Googling Food Web
Research paper link: http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000494
Google’s page-rank algorithm might be able to identify endangered species and save the ecosystem. As discussed in Chapter 14 of “Networks, Crowds, and Markets: Reasoning about a Highly Connected World”, the Page Rank algorithm based on the number of links referring to the page. Using the method of repeated improvements, we can derive the limiting values of the link analysis from the eigenvector of the network’s matrices.
The ecosystem has a network similar to the web pages. Since the food network is very complex, it is hard to identify endangered species in an isolated way, since the health of ecosystem depends on each node. According to Allesina and Pascual’s research, the species that the greatest number of other species rely on for food are the ones that are most essential to the health of an ecosystem. We can identify these species using similar algorithm to the one when Google identify the highest ranked page in search result, since the two networks are similar in a way that the most important node has other nodes pointing to it. By determining the most critical species to preserve the ecosystem, scientists will be able to focus conservation efforts on the species that will most benefit the entire system. Otherwise, one species’ extinction might result in co-extinction because of food web’s mutual dependence.
It is interesting how we can examine the ecosystem in the perspective of network. By performing link analysis, scientists are able to arrive at useful interpretation to save the ecosystem. Network analysis is indeed applicable to many situation, and has lots of potential in solving problems that involves mutual dependencies.