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 http://www.nature.com/index.html
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).

