Google's algorithm for ranking web pages can be adapted to determine which species are critical for sustaining ecosystems, say researchers.
According to a paper in PLoS Computational Biology, "PageRank" can be applied to the study of food webs. These are the complex networks of who eats whom in an ecosystem. The scientists say their version of PageRank could be a simple way of working out which extinctions would lead to ecosystem collapse. Every species is embedded in a complex network of relationships with others. So a single extinction can cascade into the loss of seemingly unrelated species.
Investigating when this might happen using more conventional methods is complicated as even in simple ecosystems, the number of combinations exceeds the number of atoms in the universe. So it would be impossible to try them all.
Co-author Dr Stefano Allesina realised he could apply PageRank to the problem when he stumbled across an article in a journal of applied mathematics describing the Google algorithm.
More: http://news.bbc.co.uk/1/hi/sci/tech/8238462.stm
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According to a paper in PLoS Computational Biology, "PageRank" can be applied to the study of food webs. These are the complex networks of who eats whom in an ecosystem. The scientists say their version of PageRank could be a simple way of working out which extinctions would lead to ecosystem collapse. Every species is embedded in a complex network of relationships with others. So a single extinction can cascade into the loss of seemingly unrelated species.
Investigating when this might happen using more conventional methods is complicated as even in simple ecosystems, the number of combinations exceeds the number of atoms in the universe. So it would be impossible to try them all.
Co-author Dr Stefano Allesina realised he could apply PageRank to the problem when he stumbled across an article in a journal of applied mathematics describing the Google algorithm.
More: http://news.bbc.co.uk/1/hi/sci/tech/8238462.stm
