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Scaling laws of marine predator search behaviour

Nature volume 451, pages 1098–1102 (2008)Cite this article

Abstract

Many free-ranging predators have to make foraging decisions with little, if any, knowledge of present resource distribution and availability1. The optimal search strategy they should use to maximize encounter rates with prey in heterogeneous natural environments remains a largely unresolved issue in ecology1,2,3. Lévy walks4 are specialized random walks giving rise to fractal movement trajectories that may represent an optimal solution for searching complex landscapes5. However, the adaptive significance of this putative strategy in response to natural prey distributions remains untested6,7. Here we analyse over a million movement displacements recorded from animal-attached electronic tags to show that diverse marine predators—sharks, bony fishes, sea turtles and penguins—exhibit Lévy-walk-like behaviour close to a theoretical optimum2. Prey density distributions also display Lévy-like fractal patterns, suggesting response movements by predators to prey distributions. Simulations show that predators have higher encounter rates when adopting Lévy-type foraging in natural-like prey fields compared with purely random landscapes. This is consistent with the hypothesis that observed search patterns are adapted to observed statistical patterns of the landscape. This may explain why Lévy-like behaviour seems to be widespread among diverse organisms3, from microbes8 to humans9, as a ‘rule’ that evolved in response to patchy resource distributions.

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Figure 1: Lévy-like scaling law among diverse marine vertebrates.
Figure 2: Macroscopic properties of a prey field.

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Acknowledgements

This research was facilitated through the European Tracking of Predators in the Atlantic (EUTOPIA) programme in the European Census of Marine Life (EuroCoML). Funding was provided by the UK Natural Environment Research Council (NERC) grant-in-aid to the Marine Biological Association of the UK (MBA), the NERC ‘Oceans 2025’ Strategic Research Programme (Theme 6 Science for Sustainable Marine Resources), UK Defra, The Royal Society and the Fisheries Society of the British Isles. D.W.S. thanks G. Budd, P. Harris, N. Hutchinson and D. Uren for field assistance. G.C.H. thanks Ocean Spirits Incorporated, J. Houghton and A. Myers for logistical help in the field. A.S.B. thanks E. Murphy, M. Brandon, R. Saunders, D. Bone and P. Enderlein for their contributions to mooring sampling at South Georgia. NERC Plymouth Marine Laboratory provided L4 zooplankton data. This research complied with all animal welfare laws of the countries or sovereign territories in which it was conducted. D.W.S. was supported by a NERC-funded MBA Research Fellowship.

Author Contributions D.W.S. conceived and planned the study, led the data analysis and wrote the manuscript. All co-authors contributed to subsequent drafts. Field data of animal movements and/or prey distributions were collected by D.W.S., E.J.S., J.D.M., G.C.H., C.J.A.B., A.S.B., M.A.H., D.M., M.K.M., D.R., V.J.W. and R.P.W. The simulation model was conceived by N.E.H. and D.W.S. with N.E.H. writing the programming code. J.W.P. and A.J. were responsible for analysis of projections of 3D Lévy movements, M.Z.A. and E.L.C.S. coded the power spectrum analysis, C.J.A.B. completed the relative likelihood modelling, and G.C.H. and M.J.W. provided additional data analysis.

Author information

Author notes

  1. Corey J. A. Bradshaw

    Present address: Present address: Research Institute for Climate Change and Sustainability, School of Earth and Environmental Sciences, University of Adelaide, Adelaide, South Australia 5005, Australia.,

Affiliations

  1. Marine Biological Association of the United Kingdom, The Laboratory, Citadel Hill, Plymouth PL1 2PB, UK

    David W. Sims, Emily J. Southall, Nicolas E. Humphries & Victoria J. Wearmouth

  2. Marine Biology and Ecology Research Centre, School of Biological Sciences,

    David W. Sims

  3. School of Computing, Communications and Electronics, University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK

    Mohammed Z. Ahmed

  4. Department of Biological Sciences, Institute of Environmental Sustainability, Swansea University, Singleton Park, Swansea SA2 8PP, UK

    Graeme C. Hays, Emily L. C. Shepard & Rory P. Wilson

  5. School for Environmental Research, Charles Darwin University, Darwin, Northern Territory 0909, Australia

    Corey J. A. Bradshaw

  6. Department of Biology and York Centre for Complex Systems Analysis, University of York, York YO10 5YW, UK

    Jonathan W. Pitchford & Alex James

  7. Department of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand

    Alex James

  8. Gatty Marine Laboratory, School of Biology, University of St Andrews, Fife KY16 8LB, UK

    Andrew S. Brierley

  9. School of Zoology, University of Tasmania, Private Bag 05, Hobart, Tasmania 7001, Australia

    Mark A. Hindell

  10. School of Biological Sciences, Royal Holloway, University of London, Egham TW20 0EX, UK

    David Morritt

  11. Joint Institute for Marine and Atmospheric Research, Pelagic Fisheries Research Programme, University of Hawaii at Manoa, Kewalo Research Facility/NOAA Fisheries, 1125-B Ala Mona Boulevard, Honolulu, Hawaii 96814, USA

    Michael K. Musyl

  12. Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory, Pakefield Road, Lowestoft NR33 0HT, UK

    David Righton & Julian D. Metcalfe

  13. Centre for Ecology and Conservation, University of Exeter in Cornwall, Tremough TR10 9EZ, UK

    Matthew J. Witt

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  1. David W. Sims
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Correspondence to David W. Sims.

Supplementary information

Supplementary Information

The file contains Supplementary Figures S1- S3 with Legends and additional references. (PDF 1323 kb)

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Sims, D., Southall, E., Humphries, N. et al. Scaling laws of marine predator search behaviour. Nature 451, 1098–1102 (2008). https://doi.org/10.1038/nature06518

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