Big data analyses reveal patterns and drivers of the movements of southern elephant seals

The growing number of large databases of animal tracking provides an opportunity for analyses of movement patterns at the scales of populations and even species. We used analytical approaches, developed to cope with big data, that require no a priori assumptions about the behaviour of the target agents, to analyse a pooled tracking dataset of 272 elephant seals (Mirounga leonina) in the Southern Ocean, that was comprised of >500,000 location estimates collected over more than a decade. Our analyses showed that the displacements of these seals were described by a truncated power law distribution across several spatial and temporal scales, with a clear signature of directed movement. This pattern was evident when analysing the aggregated tracks despite a wide diversity of individual trajectories. We also identified marine provinces that described the migratory and foraging habitats of these seals. Our analysis provides evidence for the presence of intrinsic drivers of movement, such as memory, that cannot be detected using common models of movement behaviour. These results highlight the potential for big data techniques to provide new insights into movement behaviour when applied to large datasets of animal tracking.Comment: 18 pages, 5 figures, 6 supplementary figure

Links between the three-dimensional movements of whale sharks (Rhincodon typus) and the bio-physical environment off a coral reef

Funding: This research was supported by funding from Santos Ltd and The Australian Institute of Marine Science (AIMS).Background Measuring coastal-pelagic prey fields at scales relevant to the movements of marine predators is challenging due to the dynamic and ephemeral nature of these environments. Whale sharks (Rhincodon typus) are thought to aggregate in nearshore tropical waters due to seasonally enhanced foraging opportunities. This implies that the three-dimensional movements of these animals may be associated with bio-physical properties that enhance prey availability. To date, few studies have tested this hypothesis. Methods Here, we conducted ship-based acoustic surveys, net tows and water column profiling (salinity, temperature, chlorophyll fluorescence) to determine the volumetric density, distribution and community composition of mesozooplankton (predominantly euphausiids and copepods) and oceanographic properties of the water column in the vicinity of whale sharks that were tracked simultaneously using satellite-linked tags at Ningaloo Reef, Western Australia. Generalised linear mixed effect models were used to explore relationships between the 3-dimensional movement behaviours of tracked sharks and surrounding prey fields at a spatial scale of ~ 1 km. Results We identified prey density as a significant driver of horizontal space use, with sharks occupying areas along the reef edge where densities were highest. These areas were characterised by complex bathymetry such as reef gutters and pinnacles. Temperature and salinity profiles revealed a well-mixed water column above the height of the bathymetry (top 40 m of the water column). Regions of stronger stratification were associated with reef gutters and pinnacles that concentrated prey near the seabed, and entrained productivity at local scales (~ 1 km). We found no quantitative relationship between the depth use of sharks and vertical distributions of horizontally averaged prey density. Whale sharks repeatedly dove to depths where spatially averaged prey concentration was highest but did not extend the time spent at these depth layers. Conclusions Our work reveals previously unrecognized complexity in interactions between whale sharks and their zooplankton prey.Publisher PDFPeer reviewe

Pygmy blue whale movement, distribution and important areas in the Eastern Indian Ocean

This study was conducted as part of AIMS’ North West Shoals to Shore Research Program (NWSSRP) and was supported by Santos as part of the company’s commitment to better understand Western Australia’s marine environment. Hydrophone pressure data from Ocean Bottom Seismometers (OBS) were provided by the CANPASS project, jointly funded by the National Natural Science Foundation of China (NSFC grants 91955210, 41625016), and the China Academy of Science (CAS program GJHZ1776). Instruments were provided by the Australian National instrument pool ANSIR (http://ansir.org.au/). ANSIR, OBS data was also made data available from the Geoscience Australia and Shell. Data was sourced from Australia’s Integrated Marine Observing System (IMOS).Pygmy blue whales in the South-east Indian Ocean migrate from the southern coast of Australia to Indonesia, with a significant part of their migration route passing through areas subject to oil and gas production. This study aimed at improving our understanding of the spatial extent of the distribution, migration and foraging areas, to better inform impact assessment of anthropogenic activities in these regions. Using a combination of passive acoustic monitoring of the NW Australian coast (46 instruments from 2006 to 2019) and satellite telemetry data (22 tag deployments from 2009 to 2021) we quantified the pygmy blue whale distribution and important areas during their northern and southern migration. We show extensive use of slope habitat off Western Australia and only minimal use of shelf habitat, compared to southern Australia where use of the continental shelf and shelf break predominates. In addition, movement behaviour estimated by a state-space model on satellite tag data showed that in general pygmy blue whales off Western Australia were mostly engaged in migration, interspersed with mostly relatively short periods (median = 28hours, range = 2 – 1080hours) of low move persistence (slow movement with high turning angles), which is indicative of foraging. Using the spatial overlap of time and number of whales in area analysis of the satellite tracking data (top 50% of grid cells) with foraging movement behaviour, we quantified the spatial extent of pygmy blue whale high use areas for foraging and migration. We compared these areas to the previously described areas of importance to foraging and migrating whales (Biologically Important Areas; BIAs). In some cases these had good agreement with the most important areas we calculated from our data, but others had only low (5%) to moderate (13%) overlap. Month was the most important variable predicting the number of pygmy blue whale units and number of singers (acting as indices of pygmy blue whale density). Whale density was highest in the southern part of the NW Australian coast and whales were present there between April-June, and November-December, a pattern also confirmed by the satellite tracking data. Available data indicated pygmy blue whales spent up to 124 days in Indonesian waters (34% of annual cycle). Since this area may also be the calving ground for this population, inter-jurisdictional management is necessary to ensure their full protection.Publisher PDFPeer reviewe

A comparison of the seasonal movements of tiger sharks and green turtles provides insight into their predator-prey relationship

During the reproductive season, sea turtles use a restricted area in the vicinity of their nesting beaches, making them vulnerable to predation. At Raine Island (Australia), the highest density green turtle Chelonia mydas rookery in the world, tiger sharks Galeocerdo cuvier have been observed to feed on green turtles, and it has been suggested that they may specialise on such air-breathing prey. However there is little information with which to examine this hypothesis. We compared the spatial and temporal components of movement behaviour of these two potentially interacting species in order to provide insight into the predator-prey relationship. Specifically, we tested the hypothesis that tiger shark movements are more concentrated at Raine Island during the green turtle nesting season than outside the turtle nesting season when turtles are not concentrated at Raine Island. Turtles showed area-restricted search behaviour around Raine Island for ~3–4 months during the nesting period (November–February). This was followed by direct movement (transit) to putative foraging grounds mostly in the Torres Straight where they switched to area-restricted search mode again, and remained resident for the remainder of the deployment (53–304 days). In contrast, tiger sharks displayed high spatial and temporal variation in movement behaviour which was not closely linked to the movement behaviour of green turtles or recognised turtle foraging grounds. On average, tiger sharks were concentrated around Raine Island throughout the year. While information on diet is required to determine whether tiger sharks are turtle specialists our results support the hypothesis that they target this predictable and plentiful prey during turtle nesting season, but they might not focus on this less predictable food source outside the nesting season

Convergence of marine megafauna movement patterns in coastal and open oceans

Author Posting. © The Author(s), 2017. This is the author's version of the work. It is posted here for personal use, not for redistribution. The definitive version was published in Proceedings of the National Academy of Sciences of the United States of America 115 (2018): 3072-3077, doi:10.1073/pnas.1716137115.The extent of increasing anthropogenic impacts on large marine vertebrates partly depends on the animals’ movement patterns. Effective conservation requires identification of the key drivers of movement including intrinsic properties and extrinsic constraints associated with the dynamic nature of the environments the animals inhabit. However, the relative importance of intrinsic versus extrinsic factors remains elusive. We analyse a global dataset of 2.8 million locations from > 2,600 tracked individuals across 50 marine vertebrates evolutionarily separated by millions of years and using different locomotion modes (fly, swim, walk/paddle). Strikingly, movement patterns show a remarkable convergence, being strongly conserved across species and independent of body length and mass, despite these traits ranging over 10 orders of magnitude among the species studied. This represents a fundamental difference between marine and terrestrial vertebrates not previously identified, likely linked to the reduced costs of locomotion in water. Movement patterns were primarily explained by the interaction between species-specific traits and the habitat(s) they move through, resulting in complex movement patterns when moving close to coasts compared to more predictable patterns when moving in open oceans. This distinct difference may be associated with greater complexity within coastal micro-habitats, highlighting a critical role of preferred habitat in shaping marine vertebrate global movements. Efforts to develop understanding of the characteristics of vertebrate movement should consider the habitat(s) through which they move to identify how movement patterns will alter with forecasted severe ocean changes, such as reduced Arctic sea ice cover, sea level rise and declining oxygen content.Workshops funding granted by the UWA Oceans Institute, AIMS, and KAUST. AMMS was supported by an ARC Grant DE170100841 and an IOMRC (UWA, AIMS, CSIRO) fellowship; JPR by MEDC (FPU program, Spain); DWS by UK NERC and Save Our Seas Foundation; NQ by FCT (Portugal); MMCM by a CAPES fellowship (Ministry of Education)

Translating Marine Animal Tracking Data into Conservation Policy and Management

There have been efforts around the globe to track individuals of many marine species and assess their movements and distribution with the putative goal of supporting their conservation and management. Determining whether, and how, tracking data have been successfully applied to address real-world conservation issues is however difficult. Here, we compile a broad range of case studies from diverse marine taxa to show how tracking data have helped inform conservation policy and management, including reductions in fisheries bycatch and vessel strikes, and the design and administration of marine protected areas and important habitats. Using these examples, we highlight pathways through which the past and future investment in collecting animal tracking data might be better used to achieve tangible conservation benefits

Global collision-risk hotspots of marine traffic and the world’s largest fish, the whale shark

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Womersley, F. C., Humphries, N. E., Queiroz, N., Vedor, M., da Costa, I., Furtado, M., Tyminski, J. P., Abrantes, K., Araujo, G., Bach, S. S., Barnett, A., Berumen, M. L., Bessudo Lion, S., Braun, C. D., Clingham, E., Cochran, J. E. M., de la Parra, R., Diamant, S., Dove, A. D. M., Dudgeon, C. L., Erdmann, M. V., Espinoza, E., Fitzpatrick, R., González Cano, J., Green, J. R., Guzman, H. M., Hardenstine, R., Hasan, A., Hazin, F. H. V., Hearn, A. R., Hueter, R. E., Jaidah, M. Y., Labaja, J., Ladinol, F., Macena, B. C. L., Morris Jr., J. J., Norman, B. M., Peñaherrera-Palmav, C., Pierce, S. J., Quintero, L. M., Ramırez-Macías, D., Reynolds, S. D., Richardson, A. J., Robinson, D. P., Rohner, C. A., Rowat, D. R. L., Sheaves, M., Shivji, M. S., Sianipar, A. B., Skomal, G. B., Soler, G., Syakurachman, I., Thorrold, S. R., Webb, D. H., Wetherbee, B. M., White, T. D., Clavelle, T., Kroodsma, D. A., Thums, M., Ferreira, L. C., Meekan, M. G., Arrowsmith, L. M., Lester, E. K., Meyers, M. M., Peel, L. R., Sequeira, A. M. M., Eguıluz, V. M., Duarte, C. M., & Sims, D. W. Global collision-risk hotspots of marine traffic and the world’s largest fish, the whale shark. Proceedings of the National Academy of Sciences of the United States of America, 119(20), (2022): e2117440119, https://doi.org/10.1073/pnas.2117440119.Marine traffic is increasing globally yet collisions with endangered megafauna such as whales, sea turtles, and planktivorous sharks go largely undetected or unreported. Collisions leading to mortality can have population-level consequences for endangered species. Hence, identifying simultaneous space use of megafauna and shipping throughout ranges may reveal as-yet-unknown spatial targets requiring conservation. However, global studies tracking megafauna and shipping occurrences are lacking. Here we combine satellite-tracked movements of the whale shark, Rhincodon typus, and vessel activity to show that 92% of sharks’ horizontal space use and nearly 50% of vertical space use overlap with persistent large vessel (>300 gross tons) traffic. Collision-risk estimates correlated with reported whale shark mortality from ship strikes, indicating higher mortality in areas with greatest overlap. Hotspots of potential collision risk were evident in all major oceans, predominantly from overlap with cargo and tanker vessels, and were concentrated in gulf regions, where dense traffic co-occurred with seasonal shark movements. Nearly a third of whale shark hotspots overlapped with the highest collision-risk areas, with the last known locations of tracked sharks coinciding with busier shipping routes more often than expected. Depth-recording tags provided evidence for sinking, likely dead, whale sharks, suggesting substantial “cryptic” lethal ship strikes are possible, which could explain why whale shark population declines continue despite international protection and low fishing-induced mortality. Mitigation measures to reduce ship-strike risk should be considered to conserve this species and other ocean giants that are likely experiencing similar impacts from growing global vessel traffic.Funding for data analysis was provided by the UK Natural Environment Research Council (NERC) through a University of Southampton INSPIRE DTP PhD Studentship to F.C.W. Additional funding for data analysis was provided by NERC Discovery Science (NE/R00997/X/1) and the European Research Council (ERC-AdG-2019 883583 OCEAN DEOXYFISH) to D.W.S., Fundação para a Ciência e a Tecnologia (FCT) under PTDC/BIA/28855/2017 and COMPETE POCI-01–0145-FEDER-028855, and MARINFO–NORTE-01–0145-FEDER-000031 (funded by Norte Portugal Regional Operational Program [NORTE2020] under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund–ERDF) to N.Q. FCT also supported N.Q. (CEECIND/02857/2018) and M.V. (PTDC/BIA-COM/28855/2017). D.W.S. was supported by a Marine Biological Association Senior Research Fellowship. All tagging procedures were approved by institutional ethical review bodies and complied with all relevant ethical regulations in the jurisdictions in which they were performed. Details for individual research teams are given in SI Appendix, section 8. Full acknowledgments for tagging and field research are given in SI Appendix, section 7. This research is part of the Global Shark Movement Project (https://www.globalsharkmovement.org)

Global Spatial Risk Assessment of Sharks Under the Footprint of Fisheries

Effective ocean management and conservation of highly migratory species depends on resolving overlap between animal movements and distributions and fishing effort. Yet, this information is lacking at a global scale. Here we show, using a big-data approach combining satellite-tracked movements of pelagic sharks and global fishing fleets, that 24% of the mean monthly space used by sharks falls under the footprint of pelagic longline fisheries. Space use hotspots of commercially valuable sharks and of internationally protected species had the highest overlap with longlines (up to 76% and 64%, respectively) and were also associated with significant increases in fishing effort. We conclude that pelagic sharks have limited spatial refuge from current levels of high-seas fishing effort. Results demonstrate an urgent need for conservation and management measures at high-seas shark hotspots and highlight the potential of simultaneous satellite surveillance of megafauna and fishers as a tool for near-real time, dynamic management

Diving into the vertical dimension of elasmobranch movement ecology

Knowledge of the three-dimensional movement patterns of elasmobranchs is vital to understand their ecological roles and exposure to anthropogenic pressures. To date, comparative studies among species at global scales have mostly focused on horizontal movements. Our study addresses the knowledge gap of vertical movements by compiling the first global synthesis of vertical habitat use by elasmobranchs from data obtained by deployment of 989 biotelemetry tags on 38 elasmobranch species. Elasmobranchs displayed high intra- and interspecific variability in vertical movement patterns. Substantial vertical overlap was observed for many epipelagic elasmobranchs, indicating an increased likelihood to display spatial overlap, biologically interact, and share similar risk to anthropogenic threats that vary on a vertical gradient. We highlight the critical next steps toward incorporating vertical movement into global management and monitoring strategies for elasmobranchs, emphasizing the need to address geographic and taxonomic biases in deployments and to concurrently consider both horizontal and vertical movements

Diving into the vertical dimension of elasmobranch movement ecology

Knowledge of the three-dimensional movement patterns of elasmobranchs is vital to understand their ecological roles and exposure to anthropogenic pressures. To date, comparative studies among species at global scales have mostly focused on horizontal movements. Our study addresses the knowledge gap of vertical movements by compiling the first global synthesis of vertical habitat use by elasmobranchs from data obtained by deployment of 989 biotelemetry tags on 38 elasmobranch species. Elasmobranchs displayed high intra- and interspecific variability in vertical movement patterns. Substantial vertical overlap was observed for many epipelagic elasmobranchs, indicating an increased likelihood to display spatial overlap, biologically interact, and share similar risk to anthropogenic threats that vary on a vertical gradient. We highlight the critical next steps toward incorporating vertical movement into global management and monitoring strategies for elasmobranchs, emphasizing the need to address geographic and taxonomic biases in deployments and to concurrently consider both horizontal and vertical movements