Detecting regime shifts in artificial ecosystems

Chavez, Vasthi Alonso, Doncaster, C. Patrick, Dearing, John A., Wang, Rong, Huang, Jing-Lun and Dyke, James G. (2013) Detecting regime shifts in artificial ecosystems At ECAL2013: 12th European Conference on Artificial Life, Italy. 02 - 06 Sep 2013.


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Ecosystems are subjected to a range of perturbations that have the potential to induce relatively sharp transitions in states. These can be referred to as regime shifts or critical transitions. They may be driven by perturbations that vary over a wide range of spatial and temporal scales, from responses to deforestation within a small field to responses to the gradual increase of carbon dioxide in the Earth's atmosphere. Here we investigate potential early warning signals that may presage regime shifts in model ecosystems. We hypothesise and model a relationship between biodiversity and community structure that influences ecosystem structure. We argue that Artificial Life methodologies have potential to make substantial contributions to efforts searching to predict large changes in ecosystems and other elements in the Earth system, as there is a recognised limitation in empirical data and ability to conduct experiments in the real-world. Consequently simulation and exploration of the low-level mechanisms that give rise to regime shifts in artificial in-silico ecosystems represents a useful line of enquiry.

Item Type: Conference or Workshop Item (Other)
Venue - Dates: ECAL2013: 12th European Conference on Artificial Life, Italy, 2013-09-02 - 2013-09-06
Related URLs:
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Organisations: Faculty of Natural and Environmental Sciences, Faculty of Physical Sciences and Engineering, Faculty of Social, Human and Mathematical Sciences
ePrint ID: 354178
Date :
Date Event
September 2013Accepted/In Press
Date Deposited: 03 Jul 2013 15:57
Last Modified: 17 Apr 2017 15:19
Further Information:Google Scholar

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