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Annual Review of Animal Biosciences

Volume 11, 2023

Biologging and Biotelemetry: Tools for Understanding the Lives and Environments of Marine Animals

Abstract

Addressing important questions in animal ecology, physiology, and environmental science often requires in situ information from wild animals. This difficulty is being overcome by biologging and biotelemetry, or the use of miniaturized animal-borne sensors. Although early studies recorded only simple parameters of animal movement, advanced devices and analytical methods can now provide rich information on individual and group behavior, internal states, and the surrounding environment of free-ranging animals, especially those in marine systems. We summarize the history of technologies used to track marine animals. We then identify seven major research categories of marine biologging and biotelemetry and explain significant achievements, as well as future opportunities. Big data approaches via international collaborations will be key to tackling global environmental issues (e.g., climate change impacts), and curiosity about the secret lives of marine animals will also remain a major driver of biologging and biotelemetry studies.

Keyword(s): anthropogenic stressor, field physiology, movement ecology, predator–prey interaction, social interaction
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/content/journals/10.1146/annurev-animal-050322-073657
2023-02-15
2024-05-04
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Literature Cited

  1. 1.
    Hussey NE, Kessel ST, Aarestrup K, Cooke SJ, Cowley PD et al. 2015. Aquatic animal telemetry: a panoramic window into the underwater world. Science 348:62401255642
     [Google Scholar]
  2. 2.
    Kays R, Crofoot MC, Jetz W, Wikelski M. 2015. Terrestrial animal tracking as an eye on life and planet. Science 348:6240aaa2478
     [Google Scholar]
  3. 3.
    Cooke SJ, Hinch SG, Wikelski M, Andrews RD, Kuchel LJ et al. 2004. Biotelemetry: a mechanistic approach to ecology. Trends Ecol. Evol. 19:334–43
     [Google Scholar]
  4. 4.
    Ropert-Coudert Y, Wilson RP. 2005. Trends and perspectives in animal-attached remote sensing. Front. Ecol. Environ. 3:437–44
     [Google Scholar]
  5. 5.
    Williams HJ, Taylor LA, Benhamou S, Bijleveld AI, Clay TA et al. 2020. Optimizing the use of biologgers for movement ecology research. J. Anim. Ecol. 89:186–206
     [Google Scholar]
  6. 6.
    Wilmers CC, Nickel B, Bryce CM, Smith JA, Wheat RE, Yovovich V. 2015. The golden age of bio-logging: how animal-borne sensors are advancing the frontiers of ecology. Ecology 96:1741–53
     [Google Scholar]
  7. 7.
    Scholander PF. 1940. Experimental Investigations on the Respiratory Function in Diving Mammals and Birds Oslo: Hvalråd. Skr.
  8. 8.
    Kooyman GL. 1965. Techniques used in measuring diving capacities of Weddell seals. Polar Rec. 12:391–94
     [Google Scholar]
  9. 9.
    Wilson RP, Bain CA. 1984. An inexpensive depth gauge for penguins. J. Wildl. Manag. 48:1077–84
     [Google Scholar]
  10. 10.
    Naito Y, Le Boeuf BJ, Asaga T, Huntley AC 1989. Long-term diving records of an adult female northern elephant seal. Antarct. Rec. 33:1–9
     [Google Scholar]
  11. 11.
    Naito Y, Asaga T, Ohyama Y. 1990. Diving behavior of Adélie penguins determined by time-depth recorder. Condor 92:582–86
     [Google Scholar]
  12. 12.
    Naito Y. 2004. New steps in bio-logging science. Mem. Natl. Inst. Polar Res. 58:Spec. Issue50–57
     [Google Scholar]
  13. 13.
    Yoda K, Sato K, Niizuma Y, Kurita M, Bost C et al. 1999. Precise monitoring of porpoising behaviour of Adélie penguins determined using acceleration data loggers. J. Exp. Biol. 202:3121–26
     [Google Scholar]
  14. 14.
    Davis RW, Fuiman LA, Williams TM, Collier SO, Hagey WP et al. 1999. Hunting behavior of a marine mammal beneath the Antarctic fast ice. Science 283:993–96
     [Google Scholar]
  15. 15.
    Nowacek DP, Tyack PL, Wells RS, Johnson MP. 1998. An onboard acoustic data logger to record biosonar of free-ranging bottlenose dolphins. J. Acoust. Soc. Am. 103:2908
     [Google Scholar]
  16. 16.
    Weimerskirch H, Bonadonna F, Bailleul F, Mabille G, Dell'Omo G, Lipp H-P. 2002. GPS tracking of foraging albatrosses. Science 295:1259
     [Google Scholar]
  17. 17.
    Delong RL, Stewart BS, Hill RD. 1992. Documenting migrations of northern elephant seals using day length. Mar. Mamm. Sci. 8:155–59
     [Google Scholar]
  18. 18.
    Block BA, Dewar H, Blackwell SB, Williams TD, Prince ED et al. 2001. Migratory movements, depth preferences, and thermal biology of Atlantic bluefin tuna. Science 293:1310–14
     [Google Scholar]
  19. 19.
    Weimerskirch H, Wilson RP. 2000. Oceanic respite for wandering albatrosses. Nature 406:955–56
     [Google Scholar]
  20. 20.
    Watanabe Y, Baranov EA, Sato K, Naito Y, Miyazaki N. 2004. Foraging tactics of Baikal seals differ between day and night. Mar. Ecol. Prog. Ser. 279:283–89
     [Google Scholar]
  21. 21.
    Baird R. 1997. Studying diving behavior of whales and dolphins using suction-cup attached tags. Whalewatcher 31:3–7
     [Google Scholar]
  22. 22.
    Hockersmith EE, Beeman JW 2012. A history of telemetry in fishery research. Telemetry Techniques: A User Guide for Fisheries Research NS Adams, JW Beeman, JH Eiler 7–20 Bethesda, MD: Am. Fish. Soc.
     [Google Scholar]
  23. 23.
    Trefethen PS. 1956. Sonic equipment for tracking individual fish Spec. Sci. Rep. Fish. 179 Fish Wildl. Serv., US Dep. Inter. Washington, DC:
  24. 24.
    Yuen HS. 1970. Behavior of skipjack tuna, Katsuwonus pelamis, as determined by tracking with ultrasonic devices. J. Fish. Board Can. 27:2071–79
     [Google Scholar]
  25. 25.
    Nelson DR. 1976. Ultrasonic telemetry of shark behavior. J. Acoust. Soc. Am. 59:1004–7
     [Google Scholar]
  26. 26.
    Carey FG, Lawson KD. 1973. Temperature regulation in free-swimming bluefin tuna. Comp. Biochem. Physiol. A 44:375–92
     [Google Scholar]
  27. 27.
    Klimley A, Butler S, Nelson D, Stull A 1988. Diel movements of scalloped hammerhead sharks, Sphyrna lewini Griffith and Smith, to and from a seamount in the Gulf of California. J. Fish Biol. 33:751–61
     [Google Scholar]
  28. 28.
    Heupel M, Semmens JM, Hobday A. 2006. Automated acoustic tracking of aquatic animals: scales, design and deployment of listening station arrays. Mar. Freshw. Res. 57:1–13
     [Google Scholar]
  29. 29.
    Klimley AP, Le Boeuf BJ, Cantara KM, Richert JE, Davis SF et al. 2001. The hunting strategy of white sharks (Carcharodon carcharias) near a seal colony. Mar. Biol. 138:617–36
     [Google Scholar]
  30. 30.
    Espinoza M, Farrugia TJ, Webber DM, Smith F, Lowe CG. 2011. Testing a new acoustic telemetry technique to quantify long-term, fine-scale movements of aquatic animals. Fish. Res. 108:364–71
     [Google Scholar]
  31. 31.
    Priede IG. 1984. A basking shark (Cetorhinus maximus) tracked by satellite together with simultaneous remote sensing. Fish. Res. 2:201–16
     [Google Scholar]
  32. 32.
    Jouventin P, Weimerskirch H. 1990. Satellite tracking of wandering albatrosses. Nature 343:746–48
     [Google Scholar]
  33. 33.
    Block BA, Dewar H, Farwell C, Prince ED. 1998. A new satellite technology for tracking the movements of Atlantic bluefin tuna. PNAS 95:9384–89
     [Google Scholar]
  34. 34.
    Fedak M, Lovell P, McConnell B, Hunter C. 2002. Overcoming the constraints of long range radio telemetry from animals: getting more useful data from smaller packages. Integr. Comp. Biol. 42:3–10
     [Google Scholar]
  35. 35.
    Halsey LG, Butler PJ, Blackburn TM. 2006. A phylogenetic analysis of the allometry of diving. Am. Nat. 167:276–87
     [Google Scholar]
  36. 36.
    Verberk WC, Calosi P, Brischoux F, Spicer JI, Garland T Jr., Bilton DT. 2020. Universal metabolic constraints shape the evolutionary ecology of diving in animals. Proc. R. Soc. B 287:20200488
     [Google Scholar]
  37. 37.
    Tyack PL, Johnson M, Soto NA, Sturlese A, Madsen PT. 2006. Extreme diving of beaked whales. J. Exp. Biol. 209:4238–53
     [Google Scholar]
  38. 38.
    Schorr GS, Falcone EA, Moretti DJ, Andrews RD. 2014. First long-term behavioral records from Cuvier's beaked whales (Ziphius cavirostris) reveal record-breaking dives. PLOS ONE 9:e92633
     [Google Scholar]
  39. 39.
    Braun CD, Arostegui MC, Thorrold SR, Papastamatiou YP, Gaube P et al. 2022. The functional and ecological significance of deep diving by large marine predators. Annu. Rev. Mar. Sci. 14:129–59
     [Google Scholar]
  40. 40.
    Nakamura I, Goto Y, Sato K. 2015. Ocean sunfish rewarm at the surface after deep excursions to forage for siphonophores. J. Anim. Ecol. 84:590–603
     [Google Scholar]
  41. 41.
    Tyminski JP, de la Parra-Venegas R, González Cano J, Hueter RE 2015. Vertical movements and patterns in diving behavior of whale sharks as revealed by pop-up satellite tags in the eastern Gulf of Mexico. PLOS ONE 10:e0142156
     [Google Scholar]
  42. 42.
    Thorrold SR, Afonso P, Fontes J, Braun CD, Santos RS et al. 2014. Extreme diving behaviour in devil rays links surface waters and the deep ocean. Nat. Commun. 5:4274
     [Google Scholar]
  43. 43.
    Nakamura I, Matsumoto R, Sato K. 2020. Body temperature stability in the whale shark, the world's largest fish. J. Exp. Biol. 223:jeb210286
     [Google Scholar]
  44. 44.
    Egevang C, Stenhouse IJ, Phillips RA, Petersen A, Fox JW, Silk JRD. 2010. Tracking of Arctic terns Sterna paradisaea reveals longest animal migration. PNAS 107:2078–81
     [Google Scholar]
  45. 45.
    Shaffer SA, Tremblay Y, Weimerskirch H, Scott D, Thompson DR et al. 2006. Migratory shearwaters integrate oceanic resources across the Pacific Ocean in an endless summer. PNAS 103:12799–802
     [Google Scholar]
  46. 46.
    Kopp M, Peter H-U, Mustafa O, Lisovski S, Ritz MS et al. 2011. South polar skuas from a single breeding population overwinter in different oceans though show similar migration patterns. Mar. Ecol. Prog. Ser. 435:263–67
     [Google Scholar]
  47. 47.
    Block BA, Jonsen ID, Jorgensen SJ, Winship AJ, Shaffer SA et al. 2011. Tracking apex marine predator movements in a dynamic ocean. Nature 475:86–90
     [Google Scholar]
  48. 48.
    Croxall JP, Silk JRD, Phillips RA, Afanasyev V, Briggs DR. 2005. Global circumnavigations: tracking year-round ranges of nonbreeding albatrosses. Science 307:249–50
     [Google Scholar]
  49. 49.
    Hays GC, Houghton JD, Myers AE. 2004. Pan-Atlantic leatherback turtle movements. Nature 429:522
     [Google Scholar]
  50. 50.
    Weng KC, Castilho PC, Morrissette JM, Landeira-Fernandez AM, Holts DB et al. 2005. Satellite tagging and cardiac physiology reveal niche expansion in salmon sharks. Science 310:104–6
     [Google Scholar]
  51. 51.
    Papastamatiou YP, Meyer CG, Carvalho F, Dale JJ, Hutchinson MR, Holland KN. 2013. Telemetry and random-walk models reveal complex patterns of partial migration in a large marine predator. Ecology 94:2595–606
     [Google Scholar]
  52. 52.
    Reid JM, Travis JM, Daunt F, Burthe SJ, Wanless S, Dytham C. 2018. Population and evolutionary dynamics in spatially structured seasonally varying environments. Biol. Rev. 93:1578–603
     [Google Scholar]
  53. 53.
    Watanabe YY, Goldman KJ, Caselle JE, Chapman DD, Papastamatiou YP. 2015. Comparative analyses of animal-tracking data reveal ecological significance of endothermy in fishes. PNAS 112:6104–9
     [Google Scholar]
  54. 54.
    Allgeier JE, Cline TJ, Walsworth TE, Wathen G, Layman CA, Schindler DE. 2020. Individual behavior drives ecosystem function and the impacts of harvest. Sci. Adv. 6:eaax8329
     [Google Scholar]
  55. 55.
    Hawkes L, Fahlman A, Sato K. 2021. What is physiologging? Introduction to the theme issue, part 2. Philos. Trans. R. Soc. B 376:20210028
     [Google Scholar]
  56. 56.
    Hill RD, Schneider RC, Liggins GC, Schuette AH, Elliott RL et al. 1987. Heart rate and body temperature during free diving of Weddell seals. Am. J. Physiol. Regulatory Integr. Comp. Physiol. 253:R344–R51
     [Google Scholar]
  57. 57.
    Goldbogen J, Cade D, Calambokidis J, Czapanskiy M, Fahlbusch J et al. 2019. Extreme bradycardia and tachycardia in the world's largest animal. PNAS 116:25329–32
     [Google Scholar]
  58. 58.
    Blix AS. 2018. Adaptations to deep and prolonged diving in phocid seals. J. Exp. Biol. 221:jeb182972
     [Google Scholar]
  59. 59.
    Elmegaard SL, Johnson M, Madsen PT, McDonald BI. 2016. Cognitive control of heart rate in diving harbor porpoises. Curr. Biol. 26:R1175–R76
     [Google Scholar]
  60. 60.
    Meir JU, Champagne CD, Costa DP, Williams CL, Ponganis PJ. 2009. Extreme hypoxemic tolerance and blood oxygen depletion in diving elephant seals. Am. J. Physiol.-Regul. Integr. Comp. Physiol. 297:R927–39
     [Google Scholar]
  61. 61.
    Ponganis P, Stockard T, Meir J, Williams C, Ponganis K et al. 2007. Returning on empty: extreme blood O2 depletion underlies dive capacity of emperor penguins. J. Exp. Biol. 210:4279–85
     [Google Scholar]
  62. 62.
    McKnight JC, Bennett KA, Bronkhorst M, Russell DJ, Balfour S et al. 2019. Shining new light on mammalian diving physiology using wearable near-infrared spectroscopy. PLOS Biol. 17:e3000306
     [Google Scholar]
  63. 63.
    Holland KN, Brill RW, Chang RK, Sibert JR, Fournier DA. 1992. Physiological and behavioural thermoregulation in bigeye tuna (Thunnus obesus). Nature 358:410–12
     [Google Scholar]
  64. 64.
    Goldman KJ, Anderson SD, Latour RJ, Musick JA. 2004. Homeothermy in adult salmon sharks, Lamna ditropis. Environ. . Biol. Fishes 71:403–11
     [Google Scholar]
  65. 65.
    Carey FG, Kanwisher JW, Brazier O, Gabrielson G, Casey JG, Pratt HL Jr. 1982. Temperature and activities of a white shark, Carcharodon carcharias. Copeia 1982:254–60
     [Google Scholar]
  66. 66.
    Casey JP, James MC, Williard AS. 2014. Behavioral and metabolic contributions to thermoregulation in freely swimming leatherback turtles at high latitudes. J. Exp. Biol. 217:2331–37
     [Google Scholar]
  67. 67.
    Grady JM, Enquist BJ, Dettweiler-Robinson E, Wright NA, Smith FA. 2014. Evidence for mesothermy in dinosaurs. Science 344:1268–72
     [Google Scholar]
  68. 68.
    McCosker JE. 1987. The white shark, Carcharodon carcharias, has a warm stomach. Copeia 1987:195–97
     [Google Scholar]
  69. 69.
    Sato K, Sakamoto W, Matsuzawa Y, Tanaka H, Naito Y. 1994. Correlation between stomach temperatures and ambient water temperatures in free-ranging loggerhead turtles, Caretta caretta. Mar. Biol. 118:343–51
     [Google Scholar]
  70. 70.
    Payne NL, Smith JA, van der Meulen DE, Taylor MD, Watanabe YY et al. 2016. Temperature dependence of fish performance in the wild: links with species biogeography and physiological thermal tolerance. Funct. Ecol. 30:903–12
     [Google Scholar]
  71. 71.
    Mitani Y, Andrews RD, Sato K, Kato A, Naito Y, Costa DP. 2010. Three-dimensional resting behaviour of northern elephant seals: drifting like a falling leaf. Biol. Lett. 6:163–66
     [Google Scholar]
  72. 72.
    Miller PJ, Aoki K, Rendell LE, Amano M. 2008. Stereotypical resting behavior of the sperm whale. Curr. Biol. 18:R21–R23
     [Google Scholar]
  73. 73.
    Lesku JA, Rattenborg NC, Valcu M, Vyssotski AL, Kuhn S et al. 2012. Adaptive sleep loss in polygynous pectoral sandpipers. Science 337:1654–58
     [Google Scholar]
  74. 74.
    Rattenborg NC, Voirin B, Cruz SM, Tisdale R, Dell'Omo G et al. 2016. Evidence that birds sleep in mid-flight. Nat. Commun. 7:12468
     [Google Scholar]
  75. 75.
    Lyamin OI, Kosenko PO, Korneva SM, Vyssotski AL, Mukhametov LM, Siegel JM. 2018. Fur seals suppress REM sleep for very long periods without subsequent rebound. Curr. Biol. 28:2000–5
     [Google Scholar]
  76. 76.
    Green JA. 2011. The heart rate method for estimating metabolic rate: review and recommendations. Comp. Biochem. Physiol. A 158:287–304
     [Google Scholar]
  77. 77.
    Wilson RP, White CR, Quintana F, Halsey LG, Liebsch N et al. 2006. Moving towards acceleration for estimates of activity-specific metabolic rate in free-living animals: the case of the cormorant. J. Anim. Ecol. 75:1081–90
     [Google Scholar]
  78. 78.
    Wilson RP, Börger L, Holton MD, Scantlebury DM, Gómez-Laich A et al. 2020. Estimates for energy expenditure in free-living animals using acceleration proxies: a reappraisal. J. Anim. Ecol. 89:161–72
     [Google Scholar]
  79. 79.
    Wilson RP, Cooper J, Plötz J. 1992. Can we determine when marine endotherms feed—a case-study with seabirds. J. Exp. Biol. 167:267–75
     [Google Scholar]
  80. 80.
    Naito Y, Costa DP, Adachi T, Robinson PW, Fowler M, Takahashi A. 2013. Unravelling the mysteries of a mesopelagic diet: A large apex predator specializes on small prey. Funct. Ecol. 27:710–17
     [Google Scholar]
  81. 81.
    Weimerskirch H, Gault A, Cherel Y. 2005. Prey distribution and patchiness: factors in foraging success and efficiency of wandering albatrosses. Ecology 86:2611–22
     [Google Scholar]
  82. 82.
    Wisniewska DM, Johnson M, Teilmann J, Rojano-Doñate L, Shearer J et al. 2016. Ultra-high foraging rates of harbor porpoises make them vulnerable to anthropogenic disturbance. Curr. Biol. 26:1441–46
     [Google Scholar]
  83. 83.
    Watanabe YY, Takahashi A. 2013. Linking animal-borne video to accelerometers reveals prey capture variability. PNAS 110:2199–204
     [Google Scholar]
  84. 84.
    Bestley S, Patterson TA, Hindell MA, Gunn JS. 2008. Feeding ecology of wild migratory tunas revealed by archival tag records of visceral warming. J. Anim. Ecol. 77:1223–33
     [Google Scholar]
  85. 85.
    Biuw M, Boehme L, Guinet C, Hindell M, Costa D et al. 2007. Variations in behavior and condition of a Southern Ocean top predator in relation to in situ oceanographic conditions. PNAS 104:13705–10
     [Google Scholar]
  86. 86.
    Adachi T, Takahashi A, Costa DP, Robinson PW, Hückstädt LA et al. 2021. Forced into an ecological corner: round-the-clock deep foraging on small prey by elephant seals. Sci. Adv. 7:eabg3628
     [Google Scholar]
  87. 87.
    Watanabe YY, Baranov EA, Miyazaki N. 2020. Ultrahigh foraging rates of Baikal seals make tiny endemic amphipods profitable in Lake Baikal. PNAS 117:31242–48
     [Google Scholar]
  88. 88.
    Goldbogen J, Cade D, Wisniewska D, Potvin J, Segre P et al. 2019. Why whales are big but not bigger: physiological drivers and ecological limits in the age of ocean giants. Science 366:1367–72
     [Google Scholar]
  89. 89.
    Savoca MS, Czapanskiy MF, Kahane-Rapport SR, Gough WT, Fahlbusch JA et al. 2021. Baleen whale prey consumption based on high-resolution foraging measurements. Nature 599:85–90
     [Google Scholar]
  90. 90.
    Lidgard D, Bowen W, Jonsen I, Iverson S. 2014. Predator-borne acoustic transceivers and GPS tracking reveal spatiotemporal patterns of encounters with acoustically tagged fish in the open ocean. Mar. Ecol. Prog. Ser. 501:157–68
     [Google Scholar]
  91. 91.
    Horning M, Mellish J-AE. 2009. Spatially explicit detection of predation on individual pinnipeds from implanted post-mortem satellite data transmitters. Endanger. Species Res. 10:135–43
     [Google Scholar]
  92. 92.
    Halfyard EA, Webber D, Del Papa J, Leadley T, Kessel S et al. 2017. Evaluation of an acoustic telemetry transmitter designed to identify predation events. Methods Ecol. Evol. 8:1063–71
     [Google Scholar]
  93. 93.
    Boulêtreau S, Carry L, Meyer E, Filloux D, Menchi O et al. 2020. High predation of native sea lamprey during spawning migration. Sci. Rep. 10:6122
     [Google Scholar]
  94. 94.
    Holland KN, Meyer CG, Dagorn LC. 2009. Inter-animal telemetry: results from first deployment of acoustic “business card” tags. Endanger. Species Res. 10:287–93
     [Google Scholar]
  95. 95.
    Lidgard DC, Bowen WD, Jonsen ID, Iverson SJ. 2012. Animal-borne acoustic transceivers reveal patterns of at-sea associations in an upper-trophic level predator. PLOS ONE 7:e48962
     [Google Scholar]
  96. 96.
    Barkley AN, Broell F, Pettitt-Wade H, Watanabe YY, Marcoux M, Hussey NE. 2020. A framework to estimate the likelihood of species interactions and behavioural responses using animal-borne acoustic telemetry transceivers and accelerometers. J. Anim. Ecol. 89:146–60
     [Google Scholar]
  97. 97.
    Papastamatiou YP, Mourier J, TinHan T, Luongo S, Hosoki S et al. 2022. Social dynamics and individual hunting tactics of white sharks revealed by biologging. Biol. Lett. 18:20210599
     [Google Scholar]
  98. 98.
    Lidgard DC, Bowen WD, Jonsen ID, McConnell BJ, Lovell P et al. 2014. Transmitting species-interaction data from animal-borne transceivers through Service Argos using Bluetooth communication. Methods Ecol. Evol. 5:864–71
     [Google Scholar]
  99. 99.
    Weimerskirch H, Bertrand S, Silva J, Marques JC, Goya E. 2010. Use of social information in seabirds: Compass rafts indicate the heading of food patches. PLOS ONE 5:e9928
     [Google Scholar]
  100. 100.
    Wakefield ED, Bodey TW, Bearhop S, Blackburn J, Colhoun K et al. 2013. Space partitioning without territoriality in gannets. Science 341:68–70
     [Google Scholar]
  101. 101.
    Jacoby DM, Papastamatiou YP, Freeman R. 2016. Inferring animal social networks and leadership: applications for passive monitoring arrays. J. R. Soc. Interface 13:20160676
     [Google Scholar]
  102. 102.
    Jones TB, Green JA, Patrick SC, Evans JC, Wells MR et al. 2020. Consistent sociality but flexible social associations across temporal and spatial foraging contexts in a colonial breeder. Ecol. Lett. 23:1085–96
     [Google Scholar]
  103. 103.
    Papastamatiou YP, Bodey TW, Caselle JE, Bradley D, Freeman R et al. 2020. Multiyear social stability and social information use in reef sharks with diel fission–fusion dynamics. Proc. R. Soc. B 287:20201063
     [Google Scholar]
  104. 104.
    Aspillaga E, Arlinghaus R, Martorell-Barceló M, Follana-Berná G, Lana A et al. 2021. Performance of a novel system for high-resolution tracking of marine fish societies. Anim. Biotelemetry 9:1
     [Google Scholar]
  105. 105.
    Aspillaga E, Arlinghaus R, Martorell-Barceló M, Barcelo-Serra M, Alós J 2021. High-throughput tracking of social networks in marine fish populations. Front. Mar. Sci. 8:688010
     [Google Scholar]
  106. 106.
    Fedak M. 2004. Marine animals as platforms for oceanographic sampling: a “win/win” situation for biology and operational oceanography. Mem. Natl. Inst. Polar Res. 58:133–47
     [Google Scholar]
  107. 107.
    Lydersen C, Nøst OA, Lovell P, McConnell BJ, Gammelsrød T et al. 2002. Salinity and temperature structure of a freezing Arctic fjord—monitored by white whales (Delphinapterus leucas). Geophys. Res. Lett. 29:2119
     [Google Scholar]
  108. 108.
    Charrassin J-B, Hindell M, Rintoul SR, Roquet F, Sokolov S et al. 2008. Southern Ocean frontal structure and sea-ice formation rates revealed by elephant seals. PNAS 105:11634–39
     [Google Scholar]
  109. 109.
    Roquet F, Wunsch C, Forget G, Heimbach P, Guinet C et al. 2013. Estimates of the Southern Ocean general circulation improved by animal-borne instruments. Geophys. Res. Lett. 40:6176–80
     [Google Scholar]
  110. 110.
    Ohshima KI, Fukamachi Y, Williams GD, Nihashi S, Roquet F et al. 2013. Antarctic Bottom Water production by intense sea-ice formation in the Cape Darnley polynya. Nat. Geosci. 6:235–40
     [Google Scholar]
  111. 111.
    Guinet C, Xing X, Walker E, Monestiez P, Marchand S et al. 2013. Calibration procedures and first dataset of Southern Ocean chlorophyll a profiles collected by elephant seals equipped with a newly developed CTD-fluorescence tags. Earth Syst. Sci. Data 5:15–29
     [Google Scholar]
  112. 112.
    Bailleul F, Vacquie-Garcia J, Guinet C. 2015. Dissolved oxygen sensor in animal-borne instruments: an innovation for monitoring the health of oceans and investigating the functioning of marine ecosystems. PLOS ONE 10:e0132681
     [Google Scholar]
  113. 113.
    McMahon CR, Roquet F, Baudel S, Belbeoch M, Bestley S et al. 2021. Animal Borne Ocean Sensors–AniBOS–an essential component of the Global Ocean Observing System (GOOS). Front. . Mar. Sci. 8:1625
     [Google Scholar]
  114. 114.
    Yoda K, Shiomi K, Sato K. 2014. Foraging spots of streaked shearwaters in relation to ocean surface currents as identified using their drift movements. Prog. Oceanogr. 122:54–64
     [Google Scholar]
  115. 115.
    Uesaka L, Goto Y, Yonehara Y, Komatsu K, Naruoka M et al. 2022. Ocean wave observation utilizing motion records of seabirds. Prog. Oceanogr. 200:102713
     [Google Scholar]
  116. 116.
    Yonehara Y, Goto Y, Yoda K, Watanuki Y, Young LC et al. 2016. Flight paths of seabirds soaring over the ocean surface enable measurement of fine-scale wind speed and direction. PNAS 113:9039–44
     [Google Scholar]
  117. 117.
    Miyazawa Y, Guo X, Varlamov SM, Miyama T, Yoda K et al. 2015. Assimilation of the seabird and ship drift data in the north-eastern sea of Japan into an operational ocean nowcast/forecast system. Sci. Rep. 5:17672
     [Google Scholar]
  118. 118.
    Weimerskirch H, Louzao M, de Grissac S, Delord K. 2012. Changes in wind pattern alter albatross distribution and life-history traits. Science 335:211–14
     [Google Scholar]
  119. 119.
    Watanabe YY, Ito K, Kokubun N, Takahashi A. 2020. Foraging behavior links sea ice to breeding success in Antarctic penguins. Sci. Adv. 6:eaba4828
     [Google Scholar]
  120. 120.
    Pagano A, Durner G, Rode K, Atwood T, Atkinson S et al. 2018. High-energy, high-fat lifestyle challenges an Arctic apex predator, the polar bear. Science 359:568–72
     [Google Scholar]
  121. 121.
    Hückstädt LA, Piñones A, Palacios DM, McDonald BI, Dinniman MS et al. 2020. Projected shifts in the foraging habitat of crabeater seals along the Antarctic Peninsula. Nat. Clim. Change 10:472–77
     [Google Scholar]
  122. 122.
    Hammerschlag N, McDonnell LH, Rider MJ, Street GM, Hazen EL et al. 2022. Ocean warming alters the distributional range, migratory timing, and spatial protections of an apex predator, the tiger shark (Galeocerdo cuvier). Glob. Change Biol. 28:1990–2005
     [Google Scholar]
  123. 123.
    Payne NL, Meyer CG, Smith JA, Houghton JD, Barnett A et al. 2018. Combining abundance and performance data reveals how temperature regulates coastal occurrences and activity of a roaming apex predator. Glob. Change Biol. 24:1884–93
     [Google Scholar]
  124. 124.
    Young HS, Maxwell SM, Conners MG, Shaffer SA. 2015. Pelagic marine protected areas protect foraging habitat for multiple breeding seabirds in the central Pacific. Biol. Conserv. 181:226–35
     [Google Scholar]
  125. 125.
    White TD, Carlisle AB, Kroodsma DA, Block BA, Casagrandi R et al. 2017. Assessing the effectiveness of a large marine protected area for reef shark conservation. Biol. Conserv. 207:64–71
     [Google Scholar]
  126. 126.
    Dwyer RG, Krueck NC, Udyawer V, Heupel MR, Chapman D et al. 2020. Individual and population benefits of marine reserves for reef sharks. Curr. Biol. 30:480–89.e5
     [Google Scholar]
  127. 127.
    van Zinnicq Bergmann MP, Guttridge TL, Smukall MJ, Adams VM, Bond ME et al. 2022. Using movement models and systematic conservation planning to inform marine protected area design for a multi-species predator community. Biol. Conserv. 266:109469
     [Google Scholar]
  128. 128.
    Bodey TW, Jessopp MJ, Votier SC, Gerritsen HD, Cleasby IR et al. 2014. Seabird movement reveals the ecological footprint of fishing vessels. Curr. Biol. 24:R514–R15
     [Google Scholar]
  129. 129.
    Maxwell SM, Hazen EL, Bograd SJ, Halpern BS, Breed GA et al. 2013. Cumulative human impacts on marine predators. Nat. Commun. 4:2688
     [Google Scholar]
  130. 130.
    Beal M, Dias MP, Phillips RA, Oppel S, Hazin C et al. 2021. Global political responsibility for the conservation of albatrosses and large petrels. Sci. Adv. 7:eabd7225
     [Google Scholar]
  131. 131.
    Queiroz N, Humphries NE, Couto A, Vedor M, Da Costa I et al. 2019. Global spatial risk assessment of sharks under the footprint of fisheries. Nature 572:461–66
     [Google Scholar]
  132. 132.
    Hindell MA, Reisinger RR, Ropert-Coudert Y, Hückstädt LA, Trathan PN et al. 2020. Tracking of marine predators to protect Southern Ocean ecosystems. Nature 580:87–92
     [Google Scholar]
  133. 133.
    Weimerskirch H, Collet J, Corbeau A, Pajot A, Hoarau F et al. 2020. Ocean sentinel albatrosses locate illegal vessels and provide the first estimate of the extent of nondeclared fishing. PNAS 117:3006–14
     [Google Scholar]
  134. 134.
    Hays GC, Bailey H, Bograd SJ, Bowen WD, Campagna C et al. 2019. Translating marine animal tracking data into conservation policy and management. Trends Ecol. Evol. 34:459–73
     [Google Scholar]
  135. 135.
    Goulet P, Guinet C, Swift R, Madsen PT, Johnson M. 2019. A miniature biomimetic sonar and movement tag to study the biotic environment and predator-prey interactions in aquatic animals. Deep Sea Res. I 148:1–11
     [Google Scholar]
  136. 136.
    Hussey NE, Orr J, Fisk AT, Hedges KJ, Ferguson SH, Barkley AN. 2018. Mark report satellite tags (mrPATs) to detail large-scale horizontal movements of deep water species: first results for the Greenland shark (Somniosus microcephalus). Deep Sea Res. I 134:32–40
     [Google Scholar]
  137. 137.
    Skubel RA, Wilson K, Papastamatiou YP, Verkamp HJ, Sulikowski JA et al. 2020. A scalable, satellite-transmitted data product for monitoring high-activity events in mobile aquatic animals. Anim. Biotelemetry 8:34
     [Google Scholar]
  138. 138.
    McDonald BI, Elmegaard SL, Johnson M, Wisniewska DM, Rojano-Doñate L et al. 2021. High heart rates in hunting harbour porpoises. Proc. R. Soc. B 288:20211596
     [Google Scholar]
  139. 139.
    Nathan R, Monk CT, Arlinghaus R, Adam T, Alós J et al. 2022. Big-data approaches lead to an increased understanding of the ecology of animal movement. Science 375:eabg1780
     [Google Scholar]
  140. 140.
    Sequeira AM, O'Toole M, Keates TR, McDonnell LH, Braun CD et al. 2021. A standardisation framework for bio-logging data to advance ecological research and conservation. Methods Ecol. Evol. 12:996–1007
     [Google Scholar]
  141. 141.
    Bodey TW, Cleasby IR, Bell F, Parr N, Schultz A et al. 2018. A phylogenetically controlled meta-analysis of biologging device effects on birds: deleterious effects and a call for more standardized reporting of study data. Methods Ecol. Evol. 9:946–55
     [Google Scholar]
  142. 142.
    Kay WP, Naumann DS, Bowen HJ, Withers SJ, Evans BJ et al. 2019. Minimizing the impact of biologging devices: using computational fluid dynamics for optimizing tag design and positioning. Methods Ecol. Evol. 10:1222–33
     [Google Scholar]
  143. 143.
    Bonfil R, Meÿer M, Scholl MC, Johnson R, O'Brien S et al. 2005. Transoceanic migration, spatial dynamics, and population linkages of white sharks. Science 310:100–3
     [Google Scholar]
  144. 144.
    Towner AV, Leos-Barajas V, Langrock R, Schick RS, Smale MJ et al. 2016. Sex-specific and individual preferences for hunting strategies in white sharks. Funct. Ecol. 30:1397–407
     [Google Scholar]
  145. 145.
    Watanabe YY, Payne NL, Semmens JM, Fox A, Huveneers C. 2019. Swimming strategies and energetics of endothermic white sharks during foraging. J. Exp. Biol. 222:jeb185603
     [Google Scholar]
  146. 146.
    Watanabe YY, Payne NL, Semmens JM, Fox A, Huveneers C. 2019. Hunting behaviour of white sharks recorded by animal-borne accelerometers and cameras. Mar. Ecol. Prog. Ser. 621:221–27
     [Google Scholar]
/content/journals/10.1146/annurev-animal-050322-073657
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Biologging and Biotelemetry: Tools for Understanding the Lives and Environments of Marine Animals
Annual Review of Animal Biosciences 11, 247 (2023); https://doi.org/10.1146/annurev-animal-050322-073657
/content/journals/10.1146/annurev-animal-050322-073657
/content/journals/10.1146/annurev-animal-050322-073657
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