Although this article was published in 2009, I thought its content paralleled quite nicely with our discussion of Google’s PageRank algorithm. As we discussed, while at studying at Stanford, Larry Page and Sergey Brin, developed an algorithm to determine the most important web pages on the internet. Their algorithm is based on the idea that a page is important if important pages point to it.
Ecologist Stefano Allesina of the University of California, Santa Barbara led a team of researchers in a quest to apply the PageRank algorithm to ecosystems. Specifically, they wanted to create a variation of the PageRank algorithm to identify the most important species in an ecosystem, thereby determining the species that could cause a total collapse of the ecosystem. Whereas Larry and Sergey defined a web page as important if important pages pointed to it, the researchers defined a species to be important if it “supported important species.” Previous attempts to study the collapse of ecosystems merely analyzed the number of linkages between species, but failed to address the “relative importance” of each species in the ecosystem. Incorporating this idea of importance, researchers developed a model that strongly outperformed all previous models. Their model allowed them to accurately predict “total ecosystem collapse using the fewest number of species extinctions.”
The applications of this model are vast. For instance, scientists can use this model to analyze a damaged ecosystem (e.g. an overfished marine biology ecosystem) to figure out which species are most important to the revitalization of the ecosystem. Using this information, they could introduce more of these species into the ecosystem to help repair the damage. Furthermore, for healthy ecosystems, scientists can use the model as a preventative mechanism. By knowing which species are keeping the ecosystem healthy, they can focus more of their effort and resources on protecting these species.