Population Ecology

, Volume 46, Issue 1, pp 39–53

Analysis of foraging movements of Atlantic bluefin tuna (Thunnus thynnus): individuals switch between two modes of search behaviour

  • Nathaniel K. Newlands
  • Molly E. Lutcavage
  • Tony J. Pitcher
Original Article

Abstract

We investigate the application of quantitative techniques for distinguishing adaptive search behaviour in Atlantic bluefin tuna (Thunnus thynnus). The analysis demonstrates the application of a novel spectral analysis technique for resolving and measuring periodicity in animal behaviour patterns. Two different search strategies are identified that include regulation of turning (klinokinesis) and speed (orthokinesis). Our results provide evidence that bluefin tuna attempt to optimize their searching efficiency through adjustments in the duration and timing of switching between these two searching strategies. Repetitive, diurnal deep dives were also found to coincide with switching of search behaviour. Additional tracking experiments with larger sample sizes are needed to better identify how individuals switch between the two search strategies and how such decisions may collectively improve the searching and foraging efficiency of their schools (synchrokinesis, social taxis) in response to changes in the size or composition of prey aggregations.

Keywords

Klinokinesis Non-stationary Orthokinesis Search behaviour Spectral method 

References

  1. Adler FR, Kotar M (1999) Departure times versus departure rate: how to forage optimally when you are stupid. Evol Ecol Res 1:411–421Google Scholar
  2. Alt W (1995) Elements of a systematic search in animal behaviour and model simulations. BioSystems 34:11–26CrossRefPubMedGoogle Scholar
  3. Anholt BR, Ludwig D, Rasmussen JB (1987) Optimal pursuit times: how long should predators pursue their prey? Theor Popul Biol 31:453–464Google Scholar
  4. Arnold CR, Carter GC, Ferrie JR (1979) A coherence and cross-spectral estimation program. In: Digital Signal Processing Committee of the IEEE Acoustics, Speech and Signal Processing (ASSP) Society (eds) Programs for digital signal processing. IEEE Press, New YorkGoogle Scholar
  5. Belovsky GE, Ritchie ME, Moorehead J (1989) Foraging in complex environments: when prey availability varies over time and space. Theor Popul Biol 36:144–160Google Scholar
  6. Bell WJ (1991) Searching behaviour: the behavioural ecology of finding resources. Chapman and Hall, LondonGoogle Scholar
  7. Bengtsson G, Nilsson E, Rydén T, Öhrn MA, Wiktorsson M (2002) Statistical analysis of the influence of conspecifics on the dispersal of a soil Collembola. Theor Popul Biol 61:97–113. DOI 10.1006/tpbi.2001.1564CrossRefPubMedGoogle Scholar
  8. Benhamou S (1992) Efficiency of area-concentrated searching behaviour in a continuous patchy environment. J Theor Biol 159:67–81Google Scholar
  9. Benhamou S, Bovet P (1989) How animals use their environment: a new look at kinesis. Anim Behav 38:375–383Google Scholar
  10. Benhamou S, Bovet P (1992) Distinguishing elementary orientation mechanisms by means of path analysis. Anim Behav 43:371–377Google Scholar
  11. Berec L (2002) Techniques of spatially explicit individual-based models: construction, simulation, and mean-field analysis. Ecol Modell 150:55–81CrossRefGoogle Scholar
  12. Bergman CM, Schaefer JA, Luttich SN (2000) Caribou movement as a correlated random walk. Oecologia 123:364–374CrossRefGoogle Scholar
  13. Bernstein C, Kacelnik A, Krebs JR (1988) Individual decisions and the distribution of predators in a patchy environment. J Anim Ecol 57:1007–1026Google Scholar
  14. Bernstein C, Kacelnik A, Krebs JR (1991) Individual decision and the distribution of predators in a patchy environment. II. The influence of travel costs and structure of the environment. J Anim Ecol 60:205–225Google Scholar
  15. Blake RW, Chatters LM, Domenici P (1995) Turning radius of yellowfin tuna (Thunnus albacares) in unsteady swimming manoeuvres. J Fish Biol 46:536–538Google Scholar
  16. Blanché S, Casas J, Bigler F, Janssen-van Bergeijk K (1996) An individual-based model of Trichogramma foraging behaviour: parameter estimation of single females. J Appl Ecol 33:425–434Google Scholar
  17. Block BA, Dewar H, Blackwell SB, Williams TD, Prince ED, Farwell CJ, Boustany A, Teo SLH, Seitz A, Walli A, Fudge D (2001) Migratory movements, depth preferences, and thermal biology of Atlantic bluefin tuna. Science 293:1310–1314CrossRefPubMedGoogle Scholar
  18. Bonsall MB, French DR, Hassell MP (2002) Metapopulation structures affect persistence of predator-prey interactions. J Anim Ecol 71:1075–1084CrossRefGoogle Scholar
  19. Boyd IL (1996) Temporal scales of foraging in a marine predator. Ecology 77:426–434Google Scholar
  20. Brill RW (1994) A review of temperature and oxygen tolerance studies of tunas pertinent to fisheries oceanography, movement models and stock assessments. Fish Oceanogr 3:204–216Google Scholar
  21. Brill RW, Block BA, Boggs CH, Bigelow KA, Freund EV, Marcinek DJ (1999) Horizontal movements, depth distribution, and the physical environment of large adult yellowfin tuna (Thunnus albacares) near the Hawaiian Islands recorded using ultrasonic telemetry, with implications for the physiological ecology. Mar Biol 133:395–408. DOI 10.1007/s002270050478CrossRefGoogle Scholar
  22. Brill R, Lutcavage M, Metzger G, Bushnell P, Arendt M, Lucy J, Watson C, Foley D (2002) Horizontal and vertical movement of juvenile bluefin tuna (Thunnus thynnus) in relation to oceanographic conditions of the western North Atlantic, determined with ultrasonic telemetry. Fish Bull 100:155–167Google Scholar
  23. Brillinger DR, Preisler HK, Ager AA, Kie JG (2003) An exploratory data analysis (EDA) of the paths of moving animals. J Stat Plann Infer (in press). DOI 10.1016/j.jspi.2003.06.016Google Scholar
  24. Brown JS (1988) Patch use as an indicator of habitat preference, predation risk and competition. Behav Ecol Sociobiol 22:37–47Google Scholar
  25. Cayré P, Marsac F (1993) Modeling the yellowfin tuna (Thunnus albacares) vertical distribution using sonic tagging results and local environmental parameters. Aquat Living Resour 6:1–14Google Scholar
  26. Charnov EL (1976) Optimal foraging, the Marginal Value Theorem. Theor Popul Biol 9:129–136PubMedGoogle Scholar
  27. Chase B (2002) Differences in the diet of Atlantic bluefin tuna (Thunnus thynnus) at five seasonal feeding grounds on the New England continental shelf. Fish Bull 100:168–180Google Scholar
  28. Crane J (1936) Notes on the biology and ecology of giant tuna, Thunnus thynnus Linnaeus, observed at Portland, Maine. Zool Sci Contrib NY Zool Soc 21:207–211Google Scholar
  29. Crowder LB (1985) Optimal foraging and feeding mode shifts in fishes. Environ Biol Fish 12:57–62Google Scholar
  30. Dagorn L, Menczer F, Bach P, Olson, RJ (2000a) Co-evolution of movement behaviours by tropical pelagic predatory fishes in response to prey environment: a simulation model. Ecol Modell 134:325–341CrossRefGoogle Scholar
  31. Dagorn L, Bach P, Josse E (2000b) Movement patterns of large bigeye tuna (Thunnus obesus) in the open ocean, determined from ultrasonic telemetry. Mar Biol 136:361–371CrossRefGoogle Scholar
  32. Davis TLO, Stanley CA (2002) Vertical and horizontal movements of southern bluefin tuna (Thunnus maccoyii) in the Great Australian Bight observed with ultrasonic telemetry. Fish Bull 100:448–465Google Scholar
  33. Dill LM (1983) Adaptive flexibility in the foraging behaviour of fishes. Can J Fish Aquat Sci 40:398–408Google Scholar
  34. Domenici P (2001) The scaling of locomotor performance in predator-prey encounters: from fish to killer whales. Comp Biochem Physiol A 131:169–182CrossRefGoogle Scholar
  35. Dusenbury DB (1989) Ranging strategies. J Theor Biol 136:317–326Google Scholar
  36. Emery WJ, Thomson RE (2001) Data analysis methods in physical oceanography, 2nd and revised edn. Elsevier, New YorkGoogle Scholar
  37. Farnsworth KD, Beecham JA (1999) How do grazers achieve their distribution? A continuum of models from random diffusion to the ideal free distribution using biased random walks. Am Nat 153:509–526CrossRefGoogle Scholar
  38. Forrest TG, Suter RB (1994) The discrete Fourier transform (DFT) in behavioural analysis. J Theor Biol 166:419–429CrossRefGoogle Scholar
  39. Grünbaum D (1999) Advection-diffusion equations for generalized tactic searching behaviors. J Math Biol 38:169–194CrossRefGoogle Scholar
  40. Higgins CL, Strauss RE (2004) Discrimination and classification of search paths produced by different search-tactic models. Behav Ecol (in press)Google Scholar
  41. Hilborn R (1991) Modeling the stability of fish schools: exchange of individual fish between schools of skipjack tuna (Katsuwonus pelamis). Can J Fish Aquat Sci 48:1081–1091Google Scholar
  42. Holland KN, Brill RW, Chang RKC (1990) Horizontal and vertical of yellowfin and bigeye tuna associated with fish aggregation devices. Fish Bull 88:493–507Google Scholar
  43. Hugie DM, Grand TC (1998) Movement between patches, unequal competitors and the ideal free distribution. Evol Ecol 12:1–19Google Scholar
  44. Hugie DM, Grand TC (2002) Movements between habitats of unequal competitors: effects of finite population size on ideal free distributions. Evol Ecol 12:1–19CrossRefGoogle Scholar
  45. Humston R, Ault J, Lutcavage M, Olson D (2000) Schooling and migration of large pelagic fishes relative to environmental cues. Fish Oceanogr 9:136–146CrossRefGoogle Scholar
  46. Itoh T, Tsuji S, Nitta, A (2003) Swimming depth, water temperature preference and feeding frequency of young Pacific bluefin tuna (Thunnus orientalis) determined with archival tags. Fish Bull 101:535–544Google Scholar
  47. Josse E, Bach P, Dagorn L (1998) Simultaneous observations of tuna movements and their prey by sonic tracking and acoustic surveys. Hydrobiologia 371/372:61–69Google Scholar
  48. Kantz H, Schreiber T (1997) Nonlinear time series analysis. Cambridge Nonlinear Science Series, Cambridge University Press, CambridgeGoogle Scholar
  49. Karieva P, Odell G (1987) Swarms of predators exhibit ‘preytaxis’ if individual predators use area-restricted search. Am Nat 130:233–270CrossRefGoogle Scholar
  50. Kils U (1986) Verhaltensphysiologische Untersuchungen an pelagischen Schwärmen, Schwarmbildung als Strategie zur Orientierung in Umweltgradienten, Bedeutung der Schwarmbildung in der Aquakultur. Ber Inst Meereskd Kiel 163:1–168Google Scholar
  51. Kirby D (2002) A dynamic optimisation model for the behaviour of tuna at ocean fronts. Fish Oceanogr 9:328–342. DOI 10.1046/j.1365–2419.2000.00144.xCrossRefGoogle Scholar
  52. Kitagawa T, Nagata H, Kimura S, Itoh T, Tsuji S, Nitta A (2000) Effect of ambient temperature on the vertical distribution and movement of Pacific bluefin tuna Thunnus thynnus orientalis. Mar Ecol Prog Ser 206:251–260Google Scholar
  53. Kitagawa T, Nagata H, Kimura S, Itoh T, Tsuji S, Nitta A (2001) Thermoconservation mechanisms inferred from peritoneal cavity temperature in free-swimming Pacific bluefin tuna Thunnus thynnus orientalis. Mar Ecol Prog Ser 220:253–263Google Scholar
  54. Klimley AP, Holloway CF (1999) School fidelity and homing synchronicity of yellowfin tuna, Thunnus albacares. Mar Biol 133:307–317CrossRefGoogle Scholar
  55. Knoppien P, Reddinguis J (1985) Predators with two modes of searching: a mathematical model. J Theor Biol 114:273–301Google Scholar
  56. Krishnamachari KR, Yantorno RE (2000) Spectral autocorrelation ratio as a usability measure of speech segments under co-channel conditions. IEEE International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2000Google Scholar
  57. Laguna P, Moody GB, Mark RG (1998) Power spectral density of unevenly sampled data by least-squares analysis: performance and application to heart-rate signals. IEEE Trans Biomed Eng 45:698–715CrossRefPubMedGoogle Scholar
  58. Lima SL (2002) Putting predators back into behavioral predator-prey interactions. Trends Ecol Evol 17:70–75Google Scholar
  59. Lindner B, Schimansky-Geier L, Longtin A (2002) Maximizing spike train coherence and incoherence in the leaky integrate-and-fire model. Phys Rev E 66:031916. DOI: 10.1103/PhysRevE.66.031916Google Scholar
  60. Lomb NR (1976) Least-squares frequency analysis of unequally spaced data. Astrophys Space Sci 39:447–462Google Scholar
  61. Lutcavage M, Kraus S (1995) The feasibility of direct photographic assessment of giant bluefin tuna in New England waters. Fish Bull 93:495–503Google Scholar
  62. Lutcavage M, Golstein J, Kraus S (1997) Distribution, relative abundance and behaviour of giant bluefin tuna in New England waters, 1995. Coll Sci Pap Int Comm Conserv Atl XLVI(2):332–347Google Scholar
  63. Lutcavage ME, Brill RW, Skomal GB, Chase BC, Goldstein JL, Tutein J (2000) Tracking adult North Atlantic bluefin tuna (Thunnus thynnus) in the northwestern Atlantic using ultrasonic telemetry. Mar Biol 137:347–358CrossRefGoogle Scholar
  64. Magnuson JJ (1973) Comparative study of adaptations for continuous swimming and hydrostatic equilibrium of scombroid and xiphoid fishes. Fish Bull 71:337–354Google Scholar
  65. Mangel M, Clark CW (1986) Towards a unified foraging theory. Ecology 67:1127–1138Google Scholar
  66. Marcinek DJ, Blackwell SB, Dewar H, Freund EV, Farwell C, Dau D, Seitz AC, Block BA (2001) Depth and muscle temperature of Pacific bluefin tuna examined with acoustic and pop-up satellite tags. Mar Biol 138:869–885CrossRefGoogle Scholar
  67. Mather FJ, Mason JM, Jones AC (1995) Historical document: life history and fisheries of Atlantic bluefin tuna. US Department of Commerce, NOAA Tech Memo NMFS-SEFSC 370, p 165Google Scholar
  68. Matz G, Hlawatsch F (2000) Time-frequency coherence analysis of nonstationary random processes Proc. IEEE-SP Workshop on Statistical Signal and Array Proc., Pocono Manor, Pa., pp 554–558Google Scholar
  69. Morales JM, Ellner SP (2002) Scaling up animal movements in heterogeneous landscapes: the importance of behaviour. Ecology 83:2240–2247Google Scholar
  70. Musyl MK, Brill RW, Boggs CH, Curran DS, Kazama TK, Seki MP (2003) Vertical movements of bigeye tuna (Thunnus obesus) associated with islands, buoys, and seamounts near the main Hawaiian Islands from archival tagging data. Fish Oceanogr 12:1–18. DOI 10.1046/j1365–2419.2003.00229.xCrossRefGoogle Scholar
  71. Newlands NK (2002) Shoaling dynamics and abundance estimation: Atlantic bluefin tuna (Thunnus thynnus). PhD thesis, University of British ColumbiaGoogle Scholar
  72. Newlands N, Lutcavage M (2001) From individuals to local population densities: movements of North Atlantic bluefin tuna (Thunnus thynnus) in the Gulf of Maine/Northwestern Atlantic. In: Sibert JR, Nielsen JL (eds) Electronic tagging and tracking in marine fisheries. Kluwer, Dordrecht, pp 421–441Google Scholar
  73. Niwa H-S (1996) Mathematical model for the size distribution of fish schools. Comput Math Appl 32:79–88CrossRefGoogle Scholar
  74. Nossal R, Weiss GH (1974) A descriptive theory of cell migration on surfaces. J Theor Biol 47:103–113PubMedGoogle Scholar
  75. Partridge BL, Johansson J, Kalish J (1983) The structure of schools of giant bluefin tuna in Cape Cod Bay. Environ Biol Fish 9:253–262Google Scholar
  76. Pitcher TJ, Parrish JK (1993) Functions of shoaling behaviour in teleosts: In: Pitcher TJ (ed) Behaviour of teleost fishes. Chapman and Hall, London, pp 363–439Google Scholar
  77. Press WH, Teukolsky SA, Vetterling WT, Flannery BP (1999) Numerical recipes in C: the art of scientific computing, 2nd edn. Cambridge University Press, New YorkGoogle Scholar
  78. Rands SA, Cowlishaw G, Pettifor RA, Rowcliffe GA, Johnstone RA (2003) Spontaneous emergence of leaders and followers in foraging pairs. Nature 423:423–434CrossRefGoogle Scholar
  79. Rose GA, Leggett WC (1990) The importance of scale to predator-prey spatial correlations: an example of Atlantic fishes. Ecology 71:33–43Google Scholar
  80. Royer F, Fromentin JM, Gaspar P (2004) Association between bluefin tuna schools and oceanic features in the western Mediterranean. Mar Ecol Prog Ser (in press)Google Scholar
  81. Ruxton GD, Humphries S (1999) Multiple ideal free distributions of unequal competitors. Evol Ecol Res 1:635–640Google Scholar
  82. Ruxton GD, Humphries S (2002) Non-IDF movements: reflections on past work and prospects for future developments. Evol Ecol Res 5:155–157Google Scholar
  83. Sanuy D, Bovet P (1997) A comparative study on the paths of five anura species. Behav Proc 41:193–199CrossRefGoogle Scholar
  84. Scargle JD (1982) Studies in astronomical time series analysis. II. Statistical aspects of spectral analysis of unevenly spaced data. Astrophys J 263:835–853CrossRefGoogle Scholar
  85. Scargle JD (1989) Studies in astronomical time series analysis. III. Fourier transforms, autocorrelation functions, and cross-correlation functions of unevenly spaced data. Astrophys J 343:874–887CrossRefGoogle Scholar
  86. Schaefer KM, Fuller DW (2002) Movements, behaviour, and habitat selection of bigeye tuna (Thunnus obesus) in the eastern equatorial Pacific, ascertained through archival tags. Fish Bull 100:765–788Google Scholar
  87. Schick RS, Goldstein J, Lutcavage ME (2004) Bluefin tuna (Thunnus thynnus) distribution in relation to sea surface temperature fronts in the Gulf of Maine (1994–1996). Fish Oceanogr (in press)Google Scholar
  88. Stephens DW, Krebs JR (1986) Foraging theory. Princeton University Press, Princeton, N.Y.Google Scholar
  89. Tourtellot MK, Collins RD, Bell WJ (1991) The problem of move length and turn definition in analysis of orientation data. J Theor Biol 150:287–297PubMedGoogle Scholar
  90. Vaz Nunes M, Moorhouse JE (1992) Locust marching. A mathematical model. J Theor Biol 154:137–161Google Scholar
  91. Videler JJ, Weihs D (1982) Energetic advantages of burst-and-coast swimming of fish at high speeds. J Exp Biol 97:169–178PubMedGoogle Scholar
  92. Viswanathan GM, Buldyrev SV, Havlin S, da Luz MGE, Raposa EP, Stanley HE (1999) Optimizing the success of random searches. Nature 401:911–914CrossRefPubMedGoogle Scholar
  93. Ward D, Saltz D (1994) Foraging at different spatial scales: Dorcas Gazelles foraging for lilies in the Negev desert. Ecology 75:48–58Google Scholar
  94. Wardle CS, Videler JJ, Arimoto T, Franco JM, He P (1989) The muscle twitch and the maximum swimming speed of giant bluefin tuna, Thunnus thynnus L. J Fish Biol 35:129–37Google Scholar
  95. Weihs D (1973) Mechanically efficient swimming techniques for fish with negative buoyancy. J Mar Res 31:194–209Google Scholar
  96. Weihs D (1974) Energetic advantages of burst swimming in fish. J Theor Biol 48:215–229PubMedGoogle Scholar
  97. Williams B (1992) The measurement of ‘sinuosity’ in correlated random walks. J Theor Biol 155:437–442Google Scholar
  98. With KA (1994) Ontogenetic shifts in how grasshoppers interact with landscape structure: an analysis of movement patterns. Funct Ecol 8:477–485Google Scholar
  99. Yoccoz NG, Engen S, Stenseth NC (1993) Optimal foraging: the importance of environmental stochasticity and accuracy in parameter estimation. Am Nat 141:139–157CrossRefGoogle Scholar
  100. Yuen HSH (1970) Behaviour of skipjack tuna, Katsuwonus pelamis, as determined by tracking with ultrasonic devices. J Fish Res Bd Can 27:2071–2079Google Scholar
  101. Zollner PA, Lima SL (1999) Search strategies for landscape-level interpatch movements. Ecology 80:1019–1030Google Scholar

Copyright information

© The Society of Population Ecology and Springer-Verlag Tokyo 2004

Authors and Affiliations

  • Nathaniel K. Newlands
    • 1
  • Molly E. Lutcavage
    • 2
  • Tony J. Pitcher
    • 3
  1. 1.Department of MathematicsUniversity of British ColumbiaVancouverCanada
  2. 2.Department of ZoologyUniversity of New HampshireDurhamUSA
  3. 3.Fisheries CentreUniversity of British ColumbiaVancouverCanada

Personalised recommendations