Google’s Internet Techniques Inspire Studies of Food Webs
A major reason Google’s search engine is so successful is its PageRank algorithm, which assigns a pecking order to Web pages based on the pages that point to them. A page is important, according to Google, if other important pages link to it.
But the Internet is not the only web around. In ecology, for instance, there are food webs — the often complex networks of who eats whom.
Inspired by PageRank, Stefano Allesina of the University of Chicago and Mercedes Pascual of the University of Michigan have devised an algorithm of their own for the relationships in a food web. As described in the online open-access journal PLoS Computational Biology, the algorithm uses the links between species in a food web to determine the relative importance of species in a food web, which will have the most impact if they become extinct.
Dr. Allesina, who studies network theory and biology, was reading a paper about Google’s algorithm one day while at the University of California, Santa Barbara. “I said, ‘This reminds me of something,’ ” he recalled.
One key to PageRank’s success is that its developers introduced a small probability that a Web user would jump from one page to any other. This in effect makes the Web circular, and makes the algorithm solvable. But in food webs, Dr. Allesina said, “you can’t go from the grass to the lion — the grass has to go through the gazelle first.
“We could not use the same trick to make food webs circular,” he went on.
So they used another trick, he said. Since all organisms die and decompose, they created a “detritus pool” that all species link to. The pool also links to primary producers in a food web, which make use of the decomposed matter.
Their algorithm differs also in that it determines the relative importance of species through reverse engineering — by seeing which species make the food web collapse fastest if they are removed. The researchers found that the algorithm produces results that were as accurate as much more complex (and computationally costly) software that builds webs from the ground up, simulating evolution.
The next step, Dr. Allesina said, is to refine the algorithm so that it will work with more complex webs. There are many other factors that affect extinctions, including pollution and habitat loss. The goal is to create an algorithm that can take these and other elements into account as well.
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