Hungry sharks take strange walks to find food

Sharks and other marine animals find food using a similar search pattern to the way people may shop, according to one of the largest analyses of foraging behaviour attempted so far - and the first such analysis of marine predators.   The results of the international study, published in the journal Nature today, shows that the animals' behaviour seems to have evolved as a general 'rule' to search for sparsely distributed prey in the vast
expanse of the ocean.  This rule involves a special pattern of random movement known as a Levy Walk, where the predators use a series of small motions interspersed with large jumps to new foraging locations. This increases the chance of finding food, however widely scattered it might be.       

Dr David Sims from the Marine Biological Association and the University of Plymouth, who led the research, said, 'Systematic searching is not the most efficient strategy if you're looking for sparse items. If you go to the supermarket to buy eggs you look for them in one place, and if you don't find them there you choose another location to look in. You probably won't start at one end of the supermarket and search every aisle. Predators increase energy gain by adopting the Levy Walk, so they can travel further to find food.'

The researchers analysed the dive data from sophisticated electronictags attached to a diverse range of marine predators, such as sharks, tuna, cod, sea turtles and penguins, in various locations around the
world. They compared this data to the distribution patterns of their prey and found similarities, suggesting that the predators have evolved this search rule to get the best possible results from their foraging expeditions.

Dr Sims said, 'We developed a computer model from the foraging data, and this confirmed that the observed patterns were indeed optimal for naturally dynamic prey fields. The search rule seems to be a general solution for success in complex and changeable environments.' 

Similar movement patterns appear to be present in other species' behaviour, including human travel dynamics, hinting that the patterns discovered by the team may be universal.  If so, they could prove useful
for programming robots to be more successful when collecting samples from inhospitable places such as active volcanoes, the deep sea or on other planets.  Understanding the patterns could also shed new light on
how early humans explored and colonised the continents.

The research involved an international collaboration of behavioural ecologists, mathematicians and  engineers from the UK, USA, Australia and New Zealand.  It was funded principally by the Natural Environment Research Council, Defra, the Royal Society and the Fisheries Society of the British Isles.

Further information
1.    Scaling laws of marine predator search behaviour is published in Nature on 28 February 2008

2.    The authors of the paper are:

David W. Sims1,2, Emily J. Southall1, Nicolas E. Humphries1, Graeme C. Hays3, Corey J.A. Bradshaw4, Jonathan W. Pitchford5, Alex James5,6, Mohammed Z. Ahmed7, Andrew S. Brierley8, Mark A. Hindell9, David
Morritt10, Michael K. Musyl11, David Righton12, Emily L.C. Shepard3, Victoria J. Wearmouth1, Rory P. Wilson3, Matthew J. Witt13, Julian D. Metcalfe12

1Marine Biological Association of the United Kingdom, The Laboratory, Citadel Hill, Plymouth PL1 2PB, UK; 2Marine Biology and Ecology Research Centre, School of Biological Sciences, University of Plymouth, Drake
Circus, Plymouth PL4 8AA, UK; 3Department of Biological Sciences, Institute of Environmental Sustainability, Swansea University, Singleton Park, Swansea SA2 8PP, UK; 4School for Environmental Research, Charles
Darwin University, Darwin, Northern Territory 0909, Australia; 5Department of Biology and York Centre for Complex Systems Analysis, University of York, York YO10 5YW, UK; 6Department of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand; 7School of Computing, Communications and Electronics, University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK; 8Gatty Marine Laboratory, School of
Biology, University of St Andrews, Fife KY16 8LB, UK; 9School of Zoology, University of Tasmania, Private Bag 05, Hobart, Tasmania 7001, Australia; 10School of Biological Sciences, Royal Holloway, University of London, Egham TW20 0EX, UK; 11Joint 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 HI 96814, USA; 12Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory, Pakefield Road, Lowestoft NR33 0HT, UK; 13Centre for Ecology and Conservation, University of Exeter in Cornwall, Tremough TR10 9EZ, UK
3.    This research was facilitated through the European Tracking of Predators in the Atlantic (EUTOPIA) programme in the European Census of Marine Life (EuroCoML).

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