PageRank Algorithm Applied To the Food Web

An anonymous reader brings word of a new application for PageRank, Google's link analysis algorithm: monitoring the food web in an ecosystem. A team of researchers found that a modified version of PageRank can predict with great accuracy which species are vital to the existence of others. Quoting: "Every species is embedded in a complex network of relationships with others. 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 realized he could apply PageRank to the problem when he stumbled across an article in a journal of applied mathematics describing the Google algorithm. 'First of all, we had to reverse the definition of the algorithm. In PageRank, a web page is important if important pages point to it. In our approach, a species is important if it points to important species.'"

Comments

Re:Why is this surprising?

[DeadDecoy]

Because it's a novel use of an existing method? It was published in PLoS and not some mathematics journal. So, while the algorithms are not new, they may be new to the intended audience. The actual claim of the article is that it can offer a predictive analysis of extinction rates of a species and validated them on some in-silico experiments. This could be useful for bench-scientists, as they could figure out what might happen in an experiment before running expensive tests. This might be useful for conservations trying to make sure whole ecosystems don't die out due to the removal of a species; the 'might' is significant as real-world ecosystems are generally more complex. But anyways, it's interesting because the models have practical application outside of theory to help us understand the world.