One of the barrel jelly's search-optimizing behaviors, often referred to as a "bounce," occurs when the jellyfish starts out in one depth of water and then makes a long glide either upwards or downwards to a different depth of water. If it doesn't find a meal in the new location, the jellyfish will "bounce" again to return to its original position.
Some scientists believe that the jelly's tendency to bounce around in the water may actually hinder its ability to search for food, but according to Reynolds, these unusual animals have had it right all along.
The jellyfish, which will sometimes repeat its pattern of bounces dozens of times a day, uses this strategy to slowly home in on the highest concentrations of plankton, Reynolds explained.
The behavior therefore makes the barrel jelly even more efficient than other marine animals, such as penguins and sharks, that only use Lévy walks to search for prey, Reynolds said.
If the barrel jelly's unusual way of searching for food really is the best way to do it, then why aren't other marine species using the same strategy?
The answer has to do with diet, Reynolds said. The barrel jellyfish benefits from spending long periods of time searching for concentrations of prey because it needs to eat a lot of plankton before it is satisfied, Reynolds said. This is different from sharks and penguins, which Reynolds said can survive by eating the occasional fish.
"A Lévy search is highly effective in finding the next meal, when any meal will do. Fast simulated annealing, on the other hand, takes the forager to the best possible meal," Reynolds said. "This is what makes jellyfish special — they are very discerning diners, unlike bony fish, penguins, turtles and sharks, which are just looking for any meal."
This high level of discernment is also what draws certain mathematicians and engineers to the strategy of fast simulated annealing for supercomputing, Reynolds said.
Based on mathematical and computer models, Reynolds' study found that like barrel jellyfish, mathematicians tend to implement this strategy only when they're looking for the best possible solution to a problem, not a variety of potential solutions.
The new study was published online today (Aug. 5) in the Journal of the Royal Society Interface.
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