[Colloquium] Reminder: Talk by Stefano Allesina, NCEAS Today
Katie Casey
caseyk at cs.uchicago.edu
Wed Apr 16 07:46:26 CDT 2008
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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