[Colloquium] Reminder: Talk by Stefano Allesina, NCEAS Today

[Katie Casey]

DEPARTMENT OF COMPUTER SCIENCE

UNIVERSITY OF CHICAGO

Date: Wednesday, April 16, 2008
Time: 2:30 p.m.
Place: Ryerson 251, 1100 E. 58th Street

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Speaker:	Stefano Allesina

From:		National Center for Ecological Analysis and Synthesis

Web page:	www.nceas.ucsb.edu/~allesina

Title: The Spider and The Web: The Structure, Robustness and Dynamics  
of Ecological Networks

Abstract: Karl Popper once said that one can learn more on a spider by  
looking at its web than on the web by looking at the spider. During  
the last 30 years, ecologists collected particular types of webs:  
ecological networks describing communities of interacting species.  
Despite the efforts, learning about the "spider" behind these networks  
has been harder then expected. Here I tackle this issue from three  
different angles, presenting results on the structure, robustness and  
dynamics of ecological networks.

A fundamental challenge is that the complex network structures are not  
readily converted into numbers to perform statistical analyses. A way  
to approach this problem is through the use of "null" models. The  
rationale is that if a model is capable to produce "realistic"  
networks, then it is including in its formulation basic forces that  
are responsible for the shape of real networks. I show how such models  
can be evaluated using likelihoods and how this technical advance  
opens several new lines of research.

The robustness of ecosystems to species losses is a central question  
in ecology given the current pace of extinctions and the many species  
threatened by human impacts, including habitat destruction and climate  
change. Clearly, network structure is a major determinant of  
robustness to extinction in food webs. I present tools taken from  
computer science that can advance our understanding of causes and  
consequences of extinction.

Finally, I present results on a connection between the structure of  
networks and their dynamical properties based on the analysis of  
network motifs. I show how "local" dynamical properties cascade into  
"global" attributes such as stability and resilience to changes. This  
scaling-up of properties has important implications for biological  
conservation, but also for genetic and metabolic networks.

In developing my arguments I underline future ecological, mathematical  
and computational challenges that arise from the study of these issues.
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Host:	Nina Hinrichs
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