15 meters and lasting more than 5 minutes (Allegue et al., 2023; Cox et al., 2018). Tags also ceased to function if seals were determined to be hauled out, beginning when the wet-dry sensor detected the tag was dry for more than 10 minutes (Vincent et al., 2002). Recorded dive and haul-out periods as indicated by the tag were matched to the time intervals from the state-space model to identify time steps with the presence or absence of these behaviours and modelled using a Bernoulli distribution. Fine-scale movements such as searching and foraging behaviours can be difficult to resolve with ARGOS data, especially for deeper diving marine mammals (Irvine et al., 2020; Robinson et al., 2007). To assess this, the three-state model was compared to two- and four-state models to assess the detail at which these behaviours could accurately be detected. AIC values tend to favour HMM models with a greater number of states, regardless of their biological interpretability (Pohle et al., 2017). Thus, pseudo-residuals and visual inspection of individual tracks using informed knowledge of southern elephant seal movements were used to determine the number of states that provided the best fit. A Viterbi algorithm was applied to the resulting model to decode the state sequence of behaviours and identify directed movement (Figure 2). Portions of the track decoded as 21 âtravelââcharacterized by larger step lengths and lower turning anglesâwere used to characterize the movement patterns of elephant seal migrations. All other behavioural states were excluded from the analyses. Figure 2. Decoded behaviour states for one southern elephant seal resulting from the hidden Markov model. A track from an adult female seal tagged at Campbell Island (located at bottom of plot) showing the decoded Viterbi states after fitting the hidden Markov model. Behaviour indicative of travel (shown in orange) was seen consistently among tracks when seals were moving away or towards islands, separated with an extensive segment of behaviours indicative of area restricted search (ARS) (shown in blue), sometimes interspersed with additional travel behaviour. Resting behaviours (shown in green) were most often associated with proximity to the islands. Identified travel behaviour was divided into what was classified as âoutboundâ or âreturnâ segments based on the location, time, and date of points along the track in relation to an island of reference (further defined below). In total, four sub-Antarctic islands were identified as Latitude Longitude 22 reference locations that seals travelled to and from: Kerguelen Island (49°28â58.8â S, 70°20â34.8â E), Heard Island (53° 6â25.2â S, 73°31â48â E), Macquarie Island (54°32â2.4â S, 158°56â2.4â E), and Campbell Island (52°32â34.8â S, 169°10â48â E) (Figure 1). Three of these islands, Kerguelen, Heard, and Macquarie, are large breeding colonies used by more than 60,000 southern elephant seals every year (Hindell et al., 2016). Fewer than 10 seals use Campbell Island during the breeding season, due to its lack of suitable terrain, but elephant seals, especially males, have been observed dispersing from Macquarie Island to Campbell Island as a haul-out site since the 1970s (McMahon et al., 2005; Nicholls, 1970; van den Hoff, 2002). As many of the seals included in this study were tagged at Campbell Island and showed dispersal patterns to and from the island, the island was included in the analysis as a known location that seals used for migratory homing. Outbound travel segments were defined as seal location data that moved away from one of the four islands and moved towards an open water location or the Antarctic continent. These outbound segments were often followed by extended periods of non-travel behaviour such as area-restricted search behaviour. Return travel segments were defined as seal location data that moved towards one of the four islands after an extended period of non-travel behaviour. These definitions (outbound and return) separate migratory travel periods where the end goal of the seal can be assumed (returning to a specific island) from travel periods where the goal location of the seal is not known (outbound trips to foraging patches). Return segments were further divided into full and partial returns, as some tags failed before the seal reached an island. Returns were classified as full returns when the location transmissions coincided with one of the four islands and seals either had multiple subsequent transmissions at this island and/or the tag sensors indicated that seals were hauled out. Partial returns were segments where the tag locations ended prior to reaching an island and did not provide any subsequent travel path information. Southern elephant seals generally exhibit strong philopatry to natal sites (Fabiani et al., 2006; M. Lewis et al., 1996; Reisinger & Bester, 2010). Thus, for partial returns, it was assumed that the island that the seal was heading towards before tag failure was indeed the intended âgoalâ if this island was the same one that the seal had been documented leaving from at the end of the last breeding season (assumed to be its natal site). If seals were first tagged at non-natal sites and did not complete a travel path to a natal island while 23 tagged, it was not assumed which island was chosen for their return goal, even if they were heading towards a specific island prior to tag failure. These segments were not included in return analyses that required a goal location due to their unknown site selection. For many decoded tracks, there were shorter periods of travel that occurred within or between extended periods of area restricted search. Since these travel periods tended not to move directly towards or away from an island or were short in duration, it was assumed that these periods of travel were for purposes other than migration, such as moving between foraging patches. These periods of travel were excluded from analysis, as it is unlikely seals were engaged in homing behaviour in reference to their home island and thus could be using cues unrelated to migratory navigation. The resulting travel segments following this division and their associated reference islands were used for all subsequent analysis (Table 2; Table 3). Table 2. Summary statistics of travel segment distances. Calculations for the minimum, maximum, and mean distances of elephant seal travel segments according to their classification (outbound, partial return, full return). Segment Classification Sample Size Mean Length (km) Min Length (km) Max Length (km) Outbound 285 1,209 31 4,513 Partial Return 53 1,344 60 3,594 Full Return 171 1,343 50 4,386 Table 3. Counts of travel segments by island. Counts for outbound, partial return, and full return segments for each reference island following travel segment designation. Most islands had more outbound trips than returns, as most seals were tagged on these islands and therefore tags most often captured the initial outbound routes following tagging before stopping transmissions. The exception was Heard Island, as seals were not tagged on the island, but instead tagged on the Antarctic continent part-way through their foraging trips, resulting in most seals returning to Heard Island after the initial tag attachment. Travel Segment Island Outbound Partial Return Full Return Campbell 16 3 7 Heard 20 7 25 Kerguelen 224 36 128 Macquarie 24 6 10 24 Movement Pattern Analysis Do seals show consistency in the migration routes they follow? To determine migration route consistency, analyses were run to measure the variation in initial headings along routes and the spatial overlap of these routes. These analyses were designed to both assess if routes are collectively shared by the population and determine the predictably of these routes when examining the migrations of individuals. To evaluate whether seals consistently initiated their outbound or return migrations along a specific heading, the directional bearing of seals in relation to a given island was calculated using the geosphere R package (Hijmans, 2010). Bearings were calculated along a great circle path for all segments with an associated reference island, including outbound segments and both full and partial returns. Outbound bearings were calculated in relation to the island the seal was leaving from and return bearings were calculated in reference to the goal island the seal was heading towards. For outbound routes, the first two recorded points in a sealâs track that were at least 50 kilometers away from the island were used to calculate the initial bearing. This buffer accounted for geographic features of the islands that could restrain the directional movement of the seal to more accurately capture its directional heading (e.g., leaving a breeding site on the eastern side of an island prohibits initial westward movement). For return routes, the first two recorded points along the track were used to calculate the initial bearing of the return trip with no buffers applied, as routes were initiated in open ocean. Circular plots were constructed using the circular package in R (Lund & Agostinelli, 2024), and Rayleigh tests were applied to test the uniformity of the resulting bearings for both outbound and return tracks by island. The bearings calculated by island were re-grouped and analyzed by age, with seals divided into juveniles, subadults, and adults. Circular plots and Rayleigh uniformity tests were again used to characterize outbound and return bearings to assess how age and experience impacted consistency. Most seals in the dataset transmitted only one outbound and one return segment before their tags stopped working, often following the annual molt or breeding season. However, a subset of individuals retained their tags through these events, allowing for two segments of each type to be recorded. In total, 43 seals had two outbound segments, and 24 had two return 25 segments. For these seals, a linear regression and a Wilcoxon signed-rank test were used to assess if bearing values were consistent between both trips along outbound and return migrations. To further evaluate directional consistency across repeated trips, the angular difference between the bearings across the two trips were also calculated for both repeat outbound and return migrations. To remove the potential effects of local island geography influencing these bearing comparisons, only seals that left from or arrived at the same island during both sets of migrations were considered in the analysis. To evaluate if seals collectively followed similar travel routes between their outbound and return pathsâthat is, whether outbound and return paths overlappedâthe bearing back to the island at the end of each outbound travel segment and the bearing at the start of all corresponding return segments was compared. Both bearings were calculated in relation to the goal island and only tracks from individuals that had both an outbound and return path (both full and partial returns) were used in the analysis. The absolute difference between these bearings was calculated for each individual track, and the overall distribution of these resulting differences was examined. The closer these two measuresâi.e., the smaller resulting difference between bearingsâthe more likely for potential overlap between their outgoing and return journeys. To more directly assess the spatial overlap between outbound and return paths, kernel density estimations were calculated using the MASS package in R (Ripley & Venables, 2009). The probability density function of the location data was estimated in two dimensions (latitude and longitude) to measure the spatial overlap between outbound and return routes for each individual seal. All seals that had both an outbound and full return route were included in the analysis. Partial returns were not included, as location data for unrecorded sections could not be assumed. For individual seals that had two migration trips, each migration set (outbound and full return) was treated as independent samples so overlap was not computed considering both trips, as seasonal factors might impact spatial movements and bias results. Bandwidth for kernel density estimates was set to 50 kilometers, treating points within that distance as overlapping. The resulting overlap between routes was quantified using the Bhattacharyya coefficient, which ranges from 0 (no overlap) to 1 (complete overlap). This value was used to quantify the similarity between outbound and return routes for each individual seal, and coefficient values were compared among all seals. 26 How directly do seals return to islands along their migration routes? Paths of animals moving directly between two geographic locations can follow either great circle paths (the shortest path between two points on a sphere) or rhumb lines (constant compass bearing) (Alerstam et al., 2008). To determine if southern elephant seals follow great circle paths or rhumb lines, the expected paths following each method were constructed from the start and end points of recorded return segments. These expected paths were then compared to the actual paths travelled by seals and the shortest distance from each individual point along the actual track to both the great circle path and the rhumb line path was calculated. Since the distances calculated required location points from the start of the return to its known endpoint on the island, only seals with full returns were included in the comparison. The mean distance of all measured values from the actual location points to the expected paths for both great circle paths and rhumb lines were computed and differences were compared using a linear mixed-effects model. To assess if seals maintained a consistent bearing along their return track, the bearing and distance at each point along a sealâs return track was calculated in relation to the sealâs goal island. Both partial and full return segments were considered in calculations. The absolute change in bearing was calculated between two consecutive location pointsâ calculated bearings, and this was repeated along the entirety of the track for all tracks. Distance to the island between these consecutive points was averaged to determine the distance from the island for each change in bearing. The change in bearing was then plotted against these distances, with distance to the island binned into 200 km intervals for the 1000 km closest to the island, and 1000 km bins thereafter. This resulted in multiple bearing changes from an individual seal being included in a single distance bin. Change in bearing was compared to the distance from the island using a linear mixed-effects model to assess the size of bearing changes, if changes in bearing were consistent across distance, and if there were certain âhotspotsâ (i.e., specific distances from an island) where course corrections were commonly made. To determine if seals travelled directly and followed the shortest possible path to return to their islands, a straightness index was calculated for all seals with complete return paths. 27 Straightness indexes are used to assess the efficiency of a travel path, ideally when animals are homing (Benhamou, 2004). It is calculated as follows: Beeline distance was defined as the shortest direct path from the start of the return track to the end point of the return track at the island (i.e., following a great circle path). Actual path distance was defined as the sum of all distances between each consecutive point along a sealâs transmitted return track. The greater the resulting index (maximum of 1), the more closely the actual route followed the beeline route. Indices were compared by age using a Kruskal-Wallis test. Indices were also compared between the first and second return trips taken by a subset of individuals with repeated recorded trips using a Wilcoxon signed-rank test. What factors influence return timing of seals? Arrival timing was assessed for adult female seals returning to either Kerguelen Island or Macquarie Island for the breeding season and only included adult females with full return tracks. Date of arrival was identified as the day when a seal first transmitted at least two consecutive locations on a breeding island. This date was cross-referenced with the wet-dry sensor data recorded from the tag, if available, to confirm the presence of the seal on land. The arrival timing of females (binned into weekly categories) was compared between both islands using a chi-squared test prior to further analysis. These proportions were not significantly different between islands, so arrival data was combined to increase the sample size. Division of arrival timing by year also yielded small sample sizes, so seal data from all years was combined. To understand how the return trip distance influenced the timing of return trips, linear regressions were used to compare return trip distance to the date of the start of the return trip, the date of the end of the return trip, and the average speed travelled during the return trip. Return trip distance was determined by calculating and summing the distance between each subsequent point along the return path. Average swimming speed was calculated by dividing the total distance of the return trip by the total time (in hours) the seal took to complete the trip. 28 Results Do seals show consistency in the migration routes they follow? Outbound bearings for seals leaving from all islands were oriented in the southeasterly direction (mean direction between 90° and 180°). Tagging data from Heard Island, Kerguelen Island, and Macquarie Island all indicated a significant non-uniform distribution in the bearings followed by seals away from these islands (Rayleigh test of uniformity; Z = 0.61 (HI), 0.75 (KI), 0.55 (MI); p-values < 0.001) (Figure 3a). Seals leaving from Campbell Island followed bearings not significantly different from a uniform distribution (Rayleigh test of uniformity, Z = 0.15, p-value = 0.72) (Figure 3a). Seals travelling outbound from Heard Island, Kerguelen Island, and Macquarie Island had moderate mean resultant lengths (r), indicating a moderate clustering of seal bearings around the mean direction, while seals from Campbell Island showed low mean resultant lengths, indicating a lack of directional preference (Figure 3a). Collectively, these results indicate that seals travelling outbound from Heard Island, Kerguelen Island, and Macquarie Island prefer to leave the island in the southeast direction, although these bearings are only moderately clustered around a single angular value. Seals travelling outbound from Campbell Island did not have a directional preference but notably had the smallest sample size of the islands examined (n = 14). When returning to the islands, return bearings indicated that seals from Heard Island and Kerguelen Island travelled in a northwesterly direction, while seals from Campbell Island and Macquarie Island travelled more westerly (mean directions closest to 315° (NW) for Heard and Kerguelen and mean directions closest to 270° (W) for Campbell and Macquarie) (Figure 3b). Rayleigh tests for uniformity indicated that bearings for seals returning to Heard Island and Kerguelen Island were significantly non-uniform in their distributions (Z = 0.71 (HI) and 0.55 (KI), p-values < 0.001), whereas seals returning to Campbell Island and Macquarie Island did not show significant differences from uniformity (Z = 0.43 (CI) and 0.30 (MI), p-value = 0.10 (CI) and 0.25 (MI)) (Figure 3b). All islands showed moderate mean resultant lengths (r), with seals from Heard Island and Kerguelen Island showing moderately high clustering of bearings around the mean direction, while seals from Campbell Island and Macquarie Island showed moderately low clustering of bearings (Figure 3b). Taken together, results from return bearings indicate that seals arrive to Campbell Island and Macquarie Island in somewhat non-consistent directions 29 compared to other seals, while seals arriving to Heard Island and Kerguelen Island prefer to arrive from a general northwest direction that is not tightly clustered around a single bearing. Figure 3. Circular plots of outbound and return bearings in relation to four islands used by southern elephant seals. Circular distributions of the bearings seals followed a) leaving from and b) returning to Campbell Island, Heard Island, Kerguelen Island, and Macquarie Island. Bearings were calculated a) away from the island (outbound) or b) towards the island (return). Mean angle of direction (a), mean resultant lengths (r), and number of individuals (n) is reported. All circular plots were tested using a Rayleigh test of uniformity and significance of plots are indicated with asterisks, with * = p £ 0.05, ** = p £ 0.01, *** = p £ 0.001, **** = p £ 0.0001. Seals from all islands left from their islands in the southeast direction and returned to these islands in the northwest direction. However, there was a wide range of variability in these bearings, as some seals did not follow the general outbound or return direction at all, and most seals who did follow this direction did not closely follow the same, specific angular trajectory as others. *** **** *** **** **** 30 Analysis of outbound and return bearings of seals based on age show a significant non-uniform distribution in the bearings followed by seals of all age groups for both trip directions (Rayleigh test of uniformity; outbound: Z = 0.70 (juvenile), 0.72 (subadult), 0.81 (adult); return: Z = 0.73 (juvenile), 0.82 (subadult), 0.32 (adult); outbound p-values < 0.001; return p-values < 0.001) (Figure 4a; Figure 4b). Consistent with the previous analysis by island, outbound bearings for all age groups were oriented in the southeasterly direction (mean direction between 90° and 180°), while return bearings for all age groups were oriented in the northwesterly direction (mean direction between 270° and 360°) (Figure 4a; Figure 4b). All age groups except for returning adults had mean resultant lengths (r) close to 1, suggesting that bearing distributions for these groups were strongly clustered around the mean directions (Figure 4a; Figure 4b). Despite significant findings from the Rayleigh test for uniformity, returning adults showed moderately low resulting lengths closer to 0 and their circular plot depicted a wider range of bearing values that were followed, suggesting that, for this age group, their bearings are not as strongly clustered around the mean direction as they are in other age groups (Figure 4b). In other words, adult seals are less consistent in the direction they follow during return migrations, while younger seals more consistently orient toward a similar preferred direction. It should be noted that most juvenile and subadult seals were males, while most adults were females (see 31 Table 1), although it is unclear how this sex bias may have affected these results. Figure 4. Circular plots of outbound and return bearings for southern elephant seal age classes. Circular distributions of the bearings seals followed a) leaving from and b) returning to all islands grouped by age (Juveniles: females 1â2 years old, males 1â5 years old; Subadults: non-breeding males 5â8 years old; Adults: breeding females 3+ years old, breeding males 8+ years old). Weaners were not included in the data due to their small sample size (n = 2). Bearings were calculated a) in relation from the island (outbound) or b) in relation to the island (return). Mean angle of direction (a), mean resultant lengths (r), and number of individuals (n) is reported. All circular plots were tested using a Rayleigh test of uniformity and significance of plots are indicated with asterisks, with * = p £ 0.05, ** = p £ 0.01, *** = p £ 0.001, **** = p £ 0.0001. Seals from all age classes left from their islands in the southeast direction and returned to these islands in the northwest direction. However, there was a wide range of variability in these bearings, as some seals did not follow the general outbound or return direction at all, and most seals who did follow this direction did not follow the same, specific angular trajectory as others. Comparisons of bearing values across repeated trips by individual seals indicated that while seals tended to maintain a general compass direction, they did not consistently follow **** **** **** **** *** **** 32 specific bearings between trips (Figure 5). For outbound trips, there was a weak linear relationship (R2 = 0.27) and a statistically significant difference between the first and second bearings (Wilcoxon signed-rank test, V = 24, p-value < 0.001) (Figure 5a). Similarly, for return trips, a moderate linear relationship was observed (R2 = 0.58) with a statistically significant difference in bearings (Wilcoxon signed-rank test, V = 26, p-value < 0.001) (Figure 5b). For both outbound and return trips, most seals (outbound: 86%, return: 83%) followed bearings within 90 degrees of the previous tripâs bearing (outbound median difference = 27°, return median difference = 16°) (Figure 5c, Figure 5d), suggesting that seals generally orient in a consistent directional quadrant of the compass, but that this does not follow specific bearing values. This results in variability between trips at the individual level that mirrors that observed between individuals, suggesting a similar pattern in outbound and return bearings at both the population and individual level. 33 Figure 5. Comparison of difference in outbound and return bearings between repeated trips taken by individual southern elephant seals. Panels a) and b) show the linear relationship between the first and second bearing followed by individual seals during a) outbound trips (n = 43 seals) and b) return trips (n = 24 seals). Each plotted point represents a single seal. The dotted line indicates the unity line (1:1), where points would fall if the same bearing was followed by that individual seal on both trips, while the solid line shows the fitted linear regression, with the R2 value reported. Panels c) and d) show the distribution of absolute differences in bearing between the first and second trip for the same c) outbound and d) return trips shown in a) and b). The dashed line indicates the median difference and its value is reported. Together, these plots suggest that while seals generally follow a similar compass direction, they are inconsistent in the exact angular bearing that is followed between repeated outbound or return migrations. Comparisons of the difference between the bearing to the island at the final outbound point and the bearing to the island at the initial return point of the same migratory trip resulted in small changes in bearing (median value = 16°) (Figure 6a). Considering that southern elephant seals travel an average of 1300 kilometers each way during both their outbound and return migrations (Table 2), a median difference of 16° at this distance results in a sizable displacement of approximately 500 kilometers between the location of where the seal ends its outbound trip 34 and the location of where it begins its return trip. This indicates that while most seals have small differences in the angular trajectory between their outbound and return paths, they are not closely retracing their paths. The median value of spatial overlap between outbound and return tracks was small (Bhattacharyya coefficient = 0.18) (Figure 6b), indicating minimal overlap between outbound and return routes followed by most seals, consistent with Figure 6a. It is notable that while most seals were shown to have limited overlap in their paths (Figure 6c), some individuals had coefficient values close to 1, indicating a large overlap for these individuals (Figure 6d). This shows that individual seals used their spatial areas differently, with some individuals using similar spatial areas while most others followed separate paths along different segments of their migratory travel. 35 Figure 6. Directional consistency and path overlap between outbound and return tracks of southern elephant seals. Panel a) shows counts of the absolute difference between each sealâs (n = 177) bearing at the end of its outbound trip (furthest from island) and its bearing at the start of its return trip. The median difference is plotted and reported. Panel b) shows the spatial overlap between the entirety of the outbound and return route for seals (n = 115) travelling during the same migratory trip. Spatial overlap is calculated via a Bhattacharyya coefficient ranging from 0 to 1, where 0 indicates no overlap (separate spatial distributions) and 1 indicates complete overlap (identical spatial distributions). These results indicate that while the difference in bearing angle is small, at the scale of distances seals travel, most do not closely retrace their paths and most have low overlap between their outbound and return travel routes. Panels c) and d) show two example tracks of seals with c) low spatial overlap (Bhattacharyya = 0.04) and larger difference in bearing (39°) and d) high spatial overlap (Bhattacharyya = 0.73) and smaller difference in bearing (9°). How directly do seals return to islands along their migration routes? To compare the distance between the actual return route followed by seals to both hypothetical great circle paths and hypothetical rhumb lines, a linear mixed-effects model with path type (great circle vs. rhumb line) as a fixed effect was used. Seal ID was treated as a random intercept to account for dependence and the model was fitted using restricted maximum 36 likelihood. There was no statistically significant difference in the average distance between seal return tracks compared to great circle paths and rhumb line paths (LMM: β = 13.35, SE = 8.50, df = 170, t = 1.57, p-value = 0.12) (Figure 7). Of 171 return paths examined, 86 were best explained by a great circle path and 85 were best explained by a rhumb line path (data underlying Figure 7). These results indicate that seals return along paths similar to both hypothetical route types and do not follow one type more than the other. Thus, seal return paths possess characteristics of both great circle paths and rhumb line paths. Figure 7. Comparison of southern elephant seal return paths to both great circle paths and rhumb lines. Boxplots show the distribution of the mean distance between 171 recorded seal return paths to both a hypothetical great circle path and a hypothetical rhumb line path beginning and ending at the same geographic coordinates. Shorter distances indicate a closer alignment of the actual track to the hypothetical path. Seals were just as likely to follow great circle paths as rhumb lines along their recorded return paths. Over the long distances of return trips, southern elephant seals made relatively small course corrections in their bearing (median change in bearing over total distance = 0.46°) (Figure 8). A linear mixed-effects model was used to evaluate how the changes in bearing varied with 37 distance from the island. The model included binned distances as a fixed effect, a random intercept for seal ID to account for dependence, and an exponential variance structure to account for heteroscedasticity as a function of distance. The analysis revealed a significant relationship between distance and bearing, with changes in bearing becoming larger as seals approached their island (LMM: β = -0.00013, SE = 0.0000082, t = -16.17, p-value < 0.001) (Figure 8). Residual variance also declined slightly with distance, and most variability in bearing change occurred within individuals (residual SD = 3.26) rather than between them (random intercept SD = 0.50). These results indicate that seals maintain a consistent travel direction over long distances, with course corrections becoming more variable as seals near their island destinations. The greatest changes in bearing occurred in the last 1000 kilometers of return trips (Figure 8). However, even at a close range (within 200 kilometers), the median bearing correction remained relatively small (2.9°). This demonstrates that while seals fine-tune their course as they approach their island, the initial directional decision can both be assessed with accuracy at distance, and is largely effective in ensuring successful returns, allowing seals to maintain their travel direction over thousands of kilometers. 38 Figure 8. Bearing changes in relation to distance along return paths of southern elephant seals. Plot compares the absolute change in bearing between binned distances along the total distance of the return travel path for all seals. Boxes are colour-coded to differentiate each 1000 km return segment. Note differences in scale: distances in the first 1000 km are broken into 200 km segments. Results show that seals made small overall changes in bearing across the entire length of their returns, but that larger adjustments in bearing were made as seals approached their island. The straightness index (a measure of the directness of travel paths in reference to the shortest possible path) was high for all seals returning to islands (median value of 0.94) (Figure 9). This indicated that most seals followed and maintained the shortest possible paths. As these paths were calculated accounting for the Earthâs curvature, this meant that seals travelled with high straightness that accounted for curvature, not simply 2D linear straightness (e.g., constant bearing), an important distinction for return paths that traverse thousands of kilometers of open ocean. When comparing straightness indices by age, median straightness values increased with age (weaner = 0.86, juvenile = 0.93, subadult = 0.94, adult female = 0.95, adult male = 0.96), although the differences between age groups were not statistically significant (Kruskal-Wallis test, ÏÂ² = 4.92, df = 4, p-value = 0.30) (Figure 9). The high index values seen in all age groups suggest that seals closely follow the shortest possible path, even when young. However, younger juvenile individuals showed greater variability in their index values, indicated by a greater number of outlier values below 0.8 (Figure 9). For weaners, it was not possible to assess trends 39 in distribution from two tagged individuals, but it is notable that there was wide variability in these two index value results (0.99 and 0.72). Figure 9. Straightness indices of southern elephant seal return paths across age classes. Plot shows the distribution of straightness indices calculated for the return trips of seals divided into age groups (weaner, juvenile, subadult, adult female, adult male). A separate plot for a combination of all these groups (all seals, median value = 0.94) is also included for reference. Adult males and females were split due to differences in the age that each gender reaches sexual maturity. Weaner data points were included for reference but not represented with a boxplot due to their small sample size (n = 2). Straightness index values range from 0 to 1, with 1 indicating movement that follows the ideal, shortest possible path with no deviation, and 0 indicating movement that shows high levels of meandering and no linear progression. A one-way ANOVA indicated no statistical difference between seal age groups (p-value = 0.12). These results indicate that straightness indices are high, regardless of age; thus, seals follow straight paths that account for the Earthâs curvature at any age. However, there is greater variation in this straightness index when seals are juveniles compared to when they are older. A comparison of straightness indices for individuals that had two documented return trips suggested that most individuals maintained high index values from one trip to the next (Figure 10). However, these index values possessed large variability that was statistically significant (Wilcoxon signed-rank test, V = 153, p-value < 0.001) (Figure 10). This indicates thatâwhile overall index values between trips are all impressively highâan individualâs performance 40 differed over time. There was no trend in whether the first or second return trip was more direct, and as a result, no evidence that âlearningâ took place from one trip to the next, as performance did not always improve with experience. Overall, these results suggest that southern elephant seals follow the shortest possible paths often and without differences due to age, but that individual performance can vary, even between trips. Figure 10. Comparison of straightness indices between repeated trips taken by individual southern elephant seals. Scatterplot showing the linear relationship between the straightness indices for the first and second return trips made by the same individual seal. A unity line (dotted line) indicates where data points should fall if the same straightness index was calculated for both trips (i.e., seals travelled with similar directness). Repeated seal return paths possessed high overall index values, but these index values were not often similar between trips. What factors influence return timing of seals? Adult female seals (n = 54) returned to their breeding islands within a 38-day timespan from mid-September to late-October (Figure 11). Over 50% of female seals returned within the first two weeks of the arrival distribution (September 14âSeptember 27), and over 75% of female 41 seals had returned by the third week (September 28âOctober 4) (Figure 11). Most seals returned in September, but individuals continued to return throughout the month of October. To investigate what factors influenced the distribution of adult female arrival timing, the distance of the return path that each female travelled was compared against the starting date of the return, the end date of the return (when seals arrived to the island), and the average speed seals swam along their return paths. A linear regression indicated a significant negative relationship between the distance of return paths and the start date of returns (β = -0.00536, SE = 0.0014, p-value < 0.001) (Figure 11a). This suggests that seals at farther distances away from the island might leave earlier to synchronize their arrival timing with seals starting their returns closer to the island. However, while statistically significant, the model only explains 22% of the variation in start dates (R2 = 0.22) (Figure 11a), as some individuals that were close to the island left early, while some at greater distances left later. Results suggest a clumped distribution, where most seals began their returns in mid-September regardless of the total distance they needed to travel (Figure 11a). A linear regression indicated a significant positive relationship between the distance of return paths and the end date of returns (β = 0.00647, SE = 0.0011, p-value < 0.001) (Figure 11b). This suggests that seals that arrived first were simply seals whose total travel distance was shortest. The model explained 40% of the variation in arrival dates (R2 = 0.40) (Figure 11b), suggesting that some of the variation in the timing of when seals begin their return migrations is mediated by their distance away, but this is likely not the only factor or the most significant influencing their timing. There was no significant relationship found between the distance of return paths and the swimming speed of adult females (β = 0.000075, SE = 0.00013, p-value = 0.56) (Figure 11c). Most adult females tended to swim around the same speed on average regardless of the distance they needed to travel (~3 km/hr). Thus, changes in swimming speed are unlikely to be used to synchronize arrival timing when starting from varying distances. 42 Figure 11. Arrival timing of adult female southern elephant seals to breeding beaches. Plots show a) the count and b) the cumulative percentage by calendar date of when adult female seals first arrive to their breeding island. Arrival timing is binned to show the number of individuals arriving every 7 days from September 14âOctober 25 across all years. The first seal arrived on September 14 and the last seal arrived on October 22, with most seals arriving between September 21 and October 4. 43 Figure 12. Comparing return track distance and potential drivers of return timing in adult female southern elephant seals. Plots show how the total distance of adult female seal return tracks (n = 54) relates to a) the date seals initiated their return migration, b) the data seals completed their return migration and first arrived at the island, and c) the average speed travelled during the return migration. A dashed regression line is plotted to visualize the linear relationship between the variables and the R2 value is reported. The distance of the return track (i.e., the distance the seal is away from the island) does not strongly explain the start or end date of the sealâs return, although the relationship between return track distance and end date is stronger than that of start date. There was no significant relationship between return track distance and speed, as seals on average all swam at similar speeds regardless of the distance they needed to travel. 44 Discussion Using satellite telemetry data collected from southern elephant seals I investigated how these marine mammals travel to their migratory destinations. My findings revealed that the chosen migration routes taken by southern elephant seals followed a general directional pattern, but did not adhere to a single shared pathway. Instead, their chosen routes showed notable geographic separation with minimal spatial overlap between paths taken by individuals. However, the routes that seals travelled closely followed the shortest possible path when accounting for the Earthâs curvature. Their routes were also highly directional, with seals maintaining consistent bearings over their entire route. While time also played an important role in these movements and seals synchronized their arrival at breeding beaches, the factors influencing this synchronization was not accomplished by seals further away starting their migrations earlier or travelling faster. Consistency in Movement Direction Among the sub-Antarctic islands I examined, Kerguelen Island and Heard Island are 450 kilometers apart and situated on the Kerguelen Plateau, a submerged volcanic region in the southern Indian Ocean. Approximately 4000 kilometers away in the southwestern Pacific Ocean lie Campbell Island and Macquarie Island, separated from each other by about 200 kilometers. Despite the large geographic distances between the islands, it is notable that 70% of seals leaving from all these islands, regardless of age or sex, tend to leave in a southeasterly direction. This SE dispersal direction has been documented previously for weaned pups leaving from Macquarie Island and Kerguelen Island (Cox et al., 2020; Foo et al., 2023; McConnell et al., 2002; Orgeret et al., 2019), indicating consistency in the dispersal movements from these islands. However, throughout the full range of the species, dominant dispersal direction varies by breeding island. Southern elephant seals leaving King George Island generally disperse to the SW, while seals leaving Marion Island disperse to the west (Bornemann et al., 2000; Tosh et al., 2012, 2015). This indicates that southern elephant sealsâas a speciesâcan successfully migrate from any direction, and that the exhibited consistency in dispersal direction from any one island 45 is likely not due to a lack of inherent navigational flexibility. As evidence of this, 84 individuals within this dataset did not follow the SE dispersal direction of the majority and either successfully returned to these islands after months of foraging or showed no indication of becoming lost prior to tag failure. The Antarctic Circumpolar Current is the predominant oceanographic feature to the south of the four islands examined in this study. The observed southeasterly dispersal patterns might reflect use of this feature, as weaned pups from Kerguelen Island and Macquarie Island that aligned themselves with the current and travelled eastward were shown to have 1.5 times better survival than pups that travelled westward (Foo et al., 2023). Using the current might benefit seals by limiting the amount of energy needed to swim outbound from their islands and allowing them to more quickly arrive at profitable foraging patches (Foo et al., 2023). A study of weaned pups from Marion Island showed that, unlike older seals that consistently dispersed to the west, pups dispersed in different directions from year to year to target smaller-scale oceanographic features that varied in location annually (McIntyre et al., 2024). Thus, dispersal direction is likely to be impacted by local oceanographic features surrounding each island and the benefits they confer to the seals leaving from these islands, with dispersal directions potentially varying based on age. This might indicate a more advanced navigational ability that can recognize, select, and successfully follow paths utilizing favourable ocean areas over a strategy of pre-determined dispersal, even when the benefits of this dispersal path might be located thousands of kilometers away. Following a 2â8 month period of foraging, southern elephant seals return to their islands, first in the summer/early-autumn to molt and then again in the late-winter/spring to breed. The harsh conditions experienced during open ocean travel are more greatly magnified in the Southern Ocean than in all other oceans (Young, 1999), such that seals would be more likely to be blown off course while foraging and thus make these returns from a disoriented, ârandomâ location following foraging. However, seals return with a consistency in bearing similar to that when they left, but from the opposite northwesterly direction. Seals also maintain directional precision during these return trips, with a median value of correction of 0.46 degrees between segments across the thousands of kilometers that they swim. This suggests that southern elephant seals possess a strong sense of position in the ocean to return from the opposite direction they 46 travelled from, while also effectively compensating for inevitable displacement from currents and unpredictable weather events, even as juveniles. It is also interesting that return paths followed by younger seals from my study are highly clustered in the northwest direction, whereas adults are not as strictly clustered, showing more flexibility in the return directions that adults follow. As with orientation of outbound trips, these return directions are likely influenced by the foraging patches that seals use before returning to their islands. Southern elephant seals show high site fidelity to foraging areas (Bradshaw et al., 2004), and when making repeated trips, leave from similar (but as seen in my study not identical) directions. However, the exact dispersal directions can shift over time and with experience (Foo et al., 2023). Foraging strategies and foraging locations differ between seals based on factors such as age, sex, boldness, and body size, indicating that between individuals there might be large variations in spatial use (Allegue et al., 2022; Arce et al., 2022; Hindell et al., 1991, 2016). Changes in prey distribution seasonally and annually might also impact the precise areas that are targeted (Cotté et al., 2015). Foo et al. (2023) speculated that as elephant seals age they are more likely to expand their foraging distributions as they specialize, thus starting their returns from a wider range of locations. This is consistent with the wider distribution in return directions among adults seen in this study. Increased physical capabilities due to size might also allow adults to extend their travel paths or spend time exploring new areas, and experience navigating might allow for more flexible paths to be followed, resulting in return routes that begin at a different direction from what a seal might have followed when younger. Movement Patterns and Navigation Methods The observation that seals do not demonstrate strong uniformity among individuals or even consistency within individuals when beginning or returning from migrations, raises questions regarding how they successfully return to their islands. As demonstrated by differences between outbound and return headings that suggest that seals travel along paths separated by hundreds of kilometers, southern elephant seals do not show evidence of path retracing. Additionally, seals travel both north-south and east-west, efficiently moving latitudinally and longitudinally over large distances. To achieve this, seals must have the ability to recognize the 47 relative direction they need to travel and encode information when navigating to account for these different return angles. The varied directions and routes taken between individuals could suggest that elephant seals are capable of path integration, where an individual is constantly determining its position from the distance and direction of its previous movements to return to the starting point along a direct vector that follows the shortest path (Biegler, 2000). However, external cues like visual landmarks (often used by other species for path integration) are absent along southern elephant seal paths in the open ocean. For seals to rely upon path integration, updated positional information must therefore come from an internal sense that accounts for positional changes in angle and some sensory system (such as the optic flow of the passing landscape) to account for distance (Heinze et al., 2018). This method of navigation requires that seals can keep track of all previous distances and angles incurred over many months of travel. The cognitive load to account for these changing positions would likely be immense, and as time increases, rotational errors calculated internally will accumulate (Etienne & Jeffery, 2004; Heinze et al., 2018). For honeybees, flying over water was shown to cause an under-assessment of the distances they had flown due to a lack of visual contrast in the optic flow of this environment (Tautz et al., 2004). While southern elephant seals likely are better able than honeybees to assess distances travelled in a water-based environment, it is unknown whether optic flow can be assessed accurately when seals are diving underwater in poor light conditions that limit vision. These challenges suggest that path integration solely using internal cues is unlikely. Instead, external cues found in the environment likely supply a more reliable reference system, providing seals with important location information while limiting the cognitive load. The use of external cues that are continually referenced to update navigational movement across space has traditionally been thought of as a map sense, with animals using these external cues to guide themselves along a chosen path, resulting in more precise movements (Gould, 2014). The southern elephant seals in my study seemed to follow both great circle paths and rhumb lines as they migrated. As a result, their movements showed characteristics of both types: they returned along highly directed routes that travelled over the shortest possible paths, while also maintaining a relatively constant direction as they travelled. Great circle paths have been 48 shown to be followed by birds at polar latitudes (Alerstam et al., 2008), as well as by the closely related northern elephant seal (Brillinger & Stewart, 1998; Robinson, 2009). Great circle paths are efficient in that they save considerable distance and time for a navigating animal. However, great circle paths are more complex to follow than rhumb lines (which follow a constant compass heading), and therefore the latter might be chosen for its navigational simplicity. These path models vary with geographic location, and in most regions, animals cannot simultaneously follow both paths, resulting in a clear preference for one or the other. However, depending on the location and direction of travel, sometimes it is difficult to differentiate the type of path chosen. For example, in a study by Hedenström (2010), birds at polar latitudes travelling north-south were shown to maintain a constant compass direction that also resulted in them flying along a great circle path. This was possible because at the poles the distance between longitude lines is small as these lines converge, resulting in both path types roughly following the same route. This may help to explain how the seals in my study showed navigational characteristics of both path models, and why individual seals appeared to follow a great circle route during one migration and a rhumb line during another. Use of Environmental Cues Any discussion of how and whether southern elephant seals follow great circle paths or rhumb lines must consider the specific environmental cues they are using. While strong winds and persistent currents are often discussed as a barrier to efficient navigation, such forces moving in consistent directions across the open ocean might also contribute to preferred path use. Seals might follow these features to minimize their overall energy expenditure and maximize their speed, even if these routes result in longer paths (Ventura et al., 2020), such as with following rhumb lines. Use of celestial or geomagnetic cues often results in the most direct paths, but both are fraught with difficulties; celestial cues are not always visible and geomagnetic cues can express local anomalies, making them difficult to use (Ã kesson et al., 2014; Lohmann et al., 2007). The specific environmental cues that southern elephant seals might be using to achieve the movement patterns described here are explored and tested further in Chapter 3. It is possible that southern elephant seals use multiple cues or oceanographic features simultaneously to combine both simplicity in use and precision in navigational results. However, 49 it is also possible that southern elephant seals switch between multiple cues or oceanographic features as they proceed along specific routes. It has been demonstrated that different navigational cues, with different scales of accuracy, are employed by animals across their migrations (Bingman & Cheng, 2005). At the furthest distances, thousands of kilometers from the goal, celestial and geomagnetic cues may dominate, as they can be encoded over a vast range of unfamiliar starting locations (Sequeira, 2020). Hundreds of kilometers from the goal, olfactory or chemical cues can be used to identify more specific areas and home in on the target (Bonadonna & Gagliardo, 2021; Padget et al., 2017). In the final stage tens of kilometers from the destination, visual cues and use of landmarks might be especially important to pinpoint exact locations (Biro et al., 2002; Matsumura et al., 2011). This framework divides migration routes into different phases, where each phase only needs enough cue resolution to bring the migrating animal to the next phase (Bingman & Cheng, 2005). This concept might explain why greater course adjustments were observed as southern elephant seals approached the islandsâthey may have been switching from using cues that could direct them from general oceanic areas to those more capable of finding specific breeding beaches. Many significant adjustments occurred less than 1000 kilometers away from islands, with the largest adjustments made less than 200 kilometers away, following the general patterns assumed in a multi-cue framework. While small scale movements at distances of tens of kilometers from the destination were not captured in detail due to the initial assumptions and time-steps considered for this data, it might be worthwhile exploring these near-shore movements to better understand the use of small-scale visual cues to find breeding beaches, especially when seals approach the island from directions where breeding beaches are not immediately visible. Experience in Navigation Learning, along with memory formed through experience, is an important component of the navigational process, especially for long-lived animals that make multiple migrations during their lifetime (Fagan et al., 2013; Lewis et al., 2021). Foraging strategies of southern elephant seals have been shown to be influenced by knowledge that is gained in the first year of life as seals explore initial dispersal areas, determine their profitability, and then return to profitable 50 areas based on memory (McIntyre et al., 2024). Navigational performance is also likely influenced by learning, as travel routes in other species become more efficient as animals become more experienced (Quintana et al., 2022). Social learning or group-based navigation can further improve the efficiency of travel routes (DellâAriccia et al., 2008; Flack et al., 2012; Granger & Johnsen, 2022; Nesterova et al., 2015). As southern elephant seals have not been documented travelling together (even when released together) and do not travel alongside their mothers after weaning (Crocker et al., 2001; Oliver et al., 1998), it is likely that any learned experience is gained individually and independently of others. In my study, the role of experience did appear to improve migratory performance in some metrics, but this was not required for success. Among all seals, southern elephant seals return to their islands with an average straightness (0.92) that is remarkable for an animal travelling in disruptive open ocean conditions and not following the same paths every time they travel. All age groups show highly directed returns that follow the shortest possible paths, suggesting that navigational abilities are inherent. There was wider variation in younger age groups, likely indicating that although seals are well-equipped with these skills from birth, they still learn to refine them over time, with some individuals learning more quickly than others. While data from weaners (weaned pups migrating for the first time) was limited in this study, one weaner recorded a straightness index of 0.99, indicating an incredibly straight path in its maiden migration that is unlikely to have been acquired through learning alone. These inherent abilities have also been documented for northern elephant seals, where a majority of translocated juveniles not only homed successfully, but returned to their breeding colony following direct routes with minimal wandering, even when diving underwater (Matsumura et al., 2011; Oliver, 1997; Oliver et al., 1998), and adults were documented following courses that immediately led them home with astonishing precision (Le Boeuf et al., 2000). Timing of Movement For migrating animals, knowing where to go is equally as important as knowing when to arrive. For southern elephant seals, the timing of return migrations is especially important for breeding, as adult females arrive at islands to give birth to pups then subsequently breed, and 51 adult males compete for territories and breeding partners. Arriving late to the breeding beaches can result in increased competition for breeding and birthing space or limited access to breeding partners, thus decreasing individual biological fitness (Abrahms et al., 2021). For adult males, arriving too early cuts short the time that can be spent feeding at sea to gain mass, making it harder to compete against larger competitors for breeding opportunities or maintain good body condition throughout the season, again decreasing individual fitness (Abrahms et al., 2021). Arriving too late limits opportunities for claiming prime territories, and hence access to females. For adult females, timing must be even more precise, as females need to come ashore to successfully give birth to their pups, while spending enough time at sea to accumulate sufficient energy reserves to successfully wean their pups and maintain themselves during an extended period of fasting over lactation and subsequent breeding (Crocker et al., 2001). It is important to note that the majority of the adults in my study were females, and given the sex differences in when âoptimalâ return timing occurs, only data from the adult females was used to evaluate the level and mechanisms of arrival synchrony. The timing of adult female returns documented in my study matches the breeding period previously documented for southern elephant seals (Hindell et al., 2016). Combining data from all years (2009â2019) revealed that most females started their returns beginning at the end of August through mid-September, with some individuals starting as late as the first week of October. Females arrived at the breeding beaches starting in mid-September and continued through mid-October. By October 15th, the common date used by Hindell et al. (2016) to count hauled-out adult females on all islands and estimate annual seal numbers, 94% of adult females in my study had returned to land. However, return timing was not strongly influenced by the distance that seals were away from breeding islands or by their swimming speed. In other words, southern elephant seals did not start returning earlier if they were further from the breeding beach, nor did they increase their swimming speed to compensate for the greater distances they needed to travel. This contrasts with findings in northern elephant seals that suggest that females begin their return migrations based on how far they need to travel, with seals further away from the breeding site beginning their return migrations earlier (Beltran et al., 2022). A second study examining northern elephant seal return timing also showed that seals farthest from the breeding beaches travelled three times faster than seals near the breeding beaches to synchronize arrivals together (Condit et al., 2022). 52 It is not clear why the southern elephant seals in my study did not exhibit strong correlations in return timing based on distance away or swimming speed. It is notable that my study examined return timing across multiple breeding islands and not within a single breeding colony, as was the case with the previous studies exploring return timing in northern elephant seals (Beltran et al., 2022; Condit et al., 2022). However, previous research has shown that adult female return timing has been largely consistent across all major southern elephant seal populations since the 1950s (Campagna et al., 1993; Hindell & Burton, 1988), suggesting that the drivers of this timing are robust to environmental change or island-specific variation. Another study examining the number of adult females hauled out on Macquarie Island for the breeding season between two subsequent years measured a 5-day difference in when the highest number of seals were present (Hindell & Burton, 1988). This suggests that while return timing may be synchronized within a given year, interannual variation in individual timing could weaken correlations when examining factors such as return or arrival dates across years. Analyzing tracks by year and breeding island might have revealed such patterns; however, the sample size in my dataset limited my ability to explore potential annual or regional differences. This lack of apparent relationship between the timing of return journeys or swimming speed with distance may also be related to the way that the beginning and end dates of these return journeys were determined. Return timing for this study was based on the decoded results of the HMM, whereas returns for the previous northern elephant seal studies were based on derivates of daily distance calculations and high-resolution time-depth data that allowed for accurate arrival timing within a given hour (Beltran et al., 2022; Condit et al., 2022). The methods used in my study likely led to inevitable variations in the dates selected for arrival and initial departure, with more accurate dates obtained in the northern elephant seal studies. In my study, it was unknown when adult females gave birth once they arrived at the island, or if they were even pregnant. In contrast, the birthdates of pups were directly known for northern elephant seals, as births were directly observed (Beltran et al., 2022; Condit et al., 2022). The need to give birth would be a driving factor likely impacting individual arrival timing, and without knowing the specific reproductive details for the southern elephant seals in my study, it is difficult to determine if the individuals analyzed shared the same level of motivation for their returns. In other pinniped studies, such as those on fur seals, older pregnant females have been shown to return to land earlier than younger pregnant females (Lunn & Boyd, 53 1993; Trites, 1991). Similarly, it has been shown that breeding experience also plays a role in arrival timing, as female southern elephant seals that are breeding for the first time arrive and pup earlier than females that have experience breeding (Kirkman et al., 2004). The effect of reproductive history could not be investigated in my study due to the absence of specific age data for the adult females analyzed. More accurate arrival timing or analysis considering the timing of births and the experience of mothers might change the results reported here, potentially strengthening the relationship of factors examined. Additional factors affecting return timing, such as photoperiod and temperature (both of which vary significantly with latitude), should be considered in future studies, as these have been shown to influence migration timing in other species (Kappeler, 2021; Putman et al., 2013; Tyagi & Bhardwaj, 2021). Buoyancy (a proxy for body condition) has also been suggested as a factor influencing the initiation of returns in southern elephant seals, on the assumption that seals will start their return trips once they reach an optimal, neutrally buoyant range (Orgeret et al., 2019). This means that seals might wait to travel until they attain sufficient energy stores, but might also delay travel if their body condition is too high, as this increases their cost of transport (Orgeret et al., 2019). While it has not been shown that elephant seals travel together in a traditional sense, coherency in the movements of female northern elephant seals might suggest a larger group-like network based on breeding hierarchy that could contribute to synchronicity in return movements, with seals on the outer edges of these networks initiating their returns later (Pei et al., 2023), though the exact mechanism for this synchronization of movements is unknown. The energy stores obtained from foraging trips must sustain southern elephant seals throughout the breeding season, directly translating to their reproductive success (Crocker et al., 2001). This balance of timing and knowing when to travel is important to optimize the benefits received. In theory, seals should maximize the time spent foraging to increase energy stores, while also increasing beneficial time on breeding islands. Thus, time spent travelling should be minimized, providing an evolutionary incentive for individual seals to be good navigators to reach the end points of their migrations in a timely manner. 54 Importance of Understanding Navigation I found that southern elephant seals are incredibly efficient navigators. Their migration routes are precise, directed, and timed. This ability appears to be strong from an early age, and seals migrate successfully from a wide range of directions without retracing their paths. This study also demonstrates the strengths of analyzing animal tagging data to understand the movement patterns of long-distance migrations. Not only does this shed light on the navigational abilities of a pinniped that cannot be studied using traditional techniques, but it also helps to inform further investigations testing the use of cues that potentially support these abilities. Understanding how marine mammals navigate and what cues they are using is important for constructing population trajectories and implementing measures for their conservation. For example, findings from studies like mine can help determine whether travel paths used by southern elephant seals are flexible or rigid. This has critical implications not only for identifying and protecting the most important routes, but also for predicting the speciesâ ability to adapt to rapidly changing environments. The Southern Ocean is expected to undergo some of the most rapid climate change globally, leading to major environmental disturbances that will impact higher trophic-level predators (Trathan et al., 2007). One of the main impacts of these changes will be shifts in prey location and prey availability, especially for marine mammals (Constable et al., 2014). For southern elephant seals, adapting to such changes will likely depend heavily on their navigational flexibility to locate newly distributed prey and successfully return to their islands from these new locations. Efficient navigational abilities would likely benefit seals under such conditions, but strong foraging site fidelity could result in individuals making repeated visits to poor quality sites with limited prey availability, ultimately impacting population trajectories (Abrahms et al., 2018). Despite the importance of understanding the link between climate change and migration, this relationship remains poorly understood (Shaw, 2016), highlighting the importance of conducting navigational studies to shed light on these connections. Southern elephant seals are geographically constrained to their breeding islands, making their ability to adjust migratory routes particularly important. Archaeological remains show that southern elephant seals were once common along the coasts of Australia and New Zealand, but dynamic range shifts during the Holoceneâpartly due to climate changeâled to local 55 extinctions (Berg et al., 2025). Anthropogenic pressure, both from Indigenous hunting and later industrial sealing, further contributed to their range compression, resulting in southern elephant seals primarily inhabiting sub-Antarctic islands that were more remote and less impacted by humans (Berg et al., 2025). Between the 1950s and 1990s, southern elephant seals underwent large population declines throughout their range, likely driven by environmental changes that affected prey quality and availability (McMahon et al., 2005). In recent decades, most populations have recovered; however, the population on Macquarie Island continues to decline (Chua et al., 2022; Hindell et al., 2016; McMahon et al., 2005). Seals from Macquarie Island have been shown to migrate farther to find ice-covered areas or exhibit intense search behaviour, suggesting a potential lack of nearby resources that forces them to travel further to meet energetic demands (Berg et al., 2025; Chua et al., 2022). This raises critical questions about the limits of the sealsâ navigational flexibility and how rapidly seals can respond to environmental pressures. Even if seals can extend their migratory routes and successfully return from these longer excursions, the prey they acquire may not be sufficient to support their long-term survival and reproduction. While seals from Macquarie Island face ecological limitations, other southern elephant seal populations are increasingly exposed to anthropogenic pressures in their foraging grounds. Seals travelling to and from Kerguelen Island or Heard Island must navigate through areas with active fisheries targeting Patagonian toothfish and mackerel icefish (Hindell et al., 2022). Although current impacts from these fisheries appear minimal, both male and female elephant seals use these areas for foraging and migration (Hindell et al., 2022). Females primarily forage at the depths where longlining activities occur to feed on Patagonian toothfish targeted by the fishery, raising concerns about potential competition or disturbance (Cherel et al., 2008; Hindell et al., 2022). Anthropogenic impacts from fisheriesâincluding bycatch, entanglement, and competition for preyâcan directly affect seal health and survival. Non-lethal interactions may damage or impair sensory systems that detect navigational cues or may increase ambient environmental noise, making navigation more difficult. As a result, seals may avoid certain areas or follow more circuitous routes, increasing energy expenditure and potentially compromising navigational success (Sequeira, 2020). Movements of terrestrial mammals in areas with high human footprints are half the normal range of animals in areas with low human footprints (Tucker et al., 2018). These human- 56 caused disruptions can significantly disturb migratory movements, leading to potential phenological mismatches, impacts to ecosystem processes, and population declines (Tucker et al., 2018). Despite southern elephant seals travelling across the majority of the Southern Ocean, only 7% of the ocean south of 40°S is formally protected (Hindell et al., 2020). Conservation efforts for southern elephant seals and other Southern Ocean species would benefit from incorporating cue use and navigational pathways into decision-making when designing protected areas. Managers and scientists should make use of abundant and pre-existing animal tracking data to better understand navigation and its value for conservation. 57 Chapter 3: No sun, no moon, just magnetism? Evaluating potential cue use by navigating southern elephant seals Summary Southern elephant seals (Mirounga leonina) undertake long-distance migrations across the Southern Ocean in search of food before returning to small, isolated islands several months later. Their migrations are highly directed and precise, yet the environmental cues guiding them remain a mystery. Analysis of movement patterns can provide clues to which cues they use to direct and time migrations. I compared movement patterns derived from tracking data from 271 tagged elephant seals against predictions based on the assumed use of lunar, solar, and geomagnetic cues to assess the likelihood of each cue being used for navigation. Results showed that it was unlikely that long-distance movements were facilitated using lunar or solar cues in isolation. Seal movement timing was not biased toward any specific lunar fraction, as migration start and end points did not consistently align with specific lunar fractions, either at the individual or species level. Seals did not maintain a consistent offset angle to the sun, nor did they adjust their bearing during sunrise or sunset. In contrast, results showed that the movements of southern elephant seals were potentially explained by the use of geomagnetic cues. Specifically, individual seals followed consistent geomagnetic gradients (inclination, total intensity, and declination, as well as a combination of inclination and total intensity), although individual seals followed different gradient directions. Sensitivity analyses indicated that seals must possess high sensitivity to changes in both inclination and total intensity to rely on geomagnetic information, though they may use these parameters independently or in combination to navigate. The findings of my analysis suggest that the extraordinary movements of southern elephant seals may be facilitated by a ubiquitous environmental cue and provide some of the first evidence that pinnipeds may use geomagnetic information for navigation and goal-finding. 58 Introduction Southern elephant seals (Mirounga leonina) undertake some of the longest seasonal migrations among marine mammals, travelling over 4,000 kilometers one-way (Hindell & McMahon, 2000; McConnell & Fedak, 1996). Movements cover vast areas of open ocean and connect foraging areas in the Southern Ocean to isolated terrestrial islands at sub-Antarctic latitudes (Allegue et al., 2022). Southern elephant seals display high natal fidelity to these islands, returning twice a year to molt and breed (Reisinger & Bester, 2010). This results in two distinct migrations that occur during different seasons of the year, with the first (following the end of the breeding period) lasting 2â4 months and the second (following the end of the molting period) lasting 4â8 months (Hindell et al., 2016). Sizable geographic differences and minimal overlap in routes indicate that southern elephant seals take different migratory paths from each other to reach their natal islands. Even individual seals do not repeat the same route across their two annual migrations (Chapter 2). Time also plays an important role in these movements, with adult females showing synchronicity when arriving to these islands, although the degree to which this is determined by departure time or travel speed is still unclear (Chapter 2). Despite following spatially and temporally distinct migration routes, southern elephant seals demonstrate remarkable precision in their movements. Seals maintain consistent, directed paths across thousands of kilometers, with limited corrections to trajectory, even from a wide range of starting points (Chapter 2). Paths often follow the shortest possible straight path when considering the curvature of the Earth, resulting in efficient movements that also seem to account for the effects of variable sea surface currents (Chapter 2). Numerous studies have demonstrated that animals from a wide range of taxa exhibit similar consistency in their movements when migrating, suggesting that precise directional and temporal orientation is a common feature of animal migration regardless of environment (Avens & Lohmann, 2004; Fuiman et al., 2021; Heinze & Warrant, 2016; Horton et al., 2011). This process of undertaking directed movements towards a goal is known as navigation, and has been the focus of scientific study and general curiosity for centuries (Gould, 2004). Navigation can be generally understood using the map and compass framework first presented by Kramer (1953), which proposes that animals use a two-step process when navigating over long distances. The first, the âmap stepâ, is used to determine the animalâs present position and the second, the 59 âcompass stepâ, informs the specific direction the animal needs to travel in to reach its goal (Wiltschko & Wiltschko, 2023). Breakthroughs in the study of animal navigation came in the 20th century with the discovery of different âcompassesâ in the form of environmental characteristics that animals could detect and use to direct their movements during this second step (Papi, 2001). Commonly referred to as cues, specific environmental factors that are thought to be used by different animals have since been frequently tested in many navigating species (Ã kesson et al., 2014), but have yet to be explored for southern elephant seals. One of the most widespread of these environmental cues, the Earthâs magnetic field, was first shown to influence orientation in birds. Geomagnetic cues have since been shown to be utilized in the movements of invertebrates, insects, fish, and mammals (Boles & Lohmann, 2003; Dreyer et al., 2018; Hart et al., 2013; Mouritsen, 2022; Naisbett-Jones & Lohmann, 2022), and have even been investigated in humans (Baker, 1987; Wang et al., 2019). For navigating marine animals, geomagnetic cues are thought to be especially important and many species, including but not limited to lobsters, sea turtles, and salmon have been documented using geomagnetic cues during navigation (Cain et al., 2005; Lohmann et al., 2008b; Naisbett-Jones et al., 2020). The Earthâs magnetic field is a ubiquitous environmental feature that is present in all areas of the ocean, even at depth. It is present during both the day and night and is unaffected by changes in weather, making it a potentially stable and reliable cue. In addition, several specific components of the magnetic field vary in predictable ways across the Earthâs surface, allowing animals to potentially use these expected variations to guide their movements. While some animals only respond to and use one component of the field when navigating, other animals can use a combination of two of these components, a process often referred to as âbi-coordinateâ navigation (Lohmann et al., 2007; Pizzuti et al., 2022). Of these components, geomagnetic inclination and total intensity are thought to be most commonly used by navigating animals, especially when used together, but geomagnetic declination can also be used (Kishkinev et al., 2021; Putman et al., 2014a; Wiltschko & Wiltschko, 2023). Another widely used cue is the sun, where animals use solar information as a cue to inform their direction. The sun is only present during the daytime and only visible in good weather conditions, but can be seen from any location (except at depth underwater). Solar cue use was first demonstrated in birds, and has since been shown in a wide variety of insects and 60 birds, including seabirds (Freas & Cheng, 2022; Padget et al., 2018). However, for most marine animals, solar cues are generally thought to be supplemental sources of information that complement the use of other cues, as the sunâs position has not been shown to fully explain the movements of most oceanic animals, although this has not been widely explored (Horton et al., 2011; Lohmann et al., 2008b). Unlike geomagnetic information, the use of solar cues necessitates that an animal must have a sense of time to interpret the sunâs position, as both the sunâs direction compared to true north (the solar azimuth) and the height of the sun above the horizon (the solar altitude) changes daily, seasonally, and based on latitude (Wiltschko & Wiltschko, 2023). There are some studies to suggest that animals could use the sun to indicate when to assess geomagnetic information at certain times of the day (such as at sunrise or sunset), instead of using the sun continually throughout the day (Cochran et al., 2004), lessening an animalâs reliance on precise time-keeping throughout the day or across long-distance journeys that traverse latitudes or span seasons. Both geomagnetic and solar cues are theorized to assist with determining the direction an animal needs to travel to reach its goal (the compass step). Another important component of goal-finding not often considered explicitly in the map and compass framework is that of timing. Travel timing can provide animals with a sense of where they are along their migration route (the map step), without needing to obtain specific positional information (i.e., time as a proxy for distance travelled). Timing of movement is also critical for animals that need to determine how long they should (or are expected) to travel, particularly if it is important to reach their destination within a narrow timeframe. Timing for the map step can potentially be obtained utilizing the same environmental cues used for the compass step, but requires a different interpretation. For navigators such as southern elephant seals that travel thousands of kilometers and are at sea for many months before returning to breeding islands, it is likely difficult to assess position via time using methods such as solar cues that must be assessed daily, as seals must account for changes across seasons and latitudes when timekeeping. Instead, lunar cues might offer a more consistent reference system that can better assess timing across monthly scales. While the moon is only present during the nighttime and can only be observed near the waterâs surface, it has been proposed that once the lunar cycle is integrated into an animalâs sensory system (i.e., once an internal biological clock is set based on lunar information), this system should be able to function independent of an external 61 lunar cue (Ritter & Tessmar-Raible, 2024). Humpback whales and great white sharks have been shown to arrive and depart from goal locations during full or new moons, and movements along routes indicated temporal pacing according to cycles impacted by the position of the moon (Horton et al., 2017). Thus, lunar information could be an important cue that can facilitate migrations and assist in location-finding by providing a temporal component for navigational movements. To assess if southern elephant seals might use lunar, solar, and/or geomagnetic cues when navigating, I developed predictions for how the direction or timing of seal migration routes would be expected to appear if seals utilize each cue. These predictions were then compared to the actual migration tracks of 271 satellite-tagged southern elephant seals navigating across the Southern Ocean to assess how closely these predictions matched documented routes. These predictions are as follows: 1. Lunar cues: The timing of seal movements, both at the population level and at the individual level, will be consistent with specific amounts of lunar illumination (also known as the lunar fraction). At the population level, seals are expected to initiate or terminate outbound or return migrations during a common lunar fractionâlikely near the full moon, when illumination is highest and the moon is the most visible as a cue. At the individual level, seals are expected to keep time within their own migrations, initiating and concluding outbound and return movements during the same lunar fraction, even if that differs across individuals. 2. Solar cues: Seals will either (a) maintain a consistent angular offset relative to the solar azimuth (the sunâs position along the horizon) during travel, regardless of geographic location or time of day, or (b) exhibit larger directional shifts at key times of day (i.e., major course corrections) âmost likely during sunrise and sunset when solar altitude makes the sunâs position most easily discernable. 3. Geomagnetic cues: Movements of seals will align with one or more geomagnetic parameters: inclination, total intensity, or declination. Seals will either move along gradients of this parameter (consistently moving from high to low values or vice versa) or along a single isoline of this parameter (maintaining a constant value) until they reach their goal. If movements appear responsive to both inclination and total intensity, then a combined bi-coordinate metric may better explain their paths. Sensitivity thresholds were 62 also examined to assess whether the observed changes in these parameters support feasibility of magnetoreception as a navigational cue. Coupled with the previous predictions, these analyses provide a structure for understanding the relationship between cue use and southern elephant seal movements. This approach highlights what environmental cues might be potentially used by these marine animals to achieve the migratory movements documented in Chapter 2. The results from this study can help to inform and refine future investigations that seek to directly test the use of these cues or their detection limits to better understand the information used by seals to complete their incredible navigational journeys. Methods Tagging Data & Modelling As part of previous studies, southern elephant seals were captured at five deployment sites around the Southern Ocean between 2009 and 2019 and tagged with a CTD Satellite Relay Data Logger. Tags transmitted the sealâs movements using an ARGOS satellite tracking system while also collecting diving metrics via a pressure sensor and recording haul-out information via a wet-dry sensor. For more information about these tags, how they were deployed, and additional demographic information about the seals tagged, refer to the methodology in Chapter 2. Details of data preparation, including identification of travel segments, are also provided in Chapter 2. In brief, I applied a correlated random walk state-space model to correct for errors in the ARGOS location data transmitted by the tags. This produced predicted location data at 6-hr intervals. These predicted locations, in combination with diving and haul-out information, were then used to construct a three-state hidden Markov model (HMM) to identify and classify the behaviour of the sealâs movements, with particular interest in the segments identified as âtravelâ. I made additional classification based on location, time, and date to divide travel periods into âoutboundâ or âreturnâ segments, corresponding to when seals were heading away from or towards their breeding and haul-out islands, respectively. Data preparation and 63 modelling yielded a total of 403 divided track segments from 271 southern elephant seals that were used for all subsequent analyses. Lunar Cue Use To test whether the timing of southern elephant seal migration movements are consistent with lunar cue use, I calculated the lunar fractionâdefined as the illuminated fraction of the moonâfor the first and last location points for both outbound and return travel segments using the suncalc R package (Thieurmel & Elmarhraoui, 2022) using R version 4.4.0. Calculations were considered only for seals that had outbound trips with corresponding complete return trips, such that the data accurately reflected the start and end of both segments of the migratory journey and encompassed the total timing of the trip. Lunar fraction values range from 0 to 1, with a value of zero representing no illumination (i.e., a new moon) and a value of one representing full illumination (i.e., a full moon). I binned lunar fractions into five groups each spanning a 0.2 segment of the total range and compared the proportion of seals starting or ending both their outbound and return journeys according to the lunar fraction present during these movements. The lunar fraction is not linearly proportional to the number of days in the lunar cycle, as the moonâs illumination changes at varying rates throughout the cycle. Due to this sinusoidal relationship, the change in illumination around the new and full moon is slow, while change is much faster during other phases, such that more time is spent in the former than the latter over a lunar cycle. To account for this, I calculated the lunar fraction for every day between January 1, 2009 to December 31, 2019, so as to span the entirety of the time encompassed within the tagging dataset. To test whether seals at the population level begin and/or end their outbound and/or return travel during a specific phase, the observed proportions of lunar fractions constructed from seal movements were compared to the expected proportions of lunar fractions across the tagging period using chi-squared goodness-of-fit tests for all start and end conditions. To test whether southern elephant seals also used lunar information to keep time between outbound and return migration points, I compared the previously calculated lunar fractions within an individual sealâs migration. For each individual seal, four comparisons were made to 64 assess if the lunar fraction was the same or different between each combination of the start of the outbound, the end of the outbound, the start of the return, and the end of the return. The total number of seals that were similar or different in their lunar fraction movements within each category was also compared. Solar Cue Use To test whether southern elephant seal movements conform to predictions about their reliance on the sun as a cue, I compared seal movementsâspecifically their bearingâto both the solar azimuth and the solar altitude. The solar azimuth is the angle between the sunâs position and true north, measured in degrees. The solar altitude is the angle of the sun above the horizon, also measured in degrees. Values for the solar azimuth and the solar altitude were obtained based on the location, date, and time for each recorded point along all seal return paths using the suncalc R package (Thieurmel & Elmarhraoui, 2022). The first analysis sought to determine if seals consistently align their movements in relation to the sunâthat is, travelling at a consistent, fixed angular offset to the sun. This entailed comparing the solar azimuth calculated for each given point to the bearing of the seal at that same point. The sealâs bearing was calculated in relation to the sealâs next subsequent point (also measured from true north) using the geosphere R package (Hijmans, 2010). Bearings were calculated along a great circle path for the duration of each return trip. The difference between the sealâs bearing (or its direction of movement) and the solar azimuth was presented on circular graphs showing this angular difference for all seals and a Rayleigh test for uniformity was used to test the distribution of these angles around the circle. As seal movements in association with the sunâs position were only assumed to occur when the sun was visible, only locations where the sun was above the horizon (indicated by a solar altitude greater than 0°) were plotted. An additional analysis also plotted these differences by individual, to assess if individual seals might follow patterns separate from that followed by the group. The second analysis explored the relationship between seal movements and solar altitude by testing the extent of directional changes during specific solar periodsâsunrise, sunset, day, night. I assumed that sunrise and sunset represented clearly defined periods where the sunâs position was easily discernable and would allow seals to adjust their bearing without requiring an 65 internal clock to compensate for daily or seasonal positional shifts. Sunrise was defined as the period when the top of the sun is first seen on the horizon up until 5° altitude and sunset was defined as the period from 5° altitude until when the sun first disappeared below the horizon. Adjustments to this definition were also made to incorporate atmospheric refraction, where the sun appears higher in the sky than its actual position during sunrise and sunset, providing an extended period where seals could view and use the sunrise or sunset as a reference cue. This resulted in a range of solar altitude from â0.83° to 5° that defined sunrise and sunset, leaving all other data to be classified as either day or night based on whether the altitude values were positive (day) or negative (night). Changes in a sealâs directional bearing in relation to its next subsequent point at each point across return tracks (previously calculated) were grouped within these four solar periods based on each pointâs corresponding solar altitude. I constructed boxplots to assess the distribution of these positional changes across all four periods and used Kruskal-Wallis tests to compare these groups. Geomagnetic Cue Use To test whether southern elephant seal movements conform to predictions about their use of the Earthâs magnetic field as a cue, I obtained geomagnetic inclination, total intensity, and declination values for all seal locations during return travel segments. These values were acquired using the World Magnetic Model R package (Frierson, 2021), which calculated the three components of the geomagnetic field at each given point based on the location, date, and time. Geomagnetic inclination represents the angle between the magnetic field vector and the Earthâs surface. At the equator, the field is 0°, meaning it is perfectly horizontal. At the poles the field is vertical, with field lines pointing downward in the northern hemisphere (+90° at the North Pole) and upward in the southern hemisphere (â90° at the South Pole). Total intensity represents the total strength of the geomagnetic field at a given location. Intensity varies less uniformly than inclination but tends to be strongest near the poles and weakest near the equator, ranging from ~25,000 to 65,000 nanoteslas (nT). Geomagnetic declination is difference in angle between magnetic north and geographic north at a given location (± 180°). A positive declination occurs when magnetic north is east of true north, and a negative declination occurs when 66 magnetic north is west of true north. Contour maps illustrating the spatial variation of these three geomagnetic parameters in the Southern Ocean are provided for reference (Figure 13). Figure 13. Contour maps showing variation in geomagnetic field parameters across the study area. Maps showing the contour lines for three parameters of the geomagnetic field: inclination, total intensity, and declination. Red contour lines represent a positive parameter value, blue contour lines represent a negative parameter value, and green contour lines represent zero. The white asterisk represents the position of the dip pole (magnetic field lines are perfectly vertical). The mapped area encompasses the area of the Southern Ocean where tagged southern elephant seals in this study travelled. Black dots represent the location of islands that seals left from and returned to at the beginning and end of their migratory trips (KI = Kerguelen Island, HI = Heard Island, MI = Macquarie Island, CI = Campbell Island). Maps are adapted from maps developed by NOAA/NCEI and CIRES for the 2025 US/UK world magnetic model. kjkj806040200-20-40-60806040200-20-40-600-80-8075°N60°N45°N30°N15°N0°15°S30°S45°S60°S75°S90°N75°N60°N45°N30°N15°N0°15°S30°S45°S60°S75°S90°S180°135°E90°E45°E0°45°W90°W135°W180°135°E90°E45°E0°45°W90°W135°WUS/UK World Magnetic Model - Epoch 2025.0Main Field Inclination (I)Zero lineNegative (up)Positive (down)Main FieldInclination (I) Position of Dip PoleskjContour interval: 2 degreesMiller Cylindrical ProjectionMap developed by NOAA/NCEI and CIREShttps://www.ncei.noaa.gov/products/world-magnetic-modelPublished December 2024kjkj5000045000400003500030000250005500050000450004000060000550004000035000600005500065000600005500060000500004500075°N60°N45°N30°N15°N0°15°S30°S45°S60°S75°S75°N60°N45°N30°N15°N0°15°S30°S45°S60°S75°S180°135°E90°E45°E0°45°W90°W135°W180°180°135°E90°E45°E0°45°W90°W135°W180°US/UK World Magnetic Model - Epoch 2025.0Main Field Total Intensity (F)Contour interval: 1000 nTMain FieldTotal Intensity (F)Position of Dip PoleskjMiller Cylindrical ProjectionMap developed by NOAA/NCEI and CIREShttps://www.ncei.noaa.gov/products/world-magnetic-modelPublished December 2024kjkj906050403020100-10-209080706050403020100-10-20-30-40-5090807060403020100-10-20-30-40-50-60-70-800-10-10-200-3070-40-90-5040 20100-60-70-90-800-30-90-601075°N60°N45°N30°N15°N0°15°S30°S45°S60°S75°S90°N75°N60°N45°N30°N15°N0°15°S30°S45°S60°S75°S90°S180°135°E90°E45°E0°45°W90°W135°W180°135°E90°E45°E0°45°W90°W135°WUS/UK World Magnetic Model - Epoch 2025.0Main Field Declination (D)Zero (agonic) lineNegative (west)Positive (east)Main FieldDeclination (D) Position of Dip PoleskjContour interval: 2 degreesMiller Cylindrical ProjectionMap developed by NOAA/NCEI and CIREShttps://www.ncei.noaa.gov/products/world-magnetic-modelPublished December 2024Main Field Inclination (°) HI CI MI KI MI CI KI HI KI HI MI CI Main Field Total Intensity (nT) Main Field Declination (°) 67 To assess whether seals followed geomagnetic gradients or contours during their return migrations, I analyzed changes in the three geomagnetic parameters obtained along each sealâs return path. While most studies have found that animals follow geomagnetic gradients (Wiltschko & Wiltschko, 2023), there is evidence to suggest that cetaceans might follow paths of local magnetic minima similar to geomagnetic contour use (Kirschvink et al., 1986). For each successive location, I calculated whether the parameter value increased (positive change) or decreased (negative change). If a seal consistently followed a geomagnetic gradient, changes would occur in one dominant direction (either positive or negative)âresulting in 100% of movements aligning with that gradient. In contrast, movement along a geomagnetic contour would produce roughly equal numbers of positive or negative changes (~50% each), as the seal weaves left and right along this contour line. Each return path (including seals with multiple returns, each treated independently) was assessed for the number of positive and negative directional changes occurring during the trip, resulting in multiple data points for a single return path. The direction (positive or negative) with the higher count for each trip was labelled the âmajority directionâ, and the other the âminority directionâ, with counts conducted for each track independently. For each track, I then calculated the proportion of track segments a seal spent moving in each (majority or minority) of these directions. This provided a single set of percentage values (majority or minority) for each return trip. These percentages were compiled across all return trips for each geomagnetic parameter. Wilcoxon signed-rank tests were used to test whether the percentage of majority directions differed from a theoretical median of 50%, providing insight into whether seals tended to follow gradients or contours. To assess if southern elephant seals use a combination of total intensity and inclination instead of relying on each parameter in isolation, I considered the change in both parametersâ values for each point along the return path. As both parameters could change positively or negatively independently from each other, four distinct movement options were identified to classify the majority directional pairing for each trip (positive total intensity & positive inclination; positive total intensity & negative inclination; negative total intensity & positive inclination; negative total intensity & negative inclination). For each return trip, I compared the number of location points characterized by each category, and whichever pair had the highest count was considered the majority direction pair for that trip. Combined counts for all other pair 68 categories were considered the minority direction. As with the single parameter analysis, results were compiled for all seals and the percentage of the return path spent travelling in the majority direction was compared to a theoretical 50% median using a Wilcoxon signed-rank test. Geomagnetic Cue Sensitivity To account for the possible effects of detection sensitivity on the ability of southern elephant seals to successfully navigate using the geomagnetic cues present in the Southern Ocean, low and high sensitivity thresholds were identified for each of the three geomagnetic parameters (Table 4). High sensitivity values were based on previous studies testing magnetic cue use in other taxa, with estimates for inclination and total intensity derived in Lohmann et al. (2024). Low sensitivity values were based on values assumed in Schneider et al. (2023) and tested magnetic cue use in Phillips et al. (2002). 69 Table 4. Geomagnetic detection thresholds. Low and high thresholds were assumed for each geomagnetic parameter to assess the effects of potential sensitivity on the ability of southern elephant seals to use geomagnetic cues. References used to determine sensitivity values are provided. Magnetic Parameter Low Sensitivity High Sensitivity References Inclination 0.5° 0.02° Dennis et al., 2007 Phillips et al., 2002 Putman et al., 2014b Rodda, 1984 Schneider et al., 2023 Walker & Bitterman, 1989 Wynn et al., 2020, 2022 Total Intensity 200 nT 20 nT Dennis et al., 2007 Putman et al., 2014b Schneider et al., 2023 Walker & Bitterman, 1989 Declination 0.5° 0.1° Hart et al., 2013 Schneider et al., 2023 These threshold values represent the smallest change in each parameter that are assumed to be detectable under the low and high sensitivity scenarios. In this analysis, the previously calculated change in each of the three geomagnetic parameterâs values were divided into three categories: negative and positive values above the threshold level (either classified as the majority or minority direction as before), and values (either positive or negative) below the presumed threshold level, which were classified as âundetectableâ. These three categories were quantified for all return paths using both the low sensitivity scenario and the high sensitivity scenario for all three individual geomagnetic parameters (inclination, total intensity, and declination). Using the counts for these three categories and the total number of positional changes made along each return trip, the percentage of locations that fell into the majority (positive or negative detectable), minority (positive or negative detectable) and undetectable categories were 70 calculated, and results were compiled for all seals for both the low and high sensitivity threshold scenarios. A Friedman test for repeated measures was used to compare the three categories (majority, minority, undetectable) to assess the degree to which changes below the proposed detection levels affected the apparent use of geomagnetic cues. For cases where a significant difference was found, pairwise Wilcoxon signed-rank tests were used to identify which categories differed. I undertook a similar analysis using a combined inclination and total intensity signal. In this analysis, the same three categories (majority, minority, and undetectable) were determined from each sealâs return trip, with the majority pairing for each trip determined from the highest count of combined directions (negative or positive) of both inclination and total intensity and the minority a combination of all minority pairs with lower counts. Points along each return trip were classified as âundetectableâ only if both the change in inclination and the change in total intensity was less than the threshold. This was because I assumed that a seal could still successfully move according to a single detected parameter. From these counts, I calculated the percentage of locations falling into these categories and repeated this analysis under the high and low threshold scenarios. I again compiled data for all seal returns and used a Friedman test for repeated measures to compare categories, with additional pairwise Wilcoxon signed-rank tests to identify which categories differed. Results Lunar Cue Use A greater proportion of seals begin and end both their outbound and return segments when the illuminated fraction of the moon is close to either 0 or 1 (indicating greater movements during a new or full moon) (Figure 14). However, when accounting for the naturally-occurring unequal proportions of the lunar fraction, there was no significant difference between the observed and expected proportions for both the start and end of outbound and return segments (Chi-squared goodness of fit; start of outbound: Ï = 4.46, p=value = 0.35; end of outbound: Ï = 5.11, p-value = 0.28; start of return: Ï = 7.39, p-value = 0.12; end of return: Ï = 1.62, p-value = 0.81) (Figure 14). Thus, the greater proportion of seal movements occurring during these 71 illumination levels is likely a side effect of the slower rate of fractional change occurring during these periods, and not a preferential use of this fractional period. Figure 14. Lunar fraction proportion at the start and end of southern elephant seal migration segments. Grouped bar chart showing the proportion of seals starting and ending both their outbound and return trips during various lunar fractions. Horizontal black lines on each bar indicate the expected proportion of lunar fractions if migration points were randomly distributed across the lunar cycle. Observed proportions do not differ from expected proportions for any migration points, suggesting that seals do not preferentially start or end their migrations during any lunar fraction. Consistency in the start and end of trips in relation to lunar fraction was assessed between all combinations of both start and end points for both outbound and return segments. Results indicate that most seals do not time their migrations to start or stop during the same lunar fraction, regardless of what segments of the migration path are compared, with ~77% of seals initiating and/or ending segments of their migrations during different lunar fractions (Figure 15). Among those segment pairings that showed similar use of lunar fractions, most seals moved 72 during fractions that were close to 0 and 1, again likely because these fractional periods were the longest and not due to preferential use. Figure 15. Lunar fraction consistency between the start and end of southern elephant seal migration segments. Grouped bar chart assessing the number of seals whose beginnings and ends of migration segments occur during the same or different lunar fraction. Consistency was evaluated within the same lunar fraction categories defined in Figure 14. Most seals showed no consistency in lunar fraction when starting or ending their trips for all combinations of migration segments. Solar Cue Use Angular differences between directional bearing and solar azimuth at all points along seal return paths were not statistically different from a uniform distribution (Rayleigh test of uniformity, Z = 0.035, p-value = 0.43) (Figure 16a). A mean resultant length (r) of 0.04 indicated that angular differences between seal movement and sun position for all seals were widely spread around the circle and not clustered in the calculated mean direction (Figure 16a). Thus, movements of seals in relation to the sun were statistically random and did not follow any observed patterns in offset angle. 73 It is possible that individual seals show patterns in their movement in relation to the sun, but that these patterns are not consistent between seals, potentially resulting in the apparent random distribution when individual data is combined. Three additional circular plots depicted the angular differences for select individuals chosen from the dataset. These three seals were chosen randomly from a sub-selection of the ten seals with the largest number of return points to best represent individual patterns in movement over long distances. Similar to the circular plot for all seals, angular differences for all individuals were uniformly distributed around the circle, with low measures of mean resultant lengths and non-significant p-values (Rayleigh test of uniformity; b) Z = 0.014, p-value = 0.97; c) Z = 0.054, p-value = 0.63; d) Z = 0.022, p-value = 0.92) (Figure 16b-d). Inspection of circular plots constructed for all individual seals within the dataset also confirmed that selected seals were not unique occurrences. All seals with large sample sizes did show similar uniformity, and only seals with especially small sample sizes showed any indication of a non-uniform distribution (likely due to small sample size limiting the possible range of solar azimuth values examined). Together, these plots support the conclusion that the general pattern of randomness seen for all seals was also true for individual seals. 74 Figure 16. Angular difference between southern elephant seal bearing and corresponding solar azimuth. Circular plots showing the angular difference between the directional bearing of a) all southern elephant seals (n = 224) and the corresponding solar azimuth at all points along return tracks and bâd) three selected southern elephant seals from a) (plotted individually) and the corresponding solar azimuth at all points along that individualâs return track. An angular difference of 0° indicates that seals are moving directly towards the sun, while an angular difference of 180° indicates that seals are moving directly away from the sun. Mean angle of direction (a) and mean resultant lengths (r) are reported. Movements of seals in relation to the sun were statistically random and did not follow any observed patterns in offset angle. Changes in directional bearing were not significantly different based on solar altitude, with no significant difference in bearing changes occurring during sunrise or sunset compared to periods of day and night (Kruskal-Wallis test, ÏÂ² = 3.09, df = 3, p-value = 0.38) (Figure 17). This suggests that seals do not utilize solar information to preferentially adjust their movements at clearly defined periods of sunrise and sunset, instead making similar changes in their bearing across all solar altitude periods. a) b) c) d) 75 Figure 17. Change in bearing of southern elephant seal return paths binned by solar altitude. Boxplots showing the distribution of bearing changes that seals (n = 224) undertook during different solar altitudes, grouped into categories of sunrise, day, sunset, and night. Outliers ranging from 35° to 180° and representing 5.6% of the data were removed from the plot for ease of visualization, as most changes in bearing for all seals across all return paths were less than 35°. Distributions are similar, suggesting that seals do not utilize solar information to preferentially adjust their movements at clearly defined periods of sunrise and sunset, but instead make similar changes in their bearing across all solar altitude periods. Geomagnetic Cue Use The percentage of the return path that seals spent travelling in the majority direction was statistically greater than a theoretical 50% median for all geomagnetic parameters: inclination, total intensity, and declination (Wilcoxon signed-rank test; inclination: V = 21321, p-value < 0.001; total intensity: V = 21115, p-value < 0.001; declination: V = 21115, p-value < 0.001) (Figure 18). On average, 89% of return tracks followed the majority direction, while only 11% followed the minority direction across all three parameters (Figure 18). These findings shows that seal return tracks more closely conform to the expected pattern for gradient use rather than 76 for contour use, as return paths perfectly following a geomagnetic gradient are expected to follow the majority direction 100% of the time. When analyzing performance considering the use of both inclination and total intensity, the percentage of the return path that seals spent travelling in the majority direction was again statistically greater than a theoretical 50% median (Wilcoxon signed-rank test, V = 20796, p-value < 0.001) (Figure 19). On average, 86% of return tracks followed the majority direction pair, while only 14% followed the minority direction pairs (Figure 19), consistent with seal paths more closely following gradients instead of contours. The combination of both parameters performed slightly poorer than when inclination and total intensity were analyzed separately, and a larger variance and interquartile range for the combined cues suggests a wider spread in the data resulting in more inconsistency in following the majority direction (Figure 19). Figure 18. Testing gradient or contour use of geomagnetic parameters by returning southern elephant seals. Boxplots showing the percentage of seal return tracks (n = 207) following the majority and minority directions assessed through positive or negative changes in inclination, total intensity, and declination. Majority directions are significantly different from a 50% median, supporting that seal return tracks closely conform to the expected pattern for gradient use rather than for contour use for all three geomagnetic parameters. 77 Figure 19. Testing gradient or contour use of combined inclination and total intensity by returning southern elephant seals. Boxplot showing the percentage of seal return tracks (n = 207) following the majority direction pair and minority direction pairs assessed through positive or negative changes in both inclination and total intensity. The majority direction pair is significantly different from a 50% median, supporting that seal return tracks closely conform to the expected pattern for gradient use rather than for contour use when considering these parameters in combination. Geomagnetic Cue Sensitivity Re-analyzing seal movements based on changes in geomagnetic cues with the inclusion of low and high sensitivity thresholds indicated that, for all geomagnetic parameters, the assumed sensitivity of seals to these parameters greatly influenced the expected use of geomagnetic cues along return tracks (Figure 20; Figure 21; Figure 22). Considering a high sensitivity threshold for all geomagnetic parameters (0.02° inclination, 20 nT total intensity, 0.1° declination), the percentage of the return path that seals spent travelling in the majority direction was significantly larger than the minority direction (similar to the previous analysis without thresholds), and only a relatively small proportion of the return track encountered undetectable changes that were significantly smaller than both the majority and minority directions (Friedman test; inclination: ÏÂ² = 326.27, df = 2, p-value < 0.001; total intensity: ÏÂ² = 333.28, df = 2, p-value 78 < 0.001; declination: ÏÂ² = 304.04, df = 2, p-value < 0.001) (Figure 20; Figure 21; Figure 22). At these high sensitivity levels, total intensity performed best, with 83% of the return tracks following the majority direction and only 10% moving in undetectable directions (Figure 21), followed by inclination (80% majority direction, 13% undetectable) (Figure 20), while declination performed the poorest (69% majority direction, 28% undetectable) (Figure 22). Results were markedly worse when supposing a low sensitivity threshold across all individual geomagnetic parameters (0.5° inclination and declination, 200 nT total intensity). The percentage of the return path that seals spent travelling between location points with undetectable changes in geomagnetic information was significantly greater than both the majority and minority directional categories (inclination: ÏÂ² = 400.38, df = 2, p-value < 0.001; total intensity: ÏÂ² = 388.09, df = 2, p-value < 0.001; declination: ÏÂ² = 378.43, df = 2, p-value < 0.001) (Figure 20; Figure 21; Figure 22). On average, 97% of return tracks encountered undetectable changes across all three parameters, with only 2.8% of changes able to be followed as the majority direction (Figure 20; Figure 21; Figure 22). When considering the combined inclination and intensity signal under the high sensitivity threshold (0.02° inclination and 20 nT total intensity), the percentage of the return path that seals spent travelling in the majority paired direction was statistically higher than both the minority paired directions and undetectable directions (ÏÂ² = 331.23, df = 2, p-value < 0.001) (Figure 23). On average, 85% of return tracks followed the majority direction, while only 6.5% of tracks moved in undetectable directions (Figure 23). Thus, under high sensitivity thresholds, the combined signal performed better than each parameter individually, suggesting that seals were still able to utilize geomagnetic cue information along most of their return track and that having two inputs of information decreased the amount of time they travelled in undetectable directions. Similar to when each parameter was considered separately, results were markedly worse when analyzing the combined use of inclination and total intensity under the low sensitivity threshold (0.5° inclination and 200 nT total intensity). The percentage of the return path that seals spent travelling between location points with undetectable changes in both inclination and total intensity was significantly greater than both the majority and minority directional categories (ÏÂ² = 388.09, df = 2, p-value < 0.001) (Figure 23). On average, 95% of return tracks encountered undetectable changes, with only 4.7% of changes able to be followed as the majority direction 79 (Figure 23). Thus, with most of the return track being classified as undetectable, there is very little evidence to support that seals would be able to reliably use these geomagnetic cues while possessing low levels of sensitivity, even if cues are continually present. Figure 20. Sensitivity thresholds testing the detection of inclination by returning southern elephant seals. Boxplots showing the percentage of seal return tracks (n = 207) following the majority direction, the minority direction, and undetectable directions based on changes in inclination under low sensitivity (0.5°) and high sensitivity (0.02°) threshold levels. At high sensitivity thresholds, the majority direction was followed significantly more than all other categories. However, at low sensitivity thresholds, undetectable changes were encountered significantly more than all other categories, suggesting that low sensitivity may impede the ability of seals to successfully use inclination as a cue for navigation. 80 Figure 21. Sensitivity thresholds testing the detection of total intensity by returning southern elephant seals. Boxplots showing the percentage of seal return tracks (n = 207) following the majority direction, the minority direction, and undetectable directions based on changes in total intensity under low sensitivity (200 nT) and high sensitivity (20 nT) threshold levels. At high sensitivity thresholds, the majority direction was followed significantly more than all other categories. However, at low sensitivity thresholds, undetectable changes were encountered significantly more than all other categories, suggesting that low sensitivity may impede the ability of seals to successfully use total intensity as a cue for navigation. 81 Figure 22. Sensitivity thresholds testing the detection of declination by returning southern elephant seals. Boxplots showing the percentage of seal return tracks (n = 207) following the majority direction, the minority direction, and undetectable directions based on changes in declination under low sensitivity (0.5°) and high sensitivity (0.1°) threshold levels. At high sensitivity thresholds, the majority direction was followed significantly more than all other categories. However, at low sensitivity thresholds, undetectable changes were encountered significantly more than all other categories, suggesting that low sensitivity may impede the ability of seals to successfully use inclination as a cue for navigation. 82 Figure 23. Sensitivity thresholds testing the detection of combined inclination and total intensity by returning southern elephant seals. Boxplots showing the percentage of seal return tracks (n = 207) following the majority direction pair, the minority direction pairs, and undetectable directions based on changes in both inclination and total intensity under low sensitivity (0.5° and 200 nT) and high sensitivity (0.02° and 20 nT) threshold levels. At high sensitivity thresholds, the majority direction pair was followed significantly more than all other categories. However, at low sensitivity thresholds, undetectable changes were encountered significantly more than all other categories, suggesting that low sensitivity may impede the ability of seals to successfully use both inclination and total intensity as a combined cue for navigation. Discussion The directed and precise movement patterns of southern elephant seals along their travel routes suggest that seals likely orient toward their goal using environmental cues for navigational guidance. To test which types of cues might provide this information, I developed predictions to investigate the relationship between specific environmental cues and southern elephant seal movements during long-distance migrations. Based on results from these predictions, it seems unlikely that lunar or solar information can independently explain seal movements along migratory routes, as seals do not move as expected if following these cues in the predicted manner. Seal movements do seem to follow what would be expected if using geomagnetic cues, suggesting that geomagnetic information might inform these movements and that this mechanism should be explored further. Sensitivity analyses indicate that seals must have high sensitivity to the geomagnetic cues present in the Southern Ocean to make them a relevant source of information that can be readily detected while navigating, as changes in these cues becomes largely undetectable at lower sensitivity levels. 83 Lunar Cue Use I predicted that if southern elephant seals use lunar illumination levels (lunar fraction) as a cue when timing their migratory travel, there should be clear patterns in when they move during different stages of their long-distance movements. I assumed that seals would rely on the brightest lunar illumination levels and start and/or stop their migratory movements more often during the full moon, as this would provide the most visible cue to assist with detection. Seals were shown to not display distinct patterns in these movements, starting or ending their trips seemingly at random during different lunar fractions. On average, only 23% of seals showed any consistency in the lunar fraction that they started or stopped at during one segment of the migratory journey, and of those, zero individuals showed similarity in the timing of their movements during all segments. Perhaps this lack of reliance on lunar illumination should not be surprising. Moonlight is 105 â 106 orders of magnitude dimmer than sunlight, so this cue is likely difficult to perceive for many animals (Ritter & Tessmar-Raible, 2024). Southern elephant seals are deep divers (up to 1000 kilometers), so their eyesight is largely optimized for low-light conditions when hunting prey underwater. However, like many marine animals, their eyesight is myopic and not well-suited for acute vision above the waterâs surface (Fuiman et al., 2021; Luschi et al., 1998). Cloudy or stormy weather common in the Southern Ocean adds further difficulty in detecting this cue consistently. My results are consistent with the suggestion that lunar information is largely unreliable as an independent cue and that other, more reliable cues likely assist with navigational timing. Solar Cue Use I predicted that if southern elephant seals use solar information as a cue when directing their migratory travel, there should be clear patterns in their movements in relation to the sun. However, seals did not move at a consistent offset angle to the sun or appear to reorient by referencing the sun at sunrise or sunset. Hence, there was a lack of evidence for use of solar cues by seals both as a population and as individuals. 84 Like lunar cues, the sun must also be visually perceived to be relied upon as a cue. In the winter months when seals are actively migrating, the sun is only visible for a few hours every day, and cloudy or stormy weather causes further difficulties in reliable detection. While polarized light might still be present under such conditions, it is not widely believed to be detected by mammals (Marshall & Cronin, 2011). Even across all migration routes and seasons, southern elephant seals travelled at night 58% of the time, providing little evidence for the usefulness of solar information as a continuously followed cue throughout migratory journeys. There is some evidence to suggest that birds can effectively use solar cues at high latitudes, as small longitudinal shifts can result in large perceptible changes in the sunâs position that can be more easily identified and integrated into navigational decisions than subtle changes occurring at lower latitudes (Ã kesson & Bianco, 2017; Hedenström, 2010). However, most evidence suggests that large changes in the sunâs position are difficult for animals to assess when navigating, and that at high latitudes, even minor deviations eastward or westward can cause difficulties due to the extent of these changes (Kappeler, 2021). For southern elephant seals navigating across thousands of kilometers, the vast changes in latitude and longitude result in especially large effects to solar position, greatly influencing the solar azimuth and the timing of solar events like sunrise and sunset. Polar latitudes also experience large changes in solar position across seasons. As solar information is thought to require processing via an internal clock to be used effectively, seals would need to be able to quickly and frequently shift this internal clock when travelling across time zones and between seasons. The complexity of this theoretical clock might further preclude seals from utilizing solar information, even if it were available. I also explicitly tested the use of solar cues at only sunrise and sunset, as these were periods of the day that seals might be able to use solar information to reorient their paths without necessarily needing an internal clock to interpret the sunâs position nor needing to constantly rely on solar cues. While the exact direction of sunrise and sunset varies seasonally, the general east to west movement might suffice to make generalized route corrections. However, as calculated bearing changes at sunrise and sunset were statistically similar to all other periods, this further suggested that use of solar information was not consistent with southern elephant seal movements. 85 Finally, changes in bearing were similar during the day and night. This suggests that celestial information generally might not be used as directional cues by seals, as these cues are largely observed only during the day or night, but not both. Although it does not preclude the used of separate day and night celestial cues, it is more likely that seals utilize a single cue that can be used day and night and allows for consistency in movements at any time and location. Geomagnetic Cue Use I predicted that if southern elephant seals use geomagnetic parameters as a cue when directing their migratory travel, seal movements should either follow these parameters across a gradient or along a single stable contour. Results suggest that seal movements follow paths consistent with gradient use, as most seal return paths move in one majority direction with a consistent directional change in geomagnetic parameter. Seals movements tended to follow all three studied parameters (inclination, total intensity, and declination) similarly, with no one parameter showing more consistent gradient use. The literature suggests that most studied animals move in accordance to changes or cues derived from inclination or total intensity, not declination, although declination has not been tested as often (Azumaya et al., 2016; Lohmann et al., 2001; Lohmann et al., 2008a). Inclination and total intensity are highly correlated with one another, as the more vertical the field lines of inclination become, the stronger total intensity becomes. Declination is less correlated to both inclination and total intensity, and to utilize declination, animals need to detect the direction towards geographic north and calculate the difference from the direction of true north, requiring both geomagnetic field information plus celestial information (likely stars) (Ã kesson et al., 2001). Given my study provided no evidence of use of solar cues, declination would not be expected to be followed by southern elephant seals. In addition, declination can also be especially difficult to assess at the poles, where values change readily due to the secular variation of geographic north (Mouritsen, 2022). Therefore, the results from this study suggesting association of movements with declination might be because seal routes simply follow declination gradients unintentionally while relying on other geomagnetic gradients or some other cue. 86 When considering the use of inclination and total intensity in combination, results suggest that there is more variability in the distribution of seal movements when following these in combination than when following each separately. This proposed âbi-coordinateâ navigation is thought to work most effectively when the contours of the two parameters are perpendicular (forming a grid-like structure) (Ã kesson et al., 2014). However, in the area where southern elephant seals are navigating based on the tagging data, inclination and total intensity contour lines are largely parallel and highly correlated (Figure 13). Further, most of the seals in my study departed Kerguelen Island and Heard Island in a SE direction, and then later returned from the opposite direction to these islands (Chapter 2). Boström et al. (2012) determined that this oceanic plateau extending SE from Kerguelen Island to be a âglobal red zoneâ, defined as an area with small differences between inclination and total intensity, making it unfeasible to support geomagnetic bi-coordinate navigation. An additional red zone was identified for a section of ocean south of central Australia that overlapped with the paths of a few seals (Boström et al., 2012; Chapter 2). However, outside of these two red zones, most areas that elephant seals travelled in were âgreen zonesâ where use of bi-coordinate navigation is thought to be largely feasible (Boström et al., 2012; Chapter 2). Due to the large area covered by southern elephant seals when migrating, the impact of moving through these red zones might explain the greater variability in the combined results. However, travel through these red zones do not significantly impact the overall findings, resulting in most seals still following the majority direction when considering inclination and total intensity in combination. Geomagnetic Cue Sensitivity Seal movement patterns appear to be consistent with use of geomagnetic cues when navigating, but this assessment does not explicitly test the ability of seals to perceive these cues, nor does it test their sensitivity to changes within this cue. While analysis of tagging data is not capable of directly answering these questions, I constructed sensitivity thresholds to establish proxies for sensitivity limits that seals would likely need to possess to detect the changes in geomagnetic cue information that occur along their recorded tracks. At low sensitivity levels, most geomagnetic changes were too small to be perceived, making geomagnetic information largely undetectable for all three parameters and therefore 87 useless as a reliable and consistent cue for navigation. Thus, a more acute ability is needed to make geomagnetic information relevant and usable. Southern elephant seals would be able to detect changes to the cue levels tested in the high sensitivity scenario for inclination and total intensity (around a 0.02° change in inclination and a 20 nT change in total intensity). Even under the high sensitivity scenario for declination (0.1° change) seals performed poorly, and likely would need to possess even higher sensitivity to navigate successfully using declination. The previous studies that informed the sensitivity thresholds in my analysis (Table 4) reported values at which animals responded to or aligned with magnetic cues. However, geomagnetic sensitivity has not been established definitively in any animal (Lohmann et al., 2024). None of the referenced experiments explicitly tested the full range of that animalâs sensitivity to geomagnetic stimuli, nor did every study report these values in the context of the animalâs environment. Thus, it remains unclear whether these values fall within the typical range of the tested animalâs capabilities or represent the extreme ends of their sensory spectrum. It is also unclear if these values reflect the abilities of the best-performing individuals instead of the typical performance assessed across the broader population. These sensitivity values were also not reported for any mammals, so it remains to be seen how plausible these values might be for southern elephant seals. Theoretically, animals should be well-adapted to the environments they inhabit and, if they rely on geomagnetic cues for navigation, should evolve sensory systems capable of detecting changes in geomagnetic information at levels relevant for those environments. This suggests that sensitivity to geomagnetic fields may vary between species depending on the evolutionary pressures of their environment. Therefore, it is crucial to explicitly test sensitivity thresholds when designing animal navigation experiments. Researchers should consider these assumed values when interpreting results or manipulating magnetic fields to ensure that experimental changes reflect ecologically realistic conditions for the species being studied to truly understand their navigational abilities. Conclusion Empirical analyses of tracking data indicate that southern elephant seal movements along long-distance migratory paths consistently follow geomagnetic gradients, suggesting that these 88 animals may use geomagnetic cues for navigation. It is also suggested that inclination and total intensity are the most likely used geomagnetic parameters and that it is reasonable that seals would use these parameters either independently or in combination when navigating. However, although geomagnetic navigation has been discussed as a potential cue used by these animals (Fuiman et al., 2021; Robinson, 2009), it has not yet been documented in any pinniped species. Sensitivity analyses suggest that if seals do indeed rely on geomagnetic cues, they must be highly sensitive to both inclination and total intensityâan ability that remains untested. Further research is needed to determine how and when geomagnetic information is utilized across migration routes, and what factors influence its effectiveness or viability as a navigational cue for this species. Future studies of southern elephant seal navigation should consider geomagnetic cue use and how it may support the remarkably straight and directed movements characteristic of their migratory paths. 89 Chapter 4: General Discussion Summary of Findings My study is the first to use satellite tagging data to characterize the movement patterns of migrating southern elephant seals within the framework of animal navigation (Chapter 2), and to test whether these movements are consistent with predictions based on the use of specific environmental cues for navigation (Chapter 3). I found that the long-distance migratory paths of sealsâspanning thousands of kilometers across the Southern Oceanâexhibited several defining characteristics. Migration routes were not consistent at the population level, as seals took different migratory paths from each other to reach their natal islands. Even individual seals did not repeat the same route across their two annual migrations, showing limited spatial overlap in the areas travelled. Time played an important role in these movements, with adult females synchronizing their arrivals at the islands. However, the factors driving synchronicity remain unclear, as neither departure timing nor travel speed fully explained how seals migrating from varying distances arrive together. An overarching feature of the sealsâ migration was that they returned to their islands with striking precision, following direct, efficient paths. This suggests that southern elephant seals possess a high degree of navigational accuracy from widely dispersed starting points, enabling successful returns across ages and life history stages. To explain these movements, I explored the potential use of three environmental cues: lunar, solar, and geomagnetic. Lunar and solar cues used independently are unlikely to explain migration paths, as seals did not move in ways consistent with their use. In contrast, seal movements were consistent with the use of geomagnetic cues, as individuals travelled along gradients of inclination, total intensity, and declination. Of these, inclination and total intensity appear the most likely. However, these results depend upon the relationship between geomagnetic sensitivity and the change in geomagnetic signals encountered in the Southern Ocean. 90 Strengths and Limitations Manipulation-based studies are a mainstay of animal navigation research and are often conducted in laboratory or controlled field settings. Such studies isolate and alter specific environmental cues to test behavioural reactions and identify the sensory systems or cognitive mechanisms that animals use to orient and navigate. While these experiments have greatly advanced understanding of animal navigation, they typically involve large sensory manipulations to elicit clear responses that are free from noise (Wynn & Liedvogel, 2023). This can include displacements at extreme distances (Lohmann et al., 2001; Putman et al., 2014a), or substantial compass rotations (Cochran et al., 2004). Such manipulations may make it difficult to discern whether the observed animalâs behaviour is simply a reaction to the task given to them or a true reflection of their navigational abilities. In contrast, the use of satellite tagging data offers a major strength by ensuring that studies are based in a context of biological realism, directly testing the navigational abilities of animals moving in their natural habitats. The value of this approach is that movements can be directly related to known information about cues that can be derived from the datasets, without the need for setting cue levels a priori. For example, sensitivity analyses in my study used documented changes in geomagnetic cues experienced by seals moving in the Southern Ocean and related this to a realistic understanding of what those changes might mean for the animal and how they might be interpretedâan important step toward understanding navigation in situ. Nonetheless, there are inherent limitations to what can be concluded from tagging data. Relating the track of an animal to environmental cues is not the same as directly demonstrating cue use. While correlation alone cannot confirm which cues animals use, such analyses can suggest likely navigational cues and provide evidence for driving further exploration. Although my study cannot definitively conclude that southern elephant seals use geomagnetic cues, nor that they solely rely on them, it does provide evidence that this is a worthwhile avenue of further inquiry, and places realistic bounds on the scope of potential environmental cues used in such studies. A principal limitation of this study is the high level of positional error associated with ARGOS tracking data. To address this, a state-space model was applied to regularize and improve location, followed by a hidden Markov model to classify behavioural states from the 91 fitted tracks. However, error was not propagated between these modelling stages, which means that uncertainty in position estimates from the SSM was not carried into the HMM. As a result, the tracks used for subsequent analysis may appear different than the actual movements undertaken by southern elephant seals (for example, straighter tracks than in reality). This discrepancy likely impacted the conclusions drawn regarding patterns of movement that might have been different had error been propagated throughout both models. Additionally, the use of a 6-hour time interval, while beneficial for maintaining structured outbound and return phases and for optimizing model performance, limited the ability to detect fine-scale movement complexity that might have revealed more nuanced navigational behaviour. Future studies would benefit from higher-resolution GPS data to validate these findings at shorter timesteps. Implementing multiple imputation or joint modelling approaches would also assist in accounting for error propagation to capture important deviation, thereby improving the realism and interpretability of resulting tracks. Despite error propagation, a notable strength of my study was the large sample size of the dataset, involving hundreds of tagged sealsâan often-uncommon characteristic of marine mammal tagging studies due to the logistical challenges of locating and handling these animals. This robust sample allowed for greater insights regarding seal movements, as statistically meaningful conclusions could be drawn for the population, reducing the risk of generalizing patterns from the movements of just a few individuals. However, it is important to acknowledge that tagging efforts were not random. The dataset I analyzed is disproportionately composed of juvenile males and adult females, and the subadult age group consisted entirely of males. Although these groups together provided ample data for comparison, the skewed sex and age distributions may have influenced the results. Given the pronounced sexual dimorphism in this species and the differences in foraging strategies and life history goals between males and femalesâincluding age at sexual maturityâit is plausible that navigational abilities develop or are used differently across sexes. The influence of this on navigational performance warrants further investigation that might require further sampling of underrepresented groups. 92 Future Directions My research has shown that southern elephant seals are capable of traversing thousands of kilometers of open ocean with both efficiency and precision to reach their island destinations. It is therefore reasonable to conclude that these seals are skilled navigators, likely using environmental cues available throughout the Southern Ocean to achieve this. Analysis suggests that one such cue may be geomagnetic information, and that seals may follow geomagnetic gradients along their migration routes. Based on these, the use of geomagnetic cues and their role in southern elephant seal navigation warrants further investigation. A crucial step toward strengthening the evidence for this correlation is to determine whether gradient-following occurs by chance or is intentional as a navigational strategy. My analysis considered overall movements along these gradients, but did not examine properties of this gradient at finer spatial scales. In theory, following the steepest part of a geomagnetic gradient would be most beneficial, as these areas provide the strongest signal contrast, potentially enhancing navigational guidanceâparticularly in regions where bi-coordinate navigation is hindered and animals must rely more heavily on a single cue that changes slowly. Re-assessing migration paths with a focus on the steepness of the gradient or the presence of local magnetic anomalies could help determine whether seals select routes to coincide with these features. For example, if animals are found to deviate from the most direct path to follow a steeper geomagnetic gradientâeven at the expense of energetic efficiency or optimal return timingâthis could provide compelling evidence for intentional use of geomagnetic cues. Over time, the Earthâs magnetic field undergoes secular variation, where local magnetic values drift unpredictably as geographic north shifts. This presents a challenge for long-lived species relying on geomagnetic information (Ã kesson et al., 2001; Putman, 2022). Studies on seabirds and sea turtles have shown that these species shift their nesting locations in response to changes in the geomagnetic field (Brothers & Lohmann, 2015, 2018; Freas & Cheng, 2022; Wynn et al., 2020), suggesting not only that they use the geomagnetic field for navigation but that they may imprint on the unique magnetic signature of their natal site. As the geomagnetic field shifts over time, these animals may follow that shifting signature as a navigational reference. 93 Whether southern elephant seals exhibit similar adjustments in response to geomagnetic drift remains unclear, but they are long-lived species that experience changing signatures at their natal beaches over the course of their lives. It would be valuable to explore whether individuals adjust their breeding positions across years in response to this drift to indicate if previously experienced geomagnetic information can act as a navigational reference. While my study examined island-scale goal finding, it did not assess which specific breeding sites individuals returned to, primarily due to positional uncertainty in tagging data at these finer spatial scales. Female southern elephant seals are known to prefer sandy beaches for breedingâavoiding vegetated hills or rocky terrainâdue to its thermoregulatory capacity (Campagna & Lewis, 1992). This may constrain the extent to which seals can shift breeding locations, but nevertheless, with additional fine-scale data or site-specific sources, datasets like this that span decades could be used to answer these questions. Future research should also examine the impact of sensitivity thresholds on geomagnetic cue use. It is notable that navigational studies have not explicitly tested these sensory ranges in any species, leaving a significant gap in the field. If animals cannot detect the levels of geomagnetic changes occurring in their environment, geomagnetic cues cannot be considered relevant for navigation and should not be investigated further. Updating and refining estimates of sensory thresholds is critical and would complement studies such as mine, which use tagging data to assess movement in natural habitats. In my analysis, the assumed sensitivity thresholds suggested that southern elephant seals must be highly sensitive to geomagnetic cues for these cues to be usable. Under this threshold, the number of undetectable changes in locations along return tracks was statistically lower when both inclination and total intensity were used together (6.5%) compared to when only inclination was used (13%). The biological significance of this difference remains open to interpretation. For example, assuming an average return track length of 1,343 kilometers (Chapter 2), this equates to approximately 87 kilometers of the track being âundetectableâ when both cues are used, versus 175 kilometers when only inclination is used. Whether this 88-kilometer difference impacts navigational success is unclear, but it could help to determine if the added complexity of using multiple cues is justified by the potential benefit of improved cue detection. 94 Sensitivity must also be measured in reference to time to assess if animals can detect cue differences over biologically relevant timesteps. The resolution of the AGROS tracking data used in my study was spaced at 6-hour intervals due to the application of the hidden Markov model to classify travelling behaviour. When a navigating seal encounters a region of undetectable geomagnetic change between two points spaced 6 hours apart, it raises the question: is a 6-hour loss of geomagnetic detection detrimental to the sealâs navigation? How long can a seal travel without detecting changes in geomagnetic cues before performance declines or they become disoriented? Answering such questions is key to assessing the biological relevance of these cues. As discussed in Chapter 2, different navigational cues with varying levels of spatial accuracy are thought to be employed by navigating animals across different stages of their migration (Bingman & Cheng, 2005). Within this framework, geomagnetic cues are likely most useful at far distancesâhundreds to thousands of kilometers away from the goalâwhile other cues such as olfaction and the use of visual landmarks, may be used as the animal nears its destination. Some evidence suggests that even when geomagnetic cues are noisy or have relatively low-resolution, animals can still use them to support successful navigation or supplement them with other cues (Bingman & Cheng, 2005; Johnsen et al., 2020). Thus, identifying the specific locations where geomagnetic cues become undetectable is important, as a lack of detection near to the goal may be less problematic if the animal can switch to a more detectable cue; a scenario that might not be possible at greater distances. It is not known how flexible animals are in switching between cues, or what environmental or internal factors trigger such shifts. In the context of tagging studies that incorporate environmental cue data, mapping where cues become undetectable along migratory routes may offer valuable insights into when and where animals rely on particular cues, or when they may be at a navigational disadvantage due to cue absence. Changes in path trajectories or variations to movement patterns at certain regions could also be indicative of transition zones where cue switching occurs as animals switch from a weaker cue to a stronger cue. 95 Importance of Work This is the first study to quantitatively assess movement patterns to define navigational abilities in southern elephant seals, and to evaluate potential environmental cues used during navigation using satellite tag data. It provides evidence for the navigational abilities of pinnipeds, a taxon that has been largely data deficient in the field of animal navigation. My research also highlights the value of tagging data for species that cannot be studied using traditional methods, enabling biologically relevant correlations between movement patterns and cue use. Finally, it identifies promising directions for future research, as well as important considerations for the management and conservation of navigating species. 96 References Able, K. P. (1977). The orientation of passerine nocturnal migrants following offshore drift. The Auk, 94(2), 320â330. https://doi.org/10.1093/auk/94.2.320 Able, K. P. (1995). Orientation and navigation: A perspective on fifty years of research. The Condor, 97(2), 592â604. https://doi.org/10.2307/1369049 Abrahms, B., Hazen, E. L., Bograd, S. J., Brashares, J. S., Robinson, P. W., Scales, K. L., Crocker, D. E., & Costa, D. P. (2018). Climate mediates the success of migration strategies in a marine predator. Ecology Letters, 21(1), 63â71. https://doi.org/10.1111/ele.12871 Abrahms, B., Hazen, E. L., Aikens, E. O., Savoca, M. S., Goldbogen, J. A., Bograd, S. J., Jacox, M. G., Irvine, L. M., Palacios, D. M., & Mate, B. R. (2019). Memory and resource tracking drive blue whale migrations. Proceedings of the National Academy of Sciences, 116(12), 5582â5587. https://doi.org/10.1073/pnas.1819031116 Abrahms, B., Aikens, E. O., Armstrong, J. B., Deacy, W. W., Kauffman, M. J., & Merkle, J. A. (2021). Emerging perspectives on resource tracking and animal movement ecology. Trends in Ecology & Evolution, 36(4), 308â320. https://doi.org/10.1016/j.tree.2020.10.018 Ã kesson, S., Luschi, P., Broderick, A. C., Glen, F., Godley, B. J., Papi, F., & Hays, G. C. (2001). Oceanic long-distance navigation: Do experienced migrants use the Earthâs magnetic field? Journal of Navigation, 54(3), 419â427. https://doi.org/10.1017/S0373463301001473 97 Ã kesson, S., Broderick, A. C., Glen, F., Godley, B. J., Luschi, P., Papi, F., & Hays, G. C. (2003). Navigation by green turtles: Which strategy do displaced adults use to find Ascension Island? Oikos, 103(2), 363â372. https://doi.org/10.1034/j.1600-0706.2003.12207.x Ã kesson, S., Boström, J., Liedvogel, M., & Muheim, R. (2014). Animal navigation. In L.-A. Hansson & S. Ã kesson (Eds.), Animal movement across scales (pp. 151â178). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199677184.003.0009 Ã kesson, S., & Bianco, G. (2017). Route simulations, compass mechanisms and long-distance migration flights in birds. Journal of Comparative Physiology A, 203(6â7), 475â490. https://doi.org/10.1007/s00359-017-1171-y Alerstam, T., Bäckman, J., Strandberg, R., Gudmundsson, G. A., Hedenström, A., Henningsson, S. S., Karlsson, H., & Rosén, M. (2008). Great-circle migration of Arctic passerines. The Auk, 125(4), 831â838. https://doi.org/10.1525/auk.2008.07142 Allegue, H., Guinet, C., Patrick, S. C., Hindell, M. A., McMahon, C. R., & Réale, D. (2022). Sex, body size, and boldness shape the seasonal foraging habitat selection in southern elephant seals. Ecology and Evolution, 12(1), e8457. https://doi.org/10.1002/ece3.8457 Allegue, H., Réale, D., Picard, B., & Guinet, C. (2023). Track and dive-based movement metrics do not predict the number of prey encountered by a marine predator. Movement Ecology, 11(1), 3. https://doi.org/10.1186/s40462-022-00361-2 Arce, F., Hindell, M. A., McMahon, C. R., Wotherspoon, S. J., Guinet, C., Harcourt, R. G., & Bestley, S. (2022). Elephant seal foraging success is enhanced in Antarctic coastal polynyas. Proceedings of the Royal Society B: Biological Sciences, 289(1967), 20212452. https://doi.org/10.1098/rspb.2021.2452 98 Avens, L., & Lohmann, K. J. (2004). Navigation and seasonal migratory orientation in juvenile sea turtles. Journal of Experimental Biology, 207(11), 1771â1778. https://doi.org/10.1242/jeb.00946 Azumaya, T., Sato, S., Urawa, S., & Nagasawa, T. (2016). Potential role of the magnetic field on homing in chum salmon (Oncorhynchus keta) tracked from the open sea to coastal Japan. North Pacific Anadromous Fish Commission Bulletin, 6(1), 235â241. https://doi.org/10.23849/npafcb6/235.241 Baker, R. R. (1987). Human navigation and magnetoreception: The Manchester experiments do replicate. Animal Behaviour, 35(3), 691â704. https://doi.org/10.1016/S0003-3472(87)80105-7 Beltran, R. S., Yuen, A. L., Condit, R., Robinson, P. W., Czapanskiy, M. F., Crocker, D. E., & Costa, D. P. (2022b). Elephant seals time their long-distance migrations using a map sense. Current Biology, 32(4), R156âR157. https://doi.org/10.1016/j.cub.2022.01.031 Benhamou, S. (2004). How to reliably estimate the tortuosity of an animalâs path: Straightness, sinuosity, or fractal dimension? Journal of Theoretical Biology, 229(2), 209â220. https://doi.org/10.1016/j.jtbi.2004.03.016 Berg, A. A., Askew, M., Seersholm, F. V., Verry, A. J. F., Hoelzel, A. R., Welch, A., Greig, K., Walter, R., Knapp, M., Barlow, A., Paijmans, J. L. A., Waters, J. M., Bunce, M., McDonald, K., OâConnor, S., Hall, B., Koch, P. L., Baroni, C., Salvatore, M. C., â¦ De Bruyn, M. (2025). Postglacial recolonization of the Southern Ocean by elephant seals occurred from multiple glacial refugia. Global Change Biology, 31(3), e70101. https://doi.org/10.1111/gcb.70101 Berkes, F. (2018). Sacred ecology (Fourth Edition). Routledge. 99 Bestley, S., Jonsen, I. D., Hindell, M. A., Harcourt, R. G., & Gales, N. J. (2015). Taking animal tracking to new depths: Synthesizing horizontalâvertical movement relationships for four marine predators. Ecology, 96(2), 417â427. https://doi.org/10.1890/14-0469.1 Bett, N. N., & Hinch, S. G. (2016). Olfactory navigation during spawning migrations: A review and introduction of the Hierarchical Navigation Hypothesis. Biological Reviews, 91(3), 728â759. https://doi.org/10.1111/brv.12191 Bianco, G., Ilieva, M., Veibäck, C., Ãfjäll, K., Gadomska, A., Hendeby, G., Felsberg, M., Gustafsson, F., & Ã kesson, S. (2016). Emlen funnel experiments revisited: Methods update for studying compass orientation in songbirds. Ecology and Evolution, 6(19), 6930â6942. https://doi.org/10.1002/ece3.2383 Biegler, R. (2000). Possible uses of path integration in animal navigation. Animal Learning & Behavior, 28(3), 257â277. https://doi.org/10.3758/BF03200260 Bingman, V. P., & Cheng, K. (2005). Mechanisms of animal global navigation: Comparative perspectives and enduring challenges. Ethology Ecology & Evolution, 17(4), 295â318. https://doi.org/10.1080/08927014.2005.9522584 Biro, D., Guilford, T., DellâOmo, G., & Lipp, H.-P. (2002). How the viewing of familiar landscapes prior to release allows pigeons to home faster: Evidence from GPS tracking. The Journal of Experimental Biology, 205, 3833â3844. https://doi.org/10.1242/jeb.205.24.3833 Block, B. A., Jonsen, I. D., Jorgensen, S. J., Winship, A. J., Shaffer, S. A., Bograd, S. J., Hazen, E. L., Foley, D. G., Breed, G. A., Harrison, A.-L., Ganong, J. E., Swithenbank, A., Castleton, M., Dewar, H., Mate, B. R., Shillinger, G. L., Schaefer, K. M., Benson, S. R., 100 Weise, M. J., â¦ Costa, D. P. (2011). Tracking apex marine predator movements in a dynamic ocean. Nature, 475(7354), 86â90. https://doi.org/10.1038/nature10082 Boles, L. C., & Lohmann, K. J. (2003). True navigation and magnetic maps in spiny lobsters. Nature, 421(6918), 60â63. https://doi.org/10.1038/nature01226 Bonadonna, F., & Gagliardo, A. (2021). Not only pigeons: Avian olfactory navigation studied by satellite telemetry. Ethology Ecology & Evolution, 33(3), 273â289. https://doi.org/10.1080/03949370.2021.1871967 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(1), 3â15. https://doi.org/10.1017/S095410200000002X Boström, J. E., Ã kesson, S., & Alerstam, T. (2012). Where on earth can animals use a geomagnetic biâcoordinate map for navigation? Ecography, 35(11), 1039â1047. https://doi.org/10.1111/j.1600-0587.2012.07507.x Boyd, I. L. (2004). Migration of marine mammals. In D. Werner (Ed.), Biological resources and migration (pp. 203â210). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-06083-4_20 Bradbury, I. R., Lehnert, S. J., Messmer, A., Duffy, S. J., Verspoor, E., Kess, T., Gilbey, J., Wennevik, V., Robertson, M., Chaput, G., Sheehan, T., Bentzen, P., Dempson, J. B., & Reddin, D. (2021). Range-wide genetic assignment confirms long-distance oceanic migration in Atlantic salmon over half a century. ICES Journal of Marine Science, 78(4), 1434â1443. https://doi.org/10.1093/icesjms/fsaa152 Bradshaw, C. J. A., Hindell, M. A., Sumner, M. D., & Michael, K. J. (2004). Loyalty pays: Potential life history consequences of fidelity to marine foraging regions by southern 101 elephant seals. Animal Behaviour, 68(6), 1349â1360. https://doi.org/10.1016/j.anbehav.2003.12.013 Brillinger, D. R., & Stewart, B. S. (1998). Elephantâseal movements: Modelling migration. Canadian Journal of Statistics, 26(3), 431â443. https://doi.org/10.2307/3315767 Brothers, J. R., & Lohmann, K. J. (2015). Evidence for geomagnetic imprinting and magnetic navigation in the natal homing of sea turtles. Current Biology, 25(3), 392â396. https://doi.org/10.1016/j.cub.2014.12.035 Brothers, J. R., & Lohmann, K. J. (2018). Evidence that magnetic navigation and geomagnetic imprinting shape spatial genetic variation in sea turtles. Current Biology, 28(8), 1325-1329.e2. https://doi.org/10.1016/j.cub.2018.03.022 Cain, S. D., Boles, L. C., Wang, J. H., & Lohmann, K. J. (2005). Magnetic orientation and navigation in marine turtles, lobsters, and molluscs: Concepts and conundrums. Integrative and Comparative Biology, 45(3), 539â546. https://doi.org/10.1093/icb/45.3.539 Campagna, C., & Lewis, M. (1992). Growth and distribution of a southern elephant seal colony. Marine Mammal Science, 8(4), 387â396. https://doi.org/10.1111/j.1748-7692.1992.tb00053.x Campagna, C., Lewis, M., & Baldi, R. (1993). Breeding biology of southern elephant seals in Patagonia. Marine Mammal Science, 9(1), 34â47. https://doi.org/10.1111/j.1748-7692.1993.tb00424.x CBC. (2024, April 17). âCelebrityâ seal back on Victoria-area beach after 4th relocation. CBC News. https://www.cbc.ca/news/canada/british-columbia/emerson-elephant-seal-greater-victoria- 102 1.7175946#:~:text=Fishery%20officials%20say%20they're,west%20coast%20of%20Vancouver%20Island. Cerritelli, G., Bianco, G., Santini, G., Broderick, A. C., Godley, B. J., Hays, G. C., Luschi, P., & Ã kesson, S. (2019). Assessing reliance on vector navigation in the long-distance oceanic migrations of green sea turtles. Behavioral Ecology, 30(1), 68â79. https://doi.org/10.1093/beheco/ary166 Cherel, Y., Ducatez, S., Fontaine, C., Richard, P., & Guinet, C. (2008). Stable isotopes reveal the trophic position and mesopelagic fish diet of female southern elephant seals breeding on the Kerguelen Islands. Marine Ecology Progress Series, 370, 239â247. https://doi.org/10.3354/meps07673 Chua, M., Ho, S. Y. W., McMahon, C. R., Jonsen, I. D., & De Bruyn, M. (2022). Movements of southern elephant seals (Mirounga leonina) from Davis Base, Antarctica: Combining population genetics and tracking data. Polar Biology, 45(7), 1163â1174. https://doi.org/10.1007/s00300-022-03058-9 Chung, H., Lee, J., & Lee, W. Y. (2021). A review: Marine bio-logging of animal behaviour and ocean environments. Ocean Science Journal, 56(2), 117â131. https://doi.org/10.1007/s12601-021-00015-1 Cochran, W. W., Mouritsen, H., & Wikelski, M. (2004). Migrating songbirds recalibrate their magnetic compass daily from twilight cues. Science, 304(5669), 405â408. https://doi.org/10.1126/science.1095844 Condit, R., Beltran, R. S., Robinson, P. W., Crocker, D. E., & Costa, D. P. (2022). Birth timing after the long feeding migration in northern elephant seals. Marine Mammal Science, 38(3), 931â940. https://doi.org/10.1111/mms.12896 103 Constable, A. J., MelbourneâThomas, J., Corney, S. P., Arrigo, K. R., Barbraud, C., Barnes, D. K. A., Bindoff, N. L., Boyd, P. W., Brandt, A., Costa, D. P., Davidson, A. T., Ducklow, H. W., Emmerson, L., Fukuchi, M., Gutt, J., Hindell, M. A., Hofmann, E. E., Hosie, G. W., Iida, T., â¦ Ziegler, P. (2014). Climate change and Southern Ocean ecosystems I: How changes in physical habitats directly affect marine biota. Global Change Biology, 20(10), 3004â3025. https://doi.org/10.1111/gcb.12623 Costa, D. P., Robinson, P. W., Arnould, J. P. Y., Harrison, A.-L., Simmons, S. E., Hassrick, J. L., Hoskins, A. J., Kirkman, S. P., Oosthuizen, H., Villegas-Amtmann, S., & Crocker, D. E. (2010). Accuracy of ARGOS locations of pinnipeds at-sea estimated using fastloc GPS. PLoS ONE, 5(1), e8677. https://doi.org/10.1371/journal.pone.0008677 Cotté, C., dâOvidio, F., Dragon, A.-C., Guinet, C., & Lévy, M. (2015). Flexible preference of southern elephant seals for distinct mesoscale features within the Antarctic Circumpolar Current. Progress in Oceanography, 131, 46â58. https://doi.org/10.1016/j.pocean.2014.11.011 Cox, S. L., Orgeret, F., Gesta, M., Rodde, C., Heizer, I., Weimerskirch, H., & Guinet, C. (2018). Processing of acceleration and dive data onâboard satellite relay tags to investigate diving and foraging behaviour in freeâranging marine predators. Methods in Ecology and Evolution, 9(1), 64â77. https://doi.org/10.1111/2041-210X.12845 Cox, S. L., Authier, M., Orgeret, F., Weimerskirch, H., & Guinet, C. (2020). High mortality rates in a juvenile freeâranging marine predator and links to dive and forage ability. Ecology and Evolution, 10(1), 410â430. https://doi.org/10.1002/ece3.5905 Cresci, A., Paris, C. B., Durif, C. M. F., Shema, S., Bjelland, R. M., Skiftesvik, A. B., & Browman, H. I. (2017). Glass eels (Anguilla anguilla) have a magnetic compass linked to 104 the tidal cycle. Science Advances, 3(6), e1602007. https://doi.org/10.1126/sciadv.1602007 Crocker, D. E., Williams, J. D., Costa, D. P., & Le Boeuf, B. J. (2001). Maternal traits and reproductive effort in northern elephant seals. Ecology, 82(12), 3541â3555. https://doi.org/10.1890/0012-9658(2001)082[3541:MTAREI]2.0.CO;2 Davis, R. W., Fuiman, L. A., Williams, T. M., & Le Boeuf, B. J. (2001). Three-dimensional movements and swimming activity of a northern elephant seal. Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology, 129(4), 759â770. https://doi.org/10.1016/S1095-6433(01)00345-2 de Kock, L., Oosthuizen, W. C., Beltran, R. S., Bester, M. N., & de Bruyn, P. J. N. (2021). Determinants of moult haulout phenology and duration in southern elephant seals. Scientific Reports, 11(1), 13331. https://doi.org/10.1038/s41598-021-92635-9 DellâAriccia, G., DellâOmo, G., Wolfer, D. P., & Lipp, H.-P. (2008). Flock flying improves pigeonsâ homing: GPS track analysis of individual flyers versus small groups. Animal Behaviour, 76(4), 1165â1172. https://doi.org/10.1016/j.anbehav.2008.05.022 Dennis, T. E., Rayner, M. J., & Walker, M. M. (2007). Evidence that pigeons orient to geomagnetic intensity during homing. Proceedings of the Royal Society B: Biological Sciences, 274(1614), 1153â1158. https://doi.org/10.1098/rspb.2007.3768 Dingle, H., & Drake, V. A. (2007). What is migration? BioScience, 57(2), 113â121. https://doi.org/10.1641/B570206 Dreyer, D., Frost, B., Mouritsen, H., Günther, A., Green, K., Whitehouse, M., Johnsen, S., Heinze, S., & Warrant, E. (2018). The Earthâs magnetic field and visual landmarks steer 105 migratory flight behavior in the nocturnal Australian bogong moth. Current Biology, 28(13), 2160-2166.e5. https://doi.org/10.1016/j.cub.2018.05.030 Egerton, F. N. (2002). A history of the ecological sciences, part 6: Arabic language science: Origins and zoological writings. Bulletin of the Ecological Society of America, 83(2), 142â146. Egevang, C., Stenhouse, I. J., Phillips, R. A., Petersen, A., Fox, J. W., & Silk, J. R. D. (2010). Tracking of Arctic terns Sterna paradisaea reveals longest animal migration. Proceedings of the National Academy of Sciences, 107(5), 2078â2081. https://doi.org/10.1073/pnas.0909493107 Emlen, S. T., & Emlen, J. T. (1966). A technique for recording migratory orientation of captive birds. The Auk, 83(3), 361â367. https://doi.org/10.2307/4083048 Erbe, C., Dunlop, R., & Dolman, S. (2018). Effects of anthropogenic noise on animals (Vol. 66). Springer New York. https://doi.org/10.1007/978-1-4939-8574-6 Erni, B., Liechti, F., Underhill, L. G., & Bruderer, B. (2002). Wind and rain govern the intensity of nocturnal bird migration in central EuropeâA log-linear regression analysis. https://doi.org/10.1093/beheco/ari046 Etienne, A. S., & Jeffery, K. J. (2004). Path integration in mammals. Hippocampus, 14(2), 180â192. https://doi.org/10.1002/hipo.10173 Fabiani, A., Galimberti, F., Sanvito, S., & Hoelzel, A. R. (2006). Relatedness and site fidelity at the southern elephant seal, Mirounga leonina, breeding colony in the Falkland Islands. Animal Behaviour, 72(3), 617â626. https://doi.org/10.1016/j.anbehav.2005.11.024 Fagan, W. F., Lewis, M. A., AugerâMéthé, M., Avgar, T., Benhamou, S., Breed, G., LaDage, L., Schlägel, U. E., Tang, W., Papastamatiou, Y. P., Forester, J., & Mueller, T. (2013). 106 Spatial memory and animal movement. Ecology Letters, 16(10), 1316â1329. https://doi.org/10.1111/ele.12165 Fernandez-Velasco, P., & Spiers, H. J. (2024). Wayfinding across ocean and tundra: What traditional cultures teach us about navigation. Trends in Cognitive Sciences, 28(1), 56â71. https://doi.org/10.1016/j.tics.2023.09.004 Field, I. C., McMahon, C. R., Burton, H. R., Bradshaw, C. J. A., & Harrinigton, J. (2002). Effects of age, size and condition of elephant seals ( Mirounga leonina ) on their intravenous anaesthesia with tiletamine and zolazepam. Veterinary Record, 151(8), 235â240. https://doi.org/10.1136/vr.151.8.235 Field, I. C., Harcourt, R. G., Boehme, L., Bruyn, P. J. N. de, Charrassin, J.-B., McMahon, C. R., Bester, M. N., Fedak, M. A., & Hindell, M. A. (2012). Refining instrument attachment on phocid seals. Marine Mammal Science, 28(3), E325âE332. https://doi.org/10.1111/j.1748-7692.2011.00519.x Flack, A., Pettit, B., Freeman, R., Guilford, T., & Biro, D. (2012). What are leaders made of? The role of individual experience in determining leaderâfollower relations in homing pigeons. Animal Behaviour, 83(3), 703â709. https://doi.org/10.1016/j.anbehav.2011.12.018 Foo, D., McMahon, C. R., Hindell, M. A., Fedak, M., Biuw, M., McConnell, B., & Raymond, B. (2023). Swimming with the current improves juvenile survival in southern elephant seals. https://doi.org/10.1101/2023.11.05.565668 Freas, C. A., & Cheng, K. (2022). The basis of navigation across species. Annual Review of Psychology, 73(1), 217â241. https://doi.org/10.1146/annurev-psych-020821-111311 107 Frierson, W. (2021). wmm: World Magnetic Model [Computer software]. https://CRAN.R-project.org/package=wmm Frisch, K. V. (1973). Decoding the language of the bee. Science, 185(4152), 663â668. Fuiman, L. A., Williams, T. M., & Davis, R. W. (2020). Homing tactics of Weddell seals in the Antarctic fast-ice environment. Marine Biology, 167(8), 116. https://doi.org/10.1007/s00227-020-03730-w Fuiman, L. A., Williams, T. M., & Davis, R. W. (2021). On the straight and narrow: Directed movement by Weddell seals (Leptonychotes weddellii) during on-ice travel. Polar Biology, 44(3), 601â606. https://doi.org/10.1007/s00300-021-02811-w Gan, R. (2023). The long-term evolution of agriculture in China. In Helix Network Theory (pp. 289â345). Springer Nature Singapore. https://doi.org/10.1007/978-981-19-8803-5_6 Goforth, K. M., Lohmann, C. M. F., Gavin, A., Henning, R., Harvey, A., Hinton, T. L., Lim, D. S., & Lohmann, K. J. (2025). Learned magnetic map cues and two mechanisms of magnetoreception in turtles. Nature, 638(8052), 1015â1022. https://doi.org/10.1038/s41586-024-08554-y Gould, J. L. (2004). Animal navigation. Current Biology, 14(6), R221âR224. https://doi.org/10.1016/j.cub.2004.02.049 Gould, J. L. (2014). Animal navigation: A map for all seasons. Current Biology, 24(4), R153âR155. https://doi.org/10.1016/j.cub.2014.01.030 Granger, J., & Johnsen, S. (2022). Collective movement as a solution to noisy navigation and its vulnerability to population loss. Proceedings of the Royal Society B: Biological Sciences, 289(1987), 20221910. https://doi.org/10.1098/rspb.2022.1910 108 Greif, S., Borissov, I., Yovel, Y., & Holland, R. A. (2014). A functional role of the skyâs polarization pattern for orientation in the greater mouse-eared bat. Nature Communications, 5(1), 4488. https://doi.org/10.1038/ncomms5488 Harcourt, R., Sequeira, A. M. M., Zhang, X., Roquet, F., Komatsu, K., Heupel, M., McMahon, C., Whoriskey, F., Meekan, M., Carroll, G., Brodie, S., Simpfendorfer, C., Hindell, M., Jonsen, I., Costa, D. P., Block, B., Muelbert, M., Woodward, B., Weise, M., â¦ Fedak, M. A. (2019). Animal-borne telemetry: An integral component of the ocean observing toolkit. Frontiers in Marine Science, 6, 326. https://doi.org/10.3389/fmars.2019.00326 Hart, V., Nováková, P., Malkemper, E. P., Begall, S., Hanzal, V., Ježek, M., Kušta, T., NÄmcová, V., Adámková, J., Benediktová, K., Äervený, J., & Burda, H. (2013). Dogs are sensitive to small variations of the Earthâs magnetic field. Frontiers in Zoology, 10(1), 80. https://doi.org/10.1186/1742-9994-10-80 Hays, G. C., Hobson, V. J., Metcalfe, J. D., Righton, D., & Sims, D. W. (2006). Flexible foraging movements of leatherback turtles across the north Atlantic Ocean. Ecology, 87(10), 2647â2656. https://doi.org/10.1890/0012-9658(2006)87[2647:FFMOLT]2.0.CO;2 Hays, G. C., Ferreira, L. C., Sequeira, A. M. M., Meekan, M. G., Duarte, C. M., Bailey, H., Bailleul, F., Bowen, W. D., Caley, M. J., Costa, D. P., Eguíluz, V. M., Fossette, S., Friedlaender, A. S., Gales, N., Gleiss, A. C., Gunn, J., Harcourt, R., Hazen, E. L., Heithaus, M. R., â¦ Thums, M. (2016). Key questions in marine megafauna movement ecology. Trends in Ecology & Evolution, 31(6), 463â475. https://doi.org/10.1016/j.tree.2016.02.015 109 Hedenström, A. (2010). Extreme endurance migration: What is the limit to non-stop flight? PLoS Biology, 8(5), e1000362. https://doi.org/10.1371/journal.pbio.1000362 Heinze, S., & Warrant, E. (2016). Bogong moths. Current Biology, 26(7), R263âR265. https://doi.org/10.1016/j.cub.2015.12.022 Heinze, S., Narendra, A., & Cheung, A. (2018). Principles of insect path integration. Current Biology, 28(17), R1043âR1058. https://doi.org/10.1016/j.cub.2018.04.058 Hijmans, R. J. (2010). geosphere: Spherical trigonometry (p. 1.5-20) [Computer software]. https://CRAN.R-project.org/package=geosphere Hindell, M. A., & Burton, H. R. (1988). Seasonal haul-out patterns of the southern elephant seal (Mirounga leonina L.), at Macquarie Island. Journal of Mammalogy, 69(1), 81â88. https://doi.org/10.2307/1381750 Hindell, M. A., Burton, H. R., & Slip, D. J. (1991). Foraging areas of southern elephant seals, Mirounga leonina, as inferred from water temperature data. Marine and Freshwater Research, 42(2), 115. https://doi.org/10.1071/MF9910115 Hindell, M. A., & McMahon, C. R. (2000). Long distance movement of a southern elephant seal (Mirounga Leonina) from Macquarie Island to Peter 1 Ãy. Marine Mammal Science, 16(2), 504â507. https://doi.org/10.1111/j.1748-7692.2000.tb00944.x Hindell, M. A., McMahon, C. R., Bester, M. N., Boehme, L., Costa, D., Fedak, M. A., Guinet, C., HerraizâBorreguero, L., Harcourt, R. G., Huckstadt, L., Kovacs, K. M., Lydersen, C., McIntyre, T., Muelbert, M., Patterson, T., Roquet, F., Williams, G., & Charrassin, J. (2016). Circumpolar habitat use in the southern elephant seal: Implications for foraging success and population trajectories. Ecosphere, 7(5), e01213. https://doi.org/10.1002/ecs2.1213 110 Hindell, M. A., Reisinger, R. R., Ropert-Coudert, Y., Hückstädt, L. A., Trathan, P. N., Bornemann, H., Charrassin, J.-B., Chown, S. L., Costa, D. P., Danis, B., Lea, M.-A., Thompson, D., Torres, L. G., Van De Putte, A. P., Alderman, R., Andrews-Goff, V., Arthur, B., Ballard, G., Bengtson, J., â¦ Raymond, B. (2020). Tracking of marine predators to protect Southern Ocean ecosystems. Nature, 580(7801), 87â92. https://doi.org/10.1038/s41586-020-2126-y Hindell, M. A., McMahon, C. R., Jonsen, I., Harcourt, R., Arce, F., & Guinet, C. (2021). Interâ and intrasex habitat partitioning in the highly dimorphic southern elephant seal. Ecology and Evolution, 11(4), 1620â1633. https://doi.org/10.1002/ece3.7147 Hindell, M. A., McMahon, C. R., Guinet, C., Harcourt, R., Jonsen, I. D., Raymond, B., & Maschette, D. (2022). Assessing the potential for resource competition between the Kerguelen Plateau fisheries and southern elephant seals. Frontiers in Marine Science, 9, 1006120. https://doi.org/10.3389/fmars.2022.1006120 Horton, T. W., Holdaway, R. N., Zerbini, A. N., Hauser, N., Garrigue, C., Andriolo, A., & Clapham, P. J. (2011). Straight as an arrow: Humpback whales swim constant course tracks during long-distance migration. Biology Letters, 7(5), 674â679. https://doi.org/10.1098/rsbl.2011.0279 Horton, T. W., Hauser, N., Zerbini, A. N., Francis, M. P., Domeier, M. L., Andriolo, A., Costa, D. P., Robinson, P. W., Duffy, C. A. J., Nasby-Lucas, N., Holdaway, R. N., & Clapham, P. J. (2017). Route fidelity during marine megafauna migration. Frontiers in Marine Science, 4, 422. https://doi.org/10.3389/fmars.2017.00422 111 Horton, T. W., Zerbini, A. N., Andriolo, A., Danilewicz, D., & Sucunza, F. (2020). Multi-decadal humpback whale migratory route fidelity despite oceanographic and geomagnetic change. Frontiers in Marine Science, 7, 414. https://doi.org/10.3389/fmars.2020.00414 Hume, F., Pemberton, D., Gales, R., Brothers, N., & Greenwood, M. (2002). Trapping and relocating seals from salmonid fish farms in Tasmania, 1990-2000: Was it a success? Papers and Proceedings of the Royal Society of Tasmania, 1â6. https://doi.org/10.26749/rstpp.136.1 Irvine, L. M., Winsor, M. H., Follett, T. M., Mate, B. R., & Palacios, D. M. (2020). An at-sea assessment of Argos location accuracy for three species of large whales, and the effect of deep-diving behavior on location error. Animal Biotelemetry, 8(1), 20. https://doi.org/10.1186/s40317-020-00207-x Johnsen, S., Lohmann, K. J., & Warrant, Eric. J. (2020). Animal navigation: A noisy magnetic sense? Journal of Experimental Biology, 223(18), jeb164921. https://doi.org/10.1242/jeb.164921 Jonsen, I. D., Grecian, W. J., Phillips, L., Carroll, G., McMahon, C., Harcourt, R. G., Hindell, M. A., & Patterson, T. A. (2023). aniMotum, an R package for animal movement data: Rapid quality control, behavioural estimation and simulation. Methods in Ecology and Evolution, 14(3), 806â816. https://doi.org/10.1111/2041-210X.14060 Kappeler, P. M. (2021). Animal behaviour: An evolutionary perspective. Springer International Publishing. https://doi.org/10.1007/978-3-030-82879-0 Kirkman, S. P., Bester, M. N., Hofmeyr, G. J. G., Jonker, F. C., Pistorius, P. A., Owen, R., & Strydom, N. (2004). Variation in the timing of the breeding haulout of female southern 112 elephant seals at Marion Island. Australian Journal of Zoology, 52(4), 379. https://doi.org/10.1071/ZO03038 Kirschvink, J. L., Dizon, A. E., & Westphal, J. A. (1986). Evidence from strandings for geomagnetic sensitivity in cetaceans. Journal of Experimental Biology, 120(1), 1â24. https://doi.org/10.1242/jeb.120.1.1 Kishkinev, D., Packmor, F., Zechmeister, T., Winkler, H.-C., Chernetsov, N., Mouritsen, H., & Holland, R. A. (2021). Navigation by extrapolation of geomagnetic cues in a migratory songbird. Current Biology, 31(7), 1563-1569.e4. https://doi.org/10.1016/j.cub.2021.01.051 Kowalewsky, S., Dambach, M., Mauck, B., & Dehnhardt, G. (2006). High olfactory sensitivity for dimethyl sulphide in harbour seals. Biology Letters, 2(1), 106â109. https://doi.org/10.1098/rsbl.2005.0380 Kramer, G. (1953). Wird die Sonnenhöhe bei der Heim- findeorientierung verwertet? Journal Für Ornithologie, 94(2), 201â219. https://doi.org/10.1007/BF01922508 Labrousse, S., Vacquié-Garcia, J., Heerah, K., Guinet, C., Sallée, J.-B., Authier, M., Picard, B., Roquet, F., Bailleul, F., Hindell, M., & Charrassin, J.-B. (2015). Winter use of sea ice and ocean water mass habitat by southern elephant seals: The length and breadth of the mystery. Progress in Oceanography, 137, 52â68. https://doi.org/10.1016/j.pocean.2015.05.023 Le Boeuf, B. J., Crocker, D. E., Costa, D. P., Blackwell, S. B., Webb, P. M., & Houser, D. S. (2000). Foraging ecology of northern elephant seals. Ecological Monographs, 70(3), 353â382. https://doi.org/10.1890/0012-9615(2000)070[0353:FEONES]2.0.CO;2 113 Leclerc, M., Leblond, M., Le Corre, M., Dussault, C., & Côté, S. D. (2021). Determinants of migration trajectory and movement rate in a long-distance terrestrial mammal. Journal of Mammalogy, 102(5), 1342â1352. https://doi.org/10.1093/jmammal/gyab081 Lewis, D. (1971). âExpandingâ the target in indigenous navigation. The Journal of Pacific History, 6(1), 83â95. https://doi.org/10.1080/00223347108572184 Lewis, M. A., Fagan, W. F., Auger-Méthé, M., Frair, J., Fryxell, J. M., Gros, C., Gurarie, E., Healy, S. D., & Merkle, J. A. (2021). Learning and animal movement. Frontiers in Ecology and Evolution, 9. https://doi.org/10.3389/fevo.2021.681704 Lewis, M., Campagna, C., & Quintana, F. (1996). Site fidelity and dispersion of southern elephant seals from Patagonia. Marine Mammal Science, 12(1), 138â147. https://doi.org/10.1111/j.1748-7692.1996.tb00312.x Lohmann, K. J., Cain, S. D., Dodge, S. A., & Lohmann, C. M. F. (2001). Regional magnetic fields as navigational markers for sea turtles. Science, 294(5541), 364â366. https://doi.org/10.1126/science.1064557 Lohmann, K. J., Lohmann, C. M. F., & Putman, N. F. (2007). Magnetic maps in animals: Natureâs GPS. Journal of Experimental Biology, 210(21), 3697â3705. https://doi.org/10.1242/jeb.001313 Lohmann, K. J., Luschi, P., & Hays, G. C. (2008a). Goal navigation and island-finding in sea turtles. Journal of Experimental Marine Biology and Ecology, 356(1â2), 83â95. https://doi.org/10.1016/j.jembe.2007.12.017 Lohmann, K. J., Lohmann, C. M. F., & Endres, C. S. (2008b). The sensory ecology of ocean navigation. Journal of Experimental Biology, 211(11), 1719â1728. https://doi.org/10.1242/jeb.015792 114 Lohmann, K. J., Putman, N. F., Johnsen, S., & Lohmann, C. M. F. (2024). Animal magnetic sensitivity and magnetic displacement experiments. Communications Biology, 7(1), 650. https://doi.org/10.1038/s42003-024-06269-4 Lund, U., & Agostinelli, C. (2024). circular: Circular statistics (p. 0.5-1) [Computer software]. https://CRAN.R-project.org/package=circular Lunn, N. J., & Boyd, I. L. (1993). Effects of maternal age and condition on parturition and the perinatal period of Antarctic fur seals. Journal of Zoology, 229(1), 55â67. https://doi.org/10.1111/j.1469-7998.1993.tb02620.x Luschi, P., Hays, G. C., Seppia, C. del, Marsh, R., & Papi, F. (1998). The navigational feats of green sea turtles migrating from Ascension Island investigated by satellite telemetry. Proceedings: Biological Sciences, 265(1412), 2279â2284. Luschi, P. (2013). Long-distance animal migrations in the oceanic environment: Orientation and navigation correlates. ISRN Zoology, 2013, 1â23. https://doi.org/10.1155/2013/631839 MaaÃ, E., Miersch, L., Pfuhl, G., & Hanke, F. D. (2022). A harbour seal (Phoca vitulina) can learn geometrical relationships between landmarks. Journal of Experimental Biology, 225(24), jeb244544. https://doi.org/10.1242/jeb.244544 Marshall, J., & Cronin, T. W. (2011). Polarisation vision. Current Biology, 21(3), R101âR105. https://doi.org/10.1016/j.cub.2010.12.012 Mate, B. R., Ilyashenko, V. Yu., Bradford, A. L., Vertyankin, V. V., Tsidulko, G. A., Rozhnov, V. V., & Irvine, L. M. (2015). Critically endangered western gray whales migrate to the eastern North Pacific. Biology Letters, 11(4), 20150071. https://doi.org/10.1098/rsbl.2015.0071 115 Matsumura, M., Watanabe, Y. Y., Robinson, P. W., Miller, P. J. O., Costa, D. P., & Miyazaki, N. (2011). Underwater and surface behavior of homing juvenile northern elephant seals. Journal of Experimental Biology, 214(4), 629â636. https://doi.org/10.1242/jeb.048827 Mauck, B., Gläser, N., Schlosser, W., & Dehnhardt, G. (2008). Harbour seals (Phoca vitulina) can steer by the stars. Animal Cognition, 11(4), 715â718. https://doi.org/10.1007/s10071-008-0156-1 McClintock, B. T., & Michelot, T. (2018). momentuHMM: R package for generalized hidden Markov models of animal movement. Methods in Ecology and Evolution, 9(6), 1518â1530. https://doi.org/10.1111/2041-210X.12995 McClintock, B. T., Langrock, R., Gimenez, O., Cam, E., Borchers, D. L., Glennie, R., & Patterson, T. A. (2020). Uncovering ecological state dynamics with hidden Markov models. Ecology Letters, 23(12), 1878â1903. https://doi.org/10.1111/ele.13610 McConnell, B. J., & Fedak, M. A. (1996). Movements of southern elephant seals. Canadian Journal of Zoology, 74(8), 1485â1496. https://doi.org/10.1139/z96-163 McConnell, B. J., Fedak, M. A., Burton, H. R., Engelhard, G. H., & Reijnders, P. J. H. (2002). Movements and foraging areas of naïve, recently weaned southern elephant seal pups. Journal of Animal Ecology, 71(1), 65â78. https://doi.org/10.1046/j.0021-8790.2001.00576.x McGovern, K., Rodríguez, D., Lewis, M., & Davis, R. (2019). Classification and behavior of free-ranging female southern elephant seal dives based on three-dimensional movements and video-recorded observations. Marine Ecology Progress Series, 620, 215â232. https://doi.org/10.3354/meps12936 116 McIntyre, T., de Bruyn, P. J. N., Ansorge, I. J., Bester, M. N., Bornemann, H., Plötz, J., & Tosh, C. A. (2010). A lifetime at depth: Vertical distribution of southern elephant seals in the water column. Polar Biology, 33(8), 1037â1048. https://doi.org/10.1007/s00300-010-0782-3 McIntyre, T. (2014). Trends in tagging of marine mammals: A review of marine mammal biologging studies. African Journal of Marine Science, 36(4), 409â422. https://doi.org/10.2989/1814232X.2014.976655 McIntyre, T., Bester, M. N., Bornemann, H., Tosh, C. A., & De Bruyn, P. J. N. (2017). Slow to change? Individual fidelity to three-dimensional foraging habitats in southern elephant seals, Mirounga leonina. Animal Behaviour, 127, 91â99. https://doi.org/10.1016/j.anbehav.2017.03.006 McIntyre, T., Oosthuizen, W. C., Bester, M. N., Hindell, M. A., Reisinger, R. R., Tosh, C. A., Van Den Hoff, J., & De Bruyn, P. J. N. (2024). Tracking the foraging migrations of Marion Island southern elephant seals (Mirounga leonina) during their first year of life. Marine Mammal Science, 40(2), e13078. https://doi.org/10.1111/mms.13078 McLaren, J. D., Schmaljohann, H., & Blasius, B. (2022). Predicting performance of naïve migratory animals, from many wrongs to self-correction. Communications Biology, 5(1), 1058. https://doi.org/10.1038/s42003-022-03995-5 McMahon, C. R., Burton, H., Slip, D., McLean, S., & Bester, M. (2000). Field immobilisation of southern elephant seals with intravenous tiletamine and zolazepam. Veterinary Record, 146(9), 251â254. https://doi.org/10.1136/vr.146.9.251 McMahon, C. R., Bester, M. N., Burton, H. R., Hindell, M. A., & Bradshaw, C. J. A. (2005). Population status, trends and a reâexamination of the hypotheses explaining the recent 117 declines of the southern elephant seal Mirounga leonina. Mammal Review, 35(1), 82â100. https://doi.org/10.1111/j.1365-2907.2005.00055.x Melubo, K. (2020). Why are wildlife on the Maasai doorsteps? Insights from the Maasai of Tanzania. AlterNative: An International Journal of Indigenous Peoples, 16(3), 180â192. https://doi.org/10.1177/1177180120947823 Mouritsen, H. (2022). Magnetoreception in birds and its use for long-distance migration. In Sturkieâs Avian Physiology (pp. 233â256). Elsevier. https://doi.org/10.1016/B978-0-12-819770-7.00040-2 Naisbett-Jones, L. C., Putman, N. F., Scanlan, M. M., Noakes, D. L. G., & Lohmann, K. J. (2020). Magnetoreception in fishes: The effect of magnetic pulses on orientation of juvenile Pacific salmon. Journal of Experimental Biology, jeb.222091. https://doi.org/10.1242/jeb.222091 Naisbett-Jones, L. C., & Lohmann, K. J. (2022). Magnetoreception and magnetic navigation in fishes: A half century of discovery. Journal of Comparative Physiology A, 208(1), 19â40. https://doi.org/10.1007/s00359-021-01527-w Nesterova, A. P., Flack, A., Van Loon, E. E., Bonadonna, F., & Biro, D. (2015). The effect of experienced individuals on navigation by king penguin chick pairs. Animal Behaviour, 104, 69â78. https://doi.org/10.1016/j.anbehav.2015.03.008 Nicholls, D. (1970). Dispersal and dispersion in relation to the birthsite of the southern elephant seal, Mirounga leonina (L.), of Macquarie Island. Mammalia, 34, 598â616. https://doi.org/10.1515/mamm.1970.34.4.598 118 Oliver, G. W. (1997). The homing and diving of translocated juvenile northern elephant seals, Mirounga angustirostris Gill, 1866 [Doctoral dissertation]. University of California Santa Cruz. Oliver, G. W., Morris, P. A., Thorson, P. H., & Le Boeuf, B. J. (1998). Homing behavior of juvenile northern elephant seals. Marine Mammal Science, 14(2), 245â256. https://doi.org/10.1111/j.1748-7692.1998.tb00714.x Orgeret, F., Cox, S. L., Weimerskirch, H., & Guinet, C. (2019). Body condition influences ontogeny of foraging behavior in juvenile southern elephant seals. Ecology and Evolution, 9(1), 223â236. https://doi.org/10.1002/ece3.4717 Padget, O., DellâAriccia, G., Gagliardo, A., González-Solís, J., & Guilford, T. (2017). Anosmia impairs homing orientation but not foraging behaviour in free-ranging shearwaters. Scientific Reports, 7(1), 9668. https://doi.org/10.1038/s41598-017-09738-5 Padget, O., Bond, S. L., Kavelaars, M. M., Van Loon, E., Bolton, M., Fayet, A. L., Syposz, M., Roberts, S., & Guilford, T. (2018). In situ clock shift reveals that the sun compass contributes to orientation in a pelagic seabird. Current Biology, 28(2), 275-279.e2. https://doi.org/10.1016/j.cub.2017.11.062 Papi, F. (2001). Animal navigation at the end of the century: A retrospect and a look forward. Italian Journal of Zoology, 68(3), 171â180. https://doi.org/10.1080/11250000109356405 Papi, F. (2006). Navigation of marine, freshwater and coastal animals: Concepts and current problems. Marine and Freshwater Behaviour and Physiology, 39(1), 3â12. https://doi.org/10.1080/10236240600563057 Patrick, S. C., Assink, J. D., Basille, M., Clusella-Trullas, S., Clay, T. A., Den Ouden, O. F. C., Joo, R., Zeyl, J. N., Benhamou, S., Christensen-Dalsgaard, J., Evers, L. G., Fayet, A. L., 119 Köppl, C., Malkemper, E. P., Martín López, L. M., Padget, O., Phillips, R. A., Prior, M. K., Smets, P. S. M., & Van Loon, E. E. (2021). Infrasound as a cue for seabird navigation. Frontiers in Ecology and Evolution, 9, 740027. https://doi.org/10.3389/fevo.2021.740027 Pei, S., Zhang, X., Eguíluz, V. M., Kienle, S. S., Robinson, P. W., Costa, D. P., & Duarte, C. M. (2023). Coherent movement patterns of female northern elephant seals across the NE Pacific Ocean. Frontiers in Marine Science, 10, 689953. https://doi.org/10.3389/fmars.2023.689953 Phillips, J. B., Freake, M. J., Fischer, J. H., & Borland, C. S. (2002). Behavioral titration of a magnetic map coordinate. Journal of Comparative Physiology A, 188(2), 157â160. https://doi.org/10.1007/s00359-002-0286-x Piersma, T., Gill, R. E., Ruthrauff, D. R., Guglielmo, C. G., Conklin, J. R., & Handel, C. M. (2022). The Pacific as the worldâs greatest theater of bird migration: Extreme flights spark questions about physiological capabilities, behavior, and the evolution of migratory pathways. Ornithology, 139(2), 1â29. https://doi.org/10.1093/ornithology/ukab086 Pitcher, B. J., Harcourt, R. G., Schaal, B., & Charrier, I. (2011). Social olfaction in marine mammals: Wild female Australian sea lions can identify their pupâs scent. Biology Letters, 7(1), 60â62. https://doi.org/10.1098/rsbl.2010.0569 Pizzuti, S., Bernish, M., Harvey, A., Tourangeau, L., Shriver, C., Kehl, C., & Taylor, B. (2022). Uncovering how animals use combinations of magnetic field properties to navigate: A computational approach. Journal of Comparative Physiology A, 208(1), 155â166. https://doi.org/10.1007/s00359-021-01523-0 120 Pohle, J., Langrock, R., Van Beest, F. M., & Schmidt, N. M. (2017). Selecting the number of states in hidden Markov models: Pragmatic solutions illustrated using animal movement. Journal of Agricultural, Biological and Environmental Statistics, 22(3), 270â293. https://doi.org/10.1007/s13253-017-0283-8 Pollonara, E., Luschi, P., Guilford, T., Wikelski, M., Bonadonna, F., & Gagliardo, A. (2015). Olfaction and topography, but not magnetic cues, control navigation in a pelagic seabird: Displacements with shearwaters in the Mediterranean Sea. Scientific Reports, 5(1), 16486. https://doi.org/10.1038/srep16486 Putman, N. F., Lohmann, K. J., Putman, E. M., Quinn, T. P., Klimley, A. P., & Noakes, D. L. G. (2013). Evidence for geomagnetic imprinting as a homing mechanism in Pacific salmon. Current Biology, 23(4), 312â316. https://doi.org/10.1016/j.cub.2012.12.041 Putman, N. F., Scanlan, M. M., Billman, E. J., OâNeil, J. P., Couture, R. B., Quinn, T. P., Lohmann, K. J., & Noakes, D. L. G. (2014a). An inherited magnetic map guides ocean navigation in juvenile pacific salmon. Current Biology, 24(4), 446â450. https://doi.org/10.1016/j.cub.2014.01.017 Putman, N. F., Jenkins, E. S., Michielsens, C. G. J., & Noakes, D. L. G. (2014b). Geomagnetic imprinting predicts spatio-temporal variation in homing migration of pink and sockeye salmon. Journal of The Royal Society Interface, 11(99), 20140542. https://doi.org/10.1098/rsif.2014.0542 Putman, N. F. (2022). Magnetosensation. Journal of Comparative Physiology A, 208(1), 1â7. https://doi.org/10.1007/s00359-021-01538-7 121 Quinn, T. P., & Groot, C. (1983). Orientation of Chum Salmon ( Oncorhynchus keta ) After Internal and External Magnetic Field Alteration. Canadian Journal of Fisheries and Aquatic Sciences, 40(10), 1598â1606. https://doi.org/10.1139/f83-185 Quintana, F., Gómez-Laich, A., Gunner, R. M., Gabelli, F., Omo, G. D., Duarte, C., Brogger, M., & Wilson, R. P. (2022). Long walk home: Magellanic penguins have strategies that lead them to areas where they can navigate most efficiently. Proceedings of the Royal Society B: Biological Sciences, 289(1977), 20220535. https://doi.org/10.1098/rspb.2022.0535 Ream, R. R., Sterling, J. T., & Loughlin, T. R. (2005). Oceanographic features related to northern fur seal migratory movements. Deep Sea Research Part II: Topical Studies in Oceanography, 52(5â6), 823â843. https://doi.org/10.1016/j.dsr2.2004.12.021 Reisinger, R. R., & Bester, M. N. (2010). Long distance breeding dispersal of a southern elephant seal. Polar Biology, 33(9), 1289â1291. https://doi.org/10.1007/s00300-010-0830-z Ripley, B., & Venables, B. (2009). MASS: Support functions and datasets for Venables and Ripleyâs MASS (p. 7.3-64) [Computer software]. https://CRAN.R-project.org/package=MASS Ritter, A., & Tessmar-Raible, K. (2024). Time me by the moon: The evolution and function of lunar timing systems. EMBO Reports, 25(8), 3169â3176. https://doi.org/10.1038/s44319-024-00196-5 Robinson, P., Tremblay, Y., Crocker, D. E., Kappes, M. A., Kuhn, C. E., Shaffer, S. A., Simmons, S. E., & Costa, D. P. (2007). A comparison of indirect measures of feeding behaviour based on ARGOS tracking data. Deep Sea Research Part II: Topical Studies in Oceanography, 54(3â4), 356â368. https://doi.org/10.1016/j.dsr2.2006.11.020 122 Robinson, P. (2009). Exploiting pelagic habitat: Navigation, migration, and foraging success in the northern elephant seal Mirounga angustirostris [Doctoral dissertation, University of California Santa Cruz]. https://www.proquest.com/openview/d5bd90411493a6293a57af45efe7951b/1?pq-origsite=gscholar&cbl=18750 Rodda, G. H. (1984). The orientation and navigation of juvenile alligators: Evidence of magnetic sensitivity. Journal of Comparative Physiology A, 154(5), 649â658. https://doi.org/10.1007/BF01350218 Rodríguez, J. P., Fernández-Gracia, J., Thums, M., Hindell, M. A., Sequeira, A. M. M., Meekan, M. G., Costa, D. P., Guinet, C., Harcourt, R. G., McMahon, C. R., Muelbert, M., Duarte, C. M., & Eguíluz, V. M. (2017). Big data analyses reveal patterns and drivers of the movements of southern elephant seals. Scientific Reports, 7(1), 112. https://doi.org/10.1038/s41598-017-00165-0 Rosenbaum, H. C., Maxwell, S. M., Kershaw, F., & Mate, B. (2014). Longârange movement of humpback whales and their overlap with anthropogenic activity in the south Atlantic Ocean. Conservation Biology, 28(2), 604â615. https://doi.org/10.1111/cobi.12225 Saldanha, S., Cox, S. L., Militão, T., & González-Solís, J. (2023). Animal behaviour on the move: The use of auxiliary information and semi-supervision to improve behavioural inferences from hidden Markov models applied to GPS tracking datasets. Movement Ecology, 11(1), 41. https://doi.org/10.1186/s40462-023-00401-5 Schneider, W. T., Packmor, F., Lindecke, O., & Holland, R. A. (2023). Sense of doubt: Inaccurate and alternate locations of virtual magnetic displacements may give a distorted 123 view of animal magnetoreception ability. Communications Biology, 6(1), 187. https://doi.org/10.1038/s42003-023-04530-w Sequeira, A. M. M. (2020). Animal navigation: The mystery of open ocean orientation. Current Biology, 30(18), R1054âR1056. https://doi.org/10.1016/j.cub.2020.07.049 Shaw, A. K. (2016). Drivers of animal migration and implications in changing environments. Evolutionary Ecology, 30(6), 991â1007. https://doi.org/10.1007/s10682-016-9860-5 Skiles, D. D. (1985). The geomagnetic field: Its nature, history, and biological relevance. In J. L. Kirschvink, D. S. Jones, & B. J. MacFadden (Eds.), Magnetite Biomineralization and Magnetoreception in Organisms (Vol. 5, pp. 43â102). Springer US. https://doi.org/10.1007/978-1-4613-0313-8_3 Tautz, J., Zhang, S., Spaethe, J., Brockmann, A., Si, A., & Srinivasan, M. (2004). Honeybee odometry: Performance in varying natural terrain. PLoS Biology, 2(7), e211. https://doi.org/10.1371/journal.pbio.0020211 Thieurmel, B., & Elmarhraoui, A. (2022). suncalc: Compute Sun Position, Sunlight Phases, Moon Position and Lunar Phase [Computer software]. https://CRAN.R-project.org/package=suncalc Thompson, D., Coram, A. J., Harris, R. N., & Sparling, C. E. (2021). Review of non-lethal seal control options to limit seal predation on salmonids in rivers and at finfish farms (No. Vol 12, No 6; Scottish Marine and Freshwater Science). Sea Mammal Research Unit. https://data.marine.gov.scot/dataset/review-non-lethal-seal-control-options-limit-seal-predation-salmonids-rivers-and-finfish 124 Tosh, C. A., Steyn, J., Bornemann, H., van den Hoff, J., Stewart, B. S., Plötz, J., & Bester, M. N. (2012). Marine habitats of juvenile southern elephant seals from Marion Island. Aquatic Biology, 17(1), 71â79. https://doi.org/10.3354/ab00463 Tosh, C. A., De Bruyn, P. J. N., Steyn, J., Bornemann, H., Van Den Hoff, J., Stewart, B. S., Plötz, J., & Bester, M. N. (2015). The importance of seasonal sea surface height anomalies for foraging juvenile southern elephant seals. Marine Biology, 162(10), 2131â2140. https://doi.org/10.1007/s00227-015-2743-4 Trathan, P. N., Forcada, J., & Murphy, E. J. (2007). Environmental forcing and Southern Ocean marine predator populations: Effects of climate change and variability. Philosophical Transactions of the Royal Society B: Biological Sciences, 362(1488), 2351â2365. https://doi.org/10.1098/rstb.2006.1953 Trites, A. W. (1991). Fetal growth of northern fur seals: Life-history strategy and sources of variation. Canadian Journal of Zoology, 69(10), 2608â2617. https://doi.org/10.1139/z91-367 Tucker, M. A., Böhning-Gaese, K., Fagan, W. F., Fryxell, J. M., Van Moorter, B., Alberts, S. C., Ali, A. H., Allen, A. M., Attias, N., Avgar, T., Bartlam-Brooks, H., Bayarbaatar, B., Belant, J. L., Bertassoni, A., Beyer, D., Bidner, L., Van Beest, F. M., Blake, S., Blaum, N., â¦ Mueller, T. (2018). Moving in the anthropocene: Global reductions in terrestrial mammalian movements. Science, 359(6374), 466â469. https://doi.org/10.1126/science.aam9712 Tyagi, T., & Bhardwaj, S. K. (2021). Magnetic compass orientation in a Palaearctic-Indian night migrant, the red-headed bunting. Animals, 11(6), 1541. https://doi.org/10.3390/ani11061541 125 Ugolini, A., Hoelters, L. S., Ciofini, A., Pasquali, V., & Wilcockson, D. C. (2016). Evidence for discrete solar and lunar orientation mechanisms in the beach amphipod, Talitrus saltator Montagu (Crustacea, Amphipoda). Scientific Reports, 6(1), 35575. https://doi.org/10.1038/srep35575 van den Hoff, J. (2002). Migrations of juvenile southern elephant seals from Macquarie Island [University of Tasmania]. https://figshare.utas.edu.au/articles/thesis/Migrations_of_juvenile_southern_elephant_seals_from_Macquarie_Island/23241029/1 van der Leeuw, B. K., & Tidwell, K. S. (2022). Evaluation of pinniped predation on adult salmonids and other fish in the Bonneville Dam tailrace, 2021 (p. 42 pp.). U.S. Army Corps of Engineers. https://public.crohms.org/tmt/documents/FPOM/2010/Task%20Groups/Task%20Group%20Pinnipeds/2021%20Pinniped%20Annual%20Report.pdf Ventura, F., Granadeiro, J. P., Padget, O., & Catry, P. (2020). Gadfly petrels use knowledge of the windscape, not memorized foraging patches, to optimize foraging trips on ocean-wide scales. Proceedings of the Royal Society B: Biological Sciences, 287(1918), 20191775. https://doi.org/10.1098/rspb.2019.1775 Vincent, C., Mcconnell, B. J., Ridoux, V., & Fedak, M. A. (2002). Assessment of ARGOS location accuracy from satellite tags deployed on captive gray seals. Marine Mammal Science, 18(1), 156â166. https://doi.org/10.1111/j.1748-7692.2002.tb01025.x Walker, M. M., & Bitterman, M. E. (1989). Honeybees can be trained to respond to very small changes in geomagnetic field intensity. Journal of Experimental Biology, 145(1), 489â494. https://doi.org/10.1242/jeb.145.1.489 126 Walker, M. M., Kirschvink, J. L., Ahmed, G., & Dizon, A. E. (1992). Evidence that fin whales respond to the geomagnetic field during migration. Wang, C. X., Hilburn, I. A., Wu, D.-A., Mizuhara, Y., Cousté, C. P., Abrahams, J. N. H., Bernstein, S. E., Matani, A., Shimojo, S., & Kirschvink, J. L. (2019). Transduction of the geomagnetic field as evidenced from alpha-band activity in the human brain. Eneuro, 6(2), ENEURO.0483-18.2019. https://doi.org/10.1523/ENEURO.0483-18.2019 Warrant, E. J. (2021). Unravelling the enigma of bird magnetoreception. Nature, 594(7864), 497â498. https://doi.org/10.1038/d41586-021-01596-6 Waterman, T. H. (2005). Reviving a neglected celestial underwater polarization compass for aquatic animals. Biological Reviews, 81(01), 111. https://doi.org/10.1017/S1464793105006883 Wiltschko, R., & Wiltschko, W. (2001). Clock-shift experiments with homing pigeons: A compromise between solar and magnetic information? Behavioral Ecology and Sociobiology, 49(5), 393â400. https://doi.org/10.1007/s002650000313 Wiltschko, R., & Wiltschko, W. (2023). Animal navigation: How animals use environmental factors to find their way. The European Physical Journal Special Topics, 232(2), 237â252. https://doi.org/10.1140/epjs/s11734-022-00610-w Wittlinger, M., Wehner, R., & Wolf, H. (2006). The ant odometer: Stepping on stilts and stumps. Science, 312(5782), 1965â1967. https://doi.org/10.1126/science.1126912 Wynn, J., Padget, O., Mouritsen, H., Perrins, C., & Guilford, T. (2020). Natal imprinting to the Earthâs magnetic field in a pelagic seabird. Current Biology, 30(14), 2869-2873.e2. https://doi.org/10.1016/j.cub.2020.05.039 127 Wynn, J., & Liedvogel, M. (2023). Lost: On what level should we aim to understand animal navigation? Journal of Experimental Biology, 226(10), jeb245441. https://doi.org/10.1242/jeb.245441 Young, I. R. (1999). Seasonal variability of the global ocean wind and wave climate. International Journal of Climatology, 19(9), 931â950. https://doi.org/10.1002/(SICI)1097-0088(199907)19:9<931::AID-JOC412>3.0.CO;2-O
Thesis/Dissertation
eng
Oceans and Fisheries
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Rosen, David A. S.
Evaluating southern elephant seal navigation through analysis of movement patterns and associated environmental cues
Text