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Googling Food Webs: Can an Eigenvector Measure Species' Importance for Coextinctions?
 

Summary: Googling Food Webs: Can an Eigenvector Measure
Species' Importance for Coextinctions?
Stefano Allesina1
*, Mercedes Pascual2,3,4
1 National Center for Ecological Analysis and Synthesis, Santa Barbara, California, United States of America, 2 Department of Ecology and Evolutionary Biology, University
of Michigan, Ann Arbor, Michigan, United States of America, 3 Santa Fe Institute, Santa Fe, New Mexico, United States of America, 4 Howard Hughes Medical Institute
Abstract
A major challenge in ecology is forecasting the effects of species' extinctions, a pressing problem given current human
impacts on the planet. Consequences of species losses such as secondary extinctions are difficult to forecast because
species are not isolated, but interact instead in a complex network of ecological relationships. Because of their mutual
dependence, the loss of a single species can cascade in multiple coextinctions. Here we show that an algorithm adapted
from the one Google uses to rank web-pages can order species according to their importance for coextinctions, providing
the sequence of losses that results in the fastest collapse of the network. Moreover, we use the algorithm to bridge the gap
between qualitative (who eats whom) and quantitative (at what rate) descriptions of food webs. We show that our simple
algorithm finds the best possible solution for the problem of assigning importance from the perspective of secondary
extinctions in all analyzed networks. Our approach relies on network structure, but applies regardless of the specific
dynamical model of species' interactions, because it identifies the subset of coextinctions common to all possible models,
those that will happen with certainty given the complete loss of prey of a given predator. Results show that previous
measures of importance based on the concept of ``hubs'' or number of connections, as well as centrality measures, do not
identify the most effective extinction sequence. The proposed algorithm provides a basis for further developments in the

  

Source: Allesina, Stefano - Department of Ecology and Evolution, University of Chicago
Pascual, Mercedes - Department of Ecology and Evolutionary Biology, University of Michigan

 

Collections: Biology and Medicine; Environmental Sciences and Ecology